diff --git a/.git-blame-ignore-revs b/.git-blame-ignore-revs
new file mode 100644
index 00000000..6a3765b4
--- /dev/null
+++ b/.git-blame-ignore-revs
@@ -0,0 +1,4 @@
+e451191cd772d9effbec8d64fe5d1e68a9e9e954
+d4572b0384ffdc009a8195c698b3de4e2532020b
+1d009ed2ce5a26ddb7336bde38cfe483e9278ac2
+bfd79b562cd363e155c81d73e8b8e607bf4ae087
\ No newline at end of file
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 136a830a..1392d485 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -20,7 +20,7 @@ repos:
               | docs/.*\.(svg|png)$                    # documentation images
             )
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.15.2"
+    rev: "v0.16.10"
     hooks:
       - id: ruff-check
         args: [--fix]
diff --git a/docs/swapi/figure_src/figure_utils.py b/docs/swapi/figure_src/figure_utils.py
index 9e92b4dd..21131c5f 100644
--- a/docs/swapi/figure_src/figure_utils.py
+++ b/docs/swapi/figure_src/figure_utils.py
@@ -4,15 +4,15 @@
 import os
 import sys
 import time
+from collections.abc import Callable
 from pathlib import Path
-from typing import Callable, TypeVar
+from typing import TypeVar
 
 import numpy as np
 
 REPO_ROOT = Path(__file__).resolve().parents[3]
 sys.path.insert(0, str(REPO_ROOT))
 
-# ruff: disable[E402]
 from imap_l3_processing.constants import (
     METERS_PER_KILOMETER,
     PROTON_CHARGE_COULOMBS,
@@ -20,7 +20,6 @@
 )
 from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
-# ruff: enable[E402]
 
 FIGURES_DIR = REPO_ROOT / "docs" / "swapi" / "figures"
 
@@ -180,12 +179,11 @@ def run_parallel_map(
     results: list[_T | None] = [None] * n_items
     report_every = max(1, n_items // 20)
     with multiprocessing.get_context("fork").Pool(processes=n_workers) as pool:
-        completed = 0
         for index, value in pool.imap_unordered(
             _IndexedCall(process_one), range(n_items), chunksize=chunksize
         ):
             results[index] = value
-            completed += 1
+            completed = index + 1
             if completed % report_every == 0 or completed == n_items:
                 elapsed = time.perf_counter() - start
                 print(f"  {desc}: {completed}/{n_items} ({elapsed:.1f}s)")
diff --git a/docs/swapi/figure_src/plot_alpha_peak_finding.py b/docs/swapi/figure_src/plot_alpha_peak_finding.py
old mode 100644
new mode 100755
index a4e9466c..9affb556
--- a/docs/swapi/figure_src/plot_alpha_peak_finding.py
+++ b/docs/swapi/figure_src/plot_alpha_peak_finding.py
@@ -34,6 +34,8 @@
 
 sys.path.insert(0, str(Path(__file__).resolve().parents[3]))
 
+from figure_utils import FIGURES_DIR, load_swapi_response
+
 from imap_l3_processing.constants import (
     ALPHA_MASS_PER_CHARGE_M_P_PER_E,
     ALPHA_PARTICLE_MASS_KG,
@@ -70,7 +72,6 @@
 )
 from imap_l3_processing.swapi.response.deadtime import deadtime_factor
 from imap_l3_processing.utils import SpiceKernelTypes
-from figure_utils import FIGURES_DIR, load_swapi_response
 
 DATE_YYYYMMDD = "20260101"
 N_SWEEPS = 5
@@ -126,9 +127,7 @@ def _furnish_spice_around(date_yyyymmdd: str) -> None:
     spk_start = target - timedelta(days=90)
 
     metakernel_url = (
-        urlparse(imap_data_access.config["DATA_ACCESS_URL"])
-        ._replace(path="metakernel")
-        .geturl()
+        urlparse(imap_data_access.config["DATA_ACCESS_URL"])._replace(path="metakernel").geturl()
     )
     j2000 = datetime(2000, 1, 1, 12)
 
@@ -176,23 +175,15 @@ def _read_5_sweep_block(
         epoch_ns = np.asarray(
             cdf.raw_var("epoch")[sweep_start : sweep_start + n_sweeps], dtype=np.int64
         )
-        cr = np.asarray(
-            cdf["swp_coin_rate"][sweep_start : sweep_start + n_sweeps, :], dtype=float
-        )
-        esa = np.asarray(
-            cdf["esa_energy"][sweep_start : sweep_start + n_sweeps, :], dtype=float
-        )
+        cr = np.asarray(cdf["swp_coin_rate"][sweep_start : sweep_start + n_sweeps, :], dtype=float)
+        esa = np.asarray(cdf["esa_energy"][sweep_start : sweep_start + n_sweeps, :], dtype=float)
     return epoch_ns, cr, esa
 
 
 def _coarse_measurement_times_ns(epoch_ns: np.ndarray) -> np.ndarray:
     coarse_bins = np.arange(SWAPI_COARSE_SWEEP_BINS.start, SWAPI_COARSE_SWEEP_BINS.stop)
-    seconds_into_sweep = (
-        coarse_bins * SWAPI_BIN_PERIOD_S + SWAPI_LIVETIME_CENTER_OFFSET_S
-    )
-    return (
-        epoch_ns[:, None] + seconds_into_sweep * ONE_SECOND_IN_NANOSECONDS
-    ).flatten()
+    seconds_into_sweep = coarse_bins * SWAPI_BIN_PERIOD_S + SWAPI_LIVETIME_CENTER_OFFSET_S
+    return (epoch_ns[:, None] + seconds_into_sweep * ONE_SECOND_IN_NANOSECONDS).flatten()
 
 
 # --------------------------------------------------------------------------- #
@@ -351,8 +342,7 @@ def _plot_case(ax, swapi_response, cdf_path, mag_data, chunk_index):
 def main():
     if not os.environ.get("IMAP_API_KEY"):
         raise SystemExit(
-            "IMAP_API_KEY environment variable is not set. "
-            "Export it before running this script."
+            "IMAP_API_KEY environment variable is not set. Export it before running this script."
         )
     print(f"Downloading L2 for {DATE_YYYYMMDD}…")
     cdf_path = _download_l2(DATE_YYYYMMDD)
diff --git a/docs/swapi/figure_src/plot_calibration_curves.py b/docs/swapi/figure_src/plot_calibration_curves.py
old mode 100644
new mode 100755
index ba062887..03e1fbe5
--- a/docs/swapi/figure_src/plot_calibration_curves.py
+++ b/docs/swapi/figure_src/plot_calibration_curves.py
@@ -17,9 +17,9 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
+from figure_utils import FIGURES_DIR, load_swapi_response
 
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
-from figure_utils import FIGURES_DIR, load_swapi_response
 
 _AREA_CSV = (
     Path(__file__).resolve().parents[3]
@@ -37,9 +37,7 @@ def main():
     eff_area = area_df["effective_area"].to_numpy()
 
     transmission = swapi_response._azimuthal_transmission
-    azimuths = (
-        np.arange(len(transmission)) * SwapiResponse.AZIMUTHAL_TRANSMISSION_SPACING_DEG
-    )
+    azimuths = np.arange(len(transmission)) * SwapiResponse.AZIMUTHAL_TRANSMISSION_SPACING_DEG
 
     fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))
 
diff --git a/docs/swapi/figure_src/plot_collapsed_response_grid.py b/docs/swapi/figure_src/plot_collapsed_response_grid.py
old mode 100644
new mode 100755
index 21f9a6b1..328d867f
--- a/docs/swapi/figure_src/plot_collapsed_response_grid.py
+++ b/docs/swapi/figure_src/plot_collapsed_response_grid.py
@@ -23,20 +23,16 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
+from figure_utils import FIGURES_DIR, REPO_ROOT, load_swapi_response
 
+from imap_l3_processing.constants import HE_PUI_PARTICLE_MASS_PER_CHARGE_M_P_PER_E
 from imap_l3_processing.swapi.l3a.science.pickup_ion.collapsed_response_grid import (
     build_collapsed_response_grid,
     solar_wind_frame_speed_range,
 )
-from figure_utils import FIGURES_DIR, REPO_ROOT, load_swapi_response
-from imap_l3_processing.constants import HE_PUI_PARTICLE_MASS_PER_CHARGE_M_P_PER_E
 
 _REFERENCE_CSV_PATH = (
-    REPO_ROOT
-    / "tests"
-    / "test_data"
-    / "swapi"
-    / "collapsed_response_grid_reference.csv"
+    REPO_ROOT / "tests" / "test_data" / "swapi" / "collapsed_response_grid_reference.csv"
 )
 
 _ESA_VOLTAGE = 5000.0
diff --git a/docs/swapi/figure_src/plot_fit_accuracy.py b/docs/swapi/figure_src/plot_fit_accuracy.py
old mode 100644
new mode 100755
index 040aa57f..bed60e29
--- a/docs/swapi/figure_src/plot_fit_accuracy.py
+++ b/docs/swapi/figure_src/plot_fit_accuracy.py
@@ -29,19 +29,13 @@
 
 import types
 
+import matplotlib
 import numpy as np
 import pandas as pd
 from uncertainties import UFloat
-import matplotlib
 
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
-
-from imap_l3_processing.constants import (
-    PROTON_MASS_KG,
-    PROTON_MASS_PER_CHARGE_M_P_PER_E,
-)
-from imap_l3_processing.swapi.constants import SWAPI_LIVETIME_S
 from figure_utils import (
     COARSE_BIN_INDICES_IN_SWEEP,
     COARSE_SWEEP_VOLTAGES_MEAN_V,
@@ -50,20 +44,26 @@
     load_swapi_response,
     run_parallel_map,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
-    fit_solar_wind_proton_model,
+
+from imap_l3_processing.constants import (
+    PROTON_MASS_KG,
+    PROTON_MASS_PER_CHARGE_M_P_PER_E,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.proton.calculate_initial_guess import (
-    calculate_initial_guess,
+from imap_l3_processing.swapi.constants import SWAPI_LIVETIME_S
+from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
+    build_solar_wind_fit_context,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
     model_solar_wind_ideal_coincidence_rates,
 )
-from imap_l3_processing.swapi.response.deadtime import deadtime_factor
-from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
-    build_solar_wind_fit_context,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
+from imap_l3_processing.swapi.l3a.science.solar_wind.proton.calculate_initial_guess import (
+    calculate_initial_guess,
+)
+from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
+    fit_solar_wind_proton_model,
+)
+from imap_l3_processing.swapi.response.deadtime import deadtime_factor
 
 _N_SWEEPS = 5
 _N_BINS = len(COARSE_SWEEP_VOLTAGES_MEAN_V)
@@ -86,9 +86,7 @@ def _load_wind_samples(csv_path: Path) -> tuple[np.ndarray, ...]:
             f"Missing WIND samples CSV: {csv_path}. "
             f"Run scripts/swapi/sample_wind_solar_wind.py first."
         )
-    cols = np.genfromtxt(
-        csv_path, delimiter=",", names=True, dtype=None, encoding="utf-8"
-    )
+    cols = np.genfromtxt(csv_path, delimiter=",", names=True, dtype=None, encoding="utf-8")
     return (
         cols["v_R_km_s"].astype(float),
         cols["proton_temperature_K"].astype(float),
@@ -177,7 +175,7 @@ def _process_one(i):
     )
     try:
         initial_guess = calculate_initial_guess(fit_ctx)
-    except Exception:
+    except Exception:  # noqa: BLE001
         initial_guess = SolarWindParams(
             density=float("nan"),
             velocity_rtn=np.array([float("nan")] * 3),
@@ -186,12 +184,13 @@ def _process_one(i):
         )
     try:
         result = fit_solar_wind_proton_model(fit_ctx)
-    except Exception as e:
+    except Exception as e:  # noqa: BLE001
         print(f"  case {i}: fit failed ({type(e).__name__}: {e}); flagging bad")
+        from uncertainties import ufloat
+
         from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
             ProtonSolarWindFitResult,
         )
-        from uncertainties import ufloat
 
         nan_uf = ufloat(float("nan"), float("nan"))
         result = ProtonSolarWindFitResult(
@@ -293,9 +292,7 @@ def _plot_results(data: pd.DataFrame) -> None:
     color_initial_guess = "tab:orange"
     color_final_fit = "tab:blue"
 
-    for ax, (label, true_key, init_key, fit_key, fit_sigma_key, scale) in zip(
-        axes, plot_columns
-    ):
+    for ax, (label, true_key, init_key, fit_key, fit_sigma_key, scale) in zip(axes, plot_columns):
         truth = data[true_key]
         init = data[init_key]
         fit = data[fit_key]
@@ -377,7 +374,7 @@ def _plot_results(data: pd.DataFrame) -> None:
             va="top",
             ha="left",
             fontsize=6.5,
-            bbox=dict(boxstyle="round,pad=0.3", fc="white", alpha=0.75),
+            bbox={"boxstyle": "round,pad=0.3", "fc": "white", "alpha": 0.75},
         )
 
     axes[0].legend(fontsize=8, loc="lower right", framealpha=0.8)
@@ -393,9 +390,7 @@ def _plot_results(data: pd.DataFrame) -> None:
 def _rmse_label(truth, estimated, scale):
     mask = np.isfinite(estimated)
     if scale == "log":
-        rmse = np.sqrt(
-            np.mean((np.log10(estimated[mask]) - np.log10(truth[mask])) ** 2)
-        )
+        rmse = np.sqrt(np.mean((np.log10(estimated[mask]) - np.log10(truth[mask])) ** 2))
         return f"RMSE log₁₀ = {rmse:.3f}"
     else:
         rmse = np.sqrt(np.mean((estimated[mask] - truth[mask]) ** 2))
diff --git a/docs/swapi/figure_src/plot_passband_boundaries.py b/docs/swapi/figure_src/plot_passband_boundaries.py
old mode 100644
new mode 100755
index 57abb5c8..4f707571
--- a/docs/swapi/figure_src/plot_passband_boundaries.py
+++ b/docs/swapi/figure_src/plot_passband_boundaries.py
@@ -1,3 +1,5 @@
+#!/usr/bin/env python3
+
 import sys
 from pathlib import Path
 
@@ -8,10 +10,10 @@
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import numpy as np
+from figure_utils import FIGURES_DIR, load_swapi_response
 
 from imap_l3_processing.swapi.response.passband_grid import PassbandGrid
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
-from figure_utils import FIGURES_DIR, load_swapi_response
 
 _ELEVATION_DISPLAY_LIMIT_DEG = 15.0
 _ACTIVE_ELEVATION_SAMPLE_COUNT = 300
@@ -40,9 +42,7 @@ def main():
                 else response_grid.sg_passband
             )
             axis = axes[row, column]
-            last_image = plot_region_panel(
-                axis, grid, region, esa_voltage, central_speed
-            )
+            last_image = plot_region_panel(axis, grid, region, esa_voltage, central_speed)
             if column == 0:
                 axis.set_ylabel("Elevation (deg)")
 
@@ -101,9 +101,7 @@ def grid_axis_coordinates(
 ) -> tuple[np.ndarray, np.ndarray]:
     n_elevations, n_speed_ratios = transmission_values.shape
     elevations = grid.min_elevation + np.arange(n_elevations) * grid.elevation_spacing
-    speed_ratios = (
-        grid.min_speed_ratio + np.arange(n_speed_ratios) * grid.speed_ratio_spacing
-    )
+    speed_ratios = grid.min_speed_ratio + np.arange(n_speed_ratios) * grid.speed_ratio_spacing
     return elevations, speed_ratios
 
 
@@ -148,9 +146,7 @@ def draw_integration_window_outline(
     closed_x = np.concatenate(
         [lower_speed_ratios, upper_speed_ratios[::-1], [lower_speed_ratios[0]]]
     )
-    closed_y = np.concatenate(
-        [active_elevations, active_elevations[::-1], [active_elevations[0]]]
-    )
+    closed_y = np.concatenate([active_elevations, active_elevations[::-1], [active_elevations[0]]])
     axis.plot(closed_x, closed_y, color="tab:blue", linewidth=2.5)
 
 
diff --git a/docs/swapi/figure_src/plot_pui_cutoff_staircase.py b/docs/swapi/figure_src/plot_pui_cutoff_staircase.py
old mode 100644
new mode 100755
index 7187749a..542f1bbf
--- a/docs/swapi/figure_src/plot_pui_cutoff_staircase.py
+++ b/docs/swapi/figure_src/plot_pui_cutoff_staircase.py
@@ -28,14 +28,12 @@
 REPO_ROOT = Path(__file__).resolve().parents[3]
 sys.path.insert(0, str(REPO_ROOT))
 
-# ruff: disable[E402]
 import matplotlib
 
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-
 from figure_utils import FIGURES_DIR, load_swapi_response
 
 from imap_l3_processing.constants import (
@@ -60,7 +58,6 @@
 from imap_l3_processing.swapi.l3a.utils import (
     velocity_components_to_angles_in_instrument_frame,
 )
-# ruff: enable[E402]
 
 _SW_SPEED_KMS = 450.0
 _SW_AZIMUTH_DEG = 0.0
@@ -98,9 +95,7 @@ def _params(cutoff_speed_kms: float) -> FittingParameters:
 
 def main():
     voltages = (
-        pd.read_csv(
-            REPO_ROOT / "tests" / "test_data" / "swapi" / "pui_count_rate_reference.csv"
-        )
+        pd.read_csv(REPO_ROOT / "tests" / "test_data" / "swapi" / "pui_count_rate_reference.csv")
         .iloc[:, 0]
         .to_numpy()
     )
@@ -143,10 +138,8 @@ def main():
     bin_weights = chunk_response.bin_weights[0, voltage_index, :]
 
     # Fine-grid reference response for the same voltage step.
-    bulk_azimuth_deg, bulk_elevation_deg = (
-        velocity_components_to_angles_in_instrument_frame(
-            bulk_vec[0], bulk_vec[1], bulk_vec[2]
-        )
+    bulk_azimuth_deg, bulk_elevation_deg = velocity_components_to_angles_in_instrument_frame(
+        bulk_vec[0], bulk_vec[1], bulk_vec[2]
     )
     fine_grid = np.linspace(1.0, _GRID_MAX_KMS, _FINE_GRID_POINTS)
     fine_collapsed = build_collapsed_response_grid(
@@ -183,9 +176,9 @@ def sampled_distribution(grid, params, apply_cutoff):
                 coarse_grid, params, apply_cutoff=True
             )
             # Production: trapezoidal partial cell, via the real forward model.
-            rate_with[i] = calculate_coincidence_rate(
-                chunk_response, distribution, params
-            )[0, voltage_index]
+            rate_with[i] = calculate_coincidence_rate(chunk_response, distribution, params)[
+                0, voltage_index
+            ]
             # Converged reference: grid-corrected cutoff on a fine grid.
             f_fine = sampled_distribution(fine_grid, params, apply_cutoff=False)
             apply_partial_heaviside_at_cutoff(f_fine, fine_grid, cutoff)
diff --git a/docs/swapi/figure_src/plot_pui_distribution.py b/docs/swapi/figure_src/plot_pui_distribution.py
old mode 100644
new mode 100755
index 5e1b3767..18e61899
--- a/docs/swapi/figure_src/plot_pui_distribution.py
+++ b/docs/swapi/figure_src/plot_pui_distribution.py
@@ -22,13 +22,11 @@
 REPO_ROOT = Path(__file__).resolve().parents[3]
 sys.path.insert(0, str(REPO_ROOT))
 
-# ruff: disable[E402]
 import matplotlib
 
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import numpy as np
-
 from figure_utils import FIGURES_DIR
 
 from imap_l3_processing.constants import ONE_AU_IN_KM
@@ -39,7 +37,6 @@
     FittingParameters,
     VasyliunasSiscoeDistribution,
 )
-# ruff: enable[E402]
 
 _CUTOFF_SPEED_KMS = 450.0
 _SW_SPEED_INERTIAL_KMS = 450.0
@@ -94,9 +91,7 @@ def main():
         label=r"cutoff speed $v_b$",
     )
     axis.set_yscale("log")
-    axis.set_xlabel(
-        r"Comoving speed $v' = \|\mathbf{v} - \mathbf{v}_\text{sw}\|$ [km/s]"
-    )
+    axis.set_xlabel(r"Comoving speed $v' = \|\mathbf{v} - \mathbf{v}_\text{sw}\|$ [km/s]")
     axis.set_ylabel(r"$f_\text{PUI}(v')$ [s$^3$ km$^{-6}$]")
     axis.set_xlim(speed_in_sw_frame[0], speed_in_sw_frame[-1])
     axis.set_ylim(1e0, 1e4)
diff --git a/docs/swapi/figure_src/plot_pui_reference_comparison.py b/docs/swapi/figure_src/plot_pui_reference_comparison.py
old mode 100644
new mode 100755
index 900b2b97..18d7af9b
--- a/docs/swapi/figure_src/plot_pui_reference_comparison.py
+++ b/docs/swapi/figure_src/plot_pui_reference_comparison.py
@@ -21,21 +21,17 @@
 REPO_ROOT = Path(__file__).resolve().parents[3]
 sys.path.insert(0, str(REPO_ROOT))
 
-# ruff: disable[E402]
 import matplotlib
 
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-
 from figure_utils import FIGURES_DIR
+
 from imap_l3_processing.constants import HE_PUI_PARTICLE_MASS_PER_CHARGE_M_P_PER_E
-# ruff: enable[E402]
 
-_REFERENCE_CSV_PATH = (
-    REPO_ROOT / "tests" / "test_data" / "swapi" / "pui_count_rate_reference.csv"
-)
+_REFERENCE_CSV_PATH = REPO_ROOT / "tests" / "test_data" / "swapi" / "pui_count_rate_reference.csv"
 
 # Must match scripts/swapi/pui_xarray_reference.py so the production kernel is
 # evaluated at the same point as the precomputed reference CSV.
@@ -61,6 +57,8 @@ def compute_production_rates(voltages_v: np.ndarray) -> np.ndarray:
     """Build the chunk-level collapsed response and call the in-development
     production kernel. Imports live inside the function so a broken module
     doesn't break the figure script at import time."""
+    from figure_utils import load_swapi_response
+
     from imap_l3_processing.constants import ONE_AU_IN_KM
     from imap_l3_processing.swapi.l3a.science.pickup_ion.calculate_coincidence_rate import (
         calculate_coincidence_rate,
@@ -75,7 +73,6 @@ def compute_production_rates(voltages_v: np.ndarray) -> np.ndarray:
         FittingParameters,
         VasyliunasSiscoeDistribution,
     )
-    from figure_utils import load_swapi_response
 
     fitting_params = FittingParameters(
         cooling_index=_COOLING_INDEX,
@@ -84,9 +81,7 @@ def compute_production_rates(voltages_v: np.ndarray) -> np.ndarray:
         background_count_rate=_BACKGROUND_RATE_HZ,
     )
     lut = DensityOfNeutralHeliumLookupTable.from_file(_DENSITY_LUT_PATH)
-    min_speed_kms = max(
-        1.0, _CUTOFF_SPEED_KMS * lut.get_minimum_distance() / _HELIO_DIST_AU
-    )
+    min_speed_kms = max(1.0, _CUTOFF_SPEED_KMS * lut.get_minimum_distance() / _HELIO_DIST_AU)
     vasyliunas_siscoe_distribution = VasyliunasSiscoeDistribution(
         ephemeris_time=0.0,
         solar_wind_speed_inertial_frame=_SW_SPEED_INERTIAL_KMS,
@@ -165,7 +160,7 @@ def main():
 
     try:
         production_rate_hz = compute_production_rates(voltage_v)
-    except Exception:
+    except Exception:  # noqa: BLE001
         traceback.print_exc()
         print("calculate_coincidence_rate failed — skipping production overlay.")
     else:
diff --git a/docs/swapi/figure_src/plot_real_data_fit.py b/docs/swapi/figure_src/plot_real_data_fit.py
old mode 100644
new mode 100755
index af29fe15..33fd811c
--- a/docs/swapi/figure_src/plot_real_data_fit.py
+++ b/docs/swapi/figure_src/plot_real_data_fit.py
@@ -37,40 +37,40 @@
 
 sys.path.insert(0, str(Path(__file__).resolve().parents[3]))
 
+import scipy.optimize
+from figure_utils import FIGURES_DIR, REPO_ROOT, load_swapi_response
+
 from imap_l3_processing.constants import (
     BOLTZMANN_CONSTANT_JOULES_PER_KELVIN,
     ONE_SECOND_IN_NANOSECONDS,
     PROTON_MASS_KG,
     PROTON_MASS_PER_CHARGE_M_P_PER_E,
 )
-import scipy.optimize
-
+from imap_l3_processing.swapi.constants import (
+    SWAPI_BIN_PERIOD_S,
+    SWAPI_COARSE_SWEEP_BINS,
+    SWAPI_FINE_SWEEP_BINS,
+    SWAPI_K_FACTOR,
+    SWAPI_L2_K_FACTOR,
+    SWAPI_LIVETIME_CENTER_OFFSET_S,
+    SWAPI_SCIENCE_BINS,
+)
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     build_solar_wind_fit_context,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
     model_solar_wind_ideal_coincidence_rates,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
     fit_solar_wind_proton_model,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from imap_l3_processing.swapi.l3a.utils import (
     get_spacecraft_velocity_rtn,
     get_swapi_geometry,
 )
 from imap_l3_processing.swapi.response.deadtime import deadtime_factor
-from imap_l3_processing.swapi.constants import (
-    SWAPI_BIN_PERIOD_S,
-    SWAPI_COARSE_SWEEP_BINS,
-    SWAPI_FINE_SWEEP_BINS,
-    SWAPI_K_FACTOR,
-    SWAPI_L2_K_FACTOR,
-    SWAPI_LIVETIME_CENTER_OFFSET_S,
-    SWAPI_SCIENCE_BINS,
-)
 from imap_l3_processing.utils import SpiceKernelTypes
-from figure_utils import FIGURES_DIR, REPO_ROOT, load_swapi_response
 
 _DOC_PATH = REPO_ROOT / "docs" / "swapi" / "proton-sw.md"
 _TABLE_BEGIN = "<!-- BEGIN: real_data_table"
@@ -91,16 +91,13 @@
 def main():
     if not os.environ.get("IMAP_API_KEY"):
         raise SystemExit(
-            "IMAP_API_KEY environment variable is not set. "
-            "Export it before running this script."
+            "IMAP_API_KEY environment variable is not set. Export it before running this script."
         )
     cdf_path = _download_l2(DATE_YYYYMMDD)
     _furnish_spice_around(DATE_YYYYMMDD)
 
     sweep_start = SWEEP_START
-    epoch_ns, count_rate, esa_voltage = _read_5_sweep_block(
-        cdf_path, sweep_start, N_SWEEPS
-    )
+    epoch_ns, count_rate, esa_voltage = _read_5_sweep_block(cdf_path, sweep_start, N_SWEEPS)
     chunk_center_ns = int(epoch_ns[0]) + 30 * ONE_SECOND_IN_NANOSECONDS
     chunk_center_dt = _tt2000ns_to_datetime(chunk_center_ns)
     print(
@@ -216,9 +213,7 @@ def _furnish_spice_around(date_yyyymmdd: str) -> None:
     spk_start = target - timedelta(days=90)
 
     metakernel_url = (
-        urlparse(imap_data_access.config["DATA_ACCESS_URL"])
-        ._replace(path="metakernel")
-        .geturl()
+        urlparse(imap_data_access.config["DATA_ACCESS_URL"])._replace(path="metakernel").geturl()
     )
     j2000 = datetime(2000, 1, 1, 12)
 
@@ -267,21 +262,15 @@ def _read_5_sweep_block(
         epoch_ns = np.asarray(
             cdf.raw_var("epoch")[sweep_start : sweep_start + n_sweeps], dtype=np.int64
         )
-        cr = np.asarray(
-            cdf["swp_coin_rate"][sweep_start : sweep_start + n_sweeps, :], dtype=float
-        )
-        esa = np.asarray(
-            cdf["esa_energy"][sweep_start : sweep_start + n_sweeps, :], dtype=float
-        )
+        cr = np.asarray(cdf["swp_coin_rate"][sweep_start : sweep_start + n_sweeps, :], dtype=float)
+        esa = np.asarray(cdf["esa_energy"][sweep_start : sweep_start + n_sweeps, :], dtype=float)
     return epoch_ns, cr, esa
 
 
 def _measurement_times_ns(epoch_ns: np.ndarray, bin_slice: slice) -> np.ndarray:
     bins = np.arange(bin_slice.start, bin_slice.stop)
     seconds_into_sweep = bins * SWAPI_BIN_PERIOD_S + SWAPI_LIVETIME_CENTER_OFFSET_S
-    return (
-        epoch_ns[:, None] + seconds_into_sweep * ONE_SECOND_IN_NANOSECONDS
-    ).flatten()
+    return (epoch_ns[:, None] + seconds_into_sweep * ONE_SECOND_IN_NANOSECONDS).flatten()
 
 
 # --------------------------------------------------------------------------- #
@@ -352,7 +341,7 @@ def _bootstrap_sigmas(
             mass_kg=PROTON_MASS_KG,
             mass_per_charge_m_p_per_e=PROTON_MASS_PER_CHARGE_M_P_PER_E,
         )
-
+        # ruff: disable[B023]
         cache = {}
 
         def _eval(state):
@@ -373,6 +362,8 @@ def _jacobian(state):
                 _eval(state)
             return cache["j"]
 
+        # ruff: enable[B023]
+
         try:
             raw = scipy.optimize.least_squares(
                 _residues,
@@ -381,7 +372,7 @@ def _jacobian(state):
                 method="lm",
                 xtol=xtol,
             )
-        except Exception:
+        except (TypeError, ValueError):
             continue
         if not raw.success:
             continue
@@ -458,10 +449,10 @@ def _build_intro_table(science_result, coarse_result, boot, wind):
         (
             "Temperature $`T`$ (K)",
             f"$`({sci_fit.temperature.nominal_value / 1e4:.3f} \\pm "
-            f"{sci_fit.temperature.std_dev / 1e4:.3f})\\times10^{{4}}`$",
+            + f"{sci_fit.temperature.std_dev / 1e4:.3f})\\times10^{{4}}`$",
             f"$`\\pm {boot['T_sigma'] / 1e4:.3f}\\times10^{{4}}`$",
             f"$`({coa_fit.temperature.nominal_value / 1e4:.3f} \\pm "
-            f"{coa_fit.temperature.std_dev / 1e4:.3f})\\times10^{{4}}`$",
+            + f"{coa_fit.temperature.std_dev / 1e4:.3f})\\times10^{{4}}`$",
             wind_T,
         ),
         (
@@ -586,9 +577,7 @@ def _wind_value_at(target_dt: datetime) -> dict | None:
 
     data = np.loadtxt(asc, comments=";")
 
-    fdoy_target = (
-        target_dt - datetime(target_dt.year, 1, 1)
-    ).total_seconds() / 86400.0 + 1.0
+    fdoy_target = (target_dt - datetime(target_dt.year, 1, 1)).total_seconds() / 86400.0 + 1.0
     year = data[:, 0].astype(int)
     fdoy = data[:, 1]
     in_year = year == target_dt.year
@@ -610,11 +599,7 @@ def _wind_value_at(target_dt: datetime) -> dict | None:
     # 10 σVz, 11 Wscalar, 12 σWscalar, 21 Np, 22 σNp.
     w_th = row[11]
     sigma_w = row[12]
-    T_K = (
-        PROTON_MASS_KG
-        * (w_th * 1e3) ** 2
-        / (2.0 * BOLTZMANN_CONSTANT_JOULES_PER_KELVIN)
-    )
+    T_K = PROTON_MASS_KG * (w_th * 1e3) ** 2 / (2.0 * BOLTZMANN_CONSTANT_JOULES_PER_KELVIN)
     # Linear-error propagation: T = m·w²/(2k)  ⇒  σT = (2T/w)·σw.
     sigma_T = T_K * 2.0 * sigma_w / w_th if w_th > 0 else float("nan")
     return {
@@ -700,9 +685,9 @@ def _dense_fine(values_per_bin, v_per_bin):
         keep = (v_per_bin > 100.0) & np.isfinite(values_per_bin)
         if keep.sum() < 2:
             return fine_dense_step, np.full_like(fine_dense_step, np.nan)
-        bins_keep = bin_indices[
-            SWAPI_FINE_SWEEP_BINS.start : SWAPI_FINE_SWEEP_BINS.stop
-        ][keep[SWAPI_FINE_SWEEP_BINS]]
+        bins_keep = bin_indices[SWAPI_FINE_SWEEP_BINS.start : SWAPI_FINE_SWEEP_BINS.stop][
+            keep[SWAPI_FINE_SWEEP_BINS]
+        ]
         order = np.argsort(bins_keep)
         return (
             fine_dense_step,
@@ -719,9 +704,7 @@ def _draw(panel, cr, s_curve, c_curve, v, *, draw_legend=False):
         ax_c, ax_f = panel
         ok = (v > 0) & np.isfinite(v)
         coarse_mask = ok & (bin_indices < SWAPI_FINE_SWEEP_BINS.start)
-        fine_mask_useful = (
-            ok & (bin_indices >= SWAPI_FINE_SWEEP_BINS.start) & (v > 100.0)
-        )
+        fine_mask_useful = ok & (bin_indices >= SWAPI_FINE_SWEEP_BINS.start) & (v > 100.0)
 
         ax_c.semilogy(
             bin_indices[coarse_mask],
@@ -803,9 +786,7 @@ def _add_peak_markers(panel, cr, v, *, draw_legend=False):
             v_region = v[peak_slice]
             bins_region = bin_grid[peak_slice]
             ok_region = (v_region > 0) & np.isfinite(v_region)
-            v_at_peak = float(
-                np.interp(peak_bin, bins_region[ok_region], v_region[ok_region])
-            )
+            v_at_peak = float(np.interp(peak_bin, bins_region[ok_region], v_region[ok_region]))
             e_over_q_eV = SWAPI_K_FACTOR * v_at_peak
             log10_rate = float(np.log10(max(peak_rate, 1.0)))
             x_marker = peak_bin
@@ -819,9 +800,7 @@ def _add_peak_markers(panel, cr, v, *, draw_legend=False):
                 zorder=5,
                 label=marker_label if draw_legend else None,
             )
-            text_transform = blended_transform_factory(
-                sub_ax.transData, sub_ax.transAxes
-            )
+            text_transform = blended_transform_factory(sub_ax.transData, sub_ax.transAxes)
             sub_ax.text(
                 x_marker,
                 0.98,
diff --git a/docs/swapi/figure_src/plot_spectra.py b/docs/swapi/figure_src/plot_spectra.py
old mode 100644
new mode 100755
index b3299088..3ca0e093
--- a/docs/swapi/figure_src/plot_spectra.py
+++ b/docs/swapi/figure_src/plot_spectra.py
@@ -26,24 +26,23 @@
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 import numpy as np
+from figure_utils import (
+    FIGURES_DIR,
+    load_swapi_response,
+    peak_esa_voltage_for_proton_bulk_speed,
+    velocity_rtn_from_swapi_angles,
+)
 
 from imap_l3_processing.constants import (
+    EV_TO_KELVIN,
     PROTON_MASS_KG,
     PROTON_MASS_PER_CHARGE_M_P_PER_E,
-    EV_TO_KELVIN,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
     calculate_integral,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from scripts.swapi.reference_integral import reference_integral_fixed_limits
-from figure_utils import (
-    FIGURES_DIR,
-    velocity_rtn_from_swapi_angles,
-    load_swapi_response,
-    peak_esa_voltage_for_proton_bulk_speed,
-)
-
 
 # (label, bulk_speed, T_K, bulk_azimuth, bulk_elevation, density)
 CASES = [
@@ -103,9 +102,7 @@ def main():
     handles_for_legend = None
     for ax, (label, v_b, T_k, az, el, density) in zip(axes.flat, CASES):
         v_peak = peak_esa_voltage_for_proton_bulk_speed(v_b)
-        esa_voltages = np.logspace(
-            np.log10(0.4 * v_peak), np.log10(2.5 * v_peak), n_voltages
-        )
+        esa_voltages = np.logspace(np.log10(0.4 * v_peak), np.log10(2.5 * v_peak), n_voltages)
         sw = SolarWindParams(
             density=density,
             velocity_rtn=velocity_rtn_from_swapi_angles(v_b, az, el),
@@ -122,9 +119,7 @@ def main():
             )
             rate, _ = calculate_integral(sw, response_grid, rotation_matrix)
             optimized[i] = rate
-            reference[i] = reference_integral_fixed_limits(
-                response_grid, sw, rotation_matrix
-            )
+            reference[i] = reference_integral_fixed_limits(response_grid, sw, rotation_matrix)
 
         (h_ref,) = ax.plot(
             esa_voltages,
diff --git a/docs/swapi/figure_src/plot_uncertainty_mc.py b/docs/swapi/figure_src/plot_uncertainty_mc.py
old mode 100644
new mode 100755
index 3d11baac..df00dac9
--- a/docs/swapi/figure_src/plot_uncertainty_mc.py
+++ b/docs/swapi/figure_src/plot_uncertainty_mc.py
@@ -20,18 +20,12 @@
 
 import types
 
+import matplotlib
 import numpy as np
 import pandas as pd
-import matplotlib
 
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
-
-from imap_l3_processing.constants import (
-    PROTON_MASS_KG,
-    PROTON_MASS_PER_CHARGE_M_P_PER_E,
-)
-from imap_l3_processing.swapi.constants import SWAPI_LIVETIME_S
 from figure_utils import (
     COARSE_BIN_INDICES_IN_SWEEP,
     COARSE_SWEEP_VOLTAGES_MEAN_V,
@@ -40,13 +34,17 @@
     load_swapi_response,
     run_parallel_map,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.proton.calculate_initial_guess import (
-    calculate_initial_guess,
+
+from imap_l3_processing.constants import (
+    PROTON_MASS_KG,
+    PROTON_MASS_PER_CHARGE_M_P_PER_E,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
-    _derive_uncertainties,
-    escape_local_minimum,
-    optimize_solar_wind_proton_params,
+from imap_l3_processing.swapi.constants import SWAPI_LIVETIME_S
+from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
+    build_solar_wind_fit_context,
+)
+from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
+    model_solar_wind_ideal_coincidence_rates,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
     LOG_DENSITY_IDX,
@@ -54,13 +52,15 @@
     VELOCITY_SLICE,
     SolarWindParams,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
-    model_solar_wind_ideal_coincidence_rates,
+from imap_l3_processing.swapi.l3a.science.solar_wind.proton.calculate_initial_guess import (
+    calculate_initial_guess,
 )
-from imap_l3_processing.swapi.response.deadtime import deadtime_factor
-from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
-    build_solar_wind_fit_context,
+from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
+    _derive_uncertainties,
+    escape_local_minimum,
+    optimize_solar_wind_proton_params,
 )
+from imap_l3_processing.swapi.response.deadtime import deadtime_factor
 
 _N_SWEEPS = 5
 _N_BINS = len(COARSE_SWEEP_VOLTAGES_MEAN_V)
@@ -88,7 +88,7 @@ def main():
         [
             (
                 f"Poisson + {_LOGNORMAL_REL_SIGMA:.0%} log-normal "
-                f"+ {_NOISE_FLOOR_HZ:g} Hz floor",
+                + f"+ {_NOISE_FLOOR_HZ:g} Hz floor",
                 poisson_lognormal_floor_data,
             ),
         ]
@@ -153,9 +153,7 @@ def _process_one(i):
     # counts added — a stand-in for unmodelled detector dark/leakage rate.
     # The mean adds 10 Hz to obs at every bin; the variance is √(floor·τ)/τ
     # ≈ 8 Hz per bin. The fit's model does not account for this.
-    floor_counts = rng.poisson(
-        _NOISE_FLOOR_HZ * SWAPI_LIVETIME_S, size=count_rates.shape
-    )
+    floor_counts = rng.poisson(_NOISE_FLOOR_HZ * SWAPI_LIVETIME_S, size=count_rates.shape)
     count_rates = count_rates + floor_counts.astype(float) / SWAPI_LIVETIME_S
 
     fit_ctx = build_solar_wind_fit_context(
@@ -190,7 +188,7 @@ def _process_one(i):
         initial_guess = calculate_initial_guess(fit_ctx)
         first_result = optimize_solar_wind_proton_params(initial_guess, fit_ctx)
         final_result = escape_local_minimum(first_result, fit_ctx)
-    except Exception as e:
+    except Exception as e:  # noqa: BLE001
         print(f"  case {i}: fit failed ({type(e).__name__}: {e})")
         return nan_row
 
@@ -228,9 +226,7 @@ def _uncorrected_sigmas(opt_result) -> tuple[float, float, np.ndarray]:
     J = opt_result.jacobian
     n_params = J.shape[1]
     n_obs = len(opt_result.residuals)
-    residual_variance = float(np.sum(opt_result.residuals**2)) / max(
-        n_obs - n_params, 1
-    )
+    residual_variance = float(np.sum(opt_result.residuals**2)) / max(n_obs - n_params, 1)
     try:
         cov = residual_variance * np.linalg.pinv(J.T @ J)
     except np.linalg.LinAlgError:
@@ -356,7 +352,7 @@ def _plot_results(experiments: list[tuple[str, pd.DataFrame]]) -> None:
                 va="top",
                 ha="left",
                 fontsize=7.5,
-                bbox=dict(boxstyle="round,pad=0.3", fc="white", alpha=0.8),
+                bbox={"boxstyle": "round,pad=0.3", "fc": "white", "alpha": 0.8},
             )
             if col_idx == 0:
                 ax_top.legend(fontsize=7, loc="upper right", framealpha=0.8)
@@ -368,9 +364,7 @@ def _plot_results(experiments: list[tuple[str, pd.DataFrame]]) -> None:
             ax_bot = axes[row_bot, col_idx]
             normalized_resid_sandwich = (fits - truth) / sigmas
             normalized_resid_ols = (fits - truth) / ols_sigmas
-            finite_sw = normalized_resid_sandwich[
-                np.isfinite(normalized_resid_sandwich)
-            ]
+            finite_sw = normalized_resid_sandwich[np.isfinite(normalized_resid_sandwich)]
             finite_ols_n = normalized_resid_ols[np.isfinite(normalized_resid_ols)]
             x_max = float(np.nanmax(np.abs(np.concatenate([finite_sw, finite_ols_n]))))
             x_max = max(x_max, 4.0)  # always show at least ±4σ
@@ -398,9 +392,7 @@ def _plot_results(experiments: list[tuple[str, pd.DataFrame]]) -> None:
             bin_width = bins_norm[1] - bins_norm[0]
             x_ref = np.linspace(-x_max, x_max, 200)
             unit_gaussian_pdf = (
-                (np.exp(-0.5 * x_ref**2) / np.sqrt(2 * np.pi))
-                * n_good_finite
-                * bin_width
+                (np.exp(-0.5 * x_ref**2) / np.sqrt(2 * np.pi)) * n_good_finite * bin_width
             )
             ax_bot.plot(
                 x_ref,
@@ -425,7 +417,7 @@ def _plot_results(experiments: list[tuple[str, pd.DataFrame]]) -> None:
                 va="top",
                 ha="left",
                 fontsize=7.5,
-                bbox=dict(boxstyle="round,pad=0.3", fc="white", alpha=0.8),
+                bbox={"boxstyle": "round,pad=0.3", "fc": "white", "alpha": 0.8},
             )
             if col_idx == 0:
                 ax_bot.legend(fontsize=7, loc="upper right", framealpha=0.8)
diff --git a/docs/swapi/figure_src/plot_validation_scatter.py b/docs/swapi/figure_src/plot_validation_scatter.py
old mode 100644
new mode 100755
index fd97aee7..c892c106
--- a/docs/swapi/figure_src/plot_validation_scatter.py
+++ b/docs/swapi/figure_src/plot_validation_scatter.py
@@ -21,6 +21,14 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
+from figure_utils import (
+    ANCHOR_ROTATION_SWAPI_TO_RTN,
+    FIGURES_DIR,
+    REPO_ROOT,
+    load_swapi_response,
+    peak_esa_voltage_for_proton_bulk_speed,
+    run_parallel_map,
+)
 
 from imap_l3_processing.constants import (
     PROTON_MASS_KG,
@@ -31,20 +39,9 @@
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 
-from figure_utils import (
-    ANCHOR_ROTATION_SWAPI_TO_RTN,
-    FIGURES_DIR,
-    REPO_ROOT,
-    load_swapi_response,
-    peak_esa_voltage_for_proton_bulk_speed,
-    run_parallel_map,
-)
-
 _worker_state: types.SimpleNamespace | None = None
 
-_REFERENCE_INTEGRALS_PATH = (
-    REPO_ROOT / "tests" / "test_data" / "swapi" / "reference_integrals.csv"
-)
+_REFERENCE_INTEGRALS_PATH = REPO_ROOT / "tests" / "test_data" / "swapi" / "reference_integrals.csv"
 _OUTPUT_PATH = FIGURES_DIR / "validation_scatter.svg"
 
 
@@ -139,9 +136,7 @@ def _plot_scatter(reference: np.ndarray, optimized: np.ndarray) -> None:
     ax.set_aspect("equal")
     ax.set_xlabel("Reference count rate (Hz)")
     ax.set_ylabel("Optimized count rate (Hz)")
-    ax.set_title(
-        "Optimized vs. reference integrator across 10,000 random SW configurations"
-    )
+    ax.set_title("Optimized vs. reference integrator across 10,000 random SW configurations")
     ax.grid(True, which="both", alpha=0.3)
     ax.legend(loc="upper left", framealpha=0.9)
 
@@ -169,19 +164,13 @@ def main():
     bulk_speeds = df["bulk_speed_km_s"].to_numpy(dtype=float)
 
     print(f"Warming passband cache for {len(df)} rows...")
-    peak_voltages = np.array(
-        [peak_esa_voltage_for_proton_bulk_speed(v) for v in bulk_speeds]
-    )
+    peak_voltages = np.array([peak_esa_voltage_for_proton_bulk_speed(v) for v in bulk_speeds])
     swapi_response.warm_cache(peak_voltages)
     for unique_voltage in np.unique(peak_voltages):
-        swapi_response.get_response_grid(
-            float(unique_voltage), PROTON_MASS_PER_CHARGE_M_P_PER_E
-        )
+        swapi_response.get_response_grid(float(unique_voltage), PROTON_MASS_PER_CHARGE_M_P_PER_E)
 
     _initialize_worker_state(rows, peak_voltages, swapi_response)
-    optimized = np.array(
-        run_parallel_map(_process_one, len(df), desc="integrals", chunksize=64)
-    )
+    optimized = np.array(run_parallel_map(_process_one, len(df), desc="integrals", chunksize=64))
 
     valid = (references > 0) & (optimized > 0)
     rel = np.abs(optimized[valid] / references[valid] - 1.0)
diff --git a/imap_l3_data_processor.py b/imap_l3_data_processor.py
index b664297e..80eb140c 100644
--- a/imap_l3_data_processor.py
+++ b/imap_l3_data_processor.py
@@ -19,13 +19,13 @@
 )
 from imap_l3_processing.hi.hi_processor import HiProcessor
 from imap_l3_processing.hi.hi_sp_initializer import (
-    HiSPInitializer,
     HI_SP_MAP_DESCRIPTORS,
+    HiSPInitializer,
 )
 from imap_l3_processing.hit.l3.hit_processor import HitProcessor
 from imap_l3_processing.lo.l3.lo_sp_initializer import (
-    LoSPInitializer,
     LO_SP_MAP_DESCRIPTORS,
+    LoSPInitializer,
 )
 from imap_l3_processing.lo.lo_processor import LoProcessor
 from imap_l3_processing.maps.map_descriptors import parse_map_descriptor
@@ -33,15 +33,15 @@
 from imap_l3_processing.swapi.swapi_processor import SwapiProcessor
 from imap_l3_processing.swe.swe_processor import SweProcessor
 from imap_l3_processing.ultra.ultra_combined_nsp_initializer import (
-    UltraCombinedNSPInitializer,
     ULTRA_COMBINED_NSP_DESCRIPTORS,
+    UltraCombinedNSPInitializer,
 )
 from imap_l3_processing.ultra.ultra_processor import UltraProcessor
 from imap_l3_processing.ultra.ultra_sp_initializer import (
-    UltraSPInitializer,
     ULTRA_45_DESCRIPTORS,
     ULTRA_90_DESCRIPTORS,
     ULTRA_COMBINED_SP_DESCRIPTORS,
+    UltraSPInitializer,
 )
 
 logger = logging.getLogger(__name__)
@@ -90,9 +90,7 @@ def imap_l3_processor():
         processing_input_collection.deserialize(args.dependency)
         version_map = VersionMap({}, Version(None, args.version))
     else:
-        processing_input_collection.deserialize(
-            json.dumps(parsed_dependency["dependency"])
-        )
+        processing_input_collection.deserialize(json.dumps(parsed_dependency["dependency"]))
         version_map = VersionMap(
             {
                 k: Version(v["major_version"], v["minor_version"])
@@ -102,9 +100,7 @@ def imap_l3_processor():
 
     repointing_number = None
     if args.repointing is not None:
-        repointing_number_match = re.match(
-            r"repoint(?P<repoint>\d{5})", args.repointing
-        )
+        repointing_number_match = re.match(r"repoint(?P<repoint>\d{5})", args.repointing)
         if repointing_number_match is None:
             raise ValueError("Unexpected repointing number command line format!")
         repointing_number = int(repointing_number_match["repoint"])
@@ -165,13 +161,9 @@ def imap_l3_processor():
                 )
             )
 
-        logger.info(
-            f"maps to produce {[m.input_metadata.descriptor for m in maps_to_produce]}"
-        )
+        logger.info(f"maps to produce {[m.input_metadata.descriptor for m in maps_to_produce]}")
         if len(maps_to_produce) == 0:
-            logger.info(
-                f"Did not find any maps to produce for instrument {args.instrument}"
-            )
+            logger.info(f"Did not find any maps to produce for instrument {args.instrument}")
 
         for map_to_produce in maps_to_produce:
             logger.info(
@@ -190,9 +182,7 @@ def imap_l3_processor():
                     f"Failed to produce map {map_to_produce.input_metadata.descriptor}, {map_to_produce.input_metadata.start_date}!",
                     exc_info=e,
                 )
-    elif args.instrument == "swapi" and (
-        args.data_level == "l3a" or args.data_level == "l3b"
-    ):
+    elif args.instrument == "swapi" and (args.data_level == "l3a" or args.data_level == "l3b"):
         processor = SwapiProcessor(processing_input_collection, input_dependency)
         paths = processor.process()
     elif args.instrument == "glows" and args.data_level in ["l3a", "l3b"]:
@@ -234,10 +224,10 @@ def imap_l3_processor():
         for path in paths:
             try:
                 imap_data_access.upload(path)
-            except Exception as e:
+            except Exception as e:  # noqa: BLE001
                 exceptions.append(e)
         if exceptions:
-            raise IOError(f"Failed to upload some files: {exceptions}")
+            raise OSError(f"Failed to upload some files: {exceptions}")
 
 
 def _furnish_spice_kernels(processing_input_collection):
@@ -257,6 +247,6 @@ def _furnish_spice_kernels(processing_input_collection):
 
         try:
             imap_l3_processor()
-        except Exception as e:
+        except Exception:
             logger.error("Unhandled Exception:")
-            raise e
+            raise
diff --git a/imap_l3_processing/cdf/cdf_utils.py b/imap_l3_processing/cdf/cdf_utils.py
index 39490bf8..8582dff4 100644
--- a/imap_l3_processing/cdf/cdf_utils.py
+++ b/imap_l3_processing/cdf/cdf_utils.py
@@ -14,9 +14,7 @@
 }
 
 
-def write_cdf(
-    file_path: str, data: DataProduct, attribute_manager: ImapAttributeManager
-):
+def write_cdf(file_path: str, data: DataProduct, attribute_manager: ImapAttributeManager):
     with CDF(file_path, "") as cdf:
         cdf.col_major(True)
         try:
@@ -38,9 +36,7 @@ def write_cdf(
             "glows",
         ):
             try:
-                map_descriptor = naming.MapDescriptor.from_string(
-                    data.input_metadata.descriptor
-                )
+                map_descriptor = naming.MapDescriptor.from_string(data.input_metadata.descriptor)
             except ValueError:
                 # Assume this is not actually a map
                 pass
@@ -51,9 +47,10 @@ def write_cdf(
             data_type = getattr(pycdf.const, variable_attributes["DATA_TYPE"])
             data_array = np.asanyarray(data_product.value)
 
-            if map_descriptor is not None:
-                if map_var_catdesc := map_descriptor.build_map_var_catdesc(var_name):
-                    variable_attributes["CATDESC"] = map_var_catdesc
+            if map_descriptor is not None and (
+                map_var_catdesc := map_descriptor.build_map_var_catdesc(var_name)
+            ):
+                variable_attributes["CATDESC"] = map_var_catdesc
 
             record_varying = variable_attributes["RECORD_VARYING"].lower() == "rv"
             if record_varying:
@@ -65,17 +62,13 @@ def write_cdf(
                 data_array = None
             else:
                 target_float_dtype = _CDF_FLOAT_NUMPY_DTYPE.get(data_type.value)
-                if target_float_dtype is not None and np.issubdtype(
-                    data_array.dtype, np.floating
-                ):
+                if target_float_dtype is not None and np.issubdtype(data_array.dtype, np.floating):
                     data_array = data_array.astype(target_float_dtype)
 
                 if "FILLVAL" in variable_attributes:
                     if np.issubdtype(data_array.dtype, np.floating):
                         data_array = np.ma.masked_invalid(data_array)
-                    data_array = np.ma.filled(
-                        data_array, variable_attributes["FILLVAL"]
-                    )
+                    data_array = np.ma.filled(data_array, variable_attributes["FILLVAL"])
                 else:
                     assert not np.ma.isMaskedArray(data_array)
 
diff --git a/imap_l3_processing/cdf/imap_attribute_manager.py b/imap_l3_processing/cdf/imap_attribute_manager.py
index 349354f4..9341ea8a 100644
--- a/imap_l3_processing/cdf/imap_attribute_manager.py
+++ b/imap_l3_processing/cdf/imap_attribute_manager.py
@@ -1,5 +1,4 @@
 from pathlib import Path
-from typing import Optional
 
 from sammi.cdf_attribute_manager import CdfAttributeManager
 
@@ -22,11 +21,9 @@ def __init__(self):
         )
         self.config_folder_path = Path(f"{Path(__file__).parent.resolve()}/config")
 
-        self.load_global_attributes(
-            self.config_folder_path / "imap_default_global_cdf_attrs.yaml"
-        )
+        self.load_global_attributes(self.config_folder_path / "imap_default_global_cdf_attrs.yaml")
 
-    def try_load_global_metadata(self, logical_source: str) -> Optional[dict]:
+    def try_load_global_metadata(self, logical_source: str) -> dict | None:
         try:
             return self.get_global_attributes(logical_source)
         except KeyError:
@@ -37,8 +34,7 @@ def add_instrument_attrs(self, instrument: str, level: str, descriptor: str):
             self.config_folder_path / f"imap_{instrument}_{level}_variable_attrs.yaml"
         )
         self._load_variable_attributes_if_file_exists(
-            self.config_folder_path
-            / f"imap_{instrument}_{level}_{descriptor}_variable_attrs.yaml"
+            self.config_folder_path / f"imap_{instrument}_{level}_{descriptor}_variable_attrs.yaml"
         )
 
         self._load_global_attributes_if_file_exists(
diff --git a/imap_l3_processing/codice/l3/hi/codice_hi_processor.py b/imap_l3_processing/codice/l3/hi/codice_hi_processor.py
index 421d1a6e..9dcc8305 100644
--- a/imap_l3_processing/codice/l3/hi/codice_hi_processor.py
+++ b/imap_l3_processing/codice/l3/hi/codice_hi_processor.py
@@ -7,8 +7,10 @@
 from imap_l3_processing.codice.l3.hi.direct_event.codice_hi_l3a_direct_events_dependencies import (
     CodiceHiL3aDirectEventsDependencies,
 )
-from imap_l3_processing.codice.l3.hi.models import CodiceHiL3PitchAngleDataProduct
-from imap_l3_processing.codice.l3.hi.models import CodiceL3HiDirectEvents
+from imap_l3_processing.codice.l3.hi.models import (
+    CodiceHiL3PitchAngleDataProduct,
+    CodiceL3HiDirectEvents,
+)
 from imap_l3_processing.codice.l3.hi.pitch_angle.codice_pitch_angle_dependencies import (
     CodicePitchAngleDependencies,
 )
@@ -21,9 +23,9 @@
 )
 from imap_l3_processing.models import InputMetadata
 from imap_l3_processing.pitch_angles import (
-    calculate_unit_vector,
-    calculate_pitch_angle,
     calculate_gyrophase,
+    calculate_pitch_angle,
+    calculate_unit_vector,
     rebin_by_pitch_angle_and_gyrophase,
 )
 from imap_l3_processing.processor import Processor
@@ -31,9 +33,7 @@
 
 
 class CodiceHiProcessor(Processor):
-    def __init__(
-        self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata
-    ):
+    def __init__(self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata):
         super().__init__(dependencies, input_metadata)
 
     def process(self) -> list[Path]:
@@ -43,9 +43,7 @@ def process(self) -> list[Path]:
             )
             data_product = self.process_l3a_direct_event(dependencies)
         elif self.input_metadata.data_level == "l3b":
-            dependencies = CodicePitchAngleDependencies.fetch_dependencies(
-                self.dependencies
-            )
+            dependencies = CodicePitchAngleDependencies.fetch_dependencies(self.dependencies)
             data_product = self.process_l3b(dependencies)
         else:
             raise NotImplementedError(
@@ -88,8 +86,7 @@ def process_l3a_direct_event(
 
                 incident_ion_energy[i, j, :npts] = l2_energy * correction_factors
                 estimated_mass[i, j, :npts] = (
-                    incident_ion_energy[i, j, :npts]
-                    / l2_data.energy_per_nuc[i, j, :npts]
+                    incident_ion_energy[i, j, :npts] / l2_data.energy_per_nuc[i, j, :npts]
                 )
 
         return CodiceL3HiDirectEvents(
@@ -120,22 +117,15 @@ def process_l3b(
         sectored_intensities = dependencies.codice_sectored_intensities_data
         epochs = dependencies.codice_sectored_intensities_data.epoch
         h_energy_bins = dependencies.codice_sectored_intensities_data.energy_h.shape[0]
-        he3he4_energy_bins = (
-            dependencies.codice_sectored_intensities_data.energy_he3he4.shape[0]
-        )
-        cno_energy_bins = (
-            dependencies.codice_sectored_intensities_data.energy_cno.shape[0]
-        )
-        fe_energy_bins = dependencies.codice_sectored_intensities_data.energy_fe.shape[
-            0
-        ]
+        he3he4_energy_bins = dependencies.codice_sectored_intensities_data.energy_he3he4.shape[0]
+        cno_energy_bins = dependencies.codice_sectored_intensities_data.energy_cno.shape[0]
+        fe_energy_bins = dependencies.codice_sectored_intensities_data.energy_fe.shape[0]
         rebinned_mag_data = mag_data.rebin_to(
             sectored_intensities.epoch, sectored_intensities.epoch_delta_plus
         )
 
         spin_angles_in_dps_elevation_by_spin_angle = (
-            sectored_intensities.spin_angles.T
-            + CODICE_INSTRUMENT_TO_SC_FRAME_SPIN_ANGLE_OFFSET
+            sectored_intensities.spin_angles.T + CODICE_INSTRUMENT_TO_SC_FRAME_SPIN_ANGLE_OFFSET
         ) % 360
 
         mag_unit_vectors = calculate_unit_vector(rebinned_mag_data)
@@ -151,12 +141,10 @@ def process_l3b(
         pitch_angle_delta_value = (180 / num_pitch_angle_bins) / 2
         gyrophase_delta_value = (360 / num_gyrophase_bins) / 2
         pitch_angle_bins = (
-            np.linspace(0, 180, num_pitch_angle_bins, endpoint=False)
-            + pitch_angle_delta_value
+            np.linspace(0, 180, num_pitch_angle_bins, endpoint=False) + pitch_angle_delta_value
         )
         gyrophase_bins = (
-            np.linspace(0, 360, num_gyrophase_bins, endpoint=False)
-            + gyrophase_delta_value
+            np.linspace(0, 360, num_gyrophase_bins, endpoint=False) + gyrophase_delta_value
         )
 
         h_pa_shape = (len(epochs), h_energy_bins, num_pitch_angle_bins)
@@ -222,11 +210,9 @@ def process_l3b(
             pitch_angles = calculate_pitch_angle(
                 particle_unit_vectors, mag_unit_vectors[time_index]
             )
-            gyrophases = calculate_gyrophase(
-                particle_unit_vectors, mag_unit_vectors[time_index]
-            )
+            gyrophases = calculate_gyrophase(particle_unit_vectors, mag_unit_vectors[time_index])
 
-            for species, species_intensity in species_intensities.items():
+            for species_intensity in species_intensities.values():
                 intensity = species_intensity.l2_intensity[time_index]
 
                 intensities_delta_plus = np.full_like(intensity, 0)
@@ -249,9 +235,7 @@ def process_l3b(
                     number_of_gyrophase_bins=num_gyrophase_bins,
                 )
 
-                species_intensity.intensity_by_pa[time_index] = (
-                    rebinned_intensities_by_pa
-                )
+                species_intensity.intensity_by_pa[time_index] = rebinned_intensities_by_pa
                 species_intensity.intensity_by_pa_and_gyro[time_index] = (
                     rebinned_intensities_by_pa_and_gyro
                 )
@@ -296,9 +280,7 @@ def process_l3b(
         )
 
 
-def _create_pa_and_gyro_nan_arrays(
-    pitch_angle_shape, pitch_angle_and_gyrophase_shape
-) -> np.array:
+def _create_pa_and_gyro_nan_arrays(pitch_angle_shape, pitch_angle_and_gyrophase_shape) -> np.array:
     return np.full(pitch_angle_shape, fill_value=np.nan), np.full(
         pitch_angle_and_gyrophase_shape, fill_value=np.nan
     )
diff --git a/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_l3a_direct_events_dependencies.py b/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_l3a_direct_events_dependencies.py
index 4ac6fca7..00d798b3 100644
--- a/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_l3a_direct_events_dependencies.py
+++ b/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_l3a_direct_events_dependencies.py
@@ -8,8 +8,8 @@
     CodiceHiMassCorrectionLookupTable,
 )
 from imap_l3_processing.codice.l3.hi.models import (
-    CodiceL2HiDirectEventData,
     CodiceL1aHiDirectEvents,
+    CodiceL2HiDirectEventData,
 )
 
 
@@ -27,9 +27,7 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
         l1a_hi_direct_events_file_paths = dependencies.get_file_paths(
             "codice", "hi-direct-events", data_type="l1a"
         )
-        ancillary_file_paths = dependencies.get_file_paths(
-            "codice", "l3-hi-mass-correction-lut"
-        )
+        ancillary_file_paths = dependencies.get_file_paths("codice", "l3-hi-mass-correction-lut")
 
         for download_location_file_path in [
             *l2_hi_direct_events_file_paths,
@@ -53,10 +51,8 @@ def from_file_paths(
     ):
         codice_l2_hi_data = CodiceL2HiDirectEventData.read_from_cdf(codice_l2_hi_cdf)
         codice_l1a_hi_data = CodiceL1aHiDirectEvents.read_from_cdf(codice_l1a_hi_cdf)
-        codice_hi_mass_correction_lut_ancillary = (
-            CodiceHiMassCorrectionLookupTable.from_file(
-                codice_hi_mass_correction_lut_ancillary
-            )
+        codice_hi_mass_correction_lut_ancillary = CodiceHiMassCorrectionLookupTable.from_file(
+            codice_hi_mass_correction_lut_ancillary
         )
 
         return cls(
diff --git a/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_mass_correction_lookup_table.py b/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_mass_correction_lookup_table.py
index 2c5133b9..7be21d1f 100644
--- a/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_mass_correction_lookup_table.py
+++ b/imap_l3_processing/codice/l3/hi/direct_event/codice_hi_mass_correction_lookup_table.py
@@ -6,7 +6,7 @@
 import numpy as np
 import pandas as pd
 
-SSD_SHEET_NAME_FORMAT = "ssd(\d+)"
+SSD_SHEET_NAME_FORMAT = r"ssd(\d+)"
 
 
 @dataclass
@@ -18,7 +18,7 @@ def from_file(cls, file_path: Path):
         data = {}
 
         file = pd.read_excel(file_path, sheet_name=None, index_col=0, skiprows=[0])
-        for sheet_name in file.keys():
+        for sheet_name in file:
             ssd_name_match = re.match(SSD_SHEET_NAME_FORMAT, sheet_name)
             if ssd_name_match:
                 ssd = int(ssd_name_match.group(1))
@@ -28,15 +28,11 @@ def from_file(cls, file_path: Path):
                     f"Not using sheet {sheet_name} from {file_path.name} ancillary! Expected sheet names in the format: {SSD_SHEET_NAME_FORMAT}"
                 )
 
-        assert len(data) > 0, (
-            f"Failed to read any correction factors from: {file_path.name}"
-        )
+        assert len(data) > 0, f"Failed to read any correction factors from: {file_path.name}"
 
         return cls(correction_factors=data)
 
-    def lookup_correction_factor(
-        self, ssd_id: int, energy_channel: int, tof: int
-    ) -> float:
+    def lookup_correction_factor(self, ssd_id: int, energy_channel: int, tof: int) -> float:
         data_for_ssd = self.correction_factors.get(ssd_id)
         if data_for_ssd is not None:
             return data_for_ssd[energy_channel, tof]
diff --git a/imap_l3_processing/codice/l3/hi/models.py b/imap_l3_processing/codice/l3/hi/models.py
index 5cd5fd0c..7818f50c 100644
--- a/imap_l3_processing/codice/l3/hi/models.py
+++ b/imap_l3_processing/codice/l3/hi/models.py
@@ -79,9 +79,9 @@ def read_from_cdf(cls, filename):
                 gain=read_variable_and_mask_fill_values(cdf[GAIN_VAR_NAME])[
                     :, :CODICE_HI_NUM_L2_PRIORITIES, ...
                 ],
-                spin_sector=read_variable_and_mask_fill_values(
-                    cdf[SPIN_SECTOR_VAR_NAME]
-                )[:, :CODICE_HI_NUM_L2_PRIORITIES, ...],
+                spin_sector=read_variable_and_mask_fill_values(cdf[SPIN_SECTOR_VAR_NAME])[
+                    :, :CODICE_HI_NUM_L2_PRIORITIES, ...
+                ],
             )
         # @formatter:on
 
@@ -124,21 +124,15 @@ def read_from_cdf(cls, filename):
 GYROPHASE_VAR_NAME = "gyrophase"
 GYROPHASE_DELTA_VAR_NAME = "gyrophase_delta"
 H_INTENSITY_BY_PITCH_ANGLE_VAR_NAME = "h_intensity_by_pitch_angle"
-H_INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_VAR_NAME = (
-    "h_intensity_by_pitch_angle_and_gyrophase"
-)
+H_INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_VAR_NAME = "h_intensity_by_pitch_angle_and_gyrophase"
 HE3HE4_INTENSITY_BY_PITCH_ANGLE_VAR_NAME = "he3he4_intensity_by_pitch_angle"
 HE3HE4_INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_VAR_NAME = (
     "he3he4_intensity_by_pitch_angle_and_gyrophase"
 )
 CNO_INTENSITY_BY_PITCH_ANGLE_VAR_NAME = "cno_intensity_by_pitch_angle"
-CNO_INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_VAR_NAME = (
-    "cno_intensity_by_pitch_angle_and_gyrophase"
-)
+CNO_INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_VAR_NAME = "cno_intensity_by_pitch_angle_and_gyrophase"
 FE_INTENSITY_BY_PITCH_ANGLE_VAR_NAME = "fe_intensity_by_pitch_angle"
-FE_INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_VAR_NAME = (
-    "fe_intensity_by_pitch_angle_and_gyrophase"
-)
+FE_INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_VAR_NAME = "fe_intensity_by_pitch_angle_and_gyrophase"
 ENERGY_H_LABEL_VAR_NAME = "energy_h_label"
 ENERGY_CNO_LABEL_VAR_NAME = "energy_cno_label"
 ENERGY_FE_LABEL_VAR_NAME = "energy_fe_label"
@@ -175,12 +169,8 @@ class CodiceL3HiDirectEvents(DataProduct):
     def __post_init__(self):
         self.priority_index = np.arange(CODICE_HI_NUM_L2_PRIORITIES)
         self.event_index = np.arange(self.ssd_id.shape[-1])
-        self.priority_index_label = np.array(
-            [str(i) for i in range(CODICE_HI_NUM_L2_PRIORITIES)]
-        )
-        self.event_index_label = np.array(
-            [str(i) for i in range(len(self.event_index))]
-        )
+        self.priority_index_label = np.array([str(i) for i in range(CODICE_HI_NUM_L2_PRIORITIES)])
+        self.event_index_label = np.array([str(i) for i in range(len(self.event_index))])
 
     def to_data_product_variables(self) -> list[DataProductVariable]:
         return [
@@ -203,9 +193,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(SPIN_SECTOR_VAR_NAME, self.spin_sector),
             DataProductVariable(PRIORITY_INDEX_VAR_NAME, self.priority_index),
             DataProductVariable(EVENT_INDEX_VAR_NAME, self.event_index),
-            DataProductVariable(
-                PRIORITY_INDEX_LABEL_VAR_NAME, self.priority_index_label
-            ),
+            DataProductVariable(PRIORITY_INDEX_LABEL_VAR_NAME, self.priority_index_label),
             DataProductVariable(EVENT_INDEX_LABEL_VAR_NAME, self.event_index_label),
         ]
 
diff --git a/imap_l3_processing/codice/l3/hi/pitch_angle/codice_pitch_angle_dependencies.py b/imap_l3_processing/codice/l3/hi/pitch_angle/codice_pitch_angle_dependencies.py
index 8209251d..82cf69b4 100644
--- a/imap_l3_processing/codice/l3/hi/pitch_angle/codice_pitch_angle_dependencies.py
+++ b/imap_l3_processing/codice/l3/hi/pitch_angle/codice_pitch_angle_dependencies.py
@@ -45,6 +45,4 @@ def from_file_paths(
             codice_l2_sectored_intensities_path
         )
 
-        return cls(
-            mag_data, sectored_intensities, mag_is_preliminary=mag_is_preliminary
-        )
+        return cls(mag_data, sectored_intensities, mag_is_preliminary=mag_is_preliminary)
diff --git a/imap_l3_processing/codice/l3/lo/codice_lo_l3a_direct_events_dependencies.py b/imap_l3_processing/codice/l3/lo/codice_lo_l3a_direct_events_dependencies.py
index 73d28bd6..dd5c8f0e 100644
--- a/imap_l3_processing/codice/l3/lo/codice_lo_l3a_direct_events_dependencies.py
+++ b/imap_l3_processing/codice/l3/lo/codice_lo_l3a_direct_events_dependencies.py
@@ -5,16 +5,16 @@
 from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.codice.l3.lo.direct_events.science.energy_lookup import (
-    EnergyLookup,
     ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR,
+    EnergyLookup,
 )
 from imap_l3_processing.codice.l3.lo.direct_events.science.mass_coefficient_lookup import (
     MassCoefficientLookup,
 )
 from imap_l3_processing.codice.l3.lo.models import (
-    CodiceLoL2DirectEventData,
-    CodiceLoL1aSWPriorityRates,
     CodiceLoL1aNSWPriorityRates,
+    CodiceLoL1aSWPriorityRates,
+    CodiceLoL2DirectEventData,
 )
 
 SW_PRIORITY_DESCRIPTOR = "lo-sw-priority"
@@ -38,17 +38,17 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
         direct_events_paths = []
         for science_input in dependencies.get_science_inputs():
             match science_input:
-                case ScienceInput(
-                    data_type="l1a", source="codice", descriptor=descriptor
-                ) if descriptor == SW_PRIORITY_DESCRIPTOR:
+                case ScienceInput(data_type="l1a", source="codice", descriptor=descriptor) if (
+                    descriptor == SW_PRIORITY_DESCRIPTOR
+                ):
                     sw_priority_rates_paths.extend(science_input.filename_list)
-                case ScienceInput(
-                    data_type="l1a", source="codice", descriptor=descriptor
-                ) if descriptor == NSW_PRIORITY_DESCRIPTOR:
+                case ScienceInput(data_type="l1a", source="codice", descriptor=descriptor) if (
+                    descriptor == NSW_PRIORITY_DESCRIPTOR
+                ):
                     nsw_priority_rates_paths.extend(science_input.filename_list)
-                case ScienceInput(
-                    data_type="l2", source="codice", descriptor=descriptor
-                ) if descriptor == DIRECT_EVENTS_DESCRIPTOR:
+                case ScienceInput(data_type="l2", source="codice", descriptor=descriptor) if (
+                    descriptor == DIRECT_EVENTS_DESCRIPTOR
+                ):
                     direct_events_paths.extend(science_input.filename_list)
 
         assert len(sw_priority_rates_paths) == 1
@@ -69,12 +69,8 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
         nsw_priority_rates_downloaded_path = download(nsw_priority_rates_path)
         direct_events_downloaded_path = download(direct_events_path)
 
-        mass_coefficients_file_downloaded_path = download(
-            mass_coefficients_file_path.name
-        )
-        energy_per_charge_lookup_downloaded_path = download(
-            energy_per_charge_file_path.name
-        )
+        mass_coefficients_file_downloaded_path = download(mass_coefficients_file_path.name)
+        energy_per_charge_lookup_downloaded_path = download(energy_per_charge_file_path.name)
 
         return cls.from_file_paths(
             sw_priority_rates_downloaded_path,
@@ -96,15 +92,9 @@ def from_file_paths(
         mass_coefficients_file_path = MassCoefficientLookup.read_from_csv(
             mass_coefficients_file_path
         )
-        sw_priority_rates = CodiceLoL1aSWPriorityRates.read_from_cdf(
-            sw_priority_rates_cdf
-        )
-        nsw_priority_rates = CodiceLoL1aNSWPriorityRates.read_from_cdf(
-            nsw_priority_rates_cdf
-        )
-        codice_l2_direct_events = CodiceLoL2DirectEventData.read_from_cdf(
-            direct_event_path
-        )
+        sw_priority_rates = CodiceLoL1aSWPriorityRates.read_from_cdf(sw_priority_rates_cdf)
+        nsw_priority_rates = CodiceLoL1aNSWPriorityRates.read_from_cdf(nsw_priority_rates_cdf)
+        codice_l2_direct_events = CodiceLoL2DirectEventData.read_from_cdf(direct_event_path)
         energy_lookup = EnergyLookup.read_from_csv(esa_to_energy_per_charge_file_path)
 
         return cls(
diff --git a/imap_l3_processing/codice/l3/lo/codice_lo_l3a_partial_densities_dependencies.py b/imap_l3_processing/codice/l3/lo/codice_lo_l3a_partial_densities_dependencies.py
index 910cdc6c..a4bda7b0 100644
--- a/imap_l3_processing/codice/l3/lo/codice_lo_l3a_partial_densities_dependencies.py
+++ b/imap_l3_processing/codice/l3/lo/codice_lo_l3a_partial_densities_dependencies.py
@@ -24,9 +24,9 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
 
         for science_input in dependencies.get_science_inputs():
             match science_input:
-                case ScienceInput(
-                    data_type="l2", source="codice", descriptor=descriptor
-                ) if descriptor == SW_SPECIES_DESCRIPTOR:
+                case ScienceInput(data_type="l2", source="codice", descriptor=descriptor) if (
+                    descriptor == SW_SPECIES_DESCRIPTOR
+                ):
                     sectored_intensities_file_paths.extend(science_input.filename_list)
 
         assert len(sectored_intensities_file_paths) == 1
@@ -36,9 +36,7 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
             source="codice", descriptor=MASS_PER_CHARGE_DESCRIPTOR
         )
         assert len(mass_per_charge_ancillary_file_paths) == 1
-        mass_per_charge_ancillary_file_path = mass_per_charge_ancillary_file_paths[
-            0
-        ].name
+        mass_per_charge_ancillary_file_path = mass_per_charge_ancillary_file_paths[0].name
 
         sectored_intensities_downloaded_path = imap_data_access.download(
             sectored_intensities_file_path
@@ -54,9 +52,7 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
 
     @classmethod
     def from_file_paths(cls, codice_l2_lo_cdf: Path, mass_per_charge_lookup_path: Path):
-        mass_per_charge_lookup = MassPerChargeLookup.read_from_file(
-            mass_per_charge_lookup_path
-        )
+        mass_per_charge_lookup = MassPerChargeLookup.read_from_file(mass_per_charge_lookup_path)
         codice_l2_lo_data = CodiceLoL2SWSpeciesData.read_from_cdf(codice_l2_lo_cdf)
 
         return cls(codice_l2_lo_data, mass_per_charge_lookup)
diff --git a/imap_l3_processing/codice/l3/lo/codice_lo_l3a_ratios_dependencies.py b/imap_l3_processing/codice/l3/lo/codice_lo_l3a_ratios_dependencies.py
index 89df62b0..3a86f3fd 100644
--- a/imap_l3_processing/codice/l3/lo/codice_lo_l3a_ratios_dependencies.py
+++ b/imap_l3_processing/codice/l3/lo/codice_lo_l3a_ratios_dependencies.py
@@ -27,8 +27,6 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
 
     @classmethod
     def from_file_paths(cls, codice_l2_lo_cdf: Path | str):
-        partial_density_data = CodiceLoPartialDensityData.read_from_cdf(
-            codice_l2_lo_cdf
-        )
+        partial_density_data = CodiceLoPartialDensityData.read_from_cdf(codice_l2_lo_cdf)
 
         return cls(partial_density_data)
diff --git a/imap_l3_processing/codice/l3/lo/codice_lo_l3b_3d_distributions_dependencies.py b/imap_l3_processing/codice/l3/lo/codice_lo_l3b_3d_distributions_dependencies.py
index d0aa4110..59b6c5fb 100644
--- a/imap_l3_processing/codice/l3/lo/codice_lo_l3b_3d_distributions_dependencies.py
+++ b/imap_l3_processing/codice/l3/lo/codice_lo_l3b_3d_distributions_dependencies.py
@@ -11,8 +11,8 @@
     EfficiencyLookup,
 )
 from imap_l3_processing.codice.l3.lo.direct_events.science.energy_lookup import (
-    EnergyLookup,
     ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR,
+    EnergyLookup,
 )
 from imap_l3_processing.codice.l3.lo.direct_events.science.geometric_factor_lookup import (
     GeometricFactorLookup,
@@ -43,9 +43,9 @@ def fetch_dependencies(
         l3a_direct_event_paths = []
         for input in processing_input_collection.get_science_inputs():
             match input:
-                case ScienceInput(
-                    data_type="l3a", source="codice", descriptor=descriptor
-                ) if descriptor == DIRECT_EVENTS_DESCRIPTOR:
+                case ScienceInput(data_type="l3a", source="codice", descriptor=descriptor) if (
+                    descriptor == DIRECT_EVENTS_DESCRIPTOR
+                ):
                     l3a_direct_event_paths.extend(input.filename_list)
 
         [direct_events_path] = l3a_direct_event_paths
@@ -67,15 +67,9 @@ def fetch_dependencies(
         )
 
         direct_events_downloaded_path = imap_data_access.download(direct_events_path)
-        mass_species_bin_downloaded_path = imap_data_access.download(
-            mass_species_bin_path.name
-        )
-        geometric_factor_downloaded_path = imap_data_access.download(
-            geometric_factor_path.name
-        )
-        efficiency_factor_downloaded_path = imap_data_access.download(
-            efficiency_factor_path.name
-        )
+        mass_species_bin_downloaded_path = imap_data_access.download(mass_species_bin_path.name)
+        geometric_factor_downloaded_path = imap_data_access.download(geometric_factor_path.name)
+        efficiency_factor_downloaded_path = imap_data_access.download(efficiency_factor_path.name)
         esa_to_energy_per_charge_downloaded_path = imap_data_access.download(
             esa_to_energy_per_charge_path.name
         )
@@ -99,18 +93,12 @@ def from_file_paths(
         energy_per_charge_lut: Path,
         species: str,
     ):
-        mass_species_bin_lookup = MassSpeciesBinLookup.read_from_csv(
-            mass_species_bin_lut
-        )
+        mass_species_bin_lookup = MassSpeciesBinLookup.read_from_csv(mass_species_bin_lut)
         return cls(
             l3a_direct_event_data=CodiceLoDirectEventData.read_from_cdf(l3a_file_path),
             mass_species_bin_lookup=mass_species_bin_lookup,
-            geometric_factors_lookup=GeometricFactorLookup.read_from_csv(
-                geometric_factors_lut
-            ),
-            efficiency_factors_lut=EfficiencyLookup.read_from_csv(
-                efficiency_factors_lut, species
-            ),
+            geometric_factors_lookup=GeometricFactorLookup.read_from_csv(geometric_factors_lut),
+            efficiency_factors_lut=EfficiencyLookup.read_from_csv(efficiency_factors_lut, species),
             energy_per_charge_lut=EnergyLookup.read_from_csv(energy_per_charge_lut),
             species=species,
         )
diff --git a/imap_l3_processing/codice/l3/lo/codice_lo_processor.py b/imap_l3_processing/codice/l3/lo/codice_lo_processor.py
index ade699b8..36658ef3 100644
--- a/imap_l3_processing/codice/l3/lo/codice_lo_processor.py
+++ b/imap_l3_processing/codice/l3/lo/codice_lo_processor.py
@@ -3,13 +3,10 @@
 import numpy as np
 from imap_data_access.processing_input import ProcessingInputCollection
 from imap_processing.spice.geometry import (
-    get_spacecraft_to_instrument_spin_phase_offset,
     SpiceFrame,
+    get_spacecraft_to_instrument_spin_phase_offset,
 )
 
-from imap_l3_processing.codice.l3.lo.codice_lo_l3b_3d_distributions_dependencies import (
-    CodiceLoL3b3dDistributionsDependencies,
-)
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_direct_events_dependencies import (
     CodiceLoL3aDirectEventsDependencies,
 )
@@ -19,28 +16,31 @@
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_ratios_dependencies import (
     CodiceLoL3aRatiosDependencies,
 )
+from imap_l3_processing.codice.l3.lo.codice_lo_l3b_3d_distributions_dependencies import (
+    CodiceLoL3b3dDistributionsDependencies,
+)
 from imap_l3_processing.codice.l3.lo.direct_events.science.angle_lookup import (
-    SpinAngleLookup,
     PositionToElevationLookup,
+    SpinAngleLookup,
 )
 from imap_l3_processing.codice.l3.lo.models import (
-    CodiceLoL3aPartialDensityDataProduct,
     CodiceLoL3aDirectEventDataProduct,
-    CodiceLoPartialDensityData,
+    CodiceLoL3aPartialDensityDataProduct,
     CodiceLoL3aRatiosDataProduct,
-    CodiceLoL3ChargeStateDistributionsDataProduct,
     CodiceLoL3b3dDistributionDataProduct,
+    CodiceLoL3ChargeStateDistributionsDataProduct,
+    CodiceLoPartialDensityData,
 )
 from imap_l3_processing.codice.l3.lo.science.codice_lo_calculations import (
-    calculate_partial_densities,
     calculate_mass,
     calculate_mass_per_charge,
-    convert_counts_to_intensity,
-    rebin_to_counts_by_species_elevation_and_spin_sector,
-    combine_priorities_for_species_and_calculate_count_uncertainty,
     calculate_normalization_factor,
+    calculate_partial_densities,
+    combine_priorities_for_species_and_calculate_count_uncertainty,
+    convert_counts_to_intensity,
     lookup_normalization_per_event,
     rebin_3d_distribution_azimuth_to_elevation,
+    rebin_to_counts_by_species_elevation_and_spin_sector,
 )
 from imap_l3_processing.data_utils import safe_divide
 from imap_l3_processing.models import InputMetadata
@@ -51,9 +51,7 @@
 
 
 class CodiceLoProcessor(Processor):
-    def __init__(
-        self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata
-    ):
+    def __init__(self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata):
         super().__init__(dependencies, input_metadata)
 
     def process(self):
@@ -68,14 +66,10 @@ def process(self):
             )
             data_product = self.process_l3a_direct_event_data_product(dependencies)
         elif self.input_metadata.descriptor == "lo-sw-ratios":
-            dependencies = CodiceLoL3aRatiosDependencies.fetch_dependencies(
-                self.dependencies
-            )
+            dependencies = CodiceLoL3aRatiosDependencies.fetch_dependencies(self.dependencies)
             data_product = self.process_l3a_ratios(dependencies)
         elif self.input_metadata.descriptor == "lo-sw-charge-state-distributions":
-            dependencies = CodiceLoL3aRatiosDependencies.fetch_dependencies(
-                self.dependencies
-            )
+            dependencies = CodiceLoL3aRatiosDependencies.fetch_dependencies(self.dependencies)
             data_product = self.process_l3a_charge_state_distributions(dependencies)
         elif "3d-distribution" in self.input_metadata.descriptor:
             species = self.input_metadata.descriptor.split("-")[1]
@@ -131,31 +125,21 @@ def process_l3a_charge_state_distributions(
         c5 = dependencies.partial_density_data.cplus5_partial_density
         c6 = dependencies.partial_density_data.cplus6_partial_density
 
-        o_densities = _average_over_block(
-            np.column_stack((o5, o6, o7, o8)), block_size=3
-        )
-        o_distribution = safe_divide(
-            o_densities, np.sum(o_densities, axis=1, keepdims=True)
-        )
+        o_densities = _average_over_block(np.column_stack((o5, o6, o7, o8)), block_size=3)
+        o_distribution = safe_divide(o_densities, np.sum(o_densities, axis=1, keepdims=True))
 
         c_densities = _average_over_block(np.column_stack((c4, c5, c6)), block_size=3)
-        c_distribution = safe_divide(
-            c_densities, np.sum(c_densities, axis=1, keepdims=True)
-        )
+        c_distribution = safe_divide(c_densities, np.sum(c_densities, axis=1, keepdims=True))
 
         return CodiceLoL3ChargeStateDistributionsDataProduct(
             self.input_metadata,
             epoch=_average_dates_over_block(dependencies.partial_density_data.epoch, 3),
-            epoch_delta=_sum_over_block(
-                dependencies.partial_density_data.epoch_delta, 3
-            ),
+            epoch_delta=_sum_over_block(dependencies.partial_density_data.epoch_delta, 3),
             oxygen_charge_state_distribution=o_distribution,
             carbon_charge_state_distribution=c_distribution,
         )
 
-    def process_l3a_partial_densities(
-        self, dependencies: CodiceLoL3aPartialDensitiesDependencies
-    ):
+    def process_l3a_partial_densities(self, dependencies: CodiceLoL3aPartialDensitiesDependencies):
         codice_lo_l2_data = dependencies.codice_l2_lo_data
         mass_per_charge_lookup = dependencies.mass_per_charge_lookup
         h_plus_partial_density = calculate_partial_densities(
@@ -254,12 +238,8 @@ def process_l3a_partial_densities(
     def process_l3a_direct_event_data_product(
         self, dependencies: CodiceLoL3aDirectEventsDependencies
     ) -> CodiceLoL3aDirectEventDataProduct:
-        codice_sw_priority_counts_l1a_data = (
-            dependencies.codice_lo_l1a_sw_priority_rates
-        )
-        codice_nsw_priority_counts_l1a_data = (
-            dependencies.codice_lo_l1a_nsw_priority_rates
-        )
+        codice_sw_priority_counts_l1a_data = dependencies.codice_lo_l1a_sw_priority_rates
+        codice_nsw_priority_counts_l1a_data = dependencies.codice_lo_l1a_nsw_priority_rates
         codice_direct_events = dependencies.codice_l2_direct_events
         esa_energy_per_charge_lookup = dependencies.energy_lookup
 
@@ -300,12 +280,10 @@ def process_l3a_direct_event_data_product(
             codice_sw_priority_counts_l1a_data.epoch,
             direct_event_epochs,
         )
-        nsw_aligned, nsw_missing = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                nsw_priority_counts,
-                codice_nsw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        nsw_aligned, nsw_missing = _align_priority_counts_variable_to_direct_event_epochs(
+            nsw_priority_counts,
+            codice_nsw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
         acquisition_time_per_esa_aligned, _ = (
             _align_priority_counts_variable_to_direct_event_epochs(
@@ -314,54 +292,40 @@ def process_l3a_direct_event_data_product(
                 direct_event_epochs,
             )
         )
-        rgfo_half_spin_aligned, _ = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                codice_sw_priority_counts_l1a_data.rgfo_half_spin,
-                codice_sw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        rgfo_half_spin_aligned, _ = _align_priority_counts_variable_to_direct_event_epochs(
+            codice_sw_priority_counts_l1a_data.rgfo_half_spin,
+            codice_sw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
-        rgfo_spin_sector_aligned, _ = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                codice_sw_priority_counts_l1a_data.rgfo_spin_sector,
-                codice_sw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        rgfo_spin_sector_aligned, _ = _align_priority_counts_variable_to_direct_event_epochs(
+            codice_sw_priority_counts_l1a_data.rgfo_spin_sector,
+            codice_sw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
-        rgfo_esa_step_aligned, _ = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                codice_sw_priority_counts_l1a_data.rgfo_esa_step,
-                codice_sw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        rgfo_esa_step_aligned, _ = _align_priority_counts_variable_to_direct_event_epochs(
+            codice_sw_priority_counts_l1a_data.rgfo_esa_step,
+            codice_sw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
-        half_spin_per_esa_step_aligned, _ = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                codice_sw_priority_counts_l1a_data.half_spin_per_esa_step,
-                codice_sw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        half_spin_per_esa_step_aligned, _ = _align_priority_counts_variable_to_direct_event_epochs(
+            codice_sw_priority_counts_l1a_data.half_spin_per_esa_step,
+            codice_sw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
-        nso_spin_sector_aligned, _ = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                codice_sw_priority_counts_l1a_data.nso_spin_sector,
-                codice_sw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        nso_spin_sector_aligned, _ = _align_priority_counts_variable_to_direct_event_epochs(
+            codice_sw_priority_counts_l1a_data.nso_spin_sector,
+            codice_sw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
-        nso_esa_step_aligned, _ = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                codice_sw_priority_counts_l1a_data.nso_esa_step,
-                codice_sw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        nso_esa_step_aligned, _ = _align_priority_counts_variable_to_direct_event_epochs(
+            codice_sw_priority_counts_l1a_data.nso_esa_step,
+            codice_sw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
-        nso_half_spin_aligned, _ = (
-            _align_priority_counts_variable_to_direct_event_epochs(
-                codice_sw_priority_counts_l1a_data.nso_half_spin,
-                codice_sw_priority_counts_l1a_data.epoch,
-                direct_event_epochs,
-            )
+        nso_half_spin_aligned, _ = _align_priority_counts_variable_to_direct_event_epochs(
+            codice_sw_priority_counts_l1a_data.nso_half_spin,
+            codice_sw_priority_counts_l1a_data.epoch,
+            direct_event_epochs,
         )
         stacked_priorities = np.concatenate(
             [np.ma.filled(sw_aligned, np.nan), np.ma.filled(nsw_aligned, np.nan)],
@@ -445,9 +409,7 @@ def process_l3b_3d_distribution_product(
         species_index = mass_species_bin_lookup.get_species_index(dependencies.species)
         counts_for_species = counts_3d_data[species_index]
         normalized_counts, counts_uncertainty = (
-            combine_priorities_for_species_and_calculate_count_uncertainty(
-                counts_for_species
-            )
+            combine_priorities_for_species_and_calculate_count_uncertainty(counts_for_species)
         )
         geometric_factors = geometric_factor_lut.get_geometric_factors(
             dependencies.l3a_direct_event_data.rgfo_half_spin,
@@ -485,8 +447,7 @@ def process_l3b_3d_distribution_product(
             dependencies.l3a_direct_event_data.half_spin_per_esa_step,
         )
         offset_degrees = (
-            get_spacecraft_to_instrument_spin_phase_offset(SpiceFrame.IMAP_CODICE) * 360
-            - 180
+            get_spacecraft_to_instrument_spin_phase_offset(SpiceFrame.IMAP_CODICE) * 360 - 180
         )
         spin_angle_bins_in_dps = (
             dependencies.l3a_direct_event_data.spin_angle_bin + offset_degrees
@@ -542,10 +503,7 @@ def _average_over_block(data_array: np.ndarray, block_size: int):
 
 def _sum_over_block(data_array: np.ndarray, block_size: int):
     return np.array(
-        [
-            data_array[i : i + block_size].sum()
-            for i in range(0, len(data_array), block_size)
-        ]
+        [data_array[i : i + block_size].sum() for i in range(0, len(data_array), block_size)]
     )
 
 
diff --git a/imap_l3_processing/codice/l3/lo/direct_events/science/efficiency_lookup.py b/imap_l3_processing/codice/l3/lo/direct_events/science/efficiency_lookup.py
index 77b3e1bc..cc98fe55 100644
--- a/imap_l3_processing/codice/l3/lo/direct_events/science/efficiency_lookup.py
+++ b/imap_l3_processing/codice/l3/lo/direct_events/science/efficiency_lookup.py
@@ -3,9 +3,9 @@
 from dataclasses import dataclass
 from pathlib import Path
 from typing import TypeVar
-import pandas as pd
 
 import numpy as np
+import pandas as pd
 
 POSITION = TypeVar("POSITION")
 ENERGIES = TypeVar("ENERGIES")
diff --git a/imap_l3_processing/codice/l3/lo/direct_events/science/geometric_factor_lookup.py b/imap_l3_processing/codice/l3/lo/direct_events/science/geometric_factor_lookup.py
index 7e7e0163..582c15db 100644
--- a/imap_l3_processing/codice/l3/lo/direct_events/science/geometric_factor_lookup.py
+++ b/imap_l3_processing/codice/l3/lo/direct_events/science/geometric_factor_lookup.py
@@ -7,9 +7,9 @@
 import pandas as pd
 
 from imap_l3_processing.codice.l3.lo.constants import (
-    CODICE_LO_NUM_SPIN_SECTORS,
-    CODICE_LO_NUM_ESA_STEPS,
     CODICE_LO_NUM_AZIMUTH_BINS,
+    CODICE_LO_NUM_ESA_STEPS,
+    CODICE_LO_NUM_SPIN_SECTORS,
     CODICE_SECOND_ERA,
     CODICE_THIRD_ERA,
 )
@@ -62,9 +62,7 @@ def _half_spin_to_esa_step_lookup():
 class GeometricFactorLookup:
     _full_factor: np.ndarray[(ESA_STEP, POSITION)]
     _reduced_factor: np.ndarray[(ESA_STEP, POSITION)]
-    _esa_step_end_index: np.ndarray = field(
-        default_factory=_half_spin_to_esa_step_lookup
-    )
+    _esa_step_end_index: np.ndarray = field(default_factory=_half_spin_to_esa_step_lookup)
 
     @classmethod
     def read_from_csv(cls, filepath: Path):
@@ -93,9 +91,7 @@ def get_geometric_factors(
         reduced_factor_full_shape = np.broadcast_to(
             self._reduced_factor[None, :, None, :], full_shape
         )
-        full_factor_full_shape = np.broadcast_to(
-            self._full_factor[None, :, None, :], full_shape
-        )
+        full_factor_full_shape = np.broadcast_to(self._full_factor[None, :, None, :], full_shape)
 
         if epoch < CODICE_SECOND_ERA:
             use_reduced = self._rgfo_half_spin_compare_only(rgfo_half_spin, half_spin)
@@ -132,9 +128,7 @@ def _is_past_rgfo(
 
         half_spin_e = half_spin[:, :, None, None]
         esa_step_axis = np.arange(CODICE_LO_NUM_ESA_STEPS)[None, :, None, None]
-        spin_sector_axis_mod = (
-            np.arange(CODICE_LO_NUM_SPIN_SECTORS)[None, None, :, None] % 12
-        )
+        spin_sector_axis_mod = np.arange(CODICE_LO_NUM_SPIN_SECTORS)[None, None, :, None] % 12
 
         half_spin_past = half_spin_e > rgfo_half_spin_e
         half_spin_match = half_spin_e == rgfo_half_spin_e
diff --git a/imap_l3_processing/codice/l3/lo/direct_events/science/mass_species_bin_lookup.py b/imap_l3_processing/codice/l3/lo/direct_events/science/mass_species_bin_lookup.py
index fdd9e9a5..6a6fc5ee 100644
--- a/imap_l3_processing/codice/l3/lo/direct_events/science/mass_species_bin_lookup.py
+++ b/imap_l3_processing/codice/l3/lo/direct_events/science/mass_species_bin_lookup.py
@@ -1,6 +1,5 @@
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional
 
 import numpy as np
 
@@ -15,9 +14,7 @@ class MassSpeciesBinLookup:
     def read_from_csv(cls, path: Path | str):
         loaded_csv = np.genfromtxt(path, delimiter=",", dtype=None, skip_header=1)
         range_data = list(zip(*loaded_csv))
-        [species, mpq_min, mpq_max, mass_min, mass_max] = [
-            list(column) for column in range_data
-        ]
+        [species, mpq_min, mpq_max, mass_min, mass_max] = [list(column) for column in range_data]
 
         return cls(
             species=species,
@@ -25,7 +22,7 @@ def read_from_csv(cls, path: Path | str):
             mass_ranges=list(zip(mass_min, mass_max)),
         )
 
-    def get_species(self, mass: float, mass_per_charge: float) -> Optional[str]:
+    def get_species(self, mass: float, mass_per_charge: float) -> str | None:
         for i in range(len(self.species)):
             lower_mass, upper_mass = self.mass_ranges[i]
             lower_mass_per_charge, upper_mass_per_charge = self.mass_per_charge[i]
diff --git a/imap_l3_processing/codice/l3/lo/models.py b/imap_l3_processing/codice/l3/lo/models.py
index 454ef345..0e087140 100644
--- a/imap_l3_processing/codice/l3/lo/models.py
+++ b/imap_l3_processing/codice/l3/lo/models.py
@@ -12,7 +12,7 @@
     read_numeric_variable,
     read_variable_and_mask_fill_values,
 )
-from imap_l3_processing.models import DataProductVariable, DataProduct
+from imap_l3_processing.models import DataProduct, DataProductVariable
 
 CODICE_LO_L2_NUM_PRIORITIES = 7
 
@@ -137,9 +137,9 @@ def read_from_cdf(cls, l2_direct_event_cdf: Path):
                 energy_step=read_variable_and_mask_fill_values(cdf["energy_step"])[
                     :, :CODICE_LO_L2_NUM_PRIORITIES, ...
                 ],
-                energy_per_charge=read_variable_and_mask_fill_values(
-                    cdf["energy_per_charge"]
-                )[:, :CODICE_LO_L2_NUM_PRIORITIES, ...],
+                energy_per_charge=read_variable_and_mask_fill_values(cdf["energy_per_charge"])[
+                    :, :CODICE_LO_L2_NUM_PRIORITIES, ...
+                ],
                 multi_flag=read_variable_and_mask_fill_values(cdf["multi_flag"])[
                     :, :CODICE_LO_L2_NUM_PRIORITIES, ...
                 ],
@@ -152,9 +152,9 @@ def read_from_cdf(cls, l2_direct_event_cdf: Path):
                 spin_sector=read_variable_and_mask_fill_values(cdf["spin_sector"])[
                     :, :CODICE_LO_L2_NUM_PRIORITIES, ...
                 ].astype(int),
-                elevation_angle=read_variable_and_mask_fill_values(
-                    cdf["elevation_angle"]
-                )[:, :CODICE_LO_L2_NUM_PRIORITIES, ...],
+                elevation_angle=read_variable_and_mask_fill_values(cdf["elevation_angle"])[
+                    :, :CODICE_LO_L2_NUM_PRIORITIES, ...
+                ],
                 tof=read_variable_and_mask_fill_values(cdf["tof"])[
                     :, :CODICE_LO_L2_NUM_PRIORITIES, ...
                 ],
@@ -203,16 +203,10 @@ def read_from_cdf(cls, cdf_path: Path):
                 epoch_delta_minus=cdf["epoch_delta_minus"][...],
                 acquisition_time_per_esa_step=cdf["acquisition_time_per_esa_step"][...],
                 spin_sector_index=cdf["spin_sector"][...],
-                rgfo_half_spin=read_variable_and_mask_fill_values(
-                    cdf["rgfo_half_spin"]
-                ),
+                rgfo_half_spin=read_variable_and_mask_fill_values(cdf["rgfo_half_spin"]),
                 nso_half_spin=read_variable_and_mask_fill_values(cdf["nso_half_spin"]),
-                sw_bias_gain_mode=read_variable_and_mask_fill_values(
-                    cdf["sw_bias_gain_mode"]
-                ),
-                st_bias_gain_mode=read_variable_and_mask_fill_values(
-                    cdf["st_bias_gain_mode"]
-                ),
+                sw_bias_gain_mode=read_variable_and_mask_fill_values(cdf["sw_bias_gain_mode"]),
+                st_bias_gain_mode=read_variable_and_mask_fill_values(cdf["st_bias_gain_mode"]),
                 data_quality=read_variable_and_mask_fill_values(cdf["data_quality"]),
                 spin_period=read_numeric_variable(cdf["spin_period"]),
                 p0_tcrs=read_variable_and_mask_fill_values(cdf["p0_tcrs"]),
@@ -223,13 +217,9 @@ def read_from_cdf(cls, cdf_path: Path):
                 half_spin_per_esa_step=read_variable_and_mask_fill_values(
                     cdf["half_spin_per_esa_step"]
                 ),
-                rgfo_spin_sector=read_variable_and_mask_fill_values(
-                    cdf["rgfo_spin_sector"]
-                ),
+                rgfo_spin_sector=read_variable_and_mask_fill_values(cdf["rgfo_spin_sector"]),
                 rgfo_esa_step=read_variable_and_mask_fill_values(cdf["rgfo_esa_step"]),
-                nso_spin_sector=read_variable_and_mask_fill_values(
-                    cdf["nso_spin_sector"]
-                ),
+                nso_spin_sector=read_variable_and_mask_fill_values(cdf["nso_spin_sector"]),
                 nso_esa_step=read_variable_and_mask_fill_values(cdf["nso_esa_step"]),
                 esa_step=read_variable_and_mask_fill_values(cdf["esa_step"]),
             )
@@ -260,21 +250,13 @@ def read_from_cdf(cls, cdf_path: Path):
                 epoch_delta_minus=cdf["epoch_delta_minus"][...],
                 acquisition_time_per_esa_step=cdf["acquisition_time_per_esa_step"][...],
                 spin_sector_index=cdf["spin_sector"][...],
-                rgfo_half_spin=read_variable_and_mask_fill_values(
-                    cdf["rgfo_half_spin"]
-                ),
+                rgfo_half_spin=read_variable_and_mask_fill_values(cdf["rgfo_half_spin"]),
                 data_quality=read_variable_and_mask_fill_values(cdf["data_quality"]),
                 p5_heavies=read_variable_and_mask_fill_values(cdf["p5_heavies"]),
-                p6_hplus_heplusplus=read_variable_and_mask_fill_values(
-                    cdf["p6_hplus_heplusplus"]
-                ),
+                p6_hplus_heplusplus=read_variable_and_mask_fill_values(cdf["p6_hplus_heplusplus"]),
                 nso_half_spin=read_variable_and_mask_fill_values(cdf["nso_half_spin"]),
-                sw_bias_gain_mode=read_variable_and_mask_fill_values(
-                    cdf["sw_bias_gain_mode"]
-                ),
-                st_bias_gain_mode=read_variable_and_mask_fill_values(
-                    cdf["st_bias_gain_mode"]
-                ),
+                sw_bias_gain_mode=read_variable_and_mask_fill_values(cdf["sw_bias_gain_mode"]),
+                st_bias_gain_mode=read_variable_and_mask_fill_values(cdf["st_bias_gain_mode"]),
                 spin_period=read_numeric_variable(cdf["spin_period"]),
             )
 
@@ -304,45 +286,19 @@ def read_from_cdf(cls, cdf_path: Path | str):
             return cls(
                 epoch=cdf[EPOCH_VAR_NAME][...],
                 epoch_delta=cdf[EPOCH_DELTA_VAR_NAME][...],
-                hplus_partial_density=read_numeric_variable(
-                    cdf[H_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                heplusplus_partial_density=read_numeric_variable(
-                    cdf[HE_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                cplus4_partial_density=read_numeric_variable(
-                    cdf[C4_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                cplus5_partial_density=read_numeric_variable(
-                    cdf[C5_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                cplus6_partial_density=read_numeric_variable(
-                    cdf[C6_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                oplus5_partial_density=read_numeric_variable(
-                    cdf[O5_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                oplus6_partial_density=read_numeric_variable(
-                    cdf[O6_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                oplus7_partial_density=read_numeric_variable(
-                    cdf[O7_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                oplus8_partial_density=read_numeric_variable(
-                    cdf[O8_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                ne_partial_density=read_numeric_variable(
-                    cdf[NE_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                mg_partial_density=read_numeric_variable(
-                    cdf[MG_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                si_partial_density=read_numeric_variable(
-                    cdf[SI_PARTIAL_DENSITY_VAR_NAME]
-                ),
-                fe_loq_partial_density=read_numeric_variable(
-                    cdf[FE_LOW_PARTIAL_DENSITY_VAR_NAME]
-                ),
+                hplus_partial_density=read_numeric_variable(cdf[H_PARTIAL_DENSITY_VAR_NAME]),
+                heplusplus_partial_density=read_numeric_variable(cdf[HE_PARTIAL_DENSITY_VAR_NAME]),
+                cplus4_partial_density=read_numeric_variable(cdf[C4_PARTIAL_DENSITY_VAR_NAME]),
+                cplus5_partial_density=read_numeric_variable(cdf[C5_PARTIAL_DENSITY_VAR_NAME]),
+                cplus6_partial_density=read_numeric_variable(cdf[C6_PARTIAL_DENSITY_VAR_NAME]),
+                oplus5_partial_density=read_numeric_variable(cdf[O5_PARTIAL_DENSITY_VAR_NAME]),
+                oplus6_partial_density=read_numeric_variable(cdf[O6_PARTIAL_DENSITY_VAR_NAME]),
+                oplus7_partial_density=read_numeric_variable(cdf[O7_PARTIAL_DENSITY_VAR_NAME]),
+                oplus8_partial_density=read_numeric_variable(cdf[O8_PARTIAL_DENSITY_VAR_NAME]),
+                ne_partial_density=read_numeric_variable(cdf[NE_PARTIAL_DENSITY_VAR_NAME]),
+                mg_partial_density=read_numeric_variable(cdf[MG_PARTIAL_DENSITY_VAR_NAME]),
+                si_partial_density=read_numeric_variable(cdf[SI_PARTIAL_DENSITY_VAR_NAME]),
+                fe_loq_partial_density=read_numeric_variable(cdf[FE_LOW_PARTIAL_DENSITY_VAR_NAME]),
                 fe_hiq_partial_density=read_numeric_variable(
                     cdf[FE_HIGH_PARTIAL_DENSITY_VAR_NAME]
                 ),
@@ -357,45 +313,19 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
         return [
             DataProductVariable(EPOCH_VAR_NAME, self.data.epoch),
             DataProductVariable(EPOCH_DELTA_VAR_NAME, self.data.epoch_delta),
-            DataProductVariable(
-                H_PARTIAL_DENSITY_VAR_NAME, self.data.hplus_partial_density
-            ),
-            DataProductVariable(
-                HE_PARTIAL_DENSITY_VAR_NAME, self.data.heplusplus_partial_density
-            ),
-            DataProductVariable(
-                C4_PARTIAL_DENSITY_VAR_NAME, self.data.cplus4_partial_density
-            ),
-            DataProductVariable(
-                C5_PARTIAL_DENSITY_VAR_NAME, self.data.cplus5_partial_density
-            ),
-            DataProductVariable(
-                C6_PARTIAL_DENSITY_VAR_NAME, self.data.cplus6_partial_density
-            ),
-            DataProductVariable(
-                O5_PARTIAL_DENSITY_VAR_NAME, self.data.oplus5_partial_density
-            ),
-            DataProductVariable(
-                O6_PARTIAL_DENSITY_VAR_NAME, self.data.oplus6_partial_density
-            ),
-            DataProductVariable(
-                O7_PARTIAL_DENSITY_VAR_NAME, self.data.oplus7_partial_density
-            ),
-            DataProductVariable(
-                O8_PARTIAL_DENSITY_VAR_NAME, self.data.oplus8_partial_density
-            ),
-            DataProductVariable(
-                NE_PARTIAL_DENSITY_VAR_NAME, self.data.ne_partial_density
-            ),
-            DataProductVariable(
-                MG_PARTIAL_DENSITY_VAR_NAME, self.data.mg_partial_density
-            ),
-            DataProductVariable(
-                SI_PARTIAL_DENSITY_VAR_NAME, self.data.si_partial_density
-            ),
-            DataProductVariable(
-                FE_LOW_PARTIAL_DENSITY_VAR_NAME, self.data.fe_loq_partial_density
-            ),
+            DataProductVariable(H_PARTIAL_DENSITY_VAR_NAME, self.data.hplus_partial_density),
+            DataProductVariable(HE_PARTIAL_DENSITY_VAR_NAME, self.data.heplusplus_partial_density),
+            DataProductVariable(C4_PARTIAL_DENSITY_VAR_NAME, self.data.cplus4_partial_density),
+            DataProductVariable(C5_PARTIAL_DENSITY_VAR_NAME, self.data.cplus5_partial_density),
+            DataProductVariable(C6_PARTIAL_DENSITY_VAR_NAME, self.data.cplus6_partial_density),
+            DataProductVariable(O5_PARTIAL_DENSITY_VAR_NAME, self.data.oplus5_partial_density),
+            DataProductVariable(O6_PARTIAL_DENSITY_VAR_NAME, self.data.oplus6_partial_density),
+            DataProductVariable(O7_PARTIAL_DENSITY_VAR_NAME, self.data.oplus7_partial_density),
+            DataProductVariable(O8_PARTIAL_DENSITY_VAR_NAME, self.data.oplus8_partial_density),
+            DataProductVariable(NE_PARTIAL_DENSITY_VAR_NAME, self.data.ne_partial_density),
+            DataProductVariable(MG_PARTIAL_DENSITY_VAR_NAME, self.data.mg_partial_density),
+            DataProductVariable(SI_PARTIAL_DENSITY_VAR_NAME, self.data.si_partial_density),
+            DataProductVariable(FE_LOW_PARTIAL_DENSITY_VAR_NAME, self.data.fe_loq_partial_density),
             DataProductVariable(
                 FE_HIGH_PARTIAL_DENSITY_VAR_NAME, self.data.fe_hiq_partial_density
             ),
@@ -486,12 +416,8 @@ def read_from_cdf(cls, cdf_path: Path | str):
                 apd_id=read_variable_and_mask_fill_values(cdf[APD_ID_VAR_NAME]),
                 data_quality=cdf[DATA_QUALITY_VAR_NAME][...],
                 elevation=read_numeric_variable(cdf[ELEVATION_VAR_NAME]),
-                energy_per_charge=read_numeric_variable(
-                    cdf[ENERGY_PER_CHARGE_VAR_NAME]
-                ),
-                energy_step=read_variable_and_mask_fill_values(
-                    cdf[ENERGY_STEP_VAR_NAME]
-                ),
+                energy_per_charge=read_numeric_variable(cdf[ENERGY_PER_CHARGE_VAR_NAME]),
+                energy_step=read_variable_and_mask_fill_values(cdf[ENERGY_STEP_VAR_NAME]),
                 gain=read_variable_and_mask_fill_values(cdf[GAIN_VAR_NAME]),
                 mass=read_numeric_variable(cdf[MASS_VAR_NAME]),
                 mass_per_charge=read_numeric_variable(cdf[MASS_PER_CHARGE_VAR_NAME]),
@@ -504,24 +430,16 @@ def read_from_cdf(cls, cdf_path: Path | str):
                 position=read_variable_and_mask_fill_values(cdf[POSITION_VAR_NAME]),
                 spin_angle=read_numeric_variable(cdf[SPIN_ANGLE_VAR_NAME]),
                 spin_angle_bin=read_numeric_variable(cdf[SPIN_ANGLE_BIN_VAR_NAME]),
-                spin_angle_bin_delta=read_numeric_variable(
-                    cdf[SPIN_ANGLE_DELTA_BIN_VAR_NAME]
-                ),
-                spin_sector=read_variable_and_mask_fill_values(
-                    cdf[SPIN_SECTOR_VAR_NAME]
-                ),
+                spin_angle_bin_delta=read_numeric_variable(cdf[SPIN_ANGLE_DELTA_BIN_VAR_NAME]),
+                spin_sector=read_variable_and_mask_fill_values(cdf[SPIN_SECTOR_VAR_NAME]),
                 half_spin_per_esa_step=read_variable_and_mask_fill_values(
                     cdf[HALF_SPIN_PER_ESA_STEP_VAR_NAME]
                 ),
-                rgfo_half_spin=read_variable_and_mask_fill_values(
-                    cdf[RGFO_HALF_SPIN_VAR_NAME]
-                ),
+                rgfo_half_spin=read_variable_and_mask_fill_values(cdf[RGFO_HALF_SPIN_VAR_NAME]),
                 rgfo_spin_sector=read_variable_and_mask_fill_values(
                     cdf[RGFO_SPIN_SECTOR_VAR_NAME]
                 ),
-                rgfo_esa_step=read_variable_and_mask_fill_values(
-                    cdf[RGFO_ESA_STEP_VAR_NAME]
-                ),
+                rgfo_esa_step=read_variable_and_mask_fill_values(cdf[RGFO_ESA_STEP_VAR_NAME]),
                 tof=read_variable_and_mask_fill_values(cdf[TOF_VAR_NAME]),
                 type=read_variable_and_mask_fill_values(cdf[TYPE_VAR_NAME]),
             )
@@ -567,12 +485,8 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(DATA_QUALITY_VAR_NAME, self.data_quality),
             DataProductVariable(ELEVATION_VAR_NAME, self.elevation),
             DataProductVariable(ENERGY_BIN_VAR_NAME, self.energy_bin),
-            DataProductVariable(
-                ENERGY_BIN_DELTA_MINUS_VAR_NAME, self.energy_bin_delta_minus
-            ),
-            DataProductVariable(
-                ENERGY_BIN_DELTA_PLUS_VAR_NAME, self.energy_bin_delta_plus
-            ),
+            DataProductVariable(ENERGY_BIN_DELTA_MINUS_VAR_NAME, self.energy_bin_delta_minus),
+            DataProductVariable(ENERGY_BIN_DELTA_PLUS_VAR_NAME, self.energy_bin_delta_plus),
             DataProductVariable(ENERGY_BIN_LABEL_VAR_NAME, self.energy_bin_label),
             DataProductVariable(ENERGY_PER_CHARGE_VAR_NAME, self.energy_per_charge),
             DataProductVariable(ENERGY_STEP_VAR_NAME, self.energy_step),
@@ -580,36 +494,26 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(EVENT_INDEX_VAR_NAME, self.event_index),
             DataProductVariable(EVENT_INDEX_LABEL_VAR_NAME, self.event_index_label),
             DataProductVariable(GAIN_VAR_NAME, self.gain),
-            DataProductVariable(
-                HALF_SPIN_PER_ESA_STEP_VAR_NAME, self.half_spin_per_esa_step
-            ),
+            DataProductVariable(HALF_SPIN_PER_ESA_STEP_VAR_NAME, self.half_spin_per_esa_step),
             DataProductVariable(MASS_VAR_NAME, self.mass),
             DataProductVariable(MASS_PER_CHARGE_VAR_NAME, self.mass_per_charge),
             DataProductVariable(MULTI_FLAG_VAR_NAME, self.multi_flag),
             DataProductVariable(NORMALIZATION_VAR_NAME, self.normalization),
-            DataProductVariable(
-                NORMALIZATION_PER_EVENT_VAR_NAME, self.normalization_per_event
-            ),
+            DataProductVariable(NORMALIZATION_PER_EVENT_VAR_NAME, self.normalization_per_event),
             DataProductVariable(NSO_ESA_STEP_VAR_NAME, self.nso_esa_step),
             DataProductVariable(NSO_SPIN_SECTOR_VAR_NAME, self.nso_spin_sector),
             DataProductVariable(NSO_HALF_SPIN_NAME, self.nso_half_spin),
             DataProductVariable(NUM_EVENTS_VAR_NAME, self.num_events),
             DataProductVariable(POSITION_VAR_NAME, self.position),
             DataProductVariable(PRIORITY_INDEX_VAR_NAME, self.priority_index),
-            DataProductVariable(
-                PRIORITY_INDEX_LABEL_VAR_NAME, self.priority_index_label
-            ),
+            DataProductVariable(PRIORITY_INDEX_LABEL_VAR_NAME, self.priority_index_label),
             DataProductVariable(RGFO_ESA_STEP_VAR_NAME, self.rgfo_esa_step),
             DataProductVariable(RGFO_SPIN_SECTOR_VAR_NAME, self.rgfo_spin_sector),
             DataProductVariable(RGFO_HALF_SPIN_NAME, self.rgfo_half_spin),
             DataProductVariable(SPIN_ANGLE_VAR_NAME, self.spin_angle),
             DataProductVariable(SPIN_ANGLE_BIN_VAR_NAME, self.spin_angle_bin),
-            DataProductVariable(
-                SPIN_ANGLE_DELTA_BIN_VAR_NAME, self.spin_angle_bin_delta
-            ),
-            DataProductVariable(
-                SPIN_ANGLE_BIN_LABEL_VAR_NAME, self.spin_angle_bin_label
-            ),
+            DataProductVariable(SPIN_ANGLE_DELTA_BIN_VAR_NAME, self.spin_angle_bin_delta),
+            DataProductVariable(SPIN_ANGLE_BIN_LABEL_VAR_NAME, self.spin_angle_bin_label),
             DataProductVariable(SPIN_SECTOR_VAR_NAME, self.spin_sector),
             DataProductVariable(TOF_VAR_NAME, self.tof),
             DataProductVariable(TYPE_VAR_NAME, self.type),
@@ -719,16 +623,10 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(self.species, self.species_data),
             DataProductVariable(ENERGY_LABEL_VAR_NAME, self.energy.astype(str)),
             DataProductVariable(SPIN_ANGLE_LABEL_VAR_NAME, self.spin_angle.astype(str)),
-            DataProductVariable(
-                ELEVATION_ANGLE_LABEL_VAR_NAME, self.elevation.astype(str)
-            ),
-            DataProductVariable(
-                f"{self.species}_stat_uncert", self.species_data_stat_uncert
-            ),
+            DataProductVariable(ELEVATION_ANGLE_LABEL_VAR_NAME, self.elevation.astype(str)),
+            DataProductVariable(f"{self.species}_stat_uncert", self.species_data_stat_uncert),
             DataProductVariable(RGFO_ESA_STEP_VAR_NAME, self.rgfo_esa_step),
             DataProductVariable(RGFO_SPIN_SECTOR_VAR_NAME, self.rgfo_spin_sector),
             DataProductVariable(RGFO_HALF_SPIN_VAR_NAME, self.rgfo_half_spin),
-            DataProductVariable(
-                HALF_SPIN_PER_ESA_STEP_VAR_NAME, self.half_spin_per_esa_step
-            ),
+            DataProductVariable(HALF_SPIN_PER_ESA_STEP_VAR_NAME, self.half_spin_per_esa_step),
         ]
diff --git a/imap_l3_processing/codice/l3/lo/science/codice_lo_calculations.py b/imap_l3_processing/codice/l3/lo/science/codice_lo_calculations.py
index 29224a7d..735ce52a 100644
--- a/imap_l3_processing/codice/l3/lo/science/codice_lo_calculations.py
+++ b/imap_l3_processing/codice/l3/lo/science/codice_lo_calculations.py
@@ -6,15 +6,15 @@
 
 from imap_l3_processing.codice.l3.lo.constants import (
     AZIMUTH_STEP_SIZE,
-    ELEVATION_STEP_SIZE,
-    ENERGY_STEP_SIZE,
-    ENERGY_LOST_IN_CARBON_FOIL,
-    POST_ACCELERATION_VOLTAGE_IN_KV,
-    CONVERSION_CONSTANT_K,
     CODICE_LO_NUM_AZIMUTH_BINS,
-    CONSTANT_C_FROM_INSTRUMENT_TEAM,
     CODICE_LO_NUM_ESA_STEPS,
     CODICE_LO_NUM_SPIN_SECTORS,
+    CONSTANT_C_FROM_INSTRUMENT_TEAM,
+    CONVERSION_CONSTANT_K,
+    ELEVATION_STEP_SIZE,
+    ENERGY_LOST_IN_CARBON_FOIL,
+    ENERGY_STEP_SIZE,
+    POST_ACCELERATION_VOLTAGE_IN_KV,
 )
 from imap_l3_processing.codice.l3.lo.direct_events.science.angle_lookup import (
     PositionToElevationLookup,
@@ -76,15 +76,9 @@ def calculate_mass(
     return np.e**mass_calculation
 
 
-def calculate_mass_per_charge(
-    energy_per_charge: np.ndarray, tof: np.ndarray
-) -> np.ndarray:
+def calculate_mass_per_charge(energy_per_charge: np.ndarray, tof: np.ndarray) -> np.ndarray:
     return (
-        (
-            energy_per_charge
-            + POST_ACCELERATION_VOLTAGE_IN_KV
-            - ENERGY_LOST_IN_CARBON_FOIL
-        )
+        (energy_per_charge + POST_ACCELERATION_VOLTAGE_IN_KV - ENERGY_LOST_IN_CARBON_FOIL)
         * (tof**2)
         * CONVERSION_CONSTANT_K
     )
@@ -103,8 +97,7 @@ def rebin_direct_events_for_normalization(
     half_spin = num_spin_sectors // 2
     result = np.zeros_like(base_counts)
     result[:, :, :, 0:half_spin] = (
-        base_counts[:, :, :, 0:half_spin]
-        + base_counts[:, :, :, half_spin:num_spin_sectors]
+        base_counts[:, :, :, 0:half_spin] + base_counts[:, :, :, half_spin:num_spin_sectors]
     )
     result[:, :, :, half_spin:num_spin_sectors] = result[:, :, :, 0:half_spin]
     return result
@@ -120,9 +113,7 @@ def rebin_direct_events_by_energy_and_spin_sector(
     num_epochs = num_events.shape[0]
     num_priorities = num_events.shape[1]
 
-    rebinned_output = np.zeros(
-        (num_epochs, num_priorities, num_energies, num_spin_sectors)
-    )
+    rebinned_output = np.zeros((num_epochs, num_priorities, num_energies, num_spin_sectors))
 
     for time_index in range(num_epochs):
         for priority_index in range(num_priorities):
@@ -312,9 +303,7 @@ def convert_counts_to_intensity(
     geometric_factor: np.ndarray[(EPOCH, ENERGY, SPIN_ANGLE, POSITION)],
 ) -> np.ndarray:
     count_rates = counts / acquisition_times[:, :, np.newaxis, np.newaxis]
-    reshaped_efficiency_data = efficiency_lookup.efficiency_data[
-        np.newaxis, :, np.newaxis, :
-    ]
+    reshaped_efficiency_data = efficiency_lookup.efficiency_data[np.newaxis, :, np.newaxis, :]
     denominator = (
         geometric_factor
         * energy_per_charge.bin_centers[np.newaxis, :, np.newaxis, np.newaxis]
diff --git a/imap_l3_processing/codice/quality_flags.py b/imap_l3_processing/codice/quality_flags.py
index 5bb577a9..d3c43036 100644
--- a/imap_l3_processing/codice/quality_flags.py
+++ b/imap_l3_processing/codice/quality_flags.py
@@ -1,4 +1,4 @@
-from imap_processing.quality_flags import FlagNameMixin, CommonFlags
+from imap_processing.quality_flags import CommonFlags, FlagNameMixin
 
 
 class CodiceL3Flags(FlagNameMixin):
diff --git a/imap_l3_processing/constants.py b/imap_l3_processing/constants.py
index f8bf6eed..6a7d5ef8 100644
--- a/imap_l3_processing/constants.py
+++ b/imap_l3_processing/constants.py
@@ -14,22 +14,18 @@
 HE_PUI_PARTICLE_MASS_KG = 6.64556828337e-27
 
 PROTON_CHARGE_OVER_MASS_C_PER_KG = PROTON_CHARGE_COULOMBS / PROTON_MASS_KG
-ALPHA_CHARGE_OVER_MASS_C_PER_KG = (
-    ALPHA_PARTICLE_CHARGE_COULOMBS / ALPHA_PARTICLE_MASS_KG
-)
+ALPHA_CHARGE_OVER_MASS_C_PER_KG = ALPHA_PARTICLE_CHARGE_COULOMBS / ALPHA_PARTICLE_MASS_KG
 
 PROTON_MASS_PER_CHARGE_M_P_PER_E = 1.0
 ALPHA_MASS_PER_CHARGE_M_P_PER_E = (ALPHA_PARTICLE_MASS_KG / PROTON_MASS_KG) / (
     ALPHA_PARTICLE_CHARGE_COULOMBS / PROTON_CHARGE_COULOMBS
 )
-HE_PUI_PARTICLE_MASS_PER_CHARGE_M_P_PER_E = (
-    HE_PUI_PARTICLE_MASS_KG / PROTON_MASS_KG
-) / (PUI_PARTICLE_CHARGE_COULOMBS / PROTON_CHARGE_COULOMBS)
+HE_PUI_PARTICLE_MASS_PER_CHARGE_M_P_PER_E = (HE_PUI_PARTICLE_MASS_KG / PROTON_MASS_KG) / (
+    PUI_PARTICLE_CHARGE_COULOMBS / PROTON_CHARGE_COULOMBS
+)
 
 BOLTZMANN_CONSTANT_JOULES_PER_KELVIN = 1.380_649e-23
-EV_TO_KELVIN = (
-    PROTON_CHARGE_COULOMBS / BOLTZMANN_CONSTANT_JOULES_PER_KELVIN
-)  # ≈ 11604.52 K/eV
+EV_TO_KELVIN = PROTON_CHARGE_COULOMBS / BOLTZMANN_CONSTANT_JOULES_PER_KELVIN  # ≈ 11604.52 K/eV
 
 ONE_SECOND_IN_MICROSECONDS = 1_000_000
 ONE_SECOND_IN_NANOSECONDS = 1_000_000_000
@@ -40,9 +36,7 @@
 
 CARRINGTON_ROTATION_IN_DAYS = 27.2753
 CARRINGTON_ROTATION_IN_SECONDS = CARRINGTON_ROTATION_IN_DAYS * SECONDS_PER_DAY
-CARRINGTON_ROTATION_IN_NANOSECONDS = (
-    CARRINGTON_ROTATION_IN_SECONDS * ONE_SECOND_IN_NANOSECONDS
-)
+CARRINGTON_ROTATION_IN_NANOSECONDS = CARRINGTON_ROTATION_IN_SECONDS * ONE_SECOND_IN_NANOSECONDS
 
 METERS_PER_KILOMETER = 1_000
 CENTIMETERS_PER_METER = 100
diff --git a/imap_l3_processing/data_utils.py b/imap_l3_processing/data_utils.py
index ab096f38..abeb4b64 100644
--- a/imap_l3_processing/data_utils.py
+++ b/imap_l3_processing/data_utils.py
@@ -58,17 +58,13 @@ def __init__(
         right_delta = np.abs(from_epoch_as_dt64[right_indices] - to_epoch_as_dt64)
         left_delta = np.abs(from_epoch_as_dt64[left_indices] - to_epoch_as_dt64)
 
-        self.best_indices = np.where(
-            right_delta < left_delta, right_indices, left_indices
-        )
+        self.best_indices = np.where(right_delta < left_delta, right_indices, left_indices)
 
         min_deltas = np.abs(from_epoch_as_dt64[self.best_indices] - to_epoch_as_dt64)
         self.min_outside_range = min_deltas > maximum_distance
 
     def interpolate_data(self) -> np.ndarray:
-        closest_data = self.only_valid_from_data[self.best_indices].astype(
-            float, copy=True
-        )
+        closest_data = self.only_valid_from_data[self.best_indices].astype(float, copy=True)
         closest_data[self.min_outside_range] = np.nan
         return closest_data
 
diff --git a/imap_l3_processing/glows/glows_processor.py b/imap_l3_processing/glows/glows_processor.py
index e9600bc1..60330462 100644
--- a/imap_l3_processing/glows/glows_processor.py
+++ b/imap_l3_processing/glows/glows_processor.py
@@ -9,27 +9,26 @@
 from datetime import datetime, timedelta
 from pathlib import Path
 from subprocess import run
-from typing import Optional
-from zipfile import ZipFile, ZIP_DEFLATED
+from zipfile import ZIP_DEFLATED, ZipFile
 
 import numpy as np
 from imap_data_access.file_validation import (
-    generate_imap_file_path,
-    ScienceFilePath,
     AncillaryFilePath,
+    ScienceFilePath,
     Version,
+    generate_imap_file_path,
 )
 from imap_data_access.processing_input import ProcessingInputCollection
 
 from imap_l3_processing.constants import TEMP_CDF_FOLDER_PATH
 from imap_l3_processing.glows.descriptors import (
     GLOWS_L3A_DESCRIPTOR,
-    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
-    GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
-    GLOWS_L3D_DESCRIPTOR,
     GLOWS_L3B_DESCRIPTOR,
     GLOWS_L3C_DESCRIPTOR,
+    GLOWS_L3D_DESCRIPTOR,
     GLOWS_L3E_LO_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3a.glows_l3a_dependencies import GlowsL3ADependencies
 from imap_l3_processing.glows.l3a.glows_toolkit.l3a_data import L3aData
@@ -41,10 +40,10 @@
     GlowsL3BCInitializerData,
 )
 from imap_l3_processing.glows.l3bc.models import (
+    ExternalDependencies,
+    GlowsL3BCProcessorOutput,
     GlowsL3BIonizationRate,
     GlowsL3CSolarWind,
-    GlowsL3BCProcessorOutput,
-    ExternalDependencies,
 )
 from imap_l3_processing.glows.l3bc.science.filter_out_bad_days import filter_l3a_files
 from imap_l3_processing.glows.l3bc.science.generate_l3bc import generate_l3bc
@@ -53,10 +52,10 @@
 from imap_l3_processing.glows.l3d.glows_l3d_initializer import GlowsL3DInitializer
 from imap_l3_processing.glows.l3d.models import GlowsL3DProcessorOutput
 from imap_l3_processing.glows.l3d.utils import (
-    create_glows_l3b_json_file_from_cdf,
-    create_glows_l3c_json_file_from_cdf,
     PATH_TO_L3D_TOOLKIT,
     convert_json_to_l3d_data_product,
+    create_glows_l3b_json_file_from_cdf,
+    create_glows_l3c_json_file_from_cdf,
     get_parent_file_names_from_l3d_json,
     rename_l3d_text_outputs,
 )
@@ -69,10 +68,10 @@
 from imap_l3_processing.glows.l3e.glows_l3e_lo_model import GlowsL3ELoData
 from imap_l3_processing.glows.l3e.glows_l3e_ultra_model import GlowsL3EUltraData
 from imap_l3_processing.glows.l3e.glows_l3e_utils import (
-    determine_call_args_for_l3e_executable,
-    get_lo_pivot_angles,
     compute_glows_flags_for_repoint,
+    determine_call_args_for_l3e_executable,
     determine_spacecraft_info_using_predict_if_needed,
+    get_lo_pivot_angles,
 )
 from imap_l3_processing.glows.l3e.reprocess_info import fetch_reprocess_info
 from imap_l3_processing.models import InputMetadata, VersionMap
@@ -83,16 +82,12 @@
 
 
 class GlowsProcessor(Processor):
-    def __init__(
-        self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata
-    ):
+    def __init__(self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata):
         super().__init__(dependencies, input_metadata)
 
     def process(self):
         if self.input_metadata.data_level == "l3a":
-            l3a_dependencies = GlowsL3ADependencies.fetch_dependencies(
-                self.dependencies
-            )
+            l3a_dependencies = GlowsL3ADependencies.fetch_dependencies(self.dependencies)
 
             products = []
             l3a_output = self.process_l3a(l3a_dependencies)
@@ -102,13 +97,9 @@ def process(self):
             return products
         elif self.input_metadata.data_level == "l3b":
             products_list = []
-            l3bc_major_version = self.input_metadata.version.lookup(
-                GLOWS_L3B_DESCRIPTOR
-            ).major
+            l3bc_major_version = self.input_metadata.version.lookup(GLOWS_L3B_DESCRIPTOR).major
             l3bc_initializer_data: GlowsL3BCInitializerData = (
-                GlowsL3BCInitializer.get_crs_to_process(
-                    self.dependencies, l3bc_major_version
-                )
+                GlowsL3BCInitializer.get_crs_to_process(self.dependencies, l3bc_major_version)
             )
 
             if len(l3bc_initializer_data.l3bc_dependencies) > 0:
@@ -126,9 +117,7 @@ def process(self):
 
             reprocess_info = fetch_reprocess_info(self.dependencies)
 
-            l3d_major_version = self.input_metadata.version.lookup(
-                GLOWS_L3D_DESCRIPTOR
-            ).major
+            l3d_major_version = self.input_metadata.version.lookup(GLOWS_L3D_DESCRIPTOR).major
             l3bs = list(
                 {
                     **l3bc_initializer_data.l3bs_by_cr,
@@ -149,9 +138,7 @@ def process(self):
                 l3d_major_version,
             )
             if l3d_initializer_result is None:
-                logger.info(
-                    "No inputs to L3d have changed. Skipping processing of L3d and L3e!"
-                )
+                logger.info("No inputs to L3d have changed. Skipping processing of L3d and L3e!")
                 return products_list
 
             version_number, glows_l3d_dependency, old_l3d = l3d_initializer_result
@@ -165,9 +152,7 @@ def process(self):
             logger.info(
                 f"Finished processing L3d up to CR: {process_l3d_result.last_processed_cr}"
             )
-            logger.info(
-                f"Saved L3d CDF output to: {process_l3d_result.l3d_cdf_file_path}"
-            )
+            logger.info(f"Saved L3d CDF output to: {process_l3d_result.l3d_cdf_file_path}")
             for txt_file in process_l3d_result.l3d_text_file_paths:
                 logger.info(f"Saved L3d text file output to: {txt_file}")
 
@@ -199,9 +184,7 @@ def process(self):
 
             return products_list
 
-    def process_l3a(
-        self, dependencies: GlowsL3ADependencies
-    ) -> Optional[GlowsL3LightCurve]:
+    def process_l3a(self, dependencies: GlowsL3ADependencies) -> GlowsL3LightCurve | None:
         data = dependencies.data
         l3_data = L3aData(dependencies.ancillary_files)
         l3_data.process_l2_data_file(data)
@@ -236,14 +219,11 @@ def archive_dependencies(
         start_date = l3bc_deps.start_date.strftime("%Y%m%d")
         minor_version_str = str(Version(None, l3bc_deps.version.minor))
         zip_path = (
-            TEMP_CDF_FOLDER_PATH
-            / f"imap_glows_l3b-archive_{start_date}_{minor_version_str}.zip"
+            TEMP_CDF_FOLDER_PATH / f"imap_glows_l3b-archive_{start_date}_{minor_version_str}.zip"
         )
         json_filename = "cr_to_process.json"
         with ZipFile(zip_path, "w", ZIP_DEFLATED) as file:
-            file.write(
-                external_dependencies.lyman_alpha_path, "lyman_alpha_composite.nc"
-            )
+            file.write(external_dependencies.lyman_alpha_path, "lyman_alpha_composite.nc")
             file.write(external_dependencies.omni2_data_path, "omni2_all_years.dat")
             file.write(external_dependencies.f107_index_file_path, "f107_fluxtable.txt")
             cr = {
@@ -252,12 +232,8 @@ def archive_dependencies(
                 "cr_start_date": str(l3bc_deps.start_date),
                 "cr_end_date": str(l3bc_deps.end_date),
                 "bad_days_list": l3bc_deps.ancillary_files["bad_days_list"].name,
-                "pipeline_settings": l3bc_deps.ancillary_files[
-                    "pipeline_settings"
-                ].name,
-                "waw_helioion_mp": l3bc_deps.ancillary_files[
-                    "WawHelioIonMP_parameters"
-                ].name,
+                "pipeline_settings": l3bc_deps.ancillary_files["pipeline_settings"].name,
+                "waw_helioion_mp": l3bc_deps.ancillary_files["WawHelioIonMP_parameters"].name,
                 "uv_anisotropy": l3bc_deps.ancillary_files["uv_anisotropy"].name,
                 "repointing_file": l3bc_deps.repointing_file_path.name,
             }
@@ -286,9 +262,7 @@ def process_l3bc(processor, initializer_data: GlowsL3BCInitializerData):
         with SwallowExceptionAndLog(
             f"Exception caught in L3BC science code, skipping CR {dependency.carrington_rotation_number}"
         ) as manager:
-            dependency_filtering_out_bad_days = replace(
-                dependency, l3a_data=filtered_days
-            )
+            dependency_filtering_out_bad_days = replace(dependency, l3a_data=filtered_days)
             l3b_data, l3c_data = generate_l3bc(dependency_filtering_out_bad_days)
         if manager.exception_caught:
             continue
@@ -320,16 +294,12 @@ def process_l3bc(processor, initializer_data: GlowsL3BCInitializerData):
         l3b_data_product.parent_file_names += processor.get_parent_file_names(
             [*dependency.l3a_file_names, zip_path]
         )
-        l3b_cdf = save_data(
-            l3b_data_product, cr_number=dependency.carrington_rotation_number
-        )
+        l3b_cdf = save_data(l3b_data_product, cr_number=dependency.carrington_rotation_number)
 
         l3c_data_product.parent_file_names += processor.get_parent_file_names(
             [zip_path, Path(l3b_cdf)]
         )
-        l3c_cdf = save_data(
-            l3c_data_product, cr_number=dependency.carrington_rotation_number
-        )
+        l3c_cdf = save_data(l3c_data_product, cr_number=dependency.carrington_rotation_number)
 
         logger.info(f"Finished processing CR: {dependency.carrington_rotation_number}")
         for path in [l3b_cdf, l3c_cdf]:
@@ -346,20 +316,14 @@ def process_l3bc(processor, initializer_data: GlowsL3BCInitializerData):
 
 def process_l3d(
     dependencies: GlowsL3DDependencies, version: Version
-) -> Optional[GlowsL3DProcessorOutput]:
+) -> GlowsL3DProcessorOutput | None:
 
     collections.deque(
-        (
-            create_glows_l3b_json_file_from_cdf(l3b)
-            for l3b in dependencies.l3b_file_paths
-        ),
+        (create_glows_l3b_json_file_from_cdf(l3b) for l3b in dependencies.l3b_file_paths),
         maxlen=0,
     )
     collections.deque(
-        (
-            create_glows_l3c_json_file_from_cdf(l3c)
-            for l3c in dependencies.l3c_file_paths
-        ),
+        (create_glows_l3c_json_file_from_cdf(l3c) for l3c in dependencies.l3c_file_paths),
         maxlen=0,
     )
 
@@ -383,14 +347,11 @@ def process_l3d(
     )
 
     file_manifest = {
-        "external_files": {
-            key: str(val) for key, val in dependencies.external_files.items()
-        },
+        "external_files": {key: str(val) for key, val in dependencies.external_files.items()},
         "ancillary_files": {
             "pipeline_settings": str(dependencies.ancillary_files["pipeline_settings"]),
             "WawHelioIon": {
-                key: str(val)
-                for key, val in dependencies.ancillary_files["WawHelioIon"].items()
+                key: str(val) for key, val in dependencies.ancillary_files["WawHelioIon"].items()
             },
         },
         "l3d_cdf_filename": output_l3d_cdf_filename,
@@ -421,33 +382,25 @@ def process_l3d(
         output_text_files = []
         for text_file in os.listdir(PATH_TO_L3D_TOOLKIT / "data_l3d_txt"):
             if str(last_processed_cr) in text_file:
-                output_text_files.append(
-                    PATH_TO_L3D_TOOLKIT / "data_l3d_txt" / text_file
-                )
+                output_text_files.append(PATH_TO_L3D_TOOLKIT / "data_l3d_txt" / text_file)
 
         txt_files_with_correct_version = rename_l3d_text_outputs(
             output_text_files, str(Version(None, version.minor))
         )
 
         for txt_file in txt_files_with_correct_version:
-            shutil.copy(
-                txt_file, generate_imap_file_path(txt_file.name).construct_path()
-            )
+            shutil.copy(txt_file, generate_imap_file_path(txt_file.name).construct_path())
 
         file_name = f"imap_glows_l3d_solar-params-history_19470303-cr0{last_processed_cr}_v00.json"
 
-        parent_file_names = get_parent_file_names_from_l3d_json(
-            PATH_TO_L3D_TOOLKIT / "data_l3d"
-        )
+        parent_file_names = get_parent_file_names_from_l3d_json(PATH_TO_L3D_TOOLKIT / "data_l3d")
 
         l3d_data_product = convert_json_to_l3d_data_product(
             PATH_TO_L3D_TOOLKIT / "data_l3d" / file_name,
             data_product_metadata,
             parent_file_names,
         )
-        l3d_data_product_path = save_data(
-            l3d_data_product, cr_number=dependencies.end_cr
-        )
+        l3d_data_product_path = save_data(l3d_data_product, cr_number=dependencies.end_cr)
 
         return GlowsL3DProcessorOutput(
             l3d_data_product_path, txt_files_with_correct_version, last_processed_cr
@@ -458,9 +411,7 @@ def process_l3d(
 def process_l3e(initializer_data: GlowsL3EInitializerOutput):
     products_list = []
 
-    lo_pivot_angles = get_lo_pivot_angles(
-        initializer_data.repointings.repointing_numbers
-    )
+    lo_pivot_angles = get_lo_pivot_angles(initializer_data.repointings.repointing_numbers)
     for repointing in initializer_data.repointings.repointing_numbers:
         with SwallowExceptionAndLog(
             f"Exception encountered when processing L3e for repointing {repointing}"
@@ -489,9 +440,7 @@ def process_l3e(initializer_data: GlowsL3EInitializerOutput):
                     )
                     pivot_info = lo_pivot_angles[repointing]
                     if pivot_info.parent_filename is not None:
-                        lo_parent_file_names = lo_parent_file_names + [
-                            pivot_info.parent_filename
-                        ]
+                        lo_parent_file_names = lo_parent_file_names + [pivot_info.parent_filename]
                     lo_version = initializer_data.repointings.lo_repointings[repointing]
                     products_list.extend(
                         process_l3e_lo(
@@ -513,9 +462,7 @@ def process_l3e(initializer_data: GlowsL3EInitializerOutput):
                     hi_parent_file_names = (
                         initializer_data.dependencies.get_hi_parents() + kernel_names
                     )
-                    hi_90_version = initializer_data.repointings.hi_90_repointings[
-                        repointing
-                    ]
+                    hi_90_version = initializer_data.repointings.hi_90_repointings[repointing]
                     products_list.extend(
                         process_l3e_hi(
                             hi_parent_file_names,
@@ -536,9 +483,7 @@ def process_l3e(initializer_data: GlowsL3EInitializerOutput):
                     hi_parent_file_names = (
                         initializer_data.dependencies.get_hi_parents() + kernel_names
                     )
-                    hi_45_version = initializer_data.repointings.hi_45_repointings[
-                        repointing
-                    ]
+                    hi_45_version = initializer_data.repointings.hi_45_repointings[repointing]
                     products_list.extend(
                         process_l3e_hi(
                             hi_parent_file_names,
@@ -552,17 +497,13 @@ def process_l3e(initializer_data: GlowsL3EInitializerOutput):
                         )
                     )
 
-            ul_parent_file_names = (
-                initializer_data.dependencies.get_ul_parents() + kernel_names
-            )
+            ul_parent_file_names = initializer_data.dependencies.get_ul_parents() + kernel_names
 
             with SwallowExceptionAndLog(
                 f"Exception encountered when processing L3e ultra SF for repointing {repointing}"
             ):
                 if repointing in initializer_data.repointings.ultra_sf_repointings:
-                    ul_sf_version = initializer_data.repointings.ultra_sf_repointings[
-                        repointing
-                    ]
+                    ul_sf_version = initializer_data.repointings.ultra_sf_repointings[repointing]
                     products_list.extend(
                         process_l3e_ul_sf(
                             ul_parent_file_names,
@@ -579,9 +520,7 @@ def process_l3e(initializer_data: GlowsL3EInitializerOutput):
                 f"Exception encountered when processing L3e ultra HF for repointing {repointing}"
             ):
                 if repointing in initializer_data.repointings.ultra_hf_repointings:
-                    ul_hf_version = initializer_data.repointings.ultra_hf_repointings[
-                        repointing
-                    ]
+                    ul_hf_version = initializer_data.repointings.ultra_hf_repointings[repointing]
                     products_list.extend(
                         process_l3e_ul_hf(
                             ul_parent_file_names,
@@ -618,7 +557,7 @@ def process_l3e_lo(
 
     logger.info(f"Processing L3e Lo, calling survProbLo with {call_args}")
 
-    run(["./survProbLo"] + call_args)
+    run(["./survProbLo"] + call_args, check=False)
 
     input_metadata = InputMetadata(
         instrument="glows",
@@ -683,7 +622,7 @@ def process_l3e_ul_sf(
 
     logger.info(f"Processing L3e Ultra, calling survProbUltra with {call_args}")
 
-    run(["./survProbUltra"] + call_args)
+    run(["./survProbUltra"] + call_args, check=False)
 
     input_metadata = InputMetadata(
         instrument="glows",
@@ -744,7 +683,7 @@ def process_l3e_ul_hf(
 
     call_args = call_args_object.to_argument_list()
     logger.info(f"Processing L3e Ultra, calling survProbUltra with {call_args}")
-    run(["./survProbUltra"] + call_args)
+    run(["./survProbUltra"] + call_args, check=False)
 
     input_metadata = InputMetadata(
         instrument="glows",
@@ -803,7 +742,7 @@ def process_l3e_hi(
 
     logger.info(f"Processing L3e Hi, calling survProbHi with {call_args}")
 
-    run(["./survProbHi"] + call_args)
+    run(["./survProbHi"] + call_args, check=False)
 
     descriptor = f"survival-probability-hi-{180 - elongation}"
     input_metadata = InputMetadata(
diff --git a/imap_l3_processing/glows/l3a/glows_l3a_dependencies.py b/imap_l3_processing/glows/l3a/glows_l3a_dependencies.py
index dfa57d3e..b03b6ccd 100644
--- a/imap_l3_processing/glows/l3a/glows_l3a_dependencies.py
+++ b/imap_l3_processing/glows/l3a/glows_l3a_dependencies.py
@@ -6,11 +6,11 @@
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.glows.descriptors import (
-    GLOWS_L2_DESCRIPTOR,
-    GLOWS_TIME_DEPENDENT_BACKGROUND_DESCRIPTOR,
     GLOWS_CALIBRATION_DATA_DESCRIPTOR,
     GLOWS_EXTRA_HELIOSPHERIC_BACKGROUND_DESCRIPTOR,
+    GLOWS_L2_DESCRIPTOR,
     GLOWS_PIPELINE_SETTINGS_DESCRIPTOR,
+    GLOWS_TIME_DEPENDENT_BACKGROUND_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3a.models import GlowsL2Data
 from imap_l3_processing.glows.l3a.utils import read_l2_glows_data
@@ -27,8 +27,7 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
         desired_input = next(
             science_input
             for science_input in science_inputs
-            if science_input.descriptor == GLOWS_L2_DESCRIPTOR
-            and science_input.source == "glows"
+            if science_input.descriptor == GLOWS_L2_DESCRIPTOR and science_input.source == "glows"
         )
 
         l2_cdf_file_path: Path = desired_input.imap_file_paths[0].construct_path()
@@ -51,12 +50,8 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
         )
 
         calibration_path = download(calibration_dependency[0])
-        extra_heliospheric_background = download(
-            extra_heliospheric_background_dependency[0]
-        )
-        time_dependent_background_path = download(
-            time_dependent_background_dependency[0]
-        )
+        extra_heliospheric_background = download(extra_heliospheric_background_dependency[0])
+        time_dependent_background_path = download(time_dependent_background_dependency[0])
         settings_path = download(settings_dependency[0])
 
         ancillary_files = {
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/ccsds.py b/imap_l3_processing/glows/l3a/glows_toolkit/ccsds.py
index 97d51911..bdb0d7c1 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/ccsds.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/ccsds.py
@@ -30,8 +30,7 @@ def deserialize(self, reader):
         # print('first', bit_seq_as_string)
         self.data["ccsds_ver"] = int(bit_seq_as_string[:3], 2)
         assert self.data["ccsds_ver"] == 0, (
-            "Field ccsds_ver in CCSDS header has incorrect value"
-            + " %d" % self.data["ccsds_ver"]
+            f"Field ccsds_ver in CCSDS header has incorrect value {self.data['ccsds_ver']}"
         )
         self.data["pkt_type"] = bool(int(bit_seq_as_string[3]))
         self.data["sec_header_flag"] = bool(int(bit_seq_as_string[4]))
@@ -49,16 +48,15 @@ def deserialize(self, reader):
             0x5B1,
             0x5C8,
             0x5C9,
-        ], "error deserialize(): wrong apid %d 0x%x" % (
-            self.data["apid"],
-            self.data["apid"],
+        ], "error deserialize(): wrong apid {apid:d} 0x{apid:x}".format(
+            apid=self.data["apid"],
         )
 
         aux = reader.read_uint16_be()
         bit_seq_as_string = format(aux, "b").zfill(16)
         # print('second', bit_seq_as_string)
         self.data["grouping_flag"] = int(bit_seq_as_string[:2], 2)
-        self.data["seq_count"] = int(bit_seq_as_string[2:], 2)
+        self.data["seq_count"] = int(bit_seq_as_string[2:], 2)  # noqa: FURB166
 
         # print(bit_seq_as_string, end=' ')
 
@@ -77,11 +75,8 @@ def deserialize(self, reader):
         #          exit()
 
         if not reader.overrun:
-            assert (
-                self.data["packet_length"] >= 3 and self.data["packet_length"] <= 4089
-            ), (
-                "Field packet_length in CCSDS header has incorrect value"
-                + " %d" % self.data["packet_length"]
+            assert self.data["packet_length"] >= 3 and self.data["packet_length"] <= 4089, (
+                f"Field packet_length in CCSDS header has incorrect value {self.data['packet_length']}"
             )
 
         # SCLK/MET field is expected to be included in every CCSDS packet for GLOWS so it is
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/direct_event.py b/imap_l3_processing/glows/l3a/glows_toolkit/direct_event.py
index 032d9a86..0afbbdbd 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/direct_event.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/direct_event.py
@@ -4,6 +4,7 @@
 
 import struct
 from dataclasses import dataclass
+
 from .constants import SUBSECOND_LIMIT
 
 
@@ -27,10 +28,8 @@ def build_event_from_uncompressed_data(raw) -> "DirectEvent":
         values = struct.unpack(">II", raw)
         return DirectEvent(  # see glows_appsw/-/blob/master/libs/science/data/include/science/science_direct_event.h (bits 22,23 are not used)
             seconds=values[0],
-            subseconds=values[1]
-            & 0x1FFFFF,  # subsecond encoding on the least significant 21 bits
-            impulse_length=(values[1] >> 24)
-            & 0xFF,  # first byte encodes the impulse length
+            subseconds=values[1] & 0x1FFFFF,  # subsecond encoding on the least significant 21 bits
+            impulse_length=(values[1] >> 24) & 0xFF,  # first byte encodes the impulse length
             multi_event=bool(
                 (values[1] >> 23) & 0b1
             ),  # KPLabs says it is set by FPGA and currently not used by AppSW at all
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/funcs.py b/imap_l3_processing/glows/l3a/glows_toolkit/funcs.py
index 41af3d46..ce4f091d 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/funcs.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/funcs.py
@@ -4,9 +4,11 @@
 """
 
 import datetime
+
 import numpy as np
-from .imap_time import SpacecraftTime
+
 from .constants import SUBSECOND_LIMIT
+from .imap_time import SpacecraftTime
 
 
 def calibration_factor(calibration_file_name, date_string):
@@ -32,15 +34,12 @@ def check_if_contains_actual_data(file_name):
     Args:
         file_name: name of file to be checked
     """
-    f = open(file_name, "r")
-    line = f.readline()
     is_data_in_file = False
-    while line:
-        if line.lstrip()[0] != "#" and len(line.lstrip()) > 0:
-            is_data_in_file = True
-            break
-        line = f.readline()
-    f.close()
+    with open(file_name, "r") as f:
+        for line in f:
+            if line.lstrip()[0] != "#" and len(line.lstrip()) > 0:
+                is_data_in_file = True
+                break
     return is_data_in_file
 
 
@@ -121,10 +120,9 @@ def read_l0_data(pkts_file_name):
         pkts_file_name: name of of the file with CCSDS packets
     """
     # open binary pkts file containing CCSDS packets with histograms
-    file_handler = open("%s" % pkts_file_name, mode="rb")
-    # read binary file with histograms (CCSDS headers are assumed to be included)
-    histogram_telemetry_packets = file_handler.read()
-    file_handler.close()
+    with open(str(pkts_file_name), mode="rb") as file_handler:
+        # read binary file with histograms (CCSDS headers are assumed to be included)
+        histogram_telemetry_packets = file_handler.read()
     return histogram_telemetry_packets  # byte array
 
 
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/geom_fun_libr_box/__init__.py b/imap_l3_processing/glows/l3a/glows_toolkit/geom_fun_libr_box/__init__.py
index a94a5eb5..6200dcb5 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/geom_fun_libr_box/__init__.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/geom_fun_libr_box/__init__.py
@@ -81,10 +81,10 @@ def angle_vec(vec1, vec2):
       [   0.   40.   80.  120.  160.  160.  120.   80.   40.    0.]
     """
     if np.shape(vec1) != np.shape(vec2):
-        raise Exception("angle_vec() error: np.shape(vec1)!=np.shape(vec2)")
+        raise ValueError("angle_vec() error: np.shape(vec1)!=np.shape(vec2)")
     if vec1.ndim == 1:
         if np.shape(vec1)[0] != 3:
-            raise Exception("angle_vec() error: np.shape(vec1)[0]!=3")
+            raise ValueError("angle_vec() error: np.shape(vec1)[0]!=3")
         r_1 = np.sqrt(np.dot(vec1, vec1))
         r_2 = np.sqrt(np.dot(vec2, vec2))
         cos = np.dot(vec1, vec2) / (r_1 * r_2)
@@ -99,17 +99,13 @@ def angle_vec(vec1, vec2):
         return 0.0
 
     if np.shape(vec1)[1] != 3:
-        raise Exception("angle_vec() error: np.shape(vec1)[1]!=3")
+        raise ValueError("angle_vec() error: np.shape(vec1)[1]!=3")
     r_1 = np.sqrt((vec1 * vec1).sum(axis=1))
     r_2 = np.sqrt((vec2 * vec2).sum(axis=1))
     idxs0 = np.nonzero(np.logical_and(r_1 != 0.0, r_2 != 0.0))
-    cos = (vec1[idxs0[0], :] * vec2[idxs0[0], :]).sum(axis=1) / (
-        r_1[idxs0[0]] * r_2[idxs0[0]]
-    )
+    cos = (vec1[idxs0[0], :] * vec2[idxs0[0], :]).sum(axis=1) / (r_1[idxs0[0]] * r_2[idxs0[0]])
     idxs = np.nonzero(np.logical_and(cos < -1.0, np.fabs(cos + 1.0) < 1.0e-14))
-    cos[
-        idxs[0]
-    ] = -1.0  # just in case if cos is shifted below -1 due to numerical errors
+    cos[idxs[0]] = -1.0  # just in case if cos is shifted below -1 due to numerical errors
     idxs = np.nonzero(np.logical_and(cos > 1.0, np.fabs(cos - 1.0) < 1.0e-14))
     cos[idxs[0]] = 1.0  # just in case if cos is shifted above 1 due to numerical errors
     angle = np.zeros((np.shape(vec1)[0]), dtype=float)
@@ -162,7 +158,7 @@ def get_spher_coord_rad(vec):
     """
     if vec.ndim == 1:
         if np.shape(vec)[0] != 3:
-            raise Exception("get_spher_coord_rad() error: np.shape(vec)[0]!=3")
+            raise ValueError("get_spher_coord_rad() error: np.shape(vec)[0]!=3")
         vec_m = np.sqrt(np.dot(vec, vec))
         if vec_m == 0.0:
             lat = 0.0
@@ -173,11 +169,9 @@ def get_spher_coord_rad(vec):
             lon = 0.0
         else:
             lon = np.arctan2(vec[1], vec[0]) % (2 * np.pi)
-        return np.array(
-            [vec_m, lon, lat]
-        )  # return one array similarly as in Mathematica
+        return np.array([vec_m, lon, lat])  # return one array similarly as in Mathematica
     if np.shape(vec)[1] != 3:
-        raise Exception("get_spher_coord_rad() error: np.shape(vec)[1]!=3")
+        raise ValueError("get_spher_coord_rad() error: np.shape(vec)[1]!=3")
     vec_m = np.sqrt((vec * vec).sum(axis=1))
     idxs = np.nonzero(vec_m != 0.0)
     lat = np.zeros((len(vec_m)), float)
@@ -185,9 +179,7 @@ def get_spher_coord_rad(vec):
     lon = np.arctan2(vec[:, 1], vec[:, 0]) % (2 * np.pi)  # compute longitude
     idxs = np.nonzero(np.logical_and(vec[:, 0] == 0.0, vec[:, 1] == 0.0))
     lon[idxs[0]] = 0.0  # set lon=0 if vec[:,0]==0.0 and vec[:,1]==0.0
-    return np.column_stack(
-        [vec_m, lon, lat]
-    )  # return one array similarly as in Mathematica
+    return np.column_stack([vec_m, lon, lat])  # return one array similarly as in Mathematica
 
 
 def lb2spin(l_0, b_0, soff, l_q, b_q):
@@ -291,14 +283,10 @@ def make_co_vec(l_q, b_q):
       [  1.00000000e+00  -2.44929360e-16   6.12323400e-17]]
     """
     if np.shape(l_q) != np.shape(b_q):
-        raise Exception("make_co_vec() error: np.shape(l_q)!=np.shape(b_q)")
+        raise ValueError("make_co_vec() error: np.shape(l_q)!=np.shape(b_q)")
     if np.isscalar(l_q):
-        return np.array(
-            [np.cos(l_q) * np.sin(b_q), np.sin(l_q) * np.sin(b_q), np.cos(b_q)]
-        )
-    return np.column_stack(
-        [np.cos(l_q) * np.sin(b_q), np.sin(l_q) * np.sin(b_q), np.cos(b_q)]
-    )
+        return np.array([np.cos(l_q) * np.sin(b_q), np.sin(l_q) * np.sin(b_q), np.cos(b_q)])
+    return np.column_stack([np.cos(l_q) * np.sin(b_q), np.sin(l_q) * np.sin(b_q), np.cos(b_q)])
 
 
 def make_vec(l_q, b_q):
@@ -342,14 +330,10 @@ def make_vec(l_q, b_q):
        [  6.12323400e-17  -1.49975978e-32   1.00000000e+00]]
     """
     if np.shape(l_q) != np.shape(b_q):
-        raise Exception("make_vec() error: np.shape(l_q)!=np.shape(b_q)")
+        raise ValueError("make_vec() error: np.shape(l_q)!=np.shape(b_q)")
     if np.isscalar(l_q):
-        return np.array(
-            [np.cos(l_q) * np.cos(b_q), np.sin(l_q) * np.cos(b_q), np.sin(b_q)]
-        )
-    return np.column_stack(
-        [np.cos(l_q) * np.cos(b_q), np.sin(l_q) * np.cos(b_q), np.sin(b_q)]
-    )
+        return np.array([np.cos(l_q) * np.cos(b_q), np.sin(l_q) * np.cos(b_q), np.sin(b_q)])
+    return np.column_stack([np.cos(l_q) * np.cos(b_q), np.sin(l_q) * np.cos(b_q), np.sin(b_q)])
 
 
 def position_angle(a_1, d_1, a_2, d_2):
@@ -393,9 +377,7 @@ def position_angle(a_1, d_1, a_2, d_2):
         50.43084061  62.72683044  73.55865702  82.60570856  90.        ]
     """
     delta_a = a_1 - a_2
-    pos_a = np.arctan2(
-        np.sin(delta_a), np.cos(d_2) * np.tan(d_1) - np.sin(d_2) * np.cos(delta_a)
-    )
+    pos_a = np.arctan2(np.sin(delta_a), np.cos(d_2) * np.tan(d_1) - np.sin(d_2) * np.cos(delta_a))
     return pos_a
 
 
@@ -803,9 +785,7 @@ def spin2lb(l_0, b_0, spin_ang, spin_off, tht):
         vec0 = np.array([-np.sin(tht), 0.0, np.cos(tht)])  # temporary vector to rotate
         vec = np.matmul(rot_mtrx, vec0)  # rotate vec0
     else:
-        vec0 = np.column_stack(
-            [-np.sin(tht), np.zeros((len(tht)), dtype=float), np.cos(tht)]
-        )
+        vec0 = np.column_stack([-np.sin(tht), np.zeros((len(tht)), dtype=float), np.cos(tht)])
         vec = np.einsum("lij,lj->li", rot_mtrx, vec0)
     rlb = get_spher_coord_rad(vec)
     if np.isscalar(l_0):
@@ -869,9 +849,9 @@ def spin2lb_test_on_grid(spin_off, tht):
         ist = 1
 
     if ist == 0:
-        print("spin2lb_test_on_grid(tht=%g,spin_off=%g): passed" % (tht, spin_off))
+        print(f"spin2lb_test_on_grid(tht={tht:g},spin_off={spin_off:g}): passed")
         return 1
-    print("spin2lb_test_on_grid(tht=%g,spin_off=%g): failed" % (tht, spin_off))
+    print(f"spin2lb_test_on_grid(tht={tht:g},spin_off={spin_off:g}): failed")
     return 0
 
 
@@ -901,9 +881,7 @@ def spin2lb_test_on_text_file(filename):
       1
     """
     # load a text file with testing cases
-    l_0, b_0, s_0, spin_off, tht, l_q, b_q = np.radians(
-        np.loadtxt(filename, unpack=True)
-    )
+    l_0, b_0, s_0, spin_off, tht, l_q, b_q = np.radians(np.loadtxt(filename, unpack=True))
 
     # back-and-forth transforms
     ltbt = spin2lb(l_0, b_0, s_0, spin_off, tht)
@@ -937,7 +915,7 @@ def spin2lb_test_on_text_file(filename):
         ist = 1
 
     if ist == 0:
-        print("spin2lb_test_on_text_file('%s'): passed" % filename)
+        print(f"spin2lb_test_on_text_file('{filename:s}'): passed")
         return 1
-    print("spin2lb_test_on_text_file('%s'): failed" % filename)
+    print(f"spin2lb_test_on_text_file('{filename:s}'): failed")
     return 0
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_direct_events.py b/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_direct_events.py
index c55f5ad3..80fbfa1e 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_direct_events.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_direct_events.py
@@ -2,12 +2,14 @@
 Author: Marek Strumik, maro at cbk.waw.pl
 """
 
-import json
 import copy
+import json
+
 import numpy as np
-from .constants import VERSION, SUBSECOND_LIMIT
-from .funcs import time_sec_subsec_to_utc
+
+from .constants import SUBSECOND_LIMIT, VERSION
 from .direct_event import DirectEvent
+from .funcs import time_sec_subsec_to_utc
 
 
 class L1aDataDirectEvents:
@@ -63,66 +65,30 @@ def create_l1a_from_l0_data(self, l0_data, pkts_file_name: str, packet_number: i
         # corrected (missing fields filter_temperature and hv_voltage) by looking at
         # glows_appsw-master/tooling/science/models/direct_event_file_model.py:42
         self.data["data_every_second"] = {}
-        self.data["data_every_second"]["imap_sclk_last_pps"] = int.from_bytes(
-            data[0:4], "big"
-        )
-        self.data["data_every_second"]["glows_sclk_last_pps"] = int.from_bytes(
-            data[4:8], "big"
-        )
-        self.data["data_every_second"]["glows_ssclk_last_pps"] = int.from_bytes(
-            data[8:12], "big"
-        )
-        self.data["data_every_second"]["imap_sclk_next_pps"] = int.from_bytes(
-            data[12:16], "big"
-        )
-        self.data["data_every_second"]["catbed_heater_active"] = (
-            False if int(data[16]) == 0 else True
-        )
-        self.data["data_every_second"]["spin_period_valid"] = (
-            False if int(data[17]) == 0 else True
-        )
-        self.data["data_every_second"]["spin_phase_at_next_pps_valid"] = (
-            False if int(data[18]) == 0 else True
-        )
-        self.data["data_every_second"]["spin_period_source"] = (
-            False if int(data[19]) == 0 else True
-        )
-        self.data["data_every_second"]["spin_period"] = int.from_bytes(
-            data[20:22], "big"
-        )
+        self.data["data_every_second"]["imap_sclk_last_pps"] = int.from_bytes(data[0:4], "big")
+        self.data["data_every_second"]["glows_sclk_last_pps"] = int.from_bytes(data[4:8], "big")
+        self.data["data_every_second"]["glows_ssclk_last_pps"] = int.from_bytes(data[8:12], "big")
+        self.data["data_every_second"]["imap_sclk_next_pps"] = int.from_bytes(data[12:16], "big")
+        self.data["data_every_second"]["catbed_heater_active"] = bool(int(data[16]))
+        self.data["data_every_second"]["spin_period_valid"] = bool(int(data[17]))
+        self.data["data_every_second"]["spin_phase_at_next_pps_valid"] = bool(int(data[18]))
+        self.data["data_every_second"]["spin_period_source"] = bool(int(data[19]))
+        self.data["data_every_second"]["spin_period"] = int.from_bytes(data[20:22], "big")
         self.data["data_every_second"]["spin_phase_at_next_pps"] = int.from_bytes(
             data[22:24], "big"
         )
         self.data["data_every_second"]["number_of_completed_spins"] = int.from_bytes(
             data[24:28], "big"
         )
-        self.data["data_every_second"]["filter_temperature"] = int.from_bytes(
-            data[28:30], "big"
-        )
-        self.data["data_every_second"]["hv_voltage"] = int.from_bytes(
-            data[30:32], "big"
-        )
-        self.data["data_every_second"]["glows_time_on_pps_valid"] = (
-            False if int(data[32]) == 0 else True
-        )
-        self.data["data_every_second"]["time_status_valid"] = (
-            False if int(data[33]) == 0 else True
-        )
-        self.data["data_every_second"]["housekeeping_valid"] = (
-            False if int(data[34]) == 0 else True
-        )
-        self.data["data_every_second"]["is_pps_autogenerated"] = (
-            False if int(data[35]) == 0 else True
-        )
-        self.data["data_every_second"]["hv_test_in_progress"] = (
-            False if int(data[36]) == 0 else True
-        )
-        self.data["data_every_second"]["pulse_test_in_progress"] = (
-            False if int(data[37]) == 0 else True
-        )
-        self.data["data_every_second"]["memory_error_detected"] = (
-            False if int(data[38]) == 0 else True
-        )
+        self.data["data_every_second"]["filter_temperature"] = int.from_bytes(data[28:30], "big")
+        self.data["data_every_second"]["hv_voltage"] = int.from_bytes(data[30:32], "big")
+        self.data["data_every_second"]["glows_time_on_pps_valid"] = bool(int(data[32]))
+        self.data["data_every_second"]["time_status_valid"] = bool(int(data[33]))
+        self.data["data_every_second"]["housekeeping_valid"] = bool(int(data[34]))
+        self.data["data_every_second"]["is_pps_autogenerated"] = bool(int(data[35]))
+        self.data["data_every_second"]["hv_test_in_progress"] = bool(int(data[36]))
+        self.data["data_every_second"]["pulse_test_in_progress"] = bool(int(data[37]))
+        self.data["data_every_second"]["memory_error_detected"] = bool(int(data[38]))
         # NOTE: there is one-byte padding in the C structure of data_every_seconds, so it has 40 bytes in total
 
         # DEBUG TEST
@@ -142,9 +108,7 @@ def create_l1a_from_l0_data(self, l0_data, pkts_file_name: str, packet_number: i
             return error_messages
 
         # sanity check, the first direct event must be uncompressed 8-byte structure
-        assert len(data) >= 48, (
-            "error create_l1a_from_l0_data(): len(data)=%d < 48" % len(data)
-        )
+        assert len(data) >= 48, f"error create_l1a_from_l0_data(): len(data)={len(data)} < 48"
 
         # read the first direct event, which is always uncompressed (i.e., not timedelta but full timestamp)
         current_event = DirectEvent.build_event_from_uncompressed_data(data[40:48])
@@ -167,8 +131,7 @@ def create_l1a_from_l0_data(self, l0_data, pkts_file_name: str, packet_number: i
             print(self.direct_events)
             print("###")
             error_messages.append(
-                "DE: de[0].sec %d > glows_sclk_last_pps+1 %d"
-                % (
+                "DE: de[0].sec {:d} > glows_sclk_last_pps+1 {:d}".format(
                     self.direct_events[0].seconds,
                     self.data["data_every_second"]["glows_sclk_last_pps"] + 1,
                 )
@@ -237,9 +200,7 @@ def create_l1a_from_l0_data(self, l0_data, pkts_file_name: str, packet_number: i
                 #                pass
                 #                raise Exception('error create_l1a_from_l0_data(): unexpected marker %d or end of data stream %d %d' % \
                 #                                (marker, i, len(binary_stream_of_timedeltas)))
-                error_messages.append(
-                    "DE: direct event decompressing failed at byte %d" % (i - 1)
-                )
+                error_messages.append(f"DE: direct event decompressing failed at byte {i - 1}")
                 break
 
             # sanity check
@@ -253,15 +214,15 @@ def create_l1a_from_l0_data(self, l0_data, pkts_file_name: str, packet_number: i
     def generate_file_name(self, extension):
         # file names should be tagged with utc time as suggested in Sec. 1.4.2 of
         # "IMAP SDC to Instrument Team ICD"
-        start_time_utc = time_sec_subsec_to_utc(
-            self.data["imap_start_time_seconds"], 0
-        ).strftime("%Y%m%d%H%M%S")
+        start_time_utc = time_sec_subsec_to_utc(self.data["imap_start_time_seconds"], 0).strftime(
+            "%Y%m%d%H%M%S"
+        )
 
         # the output file name is constructed using a convention defined in Sec. 1.4.2 of
         # "IMAP SDC to Instrument Team ICD"
-        file_name = "data_l1a_direct_events/imap_glows_l1a_%s_orbX_modX_p_v00.%s" % (
-            start_time_utc,
-            extension,
+        file_name = (
+            "data_l1a_direct_events/"
+            f"imap_glows_l1a_{start_time_utc:s}_orbX_modX_p_v00.{extension:s}"
         )
 
         return file_name
@@ -283,12 +244,11 @@ def read_from_json_file(self, file_name):
         Args:
             file_name: name of file with L1a data
         """
-        file_handler = open(file_name, "r")
-        self.data = json.load(file_handler)
+        with open(file_name, "r") as file_handler:
+            self.data = json.load(file_handler)
 
         # additional field to keep track where data come from
         self.data["l1a_file_name"] = file_name
-        file_handler.close()
 
     def read_direct_events(self, file_name):
         """
@@ -330,9 +290,8 @@ def save_data_to_json_file(self):
         #    print(self.data['number_of_de_packets'], self.data['seq_num_of_de_packet'])
         #    exit()
 
-        file_handler = open(file_name, "w")
-        print(json_content, file=file_handler)
-        file_handler.close()
+        with open(file_name, "w") as file_handler:
+            print(json_content, file=file_handler)
 
     def save_direct_events(self):
         """
@@ -341,9 +300,8 @@ def save_direct_events(self):
         """
 
         file_name = self.generate_file_name("dat")
-        file_handler = open(file_name, "w")
-        for i, x in enumerate(self.direct_events):
-            file_handler.write(
-                "%d %7d %3d\n" % (x.seconds, x.subseconds, x.impulse_length)
+        with open(file_name, "w") as file_handler:
+            file_handler.writelines(
+                f"{x.seconds} {x.subseconds:7d} {x.impulse_length:3d}\n"
+                for i, x in enumerate(self.direct_events)
             )
-        file_handler.close()
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_histogram.py b/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_histogram.py
index 8474e8f1..90fbcf3a 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_histogram.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/l1a_data_histogram.py
@@ -3,10 +3,12 @@
 """
 
 import json
+
 import numpy as np
-from .constants import VERSION, MAIN_TIME_FIELD
-from .time import Time
+
+from .constants import MAIN_TIME_FIELD, VERSION
 from .funcs import time_sec_subsec_to_utc
+from .time import Time
 
 
 class L1aDataHistogram:
@@ -67,9 +69,7 @@ def create_l1a_from_l0_data(self, l0_data, pkts_file_name: str, packet_number: i
         )
 
         self.data["number_of_spins_per_block"] = l0_data["number_of_spins_per_block"]
-        self.data["number_of_bins_per_histogram"] = l0_data[
-            "number_of_bins_per_histogram"
-        ]
+        self.data["number_of_bins_per_histogram"] = l0_data["number_of_bins_per_histogram"]
         self.data["histogram"] = l0_data["histogram"]
         # TMP_SOLUTION
         self.data["number_of_events"] = l0_data["number_of_events"]
@@ -77,14 +77,14 @@ def create_l1a_from_l0_data(self, l0_data, pkts_file_name: str, packet_number: i
         # sanity check
         if self.data["number_of_events"] != np.sum(self.data["histogram"]):
             error_messages.append(
-                "HIST: number of events is not equal to the sum over histogram %d %d"
-                % (self.data["number_of_events"], np.sum(self.data["histogram"]))
+                "HIST: number of events is not equal to the sum over histogram {:d} {:d}".format(
+                    self.data["number_of_events"],
+                    np.sum(self.data["histogram"]),
+                )
             )
 
         self.data["filter_temperature_average"] = l0_data["filter_temperature_average"]
-        self.data["filter_temperature_variance"] = l0_data[
-            "filter_temperature_variance"
-        ]
+        self.data["filter_temperature_variance"] = l0_data["filter_temperature_variance"]
         self.data["hv_voltage_average"] = l0_data["hv_voltage_average"]
         self.data["hv_voltage_variance"] = l0_data["hv_voltage_variance"]
         self.data["spin_period_average"] = l0_data["spin_period_average"]
@@ -114,8 +114,8 @@ def read_from_json_file(self, file_name):
         Args:
             file_name: name of file with L1a data
         """
-        file_handler = open(file_name, "r")
-        self.data = json.load(file_handler)
+        with open(file_name, "r") as file_handler:
+            self.data = json.load(file_handler)
 
         # hexadecimal values saved as strings require special treatment to make them integers
         self.data["flags"]["flags_set_onboard"] = int(
@@ -124,7 +124,6 @@ def read_from_json_file(self, file_name):
 
         # additional field to keep track where data come from
         self.data["l1a_file_name"] = file_name
-        file_handler.close()
 
     def save_data_to_file(self):
         """
@@ -159,35 +158,27 @@ def save_data_to_json_file(self):
 
         # the output file name is constructed using a convention defined in Sec. 1.4.2 of
         # "IMAP SDC to Instrument Team ICD"
-        file_name = "data_l1a_histograms/imap_glows_l1a_%s_orbX_modX_p_v00.json" % (
-            start_time_utc
-        )
+        file_name = f"data_l1a_histograms/imap_glows_l1a_{start_time_utc}_orbX_modX_p_v00.json"
 
-        file_handler = open(file_name, "w")
-        print(json_content, file=file_handler)
-        file_handler.close()
+        with open(file_name, "w") as file_handler:
+            print(json_content, file=file_handler)
 
     def total_counts_file_init(self, tag):
         """
         Initialize a file for storing total count numbers for L1a histograms
         This kind of information is needed when L1b is generated (for one of the filters)
         """
-        file_handler = open("data_l1a_histograms/total_counts_file.dat", "w")
-        file_handler.write(
-            "%s %s\n" % (tag, self.data["block_header"]["pkts_file_name"])
-        )
-        file_handler.close()
+        with open("data_l1a_histograms/total_counts_file.dat", "w") as file_handler:
+            file_handler.write(f"{tag} {self.data['block_header']['pkts_file_name']}\n")
 
     def total_counts_file_update(self):
         """
         Update a file for storing total counts numbers for L1a histograms
         """
-        file_handler = open("data_l1a_histograms/total_counts_file.dat", "a")
-        file_handler.write(
-            "%d %d\n"
-            % (
-                self.data["block_header"]["seq_count_in_pkts_file"],
-                int(np.sum(self.data["histogram"])),
+        with open("data_l1a_histograms/total_counts_file.dat", "a") as file_handler:
+            file_handler.write(
+                "{:d} {:d}".format(
+                    self.data["block_header"]["seq_count_in_pkts_file"],
+                    int(np.sum(self.data["histogram"])),
+                )
             )
-        )
-        file_handler.close()
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_direct_events.py b/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_direct_events.py
index fc70c2c6..9536eafa 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_direct_events.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_direct_events.py
@@ -2,14 +2,16 @@
 Author: Marek Strumik, maro at cbk.waw.pl
 """
 
-import json
 import copy
+import json
+
 import numpy as np
-from .constants import VERSION, SUBSECOND_LIMIT
+
+from .constants import SUBSECOND_LIMIT, VERSION
 from .funcs import (
     decode_ancillary_parameter,
-    time_sec_subsec_to_utc,
     time_sec_subsec_to_float64,
+    time_sec_subsec_to_utc,
 )
 
 
@@ -24,9 +26,7 @@ def __init__(self):
         """
         self.data = {}
 
-    def _block_header_add_list_of_anc_files(
-        self, anc_input_from_sdc, anc_input_from_instr_team
-    ):
+    def _block_header_add_list_of_anc_files(self, anc_input_from_sdc, anc_input_from_instr_team):
         """
         Add list of used ancillary files to block header
         Args:
@@ -35,9 +35,7 @@ def _block_header_add_list_of_anc_files(
         """
         self.data["header"]["ancillary_data_files"] = []
         for key in ["conversion_table_for_anc_data"]:
-            self.data["header"]["ancillary_data_files"].append(
-                anc_input_from_instr_team[key]
-            )
+            self.data["header"]["ancillary_data_files"].append(anc_input_from_instr_team[key])
         # for key in anc_input_from_sdc:
         #    self.data['block_header']['ancillary_data_files'].append(anc_input_from_sdc[key])
 
@@ -51,11 +49,8 @@ def _convert_ancillary_parameters(self, l1a_data, anc_input_from_instr_team):
         """
 
         # load conversion/decoding table for ancillary parameters collected onboard
-        file_handler = open(
-            anc_input_from_instr_team["conversion_table_for_anc_data"], "r"
-        )
-        conversion_table = json.load(file_handler)
-        file_handler.close()
+        with open(anc_input_from_instr_team["conversion_table_for_anc_data"], "r") as file_handler:
+            conversion_table = json.load(file_handler)
 
         # ancillary parameters collected onboard that need to be decoded
         self.data["filter_temperature"] = decode_ancillary_parameter(
@@ -71,9 +66,7 @@ def _convert_ancillary_parameters(self, l1a_data, anc_input_from_instr_team):
             "spin_phase", conversion_table, l1a_data["spin_phase_at_next_pps"]
         )
 
-    def create_l1b_from_l1a_data(
-        self, l1a, anc_input_from_sdc, anc_input_from_instr_team
-    ):
+    def create_l1b_from_l1a_data(self, l1a, anc_input_from_sdc, anc_input_from_instr_team):
         """
         Sets values of L1b fields using L1a data read from a file
         Args:
@@ -89,9 +82,7 @@ def create_l1b_from_l1a_data(
         }
 
         # add list of used ancillary files to block_header
-        self._block_header_add_list_of_anc_files(
-            anc_input_from_sdc, anc_input_from_instr_team
-        )
+        self._block_header_add_list_of_anc_files(anc_input_from_sdc, anc_input_from_instr_team)
 
         # self.data['unique_identifier'] = \
         #    time_sec_subsec_to_utc(l1a.data['data_every_second']['imap_sclk_last_pps'],
@@ -138,9 +129,7 @@ def create_l1b_from_l1a_data(
                 self.data["flags"][key] = l1a.data["data_every_second"][key]
 
         if np.shape(l1a.direct_events)[0] > 0:
-            if (
-                l1a.direct_events.ndim > 1
-            ):  # this is supposed to check if we have more than one DE
+            if l1a.direct_events.ndim > 1:  # this is supposed to check if we have more than one DE
                 self.data["direct_event_glows_times"] = (
                     l1a.direct_events[:, 0] + l1a.direct_events[:, 1] / SUBSECOND_LIMIT
                 ).astype(float)
@@ -150,16 +139,13 @@ def create_l1b_from_l1a_data(
                 ).astype(float)
 
             # load conversion/decoding table for ancillary parameters collected onboard
-            file_handler = open(
+            with open(
                 anc_input_from_instr_team["conversion_table_for_anc_data"], "r"
-            )
-            conversion_table = json.load(file_handler)
-            file_handler.close()
+            ) as file_handler:
+                conversion_table = json.load(file_handler)
 
             # convert pulse lengths into physical units
-            if (
-                l1a.direct_events.ndim > 1
-            ):  # this is supposed to check if we have more than one DE
+            if l1a.direct_events.ndim > 1:  # this is supposed to check if we have more than one DE
                 self.data["direct_event_pulse_lengths"] = decode_ancillary_parameter(
                     "pulse_length", conversion_table, l1a.direct_events[:, 2]
                 )
@@ -204,19 +190,13 @@ def _save_data_to_json_file(self):
         # create local copy for printing purposes
         data = copy.deepcopy(self.data)
 
-        for key in fmt["arrays"].keys():
-            if isinstance(
-                data[key], np.ndarray
-            ):  # check if we have more than one direct event
-                data[key] = (
-                    "["
-                    + ", ".join(map(lambda x: fmt["arrays"][key] % x, list(data[key])))
-                    + "]"
-                )
+        for key in fmt["arrays"]:
+            if isinstance(data[key], np.ndarray):  # check if we have more than one direct event
+                data[key] = "[" + ", ".join(fmt["arrays"][key] % x for x in list(data[key])) + "]"
             else:
                 data[key] = "[" + fmt["arrays"][key] % data[key] + "]"
-        for key in fmt["scalar variables"].keys():
-            data[key] = "|" + fmt["scalar variables"][key] % data[key] + "|"
+        for key, value in fmt["scalar variables"].items():
+            data[key] = "|" + value % data[key] + "|"
 
         # generate JSON content to be saved in output file
         json_content = json.dumps(data, indent=4, default=vars)
@@ -231,13 +211,10 @@ def _save_data_to_json_file(self):
 
         # the output file name is constructed using a convention defined in Sec. 1.4.2 of
         # "IMAP SDC to Instrument Team ICD"
-        file_name = "data_l1b_direct_events/imap_glows_l1b_%s_orbX_modX_p_v00.json" % (
-            start_time_utc
-        )
+        file_name = f"data_l1b_direct_events/imap_glows_l1b_{start_time_utc}_orbX_modX_p_v00.json"
 
-        file_handler = open(file_name, "w")
-        print(json_content, file=file_handler)
-        file_handler.close()
+        with open(file_name, "w") as file_handler:
+            print(json_content, file=file_handler)
 
     def set_times(self, l1a_data):
         """
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_histogram.py b/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_histogram.py
index a14ed10f..1b65595a 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_histogram.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/l1b_data_histogram.py
@@ -2,24 +2,26 @@
 Author: Marek Strumik, maro at cbk.waw.pl
 """
 
-import json
 import copy
+import json
+
 import numpy as np
 import pandas as pd
-from astropy.coordinates import SkyCoord
 from astropy import units as u
+from astropy.coordinates import SkyCoord
+
 from .constants import (
-    VERSION,
-    SCAN_CIRCLE_ANGULAR_RADIUS,
     L1B_L2_HIST_FLAG_FIELDS,
     MAIN_TIME_FIELD,
+    SCAN_CIRCLE_ANGULAR_RADIUS,
+    VERSION,
 )
 from .funcs import (
-    time_sec_subsec_to_utc,
-    time_sec_subsec_to_float64,
-    flags_deserialize,
-    decode_ancillary_parameters_avg_stddev,
     check_if_contains_actual_data,
+    decode_ancillary_parameters_avg_stddev,
+    flags_deserialize,
+    time_sec_subsec_to_float64,
+    time_sec_subsec_to_utc,
 )
 from .geom_fun_libr_box import spin2lb
 
@@ -39,9 +41,7 @@ def __init__(self):
         self.block_start_time = None
         self.block_end_time = None
 
-    def _block_header_add_list_of_anc_files(
-        self, anc_input_from_sdc, anc_input_from_instr_team
-    ):
+    def _block_header_add_list_of_anc_files(self, anc_input_from_sdc, anc_input_from_instr_team):
         """
         Add list of used ancillary files to block header
         Args:
@@ -54,9 +54,7 @@ def _block_header_add_list_of_anc_files(
                 anc_input_from_instr_team[key]
             )
         for key in anc_input_from_sdc:
-            self.data["block_header"]["ancillary_data_files"].append(
-                anc_input_from_sdc[key]
-            )
+            self.data["block_header"]["ancillary_data_files"].append(anc_input_from_sdc[key])
 
     def _compute_spin_period_ground_estimate(self, anc_data):
         """
@@ -161,15 +159,9 @@ def _compute_spacecraft_location(self, anc_data):
 
         # generate synthetic series with spacecraft location data (assumed to arrive every 0.1 s)
         time = np.arange(self.block_start_time, self.block_end_time, 0.1)
-        data_x = np.interp(
-            time, [df_1["imap_time"], df_2["imap_time"]], [df_1["x"], df_2["x"]]
-        )
-        data_y = np.interp(
-            time, [df_1["imap_time"], df_2["imap_time"]], [df_1["y"], df_2["y"]]
-        )
-        data_z = np.interp(
-            time, [df_1["imap_time"], df_2["imap_time"]], [df_1["z"], df_2["z"]]
-        )
+        data_x = np.interp(time, [df_1["imap_time"], df_2["imap_time"]], [df_1["x"], df_2["x"]])
+        data_y = np.interp(time, [df_1["imap_time"], df_2["imap_time"]], [df_1["y"], df_2["y"]])
+        data_z = np.interp(time, [df_1["imap_time"], df_2["imap_time"]], [df_1["z"], df_2["z"]])
 
         # compute spacecraft-location average and standard deviation over block
         average = [np.mean(data_x), np.mean(data_y), np.mean(data_z)]
@@ -195,15 +187,9 @@ def _compute_spacecraft_velocity(self, anc_data):
 
         # generate synthetic series with spacecraft velocity data (assumed to arrive every 0.1 s)
         time = np.arange(self.block_start_time, self.block_end_time, 0.1)
-        data_vx = np.interp(
-            time, [df_1["imap_time"], df_2["imap_time"]], [df_1["vx"], df_2["vx"]]
-        )
-        data_vy = np.interp(
-            time, [df_1["imap_time"], df_2["imap_time"]], [df_1["vy"], df_2["vy"]]
-        )
-        data_vz = np.interp(
-            time, [df_1["imap_time"], df_2["imap_time"]], [df_1["vz"], df_2["vz"]]
-        )
+        data_vx = np.interp(time, [df_1["imap_time"], df_2["imap_time"]], [df_1["vx"], df_2["vx"]])
+        data_vy = np.interp(time, [df_1["imap_time"], df_2["imap_time"]], [df_1["vy"], df_2["vy"]])
+        data_vz = np.interp(time, [df_1["imap_time"], df_2["imap_time"]], [df_1["vz"], df_2["vz"]])
 
         # compute spacecraft-velocity average and standard deviation over block
         average = [np.mean(data_vx), np.mean(data_vy), np.mean(data_vz)]
@@ -230,10 +216,8 @@ def _compute_histogram_bins_ecl_coords(self):
 
         # compute ecliptic longitude and latitude of histogram bin centers
         histogram_bins_ecl_coords = spin2lb(
-            np.radians(self.data["spin_axis_orientation_average"]["lon"])
-            * np.ones(n_bins, float),
-            np.radians(self.data["spin_axis_orientation_average"]["lat"])
-            * np.ones(n_bins, float),
+            np.radians(self.data["spin_axis_orientation_average"]["lon"]) * np.ones(n_bins, float),
+            np.radians(self.data["spin_axis_orientation_average"]["lat"]) * np.ones(n_bins, float),
             np.radians(spin_angle_from_north),
             0.0,
             np.radians(SCAN_CIRCLE_ANGULAR_RADIUS) * np.ones(n_bins, float),
@@ -251,11 +235,8 @@ def _convert_ancillary_parameters(self, l1a_data, anc_input_from_instr_team):
         """
 
         # load conversion/decoding table for ancillary parameters collected onboard
-        file_handler = open(
-            anc_input_from_instr_team["conversion_table_for_anc_data"], "r"
-        )
-        conversion_table = json.load(file_handler)
-        file_handler.close()
+        with open(anc_input_from_instr_team["conversion_table_for_anc_data"], "r") as file_handler:
+            conversion_table = json.load(file_handler)
 
         # ancillary parameters collected onboard that need to be decoded
         (
@@ -265,24 +246,16 @@ def _convert_ancillary_parameters(self, l1a_data, anc_input_from_instr_team):
             "filter_temperature", conversion_table, l1a_data
         )
         self.data["hv_voltage_average"], self.data["hv_voltage_std_dev"] = (
-            decode_ancillary_parameters_avg_stddev(
-                "hv_voltage", conversion_table, l1a_data
-            )
+            decode_ancillary_parameters_avg_stddev("hv_voltage", conversion_table, l1a_data)
         )
         self.data["spin_period_average"], self.data["spin_period_std_dev"] = (
-            decode_ancillary_parameters_avg_stddev(
-                "spin_period", conversion_table, l1a_data
-            )
+            decode_ancillary_parameters_avg_stddev("spin_period", conversion_table, l1a_data)
         )
         self.data["pulse_length_average"], self.data["pulse_length_std_dev"] = (
-            decode_ancillary_parameters_avg_stddev(
-                "pulse_length", conversion_table, l1a_data
-            )
+            decode_ancillary_parameters_avg_stddev("pulse_length", conversion_table, l1a_data)
         )
 
-    def create_l1b_from_l1a_data(
-        self, l1a_data, anc_input_from_sdc, anc_input_from_instr_team
-    ):
+    def create_l1b_from_l1a_data(self, l1a_data, anc_input_from_sdc, anc_input_from_instr_team):
         """
         Sets values of L1b fields using L1a data read from a file
         Args:
@@ -291,21 +264,15 @@ def create_l1b_from_l1a_data(
             anc_input_from_instr_team: ancillary input provided by IMAP/GLOWS Instrument Team
         """
         self.data["block_header"] = {
-            "flight_software_version": l1a_data["block_header"][
-                "flight_software_version"
-            ],
+            "flight_software_version": l1a_data["block_header"]["flight_software_version"],
             "ground_software_version": VERSION,
             "pkts_file_name": l1a_data["block_header"]["pkts_file_name"],
-            "seq_count_in_pkts_file": l1a_data["block_header"][
-                "seq_count_in_pkts_file"
-            ],
+            "seq_count_in_pkts_file": l1a_data["block_header"]["seq_count_in_pkts_file"],
             "l1a_file_name": l1a_data["l1a_file_name"],
         }
 
         # add list of used ancillary files to block_header
-        self._block_header_add_list_of_anc_files(
-            anc_input_from_sdc, anc_input_from_instr_team
-        )
+        self._block_header_add_list_of_anc_files(anc_input_from_sdc, anc_input_from_instr_team)
 
         self.data["unique_block_identifier"] = time_sec_subsec_to_utc(
             l1a_data[MAIN_TIME_FIELD]["seconds"],
@@ -317,9 +284,7 @@ def create_l1b_from_l1a_data(
 
         # set histogram-related quantities
         self.data["number_of_spins_per_block"] = l1a_data["number_of_spins_per_block"]
-        self.data["number_of_bins_per_histogram"] = l1a_data[
-            "number_of_bins_per_histogram"
-        ]
+        self.data["number_of_bins_per_histogram"] = l1a_data["number_of_bins_per_histogram"]
 
         # set histogram
         self.data["histogram"] = l1a_data["histogram"]
@@ -343,13 +308,9 @@ def create_l1b_from_l1a_data(
         # set block_start_time and block_end_time for funcs invoked in process_anc_input_from_sdc()
         self.block_start_time = self.data[MAIN_TIME_FIELD]
         if MAIN_TIME_FIELD == "imap_start_time":
-            self.block_end_time = (
-                self.block_start_time + self.data["imap_end_time_offset"]
-            )
+            self.block_end_time = self.block_start_time + self.data["imap_end_time_offset"]
         if MAIN_TIME_FIELD == "glows_start_time":
-            self.block_end_time = (
-                self.block_start_time + self.data["glows_end_time_offset"]
-            )
+            self.block_end_time = self.block_start_time + self.data["glows_end_time_offset"]
 
         # convert ancillary parameters collected onboard to physical units
         self._convert_ancillary_parameters(l1a_data, anc_input_from_instr_team)
@@ -366,9 +327,7 @@ def create_l1b_from_l1a_data(
                 self.data["flags"][key] = l1a_data["flags"][key]
 
         # initialize histogram bin flags
-        self.data["histogram_flag_array"] = np.zeros_like(
-            self.data["histogram"], np.int16
-        )
+        self.data["histogram_flag_array"] = np.zeros_like(self.data["histogram"], np.int16)
 
         # apply filters defined by the IMAP/GLOWS Instrument Team
         self._filters(anc_input_from_instr_team)
@@ -388,9 +347,8 @@ def _filters(self, anc_input_from_instr_team):
             anc_input_from_instr_team: ancillary input provided by IMAP/GLOWS Instrument Team
         """
         # read filter settings
-        file_handler = open(anc_input_from_instr_team["settings"], "r")
-        settings = json.load(file_handler)
-        file_handler.close()
+        with open(anc_input_from_instr_team["settings"], "r") as file_handler:
+            settings = json.load(file_handler)
 
         # set uv-source-related part of histogram flag array
         self._set_histogram_flag_array_uv_sources(anc_input_from_instr_team, settings)
@@ -414,9 +372,7 @@ def _filters(self, anc_input_from_instr_team):
         # apply filter based on filter-temperature spread and set related flag
         self._flag_compare_with_threshold(
             "filter_temperature_std_dev",
-            settings["filter_based_on_temperature_std_dev"][
-                "std_dev_threshold__celsius_deg"
-            ],
+            settings["filter_based_on_temperature_std_dev"]["std_dev_threshold__celsius_deg"],
             "is_temperature_std_dev_beyond_threshold",
         )
 
@@ -462,12 +418,8 @@ def _flag_based_on_daily_statistical_error(self, settings):
         Args:
             settings: filter settings from a file provided by IMAP/GLOWS Instrument Team
         """
-        n_lo = settings["filter_based_on_daily_statistical_error"][
-            "n_sigma_threshold_lower"
-        ]
-        n_up = settings["filter_based_on_daily_statistical_error"][
-            "n_sigma_threshold_upper"
-        ]
+        n_lo = settings["filter_based_on_daily_statistical_error"]["n_sigma_threshold_lower"]
+        n_up = settings["filter_based_on_daily_statistical_error"]["n_sigma_threshold_upper"]
         if n_lo < 0 or n_up < 0:
             # negative value means that filter is turned off, so we can immediately set the flag
             self.data["flags"]["is_beyond_daily_statistical_error"] = False
@@ -479,12 +431,8 @@ def _flag_based_on_daily_statistical_error(self, settings):
             total_counts_daily_average, total_counts_daily_std_dev = (
                 self.total_counts_daily_statistics()
             )
-            self.data["debugging_data"]["total_counts_daily_average"] = (
-                total_counts_daily_average
-            )
-            self.data["debugging_data"]["total_counts_daily_std_dev"] = (
-                total_counts_daily_std_dev
-            )
+            self.data["debugging_data"]["total_counts_daily_average"] = total_counts_daily_average
+            self.data["debugging_data"]["total_counts_daily_std_dev"] = total_counts_daily_std_dev
             if (
                 total_counts_daily_average - n_lo * total_counts_daily_std_dev
                 <= total_counts
@@ -534,9 +482,7 @@ def _flag_relative_difference_vs_threshold(
             relative_difference = np.fabs(
                 self.data[parameter_1_name] - self.data[parameter_2_name]
             ) / (self.data[parameter_1_name] + self.data[parameter_2_name])
-            self.data["debugging_data"]["spin_period_relative_difference"] = (
-                relative_difference
-            )
+            self.data["debugging_data"]["spin_period_relative_difference"] = relative_difference
             if relative_difference < threshold:
                 self.data["flags"][flag_name] = False
             else:
@@ -551,9 +497,7 @@ def _process_anc_input_from_sdc(self, anc_input_from_sdc):
 
         # read ancillary variables provided by SDC (IMAP general telemetry)
         # note that finally different CSV files can be used for different quantities
-        anc_data = pd.read_csv(
-            anc_input_from_sdc["anc_data_file_name"], sep=" ", comment="#"
-        )
+        anc_data = pd.read_csv(anc_input_from_sdc["anc_data_file_name"], sep=" ", comment="#")
         # TMP_SOLUTION: we use here a csv file with mock ancillary data generated by
         # GLOWS Team using generate_anc_file.py script
         # the following procedures invoked below:
@@ -601,9 +545,8 @@ def _read_from_json_file(self, file_name):
         Args:
             file_name: name of of file with L1b data
         """
-        file_handler = open(file_name, "r")
-        self.data = json.load(file_handler)
-        file_handler.close()
+        with open(file_name, "r") as file_handler:
+            self.data = json.load(file_handler)
 
         # hexadecimal values saved as strings require special treatment to make them integers
         self.data["histogram_flag_array"] = [
@@ -669,35 +612,20 @@ def _save_data_to_json_file(self):
         # them to be saved as one-liners (i.e., without \n after each element) or we want them to
         # be printed with a specific format by json.dumps()
         # so we convert variables to strings as defined in fmt
-        for key in fmt["arrays"].keys():
-            data[key] = (
-                "["
-                + ", ".join(map(lambda x: fmt["arrays"][key] % x, list(data[key])))
-                + "]"
-            )
-        for key in fmt["scalar variables"].keys():
-            data[key] = "|" + fmt["scalar variables"][key] % data[key] + "|"
-        for key in fmt["lon lat variables"].keys():
+        for key in fmt["arrays"]:
+            data[key] = "[" + ", ".join(fmt["arrays"][key] % x for x in list(data[key])) + "]"
+        for key, value in fmt["scalar variables"].items():
+            data[key] = "|" + value % data[key] + "|"
+        for key, value in fmt["lon lat variables"].items():
             for sec_key in ["lon", "lat"]:
-                data[key][sec_key] = (
-                    "|" + fmt["lon lat variables"][key] % data[key][sec_key] + "|"
-                )
-        for key in fmt["vector variables"].keys():
+                data[key][sec_key] = "|" + value % data[key][sec_key] + "|"
+        for key, value in fmt["vector variables"].items():
             for sec_key in ["x", "y", "z"]:
-                data[key][sec_key] = (
-                    "|" + fmt["vector variables"][key] % data[key][sec_key] + "|"
-                )
+                data[key][sec_key] = "|" + value % data[key][sec_key] + "|"
 
         # histogram_flag_array requires special hexadecimal treatment
         data["histogram_flag_array"] = (
-            "["
-            + ", ".join(
-                map(
-                    lambda x: '"0x' + format(x, "x").zfill(4) + '"',
-                    list(data["histogram_flag_array"]),
-                )
-            )
-            + "]"
+            "[" + ", ".join(f'0x{x:04x}"' for x in list(data["histogram_flag_array"])) + "]"
         )
 
         # generate JSON content to be saved in output file
@@ -708,59 +636,43 @@ def _save_data_to_json_file(self):
         json_content = json_content.replace('|"', "").replace('"|', "")
         json_content = json_content.replace('\\"', '"')
 
-        if 1 == 2:
-            # some fields need to be temporarily converted to string arrays, because we want to force
-            # them to be saved as one-liners (i.e., without \n after each element) by json.dumps()
-            spin_angle_tmp = self.data["imap_spin_angle_bin_cntr"]
-            histogram_tmp = self.data["histogram"]
-            flags_tmp = self.data["histogram_flag_array"]
-            self.data["histogram"] = (
-                "[" + ", ".join(map(str, list(histogram_tmp))) + "]"
-            )
-            self.data["imap_spin_angle_bin_cntr"] = (
-                "[" + ", ".join(map(lambda x: "%.2f" % x, list(spin_angle_tmp))) + "]"
-            )
-            self.data["histogram_flag_array"] = (
-                "["
-                + ", ".join(
-                    map(
-                        lambda x: '"0x' + format(x, "x").zfill(4) + '"', list(flags_tmp)
-                    )
-                )
-                + "]"
-            )
-            json_content = json.dumps(self.data, indent=4, default=vars)
-            self.data["imap_spin_angle_bin_cntr"] = spin_angle_tmp
-            self.data["histogram"] = histogram_tmp
-            self.data["histogram_flag_array"] = flags_tmp
-            # modify json_content to make string arrays be seen finally as number arrays
-            json_content = json_content.replace('"[', "[").replace(']"', "]")
-            json_content = json_content.replace('\\"', '"')
+        # some fields need to be temporarily converted to string arrays, because we want to force
+        # them to be saved as one-liners (i.e., without \n after each element) by json.dumps()
+        spin_angle_tmp = self.data["imap_spin_angle_bin_cntr"]
+        histogram_tmp = self.data["histogram"]
+        flags_tmp = self.data["histogram_flag_array"]
+        self.data["histogram"] = "[" + ", ".join(map(str, list(histogram_tmp))) + "]"
+        self.data["imap_spin_angle_bin_cntr"] = (
+            "[" + ", ".join(f"{x:.2f}" for x in list(spin_angle_tmp)) + "]"
+        )
+        self.data["histogram_flag_array"] = (
+            "[" + ", ".join(f'0x{x:04x}"' for x in list(flags_tmp)) + "]"
+        )
+        json_content = json.dumps(self.data, indent=4, default=vars)
+        self.data["imap_spin_angle_bin_cntr"] = spin_angle_tmp
+        self.data["histogram"] = histogram_tmp
+        self.data["histogram_flag_array"] = flags_tmp
+        # modify json_content to make string arrays be seen finally as number arrays
+        json_content = json_content.replace('"[', "[").replace(']"', "]")
+        json_content = json_content.replace('\\"', '"')
 
         # start_time_utc string for output file name, based on unique_block_identifier
-        start_time_utc = "".join(
-            filter(str.isdigit, self.data["unique_block_identifier"])
-        )
+        start_time_utc = "".join(filter(str.isdigit, self.data["unique_block_identifier"]))
 
         # the output file name is constructed using a convention defined in Sec. 1.4.2 of
         # "IMAP SDC to Instrument Team ICD"
-        file_name = "data_l1b_histograms/imap_glows_l1b_%s_orbX_modX_p_v00.json" % (
-            start_time_utc
-        )
+        file_name = f"data_l1b_histograms/imap_glows_l1b_{start_time_utc}_orbX_modX_p_v00.json"
 
         # save data
-        file_handler = open(file_name, "w")
-        print(json_content, file=file_handler)
-        file_handler.close()
+        with open(file_name, "w") as file_handler:
+            print(json_content, file=file_handler)
 
         # TO_BE_REMOVED append file name to l1b list needed for the l1b-to-l2 processing
         # file_handler = open('l1b_list.dat', 'a')
         # print(file_name, file=file_handler)
         # file_handler.close()
 
-    def _set_histogram_flag_array_by_instr_team(
-        self, anc_input_from_instr_team, type_of_list
-    ):
+    def _set_histogram_flag_array_by_instr_team(self, anc_input_from_instr_team, type_of_list):
         """
         Set histogram flag array using lists defined by IMAP/GLOWS Instrument Team
             bin indexes in the list are marked by True
@@ -768,42 +680,39 @@ def _set_histogram_flag_array_by_instr_team(
             anc_input_from_instr_team: ancillary input provided by IMAP/GLOWS Instrument Team
             type_of_list: 'exclusions_by_instr_team' or 'suspected_transients'
         """
-        file_handler = open(anc_input_from_instr_team[type_of_list], "r")
-        line = file_handler.readline()
-        while line:
-            if line[0] != "#":
-                # sanity check
-                assert line[:2] == "20" and line[10] == "T", (
-                    "Bad identifier "
-                    + line[:20]
-                    + " in "
-                    + anc_input_from_instr_team[type_of_list]
-                )
-                identifier = line.rstrip().split(" ")[0]
-                flags = line.rstrip().split(" ")[1]
-
-                # sanity check
-                # this check turned out to be inappropriate because number of bins is not always the same
-                # assert len(flags) == self.data['number_of_bins_per_histogram'], \
-                #    'Bad length of mask_array for identifier ' + identifier + ' in ' + \
-                #    anc_input_from_instr_team[type_of_list]
-
-                if identifier == self.data["unique_block_identifier"]:
-                    flags = np.array(list(flags)).astype(bool)
-                    #                    print(np.shape(flags))
-                    if type_of_list == "exclusions_by_instr_team":
-                        flags = np.left_shift(
-                            flags, L1B_L2_HIST_FLAG_FIELDS["is_excluded_by_instr_team"]
-                        )
-                    if type_of_list == "suspected_transients":
-                        flags = np.left_shift(
-                            flags, L1B_L2_HIST_FLAG_FIELDS["is_suspected_transient"]
-                        )
-                    self.data["histogram_flag_array"] = (
-                        self.data["histogram_flag_array"] | flags
+        with open(anc_input_from_instr_team[type_of_list], "r") as file_handler:
+            for line in file_handler:
+                if line[0] != "#":
+                    # sanity check
+                    assert line[:2] == "20" and line[10] == "T", (
+                        "Bad identifier "
+                        + line[:20]
+                        + " in "
+                        + anc_input_from_instr_team[type_of_list]
                     )
-            line = file_handler.readline()
-        file_handler.close()
+                    identifier = line.rstrip().split(" ")[0]
+                    flags = line.rstrip().split(" ")[1]
+
+                    # sanity check
+                    # this check turned out to be inappropriate because number of bins is not always the same
+                    # assert len(flags) == self.data['number_of_bins_per_histogram'], \
+                    #    'Bad length of mask_array for identifier ' + identifier + ' in ' + \
+                    #    anc_input_from_instr_team[type_of_list]
+
+                    if identifier == self.data["unique_block_identifier"]:
+                        flags = np.array(list(flags)).astype(bool)
+                        #                    print(np.shape(flags))
+                        if type_of_list == "exclusions_by_instr_team":
+                            flags = np.left_shift(
+                                flags, L1B_L2_HIST_FLAG_FIELDS["is_excluded_by_instr_team"]
+                            )
+                        if type_of_list == "suspected_transients":
+                            flags = np.left_shift(
+                                flags, L1B_L2_HIST_FLAG_FIELDS["is_suspected_transient"]
+                            )
+                        self.data["histogram_flag_array"] = (
+                            self.data["histogram_flag_array"] | flags
+                        )
 
     def _set_histogram_flag_array_excl_by_instr_team(self, anc_input_from_instr_team):
         """
@@ -812,38 +721,35 @@ def _set_histogram_flag_array_excl_by_instr_team(self, anc_input_from_instr_team
         Args:
             anc_input_from_instr_team: ancillary input provided by IMAP/GLOWS Instrument Team
         """
-        file_handler = open(anc_input_from_instr_team["exclusions_by_instr_team"], "r")
-        line = file_handler.readline()
-        while line:
-            if line[0] != "#":
-                # sanity check
-                assert line[:2] == "20" and line[10] == "_", (
-                    "Bad identifier "
-                    + line[:20]
-                    + " in "
-                    + anc_input_from_instr_team["exclusions_by_instr_team"]
-                )
-                identifier = line.rstrip().split(" ")[0]
-                flags = line.rstrip().split(" ")[1]
-
-                # sanity check
-                assert len(flags) == self.data["number_of_bins_per_histogram"], (
-                    "Bad length of mask_array for identifier "
-                    + identifier
-                    + " in "
-                    + anc_input_from_instr_team["exclusions_by_instr_team"]
-                )
-
-                if identifier == self.data["unique_block_identifier"]:
-                    flags = np.array(list(flags)).astype(bool)
-                    flags = np.left_shift(
-                        flags, L1B_L2_HIST_FLAG_FIELDS["is_excluded_by_instr_team"]
+        with open(anc_input_from_instr_team["exclusions_by_instr_team"], "r") as file_handler:
+            for line in file_handler:
+                if line[0] != "#":
+                    # sanity check
+                    assert line[:2] == "20" and line[10] == "_", (
+                        "Bad identifier "
+                        + line[:20]
+                        + " in "
+                        + anc_input_from_instr_team["exclusions_by_instr_team"]
                     )
-                    self.data["histogram_flag_array"] = (
-                        self.data["histogram_flag_array"] | flags
+                    identifier = line.rstrip().split(" ")[0]
+                    flags = line.rstrip().split(" ")[1]
+
+                    # sanity check
+                    assert len(flags) == self.data["number_of_bins_per_histogram"], (
+                        "Bad length of mask_array for identifier "
+                        + identifier
+                        + " in "
+                        + anc_input_from_instr_team["exclusions_by_instr_team"]
                     )
-            line = file_handler.readline()
-        file_handler.close()
+
+                    if identifier == self.data["unique_block_identifier"]:
+                        flags = np.array(list(flags)).astype(bool)
+                        flags = np.left_shift(
+                            flags, L1B_L2_HIST_FLAG_FIELDS["is_excluded_by_instr_team"]
+                        )
+                        self.data["histogram_flag_array"] = (
+                            self.data["histogram_flag_array"] | flags
+                        )
 
     def _set_histogram_flag_array_uv_sources(self, anc_input_from_instr_team, settings):
         """
@@ -854,9 +760,7 @@ def _set_histogram_flag_array_uv_sources(self, anc_input_from_instr_team, settin
             settings: filter settings
         """
 
-        if check_if_contains_actual_data(
-            anc_input_from_instr_team["map_of_uv_sources"]
-        ):
+        if check_if_contains_actual_data(anc_input_from_instr_team["map_of_uv_sources"]):
             # read ecliptic coords and angular radiuses for the masking of bright uv point sources
             uv_sources_coords_and_radiuses = np.loadtxt(
                 anc_input_from_instr_team["map_of_uv_sources"], usecols=[1, 2, 3]
@@ -869,25 +773,19 @@ def _set_histogram_flag_array_uv_sources(self, anc_input_from_instr_team, settin
 
             # a radius_bins grouping is used below for code speed up, because otherwise we would need to use
             # coord1.separation(coord2) from astropy, which turned out to be slow in tests
-            n_radius_bins = (
-                10  # actually used bins, see +2 in np.linspace() argument below
-            )
+            n_radius_bins = 10  # actually used bins, see +2 in np.linspace() argument below
             radius_bins = np.linspace(
                 uv_sources_coords_and_radiuses[:, 2].min() - 1.0e-6,
                 uv_sources_coords_and_radiuses[:, 2].max() + 1.0e-6,
                 n_radius_bins + 2,
             )
             # digitizing/binning into radius_bins
-            radius_idxs = np.digitize(
-                uv_sources_coords_and_radiuses[:, 2], bins=radius_bins
-            )
+            radius_idxs = np.digitize(uv_sources_coords_and_radiuses[:, 2], bins=radius_bins)
 
             for i in range(1, n_radius_bins + 2):  # looping over all radius_bins groups
                 rejection_radius = radius_bins[i]
                 idxs = np.nonzero(radius_idxs == i)[0]
-                if (
-                    len(idxs) > 0
-                ):  # check if we have any uv sources to check in the current group
+                if len(idxs) > 0:  # check if we have any uv sources to check in the current group
                     match_catalog = SkyCoord(
                         uv_sources_coords_and_radiuses[idxs, 0],
                         uv_sources_coords_and_radiuses[idxs, 1],
@@ -913,9 +811,7 @@ def _set_histogram_flag_array_uv_sources(self, anc_input_from_instr_team, settin
             flag = np.left_shift(flag, L1B_L2_HIST_FLAG_FIELDS["is_close_to_uv_source"])
             self.data["histogram_flag_array"] = self.data["histogram_flag_array"] | flag
 
-    def _set_histogram_flag_array_excl_regions(
-        self, anc_input_from_instr_team, settings
-    ):
+    def _set_histogram_flag_array_excl_regions(self, anc_input_from_instr_team, settings):
         """
         Set histogram flag array using a map of excluded regions, close-to-map-points bins are
             denoted by True
@@ -924,13 +820,9 @@ def _set_histogram_flag_array_excl_regions(
             settings: filter settings
         """
 
-        if check_if_contains_actual_data(
-            anc_input_from_instr_team["map_of_excluded_regions"]
-        ):
+        if check_if_contains_actual_data(anc_input_from_instr_team["map_of_excluded_regions"]):
             # read ecliptic coords of points defining excluded regions
-            excluded_pts_coords = np.loadtxt(
-                anc_input_from_instr_team["map_of_excluded_regions"]
-            )
+            excluded_pts_coords = np.loadtxt(anc_input_from_instr_team["map_of_excluded_regions"])
 
             # set angular radius below which bins are too close to map points
             rejection_radius = settings["filter_based_on_maps"][
@@ -972,9 +864,7 @@ def _set_histogram_flag_array_excl_regions(
                 flag = np.zeros_like(self.data["histogram"], bool)
                 flag[idxs_to_reject] = True
 
-            flag = np.left_shift(
-                flag, L1B_L2_HIST_FLAG_FIELDS["is_inside_excluded_region"]
-            )
+            flag = np.left_shift(flag, L1B_L2_HIST_FLAG_FIELDS["is_inside_excluded_region"])
             self.data["histogram_flag_array"] = self.data["histogram_flag_array"] | flag
 
     def _set_histogram_flag_array_test_pattern(self):
@@ -1017,25 +907,22 @@ def total_counts_daily_statistics(self):
         Compute daily average for the total number of counts in L1a histograms
         """
         file_name = "data_l1a_histograms/total_counts_file.dat"
-        file_handler = open(file_name, "r")
-        line = file_handler.readline()
-
-        # sanity check
-        assert (
-            line.rstrip().split(" ")[1] == self.data["block_header"]["pkts_file_name"]
-        ), (
-            "Packets file name "
-            + line.rstrip().split(" ")[1]
-            + " in "
-            + file_name
-            + " is different from currently processed packets file "
-            + self.data["block_header"]["pkts_file_name"]
-        )
+        with open(file_name, "r") as file_handler:
+            line = file_handler.readline()
+
+            # sanity check
+            assert line.rstrip().split(" ")[1] == self.data["block_header"]["pkts_file_name"], (
+                "Packets file name "
+                + line.rstrip().split(" ")[1]
+                + " in "
+                + file_name
+                + " is different from currently processed packets file "
+                + self.data["block_header"]["pkts_file_name"]
+            )
 
-        # the first column of data array below: 'seq_count_in_pkts_file'
-        # the second column: total counts in a L1a histogram
-        data = np.loadtxt(file_handler)
-        file_handler.close()
+            # the first column of data array below: 'seq_count_in_pkts_file'
+            # the second column: total counts in a L1a histogram
+            data = np.loadtxt(file_handler)
         total_counts_average = np.mean(data[:, 1])
         total_counts_std_dev = np.std(data[:, 1])
         return total_counts_average, total_counts_std_dev
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/l2_data_histogram.py b/imap_l3_processing/glows/l3a/glows_toolkit/l2_data_histogram.py
index 56209638..9f4eba71 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/l2_data_histogram.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/l2_data_histogram.py
@@ -2,11 +2,13 @@
 Author: Marek Strumik, maro at cbk.waw.pl
 """
 
-import json
 import copy
+import json
+
 import numpy as np
-from .constants import VERSION, L1B_L2_HIST_FLAG_FIELDS, SCAN_CIRCLE_ANGULAR_RADIUS
-from .funcs import time_sec_subsec_to_utc, calibration_factor
+
+from .constants import L1B_L2_HIST_FLAG_FIELDS, SCAN_CIRCLE_ANGULAR_RADIUS, VERSION
+from .funcs import calibration_factor, time_sec_subsec_to_utc
 from .geom_fun_libr_box import spin2lb
 
 
@@ -32,27 +34,24 @@ def __init__(self, anc_input_from_instr_team):
 
         # initialize counters
         self.var["l1b_file_counter_all"] = 0  # all l1b files processed for a given day
-        self.var["l1b_file_counter_good_time"] = (
-            0  # only good-time files for a given day
-        )
+        self.var["l1b_file_counter_good_time"] = 0  # only good-time files for a given day
 
         # read pipeline settings to be used for L2
-        file_handler = open(anc_input_from_instr_team["settings"], "r")
-        self.var["settings"] = json.load(file_handler)
-        file_handler.close()
+        with open(anc_input_from_instr_team["settings"], "r") as file_handler:
+            self.var["settings"] = json.load(file_handler)
 
         # sanity check for bad-angle flags (all L1B_L2_HIST_FLAG_FIELDS flags must be included in
         # self.var['settings'] in the correct order)
-        list_1 = list(self.var["settings"]["active_bad_angle_flags"].keys())
-        list_2 = list(L1B_L2_HIST_FLAG_FIELDS.keys())
+        list_1 = list(self.var["settings"]["active_bad_angle_flags"])
+        list_2 = list(L1B_L2_HIST_FLAG_FIELDS)
         assert len(list_1) == len(list_2), (
             "Different numbers of keys in self.var['settings']['active_bad_angle_flags'] "
             + "and in L1B_L2_HIST_FLAG_FIELDS"
         )
         for i, __ in enumerate(list_1):
-            assert list_1[i] == list_2[i], (
+            assert __ == list_2[i], (
                 'Different keys "'
-                + list_1[i]
+                + __
                 + '" and "'
                 + list_2[i]
                 + "\" in self.var['settings']['active_bad_angle_flags'] and L1B_L2_HIST_FLAG_FIELDS"
@@ -60,14 +59,14 @@ def __init__(self, anc_input_from_instr_team):
 
         # define a structure to keep track of occurences of bad-time flags
         self.var["bad_time_flag_occurences"] = {}
-        for key in self.var["settings"]["active_bad_time_flags"].keys():
+        for key in self.var["settings"]["active_bad_time_flags"]:
             self.var["bad_time_flag_occurences"][key] = 0
 
         # define a bad-time mask which is used to decide which L1b files are accepted
         # as a whole during generation of L2 data product
         self.var["bad_time_mask"] = "".join(
             [
-                "%d" % self.var["settings"]["active_bad_time_flags"][key]
+                str(self.var["settings"]["active_bad_time_flags"][key])
                 for key in self.var["settings"]["active_bad_time_flags"]
             ]
         )
@@ -77,7 +76,7 @@ def __init__(self, anc_input_from_instr_team):
         # during generation of L2 data product
         self.var["bad_angle_mask"] = "".join(
             [
-                "%d" % self.var["settings"]["active_bad_angle_flags"][key]
+                str(self.var["settings"]["active_bad_angle_flags"][key])
                 for key in self.var["settings"]["active_bad_angle_flags"]
             ]
         )
@@ -97,14 +96,12 @@ def _averages_accumulate(self, l1b_data):
         Args:
             l1b_data: L1b data provided as data field of L1bDataHistogram object
         """
-        for key in self.var["l1b_averages"].keys():
+        for key in self.var["l1b_averages"]:
             if key == "counter":
                 continue
             if isinstance(self.var["l1b_averages"][key], dict):
-                for second_key in self.var["l1b_averages"][key].keys():
-                    self.var["l1b_averages"][key][second_key].append(
-                        l1b_data[key][second_key]
-                    )
+                for second_key in self.var["l1b_averages"][key]:
+                    self.var["l1b_averages"][key][second_key].append(l1b_data[key][second_key])
             else:
                 self.var["l1b_averages"][key].append(l1b_data[key])
         self.var["l1b_averages"]["counter"] += 1
@@ -119,11 +116,11 @@ def _averages_init(self, l1b_data):
 
         # generate dictionary for computing averages over GOOD TIMES for L1b-file ancillary parameters
         self.var["l1b_averages"] = {}
-        for key in l1b_data.keys():
+        for key in l1b_data:
             if key.endswith("average"):
                 if isinstance(l1b_data[key], dict):
                     self.var["l1b_averages"][key] = {}
-                    for second_key in l1b_data[key].keys():
+                    for second_key in l1b_data[key]:
                         self.var["l1b_averages"][key][second_key] = []
                 else:
                     self.var["l1b_averages"][key] = []
@@ -139,25 +136,23 @@ def _check_l1b_bad_time_flags(self, l1b_data):
         """
         # sanity check, all bad-time flags in L1b file must be included in self.var['settings']
         # in the correct order, otherwise we can assume that an error occurred
-        list_1 = list(self.var["settings"]["active_bad_time_flags"].keys())
-        list_2 = list(l1b_data["flags"].keys())
+        list_1 = list(self.var["settings"]["active_bad_time_flags"])
+        list_2 = list(l1b_data["flags"])
         assert len(list_1) == len(list_2), (
             "Different number of keys in self.var['settings']['active_bad_time_flags'] "
             + "and in l1b_data['flags']"
         )
         for i, __ in enumerate(list_1):
-            assert list_1[i] == list_2[i], (
+            assert __ == list_2[i], (
                 'Different keys "'
-                + list_1[i]
+                + __
                 + '" and "'
                 + list_2[i]
                 + "\" in self.var['settings']['active_bad_time_flags'] and l1b_data['flags']"
             )
 
         # set bad-time-flag bits to compare it with self.var['bad_time_mask']
-        l1b_bad_time_flags = "".join(
-            ["%d" % l1b_data["flags"][key] for key in l1b_data["flags"]]
-        )
+        l1b_bad_time_flags = "".join([str(l1b_data["flags"][key]) for key in l1b_data["flags"]])
         l1b_bad_time_flags = "0b" + l1b_bad_time_flags[::-1]
 
         # compare bad_time_flags for L1b with mask
@@ -190,17 +185,15 @@ def _compute_anc_parms_averages_and_spreads(self):
         if self.var["l1b_averages"]["counter"] == 0:  # there is nothing to compute
             return
 
-        for key in self.var["l1b_averages"].keys():
+        for key in self.var["l1b_averages"]:
             spread_key = "_".join(key.split("_")[:-1]) + "_std_dev"
             if key == "counter":
                 continue
             if isinstance(self.var["l1b_averages"][key], dict):
                 self.data[key] = {}
                 self.data[spread_key] = {}
-                for second_key in self.var["l1b_averages"][key].keys():
-                    self.data[key][second_key] = np.mean(
-                        self.var["l1b_averages"][key][second_key]
-                    )
+                for second_key in self.var["l1b_averages"][key]:
+                    self.data[key][second_key] = np.mean(self.var["l1b_averages"][key][second_key])
                     self.data[spread_key][second_key] = np.std(
                         self.var["l1b_averages"][key][second_key]
                     )
@@ -216,12 +209,8 @@ def generate_l2_data(self, anc_input_from_instr_team):
                 and MOC see ANC_INPUT_FROM_INSTRUMENT_TEAM in constants.py
         """
 
-        self.data["header"]["number_of_l1b_files_used"] = self.var[
-            "l1b_file_counter_good_time"
-        ]
-        self.data["header"]["number_of_all_l1b_files"] = self.var[
-            "l1b_file_counter_all"
-        ]
+        self.data["header"]["number_of_l1b_files_used"] = self.var["l1b_file_counter_good_time"]
+        self.data["header"]["number_of_all_l1b_files"] = self.var["l1b_file_counter_all"]
 
         if self.data["header"]["number_of_l1b_files_used"] > 0:
             self.data["start_time"] = time_sec_subsec_to_utc(
@@ -241,9 +230,7 @@ def generate_l2_data(self, anc_input_from_instr_team):
             self.data["daily_lightcurve"]["exposure_times"] = np.zeros(
                 self.var["number_of_bins_per_histogram"], float
             )
-            self.var["raw_histogram"] = np.zeros(
-                self.var["number_of_bins_per_histogram"], int
-            )
+            self.var["raw_histogram"] = np.zeros(self.var["number_of_bins_per_histogram"], int)
             self.data["daily_lightcurve"]["photon_flux"] = np.zeros(
                 self.var["number_of_bins_per_histogram"], float
             )
@@ -254,8 +241,7 @@ def generate_l2_data(self, anc_input_from_instr_team):
         # compute cps from raw histogram and exposure times
         idxs = np.nonzero(self.data["daily_lightcurve"]["exposure_times"] > 0.0)[0]
         self.data["daily_lightcurve"]["photon_flux"][idxs] = (
-            self.var["raw_histogram"][idxs]
-            / self.data["daily_lightcurve"]["exposure_times"][idxs]
+            self.var["raw_histogram"][idxs] / self.data["daily_lightcurve"]["exposure_times"][idxs]
         )
 
         # add raw histogram counts
@@ -289,7 +275,7 @@ def generate_l2_data(self, anc_input_from_instr_team):
             idx = np.argsort(spin_angle_from_north)[0]
 
             # we have the shift value, so we can roll all arrays in self.data['daily_lightcurve']
-            for key in self.data["daily_lightcurve"].keys():
+            for key in self.data["daily_lightcurve"]:
                 self.data["daily_lightcurve"][key] = np.roll(
                     self.data["daily_lightcurve"][key], -idx
                 )
@@ -298,21 +284,15 @@ def generate_l2_data(self, anc_input_from_instr_team):
             ones = np.ones(len(self.data["daily_lightcurve"]["spin_angle"]), float)
             histogram_bins_ecl_coords = np.degrees(
                 spin2lb(
-                    np.radians(self.data["spin_axis_orientation_average"]["lon"])
-                    * ones,
-                    np.radians(self.data["spin_axis_orientation_average"]["lat"])
-                    * ones,
+                    np.radians(self.data["spin_axis_orientation_average"]["lon"]) * ones,
+                    np.radians(self.data["spin_axis_orientation_average"]["lat"]) * ones,
                     np.radians(self.data["daily_lightcurve"]["spin_angle"]),
                     0.0,
                     np.radians(SCAN_CIRCLE_ANGULAR_RADIUS) * ones,
                 )
             )
-            self.data["daily_lightcurve"]["ecliptic_lon"] = histogram_bins_ecl_coords[
-                :, 0
-            ]
-            self.data["daily_lightcurve"]["ecliptic_lat"] = histogram_bins_ecl_coords[
-                :, 1
-            ]
+            self.data["daily_lightcurve"]["ecliptic_lon"] = histogram_bins_ecl_coords[:, 0]
+            self.data["daily_lightcurve"]["ecliptic_lat"] = histogram_bins_ecl_coords[:, 1]
 
         # apply calibration to get helioglow intensity in physical units of Rayleigh
         cps_per_R = calibration_factor(
@@ -343,17 +323,12 @@ def is_new_observational_day(self, l1b_data):
             l1b_data: L1b data provided in the form of data field of L1bDataHistogram object
         """
 
-        is_new_observ_day = False  # init
-
         # check if is_night flag at L1b goes from True to False, if so then we have a new observational day
-        if (
-            self.var["is_night_for_previous_l1b"] >= 0
-        ):  # we are at the second (or later) l1b file
-            if (
-                self.var["is_night_for_previous_l1b"] == 1
-                and not l1b_data["flags"]["is_night"]
-            ):  # new observational day
-                is_new_observ_day = True
+        is_new_observ_day = (
+            self.var["is_night_for_previous_l1b"] >= 0  # we are at the second (or later) l1b file
+            and self.var["is_night_for_previous_l1b"] == 1
+            and not l1b_data["flags"]["is_night"]  # new observational day
+        )
 
         self.var["is_night_for_previous_l1b"] = l1b_data["flags"]["is_night"]
         return is_new_observ_day
@@ -372,20 +347,16 @@ def process_l1b_data_files(self, l1b_data, pointing_counter):
             # generate spin-angle values for L2 for which spin=0 is measured from the
             # northernmost point of lightcurve, however it must have the same resolution as
             # l1b histograms so we can use L1b imap_spin_angle values for angular-grid generation
-            self.data["daily_lightcurve"]["spin_angle"] = l1b_data[
-                "imap_spin_angle_bin_cntr"
-            ]
+            self.data["daily_lightcurve"]["spin_angle"] = l1b_data["imap_spin_angle_bin_cntr"]
         self.var["l1b_end_time_all"] = (
             l1b_data["imap_start_time"] + l1b_data["imap_end_time_offset"]
         )
-        self.var["number_of_bins_per_histogram"] = l1b_data[
-            "number_of_bins_per_histogram"
-        ]
+        self.var["number_of_bins_per_histogram"] = l1b_data["number_of_bins_per_histogram"]
 
         # increment all-l1b-files counter
         self.var["l1b_file_counter_all"] += 1
 
-        for key in self.var["settings"]["active_bad_time_flags"].keys():
+        for key in self.var["settings"]["active_bad_time_flags"]:
             if l1b_data["flags"][key]:
                 self.var["bad_time_flag_occurences"][key] += 1
 
@@ -393,14 +364,10 @@ def process_l1b_data_files(self, l1b_data, pointing_counter):
             if self.var["l1b_file_counter_good_time"] <= 0:
                 # things to do when we have the first good-time L1b data file
                 self.data["header"] = {
-                    "flight_software_version": l1b_data["block_header"][
-                        "flight_software_version"
-                    ],
+                    "flight_software_version": l1b_data["block_header"]["flight_software_version"],
                     "ground_software_version": VERSION,
                     "pkts_file_name": l1b_data["block_header"]["pkts_file_name"],
-                    "ancillary_data_files": l1b_data["block_header"][
-                        "ancillary_data_files"
-                    ],
+                    "ancillary_data_files": l1b_data["block_header"]["ancillary_data_files"],
                 }
 
                 # we are here at the first good-time L1b file, so we set the current state of
@@ -485,14 +452,12 @@ def _read_from_json_file(self, file_name):
         Args:
             file_name: name of of file with L1b data
         """
-        file_handler = open(file_name, "r")
-        self.data = json.load(file_handler)
-        file_handler.close()
+        with open(file_name, "r") as file_handler:
+            self.data = json.load(file_handler)
 
         # hexadecimal values saved as strings require special treatment to make them integers
         self.data["daily_lightcurve"]["histogram_flag_array"] = [
-            int(x, base=16)
-            for x in self.data["daily_lightcurve"]["histogram_flag_array"]
+            int(x, base=16) for x in self.data["daily_lightcurve"]["histogram_flag_array"]
         ]
 
         # additional field to keep track where data come from
@@ -558,38 +523,28 @@ def _save_data_to_json_file(self):
         # them to be saved as one-liners (i.e., without \n after each element) or we want them to
         # be printed with a specific format by json.dumps()
         # so we convert variables to strings as defined in fmt
-        for key in fmt["daily_lightcurve"].keys():
+        for key in fmt["daily_lightcurve"]:
             data["daily_lightcurve"][key] = (
                 "["
                 + ", ".join(
-                    map(
-                        lambda x: fmt["daily_lightcurve"][key] % x,
-                        list(data["daily_lightcurve"][key]),
-                    )
-                )
-                + "]"
+                    fmt["daily_lightcurve"][key] % x for x in list(data["daily_lightcurve"][key])
+                ),
+                +"]",
             )
-        for key in fmt["scalar variables"].keys():
-            data[key] = "|" + fmt["scalar variables"][key] % data[key] + "|"
-        for key in fmt["lon lat variables"].keys():
+        for key, value in fmt["scalar variables"].items():
+            data[key] = "|" + value % data[key] + "|"
+        for key, value in fmt["lon lat variables"].items():
             for sec_key in ["lon", "lat"]:
-                data[key][sec_key] = (
-                    "|" + fmt["lon lat variables"][key] % data[key][sec_key] + "|"
-                )
-        for key in fmt["vector variables"].keys():
+                data[key][sec_key] = "|" + value % data[key][sec_key] + "|"
+        for key in fmt["vector variables"].items():
             for sec_key in ["x", "y", "z"]:
-                data[key][sec_key] = (
-                    "|" + fmt["vector variables"][key] % data[key][sec_key] + "|"
-                )
+                data[key][sec_key] = "|" + value % data[key][sec_key] + "|"
 
         # histogram_flag_array requires special hexadecimal treatment
         data["daily_lightcurve"]["histogram_flag_array"] = (
             "["
             + ", ".join(
-                map(
-                    lambda x: '"0x' + format(x, "x").zfill(4) + '"',
-                    list(data["daily_lightcurve"]["histogram_flag_array"]),
-                )
+                f'0x{x:04x}"' for x in list(data["daily_lightcurve"]["histogram_flag_array"])
             )
             + "]"
         )
@@ -605,10 +560,7 @@ def _save_data_to_json_file(self):
         # the output file name is constructed using a convention defined in Sec. 1.4.2 of
         # "IMAP SDC to Instrument Team ICD"
         date_utc = "".join(filter(str.isdigit, self.data["start_time"]))
-        file_name = (
-            "data_l2_histograms/imap_glows_l2_%s_orbX_modX_p_v00.json" % date_utc
-        )
+        file_name = f"data_l2_histograms/imap_glows_l2_{date_utc}_orbX_modX_p_v00.json"
 
-        file_handler = open(file_name, "w")
-        print(json_content, file=file_handler)
-        file_handler.close()
+        with open(file_name, "w") as file_handler:
+            print(json_content, file=file_handler)
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/l3a_data.py b/imap_l3_processing/glows/l3a/glows_toolkit/l3a_data.py
index 0c093546..5b3a94cc 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/l3a_data.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/l3a_data.py
@@ -9,7 +9,7 @@
 from astropy import units as u
 from astropy_healpix import HEALPix
 
-from .constants import VERSION, SCAN_CIRCLE_ANGULAR_RADIUS
+from .constants import SCAN_CIRCLE_ANGULAR_RADIUS, VERSION
 from .funcs import calibration_factor, check_if_contains_actual_data
 from .geom_fun_libr_box import spin2lb
 
@@ -35,9 +35,8 @@ def __init__(self, anc_input_from_instr_team):
         self.var = {}
 
         # read pipeline settings to be used for L3a
-        file_handler = open(anc_input_from_instr_team["settings"], "r")
-        settings = json.load(file_handler)
-        file_handler.close()
+        with open(anc_input_from_instr_team["settings"], "r") as file_handler:
+            settings = json.load(file_handler)
         self.var["nominal_number_of_bins"] = settings["l3a_nominal_number_of_bins"]
 
     def _compute_extra_heliospheric_bckgrd(self, anc_input_from_instr_team):
@@ -49,22 +48,19 @@ def _compute_extra_heliospheric_bckgrd(self, anc_input_from_instr_team):
                 see ANC_INPUT_FROM_INSTRUMENT_TEAM in constants.py
         """
 
-        if check_if_contains_actual_data(
-            anc_input_from_instr_team["extra_heliospheric_bckgrd"]
-        ):
-            fh = open(anc_input_from_instr_team["extra_heliospheric_bckgrd"], "r")
-            for i in range(3):
-                line = fh.readline()
-            # sanity check
-            if line.split()[4] != "NSIDE":
-                raise Exception(
-                    "error _compute_extra_heliospheric_bckgrd(): NSIDE string not found"
-                )
-            # read NSIDE parameter for healpix grid
-            nside = int(line.split()[6])
-            # read ecliptic coords and background values span on a healpix grid
-            lon_lat_bckgrd = np.loadtxt(fh)
-            fh.close()
+        if check_if_contains_actual_data(anc_input_from_instr_team["extra_heliospheric_bckgrd"]):
+            with open(anc_input_from_instr_team["extra_heliospheric_bckgrd"], "r") as fh:
+                for i in range(3):
+                    line = fh.readline()
+                # sanity check
+                if line.split()[4] != "NSIDE":
+                    raise ValueError(
+                        "error _compute_extra_heliospheric_bckgrd(): NSIDE string not found"
+                    )
+                # read NSIDE parameter for healpix grid
+                nside = int(line.split()[6])
+                # read ecliptic coords and background values span on a healpix grid
+                lon_lat_bckgrd = np.loadtxt(fh)
 
             # generate Healpix grid internally here for a sanity check performed later
             ahp = HEALPix(nside=nside, order="ring")
@@ -78,7 +74,7 @@ def _compute_extra_heliospheric_bckgrd(self, anc_input_from_instr_team):
                 np.fabs(lon - lon_lat_bckgrd[:, 0]).max() > 1.0e-6
                 or np.fabs(lat - lon_lat_bckgrd[:, 1]).max() > 1.0e-6
             ):
-                raise Exception(
+                raise ValueError(
                     "error _compute_extra_heliospheric_bckgrd(): "
                     + "healpix grid mismatch (NSIDE wrong? NESTED ordering instead of RING?)"
                 )
@@ -101,43 +97,40 @@ def _compute_time_dependent_bckgrd(self, anc_input_from_instr_team):
                 see ANC_INPUT_FROM_INSTRUMENT_TEAM in constants.py
         """
 
-        if check_if_contains_actual_data(
-            anc_input_from_instr_team["time_dependent_bckgrd"]
-        ):
+        if check_if_contains_actual_data(anc_input_from_instr_team["time_dependent_bckgrd"]):
             # read the size of the background-estimate array
-            fh = open(anc_input_from_instr_team["time_dependent_bckgrd"], "r")
-            for i in range(2):
-                line = fh.readline()
-            # sanity check
-            if (
-                line.split()[5] != "array"
-                or line.split()[6] != "size"
-                or line.split()[7] != "="
-            ):
-                raise Exception(
-                    "error _compute_time_dependent_bckgrd(): input file header does not contain expected keywords (1)"
-                )
-            # read the number of bins
-            bckgrd_array_size = int(line.split()[8])
-            # sanity check
-            if bckgrd_array_size != 3600:
-                raise Exception(
-                    "error _compute_time_dependent_bckgrd(): array size in input file header is not equal to 3600"
-                )
+            with open(anc_input_from_instr_team["time_dependent_bckgrd"], "r") as fh:
+                for i in range(2):
+                    line = fh.readline()
+                # sanity check
+                if (
+                    line.split()[5] != "array"
+                    or line.split()[6] != "size"
+                    or line.split()[7] != "="
+                ):
+                    raise ValueError(
+                        "error _compute_time_dependent_bckgrd(): input file header does not contain expected keywords (1)"
+                    )
+                # read the number of bins
+                bckgrd_array_size = int(line.split()[8])
+                # sanity check
+                if bckgrd_array_size != 3600:
+                    raise ValueError(
+                        "error _compute_time_dependent_bckgrd(): array size in input file header is not equal to 3600"
+                    )
 
-            # read the array of spin angles for which the background was estimated
-            line = fh.readline()
-            # sanity check
-            if (
-                line.split()[1] != "spin"
-                or line.split()[2] != "angle"
-                or line.split()[3] != "grid:"
-            ):
-                raise Exception(
-                    "error _compute_time_dependent_bckgrd(): input file header does not contain expected keywords (2)"
-                )
-            bckgrd_array_spin_angle = np.fromstring(line[18:], dtype=float, sep=" ")
-            fh.close()
+                # read the array of spin angles for which the background was estimated
+                line = fh.readline()
+                # sanity check
+                if (
+                    line.split()[1] != "spin"
+                    or line.split()[2] != "angle"
+                    or line.split()[3] != "grid:"
+                ):
+                    raise ValueError(
+                        "error _compute_time_dependent_bckgrd(): input file header does not contain expected keywords (2)"
+                    )
+                bckgrd_array_spin_angle = np.fromstring(line[18:], dtype=float, sep=" ")
 
             # read L3a lightcurve start dates and array of corrections
             start_dates = np.loadtxt(
@@ -151,9 +144,7 @@ def _compute_time_dependent_bckgrd(self, anc_input_from_instr_team):
                 usecols=range(2, bckgrd_array_size + 2),
                 ndmin=2,
             )
-            idx = np.nonzero(self.data["start_time"].replace(" ", "T") == start_dates)[
-                0
-            ]
+            idx = np.nonzero(self.data["start_time"].replace(" ", "T") == start_dates)[0]
             print(" tdbckgrd idx:", idx, "  ", end="")
             if idx.size == 0:
                 # corrections has not been found for the current date, so we set zeros
@@ -163,10 +154,9 @@ def _compute_time_dependent_bckgrd(self, anc_input_from_instr_team):
             else:
                 idx = idx[0]
                 if idx.size != 1:
-                    raise Exception(
+                    raise ValueError(
                         "error _compute_time_dependent_bckgrd(): not-found or multiple-definition error for "
-                        + "the start date %s"
-                        % self.data["start_time"].replace(" ", "T")
+                        "the start date {}".format(self.data["start_time"].replace(" ", "T"))
                     )
 
                 # interpolate the background estimate from the bckgrd_array into the centers of the scanning circle bins
@@ -204,14 +194,10 @@ def generate_l3a_data(self, anc_input_from_instr_team):
         print(" cps/R:", cps_per_R, "  ", end="")
 
         # convert count rate to photon flux
-        self.data["daily_lightcurve"]["photon_flux"] = (
-            self.var["count_rate"] / cps_per_R
-        )
+        self.data["daily_lightcurve"]["photon_flux"] = self.var["count_rate"] / cps_per_R
 
         # compute uncertainties
-        self.var["raw_uncertainties"] = np.sqrt(
-            self.data["daily_lightcurve"]["raw_histogram"]
-        )
+        self.var["raw_uncertainties"] = np.sqrt(self.data["daily_lightcurve"]["raw_histogram"])
         self.data["daily_lightcurve"]["flux_uncertainties"] = np.zeros_like(
             self.data["daily_lightcurve"]["raw_histogram"], float
         )
@@ -370,9 +356,8 @@ def _read_from_json_file(self, file_name):
         Args:
             file_name: name of of file with L1b data
         """
-        file_handler = open(file_name, "r")
-        self.data = json.load(file_handler)
-        file_handler.close()
+        with open(file_name, "r") as file_handler:
+            self.data = json.load(file_handler)
 
         # additional field to keep track where data come from
         self.data["l3a_file_name"] = file_name
@@ -384,7 +369,7 @@ def _remove_masked_bins(self):
         good_angle_idxs = np.nonzero(
             np.array(self.data["daily_lightcurve"]["exposure_times"]) > 0
         )[0]
-        for key in self.data["daily_lightcurve"].keys():
+        for key in self.data["daily_lightcurve"]:
             self.data["daily_lightcurve"][key] = self.data["daily_lightcurve"][key][
                 good_angle_idxs
             ]
@@ -448,29 +433,18 @@ def _save_data_to_json_file(self):
         # them to be saved as one-liners (i.e., without \n after each element) or we want them to
         # be printed with a specific format by json.dumps()
         # so we convert variables to strings as defined in fmt
-        for key in fmt["daily_lightcurve"].keys():
+        for key, value in fmt["daily_lightcurve"].items:
             data["daily_lightcurve"][key] = (
-                "["
-                + ", ".join(
-                    map(
-                        lambda x: fmt["daily_lightcurve"][key] % x,
-                        list(data["daily_lightcurve"][key]),
-                    )
-                )
-                + "]"
+                "[" + ", ".join(value % x for x in list(data["daily_lightcurve"][key])) + "]"
             )
-        for key in fmt["scalar variables"].keys():
-            data[key] = "|" + fmt["scalar variables"][key] % data[key] + "|"
-        for key in fmt["lon lat variables"].keys():
+        for key, value in fmt["scalar variables"].items():
+            data[key] = "|" + value % data[key] + "|"
+        for key, value in fmt["lon lat variables"].items():
             for sec_key in ["lon", "lat"]:
-                data[key][sec_key] = (
-                    "|" + fmt["lon lat variables"][key] % data[key][sec_key] + "|"
-                )
-        for key in fmt["vector variables"].keys():
+                data[key][sec_key] = "|" + value % data[key][sec_key] + "|"
+        for key, value in fmt["vector variables"].items():
             for sec_key in ["x", "y", "z"]:
-                data[key][sec_key] = (
-                    "|" + fmt["vector variables"][key] % data[key][sec_key] + "|"
-                )
+                data[key][sec_key] = "|" + value % data[key][sec_key] + "|"
 
         # generate JSON content to be saved in output file
         json_content = json.dumps(data, indent=4, default=vars)
@@ -484,8 +458,7 @@ def _save_data_to_json_file(self):
         # "IMAP SDC to Instrument Team ICD"
         # date_utc = ''.join(filter(str.isdigit, self.data['identifier']))
         date_utc = "".join(filter(str.isdigit, self.data["start_time"]))
-        file_name = "data_l3a/imap_glows_l3a_%s_orbX_modX_p_v00.json" % date_utc
+        file_name = f"data_l3a/imap_glows_l3a_{date_utc}_orbX_modX_p_v00.json"
 
-        file_handler = open(file_name, "w")
-        print(json_content, file=file_handler)
-        file_handler.close()
+        with open(file_name, "w") as file_handler:
+            print(json_content, file=file_handler)
diff --git a/imap_l3_processing/glows/l3a/glows_toolkit/reader.py b/imap_l3_processing/glows/l3a/glows_toolkit/reader.py
index 0adb5736..a0941dfc 100644
--- a/imap_l3_processing/glows/l3a/glows_toolkit/reader.py
+++ b/imap_l3_processing/glows/l3a/glows_toolkit/reader.py
@@ -3,7 +3,7 @@
 """
 
 import struct
-from typing import Any, cast, Tuple, Union
+from typing import Any, cast
 
 
 class Reader:
@@ -11,7 +11,7 @@ class Reader:
     Reader() class for reading binary stream with GLOWS data
     """
 
-    def __init__(self, buffer: Union[memoryview, bytes]):
+    def __init__(self, buffer: memoryview | bytes):
         """
         Constructor for this class, sets init values of its fields
         """
@@ -44,7 +44,7 @@ def _read_part(self, length: int) -> bytes:
         self._offset += length
         return part
 
-    def read(self, pack_format: str) -> Tuple[Any, ...]:
+    def read(self, pack_format: str) -> tuple[Any, ...]:
         """read bytes according to pack_format"""
         length = struct.calcsize(pack_format)
         part = self._read_part(length)
@@ -60,7 +60,7 @@ def read_uint16_be(self) -> int:
 
     def read_uint24_be(self) -> int:
         """read 3 bytes as big-endian uint"""
-        high, low = cast(Tuple[int, int], self.read(">BH"))
+        high, low = cast(tuple[int, int], self.read(">BH"))
         return high << 16 | low
 
     def read_uint32_be(self) -> int:
diff --git a/imap_l3_processing/glows/l3a/models.py b/imap_l3_processing/glows/l3a/models.py
index 64108452..23094a7a 100644
--- a/imap_l3_processing/glows/l3a/models.py
+++ b/imap_l3_processing/glows/l3a/models.py
@@ -169,30 +169,18 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(
                 FILTER_TEMPERATURE_STD_DEV_CDF_VAR_NAME, self.filter_temperature_std_dev
             ),
-            DataProductVariable(
-                HV_VOLTAGE_AVERAGE_CDF_VAR_NAME, self.hv_voltage_average
-            ),
-            DataProductVariable(
-                HV_VOLTAGE_STD_DEV_CDF_VAR_NAME, self.hv_voltage_std_dev
-            ),
-            DataProductVariable(
-                SPIN_PERIOD_AVERAGE_CDF_VAR_NAME, self.spin_period_average
-            ),
-            DataProductVariable(
-                SPIN_PERIOD_STD_DEV_CDF_VAR_NAME, self.spin_period_std_dev
-            ),
+            DataProductVariable(HV_VOLTAGE_AVERAGE_CDF_VAR_NAME, self.hv_voltage_average),
+            DataProductVariable(HV_VOLTAGE_STD_DEV_CDF_VAR_NAME, self.hv_voltage_std_dev),
+            DataProductVariable(SPIN_PERIOD_AVERAGE_CDF_VAR_NAME, self.spin_period_average),
+            DataProductVariable(SPIN_PERIOD_STD_DEV_CDF_VAR_NAME, self.spin_period_std_dev),
             DataProductVariable(
                 SPIN_PERIOD_GROUND_AVERAGE_CDF_VAR_NAME, self.spin_period_ground_average
             ),
             DataProductVariable(
                 SPIN_PERIOD_GROUND_STD_DEV_CDF_VAR_NAME, self.spin_period_ground_std_dev
             ),
-            DataProductVariable(
-                PULSE_LENGTH_AVERAGE_CDF_VAR_NAME, self.pulse_length_average
-            ),
-            DataProductVariable(
-                PULSE_LENGTH_STD_DEV_CDF_VAR_NAME, self.pulse_length_std_dev
-            ),
+            DataProductVariable(PULSE_LENGTH_AVERAGE_CDF_VAR_NAME, self.pulse_length_average),
+            DataProductVariable(PULSE_LENGTH_STD_DEV_CDF_VAR_NAME, self.pulse_length_std_dev),
             DataProductVariable(
                 POSITION_ANGLE_OFFSET_AVERAGE_CDF_VAR_NAME,
                 self.position_angle_offset_average,
diff --git a/imap_l3_processing/glows/l3a/science/bad_angle_flag_configuration.py b/imap_l3_processing/glows/l3a/science/bad_angle_flag_configuration.py
index 835cc488..21235890 100644
--- a/imap_l3_processing/glows/l3a/science/bad_angle_flag_configuration.py
+++ b/imap_l3_processing/glows/l3a/science/bad_angle_flag_configuration.py
@@ -1,7 +1,6 @@
 import json
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Union
 
 import numpy as np
 
@@ -26,7 +25,7 @@ def evaluate_flags(self, flags: np.ndarray):
         return np.any(np.logical_and(configuration, flags), axis=-2)
 
     @classmethod
-    def from_file(cls, file_path: Union[Path, str]):
+    def from_file(cls, file_path: Path | str):
         with open(file_path) as f:
             config = json.load(f)
 
diff --git a/imap_l3_processing/glows/l3a/science/calculate_daily_lightcurve.py b/imap_l3_processing/glows/l3a/science/calculate_daily_lightcurve.py
index c368f7f2..adfb7a7c 100644
--- a/imap_l3_processing/glows/l3a/science/calculate_daily_lightcurve.py
+++ b/imap_l3_processing/glows/l3a/science/calculate_daily_lightcurve.py
@@ -21,8 +21,7 @@ def rebin_lightcurve(
     background: ndarray[float],
 ) -> tuple[np.ndarray, np.ndarray]:
     photon_flux_minus_time_independent_background = (
-        photon_flux
-        - time_independent_background_table.lookup(lat=latitudes, lon=longitudes)
+        photon_flux - time_independent_background_table.lookup(lat=latitudes, lon=longitudes)
     )
 
     masked = bad_angle_flag_configuration.evaluate_flags(flags)
@@ -32,9 +31,7 @@ def rebin_lightcurve(
 
     exposure_times_rebinned = np.sum(exposure_time_by_bins, axis=-1)
 
-    filtered_photon_flux = (
-        photon_flux_minus_time_independent_background * filtered_exposure_times
-    )
+    filtered_photon_flux = photon_flux_minus_time_independent_background * filtered_exposure_times
     split_by_bins = np.reshape(filtered_photon_flux, (output_size, -1))
 
     rebinned_photon_flux = np.full(
diff --git a/imap_l3_processing/glows/l3a/science/time_independent_background_lookup_table.py b/imap_l3_processing/glows/l3a/science/time_independent_background_lookup_table.py
index 0f549244..bca605e9 100644
--- a/imap_l3_processing/glows/l3a/science/time_independent_background_lookup_table.py
+++ b/imap_l3_processing/glows/l3a/science/time_independent_background_lookup_table.py
@@ -1,6 +1,6 @@
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Union, TypeVar
+from typing import TypeVar
 
 import numpy as np
 import scipy.interpolate
@@ -15,8 +15,8 @@ class TimeIndependentBackgroundLookupTable:
     background_values: np.ndarray[float]
 
     def lookup(
-        self, lat: Union[np.ndarray[float], float], lon: Union[np.ndarray[float], float]
-    ) -> Union[np.ndarray[float], float]:
+        self, lat: np.ndarray[float] | float, lon: np.ndarray[float] | float
+    ) -> np.ndarray[float] | float:
         wrapped_lon = np.mod(lon, 360)
         background_extended = np.append(
             self.background_values, self.background_values[:, :1], axis=1
diff --git a/imap_l3_processing/glows/l3a/utils.py b/imap_l3_processing/glows/l3a/utils.py
index 574f184a..f10a83ac 100644
--- a/imap_l3_processing/glows/l3a/utils.py
+++ b/imap_l3_processing/glows/l3a/utils.py
@@ -7,12 +7,12 @@
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.glows.l3a.models import (
+    XYZ,
     GlowsL2Data,
+    GlowsL2Header,
     GlowsL2LightCurve,
-    GlowsLatLon,
     GlowsL3LightCurve,
-    XYZ,
-    GlowsL2Header,
+    GlowsLatLon,
 )
 from imap_l3_processing.models import InputMetadata, Instrument
 
@@ -41,9 +41,7 @@ def _pad_lightcurve(values) -> np.ndarray:
 
 
 def read_l2_glows_data(cdf: CDF) -> GlowsL2Data:
-    assert 1 == cdf["photon_flux"].shape[0], (
-        "Level 2 file should have only one histogram"
-    )
+    assert 1 == cdf["photon_flux"].shape[0], "Level 2 file should have only one histogram"
 
     light_curve = GlowsL2LightCurve(
         photon_flux=cdf["photon_flux"][0],
@@ -146,9 +144,7 @@ def create_glows_l3a_from_dictionary(
         start_time=data["start_time"],
         end_time=data["end_time"],
         photon_flux=_pad_lightcurve(data["daily_lightcurve"]["photon_flux"]),
-        photon_flux_uncertainty=_pad_lightcurve(
-            data["daily_lightcurve"]["flux_uncertainties"]
-        ),
+        photon_flux_uncertainty=_pad_lightcurve(data["daily_lightcurve"]["flux_uncertainties"]),
         raw_histogram=_pad_lightcurve(data["daily_lightcurve"]["raw_histogram"]),
         exposure_times=_pad_lightcurve(data["daily_lightcurve"]["exposure_times"]),
         spin_angle=_pad_lightcurve(data["daily_lightcurve"]["spin_angle"]),
@@ -173,12 +169,8 @@ def create_glows_l3a_from_dictionary(
         pulse_length_std_dev=np.array([data["pulse_length_std_dev"]]),
         position_angle_offset_average=np.array([data["position_angle_offset_average"]]),
         position_angle_offset_std_dev=np.array([data["position_angle_offset_std_dev"]]),
-        spin_axis_orientation_average=get_lon_lat(
-            data["spin_axis_orientation_average"]
-        ),
-        spin_axis_orientation_std_dev=get_lon_lat(
-            data["spin_axis_orientation_std_dev"]
-        ),
+        spin_axis_orientation_average=get_lon_lat(data["spin_axis_orientation_average"]),
+        spin_axis_orientation_std_dev=get_lon_lat(data["spin_axis_orientation_std_dev"]),
         spacecraft_location_average=get_xyz(data["spacecraft_location_average"]),
         spacecraft_location_std_dev=get_xyz(data["spacecraft_location_std_dev"]),
         spacecraft_velocity_average=get_xyz(data["spacecraft_velocity_average"]),
@@ -203,9 +195,7 @@ def create_glows_l3a_dictionary_from_cdf(cdf_file_path: Path) -> dict:
             "exposure_times": cdf["exposure_times"][0][:valid_bin_count],
             "photon_flux": cdf["photon_flux"][0][:valid_bin_count],
             "flux_uncertainties": cdf["photon_flux_uncertainty"][0][:valid_bin_count],
-            "extra_heliospheric_bckgrd": cdf["extra_heliospheric_bckgrd"][0][
-                :valid_bin_count
-            ],
+            "extra_heliospheric_bckgrd": cdf["extra_heliospheric_bckgrd"][0][:valid_bin_count],
             "time_dependent_bckgrd": cdf["time_dependent_bckgrd"][0][:valid_bin_count],
             "spin_angle": cdf["spin_angle"][0][:valid_bin_count],
             "raw_histogram": cdf["raw_histogram"][0][:valid_bin_count],
diff --git a/imap_l3_processing/glows/l3bc/dependency_validator.py b/imap_l3_processing/glows/l3bc/dependency_validator.py
index 335f7401..b33d337f 100644
--- a/imap_l3_processing/glows/l3bc/dependency_validator.py
+++ b/imap_l3_processing/glows/l3bc/dependency_validator.py
@@ -17,27 +17,19 @@
 def validate_omni2_dependency(
     cr_start_date: datetime, cr_end_date_exclusive: datetime, file_path: Path
 ) -> bool:
-    omni_data: ndarray = np.loadtxt(
-        file_path, usecols=(0, 1, 2, 5, 23, 24, 27, 30, 31, 34)
-    )
+    omni_data: ndarray = np.loadtxt(file_path, usecols=(0, 1, 2, 5, 23, 24, 27, 30, 31, 34))
 
     row_day_keys = omni_data[:, YEAR_COLUMN] * 1000 + omni_data[:, DOY_COLUMN]
     start_key = cr_start_date.year * 1000 + cr_start_date.timetuple().tm_yday
-    end_key = (
-        cr_end_date_exclusive.year * 1000 + cr_end_date_exclusive.timetuple().tm_yday
-    )
+    end_key = cr_end_date_exclusive.year * 1000 + cr_end_date_exclusive.timetuple().tm_yday
 
     start_idx = np.searchsorted(row_day_keys, start_key)
     end_idx = np.searchsorted(row_day_keys, end_key)
     omni_data = omni_data[start_idx:end_idx]
 
     for data_point in omni_data:
-        mask_fill_density_rows = np.all(
-            data_point[[DENSITY_COLUMN_1, DENSITY_COLUMN_2]] < 999.9
-        )
-        mask_fill_speed_rows = np.all(
-            data_point[[SPEED_COLUMN_1, SPEED_COLUMN_2]] < 9999
-        )
+        mask_fill_density_rows = np.all(data_point[[DENSITY_COLUMN_1, DENSITY_COLUMN_2]] < 999.9)
+        mask_fill_speed_rows = np.all(data_point[[SPEED_COLUMN_1, SPEED_COLUMN_2]] < 9999)
 
         if np.all([mask_fill_density_rows, mask_fill_speed_rows]):
             return True
@@ -53,16 +45,10 @@ def validate_dependencies(
     f107_index_path: Path,
     lyman_alpha_path: Path,
 ) -> bool:
-    omni_condition = validate_omni2_dependency(
-        cr_start_date, cr_end_date, omni2_file_path
-    )
-
-    f107_condition = validate_f107_fluxtable_dependency(
-        cr_end_date, buffer, f107_index_path
-    )
-    lyman_alpha_condition = validate_lyman_alpha_dependency(
-        cr_end_date, buffer, lyman_alpha_path
-    )
+    omni_condition = validate_omni2_dependency(cr_start_date, cr_end_date, omni2_file_path)
+
+    f107_condition = validate_f107_fluxtable_dependency(cr_end_date, buffer, f107_index_path)
+    lyman_alpha_condition = validate_lyman_alpha_dependency(cr_end_date, buffer, lyman_alpha_path)
 
     return omni_condition and f107_condition and lyman_alpha_condition
 
diff --git a/imap_l3_processing/glows/l3bc/glows_l3bc_dependencies.py b/imap_l3_processing/glows/l3bc/glows_l3bc_dependencies.py
index 78c07edd..74c99cb9 100644
--- a/imap_l3_processing/glows/l3bc/glows_l3bc_dependencies.py
+++ b/imap_l3_processing/glows/l3bc/glows_l3bc_dependencies.py
@@ -38,22 +38,18 @@ def download_from_cr_to_process(
         }
 
         ancillary_files = {
-            "uv_anisotropy": imap_data_access.download(
-                cr_to_process.uv_anisotropy_file_name
-            ),
+            "uv_anisotropy": imap_data_access.download(cr_to_process.uv_anisotropy_file_name),
             "WawHelioIonMP_parameters": imap_data_access.download(
                 cr_to_process.waw_helio_ion_mp_file_name
             ),
-            "bad_days_list": imap_data_access.download(
-                cr_to_process.bad_days_list_file_name
-            ),
+            "bad_days_list": imap_data_access.download(cr_to_process.bad_days_list_file_name),
             "pipeline_settings": imap_data_access.download(
                 cr_to_process.pipeline_settings_file_name
             ),
         }
 
         l3a_data = []
-        for l3a_file in sorted(list(cr_to_process.l3a_file_names)):
+        for l3a_file in sorted(cr_to_process.l3a_file_names):
             downloaded_file_path = imap_data_access.download(l3a_file)
             l3a_data.append(create_glows_l3a_dictionary_from_cdf(downloaded_file_path))
 
diff --git a/imap_l3_processing/glows/l3bc/glows_l3bc_initializer.py b/imap_l3_processing/glows/l3bc/glows_l3bc_initializer.py
index 297378b7..d5368ccc 100644
--- a/imap_l3_processing/glows/l3bc/glows_l3bc_initializer.py
+++ b/imap_l3_processing/glows/l3bc/glows_l3bc_initializer.py
@@ -2,28 +2,27 @@
 from collections import defaultdict
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional
 
 import imap_data_access
-from imap_data_access import ScienceFilePath, ProcessingInputCollection, RepointInput
+from imap_data_access import ProcessingInputCollection, RepointInput, ScienceFilePath
 from imap_data_access.file_validation import Version
 from imap_processing.spice.repoint import set_global_repoint_table_paths
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.glows.descriptors import (
     BAD_DAYS_LIST_DESCRIPTOR,
-    WAW_HELIOION_DESCRIPTOR,
-    UV_ANISOTROPY_1CR_DESCRIPTOR,
-    PIPELINE_SETTINGS_L3BCDE_DESCRIPTOR,
     GLOWS_L3B_DESCRIPTOR,
     GLOWS_L3C_DESCRIPTOR,
+    PIPELINE_SETTINGS_L3BCDE_DESCRIPTOR,
+    UV_ANISOTROPY_1CR_DESCRIPTOR,
+    WAW_HELIOION_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3bc.glows_l3bc_dependencies import GlowsL3BCDependencies
 from imap_l3_processing.glows.l3bc.models import CRToProcess, ExternalDependencies
 from imap_l3_processing.glows.l3bc.utils import (
-    get_date_range_of_cr,
     get_best_ancillary,
     get_cr_for_date_time,
+    get_date_range_of_cr,
 )
 from imap_l3_processing.utils import read_cdf_parents
 
@@ -58,8 +57,7 @@ def get_crs_to_process(
             instrument="glows", data_level="l3a", descriptor="hist", version="latest"
         )
         l3a_files_names = [
-            Path(l3a_query_result["file_path"]).name
-            for l3a_query_result in l3a_query_results
+            Path(l3a_query_result["file_path"]).name for l3a_query_result in l3a_query_results
         ]
         cr_to_l3a_file_names = GlowsL3BCInitializer.group_l3a_by_cr(l3a_files_names)
 
@@ -77,12 +75,10 @@ def get_crs_to_process(
         )
 
         l3bs_by_cr = {
-            int(result["cr"]): Path(result["file_path"]).name
-            for result in l3b_query_result
+            int(result["cr"]): Path(result["file_path"]).name for result in l3b_query_result
         }
         l3cs_by_cr = {
-            int(result["cr"]): Path(result["file_path"]).name
-            for result in l3c_query_result
+            int(result["cr"]): Path(result["file_path"]).name for result in l3c_query_result
         }
 
         uv_anisotropy_query_result = imap_data_access.query(
@@ -165,13 +161,11 @@ def get_crs_to_process(
                     external_dependencies,
                     major_version_to_process,
                 ):
-                    l3bc_dependencies = (
-                        GlowsL3BCDependencies.download_from_cr_to_process(
-                            cr_candidate,
-                            version,
-                            external_dependencies,
-                            repoint_downloaded_path,
-                        )
+                    l3bc_dependencies = GlowsL3BCDependencies.download_from_cr_to_process(
+                        cr_candidate,
+                        version,
+                        external_dependencies,
+                        repoint_downloaded_path,
                     )
                     all_l3bc_dependencies.append(l3bc_dependencies)
                 else:
@@ -193,17 +187,13 @@ def should_process_cr_candidate(
         l3bs_by_cr: dict[int, str],
         external_dependencies: ExternalDependencies,
         major_version: int | None,
-    ) -> Optional[Version]:
+    ) -> Version | None:
         if not cr_candidate.buffer_time_has_elapsed_since_cr():
-            logger.warning(
-                f"Not enough time has elapsed for cr {cr_candidate.cr_rotation_number}"
-            )
+            logger.warning(f"Not enough time has elapsed for cr {cr_candidate.cr_rotation_number}")
             return None
 
         if not cr_candidate.has_valid_external_dependencies(external_dependencies):
-            logger.warning(
-                f"Invalid external dependencies for {cr_candidate.cr_rotation_number}"
-            )
+            logger.warning(f"Invalid external dependencies for {cr_candidate.cr_rotation_number}")
             return None
 
         match l3bs_by_cr.get(cr_candidate.cr_rotation_number):
@@ -216,10 +206,8 @@ def should_process_cr_candidate(
                     existing_path.major_version, existing_path.minor_version
                 )
                 major_version_updated = major_version != existing_version.major
-                inputs_changed = (
-                    not cr_candidate.pipeline_dependency_file_names().issubset(
-                        l3b_parents
-                    )
+                inputs_changed = not cr_candidate.pipeline_dependency_file_names().issubset(
+                    l3b_parents
                 )
                 if major_version_updated or inputs_changed:
                     return Version(major_version, existing_version.minor + 1)
diff --git a/imap_l3_processing/glows/l3bc/l3bc_toolkit/funcs.py b/imap_l3_processing/glows/l3bc/l3bc_toolkit/funcs.py
index 43b924c9..8e6daf49 100644
--- a/imap_l3_processing/glows/l3bc/l3bc_toolkit/funcs.py
+++ b/imap_l3_processing/glows/l3bc/l3bc_toolkit/funcs.py
@@ -3,17 +3,17 @@
 Functions used in L3a->L3b processing that are not class methods
 """
 
-import numpy as np
-import astropy.units as u
-import astropy.constants as const
 import json
+import logging
+
+import astropy.constants as const
+import astropy.units as u
 import netCDF4
-from astropy.time import Time
+import numpy as np
 from astropy.coordinates import get_sun
+from astropy.time import Time
 
-from .constants import PHISICAL_CONSTANTS, CONST_ALPHA_TO_PROTON
-
-import logging
+from .constants import CONST_ALPHA_TO_PROTON, PHISICAL_CONSTANTS
 
 logging.basicConfig(level=logging.ERROR)
 
@@ -70,9 +70,7 @@ def calculate_lya_monthly(t, flux):
     Calculates data that are averaged over each Carrington rotation period. Time is mean value of decimal year in each period.
     """
     t_carr, flux_carr = resize_by_carr(t, flux)
-    t_mean = Time(
-        np.array([np.mean(t.decimalyear) for t in t_carr]), format="decimalyear"
-    )
+    t_mean = Time(np.array([np.mean(t.decimalyear) for t in t_carr]), format="decimalyear")
     flux_mean = np.array([f.mean() for f in flux_carr])
 
     return t_mean, flux_mean
@@ -132,8 +130,8 @@ def check_nan(data):
     data - dictionary with the data product
     """
     for key in data:
-        if np.any((np.isnan(np.array(data[key])))):
-            raise Exception("There are NaN in the output data")
+        if np.any(np.isnan(np.array(data[key]))):
+            raise ValueError("There are NaN in the output data")
 
 
 def cr_from_l3b_fn(fn):
@@ -192,11 +190,7 @@ def cross_section_cx(E):
     A8 = 6.1091
 
     EkeV = E.to("keV").value
-    out = (
-        (1e-16)
-        * (A1 * np.log(A2 / EkeV + A3))
-        / (1 + A4 * EkeV + A5 * EkeV**A6 + A7 * EkeV**A8)
-    )
+    out = (1e-16) * (A1 * np.log(A2 / EkeV + A3)) / (1 + A4 * EkeV + A5 * EkeV**A6 + A7 * EkeV**A8)
     sigma = out * u.cm * u.cm
 
     return sigma
@@ -239,7 +233,7 @@ def f107_daily_data(t, flux):
     t_out: daily time array (astropy.time)
     flux_out: daily F10.7 flux adjusted to 1au (10^(-22) W/m^2/Hz)
     """
-    idx_noon, idx_dup = select_noon(t)  # select one measurment per day
+    idx_noon, _idx_dup = select_noon(t)  # select one measurment per day
     idx_no0 = np.where(flux[idx_noon] > 0)[0]
     t_out = t[idx_noon[idx_no0]]
     flux_out = flux[idx_noon[idx_no0]]
@@ -319,7 +313,7 @@ def get_spher_coord_rad(vec):
     """
     if vec.ndim == 1:
         if np.shape(vec)[0] != 3:
-            raise "get_spher_coord_rad() error: np.shape(vec)[0]!=3"
+            raise ValueError("get_spher_coord_rad() error: np.shape(vec)[0]!=3")
         r = np.sqrt(np.dot(vec, vec))
         if r == 0.0:
             b = 0.0
@@ -333,7 +327,7 @@ def get_spher_coord_rad(vec):
         return np.array([r, l, b])  # return one array similarly as in Mathematica
     else:
         if np.shape(vec)[1] != 3:
-            raise "get_spher_coord_rad() error: np.shape(vec)[1]!=3"
+            raise ValueError("get_spher_coord_rad() error: np.shape(vec)[1]!=3")
         r = np.sqrt((vec * vec).sum(axis=1))
         idxs = np.nonzero(r != 0.0)
         b = np.zeros((len(r)), np.float64)
@@ -341,9 +335,7 @@ def get_spher_coord_rad(vec):
         l = np.arctan2(vec[:, 1], vec[:, 0]) % (2 * np.pi)  # compute longitude
         idxs = np.nonzero(np.logical_and(vec[:, 0] == 0.0, vec[:, 1] == 0.0))
         l[idxs[0]] = 0.0  # set l=0 if vec[:,0]==0.0 and vec[:,1]==0.0
-        return np.column_stack(
-            [r, l, b]
-        )  # return one array similarly as in Mathematica
+        return np.column_stack([r, l, b])  # return one array similarly as in Mathematica
 
 
 def jd_fm_Carrington(carr):
@@ -415,10 +407,8 @@ def process_omni_param(omni_raw, cr_grid, param_settings):
     if np.logical_and(param_cr[0] <= cr_grid[0], param_cr[-1] >= cr_grid[-1]):
         param_value_interp = np.interp(cr_grid, param_cr, param_value)
     else:
-        logging.info(
-            "There are gaps in the OMNI2 data that cannot be filled by the interpolation"
-        )
-        raise Exception("OMNI Error: not enough data for interpolation")
+        logging.info("There are gaps in the OMNI2 data that cannot be filled by the interpolation")
+        raise RuntimeError("OMNI Error: not enough data for interpolation")
 
     return param_value_interp, used_nominal_per_cr
 
@@ -534,9 +524,8 @@ def read_json(fn):
     """
     Opens, reads and returns the content of the json file
     """
-    fp = open(fn, "r")
-    data = json.load(fp)
-    fp.close()
+    with open(fn, "r") as fp:
+        data = json.load(fp)
     return data
 
 
@@ -655,9 +644,7 @@ def select_noon(t_pen):
                     i = i + 3
             else:
                 h = np.array([int(t_pen[i].yday[9:11]), int(t_pen[i + 1].yday[9:11])])
-                k = (
-                    i + np.abs(h - 20).argmin()
-                )  # index of the hour that is near 20UT (local noon)
+                k = i + np.abs(h - 20).argmin()  # index of the hour that is near 20UT (local noon)
                 d = [i, i + 1]
             i = i + 2
         else:
@@ -718,24 +705,14 @@ def test_WawHelioInMP_file(model):
         lcrv_filtration = model["vg_points"][k]["parameters"]["lcrv_filtration"]
         lcrv_order = model["vg_points"][k]["parameters"]["lcrv_order"]
 
-        model_const_0 = np.array(
-            model["vg_points"][k]["parameters"]["model_const"]
-        ).shape[0]
+        model_const_0 = np.array(model["vg_points"][k]["parameters"]["model_const"]).shape[0]
         model_matrix = np.array(model["vg_points"][k]["parameters"]["model_matrix"])
-        model_matrix_0 = np.array(
-            model["vg_points"][k]["parameters"]["model_matrix"]
-        ).shape[0]
-        model_matrix_1 = np.array(
-            model["vg_points"][k]["parameters"]["model_matrix"]
-        ).shape[1]
+        model_matrix_0 = np.array(model["vg_points"][k]["parameters"]["model_matrix"]).shape[0]
+        model_matrix_1 = np.array(model["vg_points"][k]["parameters"]["model_matrix"]).shape[1]
 
         lcrv_Trmatrix = np.array(model["vg_points"][k]["parameters"]["lcrv_Trmatrix"])
-        lcrv_Trmatrix_0 = np.array(
-            model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]
-        ).shape[0]
-        lcrv_Trmatrix_1 = np.array(
-            model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]
-        ).shape[1]
+        lcrv_Trmatrix_0 = np.array(model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]).shape[0]
+        lcrv_Trmatrix_1 = np.array(model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]).shape[1]
 
         if model_const_0 != hion_filtration:
             logging.error(
@@ -746,9 +723,7 @@ def test_WawHelioInMP_file(model):
             )
             raise ArrayShapeError("Array shape error: Array shape is incorrect")
 
-        elif np.logical_or(
-            model_matrix_0 != hion_filtration, model_matrix_1 != lcrv_filtration
-        ):
+        elif np.logical_or(model_matrix_0 != hion_filtration, model_matrix_1 != lcrv_filtration):
             logging.error(
                 "model_matrix shape is incorrect.\nIt is "
                 + str(model_matrix.shape)
diff --git a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_CarringtonIonRate.py b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_CarringtonIonRate.py
index f2df1dc9..8b0a97c2 100644
--- a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_CarringtonIonRate.py
+++ b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_CarringtonIonRate.py
@@ -2,6 +2,7 @@
 Author: Izabela Kowalska-Leszczynska (ikowalska@cbk.waw.pl)
 Carrington averaged ionization rate class
 """
+# ruff: noqa: N999
 
 import json
 import logging
@@ -189,8 +190,7 @@ def calculate_charge_exchange(self):
         # statistical uncertainty
         if len(self.carr_ion_rate["cx_rate"]) > 1:
             self.carr_ion_rate["cx_rate_uncert"] = (
-                self.carr_ion_rate["ion_rate_uncert"]
-                + self.carr_ion_rate["ph_rate_uncert"]
+                self.carr_ion_rate["ion_rate_uncert"] + self.carr_ion_rate["ph_rate_uncert"]
             )
         else:
             self.carr_ion_rate["cx_rate_uncert"] = -1.0e31 * np.ones_like(
@@ -231,23 +231,13 @@ def calculate_photoion(self, anc_input_from_instr_team, ext_dependencies):
         else:
             # if there are less than 2 data points in the time window, we want to interpolate
             # between mean values of the previous and next CR
-            t_ini_next = Time(
-                fun.jd_fm_Carrington(self.carr_ion_rate["CR"] + 1), format="jd"
-            )
-            t_end_next = Time(
-                fun.jd_fm_Carrington(self.carr_ion_rate["CR"] + 2), format="jd"
-            )
-            data_window_next = fun.select_data_window(
-                [t_raw, flux_raw], [t_ini_next, t_end_next]
-            )
+            t_ini_next = Time(fun.jd_fm_Carrington(self.carr_ion_rate["CR"] + 1), format="jd")
+            t_end_next = Time(fun.jd_fm_Carrington(self.carr_ion_rate["CR"] + 2), format="jd")
+            data_window_next = fun.select_data_window([t_raw, flux_raw], [t_ini_next, t_end_next])
             if len(data_window_next[0]) > 2:
                 # if there are at least data points in the next CR, then we can interpolate
-                t_ini_prev = Time(
-                    fun.jd_fm_Carrington(self.carr_ion_rate["CR"] - 1), format="jd"
-                )
-                t_end_prev = Time(
-                    fun.jd_fm_Carrington(self.carr_ion_rate["CR"]), format="jd"
-                )
+                t_ini_prev = Time(fun.jd_fm_Carrington(self.carr_ion_rate["CR"] - 1), format="jd")
+                t_end_prev = Time(fun.jd_fm_Carrington(self.carr_ion_rate["CR"]), format="jd")
                 data_window_prev = fun.select_data_window(
                     [t_raw, flux_raw], [t_ini_prev, t_end_prev]
                 )
@@ -273,7 +263,7 @@ def calculate_photoion(self, anc_input_from_instr_team, ext_dependencies):
                 photoion_mean = self._calculate_photoion_from_f107(data_mean[1])
             else:
                 # if there are no data in the next CR, then we need to wait for another CR
-                raise Exception(
+                raise RuntimeError(
                     "There are no data to interpolate F10.7 for CR=%d",
                     self.carr_ion_rate["CR"],
                 )
@@ -336,15 +326,9 @@ def get_dict(self):
         output["ion_rate_profile"]["sum_rate"] = self.carr_ion_rate["ion_rate"].tolist()
         output["ion_rate_profile"]["ph_rate"] = self.carr_ion_rate["ph_rate"].tolist()
         output["ion_rate_profile"]["cx_rate"] = self.carr_ion_rate["cx_rate"].tolist()
-        output["ion_rate_profile"]["sum_uncert"] = self.carr_ion_rate[
-            "ion_rate_uncert"
-        ].tolist()
-        output["ion_rate_profile"]["ph_uncert"] = self.carr_ion_rate[
-            "ph_rate_uncert"
-        ].tolist()
-        output["ion_rate_profile"]["cx_uncert"] = self.carr_ion_rate[
-            "cx_rate_uncert"
-        ].tolist()
+        output["ion_rate_profile"]["sum_uncert"] = self.carr_ion_rate["ion_rate_uncert"].tolist()
+        output["ion_rate_profile"]["ph_uncert"] = self.carr_ion_rate["ph_rate_uncert"].tolist()
+        output["ion_rate_profile"]["cx_uncert"] = self.carr_ion_rate["cx_rate_uncert"].tolist()
 
         output["uv_anisotropy_factor"] = self.uv_anisotropy.tolist()
         output["uv_anisotropy_flag"] = self.uv_anisotropy_flag
@@ -375,15 +359,9 @@ def save_to_file(self, fn):
         output["ion_rate_profile"]["sum_rate"] = self.carr_ion_rate["ion_rate"].tolist()
         output["ion_rate_profile"]["ph_rate"] = self.carr_ion_rate["ph_rate"].tolist()
         output["ion_rate_profile"]["cx_rate"] = self.carr_ion_rate["cx_rate"].tolist()
-        output["ion_rate_profile"]["sum_uncert"] = self.carr_ion_rate[
-            "ion_rate_uncert"
-        ].tolist()
-        output["ion_rate_profile"]["ph_uncert"] = self.carr_ion_rate[
-            "ph_rate_uncert"
-        ].tolist()
-        output["ion_rate_profile"]["cx_uncert"] = self.carr_ion_rate[
-            "cx_rate_uncert"
-        ].tolist()
+        output["ion_rate_profile"]["sum_uncert"] = self.carr_ion_rate["ion_rate_uncert"].tolist()
+        output["ion_rate_profile"]["ph_uncert"] = self.carr_ion_rate["ph_rate_uncert"].tolist()
+        output["ion_rate_profile"]["cx_uncert"] = self.carr_ion_rate["cx_rate_uncert"].tolist()
 
         output["uv_anisotropy_factor"] = self.uv_anisotropy.tolist()
         output["uv_anisotropy_flag"] = self.uv_anisotropy_flag
@@ -393,6 +371,5 @@ def save_to_file(self, fn):
 
         json_content = json.dumps(output, indent=3)
 
-        output_fp = open(fn, "w")
-        print(json_content, file=output_fp)
-        output_fp.close()
+        with open(fn, "w") as output_fp:
+            print(json_content, file=output_fp)
diff --git a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_DailyIonRate.py b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_DailyIonRate.py
index 4e420538..1167b965 100644
--- a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_DailyIonRate.py
+++ b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3b_DailyIonRate.py
@@ -2,6 +2,7 @@
 Author: Izabela Kowalska-Leszczynska (ikowalska@cbk.waw.pl)
 Daily ionization rate class
 """
+# ruff: noqa: N999
 
 import json
 import logging
@@ -11,7 +12,7 @@
 from astropy import units as u
 from astropy.coordinates import SkyCoord
 from astropy.time import Time
-from sklearn.linear_model import LinearRegression, Lasso, Ridge
+from sklearn.linear_model import Lasso, LinearRegression, Ridge
 
 from . import funcs as fun
 from .constants import VERSION
@@ -160,9 +161,7 @@ def __init__(self, anc_input_from_instr_team):
 
         self.header = {
             "software_version": VERSION,
-            "ancillary_data_files": anc_input_from_instr_team[
-                "WawHelioIonMP_parameters"
-            ],
+            "ancillary_data_files": anc_input_from_instr_team["WawHelioIonMP_parameters"],
             "l3a_input_filename": None,
         }
 
@@ -271,9 +270,7 @@ def _decompose_light_curve(self):
                 lsq_mtrx, lightcurve, sample_weight=1.0 / (uncert * uncert)
             )
         else:
-            raise Exception(
-                "Unknown regression method. Use LinearRegression, Lasso or Ridge"
-            )
+            raise ValueError("Unknown regression method. Use LinearRegression, Lasso or Ridge")
 
         self.lcrv["decomposition_coeff"] = lin_model.coef_
 
@@ -307,9 +304,7 @@ def _find_vg_ecl(self, model):
                     k = i
             # Case when we are crossing 0-360
             else:
-                if np.logical_or(
-                    self.lcrv["ecl_lon"] >= ini, self.lcrv["ecl_lon"] <= fin
-                ):
+                if np.logical_or(self.lcrv["ecl_lon"] >= ini, self.lcrv["ecl_lon"] <= fin):
                     k = i
         return k
 
@@ -324,9 +319,7 @@ def read_l3a(self, data_l3a: dict):
         """
         # Open and load json file with L3a data
 
-        self.spacecraft_location = list(
-            data_l3a["spacecraft_location_average"].values()
-        )
+        self.spacecraft_location = list(data_l3a["spacecraft_location_average"].values())
         self.lcrv["ecl_lon"] = np.degrees(
             fun.get_spher_coord_rad(np.array(self.spacecraft_location))[1]
         )
@@ -420,9 +413,8 @@ def save_to_file(self, fn):
 
         json_content = json.dumps(output, indent=3)
 
-        output_fp = open(fn, "w")
-        print(json_content, file=output_fp)
-        output_fp.close()
+        with open(fn, "w") as output_fp:
+            print(json_content, file=output_fp)
 
     def _subtract_background(self):
         """
@@ -462,14 +454,10 @@ def _total_ion_params_from_lcrv_params(self):
         model_const = np.array(self.model["vg_points"]["parameters"]["model_const"])
         model_matrix = np.array(self.model["vg_points"]["parameters"]["model_matrix"])
         hion_const = np.array(self.model["params_hion"]["hion_const"])
-        lcrv_filtration = np.array(
-            self.model["vg_points"]["parameters"]["lcrv_filtration"]
-        )
+        lcrv_filtration = np.array(self.model["vg_points"]["parameters"]["lcrv_filtration"])
 
         # Transformation PCA (we are taking only the first few components of the light curve decomposition)
-        lcrv_params_PCA = np.dot(self.lcrv["decomposition_coeff"], lcrv_Trmatrix)[
-            :lcrv_filtration
-        ]
+        lcrv_params_PCA = np.dot(self.lcrv["decomposition_coeff"], lcrv_Trmatrix)[:lcrv_filtration]
         # Transformation from light curve parameters into total ion parameters
         total_ion_params = np.concatenate(
             (model_const + np.dot(model_matrix, lcrv_params_PCA), hion_const)
diff --git a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_CarringtonSolarWind.py b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_CarringtonSolarWind.py
index ca469f7f..a97bce93 100644
--- a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_CarringtonSolarWind.py
+++ b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_CarringtonSolarWind.py
@@ -2,17 +2,19 @@
 Author: Izabela Kowalska-Leszczynska (ikowalska@cbk.waw.pl)
 Carrington solar wind class
 """
+# ruff: noqa: N999
 
 import json
+import logging
 from dataclasses import dataclass
+
+import astropy.constants as const
+import astropy.units as u
 import numpy as np
 from astropy.time import Time
-import astropy.units as u
-import astropy.constants as const
-from . import funcs as fun
-from .constants import VERSION, PHISICAL_CONSTANTS
 
-import logging
+from . import funcs as fun
+from .constants import PHISICAL_CONSTANTS, VERSION
 
 logging.basicConfig(level=logging.ERROR)
 
@@ -148,7 +150,7 @@ def calculate_sw_profile(self):
                     "lat= %lf deg: observed cx rate is smaller than min of the cx_grid",
                     self.sw_profile["grid"][i],
                 )
-                raise Exception(
+                raise RuntimeError(
                     "L3c not generated: observed cx rate is smaller than min of the cx_grid"
                 )
             # Searching for a measured charge exchange in the cx_grid. In that way we will find sw speed
@@ -183,20 +185,12 @@ def get_dict(self):
         output["CR"] = self.sw_profile["CR"]
         output["solar_wind_ecliptic"] = {}
         output["solar_wind_ecliptic"]["plasma_speed"] = self.sw_ecliptic["mean_speed"]
-        output["solar_wind_ecliptic"]["proton_density"] = self.sw_ecliptic[
-            "mean_proton_density"
-        ]
-        output["solar_wind_ecliptic"]["alpha_abundance"] = self.sw_ecliptic[
-            "mean_alpha_abundance"
-        ]
+        output["solar_wind_ecliptic"]["proton_density"] = self.sw_ecliptic["mean_proton_density"]
+        output["solar_wind_ecliptic"]["alpha_abundance"] = self.sw_ecliptic["mean_alpha_abundance"]
         output["solar_wind_profile"] = {}
         output["solar_wind_profile"]["lat_grid"] = self.sw_profile["grid"]
-        output["solar_wind_profile"]["plasma_speed"] = self.sw_profile[
-            "plasma_speed"
-        ].tolist()
-        output["solar_wind_profile"]["proton_density"] = self.sw_profile[
-            "proton_density"
-        ].tolist()
+        output["solar_wind_profile"]["plasma_speed"] = self.sw_profile["plasma_speed"].tolist()
+        output["solar_wind_profile"]["proton_density"] = self.sw_profile["proton_density"].tolist()
 
         return output
 
@@ -218,20 +212,12 @@ def save_to_file(self, fn):
         output["CR"] = self.sw_profile["CR"]
         output["solar_wind_ecliptic"] = {}
         output["solar_wind_ecliptic"]["plasma_speed"] = self.sw_ecliptic["mean_speed"]
-        output["solar_wind_ecliptic"]["proton_density"] = self.sw_ecliptic[
-            "mean_proton_density"
-        ]
-        output["solar_wind_ecliptic"]["alpha_abundance"] = self.sw_ecliptic[
-            "mean_alpha_abundance"
-        ]
+        output["solar_wind_ecliptic"]["proton_density"] = self.sw_ecliptic["mean_proton_density"]
+        output["solar_wind_ecliptic"]["alpha_abundance"] = self.sw_ecliptic["mean_alpha_abundance"]
         output["solar_wind_profile"] = {}
         output["solar_wind_profile"]["lat_grid"] = self.sw_profile["grid"]
-        output["solar_wind_profile"]["plasma_speed"] = self.sw_profile[
-            "plasma_speed"
-        ].tolist()
-        output["solar_wind_profile"]["proton_density"] = self.sw_profile[
-            "proton_density"
-        ].tolist()
+        output["solar_wind_profile"]["plasma_speed"] = self.sw_profile["plasma_speed"].tolist()
+        output["solar_wind_profile"]["proton_density"] = self.sw_profile["proton_density"].tolist()
 
         # Check validity of the data
         fun.check_nan(output["solar_wind_ecliptic"])
@@ -239,6 +225,5 @@ def save_to_file(self, fn):
 
         json_content = json.dumps(output, indent=3)
 
-        output_fp = open(fn, "w")
-        print(json_content, file=output_fp)
-        output_fp.close()
+        with open(fn, "w") as output_fp:
+            print(json_content, file=output_fp)
diff --git a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_EclipticSolarWind.py b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_EclipticSolarWind.py
index 2fcc7dd2..3c7dbf58 100644
--- a/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_EclipticSolarWind.py
+++ b/imap_l3_processing/glows/l3bc/l3bc_toolkit/l3c_EclipticSolarWind.py
@@ -2,6 +2,7 @@
 Author: Izabela Kowalska-Leszczynska (ikowalska@cbk.waw.pl)
 Solar wind parameters data in the ecliptic plane
 """
+# ruff: noqa: N999
 
 import logging
 from dataclasses import dataclass
@@ -87,9 +88,7 @@ def calculate_invariant(self, ext_dependencies):
         # TODO: SWAPI if we have full 13 Carrington rotation periods of data
 
         # Read solar wind parameters (Carrington averaged parameters on common carrington number grid)
-        grid_cr, plasma_speed, proton_dens, p_alpha = self.read_sw_ecliptic(
-            ext_dependencies
-        )
+        _grid_cr, plasma_speed, proton_dens, p_alpha = self.read_sw_ecliptic(ext_dependencies)
 
         # Calculate solar wind energy flux for each CR
         sw_energy_flux = fun.calculate_sw_energy_flux(
@@ -139,12 +138,8 @@ def _read_OMNI_data(self, ext_dependencies):
             },
         }
 
-        proton_dens_carr, _ = fun.process_omni_param(
-            omni_raw, cr_grid, param_settings["density"]
-        )
-        plasma_speed_carr, _ = fun.process_omni_param(
-            omni_raw, cr_grid, param_settings["speed"]
-        )
+        proton_dens_carr, _ = fun.process_omni_param(omni_raw, cr_grid, param_settings["density"])
+        plasma_speed_carr, _ = fun.process_omni_param(omni_raw, cr_grid, param_settings["speed"])
         p_alpha_carr, used_nominal_alpha_per_cr = fun.process_omni_param(
             omni_raw, cr_grid, param_settings["alpha"]
         )
@@ -206,14 +201,10 @@ def read_sw_ecliptic(self, ext_dependencies):
         sw_ecliptic_source = self.settings["sw_ecliptic_source"]
 
         if sw_ecliptic_source == "OMNI":
-            grid_cr, plasma_speed, proton_dens, p_alpha = self._read_OMNI_data(
-                ext_dependencies
-            )
+            grid_cr, plasma_speed, proton_dens, p_alpha = self._read_OMNI_data(ext_dependencies)
         elif sw_ecliptic_source == "SWAPI":
-            grid_cr, plasma_speed, proton_dens, p_alpha = self._read_SWAPI_data(
-                ext_dependencies
-            )
+            grid_cr, plasma_speed, proton_dens, p_alpha = self._read_SWAPI_data(ext_dependencies)
         else:
-            raise Exception("Unknown solar wind source. Select OMNI or SWAPI")
+            raise ValueError("Unknown solar wind source. Select OMNI or SWAPI")
 
         return grid_cr, plasma_speed, proton_dens, p_alpha
diff --git a/imap_l3_processing/glows/l3bc/models.py b/imap_l3_processing/glows/l3bc/models.py
index 28b6a191..712fe4d6 100644
--- a/imap_l3_processing/glows/l3bc/models.py
+++ b/imap_l3_processing/glows/l3bc/models.py
@@ -7,13 +7,12 @@
 from datetime import datetime, timedelta
 from itertools import chain
 from pathlib import Path
-from typing import Optional
 
 import imap_data_access
 import numpy as np
 from spacepy import pycdf
 
-from imap_l3_processing.constants import TEMP_CDF_FOLDER_PATH, ONE_SECOND_IN_NANOSECONDS
+from imap_l3_processing.constants import ONE_SECOND_IN_NANOSECONDS, TEMP_CDF_FOLDER_PATH
 from imap_l3_processing.glows.l3bc.dependency_validator import validate_dependencies
 from imap_l3_processing.glows.l3bc.utils import get_date_range_of_cr
 from imap_l3_processing.models import DataProduct, DataProductVariable, InputMetadata
@@ -108,7 +107,7 @@ class CRToProcess:
     cr_end_date: datetime
     cr_rotation_number: int
 
-    _buffer_time: Optional[timedelta] = None
+    _buffer_time: timedelta | None = None
 
     def pipeline_dependency_file_names(self) -> set[str]:
         ancillary_files = {
@@ -126,14 +125,10 @@ def get_buffer_time(self) -> timedelta:
                 self.pipeline_settings_file_name
             )
             pipeline_settings = read_pipeline_settings(pipeline_settings_local_path)
-            self._buffer_time = timedelta(
-                days=pipeline_settings["initializer_time_delta_days"]
-            )
+            self._buffer_time = timedelta(days=pipeline_settings["initializer_time_delta_days"])
         return self._buffer_time
 
-    def has_valid_external_dependencies(
-        self, external_deps: ExternalDependencies
-    ) -> bool:
+    def has_valid_external_dependencies(self, external_deps: ExternalDependencies) -> bool:
         return validate_dependencies(
             self.cr_start_date,
             self.cr_end_date,
@@ -216,9 +211,7 @@ def from_instrument_team_dictionary(
 
         parent_file_names = []
         parent_file_names += collect_file_names(model["header"]["ancillary_data_files"])
-        parent_file_names += collect_file_names(
-            model["header"]["external_dependeciens"]
-        )
+        parent_file_names += collect_file_names(model["header"]["external_dependeciens"])
         return cls(
             input_metadata=input_metadata,
             parent_file_names=parent_file_names,
@@ -265,9 +258,7 @@ class GlowsL3CSolarWind(DataProduct):
 
     def to_data_product_variables(self) -> list[DataProductVariable]:
         return [
-            DataProductVariable(
-                "epoch", self.epoch, cdf_data_type=pycdf.const.CDF_TIME_TT2000
-            ),
+            DataProductVariable("epoch", self.epoch, cdf_data_type=pycdf.const.CDF_TIME_TT2000),
             DataProductVariable(
                 "epoch_delta", self.epoch_delta, cdf_data_type=pycdf.const.CDF_INT8
             ),
@@ -328,9 +319,7 @@ def from_instrument_team_dictionary(
 
         parent_file_names = []
         parent_file_names += collect_file_names(model["header"]["ancillary_data_files"])
-        parent_file_names += collect_file_names(
-            model["header"]["external_dependeciens"]
-        )
+        parent_file_names += collect_file_names(model["header"]["external_dependeciens"])
         return cls(
             input_metadata=input_metadata,
             epoch=np.array([epoch]),
@@ -339,21 +328,11 @@ def from_instrument_team_dictionary(
             cr=np.array([model["CR"]]),
             lat_grid=np.array(latitude_grid),
             lat_grid_label=[f"{x}°" for x in latitude_grid],
-            plasma_speed_ecliptic=np.array(
-                [model["solar_wind_ecliptic"]["plasma_speed"]]
-            ),
-            proton_density_ecliptic=np.array(
-                [model["solar_wind_ecliptic"]["proton_density"]]
-            ),
-            alpha_abundance_ecliptic=np.array(
-                [model["solar_wind_ecliptic"]["alpha_abundance"]]
-            ),
-            plasma_speed_profile=np.array(
-                [model["solar_wind_profile"]["plasma_speed"]]
-            ),
-            proton_density_profile=np.array(
-                [model["solar_wind_profile"]["proton_density"]]
-            ),
+            plasma_speed_ecliptic=np.array([model["solar_wind_ecliptic"]["plasma_speed"]]),
+            proton_density_ecliptic=np.array([model["solar_wind_ecliptic"]["proton_density"]]),
+            alpha_abundance_ecliptic=np.array([model["solar_wind_ecliptic"]["alpha_abundance"]]),
+            plasma_speed_profile=np.array([model["solar_wind_profile"]["plasma_speed"]]),
+            proton_density_profile=np.array([model["solar_wind_profile"]["proton_density"]]),
             glows_flags=np.array([model["glows_flags"]], dtype=np.uint16),
             parent_file_names=parent_file_names,
         )
diff --git a/imap_l3_processing/glows/l3bc/science/filter_out_bad_days.py b/imap_l3_processing/glows/l3bc/science/filter_out_bad_days.py
index 5ae4ecb1..8534f59f 100644
--- a/imap_l3_processing/glows/l3bc/science/filter_out_bad_days.py
+++ b/imap_l3_processing/glows/l3bc/science/filter_out_bad_days.py
@@ -6,9 +6,7 @@
 from imap_l3_processing.glows.l3bc.l3bc_toolkit.funcs import jd_fm_Carrington
 
 
-def filter_l3a_files(
-    l3a_data: list[dict], bad_day_list_path: Path, cr: int
-) -> list[dict]:
+def filter_l3a_files(l3a_data: list[dict], bad_day_list_path: Path, cr: int) -> list[dict]:
     carrington_start_date = jd_fm_Carrington(float(cr))
     cr_start_time = Time(carrington_start_date, format="jd")
     cr_start_time.format = "iso"
@@ -23,9 +21,7 @@ def mean_time(l3a_dict):
         return time
 
     l3a_in_cr = [
-        l3a_dict
-        for l3a_dict in l3a_data
-        if cr_start_time <= mean_time(l3a_dict) < cr_end_time
+        l3a_dict for l3a_dict in l3a_data if cr_start_time <= mean_time(l3a_dict) < cr_end_time
     ]
 
     with open(bad_day_list_path, "r") as bad_day_file:
@@ -34,9 +30,7 @@ def mean_time(l3a_dict):
         filtered_data = []
         l3a_data_index = 0
         bad_day_list_index = 0
-        while l3a_data_index < len(l3a_in_cr) and bad_day_list_index < len(
-            sorted_bad_days
-        ):
+        while l3a_data_index < len(l3a_in_cr) and bad_day_list_index < len(sorted_bad_days):
             start_time = Time(l3a_in_cr[l3a_data_index]["start_time"])
             end_time = Time(l3a_in_cr[l3a_data_index]["end_time"])
             if start_time <= sorted_bad_days[bad_day_list_index] < end_time:
diff --git a/imap_l3_processing/glows/l3bc/science/generate_l3bc.py b/imap_l3_processing/glows/l3bc/science/generate_l3bc.py
index e32f60e5..e256a394 100644
--- a/imap_l3_processing/glows/l3bc/science/generate_l3bc.py
+++ b/imap_l3_processing/glows/l3bc/science/generate_l3bc.py
@@ -73,25 +73,21 @@ def generate_l3bc(dependencies: GlowsL3BCDependencies):
     solar_wind_Carr.header["external_dependeciens"] = sw_ecliptic.external_dependeciens
 
     # Solar wind parameters passed to the CarringtonSolarWind structure for L3c processing
-    idx_current_CR = np.abs(
-        sw_ecliptic.CR_grid - ion_rate_Carr.carr_ion_rate["CR"]
-    ).argmin()
+    idx_current_CR = np.abs(sw_ecliptic.CR_grid - ion_rate_Carr.carr_ion_rate["CR"]).argmin()
     solar_wind_Carr.sw_ecliptic["mean_speed"] = sw_ecliptic.mean_speed[idx_current_CR]
-    solar_wind_Carr.sw_ecliptic["mean_proton_density"] = (
-        sw_ecliptic.mean_proton_density[idx_current_CR]
-    )
-    solar_wind_Carr.sw_ecliptic["mean_alpha_abundance"] = (
-        sw_ecliptic.mean_alpha_abundance[idx_current_CR]
-    )
+    solar_wind_Carr.sw_ecliptic["mean_proton_density"] = sw_ecliptic.mean_proton_density[
+        idx_current_CR
+    ]
+    solar_wind_Carr.sw_ecliptic["mean_alpha_abundance"] = sw_ecliptic.mean_alpha_abundance[
+        idx_current_CR
+    ]
     # Solar wind parameters passed to the CarringtonIonizationRate structure for L3c processing
     ion_rate_Carr.sw_ecliptic["mean_speed"] = sw_ecliptic.mean_speed[idx_current_CR]
     ion_rate_Carr.sw_ecliptic["mean_proton_density"] = sw_ecliptic.mean_proton_density[
         idx_current_CR
     ]
     # Calculate averaged ionization rate profile and save it to the file
-    ion_rate_Carr.calculate_photoion(
-        dependencies.ancillary_files, dependencies.external_files
-    )
+    ion_rate_Carr.calculate_photoion(dependencies.ancillary_files, dependencies.external_files)
 
     ion_rate_Carr.calculate_averaged_profile()
     ion_rate_Carr.calculate_charge_exchange()
diff --git a/imap_l3_processing/glows/l3bc/utils.py b/imap_l3_processing/glows/l3bc/utils.py
index 4cfceea6..07b6e754 100644
--- a/imap_l3_processing/glows/l3bc/utils.py
+++ b/imap_l3_processing/glows/l3bc/utils.py
@@ -1,6 +1,5 @@
-from datetime import timedelta, datetime
+from datetime import datetime, timedelta
 from pathlib import Path
-from typing import Optional
 
 import numpy as np
 import pandas as pd
@@ -9,7 +8,7 @@
 
 def get_best_ancillary(
     start_date: datetime, end_date: datetime, ancillary_query_results: list[dict]
-) -> Optional[str]:
+) -> str | None:
     valid_ancillaries = []
     for ancillary_file in ancillary_query_results:
         ancillary_start_date = datetime.strptime(ancillary_file["start_date"], "%Y%m%d")
@@ -37,9 +36,7 @@ def get_best_ancillary(
 
 
 def get_date_range_of_cr(cr_number: int) -> tuple[datetime, datetime]:
-    start_date = (
-        first_carrington_start_date + (cr_number - carrington_first) * carrington_length
-    )
+    start_date = first_carrington_start_date + (cr_number - carrington_first) * carrington_length
     return start_date, start_date + carrington_length
 
 
@@ -50,8 +47,7 @@ def get_midpoint_of_cr(cr_number: int) -> datetime:
 
 def get_cr_for_date_time(datetime_to_check: datetime) -> int:
     return int(
-        carrington_first
-        + (datetime_to_check - first_carrington_start_date) / carrington_length
+        carrington_first + (datetime_to_check - first_carrington_start_date) / carrington_length
     )
 
 
@@ -66,6 +62,4 @@ def get_pointing_date_range(repointing: int) -> (datetime, datetime):
     start_time = repointing_data_start["repoint_end_utc"]
     end_time = repointing_data_end["repoint_start_utc"]
 
-    return np.datetime64(start_time).astype(datetime), np.datetime64(end_time).astype(
-        datetime
-    )
+    return np.datetime64(start_time).astype(datetime), np.datetime64(end_time).astype(datetime)
diff --git a/imap_l3_processing/glows/l3d/glows_l3d_dependencies.py b/imap_l3_processing/glows/l3d/glows_l3d_dependencies.py
index c2d3d62d..efd134dc 100644
--- a/imap_l3_processing/glows/l3d/glows_l3d_dependencies.py
+++ b/imap_l3_processing/glows/l3d/glows_l3d_dependencies.py
@@ -6,15 +6,15 @@
 from imap_data_access.processing_input import ProcessingInputCollection
 
 from imap_l3_processing.glows.descriptors import (
-    PROTON_DENSITY_DESCRIPTOR,
-    PLASMA_SPEED_DESCRIPTOR,
-    UV_ANISOTROPY_DESCRIPTOR,
-    PHOTOION_DESCRIPTOR,
-    LYA_DESCRIPTOR,
     ELECTRON_DENSITY_DESCRIPTOR,
-    PIPELINE_SETTINGS_L3BCDE_DESCRIPTOR,
     GLOWS_L3B_DESCRIPTOR,
     GLOWS_L3C_DESCRIPTOR,
+    LYA_DESCRIPTOR,
+    PHOTOION_DESCRIPTOR,
+    PIPELINE_SETTINGS_L3BCDE_DESCRIPTOR,
+    PLASMA_SPEED_DESCRIPTOR,
+    PROTON_DENSITY_DESCRIPTOR,
+    UV_ANISOTROPY_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3bc.models import ExternalDependencies
 
@@ -42,12 +42,8 @@ def fetch_dependencies(
         uv_anisotropy_path = dependencies.get_file_paths(
             source="glows", descriptor=UV_ANISOTROPY_DESCRIPTOR
         )
-        photoion_path = dependencies.get_file_paths(
-            source="glows", descriptor=PHOTOION_DESCRIPTOR
-        )
-        lya_path = dependencies.get_file_paths(
-            source="glows", descriptor=LYA_DESCRIPTOR
-        )
+        photoion_path = dependencies.get_file_paths(source="glows", descriptor=PHOTOION_DESCRIPTOR)
+        lya_path = dependencies.get_file_paths(source="glows", descriptor=LYA_DESCRIPTOR)
         electron_density_path = dependencies.get_file_paths(
             source="glows", descriptor=ELECTRON_DENSITY_DESCRIPTOR
         )
@@ -55,19 +51,13 @@ def fetch_dependencies(
             source="glows", descriptor=PIPELINE_SETTINGS_L3BCDE_DESCRIPTOR
         )
 
-        plasma_speed_legendre = imap_data_access.download(
-            str(plasma_speed_legendre_path[0])
-        )
-        proton_density_legendre = imap_data_access.download(
-            str(proton_density_legendre_path[0])
-        )
+        plasma_speed_legendre = imap_data_access.download(str(plasma_speed_legendre_path[0]))
+        proton_density_legendre = imap_data_access.download(str(proton_density_legendre_path[0]))
         uv_anisotropy = imap_data_access.download(str(uv_anisotropy_path[0]))
         photoion = imap_data_access.download(str(photoion_path[0]))
         lya_2010a = imap_data_access.download(str(lya_path[0]))
         electron_density = imap_data_access.download(str(electron_density_path[0]))
-        pipeline_settings_l3bc = imap_data_access.download(
-            str(pipeline_settings_l3bc_path[0])
-        )
+        pipeline_settings_l3bc = imap_data_access.download(str(pipeline_settings_l3bc_path[0]))
 
         l3b_file_names = dependencies.get_file_paths(
             source="glows", descriptor=GLOWS_L3B_DESCRIPTOR
@@ -97,6 +87,4 @@ def fetch_dependencies(
         last_l3c_cr = max([ScienceFilePath(file).cr for file in l3c_file_paths])
         end_cr = min(last_l3b_cr, last_l3c_cr) + 1
 
-        return cls(
-            external_dict, ancillary_dict, l3b_file_paths, l3c_file_paths, end_cr
-        )
+        return cls(external_dict, ancillary_dict, l3b_file_paths, l3c_file_paths, end_cr)
diff --git a/imap_l3_processing/glows/l3d/glows_l3d_initializer.py b/imap_l3_processing/glows/l3d/glows_l3d_initializer.py
index 83dc78c6..75ded934 100644
--- a/imap_l3_processing/glows/l3d/glows_l3d_initializer.py
+++ b/imap_l3_processing/glows/l3d/glows_l3d_initializer.py
@@ -1,25 +1,24 @@
 import logging
 from pathlib import Path
-from typing import Optional
 
 import imap_data_access
 from imap_data_access import (
-    ProcessingInputCollection,
-    ScienceInput,
     AncillaryInput,
+    ProcessingInputCollection,
     ScienceFilePath,
+    ScienceInput,
 )
 from imap_data_access.file_validation import Version
 
 from imap_l3_processing.glows.descriptors import (
+    ELECTRON_DENSITY_DESCRIPTOR,
+    GLOWS_L3D_DESCRIPTOR,
+    LYA_DESCRIPTOR,
+    PHOTOION_DESCRIPTOR,
+    PIPELINE_SETTINGS_L3BCDE_DESCRIPTOR,
     PLASMA_SPEED_DESCRIPTOR,
     PROTON_DENSITY_DESCRIPTOR,
     UV_ANISOTROPY_DESCRIPTOR,
-    PHOTOION_DESCRIPTOR,
-    LYA_DESCRIPTOR,
-    ELECTRON_DENSITY_DESCRIPTOR,
-    PIPELINE_SETTINGS_L3BCDE_DESCRIPTOR,
-    GLOWS_L3D_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3bc.models import (
     ExternalDependencies,
@@ -28,7 +27,7 @@
 from imap_l3_processing.glows.l3d.glows_l3d_dependencies import GlowsL3DDependencies
 from imap_l3_processing.glows.l3d.utils import query_for_most_recent_l3d
 from imap_l3_processing.glows.l3e.reprocess_info import ReprocessInfo
-from imap_l3_processing.utils import read_cdf_parents, get_version_from_query_result
+from imap_l3_processing.utils import get_version_from_query_result, read_cdf_parents
 
 logger = logging.getLogger(__name__)
 
@@ -41,7 +40,7 @@ def should_process_l3d(
         l3cs: list[str],
         reprocess_info: ReprocessInfo,
         major_version: int | None,
-    ) -> Optional[tuple[Version, GlowsL3DDependencies, Optional[str]]]:
+    ) -> tuple[Version, GlowsL3DDependencies, str | None] | None:
         if len(l3bs) == 0 and len(l3cs) == 0:
             logger.info("Found no L3b and L3c files!")
             return None
@@ -96,16 +95,8 @@ def should_process_l3d(
             imap_data_access.download(pipeline_settings_filename)
         )
 
-        l3bs = [
-            l3b
-            for l3b in l3bs
-            if ScienceFilePath(l3b).cr >= pipeline_settings["start_cr"]
-        ]
-        l3cs = [
-            l3c
-            for l3c in l3cs
-            if ScienceFilePath(l3c).cr >= pipeline_settings["start_cr"]
-        ]
+        l3bs = [l3b for l3b in l3bs if ScienceFilePath(l3b).cr >= pipeline_settings["start_cr"]]
+        l3cs = [l3c for l3c in l3cs if ScienceFilePath(l3c).cr >= pipeline_settings["start_cr"]]
 
         if len(l3bs) == 0 and len(l3cs) == 0:
             logger.info("Found no L3b and L3c files after start CR!")
@@ -140,17 +131,13 @@ def should_process_l3d(
             l3d_parents = read_cdf_parents(Path(most_recent_l3d["file_path"]).name)
             old_l3d = Path(most_recent_l3d["file_path"]).name
 
-            logger.info(
-                f"Old L3d parents: {l3d_parents}, new L3d deps: {updated_input_files}"
-            )
+            logger.info(f"Old L3d parents: {l3d_parents}, new L3d deps: {updated_input_files}")
 
             most_recent_l3d_version = get_version_from_query_result(most_recent_l3d)
             minor_version_to_generate = most_recent_l3d_version.minor + 1
 
             same_major_version = most_recent_l3d_version.major == major_version
-            inputs_unchanged = same_major_version and updated_input_files.issubset(
-                l3d_parents
-            )
+            inputs_unchanged = same_major_version and updated_input_files.issubset(l3d_parents)
 
             if inputs_unchanged and not reprocess_info.should_reprocess_l3d():
                 return None
@@ -169,8 +156,6 @@ def generate_result(
     ) -> tuple[Version, GlowsL3DDependencies, str | None]:
         return (
             version_to_generate,
-            GlowsL3DDependencies.fetch_dependencies(
-                processing_input_collection, external_deps
-            ),
+            GlowsL3DDependencies.fetch_dependencies(processing_input_collection, external_deps),
             old_l3d,
         )
diff --git a/imap_l3_processing/glows/l3d/models.py b/imap_l3_processing/glows/l3d/models.py
index 114e8618..d4c09d75 100644
--- a/imap_l3_processing/glows/l3d/models.py
+++ b/imap_l3_processing/glows/l3d/models.py
@@ -58,18 +58,12 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(CR_CDF_VAR_NAME, self.cr),
             DataProductVariable(SPEED_CDF_VAR_NAME, self.plasma_speed),
             DataProductVariable(PROTON_DENSITY_CDF_VAR_NAME, self.proton_density),
-            DataProductVariable(
-                UV_ANISOTROPY_CDF_VAR_NAME, self.ultraviolet_anisotropy
-            ),
+            DataProductVariable(UV_ANISOTROPY_CDF_VAR_NAME, self.ultraviolet_anisotropy),
             DataProductVariable(PHION_CDF_VAR_NAME, self.phion),
             DataProductVariable(LYMAN_ALPHA_CDF_VAR_NAME, self.lyman_alpha),
             DataProductVariable(ELECTRON_DENSITY_CDF_VAR_NAME, self.electron_density),
             DataProductVariable(PLASMA_SPEED_FLAG_CDF_VAR_NAME, self.plasma_speed_flag),
-            DataProductVariable(
-                UV_ANISOTROPY_FLAG_CDF_VAR_NAME, self.uv_anisotropy_flag
-            ),
-            DataProductVariable(
-                PROTON_DENSITY_FLAG_CDF_VAR_NAME, self.proton_density_flag
-            ),
+            DataProductVariable(UV_ANISOTROPY_FLAG_CDF_VAR_NAME, self.uv_anisotropy_flag),
+            DataProductVariable(PROTON_DENSITY_FLAG_CDF_VAR_NAME, self.proton_density_flag),
             DataProductVariable(GLOWS_FLAGS_CDF_VAR_NAME, self.glows_flags),
         ]
diff --git a/imap_l3_processing/glows/l3d/science/generate_l3d.py b/imap_l3_processing/glows/l3d/science/generate_l3d.py
index ce532ef1..f0c60515 100644
--- a/imap_l3_processing/glows/l3d/science/generate_l3d.py
+++ b/imap_l3_processing/glows/l3d/science/generate_l3d.py
@@ -9,7 +9,6 @@
 import warnings
 
 import numpy as np
-
 import toolkit.funcs as fun
 import toolkit.l3d_SolarParamHistory as sph
 
@@ -31,9 +30,7 @@
 data_l3b = [fun.read_json(fn) for fn in l3b_fn_list]
 data_l3c = [fun.read_json(fn) for fn in l3c_fn_list]
 
-solar_param_hist = sph.SolarParamsHistory(
-    ANC_INPUT_FROM_INSTRUMENT_TEAM, EXT_DEPENDENCIES
-)
+solar_param_hist = sph.SolarParamsHistory(ANC_INPUT_FROM_INSTRUMENT_TEAM, EXT_DEPENDENCIES)
 fn_initial = ANC_INPUT_FROM_INSTRUMENT_TEAM["WawHelioIon"]
 
 # Start generating from the initial files (not using the last entry from L3d)
@@ -45,9 +42,7 @@
 solar_param_hist.header["l3d_cdf_filename"] = L3D_CDF_FILENAME
 solar_param_hist.generate_initial_history(fn_initial)
 
-solar_param_hist.update_solar_params_hist(
-    EXT_DEPENDENCIES, data_l3b, data_l3c, CR_current
-)
+solar_param_hist.update_solar_params_hist(EXT_DEPENDENCIES, data_l3b, data_l3c, CR_current)
 
 # filename of the data products (main json file and the text version)
 start_date = solar_param_hist.time_grid[0]
diff --git a/imap_l3_processing/glows/l3d/science/toolkit/funcs.py b/imap_l3_processing/glows/l3d/science/toolkit/funcs.py
index 43b924c9..8e6daf49 100644
--- a/imap_l3_processing/glows/l3d/science/toolkit/funcs.py
+++ b/imap_l3_processing/glows/l3d/science/toolkit/funcs.py
@@ -3,17 +3,17 @@
 Functions used in L3a->L3b processing that are not class methods
 """
 
-import numpy as np
-import astropy.units as u
-import astropy.constants as const
 import json
+import logging
+
+import astropy.constants as const
+import astropy.units as u
 import netCDF4
-from astropy.time import Time
+import numpy as np
 from astropy.coordinates import get_sun
+from astropy.time import Time
 
-from .constants import PHISICAL_CONSTANTS, CONST_ALPHA_TO_PROTON
-
-import logging
+from .constants import CONST_ALPHA_TO_PROTON, PHISICAL_CONSTANTS
 
 logging.basicConfig(level=logging.ERROR)
 
@@ -70,9 +70,7 @@ def calculate_lya_monthly(t, flux):
     Calculates data that are averaged over each Carrington rotation period. Time is mean value of decimal year in each period.
     """
     t_carr, flux_carr = resize_by_carr(t, flux)
-    t_mean = Time(
-        np.array([np.mean(t.decimalyear) for t in t_carr]), format="decimalyear"
-    )
+    t_mean = Time(np.array([np.mean(t.decimalyear) for t in t_carr]), format="decimalyear")
     flux_mean = np.array([f.mean() for f in flux_carr])
 
     return t_mean, flux_mean
@@ -132,8 +130,8 @@ def check_nan(data):
     data - dictionary with the data product
     """
     for key in data:
-        if np.any((np.isnan(np.array(data[key])))):
-            raise Exception("There are NaN in the output data")
+        if np.any(np.isnan(np.array(data[key]))):
+            raise ValueError("There are NaN in the output data")
 
 
 def cr_from_l3b_fn(fn):
@@ -192,11 +190,7 @@ def cross_section_cx(E):
     A8 = 6.1091
 
     EkeV = E.to("keV").value
-    out = (
-        (1e-16)
-        * (A1 * np.log(A2 / EkeV + A3))
-        / (1 + A4 * EkeV + A5 * EkeV**A6 + A7 * EkeV**A8)
-    )
+    out = (1e-16) * (A1 * np.log(A2 / EkeV + A3)) / (1 + A4 * EkeV + A5 * EkeV**A6 + A7 * EkeV**A8)
     sigma = out * u.cm * u.cm
 
     return sigma
@@ -239,7 +233,7 @@ def f107_daily_data(t, flux):
     t_out: daily time array (astropy.time)
     flux_out: daily F10.7 flux adjusted to 1au (10^(-22) W/m^2/Hz)
     """
-    idx_noon, idx_dup = select_noon(t)  # select one measurment per day
+    idx_noon, _idx_dup = select_noon(t)  # select one measurment per day
     idx_no0 = np.where(flux[idx_noon] > 0)[0]
     t_out = t[idx_noon[idx_no0]]
     flux_out = flux[idx_noon[idx_no0]]
@@ -319,7 +313,7 @@ def get_spher_coord_rad(vec):
     """
     if vec.ndim == 1:
         if np.shape(vec)[0] != 3:
-            raise "get_spher_coord_rad() error: np.shape(vec)[0]!=3"
+            raise ValueError("get_spher_coord_rad() error: np.shape(vec)[0]!=3")
         r = np.sqrt(np.dot(vec, vec))
         if r == 0.0:
             b = 0.0
@@ -333,7 +327,7 @@ def get_spher_coord_rad(vec):
         return np.array([r, l, b])  # return one array similarly as in Mathematica
     else:
         if np.shape(vec)[1] != 3:
-            raise "get_spher_coord_rad() error: np.shape(vec)[1]!=3"
+            raise ValueError("get_spher_coord_rad() error: np.shape(vec)[1]!=3")
         r = np.sqrt((vec * vec).sum(axis=1))
         idxs = np.nonzero(r != 0.0)
         b = np.zeros((len(r)), np.float64)
@@ -341,9 +335,7 @@ def get_spher_coord_rad(vec):
         l = np.arctan2(vec[:, 1], vec[:, 0]) % (2 * np.pi)  # compute longitude
         idxs = np.nonzero(np.logical_and(vec[:, 0] == 0.0, vec[:, 1] == 0.0))
         l[idxs[0]] = 0.0  # set l=0 if vec[:,0]==0.0 and vec[:,1]==0.0
-        return np.column_stack(
-            [r, l, b]
-        )  # return one array similarly as in Mathematica
+        return np.column_stack([r, l, b])  # return one array similarly as in Mathematica
 
 
 def jd_fm_Carrington(carr):
@@ -415,10 +407,8 @@ def process_omni_param(omni_raw, cr_grid, param_settings):
     if np.logical_and(param_cr[0] <= cr_grid[0], param_cr[-1] >= cr_grid[-1]):
         param_value_interp = np.interp(cr_grid, param_cr, param_value)
     else:
-        logging.info(
-            "There are gaps in the OMNI2 data that cannot be filled by the interpolation"
-        )
-        raise Exception("OMNI Error: not enough data for interpolation")
+        logging.info("There are gaps in the OMNI2 data that cannot be filled by the interpolation")
+        raise RuntimeError("OMNI Error: not enough data for interpolation")
 
     return param_value_interp, used_nominal_per_cr
 
@@ -534,9 +524,8 @@ def read_json(fn):
     """
     Opens, reads and returns the content of the json file
     """
-    fp = open(fn, "r")
-    data = json.load(fp)
-    fp.close()
+    with open(fn, "r") as fp:
+        data = json.load(fp)
     return data
 
 
@@ -655,9 +644,7 @@ def select_noon(t_pen):
                     i = i + 3
             else:
                 h = np.array([int(t_pen[i].yday[9:11]), int(t_pen[i + 1].yday[9:11])])
-                k = (
-                    i + np.abs(h - 20).argmin()
-                )  # index of the hour that is near 20UT (local noon)
+                k = i + np.abs(h - 20).argmin()  # index of the hour that is near 20UT (local noon)
                 d = [i, i + 1]
             i = i + 2
         else:
@@ -718,24 +705,14 @@ def test_WawHelioInMP_file(model):
         lcrv_filtration = model["vg_points"][k]["parameters"]["lcrv_filtration"]
         lcrv_order = model["vg_points"][k]["parameters"]["lcrv_order"]
 
-        model_const_0 = np.array(
-            model["vg_points"][k]["parameters"]["model_const"]
-        ).shape[0]
+        model_const_0 = np.array(model["vg_points"][k]["parameters"]["model_const"]).shape[0]
         model_matrix = np.array(model["vg_points"][k]["parameters"]["model_matrix"])
-        model_matrix_0 = np.array(
-            model["vg_points"][k]["parameters"]["model_matrix"]
-        ).shape[0]
-        model_matrix_1 = np.array(
-            model["vg_points"][k]["parameters"]["model_matrix"]
-        ).shape[1]
+        model_matrix_0 = np.array(model["vg_points"][k]["parameters"]["model_matrix"]).shape[0]
+        model_matrix_1 = np.array(model["vg_points"][k]["parameters"]["model_matrix"]).shape[1]
 
         lcrv_Trmatrix = np.array(model["vg_points"][k]["parameters"]["lcrv_Trmatrix"])
-        lcrv_Trmatrix_0 = np.array(
-            model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]
-        ).shape[0]
-        lcrv_Trmatrix_1 = np.array(
-            model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]
-        ).shape[1]
+        lcrv_Trmatrix_0 = np.array(model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]).shape[0]
+        lcrv_Trmatrix_1 = np.array(model["vg_points"][k]["parameters"]["lcrv_Trmatrix"]).shape[1]
 
         if model_const_0 != hion_filtration:
             logging.error(
@@ -746,9 +723,7 @@ def test_WawHelioInMP_file(model):
             )
             raise ArrayShapeError("Array shape error: Array shape is incorrect")
 
-        elif np.logical_or(
-            model_matrix_0 != hion_filtration, model_matrix_1 != lcrv_filtration
-        ):
+        elif np.logical_or(model_matrix_0 != hion_filtration, model_matrix_1 != lcrv_filtration):
             logging.error(
                 "model_matrix shape is incorrect.\nIt is "
                 + str(model_matrix.shape)
diff --git a/imap_l3_processing/glows/l3d/science/toolkit/l3d_SolarParamHistory.py b/imap_l3_processing/glows/l3d/science/toolkit/l3d_SolarParamHistory.py
index 62b71e36..7c20c623 100644
--- a/imap_l3_processing/glows/l3d/science/toolkit/l3d_SolarParamHistory.py
+++ b/imap_l3_processing/glows/l3d/science/toolkit/l3d_SolarParamHistory.py
@@ -1,12 +1,14 @@
-import numpy as np
-from astropy.time import Time
-import json
 import glob
+import json
+from dataclasses import dataclass
+
+import numpy as np
 import toolkit.funcs as fun
+from astropy.time import Time
 
 from imap_l3_processing.glows.quality_flags import GlowsL3Flags
+
 from .constants import VERSION
-from dataclasses import dataclass
 
 
 @dataclass
@@ -130,7 +132,9 @@ def __init__(self, anc_input_from_instr_team, ext_dependencies):
 
         self.lat_grid = self.settings["solar_wind_grid"]  # latitudinal grid [deg]
         self.CR_grid = None  # regular grid with Carrington rotation period resolution. Bin centered on Carr halves
-        self.time_grid = None  # decimal year corresponding to the regular grid with bins on Carrington halves
+        self.time_grid = (
+            None  # decimal year corresponding to the regular grid with bins on Carrington halves
+        )
         self.CR_last = None
 
         self.solar_params = {}  # ionization parameters interplolated to the Carrington rotation halves
@@ -141,7 +145,9 @@ def __init__(self, anc_input_from_instr_team, ext_dependencies):
         for k in anc_input_from_instr_team["WawHelioIon"]:
             self.flags[k] = None
 
-        self.glows_flags = None  # GLOWS quality-flag bitmask per CR (initialized in generate_initial_history)
+        self.glows_flags = (
+            None  # GLOWS quality-flag bitmask per CR (initialized in generate_initial_history)
+        )
 
     def _check_ini_data(self):
         """
@@ -158,7 +164,7 @@ def _check_ini_data(self):
             ]
         )
         if (diff > eps).any():
-            raise Exception(
+            raise ValueError(
                 "Incorrect format of the input files. Last CR is not the same in all files"
             )
         else:
@@ -178,11 +184,9 @@ def find_fn_initial(self):
 
         # list of the L3d text files from the latest CR
         fn_initial = {}
-        for k in l3d_txt_fn_list:
-            idx_latest = np.array(
-                [f.split("cr_")[1].split("_")[0] for f in l3d_txt_fn_list[k]]
-            ).argmax()
-            fn_initial[k] = l3d_txt_fn_list[k][idx_latest]
+        for k, value in l3d_txt_fn_list.items():
+            idx_latest = np.array([f.split("cr_")[1].split("_")[0] for f in value]).argmax()
+            fn_initial[k] = value[idx_latest]
         return fn_initial
 
     def _generate_cr_solar_params(self, CR, data_l3b, data_l3c):
@@ -215,19 +219,11 @@ def _generate_cr_solar_params(self, CR, data_l3b, data_l3c):
             idx_read_b = [idx_read_b[0]]
             idx_read_c = [idx_read_c[0]]
             cr_params["uv-anis"] = data_l3b[idx_current]["uv_anisotropy_factor"]
-            cr_params["phion"] = data_l3b[idx_current]["ion_rate_profile"]["ph_rate"][
-                Nmid
-            ]
-            cr_params["p-dens"] = data_l3c[idx_current]["solar_wind_profile"][
-                "proton_density"
-            ]
-            cr_params["speed"] = data_l3c[idx_current]["solar_wind_profile"][
-                "plasma_speed"
-            ]
+            cr_params["phion"] = data_l3b[idx_current]["ion_rate_profile"]["ph_rate"][Nmid]
+            cr_params["p-dens"] = data_l3c[idx_current]["solar_wind_profile"]["proton_density"]
+            cr_params["speed"] = data_l3c[idx_current]["solar_wind_profile"]["plasma_speed"]
             p_dens_ecl = data_l3c[idx_current]["solar_wind_ecliptic"]["proton_density"]
-            a_abundance_ecl = data_l3c[idx_current]["solar_wind_ecliptic"][
-                "alpha_abundance"
-            ]
+            a_abundance_ecl = data_l3c[idx_current]["solar_wind_ecliptic"]["alpha_abundance"]
             cr_params["e-dens"] = p_dens_ecl * (1 + 2 * a_abundance_ecl)
         else:
             # if idx_read_b[-1]>=len(CR_list_b): raise Exception('L3d not generated: there is not enough L3b data to interpolate')
@@ -239,12 +235,8 @@ def _generate_cr_solar_params(self, CR, data_l3b, data_l3c):
 
             # time nodes that will be used for interpolation. The first one is the last time stamp from the previous CR, the second and the third are next available L3bc dates
             # Usually t_b=t_c, but there could be a cases when for a current CR L3b was generated and L3c is not. Then we can still generate L3d if we have both L3b and L3c for later CR
-            t_nods_b = np.concatenate(
-                [[fun.jd_fm_Carrington(self.ini_data["CR_last"])], t_b.jd]
-            )
-            t_nods_c = np.concatenate(
-                [[fun.jd_fm_Carrington(self.ini_data["CR_last"])], t_c.jd]
-            )
+            t_nods_b = np.concatenate([[fun.jd_fm_Carrington(self.ini_data["CR_last"])], t_b.jd])
+            t_nods_c = np.concatenate([[fun.jd_fm_Carrington(self.ini_data["CR_last"])], t_c.jd])
 
             # UV-anisotropy
             anisotropy = np.concatenate(
@@ -266,10 +258,7 @@ def _generate_cr_solar_params(self, CR, data_l3b, data_l3c):
                 [
                     [self.ini_data["data"]["phion"][-1]],
                     np.array(
-                        [
-                            data_l3b[i]["ion_rate_profile"]["ph_rate"][Nmid]
-                            for i in idx_read_b
-                        ]
+                        [data_l3b[i]["ion_rate_profile"]["ph_rate"][Nmid] for i in idx_read_b]
                     ),
                 ]
             )
@@ -280,10 +269,7 @@ def _generate_cr_solar_params(self, CR, data_l3b, data_l3c):
                 [
                     [self.ini_data["data"]["p-dens"][-1]],
                     np.array(
-                        [
-                            data_l3c[i]["solar_wind_profile"]["proton_density"]
-                            for i in idx_read_c
-                        ]
+                        [data_l3c[i]["solar_wind_profile"]["proton_density"] for i in idx_read_c]
                     ),
                 ]
             )
@@ -291,38 +277,23 @@ def _generate_cr_solar_params(self, CR, data_l3b, data_l3c):
                 [
                     [self.ini_data["data"]["speed"][-1]],
                     np.array(
-                        [
-                            data_l3c[i]["solar_wind_profile"]["plasma_speed"]
-                            for i in idx_read_c
-                        ]
+                        [data_l3c[i]["solar_wind_profile"]["plasma_speed"] for i in idx_read_c]
                     ),
                 ]
             )
             cr_params["p-dens"] = np.array(
-                [
-                    np.interp(t_CR.jd, t_nods_c, p_dens[:, i])
-                    for i in np.arange(len(p_dens[0]))
-                ]
+                [np.interp(t_CR.jd, t_nods_c, p_dens[:, i]) for i in np.arange(len(p_dens[0]))]
             )
             cr_params["speed"] = np.array(
-                [
-                    np.interp(t_CR.jd, t_nods_c, sw_speed[:, i])
-                    for i in np.arange(len(sw_speed[0]))
-                ]
+                [np.interp(t_CR.jd, t_nods_c, sw_speed[:, i]) for i in np.arange(len(sw_speed[0]))]
             )
 
             # electron density in the ecliptic plane calculated from p-dens and alpha-abundance
             p_dens_ecl = np.array(
-                [
-                    data_l3c[i]["solar_wind_ecliptic"]["proton_density"]
-                    for i in idx_read_c
-                ]
+                [data_l3c[i]["solar_wind_ecliptic"]["proton_density"] for i in idx_read_c]
             )
             a_abundance_ecl = np.array(
-                [
-                    data_l3c[i]["solar_wind_ecliptic"]["alpha_abundance"]
-                    for i in idx_read_c
-                ]
+                [data_l3c[i]["solar_wind_ecliptic"]["alpha_abundance"] for i in idx_read_c]
             )
             e_dens_ecl = np.concatenate(
                 [
@@ -360,9 +331,7 @@ def generate_initial_history(self, fn_list):
         # At first all values are set at fill value defined in pipeline settings
 
         for f in fn_list:
-            if np.logical_or(
-                np.logical_or(f == "speed", f == "p-dens"), f == "uv-anis"
-            ):
+            if np.logical_or(np.logical_or(f == "speed", f == "p-dens"), f == "uv-anis"):
                 self.solar_params[f] = np.ones((Nt, Nl)) * fill_value
                 self.flags[f] = np.ones(Nt) * fill_value
             elif np.logical_or(np.logical_or(f == "lya", f == "phion"), f == "e-dens"):
@@ -422,13 +391,9 @@ def _generate_hdr_template(self):
         hdr_temp[4] = "ground software version: " + VERSION + "\n"
         hdr_temp[5] = "creation date: " + Time.now().iso + "\n"
         hdr_temp[6] = "input files: " + self.header["l3d_cdf_filename"] + "\n"
-        hdr_temp[7] = (
-            "external dependencies: " + self.header["external_dependeciens"] + "\n"
-        )
+        hdr_temp[7] = "external dependencies: " + self.header["external_dependeciens"] + "\n"
         hdr_temp[8] = "last CR: " + str(self.CR_last) + "\n"
-        hdr_temp[9] = (
-            "fill value: " + str(self.settings["WawHelioIonGlows_fill_value"]) + "\n"
-        )
+        hdr_temp[9] = "fill value: " + str(self.settings["WawHelioIonGlows_fill_value"]) + "\n"
         hdr_temp[15] = "Remarks:\n"
         hdr_temp[29] = "###############################################"
         return hdr_temp
@@ -452,17 +417,15 @@ def _read_files(self, fn_list):
         N = self.settings["hdr_txt_lines_number"]
         for f in fn_list:
             self.ini_data["hdr_txt"][f] = fun.read_hdr_txt(fn_list[f], N)
-            if np.logical_or(
-                np.logical_or(f == "speed", f == "p-dens"), f == "uv-anis"
-            ):
+            if np.logical_or(np.logical_or(f == "speed", f == "p-dens"), f == "uv-anis"):
                 (
                     self.ini_data["time"][f],
                     self.ini_data["data"][f],
                     self.ini_data["flags"][f],
                 ) = self._read_profile(fn_list[f])
             elif np.logical_or(np.logical_or(f == "lya", f == "phion"), f == "e-dens"):
-                self.ini_data["time"][f], self.ini_data["data"][f] = (
-                    self._read_ecliptic(fn_list[f])
+                self.ini_data["time"][f], self.ini_data["data"][f] = self._read_ecliptic(
+                    fn_list[f]
                 )
 
     def _read_profile(self, fn):
@@ -503,9 +466,8 @@ def save_to_file(self, fn):
         output["glows_flags"] = [int(v) for v in self.glows_flags]
 
         json_content = json.dumps(output, indent=3)
-        output_fp = open(fn, "w")
-        print(json_content, file=output_fp)
-        output_fp.close()
+        with open(fn, "w") as output_fp:
+            print(json_content, file=output_fp)
 
     def save_to_txt(self, fn_out, hdr):
         """
@@ -513,9 +475,7 @@ def save_to_txt(self, fn_out, hdr):
         """
 
         for f in fn_out:
-            if np.logical_or(
-                np.logical_or(f == "speed", f == "p-dens"), f == "uv-anis"
-            ):
+            if np.logical_or(np.logical_or(f == "speed", f == "p-dens"), f == "uv-anis"):
                 self._save_to_txt_profile(fn_out[f], f, hdr[f])
             elif np.logical_or(np.logical_or(f == "lya", f == "phion"), f == "e-dens"):
                 self._save_to_txt_ecliptic(fn_out[f], f, hdr[f])
@@ -562,9 +522,7 @@ def _update_l3bc_data(self, data_l3b, data_l3c, CR):
         """
         Generates new value for given CR of the solar parameters.
         """
-        cr_params, idx_read_b, idx_read_c = self._generate_cr_solar_params(
-            CR, data_l3b, data_l3c
-        )
+        cr_params, idx_read_b, idx_read_c = self._generate_cr_solar_params(CR, data_l3b, data_l3c)
 
         self.header["l3b_input_filename"].extend(
             data_l3b[i]["header"]["filename"] for i in idx_read_b
@@ -575,9 +533,7 @@ def _update_l3bc_data(self, data_l3b, data_l3c, CR):
 
         # add a row with values for current CR
         for k in self.ini_data["label"]:
-            if np.logical_or(
-                np.logical_or(k == "speed", k == "p-dens"), k == "uv-anis"
-            ):
+            if np.logical_or(np.logical_or(k == "speed", k == "p-dens"), k == "uv-anis"):
                 self.solar_params[k] = np.r_[self.solar_params[k], [cr_params[k]]]
             elif np.logical_or(k == "phion", k == "e-dens"):
                 self.solar_params[k] = np.append(self.solar_params[k], cr_params[k])
@@ -626,17 +582,11 @@ def _freeze_l3bc_data(self, data_l3b, data_l3c):
 
         # add a row with values copied from the last CR generated from the GLOWS data
         for k in self.ini_data["label"]:
-            if np.logical_or(
-                np.logical_or(k == "speed", k == "p-dens"), k == "uv-anis"
-            ):
-                self.solar_params[k] = np.r_[
-                    self.solar_params[k], [self.solar_params[k][-1]]
-                ]
+            if np.logical_or(np.logical_or(k == "speed", k == "p-dens"), k == "uv-anis"):
+                self.solar_params[k] = np.r_[self.solar_params[k], [self.solar_params[k][-1]]]
 
             elif np.logical_or(k == "phion", k == "e-dens"):
-                self.solar_params[k] = np.append(
-                    self.solar_params[k], self.solar_params[k][-1]
-                )
+                self.solar_params[k] = np.append(self.solar_params[k], self.solar_params[k][-1])
         # add flags
         self.flags["uv-anis"] = np.append(
             self.flags["uv-anis"], self.settings["l3d_source_flags"]["freezed"]
@@ -666,9 +616,7 @@ def _update_lya_data(self, ext_dependencies, CR):
         lya_CR = fun.generate_cr_lya(CR, data_lya)
         self.solar_params["lya"] = np.append(self.solar_params["lya"], lya_CR)
 
-    def update_solar_params_hist(
-        self, ext_dependencies, data_l3b, data_l3c, CR_current
-    ):
+    def update_solar_params_hist(self, ext_dependencies, data_l3b, data_l3c, CR_current):
         """
         Updates structure by calculating parameters values from last CR in the initial data until currently processed CR
         """
diff --git a/imap_l3_processing/glows/l3d/utils.py b/imap_l3_processing/glows/l3d/utils.py
index 22162129..04e3767c 100644
--- a/imap_l3_processing/glows/l3d/utils.py
+++ b/imap_l3_processing/glows/l3d/utils.py
@@ -2,7 +2,6 @@
 import os
 from datetime import datetime
 from pathlib import Path
-from typing import Optional
 
 import imap_data_access
 import numpy as np
@@ -10,14 +9,12 @@
 from spacepy.pycdf import CDF
 
 import imap_l3_processing
+from imap_l3_processing.cdf.cdf_utils import read_numeric_variable
 from imap_l3_processing.glows.l3bc.utils import get_midpoint_of_cr
 from imap_l3_processing.glows.l3d.models import GlowsL3DSolarParamsHistory
 from imap_l3_processing.models import InputMetadata
-from imap_l3_processing.cdf.cdf_utils import read_numeric_variable
 
-PATH_TO_L3D_TOOLKIT = (
-    Path(imap_l3_processing.__file__).parent / "glows" / "l3d" / "science"
-)
+PATH_TO_L3D_TOOLKIT = Path(imap_l3_processing.__file__).parent / "glows" / "l3d" / "science"
 
 
 def create_glows_l3c_json_file_from_cdf(cdf_file_path: Path):
@@ -27,17 +24,11 @@ def create_glows_l3c_json_file_from_cdf(cdf_file_path: Path):
         json_dict = {
             "header": {"filename": cdf_file_path.name},
             "solar_wind_profile": {
-                "proton_density": read_numeric_variable(cdf["proton_density_profile"])[
-                    0
-                ].tolist(),
-                "plasma_speed": read_numeric_variable(cdf["plasma_speed_profile"])[
-                    0
-                ].tolist(),
+                "proton_density": read_numeric_variable(cdf["proton_density_profile"])[0].tolist(),
+                "plasma_speed": read_numeric_variable(cdf["plasma_speed_profile"])[0].tolist(),
             },
             "solar_wind_ecliptic": {
-                "proton_density": float(
-                    read_numeric_variable(cdf["proton_density_ecliptic"])[0]
-                ),
+                "proton_density": float(read_numeric_variable(cdf["proton_density_ecliptic"])[0]),
                 "alpha_abundance": float(
                     read_numeric_variable(cdf["alpha_abundance_ecliptic"])[0]
                 ),
@@ -62,9 +53,7 @@ def create_glows_l3b_json_file_from_cdf(cdf_file_path: Path):
             },
             "date": cdf["mean_time"][0].isoformat(),
             "CR": cr_number,
-            "uv_anisotropy_factor": read_numeric_variable(cdf["uv_anisotropy_factor"])[
-                0
-            ].tolist(),
+            "uv_anisotropy_factor": read_numeric_variable(cdf["uv_anisotropy_factor"])[0].tolist(),
             "ion_rate_profile": {
                 "lat_grid": read_numeric_variable(cdf["lat_grid"]).tolist(),
                 "ph_rate": read_numeric_variable(cdf["ph_rate"])[0].tolist(),
@@ -95,9 +84,7 @@ def convert_json_to_l3d_data_product(
         parent_file_names=parent_file_names,
         latitude=l3d_json_dict["lat_grid"],
         cr=l3d_json_dict["cr_grid"],
-        epoch=np.array(
-            [datetime.fromisoformat(time) for time in l3d_json_dict["time_grid"]]
-        ),
+        epoch=np.array([datetime.fromisoformat(time) for time in l3d_json_dict["time_grid"]]),
         plasma_speed=l3d_json_dict["solar_params"]["speed"],
         proton_density=l3d_json_dict["solar_params"]["p-dens"],
         ultraviolet_anisotropy=l3d_json_dict["solar_params"]["uv-anis"],
@@ -120,9 +107,7 @@ def get_parent_file_names_from_l3d_json(l3d_folder: Path) -> list[str]:
 
     with open(l3d_folder / l3d_file_paths[0]) as l3d:
         l3d_data = json.load(l3d)
-        ancillary_files = [
-            Path(file).name for file in l3d_data["header"]["ancillary_data_files"]
-        ]
+        ancillary_files = [Path(file).name for file in l3d_data["header"]["ancillary_data_files"]]
         external_dependencies = Path(l3d_data["header"]["external_dependeciens"]).name
         parent_file_names.update(ancillary_files)
         parent_file_names.add(external_dependencies)
@@ -130,12 +115,8 @@ def get_parent_file_names_from_l3d_json(l3d_folder: Path) -> list[str]:
     for file_path in l3d_file_paths:
         with open(l3d_folder / file_path, "r") as l3d:
             l3d_data = json.load(l3d)
-            l3b_parents = [
-                Path(file).name for file in l3d_data["header"]["l3b_input_filename"]
-            ]
-            l3c_parents = [
-                Path(file).name for file in l3d_data["header"]["l3c_input_filename"]
-            ]
+            l3b_parents = [Path(file).name for file in l3d_data["header"]["l3b_input_filename"]]
+            l3c_parents = [Path(file).name for file in l3d_data["header"]["l3c_input_filename"]]
             parent_file_names.update(l3b_parents)
             parent_file_names.update(l3c_parents)
 
@@ -165,7 +146,7 @@ def rename_l3d_text_outputs(paths: list[Path], version: str) -> list[Path]:
     return out_paths
 
 
-def query_for_most_recent_l3d(descriptor: str) -> Optional[dict]:
+def query_for_most_recent_l3d(descriptor: str) -> dict | None:
     query_result = imap_data_access.query(
         instrument="glows", data_level="l3d", descriptor=descriptor
     )
diff --git a/imap_l3_processing/glows/l3e/glows_l3e_dependencies.py b/imap_l3_processing/glows/l3e/glows_l3e_dependencies.py
index 558bb422..27f903b0 100644
--- a/imap_l3_processing/glows/l3e/glows_l3e_dependencies.py
+++ b/imap_l3_processing/glows/l3e/glows_l3e_dependencies.py
@@ -8,7 +8,7 @@
 import imap_data_access
 from imap_data_access.processing_input import ProcessingInputCollection, RepointInput
 
-from imap_l3_processing.utils import furnish_spice_metakernel, SpiceKernelTypes
+from imap_l3_processing.utils import SpiceKernelTypes, furnish_spice_metakernel
 
 logger = logging.getLogger(__name__)
 
@@ -43,21 +43,13 @@ class GlowsL3EDependencies:
 
     @classmethod
     def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
-        lya_series_dependency = dependencies.get_file_paths(
-            source="glows", descriptor="lya"
-        )
+        lya_series_dependency = dependencies.get_file_paths(source="glows", descriptor="lya")
         solar_uv_anisotropy_dependency = dependencies.get_file_paths(
             source="glows", descriptor="uv-anis"
         )
-        speed_3d_dependency = dependencies.get_file_paths(
-            source="glows", descriptor="speed"
-        )
-        density_3d_dependency = dependencies.get_file_paths(
-            source="glows", descriptor="p-dens"
-        )
-        phion_hydrogen_dependency = dependencies.get_file_paths(
-            source="glows", descriptor="phion"
-        )
+        speed_3d_dependency = dependencies.get_file_paths(source="glows", descriptor="speed")
+        density_3d_dependency = dependencies.get_file_paths(source="glows", descriptor="p-dens")
+        phion_hydrogen_dependency = dependencies.get_file_paths(source="glows", descriptor="phion")
         sw_eqtr_electrons_dependency = dependencies.get_file_paths(
             source="glows", descriptor="e-dens"
         )
@@ -66,12 +58,8 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
             source="glows", descriptor="pipeline-settings-l3bcde"
         )
 
-        tess_xyz_dependency = dependencies.get_file_paths(
-            source="glows", descriptor="tess-xyz-8"
-        )
-        tess_ang_dependency = dependencies.get_file_paths(
-            source="glows", descriptor="tess-ang-16"
-        )
+        tess_xyz_dependency = dependencies.get_file_paths(source="glows", descriptor="tess-xyz-8")
+        tess_ang_dependency = dependencies.get_file_paths(source="glows", descriptor="tess-ang-16")
 
         energy_grid_lo_dependency = dependencies.get_file_paths(
             source="glows", descriptor="energy-grid-lo"
@@ -84,35 +72,25 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
         )
 
         lya_series_path = imap_data_access.download(lya_series_dependency[0])
-        solar_uv_anisotropy_path = imap_data_access.download(
-            solar_uv_anisotropy_dependency[0]
-        )
+        solar_uv_anisotropy_path = imap_data_access.download(solar_uv_anisotropy_dependency[0])
         speed_3d_path = imap_data_access.download(speed_3d_dependency[0])
         density_3d_path = imap_data_access.download(density_3d_dependency[0])
         phion_hydrogen_path = imap_data_access.download(phion_hydrogen_dependency[0])
-        sw_eqtr_electrons_path = imap_data_access.download(
-            sw_eqtr_electrons_dependency[0]
-        )
+        sw_eqtr_electrons_path = imap_data_access.download(sw_eqtr_electrons_dependency[0])
 
-        pipeline_settings_path = imap_data_access.download(
-            pipeline_settings_dependency[0]
-        )
+        pipeline_settings_path = imap_data_access.download(pipeline_settings_dependency[0])
 
         tess_xyz_path = imap_data_access.download(tess_xyz_dependency[0])
         tess_ang_path = imap_data_access.download(tess_ang_dependency[0])
 
         energy_grid_lo_path = imap_data_access.download(energy_grid_lo_dependency[0])
         energy_grid_hi_path = imap_data_access.download(energy_grid_hi_dependency[0])
-        energy_grid_ultra_path = imap_data_access.download(
-            energy_grid_ultra_dependency[0]
-        )
+        energy_grid_ultra_path = imap_data_access.download(energy_grid_ultra_dependency[0])
 
         with open(pipeline_settings_path) as f:
             pipeline_settings = json.load(f)
 
-        repoint_file_dependency = dependencies.get_file_paths(
-            data_type=RepointInput.data_type
-        )
+        repoint_file_dependency = dependencies.get_file_paths(data_type=RepointInput.data_type)
         repoint_file_path = imap_data_access.download(repoint_file_dependency[0])
 
         return cls(
@@ -134,9 +112,7 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
 
     @staticmethod
     def collect_spice_dependencies(start_date: datetime, end_date: datetime):
-        logger.info(
-            f"Querying for SPICE data over the range: {start_date} to {end_date}"
-        )
+        logger.info(f"Querying for SPICE data over the range: {start_date} to {end_date}")
 
         kernel_types_with_predicted = GLOWS_L3E_REQUIRED_SPICE_KERNELS
         kernel_types_without_predicted = [
@@ -174,9 +150,7 @@ def copy_dependencies(self):
         if self.energy_grid_ultra is not None:
             shutil.copy(
                 self.energy_grid_ultra,
-                self.pipeline_settings["executable_dependency_paths"][
-                    "energy-grid-ultra"
-                ],
+                self.pipeline_settings["executable_dependency_paths"]["energy-grid-ultra"],
             )
         if self.tess_xyz_8 is not None:
             shutil.copy(
@@ -197,7 +171,7 @@ def copy_dependencies(self):
 
         with open("ionization.files.dat", "w") as ionization_file:
             ionization_file.write(
-                "\n".join(
+                "\n".join(  # noqa: FLY002
                     [
                         self.lya_series.name,
                         self.solar_uv_anisotropy.name,
diff --git a/imap_l3_processing/glows/l3e/glows_l3e_hi_model.py b/imap_l3_processing/glows/l3e/glows_l3e_hi_model.py
index fd0fca95..d779273b 100644
--- a/imap_l3_processing/glows/l3e/glows_l3e_hi_model.py
+++ b/imap_l3_processing/glows/l3e/glows_l3e_hi_model.py
@@ -66,31 +66,23 @@ def convert_dat_to_glows_l3e_hi_product(
             lines = input_data.readlines()
 
             energy_line = [line for line in lines if line.startswith("#energy_grid")]
-            energies = np.array(
-                [float(i) for i in re.findall(r"\d+.\d+", energy_line[0])]
-            )
+            energies = np.array([float(i) for i in re.findall(r"\d+.\d+", energy_line[0])])
 
-            code_version_line = [
-                line for line in lines if line.startswith("# code version")
-            ]
+            code_version_line = [line for line in lines if line.startswith("# code version")]
             code_version = code_version_line[0].split(",")[0][14:].strip()
 
         spin_angle_and_survival_probabilities = np.loadtxt(
             file_path, skiprows=200, dtype=np.float64
         )
         spin_angles = spin_angle_and_survival_probabilities[:, 0]
-        survival_probabilities = np.array(
-            [spin_angle_and_survival_probabilities[:, 1:].T]
-        )
+        survival_probabilities = np.array([spin_angle_and_survival_probabilities[:, 1:].T])
 
         energy_delta_plus, energy_delta_minus = calculate_energy_deltas(energies)
 
         return cls(
             input_metadata,
             epoch=np.array([epoch]),
-            epoch_delta=np.array(
-                [epoch_delta.total_seconds() * ONE_SECOND_IN_NANOSECONDS]
-            ),
+            epoch_delta=np.array([epoch_delta.total_seconds() * ONE_SECOND_IN_NANOSECONDS]),
             energy=energies,
             energy_delta_plus=energy_delta_plus,
             energy_delta_minus=energy_delta_minus,
@@ -102,15 +94,9 @@ def convert_dat_to_glows_l3e_hi_product(
             spacecraft_radius=np.array([args.spacecraft_info.spacecraft_radius]),
             spacecraft_longitude=np.array([args.spacecraft_info.spacecraft_longitude]),
             spacecraft_latitude=np.array([args.spacecraft_info.spacecraft_latitude]),
-            spacecraft_velocity_x=np.array(
-                [args.spacecraft_info.spacecraft_velocity_x]
-            ),
-            spacecraft_velocity_y=np.array(
-                [args.spacecraft_info.spacecraft_velocity_y]
-            ),
-            spacecraft_velocity_z=np.array(
-                [args.spacecraft_info.spacecraft_velocity_z]
-            ),
+            spacecraft_velocity_x=np.array([args.spacecraft_info.spacecraft_velocity_x]),
+            spacecraft_velocity_y=np.array([args.spacecraft_info.spacecraft_velocity_y]),
+            spacecraft_velocity_z=np.array([args.spacecraft_info.spacecraft_velocity_z]),
             elongation=np.array([args.elongation]),
             glows_flags=np.array([0], dtype=np.uint16),
         )
@@ -125,9 +111,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(ENERGY_DELTA_PLUS_VAR_NAME, self.energy_delta_plus),
             DataProductVariable(ENERGY_DELTA_MINUS_VAR_NAME, self.energy_delta_minus),
             DataProductVariable(SPIN_ANGLE_VAR_NAME, self.spin_angle),
-            DataProductVariable(
-                PROBABILITY_OF_SURVIVAL_VAR_NAME, self.probability_of_survival
-            ),
+            DataProductVariable(PROBABILITY_OF_SURVIVAL_VAR_NAME, self.probability_of_survival),
             DataProductVariable(ENERGY_LABEL_VAR_NAME, energy_labels),
             DataProductVariable(SPIN_ANGLE_LABEL_VAR_NAME, spin_angle_labels),
             DataProductVariable(SPIN_AXIS_LATITUDE_VAR_NAME, self.spin_axis_lat),
@@ -135,18 +119,10 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(PROGRAM_VERSION_VAR_NAME, self.program_version),
             DataProductVariable(SPACECRAFT_RADIUS_VAR_NAME, self.spacecraft_radius),
             DataProductVariable(SPACECRAFT_LATITUDE_VAR_NAME, self.spacecraft_latitude),
-            DataProductVariable(
-                SPACECRAFT_LONGITUDE_VAR_NAME, self.spacecraft_longitude
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_X_VAR_NAME, self.spacecraft_velocity_x
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_Y_VAR_NAME, self.spacecraft_velocity_y
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_Z_VAR_NAME, self.spacecraft_velocity_z
-            ),
+            DataProductVariable(SPACECRAFT_LONGITUDE_VAR_NAME, self.spacecraft_longitude),
+            DataProductVariable(SPACECRAFT_VELOCITY_X_VAR_NAME, self.spacecraft_velocity_x),
+            DataProductVariable(SPACECRAFT_VELOCITY_Y_VAR_NAME, self.spacecraft_velocity_y),
+            DataProductVariable(SPACECRAFT_VELOCITY_Z_VAR_NAME, self.spacecraft_velocity_z),
             DataProductVariable(ELONGATION, self.elongation),
             DataProductVariable(GLOWS_FLAGS_VAR_NAME, self.glows_flags),
         ]
diff --git a/imap_l3_processing/glows/l3e/glows_l3e_initializer.py b/imap_l3_processing/glows/l3e/glows_l3e_initializer.py
index 37ff090b..24c06c18 100644
--- a/imap_l3_processing/glows/l3e/glows_l3e_initializer.py
+++ b/imap_l3_processing/glows/l3e/glows_l3e_initializer.py
@@ -3,30 +3,29 @@
 import logging
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional
 
 import imap_data_access
 import numpy as np
 from imap_data_access import (
-    ProcessingInputCollection,
     AncillaryInput,
-    ScienceInput,
+    ProcessingInputCollection,
     RepointInput,
+    ScienceInput,
 )
 from imap_data_access.file_validation import Version
 from imap_processing.spice.repoint import (
-    set_global_repoint_table_paths,
     get_repoint_data,
+    set_global_repoint_table_paths,
 )
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.glows.descriptors import (
     GLOWS_L3E_DESCRIPTORS,
-    GLOWS_L3E_HI_90_DESCRIPTOR,
     GLOWS_L3E_HI_45_DESCRIPTOR,
+    GLOWS_L3E_HI_90_DESCRIPTOR,
     GLOWS_L3E_LO_DESCRIPTOR,
-    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
     GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3bc.utils import get_pointing_date_range
 from imap_l3_processing.glows.l3d.models import GlowsL3DProcessorOutput
@@ -56,11 +55,11 @@ class GlowsL3EInitializer:
     @staticmethod
     def get_repointings_to_process(
         l3d_output: GlowsL3DProcessorOutput,
-        previous_l3d: Optional[str],
+        previous_l3d: str | None,
         repointing_file_path: Path,
         version_map: VersionMap,
         reprocess_info: ReprocessInfo,
-    ) -> Optional[GlowsL3EInitializerOutput]:
+    ) -> GlowsL3EInitializerOutput | None:
         pipeline_settings_l3bcde = get_most_recently_uploaded_ancillary(
             imap_data_access.query(
                 table="ancillary",
@@ -74,9 +73,7 @@ def get_repointings_to_process(
             )
         )
         tess_xyz_8 = get_most_recently_uploaded_ancillary(
-            imap_data_access.query(
-                table="ancillary", instrument="glows", descriptor="tess-xyz-8"
-            )
+            imap_data_access.query(table="ancillary", instrument="glows", descriptor="tess-xyz-8")
         )
         energy_grid_hi = get_most_recently_uploaded_ancillary(
             imap_data_access.query(
@@ -89,9 +86,7 @@ def get_repointings_to_process(
             )
         )
         tess_ang_16 = get_most_recently_uploaded_ancillary(
-            imap_data_access.query(
-                table="ancillary", instrument="glows", descriptor="tess-ang-16"
-            )
+            imap_data_access.query(table="ancillary", instrument="glows", descriptor="tess-ang-16")
         )
 
         processing_input_collection = ProcessingInputCollection(
@@ -113,9 +108,7 @@ def get_repointings_to_process(
 
         first_updated_cr = first_cr
         if previous_l3d is not None:
-            first_updated_cr = find_first_updated_cr(
-                l3d_output.l3d_cdf_file_path, previous_l3d
-            )
+            first_updated_cr = find_first_updated_cr(l3d_output.l3d_cdf_file_path, previous_l3d)
             if first_updated_cr is not None:
                 first_updated_cr -= 1
 
@@ -158,11 +151,11 @@ def query_existing_l3es_versions(descriptor: str) -> dict[int, Version]:
         instrument="glows", data_level="l3e", version="latest", descriptor=descriptor
     )
     for l3e in l3e_files:
-        if "major_version" in l3e.keys() and "minor_version" in l3e.keys():
+        if "major_version" in l3e and "minor_version" in l3e:
             existing_l3es_for_descriptor[int(l3e["repointing"])] = Version(
                 l3e["major_version"], l3e["minor_version"]
             )
-        elif "version" in l3e.keys():
+        elif "version" in l3e:
             existing_l3es_for_descriptor[int(l3e["repointing"])] = Version.from_version(
                 l3e["version"]
             )
@@ -174,7 +167,7 @@ def query_existing_l3es_versions(descriptor: str) -> dict[int, Version]:
 def identify_versions_for_l3e_output_files(
     start_cr_of_mission: int,
     end_cr_of_mission: int,
-    first_updated_cr_from_l3d: Optional[int],
+    first_updated_cr_from_l3d: int | None,
     repointing_path: Path,
     version_map: VersionMap,
     reprocess_info: ReprocessInfo,
@@ -247,16 +240,14 @@ def find_out_of_date_l3es(
     return out_of_date_l3es
 
 
-def find_first_updated_cr(new_l3d: Path, old_l3d: str) -> Optional[int]:
+def find_first_updated_cr(new_l3d: Path, old_l3d: str) -> int | None:
     downloaded_old_l3d = imap_data_access.download(old_l3d)
 
     old_l3d_cdf = CDF(str(downloaded_old_l3d))
     new_l3d_cdf = CDF(str(new_l3d))
 
     for i, cr in enumerate(old_l3d_cdf["cr_grid"][...]):
-        lya_matches = np.isclose(
-            old_l3d_cdf["lyman_alpha"][i], new_l3d_cdf["lyman_alpha"][i]
-        )
+        lya_matches = np.isclose(old_l3d_cdf["lyman_alpha"][i], new_l3d_cdf["lyman_alpha"][i])
         phion_matches = np.isclose(old_l3d_cdf["phion"][i], new_l3d_cdf["phion"][i])
         plasma_speed_flag_matches = np.isclose(
             old_l3d_cdf["plasma_speed_flag"][i], new_l3d_cdf["plasma_speed_flag"][i]
@@ -275,9 +266,7 @@ def find_first_updated_cr(new_l3d: Path, old_l3d: str) -> Optional[int]:
             np.isclose(old_l3d_cdf["plasma_speed"][i], new_l3d_cdf["plasma_speed"][i])
         )
         proton_density_matches = np.all(
-            np.isclose(
-                old_l3d_cdf["proton_density"][i], new_l3d_cdf["proton_density"][i]
-            )
+            np.isclose(old_l3d_cdf["proton_density"][i], new_l3d_cdf["proton_density"][i])
         )
         uv_anisotropy_matches = np.all(
             np.isclose(old_l3d_cdf["uv_anisotropy"][i], new_l3d_cdf["uv_anisotropy"][i])
diff --git a/imap_l3_processing/glows/l3e/glows_l3e_lo_model.py b/imap_l3_processing/glows/l3e/glows_l3e_lo_model.py
index 9cf9515a..257f9ff9 100644
--- a/imap_l3_processing/glows/l3e/glows_l3e_lo_model.py
+++ b/imap_l3_processing/glows/l3e/glows_l3e_lo_model.py
@@ -67,31 +67,23 @@ def convert_dat_to_glows_l3e_lo_product(
             lines = input_data.readlines()
 
             energy_line = [line for line in lines if line.startswith("#energy_grid")]
-            energies = np.array(
-                [float(i) for i in re.findall(r"\d+.\d+", energy_line[0])]
-            )
+            energies = np.array([float(i) for i in re.findall(r"\d+.\d+", energy_line[0])])
 
-            code_version_line = [
-                line for line in lines if line.startswith("# code version")
-            ]
+            code_version_line = [line for line in lines if line.startswith("# code version")]
             code_version = code_version_line[0].split(",")[0][14:].strip()
 
         spin_angle_and_survival_probabilities = np.loadtxt(
             file_path, skiprows=200, dtype=np.float64
         )
         spin_angles = spin_angle_and_survival_probabilities[:, 0]
-        survival_probabilities = np.array(
-            [spin_angle_and_survival_probabilities[:, 1:].T]
-        )
+        survival_probabilities = np.array([spin_angle_and_survival_probabilities[:, 1:].T])
 
         energy_delta_plus, energy_delta_minus = calculate_energy_deltas(energies)
 
         return cls(
             input_metadata=input_metadata,
             epoch=np.array([epoch]),
-            epoch_delta=np.array(
-                [epoch_delta.total_seconds() * ONE_SECOND_IN_NANOSECONDS]
-            ),
+            epoch_delta=np.array([epoch_delta.total_seconds() * ONE_SECOND_IN_NANOSECONDS]),
             energy=energies,
             energy_delta_plus=energy_delta_plus,
             energy_delta_minus=energy_delta_minus,
@@ -104,15 +96,9 @@ def convert_dat_to_glows_l3e_lo_product(
             spacecraft_radius=np.array([args.spacecraft_info.spacecraft_radius]),
             spacecraft_longitude=np.array([args.spacecraft_info.spacecraft_longitude]),
             spacecraft_latitude=np.array([args.spacecraft_info.spacecraft_latitude]),
-            spacecraft_velocity_x=np.array(
-                [args.spacecraft_info.spacecraft_velocity_x]
-            ),
-            spacecraft_velocity_y=np.array(
-                [args.spacecraft_info.spacecraft_velocity_y]
-            ),
-            spacecraft_velocity_z=np.array(
-                [args.spacecraft_info.spacecraft_velocity_z]
-            ),
+            spacecraft_velocity_x=np.array([args.spacecraft_info.spacecraft_velocity_x]),
+            spacecraft_velocity_y=np.array([args.spacecraft_info.spacecraft_velocity_y]),
+            spacecraft_velocity_z=np.array([args.spacecraft_info.spacecraft_velocity_z]),
             glows_flags=np.array([0], dtype=np.uint16),
         )
 
@@ -127,9 +113,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(ENERGY_DELTA_PLUS_VAR_NAME, self.energy_delta_plus),
             DataProductVariable(ENERGY_DELTA_MINUS_VAR_NAME, self.energy_delta_minus),
             DataProductVariable(SPIN_ANGLE_VAR_NAME, self.spin_angle),
-            DataProductVariable(
-                PROBABILITY_OF_SURVIVAL_VAR_NAME, self.probability_of_survival
-            ),
+            DataProductVariable(PROBABILITY_OF_SURVIVAL_VAR_NAME, self.probability_of_survival),
             DataProductVariable(ENERGY_LABEL_VAR_NAME, energy_labels),
             DataProductVariable(SPIN_ANGLE_LABEL_VAR_NAME, spin_angle_labels),
             DataProductVariable(ELONGATION_VAR_NAME, self.elongation),
@@ -138,17 +122,9 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(PROGRAM_VERSION_VAR_NAME, self.program_version),
             DataProductVariable(SPACECRAFT_RADIUS_VAR_NAME, self.spacecraft_radius),
             DataProductVariable(SPACECRAFT_LATITUDE_VAR_NAME, self.spacecraft_latitude),
-            DataProductVariable(
-                SPACECRAFT_LONGITUDE_VAR_NAME, self.spacecraft_longitude
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_X_VAR_NAME, self.spacecraft_velocity_x
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_Y_VAR_NAME, self.spacecraft_velocity_y
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_Z_VAR_NAME, self.spacecraft_velocity_z
-            ),
+            DataProductVariable(SPACECRAFT_LONGITUDE_VAR_NAME, self.spacecraft_longitude),
+            DataProductVariable(SPACECRAFT_VELOCITY_X_VAR_NAME, self.spacecraft_velocity_x),
+            DataProductVariable(SPACECRAFT_VELOCITY_Y_VAR_NAME, self.spacecraft_velocity_y),
+            DataProductVariable(SPACECRAFT_VELOCITY_Z_VAR_NAME, self.spacecraft_velocity_z),
             DataProductVariable(GLOWS_FLAGS_VAR_NAME, self.glows_flags),
         ]
diff --git a/imap_l3_processing/glows/l3e/glows_l3e_ultra_model.py b/imap_l3_processing/glows/l3e/glows_l3e_ultra_model.py
index 7eef9be5..f433c242 100644
--- a/imap_l3_processing/glows/l3e/glows_l3e_ultra_model.py
+++ b/imap_l3_processing/glows/l3e/glows_l3e_ultra_model.py
@@ -70,13 +70,9 @@ def convert_dat_to_glows_l3e_ul_product(
             lines = input_data.readlines()
 
             energy_line = [line for line in lines if line.startswith("#energy_grid")]
-            energies = np.array(
-                [float(i) for i in re.findall(r"\d+.\d+", energy_line[0])]
-            )
+            energies = np.array([float(i) for i in re.findall(r"\d+.\d+", energy_line[0])])
 
-            code_version_line = [
-                line for line in lines if line.startswith("# code version")
-            ]
+            code_version_line = [line for line in lines if line.startswith("# code version")]
             code_version = code_version_line[0].split(",")[0][14:].strip()
 
         data_table = np.loadtxt(file_path, skiprows=200, dtype=np.float64)
@@ -108,9 +104,7 @@ def convert_dat_to_glows_l3e_ul_product(
         return cls(
             input_metadata,
             epoch=np.array([epoch]),
-            epoch_delta=np.array(
-                [epoch_delta.total_seconds() * ONE_SECOND_IN_NANOSECONDS]
-            ),
+            epoch_delta=np.array([epoch_delta.total_seconds() * ONE_SECOND_IN_NANOSECONDS]),
             energy=energies,
             energy_delta_plus=energy_delta_plus,
             energy_delta_minus=energy_delta_minus,
@@ -122,15 +116,9 @@ def convert_dat_to_glows_l3e_ul_product(
             spacecraft_radius=np.array([args.spacecraft_info.spacecraft_radius]),
             spacecraft_longitude=np.array([args.spacecraft_info.spacecraft_longitude]),
             spacecraft_latitude=np.array([args.spacecraft_info.spacecraft_latitude]),
-            spacecraft_velocity_x=np.array(
-                [args.spacecraft_info.spacecraft_velocity_x]
-            ),
-            spacecraft_velocity_y=np.array(
-                [args.spacecraft_info.spacecraft_velocity_y]
-            ),
-            spacecraft_velocity_z=np.array(
-                [args.spacecraft_info.spacecraft_velocity_z]
-            ),
+            spacecraft_velocity_x=np.array([args.spacecraft_info.spacecraft_velocity_x]),
+            spacecraft_velocity_y=np.array([args.spacecraft_info.spacecraft_velocity_y]),
+            spacecraft_velocity_z=np.array([args.spacecraft_info.spacecraft_velocity_z]),
             elongation_excluded=np.array([args.elongation]),
             pixel_latitude=np.array([pixel_latitude_to_return]),
             pixel_longitude=np.array([pixel_longitude_to_return]),
@@ -147,9 +135,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(ENERGY_DELTA_PLUS_VAR_NAME, self.energy_delta_plus),
             DataProductVariable(ENERGY_DELTA_MINUS_VAR_NAME, self.energy_delta_minus),
             DataProductVariable(HEALPIX_INDEX_VAR_NAME, self.healpix_index),
-            DataProductVariable(
-                PROBABILITY_OF_SURVIVAL_VAR_NAME, self.probability_of_survival
-            ),
+            DataProductVariable(PROBABILITY_OF_SURVIVAL_VAR_NAME, self.probability_of_survival),
             DataProductVariable(ENERGY_LABEL_VAR_NAME, energy_labels),
             DataProductVariable(PIXEL_INDEX_LABEL_VAR_NAME, pixel_labels),
             DataProductVariable(SPIN_AXIS_LATITUDE_VAR_NAME, self.spin_axis_lat),
@@ -157,18 +143,10 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(PROGRAM_VERSION_VAR_NAME, self.program_version),
             DataProductVariable(SPACECRAFT_RADIUS_VAR_NAME, self.spacecraft_radius),
             DataProductVariable(SPACECRAFT_LATITUDE_VAR_NAME, self.spacecraft_latitude),
-            DataProductVariable(
-                SPACECRAFT_LONGITUDE_VAR_NAME, self.spacecraft_longitude
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_X_VAR_NAME, self.spacecraft_velocity_x
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_Y_VAR_NAME, self.spacecraft_velocity_y
-            ),
-            DataProductVariable(
-                SPACECRAFT_VELOCITY_Z_VAR_NAME, self.spacecraft_velocity_z
-            ),
+            DataProductVariable(SPACECRAFT_LONGITUDE_VAR_NAME, self.spacecraft_longitude),
+            DataProductVariable(SPACECRAFT_VELOCITY_X_VAR_NAME, self.spacecraft_velocity_x),
+            DataProductVariable(SPACECRAFT_VELOCITY_Y_VAR_NAME, self.spacecraft_velocity_y),
+            DataProductVariable(SPACECRAFT_VELOCITY_Z_VAR_NAME, self.spacecraft_velocity_z),
             DataProductVariable(ELONGATION_EXCLUDED_VAR_NAME, self.elongation_excluded),
             DataProductVariable(PIXEL_LATITUDE_VAR_NAME, self.pixel_latitude),
             DataProductVariable(PIXEL_LONGITUDE_VAR_NAME, self.pixel_longitude),
diff --git a/imap_l3_processing/glows/l3e/glows_l3e_utils.py b/imap_l3_processing/glows/l3e/glows_l3e_utils.py
index 890f651a..6327e87a 100644
--- a/imap_l3_processing/glows/l3e/glows_l3e_utils.py
+++ b/imap_l3_processing/glows/l3e/glows_l3e_utils.py
@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import typing
 from dataclasses import dataclass
 from datetime import datetime, timedelta
 from pathlib import Path
@@ -9,29 +8,23 @@
 import numpy as np
 import spiceypy
 from astropy.time import Time
-from spiceypy import SpiceyError
-
-from imap_l3_processing.glows.quality_flags import GlowsL3Flags
 from imap_data_access.file_validation import Version
 from spacepy.pycdf import CDF
-
-from typing import Optional
+from spiceypy import SpiceyError
 
 from imap_l3_processing.constants import (
     ONE_AU_IN_KM,
-    TT2000_EPOCH,
     ONE_SECOND_IN_NANOSECONDS,
+    TT2000_EPOCH,
 )
 from imap_l3_processing.glows.l3bc.l3bc_toolkit.funcs import jd_fm_Carrington
 from imap_l3_processing.glows.l3e.glows_l3e_call_arguments import (
     GlowsL3eCallArguments,
     GlowsL3eSpacecraftInfo,
 )
+from imap_l3_processing.glows.quality_flags import GlowsL3Flags
 from imap_l3_processing.utils import FurnishMetakernelOutput
 
-if typing.TYPE_CHECKING:
-    pass
-
 
 def determine_call_args_for_l3e_executable(
     start_date: datetime,
@@ -55,9 +48,7 @@ def determine_spacecraft_info_for_l3e_executable(
 ) -> GlowsL3eSpacecraftInfo:
     ephemeris_time = spiceypy.datetime2et(repointing_midpoint)
 
-    [x, y, z, vx, vy, vz], _ = spiceypy.spkezr(
-        "IMAP", ephemeris_time, "ECLIPJ2000", "NONE", "SUN"
-    )
+    [x, y, z, vx, vy, vz], _ = spiceypy.spkezr("IMAP", ephemeris_time, "ECLIPJ2000", "NONE", "SUN")
 
     radius, longitude, latitude = spiceypy.reclat([x, y, z])
 
@@ -85,16 +76,16 @@ def determine_spacecraft_info_using_predict_if_needed(
 ) -> tuple[GlowsL3eSpacecraftInfo, GlowsL3Flags, list[str]]:
     try:
         with spiceypy.KernelPool([str(spice_without_predict.metakernel_path)]):
-            spacecraft_info: GlowsL3eSpacecraftInfo = (
-                determine_spacecraft_info_for_l3e_executable(repointing_midpoint)
+            spacecraft_info: GlowsL3eSpacecraftInfo = determine_spacecraft_info_for_l3e_executable(
+                repointing_midpoint
             )
 
             glows_l3_flags: GlowsL3Flags = GlowsL3Flags.NONE
             kernel_names = [n.name for n in spice_without_predict.spice_kernel_paths]
     except SpiceyError:
         with spiceypy.KernelPool([str(spice_with_predict.metakernel_path)]):
-            spacecraft_info: GlowsL3eSpacecraftInfo = (
-                determine_spacecraft_info_for_l3e_executable(repointing_midpoint)
+            spacecraft_info: GlowsL3eSpacecraftInfo = determine_spacecraft_info_for_l3e_executable(
+                repointing_midpoint
             )
 
             glows_l3_flags: GlowsL3Flags = GlowsL3Flags.PREDICTIVE_EPHEMERIS
@@ -106,7 +97,7 @@ def determine_spacecraft_info_using_predict_if_needed(
 def _decimal_time(t: datetime) -> str:
     year_start = datetime(t.year, 1, 1)
     year_end = datetime(t.year + 1, 1, 1)
-    return "{:10.5f}".format(t.year + (t - year_start) / (year_end - year_start))
+    return f"{t.year + (t - year_start) / (year_end - year_start):10.5f}"
 
 
 @dataclass
@@ -119,9 +110,7 @@ class GlowsL3eVersionsForRepointings:
     ultra_hf_repointings: dict[int, Version]
 
 
-def compute_glows_flags_for_repoint(
-    l3d_cdf_path: Path, repoint_midpoint: datetime
-) -> int:
+def compute_glows_flags_for_repoint(l3d_cdf_path: Path, repoint_midpoint: datetime) -> int:
     with CDF(str(l3d_cdf_path)) as cdf:
         cr_epochs = cdf["epoch"][...]
         flags = cdf["glows_flags"][...]
@@ -159,7 +148,7 @@ def get_lo_pivot_angle_from_l1b_file(path: Path) -> float:
 
 @dataclass
 class LoPivotAngle:
-    parent_filename: Optional[str]
+    parent_filename: str | None
     pivot_angle: float
 
 
@@ -189,9 +178,7 @@ def get_repoint_numbers_within_cr_window(
 ) -> set[int]:
     if start_cr_number is None:
         return set()
-    first_carrington_start_date = Time(
-        jd_fm_Carrington(float(start_cr_number)), format="jd"
-    )
+    first_carrington_start_date = Time(jd_fm_Carrington(float(start_cr_number)), format="jd")
     last_cr_end_date = Time(jd_fm_Carrington(float(end_cr_number + 0.5)), format="jd")
 
     start_ns = (
@@ -204,8 +191,7 @@ def get_repoint_numbers_within_cr_window(
     vectorized_date_conv = np.vectorize(
         lambda d: (
             (
-                Time(d, format="iso").to_datetime(leap_second_strict="silent")
-                - TT2000_EPOCH
+                Time(d, format="iso").to_datetime(leap_second_strict="silent") - TT2000_EPOCH
             ).total_seconds()
             * ONE_SECOND_IN_NANOSECONDS
         )
diff --git a/imap_l3_processing/glows/l3e/reprocess_info.py b/imap_l3_processing/glows/l3e/reprocess_info.py
index 20c27421..f6be3a30 100644
--- a/imap_l3_processing/glows/l3e/reprocess_info.py
+++ b/imap_l3_processing/glows/l3e/reprocess_info.py
@@ -50,9 +50,7 @@ def parse_from_ancillary(cls, path_to_ancillary: Path) -> ReprocessInfo:
 
     @staticmethod
     def _parse_header(line: str) -> datetime:
-        ignore_after = datetime.fromisoformat(
-            line.removeprefix(IGNORE_AFTER_PREFIX).strip()
-        )
+        ignore_after = datetime.fromisoformat(line.removeprefix(IGNORE_AFTER_PREFIX).strip())
         if ignore_after.tzinfo is None:
             ignore_after = ignore_after.replace(tzinfo=timezone.utc)
         return ignore_after
@@ -78,9 +76,7 @@ def _parse_line(line: str) -> tuple[str, str, ReprocessTargets]:
 
     def should_reprocess_l3d(self) -> bool:
         return GLOWS_L3D_DESCRIPTOR in self.products_to_reprocess or any(
-            set(self.products_to_reprocess.keys()).intersection(
-                set(GLOWS_L3E_DESCRIPTORS)
-            )
+            set(self.products_to_reprocess.keys()).intersection(set(GLOWS_L3E_DESCRIPTORS))
         )
 
     def get_repoints_for_descriptor(self, descriptor: str, repointing_data) -> set[int]:
@@ -91,9 +87,7 @@ def get_repoints_for_descriptor(self, descriptor: str, repointing_data) -> set[i
         repoints = set(reprocess_targets.repoints)
 
         for cr in reprocess_targets.carrington_rotations:
-            repoints.update(
-                get_repoint_numbers_within_cr_window(cr, cr, repointing_data)
-            )
+            repoints.update(get_repoint_numbers_within_cr_window(cr, cr, repointing_data))
 
         return repoints
 
@@ -102,7 +96,5 @@ def fetch_reprocess_info(input_collection: ProcessingInputCollection) -> Reproce
     [reprocessing_file_path] = input_collection.get_file_paths(
         source="glows", descriptor=GLOWS_REPROCESSING_DESCRIPTOR
     )
-    path_to_downloaded_ancillary = imap_data_access.download(
-        reprocessing_file_path.name
-    )
+    path_to_downloaded_ancillary = imap_data_access.download(reprocessing_file_path.name)
     return ReprocessInfo.parse_from_ancillary(path_to_downloaded_ancillary)
diff --git a/imap_l3_processing/glows/quality_flags.py b/imap_l3_processing/glows/quality_flags.py
index f6350739..c8f4e639 100644
--- a/imap_l3_processing/glows/quality_flags.py
+++ b/imap_l3_processing/glows/quality_flags.py
@@ -1,6 +1,5 @@
 from imap_processing.quality_flags import CommonFlags, FlagNameMixin
 
-
 NOMINAL_ALPHA_PROTON_RATIO_VALUE: float = 0.04
 
 
diff --git a/imap_l3_processing/hi/hi_combined_initializer.py b/imap_l3_processing/hi/hi_combined_initializer.py
index 6c890071..69b62790 100644
--- a/imap_l3_processing/hi/hi_combined_initializer.py
+++ b/imap_l3_processing/hi/hi_combined_initializer.py
@@ -7,12 +7,12 @@
 
 from imap_l3_processing.maps.map_descriptors import (
     MapDescriptorParts,
-    parse_map_descriptor,
     Sensor,
-    map_descriptor_parts_to_string,
     SpinPhase,
+    map_descriptor_parts_to_string,
+    parse_map_descriptor,
 )
-from imap_l3_processing.maps.map_initializer import PossibleMapToProduce, MapInitializer
+from imap_l3_processing.maps.map_initializer import MapInitializer, PossibleMapToProduce
 from imap_l3_processing.models import InputMetadata, VersionMap
 
 HI_COMBINED_DESCRIPTORS = [
@@ -33,8 +33,8 @@ def __init__(self, canonical_map_start_date: datetime = datetime(2026, 1, 1)):
         super().__init__("hi")
 
         l2_query_results = imap_data_access.query(instrument="hi", data_level="l2")
-        l2_by_descriptor_and_start_date = (
-            self.get_latest_version_by_descriptor_and_start_date(l2_query_results)
+        l2_by_descriptor_and_start_date = self.get_latest_version_by_descriptor_and_start_date(
+            l2_query_results
         )
         self.input_maps = dict(self.existing_l3_maps, **l2_by_descriptor_and_start_date)
         self.canonical_map_start_date = canonical_map_start_date
@@ -42,21 +42,15 @@ def __init__(self, canonical_map_start_date: datetime = datetime(2026, 1, 1)):
     def furnish_spice_dependencies(self, map_to_produce: PossibleMapToProduce):
         pass
 
-    def get_maps_that_can_be_produced(
-        self, input_descriptor: str
-    ) -> list[PossibleMapToProduce]:
+    def get_maps_that_can_be_produced(self, input_descriptor: str) -> list[PossibleMapToProduce]:
         possible_maps_to_produce = []
         map_descriptor: MapDescriptorParts = parse_map_descriptor(input_descriptor)
 
         hi90_ram_descriptor = map_descriptor_parts_to_string(
-            dataclasses.replace(
-                map_descriptor, sensor=Sensor.Hi90, spin_phase=SpinPhase.RamOnly
-            )
+            dataclasses.replace(map_descriptor, sensor=Sensor.Hi90, spin_phase=SpinPhase.RamOnly)
         )
         hi45_ram_descriptor = map_descriptor_parts_to_string(
-            dataclasses.replace(
-                map_descriptor, sensor=Sensor.Hi45, spin_phase=SpinPhase.RamOnly
-            )
+            dataclasses.replace(map_descriptor, sensor=Sensor.Hi45, spin_phase=SpinPhase.RamOnly)
         )
 
         hi90_anti_descriptor = map_descriptor_parts_to_string(
diff --git a/imap_l3_processing/hi/hi_combined_sensor_dependencies.py b/imap_l3_processing/hi/hi_combined_sensor_dependencies.py
index 2992d05c..5176a13f 100644
--- a/imap_l3_processing/hi/hi_combined_sensor_dependencies.py
+++ b/imap_l3_processing/hi/hi_combined_sensor_dependencies.py
@@ -21,15 +21,12 @@ def fetch_dependencies(
         input_map_filenames = dependencies.get_file_paths(source="hi")
 
         map_files = [
-            imap_data_access.download(input_map.name)
-            for input_map in input_map_filenames
+            imap_data_access.download(input_map.name) for input_map in input_map_filenames
         ]
         return cls.from_file_paths(map_files)
 
     @classmethod
-    def from_file_paths(
-        cls, hi_l3_map_paths: list[Path]
-    ) -> HiL3CombinedMapDependencies:
+    def from_file_paths(cls, hi_l3_map_paths: list[Path]) -> HiL3CombinedMapDependencies:
         return cls(
             [
                 RectangularIntensityMapData.read_from_path(path)
diff --git a/imap_l3_processing/hi/hi_processor.py b/imap_l3_processing/hi/hi_processor.py
index 9436f5fc..e9235796 100644
--- a/imap_l3_processing/hi/hi_processor.py
+++ b/imap_l3_processing/hi/hi_processor.py
@@ -1,5 +1,4 @@
 from pathlib import Path
-from typing import Optional
 
 from imap_processing.spice.geometry import SpiceFrame
 
@@ -10,29 +9,29 @@
     HiSpectralIndexDependencies,
 )
 from imap_l3_processing.maps.hilo_l3_survival_dependencies import (
-    HiLoL3SurvivalDependencies,
     HiL3SingleSensorFullSpinDependencies,
+    HiLoL3SurvivalDependencies,
 )
 from imap_l3_processing.maps.map_combination import (
-    UncertaintyWeightedCombination,
-    UnweightedCombination,
     CombinationStrategy,
     ExposureWeightedCombination,
+    UncertaintyWeightedCombination,
+    UnweightedCombination,
 )
 from imap_l3_processing.maps.map_descriptors import (
-    parse_map_descriptor,
-    MapQuantity,
     MapDescriptorParts,
-    SurvivalCorrection,
-    SpinPhase,
-    Sensor,
+    MapQuantity,
     ReferenceFrame,
+    Sensor,
+    SpinPhase,
+    SurvivalCorrection,
+    parse_map_descriptor,
 )
 from imap_l3_processing.maps.map_models import (
+    RectangularIntensityDataProduct,
+    RectangularIntensityMapData,
     RectangularSpectralIndexDataProduct,
     RectangularSpectralIndexMapData,
-    RectangularIntensityMapData,
-    RectangularIntensityDataProduct,
 )
 from imap_l3_processing.maps.map_processor import MapProcessor
 from imap_l3_processing.maps.spectral_fit import (
@@ -47,16 +46,14 @@
 
 
 class HiProcessor(MapProcessor):
-    def process(
-        self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000
-    ) -> list[Path]:
+    def process(self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000) -> list[Path]:
         set_of_parent_file_names = set(self.get_parent_file_names())
 
         parsed_descriptor = parse_map_descriptor(self.input_metadata.descriptor)
         match parsed_descriptor:
             case MapDescriptorParts(quantity=MapQuantity.SpectralIndex):
-                hi_l3_spectral_fit_dependencies = (
-                    HiSpectralIndexDependencies.fetch_dependencies(self.dependencies)
+                hi_l3_spectral_fit_dependencies = HiSpectralIndexDependencies.fetch_dependencies(
+                    self.dependencies
                 )
                 map_data = self.process_spectral_fit_index(
                     hi_l3_spectral_fit_dependencies,
@@ -85,8 +82,7 @@ def process(
                     spice_frame_name=spice_frame_name,
                 )
                 set_of_parent_file_names.update(
-                    p.name
-                    for p in hi_l3_survival_probabilities_dependencies.dependency_file_paths
+                    p.name for p in hi_l3_survival_probabilities_dependencies.dependency_file_paths
                 )
             case MapDescriptorParts(
                 survival_correction=SurvivalCorrection.SurvivalCorrected,
@@ -95,9 +91,7 @@ def process(
                 reference_frame=ReferenceFrame.Spacecraft,
             ):
                 hi_l3_full_spin_dependencies = (
-                    HiL3SingleSensorFullSpinDependencies.fetch_dependencies(
-                        self.dependencies
-                    )
+                    HiL3SingleSensorFullSpinDependencies.fetch_dependencies(self.dependencies)
                 )
                 combination_strategy = UnweightedCombination()
                 combined_map = self.process_full_spin_single_sensor(
@@ -118,9 +112,7 @@ def process(
                 reference_frame=ReferenceFrame.Heliospheric,
             ):
                 hi_l3_full_spin_cg_corrected_dependencies = (
-                    HiL3SingleSensorFullSpinDependencies.fetch_dependencies(
-                        self.dependencies
-                    )
+                    HiL3SingleSensorFullSpinDependencies.fetch_dependencies(self.dependencies)
                 )
 
                 combination_strategy = UncertaintyWeightedCombination()
@@ -135,18 +127,22 @@ def process(
                     spice_frame_name=spice_frame_name,
                 )
             case MapDescriptorParts(sensor=Sensor.HiCombined):
-                dependencies = HiL3CombinedMapDependencies.fetch_dependencies(
-                    self.dependencies
-                )
-                h45_full_spin_12mo = UncertaintyWeightedCombination().combine_rectangular_intensity_map_data(
-                    dependencies.h45_maps
+                dependencies = HiL3CombinedMapDependencies.fetch_dependencies(self.dependencies)
+                h45_full_spin_12mo = (
+                    UncertaintyWeightedCombination().combine_rectangular_intensity_map_data(
+                        dependencies.h45_maps
+                    )
                 )
-                h90_full_spin_12mo = UncertaintyWeightedCombination().combine_rectangular_intensity_map_data(
-                    dependencies.h90_maps
+                h90_full_spin_12mo = (
+                    UncertaintyWeightedCombination().combine_rectangular_intensity_map_data(
+                        dependencies.h90_maps
+                    )
                 )
 
-                combined_map_data = ExposureWeightedCombination().combine_rectangular_intensity_map_data(
-                    [h45_full_spin_12mo, h90_full_spin_12mo]
+                combined_map_data = (
+                    ExposureWeightedCombination().combine_rectangular_intensity_map_data(
+                        [h45_full_spin_12mo, h90_full_spin_12mo]
+                    )
                 )
 
                 data_product = RectangularIntensityDataProduct(
@@ -155,9 +151,7 @@ def process(
                     spice_frame_name=spice_frame_name,
                 )
             case None:
-                raise ValueError(
-                    f"Could not parse descriptor {self.input_metadata.descriptor}"
-                )
+                raise ValueError(f"Could not parse descriptor {self.input_metadata.descriptor}")
             case _:
                 raise NotImplementedError(self.input_metadata.descriptor)
 
@@ -185,14 +179,12 @@ def process_full_spin_single_sensor(
     def process_spectral_fit_index(
         self,
         hi_l3_spectral_fit_dependencies: HiSpectralIndexDependencies,
-        spectral_index_energy_range: Optional[tuple[int, int]] = None,
+        spectral_index_energy_range: tuple[int, int] | None = None,
     ) -> RectangularSpectralIndexMapData:
         intensity_map_data = hi_l3_spectral_fit_dependencies.map_data.intensity_map_data
         if spectral_index_energy_range is not None:
             start_bin, end_bin = spectral_index_energy_range
-            intensity_map_data = slice_energy_range_by_bin(
-                intensity_map_data, start_bin, end_bin
-            )
+            intensity_map_data = slice_energy_range_by_bin(intensity_map_data, start_bin, end_bin)
         return RectangularSpectralIndexMapData(
             spectral_index_map_data=fit_spectral_index_map(intensity_map_data),
             coords=hi_l3_spectral_fit_dependencies.map_data.coords,
diff --git a/imap_l3_processing/hi/hi_sp_initializer.py b/imap_l3_processing/hi/hi_sp_initializer.py
index 19824f40..21d9fe91 100644
--- a/imap_l3_processing/hi/hi_sp_initializer.py
+++ b/imap_l3_processing/hi/hi_sp_initializer.py
@@ -7,8 +7,8 @@
 from imap_l3_processing.maps.map_descriptors import (
     MapDescriptorParts,
     Sensor,
-    SurvivalCorrection,
     SpinPhase,
+    SurvivalCorrection,
 )
 from imap_l3_processing.maps.map_initializer import PossibleMapToProduce
 from imap_l3_processing.maps.sp_map_initializer import SPMapInitializer
@@ -83,8 +83,7 @@ def __init__(self):
             version="latest",
         )
         self.glows_hi45_file_by_repoint = {
-            int(r["repointing"]): Path(r["file_path"]).name
-            for r in sp_hi45_query_result
+            int(r["repointing"]): Path(r["file_path"]).name for r in sp_hi45_query_result
         }
 
         sp_hi90_query_result = imap_data_access.query(
@@ -94,8 +93,7 @@ def __init__(self):
             version="latest",
         )
         self.glows_hi90_file_by_repoint = {
-            int(r["repointing"]): Path(r["file_path"]).name
-            for r in sp_hi90_query_result
+            int(r["repointing"]): Path(r["file_path"]).name for r in sp_hi90_query_result
         }
 
         hi_l2_query_result = imap_data_access.query(instrument="hi", data_level="l2")
@@ -108,9 +106,7 @@ def furnish_spice_dependencies(self, map_to_produce: PossibleMapToProduce):
             kernel_types=HI_SP_SPICE_KERNELS,
         )
 
-    def _get_l2_dependencies(
-        self, descriptor: MapDescriptorParts
-    ) -> list[MapDescriptorParts]:
+    def _get_l2_dependencies(self, descriptor: MapDescriptorParts) -> list[MapDescriptorParts]:
         match descriptor:
             case MapDescriptorParts(
                 survival_correction=SurvivalCorrection.SurvivalCorrected,
@@ -141,9 +137,7 @@ def _get_l2_dependencies(
             case _:
                 raise ValueError("Expected map to be produced to use a single sensor!")
 
-    def _collect_glows_psets_by_repoint(
-        self, descriptor: MapDescriptorParts
-    ) -> dict[int, str]:
+    def _collect_glows_psets_by_repoint(self, descriptor: MapDescriptorParts) -> dict[int, str]:
         match descriptor:
             case MapDescriptorParts(sensor=Sensor.Hi45):
                 return self.glows_hi45_file_by_repoint
diff --git a/imap_l3_processing/hi/utils.py b/imap_l3_processing/hi/utils.py
index c66e292c..89cdd452 100644
--- a/imap_l3_processing/hi/utils.py
+++ b/imap_l3_processing/hi/utils.py
@@ -1,5 +1,4 @@
 from pathlib import Path
-from typing import Union
 
 from imap_data_access import ScienceFilePath
 from imap_processing.spice.time import met_to_ttj2000ns
@@ -7,11 +6,11 @@
 
 from imap_l3_processing.cdf.cdf_utils import read_numeric_variable
 from imap_l3_processing.glows.l3e.glows_l3e_hi_model import (
-    PROBABILITY_OF_SURVIVAL_VAR_NAME,
-    EPOCH_CDF_VAR_NAME,
     ENERGY_VAR_NAME,
-    SPIN_ANGLE_VAR_NAME,
+    EPOCH_CDF_VAR_NAME,
     GLOWS_FLAGS_VAR_NAME,
+    PROBABILITY_OF_SURVIVAL_VAR_NAME,
+    SPIN_ANGLE_VAR_NAME,
 )
 from imap_l3_processing.maps.map_models import (
     GlowsL3eRectangularMapInputData,
@@ -20,7 +19,7 @@
 
 
 def read_l1c_rectangular_pointing_set_data(
-    path: Union[Path, str],
+    path: Path | str,
 ) -> InputRectangularPointingSet:
     repointing = ScienceFilePath(path).repointing
     with CDF(str(path)) as cdf:
@@ -37,14 +36,11 @@ def read_l1c_rectangular_pointing_set_data(
         pointing_start_met = (
             cdf["pointing_start_met"][...] if "pointing_start_met" in cdf else None
         )
-        pointing_end_met = (
-            cdf["pointing_end_met"][...] if "pointing_end_met" in cdf else None
-        )
+        pointing_end_met = cdf["pointing_end_met"][...] if "pointing_end_met" in cdf else None
         epoch_delta = (
             cdf["epoch_delta"][...]
             if "epoch_delta" in cdf
-            else met_to_ttj2000ns(pointing_end_met)
-            - met_to_ttj2000ns(pointing_start_met)
+            else met_to_ttj2000ns(pointing_end_met) - met_to_ttj2000ns(pointing_start_met)
         )
         return InputRectangularPointingSet(
             epoch=cdf["epoch"][0],
@@ -60,7 +56,7 @@ def read_l1c_rectangular_pointing_set_data(
         )
 
 
-def read_glows_l3e_data(cdf_path: Union[Path, str]) -> GlowsL3eRectangularMapInputData:
+def read_glows_l3e_data(cdf_path: Path | str) -> GlowsL3eRectangularMapInputData:
     repointing = ScienceFilePath(cdf_path).repointing
     with CDF(str(cdf_path)) as cdf:
         return GlowsL3eRectangularMapInputData(
@@ -69,8 +65,6 @@ def read_glows_l3e_data(cdf_path: Union[Path, str]) -> GlowsL3eRectangularMapInp
             repointing=repointing,
             energy=read_numeric_variable(cdf[ENERGY_VAR_NAME]),
             spin_angle=read_numeric_variable(cdf[SPIN_ANGLE_VAR_NAME]),
-            probability_of_survival=read_numeric_variable(
-                cdf[PROBABILITY_OF_SURVIVAL_VAR_NAME]
-            ),
+            probability_of_survival=read_numeric_variable(cdf[PROBABILITY_OF_SURVIVAL_VAR_NAME]),
             flags=cdf[GLOWS_FLAGS_VAR_NAME][...],
         )
diff --git a/imap_l3_processing/hit/l3/hit_processor.py b/imap_l3_processing/hit/l3/hit_processor.py
index 3b20971c..e276f9ad 100644
--- a/imap_l3_processing/hit/l3/hit_processor.py
+++ b/imap_l3_processing/hit/l3/hit_processor.py
@@ -16,17 +16,17 @@
 from imap_l3_processing.hit.l3.pha.science.calculate_pha import process_pha_event
 from imap_l3_processing.hit.l3.sectored_products.models import HitPitchAngleDataProduct
 from imap_l3_processing.hit.l3.sectored_products.science.sectored_products_algorithms import (
-    get_sector_unit_vectors,
     get_hit_bin_polar_coordinates,
+    get_sector_unit_vectors,
 )
 from imap_l3_processing.hit.quality_flags import HitL3Flags
 from imap_l3_processing.models import InputMetadata
 from imap_l3_processing.pitch_angles import (
-    calculate_unit_vector,
-    calculate_pitch_angle,
     calculate_gyrophase,
-    rotate_particle_vectors_from_hit_despun_to_imap_despun,
+    calculate_pitch_angle,
+    calculate_unit_vector,
     rebin_by_pitch_angle_and_gyrophase,
+    rotate_particle_vectors_from_hit_despun_to_imap_despun,
 )
 from imap_l3_processing.processor import Processor
 from imap_l3_processing.utils import save_data
@@ -35,24 +35,18 @@
 
 
 class HitProcessor(Processor):
-    def __init__(
-        self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata
-    ):
+    def __init__(self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata):
         super().__init__(dependencies, input_metadata)
 
     def process(self):
         if self.input_metadata.descriptor == "macropixel":
-            dependencies = HITL3SectoredDependencies.fetch_dependencies(
-                self.dependencies
-            )
+            dependencies = HITL3SectoredDependencies.fetch_dependencies(self.dependencies)
             pitch_angle_data_product = self.process_pitch_angle_product(dependencies)
             pitch_angle_data_product.parent_file_names = self.get_parent_file_names()
             cdf_file_path = save_data(pitch_angle_data_product)
             return [cdf_file_path]
         elif self.input_metadata.descriptor == "direct-events":
-            direct_event_dependencies = HitL3PhaDependencies.fetch_dependencies(
-                self.dependencies
-            )
+            direct_event_dependencies = HitL3PhaDependencies.fetch_dependencies(self.dependencies)
             direct_event_data_product = self.process_direct_event_product(
                 direct_event_dependencies
             )
@@ -77,9 +71,7 @@ def process_direct_event_product(
             try:
                 event_raw_pha_events = PHAEventReader.read_all_pha_events(event_binary)
             except Exception:
-                logger.warning(
-                    f"Could not read all pha events for epoch {epoch}", exc_info=True
-                )
+                logger.warning(f"Could not read all pha events for epoch {epoch}", exc_info=True)
                 continue
 
             epochs += [epoch] * len(event_raw_pha_events)
@@ -90,15 +82,11 @@ def process_direct_event_product(
         e_delta = np.full(shape=(len(raw_pha_events)), fill_value=np.nan)
         e_prime = np.full(shape=(len(raw_pha_events)), fill_value=np.nan)
         detected_range = np.full(shape=(len(raw_pha_events)), fill_value=np.nan)
-        particle_id = np.full(
-            shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE
-        )
+        particle_id = np.full(shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE)
         priority_buffer_number = np.full(
             shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT1_FILL_VALUE
         )
-        latency = np.full(
-            shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT1_FILL_VALUE
-        )
+        latency = np.full(shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT1_FILL_VALUE)
         stim_tag = np.full(shape=(len(raw_pha_events)), fill_value=False)
         long_event_flag = np.full(shape=(len(raw_pha_events)), fill_value=False)
         haz_tag = np.full(shape=(len(raw_pha_events)), fill_value=False)
@@ -106,29 +94,17 @@ def process_direct_event_product(
         has_unread_adcs = np.full(shape=(len(raw_pha_events)), fill_value=False)
         culling_flag = np.full(shape=(len(raw_pha_events)), fill_value=False)
 
-        pha_value = np.full(
-            shape=(len(raw_pha_events), 64), fill_value=UNSIGNED_INT2_FILL_VALUE
-        )
+        pha_value = np.full(shape=(len(raw_pha_events), 64), fill_value=UNSIGNED_INT2_FILL_VALUE)
         energy_at_detector = np.full(shape=(len(raw_pha_events), 64), fill_value=np.nan)
         is_low_gain = np.full(shape=(len(raw_pha_events), 64), fill_value=False)
 
-        detector_flags = np.full(
-            shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE
-        )
-        deindex = np.full(
-            shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE
-        )
-        epindex = np.full(
-            shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE
-        )
+        detector_flags = np.full(shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE)
+        deindex = np.full(shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE)
+        epindex = np.full(shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE)
         stim_gain = np.full(shape=(len(raw_pha_events)), fill_value=False)
         a_l_stim = np.full(shape=(len(raw_pha_events)), fill_value=False)
-        stim_step = np.full(
-            shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT1_FILL_VALUE
-        )
-        dac_value = np.full(
-            shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE
-        )
+        stim_step = np.full(shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT1_FILL_VALUE)
+        dac_value = np.full(shape=(len(raw_pha_events)), fill_value=UNSIGNED_INT2_FILL_VALUE)
 
         for i, raw_event in enumerate(raw_pha_events):
             event_output = process_pha_event(
@@ -159,9 +135,7 @@ def process_direct_event_product(
             has_unread_adcs[i] = raw_event.has_unread_adcs
             culling_flag[i] = raw_event.culling_flag
 
-            for event_energy_at_detector, word in zip(
-                event_output.energies, raw_event.pha_words
-            ):
+            for event_energy_at_detector, word in zip(event_output.energies, raw_event.pha_words):
                 pha_value[i, word.detector.address] = word.adc_value
                 energy_at_detector[i, word.detector.address] = event_energy_at_detector
                 is_low_gain[i, word.detector.address] = word.is_low_gain
@@ -303,16 +277,12 @@ def process_pitch_angle_product(
         )
 
         particle_unit_vectors = -sector_unit_vectors
-        rotated_particle_unit_vectors = (
-            rotate_particle_vectors_from_hit_despun_to_imap_despun(
-                particle_unit_vectors
-            )
+        rotated_particle_unit_vectors = rotate_particle_vectors_from_hit_despun_to_imap_despun(
+            particle_unit_vectors
         )
 
         pitch_angles, gyrophases, pitch_angle_deltas, gyrophase_deltas = (
-            get_hit_bin_polar_coordinates(
-                number_of_pitch_angle_bins, number_of_gyrophase_bins
-            )
+            get_hit_bin_polar_coordinates(number_of_pitch_angle_bins, number_of_gyrophase_bins)
         )
 
         averaged_mag_data = mag_data.rebin_to(hit_data.epoch, hit_data.epoch_delta)
diff --git a/imap_l3_processing/hit/l3/models.py b/imap_l3_processing/hit/l3/models.py
index 596f98f4..ae4e91a9 100644
--- a/imap_l3_processing/hit/l3/models.py
+++ b/imap_l3_processing/hit/l3/models.py
@@ -1,7 +1,6 @@
 from dataclasses import dataclass
 from datetime import datetime, timedelta
 from pathlib import Path
-from typing import Union
 
 import numpy as np
 from spacepy.pycdf import CDF
@@ -118,9 +117,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(E_PRIME_VAR_NAME, self.e_prime),
             DataProductVariable(DETECTED_RANGE_VAR_NAME, self.detected_range),
             DataProductVariable(PARTICLE_ID_VAR_NAME, self.particle_id),
-            DataProductVariable(
-                PRIORITY_BUFFER_NUMBER_VAR_NAME, self.priority_buffer_number
-            ),
+            DataProductVariable(PRIORITY_BUFFER_NUMBER_VAR_NAME, self.priority_buffer_number),
             DataProductVariable(LATENCY_VAR_NAME, self.latency),
             DataProductVariable(STIM_TAG_VAR_NAME, self.stim_tag),
             DataProductVariable(LONG_EVENT_FLAG_VAR_NAME, self.long_event_flag),
@@ -149,6 +146,6 @@ class HitL1Data:
     event_binary: np.ndarray[str]
 
     @classmethod
-    def read_from_cdf(cls, cdf_file_path: Union[Path, str]):
+    def read_from_cdf(cls, cdf_file_path: Path | str):
         with CDF(str(cdf_file_path)) as cdf:
             return cls(cdf["epoch"][...], cdf["pha_raw"][...])
diff --git a/imap_l3_processing/hit/l3/pha/hit_l3_pha_dependencies.py b/imap_l3_processing/hit/l3/pha/hit_l3_pha_dependencies.py
index a6489685..06509b3b 100644
--- a/imap_l3_processing/hit/l3/pha/hit_l3_pha_dependencies.py
+++ b/imap_l3_processing/hit/l3/pha/hit_l3_pha_dependencies.py
@@ -86,14 +86,14 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
         )
 
         lo_gain_lookup_path = download(
-            dependencies.get_file_paths(
-                source="hit", descriptor=HIT_L3_LO_GAIN_LOOKUP_DESCRIPTOR
-            )[0]
+            dependencies.get_file_paths(source="hit", descriptor=HIT_L3_LO_GAIN_LOOKUP_DESCRIPTOR)[
+                0
+            ]
         )
         hi_gain_lookup_path = download(
-            dependencies.get_file_paths(
-                source="hit", descriptor=HIT_L3_HI_GAIN_LOOKUP_DESCRIPTOR
-            )[0]
+            dependencies.get_file_paths(source="hit", descriptor=HIT_L3_HI_GAIN_LOOKUP_DESCRIPTOR)[
+                0
+            ]
         )
         range_2A_charge_fit_lookup_path = download(
             dependencies.get_file_paths(
@@ -139,9 +139,7 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection):
             range_3B_cosine_lookup_path,
             range_4B_cosine_lookup_path,
         )
-        gain_lookup_table = GainLookupTable.from_file(
-            hi_gain_lookup_path, lo_gain_lookup_path
-        )
+        gain_lookup_table = GainLookupTable.from_file(hi_gain_lookup_path, lo_gain_lookup_path)
         range_fit_lookup_table = RangeFitLookup.from_files(
             range_2A_charge_fit_lookup_path,
             range_3A_charge_fit_lookup_path,
diff --git a/imap_l3_processing/hit/l3/pha/pha_event_reader.py b/imap_l3_processing/hit/l3/pha/pha_event_reader.py
index 978400d7..827676dd 100644
--- a/imap_l3_processing/hit/l3/pha/pha_event_reader.py
+++ b/imap_l3_processing/hit/l3/pha/pha_event_reader.py
@@ -1,7 +1,7 @@
 import csv
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional, Literal
+from typing import ClassVar, Literal
 
 from bitstring import BitStream
 
@@ -17,14 +17,12 @@ class Detector:
     def __str__(self):
         return "L" + str(self.layer) + self.side + self.segment
 
-    detector_mapping = {}
+    detector_mapping: ClassVar[dict[int, tuple[str, str]]] = {}
 
     @classmethod
     def from_address(cls, address: int):
         if cls.detector_mapping == {}:
-            with open(
-                Path(__file__).parent / "address_to_detector.csv"
-            ) as detector_mapping_file:
+            with open(Path(__file__).parent / "address_to_detector.csv") as detector_mapping_file:
                 reader = csv.reader(detector_mapping_file)
                 next(reader)
                 for name, address_str, group in reader:
@@ -96,9 +94,9 @@ class RawPHAEvent:
     culling_flag: bool
     spare: bool
     pha_words: list[PHAWord]
-    extended_header: Optional[PHAExtendedHeader] = None
-    stim_block: Optional[StimBlock] = None
-    extended_stim_header: Optional[ExtendedStimHeader] = None
+    extended_header: PHAExtendedHeader | None = None
+    stim_block: StimBlock | None = None
+    extended_stim_header: ExtendedStimHeader | None = None
 
 
 class PHAEventReader:
@@ -126,9 +124,7 @@ def read_pha_event(cls, event_bitstream: BitStream) -> RawPHAEvent:
             delta_e_index = event_bitstream.read("uint:9")
             e_prime_index = event_bitstream.read("uint:7")
             detector_flags = event_bitstream.read("uint:8")
-            extended_header = PHAExtendedHeader(
-                detector_flags, delta_e_index, e_prime_index
-            )
+            extended_header = PHAExtendedHeader(detector_flags, delta_e_index, e_prime_index)
 
         elif stim_tag:
             if long_event_flag:
diff --git a/imap_l3_processing/hit/l3/pha/science/calculate_pha.py b/imap_l3_processing/hit/l3/pha/science/calculate_pha.py
index bc1d54ea..06597f5a 100644
--- a/imap_l3_processing/hit/l3/pha/science/calculate_pha.py
+++ b/imap_l3_processing/hit/l3/pha/science/calculate_pha.py
@@ -1,19 +1,18 @@
 from dataclasses import dataclass
-from typing import Optional
 
 import numpy as np
 from numpy import clip
 
 from imap_l3_processing.hit.l3.pha.pha_event_reader import PHAWord, RawPHAEvent
 from imap_l3_processing.hit.l3.pha.science.cosine_correction_lookup_table import (
+    CosineCorrectionLookupTable,
     DetectedRange,
     Detector,
-    CosineCorrectionLookupTable,
     DetectorRange,
 )
 from imap_l3_processing.hit.l3.pha.science.gain_lookup_table import (
-    GainLookupTable,
     DetectorGain,
+    GainLookupTable,
 )
 from imap_l3_processing.hit.l3.pha.science.hit_event_type_lookup import (
     HitEventTypeLookup,
@@ -34,12 +33,12 @@ class EventAnalysis:
 @dataclass
 class EventOutput:
     original_event: RawPHAEvent
-    total_energy: Optional[float]
-    charge: Optional[float]
+    total_energy: float | None
+    charge: float | None
     energies: list[float]
-    detected_range: Optional[DetectedRange]
-    e_delta: Optional[float]
-    e_prime: Optional[float]
+    detected_range: DetectedRange | None
+    e_delta: float | None
+    e_prime: float | None
 
 
 def calculate_mev(word: PHAWord, gain_lookup_table: GainLookupTable) -> float:
@@ -48,9 +47,7 @@ def calculate_mev(word: PHAWord, gain_lookup_table: GainLookupTable) -> float:
     return word.adc_value * gain_coeffs.a + gain_coeffs.b
 
 
-def analyze_event(
-    event: RawPHAEvent, rule_lookup: HitEventTypeLookup
-) -> Optional[EventAnalysis]:
+def analyze_event(event: RawPHAEvent, rule_lookup: HitEventTypeLookup) -> EventAnalysis | None:
 
     def get_adc_value(pha_word: PHAWord):
         return 20 * pha_word.adc_value if pha_word.is_low_gain else pha_word.adc_value
@@ -58,7 +55,7 @@ def get_adc_value(pha_word: PHAWord):
     words = [word for word in event.pha_words]
     groups_to_words = {}
     for word in words:
-        if word.detector.group in groups_to_words.keys():
+        if word.detector.group in groups_to_words:
             groups_to_words[word.detector.group].append(word)
         else:
             groups_to_words[word.detector.group] = [word]
@@ -76,39 +73,39 @@ def get_adc_value(pha_word: PHAWord):
                 unsaturated_words, key=get_adc_value
             )
 
-        l1_detector = [
+        l1_detector = next(
             group
             for group in rule.included_detector_groups
             if group[0:3] == f"L1{rule.range.side.name}"
-        ][0]
-        l2_detector = [
+        )
+        l2_detector = next(
             group
             for group in rule.included_detector_groups
             if group[0:3] == f"L2{rule.range.side.name}"
-        ][0]
+        )
 
         if rule.range.range == DetectorRange.R2:
             e_prime_group = l2_detector
             e_delta_group = l1_detector
         elif rule.range.range == DetectorRange.R3:
-            e_prime_group = [
+            e_prime_group = next(
                 group
                 for group in rule.included_detector_groups
                 if group[0:3] == f"L3{rule.range.side.name}"
-            ][0]
+            )
             e_delta_group = l2_detector
         elif rule.range.range == DetectorRange.R4:
             opposite_side = "A" if rule.range.side.name == "B" else "B"
-            e_prime_group = [
+            e_prime_group = next(
                 group
                 for group in rule.included_detector_groups
                 if group[0:3] == f"L3{opposite_side}"
-            ][0]
-            e_delta_group = [
+            )
+            e_delta_group = next(
                 group
                 for group in rule.included_detector_groups
                 if group[0:3] == f"L3{rule.range.side.name}"
-            ][0]
+            )
 
         return EventAnalysis(
             range=rule.range,
@@ -154,16 +151,12 @@ def compute_charge(
     double_power_law_lookup: RangeFitLookup,
 ) -> float:
     if valid_ranges[detected_range.range].is_in_range(e_prime, delta_e):
-        charges, deltas = double_power_law_lookup.evaluate_e_prime(
-            detected_range, e_prime
-        )
+        charges, deltas = double_power_law_lookup.evaluate_e_prime(detected_range, e_prime)
         assert np.array_equal(deltas, np.sort(deltas)), "values are not increasing"
         index_2 = clip(np.searchsorted(deltas, delta_e), 1, len(charges) - 1)
         index_1 = index_2 - 1
 
-        B = np.log(charges[index_2] / charges[index_1]) / np.log(
-            deltas[index_2] / deltas[index_1]
-        )
+        B = np.log(charges[index_2] / charges[index_1]) / np.log(deltas[index_2] / deltas[index_1])
         A = charges[index_1] / (deltas[index_1] ** B)
 
         return A * delta_e**B
@@ -188,14 +181,11 @@ def calculate_corrected_energy(word):
 
         energies = [calculate_corrected_energy(word) for word in event.pha_words]
         total_energy = sum(
-            calculate_corrected_energy(word)
-            for word in event_analysis.words_with_highest_energy
+            calculate_corrected_energy(word) for word in event_analysis.words_with_highest_energy
         )
         e_delta = calculate_corrected_energy(event_analysis.e_delta_word)
         e_prime = calculate_corrected_energy(event_analysis.e_prime_word)
-        charge = compute_charge(
-            event_analysis.range, e_delta, e_prime, range_fit_lookup
-        )
+        charge = compute_charge(event_analysis.range, e_delta, e_prime, range_fit_lookup)
 
         return EventOutput(
             original_event=event,
diff --git a/imap_l3_processing/hit/l3/pha/science/cosine_correction_lookup_table.py b/imap_l3_processing/hit/l3/pha/science/cosine_correction_lookup_table.py
index 63407dbe..46590352 100644
--- a/imap_l3_processing/hit/l3/pha/science/cosine_correction_lookup_table.py
+++ b/imap_l3_processing/hit/l3/pha/science/cosine_correction_lookup_table.py
@@ -2,6 +2,7 @@
 from dataclasses import dataclass
 from enum import Enum
 from pathlib import Path
+from typing import ClassVar
 
 from imap_l3_processing.hit.l3.pha.pha_event_reader import Detector
 
@@ -24,7 +25,7 @@ class DetectedRange:
 
 
 class CosineCorrectionLookupTable:
-    _l1_detector_order = [
+    _l1_detector_order: ClassVar[tuple[str]] = (
         "L1A0a",
         "L1A0b",
         "L1A0c",
@@ -40,8 +41,8 @@ class CosineCorrectionLookupTable:
         "L1A4a",
         "L1A4b",
         "L1A4c",
-    ]
-    _l2_detector_order = [
+    )
+    _l2_detector_order: ClassVar[tuple[str]] = (
         "L2A0",
         "L2A1",
         "L2A2",
@@ -52,7 +53,7 @@ class CosineCorrectionLookupTable:
         "L2A7",
         "L2A8",
         "L2A9",
-    ]
+    )
 
     def __init__(
         self,
@@ -103,6 +104,4 @@ def get_cosine_correction(
             DetectedRange(DetectorRange.R3, DetectorSide.B): self._range3A_corrections,
             DetectedRange(DetectorRange.R4, DetectorSide.B): self._range4A_corrections,
         }
-        return corrections_by_range[detected_range][
-            (l1_detector.segment, l2_detector.segment)
-        ]
+        return corrections_by_range[detected_range][(l1_detector.segment, l2_detector.segment)]
diff --git a/imap_l3_processing/hit/l3/pha/science/hit_event_type_lookup.py b/imap_l3_processing/hit/l3/pha/science/hit_event_type_lookup.py
index bf06b4b9..65439623 100644
--- a/imap_l3_processing/hit/l3/pha/science/hit_event_type_lookup.py
+++ b/imap_l3_processing/hit/l3/pha/science/hit_event_type_lookup.py
@@ -50,9 +50,7 @@ def from_csv(cls, file_path: Path):
                     included_detector_groups = []
                     excluded_detector_groups = []
 
-                    for detector_group, is_included in zip(
-                        detector_groups[:-1], row[:-1]
-                    ):
+                    for detector_group, is_included in zip(detector_groups[:-1], row[:-1]):
                         if is_included == "1":
                             included_detector_groups.append(detector_group)
                         elif is_included == "0":
diff --git a/imap_l3_processing/hit/l3/sectored_products/models.py b/imap_l3_processing/hit/l3/sectored_products/models.py
index 30210777..29be16e2 100644
--- a/imap_l3_processing/hit/l3/sectored_products/models.py
+++ b/imap_l3_processing/hit/l3/sectored_products/models.py
@@ -14,12 +14,8 @@
 H_MACROPIXEL_INTENSITY_DELTA_PLUS_CDF_VAR_NAME = "h_macropixel_intensity_delta_plus"
 H_MACROPIXEL_INTENSITY_DELTA_MINUS_CDF_VAR_NAME = "h_macropixel_intensity_delta_minus"
 H_MACROPIXEL_INTENSITY_PA_CDF_VAR_NAME = "h_macropixel_intensity_pa"
-H_MACROPIXEL_INTENSITY_PA_DELTA_PLUS_CDF_VAR_NAME = (
-    "h_macropixel_intensity_pa_delta_plus"
-)
-H_MACROPIXEL_INTENSITY_PA_DELTA_MINUS_CDF_VAR_NAME = (
-    "h_macropixel_intensity_pa_delta_minus"
-)
+H_MACROPIXEL_INTENSITY_PA_DELTA_PLUS_CDF_VAR_NAME = "h_macropixel_intensity_pa_delta_plus"
+H_MACROPIXEL_INTENSITY_PA_DELTA_MINUS_CDF_VAR_NAME = "h_macropixel_intensity_pa_delta_minus"
 H_ENERGY_CDF_VAR_NAME = "h_energy"
 H_ENERGY_DELTA_PLUS_CDF_VAR_NAME = "h_energy_delta_plus"
 H_ENERGY_DELTA_MINUS_CDF_VAR_NAME = "h_energy_delta_minus"
@@ -45,12 +41,8 @@
 NE_MG_SI_INTENSITY_DELTA_PLUS_CDF_VAR_NAME = "nemgsi_macropixel_intensity_delta_plus"
 NE_MG_SI_INTENSITY_DELTA_MINUS_CDF_VAR_NAME = "nemgsi_macropixel_intensity_delta_minus"
 NE_MG_SI_INTENSITY_PA_CDF_VAR_NAME = "nemgsi_macropixel_intensity_pa"
-NE_MG_SI_INTENSITY_PA_DELTA_PLUS_CDF_VAR_NAME = (
-    "nemgsi_macropixel_intensity_pa_delta_plus"
-)
-NE_MG_SI_INTENSITY_PA_DELTA_MINUS_CDF_VAR_NAME = (
-    "nemgsi_macropixel_intensity_pa_delta_minus"
-)
+NE_MG_SI_INTENSITY_PA_DELTA_PLUS_CDF_VAR_NAME = "nemgsi_macropixel_intensity_pa_delta_plus"
+NE_MG_SI_INTENSITY_PA_DELTA_MINUS_CDF_VAR_NAME = "nemgsi_macropixel_intensity_pa_delta_minus"
 NE_MG_SI_ENERGY_CDF_VAR_NAME = "nemgsi_energy"
 NE_MG_SI_ENERGY_DELTA_PLUS_CDF_VAR_NAME = "nemgsi_energy_delta_plus"
 NE_MG_SI_ENERGY_DELTA_MINUS_CDF_VAR_NAME = "nemgsi_energy_delta_minus"
@@ -146,14 +138,10 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 np.array([t.total_seconds() for t in self.epoch_deltas]) * 1e9,
             ),
             DataProductVariable(PITCH_ANGLE_CDF_VAR_NAME, self.pitch_angles),
-            DataProductVariable(
-                PITCH_ANGLE_DELTA_CDF_VAR_NAME, self.pitch_angle_deltas
-            ),
+            DataProductVariable(PITCH_ANGLE_DELTA_CDF_VAR_NAME, self.pitch_angle_deltas),
             DataProductVariable(GYROPHASE_CDF_VAR_NAME, self.gyrophases),
             DataProductVariable(GYROPHASE_DELTA_CDF_VAR_NAME, self.gyrophase_deltas),
-            DataProductVariable(
-                H_MACROPIXEL_INTENSITY_CDF_VAR_NAME, self.h_macropixel_intensity
-            ),
+            DataProductVariable(H_MACROPIXEL_INTENSITY_CDF_VAR_NAME, self.h_macropixel_intensity),
             DataProductVariable(
                 H_MACROPIXEL_INTENSITY_DELTA_PLUS_CDF_VAR_NAME,
                 self.h_macropixel_intensity_delta_plus,
@@ -174,15 +162,9 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 self.h_macropixel_intensity_pa_delta_minus,
             ),
             DataProductVariable(H_ENERGY_CDF_VAR_NAME, self.h_energies),
-            DataProductVariable(
-                H_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.h_energy_delta_plus
-            ),
-            DataProductVariable(
-                H_ENERGY_DELTA_MINUS_CDF_VAR_NAME, self.h_energy_delta_minus
-            ),
-            DataProductVariable(
-                HE4_INTENSITY_CDF_VAR_NAME, self.he4_macropixel_intensity
-            ),
+            DataProductVariable(H_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.h_energy_delta_plus),
+            DataProductVariable(H_ENERGY_DELTA_MINUS_CDF_VAR_NAME, self.h_energy_delta_minus),
+            DataProductVariable(HE4_INTENSITY_CDF_VAR_NAME, self.he4_macropixel_intensity),
             DataProductVariable(
                 HE4_INTENSITY_DELTA_PLUS_CDF_VAR_NAME,
                 self.he4_macropixel_intensity_delta_plus,
@@ -191,9 +173,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 HE4_INTENSITY_DELTA_MINUS_CDF_VAR_NAME,
                 self.he4_macropixel_intensity_delta_minus,
             ),
-            DataProductVariable(
-                HE4_INTENSITY_PA_CDF_VAR_NAME, self.he4_macropixel_intensity_pa
-            ),
+            DataProductVariable(HE4_INTENSITY_PA_CDF_VAR_NAME, self.he4_macropixel_intensity_pa),
             DataProductVariable(
                 HE4_INTENSITY_PA_DELTA_PLUS_CDF_VAR_NAME,
                 self.he4_macropixel_intensity_pa_delta_plus,
@@ -203,15 +183,9 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 self.he4_macropixel_intensity_pa_delta_minus,
             ),
             DataProductVariable(HE4_ENERGY_CDF_VAR_NAME, self.he4_energies),
-            DataProductVariable(
-                HE4_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.he4_energy_delta_plus
-            ),
-            DataProductVariable(
-                HE4_ENERGY_DELTA_MINUS_CDF_VAR_NAME, self.he4_energy_delta_minus
-            ),
-            DataProductVariable(
-                CNO_INTENSITY_CDF_VAR_NAME, self.cno_macropixel_intensity
-            ),
+            DataProductVariable(HE4_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.he4_energy_delta_plus),
+            DataProductVariable(HE4_ENERGY_DELTA_MINUS_CDF_VAR_NAME, self.he4_energy_delta_minus),
+            DataProductVariable(CNO_INTENSITY_CDF_VAR_NAME, self.cno_macropixel_intensity),
             DataProductVariable(
                 CNO_INTENSITY_DELTA_PLUS_CDF_VAR_NAME,
                 self.cno_macropixel_intensity_delta_plus,
@@ -220,9 +194,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 CNO_INTENSITY_DELTA_MINUS_CDF_VAR_NAME,
                 self.cno_macropixel_intensity_delta_minus,
             ),
-            DataProductVariable(
-                CNO_INTENSITY_PA_CDF_VAR_NAME, self.cno_macropixel_intensity_pa
-            ),
+            DataProductVariable(CNO_INTENSITY_PA_CDF_VAR_NAME, self.cno_macropixel_intensity_pa),
             DataProductVariable(
                 CNO_INTENSITY_PA_DELTA_PLUS_CDF_VAR_NAME,
                 self.cno_macropixel_intensity_pa_delta_plus,
@@ -232,12 +204,8 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 self.cno_macropixel_intensity_pa_delta_minus,
             ),
             DataProductVariable(CNO_ENERGY_CDF_VAR_NAME, self.cno_energies),
-            DataProductVariable(
-                CNO_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.cno_energy_delta_plus
-            ),
-            DataProductVariable(
-                CNO_ENERGY_DELTA_MINUS_CDF_VAR_NAME, self.cno_energy_delta_minus
-            ),
+            DataProductVariable(CNO_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.cno_energy_delta_plus),
+            DataProductVariable(CNO_ENERGY_DELTA_MINUS_CDF_VAR_NAME, self.cno_energy_delta_minus),
             DataProductVariable(
                 NE_MG_SI_INTENSITY_CDF_VAR_NAME, self.ne_mg_si_macropixel_intensity
             ),
@@ -269,9 +237,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 NE_MG_SI_ENERGY_DELTA_MINUS_CDF_VAR_NAME,
                 self.ne_mg_si_energy_delta_minus,
             ),
-            DataProductVariable(
-                IRON_INTENSITY_CDF_VAR_NAME, self.iron_macropixel_intensity
-            ),
+            DataProductVariable(IRON_INTENSITY_CDF_VAR_NAME, self.iron_macropixel_intensity),
             DataProductVariable(
                 IRON_INTENSITY_DELTA_PLUS_CDF_VAR_NAME,
                 self.iron_macropixel_intensity_delta_plus,
@@ -280,9 +246,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 IRON_INTENSITY_DELTA_MINUS_CDF_VAR_NAME,
                 self.iron_macropixel_intensity_delta_minus,
             ),
-            DataProductVariable(
-                IRON_INTENSITY_PA_CDF_VAR_NAME, self.iron_macropixel_intensity_pa
-            ),
+            DataProductVariable(IRON_INTENSITY_PA_CDF_VAR_NAME, self.iron_macropixel_intensity_pa),
             DataProductVariable(
                 IRON_INTENSITY_PA_DELTA_PLUS_CDF_VAR_NAME,
                 self.iron_macropixel_intensity_pa_delta_plus,
@@ -292,60 +256,39 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 self.iron_macropixel_intensity_pa_delta_minus,
             ),
             DataProductVariable(IRON_ENERGY_CDF_VAR_NAME, self.iron_energies),
-            DataProductVariable(
-                IRON_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.iron_energy_delta_plus
-            ),
+            DataProductVariable(IRON_ENERGY_DELTA_PLUS_CDF_VAR_NAME, self.iron_energy_delta_plus),
             DataProductVariable(
                 IRON_ENERGY_DELTA_MINUS_CDF_VAR_NAME, self.iron_energy_delta_minus
             ),
-            DataProductVariable(
-                MEASUREMENT_PITCH_ANGLE_VAR_NAME, self.measurement_pitch_angle
-            ),
-            DataProductVariable(
-                MEASUREMENT_GYROPHASE_VAR_NAME, self.measurement_gyrophase
-            ),
+            DataProductVariable(MEASUREMENT_PITCH_ANGLE_VAR_NAME, self.measurement_pitch_angle),
+            DataProductVariable(MEASUREMENT_GYROPHASE_VAR_NAME, self.measurement_gyrophase),
             DataProductVariable(
                 PITCH_ANGLE_LABEL_VAR_NAME,
-                [
-                    f"Pitch Angle Label {str(i + 1)}"
-                    for i in range(len(self.pitch_angles))
-                ],
+                [f"Pitch Angle Label {i + 1!s}" for i in range(len(self.pitch_angles))],
             ),
             DataProductVariable(
                 GYROPHASE_LABEL_VAR_NAME,
-                [f"Gyrophase Label {str(i + 1)}" for i in range(len(self.gyrophases))],
+                [f"Gyrophase Label {i + 1!s}" for i in range(len(self.gyrophases))],
             ),
             DataProductVariable(
                 H_ENERGY_LABEL_VAR_NAME,
-                [f"H Energy Label {str(i + 1)}" for i in range(len(self.h_energies))],
+                [f"H Energy Label {i + 1!s}" for i in range(len(self.h_energies))],
             ),
             DataProductVariable(
                 HE4_ENERGY_LABEL_VAR_NAME,
-                [
-                    f"He4 Energy Label {str(i + 1)}"
-                    for i in range(len(self.he4_energies))
-                ],
+                [f"He4 Energy Label {i + 1!s}" for i in range(len(self.he4_energies))],
             ),
             DataProductVariable(
                 CNO_ENERGY_LABEL_VAR_NAME,
-                [
-                    f"CNO Energy Label {str(i + 1)}"
-                    for i in range(len(self.cno_energies))
-                ],
+                [f"CNO Energy Label {i + 1!s}" for i in range(len(self.cno_energies))],
             ),
             DataProductVariable(
                 NE_MG_SI_ENERGY_LABEL_VAR_NAME,
-                [
-                    f"NeMgSi Energy Label {str(i + 1)}"
-                    for i in range(len(self.ne_mg_si_energies))
-                ],
+                [f"NeMgSi Energy Label {i + 1!s}" for i in range(len(self.ne_mg_si_energies))],
             ),
             DataProductVariable(
                 IRON_ENERGY_LABEL_VAR_NAME,
-                [
-                    f"Fe Energy Label {str(i + 1)}"
-                    for i in range(len(self.iron_energies))
-                ],
+                [f"Fe Energy Label {i + 1!s}" for i in range(len(self.iron_energies))],
             ),
             DataProductVariable(AZIMUTH_VAR_NAME, self.azimuth),
             DataProductVariable(ZENITH_VAR_NAME, self.zenith),
diff --git a/imap_l3_processing/hit/l3/utils.py b/imap_l3_processing/hit/l3/utils.py
index 051b3cf9..61b54a55 100644
--- a/imap_l3_processing/hit/l3/utils.py
+++ b/imap_l3_processing/hit/l3/utils.py
@@ -1,6 +1,5 @@
 from datetime import timedelta
 from pathlib import Path
-from typing import Union
 
 from spacepy.pycdf import CDF
 
@@ -8,7 +7,7 @@
 from imap_l3_processing.hit.l3.models import HitL2Data
 
 
-def read_l2_hit_data(cdf_file_path: Union[str, Path]) -> HitL2Data:
+def read_l2_hit_data(cdf_file_path: str | Path) -> HitL2Data:
     with CDF(str(cdf_file_path)) as cdf:
         return HitL2Data(
             epoch=cdf["epoch"][...],
diff --git a/imap_l3_processing/hit/quality_flags.py b/imap_l3_processing/hit/quality_flags.py
index 002bb8ba..ae81bf16 100644
--- a/imap_l3_processing/hit/quality_flags.py
+++ b/imap_l3_processing/hit/quality_flags.py
@@ -1,4 +1,4 @@
-from imap_processing.quality_flags import FlagNameMixin, CommonFlags
+from imap_processing.quality_flags import CommonFlags, FlagNameMixin
 
 
 class HitL3Flags(FlagNameMixin):
diff --git a/imap_l3_processing/lo/l3/lo_combined_dependencies.py b/imap_l3_processing/lo/l3/lo_combined_dependencies.py
index d392f144..617ea1df 100644
--- a/imap_l3_processing/lo/l3/lo_combined_dependencies.py
+++ b/imap_l3_processing/lo/l3/lo_combined_dependencies.py
@@ -26,6 +26,4 @@ def fetch_dependencies(cls, dependencies: ProcessingInputCollection) -> Self:
 
     @classmethod
     def from_file_paths(cls, file_paths: list[Path]) -> Self:
-        return cls(
-            map_data=[RectangularIntensityMapData.read_from_path(p) for p in file_paths]
-        )
+        return cls(map_data=[RectangularIntensityMapData.read_from_path(p) for p in file_paths])
diff --git a/imap_l3_processing/lo/l3/lo_l3_spectral_fit_dependencies.py b/imap_l3_processing/lo/l3/lo_l3_spectral_fit_dependencies.py
index bf8574ba..43bd6e13 100644
--- a/imap_l3_processing/lo/l3/lo_l3_spectral_fit_dependencies.py
+++ b/imap_l3_processing/lo/l3/lo_l3_spectral_fit_dependencies.py
@@ -1,4 +1,5 @@
 from __future__ import annotations
+
 from dataclasses import dataclass
 
 from imap_data_access import download
diff --git a/imap_l3_processing/lo/l3/lo_sp_initializer.py b/imap_l3_processing/lo/l3/lo_sp_initializer.py
index 7b4ddc5e..df6d4604 100644
--- a/imap_l3_processing/lo/l3/lo_sp_initializer.py
+++ b/imap_l3_processing/lo/l3/lo_sp_initializer.py
@@ -63,9 +63,7 @@ def __init__(self):
     def _collect_glows_psets_by_repoint(self, descriptor: str) -> dict[int, str]:
         return self.glows_files_by_repointing
 
-    def _get_l2_dependencies(
-        self, descriptor: MapDescriptorParts
-    ) -> list[MapDescriptorParts]:
+    def _get_l2_dependencies(self, descriptor: MapDescriptorParts) -> list[MapDescriptorParts]:
         return [
             dataclasses.replace(
                 descriptor, survival_correction=SurvivalCorrection.NotSurvivalCorrected
diff --git a/imap_l3_processing/lo/lo_processor.py b/imap_l3_processing/lo/lo_processor.py
index 2f6b05d0..a677d43a 100644
--- a/imap_l3_processing/lo/lo_processor.py
+++ b/imap_l3_processing/lo/lo_processor.py
@@ -16,25 +16,23 @@
 )
 from imap_l3_processing.maps.map_combination import ExposureWeightedCombination
 from imap_l3_processing.maps.map_descriptors import (
-    parse_map_descriptor,
     MapDescriptorParts,
     MapQuantity,
-    SurvivalCorrection,
     ReferenceFrame,
     Sensor,
+    SurvivalCorrection,
+    parse_map_descriptor,
 )
 from imap_l3_processing.maps.map_models import (
-    ISNRateData,
+    InputRectangularPointingSet,
     ISNBackgroundSubtractedData,
+    ISNBackgroundSubtractedDataProduct,
     ISNBackgroundSubtractedMapData,
-)
-from imap_l3_processing.maps.map_models import (
+    ISNRateData,
+    RectangularIntensityDataProduct,
     RectangularIntensityMapData,
     RectangularSpectralIndexDataProduct,
     RectangularSpectralIndexMapData,
-    RectangularIntensityDataProduct,
-    InputRectangularPointingSet,
-    ISNBackgroundSubtractedDataProduct,
 )
 from imap_l3_processing.maps.map_processor import MapProcessor
 from imap_l3_processing.maps.spectral_fit import (
@@ -49,9 +47,7 @@
 
 
 class LoProcessor(MapProcessor):
-    def process(
-        self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000
-    ) -> list[Path]:
+    def process(self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000) -> list[Path]:
         set_of_parent_file_names = set(self.get_parent_file_names())
         descriptor = parse_map_descriptor(self.input_metadata.descriptor)
         match descriptor:
@@ -89,9 +85,7 @@ def process(
                 deps = LoCombinedDependencies.fetch_dependencies(self.dependencies)
                 combination = ExposureWeightedCombination()
 
-                combined_map = combination.combine_rectangular_intensity_map_data(
-                    deps.map_data
-                )
+                combined_map = combination.combine_rectangular_intensity_map_data(deps.map_data)
                 data_product = RectangularIntensityDataProduct(
                     self.input_metadata, combined_map, spice_frame_name=spice_frame_name
                 )
@@ -104,20 +98,14 @@ def process(
                     self.dependencies, Instrument.IMAP_LO
                 )
                 deps.l1c_data = list(map(self._collapse_pset_dimension, deps.l1c_data))
-                data = process_survival_probabilities(
-                    deps, spice_frame_name, cg_corrected=False
-                )
+                data = process_survival_probabilities(deps, spice_frame_name, cg_corrected=False)
 
                 data_product = RectangularIntensityDataProduct(
                     self.input_metadata, data, spice_frame_name=spice_frame_name
                 )
-                set_of_parent_file_names.update(
-                    path.name for path in deps.dependency_file_paths
-                )
+                set_of_parent_file_names.update(path.name for path in deps.dependency_file_paths)
             case None:
-                raise ValueError(
-                    f"Could not parse descriptor {self.input_metadata.descriptor}"
-                )
+                raise ValueError(f"Could not parse descriptor {self.input_metadata.descriptor}")
             case _:
                 raise NotImplementedError(self.input_metadata.descriptor)
 
@@ -151,9 +139,7 @@ def perform_spectral_fit(
 def isn_background_subtraction(
     isn_rate_data: ISNRateData,
 ) -> ISNBackgroundSubtractedMapData:
-    isn_rate_background_subtracted = (
-        isn_rate_data.ena_count_rate - isn_rate_data.bg_rate
-    )
+    isn_rate_background_subtracted = isn_rate_data.ena_count_rate - isn_rate_data.bg_rate
     isn_bg_subtracted_stat_err = np.sqrt(
         np.square(isn_rate_data.ena_count_rate_stat_uncert)
         + np.square(isn_rate_data.bg_rate_stat_uncert)
diff --git a/imap_l3_processing/lo/lo_txt_to_cdf_converter_spike.py b/imap_l3_processing/lo/lo_txt_to_cdf_converter_spike.py
index e6d675b4..031d82df 100644
--- a/imap_l3_processing/lo/lo_txt_to_cdf_converter_spike.py
+++ b/imap_l3_processing/lo/lo_txt_to_cdf_converter_spike.py
@@ -6,7 +6,7 @@
 from concurrent.futures import ThreadPoolExecutor
 from datetime import datetime
 from pathlib import Path
-from typing import Self, Optional, override, Literal
+from typing import Literal, Self, override
 
 import imap_data_access
 import numpy as np
@@ -28,26 +28,22 @@
 from imap_l3_processing.utils import furnished_metakernel
 from tests.test_helpers import get_run_local_data_path
 
-LO_ENERGIES_IN_KEV = (
-    np.array([16.33, 30.47, 55.76, 106.3, 200.0, 405.0, 787.3]) / 1000.0
-)
+LO_ENERGIES_IN_KEV = np.array([16.33, 30.47, 55.76, 106.3, 200.0, 405.0, 787.3]) / 1000.0
 LO_ENERGY_BIN_LOWERS = np.array([10.9, 20.4, 36.8, 71.6, 135.0, 269.0, 504.7]) / 1000.0
-LO_ENERGY_BIN_UPPERS = (
-    np.array([21.7, 40.5, 74.7, 140.9, 265.0, 541.0, 1069.9]) / 1000.0
-)
+LO_ENERGY_BIN_UPPERS = np.array([21.7, 40.5, 74.7, 140.9, 265.0, 541.0, 1069.9]) / 1000.0
 
 
 class CsvNameToProduct:
     @abc.abstractmethod
-    def get_energy_and_quantity(self, filename) -> Optional[tuple[int, str]]:
+    def get_energy_and_quantity(self, filename) -> tuple[int, str] | None:
         raise NotImplementedError
 
 
 @dataclasses.dataclass
 class NBSNameMapping(CsvNameToProduct):
     @override
-    def get_energy_and_quantity(self, filename: str) -> Optional[tuple[int, str]]:
-        if fn_match := re.match("map_([a-zA-Z]+)_esa(\d{1}).csv", filename):
+    def get_energy_and_quantity(self, filename: str) -> tuple[int, str] | None:
+        if fn_match := re.match(r"map_([a-zA-Z]+)_esa(\d{1}).csv", filename):
             [quantity, energy] = fn_match.groups()
 
             csv_to_l2_cdf_mapping = {
@@ -68,8 +64,8 @@ def get_energy_and_quantity(self, filename: str) -> Optional[tuple[int, str]]:
 
 class CGNameMapping(CsvNameToProduct):
     @override
-    def get_energy_and_quantity(self, filename: str) -> Optional[tuple[int, str]]:
-        if fn_match := re.match("([a-zA-Z]+_[a-zA-Z]+)_esa(\d{1}).csv", filename):
+    def get_energy_and_quantity(self, filename: str) -> tuple[int, str] | None:
+        if fn_match := re.match(r"([a-zA-Z]+_[a-zA-Z]+)_esa(\d{1}).csv", filename):
             [quantity, energy] = fn_match.groups()
 
             csv_to_l2_cdf_mapping = {
@@ -92,10 +88,8 @@ def __init__(self, correction: Literal["sput", "boot"]):
         self.correction = correction
 
     @override
-    def get_energy_and_quantity(self, filename: str) -> Optional[tuple[int, str]]:
-        if fn_match := re.match(
-            "map_flux_(\d{1})_Hy_([a-zA-Z]+)_([a-zA-Z]+).csv", filename
-        ):
+    def get_energy_and_quantity(self, filename: str) -> tuple[int, str] | None:
+        if fn_match := re.match(r"map_flux_(\d{1})_Hy_([a-zA-Z]+)_([a-zA-Z]+).csv", filename):
             [energy, correction, quantity] = fn_match.groups()
 
             csv_to_l2_cdf_mapping = {
@@ -146,9 +140,7 @@ class LoProcessingInput:
     def load_data_dir(data_dir: Path, name_mapping: CsvNameToProduct, **kwargs):
         temp_data = {}
         for data_file_path in data_dir.iterdir():
-            if energy_and_quantity := name_mapping.get_energy_and_quantity(
-                data_file_path.name
-            ):
+            if energy_and_quantity := name_mapping.get_energy_and_quantity(data_file_path.name):
                 esa_step, data_type = energy_and_quantity
                 if data_type not in temp_data:
                     temp_data[data_type] = np.full((1, 7, 60, 30), np.nan)
@@ -170,23 +162,15 @@ def load(
     ) -> Self:
         if use_masked_data:
             loaded_data = {
-                **LoProcessingInput.load_data_dir(
-                    input_path / "maps", name_mapping, skiprows=1
-                ),
-                **LoProcessingInput.load_data_dir(
-                    input_path / "masked_maps", name_mapping
-                ),
+                **LoProcessingInput.load_data_dir(input_path / "maps", name_mapping, skiprows=1),
+                **LoProcessingInput.load_data_dir(input_path / "masked_maps", name_mapping),
             }
         else:
             loaded_data = {
-                **LoProcessingInput.load_data_dir(
-                    input_path / "maps", name_mapping, skiprows=1
-                ),
+                **LoProcessingInput.load_data_dir(input_path / "maps", name_mapping, skiprows=1),
             }
 
-        start_date_nanoseconds = (
-            manifest.start_date - TT2000_EPOCH
-        ).total_seconds() * 1e9
+        start_date_nanoseconds = (manifest.start_date - TT2000_EPOCH).total_seconds() * 1e9
         end_date_nanoseconds = (manifest.end_date - TT2000_EPOCH).total_seconds() * 1e9
 
         skymap = RectangularSkyMap(6, SpiceFrame.ECLIPJ2000)
@@ -210,10 +194,7 @@ def load(
                     ["energy"],
                     LO_ENERGY_BIN_UPPERS - LO_ENERGIES_IN_KEV,
                 ),
-                **{
-                    quantity: (map_data_coords, data)
-                    for quantity, data in loaded_data.items()
-                },
+                **{quantity: (map_data_coords, data) for quantity, data in loaded_data.items()},
                 **additional_map_data,
             },
             coords={
@@ -225,15 +206,11 @@ def load(
         )
 
         if "ena_intensity_stat_var" in l2_dataset.data_vars:
-            l2_dataset["ena_intensity_stat_uncert"] = np.sqrt(
-                l2_dataset["ena_intensity_stat_var"]
-            )
+            l2_dataset["ena_intensity_stat_uncert"] = np.sqrt(l2_dataset["ena_intensity_stat_var"])
             l2_dataset.drop_vars(["ena_intensity_stat_var"])
 
         if "bg_intensity_stat_var" in l2_dataset.data_vars:
-            l2_dataset["bg_intensity_stat_uncert"] = np.sqrt(
-                l2_dataset["bg_intensity_stat_var"]
-            )
+            l2_dataset["bg_intensity_stat_uncert"] = np.sqrt(l2_dataset["bg_intensity_stat_var"])
             l2_dataset.drop_vars(["bg_intensity_stat_var"])
 
         variables_to_mask = [
@@ -277,9 +254,7 @@ def get_spx_dependencies(self):
     def get_survival_corrected_dependencies(self, l1c_files: list[Path]):
         # l1c_results = imap_data_access.query(instrument="lo", data_level="l1c", version="latest")
         # l1c_inputs = [Path(l1c["file_path"]) for l1c in l1c_results if l1c["repointing"] in self.repoints]
-        l1c_inputs = [
-            p for p in l1c_files if ScienceFilePath(p.name).repointing in self.repoints
-        ]
+        l1c_inputs = [p for p in l1c_files if ScienceFilePath(p.name).repointing in self.repoints]
 
         glows_query_results = imap_data_access.query(
             instrument="glows",
@@ -294,10 +269,7 @@ def get_survival_corrected_dependencies(self, l1c_files: list[Path]):
         ]
 
         return ProcessingInputCollection(
-            *(
-                ScienceInput(p.name)
-                for p in [self.l2_cdf_path, *glows_paths, *l1c_inputs]
-            )
+            *(ScienceInput(p.name) for p in [self.l2_cdf_path, *glows_paths, *l1c_inputs])
         )
 
     def make_l3_input_metadata(self, l3_descriptor: str) -> InputMetadata:
@@ -335,9 +307,7 @@ def copy_to_output_directory_and_rename_for_initial_release(
         output_dir.mkdir(parents=True, exist_ok=True)
         output_path = output_dir / new_name
 
-        with CDF(
-            str(output_path), masterpath=str(generated_path), readonly=False
-        ) as cdf:
+        with CDF(str(output_path), masterpath=str(generated_path), readonly=False) as cdf:
             cdf.attrs["Logical_file_id"] = output_path.stem
 
 
@@ -345,9 +315,7 @@ def download_all_l1c(path: Path):
     original_data_dir = imap_data_access.config["DATA_DIR"]
     try:
         imap_data_access.config["DATA_DIR"] = path
-        all_l1c = imap_data_access.query(
-            instrument="lo", data_level="l1c", version="latest"
-        )
+        all_l1c = imap_data_access.query(instrument="lo", data_level="l1c", version="latest")
 
         with ThreadPoolExecutor() as pool:
             for l1c in all_l1c:
@@ -386,7 +354,7 @@ def download_all_l1c(path: Path):
         shutil.copy(file, output_path)
         l1c_paths.append(output_path)
     if len(l1c_paths) == 0:
-        raise Exception(f"Expected l1c files to be provided in {local_l1c_input}")
+        raise ValueError(f"Expected l1c files to be provided in {local_l1c_input}")
 
     output_maps = []
     for masked, descriptor_suffix in [(False, ""), (True, "Msk")]:
@@ -458,9 +426,7 @@ def download_all_l1c(path: Path):
                 manifest=manifest,
                 l2_descriptor=f"l{pivot:03d}-enasnbs{descriptor_suffix}-h-sf-nsp-ram-hae-6deg-6mo",
                 version=1,
-                input_path=sputter_or_bootstrap_input_path
-                / "outdir"
-                / f"pivot_{pivot}",
+                input_path=sputter_or_bootstrap_input_path / "outdir" / f"pivot_{pivot}",
                 name_mapping=SputterOrBootStrapNameMapping("sput"),
                 use_masked_data=masked,
                 exposure_factor=nbs_processing_input.dataset["exposure_factor"],
@@ -470,9 +436,7 @@ def download_all_l1c(path: Path):
                 manifest=manifest,
                 l2_descriptor=f"l{pivot:03d}-enasbs{descriptor_suffix}-h-sf-nsp-ram-hae-6deg-6mo",
                 version=1,
-                input_path=sputter_or_bootstrap_input_path
-                / "outdir"
-                / f"pivot_{pivot}",
+                input_path=sputter_or_bootstrap_input_path / "outdir" / f"pivot_{pivot}",
                 name_mapping=SputterOrBootStrapNameMapping("boot"),
                 use_masked_data=masked,
                 exposure_factor=nbs_processing_input.dataset["exposure_factor"],
@@ -540,10 +504,7 @@ def download_all_l1c(path: Path):
         combined_inputs = []
         for output_map in output_maps:
             if any(
-                [
-                    f"_{combined_dep}_" in output_map.name
-                    for combined_dep in combined_dependencies
-                ]
+                f"_{combined_dep}_" in output_map.name for combined_dep in combined_dependencies
             ):
                 combined_inputs.append(output_map)
 
@@ -582,6 +543,4 @@ def download_all_l1c(path: Path):
         output_maps.extend([combined_sp_map, combined_spx_map])
 
     release_directory = get_run_local_data_path("IMAP-Lo June 2nd 2026 Maps")
-    copy_to_output_directory_and_rename_for_initial_release(
-        release_directory, output_maps
-    )
+    copy_to_output_directory_and_rename_for_initial_release(release_directory, output_maps)
diff --git a/imap_l3_processing/maps/hilo_l3_survival_dependencies.py b/imap_l3_processing/maps/hilo_l3_survival_dependencies.py
index 73052d51..fea8c476 100644
--- a/imap_l3_processing/maps/hilo_l3_survival_dependencies.py
+++ b/imap_l3_processing/maps/hilo_l3_survival_dependencies.py
@@ -8,18 +8,18 @@
 from imap_data_access.processing_input import ProcessingInputCollection
 
 from imap_l3_processing.hi.utils import (
-    read_l1c_rectangular_pointing_set_data,
     read_glows_l3e_data,
+    read_l1c_rectangular_pointing_set_data,
 )
 from imap_l3_processing.maps.map_descriptors import (
     MapDescriptorParts,
-    parse_map_descriptor,
     SpinPhase,
+    parse_map_descriptor,
 )
 from imap_l3_processing.maps.map_models import (
-    RectangularIntensityMapData,
     GlowsL3eRectangularMapInputData,
     InputRectangularPointingSet,
+    RectangularIntensityMapData,
 )
 from imap_l3_processing.models import Instrument
 
@@ -37,21 +37,13 @@ class HiLoL3SurvivalDependencies:
     def fetch_dependencies(
         cls, dependencies: ProcessingInputCollection, instrument: Instrument
     ) -> HiLoL3SurvivalDependencies:
-        [l2_map_path] = dependencies.get_file_paths(
-            source=instrument.value, data_type="l2"
-        )
-        l1c_paths = dependencies.get_file_paths(
-            source=instrument.value, data_type="l1c"
-        )
+        [l2_map_path] = dependencies.get_file_paths(source=instrument.value, data_type="l2")
+        l1c_paths = dependencies.get_file_paths(source=instrument.value, data_type="l1c")
         glows_paths = dependencies.get_file_paths(source="glows")
 
         map_file_path = imap_data_access.download(l2_map_path.name)
-        l1c_downloaded_paths = [
-            imap_data_access.download(l1c.name) for l1c in l1c_paths
-        ]
-        glows_downloaded_paths = [
-            imap_data_access.download(path.name) for path in glows_paths
-        ]
+        l1c_downloaded_paths = [imap_data_access.download(l1c.name) for l1c in l1c_paths]
+        glows_downloaded_paths = [imap_data_access.download(path.name) for path in glows_paths]
 
         l2_descriptor = ScienceFilePath(l2_map_path).descriptor
 
diff --git a/imap_l3_processing/maps/map_combination.py b/imap_l3_processing/maps/map_combination.py
index 568cfab2..71bb7c5a 100644
--- a/imap_l3_processing/maps/map_combination.py
+++ b/imap_l3_processing/maps/map_combination.py
@@ -5,8 +5,8 @@
 
 from imap_l3_processing.data_utils import safe_divide
 from imap_l3_processing.maps.map_models import (
-    IntensityMapData,
     HealPixIntensityMapData,
+    IntensityMapData,
     RectangularIntensityMapData,
     calculate_datetime_weighted_average,
 )
@@ -17,18 +17,10 @@ def combine_rectangular_intensity_map_data(
         self, maps: list[RectangularIntensityMapData]
     ) -> RectangularIntensityMapData:
         for m in maps[1:]:
-            assert np.array_equal(
-                maps[0].coords.latitude_delta, m.coords.latitude_delta
-            )
-            assert np.array_equal(
-                maps[0].coords.longitude_delta, m.coords.longitude_delta
-            )
-            assert np.array_equal(
-                maps[0].coords.latitude_label, m.coords.latitude_label
-            )
-            assert np.array_equal(
-                maps[0].coords.longitude_label, m.coords.longitude_label
-            )
+            assert np.array_equal(maps[0].coords.latitude_delta, m.coords.latitude_delta)
+            assert np.array_equal(maps[0].coords.longitude_delta, m.coords.longitude_delta)
+            assert np.array_equal(maps[0].coords.latitude_label, m.coords.latitude_label)
+            assert np.array_equal(maps[0].coords.longitude_label, m.coords.longitude_label)
 
         self._check_maps_match([m.intensity_map_data for m in maps])
         intensity_map_data = self._combine([m.intensity_map_data for m in maps])
@@ -41,9 +33,7 @@ def combine_healpix_intensity_map_data(
     ) -> HealPixIntensityMapData:
         for m in maps[1:]:
             assert np.array_equal(maps[0].coords.pixel_index, m.coords.pixel_index)
-            assert np.array_equal(
-                maps[0].coords.pixel_index_label, m.coords.pixel_index_label
-            )
+            assert np.array_equal(maps[0].coords.pixel_index_label, m.coords.pixel_index_label)
 
         self._check_maps_match([m.intensity_map_data for m in maps])
         intensity_map_data = self._combine([m.intensity_map_data for m in maps])
@@ -83,9 +73,7 @@ def _check_maps_match(maps: list[IntensityMapData]):
         for field in dataclasses.fields(first_map):
             if field.name not in fields_which_may_differ:
                 differing_fields.append(field.name)
-                supports_nan = np.issubdtype(
-                    first_map_dict[field.name].dtype, np.floating
-                )
+                supports_nan = np.issubdtype(first_map_dict[field.name].dtype, np.floating)
                 assert np.all(
                     [
                         np.array_equal(
@@ -98,17 +86,13 @@ def _check_maps_match(maps: list[IntensityMapData]):
                 ), f"{field.name}"
 
     @staticmethod
-    def calculated_weighted_uncertainty(
-        values: np.ndarray, weights: np.ndarray
-    ) -> np.ndarray:
+    def calculated_weighted_uncertainty(values: np.ndarray, weights: np.ndarray) -> np.ndarray:
         masked_values = np.where(weights == 0, 0, values)
         numerator = np.sum(np.square(masked_values * weights), axis=0)
         return np.sqrt(safe_divide(numerator, np.square(np.sum(weights, axis=0))))
 
     @staticmethod
-    def calculate_weighted_sys_err(
-        values: np.ndarray, weights: np.ndarray
-    ) -> np.ndarray:
+    def calculate_weighted_sys_err(values: np.ndarray, weights: np.ndarray) -> np.ndarray:
         numerator = np.sum(values * weights, axis=0)
         denominator = np.sum(weights, axis=0)
 
@@ -155,11 +139,7 @@ def _combine(self, maps: list[IntensityMapData]) -> IntensityMapData:
 
         survival_probabilities = np.array([m.survival_probability for m in maps])
         if all(m.survival_probability is not None for m in maps):
-            sp_mask = (
-                np.isnan(survival_probabilities)
-                | (exposures == 0)
-                | np.isnan(exposures)
-            )
+            sp_mask = np.isnan(survival_probabilities) | (exposures == 0) | np.isnan(exposures)
             masked_survival_probabilities = np.where(sp_mask, 0, survival_probabilities)
             sp_masked_weights = np.where(sp_mask, 0, 1)
             summed_survival_probability = np.sum(
@@ -215,11 +195,7 @@ def _combine(self, maps: list[IntensityMapData]):
 
         survival_probabilities = np.array([m.survival_probability for m in maps])
         if all(m.survival_probability is not None for m in maps):
-            sp_mask = (
-                np.isnan(survival_probabilities)
-                | (exposures == 0)
-                | np.isnan(exposures)
-            )
+            sp_mask = np.isnan(survival_probabilities) | (exposures == 0) | np.isnan(exposures)
             masked_survival_probabilities = np.where(sp_mask, 0, survival_probabilities)
             sp_masked_exposures = np.where(sp_mask, 0, exposures)
             summed_survival_probability = np.sum(
@@ -239,12 +215,8 @@ def _combine(self, maps: list[IntensityMapData]):
         bg_intensity_sys_err = np.array([m.bg_intensity_sys_err for m in maps])
         bg_intensity_stat_uncert = np.array([m.bg_intensity_stat_uncert for m in maps])
 
-        ena_intensity_sys_err_plus = np.array(
-            [m.ena_intensity_sys_err_plus for m in maps]
-        )
-        ena_intensity_sys_err_minus = np.array(
-            [m.ena_intensity_sys_err_minus for m in maps]
-        )
+        ena_intensity_sys_err_plus = np.array([m.ena_intensity_sys_err_plus for m in maps])
+        ena_intensity_sys_err_minus = np.array([m.ena_intensity_sys_err_minus for m in maps])
 
         def all_elem_defined(array):
             return all(v is not None for v in array)
@@ -342,9 +314,7 @@ def _combine(self, maps: list[IntensityMapData]) -> IntensityMapData:
         summed_exposures = np.sum(masked_exposures, axis=0)
 
         squared_stat_unc = np.square(intensity_stat_unc)
-        inverse_squared_stat_unc = safe_divide(
-            np.ones_like(squared_stat_unc), squared_stat_unc
-        )
+        inverse_squared_stat_unc = safe_divide(np.ones_like(squared_stat_unc), squared_stat_unc)
         uncertainty_weighted_combined_intensity = safe_divide(
             np.nansum(safe_divide(intensities, squared_stat_unc), axis=0),
             np.nansum(inverse_squared_stat_unc, axis=0),
diff --git a/imap_l3_processing/maps/map_descriptors.py b/imap_l3_processing/maps/map_descriptors.py
index ec82313f..6b2985e1 100644
--- a/imap_l3_processing/maps/map_descriptors.py
+++ b/imap_l3_processing/maps/map_descriptors.py
@@ -2,7 +2,6 @@
 import re
 from dataclasses import dataclass
 from datetime import timedelta
-from typing import Optional
 
 
 class Sensor(enum.Enum):
@@ -80,7 +79,7 @@ class MapDescriptorParts:
     duration: str
     quantity: MapQuantity
     quantity_suffix: str
-    spectral_index_energy_range: Optional[tuple[int, int]] = None
+    spectral_index_energy_range: tuple[int, int] | None = None
 
 
 sensor_mapping = [
@@ -130,7 +129,7 @@ class MapDescriptorParts:
 ]
 
 
-def parse_map_descriptor(descriptor: str) -> Optional[MapDescriptorParts]:
+def parse_map_descriptor(descriptor: str) -> MapDescriptorParts | None:
     descriptor_regex = """
         (?P<sensor>hic|h45|h90|l090|l105|l075|ulc|u45|u90|ilo)-
         (?P<quantity>ena|spxnbs|spx|isn)(?P<spectral_index_range>[0-9]{4})?(?P<quantity_suffix>[a-zA-Z]*)-
@@ -148,9 +147,7 @@ def parse_map_descriptor(descriptor: str) -> Optional[MapDescriptorParts]:
         return None
 
     sensor_part_from_str = {desc: sensor_part for desc, sensor_part in sensor_mapping}
-    quantity_part_from_str = {
-        desc: quantity_part for desc, quantity_part in quantity_mapping
-    }
+    quantity_part_from_str = {desc: quantity_part for desc, quantity_part in quantity_mapping}
     cg_correction_part_from_str = {
         desc: cg_correction_part for desc, cg_correction_part in cg_correction_mapping
     }
@@ -160,9 +157,7 @@ def parse_map_descriptor(descriptor: str) -> Optional[MapDescriptorParts]:
     spin_phase_part_from_str = {
         desc: spin_phase_part for desc, spin_phase_part in spin_phase_mapping
     }
-    grid_size_part_from_str = {
-        desc: grid_size_part for desc, grid_size_part in grid_size_mapping
-    }
+    grid_size_part_from_str = {desc: grid_size_part for desc, grid_size_part in grid_size_mapping}
     spectral_index_energy_range = None
     if descriptor_part_match["spectral_index_range"] is not None:
         spectral_index_energy_range = (
@@ -188,9 +183,7 @@ def parse_map_descriptor(descriptor: str) -> Optional[MapDescriptorParts]:
 
 def map_descriptor_parts_to_string(descriptor_parts: MapDescriptorParts) -> str:
     sensor_part_to_str = {sensor_part: desc for desc, sensor_part in sensor_mapping}
-    quantity_part_to_str = {
-        quantity_part: desc for desc, quantity_part in quantity_mapping
-    }
+    quantity_part_to_str = {quantity_part: desc for desc, quantity_part in quantity_mapping}
     cg_correction_part_to_str = {
         cg_correction_part: desc for desc, cg_correction_part in cg_correction_mapping
     }
@@ -200,9 +193,7 @@ def map_descriptor_parts_to_string(descriptor_parts: MapDescriptorParts) -> str:
     spin_phase_part_to_str = {
         spin_phase_part: desc for desc, spin_phase_part in spin_phase_mapping
     }
-    grid_size_part_to_str = {
-        grid_size_part: desc for desc, grid_size_part in grid_size_mapping
-    }
+    grid_size_part_to_str = {grid_size_part: desc for desc, grid_size_part in grid_size_mapping}
     spectral_index_energy_range = ""
     if descriptor_parts.spectral_index_energy_range is not None:
         spectral_index_energy_range = f"{descriptor_parts.spectral_index_energy_range[0]:02}{descriptor_parts.spectral_index_energy_range[1]:02}"
diff --git a/imap_l3_processing/maps/map_initializer.py b/imap_l3_processing/maps/map_initializer.py
index 20fe45d1..fa2b1734 100644
--- a/imap_l3_processing/maps/map_initializer.py
+++ b/imap_l3_processing/maps/map_initializer.py
@@ -5,7 +5,7 @@
 from pathlib import Path
 
 import imap_data_access
-from imap_data_access import ScienceFilePath, ImapFilePath, ProcessingInputCollection
+from imap_data_access import ImapFilePath, ProcessingInputCollection, ScienceFilePath
 from imap_data_access.file_validation import Version
 from imap_data_access.processing_input import generate_imap_input
 
@@ -29,9 +29,7 @@ def processing_input_collection(self) -> ProcessingInputCollection:
 
 class MapInitializer(abc.ABC):
     def __init__(self, instrument: str):
-        l3_query_results = imap_data_access.query(
-            instrument=instrument, data_level="l3"
-        )
+        l3_query_results = imap_data_access.query(instrument=instrument, data_level="l3")
         self.existing_l3_maps = self.get_latest_version_by_descriptor_and_start_date(
             l3_query_results
         )
@@ -57,25 +55,18 @@ def get_maps_that_should_be_produced(
                 {descriptor: Version(major_version, 1)}
             )
 
-            if highest_version_path_by_start_date := self.existing_l3_maps.get(
-                descriptor
+            if (highest_version_path_by_start_date := self.existing_l3_maps.get(descriptor)) and (
+                path_with_highest_version := highest_version_path_by_start_date.get(start_time)
             ):
-                if path_with_highest_version := highest_version_path_by_start_date.get(
-                    start_time
+                existing_parents = read_cdf_parents(path_with_highest_version)
+                existing_path = ScienceFilePath(path_with_highest_version)
+                if (
+                    possible_map.input_files.issubset(existing_parents)
+                    and major_version == existing_path.major_version
                 ):
-                    existing_parents = read_cdf_parents(path_with_highest_version)
-                    existing_path = ScienceFilePath(path_with_highest_version)
-                    if (
-                        possible_map.input_files.issubset(existing_parents)
-                        and major_version == existing_path.major_version
-                    ):
-                        continue
-                    new_version = Version(
-                        major_version, existing_path.minor_version + 1
-                    )
-                    possible_map.input_metadata.version = VersionMap(
-                        {descriptor: new_version}
-                    )
+                    continue
+                new_version = Version(major_version, existing_path.minor_version + 1)
+                possible_map.input_metadata.version = VersionMap({descriptor: new_version})
             maps_to_make.append(possible_map)
         return maps_to_make
 
@@ -97,17 +88,15 @@ def get_latest_version_by_descriptor_and_start_date(
     ) -> defaultdict:
         qr_by_descriptor_and_start_date = defaultdict(list)
         for qr in query_results:
-            qr_by_descriptor_and_start_date[
-                (qr["descriptor"], qr["start_date"])
-            ].append(qr)
+            qr_by_descriptor_and_start_date[(qr["descriptor"], qr["start_date"])].append(qr)
 
         file_paths_by_descriptor = defaultdict(dict)
         for (
             descriptor,
             start_date,
-        ), query_results in qr_by_descriptor_and_start_date.items():
+        ), qr in qr_by_descriptor_and_start_date.items():
             highest_version_qr = max(
-                query_results,
+                qr,
                 key=lambda x: (
                     x["minor_version"]
                     if "minor_version" in x
diff --git a/imap_l3_processing/maps/map_models.py b/imap_l3_processing/maps/map_models.py
index 2ea828f6..1b18772e 100644
--- a/imap_l3_processing/maps/map_models.py
+++ b/imap_l3_processing/maps/map_models.py
@@ -2,9 +2,9 @@
 
 import abc
 from dataclasses import dataclass
-from datetime import timedelta, datetime
+from datetime import datetime, timedelta
 from pathlib import Path
-from typing import Generic, Optional
+from typing import Generic
 
 import numpy as np
 import xarray
@@ -14,12 +14,12 @@
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.cdf.cdf_utils import (
-    read_variable_and_mask_fill_values,
     read_numeric_variable,
+    read_variable_and_mask_fill_values,
 )
 from imap_l3_processing.constants import TT2000_EPOCH
 from imap_l3_processing.maps.quality_flags import MapL3Flags
-from imap_l3_processing.models import DataProduct, DataProductVariable, D
+from imap_l3_processing.models import D, DataProduct, DataProductVariable
 
 EPOCH_VAR_NAME = "epoch"
 EPOCH_DELTA_VAR_NAME = "epoch_delta"
@@ -42,9 +42,7 @@
 ENA_SPECTRAL_INDEX_VAR_NAME = "ena_spectral_index"
 ENA_SPECTRAL_INDEX_STAT_UNC_VAR_NAME = "ena_spectral_index_stat_uncert"
 ENA_SPECTRAL_INDEX_SCALAR_COEFFICIENT_VAR_NAME = "ena_spectral_scalar"
-ENA_SPECTRAL_INDEX_SCALAR_COEFFICIENT_STAT_UNCERT_VAR_NAME = (
-    "ena_spectral_scalar_stat_uncert"
-)
+ENA_SPECTRAL_INDEX_SCALAR_COEFFICIENT_STAT_UNCERT_VAR_NAME = "ena_spectral_scalar_stat_uncert"
 ENA_SPECTRAL_INDEX_CHISQ_VAR_NAME = "ena_spectral_index_chisq"
 
 ENA_INTENSITY_VAR_NAME = "ena_intensity"
@@ -115,12 +113,12 @@ class IntensityMapData(MapData):
     ena_intensity_stat_uncert: np.ndarray
     ena_intensity_sys_err: np.ndarray
     quality_flags: np.ndarray
-    ena_intensity_sys_err_minus: Optional[np.ndarray] = None
-    ena_intensity_sys_err_plus: Optional[np.ndarray] = None
-    bg_intensity: Optional[np.ndarray] = None
-    bg_intensity_stat_uncert: Optional[np.ndarray] = None
-    bg_intensity_sys_err: Optional[np.ndarray] = None
-    survival_probability: Optional[np.ndarray] = None
+    ena_intensity_sys_err_minus: np.ndarray | None = None
+    ena_intensity_sys_err_plus: np.ndarray | None = None
+    bg_intensity: np.ndarray | None = None
+    bg_intensity_stat_uncert: np.ndarray | None = None
+    bg_intensity_sys_err: np.ndarray | None = None
+    survival_probability: np.ndarray | None = None
 
 
 @dataclass
@@ -200,15 +198,9 @@ def read_from_path(cls, cdf_path: Path | str) -> ISNRateData:
             if "obs_date" in cdf and "obs_date_range" in cdf:
                 masked_obs_date = read_variable_and_mask_fill_values(cdf["obs_date"])
                 if np.issubdtype(cdf["obs_date"].dtype, np.number):
-                    obs_date = convert_tt2000_time_to_datetime(
-                        masked_obs_date.filled(0)
-                    )
-                    masked_obs_date = np.ma.masked_array(
-                        data=obs_date, mask=masked_obs_date.mask
-                    )
-                obs_date_range = read_variable_and_mask_fill_values(
-                    cdf["obs_date_range"]
-                )
+                    obs_date = convert_tt2000_time_to_datetime(masked_obs_date.filled(0))
+                    masked_obs_date = np.ma.masked_array(data=obs_date, mask=masked_obs_date.mask)
+                obs_date_range = read_variable_and_mask_fill_values(cdf["obs_date_range"])
             else:
                 obs_date_shape = cdf["bg_rate"].shape
                 all_mask_array = np.full(obs_date_shape, True)
@@ -238,12 +230,8 @@ def read_from_path(cls, cdf_path: Path | str) -> ISNRateData:
                 longitude_delta=(cdf["longitude_delta"][...]),
                 longitude_label=(cdf["longitude_label"][...]),
                 ena_intensity=read_numeric_variable(cdf["ena_intensity"]),
-                ena_intensity_stat_uncert=read_numeric_variable(
-                    cdf["ena_intensity_stat_uncert"]
-                ),
-                ena_intensity_sys_err=read_numeric_variable(
-                    cdf["ena_intensity_sys_err"]
-                ),
+                ena_intensity_stat_uncert=read_numeric_variable(cdf["ena_intensity_stat_uncert"]),
+                ena_intensity_sys_err=read_numeric_variable(cdf["ena_intensity_sys_err"]),
                 energy=(cdf["energy"][...]),
                 energy_delta_plus=(cdf["energy_delta_plus"][...]),
                 energy_delta_minus=(cdf["energy_delta_minus"][...]),
@@ -311,18 +299,15 @@ def to_healpix_skymap(self) -> HealpixSkyMap:
                 ),
                 "predicted_ephemeris_flag": (
                     full_shape,
-                    self.intensity_map_data.quality_flags
-                    & MapL3Flags.PREDICTIVE_EPHEMERIS,
+                    self.intensity_map_data.quality_flags & MapL3Flags.PREDICTIVE_EPHEMERIS,
                 ),
                 "nominal_alpha_proton_ratio_flag": (
                     full_shape,
-                    self.intensity_map_data.quality_flags
-                    & MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
+                    self.intensity_map_data.quality_flags & MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
                 ),
                 "persisted_last_point_flag": (
                     full_shape,
-                    self.intensity_map_data.quality_flags
-                    & MapL3Flags.PERSISTED_LAST_POINT,
+                    self.intensity_map_data.quality_flags & MapL3Flags.PERSISTED_LAST_POINT,
                 ),
             },
             coords={
@@ -378,9 +363,7 @@ def _read_intensity_map_data_from_open_cdf(cdf: CDF) -> IntensityMapData:
         masked_obs_date = read_variable_and_mask_fill_values(cdf["obs_date"])
         if np.issubdtype(cdf["obs_date"].dtype, np.number):
             obs_date = convert_tt2000_time_to_datetime(masked_obs_date.filled(0))
-            masked_obs_date = np.ma.masked_array(
-                data=obs_date, mask=masked_obs_date.mask
-            )
+            masked_obs_date = np.ma.masked_array(data=obs_date, mask=masked_obs_date.mask)
         obs_date_range = read_variable_and_mask_fill_values(cdf["obs_date_range"])
     else:
         obs_date_shape = cdf["ena_intensity"].shape
@@ -408,9 +391,7 @@ def _read_intensity_map_data_from_open_cdf(cdf: CDF) -> IntensityMapData:
         obs_date_range=obs_date_range,
         solid_angle=read_numeric_variable(cdf["solid_angle"]),
         ena_intensity=read_numeric_variable(cdf["ena_intensity"]),
-        ena_intensity_stat_uncert=read_numeric_variable(
-            cdf["ena_intensity_stat_uncert"]
-        ),
+        ena_intensity_stat_uncert=read_numeric_variable(cdf["ena_intensity_stat_uncert"]),
         ena_intensity_sys_err=read_numeric_variable(cdf["ena_intensity_sys_err"]),
         quality_flags=quality_flag_data,
     )
@@ -454,9 +435,7 @@ def _read_intensity_map_data_from_xarray(dataset: xarray.Dataset) -> IntensityMa
         epoch_delta=_replace_fill_values_in_xarray(dataset, "epoch_delta"),
         energy=dataset.coords[CoordNames.ENERGY_L2.value].values,
         energy_delta_plus=_replace_fill_values_in_xarray(dataset, "energy_delta_plus"),
-        energy_delta_minus=_replace_fill_values_in_xarray(
-            dataset, "energy_delta_minus"
-        ),
+        energy_delta_minus=_replace_fill_values_in_xarray(dataset, "energy_delta_minus"),
         energy_label=_replace_fill_values_in_xarray(dataset, "energy_label"),
         latitude=_replace_fill_values_in_xarray(dataset, "latitude"),
         longitude=_replace_fill_values_in_xarray(dataset, "longitude"),
@@ -468,9 +447,7 @@ def _read_intensity_map_data_from_xarray(dataset: xarray.Dataset) -> IntensityMa
         ena_intensity_stat_uncert=_replace_fill_values_in_xarray(
             dataset, "ena_intensity_stat_uncert"
         ),
-        ena_intensity_sys_err=_replace_fill_values_in_xarray(
-            dataset, "ena_intensity_sys_err"
-        ),
+        ena_intensity_sys_err=_replace_fill_values_in_xarray(dataset, "ena_intensity_sys_err"),
         quality_flags=np.full(intensity.shape, MapL3Flags.NONE),
     )
 
@@ -511,9 +488,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
         raise NotImplementedError
 
 
-class RectangularSpectralIndexDataProduct(
-    MapDataProduct[RectangularSpectralIndexMapData]
-):
+class RectangularSpectralIndexDataProduct(MapDataProduct[RectangularSpectralIndexMapData]):
     data: RectangularSpectralIndexMapData
 
     def to_data_product_variables(self) -> list[DataProductVariable]:
@@ -531,17 +506,13 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
         ) + _rectangular_coords_to_variables(self.data.coords)
 
 
-class ISNBackgroundSubtractedDataProduct(
-    MapDataProduct[ISNBackgroundSubtractedMapData]
-):
+class ISNBackgroundSubtractedDataProduct(MapDataProduct[ISNBackgroundSubtractedMapData]):
     data: ISNBackgroundSubtractedMapData
 
     def to_data_product_variables(self) -> list[DataProductVariable]:
         return [
             DataProductVariable(EPOCH_VAR_NAME, self.data.isn_rate_map_data.epoch),
-            DataProductVariable(
-                EPOCH_DELTA_VAR_NAME, self.data.isn_rate_map_data.epoch_delta
-            ),
+            DataProductVariable(EPOCH_DELTA_VAR_NAME, self.data.isn_rate_map_data.epoch_delta),
             DataProductVariable(ENERGY_VAR_NAME, self.data.isn_rate_map_data.energy),
             DataProductVariable(
                 ENERGY_DELTA_PLUS_VAR_NAME,
@@ -551,15 +522,11 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 ENERGY_DELTA_MINUS_VAR_NAME,
                 self.data.isn_rate_map_data.energy_delta_minus,
             ),
-            DataProductVariable(
-                ENERGY_LABEL_VAR_NAME, self.data.isn_rate_map_data.energy_label
-            ),
+            DataProductVariable(ENERGY_LABEL_VAR_NAME, self.data.isn_rate_map_data.energy_label),
             DataProductVariable(
                 EXPOSURE_FACTOR_VAR_NAME, self.data.isn_rate_map_data.exposure_factor
             ),
-            DataProductVariable(
-                SOLID_ANGLE_VAR_NAME, self.data.isn_rate_map_data.solid_angle
-            ),
+            DataProductVariable(SOLID_ANGLE_VAR_NAME, self.data.isn_rate_map_data.solid_angle),
             DataProductVariable(BG_RATE_VAR_NAME, self.data.isn_rate_map_data.bg_rate),
             DataProductVariable(
                 BG_RATE_STAT_UNCERT_VAR_NAME,
@@ -568,18 +535,14 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(
                 BG_RATE_SYS_ERR_VAR_NAME, self.data.isn_rate_map_data.bg_rate_sys_err
             ),
-            DataProductVariable(
-                LATITUDE_VAR_NAME, self.data.isn_rate_map_data.latitude
-            ),
+            DataProductVariable(LATITUDE_VAR_NAME, self.data.isn_rate_map_data.latitude),
             DataProductVariable(
                 LATITUDE_DELTA_VAR_NAME, self.data.isn_rate_map_data.latitude_delta
             ),
             DataProductVariable(
                 LATITUDE_LABEL_VAR_NAME, self.data.isn_rate_map_data.latitude_label
             ),
-            DataProductVariable(
-                LONGITUDE_VAR_NAME, self.data.isn_rate_map_data.longitude
-            ),
+            DataProductVariable(LONGITUDE_VAR_NAME, self.data.isn_rate_map_data.longitude),
             DataProductVariable(
                 LONGITUDE_DELTA_VAR_NAME, self.data.isn_rate_map_data.longitude_delta
             ),
@@ -634,9 +597,7 @@ def _spectral_index_data_variables(
             ENA_SPECTRAL_INDEX_SCALAR_COEFFICIENT_STAT_UNCERT_VAR_NAME,
             data.ena_spectral_index_scalar_coefficient_stat_uncert,
         ),
-        DataProductVariable(
-            ENA_SPECTRAL_INDEX_CHISQ_VAR_NAME, data.ena_spectral_index_chisq
-        ),
+        DataProductVariable(ENA_SPECTRAL_INDEX_CHISQ_VAR_NAME, data.ena_spectral_index_chisq),
         DataProductVariable(QUALITY_FLAGS_VAR_NAME, data.quality_flags),
     ]
     return variables
@@ -645,9 +606,7 @@ def _spectral_index_data_variables(
 def _intensity_data_variables(data: IntensityMapData) -> list[DataProductVariable]:
     intensity_variables = [
         DataProductVariable(ENA_INTENSITY_VAR_NAME, data.ena_intensity),
-        DataProductVariable(
-            ENA_INTENSITY_STAT_UNCERT_VAR_NAME, data.ena_intensity_stat_uncert
-        ),
+        DataProductVariable(ENA_INTENSITY_STAT_UNCERT_VAR_NAME, data.ena_intensity_stat_uncert),
         DataProductVariable(ENA_INTENSITY_SYS_ERR_VAR_NAME, data.ena_intensity_sys_err),
         DataProductVariable(QUALITY_FLAGS_VAR_NAME, data.quality_flags),
     ]
@@ -655,20 +614,14 @@ def _intensity_data_variables(data: IntensityMapData) -> list[DataProductVariabl
         intensity_variables.extend(
             [
                 DataProductVariable(BG_INTENSITY_VAR_NAME, data.bg_intensity),
-                DataProductVariable(
-                    BG_INTENSITY_STAT_UNC_VAR_NAME, data.bg_intensity_stat_uncert
-                ),
-                DataProductVariable(
-                    BG_INTENSITY_SYS_ERR_VAR_NAME, data.bg_intensity_sys_err
-                ),
+                DataProductVariable(BG_INTENSITY_STAT_UNC_VAR_NAME, data.bg_intensity_stat_uncert),
+                DataProductVariable(BG_INTENSITY_SYS_ERR_VAR_NAME, data.bg_intensity_sys_err),
             ]
         )
     if data.survival_probability is not None:
         intensity_variables.extend(
             [
-                DataProductVariable(
-                    SURVIVAL_PROBABILITY_VAR_NAME, data.survival_probability
-                ),
+                DataProductVariable(SURVIVAL_PROBABILITY_VAR_NAME, data.survival_probability),
             ]
         )
     if data.ena_intensity_sys_err_minus is not None:
@@ -735,12 +688,12 @@ class GlowsL3eRectangularMapInputData:
 @dataclass
 class InputRectangularPointingSet:
     epoch: datetime
-    epoch_delta: Optional[np.ndarray]
+    epoch_delta: np.ndarray | None
     epoch_j2000: np.ndarray
     repointing: int
     exposure_times: np.ndarray
     esa_energy_step: np.ndarray
-    pointing_start_met: Optional[float]
-    pointing_end_met: Optional[float]
+    pointing_start_met: float | None
+    pointing_end_met: float | None
     hae_longitude: np.ndarray
     hae_latitude: np.ndarray
diff --git a/imap_l3_processing/maps/map_processor.py b/imap_l3_processing/maps/map_processor.py
index 1ee3c6ac..87f1cffa 100644
--- a/imap_l3_processing/maps/map_processor.py
+++ b/imap_l3_processing/maps/map_processor.py
@@ -8,7 +8,5 @@
 
 class MapProcessor(Processor):
     @abstractmethod
-    def process(
-        self, spice_reference_frame: SpiceFrame = SpiceFrame.ECLIPJ2000
-    ) -> list[Path]:
+    def process(self, spice_reference_frame: SpiceFrame = SpiceFrame.ECLIPJ2000) -> list[Path]:
         pass
diff --git a/imap_l3_processing/maps/mpfit.py b/imap_l3_processing/maps/mpfit.py
index c5b88e25..719ad5d7 100644
--- a/imap_l3_processing/maps/mpfit.py
+++ b/imap_l3_processing/maps/mpfit.py
@@ -411,7 +411,6 @@ def myfunct(p, fjac=None, x=None, y=None, err=None)
 import numpy
 import scipy.linalg.blas
 
-
 # fmt: off
 #        Original FORTRAN documentation
 #        **********
@@ -609,7 +608,7 @@ def __init__(
         self,
         fcn,
         xall=None,
-        functkw={},
+        functkw={},  # noqa: B006
         parinfo=None,
         ftol=1.0e-10,
         xtol=1.0e-10,
@@ -619,7 +618,7 @@ def __init__(
         factor=100.0,
         nprint=1,
         iterfunct="default",
-        iterkw={},
+        iterkw={},  # noqa: B006
         nocovar=0,
         rescale=0,
         autoderivative=1,
@@ -888,9 +887,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
         # Parameter damping doesn't work when user is providing their own
         # gradients.
         if (self.damp != 0) and (autoderivative == 0):
-            self.errmsg = (
-                "ERROR: keywords DAMP and AUTODERIVATIVE are mutually exclusive"
-            )
+            self.errmsg = "ERROR: keywords DAMP and AUTODERIVATIVE are mutually exclusive"
             return
 
         # Parameters can either be stored in parinfo, or x. x takes precedence if it exists
@@ -943,9 +940,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
         pfixed = self.parinfo(parinfo, "fixed", default=0, n=npar)
         pfixed = pfixed == 1
         for i in range(npar):
-            pfixed[i] = pfixed[i] or (
-                ptied[i] != ""
-            )  # Tied parameters are also effectively fixed
+            pfixed[i] = pfixed[i] or (ptied[i] != "")  # Tied parameters are also effectively fixed
 
         # Finite differencing step, absolute and relative, and sidedness of deriv.
         step = self.parinfo(parinfo, "step", default=0.0, n=npar)
@@ -981,15 +976,12 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
         if (limited is not None) and (limits is not None):
             # Error checking on limits in parinfo
             if numpy.any(
-                (limited[:, 0] & (xall < limits[:, 0]))
-                | (limited[:, 1] & (xall > limits[:, 1]))
+                (limited[:, 0] & (xall < limits[:, 0])) | (limited[:, 1] & (xall > limits[:, 1]))
             ):
                 self.errmsg = "ERROR: parameters are not within PARINFO limits"
                 return
             if numpy.any(
-                (limited[:, 0] & limited[:, 1])
-                & (limits[:, 0] >= limits[:, 1])
-                & (pfixed == 0)
+                (limited[:, 0] & limited[:, 1]) & (limits[:, 0] >= limits[:, 1]) & (pfixed == 0)
             ):
                 self.errmsg = "ERROR: PARINFO parameter limits are not consistent"
                 return
@@ -1014,14 +1006,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
 
         n = len(x)
         # Check input parameters for errors
-        if (
-            (n < 0)
-            or (ftol <= 0)
-            or (xtol <= 0)
-            or (gtol <= 0)
-            or (maxiter < 0)
-            or (factor <= 0)
-        ):
+        if (n < 0) or (ftol <= 0) or (xtol <= 0) or (gtol <= 0) or (maxiter < 0) or (factor <= 0):
             self.errmsg = "ERROR: input keywords are inconsistent"
             return
 
@@ -1072,7 +1057,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
             if self.qanytied:
                 self.params = self.tie(self.params, ptied)
 
-            if (nprint > 0) and (iterfunct is not None):
+            if (nprint > 0) and (iterfunct is not None):  # noqa: SIM102
                 if ((self.niter - 1) % nprint) == 0:
                     xnew0 = self.params.copy()
 
@@ -1093,9 +1078,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
 
                     # Check for user termination
                     if self.status < 0:
-                        self.errmsg = "WARNING: premature termination by " + str(
-                            iterfunct
-                        )
+                        self.errmsg = "WARNING: premature termination by " + str(iterfunct)
                         return
 
                     # If parameters were changed (grrr..) then re-tie
@@ -1220,9 +1203,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
             while 1:
                 # Determine the levenberg-marquardt parameter
                 self.catch_msg = "calculating LM parameter (MPFIT_)"
-                [fjac, par, wa1, wa2] = self.lmpar(
-                    fjac, ipvt, diag, qtf, delta, wa1, wa2, par=par
-                )
+                [fjac, par, wa1, wa2] = self.lmpar(fjac, ipvt, diag, qtf, delta, wa1, wa2, par=par)
                 # Store the direction p and x+p. Calculate the norm of p
                 wa1 = -wa1
 
@@ -1246,15 +1227,11 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
                             wa1[whupeg] = numpy.clip(wa1[whupeg], numpy.min(wa1), 0.0)
 
                         dwa1 = numpy.abs(wa1) > machep
-                        whl = (
-                            numpy.nonzero(((dwa1 != 0.0) & qllim) & ((x + wa1) < llim))
-                        )[0]
+                        whl = (numpy.nonzero(((dwa1 != 0.0) & qllim) & ((x + wa1) < llim)))[0]
                         if len(whl) > 0:
                             t = (llim[whl] - x[whl]) / wa1[whl]
                             alpha = numpy.min([alpha, numpy.min(t)])
-                        whu = (
-                            numpy.nonzero(((dwa1 != 0.0) & qulim) & ((x + wa1) > ulim))
-                        )[0]
+                        whu = (numpy.nonzero(((dwa1 != 0.0) & qulim) & ((x + wa1) > ulim)))[0]
                         if len(whu) > 0:
                             t = (ulim[whu] - x[whu]) / wa1[whu]
                             alpha = numpy.min([alpha, numpy.min(t)])
@@ -1262,13 +1239,10 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
                     # Obey any max step values.
                     if qminmax:
                         nwa1 = wa1 * alpha
-                        whmax = (
-                            numpy.nonzero((qmax[ifree] != 0.0) & (maxstep[ifree] > 0))
-                        )[0]
+                        whmax = (numpy.nonzero((qmax[ifree] != 0.0) & (maxstep[ifree] > 0)))[0]
                         if len(whmax) > 0:
                             mrat = numpy.max(
-                                numpy.abs(nwa1[whmax])
-                                / numpy.abs(maxstep[ifree[whmax]])
+                                numpy.abs(nwa1[whmax]) / numpy.abs(maxstep[ifree[whmax]])
                             )
                             if mrat > 1:
                                 alpha = alpha / mrat
@@ -1359,11 +1333,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
                     self.niter = self.niter + 1
 
                 # Tests for convergence
-                if (
-                    (numpy.abs(actred) <= ftol)
-                    and (prered <= ftol)
-                    and (0.5 * ratio <= 1)
-                ):
+                if (numpy.abs(actred) <= ftol) and (prered <= ftol) and (0.5 * ratio <= 1):
                     self.status = 1
                 if delta <= xtol * xnorm:
                     self.status = 2
@@ -1380,11 +1350,7 @@ def iterfunct(myfunct, p, iter, fnorm, functkw=None,
                 # Tests for termination and stringent tolerances
                 if self.niter >= maxiter:
                     self.status = 5
-                if (
-                    (numpy.abs(actred) <= machep)
-                    and (prered <= machep)
-                    and (0.5 * ratio <= 1)
-                ):
+                if (numpy.abs(actred) <= machep) and (prered <= machep) and (0.5 * ratio <= 1):
                     self.status = 6
                 if delta <= machep * xnorm:
                     self.status = 7
@@ -1498,11 +1464,12 @@ def defiter(
         if quiet:
             return
         if fnorm is None:
-            [status, fvec] = self.call(fcn, x, functkw)
+            [_status, fvec] = self.call(fcn, x, functkw)
             fnorm = self.enorm(fvec) ** 2
 
         # Determine which parameters to print
         nprint = len(x)
+        # ruff: disable[UP031]
         print(
             "Iter ",
             ("%6i" % iter),
@@ -1522,6 +1489,7 @@ def defiter(
                 iprint = 1
             if iprint:
                 print(p + (pformat % x[i]) + "  ")
+        # ruff: enable[UP031]
         return 0
 
     # fmt: off
@@ -1903,9 +1871,7 @@ def qrfac(self, a, pivot=0):
                         a[j:, lk] = ajk - ajj * sum(ajk * ajj) / a[j, lj]
                         if (pivot != 0) and (rdiag[k] != 0):
                             temp = a[j, lk] / rdiag[k]
-                            rdiag[k] = rdiag[k] * numpy.sqrt(
-                                numpy.max([(1.0 - temp**2), 0.0])
-                            )
+                            rdiag[k] = rdiag[k] * numpy.sqrt(numpy.max([(1.0 - temp**2), 0.0]))
                             temp = rdiag[k] / wa[k]
                             if (0.05 * temp * temp) <= machep:
                                 rdiag[k] = self.enorm(a[j + 1 :, lk])
@@ -2042,9 +2008,7 @@ def qrsolv(self, r, ipvt, diag, qtb, sdiag):
                 # Accumulate the transformation in the row of s
                 if n > k + 1:
                     temp = cosine * r[k + 1 : n, k] + sine * sdiag[k + 1 : n]
-                    sdiag[k + 1 : n] = (
-                        -sine * r[k + 1 : n, k] + cosine * sdiag[k + 1 : n]
-                    )
+                    sdiag[k + 1 : n] = -sine * r[k + 1 : n, k] + cosine * sdiag[k + 1 : n]
                     r[k + 1 : n, k] = temp
             sdiag[j] = r[j, j]
             r[j, j] = x[j]
@@ -2250,7 +2214,7 @@ def lmpar(self, r, ipvt, diag, qtb, delta, x, sdiag, par=None):
 
             if (
                 (numpy.abs(fp) <= 0.1 * delta)
-                or ((parl == 0) and (fp <= temp) and (temp < 0))
+                or ((parl == 0) and (fp <= temp < 0))
                 or (iter == 10)
             ):
                 break
@@ -2290,7 +2254,7 @@ def tie(self, p, ptied=None):
             if ptied[i] == "":
                 continue
             cmd = "p[" + str(i) + "] = " + ptied[i]
-            exec(cmd)
+            exec(cmd)  # noqa: S102
         return p
 
     # fmt: off
diff --git a/imap_l3_processing/maps/quality_flags.py b/imap_l3_processing/maps/quality_flags.py
index 2e097d5c..3d2b295b 100644
--- a/imap_l3_processing/maps/quality_flags.py
+++ b/imap_l3_processing/maps/quality_flags.py
@@ -1,4 +1,4 @@
-from imap_processing.quality_flags import FlagNameMixin, CommonFlags
+from imap_processing.quality_flags import CommonFlags, FlagNameMixin
 
 
 class MapL3Flags(FlagNameMixin):
diff --git a/imap_l3_processing/maps/rectangular_survival_probability.py b/imap_l3_processing/maps/rectangular_survival_probability.py
index 3fd41f4f..e86fe740 100644
--- a/imap_l3_processing/maps/rectangular_survival_probability.py
+++ b/imap_l3_processing/maps/rectangular_survival_probability.py
@@ -1,10 +1,10 @@
 import numpy as np
 import xarray as xr
-from imap_processing.ena_maps.ena_maps import RectangularSkyMap, PointingSet
+from imap_processing.ena_maps.ena_maps import PointingSet, RectangularSkyMap
 from imap_processing.ena_maps.utils.coordinates import CoordNames
 from imap_processing.ena_maps.utils.corrections import (
-    apply_compton_getting_correction,
     add_spacecraft_position_and_velocity_to_pset,
+    apply_compton_getting_correction,
     calculate_ram_mask,
 )
 from imap_processing.spice.geometry import SpiceFrame
@@ -21,9 +21,7 @@
 def interpolate_angular_data_to_nearest_neighbor(
     input_azimuths: np.array, glows_azimuths: np.array, glows_data: np.array
 ) -> np.array:
-    expanded_az = np.concatenate(
-        [glows_azimuths - 360, glows_azimuths, glows_azimuths + 360]
-    )
+    expanded_az = np.concatenate([glows_azimuths - 360, glows_azimuths, glows_azimuths + 360])
     expanded_glows_data = np.concatenate([glows_data, glows_data, glows_data], axis=1)
     sort = np.argsort(expanded_az)
     sorted_az = expanded_az[sort]
@@ -47,17 +45,13 @@ def __init__(
         deg_spacing = 360 / num_spin_angle_bins
         half_bin_width = deg_spacing / 2
 
-        self.azimuths = (
-            np.linspace(0, 360, num_spin_angle_bins, endpoint=False) + half_bin_width
-        )
+        self.azimuths = np.linspace(0, 360, num_spin_angle_bins, endpoint=False) + half_bin_width
 
         sensor_angle = Sensor.get_sensor_angle(sensor)
         self.elevations = np.repeat(sensor_angle, num_spin_angle_bins)
 
         hae_az_el_points = xr.DataArray(
-            np.column_stack(
-                [l1c_dataset.hae_longitude[0], l1c_dataset.hae_latitude[0]]
-            ),
+            np.column_stack([l1c_dataset.hae_longitude[0], l1c_dataset.hae_latitude[0]]),
             dims=[CoordNames.GENERIC_PIXEL.value, CoordNames.AZ_EL_VECTOR.value],
         )
 
@@ -66,15 +60,10 @@ def __init__(
         if l1c_dataset.epoch_delta is not None:
             repointing_midpoint = l1c_dataset.epoch_j2000 + l1c_dataset.epoch_delta / 2
         elif (
-            l1c_dataset.pointing_start_met is not None
-            and l1c_dataset.pointing_end_met is not None
+            l1c_dataset.pointing_start_met is not None and l1c_dataset.pointing_end_met is not None
         ):
-            pointing_duration = (
-                l1c_dataset.pointing_end_met - l1c_dataset.pointing_start_met
-            )
-            repointing_midpoint = l1c_dataset.epoch_j2000 + (
-                1e9 * pointing_duration / 2
-            )
+            pointing_duration = l1c_dataset.pointing_end_met - l1c_dataset.pointing_start_met
+            repointing_midpoint = l1c_dataset.epoch_j2000 + (1e9 * pointing_duration / 2)
 
         initial_dataset = xr.Dataset(
             {},
@@ -155,12 +144,10 @@ def __init__(
             dataset["directional_mask"] = ~dataset["ram_mask"]
 
         if cg_corrected:
-            sp_interpolated_to_pset_angles = (
-                interpolate_angular_data_to_nearest_neighbor(
-                    self.azimuths,
-                    glows_dataset.spin_angle,
-                    glows_dataset.probability_of_survival[0],
-                )
+            sp_interpolated_to_pset_angles = interpolate_angular_data_to_nearest_neighbor(
+                self.azimuths,
+                glows_dataset.spin_angle,
+                glows_dataset.probability_of_survival[0],
             )
             log_sc_frame_energies = np.log10(spacecraft_frame_energies_in_kev[0])
 
@@ -173,9 +160,7 @@ def __init__(
                 )
         else:
             glows_spin_bin_count = len(glows_dataset.spin_angle)
-            sp_interpolated_to_hi_energies = np.empty(
-                shape=(len(energies), glows_spin_bin_count)
-            )
+            sp_interpolated_to_hi_energies = np.empty(shape=(len(energies), glows_spin_bin_count))
             for spin_angle_index in range(glows_spin_bin_count):
                 sp_interpolated_to_hi_energies[:, spin_angle_index] = np.interp(
                     np.log10(energies),
@@ -183,15 +168,11 @@ def __init__(
                     glows_dataset.probability_of_survival[0, :, spin_angle_index],
                 )
 
-            sp_interpolated_to_pset_angles = np.zeros(
-                (1, len(energies), num_spin_angle_bins)
-            )
-            sp_interpolated_to_pset_angles[0] = (
-                interpolate_angular_data_to_nearest_neighbor(
-                    self.azimuths,
-                    glows_dataset.spin_angle,
-                    sp_interpolated_to_hi_energies,
-                )
+            sp_interpolated_to_pset_angles = np.zeros((1, len(energies), num_spin_angle_bins))
+            sp_interpolated_to_pset_angles[0] = interpolate_angular_data_to_nearest_neighbor(
+                self.azimuths,
+                glows_dataset.spin_angle,
+                sp_interpolated_to_hi_energies,
             )
             sp_final = sp_interpolated_to_pset_angles
         flag_value = glows_dataset.flags[0]
@@ -222,9 +203,7 @@ def __init__(
                 CoordNames.AZIMUTH_L1C.value,
             ],
         )
-        nominal_alpha_proton_flag_set = (
-            flag_value & GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO != 0
-        )
+        nominal_alpha_proton_flag_set = flag_value & GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO != 0
         dataset["nominal_alpha_proton_ratio_flag"] = xr.DataArray(
             exposure * nominal_alpha_proton_flag_set,
             dims=[
@@ -234,9 +213,7 @@ def __init__(
             ],
         )
 
-        persisted_last_point_flag_set = (
-            flag_value & GlowsL3Flags.PERSISTED_LAST_POINT != 0
-        )
+        persisted_last_point_flag_set = flag_value & GlowsL3Flags.PERSISTED_LAST_POINT != 0
         dataset["persisted_last_point_flag"] = xr.DataArray(
             exposure * persisted_last_point_flag_set,
             dims=[
@@ -253,9 +230,7 @@ def __init__(
 class RectangularSurvivalProbabilitySkyMap(RectangularSkyMap):
     def __init__(
         self,
-        survival_probability_pointing_sets: list[
-            RectangularSurvivalProbabilityPointingSet
-        ],
+        survival_probability_pointing_sets: list[RectangularSurvivalProbabilityPointingSet],
         spacing_degree: float,
         spice_frame: SpiceFrame,
     ):
@@ -273,9 +248,7 @@ def __init__(
             )
 
         predicted_ephemeris_set = self.data_1d["predicted_ephemeris_flag"] != 0
-        nominal_alpha_proton_ratio_set = (
-            self.data_1d["nominal_alpha_proton_ratio_flag"] != 0
-        )
+        nominal_alpha_proton_ratio_set = self.data_1d["nominal_alpha_proton_ratio_flag"] != 0
         persisted_last_point_set = self.data_1d["persisted_last_point_flag"] != 0
         quality_flags_1d = (
             (predicted_ephemeris_set * MapL3Flags.PREDICTIVE_EPHEMERIS)
diff --git a/imap_l3_processing/maps/sp_map_initializer.py b/imap_l3_processing/maps/sp_map_initializer.py
index 08674951..ab960d83 100644
--- a/imap_l3_processing/maps/sp_map_initializer.py
+++ b/imap_l3_processing/maps/sp_map_initializer.py
@@ -7,12 +7,12 @@
 
 from imap_l3_processing.maps.map_descriptors import (
     MapDescriptorParts,
-    parse_map_descriptor,
+    Sensor,
     get_duration_from_map_descriptor,
     map_descriptor_parts_to_string,
-    Sensor,
+    parse_map_descriptor,
 )
-from imap_l3_processing.maps.map_initializer import PossibleMapToProduce, MapInitializer
+from imap_l3_processing.maps.map_initializer import MapInitializer, PossibleMapToProduce
 from imap_l3_processing.models import InputMetadata, VersionMap
 
 logger = logging.getLogger(__name__)
@@ -21,14 +21,12 @@
 class SPMapInitializer(MapInitializer):
     def __init__(self, instrument: str, l2_query_results: list[dict[str, str]]):
         super().__init__(instrument)
-        self.input_maps_by_descriptor = (
-            self.get_latest_version_by_descriptor_and_start_date(l2_query_results)
+        self.input_maps_by_descriptor = self.get_latest_version_by_descriptor_and_start_date(
+            l2_query_results
         )
 
     @abstractmethod
-    def _collect_glows_psets_by_repoint(
-        self, descriptor: MapDescriptorParts
-    ) -> dict[int, str]:
+    def _collect_glows_psets_by_repoint(self, descriptor: MapDescriptorParts) -> dict[int, str]:
         raise NotImplementedError()
 
     @abstractmethod
@@ -36,20 +34,14 @@ def _get_ancillary_files(self) -> list[str]:
         raise NotImplementedError()
 
     @abstractmethod
-    def _get_l2_dependencies(
-        self, descriptor: MapDescriptorParts
-    ) -> list[MapDescriptorParts]:
+    def _get_l2_dependencies(self, descriptor: MapDescriptorParts) -> list[MapDescriptorParts]:
         raise NotImplementedError()
 
-    def get_maps_that_can_be_produced(
-        self, descriptor: str
-    ) -> list[PossibleMapToProduce]:
+    def get_maps_that_can_be_produced(self, descriptor: str) -> list[PossibleMapToProduce]:
         l3_descriptor_parts = parse_map_descriptor(descriptor)
         map_duration = get_duration_from_map_descriptor(l3_descriptor_parts)
 
-        glows_file_by_repointing = self._collect_glows_psets_by_repoint(
-            l3_descriptor_parts
-        )
+        glows_file_by_repointing = self._collect_glows_psets_by_repoint(l3_descriptor_parts)
 
         if len(glows_file_by_repointing) == 0:
             logger.info(
@@ -57,36 +49,26 @@ def get_maps_that_can_be_produced(
             )
 
         l2_descriptors = self._get_l2_dependencies(l3_descriptor_parts)
-        l2_descriptor_strs = [
-            map_descriptor_parts_to_string(parts) for parts in l2_descriptors
-        ]
-        assert l2_descriptor_strs, (
-            f"Expected at least one L2 dependency for l3 map: {descriptor}"
-        )
+        l2_descriptor_strs = [map_descriptor_parts_to_string(parts) for parts in l2_descriptors]
+        assert l2_descriptor_strs, f"Expected at least one L2 dependency for l3 map: {descriptor}"
 
-        possible_start_dates = set(
-            self.input_maps_by_descriptor[l2_descriptor_strs[0]].keys()
-        )
+        possible_start_dates = set(self.input_maps_by_descriptor[l2_descriptor_strs[0]].keys())
         for l2_descriptor in l2_descriptor_strs[1:]:
             possible_start_dates.intersection_update(
                 self.input_maps_by_descriptor[l2_descriptor].keys()
             )
 
         possible_maps = []
-        for str_start_date in sorted(list(possible_start_dates)):
+        for str_start_date in sorted(possible_start_dates):
             start_date = datetime.strptime(str_start_date, "%Y%m%d")
 
             l2_file_paths = []
             for l2_descriptor in l2_descriptor_strs:
-                l2_file_paths.append(
-                    self.input_maps_by_descriptor[l2_descriptor][str_start_date]
-                )
+                l2_file_paths.append(self.input_maps_by_descriptor[l2_descriptor][str_start_date])
 
             if l3_descriptor_parts.sensor in [Sensor.UltraCombined, Sensor.HiCombined]:
                 l1c_names = [
-                    l1c
-                    for l2 in l2_file_paths
-                    for l1c in self.get_l1c_parents_from_map(l2)
+                    l1c for l2 in l2_file_paths for l1c in self.get_l1c_parents_from_map(l2)
                 ]
 
             else:
@@ -129,10 +111,7 @@ def get_maps_that_can_be_produced(
             )
             possible_map_to_produce = PossibleMapToProduce(
                 input_files=set(
-                    l2_file_paths
-                    + glows_files
-                    + l1c_names
-                    + self._get_ancillary_files()
+                    l2_file_paths + glows_files + l1c_names + self._get_ancillary_files()
                 ),
                 input_metadata=input_metadata,
             )
diff --git a/imap_l3_processing/maps/spectral_fit.py b/imap_l3_processing/maps/spectral_fit.py
index eebaf3e0..d00fd6a8 100644
--- a/imap_l3_processing/maps/spectral_fit.py
+++ b/imap_l3_processing/maps/spectral_fit.py
@@ -4,8 +4,8 @@
 import scipy
 
 from imap_l3_processing.maps.map_models import (
-    SpectralIndexMapData,
     IntensityMapData,
+    SpectralIndexMapData,
     calculate_datetime_weighted_average,
 )
 from imap_l3_processing.maps.mpfit import mpfit
@@ -32,9 +32,7 @@ def calculate_spectral_index_for_multiple_ranges(
         obs_date=np.concat([m.obs_date for m in spectral_maps], axis=1),
         obs_date_range=np.concat([m.obs_date_range for m in spectral_maps], axis=1),
         solid_angle=intensity_data.solid_angle,
-        ena_spectral_index=np.concat(
-            [m.ena_spectral_index for m in spectral_maps], axis=1
-        ),
+        ena_spectral_index=np.concat([m.ena_spectral_index for m in spectral_maps], axis=1),
         ena_spectral_index_stat_uncert=np.concat(
             [m.ena_spectral_index_stat_uncert for m in spectral_maps], axis=1
         ),
@@ -42,10 +40,7 @@ def calculate_spectral_index_for_multiple_ranges(
             [m.ena_spectral_index_scalar_coefficient for m in spectral_maps], axis=1
         ),
         ena_spectral_index_scalar_coefficient_stat_uncert=np.concat(
-            [
-                m.ena_spectral_index_scalar_coefficient_stat_uncert
-                for m in spectral_maps
-            ],
+            [m.ena_spectral_index_scalar_coefficient_stat_uncert for m in spectral_maps],
             axis=1,
         ),
         ena_spectral_index_chisq=np.concat(
@@ -55,9 +50,7 @@ def calculate_spectral_index_for_multiple_ranges(
     )
 
 
-def slice_energy_range(
-    data: IntensityMapData, start: float, end: float
-) -> IntensityMapData:
+def slice_energy_range(data: IntensityMapData, start: float, end: float) -> IntensityMapData:
     energy_mask = np.logical_and(data.energy >= start, data.energy < end)
     return dataclasses.replace(
         data,
@@ -79,9 +72,7 @@ def slice_energy_range_by_bin(
     data: IntensityMapData, start_bin_id: int, end_bin_id: int
 ) -> IntensityMapData:
     max_bin_id = 1 + len(data.energy)
-    bin_ids_in_range = (1 <= start_bin_id <= max_bin_id) and (
-        1 <= end_bin_id <= max_bin_id
-    )
+    bin_ids_in_range = (1 <= start_bin_id <= max_bin_id) and (1 <= end_bin_id <= max_bin_id)
     bin_ids_valid = bin_ids_in_range and start_bin_id < end_bin_id
     if not bin_ids_valid:
         raise ValueError(f"Error slicing energy bins {start_bin_id},{end_bin_id}")
@@ -132,17 +123,13 @@ def fit_spectral_index_map(intensity_data: IntensityMapData) -> SpectralIndexMap
         axis=1,
         keepdims=True,
     )
-    total_exposure_factor = np.sum(
-        intensity_data.exposure_factor, axis=1, keepdims=True
-    )
+    total_exposure_factor = np.sum(intensity_data.exposure_factor, axis=1, keepdims=True)
     positive_gammas = output_gammas < 0
     output_gammas[positive_gammas] = np.nan
     output_scalar_coefficients[positive_gammas] = np.nan
     output_gamma_errors[positive_gammas] = np.nan
     chisq[positive_gammas] = np.nan
-    quality_flags = np.bitwise_or.reduce(
-        intensity_data.quality_flags, axis=1, keepdims=True
-    )
+    quality_flags = np.bitwise_or.reduce(intensity_data.quality_flags, axis=1, keepdims=True)
 
     return SpectralIndexMapData(
         epoch=intensity_data.epoch,
@@ -228,9 +215,7 @@ def fit_arrays_to_power_law(
                     chisqs[i] = fit.fnorm / fit.dof
         output_gammas[epoch, 0] = gammas.reshape(fluxes.shape[2:])
         output_gamma_errors[epoch, 0] = gamma_errors.reshape(fluxes.shape[2:])
-        output_scalar_coefficients[epoch, 0] = scalar_coefficients.reshape(
-            fluxes.shape[2:]
-        )
+        output_scalar_coefficients[epoch, 0] = scalar_coefficients.reshape(fluxes.shape[2:])
         output_scalar_coefficients_errors[epoch, 0] = scalar_coefficient_errors.reshape(
             fluxes.shape[2:]
         )
diff --git a/imap_l3_processing/maps/survival_probability_processing.py b/imap_l3_processing/maps/survival_probability_processing.py
index 46a9f477..16301fa8 100644
--- a/imap_l3_processing/maps/survival_probability_processing.py
+++ b/imap_l3_processing/maps/survival_probability_processing.py
@@ -1,4 +1,4 @@
-from typing import Union, TypeVar
+from typing import TypeVar
 
 import numpy as np
 from imap_processing.spice.geometry import SpiceFrame
@@ -8,10 +8,10 @@
 )
 from imap_l3_processing.maps.map_descriptors import ReferenceFrame
 from imap_l3_processing.maps.map_models import (
-    RectangularIntensityMapData,
-    IntensityMapData,
-    InputRectangularPointingSet,
     GlowsL3eRectangularMapInputData,
+    InputRectangularPointingSet,
+    IntensityMapData,
+    RectangularIntensityMapData,
 )
 from imap_l3_processing.maps.rectangular_survival_probability import (
     RectangularSurvivalProbabilityPointingSet,
@@ -19,12 +19,8 @@
 )
 from imap_l3_processing.ultra.models import UltraGlowsL3eData, UltraL1CPSet
 
-L1CPointingSet = TypeVar(
-    "L1CPointingSet", bound=Union[InputRectangularPointingSet, UltraL1CPSet]
-)
-GlowsL3eData = TypeVar(
-    "GlowsL3eData", bound=Union[GlowsL3eRectangularMapInputData, UltraGlowsL3eData]
-)
+L1CPointingSet = TypeVar("L1CPointingSet", bound=InputRectangularPointingSet | UltraL1CPSet)
+GlowsL3eData = TypeVar("GlowsL3eData", bound=GlowsL3eRectangularMapInputData | UltraGlowsL3eData)
 
 
 def combine_glows_l3e_with_l1c_pointing(
@@ -35,7 +31,7 @@ def combine_glows_l3e_with_l1c_pointing(
 
     return [
         (l1c_by_repoint[repoint], glows_by_repoint[repoint])
-        for repoint in l1c_by_repoint.keys()
+        for repoint in l1c_by_repoint
         if repoint in glows_by_repoint
     ]
 
@@ -47,7 +43,7 @@ def filter_bad_days(input_psets: list[L1CPointingSet]) -> list[L1CPointingSet]:
 def process_survival_probabilities(
     survival_probabilities_dependencies: HiLoL3SurvivalDependencies,
     spice_frame_name: SpiceFrame,
-    cg_corrected: bool = None,
+    cg_corrected: bool | None = None,
 ) -> RectangularIntensityMapData:
     l2_descriptor_parts = survival_probabilities_dependencies.l2_map_descriptor_parts
 
@@ -59,9 +55,7 @@ def process_survival_probabilities(
     pointing_sets = []
 
     if cg_corrected is None:
-        cg_corrected = (
-            l2_descriptor_parts.reference_frame == ReferenceFrame.Heliospheric
-        )
+        cg_corrected = l2_descriptor_parts.reference_frame == ReferenceFrame.Heliospheric
 
     for l1c, glows_l3e in combined_glows:
         pointing_sets.append(
@@ -83,13 +77,9 @@ def process_survival_probabilities(
     survival_dataset = survival_sky_map.to_dataset()
 
     input_data = survival_probabilities_dependencies.l2_data.intensity_map_data
-    survival_probabilities = survival_dataset[
-        "exposure_weighted_survival_probabilities"
-    ].values
+    survival_probabilities = survival_dataset["exposure_weighted_survival_probabilities"].values
     survival_corrected_intensity = input_data.ena_intensity / survival_probabilities
-    corrected_stat_uncert = (
-        input_data.ena_intensity_stat_uncert / survival_probabilities
-    )
+    corrected_stat_uncert = input_data.ena_intensity_stat_uncert / survival_probabilities
     corrected_sys_err = input_data.ena_intensity_sys_err / survival_probabilities
 
     map_data = RectangularIntensityMapData(
@@ -116,9 +106,7 @@ def process_survival_probabilities(
     )
 
     if input_data.bg_intensity is not None:
-        map_data.intensity_map_data.bg_intensity = (
-            input_data.bg_intensity / survival_probabilities
-        )
+        map_data.intensity_map_data.bg_intensity = input_data.bg_intensity / survival_probabilities
         map_data.intensity_map_data.bg_intensity_sys_err = (
             input_data.bg_intensity_sys_err / survival_probabilities
         )
diff --git a/imap_l3_processing/models.py b/imap_l3_processing/models.py
index 9f944539..0fa71b85 100644
--- a/imap_l3_processing/models.py
+++ b/imap_l3_processing/models.py
@@ -4,10 +4,10 @@
 from dataclasses import dataclass, field
 from datetime import datetime
 from pathlib import Path
-from typing import Union, Optional, TypeVar, Generic
+from typing import Generic, TypeVar
 
 import numpy as np
-from imap_data_access.file_validation import Version, ScienceFilePath
+from imap_data_access.file_validation import ScienceFilePath, Version
 
 from imap_l3_processing.data_utils import rebin
 
@@ -29,16 +29,16 @@ class InputMetadata:
     instrument: str
     data_level: str
     start_date: datetime
-    end_date: Optional[datetime]
+    end_date: datetime | None
     version: VersionMap
     descriptor: str = ""
-    repointing: Optional[int] = None
+    repointing: int | None = None
 
     @property
     def logical_source(self):
         return f"imap_{self.instrument}_{self.data_level}_{self.descriptor}"
 
-    def to_science_file_path(self, cr_number: Optional[int] = None) -> ScienceFilePath:
+    def to_science_file_path(self, cr_number: int | None = None) -> ScienceFilePath:
         assert self.repointing is None or cr_number is None, (
             "You cannot call save_data with both a repointing in the metadata while passing in a CR number"
         )
@@ -60,7 +60,7 @@ def to_science_file_path(self, cr_number: Optional[int] = None) -> ScienceFilePa
 @dataclass
 class DataProductVariable:
     name: str
-    value: Union[np.ndarray, int, float, list[str], list[int]]
+    value: np.ndarray | int | float | list[str] | list[int]
     cdf_data_type: ctypes.c_long = None
     record_varying: bool = None
 
diff --git a/imap_l3_processing/pitch_angles.py b/imap_l3_processing/pitch_angles.py
index 27b46269..81cfc34e 100644
--- a/imap_l3_processing/pitch_angles.py
+++ b/imap_l3_processing/pitch_angles.py
@@ -24,9 +24,7 @@ def rotate_from_imap_despun_to_hit_despun(
         [-0.5, 0.866025, 0],
         [0, 0, 1],
     ]
-    return (
-        rotation_matrix_from_imap_despun_frame_to_hit_despun_instrument_frame @ vector
-    )
+    return rotation_matrix_from_imap_despun_frame_to_hit_despun_instrument_frame @ vector
 
 
 def rotate_particle_vectors_from_hit_despun_to_imap_despun(
@@ -43,28 +41,18 @@ def rotate_particle_vectors_from_hit_despun_to_imap_despun(
     return output
 
 
-def calculate_gyrophase(
-    particle_vectors: np.ndarray, magnetic_field_vector: np.ndarray
-):
+def calculate_gyrophase(particle_vectors: np.ndarray, magnetic_field_vector: np.ndarray):
     magnetic_field_plus_z = magnetic_field_vector
     imap_dps_plus_y = [0, 1, 0]
     if np.all(np.cross(magnetic_field_plus_z, imap_dps_plus_y) == 0):
         return np.full(shape=particle_vectors.shape[:-1], fill_value=np.nan)
-    magnetic_field_plus_x = calculate_unit_vector(
-        np.cross(imap_dps_plus_y, magnetic_field_plus_z)
-    )
+    magnetic_field_plus_x = calculate_unit_vector(np.cross(imap_dps_plus_y, magnetic_field_plus_z))
     magnetic_field_plus_y = calculate_unit_vector(
         np.cross(magnetic_field_plus_z, magnetic_field_plus_x)
     )
-    particle_magnetic_field_x_component = np.sum(
-        particle_vectors * magnetic_field_plus_x, axis=-1
-    )
-    particle_magnetic_field_y_component = np.sum(
-        particle_vectors * magnetic_field_plus_y, axis=-1
-    )
-    gyrophases = np.atan2(
-        particle_magnetic_field_x_component, particle_magnetic_field_y_component
-    )
+    particle_magnetic_field_x_component = np.sum(particle_vectors * magnetic_field_plus_x, axis=-1)
+    particle_magnetic_field_y_component = np.sum(particle_vectors * magnetic_field_plus_y, axis=-1)
+    gyrophases = np.atan2(particle_magnetic_field_x_component, particle_magnetic_field_y_component)
 
     return np.mod(np.degrees(gyrophases), 360)
 
@@ -95,12 +83,8 @@ def rebin_by_pitch_angle_and_gyrophase(
         np.zeros(shape=output_shape_pa_and_gyro), 0
     )
 
-    rebinned_summed_pa_only_with_delta_plus = uarray(
-        np.zeros(shape=output_shape_pa_only), 0
-    )
-    rebinned_summed_pa_only_with_delta_minus = uarray(
-        np.zeros(shape=output_shape_pa_only), 0
-    )
+    rebinned_summed_pa_only_with_delta_plus = uarray(np.zeros(shape=output_shape_pa_only), 0)
+    rebinned_summed_pa_only_with_delta_minus = uarray(np.zeros(shape=output_shape_pa_only), 0)
 
     rebinned_count_by_pa_and_gyro = np.zeros(shape=output_shape_pa_and_gyro)
     rebinned_count_pa_only = np.zeros(shape=output_shape_pa_only)
@@ -112,9 +96,7 @@ def rebin_by_pitch_angle_and_gyrophase(
             np.ravel(intensity_with_delta_plus[i]),
             np.ravel(intensity_with_delta_minus[i]),
         ):
-            if not (
-                np.isnan(intensity_with_plus.nominal_value) or np.isnan(pitch_angle)
-            ):
+            if not (np.isnan(intensity_with_plus.nominal_value) or np.isnan(pitch_angle)):
                 if pitch_angle == 180:
                     pitch_angle_bin = number_of_pitch_angle_bins - 1
                 else:
@@ -134,13 +116,9 @@ def rebin_by_pitch_angle_and_gyrophase(
                     rebinned_summed_by_pa_and_gyro_with_delta_minus[
                         i, pitch_angle_bin, gyrophase_bin
                     ] += intensity_with_minus
-                    rebinned_count_by_pa_and_gyro[
-                        i, pitch_angle_bin, gyrophase_bin
-                    ] += 1
+                    rebinned_count_by_pa_and_gyro[i, pitch_angle_bin, gyrophase_bin] += 1
 
-                rebinned_summed_pa_only_with_delta_plus[i, pitch_angle_bin] += (
-                    intensity_with_plus
-                )
+                rebinned_summed_pa_only_with_delta_plus[i, pitch_angle_bin] += intensity_with_plus
                 rebinned_summed_pa_only_with_delta_minus[i, pitch_angle_bin] += (
                     intensity_with_minus
                 )
diff --git a/imap_l3_processing/predicted_ephemeris_tracker.py b/imap_l3_processing/predicted_ephemeris_tracker.py
index 90ed2017..d44d05c9 100644
--- a/imap_l3_processing/predicted_ephemeris_tracker.py
+++ b/imap_l3_processing/predicted_ephemeris_tracker.py
@@ -1,7 +1,8 @@
-from typing import Callable, ParamSpec, TypeVar
+from collections.abc import Callable
+from typing import ParamSpec, TypeVar
 
 from imap_data_access import SPICEFilePath
-from spiceypy import spiceypy, KernelPool, SpiceyError
+from spiceypy import KernelPool, SpiceyError, spiceypy
 
 
 class PredictedEphemerisTracker:
diff --git a/imap_l3_processing/processor.py b/imap_l3_processing/processor.py
index 9ea73c8c..65452d39 100644
--- a/imap_l3_processing/processor.py
+++ b/imap_l3_processing/processor.py
@@ -8,9 +8,7 @@
 
 
 class Processor(abc.ABC):
-    def __init__(
-        self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata
-    ):
+    def __init__(self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata):
         self.input_metadata = input_metadata
         self.dependencies = dependencies
 
@@ -18,15 +16,12 @@ def __init__(
     def process(self) -> list[Path]:
         raise NotImplementedError()
 
-    def get_parent_file_names(self, file_paths: list[Path | str] = None) -> list[str]:
+    def get_parent_file_names(self, file_paths: list[Path | str] | None = None) -> list[str]:
         if file_paths:
-            parent_file_names = [
-                Path(parent_file_name).name for parent_file_name in file_paths
-            ]
+            parent_file_names = [Path(parent_file_name).name for parent_file_name in file_paths]
         else:
             parent_file_names = [
-                parent_file_name.name
-                for parent_file_name in self.dependencies.get_file_paths()
+                parent_file_name.name for parent_file_name in self.dependencies.get_file_paths()
             ]
 
         return parent_file_names + get_spice_parent_file_names()
diff --git a/imap_l3_processing/swapi/constants.py b/imap_l3_processing/swapi/constants.py
index de72012a..e272eca7 100644
--- a/imap_l3_processing/swapi/constants.py
+++ b/imap_l3_processing/swapi/constants.py
@@ -22,9 +22,7 @@
 SWAPI_BIN_PERIOD_S = 12 / 72  # duration of one ESA step in the 12 s, 72-bin sweep
 # Counts accumulate over the 0.145 s livetime that starts after the voltage ramp-up;
 # sample geometry at the center of that window rather than the bin's start time.
-SWAPI_LIVETIME_CENTER_OFFSET_S = (
-    SWAPI_BIN_PERIOD_S - SWAPI_LIVETIME_S
-) + SWAPI_LIVETIME_S / 2
+SWAPI_LIVETIME_CENTER_OFFSET_S = (SWAPI_BIN_PERIOD_S - SWAPI_LIVETIME_S) + SWAPI_LIVETIME_S / 2
 
 # baseline instrument background is approximately 0.1 Hz
 SWAPI_BACKGROUND_RATE = 0.1
diff --git a/imap_l3_processing/swapi/l3a/chunk_fits.py b/imap_l3_processing/swapi/l3a/chunk_fits.py
index e3d6bde3..5525f4ab 100644
--- a/imap_l3_processing/swapi/l3a/chunk_fits.py
+++ b/imap_l3_processing/swapi/l3a/chunk_fits.py
@@ -15,6 +15,12 @@
     ONE_SECOND_IN_NANOSECONDS,
     THIRTY_SECONDS_IN_NANOSECONDS,
 )
+from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
+from imap_l3_processing.swapi.constants import (
+    SWAPI_COARSE_SWEEP_BINS,
+    SWAPI_L2_K_FACTOR,
+    SWAPI_SCIENCE_BINS,
+)
 from imap_l3_processing.swapi.l3a.science.pickup_ion.calculate_pickup_ion_values import (
     PickupIonFitInputData,
     calculate_pickup_ion_values,
@@ -26,18 +32,12 @@
     AlphaSolarWindFitResult,
     fit_solar_wind_alpha_model,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
-    ProtonSolarWindFitResult,
-    fit_solar_wind_proton_model,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     build_solar_wind_fit_context,
 )
-from imap_l3_processing.swapi.species import Species
-from imap_l3_processing.swapi.constants import (
-    SWAPI_COARSE_SWEEP_BINS,
-    SWAPI_L2_K_FACTOR,
-    SWAPI_SCIENCE_BINS,
+from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
+    ProtonSolarWindFitResult,
+    fit_solar_wind_proton_model,
 )
 from imap_l3_processing.swapi.l3a.utils import (
     compute_direction_of_mean_magnetic_field_over_chunk,
@@ -49,7 +49,7 @@
     solar_wind_chunk_epoch,
 )
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
-from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
+from imap_l3_processing.swapi.species import Species
 
 logger = logging.getLogger(__name__)
 
@@ -81,7 +81,7 @@ def run(self, chunks, fitter: ChunkFitter) -> dict[str, np.ndarray]:
                 _run_one, [(chunk, geom) for chunk, geom in zip(chunks, geometries)]
             )
 
-        return {k: np.array([r[k] for r in results]) for k in results[0].keys()}
+        return {k: np.array([r[k] for r in results]) for k in results[0]}
 
 
 def _init_worker(swapi_response, efficiency_table, fitter):
@@ -103,9 +103,7 @@ def precompute_geometry(self, chunks):
             sc_vel = None
             tracker = PredictedEphemerisTracker()
             try:
-                science_bin_times = measurement_times(chunk.sci_start_time)[
-                    :, SWAPI_SCIENCE_BINS
-                ]
+                science_bin_times = measurement_times(chunk.sci_start_time)[:, SWAPI_SCIENCE_BINS]
                 rm = tracker.run(get_swapi_geometry, science_bin_times.ravel())
             except Exception:
                 logger.warning(
@@ -122,9 +120,7 @@ def precompute_geometry(self, chunks):
                         exc_info=True,
                     )
             flags = (
-                SwapiL3Flags.PREDICTIVE_EPHEMERIS
-                if tracker.used_predict
-                else SwapiL3Flags.NONE
+                SwapiL3Flags.PREDICTIVE_EPHEMERIS if tracker.used_predict else SwapiL3Flags.NONE
             )
             geometries.append((epoch, rm, sc_vel, flags))
 
@@ -156,11 +152,9 @@ def precompute_geometry(self, chunks):
             sc_vel = None
             tracker = PredictedEphemerisTracker()
             try:
-                science_bin_times = measurement_times(chunk.sci_start_time)[
-                    :, SWAPI_SCIENCE_BINS
-                ]
+                science_bin_times = measurement_times(chunk.sci_start_time)[:, SWAPI_SCIENCE_BINS]
                 rm = tracker.run(get_swapi_geometry, science_bin_times.ravel())
-            except Exception:
+            except SpiceyError:
                 logger.info(
                     f"Missing SPICE information at epoch {pycdf.lib.tt2000_to_datetime(int(epoch))}, continuing with fill value"
                 )
@@ -168,7 +162,7 @@ def precompute_geometry(self, chunks):
             if rm is not None:
                 try:
                     sc_vel = tracker.run(get_spacecraft_velocity_rtn, epoch)
-                except Exception:
+                except SpiceyError:
                     logger.warning(
                         "SPICE gap in spacecraft velocity.",
                         exc_info=True,
@@ -178,9 +172,7 @@ def precompute_geometry(self, chunks):
                 self.mag_data, int(epoch), int(THIRTY_SECONDS_IN_NANOSECONDS)
             )
             flags = (
-                SwapiL3Flags.PREDICTIVE_EPHEMERIS
-                if tracker.used_predict
-                else SwapiL3Flags.NONE
+                SwapiL3Flags.PREDICTIVE_EPHEMERIS if tracker.used_predict else SwapiL3Flags.NONE
             )
             geometries.append((epoch, rm, sc_vel, b_hat, flags))
         return geometries
@@ -194,9 +186,7 @@ def fit_chunk(
         magnetic_field_direction,
         geometry_quality_flags: SwapiL3Flags,
     ):
-        result = _fit_alpha(
-            data_chunk, epoch, rotation_matrices, magnetic_field_direction
-        )
+        result = _fit_alpha(data_chunk, epoch, rotation_matrices, magnetic_field_direction)
         moments = _alpha_moments_from_fit(result, epoch, sc_velocity_rtn)
         moments["quality_flags"] |= geometry_quality_flags
         return moments
@@ -210,9 +200,7 @@ def __init__(
         helium_inflow_vector,
         proton_sw_results: dict,
     ):
-        self.density_of_neutral_helium_lookup_table = (
-            density_of_neutral_helium_lookup_table
-        )
+        self.density_of_neutral_helium_lookup_table = density_of_neutral_helium_lookup_table
         self.hydrogen_inflow_vector = hydrogen_inflow_vector
         self.helium_inflow_vector = helium_inflow_vector
         self.proton_sw_results = proton_sw_results
@@ -226,9 +214,7 @@ def _calculate_ten_minute_velocities(
         10-minute chunks and compute the bitwise-OR of the per-minute flags.
 
         Skip fill-value solar wind fits when there aren't too many."""
-        velocities_rtn = np.asarray(
-            self.proton_sw_results["proton_sw_velocity_rtn"], dtype=float
-        )
+        velocities_rtn = np.asarray(self.proton_sw_results["proton_sw_velocity_rtn"], dtype=float)
         velocities_rtn_sun = np.asarray(
             self.proton_sw_results["proton_sw_velocity_rtn_sun"], dtype=float
         )
@@ -248,9 +234,7 @@ def _calculate_ten_minute_velocities(
             )
 
             if np.count_nonzero(is_usable) >= self.MIN_SOLAR_WIND_FITS_PER_CHUNK:
-                ten_minute_velocities_rtn.append(
-                    np.mean(chunk_velocities_rtn[is_usable], axis=0)
-                )
+                ten_minute_velocities_rtn.append(np.mean(chunk_velocities_rtn[is_usable], axis=0))
                 ten_minute_velocities_rtn_sun.append(
                     np.mean(chunk_velocities_rtn_sun[is_usable], axis=0)
                 )
@@ -258,9 +242,7 @@ def _calculate_ten_minute_velocities(
                     np.bitwise_or.reduce(chunk_quality_flags[is_usable])
                 )
             else:
-                ten_minute_velocities_rtn.append(
-                    np.full(chunk_velocities_rtn.shape[1], np.nan)
-                )
+                ten_minute_velocities_rtn.append(np.full(chunk_velocities_rtn.shape[1], np.nan))
                 ten_minute_velocities_rtn_sun.append(
                     np.full(chunk_velocities_rtn_sun.shape[1], np.nan)
                 )
@@ -288,9 +270,7 @@ def precompute_geometry(self, chunks):
             epoch = pickup_ion_chunk_epoch(chunk)
             proton_sw_quality_flag = int(sw_flags)
 
-            if np.any(np.isnan(sw_velocity_rtn_sc)) or np.any(
-                np.isnan(sw_velocity_rtn_sun)
-            ):
+            if np.any(np.isnan(sw_velocity_rtn_sc)) or np.any(np.isnan(sw_velocity_rtn_sun)):
                 logger.info(f"solar wind velocity gap at {epoch}")
                 input_data_list.append((None, proton_sw_quality_flag))
                 continue
@@ -316,14 +296,11 @@ def compute_chunk_position(
                         imap_position_eclipj2000_frame
                     )
                     inflow_angle = (
-                        np.rad2deg(longitude)
-                        - self.helium_inflow_vector.longitude_deg_eclipj2000
+                        np.rad2deg(longitude) - self.helium_inflow_vector.longitude_deg_eclipj2000
                     )
                     return distance_km, inflow_angle
 
-                distance, inflow_angle = tracker.run(
-                    compute_chunk_position, chunk_ephemeris_time
-                )
+                distance, inflow_angle = tracker.run(compute_chunk_position, chunk_ephemeris_time)
             except SpiceyError:
                 logger.info(f"SPICE gap at {epoch}")
                 input_data_list.append((None, proton_sw_quality_flag))
@@ -336,9 +313,7 @@ def compute_chunk_position(
                 (
                     PickupIonFitInputData(
                         time_as_tt2000=epoch,
-                        esa_energies=chunk.energy[:, SWAPI_COARSE_SWEEP_BINS].mean(
-                            axis=0
-                        ),
+                        esa_energies=chunk.energy[:, SWAPI_COARSE_SWEEP_BINS].mean(axis=0),
                         coincidence_count_rates=chunk.coincidence_count_rate[
                             :, SWAPI_COARSE_SWEEP_BINS
                         ],
@@ -363,13 +338,9 @@ def fit_chunk(
     ):
         epoch = pickup_ion_chunk_epoch(data_chunk)
 
-        count_rates_window = data_chunk.coincidence_count_rate[
-            :, SWAPI_COARSE_SWEEP_BINS
-        ]
+        count_rates_window = data_chunk.coincidence_count_rate[:, SWAPI_COARSE_SWEEP_BINS]
         if np.any(np.isnan(count_rates_window)):
-            return _pui_fill_result(
-                epoch, quality_flag, "gap in L2 coincidence count rate"
-            )
+            return _pui_fill_result(epoch, quality_flag, "gap in L2 coincidence count rate")
         if fit_input is None:
             return _pui_fill_result(
                 epoch,
@@ -392,14 +363,14 @@ def fit_chunk(
             )
             return _pui_fill_result(epoch, quality_flag)
 
-        return dict(
-            epoch=epoch,
-            ionization_rate=fit_result.ionization_rate,
-            cutoff_speed=fit_result.cutoff_speed,
-            density=fit_result.density,
-            temperature=fit_result.temperature,
-            quality_flags=int(quality_flag) | int(fit_result.flags),
-        )
+        return {
+            "epoch": epoch,
+            "ionization_rate": fit_result.ionization_rate,
+            "cutoff_speed": fit_result.cutoff_speed,
+            "density": fit_result.density,
+            "temperature": fit_result.temperature,
+            "quality_flags": int(quality_flag) | int(fit_result.flags),
+        }
 
 
 def _proton_moments_from_fit(result, epoch, data_chunk, sc_velocity_rtn):
@@ -428,21 +399,21 @@ def _proton_moments_from_fit(result, epoch, data_chunk, sc_velocity_rtn):
     if not np.isfinite(speed_nom):
         speed_nom = _peak_proton_speed_kms(data_chunk)
 
-    return dict(
-        epoch=epoch,
-        proton_sw_speed=speed_nom,
-        proton_sw_speed_uncert=speed_unc,
-        proton_sw_speed_sun=sun_speed_nom,
-        proton_sw_speed_sun_uncert=sun_speed_unc,
-        proton_sw_temperature=temp_nom,
-        proton_sw_temperature_uncert=temp_unc,
-        proton_sw_density=density_nom,
-        proton_sw_density_uncert=density_unc,
-        proton_sw_velocity_rtn_sun=velocity_rtn_sun,
-        proton_sw_velocity_rtn=velocity_rtn_sc,
-        proton_sw_velocity_rtn_covariance=velocity_rtn_covariance,
-        quality_flags=result.quality_flag,
-    )
+    return {
+        "epoch": epoch,
+        "proton_sw_speed": speed_nom,
+        "proton_sw_speed_uncert": speed_unc,
+        "proton_sw_speed_sun": sun_speed_nom,
+        "proton_sw_speed_sun_uncert": sun_speed_unc,
+        "proton_sw_temperature": temp_nom,
+        "proton_sw_temperature_uncert": temp_unc,
+        "proton_sw_density": density_nom,
+        "proton_sw_density_uncert": density_unc,
+        "proton_sw_velocity_rtn_sun": velocity_rtn_sun,
+        "proton_sw_velocity_rtn": velocity_rtn_sc,
+        "proton_sw_velocity_rtn_covariance": velocity_rtn_covariance,
+        "quality_flags": result.quality_flag,
+    }
 
 
 def _alpha_moments_from_fit(result, epoch, sc_velocity_rtn):
@@ -466,21 +437,21 @@ def _alpha_moments_from_fit(result, epoch, sc_velocity_rtn):
         velocity_rtn_sun = np.full(3, np.nan)
         sun_speed_nom = sun_speed_unc = np.nan
 
-    return dict(
-        epoch=epoch,
-        alpha_sw_speed=speed.nominal_value,
-        alpha_sw_speed_uncert=speed.std_dev,
-        alpha_sw_speed_sun=sun_speed_nom,
-        alpha_sw_speed_sun_uncert=sun_speed_unc,
-        alpha_sw_density=alpha.density.nominal_value,
-        alpha_sw_density_uncert=alpha.density.std_dev,
-        alpha_sw_temperature=alpha.temperature.nominal_value,
-        alpha_sw_temperature_uncert=alpha.temperature.std_dev,
-        alpha_sw_velocity_rtn_sun=velocity_rtn_sun,
-        alpha_sw_velocity_rtn=velocity_rtn_sc,
-        alpha_sw_velocity_rtn_covariance=velocity_rtn_covariance,
-        quality_flags=result.quality_flag,
-    )
+    return {
+        "epoch": epoch,
+        "alpha_sw_speed": speed.nominal_value,
+        "alpha_sw_speed_uncert": speed.std_dev,
+        "alpha_sw_speed_sun": sun_speed_nom,
+        "alpha_sw_speed_sun_uncert": sun_speed_unc,
+        "alpha_sw_density": alpha.density.nominal_value,
+        "alpha_sw_density_uncert": alpha.density.std_dev,
+        "alpha_sw_temperature": alpha.temperature.nominal_value,
+        "alpha_sw_temperature_uncert": alpha.temperature.std_dev,
+        "alpha_sw_velocity_rtn_sun": velocity_rtn_sun,
+        "alpha_sw_velocity_rtn": velocity_rtn_sc,
+        "alpha_sw_velocity_rtn_covariance": velocity_rtn_covariance,
+        "quality_flags": result.quality_flag,
+    }
 
 
 _PEAK_SPEED_HALF_WIDTH = 4
@@ -562,9 +533,9 @@ def _fit_proton(data_chunk, epoch, rotation_matrices) -> ProtonSolarWindFitResul
         n_sweeps_local, n_bins_local = voltages.shape
         voltages = voltages[:, keep_bins]
         count_rates = count_rates[:, keep_bins]
-        rotation_matrices = rotation_matrices.reshape(
-            n_sweeps_local, n_bins_local, 3, 3
-        )[:, keep_bins].reshape(-1, 3, 3)
+        rotation_matrices = rotation_matrices.reshape(n_sweeps_local, n_bins_local, 3, 3)[
+            :, keep_bins
+        ].reshape(-1, 3, 3)
 
     ctx = build_solar_wind_fit_context(
         count_rate=count_rates,
@@ -593,14 +564,14 @@ def _pui_fill_result(epoch, proton_sw_quality_flag, reason=None) -> dict:
             f"{reason}; using fill values"
         )
     nan = ufloat(np.nan, np.nan)
-    return dict(
-        epoch=epoch,
-        ionization_rate=nan,
-        cutoff_speed=nan,
-        density=nan,
-        temperature=nan,
-        quality_flags=int(proton_sw_quality_flag),
-    )
+    return {
+        "epoch": epoch,
+        "ionization_rate": nan,
+        "cutoff_speed": nan,
+        "density": nan,
+        "temperature": nan,
+        "quality_flags": int(proton_sw_quality_flag),
+    }
 
 
 def _nan_proton_result(flag) -> ProtonSolarWindFitResult:
@@ -644,9 +615,7 @@ def _fit_alpha(
     magnetic_field_direction,
 ) -> AlphaChunkFitResult:
     nan_b_hat = np.full(3, np.nan)
-    if magnetic_field_direction is None or not np.all(
-        np.isfinite(magnetic_field_direction)
-    ):
+    if magnetic_field_direction is None or not np.all(np.isfinite(magnetic_field_direction)):
         logger.warning(
             f"Alpha fit at epoch {pycdf.lib.tt2000_to_datetime(int(epoch))}: missing or non-finite magnetic field direction; using fill values"
         )
@@ -659,9 +628,7 @@ def _fit_alpha(
 
     proton_moments = _fit_proton(data_chunk, epoch, rotation_matrices)
     if not np.all(
-        np.isfinite(
-            [component.nominal_value for component in proton_moments.velocity_rtn]
-        )
+        np.isfinite([component.nominal_value for component in proton_moments.velocity_rtn])
     ):
         return AlphaChunkFitResult(
             alpha_moments=_nan_alpha_fit_result(proton_moments.quality_flag),
diff --git a/imap_l3_processing/swapi/l3a/models.py b/imap_l3_processing/swapi/l3a/models.py
index d396dcc8..fe60a5b6 100644
--- a/imap_l3_processing/swapi/l3a/models.py
+++ b/imap_l3_processing/swapi/l3a/models.py
@@ -9,8 +9,8 @@
 
 from imap_l3_processing.cdf.cdf_utils import read_numeric_variable
 from imap_l3_processing.constants import (
-    THIRTY_SECONDS_IN_NANOSECONDS,
     FIVE_MINUTES_IN_NANOSECONDS,
+    THIRTY_SECONDS_IN_NANOSECONDS,
 )
 from imap_l3_processing.models import DataProduct, DataProductVariable
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
@@ -28,19 +28,11 @@
 
 PROTON_SOLAR_WIND_VELOCITY_RTN_SUN_CDF_VAR_NAME = "proton_sw_velocity_rtn_sun"
 PROTON_SOLAR_WIND_VELOCITY_RTN_CDF_VAR_NAME = "proton_sw_velocity_rtn"
-PROTON_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME = (
-    "proton_sw_velocity_rtn_covariance"
-)
-PROTON_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME = (
-    "proton_sw_velocity_rtn_uncert"
-)
+PROTON_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME = "proton_sw_velocity_rtn_covariance"
+PROTON_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME = "proton_sw_velocity_rtn_uncert"
 PROTON_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME = "proton_sw_velocity_gse"
-PROTON_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME = (
-    "proton_sw_velocity_gse_covariance"
-)
-PROTON_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME = (
-    "proton_sw_velocity_gse_uncert"
-)
+PROTON_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME = "proton_sw_velocity_gse_covariance"
+PROTON_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME = "proton_sw_velocity_gse_uncert"
 
 ALPHA_SOLAR_WIND_SPEED_CDF_VAR_NAME = "alpha_sw_speed"
 ALPHA_SOLAR_WIND_SPEED_UNCERTAINTY_CDF_VAR_NAME = "alpha_sw_speed_uncert"
@@ -52,14 +44,10 @@
 ALPHA_SOLAR_WIND_TEMPERATURE_UNCERTAINTY_CDF_VAR_NAME = "alpha_sw_temperature_uncert"
 ALPHA_SOLAR_WIND_VELOCITY_RTN_SUN_CDF_VAR_NAME = "alpha_sw_velocity_rtn_sun"
 ALPHA_SOLAR_WIND_VELOCITY_RTN_CDF_VAR_NAME = "alpha_sw_velocity_rtn"
-ALPHA_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME = (
-    "alpha_sw_velocity_rtn_covariance"
-)
+ALPHA_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME = "alpha_sw_velocity_rtn_covariance"
 ALPHA_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME = "alpha_sw_velocity_rtn_uncert"
 ALPHA_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME = "alpha_sw_velocity_gse"
-ALPHA_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME = (
-    "alpha_sw_velocity_gse_covariance"
-)
+ALPHA_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME = "alpha_sw_velocity_gse_covariance"
 ALPHA_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME = "alpha_sw_velocity_gse_uncert"
 
 PUI_IONIZATION_RATE_CDF_VAR_NAME = "pui_ionization_rate"
@@ -79,9 +67,7 @@
 ALPHA_VELOCITY_RTN_SUN_LABEL_CDF_VAR_NAME = "alpha_sw_velocity_rtn_sun_label"
 ALPHA_VELOCITY_GSE_LABEL_CDF_VAR_NAME = "alpha_sw_velocity_gse_label"
 
-PROTON_SOLAR_WIND_VELOCITY_RTN_SUN_LABEL_CDF_VAR_NAME = (
-    "proton_sw_velocity_rtn_sun_label"
-)
+PROTON_SOLAR_WIND_VELOCITY_RTN_SUN_LABEL_CDF_VAR_NAME = "proton_sw_velocity_rtn_sun_label"
 PROTON_SOLAR_WIND_VELOCITY_RTN_LABEL_CDF_VAR_NAME = "proton_sw_velocity_rtn_label"
 PROTON_SOLAR_WIND_VELOCITY_GSE_LABEL_CDF_VAR_NAME = "proton_sw_velocity_gse_label"
 
@@ -107,9 +93,7 @@ class SwapiL3ProtonSolarWindData(DataProduct):
     def to_data_product_variables(self) -> list[DataProductVariable]:
         return [
             DataProductVariable(EPOCH_CDF_VAR_NAME, self.epoch),
-            DataProductVariable(
-                PROTON_SOLAR_WIND_SPEED_CDF_VAR_NAME, self.proton_sw_speed
-            ),
+            DataProductVariable(PROTON_SOLAR_WIND_SPEED_CDF_VAR_NAME, self.proton_sw_speed),
             DataProductVariable(
                 PROTON_SOLAR_WIND_SPEED_UNCERTAINTY_CDF_VAR_NAME,
                 self.proton_sw_speed_uncert,
@@ -133,9 +117,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 PROTON_SOLAR_WIND_TEMPERATURE_UNCERTAINTY_CDF_VAR_NAME,
                 self.proton_sw_temperature_uncert,
             ),
-            DataProductVariable(
-                PROTON_SOLAR_WIND_DENSITY_CDF_VAR_NAME, self.proton_sw_density
-            ),
+            DataProductVariable(PROTON_SOLAR_WIND_DENSITY_CDF_VAR_NAME, self.proton_sw_density),
             DataProductVariable(
                 PROTON_SOLAR_WIND_DENSITY_UNCERTAINTY_CDF_VAR_NAME,
                 self.proton_sw_density_uncert,
@@ -154,11 +136,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             ),
             DataProductVariable(
                 PROTON_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME,
-                np.sqrt(
-                    np.diagonal(
-                        self.proton_sw_velocity_rtn_covariance, axis1=1, axis2=2
-                    )
-                ),
+                np.sqrt(np.diagonal(self.proton_sw_velocity_rtn_covariance, axis1=1, axis2=2)),
             ),
             DataProductVariable(
                 PROTON_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME,
@@ -170,11 +148,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             ),
             DataProductVariable(
                 PROTON_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME,
-                np.sqrt(
-                    np.diagonal(
-                        self.proton_sw_velocity_gse_covariance, axis1=1, axis2=2
-                    )
-                ),
+                np.sqrt(np.diagonal(self.proton_sw_velocity_gse_covariance, axis1=1, axis2=2)),
             ),
             DataProductVariable(SWAPI_QUALITY_FLAGS_CDF_VAR_NAME, self.quality_flags),
             DataProductVariable(VELOCITY_RTN_LABEL_CDF_VAR_NAME, value=["R", "T", "N"]),
@@ -217,9 +191,7 @@ class SwapiL3AlphaSolarWindData(DataProduct):
     def to_data_product_variables(self) -> list[DataProductVariable]:
         return [
             DataProductVariable(EPOCH_CDF_VAR_NAME, self.epoch),
-            DataProductVariable(
-                ALPHA_SOLAR_WIND_SPEED_CDF_VAR_NAME, self.alpha_sw_speed
-            ),
+            DataProductVariable(ALPHA_SOLAR_WIND_SPEED_CDF_VAR_NAME, self.alpha_sw_speed),
             DataProductVariable(
                 ALPHA_SOLAR_WIND_SPEED_UNCERTAINTY_CDF_VAR_NAME,
                 self.alpha_sw_speed_uncert,
@@ -236,9 +208,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 EPOCH_DELTA_CDF_VAR_NAME,
                 np.full_like(self.epoch, THIRTY_SECONDS_IN_NANOSECONDS),
             ),
-            DataProductVariable(
-                ALPHA_SOLAR_WIND_DENSITY_CDF_VAR_NAME, self.alpha_sw_density
-            ),
+            DataProductVariable(ALPHA_SOLAR_WIND_DENSITY_CDF_VAR_NAME, self.alpha_sw_density),
             DataProductVariable(
                 ALPHA_SOLAR_WIND_DENSITY_UNCERTAINTY_CDF_VAR_NAME,
                 self.alpha_sw_density_uncert,
@@ -264,9 +234,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             ),
             DataProductVariable(
                 ALPHA_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME,
-                np.sqrt(
-                    np.diagonal(self.alpha_sw_velocity_rtn_covariance, axis1=1, axis2=2)
-                ),
+                np.sqrt(np.diagonal(self.alpha_sw_velocity_rtn_covariance, axis1=1, axis2=2)),
             ),
             DataProductVariable(
                 ALPHA_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME,
@@ -278,9 +246,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             ),
             DataProductVariable(
                 ALPHA_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME,
-                np.sqrt(
-                    np.diagonal(self.alpha_sw_velocity_gse_covariance, axis1=1, axis2=2)
-                ),
+                np.sqrt(np.diagonal(self.alpha_sw_velocity_gse_covariance, axis1=1, axis2=2)),
             ),
             DataProductVariable(SWAPI_QUALITY_FLAGS_CDF_VAR_NAME, self.quality_flags),
             DataProductVariable(VELOCITY_RTN_LABEL_CDF_VAR_NAME, value=["R", "T", "N"]),
@@ -325,19 +291,13 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 PUI_IONIZATION_RATE_UNCERTAINTY_CDF_VAR_NAME,
                 std_devs(self.ionization_rate),
             ),
-            DataProductVariable(
-                PUI_CUTOFF_SPEED_CDF_VAR_NAME, nominal_values(self.cutoff_speed)
-            ),
+            DataProductVariable(PUI_CUTOFF_SPEED_CDF_VAR_NAME, nominal_values(self.cutoff_speed)),
             DataProductVariable(
                 PUI_CUTOFF_SPEED_UNCERTAINTY_CDF_VAR_NAME, std_devs(self.cutoff_speed)
             ),
             DataProductVariable(PUI_DENSITY_CDF_VAR_NAME, nominal_values(self.density)),
-            DataProductVariable(
-                PUI_DENSITY_UNCERTAINTY_CDF_VAR_NAME, std_devs(self.density)
-            ),
-            DataProductVariable(
-                PUI_TEMPERATURE_CDF_VAR_NAME, nominal_values(self.temperature)
-            ),
+            DataProductVariable(PUI_DENSITY_UNCERTAINTY_CDF_VAR_NAME, std_devs(self.density)),
+            DataProductVariable(PUI_TEMPERATURE_CDF_VAR_NAME, nominal_values(self.temperature)),
             DataProductVariable(
                 PUI_TEMPERATURE_UNCERTAINTY_CDF_VAR_NAME, std_devs(self.temperature)
             ),
@@ -366,20 +326,14 @@ class SwapiL3aProtonDataFromCDF:
     def from_file(cls, data_file: Path) -> Self:
         with CDF(str(data_file)) as cdf:
             l2_parent_file_name = next(
-                parent
-                for parent in cdf.attrs["Parents"]
-                if parent.startswith("imap_swapi_l2_")
-            )
-            velocity_rtn = read_numeric_variable(
-                cdf[PROTON_SOLAR_WIND_VELOCITY_RTN_CDF_VAR_NAME]
+                parent for parent in cdf.attrs["Parents"] if parent.startswith("imap_swapi_l2_")
             )
+            velocity_rtn = read_numeric_variable(cdf[PROTON_SOLAR_WIND_VELOCITY_RTN_CDF_VAR_NAME])
             velocity_rtn_covariance = read_numeric_variable(
                 cdf[PROTON_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME]
             )
             density = read_numeric_variable(cdf[PROTON_SOLAR_WIND_DENSITY_CDF_VAR_NAME])
-            temperature = read_numeric_variable(
-                cdf[PROTON_SOLAR_WIND_TEMPERATURE_CDF_VAR_NAME]
-            )
+            temperature = read_numeric_variable(cdf[PROTON_SOLAR_WIND_TEMPERATURE_CDF_VAR_NAME])
             quality_flags = cdf[SWAPI_QUALITY_FLAGS_CDF_VAR_NAME][...]
         return cls(
             l2_parent_file_name,
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/calculate_pickup_ion_values.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/calculate_pickup_ion_values.py
index f2e926c1..ebd457e3 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/calculate_pickup_ion_values.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/calculate_pickup_ion_values.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
-from functools import partial
 
 from dataclasses import dataclass
+from functools import partial
 
 import numpy as np
 import scipy.optimize
@@ -138,9 +138,7 @@ def calculate_pickup_ion_values(
     density_of_neutral_helium_lookup_table : DensityOfNeutralHeliumLookupTable
         The neutral helium density table for the model.
     """
-    solar_wind_speed_inertial_frame = float(
-        np.linalg.norm(fit_input.solar_wind_velocity_rtn_sun)
-    )
+    solar_wind_speed_inertial_frame = float(np.linalg.norm(fit_input.solar_wind_velocity_rtn_sun))
     distance = fit_input.distance
     inflow_angle = fit_input.inflow_angle
 
@@ -164,14 +162,10 @@ def calculate_pickup_ion_values(
     shared_response = build_chunk_collapsed_response(
         swapi_response=swapi_response,
         voltages_v=shared_energies / SWAPI_L2_K_FACTOR,
-        bulk_sw_per_bin_kms=fit_input.bulk_sw_per_bin_swapi_kms[
-            :, shared_esa_step_mask, :
-        ],
+        bulk_sw_per_bin_kms=fit_input.bulk_sw_per_bin_swapi_kms[:, shared_esa_step_mask, :],
         time_as_tt2000=fit_input.time_as_tt2000,
         species=_PICKUP_ION_SPECIES,
-        cutoff_speed_max_kms=solar_wind_speed_inertial_frame
-        * MAX_CUTOFF_SPEED_RATIO
-        * 1.1,
+        cutoff_speed_max_kms=solar_wind_speed_inertial_frame * MAX_CUTOFF_SPEED_RATIO * 1.1,
     )
     fitting_response = ChunkCollapsedResponse(
         speed_grid=shared_response.speed_grid,
@@ -204,9 +198,7 @@ def model(ionization_rate, cutoff_speed, response):
     def residuals(log_parameters: np.ndarray) -> np.ndarray:
         modeled_rates = (
             fitting_window_model(
-                ionization_rate=float(
-                    np.exp(log_parameters[_LOG_IONIZATION_RATE_INDEX])
-                ),
+                ionization_rate=float(np.exp(log_parameters[_LOG_IONIZATION_RATE_INDEX])),
                 cutoff_speed=float(np.exp(log_parameters[_LOG_CUTOFF_SPEED_INDEX])),
             )
             + SWAPI_BACKGROUND_RATE
@@ -263,9 +255,7 @@ def residuals(log_parameters: np.ndarray) -> np.ndarray:
         cutoff_speed=ufloat(fitted_cutoff_speed, fitted_cutoff_speed_error),
         density=calculate_helium_pui_density(
             shared_response.speed_grid,
-            ionization_rate=ufloat(
-                fitted_ionization_rate, fitted_ionization_rate_error
-            ),
+            ionization_rate=ufloat(fitted_ionization_rate, fitted_ionization_rate_error),
             cutoff_speed=ufloat(fitted_cutoff_speed, fitted_cutoff_speed_error),
             distance=distance,
             inflow_angle=inflow_angle,
@@ -274,9 +264,7 @@ def residuals(log_parameters: np.ndarray) -> np.ndarray:
         ),
         temperature=calculate_helium_pui_temperature(
             shared_response.speed_grid,
-            ionization_rate=ufloat(
-                fitted_ionization_rate, fitted_ionization_rate_error
-            ),
+            ionization_rate=ufloat(fitted_ionization_rate, fitted_ionization_rate_error),
             cutoff_speed=ufloat(fitted_cutoff_speed, fitted_cutoff_speed_error),
             distance=distance,
             inflow_angle=inflow_angle,
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/collapsed_response_grid.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/collapsed_response_grid.py
index c49228ba..160b6ad5 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/collapsed_response_grid.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/collapsed_response_grid.py
@@ -17,19 +17,17 @@
 from imap_l3_processing.swapi.l3a.utils import (
     velocity_components_to_angles_in_instrument_frame,
 )
-from imap_l3_processing.swapi.response.passband_grid import interpolate_passband
-from imap_l3_processing.swapi.response.swapi_response import ResponseGrid, SwapiResponse
-from imap_l3_processing.swapi.species import Species
 from imap_l3_processing.swapi.response.azimuthal_transmission import (
     interpolate_azimuthal_transmission,
 )
+from imap_l3_processing.swapi.response.passband_grid import interpolate_passband
+from imap_l3_processing.swapi.response.swapi_response import ResponseGrid, SwapiResponse
+from imap_l3_processing.swapi.species import Species
 
 
 class ChunkCollapsedResponse(NamedTuple):
     speed_grid: UniformSpeedGrid  # shared v' grid of N cells
-    bin_weights: NDArray[
-        float
-    ]  # (n_sweeps, n_steps, N); count_rate = bin_weights @ f(v')
+    bin_weights: NDArray[float]  # (n_sweeps, n_steps, N); count_rate = bin_weights @ f(v')
 
 
 class CollapsedResponseGrid(NamedTuple):
@@ -59,9 +57,7 @@ def build_chunk_collapsed_response(
     bulk_sw_per_bin_kms = np.asarray(bulk_sw_per_bin_kms, dtype=float)
     n_sweeps, n_steps, _ = bulk_sw_per_bin_kms.shape
     if voltages_v.shape != (n_steps,):
-        raise ValueError(
-            f"voltages_v shape {voltages_v.shape} must match n_steps={n_steps}"
-        )
+        raise ValueError(f"voltages_v shape {voltages_v.shape} must match n_steps={n_steps}")
     bulk_speeds = np.linalg.norm(bulk_sw_per_bin_kms, axis=-1)  # (n_sweeps, n_steps)
 
     speed_grid = UniformSpeedGrid(cutoff_speed_max_kms)
@@ -78,9 +74,7 @@ def build_chunk_collapsed_response(
                     bulk_vec[0], bulk_vec[1], bulk_vec[2]
                 )
             )
-            response_grid = swapi_response.get_response_grid(
-                time_as_tt2000, voltage, species
-            )
+            response_grid = swapi_response.get_response_grid(time_as_tt2000, voltage, species)
             collapsed = build_collapsed_response_grid(
                 response_grid,
                 bulk_speed,
@@ -88,9 +82,7 @@ def build_chunk_collapsed_response(
                 bulk_elevation_deg,
                 speed_in_sw_frame=speed_grid.centers,
             )
-            bin_weights[sweep_index, step_index, :] = (
-                collapsed.values * integration_weights
-            )
+            bin_weights[sweep_index, step_index, :] = collapsed.values * integration_weights
 
     return ChunkCollapsedResponse(speed_grid=speed_grid, bin_weights=bin_weights)
 
@@ -104,9 +96,7 @@ def build_collapsed_response_grid(
 ) -> CollapsedResponseGrid:
     speed_in_sw_frame = np.asarray(speed_in_sw_frame, dtype=float)
     if speed_in_sw_frame.ndim != 1:
-        raise ValueError(
-            f"speed_in_sw_frame shape {speed_in_sw_frame.shape} must be 1D"
-        )
+        raise ValueError(f"speed_in_sw_frame shape {speed_in_sw_frame.shape} must be 1D")
 
     v_prime_min, v_prime_max = solar_wind_frame_speed_range(
         response_grid.central_speed, float(bulk_speed)
@@ -148,8 +138,7 @@ def _collapse_response(
     bulk_elevation: float,
 ):
     central_effective_area_km2 = (
-        response_grid.central_effective_area
-        / (CENTIMETERS_PER_METER * METERS_PER_KILOMETER) ** 2
+        response_grid.central_effective_area / (CENTIMETERS_PER_METER * METERS_PER_KILOMETER) ** 2
     )
     central_speed = float(response_grid.central_speed)
     cos_bulk_elevation = math.cos(math.radians(bulk_elevation))
@@ -187,9 +176,7 @@ def _collapse_response(
 
             for i in range(speed_in_sw_frame.shape[0]):
                 v_prime = speed_in_sw_frame[i]
-                cos_angle = (speed**2 + bulk_speed**2 - v_prime**2) / (
-                    2.0 * speed * bulk_speed
-                )
+                cos_angle = (speed**2 + bulk_speed**2 - v_prime**2) / (2.0 * speed * bulk_speed)
 
                 cos_delta_azimuth = (cos_angle - sin_elevation * sin_bulk_elevation) / (
                     cos_elevation * cos_bulk_elevation
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/density_of_neutral_helium_lookup_table.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/density_of_neutral_helium_lookup_table.py
index 42db7009..ed7cab46 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/density_of_neutral_helium_lookup_table.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/density_of_neutral_helium_lookup_table.py
@@ -1,5 +1,3 @@
-from typing import Union
-
 import numpy as np
 from numpy import ndarray
 from scipy.interpolate import RegularGridInterpolator
@@ -12,9 +10,7 @@ def __init__(self, calibration_table: np.ndarray):
 
         self.grid = (angle, distance)
         values_shape = tuple(len(x) for x in self.grid)
-        self.densities = np.ascontiguousarray(
-            calibration_table[:, 2].reshape(values_shape)
-        )
+        self.densities = np.ascontiguousarray(calibration_table[:, 2].reshape(values_shape))
         if 360.0 not in angle:
             assert angle[0] == 0.0, "expected table to start at angle 0"
             angle_with_360 = np.append(angle, 360.0)
@@ -25,7 +21,7 @@ def __init__(self, calibration_table: np.ndarray):
             self.grid, self.densities, bounds_error=False, fill_value=0, method="linear"
         )
 
-    def density(self, angle: Union[ndarray, float], distance: Union[ndarray, float]):
+    def density(self, angle: ndarray | float, distance: ndarray | float):
         if isinstance(distance, float):
             coords = np.array((angle % 360, distance))
             result = self._interp(coords)[0]
@@ -40,9 +36,7 @@ def density(self, angle: Union[ndarray, float], distance: Union[ndarray, float])
                 distance > self.get_minimum_distance(),
                 result,
                 (
-                    self.density(
-                        angle, np.ones_like(distance) * self.get_minimum_distance()
-                    )
+                    self.density(angle, np.ones_like(distance) * self.get_minimum_distance())
                     * (distance / self.get_minimum_distance())
                 ),
             )
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/goodness_of_fit.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/goodness_of_fit.py
index c4e4e098..b7185aa6 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/goodness_of_fit.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/goodness_of_fit.py
@@ -6,9 +6,7 @@
 MAX_CUTOFF_SPEED_KMS = 550.0  # v_cutoff <= 550 km/s
 MAX_MEAN_RELATIVE_ERROR = 0.12  # Delta_rel <= 0.12
 MAX_PAST_PEAK_RATIO = 0.4  # R_past_peak <= 0.4
-CUTOFF_DROP_RATIO = (
-    0.25  # extend up to and including the last step with model rate >= 0.25 * peak
-)
+CUTOFF_DROP_RATIO = 0.25  # extend up to and including the last step with model rate >= 0.25 * peak
 MIN_CUTOFF_SPEED_RATIO = 0.5  # v_cutoff >= 0.5 * v_sw
 MAX_CUTOFF_SPEED_RATIO = 1.5  # v_cutoff <= 1.5 * v_sw
 MIN_IONIZATION_RATE = 0.6e-9  # beta >= 0.6 * 10^-9 s^-1
@@ -69,15 +67,11 @@ def is_good_fit(
     in_range = ~past_range
 
     mean_absolute_percent_error = (
-        np.abs(
-            chunk_mean_model_rates + SWAPI_BACKGROUND_RATE - chunk_mean_observed_rates
-        )
+        np.abs(chunk_mean_model_rates + SWAPI_BACKGROUND_RATE - chunk_mean_observed_rates)
         / (chunk_mean_model_rates + SWAPI_BACKGROUND_RATE)
     )[in_range].mean()
 
-    past_cutoff_ratio = (
-        chunk_mean_observed_rates[past_range].mean() / chunk_mean_model_rates.max()
-    )
+    past_cutoff_ratio = chunk_mean_observed_rates[past_range].mean() / chunk_mean_model_rates.max()
 
     cutoff_speed_ratio = cutoff_speed_kms / sw_speed_kms
 
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/inflow_vector.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/inflow_vector.py
index ab66bb33..61a5c4a7 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/inflow_vector.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/inflow_vector.py
@@ -19,9 +19,7 @@ def from_file(cls, path: PathLike) -> InflowVector:
 
         loaded_vector = np.squeeze(np.loadtxt(path, dtype=float))
 
-        assert loaded_vector.shape == (3,), (
-            f"Failed to parse Inflow Vector from {path.name}"
-        )
+        assert loaded_vector.shape == (3,), f"Failed to parse Inflow Vector from {path.name}"
 
         return cls(
             speed_km_per_s=(loaded_vector[0]),
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/moments.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/moments.py
index 69f8114f..f36f70af 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/moments.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/moments.py
@@ -49,9 +49,7 @@ def calculate(ionization_rate, cutoff_speed):
             density_of_neutral_helium_lookup_table=density_of_neutral_helium_lookup_table,
         )
         integral = float(np.sum(speed_grid.spherical_shell_integration_weights * f_pui))
-        return (
-            4 * np.pi * integral / (CENTIMETERS_PER_METER * METERS_PER_KILOMETER) ** 3
-        )
+        return 4 * np.pi * integral / (CENTIMETERS_PER_METER * METERS_PER_KILOMETER) ** 3
 
     return calculate(ionization_rate, cutoff_speed)
 
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/uniform_speed_grid.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/uniform_speed_grid.py
index d4942192..ee8fd1dd 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/uniform_speed_grid.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/uniform_speed_grid.py
@@ -29,6 +29,4 @@ def __init__(self, max_center_speed: float) -> None:
         self.centers: NDArray = np.linspace(min_speed, max_center_speed, _CELL_COUNT)
         self.spacing: float = float(self.centers[1] - self.centers[0])
         self.size: int = int(self.centers.size)
-        self.spherical_shell_integration_weights: NDArray = (
-            self.centers**2 * self.spacing
-        )
+        self.spherical_shell_integration_weights: NDArray = self.centers**2 * self.spacing
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/utils.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/utils.py
index f44af1c7..3b367645 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/utils.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/utils.py
@@ -25,9 +25,7 @@ def convert_velocity_relative_to_imap(velocity, ephemeris_time, from_frame, to_f
     velocity_in_target_frame_relative_to_imap = convert_velocity_to_reference_frame(
         velocity, ephemeris_time, from_frame, to_frame
     )
-    imap_velocity = spiceypy.spkezr("IMAP", ephemeris_time, to_frame, "NONE", "SUN")[0][
-        3:6
-    ]
+    imap_velocity = spiceypy.spkezr("IMAP", ephemeris_time, to_frame, "NONE", "SUN")[0][3:6]
 
     return velocity_in_target_frame_relative_to_imap + imap_velocity
 
diff --git a/imap_l3_processing/swapi/l3a/science/pickup_ion/vasyliunas_siscoe_distribution.py b/imap_l3_processing/swapi/l3a/science/pickup_ion/vasyliunas_siscoe_distribution.py
index e012ee35..d1acc416 100644
--- a/imap_l3_processing/swapi/l3a/science/pickup_ion/vasyliunas_siscoe_distribution.py
+++ b/imap_l3_processing/swapi/l3a/science/pickup_ion/vasyliunas_siscoe_distribution.py
@@ -4,9 +4,9 @@
 from numpy.typing import NDArray
 
 from imap_l3_processing.constants import (
-    ONE_AU_IN_KM,
     CENTIMETERS_PER_METER,
     METERS_PER_KILOMETER,
+    ONE_AU_IN_KM,
 )
 from imap_l3_processing.swapi.constants import SWAPI_PUI_COOLING_INDEX
 from imap_l3_processing.swapi.l3a.science.pickup_ion.density_of_neutral_helium_lookup_table import (
@@ -81,8 +81,7 @@ def _filled_shell_vdf_without_cutoff(
         inflow_angle, radius_in_au * w**SWAPI_PUI_COOLING_INDEX
     )
     neutral_helium_density_per_km3 = (
-        neutral_helium_density_per_cm3
-        * (CENTIMETERS_PER_METER * METERS_PER_KILOMETER) ** 3
+        neutral_helium_density_per_cm3 * (CENTIMETERS_PER_METER * METERS_PER_KILOMETER) ** 3
     )
     term1 = SWAPI_PUI_COOLING_INDEX / (4 * np.pi)
     term2 = (ionization_rate * ONE_AU_IN_KM**2) / (
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/calculate_initial_guess.py b/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/calculate_initial_guess.py
index 44adb416..511e3c0c 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/calculate_initial_guess.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/calculate_initial_guess.py
@@ -1,5 +1,3 @@
-from typing import Optional
-
 import numpy as np
 from numpy import ndarray
 
@@ -19,7 +17,7 @@ def calculate_initial_guess(
     proton_true_rate: ndarray,
     proton_temperature: float,
     proton_velocity_rtn: ndarray,
-) -> Optional[tuple[float, float, float, ndarray]]:
+) -> tuple[float, float, float, ndarray] | None:
     if alpha_ctx.count_rate.size == 0 or alpha_ctx.count_rate.ndim != 2:
         return None
 
@@ -27,9 +25,7 @@ def calculate_initial_guess(
     counts_per_sweep = alpha_ctx.count_rate
     voltage_per_sweep = alpha_ctx.esa_voltage[0]
     proton_true_per_sweep = proton_true_rate.reshape(n_sweeps, n_bins)
-    proton_obs_per_sweep = proton_true_per_sweep * deadtime_factor(
-        proton_true_per_sweep
-    )
+    proton_obs_per_sweep = proton_true_per_sweep * deadtime_factor(proton_true_per_sweep)
 
     count_avg = counts_per_sweep.mean(axis=0)
     proton_bg_avg = proton_obs_per_sweep.mean(axis=0)
@@ -76,7 +72,7 @@ def _get_alpha_peak_indices(residuals, energies, proton_peak_index) -> slice:
             break
 
     if first_index_at_or_above_min_energy is None:
-        raise Exception("Proton peak too high to find alpha peak")
+        raise RuntimeError("Proton peak too high to find alpha peak")
 
     window_energy_min = None
     for i in reversed(range(first_index_at_or_above_min_energy + 1)):
@@ -86,7 +82,7 @@ def _get_alpha_peak_indices(residuals, energies, proton_peak_index) -> slice:
             break
 
     if window_energy_min is None:
-        raise Exception("Alpha peak not found")
+        raise RuntimeError("Alpha peak not found")
 
     window_energy_max = max_energy
 
@@ -96,5 +92,5 @@ def _get_alpha_peak_indices(residuals, energies, proton_peak_index) -> slice:
     alpha_peak_index = masked_residuals.argmax()
 
     if alpha_peak_index < 3:
-        raise Exception("Alpha peak too close to high-energy edge")
+        raise RuntimeError("Alpha peak too close to high-energy edge")
     return slice(alpha_peak_index - 3, alpha_peak_index + 2)
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/fit_solar_wind_alpha_model.py b/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/fit_solar_wind_alpha_model.py
index 7aa41baa..0df7b557 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/fit_solar_wind_alpha_model.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/alpha/fit_solar_wind_alpha_model.py
@@ -1,5 +1,4 @@
 from dataclasses import dataclass
-from typing import Optional
 
 import numpy as np
 import scipy.optimize
@@ -18,8 +17,8 @@
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
     LOG_DENSITY_IDX,
     LOG_TEMPERATURE_IDX,
-    SolarWindParams,
     VELOCITY_SLICE,
+    SolarWindParams,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
     ProtonSolarWindFitResult,
@@ -160,9 +159,7 @@ def _construct_alpha_fit_result(
     delta_v_fit = float(result.x[2])
     velocity_rtn = proton_bulk + delta_v_fit * magnetic_field_direction
 
-    speed_ratio = np.linalg.norm(velocity_rtn, axis=-1) / np.linalg.norm(
-        proton_bulk, axis=-1
-    )
+    speed_ratio = np.linalg.norm(velocity_rtn, axis=-1) / np.linalg.norm(proton_bulk, axis=-1)
     if speed_ratio < MIN_TOLERABLE_ALPHA_SPEED_RATIO:
         return _nan_alpha_fit_result(bad_fit_flag | SwapiL3Flags.BAD_FIT)
 
@@ -181,9 +178,8 @@ def _construct_alpha_fit_result(
     delta_v_sigma = float(np.sqrt(max(cov_x[2, 2], 0.0)))
 
     sigma_dv2 = max(cov_x[2, 2], 0.0)
-    velocity_covariance_rtn = (
-        proton_moments.velocity_rtn_covariance()
-        + sigma_dv2 * np.outer(magnetic_field_direction, magnetic_field_direction)
+    velocity_covariance_rtn = proton_moments.velocity_rtn_covariance() + sigma_dv2 * np.outer(
+        magnetic_field_direction, magnetic_field_direction
     )
 
     return AlphaSolarWindFitResult(
@@ -215,9 +211,9 @@ def __init__(
         self.magnetic_field_direction = magnetic_field_direction
         self.proton_true_rate = proton_true_rate
         self.alpha_ctx = alpha_ctx
-        self._last_state: Optional[ndarray] = None
-        self._last_residuals: Optional[ndarray] = None
-        self._last_jacobian: Optional[ndarray] = None
+        self._last_state: ndarray | None = None
+        self._last_residuals: ndarray | None = None
+        self._last_jacobian: ndarray | None = None
 
     def _eval(self, x: ndarray) -> None:
         alpha_density = float(np.exp(x[0]))
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/fit_context.py b/imap_l3_processing/swapi/l3a/science/solar_wind/fit_context.py
index df5b12ed..991a29fc 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/fit_context.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/fit_context.py
@@ -17,15 +17,11 @@ class SolarWindFitContext(NamedTuple):
 
     def subset(self, bin_indices: ndarray) -> Self:
         n_sweeps, n_bins = self.count_rate.shape
-        flat_indices = np.concatenate(
-            [bin_indices + s * n_bins for s in range(n_sweeps)]
-        )
+        flat_indices = np.concatenate([bin_indices + s * n_bins for s in range(n_sweeps)])
         return self._replace(
             count_rate=self.count_rate[:, bin_indices],
             esa_voltage=self.esa_voltage[:, bin_indices],
-            response_grids=numba.typed.List(
-                [self.response_grids[i] for i in flat_indices]
-            ),
+            response_grids=numba.typed.List([self.response_grids[i] for i in flat_indices]),
             rotation_matrices=self.rotation_matrices[flat_indices],
         )
 
@@ -48,10 +44,7 @@ def build_solar_wind_fit_context(
         )
 
     response_grids = numba.typed.List(
-        [
-            swapi_response.get_response_grid(time_as_tt2000, v, species)
-            for v in flat_voltage
-        ]
+        [swapi_response.get_response_grid(time_as_tt2000, v, species) for v in flat_voltage]
     )
 
     return SolarWindFitContext(
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/forward_model.py b/imap_l3_processing/swapi/l3a/science/solar_wind/forward_model.py
index 6b32ff7f..a5bc38f8 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/forward_model.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/forward_model.py
@@ -13,27 +13,27 @@
     REGION_SUNGLASSES,
     AzimuthalRegion,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
+    SolarWindFitContext,
+)
 from imap_l3_processing.swapi.l3a.science.solar_wind.integration_limits import (
     AngularQuadrature,
     get_angular_quadrature,
     get_speed_quadrature,
     speed_window_misses_passband,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.utils import (
-    count_rate_conversion_factor,
-)
-from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
-    SolarWindFitContext,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
     LOG_DENSITY_IDX,
     LOG_TEMPERATURE_IDX,
     N_STATE,
-    SolarWindParams,
     VELOCITY_SLICE,
+    SolarWindParams,
     bulk_speed,
     thermal_speed,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.utils import (
+    count_rate_conversion_factor,
+)
 from imap_l3_processing.swapi.response.swapi_response import ResponseGrid
 
 
@@ -135,11 +135,7 @@ def _integrate_region(
             for i_speed in range(speed_quadrature.points.shape[0]):
                 speed = speed_quadrature.points[i_speed]
                 exponent = (
-                    (
-                        speed**2
-                        + bulk_speed(sw_params) ** 2
-                        - 2 * speed * velocity_along_direction
-                    )
+                    (speed**2 + bulk_speed(sw_params) ** 2 - 2 * speed * velocity_along_direction)
                     * 1.0
                     / (2 * thermal_speed(sw_params) ** 2)
                 )
@@ -160,9 +156,7 @@ def _integrate_region(
 
             azimuth_rate += azimuth_weight * rate_integral
 
-            azimuth_log_temperature_jacobian += (
-                azimuth_weight * log_temperature_jacobian_integral
-            )
+            azimuth_log_temperature_jacobian += azimuth_weight * log_temperature_jacobian_integral
             azimuth_jacobian_r += azimuth_weight * (
                 direction_r * velocity_along_direction_integral - bulk_r * rate_integral
             )
@@ -178,9 +172,7 @@ def _integrate_region(
             * angular_quadrature.cos_elevation[i_elevation]
         )
         elevation_rate += azimuth_rate * elevation_weight
-        elevation_log_temperature_jacobian += (
-            azimuth_log_temperature_jacobian * elevation_weight
-        )
+        elevation_log_temperature_jacobian += azimuth_log_temperature_jacobian * elevation_weight
         elevation_jacobian_r += azimuth_jacobian_r * elevation_weight
         elevation_jacobian_t += azimuth_jacobian_t * elevation_weight
         elevation_jacobian_n += azimuth_jacobian_n * elevation_weight
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/integration_limits.py b/imap_l3_processing/swapi/l3a/science/solar_wind/integration_limits.py
index 5f9519fd..8f8063dd 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/integration_limits.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/integration_limits.py
@@ -6,14 +6,14 @@
 from imap_l3_processing.swapi.l3a.science.solar_wind.azimuthal_regions import (
     AzimuthalRegion,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.trim_open_aperture import (
-    trim_open_aperture,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
     SolarWindParams,
     bulk_speed,
     thermal_speed,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.trim_open_aperture import (
+    trim_open_aperture,
+)
 from imap_l3_processing.swapi.l3a.utils import (
     velocity_to_angles_in_instrument_frame,
 )
@@ -56,9 +56,7 @@ class SpeedQuadrature(NamedTuple):
 
 
 @numba.njit
-def speed_window_misses_passband(
-    sw_params: SolarWindParams, response_grid: ResponseGrid
-) -> bool:
+def speed_window_misses_passband(sw_params: SolarWindParams, response_grid: ResponseGrid) -> bool:
     sigma = thermal_speed(sw_params)
     speed = bulk_speed(sw_params)
 
@@ -137,9 +135,7 @@ def get_speed_quadrature(
     region: AzimuthalRegion,
     elevation: float,
 ):
-    passband = (
-        response_grid.sg_passband if region.is_sunglasses else response_grid.oa_passband
-    )
+    passband = response_grid.sg_passband if region.is_sunglasses else response_grid.oa_passband
     central_speed = response_grid.central_speed
     sigma = thermal_speed(sw_params)
     bulk_v = bulk_speed(sw_params)
@@ -174,12 +170,8 @@ def _angular_limits(
     region: AzimuthalRegion,
     response_grid: ResponseGrid,
 ):
-    half_width = _maxwellian_angular_extent(
-        sw_params, response_grid.central_speed, EPSILON
-    )
-    bulk_az, bulk_el = velocity_to_angles_in_instrument_frame(
-        sw_params, rotation_matrix
-    )
+    half_width = _maxwellian_angular_extent(sw_params, response_grid.central_speed, EPSILON)
+    bulk_az, bulk_el = velocity_to_angles_in_instrument_frame(sw_params, rotation_matrix)
 
     if region.is_sunglasses:
         el_lo, el_hi = response_grid.sg_passband.elevation_range
@@ -209,9 +201,7 @@ def _clamp(x: float, lower: float, upper: float) -> float:
 
 
 @numba.njit
-def _clamp_window(
-    center: float, half_width: float, lower_bound: float, upper_bound: float
-):
+def _clamp_window(center: float, half_width: float, lower_bound: float, upper_bound: float):
     return (
         _clamp(center - half_width, lower_bound, upper_bound),
         _clamp(center + half_width, lower_bound, upper_bound),
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/params.py b/imap_l3_processing/swapi/l3a/science/solar_wind/params.py
index ef1833ce..05814a76 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/params.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/params.py
@@ -59,8 +59,7 @@ def thermal_speed(sw_params: SolarWindParams) -> float:
 def temperature_to_thermal_speed(mass: float, temperature: float) -> float:
     """mass [kg], temperature [K] -> thermal speed [km/s]."""
     return (
-        math.sqrt(BOLTZMANN_CONSTANT_JOULES_PER_KELVIN * temperature / mass)
-        / METERS_PER_KILOMETER
+        math.sqrt(BOLTZMANN_CONSTANT_JOULES_PER_KELVIN * temperature / mass) / METERS_PER_KILOMETER
     )
 
 
@@ -68,7 +67,5 @@ def temperature_to_thermal_speed(mass: float, temperature: float) -> float:
 def thermal_speed_to_temperature(thermal_speed: float, mass: float) -> float:
     """thermal speed [km/s], mass [kg] -> temperature [K]."""
     return (
-        mass
-        * (thermal_speed * METERS_PER_KILOMETER) ** 2
-        / BOLTZMANN_CONSTANT_JOULES_PER_KELVIN
+        mass * (thermal_speed * METERS_PER_KILOMETER) ** 2 / BOLTZMANN_CONSTANT_JOULES_PER_KELVIN
     )
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/calculate_initial_guess.py b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/calculate_initial_guess.py
index ad910c12..d80923e1 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/calculate_initial_guess.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/calculate_initial_guess.py
@@ -6,28 +6,25 @@
     BOLTZMANN_CONSTANT_JOULES_PER_KELVIN,
     PROTON_CHARGE_COULOMBS,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
-    model_solar_wind_ideal_coincidence_rates,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     SolarWindFitContext,
 )
-from imap_l3_processing.swapi.l3a.utils import (
-    esa_voltage_to_proton_speed,
-    optimal_density_scale,
+from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
+    model_solar_wind_ideal_coincidence_rates,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.utils import average_spin_axis_rtn
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
     SolarWindParams,
     temperature_to_thermal_speed,
     thermal_speed_to_temperature,
 )
-
+from imap_l3_processing.swapi.l3a.science.solar_wind.utils import average_spin_axis_rtn
+from imap_l3_processing.swapi.l3a.utils import (
+    esa_voltage_to_proton_speed,
+    optimal_density_scale,
+)
 
 # 1 eV
-INITIAL_TEMPERATURE_FLOOR_K = (
-    PROTON_CHARGE_COULOMBS / BOLTZMANN_CONSTANT_JOULES_PER_KELVIN
-)
+INITIAL_TEMPERATURE_FLOOR_K = PROTON_CHARGE_COULOMBS / BOLTZMANN_CONSTANT_JOULES_PER_KELVIN
 
 
 def calculate_initial_guess(ctx: SolarWindFitContext) -> SolarWindParams:
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/escape_local_minimum.py b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/escape_local_minimum.py
index 6669cbaf..6f26e4ad 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/escape_local_minimum.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/escape_local_minimum.py
@@ -16,7 +16,6 @@
 from imap_l3_processing.swapi.l3a.utils import optimal_density_scale
 from imap_l3_processing.swapi.response.deadtime import deadtime_factor
 
-
 _MAX_BASIN_REFINE_ITERS = 6
 _ROTATED_RMSE_RATIO_THRESHOLD = 10
 
@@ -29,9 +28,7 @@ def escape_local_minimum(
 
     current_result = first_result
     for _ in range(_MAX_BASIN_REFINE_ITERS):
-        flipped_mse, flipped_seed_params = flipped_seed(
-            current_result, ctx, spin_axis_rtn
-        )
+        flipped_mse, flipped_seed_params = flipped_seed(current_result, ctx, spin_axis_rtn)
 
         flipped_seed_is_substantially_worse_than_current = (
             flipped_mse >= current_result.mse * _ROTATED_RMSE_RATIO_THRESHOLD**2
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/fit_solar_wind_proton_model.py b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/fit_solar_wind_proton_model.py
index 2de0b9f3..7e91ae6a 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/fit_solar_wind_proton_model.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/fit_solar_wind_proton_model.py
@@ -13,12 +13,12 @@
     LOG_TEMPERATURE_IDX,
     VELOCITY_SLICE,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.proton.escape_local_minimum import (
-    escape_local_minimum,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.calculate_initial_guess import (
     calculate_initial_guess,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.proton.escape_local_minimum import (
+    escape_local_minimum,
+)
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.optimize_solar_wind_proton_params import (
     OptimizeSolarWindProtonParamsResult,
     optimize_solar_wind_proton_params,
@@ -30,7 +30,6 @@
 )
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
 
-
 _R_SQUARED_PEAK_HALF_WIDTH = 4
 
 
@@ -59,9 +58,7 @@ def _construct_fit_result(final_result, ctx):
     if not final_result.success:
         return _nan_proton_fit_result(int(SwapiL3Flags.FIT_ERROR))
 
-    fit_r_squared = _coarse_peak_averaged_r_squared(
-        final_result.residuals, ctx.count_rate
-    )
+    fit_r_squared = _coarse_peak_averaged_r_squared(final_result.residuals, ctx.count_rate)
     flag_bad = fit_r_squared < 0.9 or final_result.sw_params.temperature > 5.0e5
     if flag_bad:
         return _nan_proton_fit_result(int(SwapiL3Flags.BAD_FIT))
@@ -115,20 +112,14 @@ def _derive_uncertainties(
     result: OptimizeSolarWindProtonParamsResult,
     ctx: SolarWindFitContext,
 ) -> tuple[float, float, ndarray]:
-    parameter_covariance = compute_hc3_parameter_covariance(
-        result.jacobian, result.residuals
-    )
+    parameter_covariance = compute_hc3_parameter_covariance(result.jacobian, result.residuals)
     if not np.all(np.isfinite(parameter_covariance)):
         return np.nan, np.nan, np.full((3, 3), np.nan)
 
     log_density_variance = parameter_covariance[LOG_DENSITY_IDX, LOG_DENSITY_IDX]
-    log_temperature_variance = parameter_covariance[
-        LOG_TEMPERATURE_IDX, LOG_TEMPERATURE_IDX
-    ]
+    log_temperature_variance = parameter_covariance[LOG_TEMPERATURE_IDX, LOG_TEMPERATURE_IDX]
 
-    density_error = float(
-        result.sw_params.density * np.sqrt(max(log_density_variance, 0.0))
-    )
+    density_error = float(result.sw_params.density * np.sqrt(max(log_density_variance, 0.0)))
     temperature_error = float(
         result.sw_params.temperature * np.sqrt(max(log_temperature_variance, 0.0))
     )
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/optimize_solar_wind_proton_params.py b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/optimize_solar_wind_proton_params.py
index 45c954b8..c36e2c8b 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/proton/optimize_solar_wind_proton_params.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/proton/optimize_solar_wind_proton_params.py
@@ -57,9 +57,7 @@ def __init__(self, ctx: SolarWindFitContext):
 
     def _eval(self, state: ndarray) -> None:
         sw = SolarWindParams.from_vector(state, self.ctx.mass_kg)
-        rate_ideal, jacobian_ideal = model_solar_wind_ideal_coincidence_rates(
-            sw, self.ctx
-        )
+        rate_ideal, jacobian_ideal = model_solar_wind_ideal_coincidence_rates(sw, self.ctx)
 
         df = deadtime_factor(rate_ideal)
 
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/trim_open_aperture.py b/imap_l3_processing/swapi/l3a/science/solar_wind/trim_open_aperture.py
index 8b748b50..ae8c1981 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/trim_open_aperture.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/trim_open_aperture.py
@@ -22,7 +22,6 @@
 )
 from imap_l3_processing.swapi.response.swapi_response import ResponseGrid
 
-
 OA_SCAN_THRESHOLD = 1e-6
 OA_SCAN_RESOLUTION = 64
 OA_SKIP_FRACTION = 1e-3
@@ -64,9 +63,7 @@ def trim_open_aperture(
 
     dphi_deg = scan_azimuths[1] - scan_azimuths[0]
     transmission_az_integral = float(
-        np.trapezoid(
-            transmission_x_maxwellian[lower_index : upper_index + 1], dx=dphi_deg
-        )
+        np.trapezoid(transmission_x_maxwellian[lower_index : upper_index + 1], dx=dphi_deg)
     )
     upper_bound = _oa_rate_upper_bound(
         response_grid,
@@ -91,9 +88,7 @@ def _evaluate_oa_integrand_along_azimuth(
     sigma = thermal_speed(sw_params)
     speed = bulk_speed(sw_params)
     central_speed = response_grid.central_speed
-    bulk_az, bulk_el = velocity_to_angles_in_instrument_frame(
-        sw_params, rotation_matrix
-    )
+    bulk_az, bulk_el = velocity_to_angles_in_instrument_frame(sw_params, rotation_matrix)
 
     sin_bulk_el = math.sin(np.radians(bulk_el))
     cos_bulk_el = math.cos(np.radians(bulk_el))
@@ -102,9 +97,7 @@ def _evaluate_oa_integrand_along_azimuth(
     cos_view_to_bulk = sin_bulk_el * sin_scan_el + cos_bulk_el * cos_scan_el * np.cos(
         np.radians(scan_azimuths - bulk_az)
     )
-    delta_v_sq = (
-        central_speed**2 + speed**2 - 2.0 * central_speed * speed * cos_view_to_bulk
-    )
+    delta_v_sq = central_speed**2 + speed**2 - 2.0 * central_speed * speed * cos_view_to_bulk
     maxwellian = np.exp(-delta_v_sq / (2.0 * sigma**2))
 
     for i in range(scan_azimuths.shape[0]):
diff --git a/imap_l3_processing/swapi/l3a/science/solar_wind/utils.py b/imap_l3_processing/swapi/l3a/science/solar_wind/utils.py
index 00f8a785..f8f3a091 100644
--- a/imap_l3_processing/swapi/l3a/science/solar_wind/utils.py
+++ b/imap_l3_processing/swapi/l3a/science/solar_wind/utils.py
@@ -19,9 +19,7 @@ def average_spin_axis_rtn(rotation_matrices: ndarray) -> ndarray:
 
 
 @numba.njit
-def count_rate_conversion_factor(
-    sw_params: SolarWindParams, response_grid: ResponseGrid
-) -> float:
+def count_rate_conversion_factor(sw_params: SolarWindParams, response_grid: ResponseGrid) -> float:
     sigma = thermal_speed(sw_params)
     return (
         response_grid.central_effective_area
diff --git a/imap_l3_processing/swapi/l3a/swapi_l3a_dependencies.py b/imap_l3_processing/swapi/l3a/swapi_l3a_dependencies.py
index cf6db7c5..b3d8023f 100644
--- a/imap_l3_processing/swapi/l3a/swapi_l3a_dependencies.py
+++ b/imap_l3_processing/swapi/l3a/swapi_l3a_dependencies.py
@@ -1,6 +1,5 @@
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional
 
 from imap_data_access import download
 from imap_data_access.processing_input import ProcessingInputCollection
@@ -8,15 +7,15 @@
 
 from imap_l3_processing.models import MagData
 from imap_l3_processing.swapi.descriptors import (
-    SWAPI_L2_DESCRIPTOR,
+    AZIMUTHAL_TRANSMISSION_DESCRIPTOR,
+    CENTRAL_EFFECTIVE_AREA_DESCRIPTOR,
     DENSITY_OF_NEUTRAL_HELIUM_DESCRIPTOR,
     EFFICIENCY_LOOKUP_TABLE_DESCRIPTOR,
-    HYDROGEN_INFLOW_VECTOR_DESCRIPTOR,
     HELIUM_INFLOW_VECTOR_DESCRIPTOR,
-    AZIMUTHAL_TRANSMISSION_DESCRIPTOR,
-    CENTRAL_EFFECTIVE_AREA_DESCRIPTOR,
-    PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR,
+    HYDROGEN_INFLOW_VECTOR_DESCRIPTOR,
     MAG_RTN_DESCRIPTOR,
+    PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR,
+    SWAPI_L2_DESCRIPTOR,
 )
 from imap_l3_processing.swapi.l3a.models import SwapiL2Data
 from imap_l3_processing.swapi.l3a.science.pickup_ion.density_of_neutral_helium_lookup_table import (
@@ -24,11 +23,11 @@
 )
 from imap_l3_processing.swapi.l3a.science.pickup_ion.inflow_vector import InflowVector
 from imap_l3_processing.swapi.l3a.utils import read_l2_swapi_data, read_mag_rtn_data
-from imap_l3_processing.utils import select_mag_path
 from imap_l3_processing.swapi.response.efficiency_calibration_table import (
     EfficiencyCalibrationTable,
 )
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
+from imap_l3_processing.utils import select_mag_path
 
 
 @dataclass
@@ -39,7 +38,7 @@ class SwapiL3ADependencies:
     hydrogen_inflow_vector: InflowVector
     helium_inflow_vector: InflowVector
     swapi_response: SwapiResponse
-    mag_data: Optional[MagData] = None
+    mag_data: MagData | None = None
     mag_is_preliminary: bool = False
 
     @classmethod
@@ -98,14 +97,12 @@ def from_file_paths(
         azimuthal_transmission_path: Path,
         central_effective_area_path: Path,
         passband_fit_coefficients_path: Path,
-        mag_path: Optional[Path] = None,
+        mag_path: Path | None = None,
         mag_is_preliminary: bool = False,
     ):
         return cls(
             data=read_l2_swapi_data(CDF(str(science_dependency_path))),
-            efficiency_calibration_table=EfficiencyCalibrationTable(
-                efficiency_calibration_path
-            ),
+            efficiency_calibration_table=EfficiencyCalibrationTable(efficiency_calibration_path),
             density_of_neutral_helium_calibration_table=DensityOfNeutralHeliumLookupTable.from_file(
                 neutral_helium_path
             ),
diff --git a/imap_l3_processing/swapi/l3a/utils.py b/imap_l3_processing/swapi/l3a/utils.py
index 29d2909b..dbf87582 100644
--- a/imap_l3_processing/swapi/l3a/utils.py
+++ b/imap_l3_processing/swapi/l3a/utils.py
@@ -1,10 +1,17 @@
 import math
+from collections.abc import Iterable
 from datetime import datetime
-from typing import Iterable
 
 import numba
 import numpy as np
 import scipy.optimize
+from imap_processing.spice.geometry import (
+    SpiceBody,
+    SpiceFrame,
+    get_rotation_matrix,
+    imap_state,
+)
+from imap_processing.spice.time import ttj2000ns_to_et
 from numpy import ndarray
 from numpy.typing import ArrayLike
 from spacepy import pycdf
@@ -31,14 +38,6 @@
 )
 from imap_l3_processing.swapi.l3a.models import SwapiL2Data
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
-from imap_processing.spice.geometry import (
-    SpiceBody,
-    SpiceFrame,
-    get_rotation_matrix,
-    imap_state,
-)
-from imap_processing.spice.time import ttj2000ns_to_et
-
 from imap_l3_processing.swapi.response.deadtime import deadtime_factor
 
 
@@ -53,13 +52,7 @@ def calculate_sw_speed(particle_mass, particle_charge, energy):
 
 def esa_voltage_to_proton_speed(esa_voltage: ArrayLike) -> np.ndarray:
     return (
-        np.sqrt(
-            2
-            * SWAPI_K_FACTOR
-            * PROTON_CHARGE_COULOMBS
-            * np.abs(esa_voltage)
-            / PROTON_MASS_KG
-        )
+        np.sqrt(2 * SWAPI_K_FACTOR * PROTON_CHARGE_COULOMBS * np.abs(esa_voltage) / PROTON_MASS_KG)
         / METERS_PER_KILOMETER
     )
 
@@ -112,9 +105,7 @@ def get_swapi_geometry(measurement_time: ndarray) -> ndarray:
 def get_spacecraft_velocity_rtn(epoch_tt2000_ns: float) -> ndarray:
     et = float(ttj2000ns_to_et(epoch_tt2000_ns))
     state_eclipj2000 = imap_state(et, SpiceFrame.ECLIPJ2000)
-    rtn_from_eclipj2000 = get_rotation_matrix(
-        et, SpiceFrame.ECLIPJ2000, SpiceFrame.IMAP_RTN
-    )
+    rtn_from_eclipj2000 = get_rotation_matrix(et, SpiceFrame.ECLIPJ2000, SpiceFrame.IMAP_RTN)
     return np.einsum("ij,j->i", rtn_from_eclipj2000, state_eclipj2000[3:])
 
 
@@ -181,9 +172,7 @@ def velocity_components_to_angles_in_instrument_frame(vx: float, vy: float, vz:
 
 
 @numba.njit
-def velocity_to_angles_in_instrument_frame(
-    sw_params: SolarWindParams, rotation_xyz_to_rtn
-):
+def velocity_to_angles_in_instrument_frame(sw_params: SolarWindParams, rotation_xyz_to_rtn):
     """SolarWindParams bulk flow velocity → (azimuth_deg, elevation_deg) look
     angles in the SWAPI instrument frame.
 
@@ -193,9 +182,7 @@ def velocity_to_angles_in_instrument_frame(
     flow-vs-look sign convention.
     """
     v_xyz = rotation_xyz_to_rtn.T @ sw_params.velocity_rtn
-    return velocity_components_to_angles_in_instrument_frame(
-        v_xyz[0], v_xyz[1], v_xyz[2]
-    )
+    return velocity_components_to_angles_in_instrument_frame(v_xyz[0], v_xyz[1], v_xyz[2])
 
 
 def compute_direction_of_mean_magnetic_field_over_chunk(
diff --git a/imap_l3_processing/swapi/l3b/models.py b/imap_l3_processing/swapi/l3b/models.py
index 26e7c34f..55c970b1 100644
--- a/imap_l3_processing/swapi/l3b/models.py
+++ b/imap_l3_processing/swapi/l3b/models.py
@@ -13,16 +13,12 @@
 )
 
 SOLAR_WIND_ENERGY_CDF_VAR_NAME = "combined_energy"
-SOLAR_WIND_COMBINED_ENERGY_DELTA_MINUS_CDF_VAR_NAME = (
-    "combined_energy_stat_uncert_minus"
-)
+SOLAR_WIND_COMBINED_ENERGY_DELTA_MINUS_CDF_VAR_NAME = "combined_energy_stat_uncert_minus"
 SOLAR_WIND_COMBINED_ENERGY_DELTA_PLUS_CDF_VAR_NAME = "combined_energy_stat_uncert_plus"
 SOLAR_WIND_ENERGY_LABEL_CDF_VAR_NAME = "combined_energy_label"
 
 COMBINED_SOLAR_WIND_DIFFERENTIAL_FLUX_CDF_VAR_NAME = "combined_differential_flux"
-COMBINED_SOLAR_WIND_DIFFERENTIAL_FLUX_DELTA_CDF_VAR_NAME = (
-    "combined_differential_flux_stat_uncert"
-)
+COMBINED_SOLAR_WIND_DIFFERENTIAL_FLUX_DELTA_CDF_VAR_NAME = "combined_differential_flux_stat_uncert"
 
 
 @dataclass
@@ -47,9 +43,7 @@ class SwapiL3BCombinedVDF(DataProduct):
 
     def to_data_product_variables(self) -> list[DataProductVariable]:
         energy_count = self.combined_energy.shape[-1]
-        energy_labels = numpy.char.mod(
-            "ESA %02d", np.arange(start=1, stop=energy_count + 1)
-        )
+        energy_labels = numpy.char.mod("ESA %02d", np.arange(start=1, stop=energy_count + 1))
         return [
             DataProductVariable(
                 EPOCH_CDF_VAR_NAME,
diff --git a/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_differential_flux.py b/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_differential_flux.py
index 9dbd469a..a014fed2 100644
--- a/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_differential_flux.py
+++ b/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_differential_flux.py
@@ -1,6 +1,6 @@
 from numpy import ndarray
 
-from imap_l3_processing.constants import METERS_PER_KILOMETER, CENTIMETERS_PER_METER
+from imap_l3_processing.constants import CENTIMETERS_PER_METER, METERS_PER_KILOMETER
 from imap_l3_processing.swapi.l3b.science.geometric_factor_calibration_table import (
     GeometricFactorCalibrationTable,
 )
diff --git a/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_vdf.py b/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_vdf.py
index f5e361e9..09b214de 100644
--- a/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_vdf.py
+++ b/imap_l3_processing/swapi/l3b/science/calculate_solar_wind_vdf.py
@@ -6,14 +6,14 @@
 from numpy import ndarray
 
 from imap_l3_processing.constants import (
-    PROTON_MASS_KG,
-    PROTON_CHARGE_COULOMBS,
     ALPHA_PARTICLE_CHARGE_COULOMBS,
     ALPHA_PARTICLE_MASS_KG,
+    CENTIMETERS_PER_METER,
     HE_PUI_PARTICLE_MASS_KG,
-    PUI_PARTICLE_CHARGE_COULOMBS,
     METERS_PER_KILOMETER,
-    CENTIMETERS_PER_METER,
+    PROTON_CHARGE_COULOMBS,
+    PROTON_MASS_KG,
+    PUI_PARTICLE_CHARGE_COULOMBS,
 )
 from imap_l3_processing.swapi.l3a.utils import calculate_sw_speed
 from imap_l3_processing.swapi.l3b.science.geometric_factor_calibration_table import (
diff --git a/imap_l3_processing/swapi/quality_flags.py b/imap_l3_processing/swapi/quality_flags.py
index 23dd0651..e299678f 100644
--- a/imap_l3_processing/swapi/quality_flags.py
+++ b/imap_l3_processing/swapi/quality_flags.py
@@ -1,4 +1,4 @@
-from imap_processing.quality_flags import FlagNameMixin, CommonFlags
+from imap_processing.quality_flags import CommonFlags, FlagNameMixin
 
 
 class SwapiL3Flags(FlagNameMixin):
diff --git a/imap_l3_processing/swapi/response/azimuthal_transmission.py b/imap_l3_processing/swapi/response/azimuthal_transmission.py
index 5baa39cb..50fea51b 100644
--- a/imap_l3_processing/swapi/response/azimuthal_transmission.py
+++ b/imap_l3_processing/swapi/response/azimuthal_transmission.py
@@ -5,7 +5,6 @@
 import numpy as np
 from numpy import ndarray
 
-
 SG_PLATEAU_AZIMUTH_MAX_DEG = 9.0
 SG_PLATEAU_TRANSMISSION = 1 / 1000
 
@@ -33,7 +32,7 @@ def interpolate_azimuthal_transmission(
         return SG_PLATEAU_TRANSMISSION
 
     i_float = abs_azimuth / grid.spacing
-    i_lower = int(math.floor(i_float))
+    i_lower = math.floor(i_float)
     i_upper = i_lower + 1
 
     n = len(grid.values)
diff --git a/imap_l3_processing/swapi/response/efficiency_calibration_table.py b/imap_l3_processing/swapi/response/efficiency_calibration_table.py
index 7d74dd09..f8155334 100644
--- a/imap_l3_processing/swapi/response/efficiency_calibration_table.py
+++ b/imap_l3_processing/swapi/response/efficiency_calibration_table.py
@@ -27,17 +27,11 @@ def __init__(self, path):
         )
 
     def relative_efficiency(self, time_as_tt2000: int, species: Species) -> float:
-        return self._get_entry_for(
-            time_as_tt2000, _EFFICIENCY_COLUMN_BY_SPECIES[species]
-        )
+        return self._get_entry_for(time_as_tt2000, _EFFICIENCY_COLUMN_BY_SPECIES[species])
 
     def _get_entry_for(self, time_as_tt2000, column: str) -> float:
         for d in reversed(self.data):
-            if d["time"] < np.datetime64(
-                pycdf.lib.tt2000_to_datetime(int(time_as_tt2000)), "ns"
-            ):
+            if d["time"] < np.datetime64(pycdf.lib.tt2000_to_datetime(int(time_as_tt2000)), "ns"):
                 return float(d[column])
 
-        raise ValueError(
-            f"No efficiency data for {pycdf.lib.tt2000_to_datetime(time_as_tt2000)}"
-        )
+        raise ValueError(f"No efficiency data for {pycdf.lib.tt2000_to_datetime(time_as_tt2000)}")
diff --git a/imap_l3_processing/swapi/response/passband_grid.py b/imap_l3_processing/swapi/response/passband_grid.py
index 96a54cc5..2ef3da3b 100644
--- a/imap_l3_processing/swapi/response/passband_grid.py
+++ b/imap_l3_processing/swapi/response/passband_grid.py
@@ -24,9 +24,7 @@ class PassbandGrid(NamedTuple):
 
 
 def build_passband_grid(values_df: pd.DataFrame) -> PassbandGrid:
-    grid_values = _build_passband_array(
-        values_df, _TARGET_ELEVATIONS, _TARGET_SPEED_RATIOS
-    )
+    grid_values = _build_passband_array(values_df, _TARGET_ELEVATIONS, _TARGET_SPEED_RATIOS)
     min_boundary, max_boundary = _passband_boundaries(grid_values, _TARGET_SPEED_RATIOS)
     elevation_range = _elevation_range(grid_values, _TARGET_ELEVATIONS)
 
@@ -68,8 +66,8 @@ def speed_ratio_range_at_elevation(grid, elevation: float):
         return upper_min, upper_max
     if upper_is_nan:
         return lower_min, lower_max
-    lo = lower_min if lower_min < upper_min else upper_min
-    hi = lower_max if lower_max > upper_max else upper_max
+    lo = min(upper_min, lower_min)
+    hi = max(upper_max, lower_max)
     return lo, hi
 
 
@@ -180,12 +178,8 @@ def _elevation_range(grid_values: NDArray, target_elevations: NDArray) -> tuple:
     row_max = grid_values.max(axis=1)
     above = np.flatnonzero(row_max >= cutoff)
 
-    lo = _interp_cutoff_crossing(
-        target_elevations, row_max, cutoff, above[0], above[0] - 1
-    )
-    hi = _interp_cutoff_crossing(
-        target_elevations, row_max, cutoff, above[-1], above[-1] + 1
-    )
+    lo = _interp_cutoff_crossing(target_elevations, row_max, cutoff, above[0], above[0] - 1)
+    hi = _interp_cutoff_crossing(target_elevations, row_max, cutoff, above[-1], above[-1] + 1)
     return (float(lo), float(hi))
 
 
diff --git a/imap_l3_processing/swapi/response/swapi_response.py b/imap_l3_processing/swapi/response/swapi_response.py
index 7d5a01d7..57e015cb 100644
--- a/imap_l3_processing/swapi/response/swapi_response.py
+++ b/imap_l3_processing/swapi/response/swapi_response.py
@@ -1,5 +1,6 @@
+from collections.abc import Callable
 from pathlib import Path
-from typing import Callable, NamedTuple
+from typing import NamedTuple
 
 import numpy as np
 import pandas as pd
@@ -10,6 +11,7 @@
     METERS_PER_KILOMETER,
     PROTON_CHARGE_OVER_MASS_C_PER_KG,
 )
+from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.response.azimuthal_transmission import (
     AzimuthalTransmissionGrid,
     validate_azimuthal_transmission_values,
@@ -21,7 +23,6 @@
     PassbandGrid,
     build_passband_grid,
 )
-from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.species import Species
 
 
@@ -108,9 +109,7 @@ def from_files(
     def _get_central_effective_area(self, esa_voltage: float) -> float:
         return float(self._central_effective_area_at_voltage(np.abs(esa_voltage)))
 
-    def _central_speed(
-        self, esa_voltage: float, mass_per_charge_m_p_per_e: float
-    ) -> float:
+    def _central_speed(self, esa_voltage: float, mass_per_charge_m_p_per_e: float) -> float:
         # formula: v_0 = sqrt(2 k* |V| (e/m_p) / mass_per_charge_m_p_per_e).
 
         return float(
@@ -128,7 +127,7 @@ def warm_cache(self, esa_voltages) -> None:
         for v in np.unique(np.asarray(esa_voltages, dtype=float).ravel()):
             key = self._cache_key(v)
             if np.isfinite(v) and key not in self._passband_grid_cache:
-                self._passband_grid_cache[key] = dict()
+                self._passband_grid_cache[key] = {}
                 for region in ("SG", "OA"):
                     passband = build_passband_grid(self._get_passband_values(v, region))
                     self._passband_grid_cache[key][region] = passband
@@ -139,9 +138,7 @@ def get_response_grid(
         esa_voltage: float,
         species: Species,
     ) -> ResponseGrid:
-        relative_efficiency = self._efficiency_table.relative_efficiency(
-            time_as_tt2000, species
-        )
+        relative_efficiency = self._efficiency_table.relative_efficiency(time_as_tt2000, species)
 
         cache_key = (
             self._cache_key(float(esa_voltage)),
@@ -164,9 +161,7 @@ def get_response_grid(
         response_grid = ResponseGrid(
             sg_passband=passband_pair["SG"],
             oa_passband=passband_pair["OA"],
-            central_speed=self._central_speed(
-                esa_voltage, species.mass_per_charge_m_p_per_e
-            ),
+            central_speed=self._central_speed(esa_voltage, species.mass_per_charge_m_p_per_e),
             central_effective_area=self._get_central_effective_area(esa_voltage)
             * relative_efficiency,
             azimuthal_transmission=self._azimuthal_transmission_grid,
diff --git a/imap_l3_processing/swapi/swapi_processor.py b/imap_l3_processing/swapi/swapi_processor.py
index 6f237ead..d7feb5a3 100644
--- a/imap_l3_processing/swapi/swapi_processor.py
+++ b/imap_l3_processing/swapi/swapi_processor.py
@@ -8,6 +8,10 @@
 from imap_l3_processing.constants import FIVE_MINUTES_IN_NANOSECONDS
 from imap_l3_processing.models import InputMetadata
 from imap_l3_processing.processor import Processor
+from imap_l3_processing.swapi.constants import (
+    SWAPI_COARSE_SWEEP_BINS,
+    SWAPI_L2_K_FACTOR,
+)
 from imap_l3_processing.swapi.l3a.chunk_fits import (
     AlphaChunkFitter,
     ParallelChunkRunner,
@@ -15,13 +19,9 @@
     PuiChunkFitter,
 )
 from imap_l3_processing.swapi.l3a.models import (
-    SwapiL3ProtonSolarWindData,
     SwapiL3AlphaSolarWindData,
     SwapiL3PickupIonData,
-)
-from imap_l3_processing.swapi.constants import (
-    SWAPI_COARSE_SWEEP_BINS,
-    SWAPI_L2_K_FACTOR,
+    SwapiL3ProtonSolarWindData,
 )
 from imap_l3_processing.swapi.l3a.swapi_l3a_dependencies import SwapiL3ADependencies
 from imap_l3_processing.swapi.l3a.utils import (
@@ -33,10 +33,10 @@
     calculate_combined_solar_wind_differential_flux,
 )
 from imap_l3_processing.swapi.l3b.science.calculate_solar_wind_vdf import (
-    calculate_proton_solar_wind_vdf,
     calculate_alpha_solar_wind_vdf,
-    calculate_pui_solar_wind_vdf,
     calculate_delta_minus_plus,
+    calculate_proton_solar_wind_vdf,
+    calculate_pui_solar_wind_vdf,
 )
 from imap_l3_processing.swapi.l3b.swapi_l3b_dependencies import SwapiL3BDependencies
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
@@ -71,16 +71,12 @@ def _calculate_gse_velocities(result: dict[str, np.ndarray], species: str) -> No
 
 
 class SwapiProcessor(Processor):
-    def __init__(
-        self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata
-    ):
+    def __init__(self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata):
         super().__init__(dependencies, input_metadata)
 
     def process(self):
         if self.input_metadata.data_level == "l3a":
-            l3a_dependencies = SwapiL3ADependencies.fetch_dependencies(
-                self.dependencies
-            )
+            l3a_dependencies = SwapiL3ADependencies.fetch_dependencies(self.dependencies)
 
             if self.input_metadata.descriptor == "proton-sw":
                 data = self.process_l3a_proton(l3a_dependencies.data, l3a_dependencies)
@@ -89,16 +85,12 @@ def process(self):
             elif self.input_metadata.descriptor == "pui-he":
                 data = self.process_l3a_pui(l3a_dependencies.data, l3a_dependencies)
             else:
-                raise NotImplementedError(
-                    "unknown descriptor", self.input_metadata.descriptor
-                )
+                raise NotImplementedError("unknown descriptor", self.input_metadata.descriptor)
             data.parent_file_names = self.get_parent_file_names()
             cdf_path = save_data(data)
             return [cdf_path]
         elif self.input_metadata.data_level == "l3b":
-            l3b_dependencies = SwapiL3BDependencies.fetch_dependencies(
-                self.dependencies
-            )
+            l3b_dependencies = SwapiL3BDependencies.fetch_dependencies(self.dependencies)
             l3b_combined_vdf = self.process_l3b(l3b_dependencies.data, l3b_dependencies)
             l3b_combined_vdf.parent_file_names = self.get_parent_file_names()
             cdf_path = save_data(l3b_combined_vdf)
@@ -135,16 +127,12 @@ def process_l3a_alpha(self, data, dependencies) -> SwapiL3AlphaSolarWindData:
         _calculate_gse_velocities(result, "alpha")
 
         if dependencies.mag_is_preliminary:
-            result["quality_flags"] = result["quality_flags"] | int(
-                SwapiL3Flags.PRELIMINARY_MAG
-            )
+            result["quality_flags"] = result["quality_flags"] | int(SwapiL3Flags.PRELIMINARY_MAG)
 
         metadata = replace(self.input_metadata, descriptor="alpha-sw")
         return SwapiL3AlphaSolarWindData(metadata, **result)
 
-    def process_l3a_pui(
-        self, data, dependencies: SwapiL3ADependencies
-    ) -> SwapiL3PickupIonData:
+    def process_l3a_pui(self, data, dependencies: SwapiL3ADependencies) -> SwapiL3PickupIonData:
         dependencies.swapi_response.warm_cache(data.energy / SWAPI_L2_K_FACTOR)
         runner = ParallelChunkRunner(
             dependencies.swapi_response, dependencies.efficiency_calibration_table
@@ -182,21 +170,15 @@ def process_l3b(self, data, dependencies):
 
         for data_chunk in chunk_l2_data(data, 50):
             center_of_epoch = data_chunk.sci_start_time[0] + FIVE_MINUTES_IN_NANOSECONDS
-            instrument_efficiency = (
-                dependencies.efficiency_calibration_table.relative_efficiency(
-                    center_of_epoch, Species.PROTON
-                )
+            instrument_efficiency = dependencies.efficiency_calibration_table.relative_efficiency(
+                center_of_epoch, Species.PROTON
             )
             coincidence_count_rates_with_uncertainty = uarray(
                 data_chunk.coincidence_count_rate,
                 data_chunk.coincidence_count_rate_uncertainty,
             )
-            coarse_rates = coincidence_count_rates_with_uncertainty[
-                :, SWAPI_COARSE_SWEEP_BINS
-            ]
-            average_coincident_count_rates = np.sum(coarse_rates, axis=0) / len(
-                coarse_rates
-            )
+            coarse_rates = coincidence_count_rates_with_uncertainty[:, SWAPI_COARSE_SWEEP_BINS]
+            average_coincident_count_rates = np.sum(coarse_rates, axis=0) / len(coarse_rates)
             energies = np.mean(data_chunk.energy[:, SWAPI_COARSE_SWEEP_BINS], axis=0)
             proton_velocities, proton_probabilities = calculate_proton_solar_wind_vdf(
                 energies,
@@ -216,13 +198,11 @@ def process_l3b(self, data, dependencies):
                 instrument_efficiency,
                 dependencies.geometric_factor_calibration_table,
             )
-            combined_differential_flux = (
-                calculate_combined_solar_wind_differential_flux(
-                    energies,
-                    average_coincident_count_rates,
-                    instrument_efficiency,
-                    dependencies.geometric_factor_calibration_table,
-                )
+            combined_differential_flux = calculate_combined_solar_wind_differential_flux(
+                energies,
+                average_coincident_count_rates,
+                instrument_efficiency,
+                dependencies.geometric_factor_calibration_table,
             )
             epochs.append(center_of_epoch)
             cdf_proton_velocities.append(proton_velocities)
@@ -266,9 +246,7 @@ def process_l3b(self, data, dependencies):
             pui_sw_velocities_delta_minus=np.array(
                 [delta.delta_minus for delta in cdf_pui_deltas]
             ),
-            pui_sw_velocities_delta_plus=np.array(
-                [delta.delta_plus for delta in cdf_pui_deltas]
-            ),
+            pui_sw_velocities_delta_plus=np.array([delta.delta_plus for delta in cdf_pui_deltas]),
             pui_sw_combined_vdf=np.array(cdf_pui_probabilities),
             combined_energy=np.array(combined_energies),
             combined_energy_delta_minus=np.array(
diff --git a/imap_l3_processing/swe/l3/models.py b/imap_l3_processing/swe/l3/models.py
index f25102c4..5b44676e 100644
--- a/imap_l3_processing/swe/l3/models.py
+++ b/imap_l3_processing/swe/l3/models.py
@@ -24,12 +24,8 @@
 PHASE_SPACE_DENSITY_INWARD_CDF_VAR_NAME = "phase_space_density_inward"
 PHASE_SPACE_DENSITY_OUTWARD_CDF_VAR_NAME = "phase_space_density_outward"
 INTENSITY_BY_PITCH_ANGLE_CDF_VAR_NAME = "intensity_by_pitch_angle"
-INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME = (
-    "intensity_by_pitch_angle_and_gyrophase"
-)
-INTENSITY_UNCERTAINTY_BY_PITCH_ANGLE_CDF_VAR_NAME = (
-    "intensity_uncertainty_by_pitch_angle"
-)
+INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME = "intensity_by_pitch_angle_and_gyrophase"
+INTENSITY_UNCERTAINTY_BY_PITCH_ANGLE_CDF_VAR_NAME = "intensity_uncertainty_by_pitch_angle"
 INTENSITY_UNCERTAINTY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME = (
     "intensity_uncertainty_by_pitch_angle_and_gyrophase"
 )
@@ -60,67 +56,43 @@
 TOTAL_SPEED_INTEGRATED_CDF_VAR_NAME = "total_speed_integrated"
 CORE_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME = "core_velocity_vector_rtn_integrated"
 HALO_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME = "halo_velocity_vector_rtn_integrated"
-TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME = (
-    "total_velocity_vector_rtn_integrated"
-)
+TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME = "total_velocity_vector_rtn_integrated"
 CORE_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME = "core_heat_flux_magnitude_integrated"
 CORE_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME = "core_heat_flux_theta_integrated"
 CORE_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME = "core_heat_flux_phi_integrated"
 HALO_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME = "halo_heat_flux_magnitude_integrated"
 HALO_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME = "halo_heat_flux_theta_integrated"
 HALO_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME = "halo_heat_flux_phi_integrated"
-TOTAL_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME = (
-    "total_heat_flux_magnitude_integrated"
-)
+TOTAL_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME = "total_heat_flux_magnitude_integrated"
 TOTAL_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME = "total_heat_flux_theta_integrated"
 TOTAL_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME = "total_heat_flux_phi_integrated"
 CORE_T_PARALLEL_INTEGRATED_CDF_VAR_NAME = "core_t_parallel_integrated"
 CORE_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME = "core_t_perpendicular_integrated"
-CORE_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME = (
-    "core_t_ratio_perpendicular_integrated"
-)
+CORE_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME = "core_t_ratio_perpendicular_integrated"
 HALO_T_PARALLEL_INTEGRATED_CDF_VAR_NAME = "halo_t_parallel_integrated"
 HALO_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME = "halo_t_perpendicular_integrated"
-HALO_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME = (
-    "halo_t_ratio_perpendicular_integrated"
-)
+HALO_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME = "halo_t_ratio_perpendicular_integrated"
 TOTAL_T_PARALLEL_INTEGRATED_CDF_VAR_NAME = "total_t_parallel_integrated"
 TOTAL_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME = "total_t_perpendicular_integrated"
-TOTAL_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME = (
-    "total_t_ratio_perpendicular_integrated"
-)
-CORE_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME = (
-    "core_temperature_theta_rtn_integrated"
-)
+TOTAL_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME = "total_t_ratio_perpendicular_integrated"
+CORE_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME = "core_temperature_theta_rtn_integrated"
 CORE_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME = "core_temperature_phi_rtn_integrated"
-HALO_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME = (
-    "halo_temperature_theta_rtn_integrated"
-)
+HALO_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME = "halo_temperature_theta_rtn_integrated"
 HALO_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME = "halo_temperature_phi_rtn_integrated"
-TOTAL_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME = (
-    "total_temperature_theta_rtn_integrated"
-)
-TOTAL_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME = (
-    "total_temperature_phi_rtn_integrated"
-)
+TOTAL_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME = "total_temperature_theta_rtn_integrated"
+TOTAL_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME = "total_temperature_phi_rtn_integrated"
 CORE_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME = "core_temperature_parallel_to_mag"
-CORE_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = (
-    "core_temperature_perpendicular_to_mag"
-)
+CORE_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = "core_temperature_perpendicular_to_mag"
 CORE_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = (
     "core_temperature_ratio_perpendicular_to_mag"
 )
 HALO_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME = "halo_temperature_parallel_to_mag"
-HALO_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = (
-    "halo_temperature_perpendicular_to_mag"
-)
+HALO_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = "halo_temperature_perpendicular_to_mag"
 HALO_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = (
     "halo_temperature_ratio_perpendicular_to_mag"
 )
 TOTAL_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME = "total_temperature_parallel_to_mag"
-TOTAL_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = (
-    "total_temperature_perpendicular_to_mag"
-)
+TOTAL_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = "total_temperature_perpendicular_to_mag"
 TOTAL_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME = (
     "total_temperature_ratio_perpendicular_to_mag"
 )
@@ -138,9 +110,7 @@
 HALO_VELOCITY_VECTOR_RTN_FIT_LABEL = "halo_velocity_vector_rtn_fit_label"
 CORE_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL = "core_velocity_vector_rtn_integrated_label"
 HALO_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL = "halo_velocity_vector_rtn_integrated_label"
-TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL = (
-    "total_velocity_vector_rtn_integrated_label"
-)
+TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL = "total_velocity_vector_rtn_integrated_label"
 CORE_TEMPERATURE_TENSOR_INTEGRATED_LABEL = "core_temperature_tensor_integrated_label"
 HALO_TEMPERATURE_TENSOR_INTEGRATED_LABEL = "halo_temperature_tensor_integrated_label"
 TOTAL_TEMPERATURE_TENSOR_INTEGRATED_LABEL = "total_temperature_tensor_integrated_label"
@@ -282,20 +252,12 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             DataProductVariable(EPOCH_CDF_VAR_NAME, value=self.epoch),
             DataProductVariable(EPOCH_DELTA_CDF_VAR_NAME, value=self.epoch_delta),
             DataProductVariable(ENERGY_CDF_VAR_NAME, value=self.energy),
-            DataProductVariable(
-                ENERGY_DELTA_PLUS_CDF_VAR_NAME, value=self.energy_delta_plus
-            ),
-            DataProductVariable(
-                ENERGY_DELTA_MINUS_CDF_VAR_NAME, value=self.energy_delta_minus
-            ),
+            DataProductVariable(ENERGY_DELTA_PLUS_CDF_VAR_NAME, value=self.energy_delta_plus),
+            DataProductVariable(ENERGY_DELTA_MINUS_CDF_VAR_NAME, value=self.energy_delta_minus),
             DataProductVariable(PITCH_ANGLE_CDF_VAR_NAME, value=self.pitch_angle),
-            DataProductVariable(
-                PITCH_ANGLE_DELTA_CDF_VAR_NAME, value=self.pitch_angle_delta
-            ),
+            DataProductVariable(PITCH_ANGLE_DELTA_CDF_VAR_NAME, value=self.pitch_angle_delta),
             DataProductVariable(GYROPHASE_BINS_CDF_VAR_NAME, value=self.gyrophase_bins),
-            DataProductVariable(
-                GYROPHASE_DELTA_CDF_VAR_NAME, value=self.gyrophase_delta
-            ),
+            DataProductVariable(GYROPHASE_DELTA_CDF_VAR_NAME, value=self.gyrophase_delta),
             DataProductVariable(
                 PHASE_SPACE_DENSITY_BY_PITCH_ANGLE_CDF_VAR_NAME,
                 value=self.phase_space_density_by_pitch_angle,
@@ -341,12 +303,8 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
                 CORE_FIT_NUM_POINTS_CDF_VAR_NAME,
                 value=self.moment_data.core_fit_num_points,
             ),
-            DataProductVariable(
-                CHISQ_C_CDF_VAR_NAME, value=self.moment_data.core_chisq
-            ),
-            DataProductVariable(
-                CHISQ_H_CDF_VAR_NAME, value=self.moment_data.halo_chisq
-            ),
+            DataProductVariable(CHISQ_C_CDF_VAR_NAME, value=self.moment_data.core_chisq),
+            DataProductVariable(CHISQ_H_CDF_VAR_NAME, value=self.moment_data.halo_chisq),
             DataProductVariable(
                 CORE_DENSITY_FIT_CDF_VAR_NAME, value=self.moment_data.core_density_fit
             ),
@@ -581,12 +539,8 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             ),
             DataProductVariable(SWE_FLAGS_VAR_NAME, value=self.swe_flags),
             DataProductVariable("raw_1d_psd_rebinned", value=self.raw_1d_psd_rebinned),
-            DataProductVariable(
-                "raw_psd_by_theta_rebinned", value=self.raw_psd_by_theta_rebinned
-            ),
-            DataProductVariable(
-                "raw_psd_by_phi_rebinned", value=self.raw_psd_by_phi_rebinned
-            ),
+            DataProductVariable("raw_psd_by_theta_rebinned", value=self.raw_psd_by_theta_rebinned),
+            DataProductVariable("raw_psd_by_phi_rebinned", value=self.raw_psd_by_phi_rebinned),
             DataProductVariable("inst_az", value=self.inst_az),
             DataProductVariable("inst_el", value=self.inst_el),
             DataProductVariable(
diff --git a/imap_l3_processing/swe/l3/science/moment_calculations.py b/imap_l3_processing/swe/l3/science/moment_calculations.py
index 4df23fcb..f1f3b464 100644
--- a/imap_l3_processing/swe/l3/science/moment_calculations.py
+++ b/imap_l3_processing/swe/l3/science/moment_calculations.py
@@ -2,18 +2,17 @@
 import math
 from dataclasses import dataclass
 from datetime import datetime
-from typing import Optional, Union, Tuple
 
 import numpy as np
 import spiceypy
 
 from imap_l3_processing.constants import (
-    ELECTRON_MASS_KG,
     BOLTZMANN_CONSTANT_JOULES_PER_KELVIN,
-    METERS_PER_KILOMETER,
     CENTIMETERS_PER_METER,
-    PROTON_CHARGE_COULOMBS,
+    ELECTRON_MASS_KG,
     GRAMS_PER_KILOGRAM,
+    METERS_PER_KILOMETER,
+    PROTON_CHARGE_COULOMBS,
 )
 from imap_l3_processing.pitch_angles import calculate_unit_vector
 from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
@@ -100,8 +99,8 @@ def core_fit_moments_retrying_on_failure(
     weights: np.ndarray,
     energy_start: int,
     energy_end: int,
-    density_history: Union[np.ndarray, list[float]],
-) -> Optional[MomentFitResults]:
+    density_history: np.ndarray | list[float],
+) -> MomentFitResults | None:
     return _fit_moments_retrying_on_failure(
         corrected_energy_bins,
         velocity_vectors,
@@ -121,10 +120,10 @@ def halo_fit_moments_retrying_on_failure(
     weights: np.ndarray,
     energy_start: int,
     energy_end: int,
-    density_history: Union[np.ndarray, list[float]],
-    spacecraft_potential: Union[np.float64, float],
-    core_halo_breakpoint: Union[np.float64, float],
-) -> Optional[MomentFitResults]:
+    density_history: np.ndarray | list[float],
+    spacecraft_potential: np.float64 | float,
+    core_halo_breakpoint: np.float64 | float,
+) -> MomentFitResults | None:
     return _fit_moments_retrying_on_failure(
         corrected_energy_bins,
         velocity_vectors,
@@ -147,10 +146,10 @@ def _fit_moments_retrying_on_failure(
     weights: np.ndarray,
     energy_start: int,
     energy_end: int,
-    density_history: Union[np.ndarray, list[float]],
+    density_history: np.ndarray | list[float],
     history_scalar: float,
-    halo_correction_parameters: Optional[HaloCorrectionParameters] = None,
-) -> Optional[MomentFitResults]:
+    halo_correction_parameters: HaloCorrectionParameters | None = None,
+) -> MomentFitResults | None:
     filtered_velocity_vectors, filtered_weights, filtered_yreg = (
         filter_and_flatten_regress_parameters(
             corrected_energy_bins,
@@ -162,9 +161,7 @@ def _fit_moments_retrying_on_failure(
         )
     )
 
-    fit_function, chi_squared = regress(
-        filtered_velocity_vectors, filtered_weights, filtered_yreg
-    )
+    fit_function, chi_squared = regress(filtered_velocity_vectors, filtered_weights, filtered_yreg)
     moment = calculate_fit_temperature_density_velocity(fit_function)
     average_density = np.average(density_history) * history_scalar
 
@@ -202,9 +199,7 @@ def _fit_moments_retrying_on_failure(
         )
 
 
-def regress(
-    velocity_vectors: np.ndarray, weight: np.ndarray, yreg: np.ndarray
-) -> np.ndarray:
+def regress(velocity_vectors: np.ndarray, weight: np.ndarray, yreg: np.ndarray) -> np.ndarray:
     fit_function = np.zeros((len(velocity_vectors), 9))
 
     velocity_xs = velocity_vectors[:, 0]
@@ -317,10 +312,7 @@ def calculate_fit_temperature_density_velocity(parameters: np.ndarray[float]):
             parameters[0] - parameters[3] * parameters[4] / parameters[5]
         )
         moments.t_parallel = 1.0 / (
-            parameters[0]
-            + parameters[1]
-            + parameters[2]
-            - 2.0 / moments.t_perpendicular
+            parameters[0] + parameters[1] + parameters[2] - 2.0 / moments.t_perpendicular
         )
 
     c11 = parameters[1] * parameters[2] - parameters[5] * parameters[5]
@@ -437,24 +429,20 @@ def get_dps_to_rtn_rotation_matrix(epoch: datetime) -> np.ndarray:
     return spiceypy.pxform("IMAP_DPS", "IMAP_RTN", spiceypy.datetime2et(epoch))
 
 
-def apply_rotation_matrix(
-    rotation_matrix: np.ndarray, vector: np.ndarray
-) -> np.ndarray:
+def apply_rotation_matrix(rotation_matrix: np.ndarray, vector: np.ndarray) -> np.ndarray:
     return rotation_matrix @ vector
 
 
 def rotate_rtn_vectors_to_dps(
     epochs: np.ndarray, vectors_rtn: np.ndarray
-) -> Tuple[np.ndarray, np.ndarray]:
+) -> tuple[np.ndarray, np.ndarray]:
     result = np.full_like(vectors_rtn, np.nan, dtype=float)
     predicted_ephemeris_flags = np.zeros_like(epochs, dtype=bool)
     for i, epoch in enumerate(epochs):
         tracker = PredictedEphemerisTracker()
         try:
             et_time = spiceypy.datetime2et(epoch)
-            rotation_matrix = tracker.run(
-                spiceypy.pxform, "IMAP_RTN", "IMAP_DPS", et_time
-            )
+            rotation_matrix = tracker.run(spiceypy.pxform, "IMAP_RTN", "IMAP_DPS", et_time)
         except spiceypy.SpiceyError as e:
             logger.info(f"Failed to rotate RTN→DPS at epoch {epoch}: {e}")
             continue
@@ -515,25 +503,19 @@ def compute_density_scale(
     escalep = math.erfc(scalep) if scalep < 9 else 0
     escalem = math.erfc(scalem) if scalem < 9 else 0
 
-    dscalep = density_multiplier / (
-        scalep * np.exp(-scalep2) + density_multiplier * escalep
-    )
-    dscalem = density_multiplier / (
-        scalem * np.exp(-scalem2) + density_multiplier * escalem
-    )
+    dscalep = density_multiplier / (scalep * np.exp(-scalep2) + density_multiplier * escalep)
+    dscalem = density_multiplier / (scalem * np.exp(-scalem2) + density_multiplier * escalem)
 
     return 0.5 * (dscalep + dscalem)
 
 
 def halotrunc(
     moments: Moments, core_halo_breakpoint: float, spacecraft_potential: float
-) -> Optional[np.float64]:
+) -> np.float64 | None:
     htmax = moments.t_parallel
     htmin = moments.t_perpendicular
 
-    speed = math.sqrt(
-        moments.velocity_x**2 + moments.velocity_y**2 + moments.velocity_z**2
-    )
+    speed = math.sqrt(moments.velocity_x**2 + moments.velocity_y**2 + moments.velocity_z**2)
 
     halod = moments.density
 
@@ -545,9 +527,7 @@ def halotrunc(
     if htmax <= 1e4 or htmin <= 1e4:
         dscale = 1
     elif core_halo_breakpoint - spacecraft_potential > 5 and temp < 1.0e7:
-        dscale = compute_density_scale(
-            core_halo_breakpoint - spacecraft_potential, speed, temp
-        )
+        dscale = compute_density_scale(core_halo_breakpoint - spacecraft_potential, speed, temp)
     else:
         dscale = 1
 
@@ -568,14 +548,14 @@ def integrate(
     spacecraft_potential: float,
     cdelnv: np.ndarray,
     cdelt: np.ndarray,
-) -> Optional[IntegrateOutputs]:
+) -> IntegrateOutputs | None:
     sumn = 0
     sumvx = 0
     sumvy = 0
     sumvz = 0
     base = 1000
     delphi = np.full(7, 2 * np.pi / 30)
-    delv = np.empty((len(energy)))
+    delv = np.empty(len(energy))
     fv_with_axis_order_energy_cem_spin = np.moveaxis(fv, 1, 2)
     for i in range(istart, iend + 1):
         if energy[i] > 0:
@@ -587,38 +567,20 @@ def integrate(
         ehigh = 1.175 * energy[i]
         if i < len(energy) - 1:
             ehigh = np.sqrt(
-                (energy[i + 1] + spacecraft_potential)
-                * (energy[i] + spacecraft_potential)
+                (energy[i + 1] + spacecraft_potential) * (energy[i] + spacecraft_potential)
             )
-        elow = np.sqrt(
-            (energy[i] + spacecraft_potential) * (energy[i - 1] + spacecraft_potential)
-        )
+        elow = np.sqrt((energy[i] + spacecraft_potential) * (energy[i - 1] + spacecraft_potential))
 
-        delv[i] = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * (
-            np.sqrt(ehigh) - np.sqrt(elow)
-        )
-        if elow < base:
-            base = elow
+        delv[i] = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * (np.sqrt(ehigh) - np.sqrt(elow))
+        base = min(base, elow)
         for j in range(7):
             for k in range(28):  # why 28 and not 30?
                 if energy[i] > 0:
                     delta = delv[i] * deltheta[j] * delphi[j]
                     fact = sintheta[j] * fv_with_axis_order_energy_cem_spin[i, j, k]
                     sumn += delta * v2mid * fact
-                    sumvx += (
-                        delta
-                        * v3mid
-                        * fact
-                        * sintheta[j]
-                        * np.cos(np.deg2rad(phi[i, k]))
-                    )
-                    sumvy += (
-                        delta
-                        * v3mid
-                        * fact
-                        * sintheta[j]
-                        * np.sin(np.deg2rad(phi[i, k]))
-                    )
+                    sumvx += delta * v3mid * fact * sintheta[j] * np.cos(np.deg2rad(phi[i, k]))
+                    sumvy += delta * v3mid * fact * sintheta[j] * np.sin(np.deg2rad(phi[i, k]))
                     sumvz += delta * v3mid * fact * costheta[j]
 
     totden = sumn + cdelnv[0]
@@ -652,36 +614,26 @@ def integrate(
                 if energy[i] > 0:
                     angx = sintheta[j] * np.cos(np.deg2rad(phi[i, k]))
                     vx = (
-                        -ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR
-                        * np.sqrt(energy[i])
-                        * angx
+                        -ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(energy[i]) * angx
                         - CM_PER_KM * output_velocities[0]
                     )
 
                     angy = sintheta[j] * np.sin(np.deg2rad(phi[i, k]))
                     vy = (
-                        -ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR
-                        * np.sqrt(energy[i])
-                        * angy
+                        -ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(energy[i]) * angy
                         - CM_PER_KM * output_velocities[1]
                     )
 
                     angz = costheta[j]
                     vz = (
-                        -ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR
-                        * np.sqrt(energy[i])
-                        * angz
+                        -ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(energy[i]) * angz
                         - CM_PER_KM * output_velocities[2]
                     )
 
                     vmag2 = vx * vx + vy * vy + vz * vz
 
                     delta = delv[i] * deltheta[j] * delphi[j]
-                    fact = (
-                        v2mid
-                        * sintheta[j]
-                        * fv_with_axis_order_energy_cem_spin[i, j, k]
-                    )
+                    fact = v2mid * sintheta[j] * fv_with_axis_order_energy_cem_spin[i, j, k]
                     sumtxx += delta * fact * vx * vx
                     sumtxy += delta * fact * vx * vy
                     sumtxz += delta * fact * vx * vz
@@ -700,9 +652,7 @@ def integrate(
         + cdelt
     ) / totden
 
-    heat_flux = (
-        np.array([sumqx, sumqy, sumqz]) * 500 * ELECTRON_MASS_KG * GRAMS_PER_KILOGRAM
-    )
+    heat_flux = np.array([sumqx, sumqy, sumqz]) * 500 * ELECTRON_MASS_KG * GRAMS_PER_KILOGRAM
 
     return IntegrateOutputs(totden, output_velocities, temperature, heat_flux, base)
 
@@ -730,29 +680,25 @@ def scale_core_density(
     velocity_in_sc_frame = np.zeros((2, NUMBER_OF_DETECTORS))
     for j in range(NUMBER_OF_DETECTORS):
         ehigh = np.sqrt(
-            (energy[ifit + 1] + spacecraft_potential)
-            * (energy[ifit] + spacecraft_potential)
+            (energy[ifit + 1] + spacecraft_potential) * (energy[ifit] + spacecraft_potential)
         )
         elow = np.sqrt(
-            (energy[ifit] + spacecraft_potential)
-            * (energy[ifit - 1] + spacecraft_potential)
+            (energy[ifit] + spacecraft_potential) * (energy[ifit - 1] + spacecraft_potential)
         )
         delv[0, j] = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * (
             np.sqrt(ehigh) - np.sqrt(elow)
         )
-        velocity_in_sc_frame[0, j] = (
-            ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(energy[ifit])
+        velocity_in_sc_frame[0, j] = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(
+            energy[ifit]
         )
         base_energy = min(base_energy, elow)
     base_energy -= spacecraft_potential
     if base_energy > 0:
         number_of_energies = 2
-        velocity_in_sc_frame[1, :] = (
-            ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(0.5 * base_energy)
-        )
-        delv[1, :] = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(
-            base_energy
+        velocity_in_sc_frame[1, :] = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(
+            0.5 * base_energy
         )
+        delv[1, :] = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(base_energy)
 
     factor = (
         core_moment_fit.density
@@ -774,21 +720,15 @@ def scale_core_density(
     vz = -velocity_3_dim * cos_theta
 
     fun = -zmk * np.stack(
-        np.broadcast_arrays(
-            vx * vx, vy * vy, vz * vz, vx * vy, vx * vz, vy * vz, vx, vy, vz
-        ),
+        np.broadcast_arrays(vx * vx, vy * vy, vz * vz, vx * vy, vx * vz, vy * vz, vx, vy, vz),
         axis=-1,
     )
     exponent = -zmk * core_moment_fit.aoo + np.dot(fun, regress_outputs[:9])
     delt = delv[:, :, np.newaxis] * delta_theta * delta_phi
-    common_factor = (
-        np.square(velocity_3_dim) * delt * sin_theta * factor * np.exp(exponent)
-    )
+    common_factor = np.square(velocity_3_dim) * delt * sin_theta * factor * np.exp(exponent)
 
     def integrate(array):
-        return np.sum(
-            array[:number_of_energies, :NUMBER_OF_DETECTORS, :MAX_SPIN_SECTOR_INDEX]
-        )
+        return np.sum(array[:number_of_energies, :NUMBER_OF_DETECTORS, :MAX_SPIN_SECTOR_INDEX])
 
     sumint = integrate(common_factor)
     sumvx = integrate(vx * common_factor)
@@ -849,9 +789,7 @@ def scale_halo_density(
     hchbreak = core_halo_break - spacecraft_potential
     scval = abs(hchbreak - base_energy)
     min_energy = min(base_energy, hchbreak)
-    vsch = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(
-        min_energy + 0.5 * scval
-    )
+    vsch = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(min_energy + 0.5 * scval)
     deltav = ENERGY_EV_TO_SPEED_CM_PER_S_CONVERSION_FACTOR * np.sqrt(scval)
     factor = (
         halo_moment_fit.density
@@ -872,9 +810,7 @@ def scale_halo_density(
     vz = -vsch * cos_theta
 
     fun = -zmk * np.stack(
-        np.broadcast_arrays(
-            vx * vx, vy * vy, vz * vz, vx * vy, vx * vz, vy * vz, vx, vy, vz
-        ),
+        np.broadcast_arrays(vx * vx, vy * vy, vz * vz, vx * vy, vx * vz, vy * vz, vx, vy, vz),
         axis=-1,
     )
     exponent = np.dot(fun, regress_outputs[:9])
@@ -917,10 +853,7 @@ def integrate(array):
     corrected_halo_temp = halo_temp.copy()
     corrected_halo_temp *= halo_density / corrected_density
     corrected_halo_temp += (
-        delta_temperature
-        * 1e-4
-        * ELECTRON_MASS_OVER_BOLTZMANN_IN_CGS_UNITS
-        / corrected_density
+        delta_temperature * 1e-4 * ELECTRON_MASS_OVER_BOLTZMANN_IN_CGS_UNITS / corrected_density
     )
 
     return ScaleDensityOutput(
@@ -938,16 +871,10 @@ def calculate_primary_eigenvector(
     symmetric_temperature_tensor = np.zeros(shape=(3, 3))
 
     symmetric_temperature_tensor[0][0] = temperature_tensor[0]
-    symmetric_temperature_tensor[0][1] = symmetric_temperature_tensor[1][0] = (
-        temperature_tensor[1]
-    )
+    symmetric_temperature_tensor[0][1] = symmetric_temperature_tensor[1][0] = temperature_tensor[1]
     symmetric_temperature_tensor[1][1] = temperature_tensor[2]
-    symmetric_temperature_tensor[0][2] = symmetric_temperature_tensor[2][0] = (
-        temperature_tensor[3]
-    )
-    symmetric_temperature_tensor[1][2] = symmetric_temperature_tensor[2][1] = (
-        temperature_tensor[4]
-    )
+    symmetric_temperature_tensor[0][2] = symmetric_temperature_tensor[2][0] = temperature_tensor[3]
+    symmetric_temperature_tensor[1][2] = symmetric_temperature_tensor[2][1] = temperature_tensor[4]
     symmetric_temperature_tensor[2][2] = temperature_tensor[5]
 
     nan_array = np.full(3, np.nan)
@@ -956,11 +883,7 @@ def calculate_primary_eigenvector(
     except np.linalg.LinAlgError:
         return nan_array, nan_array
 
-    if (
-        np.any(eigen_values < 0)
-        or np.all(eigen_values == 0)
-        or np.any(np.isnan(eigen_values))
-    ):
+    if np.any(eigen_values < 0) or np.all(eigen_values == 0) or np.any(np.isnan(eigen_values)):
         return nan_array, nan_array
 
     eigen_values_mean = np.mean(eigen_values)
@@ -978,16 +901,12 @@ def calculate_primary_eigenvector(
     other_evals = [v for i, v in enumerate(eigen_values) if i != ipar]
     max_eval = max(other_evals)
     min_eval = min(other_evals)
-    perpendicular_temperature = TEMPERATURE_SCALING_FACTOR * np.sqrt(
-        min_eval * max_eval
-    )
+    perpendicular_temperature = TEMPERATURE_SCALING_FACTOR * np.sqrt(min_eval * max_eval)
     if min_eval == 0:
         gyro = 1
     else:
         gyro = max(other_evals) / min_eval
-    return primary_evec, np.array(
-        [parallel_temperature, perpendicular_temperature, gyro]
-    )
+    return primary_evec, np.array([parallel_temperature, perpendicular_temperature, gyro])
 
 
 def rotation_matrix_builder(mag_vector: np.ndarray) -> np.ndarray(shape=(3, 3)):
@@ -1006,16 +925,10 @@ def rotate_temperature_tensor_to_mag(
     symmetric_temperature_tensor = np.zeros(shape=(3, 3))
 
     symmetric_temperature_tensor[0][0] = temperature_tensor[0]
-    symmetric_temperature_tensor[0][1] = symmetric_temperature_tensor[1][0] = (
-        temperature_tensor[1]
-    )
+    symmetric_temperature_tensor[0][1] = symmetric_temperature_tensor[1][0] = temperature_tensor[1]
     symmetric_temperature_tensor[1][1] = temperature_tensor[2]
-    symmetric_temperature_tensor[0][2] = symmetric_temperature_tensor[2][0] = (
-        temperature_tensor[3]
-    )
-    symmetric_temperature_tensor[1][2] = symmetric_temperature_tensor[2][1] = (
-        temperature_tensor[4]
-    )
+    symmetric_temperature_tensor[0][2] = symmetric_temperature_tensor[2][0] = temperature_tensor[3]
+    symmetric_temperature_tensor[1][2] = symmetric_temperature_tensor[2][1] = temperature_tensor[4]
     symmetric_temperature_tensor[2][2] = temperature_tensor[5]
 
     rotation_matrix = rotation_matrix_builder(mag_vector)
diff --git a/imap_l3_processing/swe/l3/science/pitch_calculations.py b/imap_l3_processing/swe/l3/science/pitch_calculations.py
index a83e347b..50aad518 100644
--- a/imap_l3_processing/swe/l3/science/pitch_calculations.py
+++ b/imap_l3_processing/swe/l3/science/pitch_calculations.py
@@ -7,13 +7,13 @@
 
 from imap_l3_processing.constants import (
     ELECTRON_MASS_KG,
-    PROTON_CHARGE_COULOMBS,
     METERS_PER_KILOMETER,
+    PROTON_CHARGE_COULOMBS,
 )
 from imap_l3_processing.pitch_angles import (
+    calculate_gyrophase,
     calculate_pitch_angle,
     calculate_unit_vector,
-    calculate_gyrophase,
 )
 from imap_l3_processing.swe.l3.models import SweConfiguration
 from imap_l3_processing.swe.quality_flags import SweL3Flags
@@ -62,21 +62,23 @@ def line_model(params, x):
         np.concatenate([[log_psd[2]], log_psd]),
         s=0.25,
     )
-    spline_energies = np.geomspace(
-        energies.min() * np.exp(-ewidth), energies.max(), 100
-    )
+    spline_energies = np.geomspace(energies.min() * np.exp(-ewidth), energies.max(), 100)
     spline_derivative = spline.derivative(2)
     curvature = spline_derivative(np.log(spline_energies))
+
+    # Defaults if the spline peak finder did not work
+    sc_pot = np.nan
+    ch_break = np.nan
+    BACKUP_SPLINE_UNRESOLVED = SweL3Flags.BACKUP_SPLINE_UNRESOLVED
     try:
         peaks = scipy.signal.find_peaks(curvature)[0]
-        sc_pot = spline_energies[peaks[0]]
-        ch_break = spline_energies[peaks[1]]
-        BACKUP_SPLINE_UNRESOLVED = SweL3Flags.NONE
-    except Exception:
-        # Spline peak finder did not work
-        BACKUP_SPLINE_UNRESOLVED = SweL3Flags.BACKUP_SPLINE_UNRESOLVED
-        sc_pot = np.nan
-        ch_break = np.nan
+    except (TypeError, ValueError):
+        pass
+    else:
+        if len(peaks) >= 2:
+            sc_pot = spline_energies[peaks[0]]
+            ch_break = spline_energies[peaks[1]]
+            BACKUP_SPLINE_UNRESOLVED = SweL3Flags.NONE
 
     def piece_wise_model_mec(x, b0, b1, b2, b3):
         """
@@ -97,8 +99,7 @@ def refine_breakpoint_value(energy, psd, breakpoint_value, num_points):
         # Find Nearest energy bin to breakpoint_value
         nearest_energy_idx = np.argmin(np.abs(energy - breakpoint_value))
         if (
-            np.abs(breakpoint_value - energy[nearest_energy_idx])
-            / energy[nearest_energy_idx]
+            np.abs(breakpoint_value - energy[nearest_energy_idx]) / energy[nearest_energy_idx]
             <= 0.075
         ):
             # Breakpoint_value was within FWHM of nearest energy bin
@@ -137,9 +138,9 @@ def refine_breakpoint_value(energy, psd, breakpoint_value, num_points):
     if FALLBACK_POTENTIAL_ESTIMATE == SweL3Flags.NONE:
         try:
             initial_guess = [log_psd[0], 1, 7, 1]
-            z, cov = scipy.optimize.curve_fit(
+            z = scipy.optimize.curve_fit(
                 fitting_model, np.exp(log_energy_sc), log_psd_sc, p0=initial_guess
-            )
+            )[0]
             # Make sure the fit converged
             if (
                 (z[0] == initial_guess[0])
@@ -155,48 +156,44 @@ def refine_breakpoint_value(energy, psd, breakpoint_value, num_points):
                 # Fit worked
                 # Check whether breakpoint has two points to left and right
                 # If so, then find intersection of linear fits to each side
-                sc_pot_output = refine_breakpoint_value(
-                    np.exp(log_energy_sc), log_psd_sc, z[2], 2
-                )
+                sc_pot_output = refine_breakpoint_value(np.exp(log_energy_sc), log_psd_sc, z[2], 2)
                 # spline not used
                 BACKUP_SPLINE_UNRESOLVED = SweL3Flags.NONE
-        except Exception:
+        except (TypeError, ValueError):
             # Fall back on Spline method
             # Fit did not converge
             BACKUP_SPLINE_UNRESOLVED = SweL3Flags.BACKUP_SPLINE_UNRESOLVED
             sc_pot_output = sc_pot
     else:
         sc_pot_output = return_value
+
+    # Default to fallback on Spline method
+    BREAKPOINT_FIT_UNCONVERGED = SweL3Flags.BREAKPOINT_FIT_UNCONVERGED
+    ch_break_output = ch_break
     # Try Core-Halo Breakpoint Fit
-    BREAKPOINT_FIT_UNCONVERGED = SweL3Flags.NONE
-    try:
-        initial_guess = [log_psd_ch[0], 1, 65, 1]
-        z, cov = scipy.optimize.curve_fit(
-            fitting_model, np.exp(log_energy_ch), log_psd_ch, p0=initial_guess
-        )
-        # Make sure the fit converged
-        if (
-            (z[0] == initial_guess[0])
-            & (z[1] == initial_guess[1])
-            & (z[2] == initial_guess[2])
-            & (z[3] == initial_guess[3])
-        ):
-            # Fall back on Spline method
-            # Fit did not converge
-            BREAKPOINT_FIT_UNCONVERGED = SweL3Flags.BREAKPOINT_FIT_UNCONVERGED
-            ch_break_output = ch_break
-        else:
-            # Fit worked
-            # Check whether breakpoint has three points to left and right
-            # If so, then find intersection of linear fits to each side
-            ch_break_output = refine_breakpoint_value(
-                np.exp(log_energy_ch), log_psd_ch, z[2], 3
-            )
-    except Exception:
-        # Fall back on Spline method
-        # Fit did not converge
-        BREAKPOINT_FIT_UNCONVERGED = SweL3Flags.BREAKPOINT_FIT_UNCONVERGED
-        ch_break_output = ch_break
+    if len(log_psd_ch) > 1:
+        try:
+            initial_guess = [log_psd_ch[0], 1, 65, 1]
+            z = scipy.optimize.curve_fit(
+                fitting_model, np.exp(log_energy_ch), log_psd_ch, p0=initial_guess
+            )[0]
+            # Make sure the fit converged...if not, fall back on spline values
+            if not (
+                (z[0] == initial_guess[0])
+                & (z[1] == initial_guess[1])
+                & (z[2] == initial_guess[2])
+                & (z[3] == initial_guess[3])
+            ):
+                # Fit worked
+                # Check whether breakpoint has three points to left and right
+                # If so, then find intersection of linear fits to each side
+                ch_break_output = refine_breakpoint_value(
+                    np.exp(log_energy_ch), log_psd_ch, z[2], 3
+                )
+                BREAKPOINT_FIT_UNCONVERGED = SweL3Flags.NONE
+        except (TypeError, ValueError):
+            # Fit did not converge, fall back on Spline method
+            pass
     return (
         sc_pot_output,
         ch_break_output,
@@ -213,9 +210,9 @@ def average_over_look_directions(
     minimum_psd_value: float,
 ) -> np.ndarray:
     enforced_minimum_psd = np.maximum(phase_space_density, minimum_psd_value)
-    weighted_average = np.sum(
-        enforced_minimum_psd * geometric_weights, axis=-1
-    ) / np.sum(geometric_weights)
+    weighted_average = np.sum(enforced_minimum_psd * geometric_weights, axis=-1) / np.sum(
+        geometric_weights
+    )
     return np.mean(weighted_average, axis=1)
 
 
@@ -233,9 +230,7 @@ def calculate_velocity_in_dsp_frame_km_s(
     energy: np.ndarray, inst_el: np.ndarray, inst_az: np.ndarray
 ) -> np.ndarray:
     particle_direction = -calculate_look_directions(inst_el, inst_az)
-    speed_meters_per_second = np.sqrt(
-        energy * PROTON_CHARGE_COULOMBS * 2 / ELECTRON_MASS_KG
-    )
+    speed_meters_per_second = np.sqrt(energy * PROTON_CHARGE_COULOMBS * 2 / ELECTRON_MASS_KG)
     speed_km_per_second = speed_meters_per_second / METERS_PER_KILOMETER
 
     for i in range(len(particle_direction)):
@@ -244,12 +239,8 @@ def calculate_velocity_in_dsp_frame_km_s(
     return particle_direction
 
 
-def rebin_by_pitch_angle(
-    flux, pitch_angles, energies, config: SweConfiguration
-) -> np.ndarray:
-    all_the_bins = rebin_by_pitch_angle_and_gyrophase(
-        flux, pitch_angles, None, energies, config
-    )
+def rebin_by_pitch_angle(flux, pitch_angles, energies, config: SweConfiguration) -> np.ndarray:
+    all_the_bins = rebin_by_pitch_angle_and_gyrophase(flux, pitch_angles, None, energies, config)
     remove_gyrophase_axis = all_the_bins[:, :, 0]
     return remove_gyrophase_axis
 
@@ -281,28 +272,22 @@ def _rebin(
         gyrophase_bins_range = [0]
         num_gyrophase_bins = 1
 
-    rebinned = np.full(
-        (num_energy_bins, num_pitch_bins, num_gyrophase_bins), np.nan, dtype=float
-    )
+    rebinned = np.full((num_energy_bins, num_pitch_bins, num_gyrophase_bins), np.nan, dtype=float)
     for g in gyrophase_bins_range:
         for j in range(num_pitch_bins):
-            mask_pitch_angle = (
-                pitch_angles_for_masked_psd >= pitch_angle_left_edges[j]
-            ) & (pitch_angles_for_masked_psd < pitch_angle_right_edges[j])
+            mask_pitch_angle = (pitch_angles_for_masked_psd >= pitch_angle_left_edges[j]) & (
+                pitch_angles_for_masked_psd < pitch_angle_right_edges[j]
+            )
 
             if gyrophase is not None:
-                mask_gyrophase = (
-                    gyrophase_for_masked_psd >= gyrophase_left_edges[g]
-                ) & (gyrophase_for_masked_psd < gyrophase_right_edges[g])
+                mask_gyrophase = (gyrophase_for_masked_psd >= gyrophase_left_edges[g]) & (
+                    gyrophase_for_masked_psd < gyrophase_right_edges[g]
+                )
             else:
                 mask_gyrophase = np.ones_like(mask_pitch_angle, dtype=bool)
 
-            psd_by_pitch_angle = psd_greater_than_zero[
-                mask_pitch_angle & mask_gyrophase
-            ]
-            energy_by_pitch_angle = energies_for_masked_psd[
-                mask_pitch_angle & mask_gyrophase
-            ]
+            psd_by_pitch_angle = psd_greater_than_zero[mask_pitch_angle & mask_gyrophase]
+            energy_by_pitch_angle = energies_for_masked_psd[mask_pitch_angle & mask_gyrophase]
 
             # maintain in new method
             if len(energy_by_pitch_angle) < 2:
@@ -316,9 +301,7 @@ def _rebin(
                 left = config["energy_bin_low_multiplier"] * center
                 right = config["energy_bin_high_multiplier"] * center
 
-                mask_energy = (energy_by_pitch_angle > left) & (
-                    energy_by_pitch_angle < right
-                )
+                mask_energy = (energy_by_pitch_angle > left) & (energy_by_pitch_angle < right)
 
                 energy_to_fit = energy_by_pitch_angle[mask_energy]
                 psd_to_fit = psd_by_pitch_angle[mask_energy]
@@ -332,9 +315,7 @@ def _rebin(
                 has_points_on_both_sides = (
                     max_within_window > center and min_within_window < center
                 )
-                is_overall_max_within_window = (
-                    overall_max_energy_for_pitch_angle in energy_to_fit
-                )
+                is_overall_max_within_window = overall_max_energy_for_pitch_angle in energy_to_fit
                 max_within_case = (
                     is_overall_max_within_window
                     and closest_energy_ratio < config["high_energy_proximity_threshold"]
@@ -354,11 +335,7 @@ def _rebin(
                     and has_points_on_both_sides
                 )
 
-                if (
-                    max_within_case
-                    or mins_within_case
-                    or max_and_mins_outside_window_case
-                ):
+                if max_within_case or mins_within_case or max_and_mins_outside_window_case:
                     log_energy_to_fit = np.log(energy_to_fit)
                     log_psd_to_fit = np.log(psd_to_fit)
                     intercept, slope = np.polynomial.polynomial.polyfit(
@@ -425,22 +402,14 @@ def correct_and_rebin(
     ],
     config: SweConfiguration,
 ) -> tuple[np.ndarray, np.ndarray]:
-    velocity_in_sw_frame = calculate_velocity_in_sw_frame(
-        dsp_velocities, solar_wind_vector
-    )
+    velocity_in_sw_frame = calculate_velocity_in_sw_frame(dsp_velocities, solar_wind_vector)
     energy_in_sw_frame = calculate_energy_in_ev_from_velocity_in_km_per_second(
         velocity_in_sw_frame
     )
-    pitch_angle = calculate_pitch_angle(
-        velocity_in_sw_frame, mag_vector[..., np.newaxis, :]
-    )
-    gyrophase = calculate_gyrophase(
-        velocity_in_sw_frame, mag_vector[..., np.newaxis, :]
-    )
+    pitch_angle = calculate_pitch_angle(velocity_in_sw_frame, mag_vector[..., np.newaxis, :])
+    gyrophase = calculate_gyrophase(velocity_in_sw_frame, mag_vector[..., np.newaxis, :])
 
-    rebinned_by_pa = rebin_by_pitch_angle(
-        flux_or_psd, pitch_angle, energy_in_sw_frame, config
-    )
+    rebinned_by_pa = rebin_by_pitch_angle(flux_or_psd, pitch_angle, energy_in_sw_frame, config)
     rebinned_by_pa_and_gyro = rebin_by_pitch_angle_and_gyrophase(
         flux_or_psd, pitch_angle, gyrophase, energy_in_sw_frame, config
     )
@@ -479,10 +448,7 @@ def integrate_distribution_to_get_inbound_and_outbound_1d_spectrum(
         (psd_by_pitch_angle * pitch_angle_bin_factors)[:, ~pitch_less_than_90], axis=1
     )
 
-    if (
-        spectrum_a[config["in_vs_out_energy_index"]]
-        > spectrum_b[config["in_vs_out_energy_index"]]
-    ):
+    if spectrum_a[config["in_vs_out_energy_index"]] > spectrum_b[config["in_vs_out_energy_index"]]:
         inbound = spectrum_b
         outbound = spectrum_a
     else:
@@ -549,9 +515,7 @@ def swe_rebin_intensity_by_pitch_angle_and_gyrophase(
                     (
                         i
                         for i, (center, delta) in enumerate(
-                            zip(
-                                config["pitch_angle_bins"], config["pitch_angle_deltas"]
-                            )
+                            zip(config["pitch_angle_bins"], config["pitch_angle_deltas"])
                         )
                         if center - delta <= pitch_angle < center + delta
                     ),
@@ -562,33 +526,25 @@ def swe_rebin_intensity_by_pitch_angle_and_gyrophase(
                         (
                             i
                             for i, (center, delta) in enumerate(
-                                zip(
-                                    config["gyrophase_bins"], config["gyrophase_deltas"]
-                                )
+                                zip(config["gyrophase_bins"], config["gyrophase_deltas"])
                             )
                             if center - delta <= gyrophase < center + delta
                         ),
                         num_gyrophase_bins - 1,
                     )
 
-                    rebinned_summed_by_pa_and_gyro[
-                        i, pitch_angle_bin, gyrophase_bin
-                    ] += intensity
-                    rebinned_count_by_pa_and_gyro[
-                        i, pitch_angle_bin, gyrophase_bin
-                    ] += 1
+                    rebinned_summed_by_pa_and_gyro[i, pitch_angle_bin, gyrophase_bin] += intensity
+                    rebinned_count_by_pa_and_gyro[i, pitch_angle_bin, gyrophase_bin] += 1
 
-                    rebinned_summed_counts_by_pa_and_gyro[
-                        i, pitch_angle_bin, gyrophase_bin
-                    ] += count
+                    rebinned_summed_counts_by_pa_and_gyro[i, pitch_angle_bin, gyrophase_bin] += (
+                        count
+                    )
 
                 rebinned_summed_pa_only[i, pitch_angle_bin] += intensity
                 rebinned_count_pa_only[i, pitch_angle_bin] += 1
                 rebinned_summed_counts_by_pa_only[i, pitch_angle_bin] += count
 
-    rebinned_summed_counts_by_pa_and_gyro[
-        rebinned_summed_counts_by_pa_and_gyro == 0
-    ] = np.nan
+    rebinned_summed_counts_by_pa_and_gyro[rebinned_summed_counts_by_pa_and_gyro == 0] = np.nan
     rebinned_summed_counts_by_pa_only[rebinned_summed_counts_by_pa_only == 0] = np.nan
 
     averaged_rebinned_intensity_by_pa_and_gyro = np.divide(
diff --git a/imap_l3_processing/swe/l3/swe_l3_dependencies.py b/imap_l3_processing/swe/l3/swe_l3_dependencies.py
index 81a4bd3d..a7b4fe10 100644
--- a/imap_l3_processing/swe/l3/swe_l3_dependencies.py
+++ b/imap_l3_processing/swe/l3/swe_l3_dependencies.py
@@ -8,16 +8,16 @@
 
 from imap_l3_processing.models import MagData
 from imap_l3_processing.swe.l3.models import (
-    SweL2Data,
-    SweConfiguration,
     SwapiL3aProtonData,
+    SweConfiguration,
     SweL1bData,
+    SweL2Data,
 )
 from imap_l3_processing.swe.l3.utils import (
+    read_l1b_swe_data,
     read_l2_swe_data,
     read_l3a_swapi_proton_data,
     read_swe_config,
-    read_l1b_swe_data,
 )
 from imap_l3_processing.utils import read_mag_data, select_mag_path
 
@@ -36,9 +36,7 @@ class SweL3Dependencies:
     mag_is_preliminary: bool = False
 
     @classmethod
-    def fetch_dependencies(
-        cls, dependencies: ProcessingInputCollection
-    ) -> SweL3Dependencies:
+    def fetch_dependencies(cls, dependencies: ProcessingInputCollection) -> SweL3Dependencies:
         science_files = dependencies.processing_input
         swe_config_dependency = dependencies.get_file_paths(
             source="swe", descriptor=SWE_CONFIG_DESCRIPTOR
diff --git a/imap_l3_processing/swe/l3/utils.py b/imap_l3_processing/swe/l3/utils.py
index 45e68695..9f78e51b 100644
--- a/imap_l3_processing/swe/l3/utils.py
+++ b/imap_l3_processing/swe/l3/utils.py
@@ -8,10 +8,10 @@
 
 from imap_l3_processing.cdf.cdf_utils import read_numeric_variable
 from imap_l3_processing.swe.l3.models import (
-    SweConfiguration,
-    SweL2Data,
     SwapiL3aProtonData,
+    SweConfiguration,
     SweL1bData,
+    SweL2Data,
 )
 
 
@@ -25,17 +25,13 @@ def read_l2_swe_data(swe_l2_data: Path) -> SweL2Data:
         inst_az_label = cdf["inst_az_label"][:]
         energy = cdf["energy"][:]
         inst_az_spin_sector = read_numeric_variable(cdf["inst_az_spin_sector"])
-        phase_space_density = read_numeric_variable(
-            cdf["phase_space_density_spin_sector"]
-        )
+        phase_space_density = read_numeric_variable(cdf["phase_space_density_spin_sector"])
         acquisition_time_in_MET = read_numeric_variable(cdf["acquisition_time"])
         valid_times_mask = np.isfinite(acquisition_time_in_MET)
         converted_valid_times = met_to_datetime64(
             acquisition_time_in_MET[valid_times_mask].ravel()
         )
-        acquisition_time_dt64 = np.full(
-            acquisition_time_in_MET.shape, np.datetime64("NaT", "ns")
-        )
+        acquisition_time_dt64 = np.full(acquisition_time_in_MET.shape, np.datetime64("NaT", "ns"))
         acquisition_time_dt64[valid_times_mask] = converted_valid_times
         acquisition_duration = cdf["acq_duration"][...]
         phase_space_density_rebinned = read_numeric_variable(cdf["phase_space_density"])
@@ -63,9 +59,7 @@ def read_l1b_swe_data(swe_l1b_data: Path) -> SweL1bData:
         count_rates = cdf["science_data"][...]
         settle_duration = cdf["settle_duration"][...]
 
-    return SweL1bData(
-        epoch=epoch, count_rates=count_rates, settle_duration=settle_duration
-    )
+    return SweL1bData(epoch=epoch, count_rates=count_rates, settle_duration=settle_duration)
 
 
 def read_l3a_swapi_proton_data(swapi_l3a_data: Path) -> SwapiL3aProtonData:
@@ -78,9 +72,7 @@ def read_l3a_swapi_proton_data(swapi_l3a_data: Path) -> SwapiL3aProtonData:
             epoch_delta = np.repeat(timedelta(seconds=epoch_delta_ns), len(epoch))
         proton_sw_speed = read_numeric_variable(cdf["proton_sw_speed"])
         if "proton_sw_velocity_rtn" in cdf:
-            proton_sw_velocity_rtn = read_numeric_variable(
-                cdf["proton_sw_velocity_rtn"]
-            )
+            proton_sw_velocity_rtn = read_numeric_variable(cdf["proton_sw_velocity_rtn"])
         else:
             proton_sw_velocity_rtn = np.full((len(epoch), 3), np.nan)
         swp_flags = cdf["swp_flags"][...]
diff --git a/imap_l3_processing/swe/quality_flags.py b/imap_l3_processing/swe/quality_flags.py
index bf4318aa..ded60983 100644
--- a/imap_l3_processing/swe/quality_flags.py
+++ b/imap_l3_processing/swe/quality_flags.py
@@ -1,4 +1,4 @@
-from imap_processing.quality_flags import FlagNameMixin, CommonFlags
+from imap_processing.quality_flags import CommonFlags, FlagNameMixin
 
 
 class SweL3Flags(FlagNameMixin):
diff --git a/imap_l3_processing/swe/swe_processor.py b/imap_l3_processing/swe/swe_processor.py
index 62783210..444154bf 100644
--- a/imap_l3_processing/swe/swe_processor.py
+++ b/imap_l3_processing/swe/swe_processor.py
@@ -12,36 +12,36 @@
 from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
 from imap_l3_processing.processor import Processor
 from imap_l3_processing.swe.l3.models import (
-    SweL3Data,
+    SweConfiguration,
     SweL1bData,
     SweL2Data,
+    SweL3Data,
     SweL3MomentData,
-    SweConfiguration,
 )
 from imap_l3_processing.swe.l3.science.moment_calculations import (
-    compute_maxwellian_weight_factors,
-    rotate_temperature,
+    Moments,
+    ScaleDensityOutput,
     apply_rotation_matrix,
-    rotate_rtn_vectors_to_dps,
+    calculate_primary_eigenvector,
+    compute_maxwellian_weight_factors,
     core_fit_moments_retrying_on_failure,
+    get_dps_to_rtn_rotation_matrix,
     halo_fit_moments_retrying_on_failure,
-    Moments,
     integrate,
+    rotate_rtn_vectors_to_dps,
+    rotate_temperature,
+    rotate_temperature_tensor_to_mag,
+    rotate_vector_to_rtn_spherical_coordinates,
     scale_core_density,
     scale_halo_density,
-    rotate_vector_to_rtn_spherical_coordinates,
-    calculate_primary_eigenvector,
-    ScaleDensityOutput,
-    rotate_temperature_tensor_to_mag,
-    get_dps_to_rtn_rotation_matrix,
 )
 from imap_l3_processing.swe.l3.science.pitch_calculations import (
     average_over_look_directions,
-    mec_breakpoint_finder,
+    calculate_velocity_in_dsp_frame_km_s,
     correct_and_rebin,
     integrate_distribution_to_get_1d_spectrum,
     integrate_distribution_to_get_inbound_and_outbound_1d_spectrum,
-    calculate_velocity_in_dsp_frame_km_s,
+    mec_breakpoint_finder,
     swe_rebin_intensity_by_pitch_angle_and_gyrophase,
 )
 from imap_l3_processing.swe.l3.swe_l3_dependencies import SweL3Dependencies
@@ -73,9 +73,7 @@
 
 
 def _detect_negative(density: np.ndarray, tensor: np.ndarray) -> np.ndarray:
-    return (density < 0) | np.any(
-        tensor[:, TEMPERATURE_TENSOR_DIAGONAL_INDICES] < 0, axis=-1
-    )
+    return (density < 0) | np.any(tensor[:, TEMPERATURE_TENSOR_DIAGONAL_INDICES] < 0, axis=-1)
 
 
 def check_and_mask_negative_moments(moment_data: SweL3MomentData) -> np.ndarray:
@@ -102,9 +100,7 @@ def check_and_mask_negative_moments(moment_data: SweL3MomentData) -> np.ndarray:
             core_negative | halo_negative | total_negative
         ] = np.nan
 
-    flags[core_negative | halo_negative | total_negative] |= np.uint16(
-        SweL3Flags.NEGATIVE_MOMENT
-    )
+    flags[core_negative | halo_negative | total_negative] |= np.uint16(SweL3Flags.NEGATIVE_MOMENT)
     return flags
 
 
@@ -117,7 +113,7 @@ def check_temperature_outlier_flag(data: np.ndarray):
     TEMPERATURE_OUTLIER[:] = SweL3Flags.NONE
     for i in np.arange(len(data)):
         # Get left and right index accounting for edges
-        left_idx = 0 if i - window // 2 < 0 else i - window // 2
+        left_idx = max(i - window // 2, 0)
         right_idx = i + window // 2 + 1
         # Loop check the current value while removing every point from the window on each iteration
         for k in np.arange(len(data[left_idx:right_idx])):
@@ -136,7 +132,7 @@ def check_temperature_outlier_flag(data: np.ndarray):
         # Don't do this is the current value is already an outlier
         if TEMPERATURE_OUTLIER[i] == SweL3Flags.NONE:
             # Get left and right index accounting for edges
-            left_idx = 0 if i - window // 2 < 0 else i - window // 2
+            left_idx = max(i - window // 2, 0)
             right_idx = i + window // 2 + 1
             # Loop check the current value while removing every point from the window on each iteration
             # This time around, we conditionally slice to avoid including already known outliers from
@@ -147,14 +143,10 @@ def check_temperature_outlier_flag(data: np.ndarray):
                 temp_data = data[left_idx:right_idx]
                 # Check if current value is beyond 3-sigma of median from data
                 median = np.nanmedian(
-                    np.delete(temp_data, k)[
-                        np.delete(tof_copy[left_idx:right_idx], k) == 0
-                    ]
+                    np.delete(temp_data, k)[np.delete(tof_copy[left_idx:right_idx], k) == 0]
                 )
                 deviation = np.nanstd(
-                    np.delete(temp_data, k)[
-                        np.delete(tof_copy[left_idx:right_idx], k) == 0
-                    ]
+                    np.delete(temp_data, k)[np.delete(tof_copy[left_idx:right_idx], k) == 0]
                 )
                 if np.abs(median - data[i]) >= deviation * 3.0:
                     TEMPERATURE_OUTLIER[i] = SweL3Flags.TEMPERATURE_OUTLIER
@@ -164,9 +156,7 @@ def check_temperature_outlier_flag(data: np.ndarray):
 
 
 class SweProcessor(Processor):
-    def __init__(
-        self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata
-    ):
+    def __init__(self, dependencies: ProcessingInputCollection, input_metadata: InputMetadata):
         super().__init__(dependencies, input_metadata)
 
     def process(self):
@@ -186,9 +176,7 @@ def calculate_products(self, dependencies: SweL3Dependencies) -> SweL3Data:
 
         average_psd = []
         swe_quality_flags = np.empty_like(swe_epoch, dtype=np.uint16)
-        spacecraft_potential: np.ndarray[np.float64] = np.empty_like(
-            swe_epoch, dtype=np.float64
-        )
+        spacecraft_potential: np.ndarray[np.float64] = np.empty_like(swe_epoch, dtype=np.float64)
         halo_core: np.ndarray[np.float64] = np.empty_like(swe_epoch, dtype=np.float64)
         corrected_energy_bins = []
         rebinned_mag_data = dependencies.mag_data.rebin_to(
@@ -199,11 +187,9 @@ def calculate_products(self, dependencies: SweL3Dependencies) -> SweL3Data:
         geometric_fractions = np.array(config["geometric_fractions"])
         for i in range(len(swe_epoch)):
             npts = 7 // 2
-            left_idx = 0 if i - npts < 0 else i - npts
+            left_idx = max(i - npts, 0)
             right_idx = i + (i - left_idx + 1)
-            time_avg_psd = np.nanmean(
-                swe_l2_data.phase_space_density[left_idx:right_idx], axis=0
-            )
+            time_avg_psd = np.nanmean(swe_l2_data.phase_space_density[left_idx:right_idx], axis=0)
 
             average_psd.append(
                 average_over_look_directions(
@@ -213,8 +199,8 @@ def calculate_products(self, dependencies: SweL3Dependencies) -> SweL3Data:
                 )
             )
 
-            spacecraft_potential[i], halo_core[i], swe_quality_flags[i] = (
-                mec_breakpoint_finder(swe_l2_data.energy, average_psd[i])
+            spacecraft_potential[i], halo_core[i], swe_quality_flags[i] = mec_breakpoint_finder(
+                swe_l2_data.energy, average_psd[i]
             )
 
             corrected_energy_bins.append(swe_l2_data.energy - spacecraft_potential[i])
@@ -277,26 +263,18 @@ def calculate_products(self, dependencies: SweL3Dependencies) -> SweL3Data:
                 psd_array > UNPHYSICAL_PSD_THRESHOLD,
                 axis=tuple(range(1, psd_array.ndim)),
             )
-            swe_quality_flags[unphysical_psd_per_epoch] |= np.uint16(
-                SweL3Flags.UNPHYSICAL_PSD
-            )
+            swe_quality_flags[unphysical_psd_per_epoch] |= np.uint16(SweL3Flags.UNPHYSICAL_PSD)
 
         if dependencies.mag_is_preliminary:
-            swe_quality_flags = np.bitwise_or(
-                swe_quality_flags, SweL3Flags.PRELIMINARY_MAG
-            )
+            swe_quality_flags = np.bitwise_or(swe_quality_flags, SweL3Flags.PRELIMINARY_MAG)
 
-        last_cal_interval = (
-            swe_l2_data.data_quality & SweL1bFlags.LAST_CAL_INTERVAL
-        ) != 0
+        last_cal_interval = (swe_l2_data.data_quality & SweL1bFlags.LAST_CAL_INTERVAL) != 0
         swe_quality_flags[last_cal_interval] |= np.uint16(
             SweL3Flags.FALLBACK_CALIBRATION_EXTRAPOLATED
         )
 
         rebinned_mask = np.ma.masked_invalid(swe_l2_data.phase_space_density_rebinned)
-        dist_by_phi_rebinned = np.average(
-            rebinned_mask, weights=geometric_fractions, axis=-1
-        )
+        dist_by_phi_rebinned = np.average(rebinned_mask, weights=geometric_fractions, axis=-1)
         dist_fun_1d_rebinned = np.ma.average(dist_by_phi_rebinned, axis=-1)
         dist_by_theta_rebinned = np.ma.average(rebinned_mask, axis=-2)
 
@@ -429,16 +407,10 @@ def calculate_moment_products(
                 core_nfit = jbreak - ifit
                 ifit += 1
                 if core_nfit == 0:
-                    logger.info(
-                        f"Bad core-halo breakpoint value at index {i}. Continuing."
-                    )
+                    logger.info(f"Bad core-halo breakpoint value at index {i}. Continuing.")
                     continue
 
-                halo_nfit = (
-                    5
-                    if len(swe_l2_data.energy) - jbreak > 5
-                    else len(swe_l2_data.energy) - jbreak
-                )
+                halo_nfit = min(len(swe_l2_data.energy) - jbreak, 5)
 
                 core_moment_fit_result = core_fit_moments_retrying_on_failure(
                     corrected_energy_bins[i],
@@ -493,9 +465,7 @@ def calculate_moment_products(
                     )
                     core_temp_theta_rtns[i] = core_temp_theta_rtn
                     core_temp_phi_rtns[i] = core_temp_phi_rtn
-                    core_temp_avg = (
-                        2 * core_moment.t_perpendicular + core_moment.t_parallel
-                    ) / 3
+                    core_temp_avg = (2 * core_moment.t_perpendicular + core_moment.t_parallel) / 3
 
                     if 1e3 < core_temp_avg < 1e7:
                         core_integrate_result = integrate(
@@ -512,26 +482,22 @@ def calculate_moment_products(
                             [0, 0, 0, 0, 0, 0],
                         )
                         if core_integrate_result is not None:
-                            scale_core_density_output: ScaleDensityOutput = (
-                                scale_core_density(
-                                    core_integrate_result.density,
-                                    core_integrate_result.velocity,
-                                    core_integrate_result.temperature,
-                                    core_moment,
-                                    ifit,
-                                    corrected_energy_bins[i],
-                                    spacecraft_potential[i],
-                                    cos_theta,
-                                    config["aperture_field_of_view_radians"],
-                                    instrument_phi[i],
-                                    core_moment_fit_result.regress_result,
-                                    core_integrate_result.base_energy,
-                                )
+                            scale_core_density_output: ScaleDensityOutput = scale_core_density(
+                                core_integrate_result.density,
+                                core_integrate_result.velocity,
+                                core_integrate_result.temperature,
+                                core_moment,
+                                ifit,
+                                corrected_energy_bins[i],
+                                spacecraft_potential[i],
+                                cos_theta,
+                                config["aperture_field_of_view_radians"],
+                                instrument_phi[i],
+                                core_moment_fit_result.regress_result,
+                                core_integrate_result.base_energy,
                             )
 
-                            core_density_integrated[i] = (
-                                scale_core_density_output.density
-                            )
+                            core_density_integrated[i] = scale_core_density_output.density
                             core_velocity_integrated[i] = apply_rotation_matrix(
                                 dps_to_rtn, scale_core_density_output.velocity
                             )
@@ -539,20 +505,16 @@ def calculate_moment_products(
                                 scale_core_density_output.temperature
                             )
 
-                            magnitude, theta, phi = (
-                                rotate_vector_to_rtn_spherical_coordinates(
-                                    dps_to_rtn, core_integrate_result.heat_flux
-                                )
+                            magnitude, theta, phi = rotate_vector_to_rtn_spherical_coordinates(
+                                dps_to_rtn, core_integrate_result.heat_flux
                             )
 
                             core_heat_flux_magnitude[i] = magnitude
                             core_heat_flux_theta[i] = theta
                             core_heat_flux_phi[i] = phi
 
-                            core_primary_eigen_vector, core_temps = (
-                                calculate_primary_eigenvector(
-                                    scale_core_density_output.temperature
-                                )
+                            core_primary_eigen_vector, core_temps = calculate_primary_eigenvector(
+                                scale_core_density_output.temperature
                             )
 
                             core_t_parallel_integrated[i] = core_temps[0]
@@ -561,10 +523,8 @@ def calculate_moment_products(
                                 core_temps[2],
                             ]
 
-                            magnitude, theta, phi = (
-                                rotate_vector_to_rtn_spherical_coordinates(
-                                    dps_to_rtn, core_primary_eigen_vector
-                                )
+                            magnitude, theta, phi = rotate_vector_to_rtn_spherical_coordinates(
+                                dps_to_rtn, core_primary_eigen_vector
                             )
                             core_temperature_theta_rtn_integrated[i] = theta
                             core_temperature_phi_rtn_integrated[i] = phi
@@ -600,9 +560,7 @@ def calculate_moment_products(
                             assert total_integration_output is not None, (
                                 "not yet checking if this is None"
                             )
-                            total_density_integrated[i] = (
-                                total_integration_output.density
-                            )
+                            total_density_integrated[i] = total_integration_output.density
                             total_velocity_integrated[i] = apply_rotation_matrix(
                                 dps_to_rtn, total_integration_output.velocity
                             )
@@ -610,10 +568,8 @@ def calculate_moment_products(
                                 total_integration_output.temperature
                             )
 
-                            magnitude, theta, phi = (
-                                rotate_vector_to_rtn_spherical_coordinates(
-                                    dps_to_rtn, total_integration_output.heat_flux
-                                )
+                            magnitude, theta, phi = rotate_vector_to_rtn_spherical_coordinates(
+                                dps_to_rtn, total_integration_output.heat_flux
                             )
 
                             total_heat_flux_magnitude[i] = magnitude
@@ -621,9 +577,7 @@ def calculate_moment_products(
                             total_heat_flux_phi[i] = phi
 
                             total_primary_eigen_vector, total_temps = (
-                                calculate_primary_eigenvector(
-                                    total_integration_output.temperature
-                                )
+                                calculate_primary_eigenvector(total_integration_output.temperature)
                             )
 
                             total_t_parallel_integrated[i] = total_temps[0]
@@ -632,10 +586,8 @@ def calculate_moment_products(
                                 total_temps[2],
                             ]
 
-                            magnitude, theta, phi = (
-                                rotate_vector_to_rtn_spherical_coordinates(
-                                    dps_to_rtn, total_primary_eigen_vector
-                                )
+                            magnitude, theta, phi = rotate_vector_to_rtn_spherical_coordinates(
+                                dps_to_rtn, total_primary_eigen_vector
                             )
                             total_temperature_theta_rtn_integrated[i] = theta
                             total_temperature_phi_rtn_integrated[i] = phi
@@ -649,9 +601,7 @@ def calculate_moment_products(
                                 rebinned_mag_data[i],
                             )
 
-                            total_temperature_parallel_to_mag[i] = (
-                                total_t_parallel_to_mag
-                            )
+                            total_temperature_parallel_to_mag[i] = total_t_parallel_to_mag
                             total_temperature_perpendicular_to_mag[i] = [
                                 total_t_perpendicular_to_mag_average,
                                 total_t_perpendicular_to_mag_ratio,
@@ -661,9 +611,7 @@ def calculate_moment_products(
                             logger.info(f"core integrate failed at index {i}")
 
                     else:
-                        logger.info(
-                            f"core temp {core_temp_avg} out of range at index {i}"
-                        )
+                        logger.info(f"core temp {core_temp_avg} out of range at index {i}")
                 else:
                     logger.info(f"bad core moment fit result at index {i}")
 
@@ -705,9 +653,7 @@ def calculate_moment_products(
                     )
                     halo_temp_theta_rtns[i] = halo_temp_theta_rtn
                     halo_temp_phi_rtns[i] = halo_temp_phi_rtn
-                    halo_temp_avg = (
-                        2 * halo_moment.t_perpendicular + halo_moment.t_parallel
-                    ) / 3
+                    halo_temp_avg = (2 * halo_moment.t_perpendicular + halo_moment.t_parallel) / 3
                     if 1e4 < halo_temp_avg < 1e8:
                         halo_integrate_result = integrate(
                             jbreak,
@@ -723,25 +669,21 @@ def calculate_moment_products(
                             [0, 0, 0, 0, 0, 0],
                         )
                         if halo_integrate_result is not None:
-                            scale_halo_density_output: ScaleDensityOutput = (
-                                scale_halo_density(
-                                    halo_integrate_result.density,
-                                    halo_integrate_result.velocity,
-                                    halo_integrate_result.temperature,
-                                    halo_moment,
-                                    spacecraft_potential[i],
-                                    halo_core[i],
-                                    cos_theta,
-                                    config["aperture_field_of_view_radians"],
-                                    instrument_phi[i],
-                                    halo_moment_fit_result.regress_result,
-                                    halo_integrate_result.base_energy,
-                                )
+                            scale_halo_density_output: ScaleDensityOutput = scale_halo_density(
+                                halo_integrate_result.density,
+                                halo_integrate_result.velocity,
+                                halo_integrate_result.temperature,
+                                halo_moment,
+                                spacecraft_potential[i],
+                                halo_core[i],
+                                cos_theta,
+                                config["aperture_field_of_view_radians"],
+                                instrument_phi[i],
+                                halo_moment_fit_result.regress_result,
+                                halo_integrate_result.base_energy,
                             )
 
-                            halo_density_integrated[i] = (
-                                scale_halo_density_output.density
-                            )
+                            halo_density_integrated[i] = scale_halo_density_output.density
                             halo_velocity_integrated[i] = apply_rotation_matrix(
                                 dps_to_rtn, scale_halo_density_output.velocity
                             )
@@ -749,20 +691,16 @@ def calculate_moment_products(
                                 scale_halo_density_output.temperature
                             )
 
-                            magnitude, theta, phi = (
-                                rotate_vector_to_rtn_spherical_coordinates(
-                                    dps_to_rtn, halo_integrate_result.heat_flux
-                                )
+                            magnitude, theta, phi = rotate_vector_to_rtn_spherical_coordinates(
+                                dps_to_rtn, halo_integrate_result.heat_flux
                             )
 
                             halo_heat_flux_magnitude[i] = magnitude
                             halo_heat_flux_theta[i] = theta
                             halo_heat_flux_phi[i] = phi
 
-                            halo_primary_eigen_vector, halo_temps = (
-                                calculate_primary_eigenvector(
-                                    scale_halo_density_output.temperature
-                                )
+                            halo_primary_eigen_vector, halo_temps = calculate_primary_eigenvector(
+                                scale_halo_density_output.temperature
                             )
 
                             halo_t_parallel_integrated[i] = halo_temps[0]
@@ -771,10 +709,8 @@ def calculate_moment_products(
                                 halo_temps[2],
                             ]
 
-                            magnitude, theta, phi = (
-                                rotate_vector_to_rtn_spherical_coordinates(
-                                    dps_to_rtn, halo_primary_eigen_vector
-                                )
+                            magnitude, theta, phi = rotate_vector_to_rtn_spherical_coordinates(
+                                dps_to_rtn, halo_primary_eigen_vector
                             )
                             halo_temperature_theta_rtn_integrated[i] = theta
                             halo_temperature_phi_rtn_integrated[i] = phi
@@ -796,9 +732,7 @@ def calculate_moment_products(
                         else:
                             logger.info(f"halo integrate failed at index {i}")
                     else:
-                        logger.info(
-                            f"halo temp {halo_temp_avg} out of range at index {i}"
-                        )
+                        logger.info(f"halo temp {halo_temp_avg} out of range at index {i}")
                 else:
                     logger.info(f"bad halo moment fit result at index {i}")
 
@@ -813,18 +747,10 @@ def calculate_moment_products(
             core_fit_num_points=core_fit_num_points,
             core_chisq=core_fit_chi_squareds,
             halo_chisq=halo_fit_chi_squareds,
-            core_density_fit=np.array(
-                [core_moment.density for core_moment in core_moments]
-            ),
-            halo_density_fit=np.array(
-                [halo_moment.density for halo_moment in halo_moments]
-            ),
-            core_t_parallel_fit=np.array(
-                [core_moment.t_parallel for core_moment in core_moments]
-            ),
-            halo_t_parallel_fit=np.array(
-                [halo_moment.t_parallel for halo_moment in halo_moments]
-            ),
+            core_density_fit=np.array([core_moment.density for core_moment in core_moments]),
+            halo_density_fit=np.array([halo_moment.density for halo_moment in halo_moments]),
+            core_t_parallel_fit=np.array([core_moment.t_parallel for core_moment in core_moments]),
+            halo_t_parallel_fit=np.array([halo_moment.t_parallel for halo_moment in halo_moments]),
             core_t_perpendicular_fit=np.array(
                 [core_moment.t_perpendicular for core_moment in core_moments]
             ),
@@ -866,21 +792,15 @@ def calculate_moment_products(
             core_temperature_theta_rtn_integrated=np.rad2deg(
                 core_temperature_theta_rtn_integrated
             ),
-            core_temperature_phi_rtn_integrated=np.rad2deg(
-                core_temperature_phi_rtn_integrated
-            ),
+            core_temperature_phi_rtn_integrated=np.rad2deg(core_temperature_phi_rtn_integrated),
             halo_temperature_theta_rtn_integrated=np.rad2deg(
                 halo_temperature_theta_rtn_integrated
             ),
-            halo_temperature_phi_rtn_integrated=np.rad2deg(
-                halo_temperature_phi_rtn_integrated
-            ),
+            halo_temperature_phi_rtn_integrated=np.rad2deg(halo_temperature_phi_rtn_integrated),
             total_temperature_theta_rtn_integrated=np.rad2deg(
                 total_temperature_theta_rtn_integrated
             ),
-            total_temperature_phi_rtn_integrated=np.rad2deg(
-                total_temperature_phi_rtn_integrated
-            ),
+            total_temperature_phi_rtn_integrated=np.rad2deg(total_temperature_phi_rtn_integrated),
             core_temperature_parallel_to_mag=core_temperature_parallel_to_mag,
             core_temperature_perpendicular_to_mag=core_temperature_perpendicular_to_mag,
             halo_temperature_parallel_to_mag=halo_temperature_parallel_to_mag,
@@ -889,8 +809,7 @@ def calculate_moment_products(
             total_temperature_perpendicular_to_mag=total_temperature_perpendicular_to_mag,
             core_temperature_tensor_integrated=core_temperature_tensor_integrated * 1e4,
             halo_temperature_tensor_integrated=halo_temperature_tensor_integrated * 1e4,
-            total_temperature_tensor_integrated=total_temperature_tensor_integrated
-            * 1e4,
+            total_temperature_tensor_integrated=total_temperature_tensor_integrated * 1e4,
             quality_flags=quality_flags,
         )
 
@@ -900,9 +819,7 @@ def calculate_pitch_angle_products(
         swe_l2_data = dependencies.swe_l2_data
         swe_epoch = swe_l2_data.epoch
         config = dependencies.configuration
-        mag_max_distance = np.timedelta64(
-            int(config["max_mag_offset_in_minutes"] * 60e9), "ns"
-        )
+        mag_max_distance = np.timedelta64(int(config["max_mag_offset_in_minutes"] * 60e9), "ns")
 
         mag_nearest_interpolator = NearestInterpolator(
             from_epoch=dependencies.mag_data.epoch,
@@ -914,11 +831,9 @@ def calculate_pitch_angle_products(
 
         swapi_l3a_proton_data = dependencies.swapi_l3a_proton_data
         swapi_epoch = swapi_l3a_proton_data.epoch
-        solar_wind_vectors, used_predict_to_rotate_solar_wind = (
-            rotate_rtn_vectors_to_dps(
-                swapi_epoch,
-                swapi_l3a_proton_data.proton_sw_velocity_rtn,
-            )
+        solar_wind_vectors, used_predict_to_rotate_solar_wind = rotate_rtn_vectors_to_dps(
+            swapi_epoch,
+            swapi_l3a_proton_data.proton_sw_velocity_rtn,
         )
         proton_sw_speed = swapi_l3a_proton_data.proton_sw_speed
         fallback_to_speed = np.any(np.isnan(solar_wind_vectors), axis=1) & np.isfinite(
@@ -944,17 +859,13 @@ def calculate_pitch_angle_products(
 
         rebinned_solar_wind_vectors = solar_wind_interpolator.interpolate_data()
 
-        rebinned_fallback_to_speed = solar_wind_interpolator.interpolate_flags(
-            fallback_to_speed
-        )
-        rebinned_used_predict_to_rotate_solar_wind = (
-            solar_wind_interpolator.interpolate_flags(used_predict_to_rotate_solar_wind)
+        rebinned_fallback_to_speed = solar_wind_interpolator.interpolate_flags(fallback_to_speed)
+        rebinned_used_predict_to_rotate_solar_wind = solar_wind_interpolator.interpolate_flags(
+            used_predict_to_rotate_solar_wind
         )
 
         swe_flags = np.full(len(swe_epoch), SweL3Flags.NONE, dtype=np.uint16)
-        swe_flags[rebinned_fallback_to_speed] |= np.uint16(
-            SweL3Flags.FALLBACK_SWAPI_SPEED
-        )
+        swe_flags[rebinned_fallback_to_speed] |= np.uint16(SweL3Flags.FALLBACK_SWAPI_SPEED)
         swe_flags[rebinned_used_predict_to_rotate_solar_wind] |= np.uint16(
             SweL3Flags.PREDICTIVE_EPHEMERIS
         )
@@ -1038,10 +949,8 @@ def calculate_pitch_angle_products(
                 phase_space_density_1d.append(
                     integrate_distribution_to_get_1d_spectrum(rebinned_psd, config)
                 )
-                inbound, outbound = (
-                    integrate_distribution_to_get_inbound_and_outbound_1d_spectrum(
-                        rebinned_psd, config
-                    )
+                inbound, outbound = integrate_distribution_to_get_inbound_and_outbound_1d_spectrum(
+                    rebinned_psd, config
                 )
                 phase_space_density_inward.append(inbound)
                 phase_space_density_outward.append(outbound)
diff --git a/imap_l3_processing/ultra/models.py b/imap_l3_processing/ultra/models.py
index 8406576c..97a50a5c 100644
--- a/imap_l3_processing/ultra/models.py
+++ b/imap_l3_processing/ultra/models.py
@@ -11,15 +11,15 @@
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.cdf.cdf_utils import read_numeric_variable
-from imap_l3_processing.constants import TT2000_EPOCH, ONE_SECOND_IN_NANOSECONDS
+from imap_l3_processing.constants import ONE_SECOND_IN_NANOSECONDS, TT2000_EPOCH
 from imap_l3_processing.glows.l3e.glows_l3e_hi_model import (
     PROBABILITY_OF_SURVIVAL_VAR_NAME,
 )
 from imap_l3_processing.glows.l3e.glows_l3e_ultra_model import (
-    HEALPIX_INDEX_VAR_NAME,
     ENERGY_VAR_NAME,
     EPOCH_CDF_VAR_NAME,
     GLOWS_FLAGS_VAR_NAME,
+    HEALPIX_INDEX_VAR_NAME,
 )
 
 
@@ -42,9 +42,7 @@ def read_from_path(cls, path_to_cdf: Path) -> UltraGlowsL3eData:
                 repointing=repointing,
                 energy=read_numeric_variable(cdf[ENERGY_VAR_NAME]),
                 healpix_index=cdf[HEALPIX_INDEX_VAR_NAME][...],
-                survival_probability=read_numeric_variable(
-                    cdf[PROBABILITY_OF_SURVIVAL_VAR_NAME]
-                ),
+                survival_probability=read_numeric_variable(cdf[PROBABILITY_OF_SURVIVAL_VAR_NAME]),
                 flags=cdf[GLOWS_FLAGS_VAR_NAME][...],
             )
 
@@ -71,12 +69,8 @@ def read_from_path(cls, path: Path) -> UltraL1CPSet:
                 epoch_delta=cdf["epoch_delta"][0],
                 energy=read_numeric_variable(cdf[CoordNames.ENERGY_ULTRA_L1C.value]),
                 exposure=read_numeric_variable(cdf["exposure_factor"]),
-                latitude=read_numeric_variable(
-                    cdf[CoordNames.ELEVATION_L1C.value]
-                ).ravel(),
-                longitude=read_numeric_variable(
-                    cdf[CoordNames.AZIMUTH_L1C.value]
-                ).ravel(),
+                latitude=read_numeric_variable(cdf[CoordNames.ELEVATION_L1C.value]).ravel(),
+                longitude=read_numeric_variable(cdf[CoordNames.AZIMUTH_L1C.value]).ravel(),
                 healpix_index=cdf[CoordNames.HEALPIX_INDEX.value][...],
                 sensitivity=read_numeric_variable(cdf["sensitivity"]),
             )
@@ -110,8 +104,7 @@ def to_xarray(self):
             },
             coords={
                 CoordNames.TIME.value: [
-                    ((self.epoch - TT2000_EPOCH).total_seconds())
-                    * ONE_SECOND_IN_NANOSECONDS
+                    ((self.epoch - TT2000_EPOCH).total_seconds()) * ONE_SECOND_IN_NANOSECONDS
                     + self.epoch_delta / 2,
                 ],
                 CoordNames.ENERGY_ULTRA_L1C.value: self.energy,
diff --git a/imap_l3_processing/ultra/science/ultra_survival_probability.py b/imap_l3_processing/ultra/science/ultra_survival_probability.py
index bd9db854..08c6b1b0 100644
--- a/imap_l3_processing/ultra/science/ultra_survival_probability.py
+++ b/imap_l3_processing/ultra/science/ultra_survival_probability.py
@@ -1,10 +1,8 @@
-from typing import Optional
-
 import numpy as np
 import spiceypy
 from astropy.units import Quantity
 from astropy_healpix import HEALPix, npix_to_nside
-from imap_processing.ena_maps.ena_maps import UltraPointingSet, HealpixSkyMap
+from imap_processing.ena_maps.ena_maps import HealpixSkyMap, UltraPointingSet
 from imap_processing.ena_maps.utils.coordinates import CoordNames
 from imap_processing.spice import geometry
 from imap_processing.ultra.l2.ultra_l2 import bin_pset_energy_bins
@@ -13,7 +11,7 @@
 from imap_l3_processing.constants import ONE_SECOND_IN_NANOSECONDS
 from imap_l3_processing.glows.quality_flags import GlowsL3Flags
 from imap_l3_processing.maps.quality_flags import MapL3Flags
-from imap_l3_processing.ultra.models import UltraL1CPSet, UltraGlowsL3eData
+from imap_l3_processing.ultra.models import UltraGlowsL3eData, UltraL1CPSet
 
 
 class UltraSurvivalProbability(UltraPointingSet):
@@ -21,20 +19,17 @@ def __init__(
         self,
         l1c_pset: UltraL1CPSet,
         l3e_glows: UltraGlowsL3eData,
-        bin_groups: Optional[np.ndarray] = None,
+        bin_groups: np.ndarray | None = None,
     ):
         coarse_bins = bin_pset_energy_bins(l1c_pset.to_xarray(), bin_groups)
         super().__init__(coarse_bins, geometry.SpiceFrame.IMAP_DPS)
 
         predicted_ephemeris = l3e_glows.flags & GlowsL3Flags.PREDICTIVE_EPHEMERIS > 0
-        nominal_alpha_proton_ratio = (
-            l3e_glows.flags & GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO > 0
-        )
+        nominal_alpha_proton_ratio = l3e_glows.flags & GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO > 0
         persisted_last_point = l3e_glows.flags & GlowsL3Flags.PERSISTED_LAST_POINT > 0
 
         l1c_epoch_in_et = spiceypy.unitim(
-            self.data.coords[CoordNames.TIME.value].values[0]
-            / ONE_SECOND_IN_NANOSECONDS,
+            self.data.coords[CoordNames.TIME.value].values[0] / ONE_SECOND_IN_NANOSECONDS,
             "TT",
             "ET",
         )
@@ -52,17 +47,13 @@ def __init__(
         spatially_interpolated_sp = np.zeros((len(l3e_glows.energy), npixels))
 
         for energy_index in range(len(l3e_glows.energy)):
-            spatially_interpolated_sp[energy_index, :] = (
-                glows_healpix.interpolate_bilinear_lonlat(
-                    Quantity(rotated_az_el_points[:, 0], unit="deg"),
-                    Quantity(rotated_az_el_points[:, 1], unit="deg"),
-                    l3e_glows.survival_probability[0, energy_index, :],
-                )
+            spatially_interpolated_sp[energy_index, :] = glows_healpix.interpolate_bilinear_lonlat(
+                Quantity(rotated_az_el_points[:, 0], unit="deg"),
+                Quantity(rotated_az_el_points[:, 1], unit="deg"),
+                l3e_glows.survival_probability[0, energy_index, :],
             )
 
-        energy_interpolated_sp = np.zeros(
-            (len(coarse_bins.energy_bin_geometric_mean), npixels)
-        )
+        energy_interpolated_sp = np.zeros((len(coarse_bins.energy_bin_geometric_mean), npixels))
         for healpix_index in range(npixels):
             energy_interpolated_sp[:, healpix_index] = np.interp(
                 np.log10(coarse_bins.energy_bin_geometric_mean),
@@ -128,15 +119,11 @@ def __init__(
             self.project_pset_values_to_map(
                 sp_pset,
                 values_to_project,
-                pset_valid_mask=np.isfinite(
-                    sp_pset.data["survival_probability_times_exposure"]
-                ),
+                pset_valid_mask=np.isfinite(sp_pset.data["survival_probability_times_exposure"]),
             )
 
         predicted_ephemeris_set = self.data_1d["predicted_ephemeris_flag"] > 0
-        nominal_proton_alpha_ratio_set = (
-            self.data_1d["nominal_alpha_proton_ratio_flag"] > 0
-        )
+        nominal_proton_alpha_ratio_set = self.data_1d["nominal_alpha_proton_ratio_flag"] > 0
         persisted_last_point_set = self.data_1d["persisted_last_point_flag"] > 0
 
         quality_flags = (
diff --git a/imap_l3_processing/ultra/ultra_combined_nsp_initializer.py b/imap_l3_processing/ultra/ultra_combined_nsp_initializer.py
index fbd7ae0f..4ba0b408 100644
--- a/imap_l3_processing/ultra/ultra_combined_nsp_initializer.py
+++ b/imap_l3_processing/ultra/ultra_combined_nsp_initializer.py
@@ -7,9 +7,9 @@
 
 from imap_l3_processing.maps.map_descriptors import (
     Sensor,
+    get_duration_from_map_descriptor,
     map_descriptor_parts_to_string,
     parse_map_descriptor,
-    get_duration_from_map_descriptor,
 )
 from imap_l3_processing.maps.map_initializer import MapInitializer, PossibleMapToProduce
 from imap_l3_processing.models import InputMetadata, VersionMap
@@ -31,13 +31,9 @@
 
 class UltraCombinedNSPInitializer(MapInitializer):
     def __init__(self):
-        l2_ultra_maps_query_results = imap_data_access.query(
-            instrument="ultra", data_level="l2"
-        )
+        l2_ultra_maps_query_results = imap_data_access.query(instrument="ultra", data_level="l2")
         self.l2_maps_by_descriptor_and_start = (
-            self.get_latest_version_by_descriptor_and_start_date(
-                l2_ultra_maps_query_results
-            )
+            self.get_latest_version_by_descriptor_and_start_date(l2_ultra_maps_query_results)
         )
         energy_bin_group_sizes_files = imap_data_access.query(
             instrument="ultra",
@@ -57,9 +53,7 @@ def furnish_spice_dependencies(self, map_to_produce: PossibleMapToProduce):
             kernel_types=ULTRA_SP_SPICE_KERNELS,
         )
 
-    def get_maps_that_can_be_produced(
-        self, descriptor: str
-    ) -> list[PossibleMapToProduce]:
+    def get_maps_that_can_be_produced(self, descriptor: str) -> list[PossibleMapToProduce]:
         descriptor_parts = parse_map_descriptor(descriptor)
         if descriptor_parts is None:
             raise ValueError(f"Invalid map descriptor: {descriptor}")
@@ -73,47 +67,35 @@ def get_maps_that_can_be_produced(
         ]
 
         first_input_descriptor = input_map_descriptors[0]
-        possible_start_dates = self.l2_maps_by_descriptor_and_start[
-            first_input_descriptor
-        ].keys()
+        possible_start_dates = self.l2_maps_by_descriptor_and_start[first_input_descriptor].keys()
 
         possible_maps_to_produce = []
         for str_start_date in possible_start_dates:
             input_map_filenames = []
             for input_descriptor in input_map_descriptors:
-                if (
-                    str_start_date
-                    in self.l2_maps_by_descriptor_and_start[input_descriptor]
-                ):
+                if str_start_date in self.l2_maps_by_descriptor_and_start[input_descriptor]:
                     input_map_filenames.append(
-                        self.l2_maps_by_descriptor_and_start[input_descriptor][
-                            str_start_date
-                        ]
+                        self.l2_maps_by_descriptor_and_start[input_descriptor][str_start_date]
                     )
 
             if len(input_map_filenames) != len(input_map_descriptors):
                 continue
 
             pset_filenames = [
-                l1c
-                for l2 in input_map_filenames
-                for l1c in self.get_l1c_parents_from_map(l2)
+                l1c for l2 in input_map_filenames for l1c in self.get_l1c_parents_from_map(l2)
             ]
 
             start_date = datetime.strptime(str_start_date, "%Y%m%d")
             possible_maps_to_produce.append(
                 PossibleMapToProduce(
                     input_files=set(
-                        pset_filenames
-                        + input_map_filenames
-                        + self.ancillary_dependencies
+                        pset_filenames + input_map_filenames + self.ancillary_dependencies
                     ),
                     input_metadata=InputMetadata(
                         instrument="ultra",
                         data_level="l3",
                         start_date=start_date,
-                        end_date=start_date
-                        + get_duration_from_map_descriptor(descriptor_parts),
+                        end_date=start_date + get_duration_from_map_descriptor(descriptor_parts),
                         version=VersionMap({}, Version(None, 1)),
                         descriptor=descriptor,
                     ),
diff --git a/imap_l3_processing/ultra/ultra_l3_dependencies.py b/imap_l3_processing/ultra/ultra_l3_dependencies.py
index 00e3447a..ef47f2cb 100644
--- a/imap_l3_processing/ultra/ultra_l3_dependencies.py
+++ b/imap_l3_processing/ultra/ultra_l3_dependencies.py
@@ -6,7 +6,6 @@
 from dataclasses import dataclass, field
 from hashlib import sha256
 from pathlib import Path
-from typing import Optional
 
 import imap_data_access
 import numpy as np
@@ -19,7 +18,7 @@
     RectangularIntensityMapData,
     SpectralIndexDependencies,
 )
-from imap_l3_processing.ultra.models import UltraL1CPSet, UltraGlowsL3eData
+from imap_l3_processing.ultra.models import UltraGlowsL3eData, UltraL1CPSet
 from imap_l3_processing.utils import (
     get_dependency_paths_by_descriptor,
     get_temp_cache_dir,
@@ -34,7 +33,7 @@ class UltraL3Dependencies:
     ultra_l2_rectangular_map: RectangularIntensityMapData
     ultra_l1c_pset: list[UltraL1CPSet]
     glows_l3e_sp: list[UltraGlowsL3eData]
-    energy_bin_group_sizes: Optional[np.ndarray]
+    energy_bin_group_sizes: np.ndarray | None
     dependency_file_paths: list[Path] = field(default_factory=list)
 
     @classmethod
@@ -52,12 +51,8 @@ def fetch_dependencies(cls, deps: ProcessingInputCollection) -> UltraL3Dependenc
         )
 
         l2_map_path = imap_data_access.download(ultra_l2_name)
-        ultra_l1c_downloaded_paths = [
-            imap_data_access.download(l1c) for l1c in ultra_l1c_names
-        ]
-        glows_l3e_download_paths = [
-            imap_data_access.download(path) for path in glows_l3e_names
-        ]
+        ultra_l1c_downloaded_paths = [imap_data_access.download(l1c) for l1c in ultra_l1c_names]
+        glows_l3e_download_paths = [imap_data_access.download(path) for path in glows_l3e_names]
 
         if energy_bin_group_sizes_names:
             energy_bin_group_sizes_path = imap_data_access.download(
@@ -79,7 +74,7 @@ def from_file_paths(
         l2_map_path: Path,
         l1c_file_paths: list[Path],
         glows_file_paths: list[Path],
-        energy_bin_path: Optional[Path],
+        energy_bin_path: Path | None,
     ) -> UltraL3Dependencies:
         ultra_l1c_data = []
         glows_l3e_data = []
@@ -91,15 +86,11 @@ def from_file_paths(
 
         l2_healpix_map_data = load_or_create_healpix_l2(l2_map_path, l1c_file_paths)
 
-        l2_rectangular_map_data = RectangularIntensityMapData.read_from_path(
-            l2_map_path
-        )
+        l2_rectangular_map_data = RectangularIntensityMapData.read_from_path(l2_map_path)
         energy_bin_group_sizes = None
         if energy_bin_path:
             paths.append(energy_bin_path)
-            energy_bin_group_sizes = np.loadtxt(
-                energy_bin_path, delimiter=",", dtype=np.uint8
-            )
+            energy_bin_group_sizes = np.loadtxt(energy_bin_path, delimiter=",", dtype=np.uint8)
 
         return cls(
             ultra_l2_healpix_map=l2_healpix_map_data,
@@ -157,26 +148,17 @@ class UltraL3CombinedDependencies:
     u90_dependencies: UltraL3Dependencies
 
     @classmethod
-    def fetch_dependencies(
-        cls, deps: ProcessingInputCollection
-    ) -> UltraL3CombinedDependencies:
+    def fetch_dependencies(cls, deps: ProcessingInputCollection) -> UltraL3CombinedDependencies:
         descriptors = ["u45", "u90", "45sensor", "90sensor", "survival-probability-ul"]
-        file_paths = get_dependency_paths_by_descriptor(
-            deps=deps, descriptors=descriptors
-        )
+        file_paths = get_dependency_paths_by_descriptor(deps=deps, descriptors=descriptors)
 
         assert len(file_paths["u45"]) == 1
         assert len(file_paths["u90"]) == 1
 
-        u45_pset_paths = [
-            imap_data_access.download(pset) for pset in file_paths["45sensor"]
-        ]
-        u90_pset_paths = [
-            imap_data_access.download(pset) for pset in file_paths["90sensor"]
-        ]
+        u45_pset_paths = [imap_data_access.download(pset) for pset in file_paths["45sensor"]]
+        u90_pset_paths = [imap_data_access.download(pset) for pset in file_paths["90sensor"]]
         glows_l3e_pset_paths = [
-            imap_data_access.download(pset)
-            for pset in file_paths["survival-probability-ul"]
+            imap_data_access.download(pset) for pset in file_paths["survival-probability-ul"]
         ]
         u45_map_path = imap_data_access.download(file_paths["u45"][0])
         u90_map_path = imap_data_access.download(file_paths["u90"][0])
@@ -208,7 +190,7 @@ def from_file_paths(
         glows_l3e_pset_paths: list[Path],
         u45_map_path: Path,
         u90_map_path: Path,
-        energy_bin_group_sizes_path: Optional[Path],
+        energy_bin_group_sizes_path: Path | None,
     ) -> UltraL3CombinedDependencies:
 
         return cls(
@@ -245,9 +227,7 @@ def load_or_create_healpix_l2(
     else:
         logger.info("Cached HEALPix L2 not found; building from pointing sets")
         l2_healpix_datasets = ultra_l2(l1c_paths_dict, descriptor=l2_descriptor)
-        l2_healpix_data = HealPixIntensityMapData.read_from_xarray(
-            l2_healpix_datasets[0]
-        )
+        l2_healpix_data = HealPixIntensityMapData.read_from_xarray(l2_healpix_datasets[0])
         logger.info("Saving HEALPix L2 to cache at %s", cache_path)
         with open(cache_path, "wb") as f:
             pickle.dump(l2_healpix_data, f)
diff --git a/imap_l3_processing/ultra/ultra_l3_to_rectangular_dependencies.py b/imap_l3_processing/ultra/ultra_l3_to_rectangular_dependencies.py
index 0ca0ec47..8484637d 100644
--- a/imap_l3_processing/ultra/ultra_l3_to_rectangular_dependencies.py
+++ b/imap_l3_processing/ultra/ultra_l3_to_rectangular_dependencies.py
@@ -1,4 +1,5 @@
 from __future__ import annotations
+
 from dataclasses import dataclass
 from pathlib import Path
 
diff --git a/imap_l3_processing/ultra/ultra_processor.py b/imap_l3_processing/ultra/ultra_processor.py
index a9d503f0..87b98906 100644
--- a/imap_l3_processing/ultra/ultra_processor.py
+++ b/imap_l3_processing/ultra/ultra_processor.py
@@ -3,9 +3,8 @@
 import re
 from dataclasses import dataclass
 from hashlib import sha256
-from typing import Optional
 
-from imap_data_access import ScienceFilePath, ImapFilePath
+from imap_data_access import ImapFilePath, ScienceFilePath
 from imap_processing.spice.geometry import SpiceFrame
 
 from imap_l3_processing.maps.map_combination import (
@@ -15,18 +14,18 @@
 from imap_l3_processing.maps.map_descriptors import (
     MapDescriptorParts,
     MapQuantity,
-    SurvivalCorrection,
-    parse_map_descriptor,
     PixelSize,
     Sensor,
+    SurvivalCorrection,
+    parse_map_descriptor,
 )
 from imap_l3_processing.maps.map_models import (
+    HealPixCoords,
     HealPixIntensityMapData,
     IntensityMapData,
-    HealPixCoords,
+    RectangularCoords,
     RectangularIntensityDataProduct,
     RectangularIntensityMapData,
-    RectangularCoords,
     RectangularSpectralIndexDataProduct,
     RectangularSpectralIndexMapData,
 )
@@ -34,24 +33,24 @@
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 from imap_l3_processing.maps.spectral_fit import (
     calculate_spectral_index_for_multiple_ranges,
-    slice_energy_range_by_bin,
     fit_spectral_index_map,
+    slice_energy_range_by_bin,
 )
 from imap_l3_processing.maps.survival_probability_processing import (
     combine_glows_l3e_with_l1c_pointing,
 )
 from imap_l3_processing.ultra.science.ultra_survival_probability import (
-    UltraSurvivalProbabilitySkyMap,
     UltraSurvivalProbability,
+    UltraSurvivalProbabilitySkyMap,
 )
 from imap_l3_processing.ultra.ultra_l3_dependencies import (
+    UltraL3CombinedDependencies,
     UltraL3Dependencies,
     UltraL3SpectralIndexDependencies,
-    UltraL3CombinedDependencies,
 )
 from imap_l3_processing.utils import (
-    save_data,
     get_temp_cache_dir,
+    save_data,
 )
 
 logger = logging.getLogger(__name__)
@@ -71,9 +70,7 @@ def process(self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000):
                 | PixelSize.SixDegrees,
             ):
                 ultra_l3_spectral_fit_dependencies = (
-                    UltraL3SpectralIndexDependencies.fetch_dependencies(
-                        self.dependencies
-                    )
+                    UltraL3SpectralIndexDependencies.fetch_dependencies(self.dependencies)
                 )
                 spectral_index_map_data = self._process_spectral_index(
                     ultra_l3_spectral_fit_dependencies,
@@ -93,10 +90,8 @@ def process(self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000):
                 | PixelSize.SixDegrees,
             ):
                 deps = UltraL3Dependencies.fetch_dependencies(self.dependencies)
-                healpix_intensity_map_data = (
-                    correct_healpix_data_for_survival_probability(
-                        deps, spice_frame_name
-                    )
+                healpix_intensity_map_data = correct_healpix_data_for_survival_probability(
+                    deps, spice_frame_name
                 )
                 data_product = self._process_healpix_intensity_to_rectangular(
                     healpix_intensity_map_data,
@@ -113,13 +108,9 @@ def process(self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000):
                 | PixelSize.FourDegrees
                 | PixelSize.SixDegrees,
             ):
-                combined_deps = UltraL3CombinedDependencies.fetch_dependencies(
-                    self.dependencies
-                )
+                combined_deps = UltraL3CombinedDependencies.fetch_dependencies(self.dependencies)
                 combined_healpix, combined_rectangular = (
-                    self._process_combined_survival_probability(
-                        combined_deps, spice_frame_name
-                    )
+                    self._process_combined_survival_probability(combined_deps, spice_frame_name)
                 )
                 data_product = self._process_healpix_intensity_to_rectangular(
                     combined_healpix,
@@ -145,21 +136,17 @@ def process(self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000):
                 deps = UltraL3CombinedDependencies.fetch_dependencies(self.dependencies)
 
                 combination_strategy = ExposureWeightedCombination()
-                combined_healpix = (
-                    combination_strategy.combine_healpix_intensity_map_data(
-                        [
-                            deps.u45_dependencies.ultra_l2_healpix_map,
-                            deps.u90_dependencies.ultra_l2_healpix_map,
-                        ]
-                    )
+                combined_healpix = combination_strategy.combine_healpix_intensity_map_data(
+                    [
+                        deps.u45_dependencies.ultra_l2_healpix_map,
+                        deps.u90_dependencies.ultra_l2_healpix_map,
+                    ]
                 )
-                combined_rectangular = (
-                    combination_strategy.combine_rectangular_intensity_map_data(
-                        [
-                            deps.u45_dependencies.ultra_l2_rectangular_map,
-                            deps.u90_dependencies.ultra_l2_rectangular_map,
-                        ]
-                    )
+                combined_rectangular = combination_strategy.combine_rectangular_intensity_map_data(
+                    [
+                        deps.u45_dependencies.ultra_l2_rectangular_map,
+                        deps.u90_dependencies.ultra_l2_rectangular_map,
+                    ]
                 )
 
                 data_product = self._process_healpix_intensity_to_rectangular(
@@ -168,12 +155,8 @@ def process(self, spice_frame_name: SpiceFrame = SpiceFrame.ECLIPJ2000):
                     parsed_descriptor.grid,
                     spice_frame_name=spice_frame_name,
                 )
-                data_product.add_paths_to_parents(
-                    deps.u45_dependencies.dependency_file_paths
-                )
-                data_product.add_paths_to_parents(
-                    deps.u90_dependencies.dependency_file_paths
-                )
+                data_product.add_paths_to_parents(deps.u45_dependencies.dependency_file_paths)
+                data_product.add_paths_to_parents(deps.u90_dependencies.dependency_file_paths)
             case _:
                 raise NotImplementedError
 
@@ -196,20 +179,18 @@ def _process_combined_survival_probability(
         combined_healpix = combination_strategy.combine_healpix_intensity_map_data(
             [u45_survival_corrected, u90_survival_corrected]
         )
-        combined_rectangular = (
-            combination_strategy.combine_rectangular_intensity_map_data(
-                [
-                    deps.u45_dependencies.ultra_l2_rectangular_map,
-                    deps.u90_dependencies.ultra_l2_rectangular_map,
-                ]
-            )
+        combined_rectangular = combination_strategy.combine_rectangular_intensity_map_data(
+            [
+                deps.u45_dependencies.ultra_l2_rectangular_map,
+                deps.u90_dependencies.ultra_l2_rectangular_map,
+            ]
         )
         return combined_healpix, combined_rectangular
 
     def _process_spectral_index(
         self,
         dependencies: UltraL3SpectralIndexDependencies,
-        spectral_index_range: Optional[tuple[int, int]],
+        spectral_index_range: tuple[int, int] | None,
     ) -> RectangularSpectralIndexMapData:
         if spectral_index_range is not None:
             start, end = spectral_index_range
@@ -233,9 +214,7 @@ def _process_healpix_intensity_to_rectangular(
         spacing_deg: int,
         spice_frame_name: SpiceFrame,
     ) -> RectangularIntensityDataProduct:
-        has_survival_data = (
-            healpix_map_data.intensity_map_data.survival_probability is not None
-        )
+        has_survival_data = healpix_map_data.intensity_map_data.survival_probability is not None
 
         variables_to_convert_to_rectangular = [
             "ena_intensity",
@@ -290,9 +269,7 @@ def _process_healpix_intensity_to_rectangular(
             ena_intensity_stat_uncert=rectangular_map_xarray_dataset[
                 "ena_intensity_stat_uncert"
             ].values,
-            ena_intensity_sys_err=rectangular_map_xarray_dataset[
-                "ena_intensity_sys_err"
-            ].values,
+            ena_intensity_sys_err=rectangular_map_xarray_dataset["ena_intensity_sys_err"].values,
             quality_flags=quality_flags,
         )
 
@@ -354,9 +331,7 @@ def correct_healpix_data_for_survival_probability(
 
     logger.info("Cached HEALPix SP-corrected data not found; building from inputs")
 
-    combined_psets = combine_glows_l3e_with_l1c_pointing(
-        deps.glows_l3e_sp, deps.ultra_l1c_pset
-    )
+    combined_psets = combine_glows_l3e_with_l1c_pointing(deps.glows_l3e_sp, deps.ultra_l1c_pset)
     survival_probability_psets = [
         UltraSurvivalProbability(_l1c, _l3e, bin_groups=deps.energy_bin_group_sizes)
         for _l1c, _l3e in combined_psets
@@ -368,17 +343,14 @@ def correct_healpix_data_for_survival_probability(
         survival_probability_psets, spice_frame_name, coords.nside
     )
     skymap_dataset = corrected_skymap.to_dataset()
-    survival_probability_map = skymap_dataset[
-        "exposure_weighted_survival_probabilities"
-    ].values
+    survival_probability_map = skymap_dataset["exposure_weighted_survival_probabilities"].values
 
     healpix_intensity_data = HealPixIntensityMapData(
         intensity_map_data=IntensityMapData(
             ena_intensity=intensity_data.ena_intensity / survival_probability_map,
             ena_intensity_stat_uncert=intensity_data.ena_intensity_stat_uncert
             / survival_probability_map,
-            ena_intensity_sys_err=intensity_data.ena_intensity_sys_err
-            / survival_probability_map,
+            ena_intensity_sys_err=intensity_data.ena_intensity_sys_err / survival_probability_map,
             epoch=intensity_data.epoch,
             epoch_delta=intensity_data.epoch_delta,
             energy=intensity_data.energy,
diff --git a/imap_l3_processing/ultra/ultra_sp_initializer.py b/imap_l3_processing/ultra/ultra_sp_initializer.py
index fba37834..9f306e3c 100644
--- a/imap_l3_processing/ultra/ultra_sp_initializer.py
+++ b/imap_l3_processing/ultra/ultra_sp_initializer.py
@@ -9,13 +9,13 @@
 )
 from imap_l3_processing.maps.map_descriptors import (
     MapDescriptorParts,
-    SurvivalCorrection,
-    Sensor,
     ReferenceFrame,
+    Sensor,
+    SurvivalCorrection,
 )
 from imap_l3_processing.maps.map_initializer import PossibleMapToProduce
 from imap_l3_processing.maps.sp_map_initializer import SPMapInitializer
-from imap_l3_processing.utils import furnish_spice_metakernel, SpiceKernelTypes
+from imap_l3_processing.utils import SpiceKernelTypes, furnish_spice_metakernel
 
 ULTRA_SP_SPICE_KERNELS = [
     SpiceKernelTypes.Leapseconds,
@@ -117,9 +117,7 @@ def furnish_spice_dependencies(self, map_to_produce: PossibleMapToProduce):
             kernel_types=ULTRA_SP_SPICE_KERNELS,
         )
 
-    def _collect_glows_psets_by_repoint(
-        self, descriptor: MapDescriptorParts
-    ) -> dict[int, str]:
+    def _collect_glows_psets_by_repoint(self, descriptor: MapDescriptorParts) -> dict[int, str]:
         if descriptor.reference_frame == ReferenceFrame.Heliospheric:
             return self.hf_glows_psets_by_repointing
         elif descriptor.reference_frame == ReferenceFrame.Spacecraft:
@@ -129,9 +127,7 @@ def _collect_glows_psets_by_repoint(
                 "Reference frame should be either Spacecraft or Heliospheric"
             )
 
-    def _get_l2_dependencies(
-        self, descriptor: MapDescriptorParts
-    ) -> list[MapDescriptorParts]:
+    def _get_l2_dependencies(self, descriptor: MapDescriptorParts) -> list[MapDescriptorParts]:
         if descriptor.sensor == Sensor.UltraCombined:
             return [
                 dataclasses.replace(
diff --git a/imap_l3_processing/utils.py b/imap_l3_processing/utils.py
index 9652b3df..b23bedf0 100644
--- a/imap_l3_processing/utils.py
+++ b/imap_l3_processing/utils.py
@@ -3,10 +3,9 @@
 import logging
 from contextlib import contextmanager
 from dataclasses import dataclass
-from datetime import datetime, date, timedelta
+from datetime import date, datetime, timedelta
 from pathlib import Path
 from tempfile import TemporaryDirectory
-from typing import Optional, Union
 from urllib.parse import urlparse
 
 import imap_data_access
@@ -19,20 +18,20 @@
 from spacepy.pycdf import CDF
 
 import imap_l3_processing
-from imap_l3_processing.cdf.cdf_utils import write_cdf, read_numeric_variable
+from imap_l3_processing.cdf.cdf_utils import read_numeric_variable, write_cdf
 from imap_l3_processing.cdf.imap_attribute_manager import ImapAttributeManager
 from imap_l3_processing.constants import TT2000_EPOCH
 from imap_l3_processing.maps.map_models import (
-    RectangularSpectralIndexMapData,
-    RectangularIntensityMapData,
     HealPixIntensityMapData,
-    RectangularSpectralIndexDataProduct,
-    RectangularIntensityDataProduct,
-    MapDataProduct,
     ISNBackgroundSubtractedDataProduct,
     ISNBackgroundSubtractedMapData,
+    MapDataProduct,
+    RectangularIntensityDataProduct,
+    RectangularIntensityMapData,
+    RectangularSpectralIndexDataProduct,
+    RectangularSpectralIndexMapData,
 )
-from imap_l3_processing.models import DataProduct, MagData, InputMetadata
+from imap_l3_processing.models import DataProduct, InputMetadata, MagData
 from imap_l3_processing.version import VERSION
 
 logger = logging.getLogger(__name__)
@@ -69,7 +68,7 @@ class SpiceKernelTypes(enum.Enum):
 def save_data(
     data: DataProduct,
     delete_if_present: bool = False,
-    folder_path: Path = None,
+    folder_path: Path | None = None,
     cr_number=None,
 ) -> Path:
     science_file_path = data.input_metadata.to_science_file_path(cr_number=cr_number)
@@ -85,18 +84,16 @@ def save_data(
         file_path.unlink(missing_ok=True)
 
     attribute_manager = ImapAttributeManager()
-    version = str(
-        data.input_metadata.version.lookup(data.input_metadata.descriptor)
-    ).replace("v", "")
+    version = str(data.input_metadata.version.lookup(data.input_metadata.descriptor)).replace(
+        "v", ""
+    )
     attribute_manager.add_global_attribute("Data_version", version)
     attribute_manager.add_instrument_attrs(
         data.input_metadata.instrument,
         data.input_metadata.data_level,
         data.input_metadata.descriptor,
     )
-    attribute_manager.add_global_attribute(
-        "Generation_date", date.today().strftime("%Y%m%d")
-    )
+    attribute_manager.add_global_attribute("Generation_date", date.today().strftime("%Y%m%d"))
     attribute_manager.add_global_attribute("Logical_source", logical_source)
     attribute_manager.add_global_attribute("Logical_file_id", logical_file_id)
     attribute_manager.add_global_attribute("ground_software_version", VERSION)
@@ -117,21 +114,15 @@ def save_data(
 
             if attribute_manager.try_load_global_metadata(logical_source) is None:
                 logical_source_global_attrs = (
-                    generate_global_metadata_for_undefined_logical_source(
-                        data.input_metadata
-                    )
-                )
-                attribute_manager.add_global_attribute(
-                    logical_source, logical_source_global_attrs
+                    generate_global_metadata_for_undefined_logical_source(data.input_metadata)
                 )
+                attribute_manager.add_global_attribute(logical_source, logical_source_global_attrs)
 
             attribute_manager.add_global_attribute(
                 "Spice_reference_frame", data.spice_frame_name.name
             )
         else:
-            raise AssertionError(
-                f"Found an unsupported map data product of type: {type(data)}"
-            )
+            raise AssertionError(f"Found an unsupported map data product of type: {type(data)}")
     elif data.parent_file_names:
         attribute_manager.add_global_attribute("Parents", data.parent_file_names)
 
@@ -205,15 +196,13 @@ def generate_global_metadata_for_undefined_logical_source(
     return logical_source_global_attrs
 
 
-def format_time(t: Optional[datetime]) -> Optional[str]:
+def format_time(t: datetime | None) -> str | None:
     if t is not None:
         return t.strftime("%Y%m%d")
     return None
 
 
-def download_external_dependency(
-    dependency_url: str, file_path: Path
-) -> Optional[Path]:
+def download_external_dependency(dependency_url: str, file_path: Path) -> Path | None:
     try:
         response = requests.get(dependency_url)
         if response.status_code == 200:
@@ -229,7 +218,7 @@ def download_external_dependency(
     return None
 
 
-def read_mag_data(cdf_path: Union[str, Path]) -> MagData:
+def read_mag_data(cdf_path: str | Path) -> MagData:
     with CDF(str(cdf_path)) as cdf:
         return MagData(
             epoch=cdf["epoch"][...],
@@ -240,16 +229,14 @@ def read_mag_data(cdf_path: Union[str, Path]) -> MagData:
 def select_mag_path(
     dependencies: ProcessingInputCollection,
     descriptor: str,
-) -> tuple[Optional[Path], Optional[str]]:
+) -> tuple[Path | None, str | None]:
     science_files = dependencies.processing_input
     for level in ("l2", "l1d"):
         match = next(
             (
                 d.imap_file_paths[0]
                 for d in science_files
-                if d.source == "mag"
-                and d.descriptor == descriptor
-                and d.data_type == level
+                if d.source == "mag" and d.descriptor == descriptor and d.data_type == level
             ),
             None,
         )
@@ -276,7 +263,7 @@ def furnish_local_spice():
 
     total_kernels = spiceypy.ktotal("ALL")
     current_kernels = []
-    for i in range(0, total_kernels):
+    for i in range(total_kernels):
         current_kernels.append(Path(spiceypy.kdata(i, "ALL")[0]).name)
 
     for file in kernels.iterdir():
@@ -286,7 +273,7 @@ def furnish_local_spice():
 
 def get_spice_parent_file_names() -> list[str]:
     count = spiceypy.ktotal("ALL")
-    return [Path(spiceypy.kdata(i, "ALL")[0]).name for i in range(0, count)]
+    return [Path(spiceypy.kdata(i, "ALL")[0]).name for i in range(count)]
 
 
 @dataclass
@@ -299,9 +286,7 @@ def get_spice_kernels_file_names(
     start_date: datetime, end_date: datetime, kernel_types: list[SpiceKernelTypes]
 ) -> list[str]:
     metakernel_url = (
-        urlparse(imap_data_access.config["DATA_ACCESS_URL"])
-        ._replace(path="metakernel")
-        .geturl()
+        urlparse(imap_data_access.config["DATA_ACCESS_URL"])._replace(path="metakernel").geturl()
     )
 
     parameters: dict = {
@@ -310,9 +295,7 @@ def get_spice_kernels_file_names(
         "end_time": f"{int((end_date - datetime(2000, 1, 1, 12)).total_seconds())}",
     }
 
-    kernels_res = requests.get(
-        metakernel_url, params={**parameters, "list_files": "true"}
-    )
+    kernels_res = requests.get(metakernel_url, params={**parameters, "list_files": "true"})
     kernels = json.loads(kernels_res.text)
 
     return kernels
@@ -324,9 +307,7 @@ def furnish_spice_metakernel(
     kernel_types: list[SpiceKernelTypes],
     metakernel_file_name: str = "metakernel.txt",
 ) -> FurnishMetakernelOutput:
-    metakernel_path = (
-        imap_data_access.config.get("DATA_DIR") / "metakernel" / metakernel_file_name
-    )
+    metakernel_path = imap_data_access.config.get("DATA_DIR") / "metakernel" / metakernel_file_name
     kernel_path = imap_data_access.config.get("DATA_DIR") / "imap" / "spice"
 
     parameters: dict = {
@@ -337,14 +318,10 @@ def furnish_spice_metakernel(
     }
 
     metakernel_url = (
-        urlparse(imap_data_access.config["DATA_ACCESS_URL"])
-        ._replace(path="metakernel")
-        .geturl()
+        urlparse(imap_data_access.config["DATA_ACCESS_URL"])._replace(path="metakernel").geturl()
     )
 
-    logger.info(
-        f"Getting SPICE Metakernel from: {metakernel_url}, with params: {parameters}"
-    )
+    logger.info(f"Getting SPICE Metakernel from: {metakernel_url}, with params: {parameters}")
 
     metakernel_res = requests.get(metakernel_url, params=parameters)
 
diff --git a/pyproject.toml b/pyproject.toml
index 7e851cea..b3154100 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -40,7 +40,7 @@ test = [
 dev = [
     "dotenv>=0.9.9",
     "pre-commit>=4.0",
-    "ruff==0.15.2",
+    "ruff==0.16.10",
 ]
 
 [tool.setuptools]
@@ -58,4 +58,6 @@ addopts = "-ra"
 
 [tool.ruff]
 target-version = "py310"
-lint.ignore = ["E741"]
+line-length = 99
+lint.ignore = ["DTZ", "E741", "LOG015"]
+lint.typing-extensions = false
diff --git a/run_local.py b/run_local.py
index 2c70197c..5ab29b18 100644
--- a/run_local.py
+++ b/run_local.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import argparse
 import logging
 import os
 import re
@@ -8,8 +9,8 @@
 from collections import defaultdict
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
-from typing import Optional, TypeVar
-from unittest.mock import patch, Mock
+from typing import TypeVar
+from unittest.mock import Mock, patch
 
 import imap_data_access
 import numpy as np
@@ -18,8 +19,8 @@
 from imap_data_access.processing_input import (
     AncillaryInput,
     ProcessingInputCollection,
-    ScienceInput,
     RepointInput,
+    ScienceInput,
 )
 from imap_processing.spice.geometry import SpiceFrame
 from spacepy.pycdf import CDF
@@ -31,9 +32,6 @@
 from imap_l3_processing.codice.l3.hi.pitch_angle.codice_pitch_angle_dependencies import (
     CodicePitchAngleDependencies,
 )
-from imap_l3_processing.codice.l3.lo.codice_lo_l3b_3d_distributions_dependencies import (
-    CodiceLoL3b3dDistributionsDependencies,
-)
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_direct_events_dependencies import (
     CodiceLoL3aDirectEventsDependencies,
 )
@@ -43,6 +41,9 @@
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_ratios_dependencies import (
     CodiceLoL3aRatiosDependencies,
 )
+from imap_l3_processing.codice.l3.lo.codice_lo_l3b_3d_distributions_dependencies import (
+    CodiceLoL3b3dDistributionsDependencies,
+)
 from imap_l3_processing.codice.l3.lo.codice_lo_processor import CodiceLoProcessor
 from imap_l3_processing.codice.l3.lo.models import CodiceLoL2SWSpeciesData
 from imap_l3_processing.codice.l3.lo.sectored_intensities.science.mass_per_charge_lookup import (
@@ -52,8 +53,8 @@
 from imap_l3_processing.glows.glows_processor import GlowsProcessor
 from imap_l3_processing.glows.l3a.glows_l3a_dependencies import GlowsL3ADependencies
 from imap_l3_processing.glows.l3a.utils import (
-    read_l2_glows_data,
     create_glows_l3a_dictionary_from_cdf,
+    read_l2_glows_data,
 )
 from imap_l3_processing.glows.l3bc.glows_l3bc_dependencies import GlowsL3BCDependencies
 from imap_l3_processing.glows.l3d.glows_l3d_dependencies import GlowsL3DDependencies
@@ -80,15 +81,15 @@
 from imap_l3_processing.lo.l3.lo_l3_spectral_fit_dependencies import (
     LoL3SpectralFitDependencies,
 )
-from imap_l3_processing.lo.lo_processor import perform_spectral_fit, LoProcessor
+from imap_l3_processing.lo.lo_processor import LoProcessor, perform_spectral_fit
 from imap_l3_processing.maps.hilo_l3_survival_dependencies import (
-    HiLoL3SurvivalDependencies,
     HiL3SingleSensorFullSpinDependencies,
+    HiLoL3SurvivalDependencies,
 )
 from imap_l3_processing.maps.map_models import (
-    RectangularSpectralIndexDataProduct,
     RectangularIntensityDataProduct,
     RectangularIntensityMapData,
+    RectangularSpectralIndexDataProduct,
 )
 from imap_l3_processing.models import InputMetadata
 from imap_l3_processing.swapi.l3a.science.pickup_ion.density_of_neutral_helium_lookup_table import (
@@ -96,17 +97,17 @@
 )
 from imap_l3_processing.swapi.l3a.swapi_l3a_dependencies import SwapiL3ADependencies
 from imap_l3_processing.swapi.l3a.utils import read_l2_swapi_data
-from imap_l3_processing.swapi.response.efficiency_calibration_table import (
-    EfficiencyCalibrationTable,
-)
 from imap_l3_processing.swapi.l3b.science.geometric_factor_calibration_table import (
     GeometricFactorCalibrationTable,
 )
 from imap_l3_processing.swapi.l3b.swapi_l3b_dependencies import SwapiL3BDependencies
+from imap_l3_processing.swapi.response.efficiency_calibration_table import (
+    EfficiencyCalibrationTable,
+)
 from imap_l3_processing.swapi.swapi_processor import SwapiProcessor
 from imap_l3_processing.swe.l3.swe_l3_dependencies import SweL3Dependencies
 from imap_l3_processing.swe.swe_processor import SweProcessor
-from imap_l3_processing.ultra.models import UltraL1CPSet, UltraGlowsL3eData
+from imap_l3_processing.ultra.models import UltraGlowsL3eData, UltraL1CPSet
 from imap_l3_processing.ultra.ultra_l3_dependencies import (
     UltraL3Dependencies,
     UltraL3SpectralIndexDependencies,
@@ -115,7 +116,7 @@
     UltraProcessor,
     correct_healpix_data_for_survival_probability,
 )
-from imap_l3_processing.utils import save_data, read_mag_data, furnish_local_spice
+from imap_l3_processing.utils import furnish_local_spice, read_mag_data, save_data
 from scripts.codice.create_fake_efficiency_ancillary import create_efficiency_lookup
 from scripts.codice.create_more_accurate_l3a_direct_event import (
     create_more_accurate_l3a_direct_events_cdf,
@@ -129,10 +130,10 @@
     create_l1c_and_glows_with_matching_date_range,
 )
 from tests.test_helpers import (
+    get_imap_data_dir_path,
     get_test_data_path,
     get_test_instrument_team_data_path,
     try_get_many_run_local_paths,
-    get_imap_data_dir_path,
 )
 
 
@@ -165,7 +166,7 @@ def create_codice_lo_l3a_partial_densities_cdf():
 
 
 def create_codice_lo_l3a_direct_events_cdf(
-    l1a_paths: Optional[tuple[Path, Path]] = None,
+    l1a_paths: tuple[Path, Path] | None = None,
 ) -> Path:
     codice_lo_l2_direct_event_cdf_path = modify_l2_direct_events(
         get_test_instrument_team_data_path(
@@ -264,11 +265,9 @@ def create_codice_lo_l3b_3d_distributions_cdf(species: str):
         ),
     )
 
-    codice_lo_l3a_direct_event_path = Path(
-        create_codice_lo_l3a_direct_events_cdf(l1a_paths)
-    )
-    accurate_codice_lo_l3a_direct_event_path = (
-        create_more_accurate_l3a_direct_events_cdf(codice_lo_l3a_direct_event_path)
+    codice_lo_l3a_direct_event_path = Path(create_codice_lo_l3a_direct_events_cdf(l1a_paths))
+    accurate_codice_lo_l3a_direct_event_path = create_more_accurate_l3a_direct_events_cdf(
+        codice_lo_l3a_direct_event_path
     )
 
     codice_lo_l1a_nsw_priority_path, codice_lo_l1a_sw_priority_path = l1a_paths
@@ -278,14 +277,10 @@ def create_codice_lo_l3b_3d_distributions_cdf(species: str):
         l1a_sw_file_path=codice_lo_l1a_sw_priority_path,
         l1a_nsw_file_path=codice_lo_l1a_nsw_priority_path,
         mass_species_bin_lut=(
-            get_test_data_path(
-                "codice/imap_codice_lo-mass-species-bin-lookup_20241110_v001.csv"
-            )
+            get_test_data_path("codice/imap_codice_lo-mass-species-bin-lookup_20241110_v001.csv")
         ),
         geometric_factors_lut=(
-            get_test_data_path(
-                "codice/imap_codice_lo-geometric-factors_20241110_v001.csv"
-            )
+            get_test_data_path("codice/imap_codice_lo-geometric-factors_20241110_v001.csv")
         ),
         efficiency_factors_lut=(create_efficiency_lookup(species)),
         energy_per_charge_lut=get_test_data_path(
@@ -308,12 +303,8 @@ def create_codice_lo_l3b_3d_distributions_cdf(species: str):
     return save_data(l3b_3d_distributions, delete_if_present=True)
 
 
-def create_swapi_l3b_cdf(
-    geometric_calibration_file, efficiency_calibration_file, cdf_file
-):
-    geometric_calibration = GeometricFactorCalibrationTable.from_file(
-        geometric_calibration_file
-    )
+def create_swapi_l3b_cdf(geometric_calibration_file, efficiency_calibration_file, cdf_file):
+    geometric_calibration = GeometricFactorCalibrationTable.from_file(geometric_calibration_file)
     efficiency_calibration = EfficiencyCalibrationTable(efficiency_calibration_file)
     swapi_cdf_data = CDF(cdf_file)
     swapi_data = read_l2_swapi_data(swapi_cdf_data)
@@ -349,9 +340,7 @@ def create_swapi_l3a_cdf(
     mock_light_time = 122.0
     mock_spice.spkezr.return_value = (np.array([0, 0, 0, 0, 0, 0]), mock_light_time)
     mock_spice.latrec.return_value = np.array([0, 2, 0])
-    mock_spice.reclat.return_value = np.array(
-        [0.99 * ONE_AU_IN_KM, np.deg2rad(255.7), 0.6]
-    )
+    mock_spice.reclat.return_value = np.array([0.99 * ONE_AU_IN_KM, np.deg2rad(255.7), 0.6])
 
     def mock_sxform(from_frame, to_frame, et):
         if from_frame == "IMAP_SWAPI":
@@ -369,13 +358,9 @@ def mock_sxform(from_frame, to_frame, et):
 
     mock_spice.sxform.side_effect = mock_sxform
 
-    efficiency_calibration_table = EfficiencyCalibrationTable(
-        imap_swapi_efficiency_lut_file
-    )
-    density_of_neutral_helium_calibration_table = (
-        DensityOfNeutralHeliumLookupTable.from_file(
-            density_of_neutral_helium_calibration_file
-        )
+    efficiency_calibration_table = EfficiencyCalibrationTable(imap_swapi_efficiency_lut_file)
+    density_of_neutral_helium_calibration_table = DensityOfNeutralHeliumLookupTable.from_file(
+        density_of_neutral_helium_calibration_file
     )
     swapi_cdf_data = CDF(cdf_file)
     swapi_data = read_l2_swapi_data(swapi_cdf_data)
@@ -421,17 +406,14 @@ def create_swe_product(dependencies: SweL3Dependencies) -> Path:
 
 
 @patch("imap_l3_processing.swe.l3.science.moment_calculations.spiceypy.pxform")
-def create_swe_product_with_fake_spice(
-    dependencies: SweL3Dependencies, mock_spice_pxform
-) -> Path:
+def create_swe_product_with_fake_spice(dependencies: SweL3Dependencies, mock_spice_pxform) -> Path:
     data = np.loadtxt(get_test_data_path("swe/ace_attitude.dat"), skiprows=1)
 
     def time_to_float(t):
         return (t - datetime(1999, 1, 1, tzinfo=timezone.utc)).total_seconds()
 
     times = [
-        datetime(1998, 12, 31, tzinfo=timezone.utc)
-        + timedelta(days=row[1], seconds=row[2])
+        datetime(1998, 12, 31, tzinfo=timezone.utc) + timedelta(days=row[1], seconds=row[2])
         for row in data
     ]
     times_as_floats = [time_to_float(t) for t in times]
@@ -490,13 +472,9 @@ def create_survival_corrected_full_spin_cdf(
         descriptor="h90-ena-h-sf-sp-full-hae-4deg-1yr",
     )
     processor = HiProcessor(Mock(), input_metadata)
-    output_data = processor.process_full_spin_single_sensor(
-        dependencies, SpiceFrame.ECLIPJ2000
-    )
+    output_data = processor.process_full_spin_single_sensor(dependencies, SpiceFrame.ECLIPJ2000)
 
-    data_product = RectangularIntensityDataProduct(
-        data=output_data, input_metadata=input_metadata
-    )
+    data_product = RectangularIntensityDataProduct(data=output_data, input_metadata=input_metadata)
     cdf_path = save_data(data_product, delete_if_present=True)
     return cdf_path
 
@@ -554,24 +532,12 @@ def create_hit_sectored_cdf(dependencies: HITL3SectoredDependencies) -> Path:
 
 def create_hit_direct_event_cdf():
     cosine_table = CosineCorrectionLookupTable(
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-2A-cosine-lookup_20250203_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-2B-cosine-lookup_20250203_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-3A-cosine-lookup_20250203_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-3B-cosine-lookup_20250203_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-4A-cosine-lookup_20250203_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-4B-cosine-lookup_20250203_v000.csv"
-        ),
+        get_test_data_path("hit/pha_events/imap_hit_range-2A-cosine-lookup_20250203_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-2B-cosine-lookup_20250203_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-3A-cosine-lookup_20250203_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-3B-cosine-lookup_20250203_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-4A-cosine-lookup_20250203_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-4B-cosine-lookup_20250203_v000.csv"),
     )
     gain_table = GainLookupTable.from_file(
         get_test_data_path("hit/pha_events/imap_hit_hi-gain-lookup_20250203_v000.csv"),
@@ -579,30 +545,16 @@ def create_hit_direct_event_cdf():
     )
 
     range_fit_lookup = RangeFitLookup.from_files(
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-2A-charge-fit-lookup_20250319_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-3A-charge-fit-lookup_20250319_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-4A-charge-fit-lookup_20250319_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-2B-charge-fit-lookup_20250319_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-3B-charge-fit-lookup_20250319_v000.csv"
-        ),
-        get_test_data_path(
-            "hit/pha_events/imap_hit_range-4B-charge-fit-lookup_20250319_v000.csv"
-        ),
+        get_test_data_path("hit/pha_events/imap_hit_range-2A-charge-fit-lookup_20250319_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-3A-charge-fit-lookup_20250319_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-4A-charge-fit-lookup_20250319_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-2B-charge-fit-lookup_20250319_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-3B-charge-fit-lookup_20250319_v000.csv"),
+        get_test_data_path("hit/pha_events/imap_hit_range-4B-charge-fit-lookup_20250319_v000.csv"),
     )
 
     event_type_look = HitEventTypeLookup.from_csv(
-        get_test_data_path(
-            "hit/pha_events/imap_hit_hit-event-type-lookup_20250228_v000.csv"
-        )
+        get_test_data_path("hit/pha_events/imap_hit_hit-event-type-lookup_20250228_v000.csv")
     )
 
     hit_l1_data = HitL1Data.read_from_cdf(
@@ -632,13 +584,9 @@ def create_hit_direct_event_cdf():
 
 
 @patch("imap_l3_processing.glows.glows_initializer.query")
-@patch(
-    "imap_l3_processing.glows.l3bc.glows_l3bc_dependencies.download_dependency_from_path"
-)
+@patch("imap_l3_processing.glows.l3bc.glows_l3bc_dependencies.download_dependency_from_path")
 @patch("imap_l3_processing.glows.glows_processor.imap_data_access")
-@patch(
-    "imap_l3_processing.glows.l3bc.glows_initializer_ancillary_dependencies.download"
-)
+@patch("imap_l3_processing.glows.l3bc.glows_initializer_ancillary_dependencies.download")
 @patch(
     "imap_l3_processing.glows.l3bc.glows_initializer_ancillary_dependencies.download_external_dependency"
 )
@@ -663,9 +611,7 @@ def run_l3b_initializer(
     mock_query.side_effect = [l3a_dicts, []]
 
     mock_download.side_effect = [
-        get_test_data_path(
-            "glows/imap_glows_pipeline-settings-l3bcde_20250423_v001.json"
-        ),
+        get_test_data_path("glows/imap_glows_pipeline-settings-l3bcde_20250423_v001.json"),
         get_test_data_path("glows/imap_2026_105_01.repoint.csv"),
     ]
 
@@ -681,9 +627,7 @@ def run_l3b_initializer(
         get_test_data_path("glows/imap_glows_uv-anisotropy-1CR_20100101_v001.json"),
         get_test_data_path("glows/imap_glows_WawHelioIonMP_20100101_v002.json"),
         get_test_data_path("glows/imap_glows_bad-days-list_20100101_v004.dat"),
-        get_test_data_path(
-            "glows/imap_glows_pipeline-settings-l3bcde_20250423_v001.json"
-        ),
+        get_test_data_path("glows/imap_glows_pipeline-settings-l3bcde_20250423_v001.json"),
         get_test_data_path(
             "glows/pipeline/l3a/imap_glows_l3a_hist_20250625-repoint01071_v001.cdf"
         ),
@@ -693,9 +637,7 @@ def run_l3b_initializer(
         get_test_data_path("glows/imap_glows_uv-anisotropy-1CR_20100101_v001.json"),
         get_test_data_path("glows/imap_glows_WawHelioIonMP_20100101_v002.json"),
         get_test_data_path("glows/imap_glows_bad-days-list_20100101_v004.dat"),
-        get_test_data_path(
-            "glows/imap_glows_pipeline-settings-l3bcde_20250423_v001.json"
-        ),
+        get_test_data_path("glows/imap_glows_pipeline-settings-l3bcde_20250423_v001.json"),
         get_test_data_path(
             "glows/pipeline/l3a/imap_glows_l3a_hist_20100521-repoint00289_v001.cdf"
         ),
@@ -707,9 +649,7 @@ def run_l3b_initializer(
     bad_days_list = AncillaryInput("imap_glows_bad-days-list_20100101_v004.dat")
     waw_helio_ion = AncillaryInput("imap_glows_WawHelioIonMP_20100101_v002.json")
     uv_anisotropy = AncillaryInput("imap_glows_uv-anisotropy-1CR_20100101_v001.json")
-    pipeline_settings = AncillaryInput(
-        "imap_glows_pipeline-settings-l3bcde_20250423_v001.json"
-    )
+    pipeline_settings = AncillaryInput("imap_glows_pipeline-settings-l3bcde_20250423_v001.json")
 
     repointings = RepointInput("imap_2026_105_01.repoint.csv")
 
@@ -759,16 +699,12 @@ def run_glows_l3bc_processor_and_initializer(mock_query):
     bad_days_list = AncillaryInput("imap_glows_bad-days-list_20100101_v001.dat")
     waw_helio_ion = AncillaryInput("imap_glows_WawHelioIonMP_20100101_v002.json")
     uv_anisotropy = AncillaryInput("imap_glows_uv-anisotropy-1CR_20300101_v003.json")
-    pipeline_settings = AncillaryInput(
-        "imap_glows_pipeline-settings-l3bcde_20100101_v006.json"
-    )
+    pipeline_settings = AncillaryInput("imap_glows_pipeline-settings-l3bcde_20100101_v006.json")
     input_collection = ProcessingInputCollection(
         bad_days_list, waw_helio_ion, uv_anisotropy, pipeline_settings
     )
 
-    processor = GlowsProcessor(
-        dependencies=input_collection, input_metadata=input_metadata
-    )
+    processor = GlowsProcessor(dependencies=input_collection, input_metadata=input_metadata)
     print(processor.process())
 
 
@@ -788,9 +724,7 @@ def run_glows_l3e_lo_with_mocks(
         Path("instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/EnGridUltra.dat"),
         Path("instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/tessXYZ8.dat"),
         Path("instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/tessAng16.dat"),
-        Path(
-            "instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/lyaSeriesV4_2021b.dat"
-        ),
+        Path("instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/lyaSeriesV4_2021b.dat"),
         Path(
             "instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/solar_uv_anisotropy_NP.1.0_SP.1.0.dat"
         ),
@@ -803,12 +737,8 @@ def run_glows_l3e_lo_with_mocks(
         Path(
             "instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/phion_Hydrogen_T12F107_2021b.dat"
         ),
-        Path(
-            "instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/swEqtrElectrons5_2021b.dat"
-        ),
-        Path(
-            "instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/ionization.files.dat"
-        ),
+        Path("instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/swEqtrElectrons5_2021b.dat"),
+        Path("instrument_team_data/glows/GLOWS_L3d_to_L3e_processing/ionization.files.dat"),
         pipeline_settings={
             "executable_dependency_paths": {
                 "energy-grid-lo": "EnGridLo.dat",
@@ -838,16 +768,8 @@ def run_glows_l3e_lo_with_mocks(
 
     mock_path.side_effect = [
         # Path(get_test_instrument_team_data_path("glows/probSur.Imap.Lo_20090101_010101_2009.000_60.00.txt")),
-        Path(
-            get_test_instrument_team_data_path(
-                "glows/probSur.Imap.Hi_2009.000_135.0.txt"
-            )
-        ),
-        Path(
-            get_test_instrument_team_data_path(
-                "glows/probSur.Imap.Hi_2009.000_90.00.txt"
-            )
-        ),
+        Path(get_test_instrument_team_data_path("glows/probSur.Imap.Hi_2009.000_135.0.txt")),
+        Path(get_test_instrument_team_data_path("glows/probSur.Imap.Hi_2009.000_90.00.txt")),
         Path(
             get_test_instrument_team_data_path(
                 "glows/probSur.Imap.Ul_20090101_010101_2009.000.txt"
@@ -1011,9 +933,7 @@ def make_glows_l3a_files():
 
 
 def run_glows_l3a(file_path):
-    date_in_path = re.search(r"imap_glows_l2_hist_(\d{8}).*.cdf", file_path.name).group(
-        1
-    )
+    date_in_path = re.search(r"imap_glows_l2_hist_(\d{8}).*.cdf", file_path.name).group(1)
     start_date = datetime.strptime(date_in_path, "%Y%m%d")
     end_date = start_date + timedelta(days=1)
     input_metadata = InputMetadata(
@@ -1053,9 +973,7 @@ def run_glows_l3a(file_path):
         l3a_data = processor.process_l3a(dependencies)
 
         glows_l3a_temp_path = TEMP_CDF_FOLDER_PATH / "glows" / "l3a"
-        print(
-            save_data(l3a_data, folder_path=glows_l3a_temp_path, delete_if_present=True)
-        )
+        print(save_data(l3a_data, folder_path=glows_l3a_temp_path, delete_if_present=True))
 
 
 def run_glows_l3bc():
@@ -1070,9 +988,7 @@ def run_glows_l3bc():
     cr = 2091
     external_files = {
         "f107_raw_data": get_test_instrument_team_data_path("glows/f107_fluxtable.txt"),
-        "omni_raw_data": get_test_instrument_team_data_path(
-            "glows/omni2_all_years.dat"
-        ),
+        "omni_raw_data": get_test_instrument_team_data_path("glows/omni2_all_years.dat"),
     }
     ancillary_files = {
         "uv_anisotropy": get_test_data_path(
@@ -1089,18 +1005,14 @@ def run_glows_l3bc():
     l3a_data_folder_path = get_test_data_path("glows/l3a_products")
     l3a_data = []
     l3a_file_names = [
-        f"imap_glows_l3a_hist_201004{x}-repoint{x + 90:05d}_v012.cdf"
-        for x in range(22, 31)
+        f"imap_glows_l3a_hist_201004{x}-repoint{x + 90:05d}_v012.cdf" for x in range(22, 31)
     ]
     l3a_file_names += [
-        f"imap_glows_l3a_hist_201005{x:02d}-repoint{x + 120:05d}_v012.cdf"
-        for x in range(1, 19)
+        f"imap_glows_l3a_hist_201005{x:02d}-repoint{x + 120:05d}_v012.cdf" for x in range(1, 19)
     ]
 
     for name in l3a_file_names:
-        l3a_data.append(
-            create_glows_l3a_dictionary_from_cdf(l3a_data_folder_path / name)
-        )
+        l3a_data.append(create_glows_l3a_dictionary_from_cdf(l3a_data_folder_path / name))
 
     dependencies = GlowsL3BCDependencies(
         l3a_data=l3a_data,
@@ -1154,9 +1066,7 @@ def run_glows_l3d(mock_shutil):
             "phion": get_test_instrument_team_data_path(
                 "glows/imap_glows_photoion-2010a_v003.dat"
             ),
-            "lya": get_test_instrument_team_data_path(
-                "glows/imap_glows_lya-2010a_v003.dat"
-            ),
+            "lya": get_test_instrument_team_data_path("glows/imap_glows_lya-2010a_v003.dat"),
             "e-dens": get_test_instrument_team_data_path(
                 "glows/imap_glows_electron-density-2010a_v003.dat"
             ),
@@ -1167,21 +1077,13 @@ def run_glows_l3d(mock_shutil):
     }
 
     l3b_file_paths = [
-        get_test_data_path(
-            "glows/pipeline/l3b/imap_glows_l3b_ion-rate-profile_20100103_v001.cdf"
-        ),
-        get_test_data_path(
-            "glows/pipeline/l3b/imap_glows_l3b_ion-rate-profile_20100519_v001.cdf"
-        ),
+        get_test_data_path("glows/pipeline/l3b/imap_glows_l3b_ion-rate-profile_20100103_v001.cdf"),
+        get_test_data_path("glows/pipeline/l3b/imap_glows_l3b_ion-rate-profile_20100519_v001.cdf"),
     ]
 
     l3c_file_paths = [
-        get_test_data_path(
-            "glows/pipeline/l3c/imap_glows_l3c_sw-profile_20100103_v001.cdf"
-        ),
-        get_test_data_path(
-            "glows/pipeline/l3c/imap_glows_l3c_sw-profile_20100519_v001.cdf"
-        ),
+        get_test_data_path("glows/pipeline/l3c/imap_glows_l3c_sw-profile_20100103_v001.cdf"),
+        get_test_data_path("glows/pipeline/l3c/imap_glows_l3c_sw-profile_20100519_v001.cdf"),
     ]
 
     l3d_dependencies: GlowsL3DDependencies = GlowsL3DDependencies(
@@ -1192,9 +1094,7 @@ def run_glows_l3d(mock_shutil):
     )
 
     processor = GlowsProcessor(ProcessingInputCollection(), input_metadata)
-    data_product, l3d_txt_paths, last_processed_cr = processor.process_l3d(
-        l3d_dependencies
-    )
+    data_product, l3d_txt_paths, last_processed_cr = processor.process_l3d(l3d_dependencies)
     print("l3d_txts:")
     [print(txt_path) for txt_path in l3d_txt_paths]
     print(save_data(data_product, cr_number=last_processed_cr))
@@ -1202,18 +1102,14 @@ def run_glows_l3d(mock_shutil):
 
 def create_empty_hi_l1c_dataset(
     epoch: datetime,
-    exposures: Optional[np.ndarray] = None,
-    spin_angles: Optional[np.ndarray] = None,
-    energies: Optional[np.ndarray] = None,
+    exposures: np.ndarray | None = None,
+    spin_angles: np.ndarray | None = None,
+    energies: np.ndarray | None = None,
 ):
     energies = energies if energies is not None else np.geomspace(1, 10000, 9)
-    spin_angles = (
-        spin_angles if spin_angles is not None else np.arange(0, 360, 0.1) + 0.05
-    )
+    spin_angles = spin_angles if spin_angles is not None else np.arange(0, 360, 0.1) + 0.05
     exposures = (
-        exposures
-        if exposures is not None
-        else np.ones(shape=(1, len(energies), len(spin_angles)))
+        exposures if exposures is not None else np.ones(shape=(1, len(energies), len(spin_angles)))
     )
 
     return xr.Dataset(
@@ -1234,8 +1130,8 @@ def create_empty_hi_l1c_dataset(
 def create_empty_glows_l3e_dataset(
     epoch: datetime,
     survival_probabilities: np.ndarray,
-    spin_angles: Optional[np.ndarray] = None,
-    energies: Optional[np.ndarray] = None,
+    spin_angles: np.ndarray | None = None,
+    energies: np.ndarray | None = None,
 ):
     energies = energies or np.geomspace(1, 10000, 16)
     spin_angles = spin_angles or np.arange(0, 360, 1) + 0.5
@@ -1263,20 +1159,12 @@ def create_empty_glows_l3e_dataset(
 
 def read_glows_survival_probability_data_from_cdf() -> tuple[np.ndarray, np.ndarray]:
     l3e = CDF(
-        str(
-            get_test_data_path(
-                "glows/imap_glows_l3e_survival-probabilities-hi_20250324_v001.cdf"
-            )
-        )
+        str(get_test_data_path("glows/imap_glows_l3e_survival-probabilities-hi_20250324_v001.cdf"))
     )
-    return l3e["probability_of_survival"][...][:, 0], l3e["probability_of_survival"][
-        ...
-    ][:, 1]
+    return l3e["probability_of_survival"][...][:, 0], l3e["probability_of_survival"][...][:, 1]
 
 
-@patch(
-    "imap_l3_processing.hi.hi_processor.HiLoL3SurvivalDependencies.fetch_dependencies"
-)
+@patch("imap_l3_processing.hi.hi_processor.HiLoL3SurvivalDependencies.fetch_dependencies")
 def create_hi_l3_survival_corrected_cdf(
     survival_dependencies: HiLoL3SurvivalDependencies,
     spacing_degree: int,
@@ -1299,9 +1187,7 @@ def create_hi_l3_survival_corrected_cdf(
     print(processor.process())
 
 
-@patch(
-    "imap_l3_processing.lo.lo_processor.HiLoL3SurvivalDependencies.fetch_dependencies"
-)
+@patch("imap_l3_processing.lo.lo_processor.HiLoL3SurvivalDependencies.fetch_dependencies")
 def create_lo_l3_survival_corrected_cdf(
     survival_dependencies: HiLoL3SurvivalDependencies,
     spacing_degree: int,
@@ -1344,18 +1230,14 @@ def create_codice_hi_l3a_direct_events_cdf():
     )
 
     codice_lo_processor = CodiceHiProcessor(ProcessingInputCollection(), input_metadata)
-    direct_event_data = codice_lo_processor.process_l3a_direct_event(
-        codice_hi_de_dependencies
-    )
+    direct_event_data = codice_lo_processor.process_l3a_direct_event(codice_hi_de_dependencies)
     cdf_path = save_data(direct_event_data, delete_if_present=True)
     return cdf_path
 
 
 def create_codice_hi_l3b_pitch_angles_cdf():
     codice_hi_pitch_angle_dependencies = CodicePitchAngleDependencies.from_file_paths(
-        mag_file_path=get_test_data_path(
-            "mag/imap_mag_l1d_norm-mago_20250814_v003.cdf"
-        ),
+        mag_file_path=get_test_data_path("mag/imap_mag_l1d_norm-mago_20250814_v003.cdf"),
         codice_l2_sectored_intensities_path=get_test_instrument_team_data_path(
             "codice/hi/imap_codice_l2_hi-sectored_20250814_v002.cdf"
         ),
@@ -1371,9 +1253,7 @@ def create_codice_hi_l3b_pitch_angles_cdf():
     )
 
     codice_hi_processor = CodiceHiProcessor(ProcessingInputCollection(), input_metadata)
-    pitch_angle_data = codice_hi_processor.process_l3b(
-        codice_hi_pitch_angle_dependencies
-    )
+    pitch_angle_data = codice_hi_processor.process_l3b(codice_hi_pitch_angle_dependencies)
     cdf_path = save_data(pitch_angle_data, delete_if_present=True)
     return cdf_path
 
@@ -1381,18 +1261,17 @@ def create_codice_hi_l3b_pitch_angles_cdf():
 if __name__ == "__main__":
     furnish_local_spice()
     logging.basicConfig(force=True, level=logging.INFO)
-    if "codice-lo" in sys.argv:
-        if "l3a" in sys.argv:
-            if "partial-densities" in sys.argv:
-                print(create_codice_lo_l3a_partial_densities_cdf())
-            elif "direct-events" in sys.argv:
-                print(create_codice_lo_l3a_direct_events_cdf())
-            elif "ratios" in sys.argv:
-                print(create_codice_lo_l3a_ratios_cdf())
-            elif "abundances" in sys.argv:
-                print(create_codice_lo_l3a_abundances_cdf())
-            elif "3d-instrument-frame" in sys.argv:
-                print(create_codice_lo_l3b_3d_distributions_cdf(sys.argv[-1]))
+    if "codice-lo" in sys.argv and "l3a" in sys.argv:
+        if "partial-densities" in sys.argv:
+            print(create_codice_lo_l3a_partial_densities_cdf())
+        elif "direct-events" in sys.argv:
+            print(create_codice_lo_l3a_direct_events_cdf())
+        elif "ratios" in sys.argv:
+            print(create_codice_lo_l3a_ratios_cdf())
+        elif "abundances" in sys.argv:
+            print(create_codice_lo_l3a_abundances_cdf())
+        elif "3d-instrument-frame" in sys.argv:
+            print(create_codice_lo_l3b_3d_distributions_cdf(sys.argv[-1]))
 
     if "codice-hi" in sys.argv:
         if "l3a" in sys.argv:
@@ -1403,37 +1282,21 @@ def create_codice_hi_l3b_pitch_angles_cdf():
     if "swapi" in sys.argv:
         if "l3a" in sys.argv:
             paths = create_swapi_l3a_cdf(
-                str(
-                    get_test_data_path(
-                        "swapi/imap_swapi_energy-gf-pui-lut_20100101_v001.csv"
-                    )
-                ),
+                str(get_test_data_path("swapi/imap_swapi_energy-gf-pui-lut_20100101_v001.csv")),
                 str(
                     get_test_data_path(
                         "swapi/imap_swapi_l2_density-of-neutral-helium-lut-text-not-cdf_20241023_v002.cdf"
                     )
                 ),
-                str(
-                    get_test_data_path(
-                        "swapi/imap_swapi_efficiency-lut_20241020_v002.dat"
-                    )
-                ),
-                str(
-                    get_test_data_path(
-                        "swapi/imap_swapi_l2_50-sweeps_20250606_v003.cdf"
-                    )
-                ),
+                str(get_test_data_path("swapi/imap_swapi_efficiency-lut_20241020_v002.dat")),
+                str(get_test_data_path("swapi/imap_swapi_l2_50-sweeps_20250606_v003.cdf")),
             )
             print(paths)
         if "l3b" in sys.argv:
             path = create_swapi_l3b_cdf(
                 "tests/test_data/swapi/imap_swapi_energy-gf-sw-lut_20100101_v001.csv",
                 "tests/test_data/swapi/imap_swapi_efficiency-lut_20241020_v002.dat",
-                str(
-                    get_test_data_path(
-                        "swapi/imap_swapi_l2_50-sweeps_20250606_v003.cdf"
-                    )
-                ),
+                str(get_test_data_path("swapi/imap_swapi_l2_50-sweeps_20250606_v003.cdf")),
             )
             print(path)
     if "glows" in sys.argv:
@@ -1453,7 +1316,7 @@ def create_codice_hi_l3b_pitch_angles_cdf():
         elif "l3a" in sys.argv:
             make_glows_l3a_files()
         else:
-            raise Exception("level not specified")
+            raise argparse.ArgumentError("level not specified")
 
     if "hit" in sys.argv:
         if "direct_event" in sys.argv:
@@ -1467,9 +1330,7 @@ def create_codice_hi_l3b_pitch_angles_cdf():
                 r"C:\Users\Petty\Downloads\HIT Validation-20250922T131655Z-1-001\HIT Validation\imap_hit_l2_macropixel-intensity_20100106_v001.cdf"
             )
             dependencies = HITL3SectoredDependencies(mag_data=mag_data, data=hit_data)
-            print(
-                f"hit macropixel data product: {create_hit_sectored_cdf(dependencies)}"
-            )
+            print(f"hit macropixel data product: {create_hit_sectored_cdf(dependencies)}")
 
     if "swe" in sys.argv:
         dependencies = SweL3Dependencies.from_file_paths(
@@ -1572,9 +1433,7 @@ def create_codice_hi_l3b_pitch_angles_cdf():
             print(create_lo_spectral_index_cdf(dependencies))
 
         if do_all or "survival_probabilities" in sys.argv:
-            glows_l3e_folder = get_test_data_path(
-                "hi/fake_l3e_survival_probabilities/90"
-            )
+            glows_l3e_folder = get_test_data_path("hi/fake_l3e_survival_probabilities/90")
             glows_l3_paths = list(glows_l3e_folder.iterdir())
 
             missing_paths, run_local_paths = try_get_many_run_local_paths(
@@ -1645,9 +1504,7 @@ def create_codice_hi_l3b_pitch_angles_cdf():
                 UltraL1CPSet.read_from_path(l1c_dependency_path)
                 for l1c_dependency_path in l1c_dependency_paths
             ]
-            l3e_dependencies = [
-                UltraGlowsL3eData.read_from_path(path) for path in l3e_glows_paths
-            ]
+            l3e_dependencies = [UltraGlowsL3eData.read_from_path(path) for path in l3e_glows_paths]
 
             dependencies = UltraL3Dependencies.from_file_paths(
                 l2_map_path, l1c_dependency_paths, l3e_glows_paths
@@ -1656,12 +1513,10 @@ def create_codice_hi_l3b_pitch_angles_cdf():
             healpix_sp_corrected_data = correct_healpix_data_for_survival_probability(
                 deps=dependencies, spice_frame_name=SpiceFrame.IMAP_HAE
             )
-            rectangular_sp_data_product = (
-                processor._process_healpix_intensity_to_rectangular(
-                    healpix_sp_corrected_data,
-                    spacing_degree,
-                    spice_frame_name=SpiceFrame.IMAP_HAE,
-                )
+            rectangular_sp_data_product = processor._process_healpix_intensity_to_rectangular(
+                healpix_sp_corrected_data,
+                spacing_degree,
+                spice_frame_name=SpiceFrame.IMAP_HAE,
             )
 
             rectangular_sp_corrected_path = save_data(
@@ -1689,9 +1544,7 @@ def create_codice_hi_l3b_pitch_angles_cdf():
                 descriptor=f"u90-spx-h-sf-sp-full-hae-{spacing_degree}deg-6mo",
             )
 
-            processor = UltraProcessor(
-                input_metadata=processor_input_metadata, dependencies=None
-            )
+            processor = UltraProcessor(input_metadata=processor_input_metadata, dependencies=None)
 
             spectral_index_map_data = processor._process_spectral_index(dependencies)
             output = processor._process_healpix_spectral_index_to_rectangular(
diff --git a/run_local_with_upload_and_download.py b/run_local_with_upload_and_download.py
index 6bbbb830..412a6438 100644
--- a/run_local_with_upload_and_download.py
+++ b/run_local_with_upload_and_download.py
@@ -30,7 +30,8 @@
             {{"type": "science", "files": ["imap_hi_l2_h45-ena-h-hf-nsp-ram-hae-4deg-1yr_20250415_{version}.cdf"]}},
             {{"type": "science", "files": ["imap_hi_l2_h90-ena-h-hf-nsp-anti-hae-4deg-1yr_20250415_{version}.cdf"]}},
             {{"type": "science", "files": ["imap_hi_l2_h90-ena-h-hf-nsp-ram-hae-4deg-1yr_20250415_{version}.cdf"]}}]""",
-                ]
+                ],
+                check=True,
             )
         case "lo", "spx":
             version = "v902"
@@ -50,7 +51,8 @@
                     "l090-spx-h-sf-sp-ram-hae-6deg-1yr",
                     "--dependency",
                     '[{"type": "science", "files": ["imap_lo_l3_l090-ena-h-sf-sp-ram-hae-6deg-1yr_20260101_v001.cdf"]}]',
-                ]
+                ],
+                check=True,
             )
             subprocess.run(
                 [
@@ -68,7 +70,8 @@
                     "l090-spx-h-sf-nsp-ram-hae-6deg-1yr",
                     "--dependency",
                     '[{"type": "science", "files": ["imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-1yr_20260101_v902.cdf"]}]',
-                ]
+                ],
+                check=True,
             )
             subprocess.run(
                 [
@@ -86,7 +89,8 @@
                     "l090-spxnbs-h-sf-nsp-ram-hae-6deg-1yr",
                     "--dependency",
                     '[{"type": "science", "files": ["imap_lo_l2_l090-enanbs-h-sf-nsp-ram-hae-6deg-1yr_20260101_v900.cdf"]}]',
-                ]
+                ],
+                check=True,
             )
         case "hi", "spx":
             subprocess.run(
@@ -105,7 +109,8 @@
                     "h90-spx-h-hf-sp-full-hae-4deg-6mo",
                     "--dependency",
                     '[{"type": "science", "files": ["imap_hi_l2_h90-ena-h-sf-nsp-ram-hae-4deg-6mo_20250415_v002.cdf"]}]',
-                ]
+                ],
+                check=True,
             )
         case "hi", "survival":
             subprocess.run(
@@ -124,7 +129,8 @@
                     "h90-ena-h-sf-sp-full-hae-4deg-6mo",
                     "--dependency",
                     '[{"type": "science", "files": ["imap_hi_l2_h90-ena-h-sf-nsp-ram-hae-4deg-6mo_20250415_v001.cdf"]},\n{"type": "science", "files": ["imap_hi_l2_h90-ena-h-sf-nsp-anti-hae-4deg-6mo_20250415_v001.cdf"]}]',
-                ]
+                ],
+                check=True,
             )
         case "hit", "direct":
             subprocess.run(
@@ -142,23 +148,26 @@
                     "--descriptor",
                     "direct-events",
                     "--dependency",
-                    '[{"type": "science", "files": ["imap_hit_l1a_direct-events_20100106_v001.cdf"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-2A-cosine-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-2B-cosine-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-3A-cosine-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-3B-cosine-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-4A-cosine-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-4B-cosine-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_hi-gain-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_lo-gain-lookup_20250203_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_hit-event-type-lookup_20250228_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-2A-charge-fit-lookup_20250319_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-3A-charge-fit-lookup_20250319_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-4A-charge-fit-lookup_20250319_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-2B-charge-fit-lookup_20250319_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-3B-charge-fit-lookup_20250319_v000.csv"]},'
-                    + '{"type": "ancillary", "files": ["imap_hit_range-4B-charge-fit-lookup_20250319_v000.csv"]}]',
-                ]
+                    (
+                        '[{"type": "science", "files": ["imap_hit_l1a_direct-events_20100106_v001.cdf"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-2A-cosine-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-2B-cosine-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-3A-cosine-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-3B-cosine-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-4A-cosine-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-4B-cosine-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_hi-gain-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_lo-gain-lookup_20250203_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_hit-event-type-lookup_20250228_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-2A-charge-fit-lookup_20250319_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-3A-charge-fit-lookup_20250319_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-4A-charge-fit-lookup_20250319_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-2B-charge-fit-lookup_20250319_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-3B-charge-fit-lookup_20250319_v000.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_hit_range-4B-charge-fit-lookup_20250319_v000.csv"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "hit", "macropixel":
             subprocess.run(
@@ -176,9 +185,12 @@
                     "--descriptor",
                     "macropixel",
                     "--dependency",
-                    '[{"type": "science", "files": ["imap_hit_l2_macropixel-intensity_20100106_v001.cdf"]},'
-                    + '{"type": "science", "files": ["imap_mag_l1d_norm-dsrf_20100106_v001.cdf"]}]',
-                ]
+                    (
+                        '[{"type": "science", "files": ["imap_hit_l2_macropixel-intensity_20100106_v001.cdf"]},'
+                        '{"type": "science", "files": ["imap_mag_l1d_norm-dsrf_20100106_v001.cdf"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "ultra", "survival":
             subprocess.run(
@@ -196,12 +208,15 @@
                     "--descriptor",
                     "u90-ena-h-sf-sp-full-hae-4deg-3mo",
                     "--dependency",
-                    '[{"type": "science", "files": ["imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20250415_v010.cdf"]},'
-                    + '{"type": "spice", "files": ["imap_sclk_0000.tsc"]},'
-                    + '{"type": "spice", "files": ["naif0012.tls"]},'
-                    + '{"type": "spice", "files": ["imap_science_0001.tf"]},'
-                    + '{"type": "spice", "files": ["imap_dps_2025_105_2026_105_01.ah.bc"]}]',
-                ]
+                    (
+                        '[{"type": "science", "files": ["imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20250415_v010.cdf"]},'
+                        '{"type": "spice", "files": ["imap_sclk_0000.tsc"]},'
+                        '{"type": "spice", "files": ["naif0012.tls"]},'
+                        '{"type": "spice", "files": ["imap_science_0001.tf"]},'
+                        '{"type": "spice", "files": ["imap_dps_2025_105_2026_105_01.ah.bc"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "ultra", "spx":
             subprocess.run(
@@ -219,11 +234,14 @@
                     "--descriptor",
                     "u90-spx-h-sf-sp-full-hae-4deg-3mo",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_ultra_l3_u90-ena-h-sf-sp-full-hae-4deg-3mo_20250415_v010.cdf"]},'
-                    '{"type": "ancillary", "files": ["imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat"]}'
-                    "]",
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_ultra_l3_u90-ena-h-sf-sp-full-hae-4deg-3mo_20250415_v010.cdf"]},'
+                        '{"type": "ancillary", "files": ["imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat"]}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case "glows", "l3b":
             subprocess.run(
@@ -239,13 +257,16 @@
                     "--version",
                     "v025",
                     "--dependency",
-                    '[{"type": "science", "files": ["imap_glows_l3a_hist_20250415-repoint01000_v026.cdf"]},'
-                    '{"type": "ancillary", "files":["imap_glows_bad-days-list_20100101_v001.dat"]},'
-                    '{"type": "ancillary", "files":["imap_glows_WawHelioIonMP_20100101_v002.json"]},'
-                    '{"type": "ancillary", "files":["imap_glows_uv-anisotropy-1CR_20100101_v001.json"]},'
-                    '{"type": "ancillary", "files":["imap_glows_pipeline-settings-l3bcde_19470303_v008.json"]},'
-                    '{"type": "repoint", "files":["imap_2026_105_01.repoint.csv"]}]',
-                ]
+                    (
+                        '[{"type": "science", "files": ["imap_glows_l3a_hist_20250415-repoint01000_v026.cdf"]},'
+                        '{"type": "ancillary", "files":["imap_glows_bad-days-list_20100101_v001.dat"]},'
+                        '{"type": "ancillary", "files":["imap_glows_WawHelioIonMP_20100101_v002.json"]},'
+                        '{"type": "ancillary", "files":["imap_glows_uv-anisotropy-1CR_20100101_v001.json"]},'
+                        '{"type": "ancillary", "files":["imap_glows_pipeline-settings-l3bcde_19470303_v008.json"]},'
+                        '{"type": "repoint", "files":["imap_2026_105_01.repoint.csv"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "glows", "l3d":
             if os.path.exists(PATH_TO_L3D_TOOLKIT / "data_l3b"):
@@ -272,17 +293,20 @@
                     "--descriptor",
                     "solar-hist",
                     "--dependency",
-                    '[{"type": "science", "files": ["imap_glows_l3b_ion-rate-profile_20100422_v013.cdf"]},'
-                    '{"type": "science", "files": ["imap_glows_l3c_sw-profile_20100422_v012.cdf"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_plasma-speed-2010a_20100101_v003.dat"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_proton-density-2010a_20100101_v003.dat"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_uv-anisotropy-2010a_20100101_v003.dat"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_photoion-2010a_20100101_v003.dat"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_electron-density-2010a_20100101_v003.dat"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_lya-2010a_20100101_v003.dat"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_l3b-archive_20100422_v011.zip"]},'
-                    '{"type": "ancillary", "files": ["imap_glows_pipeline-settings-l3bcde_20100101_v006.json"]}]',
-                ]
+                    (
+                        '[{"type": "science", "files": ["imap_glows_l3b_ion-rate-profile_20100422_v013.cdf"]},'
+                        '{"type": "science", "files": ["imap_glows_l3c_sw-profile_20100422_v012.cdf"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_plasma-speed-2010a_20100101_v003.dat"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_proton-density-2010a_20100101_v003.dat"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_uv-anisotropy-2010a_20100101_v003.dat"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_photoion-2010a_20100101_v003.dat"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_electron-density-2010a_20100101_v003.dat"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_lya-2010a_20100101_v003.dat"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_l3b-archive_20100422_v011.zip"]},'
+                        '{"type": "ancillary", "files": ["imap_glows_pipeline-settings-l3bcde_20100101_v006.json"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "swapi", "proton":
             subprocess.run(
@@ -300,21 +324,24 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    '[{"type":"science","files":["imap_swapi_l2_sci_20251208_v006.cdf"]},'
-                    '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]},'
-                    '{"type":"ancillary","files":["imap_swapi_energy-gf-pui-lut_20100101_v001.csv"]},'
-                    '{"type":"ancillary","files":["imap_swapi_density-of-neutral-helium-lut_20241023_v000.dat"]},'
-                    '{"type":"ancillary","files":["imap_swapi_azimuthal-transmission_20260425_v001.csv"]},'
-                    '{"type":"ancillary","files":["imap_swapi_central-effective-area_20260425_v001.csv"]},'
-                    '{"type":"ancillary","files":["imap_swapi_passband-fit-coefficients_20260425_v001.csv"]},'
-                    '{"type": "spice", "files": ["imap_sclk_0000.tsc"]},'
-                    + '{"type": "spice", "files": ["naif0012.tls"]},'
-                    + '{"type": "spice", "files": ["imap_science_108.tf"]},'
-                    + '{"type": "spice", "files": ["imap_001.tf"]},'
-                    + '{"type": "spice", "files": ["imap_2025_105_2026_105_01.ah.bc"]},'
-                    + '{"type": "spice", "files": ["imap_dps_2025_105_2026_105_01.ah.bc"]}'
-                    "]",
-                ]
+                    (
+                        '[{"type":"science","files":["imap_swapi_l2_sci_20251208_v006.cdf"]},'
+                        '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]},'
+                        '{"type":"ancillary","files":["imap_swapi_energy-gf-pui-lut_20100101_v001.csv"]},'
+                        '{"type":"ancillary","files":["imap_swapi_density-of-neutral-helium-lut_20241023_v000.dat"]},'
+                        '{"type":"ancillary","files":["imap_swapi_azimuthal-transmission_20260425_v001.csv"]},'
+                        '{"type":"ancillary","files":["imap_swapi_central-effective-area_20260425_v001.csv"]},'
+                        '{"type":"ancillary","files":["imap_swapi_passband-fit-coefficients_20260425_v001.csv"]},'
+                        '{"type": "spice", "files": ["imap_sclk_0000.tsc"]},'
+                        '{"type": "spice", "files": ["naif0012.tls"]},'
+                        '{"type": "spice", "files": ["imap_science_108.tf"]},'
+                        '{"type": "spice", "files": ["imap_001.tf"]},'
+                        '{"type": "spice", "files": ["imap_2025_105_2026_105_01.ah.bc"]},'
+                        '{"type": "spice", "files": ["imap_dps_2025_105_2026_105_01.ah.bc"]}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case "swapi", "alpha":
             subprocess.run(
@@ -332,12 +359,15 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    '[{"type":"science","files":["imap_swapi_l2_sci_20250606_v001.cdf"]},'
-                    '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]},'
-                    '{"type":"ancillary","files":["imap_swapi_energy-gf-pui-lut_20100101_v001.csv"]},'
-                    '{"type":"ancillary","files":["imap_swapi_density-of-neutral-helium-lut_20241023_v000.dat"]}'
-                    "]",
-                ]
+                    (
+                        '[{"type":"science","files":["imap_swapi_l2_sci_20250606_v001.cdf"]},'
+                        '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]},'
+                        '{"type":"ancillary","files":["imap_swapi_energy-gf-pui-lut_20100101_v001.csv"]},'
+                        '{"type":"ancillary","files":["imap_swapi_density-of-neutral-helium-lut_20241023_v000.dat"]}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case "swapi", "pui":
             subprocess.run(
@@ -355,20 +385,23 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    '[{"type":"science","files":["imap_swapi_l2_sci_20250606_v001.cdf"]},'
-                    '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]},'
-                    '{"type":"ancillary","files":["imap_swapi_energy-gf-pui-lut_20100101_v001.csv"]},'
-                    '{"type":"ancillary","files":["imap_swapi_density-of-neutral-helium-lut_20241023_v000.dat"]},'
-                    '{"type": "spice", "files": ["imap_sclk_0000.tsc"]},'
-                    + '{"type": "spice", "files": ["naif0012.tls"]},'
-                    + '{"type": "spice", "files": ["imap_science_0001.tf"]},'
-                    + '{"type": "spice", "files": ["imap_001.tf"]},'
-                    + '{"type": "spice", "files": ["imap_2025_105_2026_105_01.ah.bc"]},'
-                    + '{"type": "spice", "files": ["de440.bsp"]},'
-                    + '{"type": "spice", "files": ["imap_recon_20250415_20260415_v01.bsp"]},'
-                    + '{"type": "spice", "files": ["imap_dps_2025_105_2026_105_01.ah.bc"]}'
-                    "]",
-                ]
+                    (
+                        '[{"type":"science","files":["imap_swapi_l2_sci_20250606_v001.cdf"]},'
+                        '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]},'
+                        '{"type":"ancillary","files":["imap_swapi_energy-gf-pui-lut_20100101_v001.csv"]},'
+                        '{"type":"ancillary","files":["imap_swapi_density-of-neutral-helium-lut_20241023_v000.dat"]},'
+                        '{"type": "spice", "files": ["imap_sclk_0000.tsc"]},'
+                        '{"type": "spice", "files": ["naif0012.tls"]},'
+                        '{"type": "spice", "files": ["imap_science_0001.tf"]},'
+                        '{"type": "spice", "files": ["imap_001.tf"]},'
+                        '{"type": "spice", "files": ["imap_2025_105_2026_105_01.ah.bc"]},'
+                        '{"type": "spice", "files": ["de440.bsp"]},'
+                        '{"type": "spice", "files": ["imap_recon_20250415_20260415_v01.bsp"]},'
+                        '{"type": "spice", "files": ["imap_dps_2025_105_2026_105_01.ah.bc"]}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case "swapi", "l3b":
             subprocess.run(
@@ -384,10 +417,13 @@
                     "--version",
                     "v003",
                     "--dependency",
-                    '[{"type": "science", "files": ["imap_swapi_l2_sci_20250606_v001.cdf"]},'
-                    '{"type":"ancillary","files":["imap_swapi_energy-gf-sw-lut_20100101_v001.csv"]},'
-                    '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]}]',
-                ]
+                    (
+                        '[{"type": "science", "files": ["imap_swapi_l2_sci_20250606_v001.cdf"]},'
+                        '{"type":"ancillary","files":["imap_swapi_energy-gf-sw-lut_20100101_v001.csv"]},'
+                        '{"type":"ancillary","files":["imap_swapi_efficiency-lut_20241020_v002.dat"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "codice", "lo-direct-events":
             subprocess.run(
@@ -405,13 +441,16 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_codice_l1a_lo-sw-priority_20241110_v002.cdf"]},'
-                    '{"type": "science", "files": ["imap_codice_l1a_lo-nsw-priority_20241110_v003.cdf"]},'
-                    '{"type": "science", "files": ["imap_codice_l2_lo-direct-events_20241110_v006.cdf"]},'
-                    '{"type": "ancillary", "files": ["imap_codice_mass-coefficient-lookup_20241110_v002.csv"]},'
-                    '{"type": "ancillary", "files": ["imap_codice_lo-energy-per-charge_20241110_v002.csv"]}]',
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_codice_l1a_lo-sw-priority_20241110_v002.cdf"]},'
+                        '{"type": "science", "files": ["imap_codice_l1a_lo-nsw-priority_20241110_v003.cdf"]},'
+                        '{"type": "science", "files": ["imap_codice_l2_lo-direct-events_20241110_v006.cdf"]},'
+                        '{"type": "ancillary", "files": ["imap_codice_mass-coefficient-lookup_20241110_v002.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_codice_lo-energy-per-charge_20241110_v002.csv"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "codice", ("lo-partial-densities" | "partial-densities"):
             subprocess.run(
@@ -429,10 +468,13 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_codice_l2_lo-sw-species_20241110_v002.cdf"]},'
-                    '{"type": "ancillary", "files": ["imap_codice_mass-per-charge_20241110_v002.csv"]}]',
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_codice_l2_lo-sw-species_20241110_v002.cdf"]},'
+                        '{"type": "ancillary", "files": ["imap_codice_mass-per-charge_20241110_v002.csv"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "codice", ("lo-sw-ratios" | "ratios"):
             subprocess.run(
@@ -450,10 +492,13 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_codice_l3a_lo-partial-densities_20241110_v000.cdf"]}'
-                    "]",
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_codice_l3a_lo-partial-densities_20241110_v000.cdf"]}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case "codice", ("lo-sw-charge-state-distributions"):
             subprocess.run(
@@ -471,10 +516,13 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_codice_l3a_lo-partial-densities_20241110_v000.cdf"]}'
-                    "]",
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_codice_l3a_lo-partial-densities_20241110_v000.cdf"]}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case "codice", "hi-direct-events":
             subprocess.run(
@@ -492,10 +540,13 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_codice_l2_hi-direct-events_20241110_v002.cdf"]},'
-                    '{"type": "ancillary", "files": ["imap_codice_tof-lookup_20241110_v002.csv"]}]',
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_codice_l2_hi-direct-events_20241110_v002.cdf"]},'
+                        '{"type": "ancillary", "files": ["imap_codice_tof-lookup_20241110_v002.csv"]}]'
+                    ),
+                ],
+                check=True,
             )
         case "codice", "hi-pitch-angle":
             subprocess.run(
@@ -513,16 +564,19 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_codice_l2_hi-sectored_20241110_v002.cdf"]},'
-                    '{"type": "science", "files": ["imap_mag_l1d_norm-dsrf_20250630_v001.cdf"]}'
-                    "]",
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_codice_l2_hi-sectored_20241110_v002.cdf"]},'
+                        '{"type": "science", "files": ["imap_mag_l1d_norm-dsrf_20250630_v001.cdf"]}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case "codice", descriptor if "3d-distribution" in descriptor:
             species = descriptor.split("-")[1]
-            assert species in ["hplus", "heplus", "heplus2", "oplus6"], (
-                NotImplementedError("Target instrument or product not implemented")
+            assert species in ["hplus", "heplus", "heplus2", "oplus6"], NotImplementedError(
+                "Target instrument or product not implemented"
             )
 
             subprocess.run(
@@ -540,16 +594,19 @@
                     "--version",
                     "v000",
                     "--dependency",
-                    "["
-                    '{"type": "science", "files": ["imap_codice_l1a_lo-sw-priority_20241110_v002.cdf"]},'
-                    '{"type": "science", "files": ["imap_codice_l1a_lo-nsw-priority_20241110_v003.cdf"]},'
-                    '{"type": "science", "files": ["imap_codice_l3a_lo-direct-events_20241110_v005.cdf"]},'
-                    '{"type": "ancillary", "files": ["imap_codice_lo-mass-species-bin-lookup_20241110_v001.csv"]},'
-                    '{"type": "ancillary", "files": ["imap_codice_lo-geometric-factors_20241110_v001.csv"]},'
-                    '{"type": "ancillary", "files": ["imap_codice_lo-energy-per-charge_20241110_v002.csv"]},'
-                    f'{{"type": "ancillary", "files": ["imap_codice_lo-{species}-efficiency_20241110_v001.csv"]}}'
-                    "]",
-                ]
+                    (
+                        "["
+                        '{"type": "science", "files": ["imap_codice_l1a_lo-sw-priority_20241110_v002.cdf"]},'
+                        '{"type": "science", "files": ["imap_codice_l1a_lo-nsw-priority_20241110_v003.cdf"]},'
+                        '{"type": "science", "files": ["imap_codice_l3a_lo-direct-events_20241110_v005.cdf"]},'
+                        '{"type": "ancillary", "files": ["imap_codice_lo-mass-species-bin-lookup_20241110_v001.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_codice_lo-geometric-factors_20241110_v001.csv"]},'
+                        '{"type": "ancillary", "files": ["imap_codice_lo-energy-per-charge_20241110_v002.csv"]},'
+                        f'{{"type": "ancillary", "files": ["imap_codice_lo-{species}-efficiency_20241110_v001.csv"]}}'
+                        "]"
+                    ),
+                ],
+                check=True,
             )
         case _:
             raise NotImplementedError("Target instrument or product not implemented")
diff --git a/scripts/batch_download_parents.py b/scripts/batch_download_parents.py
index d182b8e6..7d07cfda 100644
--- a/scripts/batch_download_parents.py
+++ b/scripts/batch_download_parents.py
@@ -14,38 +14,32 @@ def download_parents(path: Path, output_dir: Path):
 
     imap_data_access.config["DATA_DIR"] = output_dir
 
-    try:
-        files_to_download = set()
-
-        for file in path.rglob("*.cdf"):
-            print(f"opening {path / file}")
-            with CDF(str(file)) as cdf:
-                for parent in cdf.attrs["Parents"]:
-                    files_to_download.add(parent)
-
-        print(f"Downloading {len(files_to_download)} files")
-
-        for i, file in enumerate(files_to_download):
-            print(f"[{i + 1}/{len(files_to_download)}] downloading {file}")
-            failures = 0
-            while failures < retries:
-                try:
-                    imap_data_access.download(file)
-                    break
-                except Exception as e:
-                    failures += 1
-
-                    print(
-                        f"failed to download file: {file} after {failures} attempts, retrying..."
-                    )
-                    if failures == retries:
-                        raise Exception(
-                            f"failed to download file: {file} after {retries} attempts, exiting"
-                        ).with_traceback(e.__traceback__)
-                    time.sleep(failures**2 * 0.5)
-
-    except Exception as e:
-        print(e)
+    files_to_download = set()
+
+    for file in path.rglob("*.cdf"):
+        print(f"opening {path / file}")
+        with CDF(str(file)) as cdf:
+            for parent in cdf.attrs["Parents"]:
+                files_to_download.add(parent)
+
+    print(f"Downloading {len(files_to_download)} files")
+
+    for i, file in enumerate(files_to_download):
+        print(f"[{i + 1}/{len(files_to_download)}] downloading {file}")
+        failures = 0
+        while failures < retries:
+            try:
+                imap_data_access.download(file)
+                break
+            except Exception as e:  # noqa: BLE001
+                failures += 1
+
+                print(f"failed to download file: {file} after {failures} attempts, retrying...")
+                if failures == retries:
+                    raise Exception(
+                        f"failed to download file: {file} after {retries} attempts, exiting"
+                    ).with_traceback(e.__traceback__)
+                time.sleep(failures**2 * 0.5)
 
 
 if __name__ == "__main__":
diff --git a/scripts/clean_metadata.py b/scripts/clean_metadata.py
index de3ec785..3f310854 100644
--- a/scripts/clean_metadata.py
+++ b/scripts/clean_metadata.py
@@ -15,9 +15,9 @@ def fix_fieldnam():
         with open(variable_yaml, mode="r") as file:
             yaml_data = yaml.safe_load(file)
             for key, item in yaml_data.items():
-                if "NAME" not in item.keys():
+                if "NAME" not in item:
                     continue
-                if "_" in yaml_data[key]["FIELDNAM"]:
+                if "_" in item["FIELDNAM"]:
                     yaml_data[key]["FIELDNAM"] = key.replace("_", " ").title()
                 if len(key) > 30:
                     print("key over 30", variable_yaml, key)
diff --git a/scripts/codice/create_fake_efficiency_ancillary.py b/scripts/codice/create_fake_efficiency_ancillary.py
index e8173bde..944d18d4 100644
--- a/scripts/codice/create_fake_efficiency_ancillary.py
+++ b/scripts/codice/create_fake_efficiency_ancillary.py
@@ -15,8 +15,11 @@
 
 
 def create_efficiency_lookup(
-    species: str, output_dir: Path = get_run_local_data_path("codice")
+    species: str,
+    output_dir: Path | None = None,
 ) -> Path:
+    if output_dir is None:
+        output_dir = get_run_local_data_path("codice")
     output_dir.mkdir(parents=True, exist_ok=True)
     output_path = output_dir / f"imap_codice_lo-{species}-efficiency_20241110_v001.csv"
     open(output_path, "a").close()
diff --git a/scripts/codice/create_more_accurate_l3a_direct_event.py b/scripts/codice/create_more_accurate_l3a_direct_event.py
index 8606db4b..19e80269 100644
--- a/scripts/codice/create_more_accurate_l3a_direct_event.py
+++ b/scripts/codice/create_more_accurate_l3a_direct_event.py
@@ -36,9 +36,7 @@ def create_more_accurate_l3a_direct_events_cdf(template_cdf: Path):
         position = rng.integers(1, 25, size=event_buffer_shape)
         cdf["position"] = position
 
-        cdf["spin_angle"] = rng.choice(
-            spin_angle_lut.bin_centers, size=event_buffer_shape
-        )
+        cdf["spin_angle"] = rng.choice(spin_angle_lut.bin_centers, size=event_buffer_shape)
 
         species = rng.integers(
             0, mass_species_bin_lookup.get_num_species(), size=event_buffer_shape
@@ -47,10 +45,7 @@ def create_more_accurate_l3a_direct_events_cdf(template_cdf: Path):
         mass_ranges = np.array(mass_species_bin_lookup.mass_ranges)
         lower_masses = mass_ranges[species, 0]
         upper_masses = mass_ranges[species, -1]
-        masses = (
-            rng.random(event_buffer_shape) * (upper_masses - lower_masses)
-            + lower_masses
-        )
+        masses = rng.random(event_buffer_shape) * (upper_masses - lower_masses) + lower_masses
 
         mass_per_charge_ranges = np.array(mass_species_bin_lookup.mass_per_charge)
         lower_mpc = mass_per_charge_ranges[species, 0]
diff --git a/scripts/codice/create_more_accurate_l3a_direct_event_input.py b/scripts/codice/create_more_accurate_l3a_direct_event_input.py
index d389e9ca..4b75e946 100644
--- a/scripts/codice/create_more_accurate_l3a_direct_event_input.py
+++ b/scripts/codice/create_more_accurate_l3a_direct_event_input.py
@@ -1,4 +1,4 @@
-from datetime import timedelta, datetime
+from datetime import datetime, timedelta
 from pathlib import Path
 
 import numpy as np
@@ -24,28 +24,28 @@ def extend_priority_counts_to_24_spin_angles(
     output_path = output_dir / template_cdf_path.name
     output_path.unlink(missing_ok=True)
 
-    with CDF(str(template_cdf_path)) as template_cdf:
-        with CDF(str(output_path), masterpath="") as cdf:
-            cdf["spin_sector_index"] = np.arange(24)
-            for var in template_cdf:
-                if var in priority_count_variables:
-                    cdf[var] = np.repeat(template_cdf[var][...], 2, axis=2)
-                elif var == "spin_sector_index":
-                    pass
-                else:
-                    cdf[var] = template_cdf[var]
-                cdf[var].attrs = template_cdf[var].attrs
-
-            rgfo_half_spin = rng.integers(
-                0, 33, size=template_cdf["rgfo_half_spin"].shape
-            )
-            # randomly_fill_value = rng.choice(
-            #    [False, True], size=template_cdf["rgfo_half_spin"].shape
-            # )
-
-            cdf["rgfo_half_spin"] = rgfo_half_spin
-            # cdf["rgfo_half_spin"] = np.where(randomly_fill_value, cdf["rgfo_half_spin"].attrs["FILLVAL"],
-            #                                  rgfo_half_spin)
+    with (
+        CDF(str(template_cdf_path)) as template_cdf,
+        CDF(str(output_path), masterpath="") as cdf,
+    ):
+        cdf["spin_sector_index"] = np.arange(24)
+        for var in template_cdf:
+            if var in priority_count_variables:
+                cdf[var] = np.repeat(template_cdf[var][...], 2, axis=2)
+            elif var == "spin_sector_index":
+                pass
+            else:
+                cdf[var] = template_cdf[var]
+            cdf[var].attrs = template_cdf[var].attrs
+
+        rgfo_half_spin = rng.integers(0, 33, size=template_cdf["rgfo_half_spin"].shape)
+        # randomly_fill_value = rng.choice(
+        #    [False, True], size=template_cdf["rgfo_half_spin"].shape
+        # )
+
+        cdf["rgfo_half_spin"] = rgfo_half_spin
+        # cdf["rgfo_half_spin"] = np.where(randomly_fill_value, cdf["rgfo_half_spin"].attrs["FILLVAL"],
+        #                                  rgfo_half_spin)
     return output_path
 
 
@@ -91,45 +91,41 @@ def modify_l2_direct_events(instrument_team_l2_path: Path) -> Path:
     output_path = output_dir / instrument_team_l2_path.name
     output_path.unlink(missing_ok=True)
 
-    with CDF(str(instrument_team_l2_path)) as template_cdf:
-        with CDF(str(output_path), masterpath="") as cdf:
-            epoch_delta = (
-                timedelta(minutes=2).total_seconds() * ONE_SECOND_IN_NANOSECONDS
-            )
-            cdf["epoch_delta_plus"] = np.full(template_cdf["epoch"].shape, epoch_delta)
-            cdf["epoch_delta_minus"] = np.full(template_cdf["epoch"].shape, epoch_delta)
+    with (
+        CDF(str(instrument_team_l2_path)) as template_cdf,
+        CDF(str(output_path), masterpath="") as cdf,
+    ):
+        epoch_delta = timedelta(minutes=2).total_seconds() * ONE_SECOND_IN_NANOSECONDS
+        cdf["epoch_delta_plus"] = np.full(template_cdf["epoch"].shape, epoch_delta)
+        cdf["epoch_delta_minus"] = np.full(template_cdf["epoch"].shape, epoch_delta)
 
-            for priority_i in range(CODICE_LO_L2_NUM_PRIORITIES):
-                elevation_var = f"p{priority_i}_elevation"
-                position_var = f"p{priority_i}_position"
+        for priority_i in range(CODICE_LO_L2_NUM_PRIORITIES):
+            elevation_var = f"p{priority_i}_elevation"
+            position_var = f"p{priority_i}_position"
 
-                cdf[position_var] = rng.integers(
-                    1, 25, size=template_cdf[position_var].shape
-                )
-                cdf[position_var].attrs["FILLVAL"] = int_fillval
+            cdf[position_var] = rng.integers(1, 25, size=template_cdf[position_var].shape)
+            cdf[position_var].attrs["FILLVAL"] = int_fillval
 
-                cdf[elevation_var] = rng.choice(
-                    elevation_lookup.bin_centers, size=template_cdf[position_var].shape
-                )
-                cdf[elevation_var].attrs["FILLVAL"] = float_fillval
+            cdf[elevation_var] = rng.choice(
+                elevation_lookup.bin_centers, size=template_cdf[position_var].shape
+            )
+            cdf[elevation_var].attrs["FILLVAL"] = float_fillval
 
-                for epoch_i in range(cdf[elevation_var].shape[0]):
-                    number_of_events = template_cdf[f"p{priority_i}_num_events"][
-                        epoch_i
-                    ]
+            for epoch_i in range(cdf[elevation_var].shape[0]):
+                number_of_events = template_cdf[f"p{priority_i}_num_events"][epoch_i]
 
-                    filled_position = cdf[position_var][...]
-                    filled_position[epoch_i, number_of_events:] = int_fillval
-                    cdf[position_var] = filled_position
+                filled_position = cdf[position_var][...]
+                filled_position[epoch_i, number_of_events:] = int_fillval
+                cdf[position_var] = filled_position
 
-                    filled_elevation = cdf[elevation_var][...]
-                    filled_elevation[epoch_i, number_of_events:] = float_fillval
-                    cdf[elevation_var] = filled_elevation
+                filled_elevation = cdf[elevation_var][...]
+                filled_elevation[epoch_i, number_of_events:] = float_fillval
+                cdf[elevation_var] = filled_elevation
 
-            for var in template_cdf:
-                if var not in cdf:
-                    cdf[var] = template_cdf[var]
-                    cdf[var].attrs = template_cdf[var].attrs
+        for var in template_cdf:
+            if var not in cdf:
+                cdf[var] = template_cdf[var]
+                cdf[var].attrs = template_cdf[var].attrs
 
     return output_path
 
@@ -158,11 +154,7 @@ def modify_l2_direct_events(instrument_team_l2_path: Path) -> Path:
     )
 
     convert_epoch_time(l1a_nsw_path, target_datetime)
-    l1a_nsw_path.rename(
-        l1a_nsw_path.parent / "imap_codice_l1a_lo-nsw-priority_20241111_v000.cdf"
-    )
+    l1a_nsw_path.rename(l1a_nsw_path.parent / "imap_codice_l1a_lo-nsw-priority_20241111_v000.cdf")
 
     convert_epoch_time(l1a_sw_path, target_datetime)
-    l1a_sw_path.rename(
-        l1a_sw_path.parent / "imap_codice_l1a_lo-sw-priority_20241111_v000.cdf"
-    )
+    l1a_sw_path.rename(l1a_sw_path.parent / "imap_codice_l1a_lo-sw-priority_20241111_v000.cdf")
diff --git a/scripts/compare_l2_map_metadata.py b/scripts/compare_l2_map_metadata.py
index 3d701931..5994c9a5 100644
--- a/scripts/compare_l2_map_metadata.py
+++ b/scripts/compare_l2_map_metadata.py
@@ -54,9 +54,9 @@
         continue
 
     print(var)
-    for attr in l3_attrs.keys():
+    for attr in l3_attrs:
         if attr in l2_attrs and l2_attrs[attr] != l3_attrs[attr]:
             print(f"\t{attr}: {l2_attrs[attr]}\t{l3_attrs[attr]}")
 
-    not_included_keys = [key for key in l3_attrs.keys() if key not in l2_attrs.keys()]
+    not_included_keys = [key for key in l3_attrs if key not in l2_attrs]
     print(var, not_included_keys)
diff --git a/scripts/confirm_reprocessing.py b/scripts/confirm_reprocessing.py
index 66bb9481..c7de51d2 100644
--- a/scripts/confirm_reprocessing.py
+++ b/scripts/confirm_reprocessing.py
@@ -8,9 +8,7 @@
 def report_oldest_file(**query_args):
     records = imap_data_access.query(**query_args, version="latest")
     oldest = min(records, key=lambda x: x["ingestion_date"])
-    print(
-        f"Oldest file:\n{oldest['ingestion_date']}     {Path(oldest['file_path']).name}"
-    )
+    print(f"Oldest file:\n{oldest['ingestion_date']}     {Path(oldest['file_path']).name}")
 
 
 def get_unprocessed_files(reference_time_str, **query_args):
@@ -43,9 +41,11 @@ def analyze(reference_time_str, **query_args):
 parser.add_argument("--data-level")
 parser.add_argument("--descriptor")
 args = parser.parse_args()
-query_args = dict(
-    instrument=args.instrument, descriptor=args.descriptor, data_level=args.data_level
-)
+query_args = {
+    "instrument": args.instrument,
+    "descriptor": args.descriptor,
+    "data_level": args.data_level,
+}
 if args.reprocessing_time is not None:
     analyze(args.reprocessing_time, **query_args)
 else:
diff --git a/scripts/convert_hit_event_type_to_csv.py b/scripts/convert_hit_event_type_to_csv.py
index 687b36f9..4b6b1c13 100644
--- a/scripts/convert_hit_event_type_to_csv.py
+++ b/scripts/convert_hit_event_type_to_csv.py
@@ -5,5 +5,4 @@
 fullText = []
 table = doc.tables[0]
 with open("imap_hit_l3_hit-event-types-text-not-cdf_v001.cdf", "w") as file:
-    for row in table.rows:
-        file.write(",".join([cell.text for cell in row.cells]) + "\n")
+    file.writelines(",".join([cell.text for cell in row.cells]) + "\n" for row in table.rows)
diff --git a/scripts/convert_product_definition_to_yaml.py b/scripts/convert_product_definition_to_yaml.py
index c01b728e..ef77a986 100644
--- a/scripts/convert_product_definition_to_yaml.py
+++ b/scripts/convert_product_definition_to_yaml.py
@@ -69,9 +69,7 @@ def convert_csv_to_yaml(file_path):
         with open(file_path, "r") as f:
             csvreader = csv.reader(f)
             row_headers = next(csvreader)
-            header_to_index = {
-                header: index for index, header in enumerate(row_headers)
-            }
+            header_to_index = {header: index for index, header in enumerate(row_headers)}
             for row in csvreader:
                 yaml_text += f"{row[0]}:\n"
 
@@ -89,13 +87,10 @@ def convert_csv_to_yaml(file_path):
                     required_variables = required_for_data
 
                 if (
-                    "RECORD_VARYING" in required_variables
-                    or "RECORD_VARYING" in header_to_index
+                    "RECORD_VARYING" in required_variables or "RECORD_VARYING" in header_to_index
                 ) and row[header_to_index["RECORD_VARYING"]].lower() == "nrv":
                     required_variables = [
-                        variable
-                        for variable in required_variables
-                        if variable != "DEPEND_0"
+                        variable for variable in required_variables if variable != "DEPEND_0"
                     ]
 
                 for index, rowitem in enumerate(row):
@@ -110,14 +105,11 @@ def convert_csv_to_yaml(file_path):
                     column_not_listed_in_specified_list = row_headers[index] not in (
                         required_variables + non_required_columns
                     )
-                    if (
-                        column_is_empty_and_not_required
-                        or column_not_listed_in_specified_list
-                    ):
+                    if column_is_empty_and_not_required or column_not_listed_in_specified_list:
                         continue
 
                     yaml_text += f"   {row_headers[index]}: {display_rowitem}\n"
-    except Exception as e:
+    except Exception as e:  # noqa: BLE001
         print(e)
 
     yaml_text = yaml_text.strip()
@@ -156,20 +148,20 @@ def process_csv():
     filename_without_extension = Path(file_path).name.split(".")[0]
     print(filename_without_extension)
     yaml_file_name = f"imap_l3_processing/cdf/config/{filename_without_extension}.yaml"
-    if os.path.isfile(yaml_file_name):
-        if (
-            input(
-                "The Yaml already exists in the config folder! Are you sure you want to overwrite the other pairs work? [Y/n]"
-            )
-            != "n"
-        ):
-            os.remove(yaml_file_name)
+    if (
+        os.path.isfile(yaml_file_name)
+        and input(
+            "The Yaml already exists in the config folder! Are you sure you want to overwrite the other pairs work? [Y/n]"
+        )
+        != "n"
+    ):
+        os.remove(yaml_file_name)
 
     with open(yaml_file_name, "w") as yaml_file:
         yaml_file.write(yaml_text)
 
     if args.generate_cdf_for_instrument is not None:
-        subprocess.run(["python", "run_local.py", args.generate_cdf_for_instrument])
+        subprocess.run(["python", "run_local.py", args.generate_cdf_for_instrument], check=True)
 
 
 if __name__ == "__main__":
diff --git a/scripts/convert_variable_yaml_to_csv.py b/scripts/convert_variable_yaml_to_csv.py
index e453f4b9..0f7608fd 100644
--- a/scripts/convert_variable_yaml_to_csv.py
+++ b/scripts/convert_variable_yaml_to_csv.py
@@ -12,16 +12,9 @@
         yaml_data = yaml.safe_load(yaml_file)
 
     all_headers = {
-        key: ""
-        for key in set(
-            chain.from_iterable(
-                [yaml_data[variable].keys() for variable in yaml_data.keys()]
-            )
-        )
+        key: "" for key in set(chain.from_iterable([data.keys() for data in yaml_data.values()]))
     }
-    valid_variables = [
-        yaml_data[var] for var in yaml_data.keys() if "NAME" in yaml_data[var]
-    ]
+    valid_variables = [data for data in yaml_data.values() if "NAME" in data]
     with open(outpath, "w") as out_file:
         writer = csv.DictWriter(out_file, fieldnames=all_headers.keys())
         writer.writeheader()
diff --git a/scripts/generate_hi_yaml.py b/scripts/generate_hi_yaml.py
index c9c3856c..b4ee9f47 100644
--- a/scripts/generate_hi_yaml.py
+++ b/scripts/generate_hi_yaml.py
@@ -98,10 +98,7 @@
         f"imap_{instrument}_l3_{descriptor}": {
             "Logical_source_description": "IMAP Hi Instrument Level 3 "
             + ", ".join(
-                [
-                    logical_source_description_parts[part]
-                    for part in descriptor.split("-")
-                ]
+                [logical_source_description_parts[part] for part in descriptor.split("-")]
             ),
             "Data_level": "3",
             "Data_type": f"L3_{time_range}>Level-3 {time_range}",
diff --git a/scripts/generate_lo_yaml.py b/scripts/generate_lo_yaml.py
index b3ccae87..dcf5e4dc 100644
--- a/scripts/generate_lo_yaml.py
+++ b/scripts/generate_lo_yaml.py
@@ -62,10 +62,7 @@
         f"imap_{instrument}_l3_{descriptor}": {
             "Logical_source_description": "IMAP Lo Instrument Level 3 "
             + ", ".join(
-                [
-                    logical_source_description_parts[part]
-                    for part in descriptor.split("-")
-                ]
+                [logical_source_description_parts[part] for part in descriptor.split("-")]
             ),
             "Data_level": "3",
             "Data_type": f"L3_{time_range}>Level-3 {time_range}",
diff --git a/scripts/generate_ultra_yaml.py b/scripts/generate_ultra_yaml.py
index 773d0444..0e008862 100644
--- a/scripts/generate_ultra_yaml.py
+++ b/scripts/generate_ultra_yaml.py
@@ -153,10 +153,7 @@
         f"imap_{instrument}_l3_{descriptor}": {
             "Logical_source_description": "IMAP Ultra Instrument Level 3 "
             + ", ".join(
-                [
-                    logical_source_description_parts[part]
-                    for part in descriptor.split("-")
-                ]
+                [logical_source_description_parts[part] for part in descriptor.split("-")]
             ),
             "Data_level": "3",
             "Data_type": f"L3_{time_range}>Level-3 {time_range}",
diff --git a/scripts/get_batch_jobs_status.py b/scripts/get_batch_jobs_status.py
index 030ae4af..c14d93b4 100644
--- a/scripts/get_batch_jobs_status.py
+++ b/scripts/get_batch_jobs_status.py
@@ -66,9 +66,7 @@ class Command(enum.Enum):
 
 if "log_id" not in vars(args):
     query_params = {
-        key: val
-        for key, val in vars(args).items()
-        if val is not None and key not in ["command"]
+        key: val for key, val in vars(args).items() if val is not None and key not in ["command"]
     }
     response = requests.get(
         url=f"{imap_dev_url}/processing-jobs", headers=headers, params=query_params
@@ -92,9 +90,7 @@ class Command(enum.Enum):
             "job_log_stream_id",
         ]
 
-        records.append(
-            {key: val for key, val in processing_job.items() if key in relevant_fields}
-        )
+        records.append({key: val for key, val in processing_job.items() if key in relevant_fields})
 
     pd.set_option("display.max_colwidth", None)
     if len(records) > 0:
@@ -106,7 +102,5 @@ class Command(enum.Enum):
     else:
         print("Found no jobs that matched query params!")
 else:
-    logs = requests.get(
-        url=f"{imap_dev_url}/processing-logs/{args.log_id}", headers=headers
-    )
+    logs = requests.get(url=f"{imap_dev_url}/processing-logs/{args.log_id}", headers=headers)
     print(logs.text)
diff --git a/scripts/glows/create_example_glows_l3e_survival_probabilities_cdf.py b/scripts/glows/create_example_glows_l3e_survival_probabilities_cdf.py
index 6f203465..2b9eb781 100644
--- a/scripts/glows/create_example_glows_l3e_survival_probabilities_cdf.py
+++ b/scripts/glows/create_example_glows_l3e_survival_probabilities_cdf.py
@@ -18,21 +18,14 @@ def create_survival_probabilities_file(
     glows_file_path: Path, date_for_file: datetime, sensor: str
 ):
     filename = f"imap_glows_l3e_survival-probabilities-hi-{sensor}_{date_for_file.strftime('%Y%m%d')}_v001.cdf"
-    cdf_file_path = get_test_data_path(
-        f"hi/fake_l3e_survival_probabilities/{sensor}/{filename}"
-    )
+    cdf_file_path = get_test_data_path(f"hi/fake_l3e_survival_probabilities/{sensor}/{filename}")
 
     cdf_file_path.unlink(missing_ok=True)
     with open(glows_file_path) as input_data:
-        energy_line = [
-            line for line in input_data.readlines() if line.startswith("#energy_grid")
-        ]
+        energy_line = [line for line in input_data if line.startswith("#energy_grid")]
         assert len(energy_line) == 1
         energies = np.array(
-            [
-                float("".join(list(t)))
-                for t in itertools.batched(energy_line[0][19:-1], 10)
-            ]
+            [float("".join(list(t))) for t in itertools.batched(energy_line[0][19:-1], 10)]
         )
         energy_units = re.search(r"\[(.+)]", energy_line[0]).group(1)
 
diff --git a/scripts/glows/create_l2_glows_cdf_from_json.py b/scripts/glows/create_l2_glows_cdf_from_json.py
index f048c198..b4291186 100644
--- a/scripts/glows/create_l2_glows_cdf_from_json.py
+++ b/scripts/glows/create_l2_glows_cdf_from_json.py
@@ -12,9 +12,7 @@
 from tests.test_helpers import get_test_data_path
 
 
-def fill_official_l2_cdf_with_json_values(
-    output_folder: Path, input_path: Path
-) -> None:
+def fill_official_l2_cdf_with_json_values(output_folder: Path, input_path: Path) -> None:
     official_l2_path = get_test_data_path(
         "glows/imap_glows_l2_hist_20260323-repoint00194_v005.cdf"
     )
@@ -57,18 +55,13 @@ def fill_official_l2_cdf_with_json_values(
                 "ecliptic_lat",
             ]
             for var in lightcurve_vars:
-                cdf[var] = np.array(instrument_data["daily_lightcurve"][var])[
-                    np.newaxis, :
-                ]
+                cdf[var] = np.array(instrument_data["daily_lightcurve"][var])[np.newaxis, :]
 
-            cdf["raw_histograms"] = np.array(
-                instrument_data["daily_lightcurve"]["raw_histogram"]
-            )[np.newaxis, :]
+            cdf["raw_histograms"] = np.array(instrument_data["daily_lightcurve"]["raw_histogram"])[
+                np.newaxis, :
+            ]
             cdf["histogram_flag_array"] = np.array(
-                [
-                    int(f, 16)
-                    for f in instrument_data["daily_lightcurve"]["histogram_flag_array"]
-                ]
+                [int(f, 16) for f in instrument_data["daily_lightcurve"]["histogram_flag_array"]]
             )[np.newaxis, :]
 
             single_value_vars = [
@@ -106,13 +99,9 @@ def fill_official_l2_cdf_with_json_values(
             cdf["number_of_good_l1b_inputs"][0] = instrument_data["header"][
                 "number_of_l1b_files_used"
             ]
-            cdf["total_l1b_inputs"][0] = instrument_data["header"][
-                "number_of_all_l1b_files"
-            ]
+            cdf["total_l1b_inputs"][0] = instrument_data["header"]["number_of_all_l1b_files"]
             cdf.attrs["pkts_file_name"] = instrument_data["header"]["pkts_file_name"]
-            cdf.attrs["ancillary_data_files"] = instrument_data["header"][
-                "ancillary_data_files"
-            ]
+            cdf.attrs["ancillary_data_files"] = instrument_data["header"]["ancillary_data_files"]
             cdf.attrs["flight_software_version"] = instrument_data["header"][
                 "flight_software_version"
             ]
@@ -128,5 +117,5 @@ def fill_official_l2_cdf_with_json_values(
     for file_path in json_directory.iterdir():
         try:
             fill_official_l2_cdf_with_json_values(output_directory, file_path)
-        except Exception:
+        except Exception:  # noqa: BLE001
             traceback.print_exc()
diff --git a/scripts/glows/create_l3a_glows_cdf_from_json.py b/scripts/glows/create_l3a_glows_cdf_from_json.py
index c9ae5990..55025edd 100644
--- a/scripts/glows/create_l3a_glows_cdf_from_json.py
+++ b/scripts/glows/create_l3a_glows_cdf_from_json.py
@@ -36,9 +36,7 @@
     }
     data_with_spin_angle = GlowsProcessor.add_spin_angle_delta(data, files)
 
-    glows_l3a_lightcurve = create_glows_l3a_from_dictionary(
-        data_with_spin_angle, input_metadata
-    )
+    glows_l3a_lightcurve = create_glows_l3a_from_dictionary(data_with_spin_angle, input_metadata)
 
     cdf_path = save_data(
         glows_l3a_lightcurve,
diff --git a/scripts/glows/download_l2_prod_data.py b/scripts/glows/download_l2_prod_data.py
index b626e2a3..3c642841 100644
--- a/scripts/glows/download_l2_prod_data.py
+++ b/scripts/glows/download_l2_prod_data.py
@@ -9,7 +9,7 @@
 
 dotenv.load_dotenv(".env.prod")
 
-from tests.test_helpers import get_run_local_data_path  # noqa: E402
+from tests.test_helpers import get_run_local_data_path
 
 GLOWS_L3E_REQUIRED_SPICE_KERNELS: list[SpiceKernelTypes] = [
     SpiceKernelTypes.ScienceFrames,
@@ -29,9 +29,7 @@ def datetime_to_j2000_seconds(date: datetime) -> int:
 glows_prod_data_path = get_run_local_data_path("glows_prod_data")
 imap_data_access.config["DATA_DIR"] = glows_prod_data_path
 
-l2_query_response = imap_data_access.query(
-    instrument="glows", data_level="l2", version="latest"
-)
+l2_query_response = imap_data_access.query(instrument="glows", data_level="l2", version="latest")
 
 for file in l2_query_response:
     print(f"downloading: {Path(file['file_path']).name}")
diff --git a/scripts/glows/download_validation_data.py b/scripts/glows/download_validation_data.py
index a68af4f7..6dd9203b 100644
--- a/scripts/glows/download_validation_data.py
+++ b/scripts/glows/download_validation_data.py
@@ -5,11 +5,9 @@
 from dotenv import load_dotenv
 
 load_dotenv()
-os.environ["IMAP_DATA_DIR"] = str(
-    Path(__file__).parent.parent.parent / "glows_l3_validation_data"
-)
+os.environ["IMAP_DATA_DIR"] = str(Path(__file__).parent.parent.parent / "glows_l3_validation_data")
 
-import imap_data_access  # noqa: E402
+import imap_data_access
 
 ancillary_descriptors = [
     ("calibration-data", "20100101"),
@@ -40,9 +38,7 @@
         instrument="glows",
         descriptor=descriptor,
         start_date=start_date,
-        end_date=(datetime.strptime(start_date, "%Y%m%d") + timedelta(days=1)).strftime(
-            "%Y%m%d"
-        ),
+        end_date=(datetime.strptime(start_date, "%Y%m%d") + timedelta(days=1)).strftime("%Y%m%d"),
         version="latest",
     )
 
diff --git a/scripts/hi/create_all_maps_from_inputs.py b/scripts/hi/create_all_maps_from_inputs.py
index 2d298ada..a7932067 100644
--- a/scripts/hi/create_all_maps_from_inputs.py
+++ b/scripts/hi/create_all_maps_from_inputs.py
@@ -38,9 +38,7 @@ def run_all_maps(
 
         imap_l3_data_processor.imap_l3_processor()
     spiceypy.kclear()
-    with mock_imap_data_access(
-        output_dir, list(Path(intermediate_output).rglob("*.*"))
-    ):
+    with mock_imap_data_access(output_dir, list(Path(intermediate_output).rglob("*.*"))):
         mock_arguments.descriptor = "hic-maps"
         imap_l3_data_processor.imap_l3_processor()
     spiceypy.kclear()
@@ -50,10 +48,8 @@ def run_all_maps(
     output_dir = Path(f"{datetime.now().strftime('%Y%m%d')}_hi_validation_output")
     try:
         input_dir = Path(sys.argv[1])
-    except Exception:
+    except (IndexError, ValueError):
         input_dir = Path("hi_validation_input")
-        print(
-            f"Could not open input file, using default input path of {input_dir} instead"
-        )
+        print(f"Could not open input file, using default input path of {input_dir} instead")
 
     run_all_maps(output_dir=output_dir, input_dir=input_dir)
diff --git a/scripts/hi/create_cdf_from_ibex.py b/scripts/hi/create_cdf_from_ibex.py
index 8f586f08..70b6c44a 100644
--- a/scripts/hi/create_cdf_from_ibex.py
+++ b/scripts/hi/create_cdf_from_ibex.py
@@ -30,17 +30,15 @@ def extract_data(lines: list[str]):
     if file.parts[-1].endswith("flux.txt") and "mono" not in file.parts[-1]:
         group_file_name_prefix = "-".join(file.parts[-1].split("-")[:-1])
 
-        with open(
-            file.parent / (group_file_name_prefix + "-flux.txt"), "r"
-        ) as flux_file:
+        with open(file.parent / (group_file_name_prefix + "-flux.txt"), "r") as flux_file:
             fluxes.append(extract_data(flux_file.readlines()))
-        with open(
-            file.parent / (group_file_name_prefix + "-fvar.txt"), "r"
-        ) as variance_file:
+        with open(file.parent / (group_file_name_prefix + "-fvar.txt"), "r") as variance_file:
             variances.append(extract_data(variance_file.readlines()))
 
 rng = np.random.default_rng()
-pathname = f"C://Users//Harrison//Development//imap_L3_processing//tests//test_data//{folder.name}.cdf"
+pathname = (
+    f"C://Users//Harrison//Development//imap_L3_processing//tests//test_data//{folder.name}.cdf"
+)
 
 with CDF(pathname, "") as cdf:
     cdf.col_major(True)
diff --git a/scripts/hi/create_cdf_from_instrument_team_data.py b/scripts/hi/create_cdf_from_instrument_team_data.py
index d16c44c1..4f7a609d 100644
--- a/scripts/hi/create_cdf_from_instrument_team_data.py
+++ b/scripts/hi/create_cdf_from_instrument_team_data.py
@@ -26,7 +26,7 @@ def create_l2_map_from_instrument_team(
     epoch = np.array([datetime(2025, 5, 1)])
     epoch_delta = np.array([FIVE_MINUTES_IN_NANOSECONDS])
 
-    data = defaultdict(lambda: {})
+    data = defaultdict(dict)
     for sub_folder in folder.iterdir():
         for file in sub_folder.iterdir():
             energy_string = re.search(r"_(\d*p\d*)keV", file.name).group(1)
@@ -58,9 +58,7 @@ def create_l2_map_from_instrument_team(
     if not np.isclose(pixel_size, 4):
         coords = np.stack(np.meshgrid(lon, lat), axis=-1)
 
-        new_ena_intensity = np.full(
-            (1, ena_intensity.shape[1], len(lon), len(lat)), -1e31
-        )
+        new_ena_intensity = np.full((1, ena_intensity.shape[1], len(lon), len(lat)), -1e31)
         new_ena_intensity_stat_unc = np.full(
             (1, ena_intensity.shape[1], len(lon), len(lat)), -1e31
         )
@@ -90,9 +88,7 @@ def create_l2_map_from_instrument_team(
     pathname = output_dir / f"{folder.name}.cdf"
 
     obs_date = np.full(ena_intensity.shape, datetime.now())
-    obs_date_range = np.full(
-        ena_intensity.shape, ONE_SECOND_IN_NANOSECONDS * SECONDS_PER_DAY * 2
-    )
+    obs_date_range = np.full(ena_intensity.shape, ONE_SECOND_IN_NANOSECONDS * SECONDS_PER_DAY * 2)
 
     exposure_mask = ena_intensity == 0
     exposure_factor = np.full(ena_intensity.shape, 1.0)
@@ -110,9 +106,7 @@ def create_l2_map_from_instrument_team(
         cdf.new("longitude", lon, recVary=False, type=pycdf.const.CDF_FLOAT)
         cdf.new("longitude_delta", lon_delta, recVary=False, type=pycdf.const.CDF_FLOAT)
         cdf.new("longitude_label", lon_label, recVary=False, type=pycdf.const.CDF_CHAR)
-        cdf.new(
-            "ena_intensity", ena_intensity, recVary=True, type=pycdf.const.CDF_FLOAT
-        )
+        cdf.new("ena_intensity", ena_intensity, recVary=True, type=pycdf.const.CDF_FLOAT)
         cdf.new(
             "ena_intensity_stat_uncert",
             ena_intensity_stat_uncert,
@@ -125,13 +119,9 @@ def create_l2_map_from_instrument_team(
             recVary=True,
             type=pycdf.const.CDF_FLOAT,
         )
-        cdf.new(
-            "exposure_factor", exposure_factor, recVary=True, type=pycdf.const.CDF_FLOAT
-        )
+        cdf.new("exposure_factor", exposure_factor, recVary=True, type=pycdf.const.CDF_FLOAT)
         cdf.new("obs_date", obs_date, recVary=True, type=pycdf.const.CDF_TIME_TT2000)
-        cdf.new(
-            "obs_date_range", obs_date_range, recVary=True, type=pycdf.const.CDF_INT8
-        )
+        cdf.new("obs_date_range", obs_date_range, recVary=True, type=pycdf.const.CDF_INT8)
         cdf.new("solid_angle", solid_angle, recVary=True, type=pycdf.const.CDF_FLOAT)
         cdf.new("epoch_delta", epoch_delta, recVary=True, type=pycdf.const.CDF_INT8)
         cdf.new(
@@ -153,9 +143,7 @@ def create_l2_map_from_instrument_team(
 
         for var in cdf:
             if cdf[var].type() == pycdf.const.CDF_TIME_TT2000.value:
-                cdf[var].attrs["FILLVAL"] = datetime.fromisoformat(
-                    "9999-12-31T23:59:59.999999999"
-                )
+                cdf[var].attrs["FILLVAL"] = datetime.fromisoformat("9999-12-31T23:59:59.999999999")
             elif cdf[var].type() == pycdf.const.CDF_INT8.value:
                 cdf[var].attrs["FILLVAL"] = -9223372036854775808
             elif cdf[var].type() == pycdf.const.CDF_FLOAT.value:
diff --git a/scripts/hi/create_hi_full_spin_deps.py b/scripts/hi/create_hi_full_spin_deps.py
index b4122cf5..2d3e0b1a 100644
--- a/scripts/hi/create_hi_full_spin_deps.py
+++ b/scripts/hi/create_hi_full_spin_deps.py
@@ -12,25 +12,27 @@
 )
 from imap_l3_processing.maps.map_models import RectangularIntensityDataProduct
 from imap_l3_processing.models import InputMetadata
-from imap_l3_processing.utils import save_data, furnish_local_spice
+from imap_l3_processing.utils import furnish_local_spice, save_data
 from scripts.hi.create_cdf_from_instrument_team_data import (
     create_l2_map_from_instrument_team,
 )
 from scripts.hi.generate_fake_l1c_cdfs import generate_fake_l1c
 from tests.test_helpers import (
-    get_test_instrument_team_data_path,
-    get_test_data_path,
     get_run_local_data_path,
+    get_test_data_path,
+    get_test_instrument_team_data_path,
 )
 
 
 def create_hi_full_spin_deps(
     sensor="90",
-    output_dir: Path = get_run_local_data_path("hi/full_spin_deps"),
+    output_dir: Path | None = None,
     start_date: datetime = datetime(year=2025, month=4, day=16, hour=12),
-    l2_map_dir: Path = None,
-    glows_dir: Path = None,
+    l2_map_dir: Path | None = None,
+    glows_dir: Path | None = None,
 ):
+    if output_dir is None:
+        output_dir = get_run_local_data_path("hi/full_spin_deps")
     if l2_map_dir is None:
         l2_map_dir = get_test_instrument_team_data_path(f"hi/hi{sensor}-6months")
     if glows_dir is None:
@@ -38,9 +40,7 @@ def create_hi_full_spin_deps(
     l1c_folder = output_dir / "l1c"
     l1c_folder.mkdir(parents=True, exist_ok=True)
 
-    l1c_files = [
-        Path(s) for s in generate_fake_l1c(start_date, 2, output_dir=l1c_folder)
-    ]
+    l1c_files = [Path(s) for s in generate_fake_l1c(start_date, 2, output_dir=l1c_folder)]
     original_full_spin_map_path = create_l2_map_from_instrument_team(
         l2_map_dir, output_dir=output_dir
     )
@@ -85,9 +85,7 @@ def create_hi_full_spin_deps(
         delete_if_present=True,
         folder_path=output_dir,
     )
-    ram_logical_source = (
-        f"imap_hi_l2_h{sensor}-ena-h-sf-nsp-ram-hae-4deg-6mo_20250415_v001"
-    )
+    ram_logical_source = f"imap_hi_l2_h{sensor}-ena-h-sf-nsp-ram-hae-4deg-6mo_20250415_v001"
     with CDF(str(ram_cdf_path), readonly=False) as ram:
         ram["exposure_factor"] = np.where(
             ram_exposure_is_zero, 0, ram_data.intensity_map_data.exposure_factor
@@ -106,18 +104,16 @@ def create_hi_full_spin_deps(
     antiram_data = survival_probability_processing.process_survival_probabilities(
         antiramified_map_deps, SpiceFrame.ECLIPJ2000
     )
-    antiram_exposure_is_zero = np.isnan(
-        antiram_data.intensity_map_data.ena_intensity
-    ) | (antiram_data.intensity_map_data.ena_intensity == 0)
+    antiram_exposure_is_zero = np.isnan(antiram_data.intensity_map_data.ena_intensity) | (
+        antiram_data.intensity_map_data.ena_intensity == 0
+    )
 
     antiram_cdf_path = save_data(
         RectangularIntensityDataProduct(input_metadata, antiram_data),
         delete_if_present=True,
         folder_path=output_dir,
     )
-    antiram_logical_source = (
-        f"imap_hi_l2_h{sensor}-ena-h-sf-nsp-anti-hae-4deg-6mo_20250415_v001"
-    )
+    antiram_logical_source = f"imap_hi_l2_h{sensor}-ena-h-sf-nsp-anti-hae-4deg-6mo_20250415_v001"
 
     with CDF(str(antiram_cdf_path), readonly=False) as antiram:
         antiram["exposure_factor"] = np.where(
diff --git a/scripts/hi/create_l2_from_pointing_sets.py b/scripts/hi/create_l2_from_pointing_sets.py
index fbeb1f1f..eb1ad67f 100644
--- a/scripts/hi/create_l2_from_pointing_sets.py
+++ b/scripts/hi/create_l2_from_pointing_sets.py
@@ -60,7 +60,7 @@ def generate_map(descriptor: str, start: datetime, end: datetime):
     output_filename = f"imap_hi_l2_{descriptor}_{formatted_start_date}_{version}.cdf"
     if not generate_imap_file_path(output_filename).construct_path().exists():
         command = f"imap_cli --instrument hi --data-level l2 --descriptor {descriptor} --start-date {formatted_start_date} --version {version} --dependency {dependency_file}"
-        subprocess.run(command.split(" "), env=env)
+        subprocess.run(command.split(" "), env=env, check=True)
     else:
         print(f"Skipping generation of {output_filename}, it already exists")
 
@@ -74,9 +74,7 @@ def generate_map(descriptor: str, start: datetime, end: datetime):
     for sensor in [45, 90]:
         for side in ["ram", "anti", "full"]:
             for pixelation in [4, 6]:
-                descriptor = (
-                    f"h{sensor}-ena-h-hf-nsp-{side}-hae-{pixelation}deg-{duration}"
-                )
+                descriptor = f"h{sensor}-ena-h-hf-nsp-{side}-hae-{pixelation}deg-{duration}"
                 generate_map(descriptor, start_date, end_date)
 
     duration = "6mo"
@@ -87,7 +85,5 @@ def generate_map(descriptor: str, start: datetime, end: datetime):
                     (datetime(2025, 4, 15), datetime(2025, 10, 15)),
                     (datetime(2025, 10, 15), datetime(2026, 4, 15)),
                 ]:
-                    descriptor = (
-                        f"h{sensor}-ena-h-hf-nsp-{side}-hae-{pixelation}deg-{duration}"
-                    )
+                    descriptor = f"h{sensor}-ena-h-hf-nsp-{side}-hae-{pixelation}deg-{duration}"
                     generate_map(descriptor, start_date, end_date)
diff --git a/scripts/hi/generate_fake_l1c_cdfs.py b/scripts/hi/generate_fake_l1c_cdfs.py
index 20db0ef0..f91a2a84 100644
--- a/scripts/hi/generate_fake_l1c_cdfs.py
+++ b/scripts/hi/generate_fake_l1c_cdfs.py
@@ -7,23 +7,17 @@
 from tests.test_helpers import get_test_data_path
 
 
-def generate_fake_l1c(
-    start_date: datetime, num_days: int, output_dir: Path
-) -> list[str]:
+def generate_fake_l1c(start_date: datetime, num_days: int, output_dir: Path) -> list[str]:
     output_files = []
 
     for i in range(num_days):
         date_to_set = start_date + timedelta(days=i)
-        logical_source = (
-            f"imap_hi_l1c_90sensor-pset_{date_to_set.strftime('%Y%m%d')}_v001"
-        )
+        logical_source = f"imap_hi_l1c_90sensor-pset_{date_to_set.strftime('%Y%m%d')}_v001"
         output_path = output_dir / f"{logical_source}.cdf"
         output_path.unlink(missing_ok=True)
         with CDF(
             str(output_path),
-            masterpath=str(
-                get_test_data_path("hi/imap_hi_l1c_90sensor-pset_20250415_v001.cdf")
-            ),
+            masterpath=str(get_test_data_path("hi/imap_hi_l1c_90sensor-pset_20250415_v001.cdf")),
         ) as cdf:
             del cdf["epoch"]
             cdf.new("epoch", [date_to_set], type=pycdf.const.CDF_TIME_TT2000)
diff --git a/scripts/hi/stack_arrays_to_match_number_of_energies.py b/scripts/hi/stack_arrays_to_match_number_of_energies.py
index b6138e0c..287acac6 100644
--- a/scripts/hi/stack_arrays_to_match_number_of_energies.py
+++ b/scripts/hi/stack_arrays_to_match_number_of_energies.py
@@ -1,12 +1,10 @@
 from datetime import date
 
-from spacepy.pycdf import CDF
 import numpy as np
+from spacepy.pycdf import CDF
 
 filename = f"imap_hi_l3_spectral-fit-index_{date.today().strftime('%Y%m%d')}_"
-temp_cdf = CDF(
-    rf"C:\Users\Harrison\Development\imap_L3_processing\temp_cdf_data\{filename}.cdf"
-)
+temp_cdf = CDF(rf"C:\Users\Harrison\Development\imap_L3_processing\temp_cdf_data\{filename}.cdf")
 map_cdf = CDF(
     rf"C:\Users\Harrison\Development\cava\test\test_data\map_files\map_cdfs\{filename}.cdf"
 )
diff --git a/scripts/hit/create_l1a_direct-event_data.py b/scripts/hit/create_l1a_direct-event_data.py
index 49e598fe..b286a8ad 100644
--- a/scripts/hit/create_l1a_direct-event_data.py
+++ b/scripts/hit/create_l1a_direct-event_data.py
@@ -1,5 +1,5 @@
 import os
-from datetime import timedelta, datetime
+from datetime import datetime, timedelta
 from pathlib import Path
 
 import numpy as np
@@ -8,12 +8,7 @@
 
 path = Path(__file__)
 binary_data_path = (
-    path.parent.parent.parent
-    / "tests"
-    / "test_data"
-    / "hit"
-    / "pha_events"
-    / "pha_binary"
+    path.parent.parent.parent / "tests" / "test_data" / "hit" / "pha_events" / "pha_binary"
 )
 
 start_time = datetime(year=2010, month=1, day=6)
diff --git a/scripts/hit/create_l2_hit_sectored_rates_cdf_from_csv.py b/scripts/hit/create_l2_hit_sectored_rates_cdf_from_csv.py
index 31ebf197..57e6ea1e 100644
--- a/scripts/hit/create_l2_hit_sectored_rates_cdf_from_csv.py
+++ b/scripts/hit/create_l2_hit_sectored_rates_cdf_from_csv.py
@@ -1,4 +1,3 @@
-import traceback
 from datetime import datetime
 from pathlib import Path
 
@@ -11,9 +10,7 @@
 def create_l2_hit_sectored_rates_cdf_from_csv(csv_file_path: str, output_filename: str):
     with CDF(output_filename, "") as cdf:
         cdf.col_major(True)
-        raw_data = np.loadtxt(
-            csv_file_path, delimiter=",", skiprows=1, usecols=range(1, 121)
-        )
+        raw_data = np.loadtxt(csv_file_path, delimiter=",", skiprows=1, usecols=range(1, 121))
         flux_data = raw_data.reshape((-1, 8, 15))
         epoch_count = 1
         start_time = datetime(2025, 1, 1, 0, 5)
@@ -80,10 +77,7 @@ def create_l2_hit_sectored_rates_cdf_from_csv(csv_file_path: str, output_filenam
 if __name__ == "__main__":
     path = Path(__file__)
     input_path = (
-        path.parent.parent.parent
-        / "instrument_team_data"
-        / "hit"
-        / "hit_l2_sectored_sample1.csv"
+        path.parent.parent.parent / "instrument_team_data" / "hit" / "hit_l2_sectored_sample1.csv"
     )
     cdf_file_path = (
         path.parent.parent.parent
@@ -93,7 +87,4 @@ def create_l2_hit_sectored_rates_cdf_from_csv(csv_file_path: str, output_filenam
         / "imap_hit_l2_macropixel-intensity_20250101_v002.cdf"
     )
 
-    try:
-        create_l2_hit_sectored_rates_cdf_from_csv(str(input_path), str(cdf_file_path))
-    except Exception:
-        traceback.print_exc()
+    create_l2_hit_sectored_rates_cdf_from_csv(str(input_path), str(cdf_file_path))
diff --git a/scripts/hit/create_mag_from_csv.py b/scripts/hit/create_mag_from_csv.py
index fdcd60cf..c3d8b191 100644
--- a/scripts/hit/create_mag_from_csv.py
+++ b/scripts/hit/create_mag_from_csv.py
@@ -13,9 +13,7 @@ def create_mag(csv_path, l2_path, output_path, offset):
 
     mag_data = csv_data[offset : offset + epoch_len, -3:]
     mag_sclk = csv_data[offset : offset + epoch_len, 6]
-    mag_epochs = [
-        spiceypy.et2datetime(spiceypy.scs2e(-43, str(sclk))) for sclk in mag_sclk
-    ]
+    mag_epochs = [spiceypy.et2datetime(spiceypy.scs2e(-43, str(sclk))) for sclk in mag_sclk]
     print(mag_sclk[0])
     print(mag_epochs[:5])
     print(epoch[:5])
diff --git a/scripts/hit/hit_plots.py b/scripts/hit/hit_plots.py
index c372dc66..e392678b 100644
--- a/scripts/hit/hit_plots.py
+++ b/scripts/hit/hit_plots.py
@@ -8,7 +8,7 @@
 xs = []
 ys = []
 
-for i in range(0, len(de["energy"][...])):
+for i in range(len(de["energy"][...])):
     if de["range"][i] == 3 and de["side"][i] == 1 and de["stim_tag"][i] != 1:
         ys.append(de["delta_e"][i])
         xs.append(de["e_prime"][i])
diff --git a/scripts/lo/combine_existing_maps_to_fix_frozen_data.py b/scripts/lo/combine_existing_maps_to_fix_frozen_data.py
index 7471194e..8cbf6397 100644
--- a/scripts/lo/combine_existing_maps_to_fix_frozen_data.py
+++ b/scripts/lo/combine_existing_maps_to_fix_frozen_data.py
@@ -35,7 +35,7 @@ def copy_to_output_directory(release_directory: Path, output_maps: list[Path]):
     lo_input_data_dir = get_run_local_data_path("input_lo_txt_pipeline")
     maps_to_combine = lo_input_data_dir / "maps_to_combine"
     if not maps_to_combine.exists():
-        raise Exception(f"Place maps to combine in {maps_to_combine}")
+        raise FileNotFoundError(f"Place maps to combine in {maps_to_combine}")
 
     maps_needed_for_combination = [
         (
diff --git a/scripts/lo/create_l2_from_pointing_sets.py b/scripts/lo/create_l2_from_pointing_sets.py
index 0b633d35..14107189 100644
--- a/scripts/lo/create_l2_from_pointing_sets.py
+++ b/scripts/lo/create_l2_from_pointing_sets.py
@@ -57,7 +57,7 @@ def generate_map(descriptor: str, start: datetime):
     command = f"imap_cli --instrument lo --data-level l2 --descriptor {descriptor} --start-date {formatted_start_date} --version {version} --dependency {dependency_file}"
     print(command)
     if not generate_imap_file_path(output_filename).construct_path().exists():
-        subprocess.run(command.split(" "), env=env)
+        subprocess.run(command.split(" "), env=env, check=True)
     else:
         print(f"Skipping generation of {output_filename}, it already exists")
 
diff --git a/scripts/make_cdf_all_fill.py b/scripts/make_cdf_all_fill.py
index 5f2f8cfd..f8f257e7 100644
--- a/scripts/make_cdf_all_fill.py
+++ b/scripts/make_cdf_all_fill.py
@@ -13,10 +13,7 @@
 shutil.copy(args.template_cdf, output_file_name)
 with CDF(output_file_name, readonly=False) as cdf:
     for var in cdf:
-        if (
-            var not in ["Epoch", "epoch"]
-            and cdf[var].attrs.get("VAR_TYPE") != "metadata"
-        ):
+        if var not in ["Epoch", "epoch"] and cdf[var].attrs.get("VAR_TYPE") != "metadata":
             if "FILLVAL" in cdf[var].attrs:
                 cdf[var] = np.full_like(cdf[var], cdf[var].attrs["FILLVAL"])
             else:
diff --git a/scripts/poll_batch_jobs_status.py b/scripts/poll_batch_jobs_status.py
index 24b3cbee..3a20869a 100644
--- a/scripts/poll_batch_jobs_status.py
+++ b/scripts/poll_batch_jobs_status.py
@@ -15,10 +15,7 @@ def format_job(job) -> str:
     input_collection.deserialize(dependencies_passed)
 
     processing_input = "\n".join(
-        [
-            f"\t\t{type(pi)}: {pi.filename_list}"
-            for pi in input_collection.processing_input
-        ]
+        [f"\t\t{type(pi)}: {pi.filename_list}" for pi in input_collection.processing_input]
     )
 
     return f"""
@@ -39,16 +36,13 @@ def format_job(job) -> str:
 url = "https://api.dev.imap-mission.com/batch-job"
 
 while True:
-    response = requests.get(
-        url=url, params={"instrument": INSTRUMENT, "data_level": DATA_LEVEL}
-    )
+    response = requests.get(url=url, params={"instrument": INSTRUMENT, "data_level": DATA_LEVEL})
     logs = json.loads(json.dumps(response.json()))
     relevant_logs = [
         log
         for log in logs
         if log["started_at"] is not None
-        and datetime.fromisoformat(log["started_at"]).replace(tzinfo=timezone.utc)
-        > AFTER_DATE
+        and datetime.fromisoformat(log["started_at"]).replace(tzinfo=timezone.utc) > AFTER_DATE
     ]
 
     print("\n".join([format_job(job) for job in relevant_logs]))
diff --git a/scripts/run_spectral_index.py b/scripts/run_spectral_index.py
index f90659f1..5995f23f 100644
--- a/scripts/run_spectral_index.py
+++ b/scripts/run_spectral_index.py
@@ -4,19 +4,19 @@
 from pathlib import Path
 
 from imap_data_access import (
-    ScienceFilePath,
+    AncillaryInput,
     ProcessingInputCollection,
+    ScienceFilePath,
     ScienceInput,
-    AncillaryInput,
 )
 from imap_data_access.file_validation import Version
 
 from imap_l3_processing.hi.hi_processor import HiProcessor
 from imap_l3_processing.lo.lo_processor import LoProcessor
 from imap_l3_processing.maps.map_descriptors import (
-    parse_map_descriptor,
     MapQuantity,
     map_descriptor_parts_to_string,
+    parse_map_descriptor,
 )
 from imap_l3_processing.models import InputMetadata, VersionMap
 from imap_l3_processing.ultra.ultra_processor import UltraProcessor
@@ -36,9 +36,7 @@ def run_spectral_index(input: Path):
 
     dependencies = ProcessingInputCollection(ScienceInput(input.name))
     if parsed.instrument == "ultra":
-        dependencies.add(
-            AncillaryInput("imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat")
-        )
+        dependencies.add(AncillaryInput("imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat"))
 
     data_path = parsed.construct_path()
     data_path.parent.mkdir(parents=True, exist_ok=True)
diff --git a/scripts/swapi/determine_swapi_files_with_outdated_spice.py b/scripts/swapi/determine_swapi_files_with_outdated_spice.py
index b890df0b..4c431637 100644
--- a/scripts/swapi/determine_swapi_files_with_outdated_spice.py
+++ b/scripts/swapi/determine_swapi_files_with_outdated_spice.py
@@ -17,7 +17,7 @@
         file_path = imap_data_access.download(result["file_path"])
 
         with CDF(str(file_path)) as cdf:
-            used_predict = any(["pred" in entry for entry in cdf.attrs["Parents"]])
+            used_predict = any("pred" in entry for entry in cdf.attrs["Parents"])
 
             if used_predict:
                 dates_that_used_predict.append(result["start_date"])
diff --git a/scripts/swapi/fake_alpha_sw_temperature_density_lut_generator.py b/scripts/swapi/fake_alpha_sw_temperature_density_lut_generator.py
index 89a7eb3a..a5668c1c 100644
--- a/scripts/swapi/fake_alpha_sw_temperature_density_lut_generator.py
+++ b/scripts/swapi/fake_alpha_sw_temperature_density_lut_generator.py
@@ -9,9 +9,7 @@
 densities = np.arange(1, 6.5, 0.5)
 temps = np.arange(1e4, 1.6e5, 1e4)
 
-with open(
-    "imap_swapi_l2_alpha-density-temperature-lut-text-not-cdf_20240905_v002.cdf", "w"
-) as f:
+with open("imap_swapi_l2_alpha-density-temperature-lut-text-not-cdf_20240905_v002.cdf", "w") as f:
     f.write("#\n")
     f.write(f"# Created on: {today()}\n")
     f.write("#\n")
@@ -19,7 +17,7 @@
     f.write("#\n")
     f.write("#   u_sw     n     density (cm^-3)     T     temperature (K)\n")
 
-    for u_sw, density, temp in itertools.product(u_sw_values, densities, temps):
-        f.write(
-            f"{u_sw}  {density}  {density * 1.021:.4f}  {temp:.4e}  {temp / 1.025:0.4e}\n"
-        )
+    f.writelines(
+        f"{u_sw}  {density}  {density * 1.021:.4f}  {temp:.4e}  {temp / 1.025:0.4e}\n"
+        for u_sw, density, temp in itertools.product(u_sw_values, densities, temps)
+    )
diff --git a/scripts/swapi/fake_data_generator.py b/scripts/swapi/fake_data_generator.py
index 3aafb965..b74d47d5 100644
--- a/scripts/swapi/fake_data_generator.py
+++ b/scripts/swapi/fake_data_generator.py
@@ -30,9 +30,7 @@ def generate_sweeps(n=5):
 
 def generate_sweep_energies():
     coarse_sweep_energies = np.geomspace(100, 19000, 62)
-    return np.concatenate(
-        (np.array([np.nan]), coarse_sweep_energies, np.array([np.nan] * 9))
-    )
+    return np.concatenate((np.array([np.nan]), coarse_sweep_energies, np.array([np.nan] * 9)))
 
 
 # K Factor may come from a lookup table in the future
@@ -45,11 +43,9 @@ def get_spin_phase_using_spice(time):
     arbitrary_offset = 0.4
     rotation_time = 15
     rotations = arbitrary_offset + time / rotation_time
-    fractional, integral = np.modf(rotations)
+    fractional, _integral = np.modf(rotations)
     return fractional * 360
 
 
 def generate_peak(energies, height, center, narrowness):
-    return np.exp(
-        np.log(height) - narrowness * np.square(np.log(energies) - np.log(center))
-    )
+    return np.exp(np.log(height) - narrowness * np.square(np.log(energies) - np.log(center)))
diff --git a/scripts/swapi/fit_and_plot_alpha.py b/scripts/swapi/fit_and_plot_alpha.py
index 43cff380..7a11d8b9 100644
--- a/scripts/swapi/fit_and_plot_alpha.py
+++ b/scripts/swapi/fit_and_plot_alpha.py
@@ -45,8 +45,7 @@
 # well below 9000 in every numeric column.
 WIND_FILL_THRESHOLD = 9000.0
 WIND_FTP_URL_TEMPLATE = (
-    "ftp://nssdcftp.gsfc.nasa.gov/pub/data/wind/swe/ascii/2-min/"
-    "wind_swe_2m_sw{yyyymm}.asc"
+    "ftp://nssdcftp.gsfc.nasa.gov/pub/data/wind/swe/ascii/2-min/wind_swe_2m_sw{yyyymm}.asc"
 )
 
 L3_PROCESSING_ROOT = Path(imap_l3_processing.__file__).parent.parent
@@ -136,9 +135,7 @@ def fetch_wind_swe_2min_alphas(compact_date_string, cache_directory):
     alpha_density_sigma = row[:, 38]
 
     # T = c * W^2 -> sigma_T = 2 * c * W * sigma_W (linear propagation, W >= 0).
-    alpha_temperature = (
-        WIND_ALPHA_TEMPERATURE_FACTOR_K_PER_KM2_PER_S2 * alpha_thermal_speed**2
-    )
+    alpha_temperature = WIND_ALPHA_TEMPERATURE_FACTOR_K_PER_KM2_PER_S2 * alpha_thermal_speed**2
     alpha_temperature_sigma = (
         2.0
         * WIND_ALPHA_TEMPERATURE_FACTOR_K_PER_KM2_PER_S2
@@ -204,9 +201,7 @@ def build_dependency_collection(target_date, compact_date):
         SpiceKernelTypes.EphemerisReconstructed,
         SpiceKernelTypes.EphemerisPredicted,
     ]
-    non_ephemeris_kernel_types = [
-        t for t in SpiceKernelTypes if t not in ephemeris_kernel_types
-    ]
+    non_ephemeris_kernel_types = [t for t in SpiceKernelTypes if t not in ephemeris_kernel_types]
     spice_kernel_filenames = list(
         dict.fromkeys(
             os.path.basename(path)
@@ -271,9 +266,7 @@ def build_dependency_collection(target_date, compact_date):
     processing_input_collection = build_dependency_collection(target_date, compact_date)
     processing_input_collection.download_all_files()
 
-    dependency_filename = (
-        f"imap_swapi_l3a_alpha-sw_{compact_date}_{PROCESSOR_OUTPUT_VERSION}.json"
-    )
+    dependency_filename = f"imap_swapi_l3a_alpha-sw_{compact_date}_{PROCESSOR_OUTPUT_VERSION}.json"
     dependency_path = DependencyFilePath(dependency_filename).construct_path()
     dependency_path.parent.mkdir(parents=True, exist_ok=True)
     dependency_path.write_text(processing_input_collection.serialize())
@@ -296,6 +289,7 @@ def build_dependency_collection(target_date, compact_date):
             "--dependency",
             dependency_filename,
         ],
+        check=False,
         cwd=L3_PROCESSING_ROOT,
     )
     if result.returncode != 0:
@@ -307,13 +301,9 @@ def build_dependency_collection(target_date, compact_date):
     timestamps = alpha_cdf["epoch"][...]
     quality_flags = alpha_cdf["swp_flags"][...]
     swapi_density = read_numeric_variable(alpha_cdf["alpha_sw_density"])
-    swapi_density_uncertainty = read_numeric_variable(
-        alpha_cdf["alpha_sw_density_uncert"]
-    )
+    swapi_density_uncertainty = read_numeric_variable(alpha_cdf["alpha_sw_density_uncert"])
     swapi_temperature = read_numeric_variable(alpha_cdf["alpha_sw_temperature"])
-    swapi_temperature_uncertainty = read_numeric_variable(
-        alpha_cdf["alpha_sw_temperature_uncert"]
-    )
+    swapi_temperature_uncertainty = read_numeric_variable(alpha_cdf["alpha_sw_temperature_uncert"])
     swapi_speed = read_numeric_variable(alpha_cdf["alpha_sw_speed"])
     swapi_speed_uncertainty = read_numeric_variable(alpha_cdf["alpha_sw_speed_uncert"])
     swapi_velocity_rtn = read_numeric_variable(alpha_cdf["alpha_sw_velocity_rtn_sun"])
@@ -334,9 +324,7 @@ def build_dependency_collection(target_date, compact_date):
 swapi_velocity_rtn_covariance = swapi_velocity_rtn_covariance[good_record_mask]
 
 # Diagonal of the RTN velocity covariance gives variances on (vR, vT, vN).
-swapi_velocity_rtn_sigma = np.sqrt(
-    np.diagonal(swapi_velocity_rtn_covariance, axis1=1, axis2=2)
-)
+swapi_velocity_rtn_sigma = np.sqrt(np.diagonal(swapi_velocity_rtn_covariance, axis1=1, axis2=2))
 
 wind_alphas = fetch_wind_swe_2min_alphas(compact_date, DATA_DIR / "wind") or {}
 
diff --git a/scripts/swapi/fit_and_plot_proton.py b/scripts/swapi/fit_and_plot_proton.py
index 543b0026..c50fc830 100644
--- a/scripts/swapi/fit_and_plot_proton.py
+++ b/scripts/swapi/fit_and_plot_proton.py
@@ -45,8 +45,7 @@
 # well below 9000 in every numeric column.
 WIND_FILL_THRESHOLD = 9000.0
 WIND_FTP_URL_TEMPLATE = (
-    "ftp://nssdcftp.gsfc.nasa.gov/pub/data/wind/swe/ascii/2-min/"
-    "wind_swe_2m_sw{yyyymm}.asc"
+    "ftp://nssdcftp.gsfc.nasa.gov/pub/data/wind/swe/ascii/2-min/wind_swe_2m_sw{yyyymm}.asc"
 )
 
 L3_PROCESSING_ROOT = Path(imap_l3_processing.__file__).parent.parent
@@ -135,9 +134,7 @@ def fetch_wind_swe_2min_protons(compact_date_string, cache_directory):
     proton_thermal_speed, proton_thermal_speed_sigma = row[:, 11], row[:, 12]
     proton_density, proton_density_sigma = row[:, 21], row[:, 22]
 
-    proton_temperature = (
-        WIND_PROTON_TEMPERATURE_FACTOR_K_PER_KM2_PER_S2 * proton_thermal_speed**2
-    )
+    proton_temperature = WIND_PROTON_TEMPERATURE_FACTOR_K_PER_KM2_PER_S2 * proton_thermal_speed**2
     proton_temperature_sigma = (
         2.0
         * WIND_PROTON_TEMPERATURE_FACTOR_K_PER_KM2_PER_S2
@@ -196,9 +193,7 @@ def build_dependency_collection(target_date, compact_date):
         SpiceKernelTypes.EphemerisReconstructed,
         SpiceKernelTypes.EphemerisPredicted,
     ]
-    non_ephemeris_kernel_types = [
-        t for t in SpiceKernelTypes if t not in ephemeris_kernel_types
-    ]
+    non_ephemeris_kernel_types = [t for t in SpiceKernelTypes if t not in ephemeris_kernel_types]
     spice_kernel_filenames = list(
         dict.fromkeys(
             os.path.basename(path)
@@ -286,6 +281,7 @@ def build_dependency_collection(target_date, compact_date):
             "--dependency",
             dependency_filename,
         ],
+        check=False,
         cwd=L3_PROCESSING_ROOT,
     )
     if result.returncode != 0:
@@ -297,17 +293,13 @@ def build_dependency_collection(target_date, compact_date):
     timestamps = proton_cdf["epoch"][...]
     quality_flags = proton_cdf["swp_flags"][...]
     swapi_density = read_numeric_variable(proton_cdf["proton_sw_density"])
-    swapi_density_uncertainty = read_numeric_variable(
-        proton_cdf["proton_sw_density_uncert"]
-    )
+    swapi_density_uncertainty = read_numeric_variable(proton_cdf["proton_sw_density_uncert"])
     swapi_temperature = read_numeric_variable(proton_cdf["proton_sw_temperature"])
     swapi_temperature_uncertainty = read_numeric_variable(
         proton_cdf["proton_sw_temperature_uncert"]
     )
     swapi_speed = read_numeric_variable(proton_cdf["proton_sw_speed"])
-    swapi_speed_uncertainty = read_numeric_variable(
-        proton_cdf["proton_sw_speed_uncert"]
-    )
+    swapi_speed_uncertainty = read_numeric_variable(proton_cdf["proton_sw_speed_uncert"])
     swapi_velocity_rtn = read_numeric_variable(proton_cdf["proton_sw_velocity_rtn_sun"])
     swapi_velocity_rtn_covariance = read_numeric_variable(
         proton_cdf["proton_sw_velocity_rtn_covariance"]
@@ -324,9 +316,7 @@ def build_dependency_collection(target_date, compact_date):
 swapi_velocity_rtn = swapi_velocity_rtn[good_record_mask]
 swapi_velocity_rtn_covariance = swapi_velocity_rtn_covariance[good_record_mask]
 
-swapi_velocity_rtn_sigma = np.sqrt(
-    np.diagonal(swapi_velocity_rtn_covariance, axis1=1, axis2=2)
-)
+swapi_velocity_rtn_sigma = np.sqrt(np.diagonal(swapi_velocity_rtn_covariance, axis1=1, axis2=2))
 
 wind_protons = fetch_wind_swe_2min_protons(compact_date, DATA_DIR / "wind") or {}
 
diff --git a/scripts/swapi/fit_and_plot_pui.py b/scripts/swapi/fit_and_plot_pui.py
index 859b4d75..b032f0ee 100644
--- a/scripts/swapi/fit_and_plot_pui.py
+++ b/scripts/swapi/fit_and_plot_pui.py
@@ -42,6 +42,12 @@
     SWAPI_COARSE_SWEEP_BINS,
     SWAPI_L2_K_FACTOR,
 )
+from imap_l3_processing.swapi.l3a.chunk_fits import (
+    ParallelChunkRunner,
+    ProtonChunkFitter,
+    PuiChunkFitter,
+)
+from imap_l3_processing.swapi.l3a.models import SwapiL3PickupIonData
 from imap_l3_processing.swapi.l3a.science.pickup_ion.calculate_coincidence_rate import (
     calculate_coincidence_rate,
 )
@@ -51,24 +57,17 @@
 from imap_l3_processing.swapi.l3a.science.pickup_ion.collapsed_response_grid import (
     build_chunk_collapsed_response,
 )
+from imap_l3_processing.swapi.l3a.science.pickup_ion.utils import (
+    rotate_rtn_velocity_to_swapi_per_bin,
+)
 from imap_l3_processing.swapi.l3a.science.pickup_ion.vasyliunas_siscoe_distribution import (
     FittingParameters,
     build_vasyliunas_siscoe_distribution,
 )
-from imap_l3_processing.swapi.l3a.chunk_fits import (
-    ParallelChunkRunner,
-    ProtonChunkFitter,
-    PuiChunkFitter,
-)
-from imap_l3_processing.swapi.l3a.models import SwapiL3PickupIonData
-from imap_l3_processing.swapi.l3a.science.pickup_ion.utils import (
-    rotate_rtn_velocity_to_swapi_per_bin,
-)
 from imap_l3_processing.swapi.l3a.swapi_l3a_dependencies import SwapiL3ADependencies
 from imap_l3_processing.swapi.l3a.utils import chunk_l2_data
 from imap_l3_processing.utils import SpiceKernelTypes, get_spice_kernels_file_names
 
-
 _HELIUM_MASS_PER_CHARGE_M_P_PER_E = HE_PUI_PARTICLE_MASS_PER_CHARGE_M_P_PER_E
 _COARSE_SWEEP_LEN = 62
 
@@ -81,17 +80,11 @@ def replay_chunk_spectrum(
     Mirrors the geometry path in calculate_pickup_ion_values so the energies
     and modeled rate match production exactly.
     """
-    chunk_ephemeris_time = spiceypy.unitim(
-        center_of_epoch / ONE_SECOND_IN_NANOSECONDS, "TT", "ET"
-    )
+    chunk_ephemeris_time = spiceypy.unitim(center_of_epoch / ONE_SECOND_IN_NANOSECONDS, "TT", "ET")
     sw_velocity_kms = float(np.linalg.norm(sw_velocity_rtn_kms))
 
-    voltages_flat = (
-        data_chunk.energy[:, SWAPI_COARSE_SWEEP_BINS] / SWAPI_L2_K_FACTOR
-    ).flatten()
-    count_rates_flat = data_chunk.coincidence_count_rate[
-        :, SWAPI_COARSE_SWEEP_BINS
-    ].flatten()
+    voltages_flat = (data_chunk.energy[:, SWAPI_COARSE_SWEEP_BINS] / SWAPI_L2_K_FACTOR).flatten()
+    count_rates_flat = data_chunk.coincidence_count_rate[:, SWAPI_COARSE_SWEEP_BINS].flatten()
     central_effective_area_scale = (
         dependencies.efficiency_calibration_table.central_effective_area_scale_for(
             center_of_epoch, "helium"
@@ -212,9 +205,7 @@ def replay_chunk_spectrum(
         SpiceKernelTypes.EphemerisReconstructed,
         SpiceKernelTypes.EphemerisPredicted,
     ]
-    non_ephemeris_kernel_types = [
-        t for t in SpiceKernelTypes if t not in ephemeris_kernel_types
-    ]
+    non_ephemeris_kernel_types = [t for t in SpiceKernelTypes if t not in ephemeris_kernel_types]
     spice_kernel_filenames = list(
         dict.fromkeys(
             os.path.basename(path)
@@ -258,16 +249,12 @@ def replay_chunk_spectrum(
     )
 
     if not arguments.use_cache or not cache_path.exists():
-        dependencies.swapi_response.warm_cache(
-            dependencies.data.energy / SWAPI_L2_K_FACTOR
-        )
+        dependencies.swapi_response.warm_cache(dependencies.data.energy / SWAPI_L2_K_FACTOR)
         runner = ParallelChunkRunner(
             dependencies.swapi_response, dependencies.efficiency_calibration_table
         )
         pui_chunks = list(chunk_l2_data(dependencies.data, 50))
-        proton_results = runner.run(
-            list(chunk_l2_data(dependencies.data, 5)), ProtonChunkFitter()
-        )
+        proton_results = runner.run(list(chunk_l2_data(dependencies.data, 5)), ProtonChunkFitter())
         pui_fitter = PuiChunkFitter(
             density_of_neutral_helium_lookup_table=dependencies.density_of_neutral_helium_calibration_table,
             hydrogen_inflow_vector=dependencies.hydrogen_inflow_vector,
@@ -288,22 +275,14 @@ def replay_chunk_spectrum(
         pickup_ion_data, sw_velocity_rtn_by_chunk_epoch = pickle.load(cache_file)
 
     epochs_tt2000 = np.asarray(pickup_ion_data.epoch, dtype=np.int64)
-    timestamps = np.array(
-        [cdf_library.tt2000_to_datetime(int(t)) for t in epochs_tt2000]
-    )
+    timestamps = np.array([cdf_library.tt2000_to_datetime(int(t)) for t in epochs_tt2000])
 
-    spectrogram_cache_path = Path(
-        f"/tmp/swapi_pui_spectrograms_per_sweep_{compact_date}.pkl"
-    )
+    spectrogram_cache_path = Path(f"/tmp/swapi_pui_spectrograms_per_sweep_{compact_date}.pkl")
     all_chunks = list(chunk_l2_data(dependencies.data, 50))
 
     if not arguments.use_cache or not spectrogram_cache_path.exists():
-        print(
-            "Building per-sweep observed and modeled spectrograms (one replay per chunk)..."
-        )
-        dependencies.swapi_response.warm_cache(
-            dependencies.data.energy / SWAPI_L2_K_FACTOR
-        )
+        print("Building per-sweep observed and modeled spectrograms (one replay per chunk)...")
+        dependencies.swapi_response.warm_cache(dependencies.data.energy / SWAPI_L2_K_FACTOR)
 
         chunk_count = min(len(all_chunks), len(epochs_tt2000))
         per_sweep_voltages = []
@@ -313,15 +292,11 @@ def replay_chunk_spectrum(
 
         for chunk_index in range(chunk_count):
             data_chunk = all_chunks[chunk_index]
-            voltages_2d = (
-                data_chunk.energy[:, SWAPI_COARSE_SWEEP_BINS] / SWAPI_L2_K_FACTOR
-            )
+            voltages_2d = data_chunk.energy[:, SWAPI_COARSE_SWEEP_BINS] / SWAPI_L2_K_FACTOR
             rates_2d = data_chunk.coincidence_count_rate[:, SWAPI_COARSE_SWEEP_BINS]
             per_sweep_voltages.append(voltages_2d)
             per_sweep_observed.append(rates_2d)
-            per_sweep_epoch_tt2000.append(
-                np.asarray(data_chunk.sci_start_time, dtype=np.int64)
-            )
+            per_sweep_epoch_tt2000.append(np.asarray(data_chunk.sci_start_time, dtype=np.int64))
 
             model_rates_for_chunk = np.full_like(rates_2d, np.nan, dtype=float)
 
@@ -345,17 +320,13 @@ def replay_chunk_spectrum(
                             pickup_ion_data.background_rate[chunk_index],
                         ),
                     )
-                except Exception as replay_error:
+                except Exception as replay_error:  # noqa: BLE001
                     print(f"chunk {chunk_index} replay failed: {replay_error}")
                 else:
-                    model_rates_for_chunk[:, replay["bin_mask"]] = replay[
-                        "modeled_rate_per_sweep"
-                    ]
+                    model_rates_for_chunk[:, replay["bin_mask"]] = replay["modeled_rate_per_sweep"]
             per_sweep_model.append(model_rates_for_chunk)
 
-        energies_per_sweep_ev = (
-            np.concatenate(per_sweep_voltages, axis=0) * SWAPI_L2_K_FACTOR
-        )
+        energies_per_sweep_ev = np.concatenate(per_sweep_voltages, axis=0) * SWAPI_L2_K_FACTOR
         observed_spectrogram = np.concatenate(per_sweep_observed, axis=0)
         model_spectrogram = np.concatenate(per_sweep_model, axis=0)
         sweep_epochs_tt2000 = np.concatenate(per_sweep_epoch_tt2000, axis=0)
@@ -390,10 +361,7 @@ def replay_chunk_spectrum(
     model_sorted = model_spectrogram[:, energy_sort_order]
 
     positive_rate_values = np.concatenate(
-        [
-            array[np.isfinite(array) & (array > 0)]
-            for array in (observed_sorted, model_sorted)
-        ]
+        [array[np.isfinite(array) & (array > 0)] for array in (observed_sorted, model_sorted)]
     )
     if positive_rate_values.size:
         rate_vmin = max(float(np.percentile(positive_rate_values, 1)), 1e-3)
@@ -423,9 +391,7 @@ def replay_chunk_spectrum(
     figure.colorbar(observed_mesh, ax=observed_axis, label="rate / s$^{-1}$")
     plt.setp(observed_axis.get_xticklabels(), visible=False)
 
-    model_axis = figure.add_subplot(
-        grid_spec[1], sharex=observed_axis, sharey=observed_axis
-    )
+    model_axis = figure.add_subplot(grid_spec[1], sharex=observed_axis, sharey=observed_axis)
     model_mesh = model_axis.pcolormesh(
         sweep_timestamps,
         mean_energies_ev_sorted,
@@ -436,9 +402,7 @@ def replay_chunk_spectrum(
     )
     model_axis.set_yscale("log")
     model_axis.set_ylabel("Energy / eV")
-    model_axis.set_title(
-        "Fitted helium PUI model coincidence count rate (per 12 s sweep)"
-    )
+    model_axis.set_title("Fitted helium PUI model coincidence count rate (per 12 s sweep)")
     figure.colorbar(model_mesh, ax=model_axis, label="rate / s$^{-1}$")
     plt.setp(model_axis.get_xticklabels(), visible=False)
 
@@ -489,23 +453,18 @@ def replay_chunk_spectrum(
             for _, _, _, cdf_var_name in timeseries_panels:
                 published_l3a_values_by_var[cdf_var_name] = (
                     np.asarray(published_cdf[cdf_var_name][...], dtype=float),
-                    np.asarray(
-                        published_cdf[f"{cdf_var_name}_uncert"][...], dtype=float
-                    ),
+                    np.asarray(published_cdf[f"{cdf_var_name}_uncert"][...], dtype=float),
                 )
 
     local_flags = np.asarray(pickup_ion_data.quality_flags, dtype=np.int64)
     local_flagged = local_flags != 0
 
-    for panel_index, (ylabel, yscale, values, cdf_var_name) in enumerate(
-        timeseries_panels
-    ):
+    for panel_index, (ylabel, yscale, values, cdf_var_name) in enumerate(timeseries_panels):
         axis = figure.add_subplot(grid_spec[panel_index + 2], sharex=observed_axis)
         nominal_values_array = unumpy.nominal_values(values)
         std_devs_array = unumpy.std_devs(values)
         show_legend = (
-            panel_index == CUTOFF_SPEED_PANEL_INDEX
-            or published_l3a_timestamps is not None
+            panel_index == CUTOFF_SPEED_PANEL_INDEX or published_l3a_timestamps is not None
         )
         axis.errorbar(
             timestamps,
@@ -528,9 +487,7 @@ def replay_chunk_spectrum(
                 label="flag != 0" if show_legend else None,
             )
         if published_l3a_timestamps is not None:
-            published_nominal, published_uncert = published_l3a_values_by_var[
-                cdf_var_name
-            ]
+            published_nominal, published_uncert = published_l3a_values_by_var[cdf_var_name]
             valid = (
                 np.isfinite(published_nominal)
                 & (published_uncert >= 0)
@@ -562,10 +519,7 @@ def replay_chunk_spectrum(
                 linewidth=0,
                 label=r"$\pm 20\%$ SW speed",
             )
-        if (
-            panel_index == CUTOFF_SPEED_PANEL_INDEX
-            or published_l3a_timestamps is not None
-        ):
+        if panel_index == CUTOFF_SPEED_PANEL_INDEX or published_l3a_timestamps is not None:
             axis.legend(loc="best", fontsize="small")
         axis.set_ylabel(ylabel)
         axis.set_yscale(yscale)
diff --git a/scripts/swapi/generate_cdf_from_dat.py b/scripts/swapi/generate_cdf_from_dat.py
index 81337a62..83d0c940 100644
--- a/scripts/swapi/generate_cdf_from_dat.py
+++ b/scripts/swapi/generate_cdf_from_dat.py
@@ -13,10 +13,7 @@
 def generate_cdf_from_dat(dat_file_path: str, output_filename: str):
     dat_data = read_l2_data_from_dat(dat_file_path)
     cdf_file_path = (
-        Path(imap_l3_processing.__file__).parent.parent
-        / "swapi"
-        / "test_data"
-        / output_filename
+        Path(imap_l3_processing.__file__).parent.parent / "swapi" / "test_data" / output_filename
     )
 
     with CDF(str(cdf_file_path), "") as cdf:
@@ -31,8 +28,6 @@ def generate_cdf_from_dat(dat_file_path: str, output_filename: str):
 
 if __name__ == "__main__":
     generate_cdf_from_dat(
-        os.path.abspath(
-            "../../instrument_team_data/swapi/swapi_test_data_50_sweeps.dat"
-        ),
+        os.path.abspath("../../instrument_team_data/swapi/swapi_test_data_50_sweeps.dat"),
         "imap_swapi_l2_sci_20100101_v001",
     )
diff --git a/scripts/swapi/generate_collapsed_response_grid_reference.py b/scripts/swapi/generate_collapsed_response_grid_reference.py
old mode 100644
new mode 100755
index 0222fb92..dc7256c1
--- a/scripts/swapi/generate_collapsed_response_grid_reference.py
+++ b/scripts/swapi/generate_collapsed_response_grid_reference.py
@@ -38,11 +38,7 @@
 
 _REPO_ROOT = Path(__file__).resolve().parents[2]
 _OUTPUT_PATH = (
-    _REPO_ROOT
-    / "tests"
-    / "test_data"
-    / "swapi"
-    / "collapsed_response_grid_reference.csv"
+    _REPO_ROOT / "tests" / "test_data" / "swapi" / "collapsed_response_grid_reference.csv"
 )
 
 _N_POINTS = 256
@@ -92,9 +88,7 @@ def shell_integral_h(
 
     # Right-handed orthonormal frame with bulk_direction as polar axis.
     e_in_xy = np.array([-math.cos(bulk_azimuth), math.sin(bulk_azimuth), 0.0])
-    rotation = np.column_stack(
-        [e_in_xy, np.cross(bulk_direction, e_in_xy), bulk_direction]
-    )
+    rotation = np.column_stack([e_in_xy, np.cross(bulk_direction, e_in_xy), bulk_direction])
 
     def integrate(passband, azimuth_min_deg, azimuth_max_deg):
         return dblquad(
@@ -146,33 +140,21 @@ def _shell_integrand(
     local_x = sin_alpha * math.cos(beta)
     local_y = sin_alpha * math.sin(beta)
     local_z = math.cos(alpha)
-    shell_x = (
-        rotation[0, 0] * local_x + rotation[0, 1] * local_y + rotation[0, 2] * local_z
-    )
-    shell_y = (
-        rotation[1, 0] * local_x + rotation[1, 1] * local_y + rotation[1, 2] * local_z
-    )
-    shell_z = (
-        rotation[2, 0] * local_x + rotation[2, 1] * local_y + rotation[2, 2] * local_z
-    )
+    shell_x = rotation[0, 0] * local_x + rotation[0, 1] * local_y + rotation[0, 2] * local_z
+    shell_y = rotation[1, 0] * local_x + rotation[1, 1] * local_y + rotation[1, 2] * local_z
+    shell_z = rotation[2, 0] * local_x + rotation[2, 1] * local_y + rotation[2, 2] * local_z
     vx = velocity[0] + v_prime * shell_x
     vy = velocity[1] + v_prime * shell_y
     vz = velocity[2] + v_prime * shell_z
     speed = math.sqrt(vx * vx + vy * vy + vz * vz)
-    azimuth_deg, elevation_deg = velocity_components_to_angles_in_instrument_frame(
-        vx, vy, vz
-    )
+    azimuth_deg, elevation_deg = velocity_components_to_angles_in_instrument_frame(vx, vy, vz)
     if not (azimuth_min_deg <= azimuth_deg <= azimuth_max_deg):
         return 0.0
     effective_area = (
         response_grid.central_effective_area
         * _EFFECTIVE_AREA_CM2_TO_KM2
-        * interpolate_passband(
-            passband, elevation_deg, speed / response_grid.central_speed
-        )
-        * interpolate_azimuthal_transmission(
-            response_grid.azimuthal_transmission, azimuth_deg
-        )
+        * interpolate_passband(passband, elevation_deg, speed / response_grid.central_speed)
+        * interpolate_azimuthal_transmission(response_grid.azimuthal_transmission, azimuth_deg)
     )
     # H is an angular integral (docs convention); dα dβ comes from dblquad, so
     # only the sin α solid-angle factor is multiplied in here.
@@ -199,9 +181,7 @@ def _worker_compute(v_prime):
 
 
 def main():
-    print(
-        f"Loading SWAPI response and warming cache at V={_ESA_VOLTAGE}...", flush=True
-    )
+    print(f"Loading SWAPI response and warming cache at V={_ESA_VOLTAGE}...", flush=True)
     swapi_response = load_swapi_response(warm_cache_voltages=np.array([_ESA_VOLTAGE]))
     response_grid = swapi_response.get_response_grid(
         esa_voltage=_ESA_VOLTAGE,
diff --git a/scripts/swapi/generate_reference_integrals.py b/scripts/swapi/generate_reference_integrals.py
old mode 100644
new mode 100755
index b8ee14eb..0b072372
--- a/scripts/swapi/generate_reference_integrals.py
+++ b/scripts/swapi/generate_reference_integrals.py
@@ -33,19 +33,18 @@
 sys.path.insert(0, str(_REPO_ROOT))
 sys.path.insert(0, str(_REPO_ROOT / "docs" / "swapi" / "figure_src"))
 
-# ruff: disable[E402]
+from figure_utils import ANCHOR_ROTATION_SWAPI_TO_RTN
+
 from imap_l3_processing.constants import (
     METERS_PER_KILOMETER,
     PROTON_CHARGE_COULOMBS,
     PROTON_MASS_KG,
     PROTON_MASS_PER_CHARGE_M_P_PER_E,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
+from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
 from scripts.swapi.reference_integral import reference_integrals_batch
-from figure_utils import ANCHOR_ROTATION_SWAPI_TO_RTN
-# ruff: enable[E402]
 
 _INSTRUMENT_DATA = _REPO_ROOT / "instrument_team_data" / "swapi"
 _WIND_SAMPLES_PATH = (
@@ -94,8 +93,7 @@ def main():
     voltages = [_peak_voltage(float(v)) for v in bulk_speed]
     swapi_response.warm_cache(voltages)
     response_grids = [
-        swapi_response.get_response_grid(v, PROTON_MASS_PER_CHARGE_M_P_PER_E)
-        for v in voltages
+        swapi_response.get_response_grid(v, PROTON_MASS_PER_CHARGE_M_P_PER_E) for v in voltages
     ]
 
     print(f"Computing {n_samples} reference integrals (JIT-parallel, fixed limits)...")
diff --git a/scripts/swapi/generate_with_predicted_ephemeris.py b/scripts/swapi/generate_with_predicted_ephemeris.py
index fa6c010b..893eaddf 100644
--- a/scripts/swapi/generate_with_predicted_ephemeris.py
+++ b/scripts/swapi/generate_with_predicted_ephemeris.py
@@ -7,7 +7,7 @@
 from imap_data_access import DependencyFilePath, ProcessingInputCollection
 from imap_data_access.processing_input import generate_imap_input
 
-from imap_l3_processing.utils import get_spice_kernels_file_names, SpiceKernelTypes
+from imap_l3_processing.utils import SpiceKernelTypes, get_spice_kernels_file_names
 
 SPICE_KERNELS = [
     SpiceKernelTypes.Leapseconds,
@@ -23,9 +23,7 @@
 
 
 def generate_swapi_for_given_day(descriptor: str, day: datetime):
-    spice_kernel_files = get_spice_kernels_file_names(
-        day, day + timedelta(days=1), SPICE_KERNELS
-    )
+    spice_kernel_files = get_spice_kernels_file_names(day, day + timedelta(days=1), SPICE_KERNELS)
     day_as_string = day.strftime("%Y%m%d")
     l2_file_path = imap_data_access.query(
         instrument="swapi",
@@ -35,15 +33,11 @@ def generate_swapi_for_given_day(descriptor: str, day: datetime):
         version="latest",
     )[0]["file_path"]
 
-    template_json = Path(
-        "scripts/swapi/imap_swapi_l3a_proton-sw_dependency_template.json"
-    )
+    template_json = Path("scripts/swapi/imap_swapi_l3a_proton-sw_dependency_template.json")
 
     input_files = [*spice_kernel_files, Path(l2_file_path).name]
 
-    input_collection = ProcessingInputCollection(
-        *[generate_imap_input(i) for i in input_files]
-    )
+    input_collection = ProcessingInputCollection(*[generate_imap_input(i) for i in input_files])
     input_collection.deserialize(template_json.read_text())
 
     input_collection.download_all_files()
diff --git a/scripts/swapi/pui_xarray_reference.py b/scripts/swapi/pui_xarray_reference.py
index c3f650c9..cd36a804 100644
--- a/scripts/swapi/pui_xarray_reference.py
+++ b/scripts/swapi/pui_xarray_reference.py
@@ -72,7 +72,7 @@
 import xarray as xr
 
 from imap_l3_processing.constants import HE_PUI_PARTICLE_MASS_PER_CHARGE_M_P_PER_E
-from tests.test_helpers import get_test_instrument_team_data_path, get_test_data_path
+from tests.test_helpers import get_test_data_path, get_test_instrument_team_data_path
 
 OUTPUT_PATH = get_test_data_path("swapi/pui_count_rate_reference.csv")
 
@@ -125,9 +125,7 @@
     passband_coefficients["energy_ratio"].values / K_FACTOR.to("eV/V/e").magnitude
 )
 passband_coefficients = (
-    passband_coefficients.assign_coords(
-        speed_ratio=("energy_ratio", source_speed_ratio)
-    )
+    passband_coefficients.assign_coords(speed_ratio=("energy_ratio", source_speed_ratio))
     .swap_dims({"energy_ratio": "speed_ratio"})
     .drop_vars("energy_ratio")
 )
@@ -175,9 +173,7 @@
 _abs_az = az_transmission_native["abs_azimuth"].values
 _trans = az_transmission_native.values
 _az_signed = np.concatenate([-_abs_az[:0:-1], _abs_az])
-azimuth_deg = xr.DataArray(
-    _az_signed, dims="azimuth_deg", coords={"azimuth_deg": _az_signed}
-)
+azimuth_deg = xr.DataArray(_az_signed, dims="azimuth_deg", coords={"azimuth_deg": _az_signed})
 azimuthal_transmission = xr.DataArray(
     np.concatenate([_trans[:0:-1], _trans]),
     dims="azimuth_deg",
@@ -195,9 +191,9 @@
     dim="cartesian",
 ).assign_coords(cartesian=["x", "y", "z"])
 
-central_instrument_speed = np.sqrt(
-    2 * K_FACTOR * voltages / HE_PLUS_MASS_PER_CHARGE
-).pint.to("km/s")
+central_instrument_speed = np.sqrt(2 * K_FACTOR * voltages / HE_PLUS_MASS_PER_CHARGE).pint.to(
+    "km/s"
+)
 
 """## Evaluate passband at each ESA voltage"""
 
@@ -318,11 +314,7 @@
 
 integrand = effective_area * flux * d3v
 
-integral = (
-    integrand.integrate("azimuth_deg")
-    .integrate("elevation_deg")
-    .integrate("speed_ratio")
-)
+integral = integrand.integrate("azimuth_deg").integrate("elevation_deg").integrate("speed_ratio")
 count_rate = (integral * central_instrument_speed).pint.to("counts/s")
 
 count_rate.to_series().to_csv(OUTPUT_PATH)
diff --git a/scripts/swapi/pui_xarray_reference_50sweep.py b/scripts/swapi/pui_xarray_reference_50sweep.py
index 90c90b82..9d5c74c6 100644
--- a/scripts/swapi/pui_xarray_reference_50sweep.py
+++ b/scripts/swapi/pui_xarray_reference_50sweep.py
@@ -12,7 +12,6 @@
 from dataclasses import dataclass
 from datetime import datetime, timedelta
 from pathlib import Path
-from typing import Union
 
 import numpy as np
 import pandas as pd
@@ -49,10 +48,10 @@ class PuiXArrayContext:
 
 def build_pui_xarray_context(
     *,
-    azimuthal_transmission_path: Union[str, Path],
-    central_effective_area_path: Union[str, Path],
-    passband_fit_coefficients_path: Union[str, Path],
-    density_of_neutral_helium_lut_path: Union[str, Path],
+    azimuthal_transmission_path: str | Path,
+    central_effective_area_path: str | Path,
+    passband_fit_coefficients_path: str | Path,
+    density_of_neutral_helium_lut_path: str | Path,
     helium_efficiency_ratio: float = HELIUM_EFFICIENCY_RATIO,
 ) -> PuiXArrayContext:
     """Load SWAPI calibration CSVs/DAT and assemble the xarray integration
@@ -84,9 +83,7 @@ def build_pui_xarray_context(
         passband_coefficients["energy_ratio"].values / K_FACTOR.to("eV/V/e").magnitude
     )
     passband_coefficients = (
-        passband_coefficients.assign_coords(
-            speed_ratio=("energy_ratio", source_speed_ratio)
-        )
+        passband_coefficients.assign_coords(speed_ratio=("energy_ratio", source_speed_ratio))
         .swap_dims({"energy_ratio": "speed_ratio"})
         .drop_vars("energy_ratio")
     )
@@ -143,13 +140,11 @@ def build_pui_xarray_context(
         dim="cartesian",
     ).assign_coords(cartesian=["x", "y", "z"])
 
-    central_instrument_speed = np.sqrt(
-        2 * K_FACTOR * voltages / HE_PLUS_MASS_PER_CHARGE
-    ).pint.to("km/s")
-
-    log_beam_energy = np.log(
-        np.abs(K_FACTOR * voltages).pint.to("eV/e").pint.dequantify()
+    central_instrument_speed = np.sqrt(2 * K_FACTOR * voltages / HE_PLUS_MASS_PER_CHARGE).pint.to(
+        "km/s"
     )
+
+    log_beam_energy = np.log(np.abs(K_FACTOR * voltages).pint.to("eV/e").pint.dequantify())
     passband_per_region = np.exp(
         xr.polyval(log_beam_energy, passband_coefficients, degree_dim="degree")
     ).fillna(0)
@@ -164,13 +159,11 @@ def build_pui_xarray_context(
         passband_per_region.sel(region="OA"),
     )
 
-    effective_area = (
-        central_effective_area * passband_full * azimuthal_transmission
-    ).clip(min=Q(0, "cm**2"))
-
-    speed_grid = (speed_ratio_axis * central_instrument_speed).transpose(
-        "V", "speed_ratio"
+    effective_area = (central_effective_area * passband_full * azimuthal_transmission).clip(
+        min=Q(0, "cm**2")
     )
+
+    speed_grid = (speed_ratio_axis * central_instrument_speed).transpose("V", "speed_ratio")
     cos_elevation = np.cos(np.deg2rad(elevation_deg_axis))
 
     return PuiXArrayContext(
@@ -232,9 +225,7 @@ def evaluate_pui_sweep_xarray(
     term4 = (
         context.density_table.pint.interp(
             psi=(psi % Q(360, "deg")).magnitude,
-            r=(heliocentric_distance * w**cooling_index)
-            .pint.to("au")
-            .pint.dequantify(),
+            r=(heliocentric_distance * w**cooling_index).pint.to("au").pint.dequantify(),
         )
         .drop_vars(["psi", "r"])
         .fillna(0)
@@ -247,9 +238,7 @@ def evaluate_pui_sweep_xarray(
     d3v = context.speed_grid**2 * deg2_to_sr * context.cos_elevation
     integrand = context.effective_area * flux * d3v
     integral = (
-        integrand.integrate("azimuth_deg")
-        .integrate("elevation_deg")
-        .integrate("speed_ratio")
+        integrand.integrate("azimuth_deg").integrate("elevation_deg").integrate("speed_ratio")
     )
     count_rate = (integral * context.central_instrument_speed).pint.to("counts/s")
     return count_rate.pint.dequantify().values
@@ -344,9 +333,7 @@ def evaluate_pui_sweep_xarray(
     start_et = spiceypy.str2et(START_TIME_UTC.isoformat())
     sweep_starts_et = start_et + np.arange(N_SWEEPS) * SWEEP_DURATION_S
     step_offsets_s = np.arange(N_ESA_STEPS_PER_SWEEP) * STEP_DURATION_S
-    ephemeris_time_grid = (
-        sweep_starts_et[:, None] + step_offsets_s[None, :]
-    )  # (sweep, step)
+    ephemeris_time_grid = sweep_starts_et[:, None] + step_offsets_s[None, :]  # (sweep, step)
 
     print("Computing per-bin IMAP_RTN↔IMAP_SWAPI rotations...")
     bulk_sw_per_bin_swapi_kms = np.empty((N_SWEEPS, N_ESA_STEPS_PER_SWEEP, 3))
@@ -401,9 +388,7 @@ def evaluate_pui_sweep_xarray(
             solar_wind_speed_inertial_kms=SW_SPEED_INERTIAL_KMS,
         )
 
-    print(
-        "Computing proton + alpha Maxwellian shoulder via production forward model..."
-    )
+    print("Computing proton + alpha Maxwellian shoulder via production forward model...")
     voltage_repeated = np.broadcast_to(
         pui_context.voltages_v, (N_SWEEPS, N_ESA_STEPS_PER_SWEEP)
     ).ravel()
@@ -447,9 +432,7 @@ def evaluate_pui_sweep_xarray(
     )
 
     ideal_total_rate = (
-        pui_count_rate_per_sweep
-        + proton_alpha_count_rate_per_sweep
-        + BACKGROUND_RATE_HZ
+        pui_count_rate_per_sweep + proton_alpha_count_rate_per_sweep + BACKGROUND_RATE_HZ
     )
     expected_count_rate_per_sweep = ideal_total_rate * deadtime_factor(ideal_total_rate)
 
diff --git a/scripts/swapi/reference_integral.py b/scripts/swapi/reference_integral.py
index 6385247e..012f1c38 100644
--- a/scripts/swapi/reference_integral.py
+++ b/scripts/swapi/reference_integral.py
@@ -31,9 +31,7 @@
 
 _EL = np.linspace(-15.0, 15.0, 601)
 _AZ_SG = np.linspace(-20.0, 20.0, 801)
-_AZ_OA_NEG = np.concatenate(
-    [np.arange(-150.0, -30.0, 0.5), np.linspace(-30.0, -20.0, 201)]
-)
+_AZ_OA_NEG = np.concatenate([np.arange(-150.0, -30.0, 0.5), np.linspace(-30.0, -20.0, 201)])
 _AZ_OA_POS = np.concatenate([np.linspace(20.0, 30.0, 201), np.arange(30.5, 151.0, 0.5)])
 _SP_RATIO = np.linspace(0.9, 1.1, 200)
 
@@ -139,9 +137,7 @@ def _integrate_region(
             bulk_along_direction = (
                 direction_r * bulk_r + direction_t * bulk_t + direction_n * bulk_n
             )
-            transmission_at_az = _interpolate_transmission(
-                transmission, transmission_spacing, az
-            )
+            transmission_at_az = _interpolate_transmission(transmission, transmission_spacing, az)
             az_weight = az_weights[i_az] * transmission_at_az
             for i_sp in range(sp_ratio_points.shape[0]):
                 speed_ratio = sp_ratio_points[i_sp]
@@ -156,9 +152,7 @@ def _integrate_region(
                     speed_ratio,
                 )
                 exponent = (
-                    speed * speed
-                    + bulk_speed_squared
-                    - 2.0 * speed * bulk_along_direction
+                    speed * speed + bulk_speed_squared - 2.0 * speed * bulk_along_direction
                 ) * inv_two_sigma_sq
                 integrand = passband * speed**3 * math.exp(-exponent)
                 speed_weight = central_speed * sp_ratio_weights[i_sp]
@@ -318,9 +312,7 @@ def reference_integrals_batch(response_grids, sws, rotation_matrices):
         bulk_speeds[i] = bulk_speed(sws[i])
         thermal_speeds[i] = params.thermal_speed(sws[i])
         densities[i] = sws[i].density
-    transmission = np.ascontiguousarray(
-        first_grid.azimuthal_transmission.values, dtype=np.float64
-    )
+    transmission = np.ascontiguousarray(first_grid.azimuthal_transmission.values, dtype=np.float64)
     return _batch(
         sg_values_all,
         oa_values_all,
@@ -350,9 +342,7 @@ def reference_integrals_batch(response_grids, sws, rotation_matrices):
     )
 
 
-def reference_integral_fixed_limits(
-    response_grid: ResponseGrid, sw, rotation_matrix
-) -> float:
+def reference_integral_fixed_limits(response_grid: ResponseGrid, sw, rotation_matrix) -> float:
     """Single-sample ground truth (delegates to the parallel batch)."""
     rm = np.asarray(rotation_matrix, dtype=np.float64).reshape(1, 3, 3)
     return float(reference_integrals_batch([response_grid], [sw], rm)[0])
diff --git a/scripts/swapi/report_out_of_range_uncertainties.py b/scripts/swapi/report_out_of_range_uncertainties.py
index fb34edd1..0e4ed82c 100644
--- a/scripts/swapi/report_out_of_range_uncertainties.py
+++ b/scripts/swapi/report_out_of_range_uncertainties.py
@@ -21,9 +21,7 @@ def report_out_of_range_uncertainties(path: Path | str):
 
             values = cdf[var][...]
 
-            bad_vals = ((values < valid_min) | (values > valid_max)) & (
-                values != fill_val
-            )
+            bad_vals = ((values < valid_min) | (values > valid_max)) & (values != fill_val)
             bad_indices = np.argwhere(bad_vals)
             if len(bad_indices) > 0:
                 print(
@@ -32,13 +30,9 @@ def report_out_of_range_uncertainties(path: Path | str):
 
 
 def get_all_swapi_l3a():
-    query_results = imap_data_access.query(
-        instrument="swapi", data_level="l3a", version="latest"
-    )
+    query_results = imap_data_access.query(instrument="swapi", data_level="l3a", version="latest")
     paths_to_downloaded_files = []
-    for result in sorted(
-        query_results, key=lambda r: (r["descriptor"], r["start_date"])
-    ):
+    for result in sorted(query_results, key=lambda r: (r["descriptor"], r["start_date"])):
         file_path = imap_data_access.download(result["file_path"])
         paths_to_downloaded_files.append(file_path)
     return paths_to_downloaded_files
diff --git a/scripts/swapi/sample_wind_solar_wind.py b/scripts/swapi/sample_wind_solar_wind.py
old mode 100644
new mode 100755
index 23aea951..40223e1c
--- a/scripts/swapi/sample_wind_solar_wind.py
+++ b/scripts/swapi/sample_wind_solar_wind.py
@@ -38,16 +38,14 @@
 _REPO_ROOT = Path(__file__).resolve().parents[2]
 sys.path.insert(0, str(_REPO_ROOT))
 
-from imap_l3_processing.constants import (  # noqa: E402
+from imap_l3_processing.constants import (
     BOLTZMANN_CONSTANT_JOULES_PER_KELVIN,
     PROTON_MASS_KG,
 )
 
 _BASE_URL = "https://spdf.gsfc.nasa.gov/pub/data/wind/swe/ascii/2-min"
 _DEFAULT_CACHE_DIR = Path.home() / ".cache" / "imap_l3" / "wind_swe_2m"
-_DEFAULT_OUTPUT = (
-    _REPO_ROOT / "docs" / "swapi" / "figure_src" / "wind_solar_wind_samples_2025.csv"
-)
+_DEFAULT_OUTPUT = _REPO_ROOT / "docs" / "swapi" / "figure_src" / "wind_solar_wind_samples_2025.csv"
 
 # Column indices (0-based) into the WIND ASCII record. See documentation_jck.txt
 # at the source URL for the full layout.
@@ -166,9 +164,7 @@ def main():
     print(f"  After fill-value filter: {keep.sum()} rows")
 
     if keep.sum() < args.n:
-        sys.exit(
-            f"Only {keep.sum()} rows survive filters but {args.n} samples requested."
-        )
+        sys.exit(f"Only {keep.sum()} rows survive filters but {args.n} samples requested.")
 
     rng = np.random.default_rng(args.seed)
     candidates = np.flatnonzero(keep)
@@ -233,9 +229,7 @@ def main():
         ("v_N", v_N, "km/s"),
     ]:
         q = np.percentile(arr, [1, 50, 99])
-        print(
-            f"  {label:>13s} [{unit}]  p1={q[0]:9.3g}  median={q[1]:9.3g}  p99={q[2]:9.3g}"
-        )
+        print(f"  {label:>13s} [{unit}]  p1={q[0]:9.3g}  median={q[1]:9.3g}  p99={q[2]:9.3g}")
 
 
 if __name__ == "__main__":
diff --git a/scripts/swapi/swapi_alpha_sw_speed_temperature_density_demo.py b/scripts/swapi/swapi_alpha_sw_speed_temperature_density_demo.py
index 24f6f7ee..17ee171b 100644
--- a/scripts/swapi/swapi_alpha_sw_speed_temperature_density_demo.py
+++ b/scripts/swapi/swapi_alpha_sw_speed_temperature_density_demo.py
@@ -3,31 +3,29 @@
 
 import numpy as np
 import scipy
-from matplotlib import pyplot as plt
-from numpy import ndarray
-from spacepy.pycdf import CDF
-from uncertainties import ufloat, correlated_values
-from uncertainties.unumpy import uarray, nominal_values, std_devs
-
-from imap_l3_processing.swapi.l3a.models import SwapiL2Data
 from imap_l3_processing.swapi.l3a.science.calculate_alpha_solar_wind_speed import (
     calculate_alpha_solar_wind_speed,
     calculate_combined_sweeps,
     get_alpha_peak_indices,
 )
 from imap_l3_processing.swapi.l3a.science.calculate_alpha_solar_wind_temperature_and_density import (
-    calculate_alpha_solar_wind_temperature_and_density_for_combined_sweeps,
     AlphaTemperatureDensityCalibrationTable,
     alpha_count_rate_model,
+    calculate_alpha_solar_wind_temperature_and_density_for_combined_sweeps,
 )
+from matplotlib import pyplot as plt
+from numpy import ndarray
+from spacepy.pycdf import CDF
+from uncertainties import correlated_values, ufloat
+from uncertainties.unumpy import nominal_values, std_devs, uarray
+
+from imap_l3_processing.swapi.l3a.models import SwapiL2Data
 
 
 def read_l2_data_from_dat(file_path: str) -> SwapiL2Data:
     data = np.loadtxt(file_path)
     data = data.reshape((-1, 72, 8))
-    start_time = int(
-        np.datetime64("2010-01-01", "ns") - np.datetime64("2000-01-01T12:00", "ns")
-    )
+    start_time = int(np.datetime64("2010-01-01", "ns") - np.datetime64("2000-01-01T12:00", "ns"))
     twelve_seconds_in_nanoseconds = 12_000_000_000
     epochs = start_time + twelve_seconds_in_nanoseconds * np.arange(len(data))
 
@@ -65,9 +63,7 @@ def read_l2_data(cdf_path: str) -> SwapiL2Data:
 def plot_sweeps(data):
     for i in range(len(data.sci_start_time)):
         axes = fig.add_subplot(len(data.sci_start_time) + 1, 1, i + 1)
-        axes.loglog(
-            data.energy, data.coincidence_count_rate[i, :], marker=".", linestyle="None"
-        )
+        axes.loglog(data.energy, data.coincidence_count_rate[i, :], marker=".", linestyle="None")
         axes.set(xlabel="Energy", ylabel="Count Rate")
 
 
@@ -82,7 +78,7 @@ def run_example_dat_files():
     temperature_density_lut = AlphaTemperatureDensityCalibrationTable.from_file(
         r"swapi/test_data/imap_swapi_alpha-density-temperature-lut_20240920_v000.dat"
     )
-    alpha_temperature, alpha_density = (
+    _alpha_temperature, _alpha_density = (
         calculate_alpha_solar_wind_temperature_and_density_for_combined_sweeps(
             temperature_density_lut, alpha_speed, coincident_count_rate, energy
         )
@@ -116,9 +112,9 @@ def plot_and_calculate_alpha_solar_wind_temperature_and_density_for_combined_swe
         alpha_count_rate_model(peak_energies, *values)
         - nominal_values(peak_average_alpha_count_rates)
     )
-    reduced_chisq = np.sum(
-        np.square(residual / std_devs(peak_average_alpha_count_rates))
-    ) / (len(peak_energies) - 3)
+    reduced_chisq = np.sum(np.square(residual / std_devs(peak_average_alpha_count_rates))) / (
+        len(peak_energies) - 3
+    )
     if reduced_chisq > 10:
         raise ValueError("Failed to fit - chi-squared too large", reduced_chisq)
     density, temperature, speed = correlated_values(values, covariance)
@@ -143,7 +139,7 @@ def main(file_path):
     elif file_path[-4:] == ".cdf":
         data = read_l2_data(os.path.abspath(file_path))
     else:
-        raise Exception("The demo can only load data from .dat or .cdf files!")
+        raise ValueError("The demo can only load data from .dat or .cdf files!")
 
     coincident_count_rate = uarray(
         data.coincidence_count_rate, data.coincidence_count_rate_uncertainty
@@ -181,5 +177,5 @@ def main(file_path):
     try:
         file_path = sys.argv[1]
         main(file_path)
-    except Exception:
+    except (IndexError, ValueError):
         main(os.path.abspath("../../instrument_team_data/swapi/swapi_test_data_v5.dat"))
diff --git a/scripts/swapi/upload_swapi_l3_dependencies.py b/scripts/swapi/upload_swapi_l3_dependencies.py
index 3d96b666..ee5d8fdc 100644
--- a/scripts/swapi/upload_swapi_l3_dependencies.py
+++ b/scripts/swapi/upload_swapi_l3_dependencies.py
@@ -30,5 +30,5 @@
         else:
             imap_data_access.upload(file)
             print("Successfully uploaded", file.name)
-    except Exception as e:
+    except Exception as e:  # noqa: BLE001
         print(f'File "{file.name}" failed to upload with exception {e}')
diff --git a/scripts/swapi/view_one_pui_spectrum.py b/scripts/swapi/view_one_pui_spectrum.py
index ed12b2e8..f1f48e86 100644
--- a/scripts/swapi/view_one_pui_spectrum.py
+++ b/scripts/swapi/view_one_pui_spectrum.py
@@ -28,12 +28,11 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import spiceypy
-from matplotlib.colors import LogNorm
 from imap_data_access import ProcessingInputCollection
 from imap_data_access.processing_input import generate_imap_input
-from spacepy.pycdf import lib as cdf_library
-
 from imap_processing.swapi.l2 import swapi_l2
+from matplotlib.colors import LogNorm
+from spacepy.pycdf import lib as cdf_library
 
 from imap_l3_processing.constants import ONE_AU_IN_KM, ONE_SECOND_IN_NANOSECONDS
 from imap_l3_processing.swapi.constants import (
@@ -60,15 +59,13 @@
     evaluate_pui_sweep_xarray,
 )
 
-
 argument_parser = argparse.ArgumentParser(
     description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
 )
 argument_parser.add_argument("date", help="UTC date in YYYY-MM-DD format")
 argument_parser.add_argument(
     "time",
-    help="UTC time in HH:MM[:SS] format; picks the 50-sweep "
-    "chunk whose central epoch is nearest.",
+    help="UTC time in HH:MM[:SS] format; picks the 50-sweep chunk whose central epoch is nearest.",
 )
 argument_parser.add_argument(
     "--output-path",
@@ -99,14 +96,10 @@ def _parse_hh_mm_ss(time_string: str):
     sys.exit("IMAP_API_KEY environment variable is required.")
 
 target_date = datetime.strptime(arguments.date, "%Y-%m-%d")
-target_datetime_utc = datetime.combine(
-    target_date.date(), _parse_hh_mm_ss(arguments.time)
-)
+target_datetime_utc = datetime.combine(target_date.date(), _parse_hh_mm_ss(arguments.time))
 compact_date = target_date.strftime("%Y%m%d")
 fit_cache_path = Path(f"/tmp/swapi_pui_fit_{compact_date}.pkl")
-spectrogram_cache_path = Path(
-    f"/tmp/swapi_pui_spectrograms_per_sweep_{compact_date}.pkl"
-)
+spectrogram_cache_path = Path(f"/tmp/swapi_pui_spectrograms_per_sweep_{compact_date}.pkl")
 if not fit_cache_path.exists() or not spectrogram_cache_path.exists():
     sys.exit(
         f"Missing pickle caches for {arguments.date}. "
@@ -134,9 +127,7 @@ def _parse_hh_mm_ss(time_string: str):
 
 def resolve_l2_filename_from_cache() -> str:
     matches = sorted(
-        (data_dir / "imap" / "swapi" / "l2").rglob(
-            f"imap_swapi_l2_sci_{compact_date}_v*.cdf"
-        )
+        (data_dir / "imap" / "swapi" / "l2").rglob(f"imap_swapi_l2_sci_{compact_date}_v*.cdf")
     )
     if not matches:
         sys.exit(
@@ -147,9 +138,7 @@ def resolve_l2_filename_from_cache() -> str:
 
 
 def resolve_spice_filenames_from_cache() -> list[str]:
-    names = sorted(
-        p.name for p in (data_dir / "imap" / "spice").rglob("*") if p.is_file()
-    )
+    names = sorted(p.name for p in (data_dir / "imap" / "spice").rglob("*") if p.is_file())
     if not names:
         sys.exit(
             f"No cached SPICE kernels under {data_dir}. "
@@ -178,9 +167,7 @@ def resolve_spice_filenames_from_cache() -> list[str]:
         SpiceKernelTypes.EphemerisReconstructed,
         SpiceKernelTypes.EphemerisPredicted,
     ]
-    non_ephemeris_kernel_types = [
-        t for t in SpiceKernelTypes if t not in ephemeris_kernel_types
-    ]
+    non_ephemeris_kernel_types = [t for t in SpiceKernelTypes if t not in ephemeris_kernel_types]
     spice_kernel_filenames = list(
         dict.fromkeys(
             os.path.basename(path)
@@ -213,25 +200,15 @@ def resolve_spice_filenames_from_cache() -> list[str]:
 
 
 def _swapi_ancillary_path(descriptor: str) -> Path:
-    paths = processing_input_collection.get_file_paths(
-        source="swapi", descriptor=descriptor
-    )
+    paths = processing_input_collection.get_file_paths(source="swapi", descriptor=descriptor)
     return imap_data_access.download(paths[0])
 
 
 pui_xarray_context = build_pui_xarray_context(
-    azimuthal_transmission_path=_swapi_ancillary_path(
-        AZIMUTHAL_TRANSMISSION_DESCRIPTOR
-    ),
-    central_effective_area_path=_swapi_ancillary_path(
-        CENTRAL_EFFECTIVE_AREA_DESCRIPTOR
-    ),
-    passband_fit_coefficients_path=_swapi_ancillary_path(
-        PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR
-    ),
-    density_of_neutral_helium_lut_path=_swapi_ancillary_path(
-        DENSITY_OF_NEUTRAL_HELIUM_DESCRIPTOR
-    ),
+    azimuthal_transmission_path=_swapi_ancillary_path(AZIMUTHAL_TRANSMISSION_DESCRIPTOR),
+    central_effective_area_path=_swapi_ancillary_path(CENTRAL_EFFECTIVE_AREA_DESCRIPTOR),
+    passband_fit_coefficients_path=_swapi_ancillary_path(PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR),
+    density_of_neutral_helium_lut_path=_swapi_ancillary_path(DENSITY_OF_NEUTRAL_HELIUM_DESCRIPTOR),
 )
 
 chunks = list(chunk_l2_data(dependencies.data, 50))
@@ -239,10 +216,7 @@ def _swapi_ancillary_path(descriptor: str) -> Path:
     [cdf_library.tt2000_to_datetime(int(t)) for t in pickup_ion_data.epoch]
 )
 seconds_from_target = np.array(
-    [
-        abs((central - target_datetime_utc).total_seconds())
-        for central in chunk_central_datetimes
-    ]
+    [abs((central - target_datetime_utc).total_seconds()) for central in chunk_central_datetimes]
 )
 chunk_index = int(np.argmin(seconds_from_target))
 data_chunk = chunks[chunk_index]
@@ -260,18 +234,14 @@ def _swapi_ancillary_path(descriptor: str) -> Path:
 if not np.isfinite(pickup_ion_data.cooling_index[chunk_index].n):
     sys.exit(f"Chunk {chunk_index} has no successful PUI fit.")
 
-chunk_ephemeris_time = spiceypy.unitim(
-    chunk_epoch_tt2000 / ONE_SECOND_IN_NANOSECONDS, "TT", "ET"
-)
+chunk_ephemeris_time = spiceypy.unitim(chunk_epoch_tt2000 / ONE_SECOND_IN_NANOSECONDS, "TT", "ET")
 vasyliunas_siscoe = build_vasyliunas_siscoe_distribution(
     chunk_ephemeris_time,
     sw_velocity_rtn_kms,
     dependencies.density_of_neutral_helium_calibration_table,
     dependencies.helium_inflow_vector,
 )
-bulk_sw_per_bin_swapi_kms = rotate_rtn_velocity_to_swapi_per_bin(
-    data_chunk, sw_velocity_rtn_kms
-)
+bulk_sw_per_bin_swapi_kms = rotate_rtn_velocity_to_swapi_per_bin(data_chunk, sw_velocity_rtn_kms)
 
 # Production averages per-sweep rates computed with the per-bin bulk SW
 # vector. At high E the f_PUI azimuthal window is narrow (~tens of degrees),
@@ -289,9 +259,7 @@ def _swapi_ancillary_path(descriptor: str) -> Path:
 fit_background_rate_hz = float(pickup_ion_data.background_rate[chunk_index].n)
 # A rejected background is stored as NaN (see _set_background_to_fill_if_too_high);
 # adding it would wipe out the model lines, so fall back to no offset.
-background_offset_hz = (
-    fit_background_rate_hz if np.isfinite(fit_background_rate_hz) else 0.0
-)
+background_offset_hz = fit_background_rate_hz if np.isfinite(fit_background_rate_hz) else 0.0
 
 xarray_rate_per_sweep = np.empty(bulk_sw_per_bin_swapi_kms.shape[:2])
 n_sweeps_in_chunk = bulk_sw_per_bin_swapi_kms.shape[0]
@@ -319,9 +287,7 @@ def _swapi_ancillary_path(descriptor: str) -> Path:
 
 chunk_observed_mean = np.nanmean(chunk_observed_per_sweep, axis=0)
 chunk_model_mean = np.nanmean(chunk_model_per_sweep, axis=0)
-chunk_energies_mean_ev = (
-    np.nanmean(chunk_voltages_per_sweep, axis=0) * SWAPI_L2_K_FACTOR
-)
+chunk_energies_mean_ev = np.nanmean(chunk_voltages_per_sweep, axis=0) * SWAPI_L2_K_FACTOR
 
 # Poisson uncertainty on the chunk-mean rate at each bin: the mean of N
 # independent counting measurements over a livetime each, so total counts
@@ -335,9 +301,7 @@ def _swapi_ancillary_path(descriptor: str) -> Path:
 
 xarray_energies_ev = pui_xarray_context.voltages_v * SWAPI_L2_K_FACTOR
 
-mean_energies_ev_per_step = np.nanmean(
-    chunk_voltages_per_sweep * SWAPI_L2_K_FACTOR, axis=0
-)
+mean_energies_ev_per_step = np.nanmean(chunk_voltages_per_sweep * SWAPI_L2_K_FACTOR, axis=0)
 pickup_ion_bin_indices = np.where(pickup_ion_window_bin_mask)[0]
 fit_window_energies_ev = mean_energies_ev_per_step[pickup_ion_bin_indices]
 energy_sort_order_within_window = np.argsort(fit_window_energies_ev)
@@ -438,7 +402,7 @@ def _swapi_ancillary_path(descriptor: str) -> Path:
         ha="left",
         va="top",
         fontsize=10,
-        bbox=dict(boxstyle="round,pad=0.3", fc="white", alpha=0.85, ec="none"),
+        bbox={"boxstyle": "round,pad=0.3", "fc": "white", "alpha": 0.85, "ec": "none"},
     )
 plt.setp(observed_spectrogram_axis.get_xticklabels(), visible=False)
 model_spectrogram_axis.set_xlabel("Sweep index within chunk")
diff --git a/scripts/swe/calculate_rebin_by_pitch_angle.py b/scripts/swe/calculate_rebin_by_pitch_angle.py
index e8c84a81..83b28893 100644
--- a/scripts/swe/calculate_rebin_by_pitch_angle.py
+++ b/scripts/swe/calculate_rebin_by_pitch_angle.py
@@ -7,25 +7,17 @@
 
 from imap_l3_processing.swe.l3.science.pitch_calculations import (
     calculate_velocity_in_dsp_frame_km_s,
-    swe_rebin_intensity_by_pitch_angle_and_gyrophase,
     correct_and_rebin,
+    swe_rebin_intensity_by_pitch_angle_and_gyrophase,
 )
 from imap_l3_processing.swe.l3.swe_l3_dependencies import SweL3Dependencies
 from imap_l3_processing.swe.swe_processor import SweProcessor
 
 swe_l2_file_path = Path(r"data/imap/swe/l2/2025/12/imap_swe_l2_sci_20251217_v002.cdf")
-swe_l1b_file_path = Path(
-    r"data/imap/swe/l1b/2025/12/imap_swe_l1b_sci_20251217_v004.cdf"
-)
-mag_file_path = Path(
-    r"data/imap/mag/l1d/2025/12/imap_mag_l1d_norm-dsrf_20251217_v001.cdf"
-)
-swapi_file_path = Path(
-    r"data/imap/swapi/l3a/2025/12/imap_swapi_l3a_proton-sw_20251217_v002.cdf"
-)
-configuration_file_path = Path(
-    r"data/imap/ancillary/swe/imap_swe_config_20251119_v002.json"
-)
+swe_l1b_file_path = Path(r"data/imap/swe/l1b/2025/12/imap_swe_l1b_sci_20251217_v004.cdf")
+mag_file_path = Path(r"data/imap/mag/l1d/2025/12/imap_mag_l1d_norm-dsrf_20251217_v001.cdf")
+swapi_file_path = Path(r"data/imap/swapi/l3a/2025/12/imap_swapi_l3a_proton-sw_20251217_v002.cdf")
+configuration_file_path = Path(r"data/imap/ancillary/swe/imap_swe_config_20251119_v002.json")
 
 spice_files = [
     "naif0012.tls",
@@ -99,7 +91,7 @@ def calculate(i):
         swe_l2_data.inst_az_spin_sector[i],
     )
 
-    rebinned_psd, rebinned_psd_by_pa_and_gyro = correct_and_rebin(
+    _rebinned_psd, _rebinned_psd_by_pa_and_gyro = correct_and_rebin(
         swe_l2_data.phase_space_density[i],
         np.array([0, 0, -400]),
         dsp_velocities,
diff --git a/scripts/swe/compare_outputs.py b/scripts/swe/compare_outputs.py
index a955beca..3aa4a8c6 100644
--- a/scripts/swe/compare_outputs.py
+++ b/scripts/swe/compare_outputs.py
@@ -25,9 +25,7 @@ def read_numeric_variable(var: pycdf.Var) -> np.ndarray:
     return np.where(var[...] == var.attrs["FILLVAL"], np.nan, var[...])
 
 
-OUTPUT_PATH = (
-    Path(__file__).parent.parent.parent / "comparisons" / "interpolated_calibration"
-)
+OUTPUT_PATH = Path(__file__).parent.parent.parent / "comparisons" / "interpolated_calibration"
 HERITAGE_PATH = r"instrument_team_data/swe/swepam-nswe-1999-159.v1-02.hdf"
 
 variable_mapping = {
@@ -236,9 +234,7 @@ def compute_canonicalized_data(population: str):
     plt.savefig(OUTPUT_PATH / f"{population}_temperature_rtn_theta.png")
     plt.clf()
 
-    plt.plot(
-        heritage_canonical_phi, ".", label=f"Heritage: {heritage_phi_rtn_integrated}"
-    )
+    plt.plot(heritage_canonical_phi, ".", label=f"Heritage: {heritage_phi_rtn_integrated}")
     plt.plot(canonical_phi, ".", label=f"Modern {phi_rtn_integrated}")
     plt.legend()
     plt.savefig(OUTPUT_PATH / f"{population}_temperature_rtn_phi.png")
diff --git a/scripts/swe/create_fake_l2_cdf.py b/scripts/swe/create_fake_l2_cdf.py
index f940fd9e..05605ce4 100644
--- a/scripts/swe/create_fake_l2_cdf.py
+++ b/scripts/swe/create_fake_l2_cdf.py
@@ -100,17 +100,13 @@ def create_fake_swe_l1b_and_l2_cdf(
         cdf.new("inst_el", [-63, -42, -21, 0, 21, 42, 63], recVary=False)
 
         shape_without_aperture_axis = psd.shape[:-1]
-        placeholder_insta_az_spin_sector = (
-            np.random.random(shape_without_aperture_axis) * 360
-        )
+        placeholder_insta_az_spin_sector = np.random.random(shape_without_aperture_axis) * 360
         create_variable(cdf, "inst_az_spin_sector", placeholder_insta_az_spin_sector)
 
         minutes = len(counts_in_swe_shape)
         measurement_count = placeholder_insta_az_spin_sector.size
         measurement_times = np.linspace(0, minutes * 60, measurement_count)
-        placeholder_acquisition_time = measurement_times.reshape(
-            shape_without_aperture_axis
-        )
+        placeholder_acquisition_time = measurement_times.reshape(shape_without_aperture_axis)
         create_variable(cdf, "acquisition_time", placeholder_acquisition_time)
 
         acquisition_duration = np.full((minutes, 20, 30), 80000)
@@ -121,9 +117,7 @@ def create_fake_swe_l1b_and_l2_cdf(
         cdf["settle_duration"] = np.full((minutes, 4), 133333.3333333334)
 
 
-def create_fake_swapi_l3a_cdf(
-    l2_swepam_ion_file_path: str, output_swapi_file_path: str
-):
+def create_fake_swapi_l3a_cdf(l2_swepam_ion_file_path: str, output_swapi_file_path: str):
     l2_swepam_ion_file = HDF(l2_swepam_ion_file_path)
     vs_ion = l2_swepam_ion_file.vstart()
     vd_ion = vs_ion.attach("swepam_i")
@@ -174,18 +168,14 @@ def create_fake_swapi_l3a_cdf(
 1999	160	    3600	0	-0.98089	-0.17395	-0.08711	 0.02904	 0.94059	 0.33831	 0.98116	 0.18238	-0.06375"""
 
 
-def create_fake_mag_l1d_cdf(
-    l2_swepam_electron_file_path: str, output_mag_file_path: str
-):
+def create_fake_mag_l1d_cdf(l2_swepam_electron_file_path: str, output_mag_file_path: str):
     buffer = io.StringIO(ATTITUDE_DATA)
     data = np.loadtxt(buffer, skiprows=1)
 
     def time_to_float(ts):
         return [(t - datetime(1999, 1, 1)).total_seconds() for t in ts]
 
-    times = [
-        datetime(1998, 12, 31) + timedelta(days=row[1], seconds=row[2]) for row in data
-    ]
+    times = [datetime(1998, 12, 31) + timedelta(days=row[1], seconds=row[2]) for row in data]
 
     l2_swepam_electron_file_path = HDF(l2_swepam_electron_file_path)
     vs_electron = l2_swepam_electron_file_path.vstart()
@@ -195,15 +185,9 @@ def time_to_float(ts):
 
     correction_factor = datetime(2025, 6, 30) - datetime(1999, 6, 8)
     mag_epochs_uncorrected = mag_epochs - correction_factor
-    r_att = np.interp(
-        time_to_float(mag_epochs_uncorrected), time_to_float(times), data[:, 4]
-    )
-    t_att = np.interp(
-        time_to_float(mag_epochs_uncorrected), time_to_float(times), data[:, 5]
-    )
-    n_att = np.interp(
-        time_to_float(mag_epochs_uncorrected), time_to_float(times), data[:, 6]
-    )
+    r_att = np.interp(time_to_float(mag_epochs_uncorrected), time_to_float(times), data[:, 4])
+    t_att = np.interp(time_to_float(mag_epochs_uncorrected), time_to_float(times), data[:, 5])
+    n_att = np.interp(time_to_float(mag_epochs_uncorrected), time_to_float(times), data[:, 6])
 
     rtn_att = np.stack((r_att, t_att, n_att), axis=-1)
 
@@ -289,16 +273,13 @@ def create_expected_cdf(dataset: VD, fields: list[str], file_name):
 if __name__ == "__main__":
     path = Path(__file__)
     l1_hdf_path = (
-        path.parent.parent.parent
-        / "instrument_team_data/swe/ACE_LV1_1999-159.swepam.hdf"
+        path.parent.parent.parent / "instrument_team_data/swe/ACE_LV1_1999-159.swepam.hdf"
     )
     l2_electron_hdf_path = (
-        path.parent.parent.parent
-        / "instrument_team_data/swe/swepam-nswe-1999-159.v1-02.hdf"
+        path.parent.parent.parent / "instrument_team_data/swe/swepam-nswe-1999-159.v1-02.hdf"
     )
     l2_ion_hdf_path = (
-        path.parent.parent.parent
-        / "instrument_team_data/swe/swepam-swi-1999-159.v2-01.hdf"
+        path.parent.parent.parent / "instrument_team_data/swe/swepam-swi-1999-159.v2-01.hdf"
     )
 
     l2_swe_cdf_file_path = (
diff --git a/scripts/swe/filter_good_times_from_l1b_sdc_cdf.py b/scripts/swe/filter_good_times_from_l1b_sdc_cdf.py
index be6e53c6..44357e77 100644
--- a/scripts/swe/filter_good_times_from_l1b_sdc_cdf.py
+++ b/scripts/swe/filter_good_times_from_l1b_sdc_cdf.py
@@ -5,20 +5,14 @@
 
 l1b_cdf = CDF(sys.argv[1])
 
-with CDF(
-    "imap_swe_l1b_sci-3-11-good-times_20100101_v002", masterpath="", readonly=False
-) as cdf:
-    cdf["acq_duration"] = np.array(
-        [l1b_cdf["acq_duration"][2], l1b_cdf["acq_duration"][4]]
-    )
+with CDF("imap_swe_l1b_sci-3-11-good-times_20100101_v002", masterpath="", readonly=False) as cdf:
+    cdf["acq_duration"] = np.array([l1b_cdf["acq_duration"][2], l1b_cdf["acq_duration"][4]])
     cdf["acq_duration"].attrs = l1b_cdf["acq_duration"].attrs
     cdf["acq_start_coarse"] = np.array(
         [l1b_cdf["acq_start_coarse"][2], l1b_cdf["acq_start_coarse"][4]]
     )
     cdf["acq_start_coarse"].attrs = l1b_cdf["acq_start_coarse"].attrs
-    cdf["acq_start_fine"] = np.array(
-        [l1b_cdf["acq_start_fine"][2], l1b_cdf["acq_start_fine"][4]]
-    )
+    cdf["acq_start_fine"] = np.array([l1b_cdf["acq_start_fine"][2], l1b_cdf["acq_start_fine"][4]])
     cdf["acq_start_fine"].attrs = l1b_cdf["acq_start_fine"].attrs
     cdf["acquisition_time"] = np.array(
         [l1b_cdf["acquisition_time"][2], l1b_cdf["acquisition_time"][4]]
@@ -32,27 +26,19 @@
     cdf["cksum"].attrs = l1b_cdf["cksum"].attrs
     cdf["epoch"] = np.array([l1b_cdf["epoch"][2], l1b_cdf["epoch"][4]])
     cdf["epoch"].attrs = l1b_cdf["epoch"].attrs
-    cdf["esa_acq_cfg"] = np.array(
-        [l1b_cdf["esa_acq_cfg"][2], l1b_cdf["esa_acq_cfg"][4]]
-    )
+    cdf["esa_acq_cfg"] = np.array([l1b_cdf["esa_acq_cfg"][2], l1b_cdf["esa_acq_cfg"][4]])
     cdf["esa_acq_cfg"].attrs = l1b_cdf["esa_acq_cfg"].attrs
-    cdf["esa_table_num"] = np.array(
-        [l1b_cdf["esa_table_num"][2], l1b_cdf["esa_table_num"][4]]
-    )
+    cdf["esa_table_num"] = np.array([l1b_cdf["esa_table_num"][2], l1b_cdf["esa_table_num"][4]])
     cdf["esa_table_num"].attrs = l1b_cdf["esa_table_num"].attrs
     cdf["high_count"] = np.array([l1b_cdf["high_count"][2], l1b_cdf["high_count"][4]])
     cdf["high_count"].attrs = l1b_cdf["high_count"].attrs
-    cdf["quarter_cycle"] = np.array(
-        [l1b_cdf["quarter_cycle"][2], l1b_cdf["quarter_cycle"][4]]
-    )
+    cdf["quarter_cycle"] = np.array([l1b_cdf["quarter_cycle"][2], l1b_cdf["quarter_cycle"][4]])
     cdf["quarter_cycle"].attrs = l1b_cdf["quarter_cycle"].attrs
     cdf["repoint_warning"] = np.array(
         [l1b_cdf["repoint_warning"][2], l1b_cdf["repoint_warning"][4]]
     )
     cdf["repoint_warning"].attrs = l1b_cdf["repoint_warning"].attrs
-    cdf["science_data"] = np.array(
-        [l1b_cdf["science_data"][2], l1b_cdf["science_data"][4]]
-    )
+    cdf["science_data"] = np.array([l1b_cdf["science_data"][2], l1b_cdf["science_data"][4]])
     cdf["science_data"].attrs = l1b_cdf["science_data"].attrs
     cdf["settle_duration"] = np.array(
         [l1b_cdf["settle_duration"][2], l1b_cdf["settle_duration"][4]]
@@ -60,9 +46,7 @@
     cdf["settle_duration"].attrs = l1b_cdf["settle_duration"].attrs
     cdf["shcoarse"] = np.array([l1b_cdf["shcoarse"][2], l1b_cdf["shcoarse"][4]])
     cdf["shcoarse"].attrs = l1b_cdf["shcoarse"].attrs
-    cdf["spin_period"] = np.array(
-        [l1b_cdf["spin_period"][2], l1b_cdf["spin_period"][4]]
-    )
+    cdf["spin_period"] = np.array([l1b_cdf["spin_period"][2], l1b_cdf["spin_period"][4]])
     cdf["spin_period"].attrs = l1b_cdf["spin_period"].attrs
     cdf["spin_period_source"] = np.array(
         [l1b_cdf["spin_period_source"][2], l1b_cdf["spin_period_source"][4]]
@@ -78,17 +62,11 @@
         [l1b_cdf["spin_phase_validity"][2], l1b_cdf["spin_phase_validity"][4]]
     )
     cdf["spin_phase_validity"].attrs = l1b_cdf["spin_phase_validity"].attrs
-    cdf["stim_cfg_reg"] = np.array(
-        [l1b_cdf["stim_cfg_reg"][2], l1b_cdf["stim_cfg_reg"][4]]
-    )
+    cdf["stim_cfg_reg"] = np.array([l1b_cdf["stim_cfg_reg"][2], l1b_cdf["stim_cfg_reg"][4]])
     cdf["stim_cfg_reg"].attrs = l1b_cdf["stim_cfg_reg"].attrs
-    cdf["stim_enabled"] = np.array(
-        [l1b_cdf["stim_enabled"][2], l1b_cdf["stim_enabled"][4]]
-    )
+    cdf["stim_enabled"] = np.array([l1b_cdf["stim_enabled"][2], l1b_cdf["stim_enabled"][4]])
     cdf["stim_enabled"].attrs = l1b_cdf["stim_enabled"].attrs
-    cdf["threshold_dac"] = np.array(
-        [l1b_cdf["threshold_dac"][2], l1b_cdf["threshold_dac"][4]]
-    )
+    cdf["threshold_dac"] = np.array([l1b_cdf["threshold_dac"][2], l1b_cdf["threshold_dac"][4]])
     cdf["threshold_dac"].attrs = l1b_cdf["threshold_dac"].attrs
 
     cdf["cycle"] = l1b_cdf["cycle"]
diff --git a/scripts/swe/generate_sci_using_swapi_with_predicted_ephemeris.py b/scripts/swe/generate_sci_using_swapi_with_predicted_ephemeris.py
index c3681208..09bdb1ea 100644
--- a/scripts/swe/generate_sci_using_swapi_with_predicted_ephemeris.py
+++ b/scripts/swe/generate_sci_using_swapi_with_predicted_ephemeris.py
@@ -6,7 +6,7 @@
 from imap_data_access import DependencyFilePath, ProcessingInputCollection
 from imap_data_access.processing_input import generate_imap_input
 
-from imap_l3_processing.utils import get_spice_kernels_file_names, SpiceKernelTypes
+from imap_l3_processing.utils import SpiceKernelTypes, get_spice_kernels_file_names
 
 SPICE_KERNELS = [
     SpiceKernelTypes.Leapseconds,
@@ -22,9 +22,7 @@
 
 
 def generate_swe_for_given_day(day: datetime):
-    spice_kernel_files = get_spice_kernels_file_names(
-        day, day + timedelta(days=1), SPICE_KERNELS
-    )
+    spice_kernel_files = get_spice_kernels_file_names(day, day + timedelta(days=1), SPICE_KERNELS)
     day_as_string = day.strftime("%Y%m%d")
     l2_file_name = imap_data_access.query(
         instrument="swe",
@@ -65,9 +63,7 @@ def generate_swe_for_given_day(day: datetime):
         swe_ancillary_file_name,
     ]
 
-    input_collection = ProcessingInputCollection(
-        *[generate_imap_input(i) for i in input_files]
-    )
+    input_collection = ProcessingInputCollection(*[generate_imap_input(i) for i in input_files])
     input_collection.download_all_files()
 
     dependency_file_name = f"imap_swe_l3_sci_{day_as_string}_v002.json"
diff --git a/scripts/swe/plot_swe.py b/scripts/swe/plot_swe.py
index 37aba776..4a6439cd 100644
--- a/scripts/swe/plot_swe.py
+++ b/scripts/swe/plot_swe.py
@@ -18,7 +18,5 @@
 
 (fig, (ax1, ax2)) = plt.subplots(2, 1)
 ax1.pcolormesh(dist_1d.filled(np.nan).T, norm="log")
-ax2.pcolormesh(
-    np.ma.mean(rebinned_by_phi[:, :, 0:4], axis=-1).filled(np.nan).T, norm="log"
-)
+ax2.pcolormesh(np.ma.mean(rebinned_by_phi[:, :, 0:4], axis=-1).filled(np.nan).T, norm="log")
 plt.show()
diff --git a/scripts/swe/read_ace.py b/scripts/swe/read_ace.py
old mode 100644
new mode 100755
index 0bf72886..fade6d11
--- a/scripts/swe/read_ace.py
+++ b/scripts/swe/read_ace.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 """
 Created on Tue Mar 11 16:12:45 2025
 
@@ -18,12 +17,8 @@
 from pyhdf.SD import SD, SDC
 
 # import pyhdf.SD
-from pyhdf.VS import VS
 from spacepy.pycdf import CDF
 
-SD
-VS
-
 
 def decompressed_counts(cem_count: int) -> int:
     """
@@ -98,7 +93,7 @@ def hdf4_to_xarray(hdf_file_path):
         dataset = hdf_file.select(dataset_name)
         try:
             data = dataset.get()  # Explicit read using the get method
-        except Exception as e:
+        except Exception as e:  # noqa: BLE001
             print(f"Error reading dataset {dataset_name}: {e}")
             continue
 
@@ -143,18 +138,14 @@ def calculate_phase(phase, spin_period):
             f1 = N_PHI_LEVEL1 * sss + k + 1
             f2 = 120 * sss + N_ENERGIES_LEVEL1 * k + rrr + 1
             offset = (
-                (0.0547645 + f1 * 0.0575027 + (f2 - 0.5) * K_FOR_THIS_MODE)
-                * 12.0
-                / spin_period
+                (0.0547645 + f1 * 0.0575027 + (f2 - 0.5) * K_FOR_THIS_MODE) * 12.0 / spin_period
             )
             phi[i][k] = phase + offset
     CONVERT_PHI_TO_IMAP_AZIMUTH = 270
     return (phi + CONVERT_PHI_TO_IMAP_AZIMUTH - SWE_MOUNTING_ANGLE) % 360
 
 
-def calculate_acquisition_time(
-    phase: float, spin_period: float, epoch: datetime
-) -> np.ndarray:
+def calculate_acquisition_time(phase: float, spin_period: float, epoch: datetime) -> np.ndarray:
     met = get_met_from_epoch(epoch)
 
     met_rounded = (met // 15) * 15
@@ -179,15 +170,11 @@ def plot_dnswe_data_from_hdf(file_path):
     print(f"Data:\n{data}")
 
     # For simplicity, let's plot the first 2D slice (you can change this depending on your needs)
-    data_slice = data[
-        :, 0, 0, 0, :
-    ]  # Select a slice (e.g., first 2D slice from the 5D array)
+    data_slice = data[:, 0, 0, 0, :]  # Select a slice (e.g., first 2D slice from the 5D array)
 
     # Plot the data
     plt.figure(figsize=(10, 6))
-    plt.imshow(
-        data_slice, norm=LogNorm(), aspect="auto", cmap="viridis", origin="lower"
-    )
+    plt.imshow(data_slice, norm=LogNorm(), aspect="auto", cmap="viridis", origin="lower")
     plt.colorbar(label="DNSWE Values")
     plt.title("Plot of DNSWE_COUNT dataset slice")
     plt.xlabel("Dimension 1")
@@ -263,9 +250,7 @@ def get_epochs_from_output_file(filepath: str) -> tuple[np.array, np.array]:
         "dim4": "cem",
     },
 )
-decompress_table = decompression_table = np.array(
-    [decompressed_counts(i) for i in range(256)]
-)
+decompress_table = decompression_table = np.array([decompressed_counts(i) for i in range(256)])
 counts = decompress_table[ds_expanded.values.astype(int)]
 sample_time = 0.10031
 sample_time_microseconds = int(sample_time * 1e6)
@@ -281,15 +266,13 @@ def get_epochs_from_output_file(filepath: str) -> tuple[np.array, np.array]:
     ]
 )
 
-calibration = cal_t0 + ((sc_times - t0) / (t1 - t0))[
-    :, np.newaxis, np.newaxis, np.newaxis
-] * (cal_t1 - cal_t0)
+calibration = cal_t0 + ((sc_times - t0) / (t1 - t0))[:, np.newaxis, np.newaxis, np.newaxis] * (
+    cal_t1 - cal_t0
+)
 
 rates *= calibration
 
-phase, spin = get_phase_and_spin(
-    "instrument_team_data/swe/swepam-nswe-1999-159.v1-02.hdf"
-)
+phase, spin = get_phase_and_spin("instrument_team_data/swe/swepam-nswe-1999-159.v1-02.hdf")
 
 acquisition_time = []
 
diff --git a/scripts/swe/swe_l2.py b/scripts/swe/swe_l2.py
index ff5ebdf2..1dc942a5 100644
--- a/scripts/swe/swe_l2.py
+++ b/scripts/swe/swe_l2.py
@@ -7,8 +7,7 @@
 import imap_processing.tests.conftest
 import pandas as pd
 from imap_processing import imap_module_directory
-from imap_processing.cdf.utils import load_cdf
-from imap_processing.cdf.utils import write_cdf
+from imap_processing.cdf.utils import load_cdf, write_cdf
 from imap_processing.spice.spin import set_global_spin_table_paths
 from imap_processing.swe.l1a.swe_l1a import swe_l1a
 from imap_processing.swe.l1b.swe_l1b import swe_l1b
diff --git a/scripts/swe/swe_l2_old.py b/scripts/swe/swe_l2_old.py
index 6cb58508..5c5d6eb4 100644
--- a/scripts/swe/swe_l2_old.py
+++ b/scripts/swe/swe_l2_old.py
@@ -7,8 +7,7 @@
 import imap_processing.tests.conftest
 import pandas as pd
 from imap_processing import imap_module_directory
-from imap_processing.cdf.utils import load_cdf
-from imap_processing.cdf.utils import write_cdf
+from imap_processing.cdf.utils import load_cdf, write_cdf
 
 # from imap_processing.spice.spin import set_global_spin_table_paths
 from imap_processing.swe.l1a.swe_l1a import swe_l1a
diff --git a/scripts/time_shift_cdf.py b/scripts/time_shift_cdf.py
index f39c3825..fd059dc3 100644
--- a/scripts/time_shift_cdf.py
+++ b/scripts/time_shift_cdf.py
@@ -1,17 +1,17 @@
 import sys
 from datetime import datetime
 from pathlib import Path
-from typing import Optional, Any
+from typing import Any
 
-from imap_data_access.file_validation import ScienceFilePath, ImapFilePath
+from imap_data_access.file_validation import ImapFilePath, ScienceFilePath
 from spacepy.pycdf import CDF
 
 
 def convert_epoch_time(
     filename,
     target=datetime(2026, 10, 20, 12),
-    new_science_file_parts: Optional[dict[str, Any]] = None,
-) -> Optional[Path]:
+    new_science_file_parts: dict[str, Any] | None = None,
+) -> Path | None:
     file_path = Path(filename)
     new_science_file_parts = new_science_file_parts or {}
 
diff --git a/scripts/truncate_cdf.py b/scripts/truncate_cdf.py
index 910364a4..b95a2fd2 100644
--- a/scripts/truncate_cdf.py
+++ b/scripts/truncate_cdf.py
@@ -14,9 +14,7 @@ def truncate_cdf(cdf_path: Path, number_of_epochs: int = 2) -> Path:
             cdf.attrs[attr_name] = list(original_cdf.attrs[attr_name])
 
         for var in original_cdf:
-            depends_on_epoch = (
-                var == "epoch" or original_cdf[var].attrs.get("DEPEND_0") == "epoch"
-            )
+            depends_on_epoch = var == "epoch" or original_cdf[var].attrs.get("DEPEND_0") == "epoch"
             if depends_on_epoch:
                 cdf.clone(original_cdf[var], var, data=False)
                 cdf[var][:] = original_cdf[var][...][:number_of_epochs]
diff --git a/scripts/ultra/create_example_ultra_l1c_pset.py b/scripts/ultra/create_example_ultra_l1c_pset.py
index 2ec11a78..e4b683a7 100644
--- a/scripts/ultra/create_example_ultra_l1c_pset.py
+++ b/scripts/ultra/create_example_ultra_l1c_pset.py
@@ -103,9 +103,7 @@ def create_example_ultra_l1c_pset(
 
     # Calculate probability based on distance from target latitude
     lat_diff = np.abs(lat_pix - stripe_center_lat)
-    prob_scaling_factor = counts_scaling_params[1] * np.exp(
-        -(lat_diff**2) / (2 * width_scale**2)
-    )
+    prob_scaling_factor = counts_scaling_params[1] * np.exp(-(lat_diff**2) / (2 * width_scale**2))
     # Generate counts using binomial distribution
     rng = np.random.default_rng(seed=42)
     counts = np.array(
@@ -120,16 +118,13 @@ def create_example_ultra_l1c_pset(
         -(lat_diff**2) / (2 * (3 * width_scale) ** 2)
     )
     exposure_time = (
-        peak_exposure
-        * (prob_scaling_factor_exptime / prob_scaling_factor_exptime.max())
+        peak_exposure * (prob_scaling_factor_exptime / prob_scaling_factor_exptime.max())
     )[np.newaxis, :]
 
     # Exposure time/factor can optionally be energy dependent
     if energy_dependent_exposure:
         # Add energy dimension to exposure time as axis 1
-        exposure_time = np.repeat(
-            exposure_time[:, np.newaxis, :], num_energy_bins, axis=1
-        )
+        exposure_time = np.repeat(exposure_time[:, np.newaxis, :], num_energy_bins, axis=1)
         exposure_dims = [
             CoordNames.TIME.value,
             CoordNames.ENERGY_ULTRA_L1C.value,
@@ -223,9 +218,11 @@ def create_example_ultra_l1c_pset(
 
 
 def _write_ultra_l1c_cdf_with_parents(
-    out_path: Path = get_run_local_data_path("ultra/fake_l1c_psets/test_pset.cdf"),
+    out_path: Path | None = None,
     date: str = "2025-09-01T00:00:00",
 ):
+    if out_path is None:
+        get_run_local_data_path("ultra/fake_l1c_psets/test_pset.cdf")
     out_xarray = create_example_ultra_l1c_pset(
         nside=1, timestr=date, energy_dependent_exposure=True
     )
@@ -311,14 +308,11 @@ def _write_ultra_l1c_cdf_with_parents(
                 )
             elif cdf[var].type() == pycdf.const.CDF_INT8.value:
                 cdf[var].attrs["FILLVAL"] = -9223372036854775808
-            elif (
-                cdf[var].type() == pycdf.const.CDF_FLOAT.value
-                or pycdf.const.CDF_DOUBLE.value
-            ):
+            elif cdf[var].type() == pycdf.const.CDF_FLOAT.value or pycdf.const.CDF_DOUBLE.value:
                 cdf[var].attrs["FILLVAL"] = -1e31
 
 
-def _add_depends(var: Var, depends: list[str], depend_0: str = None):
+def _add_depends(var: Var, depends: list[str], depend_0: str | None = None):
     if depend_0 is not None:
         var.attrs["DEPEND_0"] = depend_0
     for i, dep in enumerate(depends):
diff --git a/scripts/ultra/create_example_ultra_l2_map.py b/scripts/ultra/create_example_ultra_l2_map.py
index 9c256bee..0033acdb 100644
--- a/scripts/ultra/create_example_ultra_l2_map.py
+++ b/scripts/ultra/create_example_ultra_l2_map.py
@@ -1,4 +1,5 @@
 import datetime
+from pathlib import Path
 
 import astropy_healpix.healpy as hp
 import numpy as np
@@ -16,7 +17,7 @@
 DEFAULT_HEALPIX_NSIDE_L1C = 16
 
 
-def create_example_ultra_l2_map(  # noqa: PLR0913
+def create_example_ultra_l2_map(
     nside: int = DEFAULT_HEALPIX_NSIDE_L1C,
     stripe_center_lat: int = 0,
     width_scale: float = 180.0,
@@ -93,9 +94,7 @@ def create_example_ultra_l2_map(  # noqa: PLR0913
 
     # Calculate probability based on distance from target latitude
     lat_diff = np.abs(lat_pix - stripe_center_lat)
-    prob_scaling_factor = counts_scaling_params[1] * np.exp(
-        -(lat_diff**2) / (2 * width_scale**2)
-    )
+    prob_scaling_factor = counts_scaling_params[1] * np.exp(-(lat_diff**2) / (2 * width_scale**2))
     # Generate counts using binomial distribution
     rng = np.random.default_rng(seed=42)
     counts = np.array(
@@ -177,19 +176,15 @@ def create_example_ultra_l2_map(  # noqa: PLR0913
     pset_product[CoordNames.ELEVATION_L1C.value].attrs["VAR_TYPE"] = "data"
 
     pset_product.coords[CoordNames.TIME.value].attrs["VAR_TYPE"] = "support_data"
-    pset_product.coords[CoordNames.ENERGY_ULTRA_L1C.value].attrs["VAR_TYPE"] = (
-        "support_data"
-    )
-    pset_product.coords[CoordNames.HEALPIX_INDEX.value].attrs["VAR_TYPE"] = (
-        "support_data"
-    )
+    pset_product.coords[CoordNames.ENERGY_ULTRA_L1C.value].attrs["VAR_TYPE"] = "support_data"
+    pset_product.coords[CoordNames.HEALPIX_INDEX.value].attrs["VAR_TYPE"] = "support_data"
 
     return pset_product
 
 
-def _write_ultra_l2_cdf_with_parents(
-    out_path=get_run_local_data_path("ultra/fake_l2_maps/test_l2_map.cdf"),
-):
+def _write_ultra_l2_cdf_with_parents(out_path: Path | None = None):
+    if out_path is None:
+        out_path = get_run_local_data_path("ultra/fake_l2_maps/test_l2_map.cdf")
     out_xarray = create_example_ultra_l2_map(nside=2)
     out_path.parent.mkdir(parents=True, exist_ok=True)
     out_path.unlink(missing_ok=True)
@@ -198,12 +193,8 @@ def _write_ultra_l2_cdf_with_parents(
         cdf.new("ena_intensity", out_xarray["counts"].values)
         cdf.new("exposure_factor", out_xarray["exposure_time"].values)
         cdf.new("sensitivity", out_xarray["sensitivity"].values)
-        cdf.new(
-            "latitude", out_xarray[CoordNames.ELEVATION_L1C.value].values, recVary=False
-        )
-        cdf.new(
-            "longitude", out_xarray[CoordNames.AZIMUTH_L1C.value].values, recVary=False
-        )
+        cdf.new("latitude", out_xarray[CoordNames.ELEVATION_L1C.value].values, recVary=False)
+        cdf.new("longitude", out_xarray[CoordNames.AZIMUTH_L1C.value].values, recVary=False)
         cdf.new(
             "epoch",
             out_xarray[CoordNames.TIME.value].values,
@@ -246,9 +237,7 @@ def _write_ultra_l2_cdf_with_parents(
             "solid_angle",
             np.full_like(out_xarray[CoordNames.HEALPIX_INDEX.value].values, 1),
         )
-        cdf.new(
-            "ena_intensity_stat_uncert", np.full_like(out_xarray["counts"].values, 1)
-        )
+        cdf.new("ena_intensity_stat_uncert", np.full_like(out_xarray["counts"].values, 1))
         cdf.new("ena_intensity_sys_err", np.full_like(out_xarray["counts"].values, 1))
         cdf.new(
             "pixel_index_label",
@@ -262,10 +251,7 @@ def _write_ultra_l2_cdf_with_parents(
                 )
             elif cdf[var].type() == pycdf.const.CDF_INT8.value:
                 cdf[var].attrs["FILLVAL"] = -9223372036854775808
-            elif (
-                cdf[var].type() == pycdf.const.CDF_FLOAT.value
-                or pycdf.const.CDF_DOUBLE.value
-            ):
+            elif cdf[var].type() == pycdf.const.CDF_FLOAT.value or pycdf.const.CDF_DOUBLE.value:
                 cdf[var].attrs["FILLVAL"] = -1e31
 
 
diff --git a/scripts/ultra/create_example_ultra_l2_map_with_power_law.py b/scripts/ultra/create_example_ultra_l2_map_with_power_law.py
index 0dae3012..bccf958b 100644
--- a/scripts/ultra/create_example_ultra_l2_map_with_power_law.py
+++ b/scripts/ultra/create_example_ultra_l2_map_with_power_law.py
@@ -9,9 +9,7 @@
 from tests.test_helpers import get_test_data_path
 
 
-def _create_example_ultra_l2_map_with_power_law(
-    out_path: Path, parents: list[str] = None
-):
+def _create_example_ultra_l2_map_with_power_law(out_path: Path, parents: list[str] | None = None):
     out_path.parent.mkdir(parents=True, exist_ok=True)
     out_path.unlink(missing_ok=True)
     num_lon = 60
@@ -28,15 +26,9 @@ def _create_example_ultra_l2_map_with_power_law(
     energy_breakpoint = 15  # 15 keV
     for i in range(num_lon):
         for j in range(num_lat):
-            breakpoint_index = np.searchsorted(
-                energies, energy_breakpoint, side="right"
-            )
-            ena_intensities[0, :breakpoint_index, i, j] = power_law_1(
-                energies[:breakpoint_index]
-            )
-            ena_intensities[0, breakpoint_index:, i, j] = power_law_2(
-                energies[breakpoint_index:]
-            )
+            breakpoint_index = np.searchsorted(energies, energy_breakpoint, side="right")
+            ena_intensities[0, :breakpoint_index, i, j] = power_law_1(energies[:breakpoint_index])
+            ena_intensities[0, breakpoint_index:, i, j] = power_law_2(energies[breakpoint_index:])
 
     ena_intensities_delta = np.full_like(ena_intensities, 0.0001)
 
@@ -48,9 +40,7 @@ def _create_example_ultra_l2_map_with_power_law(
         cdf.new("latitude_delta", np.full_like(lat, 2), recVary=False)
         cdf.new("longitude", lon, recVary=False)
         cdf.new("longitude_delta", np.full_like(lon, 2), recVary=False)
-        cdf.new(
-            "epoch", np.array([datetime.now()]), type=pycdf.const.CDF_TIME_TT2000.value
-        )
+        cdf.new("epoch", np.array([datetime.now()]), type=pycdf.const.CDF_TIME_TT2000.value)
         cdf.new("energy", energies, recVary=False)
         cdf.new("epoch_delta", np.array([1]))
         cdf.new("energy_delta_plus", np.full_like(energies, 0.1))
@@ -58,9 +48,7 @@ def _create_example_ultra_l2_map_with_power_law(
         cdf.new("energy_label", [str(val) for val in energies])
         cdf.new(
             "obs_date",
-            np.full_like(
-                ena_intensities, (datetime.now() - TT2000_EPOCH).total_seconds() * 1e9
-            ),
+            np.full_like(ena_intensities, (datetime.now() - TT2000_EPOCH).total_seconds() * 1e9),
             type=pycdf.const.CDF_TIME_TT2000.value,
         )
         cdf.new("obs_date_range", np.full_like(ena_intensities, 1))
@@ -75,15 +63,10 @@ def _create_example_ultra_l2_map_with_power_law(
 
         for var in cdf:
             if cdf[var].type() == pycdf.const.CDF_TIME_TT2000.value:
-                cdf[var].attrs["FILLVAL"] = datetime.fromisoformat(
-                    "9999-12-31T23:59:59.999999999"
-                )
+                cdf[var].attrs["FILLVAL"] = datetime.fromisoformat("9999-12-31T23:59:59.999999999")
             elif cdf[var].type() == pycdf.const.CDF_INT8.value:
                 cdf[var].attrs["FILLVAL"] = -9223372036854775808
-            elif (
-                cdf[var].type() == pycdf.const.CDF_FLOAT.value
-                or pycdf.const.CDF_DOUBLE.value
-            ):
+            elif cdf[var].type() == pycdf.const.CDF_FLOAT.value or pycdf.const.CDF_DOUBLE.value:
                 cdf[var].attrs["FILLVAL"] = -1e31
 
 
diff --git a/scripts/ultra/create_example_ultra_l3_survival_probabilities_cdf.py b/scripts/ultra/create_example_ultra_l3_survival_probabilities_cdf.py
index 3b468663..5c5297ba 100644
--- a/scripts/ultra/create_example_ultra_l3_survival_probabilities_cdf.py
+++ b/scripts/ultra/create_example_ultra_l3_survival_probabilities_cdf.py
@@ -18,9 +18,7 @@ def create_survival_probabilities_file(
     glows_file_path: Path, date_for_file: datetime, cdf_file_path: Path
 ):
     with open(glows_file_path) as input_data:
-        energy_line = [
-            line for line in input_data.readlines() if line.startswith("#energy_grid")
-        ]
+        energy_line = [line for line in input_data if line.startswith("#energy_grid")]
         assert len(energy_line) == 1
         match = [float(x) for x in re.findall(r"\s+([0-9.]+)", energy_line[0])]
         energy_units = re.search(r"\[(.+)]", energy_line[0]).group(1)
@@ -37,7 +35,7 @@ def create_survival_probabilities_file(
     latitude = lats.value
     longitude = lons.value
     skips = 0
-    for i in range(0, 3072):
+    for i in range(3072):
         if i in healpix_index:
             output_survival_probabilities[:, i] = spin_angle_and_survival_probabilities[
                 i - skips, 3:-1
@@ -91,10 +89,10 @@ def create_survival_probabilities_file(
 
     for i in range(num_psets_to_generate):
         date_to_set = start_date + timedelta(days=i)
-        filename = f"imap_glows_l3e_survival-probability-ul_{date_to_set.strftime('%Y%m%d')}_v015.cdf"
-        cdf_file_path = get_test_data_path(
-            f"ultra/fake_l3e_survival_probabilities/{filename}"
+        filename = (
+            f"imap_glows_l3e_survival-probability-ul_{date_to_set.strftime('%Y%m%d')}_v015.cdf"
         )
+        cdf_file_path = get_test_data_path(f"ultra/fake_l3e_survival_probabilities/{filename}")
 
         cdf_file_path.unlink(missing_ok=True)
         create_survival_probabilities_file(input_file_path, date_to_set, cdf_file_path)
diff --git a/scripts/ultra/create_glows_l3e_cdf_from_dat.py b/scripts/ultra/create_glows_l3e_cdf_from_dat.py
index 860d1d25..58bcc0fb 100644
--- a/scripts/ultra/create_glows_l3e_cdf_from_dat.py
+++ b/scripts/ultra/create_glows_l3e_cdf_from_dat.py
@@ -11,9 +11,7 @@
 
 version = 0
 
-glows_dat_dir = Path(
-    r"C:\Users\Harrison\Downloads\timeshifted_glows_data\fake_l3_validation"
-)
+glows_dat_dir = Path(r"C:\Users\Harrison\Downloads\timeshifted_glows_data\fake_l3_validation")
 glows_dat_files = list(glows_dat_dir.glob("*"))
 output_dir = Path(r"C:\Users\Harrison\Downloads\timeshifted_glows_data\cdf")
 output_dir.mkdir(exist_ok=True)
diff --git a/scripts/ultra/create_l1c_l2_and_glows_with_matching_date_range.py b/scripts/ultra/create_l1c_l2_and_glows_with_matching_date_range.py
index 77b305a7..d1cd69df 100644
--- a/scripts/ultra/create_l1c_l2_and_glows_with_matching_date_range.py
+++ b/scripts/ultra/create_l1c_l2_and_glows_with_matching_date_range.py
@@ -13,14 +13,12 @@
     create_survival_probabilities_file,
 )
 from tests.test_helpers import (
-    get_test_instrument_team_data_path,
     get_run_local_data_path,
+    get_test_instrument_team_data_path,
 )
 
 
-def create_l1c_and_glows_with_matching_date_range(
-    start_date: datetime, end_date: datetime
-):
+def create_l1c_and_glows_with_matching_date_range(start_date: datetime, end_date: datetime):
     process_date = start_date
     repoint_counter = 0
     l1c_filepaths = []
@@ -38,9 +36,7 @@ def create_l1c_and_glows_with_matching_date_range(
             f"{base_path}/ultra_l1c/imap_ultra_l1c_45sensor-spacecraftpset_{process_date:%Y%m%d}-repoint{repoint_counter:05}_v{version_number:03}.cdf"
         )
         l1c_file_path.parent.mkdir(parents=True, exist_ok=True)
-        _write_ultra_l1c_cdf_with_parents(
-            date=process_date.isoformat(), out_path=l1c_file_path
-        )
+        _write_ultra_l1c_cdf_with_parents(date=process_date.isoformat(), out_path=l1c_file_path)
         l1c_filepaths.append(str(l1c_file_path))
         all_paths.append(str(l1c_file_path))
 
diff --git a/scripts/ultra/create_l2_cdf_from_instrument_team_data.py b/scripts/ultra/create_l2_cdf_from_instrument_team_data.py
index bac5cf44..46de899a 100644
--- a/scripts/ultra/create_l2_cdf_from_instrument_team_data.py
+++ b/scripts/ultra/create_l2_cdf_from_instrument_team_data.py
@@ -22,7 +22,7 @@
 
 parent = Path(args.map_folder)
 
-data = defaultdict(lambda: {})
+data = defaultdict(dict)
 for folder in parent.iterdir():
     for sub_folder in folder.iterdir():
         for file in sub_folder.iterdir():
@@ -50,9 +50,7 @@
     pixel_index_label = [f"Pixel index {x}" for x in pixel_index]
 
     obs_date = np.full(ena_intensity.shape, datetime.now())
-    obs_date_range = np.full(
-        ena_intensity.shape, ONE_SECOND_IN_NANOSECONDS * SECONDS_PER_DAY * 2
-    )
+    obs_date_range = np.full(ena_intensity.shape, ONE_SECOND_IN_NANOSECONDS * SECONDS_PER_DAY * 2)
 
     solid_angle = build_solid_angle_map(4)
 
@@ -65,9 +63,7 @@
         cdf.new("energy", energy, recVary=False, type=pycdf.const.CDF_FLOAT)
         cdf.new("latitude", lat, recVary=False, type=pycdf.const.CDF_FLOAT)
         cdf.new("longitude", lon, recVary=False, type=pycdf.const.CDF_FLOAT)
-        cdf.new(
-            "ena_intensity", ena_intensity, recVary=True, type=pycdf.const.CDF_FLOAT
-        )
+        cdf.new("ena_intensity", ena_intensity, recVary=True, type=pycdf.const.CDF_FLOAT)
         cdf.new(
             "ena_intensity_stat_uncert",
             ena_intensity_stat_uncert,
@@ -80,13 +76,9 @@
             recVary=True,
             type=pycdf.const.CDF_FLOAT,
         )
-        cdf.new(
-            "exposure_factor", exposure_factor, recVary=True, type=pycdf.const.CDF_FLOAT
-        )
+        cdf.new("exposure_factor", exposure_factor, recVary=True, type=pycdf.const.CDF_FLOAT)
         cdf.new("obs_date", obs_date, recVary=True, type=pycdf.const.CDF_TIME_TT2000)
-        cdf.new(
-            "obs_date_range", obs_date_range, recVary=True, type=pycdf.const.CDF_INT8
-        )
+        cdf.new("obs_date_range", obs_date_range, recVary=True, type=pycdf.const.CDF_INT8)
         cdf.new("solid_angle", solid_angle, recVary=True, type=pycdf.const.CDF_FLOAT)
         cdf.new("epoch_delta", epoch_delta, recVary=True, type=pycdf.const.CDF_INT8)
         cdf.new(
@@ -115,9 +107,7 @@
 
         for var in cdf:
             if cdf[var].type() == pycdf.const.CDF_TIME_TT2000.value:
-                cdf[var].attrs["FILLVAL"] = datetime.fromisoformat(
-                    "9999-12-31T23:59:59.999999999"
-                )
+                cdf[var].attrs["FILLVAL"] = datetime.fromisoformat("9999-12-31T23:59:59.999999999")
             elif cdf[var].type() == pycdf.const.CDF_INT8.value:
                 cdf[var].attrs["FILLVAL"] = -9223372036854775808
             elif cdf[var].type() == pycdf.const.CDF_FLOAT.value:
diff --git a/scripts/ultra/create_l2_dependency_files.py b/scripts/ultra/create_l2_dependency_files.py
index 413667ba..d428762a 100644
--- a/scripts/ultra/create_l2_dependency_files.py
+++ b/scripts/ultra/create_l2_dependency_files.py
@@ -73,7 +73,9 @@ def create_l2_dependency_files(sensor, reference_frame):
 
     inputs.add([generate_imap_input(f) for f in spice_files + pset_files])
 
-    dependency_file = f"imap_ultra_l2_{dependency_file_descriptor}_{START_DATE.strftime('%Y%m%d')}_v001.json"
+    dependency_file = (
+        f"imap_ultra_l2_{dependency_file_descriptor}_{START_DATE.strftime('%Y%m%d')}_v001.json"
+    )
     dependency_path = generate_imap_file_path(dependency_file).construct_path()
     dependency_path.parent.mkdir(parents=True, exist_ok=True)
     dependency_path.write_text(inputs.serialize())
diff --git a/scripts/ultra/create_l2_from_pointing_sets.py b/scripts/ultra/create_l2_from_pointing_sets.py
index 69ddb325..5e0ed32f 100644
--- a/scripts/ultra/create_l2_from_pointing_sets.py
+++ b/scripts/ultra/create_l2_from_pointing_sets.py
@@ -61,7 +61,7 @@ def generate_map(descriptor: str, start: datetime, end: datetime):
     command = f"imap_cli --instrument ultra --data-level l2 --descriptor {descriptor} --start-date {formatted_start_date} --version {version} --dependency {dependency_file}"
     print(command)
     if not generate_imap_file_path(output_filename).construct_path().exists():
-        subprocess.run(command.split(" "), env=env)
+        subprocess.run(command.split(" "), env=env, check=True)
     else:
         print(f"Skipping generation of {output_filename}, it already exists")
 
diff --git a/scripts/ultra/plot_l2_uncertainties.py b/scripts/ultra/plot_l2_uncertainties.py
index 2a863165..0e886a47 100644
--- a/scripts/ultra/plot_l2_uncertainties.py
+++ b/scripts/ultra/plot_l2_uncertainties.py
@@ -51,17 +51,15 @@
         "ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"
     ),
 )
-print(
-    ultra_nsp_combined_dep.u45_l2_map.intensity_map_data.ena_intensity_stat_uncert.shape
-)
+print(ultra_nsp_combined_dep.u45_l2_map.intensity_map_data.ena_intensity_stat_uncert.shape)
 
 hp32 = HEALPix(32)
 lon, lat = hp32.healpix_to_lonlat(np.arange(hp32.npix))
 plt.scatter(
     lon,
     lat,
-    c=ultra_nsp_combined_dep.u45_l2_map.intensity_map_data.ena_intensity_stat_uncert[
-        0
-    ].reshape(12, -1)[0],
+    c=ultra_nsp_combined_dep.u45_l2_map.intensity_map_data.ena_intensity_stat_uncert[0].reshape(
+        12, -1
+    )[0],
 )
 plt.show()
diff --git a/scripts/ultra/validation/create_L2_validation_maps.py b/scripts/ultra/validation/create_L2_validation_maps.py
index edea0e1a..9e10b953 100644
--- a/scripts/ultra/validation/create_L2_validation_maps.py
+++ b/scripts/ultra/validation/create_L2_validation_maps.py
@@ -26,7 +26,7 @@ def generate_l2_files():
     for descriptor in L2_DESCRIPTORS:
         groups[descriptor[:15]].append(descriptor)
     with ProcessPoolExecutor() as pool:
-        for group, descriptors in groups.items():
+        for descriptors in groups.values():
             pool.submit(make_maps, descriptors)
 
 
@@ -43,9 +43,7 @@ def make_maps(descriptors):
         start_date = "20251018"
         output_filename = f"imap_ultra_l2_{descriptor}_{start_date}_{version}.cdf"
         if not generate_imap_file_path(output_filename).construct_path().exists():
-            Ultra(
-                "l2", descriptor, dependency, start_date, None, "v000", False
-            ).process()
+            Ultra("l2", descriptor, dependency, start_date, None, "v000", False).process()
         else:
             print(f"Skipping generation of {output_filename}, it already exists")
 
diff --git a/scripts/ultra/validation/create_l3_validation_maps.py b/scripts/ultra/validation/create_l3_validation_maps.py
index c460dbb9..bd55e4bb 100644
--- a/scripts/ultra/validation/create_l3_validation_maps.py
+++ b/scripts/ultra/validation/create_l3_validation_maps.py
@@ -51,10 +51,8 @@ def run_all_maps(
     output_dir = Path(f"{datetime.now().strftime('%Y%m%d')}_ultra_validation_output")
     try:
         input_dir = Path(sys.argv[1])
-    except Exception:
+    except Exception:  # noqa: BLE001
         input_dir = Path(r"C:\Users\Harrison\AppData\Local\cava\cava\data")
-        print(
-            f"Could not open input file, using default input path of {input_dir} instead"
-        )
+        print(f"Could not open input file, using default input path of {input_dir} instead")
 
     run_all_maps(output_dir=output_dir, input_dir=input_dir)
diff --git a/scripts/ultra/validation/prepare_glows_for_ultra_validation.py b/scripts/ultra/validation/prepare_glows_for_ultra_validation.py
index b8d4e378..2d3f677a 100644
--- a/scripts/ultra/validation/prepare_glows_for_ultra_validation.py
+++ b/scripts/ultra/validation/prepare_glows_for_ultra_validation.py
@@ -6,9 +6,7 @@
 output_dir = Path(r"C:\Users\Harrison\Downloads\glows_l3e_for_ultra_validation")
 output_dir.mkdir(exist_ok=True)
 input_dir = Path(r"C:\Users\Harrison\Downloads\glows_l3e_from_validation\l3e")
-for i, file in enumerate(
-    input_dir.rglob("imap_glows_l3e_survival-probability-ul*.cdf")
-):
+for i, file in enumerate(input_dir.rglob("imap_glows_l3e_survival-probability-ul*.cdf")):
     if i > 184:
         break
     new_repoint = re.sub(r"repoint\d{5}", f"repoint{i:05}", file.name)
diff --git a/scripts/ultra/validation/prepare_ul_repoint_files_for_ultra_validation.py b/scripts/ultra/validation/prepare_ul_repoint_files_for_ultra_validation.py
index bc1cec2d..3180fc94 100644
--- a/scripts/ultra/validation/prepare_ul_repoint_files_for_ultra_validation.py
+++ b/scripts/ultra/validation/prepare_ul_repoint_files_for_ultra_validation.py
@@ -6,9 +6,7 @@
 output_dir = Path(r"C:\Users\Harrison\Downloads\glows_l3e_for_ultra_validation")
 output_dir.mkdir(exist_ok=True)
 input_dir = Path(r"C:\Users\Harrison\Downloads\\")
-for i, file in enumerate(
-    input_dir.rglob("imap_glows_l3e_survival-probability-ul*.cdf")
-):
+for i, file in enumerate(input_dir.rglob("imap_glows_l3e_survival-probability-ul*.cdf")):
     if i > 184:
         break
     new_repoint = re.sub(r"repoint\d{5}", f"repoint{i:05}", file.name)
diff --git a/scripts/ultra/validation/upload_files.py b/scripts/ultra/validation/upload_files.py
index 00b78e20..fe61cdec 100644
--- a/scripts/ultra/validation/upload_files.py
+++ b/scripts/ultra/validation/upload_files.py
@@ -13,9 +13,7 @@
 l1_45_folder = Path(
     r"C:\Users\Harrison\Downloads\ULTRA_45sensor_spacecraft-psets_20251113-20251125T164844Z-1-001\ULTRA_45sensor_spacecraft-psets_20251113"
 )
-l1_90_folder = Path(
-    r"C:\Users\Harrison\Downloads\ULTRA_90sensor_spacecraft-psets_20251113"
-)
+l1_90_folder = Path(r"C:\Users\Harrison\Downloads\ULTRA_90sensor_spacecraft-psets_20251113")
 glows_folder = Path(r"C:\Users\Harrison\Downloads\ultra_combined_hf_validation\glows")
 l2_45_folder = Path(r"C:\Users\Harrison\Downloads\u45_l2")
 l2_90_folder = Path(r"C:\Users\Harrison\Downloads\u90_l2")
@@ -33,7 +31,7 @@ def upload_file(f):
             uploaded.append(f.name)
             print("uploaded", f.name)
             return
-        except Exception:
+        except Exception:  # noqa: BLE001
             failures += 1
 
             print(f"failed to upload file: {f} after {failures} attempts, retrying...")
diff --git a/tests/cdf/test_cdf_utils.py b/tests/cdf/test_cdf_utils.py
index 01b64d52..7bbc5e84 100644
--- a/tests/cdf/test_cdf_utils.py
+++ b/tests/cdf/test_cdf_utils.py
@@ -7,9 +7,9 @@
 from spacepy import pycdf
 
 from imap_l3_processing.cdf.cdf_utils import (
-    write_cdf,
-    read_variable_and_mask_fill_values,
     read_numeric_variable,
+    read_variable_and_mask_fill_values,
+    write_cdf,
 )
 from imap_l3_processing.cdf.imap_attribute_manager import ImapAttributeManager
 from imap_l3_processing.models import (
@@ -94,46 +94,28 @@ def test_write_cdf(self):
             )
             self.assertTrue(actual_cdf[var_without_explicit_type.name].rv())
 
-            np.testing.assert_array_equal(
-                int_var.value, actual_cdf.raw_var(int_var.name)
-            )
-            self.assertEqual(
-                "var_val1", actual_cdf[int_var.name].attrs["variable_attr1"]
-            )
-            self.assertEqual(
-                -9223372036854775808, actual_cdf[int_var.name].attrs["FILLVAL"]
-            )
+            np.testing.assert_array_equal(int_var.value, actual_cdf.raw_var(int_var.name))
+            self.assertEqual("var_val1", actual_cdf[int_var.name].attrs["variable_attr1"])
+            self.assertEqual(-9223372036854775808, actual_cdf[int_var.name].attrs["FILLVAL"])
             self.assertEqual(
                 pycdf.const.CDF_INT8.value,
                 actual_cdf[int_var.name].attrs.type("FILLVAL"),
             )
-            self.assertEqual(
-                pycdf.const.CDF_INT8.value, actual_cdf[int_var.name].type()
-            )
+            self.assertEqual(pycdf.const.CDF_INT8.value, actual_cdf[int_var.name].type())
             self.assertTrue(actual_cdf[int_var.name].rv())
 
-            np.testing.assert_array_equal(
-                float_var.value, actual_cdf.raw_var(float_var.name)
-            )
-            self.assertEqual(
-                "var_val1", actual_cdf[float_var.name].attrs["variable_attr1"]
-            )
+            np.testing.assert_array_equal(float_var.value, actual_cdf.raw_var(float_var.name))
+            self.assertEqual("var_val1", actual_cdf[float_var.name].attrs["variable_attr1"])
             self.assertEqual(-1e31, actual_cdf[float_var.name].attrs["FILLVAL"])
             self.assertEqual(
                 pycdf.const.CDF_REAL4.value,
                 actual_cdf[float_var.name].attrs.type("FILLVAL"),
             )
-            self.assertEqual(
-                pycdf.const.CDF_REAL4.value, actual_cdf[float_var.name].type()
-            )
+            self.assertEqual(pycdf.const.CDF_REAL4.value, actual_cdf[float_var.name].type())
             self.assertTrue(actual_cdf[float_var.name].rv())
 
-            np.testing.assert_array_equal(
-                time_var.value, actual_cdf.raw_var(time_var.name)
-            )
-            self.assertEqual(
-                "var_val3", actual_cdf[time_var.name].attrs["variable_attr3"]
-            )
+            np.testing.assert_array_equal(time_var.value, actual_cdf.raw_var(time_var.name))
+            self.assertEqual("var_val3", actual_cdf[time_var.name].attrs["variable_attr3"])
             self.assertEqual(
                 datetime(9999, 12, 31, 23, 59, 59, 999999),
                 actual_cdf[time_var.name].attrs["FILLVAL"],
@@ -142,9 +124,7 @@ def test_write_cdf(self):
                 pycdf.const.CDF_TIME_TT2000.value,
                 actual_cdf[time_var.name].attrs.type("FILLVAL"),
             )
-            self.assertEqual(
-                pycdf.const.CDF_TIME_TT2000.value, actual_cdf[time_var.name].type()
-            )
+            self.assertEqual(pycdf.const.CDF_TIME_TT2000.value, actual_cdf[time_var.name].type())
             self.assertFalse(actual_cdf[time_var.name].rv())
 
             self.assertEqual(
@@ -153,9 +133,7 @@ def test_write_cdf(self):
             self.assertEqual(
                 "var_val6", actual_cdf[non_rec_varying_var.name].attrs["variable_attr6"]
             )
-            self.assertEqual(
-                non_rec_varying_var.value, actual_cdf[non_rec_varying_var.name][...]
-            )
+            self.assertEqual(non_rec_varying_var.value, actual_cdf[non_rec_varying_var.name][...])
             self.assertEqual(
                 pycdf.const.CDF_INT4.value, actual_cdf[non_rec_varying_var.name].type()
             )
@@ -294,9 +272,7 @@ def test_write_cdf_trims_numbers_in_logical_source_when_fetching_global_metadata
     def test_write_cdf_replaces_nan_inf_and_overflowing_floats_with_fill_value(self):
         epoch_fillval = datetime.fromisoformat("9999-12-31T23:59:59.999999")
 
-        epoch_data = np.ma.masked_array(
-            [datetime(2025, 3, 7, 17, 0), None], mask=[False, True]
-        )
+        epoch_data = np.ma.masked_array([datetime(2025, 3, 7, 17, 0), None], mask=[False, True])
         expected_cdf_epoch_data = np.array([datetime(2025, 3, 7, 17, 0), epoch_fillval])
 
         float_var_input = np.array(
@@ -314,12 +290,8 @@ def __init__(self):
 
             def to_data_product_variables(self) -> list[DataProductVariable]:
                 return [
-                    DataProductVariable(
-                        "epoch", epoch_data, pycdf.const.CDF_TIME_TT2000
-                    ),
-                    DataProductVariable(
-                        "float_var", float_var_input, pycdf.const.CDF_REAL4
-                    ),
+                    DataProductVariable("epoch", epoch_data, pycdf.const.CDF_TIME_TT2000),
+                    DataProductVariable("float_var", float_var_input, pycdf.const.CDF_REAL4),
                 ]
 
         path = str(self.temp_directory / "write_cdf.cdf")
@@ -346,9 +318,7 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             actual_float_var = actual_cdf["float_var"][...]
             self.assertFalse(np.any(np.isnan(actual_float_var)))
             self.assertFalse(np.any(np.isinf(actual_float_var)))
-            np.testing.assert_array_equal(
-                expected_float_var, actual_float_var, strict=True
-            )
+            np.testing.assert_array_equal(expected_float_var, actual_float_var, strict=True)
             np.testing.assert_array_equal(
                 actual_cdf["epoch"][...], expected_cdf_epoch_data, strict=True
             )
@@ -363,9 +333,7 @@ def __init__(self):
 
             def to_data_product_variables(self) -> list[DataProductVariable]:
                 return [
-                    DataProductVariable(
-                        "epoch", epoch_data, pycdf.const.CDF_TIME_TT2000
-                    ),
+                    DataProductVariable("epoch", epoch_data, pycdf.const.CDF_TIME_TT2000),
                 ]
 
         path = str(self.temp_directory / "write_cdf.cdf")
@@ -411,9 +379,7 @@ def test_can_write_empty_variables_of_various_shapes(self):
             (np.zeros((0), dtype=float), "CDF_REAL8", "RV", -1e31),
         ]
         for input_data, data_type, record_varying, fill_val in cases:
-            with self.subTest(
-                input_data=input_data, data_type=data_type, rv=record_varying
-            ):
+            with self.subTest(input_data=input_data, data_type=data_type, rv=record_varying):
 
                 class DataProductWithEmptyEpoch(DataProduct):
                     def __init__(self):
@@ -422,7 +388,9 @@ def __init__(self):
                     def to_data_product_variables(self) -> list[DataProductVariable]:
                         return [
                             DataProductVariable(
-                                "var", input_data, pycdf.const.CDF_REAL8
+                                "var",
+                                input_data,  # noqa: B023
+                                pycdf.const.CDF_REAL8,
                             ),
                         ]
 
@@ -441,18 +409,14 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
 
                 write_cdf(str(path), data, attribute_manager)
                 with pycdf.CDF(str(path)) as actual_cdf:
-                    np.testing.assert_array_equal(
-                        actual_cdf["var"][...], input_data, strict=True
-                    )
+                    np.testing.assert_array_equal(actual_cdf["var"][...], input_data, strict=True)
 
                 path.unlink()
 
     def test_does_not_write_variable_attribute_if_value_is_empty_string(self):
         path = str(self.temp_directory / "write_cdf.cdf")
         data = TestDataProduct()
-        _, _, regular_var, time_var, non_rec_varying_var = (
-            data.to_data_product_variables()
-        )
+        _, _, regular_var, time_var, non_rec_varying_var = data.to_data_product_variables()
         attribute_manager = Mock(spec=ImapAttributeManager)
         attribute_manager.get_global_attributes.return_value = {
             "global1": "global_val1",
@@ -469,9 +433,7 @@ def test_does_not_write_variable_attribute_if_value_is_empty_string(self):
         write_cdf(path, data, attribute_manager)
 
         with pycdf.CDF(path) as actual_cdf:
-            np.testing.assert_array_equal(
-                regular_var.value, actual_cdf[regular_var.name][...]
-            )
+            np.testing.assert_array_equal(regular_var.value, actual_cdf[regular_var.name][...])
             self.assertEqual("epoch", actual_cdf[regular_var.name].attrs["DEPEND_0"])
             self.assertFalse("CATDESC" in actual_cdf[time_var.name].attrs)
             self.assertFalse("DEPEND_0" in actual_cdf[non_rec_varying_var.name].attrs)
@@ -484,13 +446,11 @@ def test_read_variable_and_mask_fill_values(self):
             actual_cdf["date_var"].attrs["FILLVAL"] = datetime_fill
 
             int_fillval = -9223372036854775808
-            actual_cdf["int_var"] = np.array(
-                [-1, 2, int_fillval, int_fillval + 1], dtype=np.int64
-            )
+            actual_cdf["int_var"] = np.array([-1, 2, int_fillval, int_fillval + 1], dtype=np.int64)
             actual_cdf["int_var"].attrs["FILLVAL"] = int_fillval
 
-            masked_datetime_data: np.ma.masked_array = (
-                read_variable_and_mask_fill_values(actual_cdf["date_var"])
+            masked_datetime_data: np.ma.masked_array = read_variable_and_mask_fill_values(
+                actual_cdf["date_var"]
             )
             masked_int_data: np.ma.masked_array = read_variable_and_mask_fill_values(
                 actual_cdf["int_var"]
@@ -504,9 +464,7 @@ def test_read_variable_and_mask_fill_values(self):
             masked_int_data.data,
             np.array([-1, 2, int_fillval, int_fillval + 1], dtype=np.int64),
         )
-        np.testing.assert_equal(
-            masked_int_data.mask, np.array([False, False, True, False])
-        )
+        np.testing.assert_equal(masked_int_data.mask, np.array([False, False, True, False]))
 
     def test_read_variable_replaces_fill_values_with_nan(self):
         path = str(self.temp_directory / "cdf.cdf")
@@ -555,15 +513,11 @@ def to_data_product_variables(self) -> list[DataProductVariable]:
             "FILLVAL": -1e31,
             "RECORD_VARYING": "rV",
         }
-        attribute_manager.get_variable_attributes.side_effect = lambda _: (
-            variable_metadata.copy()
-        )
+        attribute_manager.get_variable_attributes.side_effect = lambda _: variable_metadata.copy()
 
         write_cdf(path, data, attribute_manager)
 
-        expected_data_product_logical_source = (
-            "imap_hi_l3_h45-ena-h-sf-sp-ram-hae-6deg-6mo"
-        )
+        expected_data_product_logical_source = "imap_hi_l3_h45-ena-h-sf-sp-ram-hae-6deg-6mo"
         attribute_manager.get_global_attributes.assert_called_once_with(
             expected_data_product_logical_source
         )
diff --git a/tests/cdf/test_imap_attribute_manager.py b/tests/cdf/test_imap_attribute_manager.py
index 9f0dc62d..d64827b4 100644
--- a/tests/cdf/test_imap_attribute_manager.py
+++ b/tests/cdf/test_imap_attribute_manager.py
@@ -9,9 +9,7 @@
 
 class TestImapCdfManager(TestCase):
     def setUp(self):
-        self.config_folder_path = (
-            Path(imap_l3_processing.__file__).parent.resolve() / "cdf/config"
-        )
+        self.config_folder_path = Path(imap_l3_processing.__file__).parent.resolve() / "cdf/config"
         self.base_manager = CdfAttributeManager(
             variable_schema_layers=[
                 self.config_folder_path / "imap_l3_variable_cdf_attrs_schema.yaml",
@@ -48,9 +46,7 @@ def test_load_instrument_and_variable_attributes_with_level(self):
         self.base_manager.load_variable_attributes(
             self.config_folder_path / "imap_swapi_l3a_variable_attrs.yaml"
         )
-        self.base_manager.add_global_attribute(
-            "ground_software_version", "test version"
-        )
+        self.base_manager.add_global_attribute("ground_software_version", "test version")
 
         self.assertEqual(
             self.base_manager.get_global_attributes(), manager.get_global_attributes()
@@ -121,15 +117,11 @@ def test_l3b_metadata_configuration(self):
             manager.get_variable_attributes("combined_energy"),
         )
         self.assertEqual(
-            self.base_manager.get_variable_attributes(
-                "combined_energy_stat_uncert_minus"
-            ),
+            self.base_manager.get_variable_attributes("combined_energy_stat_uncert_minus"),
             manager.get_variable_attributes("combined_energy_stat_uncert_minus"),
         )
         self.assertEqual(
-            self.base_manager.get_variable_attributes(
-                "combined_energy_stat_uncert_plus"
-            ),
+            self.base_manager.get_variable_attributes("combined_energy_stat_uncert_plus"),
             manager.get_variable_attributes("combined_energy_stat_uncert_plus"),
         )
 
@@ -138,9 +130,7 @@ def test_l3b_metadata_configuration(self):
             manager.get_variable_attributes("combined_differential_flux"),
         )
         self.assertEqual(
-            self.base_manager.get_variable_attributes(
-                "combined_differential_flux_stat_uncert"
-            ),
+            self.base_manager.get_variable_attributes("combined_differential_flux_stat_uncert"),
             manager.get_variable_attributes("combined_differential_flux_stat_uncert"),
         )
 
@@ -170,9 +160,7 @@ def test_gets_global_attrs_from_global_file_when_descriptor_specific_variable_fi
         self,
     ):
         manager = ImapAttributeManager()
-        manager.add_instrument_attrs(
-            "hi", "l3", "45sensor-spacecraft-survival-full-4deg-map"
-        )
+        manager.add_instrument_attrs("hi", "l3", "45sensor-spacecraft-survival-full-4deg-map")
 
         self.base_manager.load_global_attributes(
             self.config_folder_path / "imap_hi_l3_global_cdf_attrs.yaml"
diff --git a/tests/cdf/test_yaml_var_metadata.py b/tests/cdf/test_yaml_var_metadata.py
index 3ab501f7..458194ea 100644
--- a/tests/cdf/test_yaml_var_metadata.py
+++ b/tests/cdf/test_yaml_var_metadata.py
@@ -46,12 +46,10 @@ def test_epoch(self):
         for filename, yaml_data in self.test_cases_file:
             with self.subTest(filename):
                 self.assertIn("epoch", yaml_data.keys(), "no entry in file for 'epoch'")
-                self.assertEqual(
-                    "epoch", yaml_data["epoch"]["NAME"], "epoch must be lowercase"
-                )
+                self.assertEqual("epoch", yaml_data["epoch"]["NAME"], "epoch must be lowercase")
 
                 self._epoch_meets_schema(yaml_data)
-                if "epoch_delta" in yaml_data.keys():
+                if "epoch_delta" in yaml_data:
                     self._epoch_delta_meets_schema(yaml_data)
 
     def test_type_of_min_max_attributes(self):
@@ -83,8 +81,8 @@ def test_lablaxis_is_defined_for_required_types(self):
             with self.subTest(f"{filename}:{variable_key}"):
                 if (
                     "NAME" in variable
-                    and not variable["VAR_TYPE"] == "metadata"
-                    and not variable.get("DISPLAY_TYPE") == "no_plot"
+                    and variable["VAR_TYPE"] != "metadata"
+                    and variable.get("DISPLAY_TYPE") != "no_plot"
                 ):
                     self.assertIn(
                         "LABLAXIS",
@@ -128,9 +126,7 @@ def test_swe_l3_integrated_temperatures_have_kelvin_units(self):
             if "swe_l3" in filename and variable_key in temperature_vars:
                 found.add(variable_key)
                 with self.subTest(f"{filename}:{variable_key}"):
-                    self.assertEqual(
-                        "K", variable["UNITS"], f"{variable_key} UNITS should be 'K'"
-                    )
+                    self.assertEqual("K", variable["UNITS"], f"{variable_key} UNITS should be 'K'")
         self.assertEqual(
             temperature_vars,
             found,
@@ -165,12 +161,8 @@ def test_metadata_never_has_empty_string_as_value(self):
     def test_each_variable_has_data_type_and_fill_value(self):
         for filename, yaml_data, variable_key, variable in self.test_cases_variable:
             with self.subTest(f"{filename}:{variable_key}"):
-                self.assertIn(
-                    "DATA_TYPE", variable.keys(), f'{variable_key} requires "DATA_TYPE"'
-                )
-                self.assertIn(
-                    "FILLVAL", variable.keys(), f'{variable_key} requires "FILLVAL"'
-                )
+                self.assertIn("DATA_TYPE", variable.keys(), f'{variable_key} requires "DATA_TYPE"')
+                self.assertIn("FILLVAL", variable.keys(), f'{variable_key} requires "FILLVAL"')
 
     def test_all_angle_variables_in_degrees(self):
         for filename, yaml_data, variable_key, variable in self.test_cases_variable:
@@ -196,18 +188,15 @@ def test_variables_that_depend_on_epoch_are_record_varying(self):
 
     def test_attrs_that_point_to_another_var_actually_point_to_something(self):
         def _is_pointer_attr(attr: str) -> bool:
-            return (
-                attr.startswith("DEPEND_")
-                or attr.startswith("LABL_PTR_")
-                or attr in ["DELTA_PLUS_VAR", "DELTA_MINUS_VAR"]
-            )
+            return attr.startswith(("DEPEND_", "LABL_PTR_")) or attr in [
+                "DELTA_PLUS_VAR",
+                "DELTA_MINUS_VAR",
+            ]
 
         for filename, yaml_data, variable_key, variable in self.test_cases_variable:
             with self.subTest(f"{filename}:{variable_key}"):
                 pointed_to_vars = [
-                    (attr, variable[attr])
-                    for attr in variable
-                    if _is_pointer_attr(attr)
+                    (attr, variable[attr]) for attr in variable if _is_pointer_attr(attr)
                 ]
                 for attr, pointed_to_var in pointed_to_vars:
                     self.assertIn(
@@ -249,9 +238,7 @@ def test_variable_fill_value_matches_data_type(self):
                             datetime.fromisoformat("9999-12-31T23:59:59.999999"),
                         )
                     case _:
-                        self.assertFalse(
-                            True, f"Found unknown DATA_TYPE: {variable['DATA_TYPE']}"
-                        )
+                        self.assertFalse(True, f"Found unknown DATA_TYPE: {variable['DATA_TYPE']}")
 
     def test_all_record_varying_data_depends_on_epoch(self):
         for filename, yaml_data, variable_key, variable in self.test_cases_variable:
@@ -265,12 +252,7 @@ def test_all_record_varying_data_depends_on_epoch(self):
 
     def _epoch_meets_schema(self, yaml_data: dict):
         epoch_delta_types = ["epoch_delta", "epoch_delta_plus", "epoch_delta_minus"]
-        if any(
-            [
-                epoch_delta_type in yaml_data.keys()
-                for epoch_delta_type in epoch_delta_types
-            ]
-        ):
+        if any(epoch_delta_type in yaml_data for epoch_delta_type in epoch_delta_types):
             self.assertEqual(20, len(yaml_data["epoch"].keys()))
         else:
             self.assertEqual(18, len(yaml_data["epoch"].keys()))
@@ -294,12 +276,8 @@ def _epoch_meets_schema(self, yaml_data: dict):
             ["Epoch", "J2000 Nanoseconds"],
             "epoch FIELDNAM should be Epoch",
         )
-        self.assertEqual(
-            " ", yaml_data["epoch"]["FORMAT"], "epoch FORMAT should be ' '"
-        )
-        self.assertEqual(
-            "Epoch", yaml_data["epoch"]["LABLAXIS"], "epoch LABLAXIS should be Epoch"
-        )
+        self.assertEqual(" ", yaml_data["epoch"]["FORMAT"], "epoch FORMAT should be ' '")
+        self.assertEqual("Epoch", yaml_data["epoch"]["LABLAXIS"], "epoch LABLAXIS should be Epoch")
         self.assertEqual("ns", yaml_data["epoch"]["UNITS"], "epoch UNITS should be ns")
         self.assertEqual(
             datetime.fromisoformat("2099-12-31T00:00:00.000000"),
@@ -317,9 +295,7 @@ def _epoch_meets_schema(self, yaml_data: dict):
         self.assertEqual(
             "J2000", yaml_data["epoch"]["TIME_BASE"], "epoch TIME_BASE should be J2000"
         )
-        self.assertEqual(
-            "TT", yaml_data["epoch"]["TIME_SCALE"], "epoch TIME_SCALE should be TT"
-        )
+        self.assertEqual("TT", yaml_data["epoch"]["TIME_SCALE"], "epoch TIME_SCALE should be TT")
         self.assertEqual(
             "INCREASE",
             yaml_data["epoch"]["MONOTON"],
@@ -370,9 +346,7 @@ def _epoch_delta_meets_schema(self, yaml_data: dict):
             yaml_data["epoch_delta"]["LABLAXIS"],
             "epoch_delta LABLAXIS should be 'Epoch delta'",
         )
-        self.assertEqual(
-            "ns", yaml_data["epoch_delta"]["UNITS"], "epoch_delta UNITS should be ns"
-        )
+        self.assertEqual("ns", yaml_data["epoch_delta"]["UNITS"], "epoch_delta UNITS should be ns")
         self.assertEqual(
             0,
             yaml_data["epoch_delta"]["VALIDMIN"],
diff --git a/tests/codice/l3/hi/direct_event/test_codice_hi_mass_correction_lookup_table.py b/tests/codice/l3/hi/direct_event/test_codice_hi_mass_correction_lookup_table.py
index cda7f56e..4bf0087b 100644
--- a/tests/codice/l3/hi/direct_event/test_codice_hi_mass_correction_lookup_table.py
+++ b/tests/codice/l3/hi/direct_event/test_codice_hi_mass_correction_lookup_table.py
@@ -1,6 +1,5 @@
 import unittest
 
-
 from imap_l3_processing.codice.l3.hi.direct_event.codice_hi_mass_correction_lookup_table import (
     CodiceHiMassCorrectionLookupTable,
 )
@@ -24,35 +23,25 @@ def test_lookup_correction_factor(self):
 
         self.assertEqual(
             0.753777,
-            mass_correction_lookup.lookup_correction_factor(
-                ssd_id=7, energy_channel=40, tof=6
-            ),
+            mass_correction_lookup.lookup_correction_factor(ssd_id=7, energy_channel=40, tof=6),
         )
 
         self.assertEqual(
             7.47142,
-            mass_correction_lookup.lookup_correction_factor(
-                ssd_id=3, energy_channel=24, tof=0
-            ),
+            mass_correction_lookup.lookup_correction_factor(ssd_id=3, energy_channel=24, tof=0),
         )
         self.assertEqual(
             1,
-            mass_correction_lookup.lookup_correction_factor(
-                ssd_id=3, energy_channel=24, tof=1
-            ),
+            mass_correction_lookup.lookup_correction_factor(ssd_id=3, energy_channel=24, tof=1),
         )
         self.assertEqual(
             12.8534,
-            mass_correction_lookup.lookup_correction_factor(
-                ssd_id=3, energy_channel=24, tof=6
-            ),
+            mass_correction_lookup.lookup_correction_factor(ssd_id=3, energy_channel=24, tof=6),
         )
 
         missing_ssds = [2, 6, 8, 9, 10, 12, 13, 14, 15]
         for ssd_id in missing_ssds:
             self.assertEqual(
                 1.0,
-                mass_correction_lookup.lookup_correction_factor(
-                    ssd_id, energy_channel=24, tof=0
-                ),
+                mass_correction_lookup.lookup_correction_factor(ssd_id, energy_channel=24, tof=0),
             )
diff --git a/tests/codice/l3/hi/direct_event/test_codice_l3a_direct_events_dependencies.py b/tests/codice/l3/hi/direct_event/test_codice_l3a_direct_events_dependencies.py
index 5afa8df1..cc1015d1 100644
--- a/tests/codice/l3/hi/direct_event/test_codice_l3a_direct_events_dependencies.py
+++ b/tests/codice/l3/hi/direct_event/test_codice_l3a_direct_events_dependencies.py
@@ -4,9 +4,9 @@
 
 import imap_data_access
 from imap_data_access.processing_input import (
+    AncillaryInput,
     ProcessingInputCollection,
     ScienceInput,
-    AncillaryInput,
 )
 
 from imap_l3_processing.codice.l3.hi.direct_event.codice_hi_l3a_direct_events_dependencies import (
@@ -45,9 +45,7 @@ def test_fetch_dependencies(self, mock_from_file_paths, mock_download):
             "imap_codice_l3-hi-mass-correction-lut_20100105_v010.xlsx"
         )
 
-        codice_l2_direct_event_science_input = ScienceInput(
-            codice_l2_direct_event_input_file_name
-        )
+        codice_l2_direct_event_science_input = ScienceInput(codice_l2_direct_event_input_file_name)
         codice_l1a_direct_event_science_input = ScienceInput(
             codice_l1a_direct_event_input_file_name
         )
@@ -109,12 +107,8 @@ def test_fetch_dependencies(self, mock_from_file_paths, mock_download):
 
         self.assertEqual(mock_from_file_paths.return_value, codice_l3_dependencies)
 
-    @patch(
-        "imap_l3_processing.codice.l3.hi.models.CodiceL2HiDirectEventData.read_from_cdf"
-    )
-    @patch(
-        "imap_l3_processing.codice.l3.hi.models.CodiceL1aHiDirectEvents.read_from_cdf"
-    )
+    @patch("imap_l3_processing.codice.l3.hi.models.CodiceL2HiDirectEventData.read_from_cdf")
+    @patch("imap_l3_processing.codice.l3.hi.models.CodiceL1aHiDirectEvents.read_from_cdf")
     @patch(
         "imap_l3_processing.codice.l3.hi.direct_event.codice_hi_mass_correction_lookup_table.CodiceHiMassCorrectionLookupTable.from_file"
     )
@@ -126,9 +120,7 @@ def test_can_load_from_files(
     ):
         codice_l2_cdf_file = Path("CodiceL2CDF")
         codice_l1a_cdf_file = Path("CodiceL1aCDF")
-        codice_mass_correction_lut_ancillary_file = Path(
-            "CodiceMassCorrectionLutAncillary"
-        )
+        codice_mass_correction_lut_ancillary_file = Path("CodiceMassCorrectionLutAncillary")
 
         codice_l3_dependencies = CodiceHiL3aDirectEventsDependencies.from_file_paths(
             codice_l2_cdf_file,
diff --git a/tests/codice/l3/hi/pitch_angle/test_codice_pitch_angle_dependencies.py b/tests/codice/l3/hi/pitch_angle/test_codice_pitch_angle_dependencies.py
index bfebcf22..9a713685 100644
--- a/tests/codice/l3/hi/pitch_angle/test_codice_pitch_angle_dependencies.py
+++ b/tests/codice/l3/hi/pitch_angle/test_codice_pitch_angle_dependencies.py
@@ -1,5 +1,5 @@
 import unittest
-from unittest.mock import patch, call, sentinel
+from unittest.mock import call, patch, sentinel
 
 import imap_data_access
 from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
@@ -24,24 +24,18 @@ def test_fetch_dependencies(self, mock_download, mock_from_files):
             "imap/mag/l1d/2010/01/imap_mag_l1d_norm-dsrf_20100105_v010.cdf"
         )
 
-        science_input_codice_l2 = ScienceInput(
-            "imap_codice_l2_hi-sectored_20100105_v010.cdf"
-        )
+        science_input_codice_l2 = ScienceInput("imap_codice_l2_hi-sectored_20100105_v010.cdf")
         science_input_mag_l1d = ScienceInput("imap_mag_l1d_norm-dsrf_20100105_v010.cdf")
 
         process_input_collection = ProcessingInputCollection()
         process_input_collection.add(science_input_codice_l2)
         process_input_collection.add(science_input_mag_l1d)
 
-        dependencies = CodicePitchAngleDependencies.fetch_dependencies(
-            process_input_collection
-        )
+        dependencies = CodicePitchAngleDependencies.fetch_dependencies(process_input_collection)
 
         data_dir = imap_data_access.config["DATA_DIR"]
 
-        expected_codice_science_file_path = (
-            data_dir / expected_codice_science_file_download_path
-        )
+        expected_codice_science_file_path = data_dir / expected_codice_science_file_download_path
         expected_mag_science_file_path = data_dir / expected_mag_download_path
 
         mock_download.assert_has_calls(
@@ -64,19 +58,13 @@ def test_fetch_dependencies(self, mock_download, mock_from_files):
     @patch(
         "imap_l3_processing.codice.l3.hi.pitch_angle.codice_pitch_angle_dependencies.imap_data_access.download"
     )
-    def test_fetch_dependencies_uses_mag_l2_if_available(
-        self, mock_download, mock_from_files
-    ):
+    def test_fetch_dependencies_uses_mag_l2_if_available(self, mock_download, mock_from_files):
         expected_codice_science_file_download_path = (
             "imap/codice/l2/2010/01/imap_codice_l2_hi-sectored_20100105_v010.cdf"
         )
-        expected_mag_download_path = (
-            "imap/mag/l2/2010/01/imap_mag_l2_norm-dsrf_20100105_v010.cdf"
-        )
+        expected_mag_download_path = "imap/mag/l2/2010/01/imap_mag_l2_norm-dsrf_20100105_v010.cdf"
 
-        science_input_codice_l2 = ScienceInput(
-            "imap_codice_l2_hi-sectored_20100105_v010.cdf"
-        )
+        science_input_codice_l2 = ScienceInput("imap_codice_l2_hi-sectored_20100105_v010.cdf")
         science_input_mag_l2 = ScienceInput("imap_mag_l2_norm-dsrf_20100105_v010.cdf")
         science_input_mag_l1d = ScienceInput("imap_mag_l1d_norm-dsrf_20100105_v010.cdf")
 
@@ -86,15 +74,11 @@ def test_fetch_dependencies_uses_mag_l2_if_available(
             science_input_mag_l2,
         )
 
-        dependencies = CodicePitchAngleDependencies.fetch_dependencies(
-            process_input_collection
-        )
+        dependencies = CodicePitchAngleDependencies.fetch_dependencies(process_input_collection)
 
         data_dir = imap_data_access.config["DATA_DIR"]
 
-        expected_codice_science_file_path = (
-            data_dir / expected_codice_science_file_download_path
-        )
+        expected_codice_science_file_path = data_dir / expected_codice_science_file_download_path
         expected_mag_science_file_path = data_dir / expected_mag_download_path
 
         mock_download.assert_has_calls(
diff --git a/tests/codice/l3/hi/test_codice_hi_processor.py b/tests/codice/l3/hi/test_codice_hi_processor.py
index 4fa7e523..f69f7775 100644
--- a/tests/codice/l3/hi/test_codice_hi_processor.py
+++ b/tests/codice/l3/hi/test_codice_hi_processor.py
@@ -2,7 +2,7 @@
 import unittest
 from datetime import datetime, timedelta
 from pathlib import Path
-from unittest.mock import patch, sentinel, Mock, call, MagicMock
+from unittest.mock import MagicMock, Mock, call, patch, sentinel
 
 import numpy as np
 
@@ -11,9 +11,9 @@
     CodiceHiL3aDirectEventsDependencies,
 )
 from imap_l3_processing.codice.l3.hi.models import (
+    CodiceHiL2SectoredIntensitiesData,
     CodiceL1aHiDirectEvents,
     CodiceL2HiDirectEventData,
-    CodiceHiL2SectoredIntensitiesData,
     CodiceL3HiDirectEvents,
 )
 from imap_l3_processing.codice.l3.hi.pitch_angle.codice_pitch_angle_dependencies import (
@@ -35,9 +35,7 @@ class TestCodiceHiProcessor(unittest.TestCase):
         "imap_l3_processing.codice.l3.hi.codice_hi_processor.CodiceHiProcessor.process_l3a_direct_event"
     )
     @patch("imap_l3_processing.codice.l3.hi.codice_hi_processor.save_data")
-    def test_process_l3a(
-        self, mock_save_data, mock_process_l3a, mock_fetch_dependencies
-    ):
+    def test_process_l3a(self, mock_save_data, mock_process_l3a, mock_fetch_dependencies):
         start_date = datetime(2024, 10, 7, 10, 00, 00)
         end_date = datetime(2024, 10, 8, 10, 00, 00)
         input_metadata = InputMetadata("codice", "l3a", start_date, end_date, "v02")
@@ -54,9 +52,7 @@ def test_process_l3a(
         mock_process_l3a.assert_called_with(mock_fetch_dependencies.return_value)
         mock_save_data.assert_called_with(mock_processed_direct_events)
         self.assertEqual([mock_save_data.return_value], product)
-        self.assertEqual(
-            ["parent_file_1"], mock_processed_direct_events.parent_file_names
-        )
+        self.assertEqual(["parent_file_1"], mock_processed_direct_events.parent_file_names)
 
     def test_process_l3a_with_small_dataset(self):
         high_gain_events = {
@@ -94,7 +90,9 @@ def lookup_factor(ssd_id, energy_channel, tof):
             return expected_factors.pop(key)
 
         mock_codice_hi_mass_correction_lut_ancillary = Mock()
-        mock_codice_hi_mass_correction_lut_ancillary.lookup_correction_factor.side_effect = lookup_factor
+        mock_codice_hi_mass_correction_lut_ancillary.lookup_correction_factor.side_effect = (
+            lookup_factor
+        )
 
         codice_hi_processor = CodiceHiProcessor(
             sentinel.processing_input_collection, input_metadata=sentinel.input_metadata
@@ -186,9 +184,7 @@ def lookup_factor(ssd_id, energy_channel, tof):
             spin_sector=sentinel.l2_spin_sector,
         )
 
-        actual_output = codice_hi_processor.process_l3a_direct_event(
-            dependencies=dependencies
-        )
+        actual_output = codice_hi_processor.process_l3a_direct_event(dependencies=dependencies)
         for field in dataclasses.fields(CodiceL3HiDirectEvents):
             np.testing.assert_equal(
                 getattr(actual_output, field.name), getattr(expected_output, field.name)
@@ -284,9 +280,7 @@ def test_process_l3a_only_calculates_events_within_num_events(self):
             spin_sector=sentinel.l2_spin_sector,
         )
 
-        actual_output = codice_hi_processor.process_l3a_direct_event(
-            dependencies=dependencies
-        )
+        actual_output = codice_hi_processor.process_l3a_direct_event(dependencies=dependencies)
         mock_lut.lookup_correction_factor.assert_not_called()
         for field in dataclasses.fields(CodiceL3HiDirectEvents):
             np.testing.assert_equal(
@@ -296,13 +290,9 @@ def test_process_l3a_only_calculates_events_within_num_events(self):
     @patch(
         "imap_l3_processing.codice.l3.hi.codice_hi_processor.CodicePitchAngleDependencies.fetch_dependencies"
     )
-    @patch(
-        "imap_l3_processing.codice.l3.hi.codice_hi_processor.CodiceHiProcessor.process_l3b"
-    )
+    @patch("imap_l3_processing.codice.l3.hi.codice_hi_processor.CodiceHiProcessor.process_l3b")
     @patch("imap_l3_processing.codice.l3.hi.codice_hi_processor.save_data")
-    def test_process_l3b_saves(
-        self, mock_save_data, mock_process_l3b, mock_fetch_dependencies
-    ):
+    def test_process_l3b_saves(self, mock_save_data, mock_process_l3b, mock_fetch_dependencies):
         start_date = datetime(2024, 10, 7, 10, 00, 00)
         end_date = datetime(2024, 10, 8, 10, 00, 00)
         input_metadata = InputMetadata("codice", "l3b", start_date, end_date, "v02")
@@ -320,9 +310,7 @@ def test_process_l3b_saves(
         mock_process_l3b.assert_called_with(mock_fetch_dependencies.return_value)
         mock_save_data.assert_called_with(mock_processed_pitch_angles)
         self.assertEqual([mock_save_data.return_value], product)
-        self.assertEqual(
-            ["parent_file_2"], mock_processed_pitch_angles.parent_file_names
-        )
+        self.assertEqual(["parent_file_2"], mock_processed_pitch_angles.parent_file_names)
 
     def test_raises_exception_on_non_l3_input_metadata(self):
         input_metadata = InputMetadata("codice", "L2a", Mock(), Mock(), "v02")
@@ -333,9 +321,7 @@ def test_raises_exception_on_non_l3_input_metadata(self):
         self.assertEqual("Unknown data level for CoDICE: L2a", str(context.exception))
 
     @patch("imap_l3_processing.codice.l3.hi.codice_hi_processor.calculate_unit_vector")
-    @patch(
-        "imap_l3_processing.codice.l3.hi.codice_hi_processor.get_sector_unit_vectors"
-    )
+    @patch("imap_l3_processing.codice.l3.hi.codice_hi_processor.get_sector_unit_vectors")
     @patch("imap_l3_processing.codice.l3.hi.codice_hi_processor.calculate_pitch_angle")
     @patch("imap_l3_processing.codice.l3.hi.codice_hi_processor.calculate_gyrophase")
     @patch(
@@ -530,10 +516,7 @@ def test_process_l3b_with_mocks(
         mock_get_sector_unit_vectors.assert_called_once_with(
             codice_l2_data.elevation_angle,
             NumpyArrayMatcher(
-                (
-                    codice_l2_data.spin_angles.T
-                    + CODICE_INSTRUMENT_TO_SC_FRAME_SPIN_ANGLE_OFFSET
-                )
+                (codice_l2_data.spin_angles.T + CODICE_INSTRUMENT_TO_SC_FRAME_SPIN_ANGLE_OFFSET)
                 % 360
             ),
         )
@@ -621,27 +604,21 @@ def test_process_l3b_with_mocks(
         np.testing.assert_array_equal(epoch, codice_hi_data_product.epoch)
         np.testing.assert_array_equal(epoch_delta, codice_hi_data_product.epoch_delta)
 
-        np.testing.assert_array_equal(
-            codice_hi_data_product.energy_h, codice_l2_data.energy_h
-        )
+        np.testing.assert_array_equal(codice_hi_data_product.energy_h, codice_l2_data.energy_h)
         np.testing.assert_array_equal(
             codice_hi_data_product.energy_h_plus, codice_l2_data.energy_h_plus
         )
         np.testing.assert_array_equal(
             codice_hi_data_product.energy_h_minus, codice_l2_data.energy_h_minus
         )
-        np.testing.assert_array_equal(
-            codice_hi_data_product.energy_cno, codice_l2_data.energy_cno
-        )
+        np.testing.assert_array_equal(codice_hi_data_product.energy_cno, codice_l2_data.energy_cno)
         np.testing.assert_array_equal(
             codice_hi_data_product.energy_cno_plus, codice_l2_data.energy_cno_plus
         )
         np.testing.assert_array_equal(
             codice_hi_data_product.energy_cno_minus, codice_l2_data.energy_cno_minus
         )
-        np.testing.assert_array_equal(
-            codice_hi_data_product.energy_fe, codice_l2_data.energy_fe
-        )
+        np.testing.assert_array_equal(codice_hi_data_product.energy_fe, codice_l2_data.energy_fe)
         np.testing.assert_array_equal(
             codice_hi_data_product.energy_fe_plus, codice_l2_data.energy_fe_plus
         )
@@ -665,9 +642,7 @@ def test_process_l3b_with_mocks(
         np.testing.assert_array_equal(
             expected_pitch_angle_delta, codice_hi_data_product.pitch_angle_delta
         )
-        np.testing.assert_array_almost_equal(
-            expected_gyrophase, codice_hi_data_product.gyrophase
-        )
+        np.testing.assert_array_almost_equal(expected_gyrophase, codice_hi_data_product.gyrophase)
         np.testing.assert_array_equal(
             expected_gyrophase_delta, codice_hi_data_product.gyrophase_delta
         )
@@ -712,9 +687,7 @@ def test_process_l3b_with_mocks(
             np.array([CodiceL3Flags.PRELIMINARY_MAG, CodiceL3Flags.PRELIMINARY_MAG]),
         )
 
-        np.testing.assert_array_equal(
-            codice_hi_data_product.parent_file_names, expected_parents
-        )
+        np.testing.assert_array_equal(codice_hi_data_product.parent_file_names, expected_parents)
 
     def test_integration_test(self):
         l2_direct_event_sci_path = get_test_data_path(
@@ -741,11 +714,6 @@ def test_integration_test(self):
             version="v02",
             descriptor="hi-direct-events",
         )
-        processor = CodiceHiProcessor(
-            dependencies=Mock(), input_metadata=input_metadata
-        )
+        processor = CodiceHiProcessor(dependencies=Mock(), input_metadata=input_metadata)
 
-        try:
-            processor.process_l3a_direct_event(codice_hi_dependencies)
-        except Exception as e:
-            self.fail(e)
+        processor.process_l3a_direct_event(codice_hi_dependencies)
diff --git a/tests/codice/l3/hi/test_models.py b/tests/codice/l3/hi/test_models.py
index 5243635f..eb790bd3 100644
--- a/tests/codice/l3/hi/test_models.py
+++ b/tests/codice/l3/hi/test_models.py
@@ -9,15 +9,15 @@
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.codice.l3.hi.models import (
-    CodiceL2HiDirectEventData,
-    CodiceL3HiDirectEvents,
     CodiceHiL2SectoredIntensitiesData,
     CodiceHiL3PitchAngleDataProduct,
     CodiceL1aHiDirectEvents,
+    CodiceL2HiDirectEventData,
+    CodiceL3HiDirectEvents,
 )
 from tests.test_helpers import (
-    get_test_instrument_team_data_path,
     get_test_data_path,
+    get_test_instrument_team_data_path,
     with_tempdir,
 )
 
@@ -33,12 +33,8 @@ def tearDown(self):
 
     @with_tempdir
     def test_codice_hi_l2_data_read_from_instrument_team_cdf(self, tempdir):
-        l2_path = get_test_data_path(
-            "codice/imap_codice_l2_hi-direct-events_20250814_v001.cdf"
-        )
-        expanded_l2_path = TestModels._create_expanded_l2_hi_de_dataset(
-            l2_path, tempdir
-        )
+        l2_path = get_test_data_path("codice/imap_codice_l2_hi-direct-events_20250814_v001.cdf")
+        expanded_l2_path = TestModels._create_expanded_l2_hi_de_dataset(l2_path, tempdir)
 
         test_cases = [
             ("6 priorities", l2_path),
@@ -47,15 +43,11 @@ def test_codice_hi_l2_data_read_from_instrument_team_cdf(self, tempdir):
 
         for name, input_path in test_cases:
             with self.subTest(name):
-                l2_direct_event_data = CodiceL2HiDirectEventData.read_from_cdf(
-                    input_path
-                )
+                l2_direct_event_data = CodiceL2HiDirectEventData.read_from_cdf(input_path)
 
                 with CDF(str(l2_path)) as cdf:
                     # @formatter:off
-                    np.testing.assert_array_equal(
-                        l2_direct_event_data.epoch, cdf["epoch"]
-                    )
+                    np.testing.assert_array_equal(l2_direct_event_data.epoch, cdf["epoch"])
                     np.testing.assert_array_equal(
                         l2_direct_event_data.epoch_delta_plus, cdf["epoch_delta_plus"]
                     )
@@ -63,9 +55,7 @@ def test_codice_hi_l2_data_read_from_instrument_team_cdf(self, tempdir):
                         l2_direct_event_data.ssd_energy, cdf["ssd_energy"]
                     )
                     expected_ssd_id = cdf["ssd_id"][...]
-                    np.testing.assert_array_equal(
-                        l2_direct_event_data.ssd_id, expected_ssd_id
-                    )
+                    np.testing.assert_array_equal(l2_direct_event_data.ssd_id, expected_ssd_id)
 
                     expected_energy_per_nuc = cdf["energy_per_nuc"][...]
                     expected_energy_per_nuc[expected_energy_per_nuc == -1e31] = np.nan
@@ -100,9 +90,7 @@ def test_codice_hi_l2_data_read_from_instrument_team_cdf(self, tempdir):
                         l2_direct_event_data.multi_flag, cdf["multi_flag"]
                     )
 
-                    np.testing.assert_array_equal(
-                        l2_direct_event_data.type, cdf["type"]
-                    )
+                    np.testing.assert_array_equal(l2_direct_event_data.type, cdf["type"])
 
                     expected_elevation_angle = cdf["elevation_angle"][...]
                     expected_elevation_angle[expected_elevation_angle == -1e31] = np.nan
@@ -111,13 +99,9 @@ def test_codice_hi_l2_data_read_from_instrument_team_cdf(self, tempdir):
                     )
 
                     self.assertIsInstance(l2_direct_event_data.gain, np.ma.masked_array)
-                    np.testing.assert_array_equal(
-                        l2_direct_event_data.gain.data, cdf["gain"]
-                    )
+                    np.testing.assert_array_equal(l2_direct_event_data.gain.data, cdf["gain"])
 
-                    self.assertIsInstance(
-                        l2_direct_event_data.spin_sector, np.ma.masked_array
-                    )
+                    self.assertIsInstance(l2_direct_event_data.spin_sector, np.ma.masked_array)
                     np.testing.assert_array_equal(
                         l2_direct_event_data.spin_sector.data, cdf["spin_sector"]
                     )
@@ -142,9 +126,7 @@ def test_codice_l3_hi_direct_event_data_products(self):
         expected_priority_index_label = np.array(
             [str(i) for i in range(number_of_priority_events)]
         )
-        expected_event_index_label = np.array(
-            [str(i) for i in range(event_buffer_size)]
-        )
+        expected_event_index_label = np.array([str(i) for i in range(event_buffer_size)])
 
         l3_data_product = CodiceL3HiDirectEvents(
             Mock(),
@@ -176,9 +158,7 @@ def test_codice_l3_hi_direct_event_data_products(self):
 
         self.assertEqual(len(data_product_variables), len(non_parent_fields))
 
-        np.testing.assert_array_equal(
-            l3_data_product.priority_index, expected_priority_index
-        )
+        np.testing.assert_array_equal(l3_data_product.priority_index, expected_priority_index)
         np.testing.assert_array_equal(l3_data_product.event_index, expected_event_index)
         np.testing.assert_array_equal(
             l3_data_product.priority_index_label, expected_priority_index_label
@@ -232,18 +212,14 @@ def test_codice_hi_l3_pitch_angle_to_data_product(self):
             + 1,
             "h_intensity_by_pitch_angle_and_gyrophase": np.arange(
                 pitch_angle_and_gyrophase_size
-            ).reshape(
-                len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase)
-            )
+            ).reshape(len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase))
             + 2,
             "he3he4_intensity_by_pitch_angle": np.arange(pitch_angle_size).reshape(
                 len(epoch_data), len(energy_data), len(pitch_angle)
             ),
             "he3he4_intensity_by_pitch_angle_and_gyrophase": np.arange(
                 pitch_angle_and_gyrophase_size
-            ).reshape(
-                len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase)
-            )
+            ).reshape(len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase))
             + 3,
             "cno_intensity_by_pitch_angle": np.arange(pitch_angle_size).reshape(
                 len(epoch_data), len(energy_data), len(pitch_angle)
@@ -251,9 +227,7 @@ def test_codice_hi_l3_pitch_angle_to_data_product(self):
             + 4,
             "cno_intensity_by_pitch_angle_and_gyrophase": np.arange(
                 pitch_angle_and_gyrophase_size
-            ).reshape(
-                len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase)
-            )
+            ).reshape(len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase))
             + 5,
             "fe_intensity_by_pitch_angle": np.arange(pitch_angle_size).reshape(
                 len(epoch_data), len(energy_data), len(pitch_angle)
@@ -261,9 +235,7 @@ def test_codice_hi_l3_pitch_angle_to_data_product(self):
             + 6,
             "fe_intensity_by_pitch_angle_and_gyrophase": np.arange(
                 pitch_angle_and_gyrophase_size
-            ).reshape(
-                len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase)
-            )
+            ).reshape(len(epoch_data), len(energy_data), len(pitch_angle), len(gyrophase))
             + 7,
             "codice_flags": np.zeros(len(epoch_data), dtype=np.uint16),
         }
@@ -309,9 +281,7 @@ def test_codice_hi_l3_pitch_angle_to_data_product(self):
                     data_product_var.value, getattr(data_product, data_product_var.name)
                 )
             else:
-                np.testing.assert_array_equal(
-                    data_product_var.value, np.array([10 * 1e9])
-                )
+                np.testing.assert_array_equal(data_product_var.value, np.array([10 * 1e9]))
 
     def test_codice_hi_l1a_direct_event_read_from_sdc_cdf(self):
         l1a_path = get_test_data_path(
@@ -321,9 +291,7 @@ def test_codice_hi_l1a_direct_event_read_from_sdc_cdf(self):
 
         with CDF(str(l1a_path)) as cdf:
             np.testing.assert_array_equal(l1a_hi_direct_events.epoch, cdf["epoch"][...])
-            np.testing.assert_array_equal(
-                l1a_hi_direct_events.ssd_energy, cdf["ssd_energy"][...]
-            )
+            np.testing.assert_array_equal(l1a_hi_direct_events.ssd_energy, cdf["ssd_energy"][...])
             np.testing.assert_array_equal(l1a_hi_direct_events.tof, cdf["tof"][...])
 
     def test_l2_sectored_intensities_read_from_sdc_cdf(self):
@@ -337,55 +305,31 @@ def test_l2_sectored_intensities_read_from_sdc_cdf(self):
             expected_epoch_delta = np.array(
                 [timedelta(seconds=ns / 1e9) for ns in cdf["epoch_delta_plus"][...]]
             )
-            np.testing.assert_array_equal(
-                l2_sectored_data.epoch_delta_plus, expected_epoch_delta
-            )
-            np.testing.assert_array_equal(
-                l2_sectored_data.spin_angles, cdf["spin_angle"][...]
-            )
-            np.testing.assert_array_equal(
-                l2_sectored_data.elevation_angle, cdf["elevation_angle"]
-            )
+            np.testing.assert_array_equal(l2_sectored_data.epoch_delta_plus, expected_epoch_delta)
+            np.testing.assert_array_equal(l2_sectored_data.spin_angles, cdf["spin_angle"][...])
+            np.testing.assert_array_equal(l2_sectored_data.elevation_angle, cdf["elevation_angle"])
 
-            np.testing.assert_array_equal(
-                l2_sectored_data.data_quality, cdf["data_quality"]
-            )
+            np.testing.assert_array_equal(l2_sectored_data.data_quality, cdf["data_quality"])
 
             np.testing.assert_array_equal(l2_sectored_data.h_intensities, cdf["h"])
             np.testing.assert_array_equal(l2_sectored_data.energy_h, cdf["energy_h"])
-            np.testing.assert_array_equal(
-                l2_sectored_data.energy_h_plus, cdf["energy_h_plus"]
-            )
-            np.testing.assert_array_equal(
-                l2_sectored_data.energy_h_minus, cdf["energy_h_minus"]
-            )
+            np.testing.assert_array_equal(l2_sectored_data.energy_h_plus, cdf["energy_h_plus"])
+            np.testing.assert_array_equal(l2_sectored_data.energy_h_minus, cdf["energy_h_minus"])
 
             np.testing.assert_array_equal(l2_sectored_data.cno_intensities, cdf["cno"])
-            np.testing.assert_array_equal(
-                l2_sectored_data.energy_cno, cdf["energy_cno"]
-            )
-            np.testing.assert_array_equal(
-                l2_sectored_data.energy_cno_plus, cdf["energy_cno_plus"]
-            )
+            np.testing.assert_array_equal(l2_sectored_data.energy_cno, cdf["energy_cno"])
+            np.testing.assert_array_equal(l2_sectored_data.energy_cno_plus, cdf["energy_cno_plus"])
             np.testing.assert_array_equal(
                 l2_sectored_data.energy_cno_minus, cdf["energy_cno_minus"]
             )
 
             np.testing.assert_array_equal(l2_sectored_data.fe_intensities, cdf["fe"])
             np.testing.assert_array_equal(l2_sectored_data.energy_fe, cdf["energy_fe"])
-            np.testing.assert_array_equal(
-                l2_sectored_data.energy_fe_plus, cdf["energy_fe_plus"]
-            )
-            np.testing.assert_array_equal(
-                l2_sectored_data.energy_fe_minus, cdf["energy_fe_minus"]
-            )
+            np.testing.assert_array_equal(l2_sectored_data.energy_fe_plus, cdf["energy_fe_plus"])
+            np.testing.assert_array_equal(l2_sectored_data.energy_fe_minus, cdf["energy_fe_minus"])
 
-            np.testing.assert_array_equal(
-                l2_sectored_data.he3he4_intensities, cdf["he3he4"]
-            )
-            np.testing.assert_array_equal(
-                l2_sectored_data.energy_he3he4, cdf["energy_he3he4"]
-            )
+            np.testing.assert_array_equal(l2_sectored_data.he3he4_intensities, cdf["he3he4"])
+            np.testing.assert_array_equal(l2_sectored_data.energy_he3he4, cdf["energy_he3he4"])
             np.testing.assert_array_equal(
                 l2_sectored_data.energy_he3he4_plus, cdf["energy_he3he4_plus"]
             )
diff --git a/tests/codice/l3/lo/direct_events/science/test_angle_lookups.py b/tests/codice/l3/lo/direct_events/science/test_angle_lookups.py
index 028c94f5..5125d33b 100644
--- a/tests/codice/l3/lo/direct_events/science/test_angle_lookups.py
+++ b/tests/codice/l3/lo/direct_events/science/test_angle_lookups.py
@@ -3,8 +3,8 @@
 import numpy as np
 
 from imap_l3_processing.codice.l3.lo.direct_events.science.angle_lookup import (
-    SpinAngleLookup,
     PositionToElevationLookup,
+    SpinAngleLookup,
 )
 
 
diff --git a/tests/codice/l3/lo/direct_events/science/test_efficiency_lookup.py b/tests/codice/l3/lo/direct_events/science/test_efficiency_lookup.py
index 1288791d..ba3e6259 100644
--- a/tests/codice/l3/lo/direct_events/science/test_efficiency_lookup.py
+++ b/tests/codice/l3/lo/direct_events/science/test_efficiency_lookup.py
@@ -29,17 +29,11 @@ def test_read_from_csv(self):
                     + [f"position_{i}" for i in range(num_positions)]
                 )
                 for i in range(num_energies):
-                    csv_writer.writerow(
-                        ["hplus", "sw", i, *expected_efficiency_data[i, :]]
-                    )
+                    csv_writer.writerow(["hplus", "sw", i, *expected_efficiency_data[i, :]])
                 for i in range(num_energies):
-                    csv_writer.writerow(
-                        ["cplus6", "sw", i, *expected_efficiency_data[i, :] * 6]
-                    )
+                    csv_writer.writerow(["cplus6", "sw", i, *expected_efficiency_data[i, :] * 6])
                 for i in range(num_energies):
-                    csv_writer.writerow(
-                        ["hplus", "nsw", i, *expected_efficiency_data[i, :] * 42]
-                    )
+                    csv_writer.writerow(["hplus", "nsw", i, *expected_efficiency_data[i, :] * 42])
 
             efficiency_lookup = EfficiencyLookup.read_from_csv(output_csv, "hplus")
 
diff --git a/tests/codice/l3/lo/direct_events/science/test_energy_lookup.py b/tests/codice/l3/lo/direct_events/science/test_energy_lookup.py
index 117df203..a61c3adf 100644
--- a/tests/codice/l3/lo/direct_events/science/test_energy_lookup.py
+++ b/tests/codice/l3/lo/direct_events/science/test_energy_lookup.py
@@ -11,24 +11,17 @@
 class TestEnergyLookup(unittest.TestCase):
     def test_read_from_csv(self):
         input_file = (
-            get_test_data_path("codice")
-            / "imap_codice_lo-energy-per-charge_20241110_v002.csv"
+            get_test_data_path("codice") / "imap_codice_lo-energy-per-charge_20241110_v002.csv"
         )
         actual_energy_lookup = EnergyLookup.read_from_csv(input_file)
 
         np.testing.assert_array_equal(actual_energy_lookup.bin_centers[0], 81.216)
-        np.testing.assert_array_equal(
-            actual_energy_lookup.bin_centers[127], 0.507357072
-        )
-        np.testing.assert_array_equal(
-            actual_energy_lookup.delta_minus[0], 81.216 - 79.60339125
-        )
+        np.testing.assert_array_equal(actual_energy_lookup.bin_centers[127], 0.507357072)
+        np.testing.assert_array_equal(actual_energy_lookup.delta_minus[0], 81.216 - 79.60339125)
         np.testing.assert_array_equal(
             actual_energy_lookup.delta_minus[127], 0.507357072 - 0.497319345
         )
-        np.testing.assert_array_equal(
-            actual_energy_lookup.delta_plus[0], 82.855305 - 81.216
-        )
+        np.testing.assert_array_equal(actual_energy_lookup.delta_plus[0], 82.855305 - 81.216)
         np.testing.assert_array_equal(
             actual_energy_lookup.delta_plus[127], 0.517446956 - 0.507357072
         )
diff --git a/tests/codice/l3/lo/direct_events/science/test_geometric_factor_lookup.py b/tests/codice/l3/lo/direct_events/science/test_geometric_factor_lookup.py
index 6d510fa2..21efe05c 100644
--- a/tests/codice/l3/lo/direct_events/science/test_geometric_factor_lookup.py
+++ b/tests/codice/l3/lo/direct_events/science/test_geometric_factor_lookup.py
@@ -57,11 +57,7 @@ def test_read_from_csv(self):
         expected_num_esa_steps = 128
         expected_num_positions = 24
 
-        path = (
-            get_test_data_folder()
-            / "codice"
-            / "imap_codice_l2-lo-gfactor_20251212_v003.csv"
-        )
+        path = get_test_data_folder() / "codice" / "imap_codice_l2-lo-gfactor_20251212_v003.csv"
         lookup = GeometricFactorLookup.read_from_csv(path)
 
         self.assertIsInstance(lookup, GeometricFactorLookup)
@@ -143,9 +139,7 @@ def test_get_geometric_factors_gets_reduced_where_half_spin_greater_than_rgfo_ha
         ) in epoch_esa_step_index_pairs_and_expected_factors:
             np.testing.assert_array_equal(
                 actual[epoch, esa_step, :, :],
-                np.broadcast_to(
-                    expected_factors[esa_step], all_spin_sectors_and_positions
-                ),
+                np.broadcast_to(expected_factors[esa_step], all_spin_sectors_and_positions),
                 f"Mismatch at epoch:{epoch}, esa:{esa_step}",
             )
 
@@ -276,9 +270,7 @@ def test_get_geometric_factors_gets_reduced_where_half_spin_greater_than_rgfo_ha
         ) in epoch_esa_step_index_pairs_and_expected_factors:
             np.testing.assert_array_equal(
                 actual[epoch, esa_step, :, :],
-                np.broadcast_to(
-                    expected_factors[esa_step], all_spin_sectors_and_positions
-                ),
+                np.broadcast_to(expected_factors[esa_step], all_spin_sectors_and_positions),
             )
 
     @patch(
diff --git a/tests/codice/l3/lo/direct_events/science/test_mass_species_bin_lookup.py b/tests/codice/l3/lo/direct_events/science/test_mass_species_bin_lookup.py
index 7eab888f..1426b30f 100644
--- a/tests/codice/l3/lo/direct_events/science/test_mass_species_bin_lookup.py
+++ b/tests/codice/l3/lo/direct_events/science/test_mass_species_bin_lookup.py
@@ -23,9 +23,7 @@ def test_read_csv(self):
         np.testing.assert_array_equal(
             mass_species_bin_lookup.mass_per_charge, expected_mass_per_charge
         )
-        np.testing.assert_array_equal(
-            mass_species_bin_lookup.mass_ranges, expected_mass_range
-        )
+        np.testing.assert_array_equal(mass_species_bin_lookup.mass_ranges, expected_mass_range)
 
     def test_get_species(self):
         lookup = MassSpeciesBinLookup(
@@ -52,6 +50,4 @@ def test_get_species_index(self):
         test_cases = [("hplus", 0), ("heplusplus", 1), ("oplus6", 2), ("heplus", 3)]
         for species, index in test_cases:
             with self.subTest(species):
-                self.assertEqual(
-                    index, mass_species_bin_lookup.get_species_index(species)
-                )
+                self.assertEqual(index, mass_species_bin_lookup.get_species_index(species))
diff --git a/tests/codice/l3/lo/science/test_codice_lo_calculations.py b/tests/codice/l3/lo/science/test_codice_lo_calculations.py
index 7edfe117..f56f6613 100644
--- a/tests/codice/l3/lo/science/test_codice_lo_calculations.py
+++ b/tests/codice/l3/lo/science/test_codice_lo_calculations.py
@@ -18,19 +18,19 @@
 )
 from imap_l3_processing.codice.l3.lo.models import CodiceLoDirectEventData
 from imap_l3_processing.codice.l3.lo.science.codice_lo_calculations import (
-    calculate_partial_densities,
-    calculate_total_number_of_events,
+    CODICE_LO_NUM_AZIMUTH_BINS,
     calculate_mass,
     calculate_mass_per_charge,
-    rebin_to_counts_by_species_elevation_and_spin_sector,
-    rebin_direct_events_by_energy_and_spin_sector,
-    CODICE_LO_NUM_AZIMUTH_BINS,
+    calculate_normalization_factor,
+    calculate_partial_densities,
+    calculate_total_number_of_events,
     combine_priorities_for_species_and_calculate_count_uncertainty,
-    rebin_3d_distribution_azimuth_to_elevation,
     convert_counts_to_intensity,
-    rebin_direct_events_for_normalization,
-    calculate_normalization_factor,
     lookup_normalization_per_event,
+    rebin_3d_distribution_azimuth_to_elevation,
+    rebin_direct_events_by_energy_and_spin_sector,
+    rebin_direct_events_for_normalization,
+    rebin_to_counts_by_species_elevation_and_spin_sector,
 )
 
 
@@ -57,9 +57,7 @@ def test_calculate_mass(self):
         apd_energy = np.array([[np.exp(1)], [np.exp(2)]])
         tof = np.array([[np.exp(50)], [np.exp(60)]])
 
-        lookup = MassCoefficientLookup(
-            np.array([10e-1, 10e-2, 10e-3, 10e-4, 10e-5, 10e-6])
-        )
+        lookup = MassCoefficientLookup(np.array([10e-1, 10e-2, 10e-3, 10e-4, 10e-5, 10e-6]))
         actual_mass = calculate_mass(apd_energy, tof, lookup)
 
         expected_mass_1 = (
@@ -79,9 +77,7 @@ def test_calculate_mass(self):
             + lookup[5] * np.power(60, 3)
         )
 
-        expected_mass_calculation = np.array(
-            [[np.e**expected_mass_1], [np.e**expected_mass_2]]
-        )
+        expected_mass_calculation = np.array([[np.e**expected_mass_1], [np.e**expected_mass_2]])
 
         np.testing.assert_array_equal(actual_mass, expected_mass_calculation)
 
@@ -111,9 +107,7 @@ def test_calculate_mass_per_charge(self):
         )
 
     def test_calculate_mass_per_charge_handles_fill_value(self):
-        tof = np.ma.masked_array(
-            [[432, 234], [434, 347]], mask=[[False, True], [True, False]]
-        )
+        tof = np.ma.masked_array([[432, 234], [434, 347]], mask=[[False, True], [True, False]])
         apd_energy = np.array([[np.nan, 2342.2], [4324.8, np.nan]])
 
         actual_mass_per_charge = calculate_mass_per_charge(apd_energy, tof)
@@ -127,9 +121,7 @@ def test_calculate_mass_handles_fill_value(self):
         rng = np.random.default_rng()
         mass_coefficients = MassCoefficientLookup(coefficients=rng.random(size=6))
 
-        tof = np.ma.masked_array(
-            [[432, 234], [434, 347]], mask=[[False, True], [True, False]]
-        )
+        tof = np.ma.masked_array([[432, 234], [434, 347]], mask=[[False, True], [True, False]])
         apd_energy = np.array([[np.nan, 2342.2], [4324.8, np.nan]])
 
         actual_mass = calculate_mass(apd_energy, tof, mass_coefficients)
@@ -146,9 +138,7 @@ def test_calculate_partial_densities(self):
         intensities = rng.random((len(epochs), len(energy_steps), 1))
         mass_per_charge = 10
 
-        partial_densities = calculate_partial_densities(
-            intensities, energy_steps, mass_per_charge
-        )
+        partial_densities = calculate_partial_densities(intensities, energy_steps, mass_per_charge)
 
         expected_partial_densities = np.sum(
             2.283e-8
@@ -168,9 +158,7 @@ def test_calculate_partial_densities_ignores_nan_intensities(self):
         intensities = np.array([[[1], [2], [3]], [[4], [5], [np.nan]]])
         mass_per_charge = 10
 
-        partial_densities = calculate_partial_densities(
-            intensities, energy_steps, mass_per_charge
-        )
+        partial_densities = calculate_partial_densities(intensities, energy_steps, mass_per_charge)
 
         expected_partial_densities = (
             2.283e-8
@@ -194,9 +182,7 @@ def test_rebin_to_counts_by_species_elevation_and_spin_sector(self):
         # [[Mg, no call, None, no call], [no call, no call, no call, no call]]
         expected_species_returned = ["He+", "Fe", "He+", "O+5", "Mg", None]
         mock_species_mass_range_lookup = Mock(spec=MassSpeciesBinLookup)
-        mock_species_mass_range_lookup.get_species.side_effect = (
-            expected_species_returned
-        )
+        mock_species_mass_range_lookup.get_species.side_effect = expected_species_returned
         mock_species_mass_range_lookup.get_num_species.return_value = num_species
 
         def mock_get_species_index(species):
@@ -211,9 +197,7 @@ def mock_get_species_index(species):
         mock_species_mass_range_lookup.get_species_index = mock_get_species_index
 
         num_events = np.array([[4, 2], [3, 1]])
-        num_events = np.ma.masked_array(
-            num_events, mask=[[False, False], [False, True]]
-        )
+        num_events = np.ma.masked_array(num_events, mask=[[False, False], [False, True]])
 
         normalized_per_event = np.array(
             [
@@ -310,9 +294,7 @@ def mock_get_species_index(species):
         rebinned_shape = tuple(output_shape[1:])
         expected_he_plus_counts = np.zeros(rebinned_shape)
         expected_he_plus_counts[0, 0, 0, 2, 1] = 300.88
-        np.testing.assert_array_equal(
-            actual_counts_3d_data[0, ...], expected_he_plus_counts
-        )
+        np.testing.assert_array_equal(actual_counts_3d_data[0, ...], expected_he_plus_counts)
 
         expected_fe_counts = np.zeros(rebinned_shape)
         expected_fe_counts[0, 0, 100, 1, 23] = 30.9
@@ -332,18 +314,12 @@ def test_rebin_direct_events_by_energy_and_spin_sector(self):
         num_priorities = 3
         num_epochs = 1
         event_buffer_len = 15
-        num_events = np.ma.masked_array(
-            np.array([[1, 2, 4]]), mask=[[False, True, False]]
-        )
-        spin_sector = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=np.uint8
-        )
+        num_events = np.ma.masked_array(np.array([[1, 2, 4]]), mask=[[False, True, False]])
+        spin_sector = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=np.uint8)
         spin_sector[0, 0, :1] = [3]
         spin_sector[0, 2, :4] = [5, 6, 5, 7]
 
-        energy_step = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=np.uint8
-        )
+        energy_step = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=np.uint8)
         energy_step[0, 0, :1] = [7]
         energy_step[0, 2, :4] = [1, 3, 1, 4]
 
@@ -367,19 +343,13 @@ def test_rebin_direct_events_by_energy_and_spin_sector_ignores_masked_events(sel
         num_priorities = 3
         num_epochs = 1
         event_buffer_len = 15
-        num_events = np.ma.masked_array(
-            np.array([[1, 2, 4]]), mask=[[False, True, False]]
-        )
-        spin_sector = np.ma.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=np.uint8
-        )
+        num_events = np.ma.masked_array(np.array([[1, 2, 4]]), mask=[[False, True, False]])
+        spin_sector = np.ma.zeros((num_epochs, num_priorities, event_buffer_len), dtype=np.uint8)
         spin_sector[0, 0, :1] = [3]
         spin_sector[0, 2, :4] = [5, 6, 255, 7]
         spin_sector[0, 2, 2] = np.ma.masked
 
-        energy_step = np.ma.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=np.uint8
-        )
+        energy_step = np.ma.zeros((num_epochs, num_priorities, event_buffer_len), dtype=np.uint8)
         energy_step[0, 0, :1] = [7]
         energy_step[0, 2, :4] = [1, 255, 1, 4]
         energy_step[0, 2, 1] = np.ma.masked
@@ -404,18 +374,12 @@ def test_rebin_direct_events_for_normalization(self):
         num_priorities = 3
         num_epochs = 1
         event_buffer_len = 15
-        num_events = np.ma.masked_array(
-            np.array([[2, 2, 4]]), mask=[[False, True, False]]
-        )
-        spin_sector = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=np.uint8
-        )
+        num_events = np.ma.masked_array(np.array([[2, 2, 4]]), mask=[[False, True, False]])
+        spin_sector = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=np.uint8)
         spin_sector[0, 0, :2] = [3, 3 + 12]
         spin_sector[0, 2, :4] = [5, 6, 5, 7 + 12]
 
-        energy_step = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=np.uint8
-        )
+        energy_step = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=np.uint8)
         energy_step[0, 0, :2] = [7, 7]
         energy_step[0, 2, :4] = [1, 3, 1, 4]
 
@@ -452,12 +416,8 @@ def test_calculate_normalization_factor(self):
 
         event_buffer_len = 15
         num_events = np.zeros((num_epochs, num_priorities), dtype=int)
-        spin_sectors = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=int
-        )
-        energy_steps = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=int
-        )
+        spin_sectors = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=int)
+        energy_steps = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=int)
 
         num_events[0, 0] = 4
         spin_sectors[0, 0, :4] = [0, 2, 12, 0]
@@ -495,12 +455,8 @@ def test_calculate_normalization_factor_floor_is_one(self):
 
         event_buffer_len = 15
         num_events = np.zeros((num_epochs, num_priorities), dtype=int)
-        spin_sectors = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=int
-        )
-        energy_steps = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=int
-        )
+        spin_sectors = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=int)
+        energy_steps = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=int)
 
         num_events[0, 0] = 3
         spin_sectors[0, 0, :3] = [0, 12, 2]
@@ -539,12 +495,8 @@ def test_normalization_factor_is_fill_when_priority_nonzero_and_direct_zero(self
 
         event_buffer_len = 15
         num_events = np.zeros((num_epochs, num_priorities), dtype=int)
-        spin_sectors = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=int
-        )
-        energy_steps = np.zeros(
-            (num_epochs, num_priorities, event_buffer_len), dtype=int
-        )
+        spin_sectors = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=int)
+        energy_steps = np.zeros((num_epochs, num_priorities, event_buffer_len), dtype=int)
 
         result = calculate_normalization_factor(
             priority_counts, num_events, energy_steps, spin_sectors
@@ -572,9 +524,7 @@ def test_lookup_normalization_per_event(self):
         num_l1_spin_sectors = 12
         num_l2_spin_sectors = 2 * num_l1_spin_sectors
 
-        normalization = np.zeros(
-            (num_epochs, num_priorities, num_esa_steps, num_l2_spin_sectors)
-        )
+        normalization = np.zeros((num_epochs, num_priorities, num_esa_steps, num_l2_spin_sectors))
         normalization[0, 0, 0, 0] = 123.0
         normalization[0, 0, 0, 12] = 456.0
         normalization[0, 0, 1, 2] = 789.0
@@ -598,18 +548,14 @@ def test_lookup_normalization_per_event(self):
             normalization, num_events, energy_steps, spin_sectors
         )
 
-        np.testing.assert_array_equal(
-            normalization_per_event[0, 0, :3], [123, 456, 789]
-        )
+        np.testing.assert_array_equal(normalization_per_event[0, 0, :3], [123, 456, 789])
 
         expected_normalization_per_event = np.full(
             (num_epochs, num_priorities, event_buffer_len), np.nan
         )
         expected_normalization_per_event[0, 0, :3] = [123, 456, 789]
 
-        np.testing.assert_array_equal(
-            normalization_per_event, expected_normalization_per_event
-        )
+        np.testing.assert_array_equal(normalization_per_event, expected_normalization_per_event)
 
     def test_lookup_normalization_per_event_skips_masked_num_events(self):
         num_epochs = 2
@@ -618,17 +564,13 @@ def test_lookup_normalization_per_event_skips_masked_num_events(self):
         num_l1_spin_sectors = 12
         num_l2_spin_sectors = 2 * num_l1_spin_sectors
 
-        normalization = np.zeros(
-            (num_epochs, num_priorities, num_esa_steps, num_l2_spin_sectors)
-        )
+        normalization = np.zeros((num_epochs, num_priorities, num_esa_steps, num_l2_spin_sectors))
         normalization[0, 0, 0, 0] = 123.0
         normalization[0, 0, 0, 12] = 456.0
         normalization[0, 0, 1, 2] = 789.0
 
         event_buffer_len = 15
-        num_events = np.ma.array(
-            np.full((num_epochs, num_priorities), 65535), mask=True
-        )
+        num_events = np.ma.array(np.full((num_epochs, num_priorities), 65535), mask=True)
         spin_sectors = np.ma.array(
             np.full((num_epochs, num_priorities, event_buffer_len), 255, dtype=int),
             mask=True,
@@ -645,9 +587,7 @@ def test_lookup_normalization_per_event_skips_masked_num_events(self):
         expected_normalization_per_event = np.full(
             (num_epochs, num_priorities, event_buffer_len), np.nan
         )
-        np.testing.assert_array_equal(
-            normalization_per_event, expected_normalization_per_event
-        )
+        np.testing.assert_array_equal(normalization_per_event, expected_normalization_per_event)
 
     def test_lookup_normalization_per_event_ignores_masked_events(self):
         num_epochs = 2
@@ -656,9 +596,7 @@ def test_lookup_normalization_per_event_ignores_masked_events(self):
         num_l1_spin_sectors = 12
         num_l2_spin_sectors = 2 * num_l1_spin_sectors
 
-        normalization = np.zeros(
-            (num_epochs, num_priorities, num_esa_steps, num_l2_spin_sectors)
-        )
+        normalization = np.zeros((num_epochs, num_priorities, num_esa_steps, num_l2_spin_sectors))
         normalization[0, 0, 0, 0] = 123.0
         normalization[0, 0, 0, 12] = 456.0
         normalization[0, 0, 1, 2] = 789.0
@@ -694,9 +632,7 @@ def test_lookup_normalization_per_event_ignores_masked_events(self):
         )
         expected_normalization_per_event[0, 0, :4] = [np.nan, np.nan, np.nan, 456]
 
-        np.testing.assert_array_equal(
-            normalization_per_event, expected_normalization_per_event
-        )
+        np.testing.assert_array_equal(normalization_per_event, expected_normalization_per_event)
 
     def test_combine_priorities_for_species_and_calculate_count_uncertainty(self):
         num_epochs = 2
@@ -705,15 +641,9 @@ def test_combine_priorities_for_species_and_calculate_count_uncertainty(self):
         num_azimuth_bins = 5
 
         rng = np.random.default_rng()
-        priority_1 = rng.random(
-            (num_epochs, num_energies, num_spin_sectors, num_azimuth_bins)
-        )
-        priority_2 = rng.random(
-            (num_epochs, num_energies, num_spin_sectors, num_azimuth_bins)
-        )
-        priority_3 = rng.random(
-            (num_epochs, num_energies, num_spin_sectors, num_azimuth_bins)
-        )
+        priority_1 = rng.random((num_epochs, num_energies, num_spin_sectors, num_azimuth_bins))
+        priority_2 = rng.random((num_epochs, num_energies, num_spin_sectors, num_azimuth_bins))
+        priority_3 = rng.random((num_epochs, num_energies, num_spin_sectors, num_azimuth_bins))
 
         counts = np.stack((priority_1, priority_2, priority_3), axis=1)
 
@@ -728,9 +658,7 @@ def test_combine_priorities_for_species_and_calculate_count_uncertainty(self):
         )
 
         np.testing.assert_array_equal(actual_counts, expected_summed_counts)
-        np.testing.assert_array_equal(
-            actual_count_uncertainty, np.sqrt(expected_summed_counts)
-        )
+        np.testing.assert_array_equal(actual_count_uncertainty, np.sqrt(expected_summed_counts))
 
     def test_convert_count_rate_to_intensity(self):
         num_epochs = 3
@@ -739,9 +667,7 @@ def test_convert_count_rate_to_intensity(self):
         num_energies = 6
 
         rng = np.random.default_rng()
-        counts = rng.random(
-            (num_epochs, num_energies, num_spin_angles, num_position_bins)
-        )
+        counts = rng.random((num_epochs, num_energies, num_spin_angles, num_position_bins))
         acquisition_times = rng.random(
             (
                 num_epochs,
@@ -787,9 +713,7 @@ def test_rebin_azimuth_to_elevation(self):
         num_spin_angles = 24
         num_azimuth_bins = 24
 
-        intensity_data = np.zeros(
-            (num_epochs, num_energies, num_spin_angles, num_azimuth_bins)
-        )
+        intensity_data = np.zeros((num_epochs, num_energies, num_spin_angles, num_azimuth_bins))
         azimuth_1_intensity = 1
         azimuth_2_intensity = 2
         azimuth_3_intensity = 3
@@ -806,8 +730,8 @@ def test_rebin_azimuth_to_elevation(self):
         mock_position_to_elevation_lookup = Mock(spec=PositionToElevationLookup)
         mock_position_to_elevation_lookup.num_bins = num_elevation_bins
         mock_position_to_elevation_lookup.bin_centers = np.arange(num_elevation_bins)
-        mock_position_to_elevation_lookup.apd_to_elevation_index.return_value = (
-            np.array([1, 0, 2, 2])
+        mock_position_to_elevation_lookup.apd_to_elevation_index.return_value = np.array(
+            [1, 0, 2, 2]
         )
 
         half_spin_per_esa = np.zeros((num_epochs, num_energies))
@@ -818,9 +742,7 @@ def test_rebin_azimuth_to_elevation(self):
             half_spin_per_esa,
         )
 
-        mock_position_to_elevation_lookup.apd_to_elevation_index.assert_called_once_with(
-            azimuths
-        )
+        mock_position_to_elevation_lookup.apd_to_elevation_index.assert_called_once_with(azimuths)
 
         self.assertEqual(
             (num_epochs, num_energies, num_spin_angles, num_elevation_bins),
@@ -830,8 +752,5 @@ def test_rebin_azimuth_to_elevation(self):
         self.assertTrue(np.all(actual_rebinned[:, :, :, 0] == azimuth_2_intensity))
         self.assertTrue(np.all(actual_rebinned[:, :, :, 1] == azimuth_1_intensity))
         self.assertTrue(
-            np.all(
-                actual_rebinned[:, :, :, 2]
-                == (azimuth_3_intensity + azimuth_4_intensity)
-            )
+            np.all(actual_rebinned[:, :, :, 2] == (azimuth_3_intensity + azimuth_4_intensity))
         )
diff --git a/tests/codice/l3/lo/sectored_intensities/test_mass_per_charge_lookup.py b/tests/codice/l3/lo/sectored_intensities/test_mass_per_charge_lookup.py
index ca56e1d1..eab447cc 100644
--- a/tests/codice/l3/lo/sectored_intensities/test_mass_per_charge_lookup.py
+++ b/tests/codice/l3/lo/sectored_intensities/test_mass_per_charge_lookup.py
@@ -12,9 +12,7 @@ def test_read_from_file(self):
             "codice/imap_codice_mass-per-charge_20241110_v002.csv"
         )
 
-        mass_per_charge_lookup = MassPerChargeLookup.read_from_file(
-            mass_per_charge_csv_path
-        )
+        mass_per_charge_lookup = MassPerChargeLookup.read_from_file(mass_per_charge_csv_path)
 
         self.assertEqual(1, mass_per_charge_lookup.hplus)
         self.assertEqual(2, mass_per_charge_lookup.heplusplus)
diff --git a/tests/codice/l3/lo/test_codice_lo_l3a_direct_events_dependencies.py b/tests/codice/l3/lo/test_codice_lo_l3a_direct_events_dependencies.py
index 14c14ff1..a0ffce6a 100644
--- a/tests/codice/l3/lo/test_codice_lo_l3a_direct_events_dependencies.py
+++ b/tests/codice/l3/lo/test_codice_lo_l3a_direct_events_dependencies.py
@@ -1,19 +1,19 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, call, sentinel
+from unittest.mock import call, patch, sentinel
 
 from imap_data_access.processing_input import (
+    AncillaryInput,
     ProcessingInputCollection,
     ScienceInput,
-    AncillaryInput,
 )
 
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_direct_events_dependencies import (
-    CodiceLoL3aDirectEventsDependencies,
     DIRECT_EVENTS_DESCRIPTOR,
-    SW_PRIORITY_DESCRIPTOR,
-    NSW_PRIORITY_DESCRIPTOR,
     MASS_COEFFICIENT_DESCRIPTOR,
+    NSW_PRIORITY_DESCRIPTOR,
+    SW_PRIORITY_DESCRIPTOR,
+    CodiceLoL3aDirectEventsDependencies,
 )
 from imap_l3_processing.codice.l3.lo.direct_events.science.energy_lookup import (
     ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR,
@@ -21,9 +21,7 @@
 
 
 class TestCodiceLoL3aDirectEventsDependencies(unittest.TestCase):
-    @patch(
-        "imap_l3_processing.codice.l3.lo.codice_lo_l3a_direct_events_dependencies.download"
-    )
+    @patch("imap_l3_processing.codice.l3.lo.codice_lo_l3a_direct_events_dependencies.download")
     @patch(
         "imap_l3_processing.codice.l3.lo.codice_lo_l3a_direct_events_dependencies.CodiceLoL3aDirectEventsDependencies.from_file_paths"
     )
@@ -37,10 +35,10 @@ def test_fetch_dependencies(self, mock_from_file_paths, mock_download):
         lo_nsw_priority_science_file_name = (
             f"imap_codice_l1a_{NSW_PRIORITY_DESCRIPTOR}_20100105_v010.cdf"
         )
-        mass_coefficient_file_name = (
-            f"imap_codice_{MASS_COEFFICIENT_DESCRIPTOR}_20100105_v001.csv"
+        mass_coefficient_file_name = f"imap_codice_{MASS_COEFFICIENT_DESCRIPTOR}_20100105_v001.csv"
+        energy_lookup_file_name = (
+            f"imap_codice_{ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR}_20100105_v001.csv"
         )
-        energy_lookup_file_name = f"imap_codice_{ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR}_20100105_v001.csv"
 
         mock_download.side_effect = [
             Path("some_local_folder") / lo_sw_priority_science_file_name,
@@ -59,9 +57,7 @@ def test_fetch_dependencies(self, mock_from_file_paths, mock_download):
             AncillaryInput(
                 "imap/ancillary/hit/imap_codice_range-2A-cosine-lookup_20250203_v001.csv"
             ),
-            ScienceInput(
-                "imap/hit/l3/2010/01/imap_hit_l3_direct-events_20100105_v010.cdf"
-            ),
+            ScienceInput("imap/hit/l3/2010/01/imap_hit_l3_direct-events_20100105_v010.cdf"),
             ScienceInput("imap_codice_l1_direct-events_20100105_v010.cdf"),
         )
 
@@ -120,21 +116,11 @@ def test_from_file_paths(
             sentinel.energy_lookup_path,
         )
 
-        mock_direct_event_read_from_cdf.assert_called_once_with(
-            sentinel.direct_events_cdf_path
-        )
-        mock_mass_coefficient_lookup.assert_called_once_with(
-            sentinel.mass_coefficient_lookup_path
-        )
-        mock_codice_lo_l1a_sw_priority_rates.assert_called_once_with(
-            sentinel.sw_priority
-        )
-        mock_codice_lo_l1a_nsw_priority_rates.assert_called_once_with(
-            sentinel.nsw_priority
-        )
-        mock_energy_lookup_read_from_csv.assert_called_once_with(
-            sentinel.energy_lookup_path
-        )
+        mock_direct_event_read_from_cdf.assert_called_once_with(sentinel.direct_events_cdf_path)
+        mock_mass_coefficient_lookup.assert_called_once_with(sentinel.mass_coefficient_lookup_path)
+        mock_codice_lo_l1a_sw_priority_rates.assert_called_once_with(sentinel.sw_priority)
+        mock_codice_lo_l1a_nsw_priority_rates.assert_called_once_with(sentinel.nsw_priority)
+        mock_energy_lookup_read_from_csv.assert_called_once_with(sentinel.energy_lookup_path)
 
         self.assertEqual(
             mock_direct_event_read_from_cdf.return_value,
diff --git a/tests/codice/l3/lo/test_codice_lo_l3a_partial_densities_dependencies.py b/tests/codice/l3/lo/test_codice_lo_l3a_partial_densities_dependencies.py
index 79ddb70d..1866b21f 100644
--- a/tests/codice/l3/lo/test_codice_lo_l3a_partial_densities_dependencies.py
+++ b/tests/codice/l3/lo/test_codice_lo_l3a_partial_densities_dependencies.py
@@ -1,18 +1,18 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, call, sentinel
+from unittest.mock import call, patch, sentinel
 
 import imap_data_access
 from imap_data_access.processing_input import (
+    AncillaryInput,
     ProcessingInputCollection,
     ScienceInput,
-    AncillaryInput,
 )
 
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_partial_densities_dependencies import (
-    CodiceLoL3aPartialDensitiesDependencies,
-    SW_SPECIES_DESCRIPTOR,
     MASS_PER_CHARGE_DESCRIPTOR,
+    SW_SPECIES_DESCRIPTOR,
+    CodiceLoL3aPartialDensitiesDependencies,
 )
 
 
@@ -23,11 +23,13 @@ class TestCodiceLoL3aPartialDensitiesDependencies(unittest.TestCase):
     @patch(
         "imap_l3_processing.codice.l3.lo.codice_lo_l3a_partial_densities_dependencies.CodiceLoL3aPartialDensitiesDependencies.from_file_paths"
     )
-    def test_fetch_dependencies(
-        self, mock_from_file_paths, mock_imap_data_access_download
-    ):
-        expected_codice_science_file_download_path = f"imap/codice/l2/2010/01/imap_codice_l2_{SW_SPECIES_DESCRIPTOR}_20100105_v010.cdf"
-        expected_mass_per_charge_file_download_path = f"imap/ancillary/codice/imap_codice_{MASS_PER_CHARGE_DESCRIPTOR}_20100105_v001.csv"
+    def test_fetch_dependencies(self, mock_from_file_paths, mock_imap_data_access_download):
+        expected_codice_science_file_download_path = (
+            f"imap/codice/l2/2010/01/imap_codice_l2_{SW_SPECIES_DESCRIPTOR}_20100105_v010.cdf"
+        )
+        expected_mass_per_charge_file_download_path = (
+            f"imap/ancillary/codice/imap_codice_{MASS_PER_CHARGE_DESCRIPTOR}_20100105_v001.csv"
+        )
 
         sectored_science_input = ScienceInput(
             f"imap_codice_l2_{SW_SPECIES_DESCRIPTOR}_20100105_v010.cdf"
@@ -66,19 +68,15 @@ def test_fetch_dependencies(
             expected_local_mass_per_charge_file_download_path,
         ]
 
-        codice_l3_dependencies = (
-            CodiceLoL3aPartialDensitiesDependencies.fetch_dependencies(
-                processing_input_collection
-            )
+        codice_l3_dependencies = CodiceLoL3aPartialDensitiesDependencies.fetch_dependencies(
+            processing_input_collection
         )
 
         data_dir = imap_data_access.config["DATA_DIR"]
         expected_download_sectored_science_path = (
             data_dir / expected_codice_science_file_download_path
         )
-        expected_download_ancillary_path = (
-            data_dir / expected_mass_per_charge_file_download_path
-        )
+        expected_download_ancillary_path = data_dir / expected_mass_per_charge_file_download_path
 
         mock_imap_data_access_download.assert_has_calls(
             [
@@ -108,9 +106,7 @@ def test_from_file_paths(self, mock_mpc_read_from_file, mock_read_from_cdf):
         mock_mpc_read_from_file.assert_called_once_with(sentinel.mpc_lookup_path)
         mock_read_from_cdf.assert_called_once_with(sentinel.cdf_path)
 
-        self.assertEqual(
-            mock_read_from_cdf.return_value, actual_dependencies.codice_l2_lo_data
-        )
+        self.assertEqual(mock_read_from_cdf.return_value, actual_dependencies.codice_l2_lo_data)
         self.assertEqual(
             mock_mpc_read_from_file.return_value,
             actual_dependencies.mass_per_charge_lookup,
diff --git a/tests/codice/l3/lo/test_codice_lo_l3a_ratios_dependencies.py b/tests/codice/l3/lo/test_codice_lo_l3a_ratios_dependencies.py
index bc119f6d..49a35fa3 100644
--- a/tests/codice/l3/lo/test_codice_lo_l3a_ratios_dependencies.py
+++ b/tests/codice/l3/lo/test_codice_lo_l3a_ratios_dependencies.py
@@ -13,15 +13,11 @@ class TestCodiceLoL3aRatiosDependencies(unittest.TestCase):
         "imap_l3_processing.codice.l3.lo.codice_lo_l3a_ratios_dependencies.CodiceLoPartialDensityData.read_from_cdf"
     )
     def test_from_file_paths(self, mock_read_from_cdf):
-        actual_dependencies = CodiceLoL3aRatiosDependencies.from_file_paths(
-            sentinel.cdf_path
-        )
+        actual_dependencies = CodiceLoL3aRatiosDependencies.from_file_paths(sentinel.cdf_path)
 
         mock_read_from_cdf.assert_called_once_with(sentinel.cdf_path)
 
-        self.assertEqual(
-            mock_read_from_cdf.return_value, actual_dependencies.partial_density_data
-        )
+        self.assertEqual(mock_read_from_cdf.return_value, actual_dependencies.partial_density_data)
 
     @patch(
         "imap_l3_processing.codice.l3.lo.codice_lo_l3a_ratios_dependencies.CodiceLoPartialDensityData.read_from_cdf"
@@ -34,11 +30,7 @@ def test_fetch_dependencies(self, mock_download, mock_read_from_cdf):
         science_input = ScienceInput(expected_file_name)
         processing_inputs = ProcessingInputCollection(science_input)
 
-        dependencies = CodiceLoL3aRatiosDependencies.fetch_dependencies(
-            processing_inputs
-        )
+        dependencies = CodiceLoL3aRatiosDependencies.fetch_dependencies(processing_inputs)
 
         mock_download.assert_called_once_with(expected_file_name)
-        self.assertEqual(
-            mock_read_from_cdf.return_value, dependencies.partial_density_data
-        )
+        self.assertEqual(mock_read_from_cdf.return_value, dependencies.partial_density_data)
diff --git a/tests/codice/l3/lo/test_codice_lo_l3b_3d_distributions_dependencies.py b/tests/codice/l3/lo/test_codice_lo_l3b_3d_distributions_dependencies.py
index 2857b554..bafcc608 100644
--- a/tests/codice/l3/lo/test_codice_lo_l3b_3d_distributions_dependencies.py
+++ b/tests/codice/l3/lo/test_codice_lo_l3b_3d_distributions_dependencies.py
@@ -1,17 +1,17 @@
 import unittest
-from unittest.mock import patch, sentinel, call
+from unittest.mock import call, patch, sentinel
 
 from imap_data_access.processing_input import (
+    AncillaryInput,
     ProcessingInputCollection,
     ScienceInput,
-    AncillaryInput,
 )
 
 from imap_l3_processing.codice.l3.lo.codice_lo_l3b_3d_distributions_dependencies import (
-    CodiceLoL3b3dDistributionsDependencies,
-    MASS_SPECIES_BIN_LOOKUP_DESCRIPTOR,
-    GEOMETRIC_FACTOR_LOOKUP_DESCRIPTOR,
     EFFICIENCY_FACTOR_LOOKUP_DESCRIPTOR,
+    GEOMETRIC_FACTOR_LOOKUP_DESCRIPTOR,
+    MASS_SPECIES_BIN_LOOKUP_DESCRIPTOR,
+    CodiceLoL3b3dDistributionsDependencies,
 )
 from imap_l3_processing.codice.l3.lo.direct_events.science.energy_lookup import (
     ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR,
@@ -46,12 +46,12 @@ def _test_fetch_dependencies(
         efficiency_factors_lut_name = (
             f"imap_codice_{EFFICIENCY_FACTOR_LOOKUP_DESCRIPTOR}_20100105_v010.csv"
         )
-        energy_per_charge_lut_name = f"imap_codice_{ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR}_20100105_v010.csv"
-
-        unused_science_input = ScienceInput(
-            "imap_codice_l2_lo-direct-events_20100105_v010.cdf"
+        energy_per_charge_lut_name = (
+            f"imap_codice_{ESA_TO_ENERGY_PER_CHARGE_LOOKUP_DESCRIPTOR}_20100105_v010.csv"
         )
 
+        unused_science_input = ScienceInput("imap_codice_l2_lo-direct-events_20100105_v010.cdf")
+
         processing_input_collection = ProcessingInputCollection(
             AncillaryInput(mass_species_lut_name),
             AncillaryInput(geometric_factors_lut_name),
@@ -125,15 +125,11 @@ def test_from_file_paths(
         )
         mock_l3a_direct_event_read_from_cdf.assert_called_once_with(sentinel.l3a_path)
         mock_mass_species_from_csv.assert_called_once_with(sentinel.mass_species_path)
-        mock_geometric_factor_from_csv.assert_called_once_with(
-            sentinel.geometric_factor_path
-        )
+        mock_geometric_factor_from_csv.assert_called_once_with(sentinel.geometric_factor_path)
         mock_efficiency_lut_read_from_csv.assert_called_once_with(
             sentinel.efficiency_factor_path, "some-species"
         )
-        mock_energy_lookup_from_csv.assert_called_once_with(
-            sentinel.energy_per_charge_path
-        )
+        mock_energy_lookup_from_csv.assert_called_once_with(sentinel.energy_per_charge_path)
 
         expected_dependencies = CodiceLoL3b3dDistributionsDependencies(
             l3a_direct_event_data=mock_l3a_direct_event_read_from_cdf.return_value,
diff --git a/tests/codice/l3/lo/test_codice_lo_processor.py b/tests/codice/l3/lo/test_codice_lo_processor.py
index a3a162d6..f6b3972b 100644
--- a/tests/codice/l3/lo/test_codice_lo_processor.py
+++ b/tests/codice/l3/lo/test_codice_lo_processor.py
@@ -1,16 +1,13 @@
 import unittest
 import warnings
 from dataclasses import fields
-from datetime import datetime, timedelta, date
+from datetime import date, datetime, timedelta
 from pathlib import Path
-from unittest.mock import Mock, patch, call, sentinel, MagicMock
+from unittest.mock import MagicMock, Mock, call, patch, sentinel
 
 import numpy as np
 from imap_data_access.processing_input import ProcessingInputCollection
 
-from imap_l3_processing.codice.l3.lo.codice_lo_l3b_3d_distributions_dependencies import (
-    CodiceLoL3b3dDistributionsDependencies,
-)
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_direct_events_dependencies import (
     CodiceLoL3aDirectEventsDependencies,
 )
@@ -20,6 +17,9 @@
 from imap_l3_processing.codice.l3.lo.codice_lo_l3a_ratios_dependencies import (
     CodiceLoL3aRatiosDependencies,
 )
+from imap_l3_processing.codice.l3.lo.codice_lo_l3b_3d_distributions_dependencies import (
+    CodiceLoL3b3dDistributionsDependencies,
+)
 from imap_l3_processing.codice.l3.lo.codice_lo_processor import CodiceLoProcessor
 from imap_l3_processing.codice.l3.lo.direct_events.science.angle_lookup import (
     SpinAngleLookup,
@@ -34,17 +34,17 @@
     GeometricFactorLookup,
 )
 from imap_l3_processing.codice.l3.lo.models import (
-    CodiceLoL3aPartialDensityDataProduct,
+    CODICE_LO_L2_NUM_PRIORITIES,
+    CodiceLoL1aNSWPriorityRates,
+    CodiceLoL1aSWPriorityRates,
     CodiceLoL2DirectEventData,
-    CodiceLoL3aDirectEventDataProduct,
     CodiceLoL2SWSpeciesData,
-    CodiceLoL1aSWPriorityRates,
-    CodiceLoL1aNSWPriorityRates,
-    CodiceLoPartialDensityData,
+    CodiceLoL3aDirectEventDataProduct,
+    CodiceLoL3aPartialDensityDataProduct,
     CodiceLoL3aRatiosDataProduct,
-    CODICE_LO_L2_NUM_PRIORITIES,
-    CodiceLoL3ChargeStateDistributionsDataProduct,
     CodiceLoL3b3dDistributionDataProduct,
+    CodiceLoL3ChargeStateDistributionsDataProduct,
+    CodiceLoPartialDensityData,
 )
 from imap_l3_processing.codice.l3.lo.sectored_intensities.science.mass_per_charge_lookup import (
     MassPerChargeLookup,
@@ -52,9 +52,9 @@
 from imap_l3_processing.models import InputMetadata
 from imap_l3_processing.processor import Processor
 from tests.test_helpers import (
+    NumpyArrayMatcher,
     create_dataclass_mock,
     get_test_data_path,
-    NumpyArrayMatcher,
 )
 
 MODULE = "imap_l3_processing.codice.l3.lo.codice_lo_processor"
@@ -91,9 +91,7 @@ def test_process_partial_densities(
         )
         mock_spiceypy.ktotal.return_value = 0
 
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         product = processor.process()
 
         mock_fetch_dependencies.assert_called_once_with(processor.dependencies)
@@ -101,9 +99,7 @@ def test_process_partial_densities(
             mock_fetch_dependencies.return_value
         )
 
-        mock_save_data.assert_called_once_with(
-            mock_process_l3a_partial_densities.return_value
-        )
+        mock_save_data.assert_called_once_with(mock_process_l3a_partial_densities.return_value)
 
         self.assertEqual(
             ["parent_file_1", "parent_file_2"],
@@ -134,21 +130,15 @@ def test_process_ratios(
         )
         mock_spiceypy.ktotal.return_value = 0
 
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         product = processor.process()
 
         mock_fetch_dependencies.assert_called_once_with(processor.dependencies)
-        mock_process_l3a_ratios.assert_called_once_with(
-            mock_fetch_dependencies.return_value
-        )
+        mock_process_l3a_ratios.assert_called_once_with(mock_fetch_dependencies.return_value)
 
         mock_save_data.assert_called_once_with(mock_process_l3a_ratios.return_value)
 
-        self.assertEqual(
-            ["parent_file_1"], mock_process_l3a_ratios.return_value.parent_file_names
-        )
+        self.assertEqual(["parent_file_1"], mock_process_l3a_ratios.return_value.parent_file_names)
         self.assertEqual([mock_save_data.return_value], product)
 
     @patch(f"{MODULE}.CodiceLoL3aRatiosDependencies.fetch_dependencies")
@@ -174,15 +164,11 @@ def test_process_abundances(
         )
         mock_spiceypy.ktotal.return_value = 0
 
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         product = processor.process()
 
         mock_fetch_dependencies.assert_called_once_with(processor.dependencies)
-        mock_process_l3a_abundances.assert_called_once_with(
-            mock_fetch_dependencies.return_value
-        )
+        mock_process_l3a_abundances.assert_called_once_with(mock_fetch_dependencies.return_value)
 
         mock_save_data.assert_called_once_with(mock_process_l3a_abundances.return_value)
 
@@ -231,12 +217,10 @@ def test_process_ratios_calculate_abundance_ratios(self):
 
         dependency = CodiceLoL3aRatiosDependencies(data)
         input_metadata = Mock()
-        processor = CodiceLoProcessor(
-            dependencies=Mock(), input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=Mock(), input_metadata=input_metadata)
 
-        ratios_data_product: CodiceLoL3aRatiosDataProduct = (
-            processor.process_l3a_ratios(dependency)
+        ratios_data_product: CodiceLoL3aRatiosDataProduct = processor.process_l3a_ratios(
+            dependency
         )
         self.assertEqual(input_metadata, ratios_data_product.input_metadata)
         np.testing.assert_array_equal(
@@ -281,9 +265,7 @@ def test_process_ratios_calculate_abundance_ratios(self):
     def test_process_ratios_calculate_abundance_ratios_using_safe_divide(self):
         now = datetime.now()
         data = CodiceLoPartialDensityData(
-            epoch=np.array(
-                [now, now + timedelta(minutes=4), now + timedelta(minutes=8)]
-            ),
+            epoch=np.array([now, now + timedelta(minutes=4), now + timedelta(minutes=8)]),
             epoch_delta=np.array([120_000_000_000, 120_000_000_000, 120_000_000_000]),
             fe_hiq_partial_density=np.array([0, 0, 0]),
             fe_loq_partial_density=np.array([0, 0, 0]),
@@ -303,30 +285,18 @@ def test_process_ratios_calculate_abundance_ratios_using_safe_divide(self):
 
         dependency = CodiceLoL3aRatiosDependencies(data)
         input_metadata = Mock()
-        processor = CodiceLoProcessor(
-            dependencies=Mock(), input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=Mock(), input_metadata=input_metadata)
 
         with warnings.catch_warnings(record=True) as w:
             ratios_data_product = processor.process_l3a_ratios(dependency)
         self.assertEqual(0, len(w))
 
         self.assertEqual(input_metadata, ratios_data_product.input_metadata)
-        np.testing.assert_array_equal(
-            ratios_data_product.epoch, [now + timedelta(minutes=4)]
-        )
-        np.testing.assert_array_equal(
-            ratios_data_product.epoch_delta, [360_000_000_000]
-        )
-        np.testing.assert_array_almost_equal(
-            ratios_data_product.fe_to_o_ratio, np.array([np.nan])
-        )
-        np.testing.assert_array_almost_equal(
-            ratios_data_product.mg_to_o_ratio, np.array([np.nan])
-        )
-        np.testing.assert_array_almost_equal(
-            ratios_data_product.c_to_o_ratio, np.array([np.nan])
-        )
+        np.testing.assert_array_equal(ratios_data_product.epoch, [now + timedelta(minutes=4)])
+        np.testing.assert_array_equal(ratios_data_product.epoch_delta, [360_000_000_000])
+        np.testing.assert_array_almost_equal(ratios_data_product.fe_to_o_ratio, np.array([np.nan]))
+        np.testing.assert_array_almost_equal(ratios_data_product.mg_to_o_ratio, np.array([np.nan]))
+        np.testing.assert_array_almost_equal(ratios_data_product.c_to_o_ratio, np.array([np.nan]))
         np.testing.assert_array_almost_equal(
             ratios_data_product.c6_to_c4_ratio, np.array([np.nan])
         )
@@ -387,13 +357,9 @@ def test_process_abundances_calculates_abundance_ratios(self):
 
         dependency = CodiceLoL3aRatiosDependencies(data)
         input_metadata = Mock()
-        processor = CodiceLoProcessor(
-            dependencies=Mock(), input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=Mock(), input_metadata=input_metadata)
 
-        abundances_data_product = processor.process_l3a_charge_state_distributions(
-            dependency
-        )
+        abundances_data_product = processor.process_l3a_charge_state_distributions(dependency)
         self.assertIsInstance(
             abundances_data_product, CodiceLoL3ChargeStateDistributionsDataProduct
         )
@@ -458,14 +424,10 @@ def test_process_abundances_uses_safe_divide(self):
         )
         dependency = CodiceLoL3aRatiosDependencies(data)
         input_metadata = Mock()
-        processor = CodiceLoProcessor(
-            dependencies=Mock(), input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=Mock(), input_metadata=input_metadata)
 
         with warnings.catch_warnings(record=True) as w:
-            abundances_data_product = processor.process_l3a_charge_state_distributions(
-                dependency
-            )
+            abundances_data_product = processor.process_l3a_charge_state_distributions(dependency)
         self.assertEqual(0, len(w))
 
         self.assertIsInstance(
@@ -473,9 +435,7 @@ def test_process_abundances_uses_safe_divide(self):
         )
         self.assertEqual(input_metadata, abundances_data_product.input_metadata)
         np.testing.assert_array_equal(abundances_data_product.epoch, [now])
-        np.testing.assert_array_equal(
-            abundances_data_product.epoch_delta, [120_000_000_000]
-        )
+        np.testing.assert_array_equal(abundances_data_product.epoch_delta, [120_000_000_000])
 
         np.testing.assert_array_almost_equal(
             abundances_data_product.oxygen_charge_state_distribution,
@@ -512,24 +472,18 @@ def test_process_direct_events(
         )
         mock_spiceypy.ktotal.return_value = 0
 
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         product = processor.process()
 
         mock_fetch_dependencies.assert_called_once_with(processor.dependencies)
-        mock_process_direct_event.assert_called_once_with(
-            mock_fetch_dependencies.return_value
-        )
+        mock_process_direct_event.assert_called_once_with(mock_fetch_dependencies.return_value)
 
         mock_save_data.assert_called_once_with(mock_process_direct_event.return_value)
 
         self.assertEqual([mock_save_data.return_value], product)
 
     def test_raises_exception_on_non_l3_input_metadata(self):
-        input_metadata = InputMetadata(
-            "codice", "L2a", Mock(), Mock(), "v02", "bad-descriptor"
-        )
+        input_metadata = InputMetadata("codice", "L2a", Mock(), Mock(), "v02", "bad-descriptor")
 
         processor = CodiceLoProcessor(Mock(), input_metadata)
         with self.assertRaises(NotImplementedError) as context:
@@ -550,13 +504,9 @@ def test_process_l3a_partial_densities(self, mock_calculate_partial_densities):
             "v02",
             descriptor="lo-partial-densities",
         )
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
 
-        epochs = np.array(
-            [datetime(2025, 1, 1), datetime(2025, 1, 2), datetime(2025, 1, 3)]
-        )
+        epochs = np.array([datetime(2025, 1, 1), datetime(2025, 1, 2), datetime(2025, 1, 3)])
         num_species = 14
 
         codice_lo_l2_data = CodiceLoL2SWSpeciesData(
@@ -600,9 +550,7 @@ def test_process_l3a_partial_densities(self, mock_calculate_partial_densities):
         codice_lo_dependencies = CodiceLoL3aPartialDensitiesDependencies(
             codice_lo_l2_data, mass_per_charge_lookup
         )
-        result_data_product = processor.process_l3a_partial_densities(
-            codice_lo_dependencies
-        )
+        result_data_product = processor.process_l3a_partial_densities(codice_lo_dependencies)
 
         self.assertEqual(num_species, mock_calculate_partial_densities.call_count)
 
@@ -687,14 +635,8 @@ def test_process_l3a_partial_densities(self, mock_calculate_partial_densities):
         self.assertIsInstance(result_data, CodiceLoPartialDensityData)
 
         np.testing.assert_array_equal(result_data.epoch, codice_lo_l2_data.epoch)
-        np.testing.assert_array_equal(
-            result_data.epoch_delta, codice_lo_l2_data.epoch_delta_plus
-        )
-        (
-            self.assertEqual(
-                sentinel.hplus_partial_density, result_data.hplus_partial_density
-            ),
-        )
+        np.testing.assert_array_equal(result_data.epoch_delta, codice_lo_l2_data.epoch_delta_plus)
+        (self.assertEqual(sentinel.hplus_partial_density, result_data.hplus_partial_density),)
         (
             self.assertEqual(
                 sentinel.heplusplus_partial_density,
@@ -753,9 +695,7 @@ def test_process_l3a_direct_events(
         sw_priority_rates.p2_heplusplus = rng.random(priority_counts_variable_shape)
         sw_priority_rates.p3_heavies = rng.random(priority_counts_variable_shape)
         sw_priority_rates.p4_dcrs = rng.random(priority_counts_variable_shape)
-        sw_priority_rates.half_spin_per_esa_step = rng.random(
-            (num_epochs, num_energy_bins)
-        )
+        sw_priority_rates.half_spin_per_esa_step = rng.random((num_epochs, num_energy_bins))
         sw_priority_rates.rgfo_spin_sector = rng.random(num_epochs)
         sw_priority_rates.rgfo_esa_step = rng.random(num_epochs)
         sw_priority_rates.nso_spin_sector = rng.random(num_epochs)
@@ -763,35 +703,27 @@ def test_process_l3a_direct_events(
         sw_priority_rates.esa_step = np.arange(128)
         sw_priority_rates.rgfo_half_spin = rng.random(num_epochs)
         sw_priority_rates.nso_half_spin = rng.random(num_epochs)
-        sw_priority_rates.acquisition_time_per_esa_step = rng.random(
-            (num_epochs, num_energy_bins)
-        )
+        sw_priority_rates.acquisition_time_per_esa_step = rng.random((num_epochs, num_energy_bins))
 
         nsw_priority_rates = create_dataclass_mock(CodiceLoL1aNSWPriorityRates)
         nsw_priority_rates.epoch = epochs
         nsw_priority_rates.p5_heavies = rng.random(priority_counts_variable_shape)
-        nsw_priority_rates.p6_hplus_heplusplus = rng.random(
-            priority_counts_variable_shape
-        )
+        nsw_priority_rates.p6_hplus_heplusplus = rng.random(priority_counts_variable_shape)
 
-        mass_per_charge = rng.random(
-            (num_epochs, CODICE_LO_L2_NUM_PRIORITIES, event_buffer_size)
-        )
+        mass_per_charge = rng.random((num_epochs, CODICE_LO_L2_NUM_PRIORITIES, event_buffer_size))
         mock_calculate_mass_per_charge.return_value = mass_per_charge
         mass = rng.random((num_epochs, CODICE_LO_L2_NUM_PRIORITIES, event_buffer_size))
         mock_calculate_mass.return_value = mass
 
         codice_l2_variables = {
-            f.name: rng.random(
-                (num_epochs, CODICE_LO_L2_NUM_PRIORITIES, event_buffer_size)
-            )
+            f.name: rng.random((num_epochs, CODICE_LO_L2_NUM_PRIORITIES, event_buffer_size))
             for f in fields(CodiceLoL2DirectEventData)
         }
 
         codice_l2_variables["epoch"] = epochs
         codice_l2_variables["spin_angle"] *= 360
-        codice_l2_variables["data_quality"] = rng.random((num_epochs))
-        codice_l2_variables["num_events"] = rng.random((num_epochs))
+        codice_l2_variables["data_quality"] = rng.random(num_epochs)
+        codice_l2_variables["num_events"] = rng.random(num_epochs)
 
         expected_energy_per_charge = codice_l2_variables["energy_per_charge"]
         expected_apd_energy = codice_l2_variables["apd_energy"]
@@ -835,17 +767,13 @@ def test_process_l3a_direct_events(
         input_metadata = InputMetadata(
             "codice", "l3a", Mock(spec=datetime), Mock(spec=datetime), "v02"
         )
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         l3a_direct_event_data_product = processor.process_l3a_direct_event_data_product(
             dependencies
         )
 
         self.assertEqual(1, mock_calculate_mass.call_count)
-        np.testing.assert_equal(
-            mock_calculate_mass.call_args.args[0], expected_apd_energy
-        )
+        np.testing.assert_equal(mock_calculate_mass.call_args.args[0], expected_apd_energy)
         np.testing.assert_equal(mock_calculate_mass.call_args.args[1], expected_tof)
         np.testing.assert_equal(
             mock_calculate_mass.call_args.args[2], dependencies.mass_coefficient_lookup
@@ -855,33 +783,17 @@ def test_process_l3a_direct_events(
         np.testing.assert_equal(
             mock_calculate_mass_per_charge.call_args.args[0], expected_energy_per_charge
         )
-        np.testing.assert_equal(
-            mock_calculate_mass_per_charge.call_args.args[1], expected_tof
-        )
+        np.testing.assert_equal(mock_calculate_mass_per_charge.call_args.args[1], expected_tof)
 
         self.assertEqual(1, mock_calculate_normalization_factor.call_count)
-        actual_stacked_priorities = mock_calculate_normalization_factor.call_args.args[
-            0
-        ]
-
-        np.testing.assert_equal(
-            actual_stacked_priorities[:, 0], sw_priority_rates.p0_tcrs
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[:, 1], sw_priority_rates.p1_hplus
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[:, 2], sw_priority_rates.p2_heplusplus
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[:, 3], sw_priority_rates.p3_heavies
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[:, 4], sw_priority_rates.p4_dcrs
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[:, 5], nsw_priority_rates.p5_heavies
-        )
+        actual_stacked_priorities = mock_calculate_normalization_factor.call_args.args[0]
+
+        np.testing.assert_equal(actual_stacked_priorities[:, 0], sw_priority_rates.p0_tcrs)
+        np.testing.assert_equal(actual_stacked_priorities[:, 1], sw_priority_rates.p1_hplus)
+        np.testing.assert_equal(actual_stacked_priorities[:, 2], sw_priority_rates.p2_heplusplus)
+        np.testing.assert_equal(actual_stacked_priorities[:, 3], sw_priority_rates.p3_heavies)
+        np.testing.assert_equal(actual_stacked_priorities[:, 4], sw_priority_rates.p4_dcrs)
+        np.testing.assert_equal(actual_stacked_priorities[:, 5], nsw_priority_rates.p5_heavies)
         np.testing.assert_equal(
             actual_stacked_priorities[:, 6], nsw_priority_rates.p6_hplus_heplusplus
         )
@@ -911,9 +823,7 @@ def test_process_l3a_direct_events(
             mock_lookup_normalization_per_event.call_args.args[3], expected_spin_sector
         )
 
-        self.assertIsInstance(
-            l3a_direct_event_data_product, CodiceLoL3aDirectEventDataProduct
-        )
+        self.assertIsInstance(l3a_direct_event_data_product, CodiceLoL3aDirectEventDataProduct)
         self.assertEqual(input_metadata, l3a_direct_event_data_product.input_metadata)
 
         np.testing.assert_array_equal(l3a_direct_event_data_product.epoch, epochs)
@@ -942,18 +852,12 @@ def test_process_l3a_direct_events(
         np.testing.assert_array_equal(
             expected_apd_energy, l3a_direct_event_data_product.apd_energy
         )
-        np.testing.assert_array_equal(
-            expected_apd_gain, l3a_direct_event_data_product.gain
-        )
-        np.testing.assert_array_equal(
-            expected_apd_id, l3a_direct_event_data_product.apd_id
-        )
+        np.testing.assert_array_equal(expected_apd_gain, l3a_direct_event_data_product.gain)
+        np.testing.assert_array_equal(expected_apd_id, l3a_direct_event_data_product.apd_id)
         np.testing.assert_array_equal(
             expected_data_quality, l3a_direct_event_data_product.data_quality
         )
-        np.testing.assert_array_equal(
-            expected_elevation, l3a_direct_event_data_product.elevation
-        )
+        np.testing.assert_array_equal(expected_elevation, l3a_direct_event_data_product.elevation)
         np.testing.assert_array_equal(
             expected_energy_per_charge, l3a_direct_event_data_product.energy_per_charge
         )
@@ -966,9 +870,7 @@ def test_process_l3a_direct_events(
         np.testing.assert_array_equal(
             expected_num_events, l3a_direct_event_data_product.num_events
         )
-        np.testing.assert_array_equal(
-            expected_position, l3a_direct_event_data_product.position
-        )
+        np.testing.assert_array_equal(expected_position, l3a_direct_event_data_product.position)
         np.testing.assert_array_equal(
             expected_spin_angle, l3a_direct_event_data_product.spin_angle
         )
@@ -1087,9 +989,7 @@ def test_process_l3a_direct_events_aligns_priority_to_direct_event_epochs_when_m
         sw_priority_rates.p2_heplusplus = rng.random(sw_priority_counts_shape)
         sw_priority_rates.p3_heavies = rng.random(sw_priority_counts_shape)
         sw_priority_rates.p4_dcrs = rng.random(sw_priority_counts_shape)
-        sw_priority_rates.half_spin_per_esa_step = rng.random(
-            (num_sw_epochs, num_energy_bins)
-        )
+        sw_priority_rates.half_spin_per_esa_step = rng.random((num_sw_epochs, num_energy_bins))
         sw_priority_rates.rgfo_spin_sector = rng.random(num_sw_epochs)
         sw_priority_rates.rgfo_esa_step = rng.random(num_sw_epochs)
         sw_priority_rates.nso_spin_sector = rng.random(num_sw_epochs)
@@ -1166,15 +1066,11 @@ def test_process_l3a_direct_events_aligns_priority_to_direct_event_epochs_when_m
         input_metadata = InputMetadata(
             "codice", "l3a", Mock(spec=datetime), Mock(spec=datetime), "v02"
         )
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         result = processor.process_l3a_direct_event_data_product(dependencies)
 
         self.assertEqual(1, mock_calculate_normalization_factor.call_count)
-        actual_stacked_priorities = mock_calculate_normalization_factor.call_args.args[
-            0
-        ]
+        actual_stacked_priorities = mock_calculate_normalization_factor.call_args.args[0]
         self.assertEqual(
             (
                 num_direct_event_epochs,
@@ -1185,81 +1081,43 @@ def test_process_l3a_direct_events_aligns_priority_to_direct_event_epochs_when_m
             actual_stacked_priorities.shape,
         )
 
-        np.testing.assert_equal(
-            actual_stacked_priorities[0, 0], sw_priority_rates.p0_tcrs[0]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[0, 1], sw_priority_rates.p1_hplus[0]
-        )
+        np.testing.assert_equal(actual_stacked_priorities[0, 0], sw_priority_rates.p0_tcrs[0])
+        np.testing.assert_equal(actual_stacked_priorities[0, 1], sw_priority_rates.p1_hplus[0])
         np.testing.assert_equal(
             actual_stacked_priorities[0, 2], sw_priority_rates.p2_heplusplus[0]
         )
-        np.testing.assert_equal(
-            actual_stacked_priorities[0, 3], sw_priority_rates.p3_heavies[0]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[0, 4], sw_priority_rates.p4_dcrs[0]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[0, 5], nsw_priority_rates.p5_heavies[0]
-        )
+        np.testing.assert_equal(actual_stacked_priorities[0, 3], sw_priority_rates.p3_heavies[0])
+        np.testing.assert_equal(actual_stacked_priorities[0, 4], sw_priority_rates.p4_dcrs[0])
+        np.testing.assert_equal(actual_stacked_priorities[0, 5], nsw_priority_rates.p5_heavies[0])
         np.testing.assert_equal(
             actual_stacked_priorities[0, 6], nsw_priority_rates.p6_hplus_heplusplus[0]
         )
 
-        expected_sw_nan_block = np.full(
-            (5, num_energy_bins, priority_l1_spin_sectors), np.nan
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[1, 0:5], expected_sw_nan_block
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[1, 5], nsw_priority_rates.p5_heavies[1]
-        )
+        expected_sw_nan_block = np.full((5, num_energy_bins, priority_l1_spin_sectors), np.nan)
+        np.testing.assert_equal(actual_stacked_priorities[1, 0:5], expected_sw_nan_block)
+        np.testing.assert_equal(actual_stacked_priorities[1, 5], nsw_priority_rates.p5_heavies[1])
         np.testing.assert_equal(
             actual_stacked_priorities[1, 6], nsw_priority_rates.p6_hplus_heplusplus[1]
         )
 
-        np.testing.assert_equal(
-            actual_stacked_priorities[2, 0], sw_priority_rates.p0_tcrs[1]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[2, 1], sw_priority_rates.p1_hplus[1]
-        )
+        np.testing.assert_equal(actual_stacked_priorities[2, 0], sw_priority_rates.p0_tcrs[1])
+        np.testing.assert_equal(actual_stacked_priorities[2, 1], sw_priority_rates.p1_hplus[1])
         np.testing.assert_equal(
             actual_stacked_priorities[2, 2], sw_priority_rates.p2_heplusplus[1]
         )
-        np.testing.assert_equal(
-            actual_stacked_priorities[2, 3], sw_priority_rates.p3_heavies[1]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[2, 4], sw_priority_rates.p4_dcrs[1]
-        )
-        expected_nsw_nan_block = np.full(
-            (2, num_energy_bins, priority_l1_spin_sectors), np.nan
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[2, 5:7], expected_nsw_nan_block
-        )
+        np.testing.assert_equal(actual_stacked_priorities[2, 3], sw_priority_rates.p3_heavies[1])
+        np.testing.assert_equal(actual_stacked_priorities[2, 4], sw_priority_rates.p4_dcrs[1])
+        expected_nsw_nan_block = np.full((2, num_energy_bins, priority_l1_spin_sectors), np.nan)
+        np.testing.assert_equal(actual_stacked_priorities[2, 5:7], expected_nsw_nan_block)
 
-        np.testing.assert_equal(
-            actual_stacked_priorities[3, 0], sw_priority_rates.p0_tcrs[2]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[3, 1], sw_priority_rates.p1_hplus[2]
-        )
+        np.testing.assert_equal(actual_stacked_priorities[3, 0], sw_priority_rates.p0_tcrs[2])
+        np.testing.assert_equal(actual_stacked_priorities[3, 1], sw_priority_rates.p1_hplus[2])
         np.testing.assert_equal(
             actual_stacked_priorities[3, 2], sw_priority_rates.p2_heplusplus[2]
         )
-        np.testing.assert_equal(
-            actual_stacked_priorities[3, 3], sw_priority_rates.p3_heavies[2]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[3, 4], sw_priority_rates.p4_dcrs[2]
-        )
-        np.testing.assert_equal(
-            actual_stacked_priorities[3, 5], nsw_priority_rates.p5_heavies[2]
-        )
+        np.testing.assert_equal(actual_stacked_priorities[3, 3], sw_priority_rates.p3_heavies[2])
+        np.testing.assert_equal(actual_stacked_priorities[3, 4], sw_priority_rates.p4_dcrs[2])
+        np.testing.assert_equal(actual_stacked_priorities[3, 5], nsw_priority_rates.p5_heavies[2])
         np.testing.assert_equal(
             actual_stacked_priorities[3, 6], nsw_priority_rates.p6_hplus_heplusplus[2]
         )
@@ -1279,9 +1137,7 @@ def test_process_l3a_direct_events_aligns_priority_to_direct_event_epochs_when_m
             actual_normalization_per_event[2, 5:7, :], np.zeros((2, event_buffer_size))
         )
 
-        sentinel_row = np.full(
-            event_buffer_size, sentinel_normalization_per_event_value
-        )
+        sentinel_row = np.full(event_buffer_size, sentinel_normalization_per_event_value)
         np.testing.assert_array_equal(
             actual_normalization_per_event[0],
             np.full(
@@ -1296,27 +1152,13 @@ def test_process_l3a_direct_events_aligns_priority_to_direct_event_epochs_when_m
                 sentinel_normalization_per_event_value,
             ),
         )
-        np.testing.assert_array_equal(
-            actual_normalization_per_event[1, 5], sentinel_row
-        )
-        np.testing.assert_array_equal(
-            actual_normalization_per_event[1, 6], sentinel_row
-        )
-        np.testing.assert_array_equal(
-            actual_normalization_per_event[2, 0], sentinel_row
-        )
-        np.testing.assert_array_equal(
-            actual_normalization_per_event[2, 1], sentinel_row
-        )
-        np.testing.assert_array_equal(
-            actual_normalization_per_event[2, 2], sentinel_row
-        )
-        np.testing.assert_array_equal(
-            actual_normalization_per_event[2, 3], sentinel_row
-        )
-        np.testing.assert_array_equal(
-            actual_normalization_per_event[2, 4], sentinel_row
-        )
+        np.testing.assert_array_equal(actual_normalization_per_event[1, 5], sentinel_row)
+        np.testing.assert_array_equal(actual_normalization_per_event[1, 6], sentinel_row)
+        np.testing.assert_array_equal(actual_normalization_per_event[2, 0], sentinel_row)
+        np.testing.assert_array_equal(actual_normalization_per_event[2, 1], sentinel_row)
+        np.testing.assert_array_equal(actual_normalization_per_event[2, 2], sentinel_row)
+        np.testing.assert_array_equal(actual_normalization_per_event[2, 3], sentinel_row)
+        np.testing.assert_array_equal(actual_normalization_per_event[2, 4], sentinel_row)
 
         np.testing.assert_array_equal(
             result.normalization, np.flip(expected_normalization, axis=2)
@@ -1374,9 +1216,7 @@ def test_process_l3a_direct_events_handles_masked_priority_counts(
         sw_mask[0, 0, 0] = True
         sw_priority_rates = create_dataclass_mock(CodiceLoL1aSWPriorityRates)
         sw_priority_rates.epoch = sw_priority_epochs
-        sw_priority_rates.p0_tcrs = np.ma.array(
-            rng.random(sw_priority_counts_shape), mask=sw_mask
-        )
+        sw_priority_rates.p0_tcrs = np.ma.array(rng.random(sw_priority_counts_shape), mask=sw_mask)
         sw_priority_rates.p1_hplus = np.ma.array(
             rng.random(sw_priority_counts_shape), mask=sw_mask
         )
@@ -1386,12 +1226,8 @@ def test_process_l3a_direct_events_handles_masked_priority_counts(
         sw_priority_rates.p3_heavies = np.ma.array(
             rng.random(sw_priority_counts_shape), mask=sw_mask
         )
-        sw_priority_rates.p4_dcrs = np.ma.array(
-            rng.random(sw_priority_counts_shape), mask=sw_mask
-        )
-        sw_priority_rates.half_spin_per_esa_step = rng.random(
-            (num_sw_epochs, num_energy_bins)
-        )
+        sw_priority_rates.p4_dcrs = np.ma.array(rng.random(sw_priority_counts_shape), mask=sw_mask)
+        sw_priority_rates.half_spin_per_esa_step = rng.random((num_sw_epochs, num_energy_bins))
         sw_priority_rates.rgfo_spin_sector = rng.random(num_sw_epochs)
         sw_priority_rates.rgfo_esa_step = rng.random(num_sw_epochs)
         sw_priority_rates.nso_spin_sector = rng.random(num_sw_epochs)
@@ -1474,9 +1310,7 @@ def test_process_l3a_direct_events_handles_masked_priority_counts(
         input_metadata = InputMetadata(
             "codice", "l3a", Mock(spec=datetime), Mock(spec=datetime), "v02"
         )
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         result = processor.process_l3a_direct_event_data_product(dependencies)
         self.assertIsInstance(result, CodiceLoL3aDirectEventDataProduct)
         self.assertEqual(
@@ -1489,9 +1323,7 @@ def test_process_l3a_direct_events_handles_masked_priority_counts(
         )
 
         self.assertEqual(1, mock_calculate_normalization_factor.call_count)
-        actual_stacked_priorities = mock_calculate_normalization_factor.call_args.args[
-            0
-        ]
+        actual_stacked_priorities = mock_calculate_normalization_factor.call_args.args[0]
         self.assertEqual(
             (
                 num_direct_event_epochs,
@@ -1502,9 +1334,7 @@ def test_process_l3a_direct_events_handles_masked_priority_counts(
             actual_stacked_priorities.shape,
         )
 
-        np.testing.assert_equal(
-            actual_stacked_priorities[0, :, 0, 0], np.full(7, np.nan)
-        )
+        np.testing.assert_equal(actual_stacked_priorities[0, :, 0, 0], np.full(7, np.nan))
 
     @patch(f"{MODULE}.SpinAngleLookup")
     @patch(f"{MODULE}.lookup_normalization_per_event", autospec=True)
@@ -1562,9 +1392,7 @@ def test_process_l3a_direct_events_aligns_passthrough_vars_to_direct_event_epoch
         sw_priority_rates.p2_heplusplus = rng.random(sw_priority_counts_shape)
         sw_priority_rates.p3_heavies = rng.random(sw_priority_counts_shape)
         sw_priority_rates.p4_dcrs = rng.random(sw_priority_counts_shape)
-        sw_priority_rates.half_spin_per_esa_step = rng.random(
-            (num_sw_epochs, num_energy_bins)
-        )
+        sw_priority_rates.half_spin_per_esa_step = rng.random((num_sw_epochs, num_energy_bins))
         sw_priority_rates.rgfo_spin_sector = rng.random(num_sw_epochs)
         sw_priority_rates.rgfo_esa_step = rng.random(num_sw_epochs)
         sw_priority_rates.nso_spin_sector = rng.random(num_sw_epochs)
@@ -1641,9 +1469,7 @@ def test_process_l3a_direct_events_aligns_passthrough_vars_to_direct_event_epoch
         input_metadata = InputMetadata(
             "codice", "l3a", Mock(spec=datetime), Mock(spec=datetime), "v02"
         )
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         result = processor.process_l3a_direct_event_data_product(dependencies)
 
         variables_to_compare = [
@@ -1744,21 +1570,15 @@ def test_process_l3b_3d_distributions(
         ]
 
         counts_3d_distribution = mock_rebin.return_value
-        counts_3d_distribution.__getitem__.return_value = (
-            sentinel.counts_for_species_by_priority
-        )
+        counts_3d_distribution.__getitem__.return_value = sentinel.counts_for_species_by_priority
 
-        processor = CodiceLoProcessor(
-            dependencies=Mock(), input_metadata=input_metadata
-        )
-        l3b_3d_distribution_data_product = (
-            processor.process_l3b_3d_distribution_product(dependencies)
+        processor = CodiceLoProcessor(dependencies=Mock(), input_metadata=input_metadata)
+        l3b_3d_distribution_data_product = processor.process_l3b_3d_distribution_product(
+            dependencies
         )
 
         mock_elevation_angle_lookup_class.assert_called_once()
-        counts_3d_distribution.__getitem__.assert_called_once_with(
-            sentinel.species_index
-        )
+        counts_3d_distribution.__getitem__.assert_called_once_with(sentinel.species_index)
         mock_rebin.assert_called_once_with(
             direct_event_data=mock_l3a_direct_event_data,
             mass_species_bin_lookup=dependencies.mass_species_bin_lookup,
@@ -1825,12 +1645,8 @@ def test_process_l3b_3d_distributions(
         self.assertIsInstance(
             l3b_3d_distribution_data_product, CodiceLoL3b3dDistributionDataProduct
         )
-        self.assertEqual(
-            processor.input_metadata, l3b_3d_distribution_data_product.input_metadata
-        )
-        self.assertEqual(
-            mock_l3a_direct_event_data.epoch, l3b_3d_distribution_data_product.epoch
-        )
+        self.assertEqual(processor.input_metadata, l3b_3d_distribution_data_product.input_metadata)
+        self.assertEqual(mock_l3a_direct_event_data.epoch, l3b_3d_distribution_data_product.epoch)
         self.assertEqual(
             mock_l3a_direct_event_data.epoch_delta,
             l3b_3d_distribution_data_product.epoch_delta,
@@ -1924,9 +1740,7 @@ def _test_process_3d_distributions_save(
         )
         mock_spiceypy.ktotal.return_value = 0
 
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
         product = processor.process()
 
         mock_fetch_dependencies.assert_called_once_with(processor.dependencies, species)
@@ -1977,14 +1791,9 @@ def test_process_l3a_direct_events_all_fill_integration(self):
             ),
         )
 
-        processor = CodiceLoProcessor(
-            dependencies=input_collection, input_metadata=input_metadata
-        )
+        processor = CodiceLoProcessor(dependencies=input_collection, input_metadata=input_metadata)
 
-        try:
-            processor.process_l3a_direct_event_data_product(dependencies)
-        except Exception as e:
-            self.fail(e)
+        processor.process_l3a_direct_event_data_product(dependencies)
 
 
 if __name__ == "__main__":
diff --git a/tests/codice/l3/lo/test_models.py b/tests/codice/l3/lo/test_models.py
index 0118d1b6..efc63c00 100644
--- a/tests/codice/l3/lo/test_models.py
+++ b/tests/codice/l3/lo/test_models.py
@@ -9,34 +9,34 @@
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.codice.l3.lo.models import (
-    CodiceLoL2SWSpeciesData,
-    CodiceLoL3aPartialDensityDataProduct,
-    CodiceLoL2DirectEventData,
-    CodiceLoL3aDirectEventDataProduct,
-    CodiceLoL1aSWPriorityRates,
-    CodiceLoL1aNSWPriorityRates,
     CODICE_LO_L2_NUM_PRIORITIES,
-    CodiceLoL3aRatiosDataProduct,
-    CodiceLoPartialDensityData,
-    CodiceLoL3ChargeStateDistributionsDataProduct,
-    CodiceLoDirectEventData,
-    EPOCH_VAR_NAME,
-    EPOCH_DELTA_VAR_NAME,
-    ELEVATION_VAR_NAME,
-    ENERGY_VAR_NAME,
+    ELEVATION_ANGLE_LABEL_VAR_NAME,
     ELEVATION_DELTA_VAR_NAME,
-    CodiceLoL3b3dDistributionDataProduct,
-    ENERGY_DELTA_PLUS_VAR_NAME,
+    ELEVATION_VAR_NAME,
     ENERGY_DELTA_MINUS_VAR_NAME,
-    ELEVATION_ANGLE_LABEL_VAR_NAME,
+    ENERGY_DELTA_PLUS_VAR_NAME,
     ENERGY_LABEL_VAR_NAME,
-    SPIN_ANGLE_DELTA_VAR_NAME,
-    SPIN_ANGLE_VAR_NAME,
-    SPIN_ANGLE_LABEL_VAR_NAME,
+    ENERGY_VAR_NAME,
+    EPOCH_DELTA_VAR_NAME,
+    EPOCH_VAR_NAME,
+    HALF_SPIN_PER_ESA_STEP_VAR_NAME,
     RGFO_ESA_STEP_VAR_NAME,
-    RGFO_SPIN_SECTOR_VAR_NAME,
     RGFO_HALF_SPIN_VAR_NAME,
-    HALF_SPIN_PER_ESA_STEP_VAR_NAME,
+    RGFO_SPIN_SECTOR_VAR_NAME,
+    SPIN_ANGLE_DELTA_VAR_NAME,
+    SPIN_ANGLE_LABEL_VAR_NAME,
+    SPIN_ANGLE_VAR_NAME,
+    CodiceLoDirectEventData,
+    CodiceLoL1aNSWPriorityRates,
+    CodiceLoL1aSWPriorityRates,
+    CodiceLoL2DirectEventData,
+    CodiceLoL2SWSpeciesData,
+    CodiceLoL3aDirectEventDataProduct,
+    CodiceLoL3aPartialDensityDataProduct,
+    CodiceLoL3aRatiosDataProduct,
+    CodiceLoL3b3dDistributionDataProduct,
+    CodiceLoL3ChargeStateDistributionsDataProduct,
+    CodiceLoPartialDensityData,
 )
 from imap_l3_processing.models import InputMetadata, VersionMap
 from imap_l3_processing.utils import save_data
@@ -74,46 +74,22 @@ def test_lo_l2_sw_species_read_from_cdf(self):
                 epoch_delta_plus = rng.random(len(epoch))
                 energy_per_charge = np.geomspace(2, 1000)
                 spin_sector = np.linspace(0, 360, 24)
-                hplus = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                heplus = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                heplusplus = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
+                hplus = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                heplus = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                heplusplus = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
                 ne = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
-                cplus4 = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                cplus5 = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                cplus6 = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                oplus5 = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                oplus6 = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                oplus7 = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                oplus8 = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
+                cplus4 = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                cplus5 = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                cplus6 = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                oplus5 = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                oplus6 = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                oplus7 = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                oplus8 = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
                 mg = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
                 si = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
                 cnoplus = rng.random((len(epoch), len(energy_per_charge)))
-                fe_loq = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
-                fe_hiq = rng.random(
-                    (len(epoch), len(energy_per_charge), len(spin_sector))
-                )
+                fe_loq = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
+                fe_hiq = rng.random((len(epoch), len(energy_per_charge), len(spin_sector)))
                 data_quality = rng.random(len(epoch))
 
                 cdf_file["epoch"] = epoch
@@ -142,9 +118,7 @@ def test_lo_l2_sw_species_read_from_cdf(self):
                 for var in LO_L2_SW_SPECIES_DATA_VARS:
                     cdf_file[var].attrs["FILLVAL"] = -1e31
 
-            result: CodiceLoL2SWSpeciesData = CodiceLoL2SWSpeciesData.read_from_cdf(
-                cdf_file_path
-            )
+            result: CodiceLoL2SWSpeciesData = CodiceLoL2SWSpeciesData.read_from_cdf(cdf_file_path)
             np.testing.assert_array_equal(result.epoch, epoch)
             np.testing.assert_array_equal(result.epoch_delta_minus, epoch_delta_minus)
             np.testing.assert_array_equal(result.epoch_delta_plus, epoch_delta_plus)
@@ -177,9 +151,7 @@ def test_lo_l2_sw_species_read_from_cdf_handles_fillval(self):
                 epoch_delta_plus = rng.random(len(epoch))
                 energy_per_charge = np.geomspace(2, 1000)
                 spin_sector = np.linspace(0, 360, 24)
-                fills = np.full(
-                    (len(epoch), len(energy_per_charge), len(spin_sector)), -1e31
-                )
+                fills = np.full((len(epoch), len(energy_per_charge), len(spin_sector)), -1e31)
 
                 data_quality = rng.random(len(epoch))
 
@@ -194,13 +166,9 @@ def test_lo_l2_sw_species_read_from_cdf_handles_fillval(self):
                     cdf_file[var] = fills
                     cdf_file[var].attrs["FILLVAL"] = -1e31
 
-            nans = np.full(
-                (len(epoch), len(energy_per_charge), len(spin_sector)), np.nan
-            )
+            nans = np.full((len(epoch), len(energy_per_charge), len(spin_sector)), np.nan)
 
-            result: CodiceLoL2SWSpeciesData = CodiceLoL2SWSpeciesData.read_from_cdf(
-                cdf_file_path
-            )
+            result: CodiceLoL2SWSpeciesData = CodiceLoL2SWSpeciesData.read_from_cdf(cdf_file_path)
             np.testing.assert_array_equal(result.epoch, epoch)
             np.testing.assert_array_equal(result.epoch_delta_minus, epoch_delta_minus)
             np.testing.assert_array_equal(result.epoch_delta_plus, epoch_delta_plus)
@@ -261,6 +229,7 @@ def test_codice_lo_l3a_partial_density_to_data_product(self):
                 actual_data_product_variable.value,
                 getattr(data_product.data, input_name),
             )
+            self.assertIs(expected_value, getattr(data_product.data, input_name))
             self.assertEqual(input_name, actual_data_product_variable.name)
 
     def test_codice_lo_l3a_ratios_to_data_product(self):
@@ -291,6 +260,7 @@ def test_codice_lo_l3a_ratios_to_data_product(self):
             np.testing.assert_array_equal(
                 actual_data_product_variable.value, getattr(data_product, input_name)
             )
+            self.assertIs(expected_value, getattr(data_product, input_name))
             self.assertEqual(input_name, actual_data_product_variable.name)
 
     def test_codice_lo_l3a_partial_density_read_from_cdf(self):
@@ -329,9 +299,7 @@ def test_codice_lo_l3a_partial_density_read_from_cdf(self):
         )
 
         with tempfile.TemporaryDirectory() as tmpdir:
-            cdf_path = save_data(
-                codice_lo_l3a_partial_densities, folder_path=Path(tmpdir)
-            )
+            cdf_path = save_data(codice_lo_l3a_partial_densities, folder_path=Path(tmpdir))
 
             read_in_density_data = CodiceLoPartialDensityData.read_from_cdf(cdf_path)
 
@@ -365,6 +333,7 @@ def test_codice_lo_l3a_charge_state_distributions_to_data_product(self):
             np.testing.assert_array_equal(
                 actual_data_product_variable.value, getattr(data_product, input_name)
             )
+            self.assertIs(expected_value, getattr(data_product, input_name))
             self.assertEqual(input_name, actual_data_product_variable.name)
 
         (
@@ -389,9 +358,7 @@ def test_codice_lo_l3a_direct_event_read_from_cdf_reads_where_no_variables_have_
             tmpdir = Path(tmpdir)
 
             test_l3a_direct_event = tmpdir / "test_l3a_cdf.cdf"
-            with CDF(
-                str(test_l3a_direct_event), masterpath=str(no_fill_l3a_cdf_path)
-            ) as cdf:
+            with CDF(str(test_l3a_direct_event), masterpath=str(no_fill_l3a_cdf_path)) as cdf:
                 cdf["apd_energy"] = rng.random(cdf["apd_energy"].shape)
                 cdf["elevation"] = rng.random(cdf["elevation"].shape)
                 cdf["energy_per_charge"] = rng.random(cdf["energy_per_charge"].shape)
@@ -401,62 +368,42 @@ def test_codice_lo_l3a_direct_event_read_from_cdf_reads_where_no_variables_have_
                 cdf["normalization"] = rng.random(cdf["normalization"].shape)
                 cdf["spin_angle"] = rng.random(cdf["spin_angle"].shape)
                 cdf["spin_angle_bin"] = rng.random(cdf["spin_angle_bin"].shape)
-                cdf["spin_angle_bin_delta"] = rng.random(
-                    cdf["spin_angle_bin_delta"].shape
-                )
+                cdf["spin_angle_bin_delta"] = rng.random(cdf["spin_angle_bin_delta"].shape)
                 cdf["type"] = rng.integers(0, 5, cdf["type"].shape)
-                cdf["normalization_per_event"] = rng.random(
-                    cdf["normalization_per_event"].shape
-                )
+                cdf["normalization_per_event"] = rng.random(cdf["normalization_per_event"].shape)
                 cdf["position"] = rng.random(cdf["position"].shape)
                 cdf["spin_sector"] = rng.random(cdf["spin_sector"].shape)
                 cdf["acquisition_time_per_esa_step"] = rng.random(
                     cdf["acquisition_time_per_esa_step"].shape
                 )
 
-                cdf["rgfo_spin_sector"] = rng.integers(
-                    0, 24, cdf["rgfo_spin_sector"].shape
-                )
+                cdf["rgfo_spin_sector"] = rng.integers(0, 24, cdf["rgfo_spin_sector"].shape)
                 cdf["rgfo_half_spin"] = rng.integers(0, 32, cdf["rgfo_half_spin"].shape)
                 cdf["rgfo_esa_step"] = rng.integers(0, 128, cdf["rgfo_esa_step"].shape)
                 cdf["half_spin_per_esa_step"] = rng.integers(
                     0, 32, cdf["half_spin_per_esa_step"].shape
                 )
 
-            actual_event_data = CodiceLoDirectEventData.read_from_cdf(
-                test_l3a_direct_event
-            )
+            actual_event_data = CodiceLoDirectEventData.read_from_cdf(test_l3a_direct_event)
 
             with CDF(str(test_l3a_direct_event)) as cdf:
                 np.testing.assert_array_equal(
                     actual_event_data.normalization_per_event,
                     cdf["normalization_per_event"],
                 )
-                np.testing.assert_array_equal(
-                    actual_event_data.position, cdf["position"]
-                )
-                np.testing.assert_array_equal(
-                    actual_event_data.energy_step, cdf["energy_step"]
-                )
-                np.testing.assert_array_equal(
-                    actual_event_data.spin_sector, cdf["spin_sector"]
-                )
+                np.testing.assert_array_equal(actual_event_data.position, cdf["position"])
+                np.testing.assert_array_equal(actual_event_data.energy_step, cdf["energy_step"])
+                np.testing.assert_array_equal(actual_event_data.spin_sector, cdf["spin_sector"])
                 np.testing.assert_array_equal(
                     actual_event_data.acquisition_time_per_esa_step,
                     cdf["acquisition_time_per_esa_step"],
                 )
-                np.testing.assert_array_equal(
-                    actual_event_data.apd_energy, cdf["apd_energy"]
-                )
-                np.testing.assert_array_equal(
-                    actual_event_data.elevation, cdf["elevation"]
-                )
+                np.testing.assert_array_equal(actual_event_data.apd_energy, cdf["apd_energy"])
+                np.testing.assert_array_equal(actual_event_data.elevation, cdf["elevation"])
                 np.testing.assert_array_equal(
                     actual_event_data.energy_per_charge, cdf["energy_per_charge"]
                 )
-                np.testing.assert_array_equal(
-                    actual_event_data.energy_step, cdf["energy_step"]
-                )
+                np.testing.assert_array_equal(actual_event_data.energy_step, cdf["energy_step"])
                 np.testing.assert_array_equal(actual_event_data.mass, cdf["mass"])
                 np.testing.assert_array_equal(
                     actual_event_data.mass_per_charge, cdf["mass_per_charge"]
@@ -464,9 +411,7 @@ def test_codice_lo_l3a_direct_event_read_from_cdf_reads_where_no_variables_have_
                 np.testing.assert_array_equal(
                     actual_event_data.normalization, cdf["normalization"]
                 )
-                np.testing.assert_array_equal(
-                    actual_event_data.spin_angle, cdf["spin_angle"]
-                )
+                np.testing.assert_array_equal(actual_event_data.spin_angle, cdf["spin_angle"])
                 np.testing.assert_array_equal(
                     actual_event_data.spin_angle_bin, cdf["spin_angle_bin"]
                 )
@@ -500,9 +445,7 @@ def test_codice_lo_l3a_direct_event_read_from_cdf_handles_fill_value(self):
                 actual_event_data.apd_energy,
                 np.full_like(cdf["apd_energy"][...], np.nan),
             )
-            np.testing.assert_array_equal(
-                actual_event_data.data_quality, cdf["data_quality"]
-            )
+            np.testing.assert_array_equal(actual_event_data.data_quality, cdf["data_quality"])
             np.testing.assert_array_equal(
                 actual_event_data.elevation, np.full_like(cdf["elevation"][...], np.nan)
             )
@@ -619,9 +562,7 @@ def test_codice_lo_l3a_direct_event_to_data_product(self):
             type=rng.integers(0, 5, (len(epoch), len(priority), len(event_num))),
         )
 
-        np.testing.assert_array_equal(
-            direct_event.event_index, np.arange(len(event_num))
-        )
+        np.testing.assert_array_equal(direct_event.event_index, np.arange(len(event_num)))
         np.testing.assert_array_equal(
             direct_event.priority_index_label,
             np.array(["0", "1", "2", "3", "4", "5", "6"]),
@@ -655,17 +596,11 @@ def test_codice_lo_l3a_direct_event_to_data_product(self):
             )
 
     def test_codice_lo_l1a_sw_priority_read_from_cdf(self):
-        cdf_path = get_test_data_path(
-            "codice/imap_codice_l1a_lo-sw-priority_20260307_v004.cdf"
-        )
-        actual_l1a_sw_priority_rates = CodiceLoL1aSWPriorityRates.read_from_cdf(
-            cdf_path
-        )
+        cdf_path = get_test_data_path("codice/imap_codice_l1a_lo-sw-priority_20260307_v004.cdf")
+        actual_l1a_sw_priority_rates = CodiceLoL1aSWPriorityRates.read_from_cdf(cdf_path)
 
         with CDF(str(cdf_path)) as cdf:
-            np.testing.assert_array_equal(
-                actual_l1a_sw_priority_rates.epoch, cdf["epoch"][...]
-            )
+            np.testing.assert_array_equal(actual_l1a_sw_priority_rates.epoch, cdf["epoch"][...])
             np.testing.assert_array_equal(
                 actual_l1a_sw_priority_rates.epoch_delta_plus,
                 cdf["epoch_delta_plus"][...],
@@ -739,17 +674,11 @@ def test_codice_lo_l1a_sw_priority_read_from_cdf(self):
             )
 
     def test_codice_lo_l1a_nsw_priority_read_from_cdf(self):
-        cdf_path = get_test_data_path(
-            "codice/imap_codice_l1a_lo-nsw-priority_20260307_v004.cdf"
-        )
-        actual_l1a_nsw_priority_rates = CodiceLoL1aNSWPriorityRates.read_from_cdf(
-            cdf_path
-        )
+        cdf_path = get_test_data_path("codice/imap_codice_l1a_lo-nsw-priority_20260307_v004.cdf")
+        actual_l1a_nsw_priority_rates = CodiceLoL1aNSWPriorityRates.read_from_cdf(cdf_path)
 
         with CDF(str(cdf_path)) as cdf:
-            np.testing.assert_array_equal(
-                actual_l1a_nsw_priority_rates.epoch, cdf["epoch"][...]
-            )
+            np.testing.assert_array_equal(actual_l1a_nsw_priority_rates.epoch, cdf["epoch"][...])
             np.testing.assert_array_equal(
                 actual_l1a_nsw_priority_rates.epoch_delta_plus,
                 cdf["epoch_delta_plus"][...],
@@ -825,21 +754,15 @@ def test_codice_lo_3d_distributions_data_product(self):
         self.assertEqual(18, len(actual_data_product_variables))
         actual_variables = iter(actual_data_product_variables)
 
-        self.assert_variable_attributes(
-            next(actual_variables), sentinel.epoch, EPOCH_VAR_NAME
-        )
+        self.assert_variable_attributes(next(actual_variables), sentinel.epoch, EPOCH_VAR_NAME)
         self.assert_variable_attributes(
             next(actual_variables), sentinel.epoch_delta, EPOCH_DELTA_VAR_NAME
         )
-        self.assert_variable_attributes(
-            next(actual_variables), elevation, ELEVATION_VAR_NAME
-        )
+        self.assert_variable_attributes(next(actual_variables), elevation, ELEVATION_VAR_NAME)
         self.assert_variable_attributes(
             next(actual_variables), sentinel.elevation_delta, ELEVATION_DELTA_VAR_NAME
         )
-        self.assert_variable_attributes(
-            next(actual_variables), spin_angle, SPIN_ANGLE_VAR_NAME
-        )
+        self.assert_variable_attributes(next(actual_variables), spin_angle, SPIN_ANGLE_VAR_NAME)
         self.assert_variable_attributes(
             next(actual_variables), sentinel.spin_angle_delta, SPIN_ANGLE_DELTA_VAR_NAME
         )
@@ -854,9 +777,7 @@ def test_codice_lo_3d_distributions_data_product(self):
             sentinel.energy_delta_minus,
             ENERGY_DELTA_MINUS_VAR_NAME,
         )
-        self.assert_variable_attributes(
-            next(actual_variables), sentinel.species_data, species
-        )
+        self.assert_variable_attributes(next(actual_variables), sentinel.species_data, species)
         self.assert_variable_attributes(
             next(actual_variables), energy.astype(str), ENERGY_LABEL_VAR_NAME
         )
@@ -928,9 +849,7 @@ def test_codice_lo_l2_direct_events_reads_from_correct_float_data(self):
                 np.testing.assert_array_equal(
                     l2_direct_event.spin_angle, cdf["spin_angle"][:, :7, ...]
                 )
-                np.testing.assert_array_equal(
-                    l2_direct_event.type, cdf["type"][:, :7, ...]
-                )
+                np.testing.assert_array_equal(l2_direct_event.type, cdf["type"][:, :7, ...])
 
     def test_workaround_to_convert_float_spin_sector_to_int(self):
         all_fill_l2_cdf_path = get_test_data_path(
@@ -943,9 +862,7 @@ def test_workaround_to_convert_float_spin_sector_to_int(self):
 
             test_cdf_path = tmpdir / "test_cdf.cdf"
             with CDF(str(test_cdf_path), masterpath=str(all_fill_l2_cdf_path)) as cdf:
-                expected_spin_sector = rng.integers(
-                    0, 24, cdf["spin_sector"].shape, dtype=int
-                )
+                expected_spin_sector = rng.integers(0, 24, cdf["spin_sector"].shape, dtype=int)
                 cdf["spin_sector"] = expected_spin_sector.astype(float)
 
             l2_direct_event = CodiceLoL2DirectEventData.read_from_cdf(test_cdf_path)
@@ -997,15 +914,11 @@ def test_codice_lo_l2_direct_events_read_from_cdf_handles_fill_value(self):
             self.assertTrue(np.all(l2_direct_event.position.mask))
 
             self.assertIsInstance(l2_direct_event.gain, np.ma.masked_array)
-            np.testing.assert_array_equal(
-                l2_direct_event.gain.data, cdf["gain"][:, :7, ...]
-            )
+            np.testing.assert_array_equal(l2_direct_event.gain.data, cdf["gain"][:, :7, ...])
             self.assertTrue(np.all(l2_direct_event.gain.mask))
 
             self.assertIsInstance(l2_direct_event.apd_id, np.ma.masked_array)
-            np.testing.assert_array_equal(
-                l2_direct_event.apd_id.data, cdf["apd_id"][:, :7, ...]
-            )
+            np.testing.assert_array_equal(l2_direct_event.apd_id.data, cdf["apd_id"][:, :7, ...])
             self.assertTrue(np.all(l2_direct_event.apd_id.mask))
 
             self.assertIsInstance(l2_direct_event.data_quality, np.ma.masked_array)
@@ -1027,9 +940,7 @@ def test_codice_lo_l2_direct_events_read_from_cdf_handles_fill_value(self):
             self.assertTrue(np.all(l2_direct_event.num_events.mask))
 
             self.assertIsInstance(l2_direct_event.tof, np.ma.masked_array)
-            np.testing.assert_array_equal(
-                l2_direct_event.tof.data, cdf["tof"][:, :7, ...]
-            )
+            np.testing.assert_array_equal(l2_direct_event.tof.data, cdf["tof"][:, :7, ...])
             self.assertTrue(np.all(l2_direct_event.tof.mask))
 
     def test_codice_lo_l2_direct_events_read_from_cdf_masks_negative_tof_values(self):
@@ -1052,9 +963,7 @@ def test_codice_lo_l2_direct_events_read_from_cdf_masks_negative_tof_values(self
             expected_truncated_tof = tof[:, :CODICE_LO_L2_NUM_PRIORITIES, ...]
             expected_mask = expected_truncated_tof < 0
 
-            np.testing.assert_array_equal(
-                l2_direct_event.tof.data, expected_truncated_tof
-            )
+            np.testing.assert_array_equal(l2_direct_event.tof.data, expected_truncated_tof)
             np.testing.assert_array_equal(l2_direct_event.tof.mask, expected_mask)
 
     def test_codice_lo_l1a_sw_priority_read_from_cdf_handles_fill_value(self):
@@ -1104,21 +1013,15 @@ def test_codice_lo_l1a_nsw_priority_read_from_cdf_handles_fill_value(self):
             )
 
             self.assertIsInstance(l1a_nsw_model.rgfo_half_spin, np.ma.masked_array)
-            np.testing.assert_array_equal(
-                l1a_nsw_model.rgfo_half_spin.data, cdf["rgfo_half_spin"]
-            )
+            np.testing.assert_array_equal(l1a_nsw_model.rgfo_half_spin.data, cdf["rgfo_half_spin"])
             self.assertTrue(np.all(l1a_nsw_model.rgfo_half_spin.mask))
 
             self.assertIsInstance(l1a_nsw_model.data_quality, np.ma.masked_array)
-            np.testing.assert_array_equal(
-                l1a_nsw_model.data_quality.data, cdf["data_quality"]
-            )
+            np.testing.assert_array_equal(l1a_nsw_model.data_quality.data, cdf["data_quality"])
             self.assertTrue(np.all(l1a_nsw_model.data_quality.mask))
 
             self.assertIsInstance(l1a_nsw_model.p5_heavies, np.ma.masked_array)
-            np.testing.assert_array_equal(
-                l1a_nsw_model.p5_heavies.data, cdf["p5_heavies"]
-            )
+            np.testing.assert_array_equal(l1a_nsw_model.p5_heavies.data, cdf["p5_heavies"])
             self.assertTrue(np.all(l1a_nsw_model.p5_heavies.mask))
 
             self.assertIsInstance(l1a_nsw_model.p6_hplus_heplusplus, np.ma.masked_array)
@@ -1128,9 +1031,7 @@ def test_codice_lo_l1a_nsw_priority_read_from_cdf_handles_fill_value(self):
             self.assertTrue(np.all(l1a_nsw_model.p6_hplus_heplusplus.mask))
 
             self.assertIsInstance(l1a_nsw_model.nso_half_spin, np.ma.masked_array)
-            np.testing.assert_array_equal(
-                l1a_nsw_model.nso_half_spin.data, cdf["nso_half_spin"]
-            )
+            np.testing.assert_array_equal(l1a_nsw_model.nso_half_spin.data, cdf["nso_half_spin"])
             self.assertTrue(np.all(l1a_nsw_model.nso_half_spin.mask))
 
             self.assertIsInstance(l1a_nsw_model.sw_bias_gain_mode, np.ma.masked_array)
diff --git a/tests/glows/l3a/science/test_calculate_daily_lightcurve.py b/tests/glows/l3a/science/test_calculate_daily_lightcurve.py
index 83d9078c..f625c205 100644
--- a/tests/glows/l3a/science/test_calculate_daily_lightcurve.py
+++ b/tests/glows/l3a/science/test_calculate_daily_lightcurve.py
@@ -2,14 +2,14 @@
 from unittest.mock import Mock
 
 import numpy as np
-from uncertainties.unumpy import uarray, nominal_values, std_devs
+from uncertainties.unumpy import nominal_values, std_devs, uarray
 
 from imap_l3_processing.glows.l3a.science.bad_angle_flag_configuration import (
     BadAngleFlagConfiguration,
 )
 from imap_l3_processing.glows.l3a.science.calculate_daily_lightcurve import (
-    rebin_lightcurve,
     calculate_spin_angles,
+    rebin_lightcurve,
 )
 from imap_l3_processing.glows.l3a.science.time_independent_background_lookup_table import (
     TimeIndependentBackgroundLookupTable,
@@ -18,16 +18,12 @@
 
 class TestCalculateDailyLightcurve(unittest.TestCase):
     def setUp(self):
-        self.all_zero_time_independent_background = (
-            TimeIndependentBackgroundLookupTable(
-                latitudes=np.array([-90, 90]),
-                longitudes=np.array([0]),
-                background_values=np.zeros(shape=(2, 1)),
-            )
-        )
-        self.enable_all_flags_configuration = BadAngleFlagConfiguration(
-            True, True, True, True
+        self.all_zero_time_independent_background = TimeIndependentBackgroundLookupTable(
+            latitudes=np.array([-90, 90]),
+            longitudes=np.array([0]),
+            background_values=np.zeros(shape=(2, 1)),
         )
+        self.enable_all_flags_configuration = BadAngleFlagConfiguration(True, True, True, True)
 
     def test_rebin_with_no_flags_and_equal_exposure_times(self):
         photon_flux = np.full(3600, 1.0)
@@ -316,9 +312,7 @@ def test_rebin_subtracts_time_independent_background(self):
     def test_calculate_spin_angles(self):
         spin_angles = np.array([70, 130, 190, 250, 310, 10, 70, 130, 190, 350, 10, 30])
 
-        np.testing.assert_array_equal(
-            [130, 310, 130, 10], calculate_spin_angles(4, spin_angles)
-        )
+        np.testing.assert_array_equal([130, 310, 130, 10], calculate_spin_angles(4, spin_angles))
 
         realistic_angles = np.linspace(0, 360, 3600, endpoint=False) + 0.05
         expected_4_degree_bins = np.linspace(0, 360, 90, endpoint=False) + 2
diff --git a/tests/glows/l3a/test_glows_l3a_dependencies.py b/tests/glows/l3a/test_glows_l3a_dependencies.py
index 238cbf30..6e822d26 100644
--- a/tests/glows/l3a/test_glows_l3a_dependencies.py
+++ b/tests/glows/l3a/test_glows_l3a_dependencies.py
@@ -1,19 +1,19 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, call
+from unittest.mock import call, patch
 
 import imap_data_access
 from imap_data_access.processing_input import (
-    ScienceInput,
     AncillaryInput,
     ProcessingInputCollection,
+    ScienceInput,
 )
 
 from imap_l3_processing.glows.descriptors import (
-    GLOWS_L2_DESCRIPTOR,
     GLOWS_CALIBRATION_DATA_DESCRIPTOR,
-    GLOWS_PIPELINE_SETTINGS_DESCRIPTOR,
     GLOWS_EXTRA_HELIOSPHERIC_BACKGROUND_DESCRIPTOR,
+    GLOWS_L2_DESCRIPTOR,
+    GLOWS_PIPELINE_SETTINGS_DESCRIPTOR,
     GLOWS_TIME_DEPENDENT_BACKGROUND_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3a.glows_l3a_dependencies import GlowsL3ADependencies
@@ -51,16 +51,9 @@ def test_fetch_dependencies(
             AncillaryInput(time_dependent_background_dependency_filename),
         )
         science_data_dir = (
-            imap_data_access.config["DATA_DIR"]
-            / "imap"
-            / "glows"
-            / "l2a"
-            / "2023"
-            / "01"
-        )
-        ancillary_data_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "glows"
+            imap_data_access.config["DATA_DIR"] / "imap" / "glows" / "l2a" / "2023" / "01"
         )
+        ancillary_data_dir = imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "glows"
 
         cdf_path_str = "some_cdf.cdf"
         cdf_path_name = Path(cdf_path_str)
@@ -99,13 +92,8 @@ def test_fetch_dependencies(
             [
                 call(science_data_dir / cdf_dependency_filename),
                 call(ancillary_data_dir / calibration_data_dependency_filename),
-                call(
-                    ancillary_data_dir
-                    / extra_heliospheric_background_dependency_filename
-                ),
-                call(
-                    ancillary_data_dir / time_dependent_background_dependency_filename
-                ),
+                call(ancillary_data_dir / extra_heliospheric_background_dependency_filename),
+                call(ancillary_data_dir / time_dependent_background_dependency_filename),
                 call(ancillary_data_dir / settings_dependency_filename),
             ],
             mock_download.call_args_list,
diff --git a/tests/glows/l3a/test_models.py b/tests/glows/l3a/test_models.py
index b5a684e8..a3060084 100644
--- a/tests/glows/l3a/test_models.py
+++ b/tests/glows/l3a/test_models.py
@@ -6,41 +6,41 @@
 from numpy import ndarray
 
 from imap_l3_processing.glows.l3a.models import (
-    GlowsL3LightCurve,
-    PHOTON_FLUX_CDF_VAR_NAME,
-    EXPOSURE_TIMES_CDF_VAR_NAME,
-    NUM_OF_BINS_CDF_VAR_NAME,
+    END_TIME_CDF_VAR_NAME,
     EPOCH_CDF_VAR_NAME,
     EPOCH_DELTA_CDF_VAR_NAME,
-    PHOTON_FLUX_UNCERTAINTY_CDF_VAR_NAME,
-    SPIN_ANGLE_CDF_VAR_NAME,
-    LATITUDE_CDF_VAR_NAME,
-    LONGITUDE_CDF_VAR_NAME,
+    EXPOSURE_TIMES_CDF_VAR_NAME,
     EXTRA_HELIOSPHERIC_BACKGROUND_CDF_VAR_NAME,
-    TIME_DEPENDENT_BACKGROUND_CDF_VAR_NAME,
     FILTER_TEMPERATURE_AVERAGE_CDF_VAR_NAME,
     FILTER_TEMPERATURE_STD_DEV_CDF_VAR_NAME,
     HV_VOLTAGE_AVERAGE_CDF_VAR_NAME,
     HV_VOLTAGE_STD_DEV_CDF_VAR_NAME,
-    SPIN_PERIOD_AVERAGE_CDF_VAR_NAME,
-    SPIN_PERIOD_STD_DEV_CDF_VAR_NAME,
-    SPIN_PERIOD_GROUND_AVERAGE_CDF_VAR_NAME,
-    SPIN_PERIOD_GROUND_STD_DEV_CDF_VAR_NAME,
-    PULSE_LENGTH_AVERAGE_CDF_VAR_NAME,
-    PULSE_LENGTH_STD_DEV_CDF_VAR_NAME,
+    LATITUDE_CDF_VAR_NAME,
+    LONGITUDE_CDF_VAR_NAME,
+    NUM_OF_BINS_CDF_VAR_NAME,
+    PHOTON_FLUX_CDF_VAR_NAME,
+    PHOTON_FLUX_UNCERTAINTY_CDF_VAR_NAME,
     POSITION_ANGLE_OFFSET_AVERAGE_CDF_VAR_NAME,
     POSITION_ANGLE_OFFSET_STD_DEV_CDF_VAR_NAME,
-    SPIN_AXIS_ORIENTATION_AVERAGE_CDF_VAR_NAME,
-    SPIN_AXIS_ORIENTATION_STD_DEV_CDF_VAR_NAME,
+    PULSE_LENGTH_AVERAGE_CDF_VAR_NAME,
+    PULSE_LENGTH_STD_DEV_CDF_VAR_NAME,
+    RAW_HISTOGRAM_CDF_VAR_NAME,
+    REPOINTING_CDF_VAR_NAME,
     SPACECRAFT_LOCATION_AVERAGE_CDF_VAR_NAME,
     SPACECRAFT_LOCATION_STD_DEV_CDF_VAR_NAME,
     SPACECRAFT_VELOCITY_AVERAGE_CDF_VAR_NAME,
     SPACECRAFT_VELOCITY_STD_DEV_CDF_VAR_NAME,
-    RAW_HISTOGRAM_CDF_VAR_NAME,
+    SPIN_ANGLE_CDF_VAR_NAME,
     SPIN_ANGLE_DELTA_CDF_VAR_NAME,
+    SPIN_AXIS_ORIENTATION_AVERAGE_CDF_VAR_NAME,
+    SPIN_AXIS_ORIENTATION_STD_DEV_CDF_VAR_NAME,
+    SPIN_PERIOD_AVERAGE_CDF_VAR_NAME,
+    SPIN_PERIOD_GROUND_AVERAGE_CDF_VAR_NAME,
+    SPIN_PERIOD_GROUND_STD_DEV_CDF_VAR_NAME,
+    SPIN_PERIOD_STD_DEV_CDF_VAR_NAME,
     START_TIME_CDF_VAR_NAME,
-    END_TIME_CDF_VAR_NAME,
-    REPOINTING_CDF_VAR_NAME,
+    TIME_DEPENDENT_BACKGROUND_CDF_VAR_NAME,
+    GlowsL3LightCurve,
 )
 from tests.swapi.cdf_model_test_case import CdfModelTestCase
 
@@ -128,48 +128,28 @@ def test_data_to_product_variables(self):
 
         variables = iter(variables)
         # @formatter:off
-        self.assert_variable_attributes(
-            next(variables), [repointing], REPOINTING_CDF_VAR_NAME
-        )
-        self.assert_variable_attributes(
-            next(variables), photon_flux, PHOTON_FLUX_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), [repointing], REPOINTING_CDF_VAR_NAME)
+        self.assert_variable_attributes(next(variables), photon_flux, PHOTON_FLUX_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables),
             photon_flux_uncertainty,
             PHOTON_FLUX_UNCERTAINTY_CDF_VAR_NAME,
         )
-        self.assert_variable_attributes(
-            next(variables), raw_histogram, RAW_HISTOGRAM_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), raw_histogram, RAW_HISTOGRAM_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), exposure_times, EXPOSURE_TIMES_CDF_VAR_NAME
         )
-        self.assert_variable_attributes(
-            next(variables), number_of_bins, NUM_OF_BINS_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), number_of_bins, NUM_OF_BINS_CDF_VAR_NAME)
         self.assert_variable_attributes(next(variables), epoch, EPOCH_CDF_VAR_NAME)
-        self.assert_variable_attributes(
-            next(variables), epoch_delta, EPOCH_DELTA_CDF_VAR_NAME
-        )
-        self.assert_variable_attributes(
-            next(variables), [start_time], START_TIME_CDF_VAR_NAME
-        )
-        self.assert_variable_attributes(
-            next(variables), [end_time], END_TIME_CDF_VAR_NAME
-        )
-        self.assert_variable_attributes(
-            next(variables), spin_angle, SPIN_ANGLE_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), epoch_delta, EPOCH_DELTA_CDF_VAR_NAME)
+        self.assert_variable_attributes(next(variables), [start_time], START_TIME_CDF_VAR_NAME)
+        self.assert_variable_attributes(next(variables), [end_time], END_TIME_CDF_VAR_NAME)
+        self.assert_variable_attributes(next(variables), spin_angle, SPIN_ANGLE_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), spin_angle_delta, SPIN_ANGLE_DELTA_CDF_VAR_NAME
         )
-        self.assert_variable_attributes(
-            next(variables), latitudes, LATITUDE_CDF_VAR_NAME
-        )
-        self.assert_variable_attributes(
-            next(variables), longitudes, LONGITUDE_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), latitudes, LATITUDE_CDF_VAR_NAME)
+        self.assert_variable_attributes(next(variables), longitudes, LONGITUDE_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables),
             extra_heliospheric_background,
@@ -260,13 +240,9 @@ def test_data_to_product_variables(self):
         )
 
         self.assert_variable_attributes(next(variables), [0, 1], "lon_lat")
-        self.assert_variable_attributes(
-            next(variables), ["lon", "lat"], "lon_lat_labels"
-        )
+        self.assert_variable_attributes(next(variables), ["lon", "lat"], "lon_lat_labels")
         self.assert_variable_attributes(next(variables), [0, 1, 2], "x_y_z")
-        self.assert_variable_attributes(
-            next(variables), ["X", "Y", "Z"], "x_y_z_labels"
-        )
+        self.assert_variable_attributes(next(variables), ["X", "Y", "Z"], "x_y_z_labels")
 
 
 if __name__ == "__main__":
diff --git a/tests/glows/l3a/test_utils.py b/tests/glows/l3a/test_utils.py
index 40819541..cc2c15be 100644
--- a/tests/glows/l3a/test_utils.py
+++ b/tests/glows/l3a/test_utils.py
@@ -8,9 +8,9 @@
 
 from imap_l3_processing.glows.l3a.models import GlowsL2Data, GlowsL2Header
 from imap_l3_processing.glows.l3a.utils import (
-    read_l2_glows_data,
-    create_glows_l3a_from_dictionary,
     create_glows_l3a_dictionary_from_cdf,
+    create_glows_l3a_from_dictionary,
+    read_l2_glows_data,
 )
 from imap_l3_processing.models import InputMetadata
 from tests.test_helpers import get_test_data_path
@@ -19,11 +19,7 @@
 class TestUtils(unittest.TestCase):
     def test_reading_l2_glows_data_into_models(self):
         cdf = CDF(
-            str(
-                get_test_data_path(
-                    "glows/imap_glows_l2_hist_20251224-repoint00088_v001.cdf"
-                )
-            )
+            str(get_test_data_path("glows/imap_glows_l2_hist_20251224-repoint00088_v001.cdf"))
         )
 
         glows_l2_data: GlowsL2Data = read_l2_glows_data(cdf)
@@ -31,62 +27,36 @@ def test_reading_l2_glows_data_into_models(self):
         self.assertEqual("2025-12-24T11:36:21.588935256", glows_l2_data["start_time"])
         self.assertEqual("2025-12-25T09:39:47.969074488", glows_l2_data["end_time"])
 
-        self.assertEqual(
-            (3600,), glows_l2_data["daily_lightcurve"]["photon_flux"].shape
-        )
-        self.assertEqual(
-            887.6062785692615, glows_l2_data["daily_lightcurve"]["photon_flux"][0]
-        )
-        self.assertEqual(
-            872.260576384695, glows_l2_data["daily_lightcurve"]["photon_flux"][-1]
-        )
+        self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["photon_flux"].shape)
+        self.assertEqual(887.6062785692615, glows_l2_data["daily_lightcurve"]["photon_flux"][0])
+        self.assertEqual(872.260576384695, glows_l2_data["daily_lightcurve"]["photon_flux"][-1])
 
-        self.assertEqual(
-            (3600,), glows_l2_data["daily_lightcurve"]["flux_uncertainties"].shape
-        )
+        self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["flux_uncertainties"].shape)
         self.assertEqual(
             6.338751356172933,
             glows_l2_data["daily_lightcurve"]["flux_uncertainties"][0],
         )
 
-        self.assertEqual(
-            (3600,), glows_l2_data["daily_lightcurve"]["exposure_times"].shape
-        )
+        self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["exposure_times"].shape)
         self.assertEqual(
             22.090875733333327, glows_l2_data["daily_lightcurve"]["exposure_times"][0]
         )
 
         self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["spin_angle"].shape)
-        self.assertEqual(
-            0.08840215463658296, glows_l2_data["daily_lightcurve"]["spin_angle"][0]
-        )
+        self.assertEqual(0.08840215463658296, glows_l2_data["daily_lightcurve"]["spin_angle"][0])
 
-        self.assertEqual(
-            (3600,), glows_l2_data["daily_lightcurve"]["histogram_flag_array"].shape
-        )
-        self.assertEqual(
-            np.int64, glows_l2_data["daily_lightcurve"]["histogram_flag_array"].dtype
-        )
+        self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["histogram_flag_array"].shape)
+        self.assertEqual(np.int64, glows_l2_data["daily_lightcurve"]["histogram_flag_array"].dtype)
         self.assertEqual(
             np.uint8(0), glows_l2_data["daily_lightcurve"]["histogram_flag_array"][84]
         )
 
-        self.assertEqual(
-            (3600,), glows_l2_data["daily_lightcurve"]["ecliptic_lat"].shape
-        )
-        self.assertEqual(
-            (3600,), glows_l2_data["daily_lightcurve"]["ecliptic_lon"].shape
-        )
-        self.assertEqual(
-            75.04420784333895, glows_l2_data["daily_lightcurve"]["ecliptic_lat"][0]
-        )
-        self.assertEqual(
-            268.7416390634532, glows_l2_data["daily_lightcurve"]["ecliptic_lon"][0]
-        )
+        self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["ecliptic_lat"].shape)
+        self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["ecliptic_lon"].shape)
+        self.assertEqual(75.04420784333895, glows_l2_data["daily_lightcurve"]["ecliptic_lat"][0])
+        self.assertEqual(268.7416390634532, glows_l2_data["daily_lightcurve"]["ecliptic_lon"][0])
 
-        self.assertEqual(
-            (3600,), glows_l2_data["daily_lightcurve"]["raw_histogram"].shape
-        )
+        self.assertEqual((3600,), glows_l2_data["daily_lightcurve"]["raw_histogram"].shape)
         self.assertEqual(19608, glows_l2_data["daily_lightcurve"]["raw_histogram"][0])
 
         self.assertEqual(
@@ -103,18 +73,10 @@ def test_reading_l2_glows_data_into_models(self):
             cdf["filter_temperature_std_dev"][0],
             glows_l2_data["filter_temperature_std_dev"],
         )
-        self.assertEqual(
-            cdf["hv_voltage_average"][0], glows_l2_data["hv_voltage_average"]
-        )
-        self.assertEqual(
-            cdf["hv_voltage_std_dev"][0], glows_l2_data["hv_voltage_std_dev"]
-        )
-        self.assertEqual(
-            cdf["spin_period_average"][0], glows_l2_data["spin_period_average"]
-        )
-        self.assertEqual(
-            cdf["spin_period_std_dev"][0], glows_l2_data["spin_period_std_dev"]
-        )
+        self.assertEqual(cdf["hv_voltage_average"][0], glows_l2_data["hv_voltage_average"])
+        self.assertEqual(cdf["hv_voltage_std_dev"][0], glows_l2_data["hv_voltage_std_dev"])
+        self.assertEqual(cdf["spin_period_average"][0], glows_l2_data["spin_period_average"])
+        self.assertEqual(cdf["spin_period_std_dev"][0], glows_l2_data["spin_period_std_dev"])
         self.assertEqual(
             cdf["spin_period_ground_average"][0],
             glows_l2_data["spin_period_ground_average"],
@@ -123,12 +85,8 @@ def test_reading_l2_glows_data_into_models(self):
             cdf["spin_period_ground_std_dev"][0],
             glows_l2_data["spin_period_ground_std_dev"],
         )
-        self.assertEqual(
-            cdf["pulse_length_average"][0], glows_l2_data["pulse_length_average"]
-        )
-        self.assertEqual(
-            cdf["pulse_length_std_dev"][0], glows_l2_data["pulse_length_std_dev"]
-        )
+        self.assertEqual(cdf["pulse_length_average"][0], glows_l2_data["pulse_length_average"])
+        self.assertEqual(cdf["pulse_length_std_dev"][0], glows_l2_data["pulse_length_std_dev"])
         self.assertEqual(
             cdf["position_angle_offset_average"][0],
             glows_l2_data["position_angle_offset_average"],
@@ -166,21 +124,15 @@ def assert_equal_xyz(self, cdf, variable_name, actual):
         self.assertEqual(expected_spacecraft_location_average, actual[variable_name])
 
     def test_fails_if_cdf_has_more_than_one_histogram(self):
-        cdf = CDF(
-            str(get_test_data_path("glows/glows_l2_with_too_many_histograms.cdf"))
-        )
+        cdf = CDF(str(get_test_data_path("glows/glows_l2_with_too_many_histograms.cdf")))
 
         with self.assertRaises(AssertionError) as cm:
             _ = read_l2_glows_data(cdf)
-        self.assertEqual(
-            ("Level 2 file should have only one histogram",), cm.exception.args
-        )
+        self.assertEqual(("Level 2 file should have only one histogram",), cm.exception.args)
 
     def test_create_glows_l3a_from_dictionary(self):
         with open(
-            get_test_data_path(
-                "glows/imap_glows_l3a_20130908085214_orbX_modX_p_v00.json"
-            )
+            get_test_data_path("glows/imap_glows_l3a_20130908085214_orbX_modX_p_v00.json")
         ) as f:
             data = json.load(f)
             expected_spin_delta = 3
@@ -315,9 +267,7 @@ def test_create_glows_l3a_dictionary_from_cdf(self):
         cdf_path = get_test_data_path("glows") / "imap_glows_l3a_hist_20100101_v001.cdf"
         actual_dictionary = create_glows_l3a_dictionary_from_cdf(cdf_path)
 
-        self.assertEqual(
-            "imap_glows_l3a_hist_20100101_v001.cdf", actual_dictionary["filename"]
-        )
+        self.assertEqual("imap_glows_l3a_hist_20100101_v001.cdf", actual_dictionary["filename"])
         self.assertEqual(
             datetime(2013, 9, 8, 8, 52, 14).strftime("%Y-%m-%d %H:%M:%S"),
             actual_dictionary["start_time"],
@@ -340,12 +290,8 @@ def test_create_glows_l3a_dictionary_from_cdf(self):
             169.51280659858702,
             actual_dictionary["daily_lightcurve"]["ecliptic_lon"][-1],
         )
-        self.assertEqual(
-            802.8, actual_dictionary["daily_lightcurve"]["exposure_times"][0]
-        )
-        self.assertEqual(
-            80.28, actual_dictionary["daily_lightcurve"]["exposure_times"][2]
-        )
+        self.assertEqual(802.8, actual_dictionary["daily_lightcurve"]["exposure_times"][0])
+        self.assertEqual(80.28, actual_dictionary["daily_lightcurve"]["exposure_times"][2])
         self.assertAlmostEqual(
             620.93173891, actual_dictionary["daily_lightcurve"]["photon_flux"][0]
         )
@@ -366,61 +312,39 @@ def test_create_glows_l3a_dictionary_from_cdf(self):
             3.66514655e-04,
             actual_dictionary["daily_lightcurve"]["extra_heliospheric_bckgrd"][-1],
         )
-        self.assertEqual(
-            0, actual_dictionary["daily_lightcurve"]["time_dependent_bckgrd"][0]
-        )
+        self.assertEqual(0, actual_dictionary["daily_lightcurve"]["time_dependent_bckgrd"][0])
         self.assertEqual(
             1.0000e-02,
             actual_dictionary["daily_lightcurve"]["time_dependent_bckgrd"][10],
         )
         self.assertEqual(2, actual_dictionary["daily_lightcurve"]["spin_angle"][0])
         self.assertEqual(358, actual_dictionary["daily_lightcurve"]["spin_angle"][-1])
-        self.assertEqual(
-            498484, actual_dictionary["daily_lightcurve"]["raw_histogram"][0]
-        )
-        self.assertEqual(
-            510152, actual_dictionary["daily_lightcurve"]["raw_histogram"][-1]
-        )
+        self.assertEqual(498484, actual_dictionary["daily_lightcurve"]["raw_histogram"][0])
+        self.assertEqual(510152, actual_dictionary["daily_lightcurve"]["raw_histogram"][-1])
         self.assertEqual(65, actual_dictionary["daily_lightcurve"]["number_of_bins"])
 
-        self.assertEqual(
-            -27.84000015258789, actual_dictionary["filter_temperature_average"]
-        )
+        self.assertEqual(-27.84000015258789, actual_dictionary["filter_temperature_average"])
         self.assertEqual(0.0, actual_dictionary["filter_temperature_std_dev"])
         self.assertEqual(1527.0999755859375, actual_dictionary["hv_voltage_average"])
         self.assertEqual(87.94999694824219, actual_dictionary["hv_voltage_std_dev"])
         self.assertEqual(15.0, actual_dictionary["spin_period_average"])
         self.assertEqual(0.0, actual_dictionary["spin_period_std_dev"])
-        self.assertEqual(
-            15.236681938171387, actual_dictionary["spin_period_ground_average"]
-        )
-        self.assertEqual(
-            0.0014979999978095293, actual_dictionary["spin_period_ground_std_dev"]
-        )
+        self.assertEqual(15.236681938171387, actual_dictionary["spin_period_ground_average"])
+        self.assertEqual(0.0014979999978095293, actual_dictionary["spin_period_ground_std_dev"])
         self.assertEqual(0.29899999499320984, actual_dictionary["pulse_length_average"])
-        self.assertEqual(
-            0.017260000109672546, actual_dictionary["pulse_length_std_dev"]
-        )
+        self.assertEqual(0.017260000109672546, actual_dictionary["pulse_length_std_dev"])
 
-        self.assertEqual(
-            91.5780029296875, actual_dictionary["position_angle_offset_average"]
-        )
-        self.assertEqual(
-            0.009991000406444073, actual_dictionary["position_angle_offset_std_dev"]
-        )
+        self.assertEqual(91.5780029296875, actual_dictionary["position_angle_offset_average"])
+        self.assertEqual(0.009991000406444073, actual_dictionary["position_angle_offset_std_dev"])
 
         self.assertAlmostEqual(
             162.09199524, actual_dictionary["spin_axis_orientation_average"]["lon"]
         )
-        self.assertAlmostEqual(
-            0.0, actual_dictionary["spin_axis_orientation_average"]["lat"]
-        )
+        self.assertAlmostEqual(0.0, actual_dictionary["spin_axis_orientation_average"]["lat"])
         self.assertAlmostEqual(
             0.23450001, actual_dictionary["spin_axis_orientation_std_dev"]["lon"]
         )
-        self.assertAlmostEqual(
-            0.0, actual_dictionary["spin_axis_orientation_std_dev"]["lat"]
-        )
+        self.assertAlmostEqual(0.0, actual_dictionary["spin_axis_orientation_std_dev"]["lat"])
 
         self.assertAlmostEqual(
             1.46231104e08, actual_dictionary["spacecraft_location_average"]["x"]
diff --git a/tests/glows/l3bc/l3bc_toolkit/test_funcs.py b/tests/glows/l3bc/l3bc_toolkit/test_funcs.py
index 31726af8..02194f35 100644
--- a/tests/glows/l3bc/l3bc_toolkit/test_funcs.py
+++ b/tests/glows/l3bc/l3bc_toolkit/test_funcs.py
@@ -5,7 +5,6 @@
 from imap_l3_processing.glows.l3bc.l3bc_toolkit.funcs import process_omni_param
 from imap_l3_processing.glows.quality_flags import NOMINAL_ALPHA_PROTON_RATIO_VALUE
 
-
 ALPHA_PARAM_SETTINGS = {
     "column_numbers": (0, 1, 2, 6, 9),
     "gap_marker": 9.999,
@@ -31,9 +30,7 @@ def test_returns_zero_substitution_for_all_valid_alpha(self):
 
         cr_grid = np.array([1957, 1958])
 
-        averaged, used_nominal_per_cr = process_omni_param(
-            omni_raw, cr_grid, ALPHA_PARAM_SETTINGS
-        )
+        averaged, used_nominal_per_cr = process_omni_param(omni_raw, cr_grid, ALPHA_PARAM_SETTINGS)
 
         np.testing.assert_array_equal(used_nominal_per_cr, np.array([False, False]))
         np.testing.assert_array_almost_equal(averaged, np.array([0.05, 0.06]))
@@ -52,9 +49,7 @@ def test_filters_invalid_samples_and_does_not_flag_cr_when_some_samples_remain(
 
         cr_grid = np.array([1957, 1958])
 
-        averaged, used_nominal_per_cr = process_omni_param(
-            omni_raw, cr_grid, ALPHA_PARAM_SETTINGS
-        )
+        averaged, used_nominal_per_cr = process_omni_param(omni_raw, cr_grid, ALPHA_PARAM_SETTINGS)
 
         np.testing.assert_array_equal(used_nominal_per_cr, np.array([False, False]))
         np.testing.assert_array_almost_equal(averaged, np.array([0.04, 0.06]))
@@ -71,13 +66,9 @@ def test_fills_trailing_missing_crs_with_nominal_value(self):
 
         cr_grid = np.array([1957, 1958, 1959, 1960])
 
-        averaged, used_nominal_per_cr = process_omni_param(
-            omni_raw, cr_grid, ALPHA_PARAM_SETTINGS
-        )
+        averaged, used_nominal_per_cr = process_omni_param(omni_raw, cr_grid, ALPHA_PARAM_SETTINGS)
 
-        np.testing.assert_array_equal(
-            used_nominal_per_cr, np.array([False, False, True, True])
-        )
+        np.testing.assert_array_equal(used_nominal_per_cr, np.array([False, False, True, True]))
         np.testing.assert_array_almost_equal(
             averaged,
             np.array(
@@ -105,9 +96,7 @@ def test_raises_when_param_cr_starts_after_cr_grid_start(self):
         with self.assertRaises(Exception) as ctx:
             process_omni_param(omni_raw, cr_grid, ALPHA_PARAM_SETTINGS)
 
-        self.assertEqual(
-            str(ctx.exception), "OMNI Error: not enough data for interpolation"
-        )
+        self.assertEqual(str(ctx.exception), "OMNI Error: not enough data for interpolation")
 
     def test_smooths_interior_cr_gap_via_interpolation_and_does_not_flag(self):
         omni_raw = np.array(
@@ -121,13 +110,9 @@ def test_smooths_interior_cr_gap_via_interpolation_and_does_not_flag(self):
 
         cr_grid = np.array([1957, 1958, 1959])
 
-        averaged, used_nominal_per_cr = process_omni_param(
-            omni_raw, cr_grid, ALPHA_PARAM_SETTINGS
-        )
+        averaged, used_nominal_per_cr = process_omni_param(omni_raw, cr_grid, ALPHA_PARAM_SETTINGS)
 
-        np.testing.assert_array_equal(
-            used_nominal_per_cr, np.array([False, False, False])
-        )
+        np.testing.assert_array_equal(used_nominal_per_cr, np.array([False, False, False]))
         np.testing.assert_array_almost_equal(averaged, np.array([0.05, 0.06, 0.07]))
 
 
diff --git a/tests/glows/l3bc/science/test_filter_out_bad_days.py b/tests/glows/l3bc/science/test_filter_out_bad_days.py
index e588aa47..b8513293 100644
--- a/tests/glows/l3bc/science/test_filter_out_bad_days.py
+++ b/tests/glows/l3bc/science/test_filter_out_bad_days.py
@@ -30,8 +30,7 @@ def test_filter_l3a_files(self):
 
         filtered_list = filter_l3a_files(
             l3a_data=l3a_data,
-            bad_day_list_path=get_test_data_path("glows")
-            / "imap_glows_bad-days-list_v001.dat",
+            bad_day_list_path=get_test_data_path("glows") / "imap_glows_bad-days-list_v001.dat",
             cr=2092,
         )
         self.assertEqual(expected_filtered_list, filtered_list)
diff --git a/tests/glows/l3bc/science/test_generate_l3bc.py b/tests/glows/l3bc/science/test_generate_l3bc.py
index 8b6ba01f..e7da046f 100644
--- a/tests/glows/l3bc/science/test_generate_l3bc.py
+++ b/tests/glows/l3bc/science/test_generate_l3bc.py
@@ -13,9 +13,9 @@
 from imap_l3_processing.glows.l3bc.science.generate_l3bc import generate_l3bc
 from imap_l3_processing.glows.quality_flags import GlowsL3Flags
 from tests.test_helpers import (
+    assert_dict_close,
     get_test_data_path,
     get_test_instrument_team_data_path,
-    assert_dict_close,
 )
 
 
@@ -23,12 +23,8 @@ class TestGenerateL3BC(TestCase):
     def test_generate_l3bc_integration(self):
         cr = 2091
         external_files = {
-            "f107_raw_data": get_test_instrument_team_data_path(
-                "glows/f107_fluxtable.txt"
-            ),
-            "omni_raw_data": get_test_instrument_team_data_path(
-                "glows/omni2_all_years.dat"
-            ),
+            "f107_raw_data": get_test_instrument_team_data_path("glows/f107_fluxtable.txt"),
+            "omni_raw_data": get_test_instrument_team_data_path("glows/omni2_all_years.dat"),
         }
         ancillary_files = {
             "uv_anisotropy": get_test_data_path(
@@ -37,9 +33,7 @@ def test_generate_l3bc_integration(self):
             "WawHelioIonMP_parameters": get_test_data_path(
                 "glows/imap_glows_WawHelioIonMP_v002.json"
             ),
-            "bad_days_list": get_test_data_path(
-                "glows/imap_glows_bad-days-list_v001.dat"
-            ),
+            "bad_days_list": get_test_data_path("glows/imap_glows_bad-days-list_v001.dat"),
             "pipeline_settings": get_test_data_path(
                 "glows/l3d_drift_test/imap_glows_pipeline-settings-l3bcde_20100101_v006.json"
             ),
@@ -50,9 +44,7 @@ def test_generate_l3bc_integration(self):
             f"imap_glows_l3a_hist_2010010{x}-repoint0000{x}_v001.cdf" for x in (1, 2, 3)
         ]
         for name in l3a_file_names:
-            l3a_data.append(
-                create_glows_l3a_dictionary_from_cdf(l3a_data_folder_path / name)
-            )
+            l3a_data.append(create_glows_l3a_dictionary_from_cdf(l3a_data_folder_path / name))
 
         dependencies = GlowsL3BCDependencies(
             l3a_data=l3a_data,
@@ -96,12 +88,8 @@ def test_generate_l3bc_integration(self):
     def test_generate_l3bc_integration_all_data_in_bad_season(self):
         cr = 2093
         external_files = {
-            "f107_raw_data": get_test_instrument_team_data_path(
-                "glows/f107_fluxtable.txt"
-            ),
-            "omni_raw_data": get_test_instrument_team_data_path(
-                "glows/omni2_all_years.dat"
-            ),
+            "f107_raw_data": get_test_instrument_team_data_path("glows/f107_fluxtable.txt"),
+            "omni_raw_data": get_test_instrument_team_data_path("glows/omni2_all_years.dat"),
         }
         ancillary_files = {
             "uv_anisotropy": get_test_data_path(
@@ -110,9 +98,7 @@ def test_generate_l3bc_integration_all_data_in_bad_season(self):
             "WawHelioIonMP_parameters": get_test_data_path(
                 "glows/imap_glows_WawHelioIonMP_20100101_v002.json"
             ),
-            "bad_days_list": get_test_data_path(
-                "glows/imap_glows_bad-days-list_v001.dat"
-            ),
+            "bad_days_list": get_test_data_path("glows/imap_glows_bad-days-list_v001.dat"),
             "pipeline_settings": get_test_instrument_team_data_path(
                 "glows/imap_glows_pipeline-settings-L3bc_20250707_v002.json"
             ),
@@ -120,8 +106,7 @@ def test_generate_l3bc_integration_all_data_in_bad_season(self):
         l3a_data_folder_path = get_test_data_path("glows/l3a_products")
         l3a_data = [
             create_glows_l3a_dictionary_from_cdf(
-                l3a_data_folder_path
-                / "imap_glows_l3a_hist_20100201-repoint00032_v001.cdf"
+                l3a_data_folder_path / "imap_glows_l3a_hist_20100201-repoint00032_v001.cdf"
             )
         ]
 
@@ -139,19 +124,14 @@ def test_generate_l3bc_integration_all_data_in_bad_season(self):
         with self.assertRaises(CannotProcessCarringtonRotationError) as context:
             generate_l3bc(dependencies)
         self.assertTrue(
-            "All days for Carrington Rotation are in a bad season."
-            in str(context.exception)
+            "All days for Carrington Rotation are in a bad season." in str(context.exception)
         )
 
     def test_generate_l3bc_appends_used_l3a_files_to_header(self):
         cr = 2096
         external_files = {
-            "f107_raw_data": get_test_instrument_team_data_path(
-                "glows/f107_fluxtable.txt"
-            ),
-            "omni_raw_data": get_test_instrument_team_data_path(
-                "glows/omni2_all_years.dat"
-            ),
+            "f107_raw_data": get_test_instrument_team_data_path("glows/f107_fluxtable.txt"),
+            "omni_raw_data": get_test_instrument_team_data_path("glows/omni2_all_years.dat"),
         }
         ancillary_files = {
             "uv_anisotropy": get_test_data_path(
@@ -160,9 +140,7 @@ def test_generate_l3bc_appends_used_l3a_files_to_header(self):
             "WawHelioIonMP_parameters": get_test_data_path(
                 "glows/imap_glows_WawHelioIonMP_20100101_v002.json"
             ),
-            "bad_days_list": get_test_data_path(
-                "glows/imap_glows_bad-days-list_v001.dat"
-            ),
+            "bad_days_list": get_test_data_path("glows/imap_glows_bad-days-list_v001.dat"),
             "pipeline_settings": get_test_data_path(
                 "glows/imap_glows_pipeline-settings-l3bcde_20250423_v001.json"
             ),
@@ -199,8 +177,7 @@ def test_generate_l3bc_appends_used_l3a_files_to_header(self):
 
         l3a_folder_path = get_test_data_path("glows/l3a_products")
         l3a_data = [
-            create_glows_l3a_dictionary_from_cdf(l3a_folder_path / file)
-            for file in l3a_files
+            create_glows_l3a_dictionary_from_cdf(l3a_folder_path / file) for file in l3a_files
         ]
 
         dependencies = GlowsL3BCDependencies(
@@ -213,7 +190,7 @@ def test_generate_l3bc_appends_used_l3a_files_to_header(self):
             version=Version(1, 1),
             repointing_file_path=sentinel.repointing_file_path,
         )
-        l3b, l3c = generate_l3bc(dependencies)
+        l3b, _l3c = generate_l3bc(dependencies)
 
         expected_l3a_parent_files = [
             "imap_glows_l3a_hist_20100511-repoint00131_v012.cdf",
@@ -226,6 +203,4 @@ def test_generate_l3bc_appends_used_l3a_files_to_header(self):
             "imap_glows_l3a_hist_20100518-repoint00138_v012.cdf",
         ]
 
-        self.assertEqual(
-            expected_l3a_parent_files, l3b["header"]["l3a_input_files_name"]
-        )
+        self.assertEqual(expected_l3a_parent_files, l3b["header"]["l3a_input_files_name"])
diff --git a/tests/glows/l3bc/science/test_time_parsing.py b/tests/glows/l3bc/science/test_time_parsing.py
index 8050ba64..7395e15c 100644
--- a/tests/glows/l3bc/science/test_time_parsing.py
+++ b/tests/glows/l3bc/science/test_time_parsing.py
@@ -25,9 +25,7 @@ def test_works_with_fast_parser(self):
                 result_l3bc = time_from_yday_l3bc(time_rows)
                 result_l3d = time_from_yday_l3d(time_rows)
             except ValueError:
-                self.fail(
-                    "Fast parser should not crash, check formatting of date string."
-                )
+                self.fail("Fast parser should not crash, check formatting of date string.")
 
         np.testing.assert_array_equal(
             result_l3bc,
diff --git a/tests/glows/l3bc/test_dependency_validator.py b/tests/glows/l3bc/test_dependency_validator.py
index 66439f27..b79b34f0 100644
--- a/tests/glows/l3bc/test_dependency_validator.py
+++ b/tests/glows/l3bc/test_dependency_validator.py
@@ -2,14 +2,13 @@
 from datetime import datetime, timedelta
 from pathlib import Path
 from tempfile import TemporaryDirectory
-from unittest.mock import patch, Mock
-
+from unittest.mock import Mock, patch
 
 from imap_l3_processing.glows.l3bc.dependency_validator import (
-    validate_omni2_dependency,
     validate_dependencies,
     validate_f107_fluxtable_dependency,
     validate_lyman_alpha_dependency,
+    validate_omni2_dependency,
 )
 from tests.test_helpers import get_test_data_path
 
@@ -64,15 +63,9 @@ def test_validate_omni2_dependency(self):
                 )
                 self.assertEqual(expected, actual)
 
-    @patch(
-        "imap_l3_processing.glows.l3bc.dependency_validator.validate_lyman_alpha_dependency"
-    )
-    @patch(
-        "imap_l3_processing.glows.l3bc.dependency_validator.validate_f107_fluxtable_dependency"
-    )
-    @patch(
-        "imap_l3_processing.glows.l3bc.dependency_validator.validate_omni2_dependency"
-    )
+    @patch("imap_l3_processing.glows.l3bc.dependency_validator.validate_lyman_alpha_dependency")
+    @patch("imap_l3_processing.glows.l3bc.dependency_validator.validate_f107_fluxtable_dependency")
+    @patch("imap_l3_processing.glows.l3bc.dependency_validator.validate_omni2_dependency")
     def test_validate_dependencies(
         self,
         mock_validate_omni2_dependency: Mock,
@@ -102,9 +95,7 @@ def test_validate_dependencies(
             with self.subTest(case_name):
                 mock_validate_omni2_dependency.return_value = omni2_validation
                 mock_validate_f107_fluxtable_dependency.return_value = flux_validation
-                mock_validate_lyman_alpha_dependency.return_value = (
-                    lyman_alpha_validation
-                )
+                mock_validate_lyman_alpha_dependency.return_value = lyman_alpha_validation
 
                 actual = validate_dependencies(
                     cr_start_date,
diff --git a/tests/glows/l3bc/test_glows_l3bc_dependencies.py b/tests/glows/l3bc/test_glows_l3bc_dependencies.py
index 2281853a..07666bce 100644
--- a/tests/glows/l3bc/test_glows_l3bc_dependencies.py
+++ b/tests/glows/l3bc/test_glows_l3bc_dependencies.py
@@ -1,7 +1,7 @@
 import unittest
 from datetime import datetime
 from pathlib import Path
-from unittest.mock import patch, sentinel, call
+from unittest.mock import call, patch, sentinel
 
 from imap_l3_processing.constants import TEMP_CDF_FOLDER_PATH
 from imap_l3_processing.glows.l3bc.glows_l3bc_dependencies import GlowsL3BCDependencies
@@ -12,12 +12,8 @@ class TestGlowsL3BCDependencies(unittest.TestCase):
     @patch(
         "imap_l3_processing.glows.l3bc.glows_l3bc_dependencies.create_glows_l3a_dictionary_from_cdf"
     )
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_dependencies.imap_data_access.download"
-    )
-    def test_download_from_cr_to_process(
-        self, mock_download, mock_create_dictionary_from_cdf
-    ):
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_dependencies.imap_data_access.download")
+    def test_download_from_cr_to_process(self, mock_download, mock_create_dictionary_from_cdf):
         mock_download.side_effect = [
             sentinel.uv_anisotropy_downloaded_path,
             sentinel.waw_downloaded_path,
@@ -50,13 +46,11 @@ def test_download_from_cr_to_process(
             lyman_alpha_path=Path("not used"),
         )
 
-        dependency: GlowsL3BCDependencies = (
-            GlowsL3BCDependencies.download_from_cr_to_process(
-                cr_to_process,
-                sentinel.version,
-                external_dependencies,
-                repointing_file_path,
-            )
+        dependency: GlowsL3BCDependencies = GlowsL3BCDependencies.download_from_cr_to_process(
+            cr_to_process,
+            sentinel.version,
+            external_dependencies,
+            repointing_file_path,
         )
 
         self.assertEqual(
diff --git a/tests/glows/l3bc/test_glows_l3bc_initializer.py b/tests/glows/l3bc/test_glows_l3bc_initializer.py
index 152a66b7..32e3326f 100644
--- a/tests/glows/l3bc/test_glows_l3bc_initializer.py
+++ b/tests/glows/l3bc/test_glows_l3bc_initializer.py
@@ -2,7 +2,7 @@
 import unittest
 from datetime import datetime
 from pathlib import Path
-from unittest.mock import Mock, patch, call, sentinel
+from unittest.mock import Mock, call, patch, sentinel
 
 from imap_data_access import ProcessingInputCollection, RepointInput
 from imap_data_access.file_validation import Version
@@ -20,9 +20,7 @@ def setUp(self):
         self.external_dependencies_fetch_patcher = patch(
             "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.ExternalDependencies.fetch_dependencies"
         )
-        self.mock_external_dependencies_fetch = (
-            self.external_dependencies_fetch_patcher.start()
-        )
+        self.mock_external_dependencies_fetch = self.external_dependencies_fetch_patcher.start()
 
         self.download_patcher = patch(
             "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download"
@@ -39,12 +37,8 @@ def tearDown(self):
         self.download_patcher.stop()
         self.set_global_repoint_table_paths_patcher.stop()
 
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download"
-    )
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.set_global_repoint_table_paths"
-    )
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download")
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.set_global_repoint_table_paths")
     @patch(
         "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.GlowsL3BCDependencies.download_from_cr_to_process"
     )
@@ -53,9 +47,7 @@ def tearDown(self):
     )
     @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.get_date_range_of_cr")
     @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.get_best_ancillary")
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.query"
-    )
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.query")
     @patch(
         "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.GlowsL3BCInitializer.group_l3a_by_cr"
     )
@@ -141,9 +133,7 @@ def test_get_crs_to_process(
         )
 
         mock_download.assert_called_once()
-        mock_set_global_repoint_table_paths.assert_called_with(
-            [mock_download.return_value]
-        )
+        mock_set_global_repoint_table_paths.assert_called_with([mock_download.return_value])
 
         mock_query.assert_has_calls(
             [
@@ -291,15 +281,11 @@ def test_get_crs_to_process(
 
         self.assertEqual(expected_initializer_data, l3bc_initializer_data)
 
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download")
     @patch(
         "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.GlowsL3BCInitializer.group_l3a_by_cr"
     )
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.query"
-    )
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.query")
     def test_get_crs_to_process_return_no_crs_when_missing_ancillaries(
         self, mock_query, mock_group_l3a_by_cr, mock_download
     ):
@@ -317,31 +303,25 @@ def test_get_crs_to_process_return_no_crs_when_missing_ancillaries(
                 def query_that_returns_empty_list_for_missing_ancillary(**kwargs):
                     if (
                         kwargs.get("table") == "ancillary"
-                        and kwargs["descriptor"] != missing_ancillary
+                        and kwargs["descriptor"] != missing_ancillary  # noqa: B023
                     ):
                         return [
                             {
                                 "start_date": "20100101",
                                 "end_date": None,
                                 "ingestion_date": "20100101 00:00:00",
-                                "file_path": f"some/ancillary/{missing_ancillary}",
+                                "file_path": f"some/ancillary/{missing_ancillary}",  # noqa: B023
                             }
                         ]
                     else:
                         return []
 
-                mock_group_l3a_by_cr.return_value = {
-                    2091: {"glows_l3a_hist_20100101_v001.cdf"}
-                }
+                mock_group_l3a_by_cr.return_value = {2091: {"glows_l3a_hist_20100101_v001.cdf"}}
 
-                mock_query.side_effect = (
-                    query_that_returns_empty_list_for_missing_ancillary
-                )
+                mock_query.side_effect = query_that_returns_empty_list_for_missing_ancillary
 
                 actual_crs_to_process = GlowsL3BCInitializer.get_crs_to_process(
-                    ProcessingInputCollection(
-                        RepointInput("imap_2026_269_05.repoint.csv")
-                    ),
+                    ProcessingInputCollection(RepointInput("imap_2026_269_05.repoint.csv")),
                     sentinel.major_version,
                 )
 
@@ -403,12 +383,8 @@ def query_that_returns_empty_list_for_missing_ancillary(**kwargs):
         return_value=True,
     )
     @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.get_best_ancillary")
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download"
-    )
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.query"
-    )
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download")
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.query")
     @patch(
         "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.ExternalDependencies.fetch_dependencies"
     )
@@ -435,38 +411,26 @@ def test_get_crs_to_process_returns_no_crs_when_missing_external_deps(
                 mock_query.reset_mock()
 
                 mock_fetch_ext_dependencies.return_value = external_deps
-                mock_group_l3a_by_cr.return_value = {
-                    2091: {"glows_l3a_hist_20100101_v001.cdf"}
-                }
+                mock_group_l3a_by_cr.return_value = {2091: {"glows_l3a_hist_20100101_v001.cdf"}}
 
                 mock_query.side_effect = [
-                    create_mock_query_results(
-                        ["imap_glows_l3a_hist_20100101_v001.cdf"]
-                    ),
+                    create_mock_query_results(["imap_glows_l3a_hist_20100101_v001.cdf"]),
                     create_mock_query_results(
                         ["imap_glows_l3b_ion-rate-profile_20100101-cr00001_v001.cdf"]
                     ),
                     create_mock_query_results(
                         ["imap_glows_l3c_sw-profile_20100101-cr00001_v001.cdf"]
                     ),
-                    create_mock_query_results(
-                        ["imap_glows_uv-anisotropy-1CR_20100101_v001.dat"]
-                    ),
-                    create_mock_query_results(
-                        ["imap_glows_WawHelioIonMP_20100101_v001.dat"]
-                    ),
-                    create_mock_query_results(
-                        ["imap_glows_bad-days-list_20100101_v001.dat"]
-                    ),
+                    create_mock_query_results(["imap_glows_uv-anisotropy-1CR_20100101_v001.dat"]),
+                    create_mock_query_results(["imap_glows_WawHelioIonMP_20100101_v001.dat"]),
+                    create_mock_query_results(["imap_glows_bad-days-list_20100101_v001.dat"]),
                     create_mock_query_results(
                         ["imap_glows_pipeline-settings-l3bcde_20100101_v003.json"]
                     ),
                 ]
 
                 actual_crs_to_process = GlowsL3BCInitializer.get_crs_to_process(
-                    ProcessingInputCollection(
-                        RepointInput("imap_2026_269_05.repoint.csv")
-                    ),
+                    ProcessingInputCollection(RepointInput("imap_2026_269_05.repoint.csv")),
                     sentinel.major_version,
                 )
 
@@ -516,12 +480,8 @@ def test_get_crs_to_process_returns_no_crs_when_missing_external_deps(
                 expected_initializer_result = GlowsL3BCInitializerData(
                     external_dependencies=external_deps,
                     l3bc_dependencies=[],
-                    l3bs_by_cr={
-                        1: "imap_glows_l3b_ion-rate-profile_20100101-cr00001_v001.cdf"
-                    },
-                    l3cs_by_cr={
-                        1: "imap_glows_l3c_sw-profile_20100101-cr00001_v001.cdf"
-                    },
+                    l3bs_by_cr={1: "imap_glows_l3b_ion-rate-profile_20100101-cr00001_v001.cdf"},
+                    l3cs_by_cr={1: "imap_glows_l3c_sw-profile_20100101-cr00001_v001.cdf"},
                     repoint_file_path=mock_download.return_value,
                 )
 
@@ -593,7 +553,7 @@ def test_should_process_cr_existing_cr_should_process(self, mock_read_cdf_parent
         new_l3a_file = {
             "l3a_file_names": {
                 "imap_glows_l3a_hist_20100101-repoint000001_v001.cdf",
-                "imap_glows_l3a_hist_20100102-repoint000002_v001.cdf"
+                "imap_glows_l3a_hist_20100102-repoint000002_v001.cdf",
                 "imap_glows_l3a_hist_20100103-repoint000002_v001.cdf",
             }
         }
@@ -634,9 +594,7 @@ def test_should_process_cr_existing_cr_should_process(self, mock_read_cdf_parent
                     omni2_data_path=Path("omni2_data_path"),
                 )
 
-                cr_candidate = dataclasses.replace(
-                    already_processed_cr, **new_server_data
-                )
+                cr_candidate = dataclasses.replace(already_processed_cr, **new_server_data)
                 cr_candidate.buffer_time_has_elapsed_since_cr = Mock(return_value=True)
                 cr_candidate.has_valid_external_dependencies = Mock(return_value=True)
 
@@ -659,9 +617,7 @@ def test_should_process_cr_existing_cr_should_process(self, mock_read_cdf_parent
                 actual_version = GlowsL3BCInitializer.should_process_cr_candidate(
                     cr_candidate, l3bs, external_dependencies, new_major_version
                 )
-                expected_version = Version(
-                    new_major_version, existing_file_minor_version + 1
-                )
+                expected_version = Version(new_major_version, existing_file_minor_version + 1)
 
                 mock_read_cdf_parents.assert_called_once_with(
                     f"imap_glows_l3b_ion-rate-profile_20100101-cr02091_{existing_file_version}.cdf"
@@ -670,9 +626,7 @@ def test_should_process_cr_existing_cr_should_process(self, mock_read_cdf_parent
                 self.assertEqual(expected_version, actual_version)
 
     @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.read_cdf_parents")
-    def test_should_process_cr_existing_cr_should_not_reprocess(
-        self, mock_read_cdf_parents
-    ):
+    def test_should_process_cr_existing_cr_should_not_reprocess(self, mock_read_cdf_parents):
         cr_candidate = CRToProcess(
             l3a_file_names={
                 "imap_glows_l3a_hist_20100101-repoint000001_v001.cdf",
@@ -689,9 +643,7 @@ def test_should_process_cr_existing_cr_should_not_reprocess(
         cr_candidate.buffer_time_has_elapsed_since_cr = Mock(return_value=True)
         cr_candidate.has_valid_external_dependencies = Mock(return_value=True)
         existing_version = Version(2, 1)
-        l3bs = {
-            2091: f"imap_glows_l3b_ion-rate-profile_20100101-cr02091_{existing_version}.cdf"
-        }
+        l3bs = {2091: f"imap_glows_l3b_ion-rate-profile_20100101-cr02091_{existing_version}.cdf"}
 
         external_dependencies = ExternalDependencies(
             f107_index_file_path=Path("f107_index_file_path"),
@@ -746,13 +698,9 @@ def test_should_process_cr_with_invalid_dependencies(self):
             )
         )
 
-        cr_candidate.has_valid_external_dependencies.assert_called_once_with(
-            external_dependencies
-        )
+        cr_candidate.has_valid_external_dependencies.assert_called_once_with(external_dependencies)
 
-    @patch(
-        "imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3bc.glows_l3bc_initializer.imap_data_access.download")
     def test_group_l3a_by_cr(self, mock_download):
         l3a_1 = "imap_glows_l3a_hist_20100101-repoint00001_v001.cdf"
         l3a_2 = "imap_glows_l3a_hist_20100102-repoint00002_v001.cdf"
@@ -770,12 +718,8 @@ def test_group_l3a_by_cr(self, mock_download):
 
         expected = {2091: {l3a_1, l3a_2, l3a_3}, 2092: {l3a_4}}
 
-        grouped_l3a_files = GlowsL3BCInitializer.group_l3a_by_cr(
-            [l3a_1, l3a_2, l3a_3, l3a_4]
-        )
+        grouped_l3a_files = GlowsL3BCInitializer.group_l3a_by_cr([l3a_1, l3a_2, l3a_3, l3a_4])
 
-        mock_download.assert_has_calls(
-            [call(l3a_1), call(l3a_2), call(l3a_3), call(l3a_4)]
-        )
+        mock_download.assert_has_calls([call(l3a_1), call(l3a_2), call(l3a_3), call(l3a_4)])
 
         self.assertEqual(expected, grouped_l3a_files)
diff --git a/tests/glows/l3bc/test_models.py b/tests/glows/l3bc/test_models.py
index 4aab5333..a3dec4a9 100644
--- a/tests/glows/l3bc/test_models.py
+++ b/tests/glows/l3bc/test_models.py
@@ -4,23 +4,23 @@
 from datetime import datetime, timedelta
 from pathlib import Path
 from tempfile import TemporaryDirectory
-from unittest.mock import sentinel, patch, call
+from unittest.mock import call, patch, sentinel
 
 import numpy as np
 from spacepy import pycdf
 
 from imap_l3_processing.constants import (
-    TEMP_CDF_FOLDER_PATH,
     CARRINGTON_ROTATION_IN_NANOSECONDS,
+    TEMP_CDF_FOLDER_PATH,
 )
 from imap_l3_processing.glows.l3bc.models import (
-    GlowsL3BIonizationRate,
-    GlowsL3CSolarWind,
-    CRToProcess,
-    ExternalDependencies,
     F107_FLUX_TABLE_URL,
     LYMAN_ALPHA_COMPOSITE_INDEX_URL,
     OMNI2_URL,
+    CRToProcess,
+    ExternalDependencies,
+    GlowsL3BIonizationRate,
+    GlowsL3CSolarWind,
 )
 from tests.swapi.cdf_model_test_case import CdfModelTestCase
 from tests.test_helpers import get_test_instrument_team_data_path
@@ -61,9 +61,7 @@ def test_external_dependencies_fetch_dependencies(
         self.assertEqual(expected_external_deps, external_dependencies)
 
     @patch("imap_l3_processing.glows.l3bc.models.download_external_dependency")
-    def test_external_dependencies_files_not_found(
-        self, mock_download_external_dependencies
-    ):
+    def test_external_dependencies_files_not_found(self, mock_download_external_dependencies):
         mock_download_external_dependencies.return_value = None
 
         external_dependencies = ExternalDependencies.fetch_dependencies()
@@ -71,9 +69,7 @@ def test_external_dependencies_files_not_found(
         self.assertEqual(ExternalDependencies(None, None, None), external_dependencies)
 
     @patch("imap_l3_processing.glows.l3bc.models.download_external_dependency")
-    def test_external_dependencies_comment_headers(
-        self, mock_download_external_dependencies
-    ):
+    def test_external_dependencies_comment_headers(self, mock_download_external_dependencies):
         with tempfile.TemporaryDirectory() as tmpdir:
             file_name = Path(tmpdir) / "flux_table.txt"
             with open(file_name, "w") as fp:
@@ -97,9 +93,7 @@ def test_external_dependencies_comment_headers(
 
     @patch("imap_l3_processing.glows.l3bc.models.datetime")
     @patch("imap_l3_processing.glows.l3bc.models.imap_data_access.download")
-    def test_cr_to_process_buffer_time_has_elapsed_since_cr(
-        self, mock_download, mock_datetime
-    ):
+    def test_cr_to_process_buffer_time_has_elapsed_since_cr(self, mock_download, mock_datetime):
         with TemporaryDirectory() as temp_dir:
             temp_dir = Path(temp_dir)
             fake_pipeline_settings = temp_dir / "fake_pipeline_settings.json"
@@ -177,9 +171,7 @@ def test_cr_to_process_has_valid_external_dependencies(
                 Path("f107_index_file_path"),
                 Path("lyman_alpha_path"),
             )
-            self.assertEqual(
-                mock_validate_dependencies.return_value, actual_has_valid_ext_deps
-            )
+            self.assertEqual(mock_validate_dependencies.return_value, actual_has_valid_ext_deps)
 
     def test_l3b_to_data_product_variables(self):
         data = GlowsL3BIonizationRate(
@@ -206,12 +198,8 @@ def test_l3b_to_data_product_variables(self):
 
         variables = iter(variables)
         self.assert_variable_attributes(next(variables), sentinel.epoch, "epoch")
-        self.assert_variable_attributes(
-            next(variables), sentinel.epoch_delta, "epoch_delta"
-        )
-        self.assert_variable_attributes(
-            next(variables), sentinel.mean_time, "mean_time"
-        )
+        self.assert_variable_attributes(next(variables), sentinel.epoch_delta, "epoch_delta")
+        self.assert_variable_attributes(next(variables), sentinel.mean_time, "mean_time")
         self.assert_variable_attributes(next(variables), sentinel.cr, "cr")
         self.assert_variable_attributes(
             next(variables), sentinel.uv_anisotropy_factor, "uv_anisotropy_factor"
@@ -220,38 +208,24 @@ def test_l3b_to_data_product_variables(self):
         self.assert_variable_attributes(next(variables), sentinel.sum_rate, "sum_rate")
         self.assert_variable_attributes(next(variables), sentinel.ph_rate, "ph_rate")
         self.assert_variable_attributes(next(variables), sentinel.cx_rate, "cx_rate")
-        self.assert_variable_attributes(
-            next(variables), sentinel.sum_uncert, "sum_uncert"
-        )
-        self.assert_variable_attributes(
-            next(variables), sentinel.ph_uncert, "ph_uncert"
-        )
-        self.assert_variable_attributes(
-            next(variables), sentinel.cx_uncert, "cx_uncert"
-        )
-        self.assert_variable_attributes(
-            next(variables), sentinel.lat_grid_label, "lat_grid_label"
-        )
+        self.assert_variable_attributes(next(variables), sentinel.sum_uncert, "sum_uncert")
+        self.assert_variable_attributes(next(variables), sentinel.ph_uncert, "ph_uncert")
+        self.assert_variable_attributes(next(variables), sentinel.cx_uncert, "cx_uncert")
+        self.assert_variable_attributes(next(variables), sentinel.lat_grid_label, "lat_grid_label")
         self.assert_variable_attributes(
             next(variables), sentinel.uv_anisotropy_flag, "uv_anisotropy_flag"
         )
         self.assert_variable_attributes(next(variables), sentinel.used_l3a, "used_l3a")
-        self.assert_variable_attributes(
-            next(variables), sentinel.glows_flags, "glows_flags"
-        )
+        self.assert_variable_attributes(next(variables), sentinel.glows_flags, "glows_flags")
 
         self.assertIsNone(next(variables, None))
 
     def test_l3b_from_instrument_team_dictionary(self):
         glows_instrument_team_data_path = get_test_instrument_team_data_path("glows")
-        with open(
-            glows_instrument_team_data_path / "imap_glows_l3b_cr_2091_v00.json"
-        ) as f:
+        with open(glows_instrument_team_data_path / "imap_glows_l3b_cr_2091_v00.json") as f:
             instrument_team_l3b_dict = json.load(f)
 
-        instrument_team_l3b_dict["header"]["ancillary_data_files"][
-            "pipeline_settings"
-        ] = (
+        instrument_team_l3b_dict["header"]["ancillary_data_files"]["pipeline_settings"] = (
             glows_instrument_team_data_path
             / "imap_glows_pipeline-settings-l3bcde_20250514_v004.json"
         )
@@ -260,9 +234,7 @@ def test_l3b_from_instrument_team_dictionary(self):
             instrument_team_l3b_dict, sentinel.input_metadata
         )
 
-        latitude_grid = np.array(
-            instrument_team_l3b_dict["ion_rate_profile"]["lat_grid"]
-        )
+        latitude_grid = np.array(instrument_team_l3b_dict["ion_rate_profile"]["lat_grid"])
         self.assertIsInstance(result, GlowsL3BIonizationRate)
 
         self.assertEqual(sentinel.input_metadata, result.input_metadata)
@@ -270,9 +242,7 @@ def test_l3b_from_instrument_team_dictionary(self):
         np.testing.assert_array_equal(
             [datetime.fromisoformat("2009-12-20 20:14:51.360")], result.epoch
         )
-        np.testing.assert_equal(
-            [CARRINGTON_ROTATION_IN_NANOSECONDS / 2], result.epoch_delta
-        )
+        np.testing.assert_equal([CARRINGTON_ROTATION_IN_NANOSECONDS / 2], result.epoch_delta)
         np.testing.assert_equal(
             [datetime.fromisoformat("2010-01-02 03:43:28.667")], result.mean_time
         )
@@ -356,9 +326,7 @@ def test_l3b_from_instrument_team_dictionary(self):
         )
         self.assertEqual((1, 50), result.used_l3a.shape)
         np.testing.assert_array_equal(result.used_l3a[0, 3:], "")
-        np.testing.assert_equal(
-            [instrument_team_l3b_dict["glows_flags"]], result.glows_flags
-        )
+        np.testing.assert_equal([instrument_team_l3b_dict["glows_flags"]], result.glows_flags)
 
     def test_l3c_to_data_product_variables(self):
         data = GlowsL3CSolarWind(
@@ -445,26 +413,20 @@ def test_l3c_to_data_product_variables(self):
             "proton_density_profile",
             expected_data_type=pycdf.const.CDF_FLOAT,
         )
-        self.assert_variable_attributes(
-            next(variables), sentinel.glows_flags, "glows_flags"
-        )
+        self.assert_variable_attributes(next(variables), sentinel.glows_flags, "glows_flags")
 
         self.assertIsNone(next(variables, None))
 
     def test_l3c_from_instrument_team_dictionary(self):
         glows_instrument_team_data_path = get_test_instrument_team_data_path("glows")
-        with open(
-            glows_instrument_team_data_path / "imap_glows_l3c_cr_2091_v00.json"
-        ) as f:
+        with open(glows_instrument_team_data_path / "imap_glows_l3c_cr_2091_v00.json") as f:
             model = json.load(f)
         model["header"]["ancillary_data_files"]["pipeline_settings"] = (
             glows_instrument_team_data_path
             / "imap_glows_pipeline-settings-L3bc_20250707_v002.json"
         )
         latitude_grid = model["solar_wind_profile"]["lat_grid"]
-        result = GlowsL3CSolarWind.from_instrument_team_dictionary(
-            model, sentinel.input_metadata
-        )
+        result = GlowsL3CSolarWind.from_instrument_team_dictionary(model, sentinel.input_metadata)
 
         self.assertIsInstance(result, GlowsL3CSolarWind)
 
@@ -472,9 +434,7 @@ def test_l3c_from_instrument_team_dictionary(self):
         np.testing.assert_array_equal(
             [datetime.fromisoformat("2009-12-20 20:14:51.360")], result.epoch
         )
-        np.testing.assert_equal(
-            [CARRINGTON_ROTATION_IN_NANOSECONDS / 2], result.epoch_delta
-        )
+        np.testing.assert_equal([CARRINGTON_ROTATION_IN_NANOSECONDS / 2], result.epoch_delta)
         np.testing.assert_array_equal(
             [datetime.fromisoformat("2010-01-02 03:43:28.667")], result.mean_time
         )
diff --git a/tests/glows/l3bc/test_utils.py b/tests/glows/l3bc/test_utils.py
index 10c3b47a..38887a97 100644
--- a/tests/glows/l3bc/test_utils.py
+++ b/tests/glows/l3bc/test_utils.py
@@ -1,13 +1,12 @@
 import unittest
 from datetime import datetime
-from typing import Optional
 
 import numpy as np
 from imap_processing.spice.repoint import set_global_repoint_table_paths
 
 from imap_l3_processing.glows.l3bc.utils import (
-    get_pointing_date_range,
     get_best_ancillary,
+    get_pointing_date_range,
 )
 from tests.test_helpers import get_test_data_path
 
@@ -91,9 +90,7 @@ def test_determine_crs_to_process_based_on_ancillary_files(self):
                     start_date, end_date, available_ancillaries
                 )
 
-                self.assertEqual(
-                    expected_best_ancillary_file_name, actual_ancillary_name
-                )
+                self.assertEqual(expected_best_ancillary_file_name, actual_ancillary_name)
 
     def test_get_pointing_date_range(self):
         repointing_number = 13
@@ -137,7 +134,7 @@ def create_imap_data_access_json(
     start_date: str,
     descriptor: str = "hist",
     version: str = "v001",
-    repointing: Optional[int] = None,
+    repointing: int | None = None,
 ) -> dict:
     return {
         "file_path": file_path,
diff --git a/tests/glows/l3d/test_glows_l3d_dependencies.py b/tests/glows/l3d/test_glows_l3d_dependencies.py
index 2e35b6ae..4ef0d068 100644
--- a/tests/glows/l3d/test_glows_l3d_dependencies.py
+++ b/tests/glows/l3d/test_glows_l3d_dependencies.py
@@ -1,6 +1,6 @@
 import unittest
 from pathlib import Path
-from unittest.mock import Mock, sentinel, patch, call
+from unittest.mock import Mock, call, patch, sentinel
 
 from imap_data_access.processing_input import ProcessingInputCollection
 
@@ -11,9 +11,7 @@
 
 class TestGlowsL3DDependencies(unittest.TestCase):
     @patch("imap_l3_processing.glows.l3d.glows_l3d_dependencies.ScienceFilePath")
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_dependencies.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_dependencies.imap_data_access.download")
     def test_fetch_dependencies(self, mock_download, mock_science_file_path):
         waw_helio_ion_mp_speed = get_test_data_path(
             "glows/imap_glows_plasma-speed-2026d_20251113_v003.dat"
@@ -27,9 +25,7 @@ def test_fetch_dependencies(self, mock_download, mock_science_file_path):
         waw_helio_ion_mp_phion = get_test_data_path(
             "glows/imap_glows_photoion-2026d_20251113_v003.dat"
         )
-        waw_helio_ion_mp_lya = get_test_data_path(
-            "glows/imap_glows_lya-2026d_20251113_v003.dat"
-        )
+        waw_helio_ion_mp_lya = get_test_data_path("glows/imap_glows_lya-2026d_20251113_v003.dat")
         waw_helio_ion_mp_e_dens = get_test_data_path(
             "glows/imap_glows_electron-density-2026d_20251113_v003.dat"
         )
@@ -83,10 +79,8 @@ def test_fetch_dependencies(self, mock_download, mock_science_file_path):
             omni2_data_path=None,
         )
 
-        actual_dependencies: GlowsL3DDependencies = (
-            GlowsL3DDependencies.fetch_dependencies(
-                mock_processing_input_collection, external_dependencies
-            )
+        actual_dependencies: GlowsL3DDependencies = GlowsL3DDependencies.fetch_dependencies(
+            mock_processing_input_collection, external_dependencies
         )
 
         mock_processing_input_collection.get_file_paths.assert_has_calls(
diff --git a/tests/glows/l3d/test_glows_l3d_initializer.py b/tests/glows/l3d/test_glows_l3d_initializer.py
index eda08f4f..a49dae99 100644
--- a/tests/glows/l3d/test_glows_l3d_initializer.py
+++ b/tests/glows/l3d/test_glows_l3d_initializer.py
@@ -1,15 +1,15 @@
 import unittest
-from unittest.mock import patch, call, Mock, sentinel
+from unittest.mock import Mock, call, patch, sentinel
 
 from imap_data_access.file_validation import Version
 
 from imap_l3_processing.glows.descriptors import (
-    GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
+    GLOWS_L3B_DESCRIPTOR,
     GLOWS_L3E_HI_45_DESCRIPTOR,
     GLOWS_L3E_HI_90_DESCRIPTOR,
     GLOWS_L3E_LO_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
     GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
-    GLOWS_L3B_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3d.glows_l3d_initializer import GlowsL3DInitializer
 from imap_l3_processing.glows.l3e.reprocess_info import ReprocessInfo, ReprocessTargets
@@ -20,9 +20,7 @@ class TestGlowsL3DInitializer(unittest.TestCase):
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_cdf_parents")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_pipeline_settings")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.query")
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download")
     @patch(
         "imap_l3_processing.glows.l3d.glows_l3d_initializer.GlowsL3DDependencies.fetch_dependencies"
     )
@@ -61,7 +59,7 @@ def test_l3d_initializer(
             "imap_glows_lya-2026d_19470301_v000.dat",
             "imap_glows_uv-anisotropy-2026d_19470301_v000.dat",
             "imap_glows_photoion-2026d_19470301_v000.dat",
-            "imap_glows_electron-density-2026d_19470301_v000.dat"
+            "imap_glows_electron-density-2026d_19470301_v000.dat",
             "lyman-alpha-composite.nc",
         }
 
@@ -158,20 +156,14 @@ def test_l3d_initializer(
                 mock_download.assert_called_once_with(
                     "imap_glows_pipeline-settings-l3bcde_19470301_v000.json"
                 )
-                mock_read_pipeline_settings.assert_called_once_with(
-                    mock_download.return_value
-                )
+                mock_read_pipeline_settings.assert_called_once_with(mock_download.return_value)
 
                 [fetch_dependencies_call] = mock_fetch_l3d_dependencies.call_args_list
 
                 [actual_l3d_inputs, actual_external_deps] = fetch_dependencies_call.args
 
-                pipeline_l3d_input_paths = actual_l3d_inputs.get_file_paths(
-                    source="glows"
-                )
-                pipeline_l3d_input_filenames = [
-                    p.name for p in pipeline_l3d_input_paths
-                ]
+                pipeline_l3d_input_paths = actual_l3d_inputs.get_file_paths(source="glows")
+                pipeline_l3d_input_filenames = [p.name for p in pipeline_l3d_input_paths]
                 self.assertEqual(
                     [
                         "imap_glows_l3b_ion-rate-profile_20200101-cr00001_v000.cdf",
@@ -194,16 +186,12 @@ def test_l3d_initializer(
                 self.assertEqual(external_dependencies, actual_external_deps)
 
                 self.assertEqual(Version(requested_major_version, 2), actual_version)
-                self.assertEqual(
-                    mock_fetch_l3d_dependencies.return_value, actual_l3d_deps
-                )
+                self.assertEqual(mock_fetch_l3d_dependencies.return_value, actual_l3d_deps)
                 self.assertEqual(most_recent_l3d, actual_old_l3d)
 
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_cdf_parents")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_pipeline_settings")
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.query")
     @patch(
         "imap_l3_processing.glows.l3d.glows_l3d_initializer.GlowsL3DDependencies.fetch_dependencies"
@@ -251,19 +239,15 @@ def test_l3d_initializer_should_process_l3d_when_major_version_changes(
 
         mock_query.side_effect = self._create_ancillary_query_results([most_recent_l3d])
         new_major_version = 1
-        actual_version, actual_l3d_deps, actual_old_l3d = (
-            GlowsL3DInitializer.should_process_l3d(
-                external_dependencies, l3bs, l3cs, ReprocessInfo([]), new_major_version
-            )
+        actual_version, actual_l3d_deps, actual_old_l3d = GlowsL3DInitializer.should_process_l3d(
+            external_dependencies, l3bs, l3cs, ReprocessInfo([]), new_major_version
         )
 
         self.assertEqual(Version(new_major_version, 2), actual_version)
         self.assertEqual(mock_fetch_l3d_dependencies.return_value, actual_l3d_deps)
         self.assertEqual(most_recent_l3d, actual_old_l3d)
 
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download")
     @patch(
         "imap_l3_processing.glows.l3d.glows_l3d_initializer.read_pipeline_settings",
         return_value={"start_cr": 0},
@@ -290,9 +274,7 @@ def test_l3d_initializer_returns_no_old_cdf_if_none_found(
         mock_fetch_l3d_deps.assert_called_once()
         self.assertIsNone(old_l3d)
 
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_pipeline_settings")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_cdf_parents")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.query")
@@ -357,9 +339,7 @@ def test_l3d_initializer_should_not_process_when_no_l3bs(self, mock_fetch_l3d_de
         mock_fetch_l3d_deps.assert_not_called()
         self.assertIsNone(actual_l3d_deps)
 
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.query")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_pipeline_settings")
     @patch(
@@ -387,9 +367,7 @@ def test_l3d_initializer_does_not_process_when_no_l3bs_after_start_cr(
         mock_fetch_l3d_deps.assert_not_called()
         self.assertIsNone(actual_l3d_deps)
 
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_cdf_parents")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.query")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_pipeline_settings")
@@ -407,9 +385,7 @@ def test_l3d_initializer_forces_reprocess_if_reprocess_ancillary_specifies_l3e(
         most_recent_l3d = "imap_glows_l3d_solar-hist_19470301-cr00002_v001.0002.cdf"
 
         mock_fetch_dependencies.return_value = sentinel.l3d_deps
-        mock_query.side_effect = (
-            self._create_ancillary_query_results([most_recent_l3d]) * 6
-        )
+        mock_query.side_effect = self._create_ancillary_query_results([most_recent_l3d]) * 6
         mock_read_pipeline_settings.return_value = {"start_cr": 1}
 
         l3bs = [
@@ -481,12 +457,8 @@ def test_l3d_initializer_forces_reprocess_if_reprocess_ancillary_specifies_l3e(
 
                 [actual_l3d_inputs, actual_external_deps] = fetch_dependencies_call.args
 
-                pipeline_l3d_input_paths = actual_l3d_inputs.get_file_paths(
-                    source="glows"
-                )
-                pipeline_l3d_input_filenames = [
-                    p.name for p in pipeline_l3d_input_paths
-                ]
+                pipeline_l3d_input_paths = actual_l3d_inputs.get_file_paths(source="glows")
+                pipeline_l3d_input_filenames = [p.name for p in pipeline_l3d_input_paths]
                 self.assertEqual(
                     [
                         "imap_glows_l3b_ion-rate-profile_20200101-cr00001_v000.cdf",
@@ -506,9 +478,7 @@ def test_l3d_initializer_forces_reprocess_if_reprocess_ancillary_specifies_l3e(
 
                 self.assertEqual(external_dependencies, actual_external_deps)
 
-    @patch(
-        "imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.download")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_cdf_parents")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.imap_data_access.query")
     @patch("imap_l3_processing.glows.l3d.glows_l3d_initializer.read_pipeline_settings")
@@ -526,9 +496,7 @@ def test_l3d_initializer_does_not_force_reprocess_if_no_l3e_products(
         most_recent_l3d = "imap_glows_l3d_solar-hist_19470301-cr00002_v001.0002.cdf"
 
         mock_fetch_dependencies.return_value = sentinel.l3d_deps
-        mock_query.side_effect = (
-            self._create_ancillary_query_results([most_recent_l3d]) * 2
-        )
+        mock_query.side_effect = self._create_ancillary_query_results([most_recent_l3d]) * 2
         mock_read_pipeline_settings.return_value = {"start_cr": 1}
 
         l3bs = ["imap_glows_l3b_ion-rate-profile_20200101-cr00001_v000.cdf"]
@@ -569,21 +537,11 @@ def test_l3d_initializer_does_not_force_reprocess_if_no_l3e_products(
     def _create_ancillary_query_results(self, l3d_query_result):
         return [
             create_mock_query_results(l3d_query_result),
-            create_mock_query_results(
-                ["imap_glows_plasma-speed-2026d_19470301_v001.dat"]
-            ),
-            create_mock_query_results(
-                ["imap_glows_proton-density-2026d_19470301_v000.dat"]
-            ),
-            create_mock_query_results(
-                ["imap_glows_uv-anisotropy-2026d_19470301_v000.dat"]
-            ),
+            create_mock_query_results(["imap_glows_plasma-speed-2026d_19470301_v001.dat"]),
+            create_mock_query_results(["imap_glows_proton-density-2026d_19470301_v000.dat"]),
+            create_mock_query_results(["imap_glows_uv-anisotropy-2026d_19470301_v000.dat"]),
             create_mock_query_results(["imap_glows_photoion-2026d_19470301_v000.dat"]),
             create_mock_query_results(["imap_glows_lya-2026d_19470301_v000.dat"]),
-            create_mock_query_results(
-                ["imap_glows_electron-density-2026d_19470301_v000.dat"]
-            ),
-            create_mock_query_results(
-                ["imap_glows_pipeline-settings-l3bcde_19470301_v000.json"]
-            ),
+            create_mock_query_results(["imap_glows_electron-density-2026d_19470301_v000.dat"]),
+            create_mock_query_results(["imap_glows_pipeline-settings-l3bcde_19470301_v000.json"]),
         ]
diff --git a/tests/glows/l3d/test_l3d_utils.py b/tests/glows/l3d/test_l3d_utils.py
index 4b1c412b..3e3b761c 100644
--- a/tests/glows/l3d/test_l3d_utils.py
+++ b/tests/glows/l3d/test_l3d_utils.py
@@ -2,34 +2,30 @@
 import unittest
 from datetime import datetime
 from pathlib import Path
-from unittest.mock import patch, mock_open, MagicMock, sentinel, Mock, call
+from unittest.mock import MagicMock, Mock, call, mock_open, patch, sentinel
 
 import numpy as np
 
 import imap_l3_processing
 from imap_l3_processing.glows.l3d.models import GlowsL3DSolarParamsHistory
 from imap_l3_processing.glows.l3d.utils import (
-    create_glows_l3b_json_file_from_cdf,
     convert_json_to_l3d_data_product,
+    create_glows_l3b_json_file_from_cdf,
     create_glows_l3c_json_file_from_cdf,
+    get_most_recently_uploaded_ancillary,
     get_parent_file_names_from_l3d_json,
     rename_l3d_text_outputs,
-    get_most_recently_uploaded_ancillary,
 )
 from imap_l3_processing.models import InputMetadata
-from tests.test_helpers import get_test_data_path, create_mock_query_results
+from tests.test_helpers import create_mock_query_results, get_test_data_path
 
 
 class TestL3dUtils(unittest.TestCase):
     @patch("imap_l3_processing.glows.l3d.utils.os")
     @patch("imap_l3_processing.glows.l3d.utils.json")
     @patch("builtins.open", new_callable=mock_open, create=False)
-    def test_create_glows_l3c_json_file_from_cdf(
-        self, mock_open_file, mock_json, mock_os
-    ):
-        l3c_path = get_test_data_path(
-            "glows/imap_glows_l3c_sw-profile_20101030_v008.cdf"
-        )
+    def test_create_glows_l3c_json_file_from_cdf(self, mock_open_file, mock_json, mock_os):
+        l3c_path = get_test_data_path("glows/imap_glows_l3c_sw-profile_20101030_v008.cdf")
 
         expected: dict = {
             "solar_wind_profile": {
@@ -89,18 +85,12 @@ def test_create_glows_l3c_json_file_from_cdf(
         create_glows_l3c_json_file_from_cdf(l3c_path)
 
         data_path = (
-            Path(imap_l3_processing.__file__).parent
-            / "glows"
-            / "l3d"
-            / "science"
-            / "data_l3c"
+            Path(imap_l3_processing.__file__).parent / "glows" / "l3d" / "science" / "data_l3c"
         )
 
         mock_os.makedirs.assert_called_once_with(data_path, exist_ok=True)
 
-        mock_open_file.assert_called_once_with(
-            data_path / "imap_glows_l3c_cr_2103_v008.json", "w"
-        )
+        mock_open_file.assert_called_once_with(data_path / "imap_glows_l3c_cr_2103_v008.json", "w")
 
         mock_json.dump.assert_called_once()
         actual = mock_json.dump.call_args.args[0]
@@ -139,12 +129,8 @@ def test_create_glows_l3c_json_file_from_cdf(
     @patch("imap_l3_processing.glows.l3d.utils.os")
     @patch("imap_l3_processing.glows.l3d.utils.json")
     @patch("builtins.open", new_callable=mock_open, create=False)
-    def test_create_glows_l3b_json_file_from_cdf(
-        self, mock_open_file, mock_json, mock_os
-    ):
-        l3b_path = get_test_data_path(
-            "glows/imap_glows_l3b_ion-rate-profile_20100422_v011.cdf"
-        )
+    def test_create_glows_l3b_json_file_from_cdf(self, mock_open_file, mock_json, mock_os):
+        l3b_path = get_test_data_path("glows/imap_glows_l3b_ion-rate-profile_20100422_v011.cdf")
 
         expected: dict = {
             "header": {
@@ -227,11 +213,7 @@ def test_create_glows_l3b_json_file_from_cdf(
         create_glows_l3b_json_file_from_cdf(l3b_path)
 
         data_path = (
-            Path(imap_l3_processing.__file__).parent
-            / "glows"
-            / "l3d"
-            / "science"
-            / "data_l3b"
+            Path(imap_l3_processing.__file__).parent / "glows" / "l3d" / "science" / "data_l3b"
         )
 
         mock_os.makedirs.assert_called_once_with(data_path, exist_ok=True)
@@ -240,9 +222,7 @@ def test_create_glows_l3b_json_file_from_cdf(
         actual = mock_json.dump.call_args.args[0]
         self.assertEqual(json_file, mock_json.dump.call_args.args[1])
 
-        mock_open_file.assert_called_once_with(
-            data_path / "imap_glows_l3b_cr_2096_v011.json", "w"
-        )
+        mock_open_file.assert_called_once_with(data_path / "imap_glows_l3b_cr_2096_v011.json", "w")
 
         self.assertIsInstance(actual["CR"], int)
         self.assertEqual(expected["CR"], actual["CR"])
@@ -250,9 +230,7 @@ def test_create_glows_l3b_json_file_from_cdf(
         self.assertIsInstance(actual["date"], str)
         self.assertEqual(actual["date"], expected["date"])
 
-        np.testing.assert_array_equal(
-            expected["header"]["filename"], actual["header"]["filename"]
-        )
+        np.testing.assert_array_equal(expected["header"]["filename"], actual["header"]["filename"])
 
         self.assertIsInstance(actual["uv_anisotropy_factor"], list)
         np.testing.assert_array_equal(
@@ -289,9 +267,7 @@ def test_convert_json_l3d_to_data_product(self):
         )
 
         self.assertEqual(input_metadata, l3d_data_product.input_metadata)
-        self.assertEqual(
-            input_metadata.start_date, datetime.fromisoformat("1947-03-03").date()
-        )
+        self.assertEqual(input_metadata.start_date, datetime.fromisoformat("1947-03-03").date())
 
         self.assertEqual(sentinel.parent_file_names, l3d_data_product.parent_file_names)
 
@@ -333,9 +309,7 @@ def test_convert_json_l3d_to_data_product(self):
             l3d_data_product.epoch[-1],
         )
 
-        np.testing.assert_array_equal(
-            np.arange(-90, 100, step=10), l3d_data_product.latitude
-        )
+        np.testing.assert_array_equal(np.arange(-90, 100, step=10), l3d_data_product.latitude)
 
         self.assertEqual(846, len(l3d_data_product.plasma_speed))
         np.testing.assert_allclose(
@@ -494,20 +468,12 @@ def test_convert_json_l3d_to_data_product(self):
         )
 
         self.assertEqual(846, len(l3d_data_product.phion))
-        np.testing.assert_allclose(
-            1.830438692701064e-07, l3d_data_product.phion[0], rtol=1e-6
-        )
-        np.testing.assert_allclose(
-            1.0538921234648196e-07, l3d_data_product.phion[-1], rtol=1e-6
-        )
+        np.testing.assert_allclose(1.830438692701064e-07, l3d_data_product.phion[0], rtol=1e-6)
+        np.testing.assert_allclose(1.0538921234648196e-07, l3d_data_product.phion[-1], rtol=1e-6)
 
         self.assertEqual(846, len(l3d_data_product.lyman_alpha))
-        np.testing.assert_allclose(
-            619975763789.9209, l3d_data_product.lyman_alpha[0], rtol=1e-6
-        )
-        np.testing.assert_allclose(
-            396312787467.8571, l3d_data_product.lyman_alpha[-1], rtol=1e-6
-        )
+        np.testing.assert_allclose(619975763789.9209, l3d_data_product.lyman_alpha[0], rtol=1e-6)
+        np.testing.assert_allclose(396312787467.8571, l3d_data_product.lyman_alpha[-1], rtol=1e-6)
 
         self.assertEqual(846, len(l3d_data_product.electron_density))
         self.assertEqual(-1.0, l3d_data_product.electron_density[0])
@@ -517,21 +483,15 @@ def test_convert_json_l3d_to_data_product(self):
 
         self.assertEqual(846, len(l3d_data_product.plasma_speed_flag))
         self.assertEqual(-1.0, l3d_data_product.plasma_speed_flag[0])
-        np.testing.assert_allclose(
-            20001.0, l3d_data_product.plasma_speed_flag[-1], rtol=1e-6
-        )
+        np.testing.assert_allclose(20001.0, l3d_data_product.plasma_speed_flag[-1], rtol=1e-6)
 
         self.assertEqual(846, len(l3d_data_product.uv_anisotropy_flag))
         self.assertEqual(-1.0, l3d_data_product.uv_anisotropy_flag[0])
-        np.testing.assert_allclose(
-            30001.0, l3d_data_product.uv_anisotropy_flag[-1], rtol=1e-6
-        )
+        np.testing.assert_allclose(30001.0, l3d_data_product.uv_anisotropy_flag[-1], rtol=1e-6)
 
         self.assertEqual(846, len(l3d_data_product.proton_density_flag))
         self.assertEqual(-1.0, l3d_data_product.proton_density_flag[0])
-        np.testing.assert_allclose(
-            10001.0, l3d_data_product.proton_density_flag[-1], rtol=1e-6
-        )
+        np.testing.assert_allclose(10001.0, l3d_data_product.proton_density_flag[-1], rtol=1e-6)
 
         self.assertEqual(846, len(l3d_data_product.glows_flags))
         self.assertEqual(0, int(l3d_data_product.glows_flags[0]))
@@ -563,9 +523,7 @@ def test_rename_l3d_text_outputs(self, mock_get_midpoint_of_cr):
         with tempfile.TemporaryDirectory() as tmpdir:
             tmpdir = Path(tmpdir)
             original_lya_path = tmpdir / "imap_glows_l3d_lya_19470303-cr02092_v00.dat"
-            original_p_dens_path = (
-                tmpdir / "imap_glows_l3d_p-dens_19470303-cr02092_v00.dat"
-            )
+            original_p_dens_path = tmpdir / "imap_glows_l3d_p-dens_19470303-cr02092_v00.dat"
 
             original_lya_path.write_text("lya")
             original_p_dens_path.write_text("p_dens")
@@ -580,13 +538,9 @@ def test_rename_l3d_text_outputs(self, mock_get_midpoint_of_cr):
             mock_get_midpoint_of_cr.assert_has_calls([call(2092), call(2092)])
 
             expected_lya_output = tmpdir / "imap_glows_lya_19470303_20100201_v012.dat"
-            expected_p_dens_output = (
-                tmpdir / "imap_glows_p-dens_19470303_20100201_v012.dat"
-            )
+            expected_p_dens_output = tmpdir / "imap_glows_p-dens_19470303_20100201_v012.dat"
 
-            self.assertEqual(
-                [expected_lya_output, expected_p_dens_output], actual_new_paths
-            )
+            self.assertEqual([expected_lya_output, expected_p_dens_output], actual_new_paths)
 
             self.assertEqual("lya", expected_lya_output.read_text())
             self.assertEqual("p_dens", expected_p_dens_output.read_text())
diff --git a/tests/glows/l3d/test_models.py b/tests/glows/l3d/test_models.py
index 89930104..779afc70 100644
--- a/tests/glows/l3d/test_models.py
+++ b/tests/glows/l3d/test_models.py
@@ -4,22 +4,22 @@
 
 from imap_l3_processing.constants import CARRINGTON_ROTATION_IN_NANOSECONDS
 from imap_l3_processing.glows.l3d.models import (
-    GlowsL3DSolarParamsHistory,
-    SPEED_CDF_VAR_NAME,
-    PHION_CDF_VAR_NAME,
+    CR_CDF_VAR_NAME,
+    ELECTRON_DENSITY_CDF_VAR_NAME,
     EPOCH_CDF_VAR_NAME,
     EPOCH_DELTA_CDF_VAR_NAME,
+    GLOWS_FLAGS_CDF_VAR_NAME,
     LATITUDE_CDF_CDF_VAR_NAME,
     LATITUDE_LABEL_CDF_VAR_NAME,
-    CR_CDF_VAR_NAME,
-    PROTON_DENSITY_CDF_VAR_NAME,
-    UV_ANISOTROPY_CDF_VAR_NAME,
     LYMAN_ALPHA_CDF_VAR_NAME,
-    ELECTRON_DENSITY_CDF_VAR_NAME,
+    PHION_CDF_VAR_NAME,
     PLASMA_SPEED_FLAG_CDF_VAR_NAME,
-    UV_ANISOTROPY_FLAG_CDF_VAR_NAME,
+    PROTON_DENSITY_CDF_VAR_NAME,
     PROTON_DENSITY_FLAG_CDF_VAR_NAME,
-    GLOWS_FLAGS_CDF_VAR_NAME,
+    SPEED_CDF_VAR_NAME,
+    UV_ANISOTROPY_CDF_VAR_NAME,
+    UV_ANISOTROPY_FLAG_CDF_VAR_NAME,
+    GlowsL3DSolarParamsHistory,
 )
 from tests.swapi.cdf_model_test_case import CdfModelTestCase
 
@@ -62,9 +62,7 @@ def test_glows_l3d_solar_params_history_to_data_product(self):
 
         variables = data_product.to_data_product_variables()
 
-        expected_epoch_delta = np.full_like(
-            epoch, CARRINGTON_ROTATION_IN_NANOSECONDS / 2
-        )
+        expected_epoch_delta = np.full_like(epoch, CARRINGTON_ROTATION_IN_NANOSECONDS / 2)
         expected_latitude_label = [f"{deg:.1f} degrees" for deg in latitude]
 
         self.assertEqual(15, len(variables))
@@ -73,16 +71,12 @@ def test_glows_l3d_solar_params_history_to_data_product(self):
         self.assert_variable_attributes(
             next(variables), expected_epoch_delta, EPOCH_DELTA_CDF_VAR_NAME
         )
-        self.assert_variable_attributes(
-            next(variables), latitude, LATITUDE_CDF_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), latitude, LATITUDE_CDF_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), expected_latitude_label, LATITUDE_LABEL_CDF_VAR_NAME
         )
         self.assert_variable_attributes(next(variables), cr, CR_CDF_VAR_NAME)
-        self.assert_variable_attributes(
-            next(variables), plasma_speed, SPEED_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), plasma_speed, SPEED_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), proton_density, PROTON_DENSITY_CDF_VAR_NAME
         )
@@ -90,9 +84,7 @@ def test_glows_l3d_solar_params_history_to_data_product(self):
             next(variables), ultraviolet_anisotropy, UV_ANISOTROPY_CDF_VAR_NAME
         )
         self.assert_variable_attributes(next(variables), phion, PHION_CDF_VAR_NAME)
-        self.assert_variable_attributes(
-            next(variables), lyman_alpha, LYMAN_ALPHA_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), lyman_alpha, LYMAN_ALPHA_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), electron_density, ELECTRON_DENSITY_CDF_VAR_NAME
         )
@@ -105,6 +97,4 @@ def test_glows_l3d_solar_params_history_to_data_product(self):
         self.assert_variable_attributes(
             next(variables), proton_density_flag, PROTON_DENSITY_FLAG_CDF_VAR_NAME
         )
-        self.assert_variable_attributes(
-            next(variables), glows_flags, GLOWS_FLAGS_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), glows_flags, GLOWS_FLAGS_CDF_VAR_NAME)
diff --git a/tests/glows/l3e/test_glows_l3e_dependencies.py b/tests/glows/l3e/test_glows_l3e_dependencies.py
index 5b5fdddd..04bb0f0b 100644
--- a/tests/glows/l3e/test_glows_l3e_dependencies.py
+++ b/tests/glows/l3e/test_glows_l3e_dependencies.py
@@ -1,18 +1,16 @@
 from pathlib import Path
 from unittest import TestCase
-from unittest.mock import patch, Mock, call, sentinel, mock_open
+from unittest.mock import Mock, call, mock_open, patch, sentinel
 
 from imap_data_access import RepointInput
 
 from imap_l3_processing.glows.l3e.glows_l3e_dependencies import GlowsL3EDependencies
-from imap_l3_processing.utils import SpiceKernelTypes, FurnishMetakernelOutput
+from imap_l3_processing.utils import FurnishMetakernelOutput, SpiceKernelTypes
 from tests.test_helpers import get_test_data_path
 
 
 class TestGlowsL3EDependencies(TestCase):
-    @patch(
-        "imap_l3_processing.glows.l3e.glows_l3e_dependencies.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3e.glows_l3e_dependencies.imap_data_access.download")
     def test_fetch_dependencies(self, mock_download):
         mock_processing_input_collection = Mock()
 
@@ -133,37 +131,25 @@ def test_fetch_dependencies(self, mock_download):
         }
 
         self.assertEqual(mock_lya_series_path, actual_dependencies.lya_series)
-        self.assertEqual(
-            mock_solar_uv_anisotropy_path, actual_dependencies.solar_uv_anisotropy
-        )
+        self.assertEqual(mock_solar_uv_anisotropy_path, actual_dependencies.solar_uv_anisotropy)
         self.assertEqual(mock_speed_3d_sw_path, actual_dependencies.speed_3d_sw)
         self.assertEqual(mock_density_3d_sw_path, actual_dependencies.density_3d_sw)
         self.assertEqual(mock_phion_hydrogen_path, actual_dependencies.phion_hydrogen)
-        self.assertEqual(
-            mock_sw_eqtr_electrons_path, actual_dependencies.sw_eqtr_electrons
-        )
+        self.assertEqual(mock_sw_eqtr_electrons_path, actual_dependencies.sw_eqtr_electrons)
         self.assertEqual(
             expected_pipeline_settings["executable_dependency_paths"],
             actual_dependencies.pipeline_settings["executable_dependency_paths"],
         )
         self.assertEqual(mock_energy_grid_lo_path, actual_dependencies.energy_grid_lo)
         self.assertEqual(mock_energy_grid_hi_path, actual_dependencies.energy_grid_hi)
-        self.assertEqual(
-            mock_energy_grid_ultra_path, actual_dependencies.energy_grid_ultra
-        )
+        self.assertEqual(mock_energy_grid_ultra_path, actual_dependencies.energy_grid_ultra)
         self.assertEqual(mock_tess_xyz_8_path, actual_dependencies.tess_xyz_8)
         self.assertEqual(mock_tess_ang_16_path, actual_dependencies.tess_ang16)
-        self.assertEqual(
-            pipeline_settings_path, actual_dependencies.pipeline_settings_file
-        )
+        self.assertEqual(pipeline_settings_path, actual_dependencies.pipeline_settings_file)
 
-        self.assertEqual(
-            mock_downloaded_repoint_file, actual_dependencies.repointing_file
-        )
+        self.assertEqual(mock_downloaded_repoint_file, actual_dependencies.repointing_file)
 
-    @patch(
-        "imap_l3_processing.glows.l3e.glows_l3e_dependencies.furnish_spice_metakernel"
-    )
+    @patch("imap_l3_processing.glows.l3e.glows_l3e_dependencies.furnish_spice_metakernel")
     def test_collect_spice_dependencies(self, mock_furnish_spice_metakernel):
         expected_kernel_types_with_predicted = [
             SpiceKernelTypes.ScienceFrames,
@@ -206,9 +192,7 @@ def test_collect_spice_dependencies(self, mock_furnish_spice_metakernel):
         ]
 
         actual_metakernel_with_predict, actual_metakernel_without_predict = (
-            GlowsL3EDependencies.collect_spice_dependencies(
-                sentinel.start_date, sentinel.end_date
-            )
+            GlowsL3EDependencies.collect_spice_dependencies(sentinel.start_date, sentinel.end_date)
         )
 
         mock_furnish_spice_metakernel.assert_has_calls(
@@ -229,9 +213,7 @@ def test_collect_spice_dependencies(self, mock_furnish_spice_metakernel):
         )
 
         self.assertEqual(metakernel_output_with_predict, actual_metakernel_with_predict)
-        self.assertEqual(
-            metakernel_output_without_predict, actual_metakernel_without_predict
-        )
+        self.assertEqual(metakernel_output_without_predict, actual_metakernel_without_predict)
 
     def test_get_hi_parents(self):
         dependencies = self._create_l3e_dependencies()
@@ -327,9 +309,7 @@ def test_copy_dependencies(self, mock_shutil, mock_file):
             [
                 call(glows_l3e_dependencies.energy_grid_lo, expected_energy_grid_lo),
                 call(glows_l3e_dependencies.energy_grid_hi, expected_energy_grid_hi),
-                call(
-                    glows_l3e_dependencies.energy_grid_ultra, expected_energy_grid_ultra
-                ),
+                call(glows_l3e_dependencies.energy_grid_ultra, expected_energy_grid_ultra),
                 call(glows_l3e_dependencies.tess_xyz_8, expected_tess_xyz_8),
                 call(glows_l3e_dependencies.tess_ang16, expected_tess_ang16),
                 call(
@@ -361,14 +341,12 @@ def test_copy_dependencies(self, mock_shutil, mock_file):
 
         mock_file.assert_called_once_with("ionization.files.dat", "w")
         mock_file.return_value.write.assert_called_once_with(
-            (
-                f"{glows_l3e_dependencies.lya_series.name}\n"
-                f"{glows_l3e_dependencies.solar_uv_anisotropy.name}\n"
-                f"{glows_l3e_dependencies.speed_3d_sw.name}\n"
-                f"{glows_l3e_dependencies.density_3d_sw.name}\n"
-                f"{glows_l3e_dependencies.phion_hydrogen.name}\n"
-                f"{glows_l3e_dependencies.sw_eqtr_electrons.name}\n"
-            )
+            f"{glows_l3e_dependencies.lya_series.name}\n"
+            f"{glows_l3e_dependencies.solar_uv_anisotropy.name}\n"
+            f"{glows_l3e_dependencies.speed_3d_sw.name}\n"
+            f"{glows_l3e_dependencies.density_3d_sw.name}\n"
+            f"{glows_l3e_dependencies.phion_hydrogen.name}\n"
+            f"{glows_l3e_dependencies.sw_eqtr_electrons.name}\n"
         )
 
     def _create_l3e_dependencies(self) -> GlowsL3EDependencies:
diff --git a/tests/glows/l3e/test_glows_l3e_hi_model.py b/tests/glows/l3e/test_glows_l3e_hi_model.py
index 9212d8f9..df1a068a 100644
--- a/tests/glows/l3e/test_glows_l3e_hi_model.py
+++ b/tests/glows/l3e/test_glows_l3e_hi_model.py
@@ -1,6 +1,6 @@
 import unittest
 from datetime import datetime, timedelta
-from unittest.mock import sentinel, Mock, MagicMock, patch
+from unittest.mock import MagicMock, Mock, patch, sentinel
 
 import numpy as np
 
@@ -66,41 +66,21 @@ def test_l3e_hi_model_to_data_product_variables(self):
                     DataProductVariable("epoch", sentinel.epoch),
                     DataProductVariable("epoch_delta", sentinel.epoch_delta),
                     DataProductVariable("energy_grid", energy_array),
-                    DataProductVariable(
-                        "energy_delta_plus", sentinel.energy_delta_plus
-                    ),
-                    DataProductVariable(
-                        "energy_delta_minus", sentinel.energy_delta_minus
-                    ),
+                    DataProductVariable("energy_delta_plus", sentinel.energy_delta_plus),
+                    DataProductVariable("energy_delta_minus", sentinel.energy_delta_minus),
                     DataProductVariable("spin_angle", spin_angle_array),
                     DataProductVariable("surv_prob", sentinel.probability_of_survival),
                     DataProductVariable("energy_label", expected_energy_labels),
                     DataProductVariable("spin_angle_label", expected_spin_angle_labels),
-                    DataProductVariable(
-                        "spin_axis_latitude", sentinel.spin_axis_latitude
-                    ),
-                    DataProductVariable(
-                        "spin_axis_longitude", sentinel.spin_axis_longitude
-                    ),
+                    DataProductVariable("spin_axis_latitude", sentinel.spin_axis_latitude),
+                    DataProductVariable("spin_axis_longitude", sentinel.spin_axis_longitude),
                     DataProductVariable("program_version", sentinel.program_version),
-                    DataProductVariable(
-                        "spacecraft_radius", sentinel.spacecraft_radius
-                    ),
-                    DataProductVariable(
-                        "spacecraft_latitude", sentinel.spacecraft_latitude
-                    ),
-                    DataProductVariable(
-                        "spacecraft_longitude", sentinel.spacecraft_longitude
-                    ),
-                    DataProductVariable(
-                        "spacecraft_velocity_x", sentinel.spacecraft_velocity_x
-                    ),
-                    DataProductVariable(
-                        "spacecraft_velocity_y", sentinel.spacecraft_velocity_y
-                    ),
-                    DataProductVariable(
-                        "spacecraft_velocity_z", sentinel.spacecraft_velocity_z
-                    ),
+                    DataProductVariable("spacecraft_radius", sentinel.spacecraft_radius),
+                    DataProductVariable("spacecraft_latitude", sentinel.spacecraft_latitude),
+                    DataProductVariable("spacecraft_longitude", sentinel.spacecraft_longitude),
+                    DataProductVariable("spacecraft_velocity_x", sentinel.spacecraft_velocity_x),
+                    DataProductVariable("spacecraft_velocity_y", sentinel.spacecraft_velocity_y),
+                    DataProductVariable("spacecraft_velocity_z", sentinel.spacecraft_velocity_z),
                     DataProductVariable("elongation", sentinel.elongation),
                     DataProductVariable("glows_flags", sentinel.glows_flags),
                 ]
@@ -893,24 +873,18 @@ def test_convert_dat_to_glows_l3e_hi_product(self, mock_calculate_energy_deltas)
 
         expected_program_version = "Hi.v00.01"
 
-        l3e_hi_product: GlowsL3EHiData = (
-            GlowsL3EHiData.convert_dat_to_glows_l3e_hi_product(
-                mock_metadata, hi_file_path, expected_epoch, epoch_delta, args
-            )
+        l3e_hi_product: GlowsL3EHiData = GlowsL3EHiData.convert_dat_to_glows_l3e_hi_product(
+            mock_metadata, hi_file_path, expected_epoch, epoch_delta, args
         )
 
-        np.testing.assert_equal(
-            np.array([expected_epoch]), l3e_hi_product.epoch, strict=True
-        )
+        np.testing.assert_equal(np.array([expected_epoch]), l3e_hi_product.epoch, strict=True)
         np.testing.assert_equal(
             np.array([expected_epoch_delta_in_nanoseconds]),
             l3e_hi_product.epoch_delta,
             strict=True,
         )
         np.testing.assert_equal(l3e_hi_product.energy, expected_energy, strict=True)
-        np.testing.assert_equal(
-            l3e_hi_product.spin_angle, expected_spin_angle, strict=True
-        )
+        np.testing.assert_equal(l3e_hi_product.spin_angle, expected_spin_angle, strict=True)
         np.testing.assert_equal(
             l3e_hi_product.probability_of_survival.shape,
             expected_survival_probability_shape,
@@ -934,25 +908,13 @@ def test_convert_dat_to_glows_l3e_hi_product(self, mock_calculate_energy_deltas)
             strict=True,
         )
 
-        np.testing.assert_equal(
-            np.array([0.5]), l3e_hi_product.spacecraft_radius, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([85.4]), l3e_hi_product.spacecraft_longitude, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([45.1]), l3e_hi_product.spacecraft_latitude, strict=True
-        )
+        np.testing.assert_equal(np.array([0.5]), l3e_hi_product.spacecraft_radius, strict=True)
+        np.testing.assert_equal(np.array([85.4]), l3e_hi_product.spacecraft_longitude, strict=True)
+        np.testing.assert_equal(np.array([45.1]), l3e_hi_product.spacecraft_latitude, strict=True)
 
-        np.testing.assert_equal(
-            np.array([2.1]), l3e_hi_product.spacecraft_velocity_x, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([2.2]), l3e_hi_product.spacecraft_velocity_y, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([2.3]), l3e_hi_product.spacecraft_velocity_z, strict=True
-        )
+        np.testing.assert_equal(np.array([2.1]), l3e_hi_product.spacecraft_velocity_x, strict=True)
+        np.testing.assert_equal(np.array([2.2]), l3e_hi_product.spacecraft_velocity_y, strict=True)
+        np.testing.assert_equal(np.array([2.3]), l3e_hi_product.spacecraft_velocity_z, strict=True)
 
         np.testing.assert_equal([135.0], l3e_hi_product.elongation)
         np.testing.assert_equal(
diff --git a/tests/glows/l3e/test_glows_l3e_initializer.py b/tests/glows/l3e/test_glows_l3e_initializer.py
index 4b2e190e..e7fbbdb2 100644
--- a/tests/glows/l3e/test_glows_l3e_initializer.py
+++ b/tests/glows/l3e/test_glows_l3e_initializer.py
@@ -1,7 +1,7 @@
 import unittest
 from datetime import datetime
 from pathlib import Path
-from unittest.mock import patch, call, sentinel, Mock, create_autospec
+from unittest.mock import Mock, call, create_autospec, patch, sentinel
 
 import numpy as np
 from imap_data_access import RepointInput
@@ -9,12 +9,12 @@
 
 from imap_l3_processing.glows.descriptors import (
     GLOWS_L3BCDE_DESCRIPTORS,
+    GLOWS_L3E_DESCRIPTORS,
     GLOWS_L3E_HI_45_DESCRIPTOR,
     GLOWS_L3E_HI_90_DESCRIPTOR,
     GLOWS_L3E_LO_DESCRIPTOR,
-    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
     GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
-    GLOWS_L3E_DESCRIPTORS,
+    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3d.models import GlowsL3DProcessorOutput
 from imap_l3_processing.glows.l3e.glows_l3e_initializer import (
@@ -61,19 +61,13 @@ def test_get_repointings_to_process(
         )
 
         mock_get_most_recently_uploaded_ancillary.side_effect = [
-            create_mock_query_results(
-                ["imap_glows_pipeline-settings-l3bcde_20200101_v000.cdf"]
-            )[0],
-            create_mock_query_results(["imap_glows_energy-grid-lo_20200101_v000.cdf"])[
+            create_mock_query_results(["imap_glows_pipeline-settings-l3bcde_20200101_v000.cdf"])[
                 0
             ],
+            create_mock_query_results(["imap_glows_energy-grid-lo_20200101_v000.cdf"])[0],
             create_mock_query_results(["imap_glows_tess-xyz-8_20200101_v000.cdf"])[0],
-            create_mock_query_results(["imap_glows_energy-grid-hi_20200101_v000.cdf"])[
-                0
-            ],
-            create_mock_query_results(
-                ["imap_glows_energy-grid-ultra_20200101_v000.cdf"]
-            )[0],
+            create_mock_query_results(["imap_glows_energy-grid-hi_20200101_v000.cdf"])[0],
+            create_mock_query_results(["imap_glows_energy-grid-ultra_20200101_v000.cdf"])[0],
             create_mock_query_results(["imap_glows_tess-ang-16_20200101_v000.cdf"])[0],
         ]
 
@@ -84,12 +78,8 @@ def test_get_repointings_to_process(
             mock_spice_without_predict,
         )
 
-        updated_l3d = Path(
-            "path/to/imap_glows_l3d_solar-hist_19470303-cr02091_v000.cdf"
-        )
-        updated_l3d_text_file_path = Path(
-            "imap_glows_e-dens_19470303_20100101_v000.dat"
-        )
+        updated_l3d = Path("path/to/imap_glows_l3d_solar-hist_19470303-cr02091_v000.cdf")
+        updated_l3d_text_file_path = Path("imap_glows_e-dens_19470303_20100101_v000.dat")
         glows_l3d_processor_output = GlowsL3DProcessorOutput(
             updated_l3d, [updated_l3d_text_file_path], sentinel.last_processed_cr
         )
@@ -98,9 +88,7 @@ def test_get_repointings_to_process(
         mock_find_first_updated_cr.return_value = 2091
 
         mock_l3e_dependencies = mock_fetch_dependencies.return_value
-        mock_l3e_dependencies.pipeline_settings = {
-            "start_cr": sentinel.start_of_mission_cr
-        }
+        mock_l3e_dependencies.pipeline_settings = {"start_cr": sentinel.start_of_mission_cr}
         mock_l3e_dependencies.repointing_file = Path("path/to/repointing_file")
 
         expected_hi_45 = {1234: Version(None, 1), 2468: Version(None, 1)}
@@ -163,13 +151,9 @@ def test_get_repointings_to_process(
                     instrument="glows",
                     descriptor="pipeline-settings-l3bcde",
                 ),
-                call(
-                    table="ancillary", instrument="glows", descriptor="energy-grid-lo"
-                ),
+                call(table="ancillary", instrument="glows", descriptor="energy-grid-lo"),
                 call(table="ancillary", instrument="glows", descriptor="tess-xyz-8"),
-                call(
-                    table="ancillary", instrument="glows", descriptor="energy-grid-hi"
-                ),
+                call(table="ancillary", instrument="glows", descriptor="energy-grid-hi"),
                 call(
                     table="ancillary",
                     instrument="glows",
@@ -202,9 +186,7 @@ def test_get_repointings_to_process(
             pipeline_l3e_input_filenames,
         )
 
-        [repoint_input] = actual_l3e_inputs.get_file_paths(
-            data_type=RepointInput.data_type
-        )
+        [repoint_input] = actual_l3e_inputs.get_file_paths(data_type=RepointInput.data_type)
         self.assertEqual("imap_2026_105_01.repoint.csv", repoint_input.name)
 
         self.assertEqual(actual_initializer_output, expected_initializer_data)
@@ -229,12 +211,8 @@ def test_get_repointings_to_process_identical_l3d_files(
         mock_imap_data_access,
         mock_get_most_recently_uploaded_ancillary,
     ):
-        updated_l3d = Path(
-            "path/to/imap_glows_l3d_solar-hist_19470303-cr02091_v000.cdf"
-        )
-        updated_l3d_text_file_path = Path(
-            "imap_glows_e-dens_19470303_20100101_v000.dat"
-        )
+        updated_l3d = Path("path/to/imap_glows_l3d_solar-hist_19470303-cr02091_v000.cdf")
+        updated_l3d_text_file_path = Path("imap_glows_e-dens_19470303_20100101_v000.dat")
         expected_last_cr = 2091
         glows_l3d_processor_output = GlowsL3DProcessorOutput(
             updated_l3d, [updated_l3d_text_file_path], expected_last_cr
@@ -242,34 +220,24 @@ def test_get_repointings_to_process_identical_l3d_files(
         previous_l3d = "imap_glows_l3d_solar-hist_19470303-cr02091_v000.cdf"
 
         mock_l3e_dependencies = mock_fetch_dependencies.return_value
-        mock_l3e_dependencies.pipeline_settings = {
-            "start_cr": sentinel.start_of_mission_cr
-        }
+        mock_l3e_dependencies.pipeline_settings = {"start_cr": sentinel.start_of_mission_cr}
         mock_find_first_updated_cr.return_value = None
-        mock_identify_versions_for_l3e_output_files.return_value = (
-            GlowsL3eVersionsForRepointings(
-                repointing_numbers=[],
-                hi_90_repointings={},
-                hi_45_repointings={},
-                lo_repointings={},
-                ultra_sf_repointings={},
-                ultra_hf_repointings={},
-            )
+        mock_identify_versions_for_l3e_output_files.return_value = GlowsL3eVersionsForRepointings(
+            repointing_numbers=[],
+            hi_90_repointings={},
+            hi_45_repointings={},
+            lo_repointings={},
+            ultra_sf_repointings={},
+            ultra_hf_repointings={},
         )
         mock_get_most_recently_uploaded_ancillary.side_effect = [
-            create_mock_query_results(
-                ["imap_glows_pipeline-settings-l3bcde_20200101_v000.cdf"]
-            )[0],
-            create_mock_query_results(["imap_glows_energy-grid-lo_20200101_v000.cdf"])[
+            create_mock_query_results(["imap_glows_pipeline-settings-l3bcde_20200101_v000.cdf"])[
                 0
             ],
+            create_mock_query_results(["imap_glows_energy-grid-lo_20200101_v000.cdf"])[0],
             create_mock_query_results(["imap_glows_tess-xyz-8_20200101_v000.cdf"])[0],
-            create_mock_query_results(["imap_glows_energy-grid-hi_20200101_v000.cdf"])[
-                0
-            ],
-            create_mock_query_results(
-                ["imap_glows_energy-grid-ultra_20200101_v000.cdf"]
-            )[0],
+            create_mock_query_results(["imap_glows_energy-grid-hi_20200101_v000.cdf"])[0],
+            create_mock_query_results(["imap_glows_energy-grid-ultra_20200101_v000.cdf"])[0],
             create_mock_query_results(["imap_glows_tess-ang-16_20200101_v000.cdf"])[0],
         ]
 
@@ -308,35 +276,25 @@ def test_get_repointings_to_process_uses_mission_start_cr_when_no_previous_l3d(
         _,
     ):
         mock_get_most_recently_uploaded_ancillary.side_effect = [
-            create_mock_query_results(
-                ["imap_glows_pipeline-settings-l3bcde_20200101_v000.cdf"]
-            )[0],
-            create_mock_query_results(["imap_glows_energy-grid-lo_20200101_v000.cdf"])[
+            create_mock_query_results(["imap_glows_pipeline-settings-l3bcde_20200101_v000.cdf"])[
                 0
             ],
+            create_mock_query_results(["imap_glows_energy-grid-lo_20200101_v000.cdf"])[0],
             create_mock_query_results(["imap_glows_tess-xyz-8_20200101_v000.cdf"])[0],
-            create_mock_query_results(["imap_glows_energy-grid-hi_20200101_v000.cdf"])[
-                0
-            ],
-            create_mock_query_results(
-                ["imap_glows_energy-grid-ultra_20200101_v000.cdf"]
-            )[0],
+            create_mock_query_results(["imap_glows_energy-grid-hi_20200101_v000.cdf"])[0],
+            create_mock_query_results(["imap_glows_energy-grid-ultra_20200101_v000.cdf"])[0],
             create_mock_query_results(["imap_glows_tess-ang-16_20200101_v000.cdf"])[0],
         ]
-        mock_identify_versions_for_l3e_output_files.return_value = (
-            GlowsL3eVersionsForRepointings(
-                repointing_numbers=[],
-                ultra_sf_repointings={},
-                ultra_hf_repointings={},
-                lo_repointings={},
-                hi_45_repointings={},
-                hi_90_repointings={},
-            )
+        mock_identify_versions_for_l3e_output_files.return_value = GlowsL3eVersionsForRepointings(
+            repointing_numbers=[],
+            ultra_sf_repointings={},
+            ultra_hf_repointings={},
+            lo_repointings={},
+            hi_45_repointings={},
+            hi_90_repointings={},
         )
 
-        updated_l3d = Path(
-            "path/to/imap_glows_l3d_solar-hist_19470303-cr02091_v012.0001.cdf"
-        )
+        updated_l3d = Path("path/to/imap_glows_l3d_solar-hist_19470303-cr02091_v012.0001.cdf")
         glows_l3d_processor_output = GlowsL3DProcessorOutput(
             updated_l3d, [], sentinel.last_processed_cr
         )
@@ -365,9 +323,7 @@ def test_get_repointings_to_process_uses_mission_start_cr_when_no_previous_l3d(
             sentinel.reprocess_info,
         )
 
-    @patch(
-        "imap_l3_processing.glows.l3e.glows_l3e_initializer.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.glows.l3e.glows_l3e_initializer.imap_data_access.download")
     @patch("imap_l3_processing.glows.l3e.glows_l3e_initializer.CDF")
     def test_find_first_updated_cr(self, mock_CDF, mock_download):
         num_crs = 10
@@ -438,9 +394,7 @@ def test_find_first_updated_cr(self, mock_CDF, mock_download):
 
                 mock_CDF.side_effect = [old_l3d, new_l3d]
 
-                actual_cr = find_first_updated_cr(
-                    sentinel.new_l3d_path, sentinel.old_l3d_filename
-                )
+                actual_cr = find_first_updated_cr(sentinel.new_l3d_path, sentinel.old_l3d_filename)
 
                 mock_download.assert_called_once_with(sentinel.old_l3d_filename)
                 mock_CDF.assert_has_calls(
@@ -544,12 +498,8 @@ def test_identify_versions_for_l3e_output_files_gives_minor_version_1_for_non_ex
         }
 
         self.assertCountEqual(all_repointing_numbers, result.repointing_numbers)
-        self.assertEqual(
-            expected_versions_for_hi90_repoint_number, result.hi_90_repointings
-        )
-        self.assertEqual(
-            expected_versions_for_hi45_repoint_number, result.hi_45_repointings
-        )
+        self.assertEqual(expected_versions_for_hi90_repoint_number, result.hi_90_repointings)
+        self.assertEqual(expected_versions_for_hi45_repoint_number, result.hi_45_repointings)
         self.assertEqual(expected_versions_for_lo_repoint_number, result.lo_repointings)
         self.assertEqual(
             expected_versions_for_ultra_sf_repoint_number, result.ultra_sf_repointings
@@ -781,33 +731,24 @@ def test_identify_versions_for_l3e_output_files_increments_minor_when_same_major
         )
 
         expected_versions_for_hi45_repoint_number = {
-            repoint_number: Version(3, 2)
-            for repoint_number in updated_repointing_numbers
+            repoint_number: Version(3, 2) for repoint_number in updated_repointing_numbers
         }
         expected_versions_for_hi90_repoint_number = {
-            repoint_number: Version(4, 3)
-            for repoint_number in updated_repointing_numbers
+            repoint_number: Version(4, 3) for repoint_number in updated_repointing_numbers
         }
         expected_versions_for_lo_repoint_number = {
-            repoint_number: Version(5, 4)
-            for repoint_number in updated_repointing_numbers
+            repoint_number: Version(5, 4) for repoint_number in updated_repointing_numbers
         }
         expected_versions_for_ultra_sf_repoint_number = {
-            repoint_number: Version(6, 5)
-            for repoint_number in updated_repointing_numbers
+            repoint_number: Version(6, 5) for repoint_number in updated_repointing_numbers
         }
         expected_versions_for_ultra_hf_repoint_number = {
-            repoint_number: Version(7, 6)
-            for repoint_number in updated_repointing_numbers
+            repoint_number: Version(7, 6) for repoint_number in updated_repointing_numbers
         }
 
         self.assertCountEqual(updated_repointing_numbers, result.repointing_numbers)
-        self.assertEqual(
-            expected_versions_for_hi90_repoint_number, result.hi_90_repointings
-        )
-        self.assertEqual(
-            expected_versions_for_hi45_repoint_number, result.hi_45_repointings
-        )
+        self.assertEqual(expected_versions_for_hi90_repoint_number, result.hi_90_repointings)
+        self.assertEqual(expected_versions_for_hi45_repoint_number, result.hi_45_repointings)
         self.assertEqual(expected_versions_for_lo_repoint_number, result.lo_repointings)
         self.assertEqual(
             expected_versions_for_ultra_sf_repoint_number, result.ultra_sf_repointings
diff --git a/tests/glows/l3e/test_glows_l3e_lo_model.py b/tests/glows/l3e/test_glows_l3e_lo_model.py
index 5c55f8b4..24882bb1 100644
--- a/tests/glows/l3e/test_glows_l3e_lo_model.py
+++ b/tests/glows/l3e/test_glows_l3e_lo_model.py
@@ -1,6 +1,6 @@
 import unittest
 from datetime import datetime, timedelta
-from unittest.mock import sentinel, Mock, MagicMock, patch
+from unittest.mock import MagicMock, Mock, patch, sentinel
 
 import numpy as np
 
@@ -9,30 +9,30 @@
     GlowsL3eSpacecraftInfo,
 )
 from imap_l3_processing.glows.l3e.glows_l3e_lo_model import (
-    GlowsL3ELoData,
-    SPIN_AXIS_LONGITUDE_VAR_NAME,
-    SPIN_AXIS_LATITUDE_VAR_NAME,
-    EPOCH_CDF_VAR_NAME,
+    ELONGATION_VAR_NAME,
+    ENERGY_DELTA_MINUS_VAR_NAME,
+    ENERGY_DELTA_PLUS_VAR_NAME,
+    ENERGY_LABEL_VAR_NAME,
     ENERGY_VAR_NAME,
-    SPIN_ANGLE_VAR_NAME,
+    EPOCH_CDF_VAR_NAME,
+    EPOCH_DELTA_CDF_VAR_NAME,
+    GLOWS_FLAGS_VAR_NAME,
     PROBABILITY_OF_SURVIVAL_VAR_NAME,
-    ENERGY_LABEL_VAR_NAME,
-    SPIN_ANGLE_LABEL_VAR_NAME,
-    ELONGATION_VAR_NAME,
     PROGRAM_VERSION_VAR_NAME,
-    SPACECRAFT_RADIUS_VAR_NAME,
-    SPACECRAFT_LONGITUDE_VAR_NAME,
     SPACECRAFT_LATITUDE_VAR_NAME,
+    SPACECRAFT_LONGITUDE_VAR_NAME,
+    SPACECRAFT_RADIUS_VAR_NAME,
     SPACECRAFT_VELOCITY_X_VAR_NAME,
     SPACECRAFT_VELOCITY_Y_VAR_NAME,
     SPACECRAFT_VELOCITY_Z_VAR_NAME,
-    GLOWS_FLAGS_VAR_NAME,
-    ENERGY_DELTA_PLUS_VAR_NAME,
-    ENERGY_DELTA_MINUS_VAR_NAME,
-    EPOCH_DELTA_CDF_VAR_NAME,
+    SPIN_ANGLE_LABEL_VAR_NAME,
+    SPIN_ANGLE_VAR_NAME,
+    SPIN_AXIS_LATITUDE_VAR_NAME,
+    SPIN_AXIS_LONGITUDE_VAR_NAME,
+    GlowsL3ELoData,
 )
 from imap_l3_processing.models import DataProductVariable
-from tests.test_helpers import get_test_instrument_team_data_path, NumpyArrayMatcher
+from tests.test_helpers import NumpyArrayMatcher, get_test_instrument_team_data_path
 
 
 class TestL3eLoModel(unittest.TestCase):
@@ -86,21 +86,15 @@ def test_l3e_lo_model_to_data_product_variables(self):
                     DataProductVariable(EPOCH_CDF_VAR_NAME, sentinel.epoch),
                     DataProductVariable(EPOCH_DELTA_CDF_VAR_NAME, sentinel.epoch_delta),
                     DataProductVariable(ENERGY_VAR_NAME, energy_array),
-                    DataProductVariable(
-                        ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus
-                    ),
-                    DataProductVariable(
-                        ENERGY_DELTA_MINUS_VAR_NAME, sentinel.energy_delta_minus
-                    ),
+                    DataProductVariable(ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus),
+                    DataProductVariable(ENERGY_DELTA_MINUS_VAR_NAME, sentinel.energy_delta_minus),
                     DataProductVariable(SPIN_ANGLE_VAR_NAME, spin_angle_array),
                     DataProductVariable(
                         PROBABILITY_OF_SURVIVAL_VAR_NAME,
                         sentinel.probability_of_survival,
                     ),
                     DataProductVariable(ENERGY_LABEL_VAR_NAME, expected_energy_labels),
-                    DataProductVariable(
-                        SPIN_ANGLE_LABEL_VAR_NAME, expected_spin_angle_labels
-                    ),
+                    DataProductVariable(SPIN_ANGLE_LABEL_VAR_NAME, expected_spin_angle_labels),
                     DataProductVariable(ELONGATION_VAR_NAME, sentinel.elongation),
                     DataProductVariable(
                         SPIN_AXIS_LATITUDE_VAR_NAME,
@@ -558,10 +552,8 @@ def test_convert_dat_to_glows_l3e_lo_product(self, mock_calculate_energy_deltas)
 
         args.spacecraft_info = spacecraft_info
 
-        l3e_lo_product: GlowsL3ELoData = (
-            GlowsL3ELoData.convert_dat_to_glows_l3e_lo_product(
-                mock_metadata, lo_file_path, epoch, epoch_delta, elongation_value, args
-            )
+        l3e_lo_product: GlowsL3ELoData = GlowsL3ELoData.convert_dat_to_glows_l3e_lo_product(
+            mock_metadata, lo_file_path, epoch, epoch_delta, elongation_value, args
         )
 
         mock_calculate_energy_deltas.assert_called_once_with(
@@ -575,17 +567,13 @@ def test_convert_dat_to_glows_l3e_lo_product(self, mock_calculate_energy_deltas)
             strict=True,
         )
         np.testing.assert_equal(l3e_lo_product.energy, expected_energy, strict=True)
-        np.testing.assert_equal(
-            l3e_lo_product.energy_delta_plus, sentinel.energy_delta_plus
-        )
+        np.testing.assert_equal(l3e_lo_product.energy_delta_plus, sentinel.energy_delta_plus)
         np.testing.assert_equal(
             l3e_lo_product.energy_delta_minus,
             sentinel.energy_delta_minus,
         )
 
-        np.testing.assert_equal(
-            l3e_lo_product.spin_angle, expected_spin_angle, strict=True
-        )
+        np.testing.assert_equal(l3e_lo_product.spin_angle, expected_spin_angle, strict=True)
         np.testing.assert_equal(
             l3e_lo_product.probability_of_survival.shape,
             expected_survival_probability_shape,
@@ -611,22 +599,10 @@ def test_convert_dat_to_glows_l3e_lo_product(self, mock_calculate_energy_deltas)
             [expected_program_version], l3e_lo_product.program_version, strict=True
         )
 
-        np.testing.assert_equal(
-            l3e_lo_product.spacecraft_radius, np.array([0.5]), strict=True
-        )
-        np.testing.assert_equal(
-            l3e_lo_product.spacecraft_longitude, np.array([85.4]), strict=True
-        )
-        np.testing.assert_equal(
-            l3e_lo_product.spacecraft_latitude, np.array([45.1]), strict=True
-        )
+        np.testing.assert_equal(l3e_lo_product.spacecraft_radius, np.array([0.5]), strict=True)
+        np.testing.assert_equal(l3e_lo_product.spacecraft_longitude, np.array([85.4]), strict=True)
+        np.testing.assert_equal(l3e_lo_product.spacecraft_latitude, np.array([45.1]), strict=True)
 
-        np.testing.assert_equal(
-            l3e_lo_product.spacecraft_velocity_x, np.array([2.1]), strict=True
-        )
-        np.testing.assert_equal(
-            l3e_lo_product.spacecraft_velocity_y, np.array([2.2]), strict=True
-        )
-        np.testing.assert_equal(
-            l3e_lo_product.spacecraft_velocity_z, np.array([2.3]), strict=True
-        )
+        np.testing.assert_equal(l3e_lo_product.spacecraft_velocity_x, np.array([2.1]), strict=True)
+        np.testing.assert_equal(l3e_lo_product.spacecraft_velocity_y, np.array([2.2]), strict=True)
+        np.testing.assert_equal(l3e_lo_product.spacecraft_velocity_z, np.array([2.3]), strict=True)
diff --git a/tests/glows/l3e/test_glows_l3e_ultra_model.py b/tests/glows/l3e/test_glows_l3e_ultra_model.py
index dff3996c..fa0a8e39 100644
--- a/tests/glows/l3e/test_glows_l3e_ultra_model.py
+++ b/tests/glows/l3e/test_glows_l3e_ultra_model.py
@@ -1,6 +1,6 @@
 import unittest
 from datetime import datetime, timedelta
-from unittest.mock import sentinel, Mock, MagicMock, patch
+from unittest.mock import MagicMock, Mock, patch, sentinel
 
 import numpy as np
 
@@ -9,32 +9,32 @@
     GlowsL3eSpacecraftInfo,
 )
 from imap_l3_processing.glows.l3e.glows_l3e_ultra_model import (
-    GlowsL3EUltraData,
+    ELONGATION_EXCLUDED_VAR_NAME,
+    ENERGY_DELTA_MINUS_VAR_NAME,
+    ENERGY_DELTA_PLUS_VAR_NAME,
+    ENERGY_LABEL_VAR_NAME,
+    ENERGY_VAR_NAME,
     EPOCH_CDF_VAR_NAME,
     EPOCH_DELTA_CDF_VAR_NAME,
-    ENERGY_VAR_NAME,
-    PROBABILITY_OF_SURVIVAL_VAR_NAME,
+    GLOWS_FLAGS_VAR_NAME,
     HEALPIX_INDEX_VAR_NAME,
-    ENERGY_LABEL_VAR_NAME,
     PIXEL_INDEX_LABEL_VAR_NAME,
-    SPIN_AXIS_LATITUDE_VAR_NAME,
-    SPIN_AXIS_LONGITUDE_VAR_NAME,
+    PIXEL_LATITUDE_VAR_NAME,
+    PIXEL_LONGITUDE_VAR_NAME,
+    PROBABILITY_OF_SURVIVAL_VAR_NAME,
     PROGRAM_VERSION_VAR_NAME,
-    SPACECRAFT_RADIUS_VAR_NAME,
-    SPACECRAFT_LONGITUDE_VAR_NAME,
     SPACECRAFT_LATITUDE_VAR_NAME,
+    SPACECRAFT_LONGITUDE_VAR_NAME,
+    SPACECRAFT_RADIUS_VAR_NAME,
     SPACECRAFT_VELOCITY_X_VAR_NAME,
     SPACECRAFT_VELOCITY_Y_VAR_NAME,
     SPACECRAFT_VELOCITY_Z_VAR_NAME,
-    ELONGATION_EXCLUDED_VAR_NAME,
-    PIXEL_LATITUDE_VAR_NAME,
-    PIXEL_LONGITUDE_VAR_NAME,
-    GLOWS_FLAGS_VAR_NAME,
-    ENERGY_DELTA_PLUS_VAR_NAME,
-    ENERGY_DELTA_MINUS_VAR_NAME,
+    SPIN_AXIS_LATITUDE_VAR_NAME,
+    SPIN_AXIS_LONGITUDE_VAR_NAME,
+    GlowsL3EUltraData,
 )
 from imap_l3_processing.models import DataProductVariable
-from tests.test_helpers import get_test_instrument_team_data_path, NumpyArrayMatcher
+from tests.test_helpers import NumpyArrayMatcher, get_test_instrument_team_data_path
 
 
 class TestL3eUltraModel(unittest.TestCase):
@@ -90,33 +90,21 @@ def test_l3e_ultra_model_to_data_product_variables(self):
                     DataProductVariable(EPOCH_CDF_VAR_NAME, sentinel.epoch),
                     DataProductVariable(EPOCH_DELTA_CDF_VAR_NAME, sentinel.epoch_delta),
                     DataProductVariable(ENERGY_VAR_NAME, energy_array),
-                    DataProductVariable(
-                        ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus
-                    ),
-                    DataProductVariable(
-                        ENERGY_DELTA_MINUS_VAR_NAME, sentinel.energy_delta_minus
-                    ),
+                    DataProductVariable(ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus),
+                    DataProductVariable(ENERGY_DELTA_MINUS_VAR_NAME, sentinel.energy_delta_minus),
                     DataProductVariable(HEALPIX_INDEX_VAR_NAME, healpix_index_array),
                     DataProductVariable(
                         PROBABILITY_OF_SURVIVAL_VAR_NAME,
                         sentinel.probability_of_survival,
                     ),
                     DataProductVariable(ENERGY_LABEL_VAR_NAME, expected_energy_labels),
-                    DataProductVariable(
-                        PIXEL_INDEX_LABEL_VAR_NAME, expected_healpix_labels
-                    ),
-                    DataProductVariable(
-                        SPIN_AXIS_LATITUDE_VAR_NAME, sentinel.spin_axis_latitude
-                    ),
+                    DataProductVariable(PIXEL_INDEX_LABEL_VAR_NAME, expected_healpix_labels),
+                    DataProductVariable(SPIN_AXIS_LATITUDE_VAR_NAME, sentinel.spin_axis_latitude),
                     DataProductVariable(
                         SPIN_AXIS_LONGITUDE_VAR_NAME, sentinel.spin_axis_longitude
                     ),
-                    DataProductVariable(
-                        PROGRAM_VERSION_VAR_NAME, sentinel.program_version
-                    ),
-                    DataProductVariable(
-                        SPACECRAFT_RADIUS_VAR_NAME, sentinel.spacecraft_radius
-                    ),
+                    DataProductVariable(PROGRAM_VERSION_VAR_NAME, sentinel.program_version),
+                    DataProductVariable(SPACECRAFT_RADIUS_VAR_NAME, sentinel.spacecraft_radius),
                     DataProductVariable(
                         SPACECRAFT_LATITUDE_VAR_NAME, sentinel.spacecraft_latitude
                     ),
@@ -135,12 +123,8 @@ def test_l3e_ultra_model_to_data_product_variables(self):
                     DataProductVariable(
                         ELONGATION_EXCLUDED_VAR_NAME, sentinel.elongation_excluded
                     ),
-                    DataProductVariable(
-                        PIXEL_LATITUDE_VAR_NAME, sentinel.pixel_latitude
-                    ),
-                    DataProductVariable(
-                        PIXEL_LONGITUDE_VAR_NAME, sentinel.pixel_longitude
-                    ),
+                    DataProductVariable(PIXEL_LATITUDE_VAR_NAME, sentinel.pixel_latitude),
+                    DataProductVariable(PIXEL_LONGITUDE_VAR_NAME, sentinel.pixel_longitude),
                     DataProductVariable(GLOWS_FLAGS_VAR_NAME, sentinel.glows_flags),
                 ]
 
@@ -285,10 +269,8 @@ def test_convert_dat_to_glows_l3e_ul_product(self, mock_calculate_energy_deltas)
 
         args.elongation = 30.0
 
-        l3e_ul_product: GlowsL3EUltraData = (
-            GlowsL3EUltraData.convert_dat_to_glows_l3e_ul_product(
-                mock_metadata, ul_file_path, expected_epoch, epoch_delta, args
-            )
+        l3e_ul_product: GlowsL3EUltraData = GlowsL3EUltraData.convert_dat_to_glows_l3e_ul_product(
+            mock_metadata, ul_file_path, expected_epoch, epoch_delta, args
         )
 
         mock_calculate_energy_deltas.assert_called_once_with(
@@ -310,9 +292,7 @@ def test_convert_dat_to_glows_l3e_ul_product(self, mock_calculate_energy_deltas)
             l3e_ul_product.energy_delta_minus, sentinel.energy_delta_minus, strict=True
         )
 
-        np.testing.assert_equal(
-            expected_heal_pix, l3e_ul_product.healpix_index, strict=True
-        )
+        np.testing.assert_equal(expected_heal_pix, l3e_ul_product.healpix_index, strict=True)
         np.testing.assert_equal(
             expected_survival_probability_shape,
             l3e_ul_product.probability_of_survival.shape,
@@ -347,36 +327,18 @@ def test_convert_dat_to_glows_l3e_ul_product(self, mock_calculate_energy_deltas)
             strict=True,
         )
 
-        np.testing.assert_equal(
-            np.array([0.5]), l3e_ul_product.spacecraft_radius, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([85.4]), l3e_ul_product.spacecraft_longitude, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([45.1]), l3e_ul_product.spacecraft_latitude, strict=True
-        )
+        np.testing.assert_equal(np.array([0.5]), l3e_ul_product.spacecraft_radius, strict=True)
+        np.testing.assert_equal(np.array([85.4]), l3e_ul_product.spacecraft_longitude, strict=True)
+        np.testing.assert_equal(np.array([45.1]), l3e_ul_product.spacecraft_latitude, strict=True)
 
-        np.testing.assert_equal(
-            np.array([2.1]), l3e_ul_product.spacecraft_velocity_x, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([2.2]), l3e_ul_product.spacecraft_velocity_y, strict=True
-        )
-        np.testing.assert_equal(
-            np.array([2.3]), l3e_ul_product.spacecraft_velocity_z, strict=True
-        )
+        np.testing.assert_equal(np.array([2.1]), l3e_ul_product.spacecraft_velocity_x, strict=True)
+        np.testing.assert_equal(np.array([2.2]), l3e_ul_product.spacecraft_velocity_y, strict=True)
+        np.testing.assert_equal(np.array([2.3]), l3e_ul_product.spacecraft_velocity_z, strict=True)
 
-        np.testing.assert_equal(
-            np.array([30.0]), l3e_ul_product.elongation_excluded, strict=True
-        )
+        np.testing.assert_equal(np.array([30.0]), l3e_ul_product.elongation_excluded, strict=True)
 
-        np.testing.assert_equal(
-            (1, 3072), l3e_ul_product.pixel_latitude.shape, strict=True
-        )
-        np.testing.assert_equal(
-            (1, 3072), l3e_ul_product.pixel_longitude.shape, strict=True
-        )
+        np.testing.assert_equal((1, 3072), l3e_ul_product.pixel_latitude.shape, strict=True)
+        np.testing.assert_equal((1, 3072), l3e_ul_product.pixel_longitude.shape, strict=True)
         np.testing.assert_equal(87.07582, l3e_ul_product.pixel_latitude[0, 0])
         np.testing.assert_equal(45.00000, l3e_ul_product.pixel_longitude[0, 0])
 
diff --git a/tests/glows/l3e/test_glows_l3e_utils.py b/tests/glows/l3e/test_glows_l3e_utils.py
index 66e47959..5d2b33d8 100644
--- a/tests/glows/l3e/test_glows_l3e_utils.py
+++ b/tests/glows/l3e/test_glows_l3e_utils.py
@@ -2,7 +2,7 @@
 import unittest
 from datetime import datetime, timedelta
 from pathlib import Path
-from unittest.mock import patch, Mock, call
+from unittest.mock import Mock, call, patch
 
 import imap_data_access
 import numpy as np
@@ -18,23 +18,23 @@
     GlowsL3eSpacecraftInfo,
 )
 from imap_l3_processing.glows.l3e.glows_l3e_utils import (
-    determine_call_args_for_l3e_executable,
-    get_lo_pivot_angles,
-    get_lo_pivot_angle_from_l1b_file,
     LoPivotAngle,
+    calculate_energy_deltas,
     compute_glows_flags_for_repoint,
-    get_repoint_numbers_within_cr_window,
+    determine_call_args_for_l3e_executable,
     determine_spacecraft_info_for_l3e_executable,
     determine_spacecraft_info_using_predict_if_needed,
-    calculate_energy_deltas,
+    get_lo_pivot_angle_from_l1b_file,
+    get_lo_pivot_angles,
+    get_repoint_numbers_within_cr_window,
 )
 from imap_l3_processing.glows.quality_flags import GlowsL3Flags
 from imap_l3_processing.utils import FurnishMetakernelOutput
 from tests.integration.integration_test_helpers import (
-    mock_imap_data_access,
     create_metakernel,
+    mock_imap_data_access,
 )
-from tests.test_helpers import get_test_data_path, get_integration_test_data_path
+from tests.test_helpers import get_integration_test_data_path, get_test_data_path
 
 
 class TestGlowsL3EUtils(unittest.TestCase):
@@ -82,9 +82,7 @@ def test_determine_spacecraft_info_for_l3e_executable(
 
         radius, longitude, latitude = 70000000, -8.0, -0.9
 
-        rotation_matrix = np.array(
-            [[10.0, 11.0, 12.0], [13.0, 14.0, 15.0], [16.0, 17.0, 18.0]]
-        )
+        rotation_matrix = np.array([[10.0, 11.0, 12.0], [13.0, 14.0, 15.0], [16.0, 17.0, 18.0]])
         mock_pxform.return_value = rotation_matrix
 
         spin_axis_long, spin_axis_lat = -1.4, 0.2
@@ -93,8 +91,8 @@ def test_determine_spacecraft_info_for_l3e_executable(
             (Mock(), spin_axis_long, spin_axis_lat),
         ]
 
-        call_args: GlowsL3eSpacecraftInfo = (
-            determine_spacecraft_info_for_l3e_executable(repointing_midpoint)
+        call_args: GlowsL3eSpacecraftInfo = determine_spacecraft_info_for_l3e_executable(
+            repointing_midpoint
         )
 
         self.assertIsInstance(call_args, GlowsL3eSpacecraftInfo)
@@ -110,9 +108,7 @@ def test_determine_spacecraft_info_for_l3e_executable(
         mock_pxform.assert_called_once_with(
             "IMAP_DPS", "ECLIPJ2000", mock_date_time_2et.return_value
         )
-        np.testing.assert_array_equal(
-            [12.0, 15.0, 18.0], mock_reclat.call_args_list[1][0][0]
-        )
+        np.testing.assert_array_equal([12.0, 15.0, 18.0], mock_reclat.call_args_list[1][0][0])
 
         self.assertEqual(0.4679210985587912, call_args.spacecraft_radius)
         self.assertEqual(261.6337638953414, call_args.spacecraft_longitude)
@@ -120,24 +116,16 @@ def test_determine_spacecraft_info_for_l3e_executable(
         self.assertEqual(vx, call_args.spacecraft_velocity_x)
         self.assertEqual(vy, call_args.spacecraft_velocity_y)
         self.assertEqual(vz, call_args.spacecraft_velocity_z)
-        self.assertEqual(
-            np.rad2deg(spin_axis_long) % 360, call_args.spin_axis_longitude
-        )
+        self.assertEqual(np.rad2deg(spin_axis_long) % 360, call_args.spin_axis_longitude)
         self.assertEqual(np.rad2deg(spin_axis_lat), call_args.spin_axis_latitude)
 
     def test_determine_spacecraft_info_using_predict_if_needed(self):
         with tempfile.TemporaryDirectory() as tmp_dir:
             input_files = [
                 get_integration_test_data_path("spice/de440.bsp"),
-                get_integration_test_data_path(
-                    "spice/imap_dps_2025_359_2026_058_002.ah.bc"
-                ),
-                get_integration_test_data_path(
-                    "spice/imap_dps_2025_359_2026_131_002.ah.bc"
-                ),
-                get_integration_test_data_path(
-                    "spice/imap_recon_20250925_20260520_v01.bsp"
-                ),
+                get_integration_test_data_path("spice/imap_dps_2025_359_2026_058_002.ah.bc"),
+                get_integration_test_data_path("spice/imap_dps_2025_359_2026_131_002.ah.bc"),
+                get_integration_test_data_path("spice/imap_recon_20250925_20260520_v01.bsp"),
                 get_integration_test_data_path("spice/imap_science_120.tf"),
                 get_integration_test_data_path("spice/imap_sclk_0171.tsc"),
                 get_integration_test_data_path("spice/naif0012.tls"),
@@ -185,16 +173,12 @@ def test_determine_spacecraft_info_using_predict_if_needed(self):
                 date_with_predict = datetime(2026, 3, 25, 12)
                 date_without_predict = datetime(2026, 1, 15, 12)
 
-                result_without_predict = (
-                    determine_spacecraft_info_using_predict_if_needed(
-                        date_without_predict, spice_with_predict, spice_without_predict
-                    )
+                result_without_predict = determine_spacecraft_info_using_predict_if_needed(
+                    date_without_predict, spice_with_predict, spice_without_predict
                 )
                 spacecraft_info, glows_flags, kernel_names = result_without_predict
                 self.assertEqual(GlowsL3Flags.NONE, glows_flags)
-                self.assertEqual(
-                    ["kernel 5", "kernel 6", "kernel 7", "kernel 8"], kernel_names
-                )
+                self.assertEqual(["kernel 5", "kernel 6", "kernel 7", "kernel 8"], kernel_names)
                 self.assertEqual(
                     GlowsL3eSpacecraftInfo(
                         spacecraft_radius=0.974926812207828,
@@ -214,9 +198,7 @@ def test_determine_spacecraft_info_using_predict_if_needed(self):
                 )
                 spacecraft_info, glows_flags, kernel_names = result_with_predict
                 self.assertEqual(GlowsL3Flags.PREDICTIVE_EPHEMERIS, glows_flags)
-                self.assertEqual(
-                    ["kernel 1", "kernel 2", "kernel 3", "kernel 4"], kernel_names
-                )
+                self.assertEqual(["kernel 1", "kernel 2", "kernel 3", "kernel 4"], kernel_names)
                 self.assertEqual(
                     GlowsL3eSpacecraftInfo(
                         spacecraft_radius=0.9869148557889134,
@@ -232,9 +214,7 @@ def test_determine_spacecraft_info_using_predict_if_needed(self):
                 )
 
     def test_get_lo_pivot_angle_from_l1b_file_real_cdf(self):
-        l1b_file = get_test_data_path(
-            "glows/imap_lo_l1b_nhk_20260318-repoint00189_v003.cdf"
-        )
+        l1b_file = get_test_data_path("glows/imap_lo_l1b_nhk_20260318-repoint00189_v003.cdf")
         actual = get_lo_pivot_angle_from_l1b_file(l1b_file)
         self.assertEqual(90.0, actual)
 
@@ -289,14 +269,13 @@ def test_get_lo_pivot_angle_from_l1b_file_scenarios(self):
             ("fallback to 90 if no points at all", [], [], 90),
         ]
         for name, epochs, pivot_angles, expected in cases:
-            with self.subTest(name):
-                with tempfile.TemporaryDirectory() as tmp_dir:
-                    cdf_path = Path(tmp_dir, "l1b.cdf")
-                    with CDF(str(cdf_path), create=True) as cdf:
-                        cdf["epoch"] = epochs
-                        cdf["pcc_coarse_pot_pri"] = pivot_angles
-                    actual = get_lo_pivot_angle_from_l1b_file(cdf_path)
-                    self.assertEqual(expected, actual)
+            with self.subTest(name), tempfile.TemporaryDirectory() as tmp_dir:
+                cdf_path = Path(tmp_dir, "l1b.cdf")
+                with CDF(str(cdf_path), create=True) as cdf:
+                    cdf["epoch"] = epochs
+                    cdf["pcc_coarse_pot_pri"] = pivot_angles
+                actual = get_lo_pivot_angle_from_l1b_file(cdf_path)
+                self.assertEqual(expected, actual)
 
     def test_compute_glows_flags_for_repoint(self):
         epochs = [
@@ -334,50 +313,40 @@ def test_compute_glows_flags_for_repoint(self):
             (
                 "between cr 4 and 5",
                 datetime(2025, 6, 7),
-                GlowsL3Flags.PREDICTIVE_EPHEMERIS
-                | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
+                GlowsL3Flags.PREDICTIVE_EPHEMERIS | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
             ),
             (
                 "after last data point",
                 datetime(2025, 6, 15, 1),
-                GlowsL3Flags.PREDICTIVE_EPHEMERIS
-                | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
+                GlowsL3Flags.PREDICTIVE_EPHEMERIS | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
             ),
         ]
 
         for name, repoint_midpoint, expected in cases:
-            with self.subTest(name):
-                with tempfile.TemporaryDirectory() as tmp_dir:
-                    cdf_path = Path(tmp_dir, "l3d.cdf")
-                    with CDF(str(cdf_path), create=True) as cdf:
-                        cdf["epoch"] = epochs
-                        cdf.new(
-                            "glows_flags",
-                            data=flags,
-                            type=const.CDF_UINT2,
-                            recVary=True,
-                        )
-
-                    actual = compute_glows_flags_for_repoint(cdf_path, repoint_midpoint)
-
-                    self.assertIsInstance(actual, int)
-                    self.assertEqual(expected, actual)
-
-    @patch(
-        "imap_l3_processing.glows.l3e.glows_l3e_utils.get_lo_pivot_angle_from_l1b_file"
-    )
+            with self.subTest(name), tempfile.TemporaryDirectory() as tmp_dir:
+                cdf_path = Path(tmp_dir, "l3d.cdf")
+                with CDF(str(cdf_path), create=True) as cdf:
+                    cdf["epoch"] = epochs
+                    cdf.new(
+                        "glows_flags",
+                        data=flags,
+                        type=const.CDF_UINT2,
+                        recVary=True,
+                    )
+
+                actual = compute_glows_flags_for_repoint(cdf_path, repoint_midpoint)
+
+                self.assertIsInstance(actual, int)
+                self.assertEqual(expected, actual)
+
+    @patch("imap_l3_processing.glows.l3e.glows_l3e_utils.get_lo_pivot_angle_from_l1b_file")
     @patch("imap_l3_processing.glows.l3e.glows_l3e_utils.imap_data_access")
-    def test_get_lo_pivot_angles(
-        self, mock_imap_data_access, mock_get_pivot_angle_from_file
-    ):
+    def test_get_lo_pivot_angles(self, mock_imap_data_access, mock_get_pivot_angle_from_file):
         available_repointings = [1, 2, 3, 4, 5, 6]
         mock_imap_data_access.query.return_value = [
-            {"file_path": f"file{i}.cdf", "repointing": i}
-            for i in available_repointings
+            {"file_path": f"file{i}.cdf", "repointing": i} for i in available_repointings
         ]
-        mock_imap_data_access.download.side_effect = lambda name: Path(
-            "local/path/to", name
-        )
+        mock_imap_data_access.download.side_effect = lambda name: Path("local/path/to", name)
         pivot_angles_by_file_path = {
             Path("local/path/to/file1.cdf"): 25,
             Path("local/path/to/file2.cdf"): 75,
@@ -453,13 +422,7 @@ def test_calculate_energy_deltas(self):
         expected_energy_delta_minus = np.array([9, 900, 90000])
         expected_energy_delta_plus = np.array([90, 9000, 900000])
 
-        actual_energy_delta_plus, actual_energy_delta_minus = calculate_energy_deltas(
-            centers
-        )
+        actual_energy_delta_plus, actual_energy_delta_minus = calculate_energy_deltas(centers)
 
-        np.testing.assert_array_equal(
-            actual_energy_delta_plus, expected_energy_delta_plus
-        )
-        np.testing.assert_array_equal(
-            actual_energy_delta_minus, expected_energy_delta_minus
-        )
+        np.testing.assert_array_equal(actual_energy_delta_plus, expected_energy_delta_plus)
+        np.testing.assert_array_equal(actual_energy_delta_minus, expected_energy_delta_minus)
diff --git a/tests/glows/l3e/test_reprocess_info.py b/tests/glows/l3e/test_reprocess_info.py
index 6e880071..8c6a9a8a 100644
--- a/tests/glows/l3e/test_reprocess_info.py
+++ b/tests/glows/l3e/test_reprocess_info.py
@@ -3,21 +3,21 @@
 from pathlib import Path
 from unittest.mock import patch
 
-from imap_data_access import ProcessingInputCollection, AncillaryInput, RepointInput
+from imap_data_access import AncillaryInput, ProcessingInputCollection, RepointInput
 from imap_processing.spice.repoint import (
-    set_global_repoint_table_paths,
     get_repoint_data,
+    set_global_repoint_table_paths,
 )
 
 from imap_l3_processing.glows.descriptors import (
+    GLOWS_L3B_DESCRIPTOR,
+    GLOWS_L3C_DESCRIPTOR,
+    GLOWS_L3D_DESCRIPTOR,
     GLOWS_L3E_HI_45_DESCRIPTOR,
     GLOWS_L3E_HI_90_DESCRIPTOR,
     GLOWS_L3E_LO_DESCRIPTOR,
-    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
     GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
-    GLOWS_L3B_DESCRIPTOR,
-    GLOWS_L3C_DESCRIPTOR,
-    GLOWS_L3D_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
     GLOWS_REPROCESSING_DESCRIPTOR,
 )
 from imap_l3_processing.glows.l3e.reprocess_info import (
@@ -42,9 +42,7 @@ def test_parse_from_ancillary(self, mock_datetime):
         test_file: Path = (
             get_test_data_folder() / "glows" / "glows_reprocessing_ancillary_file.dat"
         )
-        mock_datetime.now.return_value = datetime(
-            2026, 8, 11, 11, 40, tzinfo=timezone.utc
-        )
+        mock_datetime.now.return_value = datetime(2026, 8, 11, 11, 40, tzinfo=timezone.utc)
         cases = [
             (datetime(2026, 8, 11, 11, 41, tzinfo=timezone.utc), products),
             (datetime(2026, 8, 11, 11, 41), products),
@@ -57,9 +55,7 @@ def test_parse_from_ancillary(self, mock_datetime):
 
                 reprocess_info = ReprocessInfo.parse_from_ancillary(test_file)
 
-                self.assertEqual(
-                    expected_products, reprocess_info.products_to_reprocess
-                )
+                self.assertEqual(expected_products, reprocess_info.products_to_reprocess)
                 mock_datetime.fromisoformat.assert_called_with("2226-08-11 11:40")
                 mock_datetime.now.assert_called_with(timezone.utc)
 
@@ -131,9 +127,7 @@ def test_should_reprocess_l3d_if_l3d_or_l3e_products_are_specified(self):
     def test_get_repoints(self):
         reprocess_info = ReprocessInfo(
             {
-                GLOWS_L3E_LO_DESCRIPTOR: ReprocessTargets(
-                    [2045, 2046, 3700], [2093, 2094]
-                ),
+                GLOWS_L3E_LO_DESCRIPTOR: ReprocessTargets([2045, 2046, 3700], [2093, 2094]),
                 GLOWS_L3E_HI_45_DESCRIPTOR: ReprocessTargets([2050], []),
             }
         )
@@ -165,13 +159,9 @@ def test_get_repoints(self):
         self.assertEqual(expected_repoints_ultra, repoints_for_ultra)
 
     @patch("imap_l3_processing.glows.l3e.glows_l3e_utils.imap_data_access.download")
-    def test_fetch_reprocess_info_downloads_and_parses_reprocess_info(
-        self, mock_download
-    ):
+    def test_fetch_reprocess_info_downloads_and_parses_reprocess_info(self, mock_download):
         processing_input = ProcessingInputCollection(
-            AncillaryInput(
-                f"imap_glows_{GLOWS_REPROCESSING_DESCRIPTOR}_20250101_v000.dat"
-            ),
+            AncillaryInput(f"imap_glows_{GLOWS_REPROCESSING_DESCRIPTOR}_20250101_v000.dat"),
             RepointInput("imap_2026_269_12.repoint.csv"),
         )
         path_to_downloaded_ancillary = (
@@ -193,6 +183,4 @@ def test_fetch_reprocess_info_downloads_and_parses_reprocess_info(
             GLOWS_L3E_ULTRA_HF_DESCRIPTOR: ReprocessTargets([243], []),
             GLOWS_L3D_DESCRIPTOR: ReprocessTargets([], []),
         }
-        self.assertEqual(
-            expected_products_to_reprocess, reprocess_info.products_to_reprocess
-        )
+        self.assertEqual(expected_products_to_reprocess, reprocess_info.products_to_reprocess)
diff --git a/tests/glows/test_glows_processor.py b/tests/glows/test_glows_processor.py
index fc3de6c1..1453236f 100644
--- a/tests/glows/test_glows_processor.py
+++ b/tests/glows/test_glows_processor.py
@@ -10,7 +10,7 @@
 from datetime import datetime, timedelta
 from pathlib import Path
 from subprocess import CalledProcessError, CompletedProcess
-from unittest.mock import patch, Mock, sentinel, call, MagicMock
+from unittest.mock import MagicMock, Mock, call, patch, sentinel
 from zipfile import ZIP_DEFLATED
 
 import imap_data_access
@@ -23,24 +23,24 @@
 from imap_l3_processing.glows import l3d
 from imap_l3_processing.glows.descriptors import (
     GLOWS_L3A_DESCRIPTOR,
-    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
-    GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
     GLOWS_L3B_DESCRIPTOR,
     GLOWS_L3C_DESCRIPTOR,
     GLOWS_L3D_DESCRIPTOR,
     GLOWS_L3E_HI_45_DESCRIPTOR,
     GLOWS_L3E_HI_90_DESCRIPTOR,
     GLOWS_L3E_LO_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
 )
 from imap_l3_processing.glows.glows_processor import (
     GlowsProcessor,
+    process_l3bc,
     process_l3d,
     process_l3e,
-    process_l3bc,
-    process_l3e_ul_sf,
     process_l3e_hi,
     process_l3e_lo,
     process_l3e_ul_hf,
+    process_l3e_ul_sf,
 )
 from imap_l3_processing.glows.l3a.utils import (
     create_glows_l3a_dictionary_from_cdf,
@@ -74,10 +74,10 @@
 from imap_l3_processing.models import InputMetadata, VersionMap
 from imap_l3_processing.utils import save_data
 from tests.test_helpers import (
-    get_test_instrument_team_data_path,
-    get_test_data_path,
-    get_test_data_folder,
     assert_dataclass_fields,
+    get_test_data_folder,
+    get_test_data_path,
+    get_test_instrument_team_data_path,
 )
 
 MODULE = "imap_l3_processing.glows.glows_processor"
@@ -85,9 +85,7 @@
 
 class TestGlowsProcessor(unittest.TestCase):
     def setUp(self):
-        self.l3bc_initializer_patcher = patch(
-            f"{MODULE}.GlowsL3BCInitializer.get_crs_to_process"
-        )
+        self.l3bc_initializer_patcher = patch(f"{MODULE}.GlowsL3BCInitializer.get_crs_to_process")
         self.mock_l3bc_initializer = self.l3bc_initializer_patcher.start()
 
         self.mock_external_deps = Mock()
@@ -161,18 +159,14 @@ def test_processor_handles_l3a(
         outgoing_data_level = "l3a"
         outgoing_version = "v002"
 
-        mock_fetched_dependencies = (
-            mock_glows_dependencies_class.fetch_dependencies.return_value
-        )
+        mock_fetched_dependencies = mock_glows_dependencies_class.fetch_dependencies.return_value
         mock_fetched_dependencies.ancillary_files = {
             "settings": get_test_instrument_team_data_path(
                 "glows/imap_glows_pipeline-settings_20100101_v001.json"
             )
         }
         l3a_json_path = (
-            get_test_data_folder()
-            / "glows"
-            / "imap_glows_l3a_20130908085214_orbX_modX_p_v00.json"
+            get_test_data_folder() / "glows" / "imap_glows_l3a_20130908085214_orbX_modX_p_v00.json"
         )
         with open(l3a_json_path) as f:
             mock_l3a_data.return_value.data = json.load(f)
@@ -208,9 +202,7 @@ def test_processor_handles_l3a(
             ],
             "l2_input_file_name": "data_l2_histograms/imap_glows_l2_20130908085214_orbX_modX_p_v00.json",
         }
-        mock_processing_input_collection.get_file_paths.return_value = [
-            parent_file_path
-        ]
+        mock_processing_input_collection.get_file_paths.return_value = [parent_file_path]
 
         processor = GlowsProcessor(
             dependencies=mock_processing_input_collection, input_metadata=input_metadata
@@ -229,12 +221,8 @@ def test_processor_handles_l3a(
         expected_data_to_save.parent_file_names = expected_parent_file_names
         actual_data = mock_save_data.call_args.args[0]
         self.assertEqual(expected_parent_file_names, actual_data.parent_file_names)
-        self.assertEqual(
-            expected_global_metadata_attrs, actual_data.global_metadata_attrs
-        )
-        assert_dataclass_fields(
-            expected_data_to_save, actual_data, omit=["global_metadata_attrs"]
-        )
+        self.assertEqual(expected_global_metadata_attrs, actual_data.global_metadata_attrs)
+        assert_dataclass_fields(expected_data_to_save, actual_data, omit=["global_metadata_attrs"])
         self.assertEqual([mock_cdf_path], products)
 
     @patch("imap_l3_processing.glows.glows_processor.GlowsL3ADependencies")
@@ -285,12 +273,8 @@ def test_process_l3a(self, l3a_data_constructor, create_glows_l3a_from_dictionar
         result = processor.process_l3a(fetched_dependencies)
 
         self.assertIs(create_glows_l3a_from_dictionary.return_value, result)
-        l3a_data_constructor.assert_called_once_with(
-            fetched_dependencies.ancillary_files
-        )
-        mock_l3a_data.process_l2_data_file.assert_called_once_with(
-            fetched_dependencies.data
-        )
+        l3a_data_constructor.assert_called_once_with(fetched_dependencies.ancillary_files)
+        mock_l3a_data.process_l2_data_file.assert_called_once_with(fetched_dependencies.data)
         mock_l3a_data.generate_l3a_data.assert_called_once_with(
             fetched_dependencies.ancillary_files
         )
@@ -326,9 +310,7 @@ def test_process_l3a_returns_none_when_no_input_histrogram_bins_are_valid(
 
         self.assertIsNone(result)
 
-        mock_l3a_data.process_l2_data_file.assert_called_once_with(
-            fetched_dependencies.data
-        )
+        mock_l3a_data.process_l2_data_file.assert_called_once_with(fetched_dependencies.data)
         mock_l3a_data.generate_l3a_data.assert_called_once_with(
             fetched_dependencies.ancillary_files
         )
@@ -342,9 +324,7 @@ def test_add_spin_angle_delta(self):
             with self.subTest(bin=bins, expected_delta=expected_delta):
                 ancillary_files = {}
                 with open(
-                    get_test_data_path(
-                        "glows/imap_glows_l3a_20130908085214_orbX_modX_p_v00.json"
-                    )
+                    get_test_data_path("glows/imap_glows_l3a_20130908085214_orbX_modX_p_v00.json")
                 ) as f:
                     example_data = json.load(f)
 
@@ -385,9 +365,7 @@ def test_add_spin_angle_delta(self):
     @patch("imap_l3_processing.glows.glows_processor.GlowsL3CSolarWind")
     @patch("imap_l3_processing.glows.glows_processor.filter_l3a_files")
     @patch("imap_l3_processing.glows.glows_processor.generate_l3bc")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies")
     @patch("imap_l3_processing.glows.glows_processor.GlowsL3BCInitializer")
     def test_process_l3bc(
         self,
@@ -492,14 +470,12 @@ def test_process_l3bc(
             version=input_version,
         )
 
-        mock_glows_l3bc_initializer.get_crs_to_process.return_value = (
-            GlowsL3BCInitializerData(
-                external_dependencies=external_deps,
-                l3bc_dependencies=[first_dependency, second_dependency],
-                l3bs_by_cr={},
-                l3cs_by_cr={},
-                repoint_file_path=sentinel.repoint_file_path,
-            )
+        mock_glows_l3bc_initializer.get_crs_to_process.return_value = GlowsL3BCInitializerData(
+            external_dependencies=external_deps,
+            l3bc_dependencies=[first_dependency, second_dependency],
+            l3bs_by_cr={},
+            l3cs_by_cr={},
+            repoint_file_path=sentinel.repoint_file_path,
         )
 
         processor = GlowsProcessor(
@@ -528,12 +504,8 @@ def test_process_l3bc(
 
         mock_filter_bad_days.assert_has_calls(
             [
-                call(
-                    [l3a_data_1], sentinel.bad_days_list_1, first_cr_number_to_process
-                ),
-                call(
-                    [l3a_data_2], sentinel.bad_days_list_2, second_cr_number_to_process
-                ),
+                call([l3a_data_1], sentinel.bad_days_list_1, first_cr_number_to_process),
+                call([l3a_data_2], sentinel.bad_days_list_2, second_cr_number_to_process),
             ]
         )
 
@@ -645,9 +617,7 @@ def test_process_l3bc(
         "imap_l3_processing.glows.glows_processor.GlowsL3CSolarWind.from_instrument_team_dictionary"
     )
     @patch("imap_l3_processing.glows.glows_processor.generate_l3bc")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies")
     @patch("imap_l3_processing.glows.glows_processor.save_data")
     @patch("imap_l3_processing.glows.glows_processor.GlowsL3BCInitializer")
     def test_process_l3bc_catches_no_data_error_and_continues(
@@ -681,14 +651,12 @@ def test_process_l3bc_catches_no_data_error_and_continues(
             repointing_file_path=sentinel.repointing_file_path,
         )
         external_dependencies = ExternalDependencies(None, None, None)
-        mock_glows_initializer_class.get_crs_to_process.return_value = (
-            GlowsL3BCInitializerData(
-                external_dependencies=external_dependencies,
-                l3bc_dependencies=[bc_dependencies_1, bc_dependencies_2],
-                l3bs_by_cr={},
-                l3cs_by_cr={},
-                repoint_file_path=sentinel.repoint_file_path,
-            )
+        mock_glows_initializer_class.get_crs_to_process.return_value = GlowsL3BCInitializerData(
+            external_dependencies=external_dependencies,
+            l3bc_dependencies=[bc_dependencies_1, bc_dependencies_2],
+            l3bs_by_cr={},
+            l3cs_by_cr={},
+            repoint_file_path=sentinel.repoint_file_path,
         )
 
         zip_file_1 = "imap_glows_archive_20210101_v001.zip"
@@ -765,9 +733,7 @@ def test_process_l3bc_catches_no_data_error_and_continues(
         self.assertEqual(3, len(products))
         self.assertEqual([l3b_path, l3c_path, zip_file_2], products)
 
-    @patch(
-        "imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies")
     @patch("imap_l3_processing.glows.glows_processor.generate_l3bc")
     def test_process_l3bc_catches_exceptions_from_science_code_and_continues(
         self, mock_generate_l3bc, _
@@ -775,15 +741,12 @@ def test_process_l3bc_catches_exceptions_from_science_code_and_continues(
         l3a_data_folder_path = get_test_data_path("glows/l3a_products")
         l3a_data = [
             create_glows_l3a_dictionary_from_cdf(
-                l3a_data_folder_path
-                / "imap_glows_l3a_hist_20100201-repoint00032_v001.cdf"
+                l3a_data_folder_path / "imap_glows_l3a_hist_20100201-repoint00032_v001.cdf"
             )
         ]
 
         external_dependencies = ExternalDependencies(
-            f107_index_file_path=get_test_instrument_team_data_path(
-                "glows/f107_fluxtable.txt"
-            ),
+            f107_index_file_path=get_test_instrument_team_data_path("glows/f107_fluxtable.txt"),
             omni2_data_path=get_test_instrument_team_data_path("glows/omni_2010.dat"),
             lyman_alpha_path=None,
         )
@@ -797,20 +760,14 @@ def test_process_l3bc_catches_exceptions_from_science_code_and_continues(
                 "WawHelioIonMP_parameters": get_test_data_path(
                     "glows/imap_glows_WawHelioIonMP_20100101_v002.json"
                 ),
-                "bad_days_list": get_test_data_path(
-                    "glows/imap_glows_bad-days-list_v001.dat"
-                ),
+                "bad_days_list": get_test_data_path("glows/imap_glows_bad-days-list_v001.dat"),
                 "pipeline_settings": get_test_instrument_team_data_path(
                     "glows/imap_glows_pipeline-settings-L3bc_20250707_v002.json"
                 ),
             },
             external_files={
-                "f107_raw_data": get_test_instrument_team_data_path(
-                    "glows/f107_fluxtable.txt"
-                ),
-                "omni_raw_data": get_test_instrument_team_data_path(
-                    "glows/omni_2010.dat"
-                ),
+                "f107_raw_data": get_test_instrument_team_data_path("glows/f107_fluxtable.txt"),
+                "omni_raw_data": get_test_instrument_team_data_path("glows/omni_2010.dat"),
             },
             carrington_rotation_number=1,
             start_date=Mock(),
@@ -836,13 +793,9 @@ def test_process_l3bc_catches_exceptions_from_science_code_and_continues(
 
         self.assertEqual([], processor_output.data_products)
 
-    @patch(
-        "imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.GlowsProcessor.archive_dependencies")
     @patch("imap_l3_processing.glows.glows_processor.save_data")
-    def test_l3bc_uses_all_l3a_file_names_for_l3b_parents(
-        self, mock_save_data, mock_archive_deps
-    ):
+    def test_l3bc_uses_all_l3a_file_names_for_l3b_parents(self, mock_save_data, mock_archive_deps):
         mock_archive_deps.return_value = Path("some/path/to/archive.zip")
 
         l3a_data_folder_path = get_test_data_path("glows/l3a_products")
@@ -865,20 +818,14 @@ def test_l3bc_uses_all_l3a_file_names_for_l3b_parents(
                 "WawHelioIonMP_parameters": get_test_data_path(
                     "glows/imap_glows_WawHelioIonMP_20100101_v002.json"
                 ),
-                "bad_days_list": get_test_data_path(
-                    "glows/imap_glows_bad-days-list_v001.dat"
-                ),
+                "bad_days_list": get_test_data_path("glows/imap_glows_bad-days-list_v001.dat"),
                 "pipeline_settings": get_test_instrument_team_data_path(
                     "glows/imap_glows_pipeline-settings-L3bc_20250707_v002.json"
                 ),
             },
             external_files={
-                "f107_raw_data": get_test_instrument_team_data_path(
-                    "glows/f107_fluxtable.txt"
-                ),
-                "omni_raw_data": get_test_instrument_team_data_path(
-                    "glows/omni2_all_years.dat"
-                ),
+                "f107_raw_data": get_test_instrument_team_data_path("glows/f107_fluxtable.txt"),
+                "omni_raw_data": get_test_instrument_team_data_path("glows/omni2_all_years.dat"),
             },
             carrington_rotation_number=2092,
             start_date=Mock(),
@@ -923,17 +870,11 @@ def test_process_l3d_uploads_even_if_no_l3e_needs_to_be_produced(
         self.test_process_l3d()
 
     @patch("imap_l3_processing.glows.glows_processor.process_l3e")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.create_glows_l3b_json_file_from_cdf"
-    )
-    @patch(
-        "imap_l3_processing.glows.glows_processor.create_glows_l3c_json_file_from_cdf"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.create_glows_l3b_json_file_from_cdf")
+    @patch("imap_l3_processing.glows.glows_processor.create_glows_l3c_json_file_from_cdf")
     @patch("imap_l3_processing.glows.glows_processor.save_data")
     @patch("imap_l3_processing.glows.glows_processor.rename_l3d_text_outputs")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.get_parent_file_names_from_l3d_json"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.get_parent_file_names_from_l3d_json")
     @patch("imap_l3_processing.glows.glows_processor.convert_json_to_l3d_data_product")
     @patch("imap_l3_processing.glows.glows_processor.run")
     @patch("imap_l3_processing.glows.glows_processor.shutil")
@@ -1081,9 +1022,7 @@ def test_process_l3d(
                 },
                 "ancillary_files": {
                     "pipeline_settings": str(
-                        Path(
-                            "glows/imap_glows_pipeline-settings-l3bcde_20250514_v004.json"
-                        )
+                        Path("glows/imap_glows_pipeline-settings-l3bcde_20250514_v004.json")
                     ),
                     "WawHelioIon": {
                         "speed": str(Path("path/to/speed")),
@@ -1169,40 +1108,22 @@ def test_process_l3d_adds_parent_file_names_to_output(
         self, mock_spicepy, mock_run, mock_rename_l3d_text_output, mock_save_data
     ):
         mock_spicepy.ktotal.return_value = 0
-        l3b_path_1 = get_test_data_path(
-            "glows/imap_glows_l3b_ion-rate-profile_20100422_v011.cdf"
-        )
-        l3b_path_2 = get_test_data_path(
-            "glows/imap_glows_l3b_ion-rate-profile_20100519_v011.cdf"
-        )
-        l3c_path_1 = get_test_data_path(
-            "glows/imap_glows_l3c_sw-profile_20100422_v011.cdf"
-        )
-        l3c_path_2 = get_test_data_path(
-            "glows/imap_glows_l3c_sw-profile_20100519_v011.cdf"
-        )
+        l3b_path_1 = get_test_data_path("glows/imap_glows_l3b_ion-rate-profile_20100422_v011.cdf")
+        l3b_path_2 = get_test_data_path("glows/imap_glows_l3b_ion-rate-profile_20100519_v011.cdf")
+        l3c_path_1 = get_test_data_path("glows/imap_glows_l3c_sw-profile_20100422_v011.cdf")
+        l3c_path_2 = get_test_data_path("glows/imap_glows_l3c_sw-profile_20100519_v011.cdf")
 
         pipeline_settings_path = get_test_data_path(
             "glows/l3d_drift_test/imap_glows_pipeline-settings-l3bcde_20100101_v006.json"
         )
-        speed_path = get_test_data_path(
-            "glows/imap_glows_plasma-speed-Legendre-2010a_v001.dat"
-        )
-        p_dens_path = get_test_data_path(
-            "glows/imap_glows_proton-density-Legendre-2010a_v001.dat"
-        )
-        uv_anis_path = get_test_data_path(
-            "glows/imap_glows_uv-anisotropy-2010a_v001.dat"
-        )
+        speed_path = get_test_data_path("glows/imap_glows_plasma-speed-Legendre-2010a_v001.dat")
+        p_dens_path = get_test_data_path("glows/imap_glows_proton-density-Legendre-2010a_v001.dat")
+        uv_anis_path = get_test_data_path("glows/imap_glows_uv-anisotropy-2010a_v001.dat")
         phion_path = get_test_data_path("glows/imap_glows_photoion-2010a_v001.dat")
         lya_path = get_test_data_path("glows/imap_glows_lya-2010a_v001.dat")
-        e_dens_path = get_test_data_path(
-            "glows/imap_glows_electron-density-2010a_v001.dat"
-        )
+        e_dens_path = get_test_data_path("glows/imap_glows_electron-density-2010a_v001.dat")
 
-        lyman_alpha_composite_path = get_test_data_path(
-            "glows/lyman_alpha_composite.nc"
-        )
+        lyman_alpha_composite_path = get_test_data_path("glows/lyman_alpha_composite.nc")
 
         l3b_file_paths = [l3b_path_1, l3b_path_2]
         l3c_file_paths = [l3c_path_1, l3c_path_2]
@@ -1272,18 +1193,14 @@ def test_process_l3d_adds_parent_file_names_to_output(
             / "imap_glows_l3d_speed_19470303-cr02095_v00.dat",
         ]
 
-        self.assertCountEqual(
-            expected_parent_file_names, actual_data_product.parent_file_names
-        )
+        self.assertCountEqual(expected_parent_file_names, actual_data_product.parent_file_names)
         self.assertCountEqual(
             expected_l3d_txt_file_paths, mock_rename_l3d_text_output.call_args[0][0]
         )
         self.assertEqual("v001", mock_rename_l3d_text_output.call_args[0][1])
 
     @patch("imap_l3_processing.glows.glows_processor.rename_l3d_text_outputs")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.get_parent_file_names_from_l3d_json"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.get_parent_file_names_from_l3d_json")
     @patch("imap_l3_processing.glows.glows_processor.os")
     @patch("imap_l3_processing.glows.glows_processor.run")
     @patch("imap_l3_processing.glows.glows_processor.convert_json_to_l3d_data_product")
@@ -1359,12 +1276,8 @@ def test_process_glows_l3d_drift(self, mock_save_data, _):
         lyman_alpha_composite = l3d_drift_test_data / "lyman_alpha_composite.nc"
         expected_cr = 2098
 
-        l3b_1 = (
-            l3d_drift_test_data / "imap_glows_l3b_ion-rate-profile_20100422_v013.cdf"
-        )
-        l3b_2 = (
-            l3d_drift_test_data / "imap_glows_l3b_ion-rate-profile_20100519_v013.cdf"
-        )
+        l3b_1 = l3d_drift_test_data / "imap_glows_l3b_ion-rate-profile_20100422_v013.cdf"
+        l3b_2 = l3d_drift_test_data / "imap_glows_l3b_ion-rate-profile_20100519_v013.cdf"
         l3c_1 = l3d_drift_test_data / "imap_glows_l3c_sw-profile_20100422_v012.cdf"
         l3c_2 = l3d_drift_test_data / "imap_glows_l3c_sw-profile_20100519_v012.cdf"
 
@@ -1374,17 +1287,14 @@ def test_process_glows_l3d_drift(self, mock_save_data, _):
         proton_density_legendre = (
             l3d_drift_test_data / "imap_glows_proton-density-2010a_20100101_v003.dat"
         )
-        uv_anisotropy = (
-            l3d_drift_test_data / "imap_glows_uv-anisotropy-2010a_20100101_v003.dat"
-        )
+        uv_anisotropy = l3d_drift_test_data / "imap_glows_uv-anisotropy-2010a_20100101_v003.dat"
         photoion = l3d_drift_test_data / "imap_glows_photoion-2010a_20100101_v003.dat"
         lya_2010a = l3d_drift_test_data / "imap_glows_lya-2010a_20100101_v003.dat"
         electron_density = (
             l3d_drift_test_data / "imap_glows_electron-density-2010a_20100101_v003.dat"
         )
         pipeline_settings = (
-            l3d_drift_test_data
-            / "imap_glows_pipeline-settings-l3bcde_20100101_v006.json"
+            l3d_drift_test_data / "imap_glows_pipeline-settings-l3bcde_20100101_v006.json"
         )
 
         l3d_dependencies = GlowsL3DDependencies(
@@ -1633,9 +1543,7 @@ def test_process_glows_l3d_drift(self, mock_save_data, _):
         [save_data_call_args] = mock_save_data.call_args_list
         l3d_data_product = save_data_call_args.args[0]
 
-        expected_cdf_filename = (
-            "imap_glows_l3d_solar-hist_19470303-cr02098_v001.0004.cdf"
-        )
+        expected_cdf_filename = "imap_glows_l3d_solar-hist_19470303-cr02098_v001.0004.cdf"
         with tempfile.TemporaryDirectory() as tmp_dir:
             tmp_dir = Path(tmp_dir)
             save_data(l3d_data_product, cr_number=expected_cr, folder_path=tmp_dir)
@@ -1662,17 +1570,11 @@ def test_process_glows_l3d_drift(self, mock_save_data, _):
                         )
                         self.assertIsNotNone(actual_input_file_line)
 
-                        expected_input_file_line = (
-                            f"# input files: {expected_cdf_filename}"
-                        )
-                        self.assertEqual(
-                            expected_input_file_line, actual_input_file_line
-                        )
+                        expected_input_file_line = f"# input files: {expected_cdf_filename}"
+                        self.assertEqual(expected_input_file_line, actual_input_file_line)
 
                         self.assertEqual(length_of_data, len(actual))
-                        self.assertEqual(
-                            length_of_data, len(actual_cdf[cdf_var_name][...])
-                        )
+                        self.assertEqual(length_of_data, len(actual_cdf[cdf_var_name][...]))
 
                         np.testing.assert_allclose(actual[0], first_line)
                         np.testing.assert_allclose(actual[-1], last_line)
@@ -2008,9 +1910,7 @@ def test_process_l3e_invoked_from_top_level_process(
             self.mock_reprocess_info,
         )
         self.assertEqual(expected_products, products)
-        self.mock_fetch_reprocess_info.assert_called_once_with(
-            processing_input_collection
-        )
+        self.mock_fetch_reprocess_info.assert_called_once_with(processing_input_collection)
 
     @patch("imap_l3_processing.glows.glows_processor.Processor.get_parent_file_names")
     @patch("imap_l3_processing.glows.glows_processor.save_data")
@@ -2018,9 +1918,7 @@ def test_process_l3e_invoked_from_top_level_process(
         "imap_l3_processing.glows.glows_processor.GlowsL3EUltraData.convert_dat_to_glows_l3e_ul_product"
     )
     @patch("imap_l3_processing.glows.glows_processor.run")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable")
     @patch("imap_l3_processing.glows.glows_processor.shutil")
     def test_process_l3e_ultra_sf(
         self,
@@ -2062,7 +1960,9 @@ def test_process_l3e_ultra_sf(
 
         mock_convert_dat_to_glows_l3e_ul_product.return_value = sentinel.ultra_data_1
 
-        mock_save_data.return_value = "imap_glows_l3e_survival-probability-ul-sf_20241007-repoint00020_v001.0012.cdf"
+        mock_save_data.return_value = (
+            "imap_glows_l3e_survival-probability-ul-sf_20241007-repoint00020_v001.0012.cdf"
+        )
 
         parent_file_names = ["l3d_file", "ancillary_1", "ancillary_2", "ancillary_3"]
         glows_flags = 4
@@ -2085,7 +1985,7 @@ def test_process_l3e_ultra_sf(
             spacecraft_info=spacecraft_info,
         )
 
-        mock_run.assert_called_once_with(["./survProbUltra"] + ultra_args)
+        mock_run.assert_called_once_with(["./survProbUltra"] + ultra_args, check=False)
 
         output_data_path = Path("probSur.Imap.Ul_20241007_000000_date.001.dat")
 
@@ -2101,14 +2001,10 @@ def test_process_l3e_ultra_sf(
             "imap_glows_survival-probability-ul-sf-raw_20241007-repoint00020_v012.dat"
         ).construct_path()
 
-        mock_shutil.move.assert_called_once_with(
-            output_data_path, expected_first_data_path
-        )
+        mock_shutil.move.assert_called_once_with(output_data_path, expected_first_data_path)
 
         mock_save_data.assert_called_once_with(sentinel.ultra_data_1)
-        survival_data_product: GlowsL3EUltraData = mock_save_data.call_args_list[
-            0
-        ].args[0]
+        survival_data_product: GlowsL3EUltraData = mock_save_data.call_args_list[0].args[0]
         self.assertEqual(
             ["l3d_file", "ancillary_1", "ancillary_2", "ancillary_3"],
             survival_data_product.parent_file_names,
@@ -2131,9 +2027,7 @@ def test_process_l3e_ultra_sf(
         "imap_l3_processing.glows.glows_processor.GlowsL3EUltraData.convert_dat_to_glows_l3e_ul_product"
     )
     @patch("imap_l3_processing.glows.glows_processor.run")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable")
     @patch("imap_l3_processing.glows.glows_processor.shutil")
     def test_process_l3e_ultra_hf(
         self,
@@ -2203,7 +2097,9 @@ def test_process_l3e_ultra_hf(
 
         mock_convert_dat_to_glows_l3e_ul_product.return_value = sentinel.ultra_data_hf
 
-        mock_save_data.return_value = "imap_glows_l3e_survival-probability-ul-hf_20241007-repoint00020_v001.0012.cdf"
+        mock_save_data.return_value = (
+            "imap_glows_l3e_survival-probability-ul-hf_20241007-repoint00020_v001.0012.cdf"
+        )
 
         parent_file_names = ["l3d_file", "ancillary_1", "ancillary_2", "ancillary_3"]
         glows_flags = 8
@@ -2226,7 +2122,7 @@ def test_process_l3e_ultra_hf(
         )
 
         mock_run.assert_called_once_with(
-            ["./survProbUltra"] + expected_rest_frame_args.to_argument_list()
+            ["./survProbUltra"] + expected_rest_frame_args.to_argument_list(), check=False
         )
 
         output_data_path = Path("probSur.Imap.Ul.V0_20241007_000000_date.001.dat")
@@ -2243,14 +2139,10 @@ def test_process_l3e_ultra_hf(
             "imap_glows_survival-probability-ul-hf-raw_20241007-repoint00020_v012.dat"
         ).construct_path()
 
-        mock_shutil.move.assert_called_once_with(
-            output_data_path, expected_first_data_path
-        )
+        mock_shutil.move.assert_called_once_with(output_data_path, expected_first_data_path)
 
         mock_save_data.assert_called_once_with(sentinel.ultra_data_hf)
-        survival_data_product: GlowsL3EUltraData = mock_save_data.call_args_list[
-            0
-        ].args[0]
+        survival_data_product: GlowsL3EUltraData = mock_save_data.call_args_list[0].args[0]
         self.assertEqual(
             ["l3d_file", "ancillary_1", "ancillary_2", "ancillary_3"],
             survival_data_product.parent_file_names,
@@ -2272,9 +2164,7 @@ def test_process_l3e_ultra_hf(
         "imap_l3_processing.glows.glows_processor.GlowsL3EHiData.convert_dat_to_glows_l3e_hi_product"
     )
     @patch("imap_l3_processing.glows.glows_processor.run")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable")
     @patch("imap_l3_processing.glows.glows_processor.shutil")
     def test_process_l3e_hi(
         self,
@@ -2332,9 +2222,7 @@ def test_process_l3e_hi(
                 mock_call_args_object = MagicMock(spec=GlowsL3eCallArguments)
                 mock_call_args_object.to_argument_list.return_value = hi_args
                 mock_determine_call_args.return_value = mock_call_args_object
-                mock_convert_dat_to_glows_l3e_hi_product.return_value = (
-                    sentinel.hi_data_1
-                )
+                mock_convert_dat_to_glows_l3e_hi_product.return_value = sentinel.hi_data_1
 
                 saved_cdf_path = Path(
                     f"imap_glows_l3e_survival-probability-hi-{descriptor_elongation}_20241007-repoint00020_v001.0012.cdf"
@@ -2367,7 +2255,7 @@ def test_process_l3e_hi(
                     spacecraft_info=spacecraft_info,
                 )
 
-                mock_run.assert_called_once_with(["./survProbHi"] + hi_args)
+                mock_run.assert_called_once_with(["./survProbHi"] + hi_args, check=False)
 
                 first_output_data_path = Path(
                     f"probSur.Imap.Hi_20241007_000000_date.001_{descriptor_elongation[:5]}.dat"
@@ -2383,12 +2271,8 @@ def test_process_l3e_hi(
 
                 mock_save_data.assert_called_once_with(sentinel.hi_data_1)
 
-                survival_data_product: GlowsL3EHiData = mock_save_data.call_args_list[
-                    0
-                ].args[0]
-                self.assertEqual(
-                    parent_file_names, survival_data_product.parent_file_names
-                )
+                survival_data_product: GlowsL3EHiData = mock_save_data.call_args_list[0].args[0]
+                self.assertEqual(parent_file_names, survival_data_product.parent_file_names)
                 np.testing.assert_array_equal(
                     survival_data_product.glows_flags,
                     np.array([glows_flags], dtype=np.uint16),
@@ -2410,9 +2294,7 @@ def test_process_l3e_hi(
         "imap_l3_processing.glows.glows_processor.GlowsL3ELoData.convert_dat_to_glows_l3e_lo_product"
     )
     @patch("imap_l3_processing.glows.glows_processor.run")
-    @patch(
-        "imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable"
-    )
+    @patch("imap_l3_processing.glows.glows_processor.determine_call_args_for_l3e_executable")
     @patch("imap_l3_processing.glows.glows_processor.shutil")
     def test_process_l3e_lo(
         self,
@@ -2507,7 +2389,7 @@ def test_process_l3e_lo(
                     spacecraft_info=spacecraft_info,
                 )
 
-                mock_run.assert_called_once_with(["./survProbLo"] + lo_call_args)
+                mock_run.assert_called_once_with(["./survProbLo"] + lo_call_args, check=False)
 
                 first_output_file_path = Path(
                     f"probSur.Imap.Lo_20241007_000000_date.100_{elongation_filename}.dat"
@@ -2531,20 +2413,14 @@ def test_process_l3e_lo(
                 )
 
                 mock_save_data.assert_called_once_with(lo_data_1)
-                survival_data_product: GlowsL3ELoData = mock_save_data.call_args_list[
-                    0
-                ].args[0]
-                self.assertEqual(
-                    parent_file_names, survival_data_product.parent_file_names
-                )
+                survival_data_product: GlowsL3ELoData = mock_save_data.call_args_list[0].args[0]
+                self.assertEqual(parent_file_names, survival_data_product.parent_file_names)
                 np.testing.assert_array_equal(
                     survival_data_product.glows_flags,
                     np.array([glows_flags], dtype=np.uint16),
                 )
 
-                self.assertEqual(
-                    [output_cdf_path, expected_first_output_file_path], products
-                )
+                self.assertEqual([output_cdf_path, expected_first_output_file_path], products)
 
                 mock_shutil.reset_mock()
                 mock_determine_call_args.reset_mock()
@@ -2719,9 +2595,7 @@ def test_process_l3e_skips_repointing_on_exception(
 
         actual_l3e_products = process_l3e(initializer_data)
 
-        mock_get_pointing_date_range.assert_has_calls(
-            [call(24), call(25), call(26), call(27)]
-        )
+        mock_get_pointing_date_range.assert_has_calls([call(24), call(25), call(26), call(27)])
 
         mock_process_hi.assert_has_calls(
             [
@@ -2941,9 +2815,7 @@ def test_process_l3e_skips_repointing_on_exception(
     @patch("imap_l3_processing.glows.glows_processor.ZipFile")
     def test_archive_dependencies(self, mock_zip, mock_json):
         version_number = Version(1, 1)
-        expected_filepath = (
-            TEMP_CDF_FOLDER_PATH / "imap_glows_l3b-archive_20250314_v001.zip"
-        )
+        expected_filepath = TEMP_CDF_FOLDER_PATH / "imap_glows_l3b-archive_20250314_v001.zip"
         expected_json_filename = "cr_to_process.json"
 
         l3bc_dependencies = GlowsL3BCDependencies(
diff --git a/tests/hi/test_hi_combined_dependencies.py b/tests/hi/test_hi_combined_dependencies.py
index 634f342b..e02e4ac9 100644
--- a/tests/hi/test_hi_combined_dependencies.py
+++ b/tests/hi/test_hi_combined_dependencies.py
@@ -1,6 +1,6 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, call, sentinel
+from unittest.mock import call, patch, sentinel
 
 from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
 
@@ -49,9 +49,7 @@ def test_from_file_paths(self, read_cdf):
         self.assertEqual(expected_45_return_maps, result.h45_maps)
         self.assertEqual(expected_90_return_maps, result.h90_maps)
 
-    @patch(
-        "imap_l3_processing.hi.hi_combined_sensor_dependencies.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.hi.hi_combined_sensor_dependencies.imap_data_access.download")
     @patch(
         "imap_l3_processing.hi.hi_combined_sensor_dependencies.RectangularIntensityMapData.read_from_path"
     )
diff --git a/tests/hi/test_hi_combined_initializer.py b/tests/hi/test_hi_combined_initializer.py
index fca3253e..e8503a68 100644
--- a/tests/hi/test_hi_combined_initializer.py
+++ b/tests/hi/test_hi_combined_initializer.py
@@ -1,6 +1,6 @@
 import unittest
 from datetime import datetime
-from unittest.mock import patch, Mock, call
+from unittest.mock import Mock, call, patch
 
 from imap_data_access.file_validation import Version
 
@@ -41,9 +41,7 @@ def test_get_maps_that_should_be_produced_no_existing_combined_sp(self):
             descriptor = f"hic-ena-h-hf-sp-full-hae-{deg}-1yr"
 
             for input_major_version in [None, 2]:
-                expected_version_map = VersionMap(
-                    {descriptor: Version(input_major_version, 1)}
-                )
+                expected_version_map = VersionMap({descriptor: Version(input_major_version, 1)})
 
                 with self.subTest(deg=deg, major_version=input_major_version):
                     self.hi_combined_initializer_mock_query.side_effect = [
@@ -78,10 +76,8 @@ def test_get_maps_that_should_be_produced_no_existing_combined_sp(self):
                     ]
 
                     initializer = HiCombinedInitializer()
-                    actual_maps_to_produce = (
-                        initializer.get_maps_that_should_be_produced(
-                            descriptor, input_major_version
-                        )
+                    actual_maps_to_produce = initializer.get_maps_that_should_be_produced(
+                        descriptor, input_major_version
                     )
 
                     self.hi_combined_initializer_mock_query.assert_has_calls(
@@ -94,9 +90,7 @@ def test_get_maps_that_should_be_produced_no_existing_combined_sp(self):
                     self.assertEqual(expected_maps_to_produce, actual_maps_to_produce)
 
     @patch("imap_l3_processing.maps.map_initializer.read_cdf_parents")
-    def test_get_maps_that_should_be_produced_new_major_version(
-        self, mock_read_cdf_parents: Mock
-    ):
+    def test_get_maps_that_should_be_produced_new_major_version(self, mock_read_cdf_parents: Mock):
         mock_read_cdf_parents.return_value = {*l3_sp_input_maps}
 
         existing_file_without_major_number = (
@@ -318,11 +312,7 @@ def test_get_maps_that_should_be_produced_increments_versions_correctly(
                             start_date=datetime(2025, 1, 1),
                             end_date=datetime(2026, 1, 1),
                             version=VersionMap(
-                                {
-                                    descriptor: Version(
-                                        input_major_version, expected_minor_version
-                                    )
-                                }
+                                {descriptor: Version(input_major_version, expected_minor_version)}
                             ),
                             descriptor=descriptor,
                         ),
diff --git a/tests/hi/test_hi_processor.py b/tests/hi/test_hi_processor.py
index db14915c..b2ba4183 100644
--- a/tests/hi/test_hi_processor.py
+++ b/tests/hi/test_hi_processor.py
@@ -1,7 +1,7 @@
 import unittest
 from datetime import datetime, timedelta
 from pathlib import Path
-from unittest.mock import patch, call, sentinel, Mock
+from unittest.mock import Mock, call, patch, sentinel
 
 import numpy as np
 from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
@@ -16,8 +16,8 @@
     HiLoL3SurvivalDependencies,
 )
 from imap_l3_processing.maps.map_models import (
-    RectangularSpectralIndexDataProduct,
     RectangularIntensityDataProduct,
+    RectangularSpectralIndexDataProduct,
 )
 from imap_l3_processing.models import InputMetadata, Instrument
 from tests.maps.test_builders import create_rectangular_intensity_map_data
@@ -26,9 +26,7 @@
 
 class TestHiProcessor(unittest.TestCase):
     @patch("imap_l3_processing.hi.hi_processor.MapProcessor.get_parent_file_names")
-    @patch(
-        "imap_l3_processing.hi.hi_processor.HiSpectralIndexDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.hi.hi_processor.HiSpectralIndexDependencies.fetch_dependencies")
     @patch("imap_l3_processing.maps.spectral_fit.fit_arrays_to_power_law")
     @patch("imap_l3_processing.hi.hi_processor.save_data")
     def test_process_spectral_fit(
@@ -97,9 +95,7 @@ def test_process_spectral_fit(
 
         mock_save_data.assert_called_once()
         actual_hi_data_product = mock_save_data.call_args_list[0].args[0]
-        self.assertIsInstance(
-            actual_hi_data_product, RectangularSpectralIndexDataProduct
-        )
+        self.assertIsInstance(actual_hi_data_product, RectangularSpectralIndexDataProduct)
         self.assertEqual(input_metadata, actual_hi_data_product.input_metadata)
         actual_data = actual_hi_data_product.data
         spectral_index_data = actual_data.spectral_index_map_data
@@ -114,9 +110,7 @@ def test_process_spectral_fit(
         np.testing.assert_array_equal(
             spectral_index_data.energy_delta_plus, expected_energy_delta_plus
         )
-        np.testing.assert_array_equal(
-            spectral_index_data.ena_spectral_index, expected_index
-        )
+        np.testing.assert_array_equal(spectral_index_data.ena_spectral_index, expected_index)
         np.testing.assert_array_equal(
             spectral_index_data.ena_spectral_index_stat_uncert, expected_index_unc
         )
@@ -127,20 +121,12 @@ def test_process_spectral_fit(
             spectral_index_data.ena_spectral_index_scalar_coefficient_stat_uncert,
             expected_scalar_unc,
         )
-        np.testing.assert_array_equal(
-            spectral_index_data.ena_spectral_index_chisq, expected_chisq
-        )
+        np.testing.assert_array_equal(spectral_index_data.ena_spectral_index_chisq, expected_chisq)
         np.testing.assert_array_equal(spectral_index_data.energy, expected_energy)
-        np.testing.assert_array_equal(
-            spectral_index_data.latitude, intensity_data.latitude
-        )
-        np.testing.assert_array_equal(
-            spectral_index_data.longitude, intensity_data.longitude
-        )
+        np.testing.assert_array_equal(spectral_index_data.latitude, intensity_data.latitude)
+        np.testing.assert_array_equal(spectral_index_data.longitude, intensity_data.longitude)
         np.testing.assert_array_equal(spectral_index_data.epoch, intensity_data.epoch)
-        np.testing.assert_array_equal(
-            spectral_index_data.exposure_factor, expected_exposure
-        )
+        np.testing.assert_array_equal(spectral_index_data.exposure_factor, expected_exposure)
         self.assertEqual(["l2_or_l3_map"], actual_hi_data_product.parent_file_names)
         self.assertEqual(hi_l3_data.coords, spectral_index_coords)
         self.assertEqual(SpiceFrame.ECLIPJ2000, actual_hi_data_product.spice_frame_name)
@@ -218,9 +204,7 @@ def test_spectral_fit_against_validation_data(self):
                     atol=1e-3,
                 )
                 np.testing.assert_allclose(
-                    output_data.spectral_index_map_data.ena_spectral_index_stat_uncert[
-                        0, 0
-                    ],
+                    output_data.spectral_index_map_data.ena_spectral_index_stat_uncert[0, 0],
                     expected_gamma_sigma,
                     atol=1e-3,
                 )
@@ -301,9 +285,7 @@ def test_spectral_fit_other_fields_with_one_zero_exposure(self):
         intensity_data.obs_date_range[0, 0] = 1
         intensity_data.obs_date_range[0, 1] = 1
         intensity_data.obs_date_range[0, 2] = 3
-        intensity_data.obs_date_range.mask = np.ma.getmaskarray(
-            intensity_data.obs_date_range
-        )
+        intensity_data.obs_date_range.mask = np.ma.getmaskarray(intensity_data.obs_date_range)
         intensity_data.obs_date_range.mask[0, 1] = True
 
         processor = HiProcessor(sentinel.input_metadata, sentinel.dependencies)
@@ -339,9 +321,7 @@ def test_spectral_fit_other_fields_with_all_zero_exposure(self):
 
         intensity_data.exposure_factor[:] = 0.0
 
-        intensity_data.obs_date_range.mask = np.ma.getmaskarray(
-            intensity_data.obs_date_range
-        )
+        intensity_data.obs_date_range.mask = np.ma.getmaskarray(intensity_data.obs_date_range)
         intensity_data.obs_date_range.mask[:] = True
 
         processor = HiProcessor(sentinel.input_metadata, sentinel.dependencies)
@@ -364,9 +344,7 @@ def test_spectral_fit_other_fields_with_all_zero_exposure(self):
         )
 
     @patch("imap_l3_processing.hi.hi_processor.MapProcessor.get_parent_file_names")
-    @patch(
-        "imap_l3_processing.hi.hi_processor.HiLoL3SurvivalDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.hi.hi_processor.HiLoL3SurvivalDependencies.fetch_dependencies")
     @patch("imap_l3_processing.hi.hi_processor.process_survival_probabilities")
     @patch("imap_l3_processing.hi.hi_processor.save_data")
     def test_process_ram_or_antiram_spin(
@@ -408,9 +386,7 @@ def test_process_ram_or_antiram_spin(
                     Path("folder/l1c"),
                 ]
 
-                mock_process_survival_prob.return_value = (
-                    sentinel.survival_probabilities
-                )
+                mock_process_survival_prob.return_value = sentinel.survival_probabilities
 
                 processor = HiProcessor(sentinel.input_dependencies, input_metadata)
                 product = processor.process(spice_frame_name=spice_frame_name)
@@ -419,9 +395,7 @@ def test_process_ram_or_antiram_spin(
                     sentinel.input_dependencies, Instrument.IMAP_HI
                 )
 
-                mock_process_survival_prob.assert_called_once_with(
-                    dependencies, spice_frame_name
-                )
+                mock_process_survival_prob.assert_called_once_with(dependencies, spice_frame_name)
 
                 mock_save_data.assert_called_once_with(
                     RectangularIntensityDataProduct(
@@ -537,9 +511,7 @@ def test_process_cg_corrected_full_spin_map(
 
                 full_spin_dependencies: HiL3SingleSensorFullSpinDependencies = Mock()
                 full_spin_dependencies.dependency_file_paths = [
-                    Path(
-                        "folder/ram_map", Path("folder/antiram_map"), Path("folder/l1c")
-                    )
+                    Path("folder/ram_map", Path("folder/antiram_map"), Path("folder/l1c"))
                 ]
                 mock_fetch_dependencies.return_value = full_spin_dependencies
 
@@ -594,9 +566,7 @@ def test_process_cg_corrected_full_spin_map(
 
     @patch("imap_l3_processing.hi.hi_processor.MapProcessor.get_parent_file_names")
     @patch("imap_l3_processing.hi.hi_processor.save_data")
-    @patch(
-        "imap_l3_processing.hi.hi_processor.HiL3CombinedMapDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.hi.hi_processor.HiL3CombinedMapDependencies.fetch_dependencies")
     @patch("imap_l3_processing.hi.hi_processor.ExposureWeightedCombination")
     @patch("imap_l3_processing.hi.hi_processor.UncertaintyWeightedCombination")
     def test_process_combined_sensor_map(
@@ -608,9 +578,7 @@ def test_process_combined_sensor_map(
         mock_get_parent_file_names,
     ):
         mock_exposure_combination = Mock()
-        mock_exposure_weighted_combination_class.return_value = (
-            mock_exposure_combination
-        )
+        mock_exposure_weighted_combination_class.return_value = mock_exposure_combination
 
         mock_uncertainty_weighted_combination = Mock()
 
@@ -688,9 +656,7 @@ def test_raises_error_for_currently_unimplemented_maps(self):
                 with self.assertRaises(NotImplementedError):
                     _ = processor.process()
 
-    @patch(
-        "imap_l3_processing.hi.hi_processor.HiSpectralIndexDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.hi.hi_processor.HiSpectralIndexDependencies.fetch_dependencies")
     @patch("imap_l3_processing.hi.hi_processor.fit_spectral_index_map")
     @patch("imap_l3_processing.hi.hi_processor.slice_energy_range_by_bin")
     @patch("imap_l3_processing.hi.hi_processor.save_data")
@@ -719,6 +685,4 @@ def test_spectral_fit_with_energy_range(
         mock_slice_energy_range_by_bin.assert_called_with(
             dependencies.map_data.intensity_map_data, 10, 20
         )
-        mock_fit_spectral_index_map.assert_called_with(
-            mock_slice_energy_range_by_bin.return_value
-        )
+        mock_fit_spectral_index_map.assert_called_with(mock_slice_energy_range_by_bin.return_value)
diff --git a/tests/hi/test_hi_sp_initializer.py b/tests/hi/test_hi_sp_initializer.py
index 91fc8bdf..7018fabc 100644
--- a/tests/hi/test_hi_sp_initializer.py
+++ b/tests/hi/test_hi_sp_initializer.py
@@ -1,14 +1,14 @@
 import unittest
+from collections.abc import Callable
 from datetime import datetime
-from typing import Callable
-from unittest.mock import patch, call, Mock, sentinel
+from unittest.mock import Mock, call, patch, sentinel
 
 from imap_data_access.file_validation import Version
 
-from imap_l3_processing.hi.hi_sp_initializer import HiSPInitializer, HI_SP_SPICE_KERNELS
+from imap_l3_processing.hi.hi_sp_initializer import HI_SP_SPICE_KERNELS, HiSPInitializer
 from imap_l3_processing.maps.map_descriptors import (
-    parse_map_descriptor,
     map_descriptor_parts_to_string,
+    parse_map_descriptor,
 )
 from imap_l3_processing.maps.map_initializer import PossibleMapToProduce
 from imap_l3_processing.maps.sp_map_initializer import logger
@@ -61,9 +61,7 @@ def test_get_maps_that_can_be_produced_always_returns_possible_maps_with_default
                     create_mock_query_results([]),
                 ]
 
-                mock_read_cdf_parents.side_effect = self.create_fake_read_cdf_parents(
-                    "45"
-                )
+                mock_read_cdf_parents.side_effect = self.create_fake_read_cdf_parents("45")
 
                 expected_possible_maps = [
                     PossibleMapToProduce(
@@ -150,18 +148,10 @@ def test_get_maps_that_can_be_produced_always_returns_possible_maps_with_default
 
                 mock_read_cdf_parents.assert_has_calls(
                     [
-                        call(
-                            "imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20100101_v001.cdf"
-                        ),
-                        call(
-                            "imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20100401_v001.cdf"
-                        ),
-                        call(
-                            "imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20100701_v001.cdf"
-                        ),
-                        call(
-                            "imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20101001_v001.cdf"
-                        ),
+                        call("imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20100101_v001.cdf"),
+                        call("imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20100401_v001.cdf"),
+                        call("imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20100701_v001.cdf"),
+                        call("imap_hi_l2_h45-ena-h-sf-nsp-anti-hae-4deg-3mo_20101001_v001.cdf"),
                     ],
                     any_order=True,
                 )
@@ -169,9 +159,7 @@ def test_get_maps_that_can_be_produced_always_returns_possible_maps_with_default
                 self.assertEqual(expected_possible_maps, actual_possible_maps)
 
     @patch("imap_l3_processing.maps.map_initializer.read_cdf_parents")
-    def test_get_maps_that_can_be_produced_full_spin_descriptor(
-        self, mock_read_cdf_parents
-    ):
+    def test_get_maps_that_can_be_produced_full_spin_descriptor(self, mock_read_cdf_parents):
         self.mock_query.side_effect = [
             create_mock_query_results([]),
             create_mock_query_results(
@@ -427,9 +415,7 @@ def test_get_maps_that_should_be_produced(self, mock_read_cdf_parents):
             ]
         )
 
-        actual_possible_maps = initializer.get_maps_that_should_be_produced(
-            descriptor, None
-        )
+        actual_possible_maps = initializer.get_maps_that_should_be_produced(descriptor, None)
 
         mock_read_cdf_parents.assert_has_calls(
             [
@@ -475,9 +461,7 @@ def test_get_maps_that_should_be_produced_remakes_when_major_version_changes(
                     ),
                 ]
 
-                mock_read_cdf_parents.side_effect = self.create_fake_read_cdf_parents(
-                    "90"
-                )
+                mock_read_cdf_parents.side_effect = self.create_fake_read_cdf_parents("90")
 
                 descriptor = "h90-ena-h-sf-sp-anti-hae-4deg-3mo"
                 expected_possible_maps = [
@@ -529,12 +513,8 @@ def test_get_maps_that_should_be_produced_remakes_when_major_version_changes(
 
                 mock_read_cdf_parents.assert_has_calls(
                     [
-                        call(
-                            "imap_hi_l2_h90-ena-h-sf-nsp-anti-hae-4deg-3mo_20100101_v001.cdf"
-                        ),
-                        call(
-                            "imap_hi_l3_h90-ena-h-sf-sp-anti-hae-4deg-3mo_20100101_v001.cdf"
-                        ),
+                        call("imap_hi_l2_h90-ena-h-sf-nsp-anti-hae-4deg-3mo_20100101_v001.cdf"),
+                        call("imap_hi_l3_h90-ena-h-sf-sp-anti-hae-4deg-3mo_20100101_v001.cdf"),
                     ]
                 )
 
@@ -623,9 +603,7 @@ def mock_generate_input(path):
             input_files=files, input_metadata=Mock()
         ).processing_input_collection
 
-        mock_collection.assert_called_once_with(
-            sentinel.file1, sentinel.file2, sentinel.file3
-        )
+        mock_collection.assert_called_once_with(sentinel.file1, sentinel.file2, sentinel.file3)
 
         self.assertEqual(mock_collection.return_value, processing_input)
 
diff --git a/tests/hi/test_hi_spectral_fit_dependencies.py b/tests/hi/test_hi_spectral_fit_dependencies.py
index 38cb519f..d75094ab 100644
--- a/tests/hi/test_hi_spectral_fit_dependencies.py
+++ b/tests/hi/test_hi_spectral_fit_dependencies.py
@@ -1,20 +1,20 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, Mock
+from unittest.mock import Mock, patch
 
 import numpy as np
 from imap_data_access.processing_input import (
-    ScienceInput,
-    ProcessingInputCollection,
     AncillaryInput,
+    ProcessingInputCollection,
+    ScienceInput,
 )
 
 from imap_l3_processing.hi.hi_spectral_fit_dependencies import (
     HiSpectralIndexDependencies,
 )
 from imap_l3_processing.maps.map_models import (
-    RectangularIntensityMapData,
     IntensityMapData,
+    RectangularIntensityMapData,
 )
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 
@@ -33,9 +33,7 @@ def test_from_file_paths(self, mock_read_from_path):
         self.assertEqual(mock_read_from_path.call_count, 1)
         self.assertEqual(mock_read_from_path.return_value, result.map_data)
 
-    @patch(
-        "imap_l3_processing.hi.hi_spectral_fit_dependencies.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.hi.hi_spectral_fit_dependencies.imap_data_access.download")
     @patch(
         "imap_l3_processing.hi.hi_spectral_fit_dependencies.RectangularIntensityMapData.read_from_path"
     )
@@ -82,9 +80,7 @@ def _create_intensity_map_data(
 ):
     full_shape = (1, 1, 8, 15)
     return IntensityMapData(
-        ena_intensity=ena_intensity
-        if ena_intensity is not None
-        else np.full(full_shape, 1),
+        ena_intensity=ena_intensity if ena_intensity is not None else np.full(full_shape, 1),
         ena_intensity_stat_uncert=None,
         ena_intensity_sys_err=None,
         epoch=None,
diff --git a/tests/hi/test_utils.py b/tests/hi/test_utils.py
index ae4f8569..c7544302 100644
--- a/tests/hi/test_utils.py
+++ b/tests/hi/test_utils.py
@@ -2,22 +2,22 @@
 import unittest
 from datetime import datetime
 from pathlib import Path
-from unittest.mock import patch, call
+from unittest.mock import call, patch
 
 import numpy as np
 from spacepy import pycdf
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.glows.l3e.glows_l3e_hi_model import (
-    PROBABILITY_OF_SURVIVAL_VAR_NAME,
-    SPIN_ANGLE_VAR_NAME,
     ENERGY_VAR_NAME,
     EPOCH_CDF_VAR_NAME,
     GLOWS_FLAGS_VAR_NAME,
+    PROBABILITY_OF_SURVIVAL_VAR_NAME,
+    SPIN_ANGLE_VAR_NAME,
 )
 from imap_l3_processing.hi.utils import (
-    read_l1c_rectangular_pointing_set_data,
     read_glows_l3e_data,
+    read_l1c_rectangular_pointing_set_data,
 )
 from tests.test_helpers import get_test_data_folder, with_tempdir
 
@@ -43,7 +43,7 @@ def test_read_l1c_data(self):
                 epoch_delta = np.array([1_000_000_000])
                 repointing = 1111
                 exposure_times = rng.random((1, 9, 3600))
-                energy_step = rng.random((9))
+                energy_step = rng.random(9)
                 hae_longitude = np.ones(3600).reshape((1, 3600))
                 hae_latitude = np.ones(3600).reshape((1, 3600)) * 2
 
@@ -58,14 +58,10 @@ def test_read_l1c_data(self):
                     cdf[var].attrs["FILLVAL"] = 1000000
 
             for path in [pathname, Path(pathname)]:
-                with self.subTest(
-                    path=path, exposure_time_var_name=exposure_time_var_name
-                ):
+                with self.subTest(path=path, exposure_time_var_name=exposure_time_var_name):
                     result = read_l1c_rectangular_pointing_set_data(path)
                     self.assertEqual(epoch[0], result.epoch)
-                    np.testing.assert_array_equal(
-                        result.epoch_delta, epoch_delta, strict=True
-                    )
+                    np.testing.assert_array_equal(result.epoch_delta, epoch_delta, strict=True)
                     self.assertEqual(repointing, result.repointing)
                     self.assertEqual([43264184000000], result.epoch_j2000)
                     np.testing.assert_array_equal(exposure_times, result.exposure_times)
@@ -85,24 +81,16 @@ def test_read_hi_l1c_fill_values_create_nan_data(self):
 
         with CDF(str(path)) as cdf:
             self.assertEqual(cdf["epoch"][0], result.epoch)
-            np.testing.assert_array_equal(
-                result.epoch_delta, cdf["epoch_delta"], strict=True
-            )
+            np.testing.assert_array_equal(result.epoch_delta, cdf["epoch_delta"], strict=True)
             self.assertEqual(1, result.repointing)
-            np.testing.assert_array_equal(
-                result.esa_energy_step, cdf["esa_energy_step"]
-            )
+            np.testing.assert_array_equal(result.esa_energy_step, cdf["esa_energy_step"])
             np.testing.assert_array_equal(
                 result.exposure_times, np.full_like(cdf["exposure_times"], 0)
             )
 
     @patch("imap_l3_processing.hi.utils.met_to_ttj2000ns")
     def test_read_lo_l1c(self, mock_met_to_ttj2000ns):
-        path = (
-            get_test_data_folder()
-            / "lo"
-            / "imap_lo_l1c_pset_20260101-repoint01261_v001.cdf"
-        )
+        path = get_test_data_folder() / "lo" / "imap_lo_l1c_pset_20260101-repoint01261_v001.cdf"
 
         mock_met_to_ttj2000ns.side_effect = [np.array([3]), np.array([2])]
 
@@ -117,12 +105,8 @@ def test_read_lo_l1c(self, mock_met_to_ttj2000ns):
             self.assertEqual((1,), result.epoch_delta.shape)
             np.testing.assert_array_almost_equal(result.epoch_delta, [1])
             self.assertEqual(1261, result.repointing)
-            np.testing.assert_array_equal(
-                result.esa_energy_step, cdf["esa_energy_step"]
-            )
-            np.testing.assert_array_equal(
-                result.exposure_times, cdf["exposure_time"][...]
-            )
+            np.testing.assert_array_equal(result.esa_energy_step, cdf["esa_energy_step"])
+            np.testing.assert_array_equal(result.exposure_times, cdf["exposure_time"][...])
             self.assertEqual(cdf["pointing_start_met"][0], result.pointing_start_met)
             self.assertEqual(cdf["pointing_end_met"][0], result.pointing_end_met)
 
@@ -131,8 +115,7 @@ def test_read_glows_l3e_data(self, temp_dir: Path):
         rng = np.random.default_rng()
 
         pathname = str(
-            temp_dir
-            / "imap_glows_l3e_survival-probability-hi_20250415-repoint01000_v001.cdf"
+            temp_dir / "imap_glows_l3e_survival-probability-hi_20250415-repoint01000_v001.cdf"
         )
 
         with CDF(pathname, "") as cdf:
diff --git a/tests/hit/l3/hit_test_builders.py b/tests/hit/l3/hit_test_builders.py
index dc85ad0a..67ea4a04 100644
--- a/tests/hit/l3/hit_test_builders.py
+++ b/tests/hit/l3/hit_test_builders.py
@@ -1,7 +1,7 @@
 from imap_l3_processing.hit.l3.pha.pha_event_reader import (
-    RawPHAEvent,
-    PHAWord,
     Detector,
+    PHAWord,
+    RawPHAEvent,
 )
 
 
diff --git a/tests/hit/l3/pha/science/test_calculate_pha.py b/tests/hit/l3/pha/science/test_calculate_pha.py
index 18d85eca..c32f1a11 100644
--- a/tests/hit/l3/pha/science/test_calculate_pha.py
+++ b/tests/hit/l3/pha/science/test_calculate_pha.py
@@ -1,17 +1,17 @@
 import math
 import unittest
-from unittest.mock import patch, Mock, sentinel
+from unittest.mock import Mock, patch, sentinel
 
 import numpy as np
 
-from imap_l3_processing.hit.l3.pha.pha_event_reader import PHAWord, Detector
+from imap_l3_processing.hit.l3.pha.pha_event_reader import Detector, PHAWord
 from imap_l3_processing.hit.l3.pha.science.calculate_pha import (
     EventAnalysis,
+    EventOutput,
     analyze_event,
     calculate_mev,
-    process_pha_event,
-    EventOutput,
     compute_charge,
+    process_pha_event,
 )
 from imap_l3_processing.hit.l3.pha.science.cosine_correction_lookup_table import (
     DetectedRange,
@@ -57,23 +57,13 @@ def test_calculate_mev(self):
             adc_overflow=False,
         )
         mev = calculate_mev(low_gain_word, gain_lookup_table)
-        self.assertEqual(
-            high_gain_a_value * high_gain_adc_value + high_gain_b_value, mev
-        )
+        self.assertEqual(high_gain_a_value * high_gain_adc_value + high_gain_b_value, mev)
 
     def test_analyze_range(self):
-        detector_1_in_group_1 = Detector(
-            layer=1, side="A", segment="b", address=10, group="L1A14"
-        )
-        detector_2_in_group_1 = Detector(
-            layer=1, side="A", segment="c", address=11, group="L1A14"
-        )
-        detector_1_in_group_2 = Detector(
-            layer=2, side="A", segment="c", address=15, group="L2A"
-        )
-        detector_1_in_group_3 = Detector(
-            layer=3, side="A", segment="a", address=20, group="L3A"
-        )
+        detector_1_in_group_1 = Detector(layer=1, side="A", segment="b", address=10, group="L1A14")
+        detector_2_in_group_1 = Detector(layer=1, side="A", segment="c", address=11, group="L1A14")
+        detector_1_in_group_2 = Detector(layer=2, side="A", segment="c", address=15, group="L2A")
+        detector_1_in_group_3 = Detector(layer=3, side="A", segment="a", address=20, group="L3A")
 
         detector_to_pha_value = [
             (detector_1_in_group_1, 10),
@@ -116,15 +106,9 @@ def test_analyze_range(self):
         self.assertEqual(expected_event_analysis, event_analysis)
 
     def test_analyze_range_mixed_sides(self):
-        detector_2_in_L2A_group = Detector(
-            layer=2, side="A", segment="c", address=11, group="L2A"
-        )
-        detector_1_in_L2A_group = Detector(
-            layer=2, side="A", segment="b", address=10, group="L2A"
-        )
-        detector_1_in_L2B_group = Detector(
-            layer=2, side="B", segment="c", address=15, group="L2B"
-        )
+        detector_2_in_L2A_group = Detector(layer=2, side="A", segment="c", address=11, group="L2A")
+        detector_1_in_L2A_group = Detector(layer=2, side="A", segment="b", address=10, group="L2A")
+        detector_1_in_L2B_group = Detector(layer=2, side="B", segment="c", address=15, group="L2B")
         detector_1_in_L1B14_group = Detector(
             layer=1, side="B", segment="a", address=20, group="L1B14"
         )
@@ -180,24 +164,12 @@ def test_analyze_range_mixed_sides(self):
         self.assertEqual(expected_event_analysis, event_analysis)
 
     def test_analyze_range_with_range_4(self):
-        detector_1_in_group_1 = Detector(
-            layer=1, side="A", segment="b", address=10, group="L1A14"
-        )
-        detector_2_in_group_1 = Detector(
-            layer=1, side="A", segment="c", address=11, group="L1A14"
-        )
-        detector_1_in_group_2 = Detector(
-            layer=2, side="A", segment="c", address=15, group="L2A"
-        )
-        detector_1_in_group_3 = Detector(
-            layer=3, side="A", segment="a", address=20, group="L3A"
-        )
-        detector_1_in_group_4 = Detector(
-            layer=3, side="B", segment="a", address=21, group="L3B"
-        )
-        detector_1_in_group_5 = Detector(
-            layer=2, side="B", segment="a", address=22, group="L2B"
-        )
+        detector_1_in_group_1 = Detector(layer=1, side="A", segment="b", address=10, group="L1A14")
+        detector_2_in_group_1 = Detector(layer=1, side="A", segment="c", address=11, group="L1A14")
+        detector_1_in_group_2 = Detector(layer=2, side="A", segment="c", address=15, group="L2A")
+        detector_1_in_group_3 = Detector(layer=3, side="A", segment="a", address=20, group="L3A")
+        detector_1_in_group_4 = Detector(layer=3, side="B", segment="a", address=21, group="L3B")
+        detector_1_in_group_5 = Detector(layer=2, side="B", segment="a", address=22, group="L2B")
 
         detector_to_pha_value = [
             (detector_1_in_group_1, 10),
@@ -224,9 +196,7 @@ def test_analyze_range_with_range_4(self):
 
         event_analysis = analyze_event(raw_pha_event, range_lookup_table)
 
-        range_lookup_table.lookup_range.assert_called_with(
-            {"L1A14", "L2A", "L3A", "L3B", "L2B"}
-        )
+        range_lookup_table.lookup_range.assert_called_with({"L1A14", "L2A", "L3A", "L3B", "L2B"})
 
         expected_highest_words = [
             detector_to_word_tuples[str(detector_2_in_group_1)],
@@ -248,15 +218,9 @@ def test_analyze_range_with_range_4(self):
 
     def test_analyze_event_uses_detectors_with_highest_adc_values(self):
 
-        detector_l1ab = Detector(
-            layer=1, side="A", segment="b", address=10, group="L1A14"
-        )
-        detector_l1ac = Detector(
-            layer=1, side="A", segment="c", address=11, group="L1A14"
-        )
-        detector_l2ac = Detector(
-            layer=2, side="A", segment="c", address=15, group="L2A"
-        )
+        detector_l1ab = Detector(layer=1, side="A", segment="b", address=10, group="L1A14")
+        detector_l1ac = Detector(layer=1, side="A", segment="c", address=11, group="L1A14")
+        detector_l2ac = Detector(layer=2, side="A", segment="c", address=15, group="L2A")
 
         word_l1ab = PHAWord(
             adc_value=1,
@@ -343,9 +307,7 @@ def test_analyze_event_uses_detectors_with_highest_adc_values(self):
                 word_l1ac.adc_value = l1ac_adc
                 word_l1ac.is_low_gain = l1ac_is_low_gain
 
-                raw_pha_event = create_raw_pha_event(
-                    pha_words=[word_l1ab, word_l1ac, word_l2ac]
-                )
+                raw_pha_event = create_raw_pha_event(pha_words=[word_l1ab, word_l1ac, word_l2ac])
 
                 rule_stub = Rule(
                     range=DetectedRange(DetectorRange.R2, DetectorSide.A),
@@ -367,33 +329,19 @@ def test_analyze_event_uses_detectors_with_highest_adc_values(self):
                 )
 
                 self.assertEqual(expected_event_analysis.range, event_analysis.range)
-                self.assertEqual(
-                    expected_event_analysis.l1_detector, event_analysis.l1_detector
-                )
-                self.assertEqual(
-                    expected_event_analysis.l2_detector, event_analysis.l2_detector
-                )
-                self.assertEqual(
-                    expected_event_analysis.e_delta_word, event_analysis.e_delta_word
-                )
-                self.assertEqual(
-                    expected_event_analysis.e_prime_word, event_analysis.e_prime_word
-                )
+                self.assertEqual(expected_event_analysis.l1_detector, event_analysis.l1_detector)
+                self.assertEqual(expected_event_analysis.l2_detector, event_analysis.l2_detector)
+                self.assertEqual(expected_event_analysis.e_delta_word, event_analysis.e_delta_word)
+                self.assertEqual(expected_event_analysis.e_prime_word, event_analysis.e_prime_word)
                 self.assertEqual(
                     expected_event_analysis.words_with_highest_energy,
                     event_analysis.words_with_highest_energy,
                 )
 
     def test_analyze_event_filters_out_events_with_all_saturated_data(self):
-        detector_l1ab = Detector(
-            layer=1, side="A", segment="b", address=10, group="L1A14"
-        )
-        detector_l1ac = Detector(
-            layer=1, side="A", segment="c", address=11, group="L1A14"
-        )
-        detector_l2ac = Detector(
-            layer=2, side="A", segment="c", address=15, group="L2A"
-        )
+        detector_l1ab = Detector(layer=1, side="A", segment="b", address=10, group="L1A14")
+        detector_l1ac = Detector(layer=1, side="A", segment="c", address=11, group="L1A14")
+        detector_l2ac = Detector(layer=2, side="A", segment="c", address=15, group="L2A")
 
         word_l1ab = PHAWord(
             adc_value=2047,
@@ -417,9 +365,7 @@ def test_analyze_event_filters_out_events_with_all_saturated_data(self):
             is_last_pha=False,
         )
 
-        raw_pha_event = create_raw_pha_event(
-            pha_words=[word_l1ab, word_l1ac, word_l2ac]
-        )
+        raw_pha_event = create_raw_pha_event(pha_words=[word_l1ab, word_l1ac, word_l2ac])
 
         rule_stub = Rule(
             range=DetectedRange(DetectorRange.R2, DetectorSide.A),
@@ -434,18 +380,10 @@ def test_analyze_event_filters_out_events_with_all_saturated_data(self):
         self.assertIsNone(event_analysis)
 
     def test_analyze_event_handles_no_calc_rules(self):
-        detector_1_in_group_1 = Detector(
-            layer=1, side="A", segment="b", address=10, group="L1A14"
-        )
-        detector_2_in_group_1 = Detector(
-            layer=1, side="A", segment="c", address=11, group="L1A14"
-        )
-        detector_1_in_group_2 = Detector(
-            layer=2, side="A", segment="c", address=15, group="L2A"
-        )
-        detector_1_in_group_3 = Detector(
-            layer=3, side="A", segment="a", address=20, group="L3A"
-        )
+        detector_1_in_group_1 = Detector(layer=1, side="A", segment="b", address=10, group="L1A14")
+        detector_2_in_group_1 = Detector(layer=1, side="A", segment="c", address=11, group="L1A14")
+        detector_1_in_group_2 = Detector(layer=2, side="A", segment="c", address=15, group="L2A")
+        detector_1_in_group_3 = Detector(layer=3, side="A", segment="a", address=20, group="L3A")
 
         detector_to_pha_value = [
             (detector_1_in_group_1, 10),
@@ -569,9 +507,7 @@ def test_process_pha_event(self, mock_analyze_event, mock_compute_charge):
         cosine_correction = 12.2
 
         mock_cosine_correction_table = Mock()
-        mock_cosine_correction_table.get_cosine_correction.return_value = (
-            cosine_correction
-        )
+        mock_cosine_correction_table.get_cosine_correction.return_value = cosine_correction
 
         event_output = process_pha_event(
             raw_pha_event,
@@ -595,17 +531,13 @@ def test_process_pha_event(self, mock_analyze_event, mock_compute_charge):
         expected_l2_higher_energy = cosine_correction * (
             word2_gain.a * pha_word2_adc_value + word2_gain.b
         )
-        expected_energy3 = cosine_correction * (
-            word3_gain.a * pha_word3_adc_value + word3_gain.b
-        )
+        expected_energy3 = cosine_correction * (word3_gain.a * pha_word3_adc_value + word3_gain.b)
         self.assertEqual(
             [expected_l1_energy, expected_l2_higher_energy, expected_energy3],
             event_output.energies,
         )
 
-        self.assertEqual(
-            expected_l1_energy + expected_l2_higher_energy, event_output.total_energy
-        )
+        self.assertEqual(expected_l1_energy + expected_l2_higher_energy, event_output.total_energy)
         self.assertEqual(raw_pha_event, event_output.original_event)
 
         mock_compute_charge.assert_called_once_with(
@@ -638,9 +570,7 @@ def test_compute_charge(self):
                     delta_e_losses,
                 )
 
-                detected_range = DetectedRange(
-                    range=DetectorRange.R2, side=DetectorSide.A
-                )
+                detected_range = DetectedRange(range=DetectorRange.R2, side=DetectorSide.A)
                 e_prime = 200
                 charge = compute_charge(
                     detected_range, delta_e, e_prime, mock_double_power_law_fit_params
@@ -720,7 +650,7 @@ def test_compute_charge_returns_nan_if_e_prime_or_delta_e_are_outside_of_range(
                 self.assertEqual(expected_nan, np.isnan(result))
 
     def _create_detector_from_string(
-        self, detector_string: str, detector_group: str = None
+        self, detector_string: str, detector_group: str | None = None
     ):
         layer = int(detector_string[1])
         group = detector_group if detector_group is not None else "L1A4c"
@@ -734,12 +664,10 @@ def _create_detector_from_string(
         )
 
     def _create_event_from_detectors_and_groups(
-        self, detectors: list[str], groups: list[str] = None
+        self, detectors: list[str], groups: list[str] | None = None
     ):
         if groups and len(detectors) != len(groups):
-            self.assertTrue(
-                False, msg="Detectors and groups must have the same length in setup"
-            )
+            self.assertTrue(False, msg="Detectors and groups must have the same length in setup")
 
         detector_objects = [
             self._create_detector_from_string(d, g) for d, g in zip(detectors, groups)
diff --git a/tests/hit/l3/pha/science/test_cosine_correction_lookup_table.py b/tests/hit/l3/pha/science/test_cosine_correction_lookup_table.py
index a5be36ac..878f3287 100644
--- a/tests/hit/l3/pha/science/test_cosine_correction_lookup_table.py
+++ b/tests/hit/l3/pha/science/test_cosine_correction_lookup_table.py
@@ -2,10 +2,10 @@
 
 from imap_l3_processing.hit.l3.pha.science.cosine_correction_lookup_table import (
     CosineCorrectionLookupTable,
-    Detector,
     DetectedRange,
-    DetectorSide,
+    Detector,
     DetectorRange,
+    DetectorSide,
 )
 from tests.test_helpers import get_test_data_path
 
@@ -13,24 +13,12 @@
 class TestCosineCorrectionLookupTable(unittest.TestCase):
     def test_can_create_from_file(self):
         lookup_table = CosineCorrectionLookupTable(
-            get_test_data_path(
-                "hit/pha_events/imap_hit_range-2A-cosine-lookup_20250203_v000.csv"
-            ),
-            get_test_data_path(
-                "hit/pha_events/imap_hit_range-3A-cosine-lookup_20250203_v000.csv"
-            ),
-            get_test_data_path(
-                "hit/pha_events/imap_hit_range-4A-cosine-lookup_20250203_v000.csv"
-            ),
-            get_test_data_path(
-                "hit/pha_events/imap_hit_range-2B-cosine-lookup_20250203_v000.csv"
-            ),
-            get_test_data_path(
-                "hit/pha_events/imap_hit_range-3B-cosine-lookup_20250203_v000.csv"
-            ),
-            get_test_data_path(
-                "hit/pha_events/imap_hit_range-4B-cosine-lookup_20250203_v000.csv"
-            ),
+            get_test_data_path("hit/pha_events/imap_hit_range-2A-cosine-lookup_20250203_v000.csv"),
+            get_test_data_path("hit/pha_events/imap_hit_range-3A-cosine-lookup_20250203_v000.csv"),
+            get_test_data_path("hit/pha_events/imap_hit_range-4A-cosine-lookup_20250203_v000.csv"),
+            get_test_data_path("hit/pha_events/imap_hit_range-2B-cosine-lookup_20250203_v000.csv"),
+            get_test_data_path("hit/pha_events/imap_hit_range-3B-cosine-lookup_20250203_v000.csv"),
+            get_test_data_path("hit/pha_events/imap_hit_range-4B-cosine-lookup_20250203_v000.csv"),
         )
 
         self.assertEqual(150, len(lookup_table._range2A_corrections))
@@ -41,19 +29,11 @@ def test_can_create_from_file(self):
         self.assertEqual(150, len(lookup_table._range3B_corrections))
         self.assertEqual(150, len(lookup_table._range4B_corrections))
 
-        L1A0b_detector = Detector(
-            layer=1, side="A", segment="0b", address=1234, group="L1A"
-        )
-        L2A0_detector = Detector(
-            layer=2, side="A", segment="0", address=5678, group="L2A"
-        )
+        L1A0b_detector = Detector(layer=1, side="A", segment="0b", address=1234, group="L1A")
+        L2A0_detector = Detector(layer=2, side="A", segment="0", address=5678, group="L2A")
 
-        L1B0b_detector = Detector(
-            layer=1, side="B", segment="0b", address=1234, group="L1A"
-        )
-        L2B0_detector = Detector(
-            layer=2, side="B", segment="0", address=5678, group="L2A"
-        )
+        L1B0b_detector = Detector(layer=1, side="B", segment="0b", address=1234, group="L1A")
+        L2B0_detector = Detector(layer=2, side="B", segment="0", address=5678, group="L2A")
 
         self.assertEqual(
             0.978643,
diff --git a/tests/hit/l3/pha/science/test_gain_lookup_table.py b/tests/hit/l3/pha/science/test_gain_lookup_table.py
index bc5ca289..99afb90e 100644
--- a/tests/hit/l3/pha/science/test_gain_lookup_table.py
+++ b/tests/hit/l3/pha/science/test_gain_lookup_table.py
@@ -1,8 +1,8 @@
 import unittest
 
 from imap_l3_processing.hit.l3.pha.science.gain_lookup_table import (
-    GainLookupTable,
     DetectorGain,
+    GainLookupTable,
 )
 from tests.test_helpers import get_test_data_path
 
diff --git a/tests/hit/l3/pha/science/test_hit_event_type_lookup.py b/tests/hit/l3/pha/science/test_hit_event_type_lookup.py
index abade951..c9fcd5cc 100644
--- a/tests/hit/l3/pha/science/test_hit_event_type_lookup.py
+++ b/tests/hit/l3/pha/science/test_hit_event_type_lookup.py
@@ -23,7 +23,7 @@ def tearDown(self):
     def test_hit_event_type_lookup_from_csv(self):
         with open(self.fake_lookup_path, "w") as csvfile:
             csvfile.write(
-                "\n".join(
+                "\n".join(  # noqa: FLY002
                     [
                         "L1A4,L1B14,L2A,L3A,L2B,L40B,L4B14,Range",
                         "1,0,1,0,0,0,0,2A",
@@ -44,9 +44,7 @@ def test_hit_event_type_lookup_from_csv(self):
 
         test_cases = [
             (
-                Rule(
-                    Range2A, ["L1A4", "L2A"], ["L1B14", "L3A", "L2B", "L40B", "L4B14"]
-                ),
+                Rule(Range2A, ["L1A4", "L2A"], ["L1B14", "L3A", "L2B", "L40B", "L4B14"]),
                 {"L1A4", "L2A"},
             ),
             (
diff --git a/tests/hit/l3/pha/science/test_range_fit_lookup.py b/tests/hit/l3/pha/science/test_range_fit_lookup.py
index 35d2d786..8639df56 100644
--- a/tests/hit/l3/pha/science/test_range_fit_lookup.py
+++ b/tests/hit/l3/pha/science/test_range_fit_lookup.py
@@ -7,12 +7,12 @@
 
 from imap_l3_processing.hit.l3.pha.science.cosine_correction_lookup_table import (
     DetectedRange,
-    DetectorSide,
     DetectorRange,
+    DetectorSide,
 )
 from imap_l3_processing.hit.l3.pha.science.range_fit_lookup import (
-    double_power_law,
     RangeFitLookup,
+    double_power_law,
 )
 from tests.test_helpers import get_test_data_path
 
@@ -42,64 +42,61 @@ def test_loads_csv_into_array(self):
             (DetectedRange(DetectorRange.R4, DetectorSide.B), "range4B.csv"),
         ]
         for range, file_to_populate in test_cases:
-            with self.subTest(range):
-                with tempfile.TemporaryDirectory() as tempdir:
-                    range2A_path = os.path.join(tempdir, "range2A.csv")
-                    range3A_path = os.path.join(tempdir, "range3A.csv")
-                    range4A_path = os.path.join(tempdir, "range4A.csv")
-                    range2B_path = os.path.join(tempdir, "range2B.csv")
-                    range3B_path = os.path.join(tempdir, "range3B.csv")
-                    range4B_path = os.path.join(tempdir, "range4B.csv")
+            with self.subTest(range), tempfile.TemporaryDirectory() as tempdir:
+                range2A_path = os.path.join(tempdir, "range2A.csv")
+                range3A_path = os.path.join(tempdir, "range3A.csv")
+                range4A_path = os.path.join(tempdir, "range4A.csv")
+                range2B_path = os.path.join(tempdir, "range2B.csv")
+                range3B_path = os.path.join(tempdir, "range3B.csv")
+                range4B_path = os.path.join(tempdir, "range4B.csv")
 
-                    expected_charges = [12, 13]
-                    charge1_parameters = [1, 2, 3, 4, 5]
-                    charge2_parameters = [4, 5, 6, 7, 8]
+                expected_charges = [12, 13]
+                charge1_parameters = [1, 2, 3, 4, 5]
+                charge2_parameters = [4, 5, 6, 7, 8]
 
-                    for path in [
-                        range2A_path,
-                        range3A_path,
-                        range4A_path,
-                        range2B_path,
-                        range3B_path,
-                        range4B_path,
-                    ]:
-                        with open(path, "w") as f:
-                            csv_writer = csv.writer(f)
-                            csv_writer.writerow([0, 0, 0, 0, 0, 0])
+                for path in [
+                    range2A_path,
+                    range3A_path,
+                    range4A_path,
+                    range2B_path,
+                    range3B_path,
+                    range4B_path,
+                ]:
+                    with open(path, "w") as f:
+                        csv_writer = csv.writer(f)
+                        csv_writer.writerow([0, 0, 0, 0, 0, 0])
 
-                    path_to_populate = os.path.join(tempdir, file_to_populate)
-                    with open(path_to_populate, "w") as range_file:
-                        range_file.write("""#
+                path_to_populate = os.path.join(tempdir, file_to_populate)
+                with open(path_to_populate, "w") as range_file:
+                    range_file.write("""#
 # Format: ion_charge, a1, b1, a2, b2, gamma
 #
 """)
-                        csv_writer = csv.writer(range_file)
-                        csv_writer.writerow(expected_charges[0:1] + charge1_parameters)
-                        csv_writer.writerow(expected_charges[1:2] + charge2_parameters)
+                    csv_writer = csv.writer(range_file)
+                    csv_writer.writerow(expected_charges[0:1] + charge1_parameters)
+                    csv_writer.writerow(expected_charges[1:2] + charge2_parameters)
 
-                    lookup_table = RangeFitLookup.from_files(
-                        range2A_file=range2A_path,
-                        range3A_file=range3A_path,
-                        range4A_file=range4A_path,
-                        range2B_file=range2B_path,
-                        range3B_file=range3B_path,
-                        range4B_file=range4B_path,
-                    )
+                lookup_table = RangeFitLookup.from_files(
+                    range2A_file=range2A_path,
+                    range3A_file=range3A_path,
+                    range4A_file=range4A_path,
+                    range2B_file=range2B_path,
+                    range3B_file=range3B_path,
+                    range4B_file=range4B_path,
+                )
 
-                    e_prime = 11.2
+                e_prime = 11.2
 
-                    charges, delta_e_loss = lookup_table.evaluate_e_prime(
-                        range, e_prime
-                    )
+                charges, delta_e_loss = lookup_table.evaluate_e_prime(range, e_prime)
 
-                    np.testing.assert_equal(charges, expected_charges)
-                    np.testing.assert_allclose(
-                        [
-                            double_power_law(e_prime, *charge1_parameters),
-                            double_power_law(e_prime, *charge2_parameters),
-                        ],
-                        delta_e_loss,
-                    )
+                np.testing.assert_equal(charges, expected_charges)
+                np.testing.assert_allclose(
+                    [
+                        double_power_law(e_prime, *charge1_parameters),
+                        double_power_law(e_prime, *charge2_parameters),
+                    ],
+                    delta_e_loss,
+                )
 
     def test_load_from_real_example_files(self):
         range_fit_lookup = RangeFitLookup.from_files(
diff --git a/tests/hit/l3/pha/test_l3_pha_dependencies.py b/tests/hit/l3/pha/test_l3_pha_dependencies.py
index 6e3a02c3..59debfec 100644
--- a/tests/hit/l3/pha/test_l3_pha_dependencies.py
+++ b/tests/hit/l3/pha/test_l3_pha_dependencies.py
@@ -1,51 +1,41 @@
 import unittest
-from unittest.mock import patch, call, sentinel
+from unittest.mock import call, patch, sentinel
 
 import imap_data_access
 from imap_data_access.processing_input import (
+    AncillaryInput,
     ProcessingInputCollection,
     ScienceInput,
-    AncillaryInput,
 )
 
 from imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies import (
-    HitL3PhaDependencies,
     HIT_L1A_EVENT_DESCRIPTOR,
-    HIT_L3_LO_GAIN_LOOKUP_DESCRIPTOR,
-    HIT_L3_HI_GAIN_LOOKUP_DESCRIPTOR,
     HIT_L3_EVENT_TYPE_LOOKUP_DESCRIPTOR,
+    HIT_L3_HI_GAIN_LOOKUP_DESCRIPTOR,
+    HIT_L3_LO_GAIN_LOOKUP_DESCRIPTOR,
+    HIT_L3_RANGE_2A_CHARGE_FIT_LOOKUP_DESCRIPTOR,
     HIT_L3_RANGE_2A_COSINE_LOOKUP_DESCRIPTOR,
-    HIT_L3_RANGE_3A_COSINE_LOOKUP_DESCRIPTOR,
-    HIT_L3_RANGE_4A_COSINE_LOOKUP_DESCRIPTOR,
+    HIT_L3_RANGE_2B_CHARGE_FIT_LOOKUP_DESCRIPTOR,
     HIT_L3_RANGE_2B_COSINE_LOOKUP_DESCRIPTOR,
-    HIT_L3_RANGE_3B_COSINE_LOOKUP_DESCRIPTOR,
-    HIT_L3_RANGE_4B_COSINE_LOOKUP_DESCRIPTOR,
-    HIT_L3_RANGE_2A_CHARGE_FIT_LOOKUP_DESCRIPTOR,
     HIT_L3_RANGE_3A_CHARGE_FIT_LOOKUP_DESCRIPTOR,
-    HIT_L3_RANGE_4A_CHARGE_FIT_LOOKUP_DESCRIPTOR,
-    HIT_L3_RANGE_2B_CHARGE_FIT_LOOKUP_DESCRIPTOR,
+    HIT_L3_RANGE_3A_COSINE_LOOKUP_DESCRIPTOR,
     HIT_L3_RANGE_3B_CHARGE_FIT_LOOKUP_DESCRIPTOR,
+    HIT_L3_RANGE_3B_COSINE_LOOKUP_DESCRIPTOR,
+    HIT_L3_RANGE_4A_CHARGE_FIT_LOOKUP_DESCRIPTOR,
+    HIT_L3_RANGE_4A_COSINE_LOOKUP_DESCRIPTOR,
     HIT_L3_RANGE_4B_CHARGE_FIT_LOOKUP_DESCRIPTOR,
+    HIT_L3_RANGE_4B_COSINE_LOOKUP_DESCRIPTOR,
+    HitL3PhaDependencies,
 )
 
 
 class TestHitL3PhaDependencies(unittest.TestCase):
     @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.download")
-    @patch(
-        "imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.HitL1Data.read_from_cdf"
-    )
-    @patch(
-        "imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.CosineCorrectionLookupTable"
-    )
-    @patch(
-        "imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.GainLookupTable.from_file"
-    )
-    @patch(
-        "imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.RangeFitLookup.from_files"
-    )
-    @patch(
-        "imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.HitEventTypeLookup.from_csv"
-    )
+    @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.HitL1Data.read_from_cdf")
+    @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.CosineCorrectionLookupTable")
+    @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.GainLookupTable.from_file")
+    @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.RangeFitLookup.from_files")
+    @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.HitEventTypeLookup.from_csv")
     def test_fetch_dependencies(
         self,
         mock_hit_event_type_from_lookup,
@@ -106,16 +96,10 @@ def test_fetch_dependencies(
         science_input = ScienceInput(science_l1a_event_path)
         input_collection.add([science_input, *ancillary_input_file_paths])
 
-        hit_l3_pha_dependencies = HitL3PhaDependencies.fetch_dependencies(
-            input_collection
-        )
+        hit_l3_pha_dependencies = HitL3PhaDependencies.fetch_dependencies(input_collection)
 
-        science_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "hit" / "l2" / "2010" / "01"
-        )
-        ancillary_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "hit"
-        )
+        science_dir = imap_data_access.config["DATA_DIR"] / "imap" / "hit" / "l2" / "2010" / "01"
+        ancillary_dir = imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "hit"
         expected_file_paths = [ancillary_dir / path for path in file_paths]
 
         mock_download.assert_has_calls(
@@ -147,13 +131,9 @@ def test_fetch_dependencies(
             sentinel.range_4B_charge_fit_lookup_cdf_path,
         )
 
-        mock_hit_event_type_from_lookup.assert_called_once_with(
-            sentinel.event_type_lookup_path
-        )
+        mock_hit_event_type_from_lookup.assert_called_once_with(sentinel.event_type_lookup_path)
 
-        self.assertEqual(
-            mock_read_from_cdf.return_value, hit_l3_pha_dependencies.hit_l1_data
-        )
+        self.assertEqual(mock_read_from_cdf.return_value, hit_l3_pha_dependencies.hit_l1_data)
         self.assertEqual(
             mock_cosine_correction_lookup_from_file.return_value,
             hit_l3_pha_dependencies.cosine_correction_lookup,
@@ -171,14 +151,10 @@ def test_fetch_dependencies(
         )
 
     @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.download")
-    @patch(
-        "imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.HitL1Data.read_from_cdf"
-    )
+    @patch("imap_l3_processing.hit.l3.pha.hit_l3_pha_dependencies.HitL1Data.read_from_cdf")
     def test_fetch_dependencies_throws_when_no_data_dependency_provided(
         self, mock_read_from_cdf, mock_download_dependency
     ):
         with self.assertRaises(ValueError) as e:
             _ = HitL3PhaDependencies.fetch_dependencies(ProcessingInputCollection())
-        self.assertEqual(
-            str(e.exception), f"Missing {HIT_L1A_EVENT_DESCRIPTOR} dependency."
-        )
+        self.assertEqual(str(e.exception), f"Missing {HIT_L1A_EVENT_DESCRIPTOR} dependency.")
diff --git a/tests/hit/l3/pha/test_pha_event_reader.py b/tests/hit/l3/pha/test_pha_event_reader.py
index 2c006658..630c533e 100644
--- a/tests/hit/l3/pha/test_pha_event_reader.py
+++ b/tests/hit/l3/pha/test_pha_event_reader.py
@@ -5,14 +5,16 @@
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.hit.l3.pha.pha_event_reader import (
+    Detector,
     PHAEventReader,
-    RawPHAEvent,
     PHAWord,
-    Detector,
+    RawPHAEvent,
 )
 from tests.hit.l3.hit_test_builders import create_raw_pha_event
 from tests.test_helpers import get_test_data_path
 
+# ruff: noqa: FLY002
+
 
 class TestPHAEventReader(unittest.TestCase):
     def test_can_create_detector_from_address(self):
@@ -35,9 +37,7 @@ def test_can_create_detector_from_address(self):
             (
                 10,
                 "L4AUnknown_10",
-                Detector(
-                    layer=4, side="A", segment="UNKNOWN_10", address=10, group="Unknown"
-                ),
+                Detector(layer=4, side="A", segment="UNKNOWN_10", address=10, group="Unknown"),
             ),
         ]
 
@@ -145,17 +145,13 @@ def test_read_l1_pha_data(self):
         self.assertEqual(2, len(event_data.pha_words))
         self.assertEqual(pha1_adc_value, event_data.pha_words[0].adc_value)
         self.assertEqual(pha1_adc_overflow, event_data.pha_words[0].adc_overflow)
-        self.assertEqual(
-            pha1_adc_detector_address, event_data.pha_words[0].detector.address
-        )
+        self.assertEqual(pha1_adc_detector_address, event_data.pha_words[0].detector.address)
         self.assertEqual(pha1_is_low_gain, event_data.pha_words[0].is_low_gain)
         self.assertEqual(pha1_is_last_event, event_data.pha_words[0].is_last_pha)
 
         self.assertEqual(pha2_adc_value, event_data.pha_words[1].adc_value)
         self.assertEqual(pha2_adc_overflow, event_data.pha_words[1].adc_overflow)
-        self.assertEqual(
-            pha2_adc_detector_address, event_data.pha_words[1].detector.address
-        )
+        self.assertEqual(pha2_adc_detector_address, event_data.pha_words[1].detector.address)
         self.assertEqual(pha2_is_low_gain, event_data.pha_words[1].is_low_gain)
         self.assertEqual(pha2_is_last_event, event_data.pha_words[1].is_last_pha)
 
@@ -181,15 +177,9 @@ def test_reads_extended_header_section_when_long_event_flag_set(self):
         event_data = PHAEventReader.read_pha_event(bitstream)
 
         self.assertIsNone(event_data.extended_stim_header)
-        self.assertEqual(
-            expected_detector_flags, event_data.extended_header.detector_flags
-        )
-        self.assertEqual(
-            expected_delta_e_index, event_data.extended_header.delta_e_index
-        )
-        self.assertEqual(
-            expected_e_prime_index, event_data.extended_header.e_prime_index
-        )
+        self.assertEqual(expected_detector_flags, event_data.extended_header.detector_flags)
+        self.assertEqual(expected_delta_e_index, event_data.extended_header.delta_e_index)
+        self.assertEqual(expected_e_prime_index, event_data.extended_header.e_prime_index)
 
     def test_reads_extended_stim_header_section_when_long_event_and_stim_flag_set(self):
         header_binary = self._create_pha_header(stim_tag=True, long_event_flag=True)
@@ -252,9 +242,7 @@ def test_reads_stim_block_when_stim_flag_set(self):
 
         pha_word1 = self._create_pha_data(is_last_event=False)
         pha_word2 = self._create_pha_data(is_last_event=True)
-        bitstream = BitStream(
-            "0b" + header_binary + stim_block_binary + pha_word1 + pha_word2
-        )
+        bitstream = BitStream("0b" + header_binary + stim_block_binary + pha_word1 + pha_word2)
         event_data = PHAEventReader.read_pha_event(bitstream)
 
         self.assertIsNone(event_data.extended_header)
@@ -307,11 +295,7 @@ def test_read_events_adds_extra_bits_for_odd_length_pha_words(self):
 
     def test_reads_pha_events_from_cdf(self):
         cdf = CDF(
-            str(
-                get_test_data_path(
-                    "hit/pha_events/imap_hit_l1a_direct-events_20100105_v009.cdf"
-                )
-            )
+            str(get_test_data_path("hit/pha_events/imap_hit_l1a_direct-events_20100105_v009.cdf"))
         )
 
         event_total = 0
@@ -339,16 +323,14 @@ def test_verify_against_HIT_script_output(self):
                         continue
                     if not pha_word.is_low_gain:
                         index = pha_word.detector.address
-                        row[index] = "{: 6}".format(pha_word.adc_value)
+                        row[index] = f"{pha_word.adc_value: 6}"
                     else:
                         index = pha_word.detector.address + 64
-                        row[index] = "{: 6}".format(pha_word.adc_value)
+                        row[index] = f"{pha_word.adc_value: 6}"
                 self.assertEqual(expected_row[2:], row)
 
     def _create_pha_event_binary(self, pha_event: RawPHAEvent) -> str:
-        binary_string = ""
-
-        binary_string += self._create_pha_header(
+        binary_string = self._create_pha_header(
             particle_id=pha_event.particle_id,
             buf_priority_num=pha_event.priority_buffer_num,
             stim_tag=pha_event.stim_tag,
@@ -364,15 +346,9 @@ def _create_pha_event_binary(self, pha_event: RawPHAEvent) -> str:
         if pha_event.extended_header is not None:
             binary_string += "".join(
                 [
-                    BitArray(
-                        uint=pha_event.extended_header.e_prime_index, length=8
-                    ).bin,
-                    BitArray(
-                        uint=pha_event.extended_header.delta_e_index, length=8
-                    ).bin,
-                    BitArray(
-                        uint=pha_event.extended_header.detector_flags, length=8
-                    ).bin,
+                    BitArray(uint=pha_event.extended_header.e_prime_index, length=8).bin,
+                    BitArray(uint=pha_event.extended_header.delta_e_index, length=8).bin,
+                    BitArray(uint=pha_event.extended_header.detector_flags, length=8).bin,
                 ]
             )
 
@@ -390,9 +366,7 @@ def _create_pha_event_binary(self, pha_event: RawPHAEvent) -> str:
             binary_string += "".join(
                 [
                     BitArray(uint=pha_event.extended_stim_header.tbd, length=12).bin,
-                    BitArray(
-                        uint=pha_event.extended_stim_header.dac_value, length=12
-                    ).bin,
+                    BitArray(uint=pha_event.extended_stim_header.dac_value, length=12).bin,
                 ]
             )
 
diff --git a/tests/hit/l3/sectored_products/science/test_sectored_products_algorithms.py b/tests/hit/l3/sectored_products/science/test_sectored_products_algorithms.py
index 484a7841..dcf788d1 100644
--- a/tests/hit/l3/sectored_products/science/test_sectored_products_algorithms.py
+++ b/tests/hit/l3/sectored_products/science/test_sectored_products_algorithms.py
@@ -3,8 +3,8 @@
 import numpy as np
 
 from imap_l3_processing.hit.l3.sectored_products.science.sectored_products_algorithms import (
-    get_sector_unit_vectors,
     get_hit_bin_polar_coordinates,
+    get_sector_unit_vectors,
 )
 
 
@@ -31,13 +31,9 @@ def test_get_sector_unit_vectors(self):
                 )
 
     def test_get_hit_bin_polar_coordinates(self):
-        declinations, azimuths, declination_delta, azimuth_delta = (
-            get_hit_bin_polar_coordinates()
-        )
+        declinations, azimuths, declination_delta, azimuth_delta = get_hit_bin_polar_coordinates()
 
         np.testing.assert_array_equal(declination_delta, [11.25] * 8, strict=True)
         np.testing.assert_array_equal(azimuth_delta, [12.0] * 15, strict=True)
-        np.testing.assert_array_almost_equal(
-            declinations, 11.25 + np.arange(0, 8) * 22.5
-        )
+        np.testing.assert_array_almost_equal(declinations, 11.25 + np.arange(0, 8) * 22.5)
         np.testing.assert_array_almost_equal(azimuths, 12 + np.arange(15) * 24)
diff --git a/tests/hit/l3/sectored_products/test_models.py b/tests/hit/l3/sectored_products/test_models.py
index dea37aac..62317d8c 100644
--- a/tests/hit/l3/sectored_products/test_models.py
+++ b/tests/hit/l3/sectored_products/test_models.py
@@ -1,6 +1,6 @@
 from datetime import timedelta
 from unittest import TestCase
-from unittest.mock import sentinel, Mock
+from unittest.mock import Mock, sentinel
 
 import numpy as np
 
@@ -93,9 +93,7 @@ def test_to_data_product_variables(self):
             DataProductVariable("pitch_angle_delta", sentinel.pitch_angles_deltas),
             DataProductVariable("gyrophase", NumpyArrayMatcher(gyrophases)),
             DataProductVariable("gyrophase_delta", sentinel.gyrophase_deltas),
-            DataProductVariable(
-                "h_macropixel_intensity", sentinel.h_macropixel_intensity
-            ),
+            DataProductVariable("h_macropixel_intensity", sentinel.h_macropixel_intensity),
             DataProductVariable(
                 "h_macropixel_intensity_delta_plus",
                 sentinel.h_macropixel_intensity_delta_plus,
@@ -116,9 +114,7 @@ def test_to_data_product_variables(self):
             DataProductVariable("h_energy", NumpyArrayMatcher(h_energy)),
             DataProductVariable("h_energy_delta_plus", sentinel.h_energy_delta_plus),
             DataProductVariable("h_energy_delta_minus", sentinel.h_energy_delta_minus),
-            DataProductVariable(
-                "he4_macropixel_intensity", sentinel.he4_macropixel_intensity
-            ),
+            DataProductVariable("he4_macropixel_intensity", sentinel.he4_macropixel_intensity),
             DataProductVariable(
                 "he4_macropixel_intensity_delta_plus",
                 sentinel.he4_macropixel_intensity_delta_plus,
@@ -127,9 +123,7 @@ def test_to_data_product_variables(self):
                 "he4_macropixel_intensity_delta_minus",
                 sentinel.he4_macropixel_intensity_delta_minus,
             ),
-            DataProductVariable(
-                "he4_macropixel_intensity_pa", sentinel.he4_pa_intensity
-            ),
+            DataProductVariable("he4_macropixel_intensity_pa", sentinel.he4_pa_intensity),
             DataProductVariable(
                 "he4_macropixel_intensity_pa_delta_plus",
                 sentinel.he4_pa_intensity_delta_plus,
@@ -139,15 +133,9 @@ def test_to_data_product_variables(self):
                 sentinel.he4_pa_intensity_delta_minus,
             ),
             DataProductVariable("he4_energy", NumpyArrayMatcher(he_energy)),
-            DataProductVariable(
-                "he4_energy_delta_plus", sentinel.he4_energy_delta_plus
-            ),
-            DataProductVariable(
-                "he4_energy_delta_minus", sentinel.he4_energy_delta_minus
-            ),
-            DataProductVariable(
-                "cno_macropixel_intensity", sentinel.cno_macropixel_intensity
-            ),
+            DataProductVariable("he4_energy_delta_plus", sentinel.he4_energy_delta_plus),
+            DataProductVariable("he4_energy_delta_minus", sentinel.he4_energy_delta_minus),
+            DataProductVariable("cno_macropixel_intensity", sentinel.cno_macropixel_intensity),
             DataProductVariable(
                 "cno_macropixel_intensity_delta_plus",
                 sentinel.cno_macropixel_intensity_delta_plus,
@@ -156,9 +144,7 @@ def test_to_data_product_variables(self):
                 "cno_macropixel_intensity_delta_minus",
                 sentinel.cno_macropixel_intensity_delta_minus,
             ),
-            DataProductVariable(
-                "cno_macropixel_intensity_pa", sentinel.cno_pa_intensity
-            ),
+            DataProductVariable("cno_macropixel_intensity_pa", sentinel.cno_pa_intensity),
             DataProductVariable(
                 "cno_macropixel_intensity_pa_delta_plus",
                 sentinel.cno_pa_intensity_delta_plus,
@@ -168,12 +154,8 @@ def test_to_data_product_variables(self):
                 sentinel.cno_pa_intensity_delta_minus,
             ),
             DataProductVariable("cno_energy", NumpyArrayMatcher(cno_energy)),
-            DataProductVariable(
-                "cno_energy_delta_plus", sentinel.cno_energy_delta_plus
-            ),
-            DataProductVariable(
-                "cno_energy_delta_minus", sentinel.cno_energy_delta_minus
-            ),
+            DataProductVariable("cno_energy_delta_plus", sentinel.cno_energy_delta_plus),
+            DataProductVariable("cno_energy_delta_minus", sentinel.cno_energy_delta_minus),
             DataProductVariable(
                 "nemgsi_macropixel_intensity", sentinel.ne_mg_si_macropixel_intensity
             ),
@@ -185,9 +167,7 @@ def test_to_data_product_variables(self):
                 "nemgsi_macropixel_intensity_delta_minus",
                 sentinel.ne_mg_si_macropixel_intensity_delta_minus,
             ),
-            DataProductVariable(
-                "nemgsi_macropixel_intensity_pa", sentinel.ne_mg_si_pa_intensity
-            ),
+            DataProductVariable("nemgsi_macropixel_intensity_pa", sentinel.ne_mg_si_pa_intensity),
             DataProductVariable(
                 "nemgsi_macropixel_intensity_pa_delta_plus",
                 sentinel.ne_mg_si_pa_intensity_delta_plus,
@@ -197,15 +177,9 @@ def test_to_data_product_variables(self):
                 sentinel.ne_mg_si_pa_intensity_delta_minus,
             ),
             DataProductVariable("nemgsi_energy", NumpyArrayMatcher(nemgsi_energy)),
-            DataProductVariable(
-                "nemgsi_energy_delta_plus", sentinel.ne_mg_si_energy_delta_plus
-            ),
-            DataProductVariable(
-                "nemgsi_energy_delta_minus", sentinel.ne_mg_si_energy_delta_minus
-            ),
-            DataProductVariable(
-                "fe_macropixel_intensity", sentinel.iron_macropixel_intensity
-            ),
+            DataProductVariable("nemgsi_energy_delta_plus", sentinel.ne_mg_si_energy_delta_plus),
+            DataProductVariable("nemgsi_energy_delta_minus", sentinel.ne_mg_si_energy_delta_minus),
+            DataProductVariable("fe_macropixel_intensity", sentinel.iron_macropixel_intensity),
             DataProductVariable(
                 "fe_macropixel_intensity_delta_plus",
                 sentinel.iron_macropixel_intensity_delta_plus,
@@ -214,9 +188,7 @@ def test_to_data_product_variables(self):
                 "fe_macropixel_intensity_delta_minus",
                 sentinel.iron_macropixel_intensity_delta_minus,
             ),
-            DataProductVariable(
-                "fe_macropixel_intensity_pa", sentinel.iron_pa_intensity
-            ),
+            DataProductVariable("fe_macropixel_intensity_pa", sentinel.iron_pa_intensity),
             DataProductVariable(
                 "fe_macropixel_intensity_pa_delta_plus",
                 sentinel.iron_pa_intensity_delta_plus,
@@ -226,18 +198,10 @@ def test_to_data_product_variables(self):
                 sentinel.iron_pa_intensity_delta_minus,
             ),
             DataProductVariable("fe_energy", NumpyArrayMatcher(fe_energy)),
-            DataProductVariable(
-                "fe_energy_delta_plus", sentinel.iron_energy_delta_plus
-            ),
-            DataProductVariable(
-                "fe_energy_delta_minus", sentinel.iron_energy_delta_minus
-            ),
-            DataProductVariable(
-                "measurement_pitch_angle", mock_measurement_pitch_angle
-            ),
-            DataProductVariable(
-                "measurement_gyrophase", sentinel.measurement_gyrophase
-            ),
+            DataProductVariable("fe_energy_delta_plus", sentinel.iron_energy_delta_plus),
+            DataProductVariable("fe_energy_delta_minus", sentinel.iron_energy_delta_minus),
+            DataProductVariable("measurement_pitch_angle", mock_measurement_pitch_angle),
+            DataProductVariable("measurement_gyrophase", sentinel.measurement_gyrophase),
             DataProductVariable(
                 "pitch_angle_label",
                 [
@@ -304,9 +268,7 @@ def test_to_data_product_variables(self):
                 ],
             ),
             DataProductVariable("azimuth", NumpyArrayMatcher(np.array([10, 180, 350]))),
-            DataProductVariable(
-                "zenith", NumpyArrayMatcher(np.array([10.25, 90.75, 170.5]))
-            ),
+            DataProductVariable("zenith", NumpyArrayMatcher(np.array([10.25, 90.75, 170.5]))),
             DataProductVariable("azimuth_label", ["10.0", "180.0", "350.0"]),
             DataProductVariable("zenith_label", ["10.25", "90.75", "170.5"]),
             DataProductVariable("hit_flags", sentinel.quality_flags),
diff --git a/tests/hit/l3/test_hit_processor.py b/tests/hit/l3/test_hit_processor.py
index c406a28e..8816db4b 100644
--- a/tests/hit/l3/test_hit_processor.py
+++ b/tests/hit/l3/test_hit_processor.py
@@ -3,36 +3,36 @@
 from pathlib import Path
 from typing import TypeVar
 from unittest import TestCase
-from unittest.mock import sentinel, patch, call, Mock
+from unittest.mock import Mock, call, patch, sentinel
 
 import numpy as np
 
 from imap_l3_processing.constants import (
-    UNSIGNED_INT2_FILL_VALUE,
     UNSIGNED_INT1_FILL_VALUE,
+    UNSIGNED_INT2_FILL_VALUE,
 )
 from imap_l3_processing.hit.l3.hit_l3_sectored_dependencies import (
     HITL3SectoredDependencies,
 )
 from imap_l3_processing.hit.l3.hit_processor import HitProcessor
-from imap_l3_processing.hit.l3.models import HitL2Data, HitL1Data
+from imap_l3_processing.hit.l3.models import HitL1Data, HitL2Data
 from imap_l3_processing.hit.l3.pha.pha_event_reader import (
-    PHAWord,
     Detector,
-    RawPHAEvent,
+    ExtendedStimHeader,
     PHAExtendedHeader,
+    PHAWord,
+    RawPHAEvent,
     StimBlock,
-    ExtendedStimHeader,
 )
 from imap_l3_processing.hit.l3.pha.science.calculate_pha import EventOutput
 from imap_l3_processing.hit.l3.pha.science.cosine_correction_lookup_table import (
     DetectedRange,
-    DetectorSide,
     DetectorRange,
+    DetectorSide,
 )
 from imap_l3_processing.hit.l3.sectored_products.models import HitPitchAngleDataProduct
 from imap_l3_processing.hit.quality_flags import HitL3Flags
-from imap_l3_processing.models import MagData, InputMetadata
+from imap_l3_processing.models import InputMetadata, MagData
 from imap_l3_processing.processor import Processor
 from tests.test_helpers import NumpyArrayMatcher, create_dataclass_mock
 
@@ -43,9 +43,7 @@ def test_is_a_processor(self):
 
     @patch("imap_l3_processing.utils.spiceypy")
     @patch("imap_l3_processing.hit.l3.hit_processor.save_data")
-    @patch(
-        "imap_l3_processing.hit.l3.hit_processor.HITL3SectoredDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.hit.l3.hit_processor.HITL3SectoredDependencies.fetch_dependencies")
     @patch("imap_l3_processing.hit.l3.hit_processor.calculate_unit_vector")
     @patch("imap_l3_processing.hit.l3.hit_processor.get_hit_bin_polar_coordinates")
     @patch("imap_l3_processing.hit.l3.hit_processor.get_sector_unit_vectors")
@@ -80,9 +78,7 @@ def test_process_pitch_angle_product(
         )
 
         mock_processing_input_collection = Mock()
-        mock_processing_input_collection.get_file_paths.return_value = [
-            Path("test/parent_path")
-        ]
+        mock_processing_input_collection.get_file_paths.return_value = [Path("test/parent_path")]
 
         epochs = np.array([123, 234])
         epoch_deltas = np.array([12, 13])
@@ -130,12 +126,8 @@ def test_process_pitch_angle_product(
         delta_minus_NeMgSi_time2 = np.full(2, 102)
 
         mock_hit_data.cno = np.array([CNO_time1, CNO_time2])
-        mock_hit_data.delta_plus_cno = np.array(
-            [delta_plus_CNO_time1, delta_plus_CNO_time2]
-        )
-        mock_hit_data.delta_minus_cno = np.array(
-            [delta_minus_CNO_time1, delta_minus_CNO_time2]
-        )
+        mock_hit_data.delta_plus_cno = np.array([delta_plus_CNO_time1, delta_plus_CNO_time2])
+        mock_hit_data.delta_minus_cno = np.array([delta_minus_CNO_time1, delta_minus_CNO_time2])
         mock_hit_data.he4 = np.array([helium4_time1, helium4_time2])
         mock_hit_data.delta_plus_he4 = np.array(
             [delta_plus_helium4_time1, delta_plus_helium4_time2]
@@ -151,12 +143,8 @@ def test_process_pitch_angle_product(
             [delta_minus_hydrogen_time1, delta_minus_hydrogen_time2]
         )
         mock_hit_data.fe = np.array([iron_time1, iron_time2])
-        mock_hit_data.delta_plus_fe = np.array(
-            [delta_plus_iron_time1, delta_plus_iron_time2]
-        )
-        mock_hit_data.delta_minus_fe = np.array(
-            [delta_minus_iron_time1, delta_minus_iron_time2]
-        )
+        mock_hit_data.delta_plus_fe = np.array([delta_plus_iron_time1, delta_plus_iron_time2])
+        mock_hit_data.delta_minus_fe = np.array([delta_minus_iron_time1, delta_minus_iron_time2])
         mock_hit_data.nemgsi = np.array([NeMgSi_time1, NeMgSi_time2])
         mock_hit_data.delta_plus_nemgsi = np.array(
             [delta_plus_NeMgSi_time1, delta_plus_NeMgSi_time2]
@@ -342,9 +330,7 @@ def test_process_pitch_angle_product(
 
         processor = HitProcessor(mock_processing_input_collection, input_metadata)
         product = processor.process()
-        mock_fetch_dependencies.assert_called_once_with(
-            mock_processing_input_collection
-        )
+        mock_fetch_dependencies.assert_called_once_with(mock_processing_input_collection)
 
         mock_mag_data.rebin_to.assert_called_once_with(
             mock_hit_data.epoch, mock_hit_data.epoch_delta
@@ -357,13 +343,9 @@ def test_process_pitch_angle_product(
             mock_hit_data.zenith, mock_hit_data.azimuth
         )
 
-        self.assertEqual(
-            1, mock_rotate_particle_vectors_from_hit_despun_to_imap_despun.call_count
-        )
+        self.assertEqual(1, mock_rotate_particle_vectors_from_hit_despun_to_imap_despun.call_count)
         np.testing.assert_array_equal(
-            mock_rotate_particle_vectors_from_hit_despun_to_imap_despun.call_args_list[
-                0
-            ].args[0],
+            mock_rotate_particle_vectors_from_hit_despun_to_imap_despun.call_args_list[0].args[0],
             -expected_sector_unit_vectors,
         )
 
@@ -503,24 +485,18 @@ def test_process_pitch_angle_product(
             ]
         )
 
-        saved_data_product: HitPitchAngleDataProduct = mock_save_data.call_args_list[
-            0
-        ].args[0]
+        saved_data_product: HitPitchAngleDataProduct = mock_save_data.call_args_list[0].args[0]
 
         self.assertEqual(input_metadata, saved_data_product.input_metadata)
         self.assertEqual(["parent_path"], saved_data_product.parent_file_names)
         np.testing.assert_array_equal(saved_data_product.epochs, epochs)
         np.testing.assert_array_equal(saved_data_product.epoch_deltas, epoch_deltas)
 
-        np.testing.assert_array_equal(
-            saved_data_product.pitch_angles, sentinel.pitch_angles
-        )
+        np.testing.assert_array_equal(saved_data_product.pitch_angles, sentinel.pitch_angles)
         np.testing.assert_array_equal(
             saved_data_product.pitch_angle_deltas, sentinel.pitch_angle_deltas
         )
-        np.testing.assert_array_equal(
-            saved_data_product.gyrophases, sentinel.gyrophases
-        )
+        np.testing.assert_array_equal(saved_data_product.gyrophases, sentinel.gyrophases)
         np.testing.assert_array_equal(
             saved_data_product.gyrophase_deltas, sentinel.gyrophase_deltas
         )
@@ -699,12 +675,8 @@ def test_process_pitch_angle_product(
         )
 
         self.assertIs(mock_hit_data.h_energy, saved_data_product.h_energies)
-        self.assertIs(
-            mock_hit_data.h_energy_delta_plus, saved_data_product.h_energy_delta_plus
-        )
-        self.assertIs(
-            mock_hit_data.h_energy_delta_minus, saved_data_product.h_energy_delta_minus
-        )
+        self.assertIs(mock_hit_data.h_energy_delta_plus, saved_data_product.h_energy_delta_plus)
+        self.assertIs(mock_hit_data.h_energy_delta_minus, saved_data_product.h_energy_delta_minus)
         self.assertIs(mock_hit_data.he4_energy, saved_data_product.he4_energies)
         self.assertIs(
             mock_hit_data.he4_energy_delta_plus,
@@ -763,9 +735,7 @@ def test_process_pitch_angle_product(
     @patch("imap_l3_processing.utils.spiceypy")
     @patch("imap_l3_processing.hit.l3.hit_processor.save_data")
     @patch("imap_l3_processing.hit.l3.hit_processor.process_pha_event", autospec=True)
-    @patch(
-        "imap_l3_processing.hit.l3.hit_processor.HitL3PhaDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.hit.l3.hit_processor.HitL3PhaDependencies.fetch_dependencies")
     @patch("imap_l3_processing.hit.l3.hit_processor.PHAEventReader.read_all_pha_events")
     def test_process_direct_event_product(
         self,
@@ -885,9 +855,7 @@ def test_process_direct_event_product(
         )
 
         mock_processing_input_collection = Mock()
-        mock_processing_input_collection.get_file_paths.return_value = [
-            Path("test/parent_path")
-        ]
+        mock_processing_input_collection.get_file_paths.return_value = [Path("test/parent_path")]
 
         mock_hit_l3_pha_dependencies = mock_fetch_dependencies.return_value
         mock_hit_l3_pha_dependencies.hit_l1_data.epoch = [
@@ -912,9 +880,7 @@ def test_process_direct_event_product(
         processor = HitProcessor(mock_processing_input_collection, input_metadata)
         product = processor.process()
 
-        mock_fetch_dependencies.assert_called_once_with(
-            mock_processing_input_collection
-        )
+        mock_fetch_dependencies.assert_called_once_with(mock_processing_input_collection)
         mock_read_all_events.assert_has_calls(
             [call(sentinel.binary_stream_1), call(sentinel.binary_stream_2)]
         )
@@ -964,15 +930,9 @@ def test_process_direct_event_product(
                 ]
             ),
         )
-        np.testing.assert_array_equal(
-            direct_event_product.charge, np.array([9.0, 10.0, 12.0])
-        )
-        np.testing.assert_array_equal(
-            direct_event_product.energy, np.array([99, 100, 200])
-        )
-        np.testing.assert_array_equal(
-            direct_event_product.particle_id, np.array([1, 1, 2])
-        )
+        np.testing.assert_array_equal(direct_event_product.charge, np.array([9.0, 10.0, 12.0]))
+        np.testing.assert_array_equal(direct_event_product.energy, np.array([99, 100, 200]))
+        np.testing.assert_array_equal(direct_event_product.particle_id, np.array([1, 1, 2]))
 
         np.testing.assert_array_equal(
             direct_event_product.e_delta, np.array([103.7, np.nan, 106.7])
@@ -988,21 +948,15 @@ def test_process_direct_event_product(
         np.testing.assert_array_equal(
             direct_event_product.priority_buffer_number, np.array([2, 2, 3])
         )
-        np.testing.assert_array_equal(
-            direct_event_product.latency, np.array([20, 20, 30])
-        )
+        np.testing.assert_array_equal(direct_event_product.latency, np.array([20, 20, 30]))
         np.testing.assert_array_equal(
             direct_event_product.stim_tag, np.array([False, False, True])
         )
         np.testing.assert_array_equal(
             direct_event_product.long_event_flag, np.array([False, False, True])
         )
-        np.testing.assert_array_equal(
-            direct_event_product.haz_tag, np.array([False, False, True])
-        )
-        np.testing.assert_array_equal(
-            direct_event_product.a_b_side, np.array([0, np.nan, 0])
-        )
+        np.testing.assert_array_equal(direct_event_product.haz_tag, np.array([False, False, True]))
+        np.testing.assert_array_equal(direct_event_product.a_b_side, np.array([0, np.nan, 0]))
         np.testing.assert_array_equal(
             direct_event_product.has_unread_adcs, np.array([True, True, False])
         )
@@ -1053,9 +1007,7 @@ def test_process_direct_event_product(
             )
             mask[idx] = False
 
-        self.assertTrue(
-            np.all(direct_event_product.pha_value[mask] == UNSIGNED_INT2_FILL_VALUE)
-        )
+        self.assertTrue(np.all(direct_event_product.pha_value[mask] == UNSIGNED_INT2_FILL_VALUE))
         self.assertTrue(np.all(np.isnan(direct_event_product.energy_at_detector[mask])))
         self.assertFalse(np.any(direct_event_product.is_low_gain[mask]))
 
@@ -1135,14 +1087,10 @@ def test_direct_event_parsing_errors_result_in_skipped_event(
 
         processor = HitProcessor(Mock(), input_metadata)
         with self.assertLogs():
-            actual_product = processor.process_direct_event_product(
-                mock_direct_event_dependencies
-            )
+            actual_product = processor.process_direct_event_product(mock_direct_event_dependencies)
 
         self.assertEqual(1, len(actual_product.epoch))
-        self.assertEqual(
-            datetime(year=2020, month=2, day=1, hour=1), actual_product.epoch[0]
-        )
+        self.assertEqual(datetime(year=2020, month=2, day=1, hour=1), actual_product.epoch[0])
 
     def test_raise_error_if_descriptor_doesnt_match(self):
         input_metadata = InputMetadata(
diff --git a/tests/hit/l3/test_l3_sectored_dependencies.py b/tests/hit/l3/test_l3_sectored_dependencies.py
index 4e7c43d4..05234eb3 100644
--- a/tests/hit/l3/test_l3_sectored_dependencies.py
+++ b/tests/hit/l3/test_l3_sectored_dependencies.py
@@ -1,36 +1,26 @@
 from pathlib import Path
 from unittest import TestCase
-from unittest.mock import patch, call
+from unittest.mock import call, patch
 
 import imap_data_access
-from imap_data_access.processing_input import ScienceInput, ProcessingInputCollection
+from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.hit.l3.hit_l3_sectored_dependencies import (
-    HITL3SectoredDependencies,
     HIT_L2_DESCRIPTOR,
+    HITL3SectoredDependencies,
 )
 
 
 class TestHITL3SectoredDependencies(TestCase):
     @patch("imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.read_mag_data")
     @patch("imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.read_l2_hit_data")
-    @patch(
-        "imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.imap_data_access.download"
-    )
-    def test_fetch_dependencies(
-        self, mock_download, mock_read_hit_data, mock_read_mag_data
-    ):
-        hit_l2_data_dependency = ScienceInput(
-            f"imap_hit_l2_{HIT_L2_DESCRIPTOR}_20240908_v001.cdf"
-        )
+    @patch("imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.imap_data_access.download")
+    def test_fetch_dependencies(self, mock_download, mock_read_hit_data, mock_read_mag_data):
+        hit_l2_data_dependency = ScienceInput(f"imap_hit_l2_{HIT_L2_DESCRIPTOR}_20240908_v001.cdf")
         mag_data_dependency = ScienceInput("imap_mag_l1d_norm-dsrf_20240906_v001.cdf")
 
-        hit_data_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "hit" / "l2" / "2024" / "09"
-        )
-        mag_data_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "mag" / "l1d" / "2024" / "09"
-        )
+        hit_data_dir = imap_data_access.config["DATA_DIR"] / "imap" / "hit" / "l2" / "2024" / "09"
+        mag_data_dir = imap_data_access.config["DATA_DIR"] / "imap" / "mag" / "l1d" / "2024" / "09"
 
         expected_file_paths = [
             hit_data_dir / f"imap_hit_l2_{HIT_L2_DESCRIPTOR}_20240908_v001.cdf",
@@ -59,24 +49,16 @@ def test_fetch_dependencies(
 
     @patch("imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.read_mag_data")
     @patch("imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.read_l2_hit_data")
-    @patch(
-        "imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.hit.l3.hit_l3_sectored_dependencies.imap_data_access.download")
     def test_fetch_dependencies_uses_mag_l2_if_available(
         self, mock_download, mock_read_hit_data, mock_read_mag_data
     ):
-        hit_l2_data_dependency = ScienceInput(
-            f"imap_hit_l2_{HIT_L2_DESCRIPTOR}_20240908_v001.cdf"
-        )
+        hit_l2_data_dependency = ScienceInput(f"imap_hit_l2_{HIT_L2_DESCRIPTOR}_20240908_v001.cdf")
         mag_data_dependency = ScienceInput("imap_mag_l1d_norm-dsrf_20240906_v001.cdf")
         mag_l2_data_dependency = ScienceInput("imap_mag_l2_norm-dsrf_20240906_v001.cdf")
 
-        hit_data_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "hit" / "l2" / "2024" / "09"
-        )
-        mag_data_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "mag" / "l2" / "2024" / "09"
-        )
+        hit_data_dir = imap_data_access.config["DATA_DIR"] / "imap" / "hit" / "l2" / "2024" / "09"
+        mag_data_dir = imap_data_access.config["DATA_DIR"] / "imap" / "mag" / "l2" / "2024" / "09"
 
         expected_file_paths = [
             hit_data_dir / f"imap_hit_l2_{HIT_L2_DESCRIPTOR}_20240908_v001.cdf",
diff --git a/tests/hit/l3/test_models.py b/tests/hit/l3/test_models.py
index f226f3d2..532a604f 100644
--- a/tests/hit/l3/test_models.py
+++ b/tests/hit/l3/test_models.py
@@ -96,9 +96,7 @@ def test_direct_events_to_data_product_variables_with_multiple_events(self):
             DataProductVariable(models.E_PRIME_VAR_NAME, e_prime),
             DataProductVariable(models.DETECTED_RANGE_VAR_NAME, detected_range),
             DataProductVariable(models.PARTICLE_ID_VAR_NAME, particle),
-            DataProductVariable(
-                models.PRIORITY_BUFFER_NUMBER_VAR_NAME, priority_buffer_number
-            ),
+            DataProductVariable(models.PRIORITY_BUFFER_NUMBER_VAR_NAME, priority_buffer_number),
             DataProductVariable(models.LATENCY_VAR_NAME, latency),
             DataProductVariable(models.STIM_TAG_VAR_NAME, stim_tag),
             DataProductVariable(models.LONG_EVENT_FLAG_VAR_NAME, long_event_flag),
@@ -191,9 +189,7 @@ def test_direct_events_to_data_product_variables_with_multiple_events(self):
         actual_variables = direct_event.to_data_product_variables()
 
         self.assertEqual(28, len(actual_variables))
-        for expected_variable, actual_variable in zip(
-            expected_variables, actual_variables
-        ):
+        for expected_variable, actual_variable in zip(expected_variables, actual_variables):
             self.assert_variable_attributes(
                 actual_variable,
                 expected_variable.value,
@@ -221,6 +217,4 @@ def test_hit_l1_data_read_from_cdf(self):
                 hit_l1_data = HitL1Data.read_from_cdf(file_path)
 
                 np.testing.assert_array_equal(hit_l1_data.epoch, expected_epochs)
-                np.testing.assert_array_equal(
-                    expected_raw_binaries, hit_l1_data.event_binary
-                )
+                np.testing.assert_array_equal(expected_raw_binaries, hit_l1_data.event_binary)
diff --git a/tests/hit/l3/test_utils.py b/tests/hit/l3/test_utils.py
index 5705f92c..544a93b5 100644
--- a/tests/hit/l3/test_utils.py
+++ b/tests/hit/l3/test_utils.py
@@ -159,21 +159,11 @@ def test_read_l2_hit_data_handles_fill_values(self):
             with self.subTest(path):
                 result = read_l2_hit_data(path)
 
-                np.testing.assert_array_equal(
-                    result.h, np.full_like(hydrogen_data, np.nan)
-                )
-                np.testing.assert_array_equal(
-                    result.he4, np.full_like(helium_data, np.nan)
-                )
-                np.testing.assert_array_equal(
-                    result.cno, np.full_like(cno_data, np.nan)
-                )
-                np.testing.assert_array_equal(
-                    result.nemgsi, np.full_like(nemgsi_data, np.nan)
-                )
-                np.testing.assert_array_equal(
-                    result.fe, np.full_like(iron_data, np.nan)
-                )
+                np.testing.assert_array_equal(result.h, np.full_like(hydrogen_data, np.nan))
+                np.testing.assert_array_equal(result.he4, np.full_like(helium_data, np.nan))
+                np.testing.assert_array_equal(result.cno, np.full_like(cno_data, np.nan))
+                np.testing.assert_array_equal(result.nemgsi, np.full_like(nemgsi_data, np.nan))
+                np.testing.assert_array_equal(result.fe, np.full_like(iron_data, np.nan))
 
                 np.testing.assert_array_equal(
                     result.delta_plus_h, np.full_like(hydrogen_data, np.nan)
diff --git a/tests/integration/integration_test_helpers.py b/tests/integration/integration_test_helpers.py
index 137f236d..4a0ccb53 100644
--- a/tests/integration/integration_test_helpers.py
+++ b/tests/integration/integration_test_helpers.py
@@ -2,18 +2,18 @@
 import os
 import shutil
 from collections import defaultdict
+from collections.abc import Callable
 from pathlib import Path
-from typing import Callable
-from unittest.mock import patch, Mock
+from unittest.mock import Mock, patch
 from urllib.parse import urlparse
 
 import imap_data_access
 import requests
 from imap_data_access import AncillaryFilePath
 from imap_data_access.file_validation import (
-    generate_imap_file_path,
     ScienceFilePath,
     SPICEFilePath,
+    generate_imap_file_path,
 )
 from requests import Response
 
@@ -35,8 +35,7 @@ def stop(self):
 
     def __call__(self, **kwargs):
         table = kwargs.get("table") or "science"
-        if "table" in kwargs:
-            del kwargs["table"]
+        kwargs.pop("table", None)
 
         use_latest = kwargs.get("version") == "latest"
         if kwargs.get("version") == "latest":
@@ -61,9 +60,7 @@ def __call__(self, **kwargs):
             qr for qr in query_results if desired_attributes.issubset(set(qr.items()))
         ]
         if use_latest:
-            filtered_query_results = self.filter_results_for_latest(
-                filtered_query_results
-            )
+            filtered_query_results = self.filter_results_for_latest(filtered_query_results)
         return filtered_query_results
 
     @staticmethod
@@ -72,8 +69,7 @@ def filter_results_for_latest(query_results: list[dict]):
         for qr in query_results:
             query_results_by_date[qr["start_date"]].append(qr)
         return [
-            max(qrs, key=get_version_from_query_result)
-            for qrs in query_results_by_date.values()
+            max(qrs, key=get_version_from_query_result) for qrs in query_results_by_date.values()
         ]
 
 
@@ -109,18 +105,14 @@ def stage_input_file(file_path: Path) -> Path:
 """
 
 
-def create_metakernel(
-    path_to_spice_dir: str, requested_spice_paths: list[SPICEFilePath]
-) -> str:
+def create_metakernel(path_to_spice_dir: str, requested_spice_paths: list[SPICEFilePath]) -> str:
     all_spice_paths = []
     for spice_file in requested_spice_paths:
         spice_subdir_name = spice_file.construct_path().parent.name
         spice_file_name = spice_file.construct_path().name
         spice_path = str(Path(path_to_spice_dir) / spice_subdir_name / spice_file_name)
 
-        chunked_spice_path = [
-            spice_path[i : i + 79] for i in range(0, len(spice_path), 79)
-        ]
+        chunked_spice_path = [spice_path[i : i + 79] for i in range(0, len(spice_path), 79)]
         for i, chunk in enumerate(chunked_spice_path[:-1]):
             chunked_spice_path[i] = f"{chunk}+"
 
@@ -154,9 +146,7 @@ def __call__(self, url, **kwargs):
                 elif "params" in kwargs:
                     prefix = kwargs["params"].get("spice_path") or ""
 
-                    spice_file_paths = [
-                        SPICEFilePath(fn) for fn in self.spice_file_names
-                    ]
+                    spice_file_paths = [SPICEFilePath(fn) for fn in self.spice_file_names]
                     requested_spice_paths = [
                         p
                         for p in spice_file_paths
@@ -177,32 +167,26 @@ def __call__(self, url, **kwargs):
 
 
 class mock_imap_data_access:
-    def __init__(
-        self, data_dir: Path, input_files: list[Path], omni_file: Path | None = None
-    ):
+    def __init__(self, data_dir: Path, input_files: list[Path], omni_file: Path | None = None):
         self.data_dir = data_dir
 
         valid_files = []
         spice_file_paths = []
         for input_file in input_files:
             if not input_file.exists():
-                raise Exception(f"Could not find file {input_file}")
+                raise FileNotFoundError(f"Could not find file {input_file}")
             try:
                 imap_input_file_path = generate_imap_file_path(input_file.name)
                 valid_files.append(input_file)
                 if isinstance(imap_input_file_path, SPICEFilePath):
                     spice_file_paths.append(input_file)
-            except Exception:
+            except Exception:  # noqa: BLE001, S112
                 continue
         self.input_files = valid_files
 
         self.env_patcher = patch.dict(os.environ, {"IMAP_DATA_DIR": str(self.data_dir)})
-        self.data_dir_patcher = patch.dict(
-            imap_data_access.config, {"DATA_DIR": self.data_dir}
-        )
-        self.download_patcher = patch.object(
-            imap_data_access, "download", new=fake_download
-        )
+        self.data_dir_patcher = patch.dict(imap_data_access.config, {"DATA_DIR": self.data_dir})
+        self.download_patcher = patch.object(imap_data_access, "download", new=fake_download)
         self.query_patcher = ImapQueryPatcher(self.input_files)
         self.requests_get_patcher = RequestsGetPatcher(spice_file_paths, omni_file)
 
@@ -220,7 +204,7 @@ def __enter__(self):
         for file_path in self.input_files:
             try:
                 stage_input_file(file_path)
-            except Exception:
+            except Exception:  # noqa: BLE001, S110
                 pass
 
     def __exit__(self, exc_type, exc_val, exc_tb):
@@ -241,11 +225,12 @@ def wrapped(obj, *args, **kwargs):
 
 
 def run_istp_compliance_check(cdf_path: Path):
-    cdf_as_json = requests.post(
-        "https://skteditor.heliophysics.net/cgi-bin/cdf2json.cgi",
-        files={"file": open(cdf_path, "rb")},
-    ).json()
-    cdf_json = list(cdf_as_json.values())[0]
+    with open(cdf_path, "rb") as cdffile:
+        cdf_as_json = requests.post(
+            "https://skteditor.heliophysics.net/cgi-bin/cdf2json.cgi",
+            files={"file": cdffile},
+        ).json()
+    cdf_json = next(iter(cdf_as_json.values()))
     return requests.post(
         "https://skteditor.heliophysics.net/cgi-bin/validate.cgi",
         json={cdf_path.name: cdf_json},
diff --git a/tests/integration/test_codice_processor_integration.py b/tests/integration/test_codice_processor_integration.py
index 1933acd6..4bbc2d7b 100644
--- a/tests/integration/test_codice_processor_integration.py
+++ b/tests/integration/test_codice_processor_integration.py
@@ -25,8 +25,7 @@ def test_codice_lo_direct_events(self, mock_parse_cli_arguments):
             CODICE_TEST_DATA_DIR / "imap_codice_lo-energy-per-charge_20241110_v002.csv"
         )
         mass_coefficient_path = (
-            CODICE_TEST_DATA_DIR
-            / "imap_codice_mass-coefficient-lookup_20241110_v003.csv"
+            CODICE_TEST_DATA_DIR / "imap_codice_mass-coefficient-lookup_20241110_v003.csv"
         )
         input_files = [
             CODICE_TEST_DATA_DIR / "imap_codice_l2_lo-direct-events_20260307_v004.cdf",
@@ -82,16 +81,13 @@ def test_codice_lo_direct_events(self, mock_parse_cli_arguments):
                 self.assertEqual(expected_parents, set(cdf.attrs["Parents"]))
 
     @patch("imap_l3_data_processor._parse_cli_arguments")
-    def test_codice_lo_partial_densities_and_sw_products(
-        self, mock_parse_cli_arguments
-    ):
+    def test_codice_lo_partial_densities_and_sw_products(self, mock_parse_cli_arguments):
         input_files = [
             INTEGRATION_DATA_DIR / "imap_codice_l2_lo-sw-species_20260301_v001.cdf",
             INTEGRATION_DATA_DIR / "imap_codice_mass-per-charge_20241110_v003.csv",
             INTEGRATION_DATA_DIR
             / "imap_codice_l3a_lo-partial-densities-25ccf871_20260301_v001.json",
-            INTEGRATION_DATA_DIR
-            / "imap_codice_l3a_lo-sw-ratios-25ccf871_20260301_v001.json",
+            INTEGRATION_DATA_DIR / "imap_codice_l3a_lo-sw-ratios-25ccf871_20260301_v001.json",
         ]
         with mock_imap_data_access(OUTPUT_DIR, input_files):
 
@@ -143,8 +139,7 @@ def test_codice_lo_3d_distributions(self, mock_parse_cli_arguments):
             CODICE_TEST_DATA_DIR / "imap_codice_lo-energy-per-charge_20241110_v002.csv",
             CODICE_TEST_DATA_DIR / "imap_codice_l3-lo-efficiency_20251008_v003.csv",
             CODICE_TEST_DATA_DIR / "imap_codice_l2-lo-gfactor_20251212_v003.csv",
-            CODICE_TEST_DATA_DIR
-            / "imap_codice_lo-mass-species-bin-lookup_20250309_v003.csv",
+            CODICE_TEST_DATA_DIR / "imap_codice_lo-mass-species-bin-lookup_20250309_v003.csv",
         ]
 
         processing_input = ProcessingInputCollection(
@@ -178,14 +173,11 @@ def test_codice_lo_3d_distributions(self, mock_parse_cli_arguments):
     @patch("imap_l3_data_processor._parse_cli_arguments")
     def test_codice_hi_direct_events(self, mock_parse_cli_arguments):
         input_files = [
-            CODICE_TEST_DATA_DIR
-            / "imap_codice_l1a_hi-direct-events_20260831_v001.0003.cdf",
-            CODICE_TEST_DATA_DIR
-            / "imap_codice_l2_hi-direct-events_20260831_v001.0003.cdf",
+            CODICE_TEST_DATA_DIR / "imap_codice_l1a_hi-direct-events_20260831_v001.0003.cdf",
+            CODICE_TEST_DATA_DIR / "imap_codice_l2_hi-direct-events_20260831_v001.0003.cdf",
             CODICE_TEST_DATA_DIR
             / "imap_codice_l3-hi-mass-correction-lut-truncated_20251008_v001.xlsx",
-            INTEGRATION_DATA_DIR
-            / "imap_codice_l3a_hi-direct-events-e968219e_20260831_v001.json",
+            INTEGRATION_DATA_DIR / "imap_codice_l3a_hi-direct-events-e968219e_20260831_v001.json",
         ]
         with mock_imap_data_access(OUTPUT_DIR, input_files):
             mock_arguments = Mock()
diff --git a/tests/integration/test_glows_processor_integration.py b/tests/integration/test_glows_processor_integration.py
index 8a621ea6..b3b0d10b 100644
--- a/tests/integration/test_glows_processor_integration.py
+++ b/tests/integration/test_glows_processor_integration.py
@@ -5,19 +5,23 @@
 import shutil
 import subprocess
 import unittest
+from collections.abc import Callable
 from contextlib import contextmanager
-from datetime import timedelta, datetime
-from functools import wraps, partial
+from datetime import datetime, timedelta
+from functools import partial, wraps
 from pathlib import Path
-from typing import Callable
 from unittest import skipIf
-from unittest.mock import patch, Mock
+from unittest.mock import Mock, patch
 
 import imap_data_access
 import numpy as np
-from imap_data_access import ProcessingInputCollection, RepointInput
-from imap_data_access import ScienceInput, AncillaryInput
-from imap_data_access.file_validation import ScienceFilePath, AncillaryFilePath, Version
+from imap_data_access import (
+    AncillaryInput,
+    ProcessingInputCollection,
+    RepointInput,
+    ScienceInput,
+)
+from imap_data_access.file_validation import AncillaryFilePath, ScienceFilePath, Version
 from spacepy.pycdf import CDF
 
 import imap_l3_data_processor
@@ -26,8 +30,8 @@
 from imap_l3_processing.glows.glows_processor import GlowsProcessor
 from imap_l3_processing.glows.l3a.glows_l3a_dependencies import GlowsL3ADependencies
 from imap_l3_processing.glows.l3a.utils import (
-    read_l2_glows_data,
     create_glows_l3a_from_dictionary,
+    read_l2_glows_data,
 )
 from imap_l3_processing.glows.l3d.utils import PATH_TO_L3D_TOOLKIT
 from imap_l3_processing.glows.l3e.glows_l3e_initializer import (
@@ -41,29 +45,23 @@
     run_istp_compliance_check,
 )
 from tests.test_helpers import (
+    create_mock_version_map,
+    get_run_local_data_path,
     get_test_data_path,
     get_test_instrument_team_data_path,
-    with_tempdir,
-    get_run_local_data_path,
     run_periodically,
-    create_mock_version_map,
+    with_tempdir,
 )
 
-GLOWS_INTEGRATION_DATA_DIR = get_run_local_data_path(
-    "glows_l3bcde_integration_data_dir"
-)
+GLOWS_INTEGRATION_DATA_DIR = get_run_local_data_path("glows_l3bcde_integration_data_dir")
 INTEGRATION_TEST_DATA = Path(__file__).parent / "test_data"
 GLOWS_TEST_DATA = get_test_data_path("glows")
 
 
 def generate_test_function_import_path(fn: Callable) -> str:
     path_to_imap_processing_dir = Path(tests.__file__).parent.parent
-    path_to_file = Path(fn.__code__.co_filename).relative_to(
-        path_to_imap_processing_dir
-    )
-    path_in_import_style = (
-        str(path_to_file).replace(".py", ".").replace(os.path.sep, ".")
-    )
+    path_to_file = Path(fn.__code__.co_filename).relative_to(path_to_imap_processing_dir)
+    path_in_import_style = str(path_to_file).replace(".py", ".").replace(os.path.sep, ".")
     return path_in_import_style + fn.__qualname__
 
 
@@ -184,9 +182,7 @@ def test_glows_l3a(self, tmp_dir):
         )
         with open(expected_json_path) as f:
             instrument_team_dict = json.load(f)
-        expected_output = create_glows_l3a_from_dictionary(
-            instrument_team_dict, input_metadata
-        )
+        expected_output = create_glows_l3a_from_dictionary(instrument_team_dict, input_metadata)
 
         with CDF(str(input_l2_cdf_path)) as cdf_data:
             l2_glows_data = read_l2_glows_data(cdf_data)
@@ -228,31 +224,19 @@ def test_glows_l3a(self, tmp_dir):
             expected_dict["photon_flux_uncertainty"],
             rtol=1e-3,
         )
-        np.testing.assert_allclose(
-            actual_dict["raw_histogram"], expected_dict["raw_histogram"]
-        )
+        np.testing.assert_allclose(actual_dict["raw_histogram"], expected_dict["raw_histogram"])
         np.testing.assert_allclose(
             actual_dict["exposure_times"], expected_dict["exposure_times"], rtol=1e-3
         )
-        np.testing.assert_allclose(
-            actual_dict["number_of_bins"], expected_dict["number_of_bins"]
-        )
+        np.testing.assert_allclose(actual_dict["number_of_bins"], expected_dict["number_of_bins"])
         self.assertEqual(actual_dict["epoch"], expected_dict["epoch"])
-        np.testing.assert_allclose(
-            actual_dict["epoch_delta"], expected_dict["epoch_delta"]
-        )
-        np.testing.assert_allclose(
-            actual_dict["spin_angle"], expected_dict["spin_angle"]
-        )
+        np.testing.assert_allclose(actual_dict["epoch_delta"], expected_dict["epoch_delta"])
+        np.testing.assert_allclose(actual_dict["spin_angle"], expected_dict["spin_angle"])
         np.testing.assert_allclose(
             actual_dict["spin_angle_delta"], expected_dict["spin_angle_delta"]
         )
-        np.testing.assert_allclose(
-            actual_dict["latitude"], expected_dict["latitude"], atol=1e-3
-        )
-        np.testing.assert_allclose(
-            actual_dict["longitude"], expected_dict["longitude"], atol=1e-3
-        )
+        np.testing.assert_allclose(actual_dict["latitude"], expected_dict["latitude"], atol=1e-3)
+        np.testing.assert_allclose(actual_dict["longitude"], expected_dict["longitude"], atol=1e-3)
         np.testing.assert_allclose(
             actual_dict["filter_temperature_average"],
             expected_dict["filter_temperature_average"],
@@ -413,9 +397,7 @@ def test_l3bcde_first_time_processing(self):
 
             processing_input = ProcessingInputCollection(
                 RepointInput("imap_2026_090_01.repoint"),
-                AncillaryInput(
-                    "imap_glows_force-reprocessing-config_20250101_v000.csv"
-                ),
+                AncillaryInput("imap_glows_force-reprocessing-config_20250101_v000.csv"),
             )
 
             version_map = VersionMap(
@@ -440,12 +422,8 @@ def test_l3bcde_first_time_processing(self):
             [unfiltered] = identified
             repointings_to_update = set(range(36, 116))
             # Repoint 20 is not otherwise updated, so it is only there because the force reprocessing config lists it
-            self.assertEqual(
-                repointings_to_update | {20}, set(unfiltered.repointing_numbers)
-            )
-            self.assertEqual(
-                repointings_to_update | {20}, set(unfiltered.ultra_sf_repointings)
-            )
+            self.assertEqual(repointings_to_update | {20}, set(unfiltered.repointing_numbers))
+            self.assertEqual(repointings_to_update | {20}, set(unfiltered.ultra_sf_repointings))
             for versions in [
                 unfiltered.hi_90_repointings,
                 unfiltered.hi_45_repointings,
@@ -455,21 +433,11 @@ def test_l3bcde_first_time_processing(self):
                 self.assertEqual(repointings_to_update, set(versions))
 
             expected_files = [
-                ScienceFilePath(
-                    "imap_glows_l3b_ion-rate-profile_20251102-cr02304_v000.0001.cdf"
-                ),
-                ScienceFilePath(
-                    "imap_glows_l3b_ion-rate-profile_20251130-cr02305_v000.0001.cdf"
-                ),
-                ScienceFilePath(
-                    "imap_glows_l3c_sw-profile_20251102-cr02304_v000.0001.cdf"
-                ),
-                ScienceFilePath(
-                    "imap_glows_l3c_sw-profile_20251130-cr02305_v000.0001.cdf"
-                ),
-                ScienceFilePath(
-                    "imap_glows_l3d_solar-hist_19470303-cr02306_v002.0001.cdf"
-                ),
+                ScienceFilePath("imap_glows_l3b_ion-rate-profile_20251102-cr02304_v000.0001.cdf"),
+                ScienceFilePath("imap_glows_l3b_ion-rate-profile_20251130-cr02305_v000.0001.cdf"),
+                ScienceFilePath("imap_glows_l3c_sw-profile_20251102-cr02304_v000.0001.cdf"),
+                ScienceFilePath("imap_glows_l3c_sw-profile_20251130-cr02305_v000.0001.cdf"),
+                ScienceFilePath("imap_glows_l3d_solar-hist_19470303-cr02306_v002.0001.cdf"),
                 AncillaryFilePath("imap_glows_uv-anis_19470303_20260110_v001.dat"),
                 AncillaryFilePath("imap_glows_lya_19470303_20260110_v001.dat"),
                 AncillaryFilePath("imap_glows_e-dens_19470303_20260110_v001.dat"),
@@ -547,19 +515,15 @@ def test_l3bcde_first_time_processing(self):
     @run_periodically(timedelta(days=14))
     @run_test_in_docker
     def test_l3bcde_automatic_reprocessing(self):
-        new_l3a_file = (
-            GLOWS_TEST_DATA / "imap_glows_l3a_hist_20251118-repoint00052_v001.cdf"
-        )
+        new_l3a_file = GLOWS_TEST_DATA / "imap_glows_l3a_hist_20251118-repoint00052_v001.cdf"
         l3bcde_input_files = [
             GLOWS_TEST_DATA / "imap_glows_l3a_hist_20251113-repoint00047_v001.cdf",
             GLOWS_TEST_DATA / "imap_glows_l3a_hist_20251129-repoint00063_v001.cdf",
             GLOWS_TEST_DATA / "imap_glows_l3a_hist_20251201-repoint00065_v001.cdf",
             GLOWS_TEST_DATA / "imap_glows_l3a_hist_20251226-repoint00090_v001.cdf",
             new_l3a_file,
-            GLOWS_TEST_DATA
-            / "imap_glows_l3b_ion-rate-profile_20251102-cr02304_v001.cdf",
-            GLOWS_TEST_DATA
-            / "imap_glows_l3b_ion-rate-profile_20251130-cr02305_v001.cdf",
+            GLOWS_TEST_DATA / "imap_glows_l3b_ion-rate-profile_20251102-cr02304_v001.cdf",
+            GLOWS_TEST_DATA / "imap_glows_l3b_ion-rate-profile_20251130-cr02305_v001.cdf",
             GLOWS_TEST_DATA / "imap_glows_l3c_sw-profile_20251102-cr02304_v001.cdf",
             GLOWS_TEST_DATA / "imap_glows_l3c_sw-profile_20251130-cr02305_v001.cdf",
             GLOWS_TEST_DATA / "imap_glows_l3d_solar-hist_19470303-cr02304_v001.cdf",
@@ -611,9 +575,7 @@ def test_l3bcde_automatic_reprocessing(self):
         ):
             processing_input = ProcessingInputCollection(
                 RepointInput("imap_2026_090_01.repoint"),
-                AncillaryInput(
-                    "imap_glows_force-reprocessing-config_20250101_v000.csv"
-                ),
+                AncillaryInput("imap_glows_force-reprocessing-config_20250101_v000.csv"),
             )
             input_metadata = InputMetadata(
                 instrument="glows",
@@ -635,15 +597,9 @@ def test_l3bcde_automatic_reprocessing(self):
                 self.assertEqual(all_repointings, set(versions))
 
             expected_files = [
-                ScienceFilePath(
-                    "imap_glows_l3b_ion-rate-profile_20251102-cr02304_v001.0002.cdf"
-                ),
-                ScienceFilePath(
-                    "imap_glows_l3c_sw-profile_20251102-cr02304_v001.0002.cdf"
-                ),
-                ScienceFilePath(
-                    "imap_glows_l3d_solar-hist_19470303-cr02306_v001.0002.cdf"
-                ),
+                ScienceFilePath("imap_glows_l3b_ion-rate-profile_20251102-cr02304_v001.0002.cdf"),
+                ScienceFilePath("imap_glows_l3c_sw-profile_20251102-cr02304_v001.0002.cdf"),
+                ScienceFilePath("imap_glows_l3d_solar-hist_19470303-cr02306_v001.0002.cdf"),
                 AncillaryFilePath("imap_glows_uv-anis_19470303_20260110_v002.dat"),
                 AncillaryFilePath("imap_glows_lya_19470303_20260110_v002.dat"),
                 AncillaryFilePath("imap_glows_e-dens_19470303_20260110_v002.dat"),
@@ -678,8 +634,7 @@ def test_l3bcde_automatic_reprocessing(self):
     def test_glows_l3abcde_from_l2(self):
         ancillary_file_paths = [
             GLOWS_TEST_DATA / "imap_glows_l2-calibration_20251112_v003.dat",
-            GLOWS_TEST_DATA
-            / "imap_glows_l3a-map-of-extra-helio-bckgrd_20251112_v001.dat",
+            GLOWS_TEST_DATA / "imap_glows_l3a-map-of-extra-helio-bckgrd_20251112_v001.dat",
             GLOWS_TEST_DATA / "imap_glows_pipeline-settings_20251112_v002.json",
             GLOWS_TEST_DATA / "imap_glows_l3a-time-dep-bckgrd_20251112_v001.dat",
         ]
@@ -717,7 +672,7 @@ def test_glows_l3abcde_from_l2(self):
 
                 try:
                     _ = processor.process()
-                except Exception as e:
+                except Exception as e:  # noqa: BLE001
                     print(f"Processing L3a day {start_date} failed! Reason: {e}")
 
         l3bcde_ancillary_inputs = [
@@ -747,16 +702,12 @@ def test_glows_l3abcde_from_l2(self):
             INTEGRATION_TEST_DATA / "spice" / "imap_recon_20250925_20260520_v01.bsp",
         ]
 
-        lo_l1b_folder = Path(
-            "/Users/harrison/Development/imap_L3_processing/data/imap/lo/l1b"
-        )
+        lo_l1b_folder = Path("/Users/harrison/Development/imap_L3_processing/data/imap/lo/l1b")
         lo_l1b_inputs = list(lo_l1b_folder.rglob("*.cdf"))
 
         l3a_inputs = list((l3a_integration_data_dir / "imap/glows/l3a").rglob("*.cdf"))
 
-        repoint_file_path = [
-            INTEGRATION_TEST_DATA / "spice" / "imap_2026_139_01.repoint"
-        ]
+        repoint_file_path = [INTEGRATION_TEST_DATA / "spice" / "imap_2026_139_01.repoint"]
 
         logging.basicConfig(
             force=True,
@@ -764,17 +715,13 @@ def test_glows_l3abcde_from_l2(self):
             format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
         )
 
-        input_paths = (
-            l3bcde_ancillary_inputs + l3a_inputs + repoint_file_path + lo_l1b_inputs
-        )
+        input_paths = l3bcde_ancillary_inputs + l3a_inputs + repoint_file_path + lo_l1b_inputs
         with mock_imap_data_access(
             get_run_local_data_path("glows_l3bcde_with_prod_l2"), input_paths
         ):
             processing_input = ProcessingInputCollection(
                 RepointInput("imap_2026_139_01.repoint"),
-                AncillaryInput(
-                    "imap_glows_force-reprocessing-config_20250101_v000.csv"
-                ),
+                AncillaryInput("imap_glows_force-reprocessing-config_20250101_v000.csv"),
             )
             input_metadata = InputMetadata(
                 instrument="glows",
@@ -797,9 +744,7 @@ def test_run_glows_l3be_against_prod(self):
             format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
         )
 
-        imap_data_access.config["DATA_DIR"] = get_run_local_data_path(
-            "glows_l3bcde_prod"
-        )
+        imap_data_access.config["DATA_DIR"] = get_run_local_data_path("glows_l3bcde_prod")
 
         test_reprocessing_file = get_test_data_path(
             "glows/imap_glows_force-reprocessing-config_20250101_v000.csv"
@@ -839,9 +784,7 @@ def test_run_glows_l3be_against_prod(self):
 
         # Nothing is uploaded, so reruns compute the same output names as earlier local runs; overwrite them
         with (
-            patch(
-                "imap_l3_data_processor._parse_cli_arguments"
-            ) as mock_parse_cli_arguments,
+            patch("imap_l3_data_processor._parse_cli_arguments") as mock_parse_cli_arguments,
             patch(
                 "imap_l3_processing.glows.glows_processor.save_data",
                 side_effect=partial(save_data, delete_if_present=True),
@@ -873,86 +816,72 @@ def _fill_official_l2_cdf_with_json_values(output_folder: Path) -> Path:
         new_file_path = output_folder / official_l2_path.name
         new_file_path.unlink(missing_ok=True)
 
+        with open(json_file_path) as f:
+            instrument_data = json.load(f)
         with CDF(str(new_file_path), masterpath=str(official_l2_path)) as cdf:
-            with open(json_file_path) as f:
-                instrument_data = json.load(f)
+            start_of_epoch_window = datetime.fromisoformat(instrument_data["start_time"])
+            end_of_epoch_window = datetime.fromisoformat(instrument_data["end_time"])
+            epoch_window = end_of_epoch_window - start_of_epoch_window
+            epoch = start_of_epoch_window + epoch_window / 2
+
+            cdf["epoch"][0] = epoch
+            cdf["start_time"][0] = instrument_data["start_time"]
+            cdf["end_time"][0] = instrument_data["end_time"]
+
+            lightcurve_vars = [
+                "spin_angle",
+                "photon_flux",
+                "exposure_times",
+                "flux_uncertainties",
+                "ecliptic_lon",
+                "ecliptic_lat",
+            ]
+            for var in lightcurve_vars:
+                cdf[var] = np.array(instrument_data["daily_lightcurve"][var])[np.newaxis, :]
 
-                start_of_epoch_window = datetime.fromisoformat(
-                    instrument_data["start_time"]
-                )
-                end_of_epoch_window = datetime.fromisoformat(
-                    instrument_data["end_time"]
-                )
-                epoch_window = end_of_epoch_window - start_of_epoch_window
-                epoch = start_of_epoch_window + epoch_window / 2
-
-                cdf["epoch"][0] = epoch
-                cdf["start_time"][0] = instrument_data["start_time"]
-                cdf["end_time"][0] = instrument_data["end_time"]
-
-                lightcurve_vars = [
-                    "spin_angle",
-                    "photon_flux",
-                    "exposure_times",
-                    "flux_uncertainties",
-                    "ecliptic_lon",
-                    "ecliptic_lat",
-                ]
-                for var in lightcurve_vars:
-                    cdf[var] = np.array(instrument_data["daily_lightcurve"][var])[
-                        np.newaxis, :
-                    ]
-
-                cdf["raw_histograms"] = np.array(
-                    instrument_data["daily_lightcurve"]["raw_histogram"]
-                )[np.newaxis, :]
-                cdf["histogram_flag_array"] = np.array(
-                    [
-                        int(f, 16)
-                        for f in instrument_data["daily_lightcurve"][
-                            "histogram_flag_array"
-                        ]
-                    ]
-                )[np.newaxis, :]
-
-                single_value_vars = [
-                    "filter_temperature_average",
-                    "filter_temperature_std_dev",
-                    "hv_voltage_average",
-                    "hv_voltage_std_dev",
-                    "spin_period_average",
-                    "spin_period_std_dev",
-                    "pulse_length_average",
-                    "pulse_length_std_dev",
-                    "spin_period_ground_average",
-                    "spin_period_ground_std_dev",
-                    "position_angle_offset_average",
-                    "position_angle_offset_std_dev",
-                    "identifier",
-                ]
-                for var in single_value_vars:
-                    cdf[var][0] = instrument_data[var]
-
-                vector_vars = [
-                    "spacecraft_location_average",
-                    "spacecraft_location_std_dev",
-                    "spacecraft_velocity_average",
-                    "spacecraft_velocity_std_dev",
-                    "spin_axis_orientation_average",
-                    "spin_axis_orientation_std_dev",
-                ]
-                for var in vector_vars:
-                    cdf[var][0] = np.array(list(instrument_data[var].values()))
+            cdf["raw_histograms"] = np.array(instrument_data["daily_lightcurve"]["raw_histogram"])[
+                np.newaxis, :
+            ]
+            cdf["histogram_flag_array"] = np.array(
+                [int(f, 16) for f in instrument_data["daily_lightcurve"]["histogram_flag_array"]]
+            )[np.newaxis, :]
+
+            single_value_vars = [
+                "filter_temperature_average",
+                "filter_temperature_std_dev",
+                "hv_voltage_average",
+                "hv_voltage_std_dev",
+                "spin_period_average",
+                "spin_period_std_dev",
+                "pulse_length_average",
+                "pulse_length_std_dev",
+                "spin_period_ground_average",
+                "spin_period_ground_std_dev",
+                "position_angle_offset_average",
+                "position_angle_offset_std_dev",
+                "identifier",
+            ]
+            for var in single_value_vars:
+                cdf[var][0] = instrument_data[var]
+
+            vector_vars = [
+                "spacecraft_location_average",
+                "spacecraft_location_std_dev",
+                "spacecraft_velocity_average",
+                "spacecraft_velocity_std_dev",
+                "spin_axis_orientation_average",
+                "spin_axis_orientation_std_dev",
+            ]
+            for var in vector_vars:
+                cdf[var][0] = np.array(list(instrument_data[var].values()))
 
-                cdf["bad_time_flag_occurrences"][0] = list(
-                    instrument_data["bad_time_flag_occurences"].values()
-                )
-                cdf["number_of_good_l1b_inputs"][0] = instrument_data["header"][
-                    "number_of_l1b_files_used"
-                ]
-                cdf["total_l1b_inputs"][0] = instrument_data["header"][
-                    "number_of_all_l1b_files"
-                ]
+            cdf["bad_time_flag_occurrences"][0] = list(
+                instrument_data["bad_time_flag_occurences"].values()
+            )
+            cdf["number_of_good_l1b_inputs"][0] = instrument_data["header"][
+                "number_of_l1b_files_used"
+            ]
+            cdf["total_l1b_inputs"][0] = instrument_data["header"]["number_of_all_l1b_files"]
 
         return new_file_path
 
diff --git a/tests/integration/test_hit_processor_integration.py b/tests/integration/test_hit_processor_integration.py
index a6cf7948..8bc3be2e 100644
--- a/tests/integration/test_hit_processor_integration.py
+++ b/tests/integration/test_hit_processor_integration.py
@@ -1,25 +1,23 @@
 import logging
 import unittest
-from unittest.mock import patch, Mock
+from unittest.mock import Mock, patch
 
 from imap_data_access.processing_input import (
     ProcessingInputCollection,
-    generate_imap_input,
     ScienceFilePath,
+    generate_imap_input,
 )
 
 import imap_l3_data_processor
 from tests.integration.integration_test_helpers import mock_imap_data_access
-from tests.test_helpers import get_test_data_path, get_run_local_data_path
+from tests.test_helpers import get_run_local_data_path, get_test_data_path
 
 
 class HitProcessorIntegration(unittest.TestCase):
     @patch("imap_l3_data_processor._parse_cli_arguments")
     def test_hit_macropixel_product(self, mock_parse_cli_arguments):
         input_files = [
-            get_test_data_path(
-                "hit/imap_hit_l2_macropixel-intensity_20260228_v001.0002.cdf"
-            ),
+            get_test_data_path("hit/imap_hit_l2_macropixel-intensity_20260228_v001.0002.cdf"),
             get_test_data_path("hit/imap_mag_l1d_norm-dsrf_20260228_v005.cdf"),
             get_test_data_path("hit/imap_mag_l2_norm-dsrf_20260228_v002.cdf"),
         ]
diff --git a/tests/integration/test_map_processor_integration.py b/tests/integration/test_map_processor_integration.py
index 983c9369..b6f1e62b 100644
--- a/tests/integration/test_map_processor_integration.py
+++ b/tests/integration/test_map_processor_integration.py
@@ -3,11 +3,10 @@
 import unittest
 from datetime import timedelta
 from pathlib import Path
-from unittest.mock import patch, Mock
+from unittest.mock import Mock, patch
 
 import numpy as np
-from imap_data_access import ProcessingInputCollection, ScienceInput
-from imap_data_access import ScienceFilePath
+from imap_data_access import ProcessingInputCollection, ScienceFilePath, ScienceInput
 from spacepy.pycdf import CDF
 from spiceypy import spiceypy
 
@@ -16,8 +15,8 @@
 from tests.integration.integration_test_helpers import mock_imap_data_access
 from tests.test_helpers import (
     get_run_local_data_path,
-    run_periodically,
     get_test_data_path,
+    run_periodically,
 )
 
 INTEGRATION_TEST_DATA_PATH = Path(__file__).parent / "test_data"
@@ -39,13 +38,9 @@ def test_lo_l3_multiple_arcs(self, mock_parse_cli_arguments):
             INTEGRATION_TEST_DATA_PATH / "spice" / "naif020.tls",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_science_108.tf",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_sclk_008.tsc",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_dps_2025_105_2026_105_009.ah.bc",
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_dps_2025_105_2026_105_009.ah.bc",
             INTEGRATION_TEST_DATA_PATH / "spice" / "de440.bsp",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_recon_20250415_20260415_v01.bsp",
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_recon_20250415_20260415_v01.bsp",
         ]
 
         with mock_imap_data_access(lo_imap_data_dir, input_files):
@@ -154,13 +149,9 @@ def test_hi_all_sp_maps_single_sensor(self, mock_parse_cli_arguments):
             INTEGRATION_TEST_DATA_PATH / "spice" / "naif020.tls",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_science_108.tf",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_sclk_008.tsc",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_dps_2025_105_2026_105_009.ah.bc",
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_dps_2025_105_2026_105_009.ah.bc",
             INTEGRATION_TEST_DATA_PATH / "spice" / "de440.bsp",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_recon_20250415_20260415_v01.bsp",
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_recon_20250415_20260415_v01.bsp",
         ]
 
         with mock_imap_data_access(hi_imap_data_dir, input_files):
@@ -303,9 +294,7 @@ def test_hi_combined_sensor(self, mock_parse_cli_arguments):
             "imap_hi_l2_h90-ena-h-hf-nsp-ram-hae-6deg-1yr_20250415_v000.cdf",
         ]
 
-        input_files = [
-            hi_test_data_dir / "combined" / f for f in [*sp_files, *nsp_files]
-        ]
+        input_files = [hi_test_data_dir / "combined" / f for f in [*sp_files, *nsp_files]]
 
         with mock_imap_data_access(hi_imap_data_dir, input_files):
             logging.basicConfig(
@@ -366,10 +355,8 @@ def test_lo_all_sp_maps(self, mock_parse_cli_arguments):
         lo_imap_data_dir = get_run_local_data_path("lo/integration_data")
 
         input_files = [
-            lo_test_data_dir
-            / "imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-1yr_20260101_v900.cdf",
-            lo_test_data_dir
-            / "imap_lo_l2_l090-ena-h-hf-nsp-ram-hae-6deg-1yr_20260101_v900.cdf",
+            lo_test_data_dir / "imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-1yr_20260101_v900.cdf",
+            lo_test_data_dir / "imap_lo_l2_l090-ena-h-hf-nsp-ram-hae-6deg-1yr_20260101_v900.cdf",
             get_test_data_path("lo/imap_lo_l1c_pset_20260101-repoint01261_v001.cdf"),
             lo_test_data_dir
             / "imap_glows_l3e_survival-probability-lo_20260101-repoint01261_v001.cdf",
@@ -378,13 +365,9 @@ def test_lo_all_sp_maps(self, mock_parse_cli_arguments):
             INTEGRATION_TEST_DATA_PATH / "spice" / "naif020.tls",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_science_108.tf",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_sclk_008.tsc",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_dps_2025_105_2026_105_009.ah.bc",
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_dps_2025_105_2026_105_009.ah.bc",
             INTEGRATION_TEST_DATA_PATH / "spice" / "de440.bsp",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_recon_20250415_20260415_v01.bsp",
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_recon_20250415_20260415_v01.bsp",
         ]
 
         with mock_imap_data_access(lo_imap_data_dir, input_files):
@@ -447,17 +430,11 @@ def test_lo_isn_maps(self, mock_parse_cli_arguments):
         lo_test_data_dir = INTEGRATION_TEST_DATA_PATH / "lo"
         lo_imap_data_dir = get_run_local_data_path("lo/integration_data")
 
-        input_file = (
-            "imap_lo_l2_l090-enanbs-h-sf-nsp-ram-hae-6deg-1yr_20250415_v000.cdf"
-        )
+        input_file = "imap_lo_l2_l090-enanbs-h-sf-nsp-ram-hae-6deg-1yr_20250415_v000.cdf"
         descriptor = "l090-isn-h-sf-nsp-ram-hae-6deg-1yr"
-        expected_output_file = (
-            "imap_lo_l3_l090-isn-h-sf-nsp-ram-hae-6deg-1yr_20250415_v001.cdf"
-        )
+        expected_output_file = "imap_lo_l3_l090-isn-h-sf-nsp-ram-hae-6deg-1yr_20250415_v001.cdf"
 
-        processing_input_collection = ProcessingInputCollection(
-            ScienceInput(input_file)
-        )
+        processing_input_collection = ProcessingInputCollection(ScienceInput(input_file))
 
         with mock_imap_data_access(lo_imap_data_dir, [lo_test_data_dir / input_file]):
             logging.basicConfig(
@@ -514,12 +491,8 @@ def test_ultra_all_sp_maps(self, mock_parse_cli_arguments):
             INTEGRATION_TEST_DATA_PATH / "spice" / "naif020.tls",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_science_108.tf",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_sclk_008.tsc",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_dps_2025_105_2026_105_009.ah.bc",
-            get_test_data_path(
-                "ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"
-            ),
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_dps_2025_105_2026_105_009.ah.bc",
+            get_test_data_path("ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"),
         ]
 
         with mock_imap_data_access(ultra_imap_data_dir, input_files):
@@ -571,26 +544,16 @@ def test_ultra_combined_sp_maps(self, mock_parse_cli_arguments):
             INTEGRATION_TEST_DATA_PATH / "spice" / "naif020.tls",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_science_108.tf",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_sclk_008.tsc",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_dps_2025_105_2026_105_009.ah.bc",
-            get_test_data_path(
-                "ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"
-            ),
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_dps_2025_105_2026_105_009.ah.bc",
+            get_test_data_path("ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"),
         ]
         input_files = [
-            ultra_path
-            / "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
-            ultra_path
-            / "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
-            ultra_path
-            / "imap_ultra_l1c_45sensor-heliopset_20250416-repoint00000_v000.cdf",
-            ultra_path
-            / "imap_ultra_l1c_45sensor-heliopset_20251017-repoint00184_v000.cdf",
-            ultra_path
-            / "imap_ultra_l1c_90sensor-heliopset_20250416-repoint00000_v000.cdf",
-            ultra_path
-            / "imap_ultra_l1c_90sensor-heliopset_20251017-repoint00184_v000.cdf",
+            ultra_path / "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
+            ultra_path / "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
+            ultra_path / "imap_ultra_l1c_45sensor-heliopset_20250416-repoint00000_v000.cdf",
+            ultra_path / "imap_ultra_l1c_45sensor-heliopset_20251017-repoint00184_v000.cdf",
+            ultra_path / "imap_ultra_l1c_90sensor-heliopset_20250416-repoint00000_v000.cdf",
+            ultra_path / "imap_ultra_l1c_90sensor-heliopset_20251017-repoint00184_v000.cdf",
             ultra_path
             / "imap_glows_l3e_survival-probability-ul-hf_20250415-repoint00000_v001.cdf",
             ultra_path
@@ -647,26 +610,16 @@ def test_ultra_combined_nsp_maps(self, mock_parse_cli_arguments):
             INTEGRATION_TEST_DATA_PATH / "spice" / "naif020.tls",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_science_108.tf",
             INTEGRATION_TEST_DATA_PATH / "spice" / "imap_sclk_008.tsc",
-            INTEGRATION_TEST_DATA_PATH
-            / "spice"
-            / "imap_dps_2025_105_2026_105_009.ah.bc",
-            get_test_data_path(
-                "ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"
-            ),
+            INTEGRATION_TEST_DATA_PATH / "spice" / "imap_dps_2025_105_2026_105_009.ah.bc",
+            get_test_data_path("ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"),
         ]
         input_files = [
-            ultra_path
-            / "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
-            ultra_path
-            / "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
-            ultra_path
-            / "imap_ultra_l1c_45sensor-heliopset_20250416-repoint00000_v000.cdf",
-            ultra_path
-            / "imap_ultra_l1c_45sensor-heliopset_20251017-repoint00184_v000.cdf",
-            ultra_path
-            / "imap_ultra_l1c_90sensor-heliopset_20250416-repoint00000_v000.cdf",
-            ultra_path
-            / "imap_ultra_l1c_90sensor-heliopset_20251017-repoint00184_v000.cdf",
+            ultra_path / "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
+            ultra_path / "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-6deg-3mo_20250416_v001.cdf",
+            ultra_path / "imap_ultra_l1c_45sensor-heliopset_20250416-repoint00000_v000.cdf",
+            ultra_path / "imap_ultra_l1c_45sensor-heliopset_20251017-repoint00184_v000.cdf",
+            ultra_path / "imap_ultra_l1c_90sensor-heliopset_20250416-repoint00000_v000.cdf",
+            ultra_path / "imap_ultra_l1c_90sensor-heliopset_20251017-repoint00184_v000.cdf",
         ]
 
         with mock_imap_data_access(ultra_imap_data_dir, input_files + ancil_files):
diff --git a/tests/integration/test_swapi_processor_integration.py b/tests/integration/test_swapi_processor_integration.py
index 3d250df9..b0da8905 100644
--- a/tests/integration/test_swapi_processor_integration.py
+++ b/tests/integration/test_swapi_processor_integration.py
@@ -13,6 +13,7 @@
 would just be duplicate data.
 """
 
+import datetime
 import os
 import subprocess
 import sys
@@ -25,7 +26,6 @@
 import numpy.testing
 from imap_data_access import ScienceFilePath
 from spacepy.pycdf import CDF
-import datetime
 
 import imap_l3_processing
 from imap_l3_processing.swapi.constants import SWAPI_COARSE_SWEEP_BINS
@@ -122,6 +122,7 @@ def test_proton_sw_with_production_data(self):
                 "--dependency",
                 dependency_filename,
             ],
+            check=False,
             env={**os.environ, "IMAP_DATA_DIR": str(data_dir)},
         )
 
@@ -131,7 +132,7 @@ def test_proton_sw_with_production_data(self):
         bulk_speed_atol = 1e-3 * float(expected_values["proton_sw_speed"])
 
         with CDF(str(expected_file_path)) as cdf:
-            for key in expected_values.keys():
+            for key, expected_value in expected_values.items():
                 actual_value = cdf[key][0]
                 if key.endswith("_uncert"):
                     rtol, atol = 1e-2, 0.0
@@ -142,13 +143,13 @@ def test_proton_sw_with_production_data(self):
                 try:
                     numpy.testing.assert_allclose(
                         actual_value,
-                        expected_values[key],
+                        expected_value,
                         rtol=rtol,
                         atol=atol,
                         err_msg=key,
                     )
                 except TypeError:
-                    self.assertEqual(expected_values[key], actual_value, msg=key)
+                    self.assertEqual(expected_value, actual_value, msg=key)
 
     @skipUnless(os.environ.get("IMAP_API_KEY"), "requires production API key")
     def test_alpha_sw_with_production_data(self):
@@ -242,6 +243,7 @@ def test_alpha_sw_with_production_data(self):
                 "--dependency",
                 dependency_filename,
             ],
+            check=False,
             env={**os.environ, "IMAP_DATA_DIR": str(data_dir)},
         )
 
@@ -251,7 +253,7 @@ def test_alpha_sw_with_production_data(self):
         bulk_speed_atol = 1e-3 * float(expected_values["alpha_sw_speed"])
 
         with CDF(str(expected_file_path)) as cdf:
-            for key in expected_values.keys():
+            for key, expected_value in expected_values.items():
                 actual_value = cdf[key][sample_index]
                 if key.endswith("_uncert"):
                     rtol, atol = 3e-2, 0.0
@@ -262,13 +264,13 @@ def test_alpha_sw_with_production_data(self):
                 try:
                     numpy.testing.assert_allclose(
                         actual_value,
-                        expected_values[key],
+                        expected_value,
                         rtol=rtol,
                         atol=atol,
                         err_msg=key,
                     )
                 except TypeError:
-                    self.assertEqual(expected_values[key], actual_value, msg=key)
+                    self.assertEqual(expected_value, actual_value, msg=key)
 
     @skipUnless(os.environ.get("IMAP_API_KEY"), "requires production API key")
     def test_pui_he_with_production_data(self):
@@ -324,6 +326,7 @@ def test_pui_he_with_production_data(self):
                 "--dependency",
                 dependency_filename,
             ],
+            check=False,
             env={**os.environ, "IMAP_DATA_DIR": str(data_dir)},
         )
 
@@ -331,7 +334,7 @@ def test_pui_he_with_production_data(self):
         self.assertTrue(expected_file_path.exists())
 
         with CDF(str(expected_file_path)) as cdf:
-            for key in expected_values.keys():
+            for key, expected_value in expected_values.items():
                 actual_value = cdf[key][sample_index]
                 if key.endswith("_uncert"):
                     rtol, atol = 1e-2, 0.0
@@ -340,13 +343,13 @@ def test_pui_he_with_production_data(self):
                 try:
                     numpy.testing.assert_allclose(
                         actual_value,
-                        expected_values[key],
+                        expected_value,
                         rtol=rtol,
                         atol=atol,
                         err_msg=key,
                     )
                 except TypeError:
-                    self.assertEqual(expected_values[key], actual_value, msg=key)
+                    self.assertEqual(expected_value, actual_value, msg=key)
 
     @skipUnless(os.environ.get("IMAP_API_KEY"), "requires production API key")
     def test_l3b_with_production_data(self):
@@ -385,22 +388,21 @@ def test_l3b_with_production_data(self):
                 "--dependency",
                 dependency_filename,
             ],
+            check=False,
             env={**os.environ, "IMAP_DATA_DIR": str(data_dir)},
         )
 
         self.assertEqual(0, result.returncode)
         self.assertTrue(expected_file_path.exists())
 
-        l2_file_path = ScienceFilePath(
-            "imap_swapi_l2_sci_20260101_v001.0001.cdf"
-        ).construct_path()
+        l2_file_path = ScienceFilePath("imap_swapi_l2_sci_20260101_v001.0001.cdf").construct_path()
         self.assertTrue(l2_file_path.exists())
 
         with CDF(str(l2_file_path)) as l2_cdf, CDF(str(expected_file_path)) as l3b_cdf:
             print(l3b_cdf.keys())
-            l2_coincidence_rate = l2_cdf["swp_coin_rate"][
-                :50, SWAPI_COARSE_SWEEP_BINS
-            ].mean(axis=0)
+            l2_coincidence_rate = l2_cdf["swp_coin_rate"][:50, SWAPI_COARSE_SWEEP_BINS].mean(
+                axis=0
+            )
             combined_differential_flux = l3b_cdf["combined_differential_flux"][0]
 
             geometric_factor = l2_coincidence_rate / combined_differential_flux
diff --git a/tests/integration/test_swe_processor_integration.py b/tests/integration/test_swe_processor_integration.py
index 7f0f3f6f..3f6ed015 100644
--- a/tests/integration/test_swe_processor_integration.py
+++ b/tests/integration/test_swe_processor_integration.py
@@ -12,9 +12,9 @@
 import imap_l3_processing
 from tests.integration.integration_test_helpers import mock_imap_data_access
 from tests.test_helpers import (
+    get_integration_test_data_path,
     get_run_local_data_path,
     get_test_data_path,
-    get_integration_test_data_path,
     run_periodically,
 )
 
@@ -64,6 +64,7 @@ def test_swe_processor_with_local_data(self):
                     "--dependency",
                     "imap_swe_l3_sci-9ad0ccff_20260120_v009.json",
                 ],
+                check=False,
             )
 
             expected_file_path = ScienceFilePath(
diff --git a/tests/lo/l3/test_lo_combined_dependencies.py b/tests/lo/l3/test_lo_combined_dependencies.py
index 07c28513..1617f13e 100644
--- a/tests/lo/l3/test_lo_combined_dependencies.py
+++ b/tests/lo/l3/test_lo_combined_dependencies.py
@@ -1,7 +1,7 @@
 import unittest
-from unittest.mock import sentinel, call, patch
+from unittest.mock import call, patch, sentinel
 
-from imap_data_access import ScienceInput, ProcessingInputCollection
+from imap_data_access import ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.lo.l3.lo_combined_dependencies import LoCombinedDependencies
 
@@ -10,9 +10,7 @@ class TestLoCombinedDependencies(unittest.TestCase):
     @patch(
         "imap_l3_processing.lo.l3.lo_combined_dependencies.RectangularIntensityMapData.read_from_path"
     )
-    @patch(
-        "imap_l3_processing.lo.l3.lo_combined_dependencies.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.lo.l3.lo_combined_dependencies.imap_data_access.download")
     def test_fetch_dependencies(self, mock_download, mock_read_from_path):
         lo75_input = "imap_lo_l3_l075-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"
         lo90_input = "imap_lo_l3_l090-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"
@@ -28,9 +26,7 @@ def test_fetch_dependencies(self, mock_download, mock_read_from_path):
         )
         dependencies = LoCombinedDependencies.fetch_dependencies(inputs)
 
-        mock_download.assert_has_calls(
-            [call(lo75_input), call(lo90_input), call(lo105_input)]
-        )
+        mock_download.assert_has_calls([call(lo75_input), call(lo90_input), call(lo105_input)])
 
         mock_read_from_path.assert_called_with(mock_download.return_value)
         self.assertEqual(mock_lo_map_data, dependencies.map_data)
diff --git a/tests/lo/l3/test_lo_l3_isn_background_subtracted_dependencies.py b/tests/lo/l3/test_lo_l3_isn_background_subtracted_dependencies.py
index ec6dd9b9..9a69ea56 100644
--- a/tests/lo/l3/test_lo_l3_isn_background_subtracted_dependencies.py
+++ b/tests/lo/l3/test_lo_l3_isn_background_subtracted_dependencies.py
@@ -1,7 +1,7 @@
 import unittest
 from unittest.mock import patch
 
-from imap_data_access.processing_input import ScienceInput, ProcessingInputCollection
+from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.lo.l3.lo_l3_isn_background_subtracted_dependencies import (
     LoL3ISNBackgroundSubtractedDependencies,
@@ -12,13 +12,9 @@ class TestLoL3ISNBackgroundSubtractedDependencies(unittest.TestCase):
     @patch(
         "imap_l3_processing.lo.l3.lo_l3_isn_background_subtracted_dependencies.ISNRateData.read_from_path"
     )
-    @patch(
-        "imap_l3_processing.lo.l3.lo_l3_isn_background_subtracted_dependencies.download"
-    )
+    @patch("imap_l3_processing.lo.l3.lo_l3_isn_background_subtracted_dependencies.download")
     def test_fetch_dependencies(self, mock_download, mock_read_from_path):
-        file_name = (
-            "imap_lo_l2_l090-isnnbkgnd-h-sf-nsp-ram-hae-6deg-1yr_20250422_v001.cdf"
-        )
+        file_name = "imap_lo_l2_l090-isnnbkgnd-h-sf-nsp-ram-hae-6deg-1yr_20250422_v001.cdf"
         input = ScienceInput(file_name)
         processing_input_collection = ProcessingInputCollection(input)
 
diff --git a/tests/lo/l3/test_lo_l3_spectral_fit_dependencies.py b/tests/lo/l3/test_lo_l3_spectral_fit_dependencies.py
index bf1eea77..6deb59bc 100644
--- a/tests/lo/l3/test_lo_l3_spectral_fit_dependencies.py
+++ b/tests/lo/l3/test_lo_l3_spectral_fit_dependencies.py
@@ -1,7 +1,7 @@
 import unittest
 from unittest.mock import patch
 
-from imap_data_access.processing_input import ScienceInput, ProcessingInputCollection
+from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.lo.l3.lo_l3_spectral_fit_dependencies import (
     LoL3SpectralFitDependencies,
@@ -25,14 +25,10 @@ def test_fetch_dependencies(self, mock_download, mock_read_from_path):
 
                 input_deps = ProcessingInputCollection(ena_input, *extra_inputs)
 
-                dependencies = LoL3SpectralFitDependencies.fetch_dependencies(
-                    input_deps
-                )
+                dependencies = LoL3SpectralFitDependencies.fetch_dependencies(input_deps)
 
                 mock_download.assert_called_once_with(file_name)
-                self.assertEqual(
-                    dependencies.map_data, mock_read_from_path.return_value
-                )
+                self.assertEqual(dependencies.map_data, mock_read_from_path.return_value)
 
                 mock_read_from_path.assert_called_with(mock_download.return_value)
 
@@ -50,15 +46,11 @@ def test_raises_error_if_unexpected_number_of_files(self):
             ),
             (
                 "1 L2 and 1 L3 file",
-                ProcessingInputCollection(
-                    ScienceInput(l2_file_name), ScienceInput(l3_file_name)
-                ),
+                ProcessingInputCollection(ScienceInput(l2_file_name), ScienceInput(l3_file_name)),
             ),
             (
                 "2 L2 files",
-                ProcessingInputCollection(
-                    ScienceInput(l2_file_name), ScienceInput(l2_file_name)
-                ),
+                ProcessingInputCollection(ScienceInput(l2_file_name), ScienceInput(l2_file_name)),
             ),
         ]
 
diff --git a/tests/lo/l3/test_lo_sp_initializer.py b/tests/lo/l3/test_lo_sp_initializer.py
index f2510cb9..d5474caa 100644
--- a/tests/lo/l3/test_lo_sp_initializer.py
+++ b/tests/lo/l3/test_lo_sp_initializer.py
@@ -1,14 +1,14 @@
 import unittest
 from datetime import datetime
-from unittest.mock import patch, call
+from unittest.mock import call, patch
 
 from imap_data_access.file_validation import Version
 
 from imap_l3_processing.lo.l3.lo_sp_initializer import (
-    LoSPInitializer,
     LO_SP_MAP_KERNELS,
+    LoSPInitializer,
 )
-from imap_l3_processing.maps.map_initializer import PossibleMapToProduce, MapInitializer
+from imap_l3_processing.maps.map_initializer import MapInitializer, PossibleMapToProduce
 from imap_l3_processing.models import InputMetadata, VersionMap
 from tests.integration.integration_test_helpers import ImapQueryPatcher
 
@@ -91,9 +91,7 @@ def test_get_maps_that_should_be_produced(self, mock_read_cdf_parents):
 
         initializer = LoSPInitializer()
         descriptor = "l090-ena-h-sf-sp-ram-hae-6deg-12mo"
-        actual_maps_to_produce = initializer.get_maps_that_should_be_produced(
-            descriptor, 3
-        )
+        actual_maps_to_produce = initializer.get_maps_that_should_be_produced(descriptor, 3)
 
         self.mock_query.assert_has_calls(
             [
@@ -110,24 +108,12 @@ def test_get_maps_that_should_be_produced(self, mock_read_cdf_parents):
 
         mock_read_cdf_parents.assert_has_calls(
             [
-                call(
-                    "imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20100101_v001.cdf"
-                ),
-                call(
-                    "imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20100401_v001.cdf"
-                ),
-                call(
-                    "imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20100701_v001.cdf"
-                ),
-                call(
-                    "imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20101001_v001.cdf"
-                ),
-                call(
-                    "imap_lo_l3_l090-ena-h-sf-sp-ram-hae-6deg-12mo_20100101_v003.0001.cdf"
-                ),
-                call(
-                    "imap_lo_l3_l090-ena-h-sf-sp-ram-hae-6deg-12mo_20100401_v003.0001.cdf"
-                ),
+                call("imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20100101_v001.cdf"),
+                call("imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20100401_v001.cdf"),
+                call("imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20100701_v001.cdf"),
+                call("imap_lo_l2_l090-ena-h-sf-nsp-ram-hae-6deg-12mo_20101001_v001.cdf"),
+                call("imap_lo_l3_l090-ena-h-sf-sp-ram-hae-6deg-12mo_20100101_v003.0001.cdf"),
+                call("imap_lo_l3_l090-ena-h-sf-sp-ram-hae-6deg-12mo_20100401_v003.0001.cdf"),
             ]
         )
 
diff --git a/tests/lo/test_lo_processor.py b/tests/lo/test_lo_processor.py
index 29ffd10a..99dd0806 100644
--- a/tests/lo/test_lo_processor.py
+++ b/tests/lo/test_lo_processor.py
@@ -10,12 +10,12 @@
 from imap_l3_processing.lo.l3.lo_combined_dependencies import LoCombinedDependencies
 from imap_l3_processing.lo.lo_processor import LoProcessor, isn_background_subtraction
 from imap_l3_processing.maps.map_models import (
-    RectangularSpectralIndexDataProduct,
-    RectangularIntensityDataProduct,
     InputRectangularPointingSet,
-    ISNRateData,
     ISNBackgroundSubtractedData,
     ISNBackgroundSubtractedMapData,
+    ISNRateData,
+    RectangularIntensityDataProduct,
+    RectangularSpectralIndexDataProduct,
 )
 from imap_l3_processing.models import InputMetadata, Instrument
 from tests.maps import test_builders
@@ -24,9 +24,7 @@
 class TestLoProcessor(unittest.TestCase):
     @patch("imap_l3_processing.hi.hi_processor.MapProcessor.get_parent_file_names")
     @patch("imap_l3_processing.lo.lo_processor.slice_energy_range_by_bin")
-    @patch(
-        "imap_l3_processing.lo.lo_processor.LoL3SpectralFitDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.lo.lo_processor.LoL3SpectralFitDependencies.fetch_dependencies")
     @patch("imap_l3_processing.lo.lo_processor.fit_spectral_index_map")
     @patch("imap_l3_processing.lo.lo_processor.save_data")
     def test_process_spectral_index(
@@ -76,18 +74,14 @@ def test_process_spectral_index(
             data_product.data.spectral_index_map_data,
             mock_fit_spectral_index_map.return_value,
         )
-        self.assertEqual(
-            data_product.data.coords, lo_l3_spectral_fit_dependency.map_data.coords
-        )
+        self.assertEqual(data_product.data.coords, lo_l3_spectral_fit_dependency.map_data.coords)
         self.assertEqual(data_product.input_metadata, processor.input_metadata)
         self.assertEqual(data_product.parent_file_names, ["some_input_file_name"])
         self.assertEqual(data_product.spice_frame_name, SpiceFrame.ECLIPJ2000)
         self.assertEqual([mock_save_data.return_value], product)
 
     @patch("imap_l3_processing.hi.hi_processor.MapProcessor.get_parent_file_names")
-    @patch(
-        "imap_l3_processing.lo.lo_processor.LoL3SpectralFitDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.lo.lo_processor.LoL3SpectralFitDependencies.fetch_dependencies")
     @patch("imap_l3_processing.lo.lo_processor.fit_spectral_index_map")
     @patch("imap_l3_processing.lo.lo_processor.save_data")
     @patch("imap_l3_processing.lo.lo_processor.slice_energy_range_by_bin")
@@ -117,8 +111,8 @@ def test_process_spectral_index_with_range_specified(
 
                 input_collection = Mock()
                 lo_l3_spectral_fit_dependency = mock_fetch_dependencies.return_value
-                lo_l3_spectral_fit_dependency.map_data.intensity_map_data.energy = (
-                    np.array([1, 10, 1000, 10000, 100000, 1000000, 10000000])
+                lo_l3_spectral_fit_dependency.map_data.intensity_map_data.energy = np.array(
+                    [1, 10, 1000, 10000, 100000, 1000000, 10000000]
                 )
 
                 metadata = InputMetadata(
@@ -157,15 +151,11 @@ def test_process_spectral_index_with_range_specified(
                 )
                 self.assertEqual(data_product.input_metadata, processor.input_metadata)
                 self.assertEqual(data_product.spice_frame_name, SpiceFrame.ECLIPJ2000)
-                self.assertEqual(
-                    data_product.parent_file_names, ["some_input_file_name"]
-                )
+                self.assertEqual(data_product.parent_file_names, ["some_input_file_name"])
                 self.assertEqual([mock_save_data.return_value], product)
 
     @patch("imap_l3_processing.lo.lo_processor.MapProcessor.get_parent_file_names")
-    @patch(
-        "imap_l3_processing.lo.lo_processor.HiLoL3SurvivalDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.lo.lo_processor.HiLoL3SurvivalDependencies.fetch_dependencies")
     @patch("imap_l3_processing.lo.lo_processor.process_survival_probabilities")
     @patch("imap_l3_processing.lo.lo_processor.save_data")
     def test_process_survival_probabilities(
@@ -208,9 +198,7 @@ def test_process_survival_probabilities(
                 )
                 mock_fetch_survival_dependencies.return_value = dependencies
 
-                mock_process_survival_prob.return_value = (
-                    sentinel.survival_probabilities
-                )
+                mock_process_survival_prob.return_value = sentinel.survival_probabilities
 
                 processor = LoProcessor(sentinel.input_dependencies, input_metadata)
                 product = processor.process(spice_frame_name=SpiceFrame.IMAP_DPS)
@@ -241,9 +229,7 @@ def test_process_survival_probabilities(
                 mock_process_survival_prob.reset_mock()
                 mock_save_data.reset_mock()
 
-    @patch(
-        "imap_l3_processing.lo.lo_processor.LoCombinedDependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.lo.lo_processor.LoCombinedDependencies.fetch_dependencies")
     @patch("imap_l3_processing.lo.lo_processor.ExposureWeightedCombination")
     @patch("imap_l3_processing.lo.lo_processor.save_data")
     def test_process_lo_combined(
@@ -253,9 +239,7 @@ def test_process_lo_combined(
         mock_fetch_combined_dependencies,
     ):
 
-        mock_exposure_weighted_combination = (
-            mock_exposure_weighted_combination_class.return_value
-        )
+        mock_exposure_weighted_combination = mock_exposure_weighted_combination_class.return_value
 
         input_metadata = InputMetadata(
             instrument="lo",
@@ -271,32 +255,20 @@ def test_process_lo_combined(
         )
 
         processing_input = ProcessingInputCollection(
-            ScienceInput(
-                "imap_lo_l3_l075-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"
-            ),
-            ScienceInput(
-                "imap_lo_l3_l090-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"
-            ),
-            ScienceInput(
-                "imap_lo_l3_l105-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"
-            ),
+            ScienceInput("imap_lo_l3_l075-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"),
+            ScienceInput("imap_lo_l3_l090-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"),
+            ScienceInput("imap_lo_l3_l105-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf"),
         )
 
         lo_processor = LoProcessor(processing_input, input_metadata)
 
-        [combined_product] = lo_processor.process(
-            spice_frame_name=SpiceFrame.ECLIPJ2000
-        )
+        [combined_product] = lo_processor.process(spice_frame_name=SpiceFrame.ECLIPJ2000)
 
         mock_fetch_combined_dependencies.assert_called_once_with(processing_input)
 
-        mock_combine = (
-            mock_exposure_weighted_combination.combine_rectangular_intensity_map_data
-        )
+        mock_combine = mock_exposure_weighted_combination.combine_rectangular_intensity_map_data
 
-        mock_combine.assert_called_once_with(
-            [sentinel.l075, sentinel.l090, sentinel.l105]
-        )
+        mock_combine.assert_called_once_with([sentinel.l075, sentinel.l090, sentinel.l105])
 
         expected_parents = [
             "imap_lo_l3_l075-ena-h-hf-sp-ram-hae-6deg-6mo_20250422_v001.cdf",
@@ -361,27 +333,19 @@ def test_isn_background_subtraction(self):
             obs_date=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30)) * 5,
             obs_date_range=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30)) * 6,
             ena_intensity=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30)) * 7,
-            ena_intensity_sys_err=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30))
-            * 8,
-            ena_intensity_stat_uncert=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30))
-            * 9,
+            ena_intensity_sys_err=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30)) * 8,
+            ena_intensity_stat_uncert=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30)) * 9,
             bg_rate_sys_err=np.arange(1 * 7 * 60 * 30).reshape((1, 7, 60, 30)) * 11,
             ena_count_rate=np.ones((1, 7, 60, 30)) * 3,
             bg_rate=np.ones((1, 7, 60, 30)) * 2,
             bg_rate_stat_uncert=np.ones((1, 7, 60, 30)) * 3,
             ena_count_rate_stat_uncert=np.ones((1, 7, 60, 30)) * 2,
         )
-        actual_map_data: ISNBackgroundSubtractedMapData = isn_background_subtraction(
-            input_data
-        )
-        actual_isn_rate_map_data: ISNBackgroundSubtractedData = (
-            actual_map_data.isn_rate_map_data
-        )
+        actual_map_data: ISNBackgroundSubtractedMapData = isn_background_subtraction(input_data)
+        actual_isn_rate_map_data: ISNBackgroundSubtractedData = actual_map_data.isn_rate_map_data
 
         expected_isn_bg_rate_subtracted = np.ones((1, 7, 60, 30))
-        expected_isn_bg_rate_subtracted_stat_uncert = np.ones((1, 7, 60, 30)) * np.sqrt(
-            13
-        )
+        expected_isn_bg_rate_subtracted_stat_uncert = np.ones((1, 7, 60, 30)) * np.sqrt(13)
 
         np.testing.assert_array_equal(
             actual_isn_rate_map_data.isn_bg_rate_subtracted,
@@ -392,9 +356,7 @@ def test_isn_background_subtraction(self):
             expected_isn_bg_rate_subtracted_stat_uncert,
         )
 
-        np.testing.assert_array_equal(
-            actual_isn_rate_map_data.energy, input_data.energy
-        )
+        np.testing.assert_array_equal(actual_isn_rate_map_data.energy, input_data.energy)
         np.testing.assert_array_equal(
             actual_isn_rate_map_data.energy_delta_plus, input_data.energy_delta_plus
         )
@@ -407,15 +369,11 @@ def test_isn_background_subtraction(self):
         np.testing.assert_array_equal(
             actual_isn_rate_map_data.exposure_factor, input_data.exposure_factor
         )
-        np.testing.assert_array_equal(
-            actual_isn_rate_map_data.obs_date, input_data.obs_date
-        )
+        np.testing.assert_array_equal(actual_isn_rate_map_data.obs_date, input_data.obs_date)
         np.testing.assert_array_equal(
             actual_isn_rate_map_data.obs_date_range, input_data.obs_date_range
         )
-        np.testing.assert_array_equal(
-            actual_isn_rate_map_data.bg_rate, input_data.bg_rate
-        )
+        np.testing.assert_array_equal(actual_isn_rate_map_data.bg_rate, input_data.bg_rate)
         np.testing.assert_array_equal(
             actual_isn_rate_map_data.bg_rate_stat_uncert, input_data.bg_rate_stat_uncert
         )
@@ -430,17 +388,9 @@ def test_isn_background_subtraction(self):
         self.assertEqual(actual_isn_rate_map_data.epoch, sentinel.epoch)
         self.assertEqual(actual_isn_rate_map_data.solid_angle, sentinel.solid_angle)
         self.assertEqual(actual_isn_rate_map_data.latitude, sentinel.latitude)
-        self.assertEqual(
-            actual_isn_rate_map_data.latitude_delta, sentinel.latitude_delta
-        )
-        self.assertEqual(
-            actual_isn_rate_map_data.latitude_label, sentinel.latitude_label
-        )
+        self.assertEqual(actual_isn_rate_map_data.latitude_delta, sentinel.latitude_delta)
+        self.assertEqual(actual_isn_rate_map_data.latitude_label, sentinel.latitude_label)
         self.assertEqual(actual_isn_rate_map_data.longitude, sentinel.longitude)
-        self.assertEqual(
-            actual_isn_rate_map_data.longitude_delta, sentinel.longitude_delta
-        )
-        self.assertEqual(
-            actual_isn_rate_map_data.longitude_label, sentinel.longitude_label
-        )
+        self.assertEqual(actual_isn_rate_map_data.longitude_delta, sentinel.longitude_delta)
+        self.assertEqual(actual_isn_rate_map_data.longitude_label, sentinel.longitude_label)
         self.assertEqual(actual_isn_rate_map_data.epoch_delta, sentinel.epoch_delta)
diff --git a/tests/maps/test_builders.py b/tests/maps/test_builders.py
index 92210515..7537b698 100644
--- a/tests/maps/test_builders.py
+++ b/tests/maps/test_builders.py
@@ -1,15 +1,14 @@
 from datetime import datetime
-from typing import Optional
 
 import numpy as np
 import spiceypy
 
 from imap_l3_processing.maps.map_models import (
-    RectangularIntensityMapData,
+    GlowsL3eRectangularMapInputData,
+    InputRectangularPointingSet,
     IntensityMapData,
     RectangularCoords,
-    InputRectangularPointingSet,
-    GlowsL3eRectangularMapInputData,
+    RectangularIntensityMapData,
     RectangularSpectralIndexMapData,
     SpectralIndexMapData,
 )
@@ -29,9 +28,7 @@ def create_intensity_map_data(
     lon = lon if lon is not None else np.array([1.0])
     lat = lat if lat is not None else np.array([1.0])
     energy = energy if energy is not None else np.array([1.0])
-    energy_delta = (
-        energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
-    )
+    energy_delta = energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
     epoch = epoch if epoch is not None else np.ma.array([datetime.now()])
     epoch_delta = epoch_delta if epoch_delta is not None else np.ma.array([86400 * 1e9])
     flux = (
@@ -61,9 +58,7 @@ def create_intensity_map_data(
         latitude=lat,
         longitude=lon,
         exposure_factor=np.full_like(flux, 0),
-        obs_date=np.ma.array(
-            np.full(more_real_flux.shape, datetime(year=2010, month=1, day=1))
-        ),
+        obs_date=np.ma.array(np.full(more_real_flux.shape, datetime(year=2010, month=1, day=1))),
         obs_date_range=np.ma.array(np.full_like(more_real_flux, 0)),
         solid_angle=np.full_like(more_real_flux, 0),
         ena_intensity=flux,
@@ -90,9 +85,7 @@ def create_rectangular_intensity_map_data(
     lon = lon if lon is not None else np.array([1.0])
     lat = lat if lat is not None else np.array([1.0])
     energy = energy if energy is not None else np.array([1.0])
-    energy_delta = (
-        energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
-    )
+    energy_delta = energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
     epoch = epoch if epoch is not None else np.ma.array([datetime.now()])
     epoch_delta = epoch_delta if epoch_delta is not None else np.ma.array([86400 * 1e9])
     flux = (
@@ -160,9 +153,7 @@ def create_rectangular_intensity_map(
     intensity_map_data: IntensityMapData = None, coords: RectangularCoords = None
 ) -> RectangularIntensityMapData:
     intensity_map = (
-        intensity_map_data
-        if intensity_map_data is not None
-        else create_intensity_map_data()
+        intensity_map_data if intensity_map_data is not None else create_intensity_map_data()
     )
 
     if coords is None:
@@ -218,9 +209,7 @@ def create_rectangular_spectral_index_map_data(
     lon = lon if lon is not None else np.array([1.0])
     lat = lat if lat is not None else np.array([1.0])
     energy = energy if energy is not None else np.array([1.0])
-    energy_delta = (
-        energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
-    )
+    energy_delta = energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
     epoch = epoch if epoch is not None else np.ma.array([datetime.now()])
     epoch_delta = epoch_delta if epoch_delta is not None else np.ma.array([86400 * 1e9])
     spectral_index = (
@@ -276,15 +265,19 @@ def create_rectangular_spectral_index_map_data(
 
 def create_l1c_pset(
     epoch: datetime = datetime(2025, 4, 15, 12),
-    epoch_delta: np.ndarray = np.array([43200_000_000_000]),
+    epoch_delta: np.ndarray | None | tuple = (),
     repointing: int = 1,
-    energy_steps: np.ndarray = np.array([1]),
-    exposures: Optional[np.ndarray] = None,
+    energy_steps: np.ndarray | None = None,
+    exposures: np.ndarray | None = None,
     pointing_start_met=None,
     pointing_end_met=None,
     hae_longitude=None,
     hae_latitude=None,
 ) -> InputRectangularPointingSet:
+    if isinstance(epoch_delta, tuple) and epoch_delta == ():
+        epoch_delta = np.array([43200_000_000_000])
+    if energy_steps is None:
+        energy_steps = np.array([1])
     epoch_j2000 = np.array([spiceypy.datetime2et(epoch)]) * 1e9
     exposures = (
         exposures
@@ -315,11 +308,15 @@ def create_l1c_pset(
 def create_l3e_pset(
     epoch: datetime = datetime(2025, 4, 15, 12),
     repointing: int = 1,
-    energy_steps=np.array([0.5, 5.0, 12.0]),
-    spin_angle=np.arange(0, 360),
-    sp: Optional[np.array] = None,
-    flags: Optional[np.array] = None,
+    energy_steps: np.ndarray | None = None,
+    spin_angle: np.ndarray | None = None,
+    sp: np.ndarray | None = None,
+    flags: np.ndarray | None = None,
 ) -> GlowsL3eRectangularMapInputData:
+    if energy_steps is None:
+        energy_steps = np.array([0.5, 5.0, 12.0])
+    if spin_angle is None:
+        spin_angle = np.arange(0, 360)
     epoch_j2000 = np.array([spiceypy.datetime2et(epoch)]) * 1e9
     sp = sp or np.full(shape=(1, len(energy_steps), len(spin_angle)), fill_value=0.5)
     flags = flags or np.full(1, 0, dtype=np.uint16)
diff --git a/tests/maps/test_hilo_l3_survival_dependencies.py b/tests/maps/test_hilo_l3_survival_dependencies.py
index 56fadbb9..5e5d066a 100644
--- a/tests/maps/test_hilo_l3_survival_dependencies.py
+++ b/tests/maps/test_hilo_l3_survival_dependencies.py
@@ -1,21 +1,19 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, Mock, sentinel, call
+from unittest.mock import Mock, call, patch, sentinel
 
 from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.maps.hilo_l3_survival_dependencies import (
-    HiLoL3SurvivalDependencies,
     HiL3SingleSensorFullSpinDependencies,
+    HiLoL3SurvivalDependencies,
 )
 from imap_l3_processing.models import Instrument
 
 
 class TestHiLoL3SurvivalDependencies(unittest.TestCase):
     @patch("imap_l3_processing.maps.hilo_l3_survival_dependencies.parse_map_descriptor")
-    @patch(
-        "imap_l3_processing.maps.hilo_l3_survival_dependencies.imap_data_access.download"
-    )
+    @patch("imap_l3_processing.maps.hilo_l3_survival_dependencies.imap_data_access.download")
     @patch("imap_l3_processing.maps.hilo_l3_survival_dependencies.read_glows_l3e_data")
     @patch(
         "imap_l3_processing.maps.hilo_l3_survival_dependencies.read_l1c_rectangular_pointing_set_data"
@@ -47,9 +45,7 @@ def test_fetch_dependencies(
             ]
 
             l2_map_descriptor = "ena-h-sf-nsp-ram-hae-6deg-1yr"
-            l2_filename = (
-                f"imap_{instrument.value}_l2_{l2_map_descriptor}_20250415_v001.cdf"
-            )
+            l2_filename = f"imap_{instrument.value}_l2_{l2_map_descriptor}_20250415_v001.cdf"
 
             dependencies = ProcessingInputCollection(
                 ScienceInput(l2_filename),
@@ -80,16 +76,12 @@ def test_fetch_dependencies(
                 sentinel.glows_data_3,
             ]
 
-            actual = HiLoL3SurvivalDependencies.fetch_dependencies(
-                dependencies, instrument
-            )
+            actual = HiLoL3SurvivalDependencies.fetch_dependencies(dependencies, instrument)
 
             expected_imap_data_access_calls = [call(l2_filename)] + [
                 call(path) for path in l1c_file_names + glows_file_names
             ]
-            mock_imap_data_access_download.assert_has_calls(
-                expected_imap_data_access_calls
-            )
+            mock_imap_data_access_download.assert_has_calls(expected_imap_data_access_calls)
 
             mock_read_from_path.assert_called_once_with(sentinel.l2_file_path)
 
@@ -145,9 +137,7 @@ def test_fetch_single_sensor_full_spin_dependencies(self, mock_fetch_dependencie
         anti_input = ScienceInput(anti_l2_filename)
         glows_input = ScienceInput(glows_l3e_filename)
         l1c_input = ScienceInput(l1c_filename)
-        dependencies = ProcessingInputCollection(
-            ram_input, anti_input, glows_input, l1c_input
-        )
+        dependencies = ProcessingInputCollection(ram_input, anti_input, glows_input, l1c_input)
 
         mock_ram_survival_dependencies = Mock(spec=HiLoL3SurvivalDependencies)
         mock_ram_survival_dependencies.dependency_file_paths = [
@@ -168,20 +158,14 @@ def test_fetch_single_sensor_full_spin_dependencies(self, mock_fetch_dependencie
         result = HiL3SingleSensorFullSpinDependencies.fetch_dependencies(dependencies)
         self.assertIsInstance(result, HiL3SingleSensorFullSpinDependencies)
         self.assertEqual(result.ram_dependencies, mock_ram_survival_dependencies)
-        self.assertEqual(
-            result.antiram_dependencies, mock_antiram_survival_dependencies
-        )
+        self.assertEqual(result.antiram_dependencies, mock_antiram_survival_dependencies)
 
         [ram_dependencies, instrument] = mock_fetch_dependencies.call_args_list[0].args
         self.assertIsInstance(ram_dependencies, ProcessingInputCollection)
-        self.assertEqual(
-            [ram_input, glows_input, l1c_input], ram_dependencies.processing_input
-        )
+        self.assertEqual([ram_input, glows_input, l1c_input], ram_dependencies.processing_input)
         self.assertEqual(Instrument.IMAP_HI, instrument)
 
-        [antiram_dependencies, instrument] = mock_fetch_dependencies.call_args_list[
-            1
-        ].args
+        [antiram_dependencies, instrument] = mock_fetch_dependencies.call_args_list[1].args
         self.assertIsInstance(antiram_dependencies, ProcessingInputCollection)
         self.assertEqual(
             [anti_input, glows_input, l1c_input], antiram_dependencies.processing_input
diff --git a/tests/maps/test_map_combination.py b/tests/maps/test_map_combination.py
index 7a0dd1db..01fc257b 100644
--- a/tests/maps/test_map_combination.py
+++ b/tests/maps/test_map_combination.py
@@ -5,17 +5,17 @@
 import numpy as np
 
 from imap_l3_processing.maps.map_combination import (
-    UnweightedCombination,
     CombinationStrategy,
     ExposureWeightedCombination,
     UncertaintyWeightedCombination,
+    UnweightedCombination,
 )
 from imap_l3_processing.maps.map_models import (
+    HealPixCoords,
+    HealPixIntensityMapData,
     IntensityMapData,
-    RectangularIntensityMapData,
     RectangularCoords,
-    HealPixIntensityMapData,
-    HealPixCoords,
+    RectangularIntensityMapData,
 )
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 from tests.maps.test_builders import (
@@ -91,9 +91,7 @@ def _combine_single_map(self, combination: CombinationStrategy):
         map_1.ena_intensity_stat_uncert = np.array([1])
 
         combine_one = combination._combine([map_1])
-        np.testing.assert_equal(
-            dataclasses.asdict(combine_one), dataclasses.asdict(map_1)
-        )
+        np.testing.assert_equal(dataclasses.asdict(combine_one), dataclasses.asdict(map_1))
 
     def _combine_maps_with_no_background_data(self, combination: CombinationStrategy):
         map_1 = construct_intensity_data_with_all_zero_fields()
@@ -103,22 +101,16 @@ def _combine_maps_with_no_background_data(self, combination: CombinationStrategy
         map_1.bg_intensity_stat_uncert = None
 
         combine_one = combination._combine([map_1])
-        np.testing.assert_equal(
-            dataclasses.asdict(combine_one), dataclasses.asdict(map_1)
-        )
+        np.testing.assert_equal(dataclasses.asdict(combine_one), dataclasses.asdict(map_1))
 
-    def _combine_maps_with_no_intensity_sys_errors(
-        self, combination: CombinationStrategy
-    ):
+    def _combine_maps_with_no_intensity_sys_errors(self, combination: CombinationStrategy):
         map_1 = construct_intensity_data_with_all_zero_fields()
         map_1.ena_intensity_stat_uncert = np.array([1])
         map_1.ena_intensity_sys_err_plus = None
         map_1.ena_intensity_sys_err_minus = None
 
         combine_one = combination._combine([map_1])
-        np.testing.assert_equal(
-            dataclasses.asdict(combine_one), dataclasses.asdict(map_1)
-        )
+        np.testing.assert_equal(dataclasses.asdict(combine_one), dataclasses.asdict(map_1))
 
     def _check_maps_match(self, combination: CombinationStrategy):
         map_1 = construct_intensity_data_with_all_zero_fields()
@@ -159,10 +151,8 @@ def _check_maps_match(self, combination: CombinationStrategy):
             else:
                 try:
                     combination._check_maps_match([map_1, map_with_difference])
-                except Exception:
-                    self.fail(
-                        f"Differences in other fields should be alright: {field.name}"
-                    )
+                except AssertionError:
+                    self.fail(f"Differences in other fields should be alright: {field.name}")
 
     def test_combine_maps_does_a_time_weighted_average_of_intensity(self):
         map_1 = construct_intensity_data_with_all_zero_fields()
@@ -282,12 +272,8 @@ def test_combine_maps_does_a_time_weighted_average_of_intensity(self):
 
         exposure_weighted_strategy = ExposureWeightedCombination()
 
-        rectangular_map_1: RectangularIntensityMapData = (
-            create_rectangular_intensity_map(map_1)
-        )
-        rectangular_map_2: RectangularIntensityMapData = (
-            create_rectangular_intensity_map(map_2)
-        )
+        rectangular_map_1: RectangularIntensityMapData = create_rectangular_intensity_map(map_1)
+        rectangular_map_2: RectangularIntensityMapData = create_rectangular_intensity_map(map_2)
         combine_two = exposure_weighted_strategy.combine_rectangular_intensity_map_data(
             [rectangular_map_1, rectangular_map_2]
         )
@@ -307,9 +293,7 @@ def test_combine_maps_does_a_time_weighted_average_of_intensity(self):
         np.testing.assert_equal(
             combine_two.intensity_map_data.obs_date.mask, expected_obs_date.mask
         )
-        np.testing.assert_equal(
-            combine_two.intensity_map_data.obs_date, expected_obs_date
-        )
+        np.testing.assert_equal(combine_two.intensity_map_data.obs_date, expected_obs_date)
         np.testing.assert_equal(
             combine_two.intensity_map_data.bg_intensity, expected_combined_bg_intensity
         )
@@ -381,13 +365,11 @@ def test_combine_handles_maps_with_different_patterns_of_missing_intensity_and_b
             np.nan,
         ]
 
-        combined_map = (
-            ExposureWeightedCombination().combine_rectangular_intensity_map_data(
-                [
-                    create_rectangular_intensity_map(map_1),
-                    create_rectangular_intensity_map(map_2),
-                ]
-            )
+        combined_map = ExposureWeightedCombination().combine_rectangular_intensity_map_data(
+            [
+                create_rectangular_intensity_map(map_1),
+                create_rectangular_intensity_map(map_2),
+            ]
         )
 
         np.testing.assert_array_equal(
@@ -410,25 +392,17 @@ def test_combine_maps_handles_integer_obs_date(self):
         map_1 = construct_intensity_data_with_all_zero_fields()
         map_1.exposure_factor = np.array([1, 0, 5, 6, 0])
         DATETIME_FILL = -9223372036854775808
-        map_1.obs_date = np.ma.masked_equal(
-            [5, DATETIME_FILL, 7, 8, DATETIME_FILL], DATETIME_FILL
-        )
+        map_1.obs_date = np.ma.masked_equal([5, DATETIME_FILL, 7, 8, DATETIME_FILL], DATETIME_FILL)
 
         map_2 = construct_intensity_data_with_all_zero_fields()
         map_2.exposure_factor = np.array([3, 1, 5, 2, 0])
-        map_2.obs_date = np.ma.masked_equal(
-            [9, 10, 11, 12, DATETIME_FILL], DATETIME_FILL
-        )
+        map_2.obs_date = np.ma.masked_equal([9, 10, 11, 12, DATETIME_FILL], DATETIME_FILL)
         expected_obs_date = np.ma.array([8, 10, 9, 9, np.ma.masked])
 
         exposure_weighted_strategy = ExposureWeightedCombination()
 
-        rectangular_map_1: RectangularIntensityMapData = (
-            create_rectangular_intensity_map(map_1)
-        )
-        rectangular_map_2: RectangularIntensityMapData = (
-            create_rectangular_intensity_map(map_2)
-        )
+        rectangular_map_1: RectangularIntensityMapData = create_rectangular_intensity_map(map_1)
+        rectangular_map_2: RectangularIntensityMapData = create_rectangular_intensity_map(map_2)
 
         combine_two = exposure_weighted_strategy.combine_rectangular_intensity_map_data(
             [rectangular_map_1, rectangular_map_2]
@@ -437,9 +411,7 @@ def test_combine_maps_handles_integer_obs_date(self):
         np.testing.assert_equal(
             combine_two.intensity_map_data.obs_date.mask, expected_obs_date.mask
         )
-        np.testing.assert_equal(
-            combine_two.intensity_map_data.obs_date, expected_obs_date
-        )
+        np.testing.assert_equal(combine_two.intensity_map_data.obs_date, expected_obs_date)
 
     def test_combine_unweighted_combination_strategy(self):
         map_1 = construct_intensity_data_with_all_zero_fields()
@@ -484,9 +456,7 @@ def test_combine_unweighted_combination_strategy(self):
         map_2 = construct_intensity_data_with_all_zero_fields()
         map_2.ena_intensity = np.array([5, 6, 7, 8, np.nan, 100, 9, 10, 11])
         map_2.exposure_factor = np.array([10, 0, 10, 10, 10, 100, 100, np.nan, 30])
-        map_2.ena_intensity_sys_err = np.array(
-            [4, 1, 4, 5, np.nan, 1, np.nan, np.nan, np.nan]
-        )
+        map_2.ena_intensity_sys_err = np.array([4, 1, 4, 5, np.nan, 1, np.nan, np.nan, np.nan])
         map_2.ena_intensity_stat_uncert = np.array(
             [8, 1, 8, 10, np.nan, 1, np.nan, np.nan, np.nan]
         )
@@ -538,17 +508,11 @@ def test_combine_unweighted_combination_strategy(self):
 
         exposure_unweighted_strategy = UnweightedCombination()
 
-        rectangular_map_1: RectangularIntensityMapData = (
-            create_rectangular_intensity_map(map_1)
-        )
-        rectangular_map_2: RectangularIntensityMapData = (
-            create_rectangular_intensity_map(map_2)
-        )
+        rectangular_map_1: RectangularIntensityMapData = create_rectangular_intensity_map(map_1)
+        rectangular_map_2: RectangularIntensityMapData = create_rectangular_intensity_map(map_2)
 
-        combine_two = (
-            exposure_unweighted_strategy.combine_rectangular_intensity_map_data(
-                [rectangular_map_1, rectangular_map_2]
-            )
+        combine_two = exposure_unweighted_strategy.combine_rectangular_intensity_map_data(
+            [rectangular_map_1, rectangular_map_2]
         )
 
         np.testing.assert_equal(
@@ -560,9 +524,7 @@ def test_combine_unweighted_combination_strategy(self):
         np.testing.assert_equal(
             combine_two.intensity_map_data.ena_intensity_stat_uncert, expected_stat_unc
         )
-        np.testing.assert_equal(
-            combine_two.intensity_map_data.obs_date[-1], expected_obs_date
-        )
+        np.testing.assert_equal(combine_two.intensity_map_data.obs_date[-1], expected_obs_date)
         np.testing.assert_equal(
             combine_two.intensity_map_data.survival_probability,
             expected_survival_probability,
@@ -599,12 +561,9 @@ def make_data(
             ("lon_label", make_data(lon_label=np.array(["two"]))),
         ]
         for name, not_matching_map in cases:
-            with self.subTest(name):
-                with self.assertRaises(AssertionError):
-                    strategy = UnweightedCombination()
-                    strategy.combine_rectangular_intensity_map_data(
-                        [base_map, not_matching_map]
-                    )
+            with self.subTest(name), self.assertRaises(AssertionError):
+                strategy = UnweightedCombination()
+                strategy.combine_rectangular_intensity_map_data([base_map, not_matching_map])
 
     def test_combine_healpix_intensity_map_data_errors_if_coords_not_matching(self):
         index_array = np.array([1])
@@ -627,18 +586,13 @@ def make_data(pixel_index=index_array, pixel_index_label=label_array):
             ),
             (
                 "pixel_index_label",
-                make_data(
-                    pixel_index=index_array, pixel_index_label=np.array(["diff label"])
-                ),
+                make_data(pixel_index=index_array, pixel_index_label=np.array(["diff label"])),
             ),
         ]
         for name, not_matching_map in cases:
-            with self.subTest(name):
-                with self.assertRaises(AssertionError):
-                    strategy = UnweightedCombination()
-                    strategy.combine_healpix_intensity_map_data(
-                        [base_map, not_matching_map]
-                    )
+            with self.subTest(name), self.assertRaises(AssertionError):
+                strategy = UnweightedCombination()
+                strategy.combine_healpix_intensity_map_data([base_map, not_matching_map])
 
     def test_calculate_weighted_sys_err(self):
         uncertainties_1 = np.array([10, 20, 30, 40])
@@ -748,9 +702,7 @@ def test_uncertainty_weighted_combination(self):
         np.testing.assert_equal(
             combine_two.intensity_map_data.obs_date.mask, expected_obs_date.mask
         )
-        np.testing.assert_equal(
-            combine_two.intensity_map_data.obs_date, expected_obs_date
-        )
+        np.testing.assert_equal(combine_two.intensity_map_data.obs_date, expected_obs_date)
         np.testing.assert_equal(
             combine_two.intensity_map_data.survival_probability,
             expected_survival_probability,
@@ -771,13 +723,11 @@ def test_combination_handles_missing_sp_data(self):
                 map_2 = construct_intensity_data_with_all_zero_fields()
                 map_2.survival_probability = None
 
-                combined_map = (
-                    combination_strategy().combine_rectangular_intensity_map_data(
-                        [
-                            create_rectangular_intensity_map(map_1),
-                            create_rectangular_intensity_map(map_2),
-                        ]
-                    )
+                combined_map = combination_strategy().combine_rectangular_intensity_map_data(
+                    [
+                        create_rectangular_intensity_map(map_1),
+                        create_rectangular_intensity_map(map_2),
+                    ]
                 )
 
                 self.assertIsNone(combined_map.intensity_map_data.survival_probability)
@@ -815,13 +765,11 @@ def test_combination_handles_quality_flag(self):
                     ]
                 )
 
-                combined_map = (
-                    combination_strategy().combine_rectangular_intensity_map_data(
-                        [
-                            create_rectangular_intensity_map(map_1),
-                            create_rectangular_intensity_map(map_2),
-                        ]
-                    )
+                combined_map = combination_strategy().combine_rectangular_intensity_map_data(
+                    [
+                        create_rectangular_intensity_map(map_1),
+                        create_rectangular_intensity_map(map_2),
+                    ]
                 )
 
                 np.testing.assert_equal(
@@ -832,7 +780,6 @@ def test_combination_handles_quality_flag(self):
                         MapL3Flags.PREDICTIVE_EPHEMERIS,
                         MapL3Flags.PREDICTIVE_EPHEMERIS,
                         MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
-                        MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO
-                        | MapL3Flags.PREDICTIVE_EPHEMERIS,
+                        MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO | MapL3Flags.PREDICTIVE_EPHEMERIS,
                     ],
                 )
diff --git a/tests/maps/test_map_descriptors.py b/tests/maps/test_map_descriptors.py
index c0b1ffe5..5a8c5274 100644
--- a/tests/maps/test_map_descriptors.py
+++ b/tests/maps/test_map_descriptors.py
@@ -1,15 +1,15 @@
 import unittest
 
 from imap_l3_processing.maps.map_descriptors import (
-    ReferenceFrame,
-    SurvivalCorrection,
     MapDescriptorParts,
-    Sensor,
     MapQuantity,
-    SpinPhase,
     PixelSize,
-    parse_map_descriptor,
+    ReferenceFrame,
+    Sensor,
+    SpinPhase,
+    SurvivalCorrection,
     map_descriptor_parts_to_string,
+    parse_map_descriptor,
 )
 
 
@@ -432,9 +432,7 @@ def test_parse_map_descriptor(self):
                 self.assertEqual(expected, descriptor_parts)
 
                 if descriptor_parts is not None:
-                    self.assertEqual(
-                        descriptor, map_descriptor_parts_to_string(descriptor_parts)
-                    )
+                    self.assertEqual(descriptor, map_descriptor_parts_to_string(descriptor_parts))
 
 
 if __name__ == "__main__":
diff --git a/tests/maps/test_map_models.py b/tests/maps/test_map_models.py
index b802bef5..b50cb2de 100644
--- a/tests/maps/test_map_models.py
+++ b/tests/maps/test_map_models.py
@@ -4,7 +4,7 @@
 import unittest
 from datetime import datetime, timedelta
 from pathlib import Path
-from unittest.mock import sentinel, Mock
+from unittest.mock import Mock, sentinel
 
 import numpy as np
 from imap_processing.ena_maps.ena_maps import HealpixSkyMap
@@ -15,40 +15,40 @@
 from xarray import Dataset
 
 from imap_l3_processing.cdf.cdf_utils import (
-    read_variable_and_mask_fill_values,
     read_numeric_variable,
+    read_variable_and_mask_fill_values,
 )
 from imap_l3_processing.constants import (
+    FIVE_MINUTES_IN_NANOSECONDS,
     ONE_SECOND_IN_NANOSECONDS,
     SECONDS_PER_DAY,
-    FIVE_MINUTES_IN_NANOSECONDS,
     TT2000_EPOCH,
 )
 from imap_l3_processing.maps import map_models
 from imap_l3_processing.maps.map_models import (
-    RectangularCoords,
-    SpectralIndexMapData,
-    RectangularSpectralIndexMapData,
-    RectangularSpectralIndexDataProduct,
-    RectangularIntensityMapData,
-    IntensityMapData,
-    RectangularIntensityDataProduct,
-    HealPixIntensityMapData,
+    QUALITY_FLAGS_VAR_NAME,
     HealPixCoords,
-    convert_tt2000_time_to_datetime,
-    _read_intensity_map_data_from_open_cdf,
-    calculate_datetime_weighted_average,
-    ISNRateData,
+    HealPixIntensityMapData,
+    IntensityMapData,
     ISNBackgroundSubtractedData,
     ISNBackgroundSubtractedDataProduct,
     ISNBackgroundSubtractedMapData,
-    QUALITY_FLAGS_VAR_NAME,
+    ISNRateData,
+    RectangularCoords,
+    RectangularIntensityDataProduct,
+    RectangularIntensityMapData,
+    RectangularSpectralIndexDataProduct,
+    RectangularSpectralIndexMapData,
+    SpectralIndexMapData,
+    _read_intensity_map_data_from_open_cdf,
+    calculate_datetime_weighted_average,
+    convert_tt2000_time_to_datetime,
 )
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 from imap_l3_processing.models import DataProductVariable
 from tests.test_helpers import (
-    get_test_data_folder,
     get_integration_test_data_path,
+    get_test_data_folder,
 )
 
 
@@ -95,24 +95,16 @@ def test_rectangular_spectral_index_to_data_product_variables(self):
             DataProductVariable(map_models.EPOCH_VAR_NAME, sentinel.epoch),
             DataProductVariable(map_models.EPOCH_DELTA_VAR_NAME, sentinel.epoch_delta),
             DataProductVariable(map_models.ENERGY_VAR_NAME, sentinel.energy),
-            DataProductVariable(
-                map_models.ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus
-            ),
+            DataProductVariable(map_models.ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus),
             DataProductVariable(
                 map_models.ENERGY_DELTA_MINUS_VAR_NAME, sentinel.energy_delta_minus
             ),
-            DataProductVariable(
-                map_models.ENERGY_LABEL_VAR_NAME, sentinel.energy_label
-            ),
+            DataProductVariable(map_models.ENERGY_LABEL_VAR_NAME, sentinel.energy_label),
             DataProductVariable(map_models.LATITUDE_VAR_NAME, sentinel.latitude),
             DataProductVariable(map_models.LONGITUDE_VAR_NAME, sentinel.longitude),
-            DataProductVariable(
-                map_models.EXPOSURE_FACTOR_VAR_NAME, sentinel.exposure_factor
-            ),
+            DataProductVariable(map_models.EXPOSURE_FACTOR_VAR_NAME, sentinel.exposure_factor),
             DataProductVariable(map_models.OBS_DATE_VAR_NAME, sentinel.obs_date),
-            DataProductVariable(
-                map_models.OBS_DATE_RANGE_VAR_NAME, sentinel.obs_date_range
-            ),
+            DataProductVariable(map_models.OBS_DATE_RANGE_VAR_NAME, sentinel.obs_date_range),
             DataProductVariable(map_models.SOLID_ANGLE_VAR_NAME, sentinel.solid_angle),
             DataProductVariable(
                 map_models.ENA_SPECTRAL_INDEX_VAR_NAME, sentinel.ena_spectral_index
@@ -133,21 +125,11 @@ def test_rectangular_spectral_index_to_data_product_variables(self):
                 map_models.ENA_SPECTRAL_INDEX_CHISQ_VAR_NAME,
                 sentinel.ena_spectral_index_chisq,
             ),
-            DataProductVariable(
-                map_models.QUALITY_FLAGS_VAR_NAME, sentinel.quality_flags
-            ),
-            DataProductVariable(
-                map_models.LATITUDE_DELTA_VAR_NAME, sentinel.latitude_delta
-            ),
-            DataProductVariable(
-                map_models.LATITUDE_LABEL_VAR_NAME, sentinel.latitude_label
-            ),
-            DataProductVariable(
-                map_models.LONGITUDE_DELTA_VAR_NAME, sentinel.longitude_delta
-            ),
-            DataProductVariable(
-                map_models.LONGITUDE_LABEL_VAR_NAME, sentinel.longitude_label
-            ),
+            DataProductVariable(map_models.QUALITY_FLAGS_VAR_NAME, sentinel.quality_flags),
+            DataProductVariable(map_models.LATITUDE_DELTA_VAR_NAME, sentinel.latitude_delta),
+            DataProductVariable(map_models.LATITUDE_LABEL_VAR_NAME, sentinel.latitude_label),
+            DataProductVariable(map_models.LONGITUDE_DELTA_VAR_NAME, sentinel.longitude_delta),
+            DataProductVariable(map_models.LONGITUDE_LABEL_VAR_NAME, sentinel.longitude_label),
         ]
 
         self.assertEqual(expected_variables, actual_variables)
@@ -163,9 +145,7 @@ def test_rectangular_intensity_to_data_product_variables(self):
                     "bg_intensity_sys_err": sentinel.bg_intensity_sys_err,
                 },
                 [
-                    DataProductVariable(
-                        map_models.BG_INTENSITY_VAR_NAME, sentinel.bg_intensity
-                    ),
+                    DataProductVariable(map_models.BG_INTENSITY_VAR_NAME, sentinel.bg_intensity),
                     DataProductVariable(
                         map_models.BG_INTENSITY_STAT_UNC_VAR_NAME,
                         sentinel.bg_intensity_stat_uncert,
@@ -250,9 +230,7 @@ def test_rectangular_intensity_to_data_product_variables(self):
 
                 expected_variables = [
                     DataProductVariable(map_models.EPOCH_VAR_NAME, sentinel.epoch),
-                    DataProductVariable(
-                        map_models.EPOCH_DELTA_VAR_NAME, sentinel.epoch_delta
-                    ),
+                    DataProductVariable(map_models.EPOCH_DELTA_VAR_NAME, sentinel.epoch_delta),
                     DataProductVariable(map_models.ENERGY_VAR_NAME, sentinel.energy),
                     DataProductVariable(
                         map_models.ENERGY_DELTA_PLUS_VAR_NAME,
@@ -262,30 +240,18 @@ def test_rectangular_intensity_to_data_product_variables(self):
                         map_models.ENERGY_DELTA_MINUS_VAR_NAME,
                         sentinel.energy_delta_minus,
                     ),
-                    DataProductVariable(
-                        map_models.ENERGY_LABEL_VAR_NAME, sentinel.energy_label
-                    ),
-                    DataProductVariable(
-                        map_models.LATITUDE_VAR_NAME, sentinel.latitude
-                    ),
-                    DataProductVariable(
-                        map_models.LONGITUDE_VAR_NAME, sentinel.longitude
-                    ),
+                    DataProductVariable(map_models.ENERGY_LABEL_VAR_NAME, sentinel.energy_label),
+                    DataProductVariable(map_models.LATITUDE_VAR_NAME, sentinel.latitude),
+                    DataProductVariable(map_models.LONGITUDE_VAR_NAME, sentinel.longitude),
                     DataProductVariable(
                         map_models.EXPOSURE_FACTOR_VAR_NAME, sentinel.exposure_factor
                     ),
-                    DataProductVariable(
-                        map_models.OBS_DATE_VAR_NAME, sentinel.obs_date
-                    ),
+                    DataProductVariable(map_models.OBS_DATE_VAR_NAME, sentinel.obs_date),
                     DataProductVariable(
                         map_models.OBS_DATE_RANGE_VAR_NAME, sentinel.obs_date_range
                     ),
-                    DataProductVariable(
-                        map_models.SOLID_ANGLE_VAR_NAME, sentinel.solid_angle
-                    ),
-                    DataProductVariable(
-                        map_models.ENA_INTENSITY_VAR_NAME, sentinel.ena_intensity
-                    ),
+                    DataProductVariable(map_models.SOLID_ANGLE_VAR_NAME, sentinel.solid_angle),
+                    DataProductVariable(map_models.ENA_INTENSITY_VAR_NAME, sentinel.ena_intensity),
                     DataProductVariable(
                         map_models.ENA_INTENSITY_STAT_UNCERT_VAR_NAME,
                         sentinel.ena_intensity_stat_uncert,
@@ -355,40 +321,24 @@ def test_isn_background_subtracted_to_data_product_variables(self):
             DataProductVariable(map_models.EPOCH_VAR_NAME, sentinel.epoch),
             DataProductVariable(map_models.EPOCH_DELTA_VAR_NAME, sentinel.epoch_delta),
             DataProductVariable(map_models.ENERGY_VAR_NAME, sentinel.energy),
-            DataProductVariable(
-                map_models.ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus
-            ),
+            DataProductVariable(map_models.ENERGY_DELTA_PLUS_VAR_NAME, sentinel.energy_delta_plus),
             DataProductVariable(
                 map_models.ENERGY_DELTA_MINUS_VAR_NAME, sentinel.energy_delta_minus
             ),
-            DataProductVariable(
-                map_models.ENERGY_LABEL_VAR_NAME, sentinel.energy_label
-            ),
-            DataProductVariable(
-                map_models.EXPOSURE_FACTOR_VAR_NAME, sentinel.exposure_factor
-            ),
+            DataProductVariable(map_models.ENERGY_LABEL_VAR_NAME, sentinel.energy_label),
+            DataProductVariable(map_models.EXPOSURE_FACTOR_VAR_NAME, sentinel.exposure_factor),
             DataProductVariable(map_models.SOLID_ANGLE_VAR_NAME, sentinel.solid_angle),
             DataProductVariable(map_models.BG_RATE_VAR_NAME, sentinel.bg_rate),
             DataProductVariable(
                 map_models.BG_RATE_STAT_UNCERT_VAR_NAME, sentinel.bg_rate_stat_uncert
             ),
-            DataProductVariable(
-                map_models.BG_RATE_SYS_ERR_VAR_NAME, sentinel.bg_rate_sys_err
-            ),
+            DataProductVariable(map_models.BG_RATE_SYS_ERR_VAR_NAME, sentinel.bg_rate_sys_err),
             DataProductVariable(map_models.LATITUDE_VAR_NAME, sentinel.latitude),
-            DataProductVariable(
-                map_models.LATITUDE_DELTA_VAR_NAME, sentinel.latitude_delta
-            ),
-            DataProductVariable(
-                map_models.LATITUDE_LABEL_VAR_NAME, sentinel.latitude_label
-            ),
+            DataProductVariable(map_models.LATITUDE_DELTA_VAR_NAME, sentinel.latitude_delta),
+            DataProductVariable(map_models.LATITUDE_LABEL_VAR_NAME, sentinel.latitude_label),
             DataProductVariable(map_models.LONGITUDE_VAR_NAME, sentinel.longitude),
-            DataProductVariable(
-                map_models.LONGITUDE_DELTA_VAR_NAME, sentinel.longitude_delta
-            ),
-            DataProductVariable(
-                map_models.LONGITUDE_LABEL_VAR_NAME, sentinel.longitude_label
-            ),
+            DataProductVariable(map_models.LONGITUDE_DELTA_VAR_NAME, sentinel.longitude_delta),
+            DataProductVariable(map_models.LONGITUDE_LABEL_VAR_NAME, sentinel.longitude_label),
             DataProductVariable(
                 map_models.ISN_BG_RATE_SUBTRACTED_VAR_NAME,
                 sentinel.isn_bg_rate_subtracted,
@@ -406,9 +356,7 @@ def test_isn_background_subtracted_to_data_product_variables(self):
         self.assertEqual(expected_variables, actual_variables)
 
     def test_healpix_map_nside_property(self):
-        path_to_cdf = (
-            get_test_data_folder() / "ultra" / "fake_l2_maps" / "test_l2_map.cdf"
-        )
+        path_to_cdf = get_test_data_folder() / "ultra" / "fake_l2_maps" / "test_l2_map.cdf"
         actual = HealPixIntensityMapData.read_from_path(path_to_cdf)
         expected_nside = 2
 
@@ -427,9 +375,7 @@ def test_ultra_l2_map_read_from_file(self):
         actual_coords = map_data.coords
 
         with CDF(str(path_to_cdf)) as expected:
-            date_range_var = read_variable_and_mask_fill_values(
-                expected["obs_date_range"]
-            )
+            date_range_var = read_variable_and_mask_fill_values(expected["obs_date_range"])
             obs_date = convert_tt2000_time_to_datetime(
                 read_variable_and_mask_fill_values(expected["obs_date"]).filled(0)
             )
@@ -438,9 +384,7 @@ def test_ultra_l2_map_read_from_file(self):
             np.testing.assert_array_equal(
                 expected["epoch_delta"][...], actual_intensity_data.epoch_delta
             )
-            np.testing.assert_array_equal(
-                expected["energy"][...], actual_intensity_data.energy
-            )
+            np.testing.assert_array_equal(expected["energy"][...], actual_intensity_data.energy)
             np.testing.assert_array_equal(
                 expected["energy_delta_plus"][...],
                 actual_intensity_data.energy_delta_plus,
@@ -474,9 +418,7 @@ def test_ultra_l2_map_read_from_file(self):
                 expected["exposure_factor"][...], actual_intensity_data.exposure_factor
             )
             np.testing.assert_array_equal(obs_date, actual_intensity_data.obs_date)
-            np.testing.assert_array_equal(
-                date_range_var, actual_intensity_data.obs_date_range
-            )
+            np.testing.assert_array_equal(date_range_var, actual_intensity_data.obs_date_range)
             np.testing.assert_array_equal(
                 expected["solid_angle"][...], actual_intensity_data.solid_angle
             )
@@ -528,22 +470,16 @@ def test_ultra_healpix_intensity_read_from_xarray(self):
             },
         )
 
-        output: HealPixIntensityMapData = HealPixIntensityMapData.read_from_xarray(
-            input_xarray
-        )
+        output: HealPixIntensityMapData = HealPixIntensityMapData.read_from_xarray(input_xarray)
 
-        np.testing.assert_array_equal(
-            input_xarray["latitude"], output.intensity_map_data.latitude
-        )
+        np.testing.assert_array_equal(input_xarray["latitude"], output.intensity_map_data.latitude)
         np.testing.assert_array_equal(
             input_xarray["longitude"], output.intensity_map_data.longitude
         )
         np.testing.assert_array_equal(
             input_xarray["solid_angle"], output.intensity_map_data.solid_angle
         )
-        np.testing.assert_array_equal(
-            input_xarray["obs_date"], output.intensity_map_data.obs_date
-        )
+        np.testing.assert_array_equal(input_xarray["obs_date"], output.intensity_map_data.obs_date)
         np.testing.assert_array_equal(
             input_xarray["obs_date_range"], output.intensity_map_data.obs_date_range
         )
@@ -690,9 +626,7 @@ def test_read_intensity_map_with_rectangular_cords_data_from_cdf(self):
                         ena_intensity_stat_uncert,
                         recVary=True,
                     )
-                    cdf.new(
-                        "ena_intensity_sys_err", ena_intensity_sys_err, recVary=True
-                    )
+                    cdf.new("ena_intensity_sys_err", ena_intensity_sys_err, recVary=True)
                     cdf.new("exposure_factor", exposure, recVary=True)
                     cdf.new("obs_date", obs_date, recVary=True)
                     cdf.new("obs_date_range", obs_date_range, recVary=True)
@@ -709,9 +643,7 @@ def test_read_intensity_map_with_rectangular_cords_data_from_cdf(self):
                             bg_intensity_stat_unc,
                             recVary=True,
                         )
-                        cdf.new(
-                            "bg_intensity_sys_err", bg_intensity_sys_err, recVary=True
-                        )
+                        cdf.new("bg_intensity_sys_err", bg_intensity_sys_err, recVary=True)
 
                     if include_ena_sys_err_minus:
                         cdf.new(
@@ -747,16 +679,10 @@ def test_read_intensity_map_with_rectangular_cords_data_from_cdf(self):
                         np.testing.assert_array_equal(
                             map_data.energy_delta_minus, energy_delta_minus
                         )
-                        np.testing.assert_array_equal(
-                            map_data.energy_label, energy_label
-                        )
+                        np.testing.assert_array_equal(map_data.energy_label, energy_label)
                         np.testing.assert_array_equal(map_data.latitude, lat)
-                        np.testing.assert_array_equal(
-                            rectangular_coords.latitude_delta, lat_delta
-                        )
-                        np.testing.assert_array_equal(
-                            rectangular_coords.latitude_label, lat_label
-                        )
+                        np.testing.assert_array_equal(rectangular_coords.latitude_delta, lat_delta)
+                        np.testing.assert_array_equal(rectangular_coords.latitude_label, lat_label)
                         np.testing.assert_array_equal(map_data.longitude, lon)
                         np.testing.assert_array_equal(
                             rectangular_coords.longitude_delta, lon_delta
@@ -764,9 +690,7 @@ def test_read_intensity_map_with_rectangular_cords_data_from_cdf(self):
                         np.testing.assert_array_equal(
                             rectangular_coords.longitude_label, lon_label
                         )
-                        np.testing.assert_array_equal(
-                            map_data.ena_intensity, ena_intensity
-                        )
+                        np.testing.assert_array_equal(map_data.ena_intensity, ena_intensity)
                         np.testing.assert_array_equal(
                             map_data.ena_intensity_stat_uncert,
                             ena_intensity_stat_uncert,
@@ -774,26 +698,18 @@ def test_read_intensity_map_with_rectangular_cords_data_from_cdf(self):
                         np.testing.assert_array_equal(
                             map_data.ena_intensity_sys_err, ena_intensity_sys_err
                         )
-                        np.testing.assert_array_equal(
-                            map_data.exposure_factor, exposure
-                        )
-                        np.testing.assert_array_equal(
-                            map_data.obs_date.data, expected_obs_date
-                        )
+                        np.testing.assert_array_equal(map_data.exposure_factor, exposure)
+                        np.testing.assert_array_equal(map_data.obs_date.data, expected_obs_date)
                         np.testing.assert_array_equal(
                             map_data.obs_date.mask, expected_obs_date_mask
                         )
-                        np.testing.assert_array_equal(
-                            map_data.obs_date_range, obs_date_range
-                        )
+                        np.testing.assert_array_equal(map_data.obs_date_range, obs_date_range)
                         np.testing.assert_array_equal(map_data.solid_angle, solid_angle)
                         np.testing.assert_array_equal(
                             map_data.survival_probability, survival_probability
                         )
                         if include_bg:
-                            np.testing.assert_array_equal(
-                                map_data.bg_intensity, bg_intensity
-                            )
+                            np.testing.assert_array_equal(map_data.bg_intensity, bg_intensity)
                             np.testing.assert_array_equal(
                                 map_data.bg_intensity_sys_err, bg_intensity_sys_err
                             )
@@ -826,9 +742,7 @@ def test_read_intensity_map_with_rectangular_coords_data_from_cdf_missing_flags(
         map_data_shape = (1, 9, 90, 45)
         obs_date_fillval = -sys.maxsize - 1
         obs_date_in_cdf = (np.full(map_data_shape, 1e9, dtype=int),)
-        expected_obs_date = (
-            np.full(map_data_shape, TT2000_EPOCH) + timedelta(seconds=1),
-        )
+        expected_obs_date = (np.full(map_data_shape, TT2000_EPOCH) + timedelta(seconds=1),)
         expected_obs_date_mask = (np.full(map_data_shape, False),)
 
         input_quality_flags = np.full(map_data_shape, MapL3Flags.NONE)
@@ -904,9 +818,7 @@ def test_read_intensity_map_with_rectangular_coords_data_from_cdf_missing_flags(
                         ena_intensity_stat_uncert,
                         recVary=True,
                     )
-                    cdf.new(
-                        "ena_intensity_sys_err", ena_intensity_sys_err, recVary=True
-                    )
+                    cdf.new("ena_intensity_sys_err", ena_intensity_sys_err, recVary=True)
                     cdf.new("exposure_factor", exposure, recVary=True)
                     cdf.new("obs_date", obs_date, recVary=True)
                     cdf.new("obs_date_range", obs_date_range, recVary=True)
@@ -917,9 +829,7 @@ def test_read_intensity_map_with_rectangular_coords_data_from_cdf_missing_flags(
                     cdf.new("energy_label", energy_label, recVary=False)
                     cdf.new("survival_probability", survival_probability, recVary=False)
                     cdf.new("bg_intensity", bg_intensity, recVary=True)
-                    cdf.new(
-                        "bg_intensity_stat_uncert", bg_intensity_stat_unc, recVary=True
-                    )
+                    cdf.new("bg_intensity_stat_uncert", bg_intensity_stat_unc, recVary=True)
                     cdf.new("bg_intensity_sys_err", bg_intensity_sys_err, recVary=True)
                     cdf.new(
                         "ena_intensity_sys_err_minus",
@@ -932,9 +842,7 @@ def test_read_intensity_map_with_rectangular_coords_data_from_cdf_missing_flags(
                         recVary=True,
                     )
                     if input_quality_flags is not None:
-                        cdf.new(
-                            QUALITY_FLAGS_VAR_NAME, input_quality_flags, recVary=True
-                        )
+                        cdf.new(QUALITY_FLAGS_VAR_NAME, input_quality_flags, recVary=True)
 
                     for var in cdf:
                         cdf[var].attrs["FILLVAL"] = 1000000
@@ -951,27 +859,15 @@ def test_read_intensity_map_with_rectangular_coords_data_from_cdf_missing_flags(
                     np.testing.assert_array_equal(map_data.epoch, epoch)
                     np.testing.assert_array_equal(map_data.epoch_delta, epoch_delta)
                     np.testing.assert_array_equal(map_data.energy, energy)
-                    np.testing.assert_array_equal(
-                        map_data.energy_delta_plus, energy_delta_plus
-                    )
-                    np.testing.assert_array_equal(
-                        map_data.energy_delta_minus, energy_delta_minus
-                    )
+                    np.testing.assert_array_equal(map_data.energy_delta_plus, energy_delta_plus)
+                    np.testing.assert_array_equal(map_data.energy_delta_minus, energy_delta_minus)
                     np.testing.assert_array_equal(map_data.energy_label, energy_label)
                     np.testing.assert_array_equal(map_data.latitude, lat)
-                    np.testing.assert_array_equal(
-                        rectangular_coords.latitude_delta, lat_delta
-                    )
-                    np.testing.assert_array_equal(
-                        rectangular_coords.latitude_label, lat_label
-                    )
+                    np.testing.assert_array_equal(rectangular_coords.latitude_delta, lat_delta)
+                    np.testing.assert_array_equal(rectangular_coords.latitude_label, lat_label)
                     np.testing.assert_array_equal(map_data.longitude, lon)
-                    np.testing.assert_array_equal(
-                        rectangular_coords.longitude_delta, lon_delta
-                    )
-                    np.testing.assert_array_equal(
-                        rectangular_coords.longitude_label, lon_label
-                    )
+                    np.testing.assert_array_equal(rectangular_coords.longitude_delta, lon_delta)
+                    np.testing.assert_array_equal(rectangular_coords.longitude_label, lon_label)
                     np.testing.assert_array_equal(map_data.ena_intensity, ena_intensity)
                     np.testing.assert_array_equal(
                         map_data.ena_intensity_stat_uncert, ena_intensity_stat_uncert
@@ -980,15 +876,9 @@ def test_read_intensity_map_with_rectangular_coords_data_from_cdf_missing_flags(
                         map_data.ena_intensity_sys_err, ena_intensity_sys_err
                     )
                     np.testing.assert_array_equal(map_data.exposure_factor, exposure)
-                    np.testing.assert_array_equal(
-                        map_data.obs_date.data, expected_obs_date
-                    )
-                    np.testing.assert_array_equal(
-                        map_data.obs_date.mask, expected_obs_date_mask
-                    )
-                    np.testing.assert_array_equal(
-                        map_data.obs_date_range, obs_date_range
-                    )
+                    np.testing.assert_array_equal(map_data.obs_date.data, expected_obs_date)
+                    np.testing.assert_array_equal(map_data.obs_date.mask, expected_obs_date_mask)
+                    np.testing.assert_array_equal(map_data.obs_date_range, obs_date_range)
                     np.testing.assert_array_equal(map_data.solid_angle, solid_angle)
                     np.testing.assert_array_equal(
                         map_data.survival_probability, survival_probability
@@ -1026,9 +916,7 @@ def test_fill_values_in_read_rectangular_intensity_map_data_from_cdf(self):
             self.assertTrue(np.all(map_data.obs_date.mask))
             self.assertTrue(np.all(map_data.obs_date_range.mask))
 
-            np.testing.assert_array_equal(
-                map_data.energy, np.full_like(cdf["energy"], np.nan)
-            )
+            np.testing.assert_array_equal(map_data.energy, np.full_like(cdf["energy"], np.nan))
             np.testing.assert_array_equal(
                 map_data.energy_delta_plus,
                 np.full_like(cdf["energy_delta_plus"], np.nan),
@@ -1037,9 +925,7 @@ def test_fill_values_in_read_rectangular_intensity_map_data_from_cdf(self):
                 map_data.energy_delta_minus,
                 np.full_like(cdf["energy_delta_minus"], np.nan),
             )
-            np.testing.assert_array_equal(
-                map_data.latitude, np.full_like(cdf["latitude"], np.nan)
-            )
+            np.testing.assert_array_equal(map_data.latitude, np.full_like(cdf["latitude"], np.nan))
             np.testing.assert_array_equal(
                 map_data.longitude, np.full_like(cdf["longitude"], np.nan)
             )
@@ -1103,9 +989,7 @@ def test_healpix_intensity_map_data_to_skymap(self):
         quality_flags[0, :, 18] = MapL3Flags.PERSISTED_LAST_POINT
 
         expected_pred_ephem = quality_flags & MapL3Flags.PREDICTIVE_EPHEMERIS
-        expected_nominal_alpha_proton = (
-            quality_flags & MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO
-        )
+        expected_nominal_alpha_proton = quality_flags & MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO
         expected_persisted_last_point = quality_flags & MapL3Flags.PERSISTED_LAST_POINT
 
         intensity_map_data = IntensityMapData(
@@ -1118,8 +1002,7 @@ def test_healpix_intensity_map_data_to_skymap(self):
             latitude=fake_data_per_pixel * 2.2,
             longitude=fake_data_per_pixel * 2.3,
             exposure_factor=fake_data_per_energy_per_pixel * 2.2,
-            obs_date=np.datetime64("1970-01-01T00:00:00")
-            + fake_data_per_energy_per_pixel * 10000,
+            obs_date=np.datetime64("1970-01-01T00:00:00") + fake_data_per_energy_per_pixel * 10000,
             obs_date_range=fake_data_per_energy_per_pixel * 3.2,
             solid_angle=fake_data_per_pixel * 3.4,
             ena_intensity=fake_data_per_energy_per_pixel * 2.2,
@@ -1233,9 +1116,7 @@ def test_healpix_intensity_map_data_to_skymap(self):
                 actual_dataset.data_vars[key].dims,
             )
         for key in ["latitude", "longitude", "solid_angle"]:
-            self.assertEqual(
-                (CoordNames.GENERIC_PIXEL.value,), actual_dataset.data_vars[key].dims
-            )
+            self.assertEqual((CoordNames.GENERIC_PIXEL.value,), actual_dataset.data_vars[key].dims)
         # @formatter:on
 
     def test_healpix_intensity_map_data_to_skymap_with_no_sp(self):
@@ -1261,8 +1142,7 @@ def test_healpix_intensity_map_data_to_skymap_with_no_sp(self):
             latitude=fake_data_per_pixel * 2.2,
             longitude=fake_data_per_pixel * 2.3,
             exposure_factor=fake_data_per_energy_per_pixel * 2.2,
-            obs_date=np.datetime64("1970-01-01T00:00:00")
-            + fake_data_per_energy_per_pixel * 10000,
+            obs_date=np.datetime64("1970-01-01T00:00:00") + fake_data_per_energy_per_pixel * 10000,
             obs_date_range=fake_data_per_energy_per_pixel * 3.2,
             solid_angle=fake_data_per_pixel * 3.4,
             ena_intensity=fake_data_per_energy_per_pixel * 2.2,
@@ -1328,9 +1208,7 @@ def test_calculate_datetime_weighted_average(self):
         self.assertEqual(TT2000_EPOCH, average_obs_date.data[2])
         self.assertTrue(average_obs_date.mask[2])
 
-        np.testing.assert_equal(
-            weights, original_weights, "should not mutate the input weights"
-        )
+        np.testing.assert_equal(weights, original_weights, "should not mutate the input weights")
 
     def test_lo_isn_data_read_from_path(self):
         path_to_cdf = (
@@ -1378,13 +1256,9 @@ def test_lo_isn_data_read_from_path(self):
                 actual.exposure_factor,
                 read_numeric_variable(expected["exposure_factor"]),
             )
-            np.testing.assert_array_equal(
-                actual.latitude_delta, expected["latitude_delta"][...]
-            )
+            np.testing.assert_array_equal(actual.latitude_delta, expected["latitude_delta"][...])
             np.testing.assert_array_equal(actual.latitude, expected["latitude"][...])
-            np.testing.assert_array_equal(
-                actual.longitude_delta, expected["longitude_delta"][...]
-            )
+            np.testing.assert_array_equal(actual.longitude_delta, expected["longitude_delta"][...])
             np.testing.assert_array_equal(actual.longitude, expected["longitude"][...])
             np.testing.assert_array_equal(
                 actual.solid_angle, read_numeric_variable(expected["solid_angle"])
diff --git a/tests/maps/test_rectangular_survival_probability.py b/tests/maps/test_rectangular_survival_probability.py
index 12321f32..6fd53714 100644
--- a/tests/maps/test_rectangular_survival_probability.py
+++ b/tests/maps/test_rectangular_survival_probability.py
@@ -1,12 +1,12 @@
-import dataclasses
 import copy
+import dataclasses
 from datetime import datetime
-from unittest.mock import patch, sentinel, call, MagicMock
+from unittest.mock import MagicMock, call, patch, sentinel
 
 import numpy as np
 import spiceypy
 import xarray as xr
-from imap_processing.ena_maps.ena_maps import RectangularSkyMap, PointingSet
+from imap_processing.ena_maps.ena_maps import PointingSet, RectangularSkyMap
 from imap_processing.ena_maps.utils.coordinates import CoordNames
 from imap_processing.spice import geometry
 from imap_processing.spice.geometry import SpiceFrame
@@ -19,9 +19,9 @@
 )
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 from imap_l3_processing.maps.rectangular_survival_probability import (
-    Sensor,
-    RectangularSurvivalProbabilitySkyMap,
     RectangularSurvivalProbabilityPointingSet,
+    RectangularSurvivalProbabilitySkyMap,
+    Sensor,
     interpolate_angular_data_to_nearest_neighbor,
 )
 from tests.maps import test_builders
@@ -34,12 +34,10 @@ def setUp(self):
         self.num_energies = 2
         self.l1c_epoch = datetime(2025, 1, 1, 0, 30)
         self.l1c_epoch_delta = np.array([86400_000_000_000])
-        self.l1c_hae_longitude = (
-            0.05 + np.linspace(0, 360, 3600, endpoint=False) + 90
-        ).reshape((1, -1)) % 360
-        self.l1c_hae_latitude = np.linspace(-90, 90, 3600, endpoint=False).reshape(
+        self.l1c_hae_longitude = (0.05 + np.linspace(0, 360, 3600, endpoint=False) + 90).reshape(
             (1, -1)
-        )
+        ) % 360
+        self.l1c_hae_latitude = np.linspace(-90, 90, 3600, endpoint=False).reshape((1, -1))
 
         self.hi_energies = np.geomspace(1, 10000, self.num_energies)
 
@@ -47,9 +45,7 @@ def setUp(self):
             epoch=self.l1c_epoch,
             epoch_delta=self.l1c_epoch_delta,
             repointing=1,
-            epoch_j2000=np.array(
-                np.array([spiceypy.datetime2et(self.l1c_epoch)]) * 1e9
-            ),
+            epoch_j2000=np.array(np.array([spiceypy.datetime2et(self.l1c_epoch)]) * 1e9),
             exposure_times=np.arange(self.num_energies * 3600).reshape(
                 (1, self.num_energies, 3600)
             )
@@ -104,15 +100,11 @@ def tearDown(self):
         self.mock_add_spacecraft_position_and_velocity_to_pset_patcher.stop()
         self.mock_calculate_ram_mask_patcher.stop()
 
-    @patch(
-        "imap_l3_processing.maps.rectangular_survival_probability.PointingSet.__init__"
-    )
+    @patch("imap_l3_processing.maps.rectangular_survival_probability.PointingSet.__init__")
     @patch(
         "imap_l3_processing.maps.rectangular_survival_probability.add_spacecraft_position_and_velocity_to_pset"
     )
-    @patch(
-        "imap_l3_processing.maps.rectangular_survival_probability.calculate_ram_mask"
-    )
+    @patch("imap_l3_processing.maps.rectangular_survival_probability.calculate_ram_mask")
     def test_survival_probability_pointing_set_calls_parent_constructor(
         self, _, __, mock_rectangular_pointing_set_constructor
     ):
@@ -130,9 +122,7 @@ def test_survival_probability_pointing_set_calls_parent_constructor(
     @patch(
         "imap_l3_processing.maps.rectangular_survival_probability.add_spacecraft_position_and_velocity_to_pset"
     )
-    @patch(
-        "imap_l3_processing.maps.rectangular_survival_probability.calculate_ram_mask"
-    )
+    @patch("imap_l3_processing.maps.rectangular_survival_probability.calculate_ram_mask")
     def test_survival_probability_pointing_set_no_cg(
         self, mock_calculate_ram_mask, mock_add_sc_velocity_to_pset
     ):
@@ -147,9 +137,7 @@ def test_survival_probability_pointing_set_no_cg(
             False,
         )
 
-        mock_calculate_ram_mask.assert_called_once_with(
-            mock_add_sc_velocity_to_pset.return_value
-        )
+        mock_calculate_ram_mask.assert_called_once_with(mock_add_sc_velocity_to_pset.return_value)
 
         self.assertEqual(pointing_set.data["directional_mask"], [True])
 
@@ -162,9 +150,7 @@ def test_survival_probability_pointing_set(self):
             (Sensor.Lo90, 0, SpinPhase.AntiRamOnly, ~self.ram_mask),
         ]
 
-        expected_repointing_midpoint = (
-            self.l1c_hi_dataset.epoch_j2000 + self.l1c_epoch_delta / 2
-        )
+        expected_repointing_midpoint = self.l1c_hi_dataset.epoch_j2000 + self.l1c_epoch_delta / 2
 
         for sensor, expected_sensor_angle, spin_phase, expected_mask in test_cases:
             with self.subTest(f"{sensor.value}"):
@@ -176,9 +162,7 @@ def test_survival_probability_pointing_set(self):
                     self.hi_energies,
                 )
                 self.assertIsInstance(pointing_set, PointingSet)
-                self.assertEqual(
-                    pointing_set.spice_reference_frame, geometry.SpiceFrame.IMAP_HAE
-                )
+                self.assertEqual(pointing_set.spice_reference_frame, geometry.SpiceFrame.IMAP_HAE)
 
                 self.assertIn("exposure", pointing_set.data.data_vars)
                 np.testing.assert_array_equal(
@@ -196,9 +180,7 @@ def test_survival_probability_pointing_set(self):
                     pointing_set.data[CoordNames.AZIMUTH_L1C.value].values,
                 )
 
-                self.assertIn(
-                    CoordNames.ENERGY_ULTRA_L1C.value, pointing_set.data.coords
-                )
+                self.assertIn(CoordNames.ENERGY_ULTRA_L1C.value, pointing_set.data.coords)
                 np.testing.assert_array_equal(
                     self.l1c_hi_dataset.esa_energy_step,
                     pointing_set.data[CoordNames.ENERGY_ULTRA_L1C.value].values,
@@ -221,9 +203,7 @@ def test_survival_probability_pointing_set(self):
     @patch(
         "imap_l3_processing.maps.rectangular_survival_probability.apply_compton_getting_correction"
     )
-    def test_hi_cg_corrected_survival_probability_pointing_set(
-        self, mock_cg_correction
-    ):
+    def test_hi_cg_corrected_survival_probability_pointing_set(self, mock_cg_correction):
         self.mock_add_sc_velocity_to_pset.side_effect = None
         corrected_hae_longitude = np.full((1, 3, 3600), 2)
         corrected_hae_latitude = np.full((1, 3, 3600), 1)
@@ -231,9 +211,7 @@ def test_hi_cg_corrected_survival_probability_pointing_set(
         l1c_dataset = test_builders.create_l1c_pset(
             epoch=self.l1c_hi_dataset.epoch,
             epoch_delta=self.l1c_hi_dataset.epoch_delta,
-            exposures=np.array(
-                [[np.full((3600,), 1), np.full((3600,), 2), np.full((3600,), 3)]]
-            ),
+            exposures=np.array([[np.full((3600,), 1), np.full((3600,), 2), np.full((3600,), 3)]]),
         )
 
         corrected_az_el_pairs = np.stack(
@@ -336,12 +314,8 @@ def test_hi_cg_corrected_survival_probability_pointing_set(
         )
 
         pset_with_sc_velocity, actual_hf_energies = mock_cg_correction.call_args[0]
-        self.assertEqual(
-            pset_with_sc_velocity, self.mock_add_sc_velocity_to_pset.return_value
-        )
-        self.mock_calculate_ram_mask.assert_called_once_with(
-            mock_cg_correction.return_value
-        )
+        self.assertEqual(pset_with_sc_velocity, self.mock_add_sc_velocity_to_pset.return_value)
+        self.mock_calculate_ram_mask.assert_called_once_with(mock_cg_correction.return_value)
 
         expected_energies_in_eV = hi_hf_energies * 1000
         np.testing.assert_array_equal(actual_hf_energies, expected_energies_in_eV)
@@ -351,13 +325,9 @@ def test_hi_cg_corrected_survival_probability_pointing_set(
             cg_pointing_set.data["epoch"],
             self.l1c_hi_dataset.epoch_j2000 + (self.l1c_hi_dataset.epoch_delta / 2),
         )
-        np.testing.assert_array_equal(
-            cg_pointing_set.az_el_points, corrected_az_el_pairs
-        )
+        np.testing.assert_array_equal(cg_pointing_set.az_el_points, corrected_az_el_pairs)
 
-        np.testing.assert_array_equal(
-            cg_pointing_set.data["exposure"], expected_exposures
-        )
+        np.testing.assert_array_equal(cg_pointing_set.data["exposure"], expected_exposures)
 
     @patch(
         "imap_l3_processing.maps.rectangular_survival_probability.add_spacecraft_position_and_velocity_to_pset"
@@ -380,9 +350,7 @@ def test_lo_cg_corrected_survival_probability_pointing_set(
         l1c_dataset = test_builders.create_l1c_pset(
             epoch=self.l1c_hi_dataset.epoch,
             epoch_delta=None,
-            exposures=np.array(
-                [[np.full((3600,), 1), np.full((3600,), 2), np.full((3600,), 3)]]
-            ),
+            exposures=np.array([[np.full((3600,), 1), np.full((3600,), 2), np.full((3600,), 3)]]),
             pointing_start_met=np.array([800_000_000]),
             pointing_end_met=np.array([800_100_000]),
         )
@@ -486,41 +454,27 @@ def test_lo_cg_corrected_survival_probability_pointing_set(
                     actual_uncorrected_pset["epoch"].values,
                     self.l1c_hi_dataset.epoch_j2000,
                 )
-                np.testing.assert_array_equal(
-                    actual_uncorrected_pset["epoch_delta"].values, None
-                )
+                np.testing.assert_array_equal(actual_uncorrected_pset["epoch_delta"].values, None)
                 np.testing.assert_array_equal(
                     actual_uncorrected_pset["pointing_start_met"].values, [800_000_000]
                 )
                 np.testing.assert_array_equal(
                     actual_uncorrected_pset["pointing_end_met"].values, [800_100_000]
                 )
-                self.assertEqual(
-                    actual_uncorrected_pset.attrs["Logical_source"], "imap_lo"
-                )
+                self.assertEqual(actual_uncorrected_pset.attrs["Logical_source"], "imap_lo")
 
-                pset_with_sc_velocity, actual_hf_energies = (
-                    mock_cg_correction.call_args[0]
-                )
-                self.assertEqual(
-                    pset_with_sc_velocity, mock_add_sc_velocity_to_pset.return_value
-                )
+                pset_with_sc_velocity, actual_hf_energies = mock_cg_correction.call_args[0]
+                self.assertEqual(pset_with_sc_velocity, mock_add_sc_velocity_to_pset.return_value)
 
                 expected_energies_in_eV = lo_hf_energies * 1000
-                np.testing.assert_array_equal(
-                    actual_hf_energies, expected_energies_in_eV
-                )
+                np.testing.assert_array_equal(actual_hf_energies, expected_energies_in_eV)
 
                 np.testing.assert_array_equal(
                     cg_pointing_set.data["epoch"], expected_pointing_epoch_midpoint
                 )
-                np.testing.assert_array_equal(
-                    cg_pointing_set.az_el_points, corrected_az_el_pairs
-                )
+                np.testing.assert_array_equal(cg_pointing_set.az_el_points, corrected_az_el_pairs)
 
-                np.testing.assert_array_equal(
-                    cg_pointing_set.data["exposure"], expected_exposures
-                )
+                np.testing.assert_array_equal(cg_pointing_set.data["exposure"], expected_exposures)
 
     def test_exposure_weighting_with_interpolated_survival_probabilities(self):
         test_cases = [
@@ -532,9 +486,9 @@ def test_exposure_weighting_with_interpolated_survival_probabilities(self):
             with self.subTest(spin_phase):
                 self.hi_energies = np.array([10, 10_000])
                 self.glows_data.energy = np.array([1, 100, 100_000])
-                self.glows_data.probability_of_survival = np.repeat(
-                    [2, 4, 7], 360
-                ).reshape(1, 3, 360)
+                self.glows_data.probability_of_survival = np.repeat([2, 4, 7], 360).reshape(
+                    1, 3, 360
+                )
 
                 expected_interpolated_survival_probabilities = (
                     np.repeat([3, 6], 3600).reshape(1, 2, 3600)
@@ -550,14 +504,10 @@ def test_exposure_weighting_with_interpolated_survival_probabilities(self):
                     self.hi_energies,
                 )
 
-                self.assertIn(
-                    "survival_probability_times_exposure", pointing_set.data.data_vars
-                )
+                self.assertIn("survival_probability_times_exposure", pointing_set.data.data_vars)
                 self.assertEqual(
                     (1, self.num_energies, 3600),
-                    pointing_set.data[
-                        "survival_probability_times_exposure"
-                    ].values.shape,
+                    pointing_set.data["survival_probability_times_exposure"].values.shape,
                 )
 
                 np.testing.assert_array_equal(
@@ -565,9 +515,7 @@ def test_exposure_weighting_with_interpolated_survival_probabilities(self):
                     pointing_set.data["survival_probability_times_exposure"].values,
                 )
 
-                np.testing.assert_array_equal(
-                    pointing_set.data["directional_mask"], expected_mask
-                )
+                np.testing.assert_array_equal(pointing_set.data["directional_mask"], expected_mask)
 
     def test_exposure_weighted_survivals_are_repeated_to_match_l1c_shape(self):
         pointing_set = RectangularSurvivalProbabilityPointingSet(
@@ -617,9 +565,7 @@ def test_survivals_matched_with_corresponding_exposures(self, mock_interpolate):
         mock_interpolate.assert_called_once()
         get_interpolated_glows_data_args = mock_interpolate.call_args_list[0].args
 
-        np.testing.assert_array_equal(
-            pset_azimuths, get_interpolated_glows_data_args[0]
-        )
+        np.testing.assert_array_equal(pset_azimuths, get_interpolated_glows_data_args[0])
         np.testing.assert_array_equal(
             self.glows_data.spin_angle, get_interpolated_glows_data_args[1]
         )
@@ -665,9 +611,7 @@ def test_survivals_matched_with_corresponding_exposures_cg_corrected(
                 self.glows_data.energy = np.array([1.25, 1.85, 3])
 
                 energy_sc = np.array([[np.full((3600,), 1250), np.full((3600,), 1850)]])
-                exposure_times = np.array(
-                    [[np.full((3600,), 10), np.full((3600,), 100)]]
-                )
+                exposure_times = np.array([[np.full((3600,), 10), np.full((3600,), 100)]])
                 l1c_dataset = create_l1c_pset(exposures=exposure_times)
 
                 corrected_hae_lon = np.ones((1, 2, 3600))
@@ -733,9 +677,7 @@ def test_survivals_matched_with_corresponding_exposures_cg_corrected(
 
                 self.assertEqual(1, mock_interpolate.call_count)
                 mock_interpolate_call_args = mock_interpolate.call_args_list[0].args
-                np.testing.assert_array_equal(
-                    pset_azimuths, mock_interpolate_call_args[0]
-                )
+                np.testing.assert_array_equal(pset_azimuths, mock_interpolate_call_args[0])
                 np.testing.assert_array_equal(
                     self.glows_data.spin_angle, mock_interpolate_call_args[1]
                 )
@@ -765,8 +707,7 @@ def test_survival_probability_pointing_set_propagates_flags(
             (GlowsL3Flags.PREDICTIVE_EPHEMERIS, 1.0, 0.0, 0.0),
             (GlowsL3Flags.PERSISTED_LAST_POINT, 0.0, 0.0, 1.0),
             (
-                GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO
-                | GlowsL3Flags.PREDICTIVE_EPHEMERIS,
+                GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO | GlowsL3Flags.PREDICTIVE_EPHEMERIS,
                 1.0,
                 1.0,
                 0.0,
@@ -778,8 +719,7 @@ def test_survival_probability_pointing_set_propagates_flags(
                 1.0,
             ),
             (
-                GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO
-                | GlowsL3Flags.PERSISTED_LAST_POINT,
+                GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO | GlowsL3Flags.PERSISTED_LAST_POINT,
                 0.0,
                 1.0,
                 1.0,
@@ -817,9 +757,7 @@ def test_survival_probability_pointing_set_propagates_flags(
                     (1, self.num_energies, 3600), expected_pred_ephem_value
                 )
                 expected_pred_ephem[:, :, 1000] = 0
-                np.testing.assert_array_equal(
-                    actual_pred_ephem, expected_pred_ephem, strict=True
-                )
+                np.testing.assert_array_equal(actual_pred_ephem, expected_pred_ephem, strict=True)
                 self.assertEqual(
                     pointing_set.data["predicted_ephemeris_flag"].dims,
                     pointing_set.data["survival_probability_times_exposure"].dims,
@@ -842,9 +780,7 @@ def test_survival_probability_pointing_set_propagates_flags(
                     pointing_set.data["survival_probability_times_exposure"].dims,
                 )
 
-                actual_persisted_last_point = pointing_set.data[
-                    "persisted_last_point_flag"
-                ].values
+                actual_persisted_last_point = pointing_set.data["persisted_last_point_flag"].values
                 expected_persisted_last_point = np.full(
                     (1, self.num_energies, 3600), expected_persisted_last_point_value
                 )
@@ -902,15 +838,11 @@ def test_interpolate_angular_data_to_nearest_neighbor(self):
     @patch(
         "imap_l3_processing.maps.rectangular_survival_probability.RectangularSkyMap.project_pset_values_to_map"
     )
-    @patch(
-        "imap_l3_processing.maps.rectangular_survival_probability.RectangularSkyMap.__init__"
-    )
+    @patch("imap_l3_processing.maps.rectangular_survival_probability.RectangularSkyMap.__init__")
     def test_survival_probability_map_construction(
         self, mock_skymap_constructor, mock_project_pset
     ):
-        class TestableRectangularSurvivalProbabilitySkyMap(
-            RectangularSurvivalProbabilitySkyMap
-        ):
+        class TestableRectangularSurvivalProbabilitySkyMap(RectangularSurvivalProbabilitySkyMap):
             def __init__(self, *args):
                 self.data_1d = MagicMock()
                 super().__init__(*args)
@@ -925,9 +857,7 @@ def __init__(self, *args):
         )
         self.assertIsInstance(actual_sky_map, RectangularSkyMap)
 
-        mock_skymap_constructor.assert_called_with(
-            sentinel.spacing_deg, sentinel.spice_frame
-        )
+        mock_skymap_constructor.assert_called_with(sentinel.spacing_deg, sentinel.spice_frame)
 
         expected_values_to_project = [
             "survival_probability_times_exposure",
@@ -986,9 +916,7 @@ def test_survival_probability_sky_map_returns_exposure_weighted_survival_probabi
         )
 
         spice_frame = SpiceFrame.IMAP_HAE
-        actual_skymap = RectangularSurvivalProbabilitySkyMap(
-            [pset1, pset2], 0.1, spice_frame
-        )
+        actual_skymap = RectangularSurvivalProbabilitySkyMap([pset1, pset2], 0.1, spice_frame)
         survival_probability_dataset = actual_skymap.to_dataset()
         expected = 3 * np.repeat(
             self.glows_data.probability_of_survival[:, [0, -1], 0:180], 10, axis=2
@@ -998,14 +926,10 @@ def test_survival_probability_sky_map_returns_exposure_weighted_survival_probabi
         survival_prob_in_skygrid_shape = np.full((1, 2, 3600, 1800), np.nan)
         survival_prob_in_skygrid_shape[:, :, 300, :] = expected
 
-        self.assertIn(
-            "exposure_weighted_survival_probabilities", survival_probability_dataset
-        )
+        self.assertIn("exposure_weighted_survival_probabilities", survival_probability_dataset)
         self.assertEqual(
             (1, 2, 3600, 1800),
-            survival_probability_dataset[
-                "exposure_weighted_survival_probabilities"
-            ].values.shape,
+            survival_probability_dataset["exposure_weighted_survival_probabilities"].values.shape,
         )
 
         actual_sp_at_relevant_long = survival_probability_dataset[
@@ -1016,9 +940,7 @@ def test_survival_probability_sky_map_returns_exposure_weighted_survival_probabi
 
         np.testing.assert_array_almost_equal(
             survival_prob_in_skygrid_shape,
-            survival_probability_dataset[
-                "exposure_weighted_survival_probabilities"
-            ].values,
+            survival_probability_dataset["exposure_weighted_survival_probabilities"].values,
         )
 
     def test_survival_probability_sky_map_returns_flags(self):
@@ -1052,8 +974,7 @@ def test_survival_probability_sky_map_returns_flags(self):
                 GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
             ),
             (
-                GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO
-                | GlowsL3Flags.PREDICTIVE_EPHEMERIS,
+                GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO | GlowsL3Flags.PREDICTIVE_EPHEMERIS,
                 GlowsL3Flags.NONE,
                 MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO | MapL3Flags.PREDICTIVE_EPHEMERIS,
             ),
@@ -1104,9 +1025,7 @@ def test_survival_probability_sky_map_returns_flags(self):
                 )
                 survival_probability_dataset = actual_skymap.to_dataset()
 
-                expected_flags_in_full_shape = np.full(
-                    (1, 2, 3600, 1800), MapL3Flags.NONE
-                )
+                expected_flags_in_full_shape = np.full((1, 2, 3600, 1800), MapL3Flags.NONE)
                 expected_flags_in_full_shape[:, :, 300, :] = expected_quality_flags
 
                 self.assertIn("quality_flags", survival_probability_dataset)
diff --git a/tests/maps/test_spectral_fit.py b/tests/maps/test_spectral_fit.py
index d1e33823..273b953f 100644
--- a/tests/maps/test_spectral_fit.py
+++ b/tests/maps/test_spectral_fit.py
@@ -1,7 +1,7 @@
 import dataclasses
 import unittest
 from datetime import datetime
-from unittest.mock import patch, Mock, sentinel
+from unittest.mock import Mock, patch, sentinel
 
 import numpy as np
 from scipy.stats import linregress
@@ -13,10 +13,10 @@
 from imap_l3_processing.maps.mpfit import mpfit
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 from imap_l3_processing.maps.spectral_fit import (
-    power_law,
+    calculate_spectral_index_for_multiple_ranges,
     fit_arrays_to_power_law,
     fit_spectral_index_map,
-    calculate_spectral_index_for_multiple_ranges,
+    power_law,
     slice_energy_range_by_bin,
 )
 from tests.test_helpers import get_test_data_path
@@ -47,12 +47,8 @@ def test_finds_best_fit(self):
 
         for name, spacial_dimension_shape in cases:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     result_A,
@@ -89,18 +85,14 @@ def test_finds_chi_squared_for_fit(self):
 
         for name, spacial_dimension_shape in cases:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     result_A,
-                    result_A_error,
+                    _result_A_error,
                     result_gamma,
-                    result_gamma_error,
+                    _result_gamma_error,
                     result_chi_square,
                 ) = fit_arrays_to_power_law(flux, uncertainty, energies)
                 fitted_flux = result_A * np.power(
@@ -109,9 +101,7 @@ def test_finds_chi_squared_for_fit(self):
                 residual = fitted_flux - flux
                 chisquared = np.sum(np.square(residual / uncertainty))
                 reduced_chisquared = chisquared / (len(energies) - 2)
-                np.testing.assert_array_almost_equal(
-                    result_chi_square, reduced_chisquared
-                )
+                np.testing.assert_array_almost_equal(result_chi_square, reduced_chisquared)
 
     def test_handles_small_fluxes(self):
         energies = np.array([5.65826829, 8.45453724, 12.70203527])
@@ -122,19 +112,15 @@ def test_handles_small_fluxes(self):
 
         for name, spacial_dimension_shape in cases:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     result_a,
-                    result_a_error,
-                    result_gamma,
-                    result_gamma_error,
-                    result_chi_square,
+                    _result_a_error,
+                    _result_gamma,
+                    _result_gamma_error,
+                    _result_chi_square,
                 ) = fit_arrays_to_power_law(flux, uncertainty, energies)
                 self.assertGreater(result_a, 0)
 
@@ -158,9 +144,7 @@ def test_spectral_fit_map(self):
             latitude=latitude,
             longitude=longitude,
             exposure_factor=np.full(full_shape, 1.0),
-            obs_date=np.ma.array(
-                np.full(full_shape, datetime(year=2010, month=1, day=1))
-            ),
+            obs_date=np.ma.array(np.full(full_shape, datetime(year=2010, month=1, day=1))),
             obs_date_range=np.full(full_shape, 100000),
             solid_angle=np.full(full_shape, 1.23),
             ena_intensity=np.array(flux_data).reshape(full_shape),
@@ -199,19 +183,11 @@ def test_spectral_fit_map(self):
         np.testing.assert_array_almost_equal(
             spectral_intensity_map.energy_delta_plus, [expected_energy_plus]
         )
-        np.testing.assert_equal(
-            spectral_intensity_map.energy_label, [expected_energy_label]
-        )
+        np.testing.assert_equal(spectral_intensity_map.energy_label, [expected_energy_label])
 
-        np.testing.assert_array_almost_equal(
-            spectral_intensity_map.longitude, data.longitude
-        )
-        np.testing.assert_array_almost_equal(
-            spectral_intensity_map.latitude, data.latitude
-        )
-        np.testing.assert_array_almost_equal(
-            spectral_intensity_map.solid_angle, data.solid_angle
-        )
+        np.testing.assert_array_almost_equal(spectral_intensity_map.longitude, data.longitude)
+        np.testing.assert_array_almost_equal(spectral_intensity_map.latitude, data.latitude)
+        np.testing.assert_array_almost_equal(spectral_intensity_map.solid_angle, data.solid_angle)
 
     def test_spectral_fit_fields_other_than_fit_fields(self):
         input_energies = np.array([1, 10, 99]) + 0.5
@@ -272,12 +248,8 @@ def test_spectral_fit_fields_other_than_fit_fields(self):
         np.testing.assert_array_equal(
             output.obs_date, np.full(expected_ena_shape, datetime(2026, 1, 1))
         )
-        np.testing.assert_array_equal(
-            output.obs_date_range, np.full(expected_ena_shape, 2)
-        )
-        np.testing.assert_array_equal(
-            output.exposure_factor, np.full(expected_ena_shape, 6)
-        )
+        np.testing.assert_array_equal(output.obs_date_range, np.full(expected_ena_shape, 2))
+        np.testing.assert_array_equal(output.exposure_factor, np.full(expected_ena_shape, 6))
 
         expected_quality_flags = np.full(expected_ena_shape, MapL3Flags.NONE)
         expected_quality_flags[0, 0, 0] = MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO
@@ -303,18 +275,14 @@ def test_finds_best_fit_with_nan_in_flux(self):
 
         for name, spacial_dimension_shape in cases:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     scalar_coefficients,
-                    scalar_coefficient_error,
+                    _scalar_coefficient_error,
                     result,
-                    result_error,
+                    _result_error,
                     chisq,
                 ) = fit_arrays_to_power_law(flux, uncertainty, energies)
                 np.testing.assert_array_equal(
@@ -324,9 +292,7 @@ def test_finds_best_fit_with_nan_in_flux(self):
                     scalar_coefficients,
                     np.array(true_A).reshape(1, 1, *spacial_dimension_shape),
                 )
-                np.testing.assert_array_equal(
-                    chisq, np.zeros((1, 1, *spacial_dimension_shape))
-                )
+                np.testing.assert_array_equal(chisq, np.zeros((1, 1, *spacial_dimension_shape)))
 
     def test_spectral_fit_map_negative_gammas(self):
         epoch = np.array([datetime.now()])
@@ -348,9 +314,7 @@ def test_spectral_fit_map_negative_gammas(self):
             latitude=latitude,
             longitude=longitude,
             exposure_factor=np.full(full_shape, 1.0),
-            obs_date=np.ma.array(
-                np.full(full_shape, datetime(year=2010, month=1, day=1))
-            ),
+            obs_date=np.ma.array(np.full(full_shape, datetime(year=2010, month=1, day=1))),
             obs_date_range=np.full(full_shape, 100000),
             solid_angle=np.full(full_shape, 1.23),
             ena_intensity=np.array(flux_data).reshape(full_shape),
@@ -391,19 +355,11 @@ def test_spectral_fit_map_negative_gammas(self):
         np.testing.assert_array_almost_equal(
             spectral_intensity_map.energy_delta_plus, [expected_energy_plus]
         )
-        np.testing.assert_equal(
-            spectral_intensity_map.energy_label, [expected_energy_label]
-        )
+        np.testing.assert_equal(spectral_intensity_map.energy_label, [expected_energy_label])
 
-        np.testing.assert_array_almost_equal(
-            spectral_intensity_map.longitude, data.longitude
-        )
-        np.testing.assert_array_almost_equal(
-            spectral_intensity_map.latitude, data.latitude
-        )
-        np.testing.assert_array_almost_equal(
-            spectral_intensity_map.solid_angle, data.solid_angle
-        )
+        np.testing.assert_array_almost_equal(spectral_intensity_map.longitude, data.longitude)
+        np.testing.assert_array_almost_equal(spectral_intensity_map.latitude, data.latitude)
+        np.testing.assert_array_almost_equal(spectral_intensity_map.solid_angle, data.solid_angle)
 
     def test_finds_best_fit_with_nan_in_uncertainty(self):
         energies = np.geomspace(1, 10, 23)
@@ -420,18 +376,14 @@ def test_finds_best_fit_with_nan_in_uncertainty(self):
             ("healpix", (1,)),
         ]:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     scalar_coefficients,
-                    scalar_coefficient_error,
+                    _scalar_coefficient_error,
                     result,
-                    result_error,
+                    _result_error,
                     chisq,
                 ) = fit_arrays_to_power_law(flux, uncertainty, energies)
                 np.testing.assert_array_equal(
@@ -441,9 +393,7 @@ def test_finds_best_fit_with_nan_in_uncertainty(self):
                     scalar_coefficients,
                     np.array(true_A).reshape(1, 1, *spacial_dimension_shape),
                 )
-                np.testing.assert_array_equal(
-                    chisq, np.zeros((1, 1, *spacial_dimension_shape))
-                )
+                np.testing.assert_array_equal(chisq, np.zeros((1, 1, *spacial_dimension_shape)))
 
     def test_finds_best_fit_with_zero_in_flux_and_uncertainty(self):
         energies = np.geomspace(1, 10, 23)
@@ -459,18 +409,14 @@ def test_finds_best_fit_with_zero_in_flux_and_uncertainty(self):
             ("healpix", (1,)),
         ]:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     scalar_coefficients,
-                    scalar_coefficient_error,
+                    _scalar_coefficient_error,
                     result,
-                    result_error,
+                    _result_error,
                     chisq,
                 ) = fit_arrays_to_power_law(flux, uncertainty, energies)
                 np.testing.assert_array_equal(
@@ -480,9 +426,7 @@ def test_finds_best_fit_with_zero_in_flux_and_uncertainty(self):
                     scalar_coefficients,
                     np.array(true_A).reshape(1, 1, *spacial_dimension_shape),
                 )
-                np.testing.assert_array_equal(
-                    chisq, np.zeros((1, 1, *spacial_dimension_shape))
-                )
+                np.testing.assert_array_equal(chisq, np.zeros((1, 1, *spacial_dimension_shape)))
 
     def test_finds_best_fit_with_ibex_data(self):
         energies = np.array([0.71, 1.11, 1.74, 2.73, 4.29])
@@ -547,18 +491,14 @@ def test_finds_best_fit_with_zeros_in_flux_and_not_uncertainty(self):
             ("healpix", (1,)),
         ]:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     scalar_coefficients,
-                    scalar_coefficient_error,
+                    _scalar_coefficient_error,
                     result,
-                    result_error,
+                    _result_error,
                     chisq,
                 ) = fit_arrays_to_power_law(flux, uncertainty, energies)
                 np.testing.assert_array_almost_equal(
@@ -587,12 +527,8 @@ def test_returns_nan_when_only_one_point_is_valid(self):
             ("healpix", (1,)),
         ]:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
                 (
                     scalar_coefficients,
                     scalar_coefficient_error,
@@ -631,12 +567,8 @@ def test_returns_nan_when_there_are_less_than_2_positive_fluxes(self):
             ("healpix", (1,)),
         ]:
             with self.subTest(name):
-                flux = np.array(flux_data).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
-                uncertainty = np.array(errors).reshape(
-                    1, len(energies), *spacial_dimension_shape
-                )
+                flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
+                uncertainty = np.array(errors).reshape(1, len(energies), *spacial_dimension_shape)
 
                 (
                     scalar_coefficients,
@@ -670,12 +602,8 @@ def test_spectral_fit_can_fit_multiple_energy_ranges(self):
         input_energy_range_2 = np.geomspace(101, 10000, 12)
         true_A_range_1, true_gamma_range_1 = 2.0, 1.5
         true_A_range_2, true_gamma_range_2 = 0.1, 3.5
-        flux_data_range_1 = true_A_range_1 * np.power(
-            input_energy_range_1, -true_gamma_range_1
-        )
-        flux_data_range_2 = true_A_range_2 * np.power(
-            input_energy_range_2, -true_gamma_range_2
-        )
+        flux_data_range_1 = true_A_range_1 * np.power(input_energy_range_1, -true_gamma_range_1)
+        flux_data_range_2 = true_A_range_2 * np.power(input_energy_range_2, -true_gamma_range_2)
         longitude = np.array([45])
         latitude = np.array([90])
         errors_range_1 = 0.1 * np.abs(flux_data_range_1)
@@ -691,9 +619,9 @@ def test_spectral_fit_can_fit_multiple_energy_ranges(self):
         quality_flags_range_2 = np.full((12,), MapL3Flags.NONE)
         quality_flags_range_2[1] = MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO
         quality_flags_range_2[2] = MapL3Flags.PREDICTIVE_EPHEMERIS
-        quality_flags = np.concat(
-            (quality_flags_range_1, quality_flags_range_2)
-        ).reshape(full_shape)
+        quality_flags = np.concat((quality_flags_range_1, quality_flags_range_2)).reshape(
+            full_shape
+        )
 
         expected_quality_flags = np.array(
             [
@@ -712,9 +640,7 @@ def test_spectral_fit_can_fit_multiple_energy_ranges(self):
             latitude=latitude,
             longitude=longitude,
             exposure_factor=np.full(full_shape, 1.0),
-            obs_date=np.ma.array(
-                np.full(full_shape, datetime(year=2010, month=1, day=1))
-            ),
+            obs_date=np.ma.array(np.full(full_shape, datetime(year=2010, month=1, day=1))),
             obs_date_range=np.full(full_shape, 100000),
             solid_angle=np.full(full_shape, 1.23),
             ena_intensity=flux,
@@ -762,14 +688,10 @@ def test_spectral_fit_can_fit_multiple_energy_ranges(self):
             np.array([6.5887234, 902.0219449]),
         )
         np.testing.assert_array_equal(spectral_index_map_data.epoch, epoch)
-        np.testing.assert_array_equal(
-            spectral_index_map_data.epoch_delta, data.epoch_delta
-        )
+        np.testing.assert_array_equal(spectral_index_map_data.epoch_delta, data.epoch_delta)
         np.testing.assert_array_equal(spectral_index_map_data.latitude, latitude)
         np.testing.assert_array_equal(spectral_index_map_data.longitude, longitude)
-        np.testing.assert_array_equal(
-            spectral_index_map_data.solid_angle, data.solid_angle
-        )
+        np.testing.assert_array_equal(spectral_index_map_data.solid_angle, data.solid_angle)
 
         np.testing.assert_array_equal(
             spectral_index_map_data.energy_label, ["0.5 - 100.5", "100.5 - 10000.5"]
@@ -809,19 +731,15 @@ def test_spectral_fit_returns_nan_if_fit_status_is_not_positive_or_equal_to_five
             for status_code in invalid_status_cases:
                 with self.subTest(f"Pixelization: {name}, status_code: {status_code}"):
                     mock_mpfit.return_value = Mock(status=status_code, params=(0, 0))
-                    flux = np.array(flux_data).reshape(
-                        1, len(energies), *spacial_dimension_shape
-                    )
+                    flux = np.array(flux_data).reshape(1, len(energies), *spacial_dimension_shape)
                     uncertainty = np.array(errors).reshape(
                         1, len(energies), *spacial_dimension_shape
                     )
 
-                    scalar, scalar_error, result, result_error, chisq = (
-                        fit_arrays_to_power_law(flux, uncertainty, energies)
-                    )
-                    expected_nan_result = np.full(
-                        (1, 1, *spacial_dimension_shape), np.nan
+                    scalar, scalar_error, result, result_error, chisq = fit_arrays_to_power_law(
+                        flux, uncertainty, energies
                     )
+                    expected_nan_result = np.full((1, 1, *spacial_dimension_shape), np.nan)
                     np.testing.assert_array_equal(result, expected_nan_result)
                     np.testing.assert_array_equal(result_error, expected_nan_result)
                     np.testing.assert_array_equal(scalar, expected_nan_result)
@@ -829,9 +747,7 @@ def test_spectral_fit_returns_nan_if_fit_status_is_not_positive_or_equal_to_five
                     np.testing.assert_array_equal(chisq, expected_nan_result)
 
     @patch("imap_l3_processing.maps.spectral_fit.mpfit", wraps=mpfit)
-    @patch(
-        "imap_l3_processing.maps.spectral_fit.scipy.stats.linregress", wraps=linregress
-    )
+    @patch("imap_l3_processing.maps.spectral_fit.scipy.stats.linregress", wraps=linregress)
     def test_passes_initial_guess_to_mpfit_based_on_linear_fit_in_log_space(
         self, mock_linregress, mock_mpfit
     ):
diff --git a/tests/maps/test_survival_probability_processing.py b/tests/maps/test_survival_probability_processing.py
index 60cb9fbd..c0f7f55a 100644
--- a/tests/maps/test_survival_probability_processing.py
+++ b/tests/maps/test_survival_probability_processing.py
@@ -1,5 +1,5 @@
 from datetime import datetime
-from unittest.mock import sentinel, patch, call, Mock
+from unittest.mock import Mock, call, patch, sentinel
 
 import numpy as np
 import xarray as xr
@@ -11,8 +11,8 @@
 )
 from imap_l3_processing.maps.map_descriptors import (
     PixelSize,
-    parse_map_descriptor,
     ReferenceFrame,
+    parse_map_descriptor,
 )
 from imap_l3_processing.maps.map_models import (
     GlowsL3eRectangularMapInputData,
@@ -20,14 +20,14 @@
 )
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 from imap_l3_processing.maps.survival_probability_processing import (
-    process_survival_probabilities,
     combine_glows_l3e_with_l1c_pointing,
     filter_bad_days,
+    process_survival_probabilities,
 )
 from tests.maps.test_builders import (
-    create_rectangular_intensity_map_data,
     create_l1c_pset,
     create_l3e_pset,
+    create_rectangular_intensity_map_data,
 )
 from tests.spice_test_case import SpiceTestCase
 from tests.test_helpers import create_dataclass_mock
@@ -93,12 +93,8 @@ def test_process_survival_probability(
 
         computed_survival_probabilities = rng.random((1, 9, 90, 45))
         quality_flags = np.full((1, 9, 90, 45), MapL3Flags.NONE)
-        quality_flags[rng.random((1, 9, 90, 45)) > 0.8] = (
-            MapL3Flags.PREDICTIVE_EPHEMERIS
-        )
-        quality_flags[rng.random((1, 9, 90, 45)) > 0.7] = (
-            MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO
-        )
+        quality_flags[rng.random((1, 9, 90, 45)) > 0.8] = MapL3Flags.PREDICTIVE_EPHEMERIS
+        quality_flags[rng.random((1, 9, 90, 45)) > 0.7] = MapL3Flags.NOMINAL_ALPHA_PROTON_RATIO
 
         mock_survival_skymap.return_value.to_dataset.return_value = xr.Dataset(
             data_vars={
@@ -129,9 +125,7 @@ def test_process_survival_probability(
             },
         )
 
-        survival_data = process_survival_probabilities(
-            dependencies, SpiceFrame.IMAP_DPS
-        )
+        survival_data = process_survival_probabilities(dependencies, SpiceFrame.IMAP_DPS)
 
         mock_filter_bad_days.assert_called_once_with(sentinel.l1c_data)
 
@@ -182,8 +176,7 @@ def test_process_survival_probability(
         )
         np.testing.assert_array_equal(
             survival_data.intensity_map_data.ena_intensity_stat_uncert,
-            intensity_map_data.ena_intensity_stat_uncert
-            / computed_survival_probabilities,
+            intensity_map_data.ena_intensity_stat_uncert / computed_survival_probabilities,
         )
         np.testing.assert_array_equal(
             survival_data.intensity_map_data.ena_intensity_sys_err,
@@ -200,8 +193,7 @@ def test_process_survival_probability(
         )
         np.testing.assert_array_equal(
             survival_data.intensity_map_data.bg_intensity_stat_uncert,
-            intensity_map_data.bg_intensity_stat_uncert
-            / computed_survival_probabilities,
+            intensity_map_data.bg_intensity_stat_uncert / computed_survival_probabilities,
         )
 
         np.testing.assert_array_equal(
@@ -211,14 +203,12 @@ def test_process_survival_probability(
 
         np.testing.assert_array_equal(
             survival_data.intensity_map_data.ena_intensity_sys_err_minus,
-            intensity_map_data.ena_intensity_sys_err_minus
-            / computed_survival_probabilities,
+            intensity_map_data.ena_intensity_sys_err_minus / computed_survival_probabilities,
         )
 
         np.testing.assert_array_equal(
             survival_data.intensity_map_data.ena_intensity_sys_err_plus,
-            intensity_map_data.ena_intensity_sys_err_plus
-            / computed_survival_probabilities,
+            intensity_map_data.ena_intensity_sys_err_plus / computed_survival_probabilities,
         )
 
         np.testing.assert_array_equal(
@@ -301,9 +291,7 @@ def test_process_survival_probability_cg_correction_argument(
             input_map_flux = rng.random((1, 9, 90, 45))
             epoch = datetime.now()
 
-            input_map = create_rectangular_intensity_map_data(
-                epoch=[epoch], flux=input_map_flux
-            )
+            input_map = create_rectangular_intensity_map_data(epoch=[epoch], flux=input_map_flux)
 
             input_map.intensity_map_data.energy = sentinel.hi_l2_energies
 
@@ -335,9 +323,7 @@ def test_process_survival_probability_cg_correction_argument(
             ]
 
             computed_survival_probabilities = rng.random((1, 9, 90, 45))
-            quality_flags = np.full_like(
-                computed_survival_probabilities, MapL3Flags.NONE
-            )
+            quality_flags = np.full_like(computed_survival_probabilities, MapL3Flags.NONE)
 
             mock_survival_skymap.return_value.to_dataset.return_value = xr.Dataset(
                 {
@@ -411,30 +397,30 @@ def test_integration_uses_fill_values_for_missing_l3e_data(self):
             create_l1c_pset(
                 epoch=t1,
                 repointing=1,
-                hae_longitude=np.concat(
-                    [np.full((1800), 304 + 2), np.full((1800), 124 + 2)]
-                )[np.newaxis, :],
+                hae_longitude=np.concat([np.full((1800), 304 + 2), np.full((1800), 124 + 2)])[
+                    np.newaxis, :
+                ],
             ),
             create_l1c_pset(
                 epoch=t2,
                 repointing=2,
-                hae_longitude=np.concat(
-                    [np.full((1800), 312 + 2), np.full((1800), 132 + 2)]
-                )[np.newaxis, :],
+                hae_longitude=np.concat([np.full((1800), 312 + 2), np.full((1800), 132 + 2)])[
+                    np.newaxis, :
+                ],
             ),
             create_l1c_pset(
                 epoch=t3,
                 repointing=3,
-                hae_longitude=np.concat(
-                    [np.full((1800), 316 + 2), np.full((1800), 136 + 2)]
-                )[np.newaxis, :],
+                hae_longitude=np.concat([np.full((1800), 316 + 2), np.full((1800), 136 + 2)])[
+                    np.newaxis, :
+                ],
             ),
             create_l1c_pset(
                 epoch=t4,
                 repointing=4,
-                hae_longitude=np.concat(
-                    [np.full((1800), 320 + 2), np.full((1800), 140 + 2)]
-                )[np.newaxis, :],
+                hae_longitude=np.concat([np.full((1800), 320 + 2), np.full((1800), 140 + 2)])[
+                    np.newaxis, :
+                ],
             ),
         ]
         l3e_psets = [
@@ -452,9 +438,7 @@ def test_integration_uses_fill_values_for_missing_l3e_data(self):
         expected_sky_strip = np.full(45, 2.0)
         default_sp_sky_strip = np.full(45, np.nan)
 
-        output_map = process_survival_probabilities(
-            survival_dependencies, SpiceFrame.IMAP_HAE
-        )
+        output_map = process_survival_probabilities(survival_dependencies, SpiceFrame.IMAP_HAE)
         np.testing.assert_equal(
             output_map.intensity_map_data.ena_intensity[0, 0, 76, :], expected_sky_strip
         )
diff --git a/tests/scripts/test_convert_product_definition_to_yaml.py b/tests/scripts/test_convert_product_definition_to_yaml.py
index d5c8c03e..c103f6d6 100644
--- a/tests/scripts/test_convert_product_definition_to_yaml.py
+++ b/tests/scripts/test_convert_product_definition_to_yaml.py
@@ -36,7 +36,7 @@ def test_parse_required_for_data_with_multiple_depend(self):
         }
 
         rows = [
-            [k for k in row_columns.keys()],
+            [k for k in row_columns],
             [v[0] for v in row_columns.values()],
             [v[1] for v in row_columns.values()],
             [v[2] for v in row_columns.values()],
diff --git a/tests/swapi/_helpers.py b/tests/swapi/_helpers.py
index e0e90591..6aed11f7 100644
--- a/tests/swapi/_helpers.py
+++ b/tests/swapi/_helpers.py
@@ -1,5 +1,4 @@
 from datetime import datetime
-from typing import Optional
 
 import numpy as np
 from spacepy import pycdf
@@ -16,7 +15,6 @@
 from imap_l3_processing.swapi.response.swapi_response import ResponseGrid, SwapiResponse
 from tests.test_helpers import get_test_data_path, get_test_instrument_team_data_path
 
-
 # Calibration CSVs shipped with the repo. Loading the full SwapiResponse from
 # these triggers the same code path the production pipeline uses.
 SWAPI_AZIMUTHAL_TRANSMISSION_PATH = get_test_instrument_team_data_path(
@@ -34,7 +32,7 @@
 
 
 def load_swapi_response(
-    warm_cache_voltages: Optional[np.ndarray] = None,
+    warm_cache_voltages: np.ndarray | None = None,
 ) -> SwapiResponse:
     """Build a `SwapiResponse` from the CSV files."""
     response = SwapiResponse.from_files(
diff --git a/tests/swapi/l3a/science/pickup_ion/test_build_collapsed_response_grid.py b/tests/swapi/l3a/science/pickup_ion/test_build_collapsed_response_grid.py
index 3b0fd3dc..083a20d2 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_build_collapsed_response_grid.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_build_collapsed_response_grid.py
@@ -34,9 +34,7 @@
 class BuildCollapsedResponseGridTest(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
-        swapi_response = load_swapi_response(
-            warm_cache_voltages=np.array([_ESA_VOLTAGE])
-        )
+        swapi_response = load_swapi_response(warm_cache_voltages=np.array([_ESA_VOLTAGE]))
         cls.response_grid = swapi_response.get_response_grid(
             NOMINAL_TEST_EPOCH_TT2000, _ESA_VOLTAGE, _SPECIES
         )
@@ -45,9 +43,7 @@ def setUpClass(cls):
         cls.reference_h = reference["h_truth_km3_per_s"].to_numpy()
 
     def test_grid_matches_precomputed_shell_integral_reference(self):
-        speed_in_sw_frame = build_default_v_prime_grid_kms(
-            self.response_grid, _BULK_SPEED
-        )
+        speed_in_sw_frame = build_default_v_prime_grid_kms(self.response_grid, _BULK_SPEED)
         collapsed = build_collapsed_response_grid(
             self.response_grid,
             bulk_speed=_BULK_SPEED,
@@ -69,9 +65,7 @@ def test_grid_matches_precomputed_shell_integral_reference(self):
             msg="production v' axis upper endpoint must match reference",
         )
 
-        h_truth = np.interp(
-            collapsed.speed_in_sw_frame, self.reference_v_prime, self.reference_h
-        )
+        h_truth = np.interp(collapsed.speed_in_sw_frame, self.reference_v_prime, self.reference_h)
 
         # Compare only where the reference is meaningfully above the noise
         # floor. Near v' extremes both implementations differ in their
@@ -83,9 +77,7 @@ def test_grid_matches_precomputed_shell_integral_reference(self):
         trusted = h_truth > 0.05 * peak
         self.assertGreater(trusted.sum(), 16, "trusted region too small")
 
-        rel_err = (
-            np.abs(collapsed.values[trusted] - h_truth[trusted]) / h_truth[trusted]
-        )
+        rel_err = np.abs(collapsed.values[trusted] - h_truth[trusted]) / h_truth[trusted]
         worst = int(np.argmax(rel_err))
         worst_index = int(np.flatnonzero(trusted)[worst])
         self.assertLess(
@@ -123,9 +115,7 @@ def test_matches_shell_integral_when_grid_cell_aligned_with_singularity(self):
         # dblquad truth — while sr_idx 21 is still inside the passband-filter
         # cutoff (passband > 1e-3) so the cos guard genuinely activates.
         esa_voltage = 10000.0
-        swapi_response = load_swapi_response(
-            warm_cache_voltages=np.array([esa_voltage])
-        )
+        swapi_response = load_swapi_response(warm_cache_voltages=np.array([esa_voltage]))
         response_grid = swapi_response.get_response_grid(
             NOMINAL_TEST_EPOCH_TT2000, esa_voltage, _SPECIES
         )
@@ -139,9 +129,7 @@ def test_matches_shell_integral_when_grid_cell_aligned_with_singularity(self):
         cos_delta_azimuth_target = 1.0 - 5e-7
         cos_angle_target = cos_delta_azimuth_target * cos_elevation
         v_singular_kms = float(
-            np.sqrt(
-                speed**2 + bulk_speed**2 - 2 * cos_angle_target * speed * bulk_speed
-            )
+            np.sqrt(speed**2 + bulk_speed**2 - 2 * cos_angle_target * speed * bulk_speed)
         )
 
         collapsed = build_collapsed_response_grid(
diff --git a/tests/swapi/l3a/science/pickup_ion/test_calculate_coincidence_rate.py b/tests/swapi/l3a/science/pickup_ion/test_calculate_coincidence_rate.py
index fd4a5929..a35bf1f6 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_calculate_coincidence_rate.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_calculate_coincidence_rate.py
@@ -32,9 +32,7 @@
 from tests.test_helpers import get_test_data_path, get_test_instrument_team_data_path
 
 _REFERENCE_CSV_PATH = get_test_data_path("swapi/pui_count_rate_reference.csv")
-_DENSITY_LUT_PATH = get_test_instrument_team_data_path(
-    "swapi/density-of-neutral-helium-lut.dat"
-)
+_DENSITY_LUT_PATH = get_test_instrument_team_data_path("swapi/density-of-neutral-helium-lut.dat")
 
 # Must match scripts/swapi/pui_xarray_reference.py so the production kernel is
 # evaluated at the same point as the precomputed reference CSV.
@@ -69,9 +67,7 @@ def test_matches_xarray_reference_per_voltage(self):
         )
         bulk_sw_per_bin = np.broadcast_to(bulk_vec, (1, voltage_v.size, 3)).copy()
 
-        swapi_response = load_swapi_response(
-            warm_cache_voltages=voltage_v.astype(float)
-        )
+        swapi_response = load_swapi_response(warm_cache_voltages=voltage_v.astype(float))
         chunk_response = build_chunk_collapsed_response(
             swapi_response=swapi_response,
             voltages_v=voltage_v.astype(float),
@@ -94,9 +90,7 @@ def test_matches_xarray_reference_per_voltage(self):
         # rtol covers the deep-falloff collapse difference (production reads a
         # few percent low there); atol covers the low-rate tail where the two
         # quadratures' relative spread is large but absolute rates are tiny.
-        np.testing.assert_allclose(
-            production_rate_hz, reference_rate_hz, atol=0.1, rtol=0.03
-        )
+        np.testing.assert_allclose(production_rate_hz, reference_rate_hz, atol=0.1, rtol=0.03)
 
 
 if __name__ == "__main__":
diff --git a/tests/swapi/l3a/science/pickup_ion/test_calculate_pickup_ion_values.py b/tests/swapi/l3a/science/pickup_ion/test_calculate_pickup_ion_values.py
index bde4148a..d21edbd5 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_calculate_pickup_ion_values.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_calculate_pickup_ion_values.py
@@ -81,9 +81,7 @@ def setUpClass(cls):
             bulk_sw_per_bin_kms=bulk_sw_per_bin_swapi_kms,
             time_as_tt2000=NOMINAL_TEST_EPOCH_TT2000,
             species=Species.HELIUM_PLUS,
-            cutoff_speed_max_kms=_SOLAR_WIND_SPEED_INERTIAL_KMS
-            * MAX_CUTOFF_SPEED_RATIO
-            * 1.1,
+            cutoff_speed_max_kms=_SOLAR_WIND_SPEED_INERTIAL_KMS * MAX_CUTOFF_SPEED_RATIO * 1.1,
         )
         noiseless_count_rates = (
             calculate_coincidence_rate(
@@ -126,9 +124,7 @@ def test_recovers_the_generating_parameters(self):
             ),
         ]:
             with self.subTest(parameter=name):
-                self.assertAlmostEqual(
-                    fitted.nominal_value, truth, delta=truth * 1e-6, msg=name
-                )
+                self.assertAlmostEqual(fitted.nominal_value, truth, delta=truth * 1e-6, msg=name)
 
     def test_the_fit_is_accepted_and_every_reported_value_is_finite(self):
         self.assertEqual(int(self.fit_result.flags), int(SwapiL3Flags.NONE))
@@ -165,11 +161,7 @@ def test_wrong_input_shapes_are_rejected(self):
             ),
             (
                 "count rates given on the full sweep instead of the coarse sweep",
-                {
-                    "coincidence_count_rates": np.zeros(
-                        (_N_SWEEPS, SWAPI_SWEEP_BIN_COUNT)
-                    )
-                },
+                {"coincidence_count_rates": np.zeros((_N_SWEEPS, SWAPI_SWEEP_BIN_COUNT))},
             ),
             (
                 "count rates holding a number of sweeps other than the 50 in a window",
@@ -177,11 +169,7 @@ def test_wrong_input_shapes_are_rejected(self):
             ),
             (
                 "bulk velocities given on the full sweep instead of the coarse sweep",
-                {
-                    "bulk_sw_per_bin_swapi_kms": np.zeros(
-                        (_N_SWEEPS, SWAPI_SWEEP_BIN_COUNT, 3)
-                    )
-                },
+                {"bulk_sw_per_bin_swapi_kms": np.zeros((_N_SWEEPS, SWAPI_SWEEP_BIN_COUNT, 3))},
             ),
             (
                 "bulk velocities missing their component axis",
@@ -212,9 +200,7 @@ def test_wrong_input_shapes_are_rejected(self):
 class CalculatePickupIonValuesFillTest(unittest.TestCase):
     """Tests for fill value logic in `calculate_pickup_ion_values`."""
 
-    MODULE_PATH = (
-        "imap_l3_processing.swapi.l3a.science.pickup_ion.calculate_pickup_ion_values"
-    )
+    MODULE_PATH = "imap_l3_processing.swapi.l3a.science.pickup_ion.calculate_pickup_ion_values"
     ENERGY_PER_COARSE_STEP = np.linspace(100.0, 8000.0, _N_COARSE_BINS)
     ENERGY_RANGE_ADMITTING_EVERY_BIN = (0.0, 1.0e9)
     MODELED_RATES = np.full((_N_SWEEPS, _N_COARSE_BINS), 3.0)
@@ -264,9 +250,7 @@ def _run_calculate_with_mocked_fit(
 
         with (
             patch(f"{module_path}.build_chunk_collapsed_response") as mock_build,
-            patch(
-                f"{module_path}.scipy.optimize.least_squares", return_value=fake_result
-            ),
+            patch(f"{module_path}.scipy.optimize.least_squares", return_value=fake_result),
             patch(
                 f"{module_path}.compute_hc3_parameter_covariance",
                 return_value=np.diag(log_parameter_variances),
@@ -279,15 +263,9 @@ def _run_calculate_with_mocked_fit(
                 f"{module_path}.calculate_pickup_ion_fit_energy_range",
                 return_value=self.ENERGY_RANGE_ADMITTING_EVERY_BIN,
             ),
-            patch(
-                f"{module_path}.is_good_fit", return_value=fit_is_good
-            ) as mock_is_good_fit,
-            patch(
-                f"{module_path}.calculate_helium_pui_density"
-            ) as mock_calculate_density,
-            patch(
-                f"{module_path}.calculate_helium_pui_temperature"
-            ) as mock_calculate_temperature,
+            patch(f"{module_path}.is_good_fit", return_value=fit_is_good) as mock_is_good_fit,
+            patch(f"{module_path}.calculate_helium_pui_density") as mock_calculate_density,
+            patch(f"{module_path}.calculate_helium_pui_temperature") as mock_calculate_temperature,
         ):
             mock_build.return_value = MagicMock()
             fit_result = calculate_pickup_ion_values(
@@ -380,9 +358,7 @@ def test_coarse_quantities_are_used_as_given(self):
         np.testing.assert_allclose(
             response_args["voltages_v"], self.ENERGY_PER_COARSE_STEP / SWAPI_L2_K_FACTOR
         )
-        np.testing.assert_allclose(
-            response_args["bulk_sw_per_bin_kms"], bulk_sw_per_bin_swapi_kms
-        )
+        np.testing.assert_allclose(response_args["bulk_sw_per_bin_kms"], bulk_sw_per_bin_swapi_kms)
         np.testing.assert_allclose(
             run.is_good_fit_mock.call_args.kwargs["observed_rates"],
             np.tile(count_rates_per_step, (_N_SWEEPS, 1)),
@@ -412,9 +388,7 @@ def test_is_good_fit_receives_correct_input(
         np.testing.assert_allclose(modeled_params["cutoff_speed"], 450.0)
 
         goodness_of_fit_args = run.is_good_fit_mock.call_args.kwargs
-        np.testing.assert_array_equal(
-            goodness_of_fit_args["model_rates"], self.MODELED_RATES
-        )
+        np.testing.assert_array_equal(goodness_of_fit_args["model_rates"], self.MODELED_RATES)
         np.testing.assert_allclose(goodness_of_fit_args["cutoff_speed_kms"], 450.0)
         np.testing.assert_allclose(goodness_of_fit_args["ionization_rate"], 1e-7)
         np.testing.assert_allclose(
@@ -448,9 +422,7 @@ def test_accepted_fit_reports_the_moment_integrals(self):
         run = self._run_calculate_with_mocked_fit(nominal=self._good_nominal())
 
         self.assertIs(run.fit_result.density, run.calculate_density_mock.return_value)
-        self.assertIs(
-            run.fit_result.temperature, run.calculate_temperature_mock.return_value
-        )
+        self.assertIs(run.fit_result.temperature, run.calculate_temperature_mock.return_value)
 
     def test_solar_wind_speed_in_the_sun_frame_is_the_rtn_vector_sum(self):
         """The model is defined against the Sun-frame solar wind speed, which is
@@ -516,16 +488,12 @@ def test_edges_are_scaled_from_the_proton_energy_of_the_given_bulk_speed(self):
             with self.subTest(case=label):
                 bulk_speed = solar_wind_bulk_speed_kms * units.km / units.s
                 proton_energy_per_charge_volts = (
-                    (0.5 * constants.m_p * bulk_speed**2 / constants.e.si)
-                    .to(units.V)
-                    .value
+                    (0.5 * constants.m_p * bulk_speed**2 / constants.e.si).to(units.V).value
                 )
                 nominal_alpha_peak = 2 * proton_energy_per_charge_volts
                 nominal_pickup_ion_cutoff = 16 * proton_energy_per_charge_volts
                 expected_upper_edge = nominal_pickup_ion_cutoff
-                expected_lower_edge = np.sqrt(
-                    nominal_alpha_peak * nominal_pickup_ion_cutoff
-                )
+                expected_lower_edge = np.sqrt(nominal_alpha_peak * nominal_pickup_ion_cutoff)
 
                 lower_edge, upper_edge = calculate_pickup_ion_fit_energy_range(
                     solar_wind_bulk_speed_kms
@@ -548,9 +516,7 @@ def test_edges_scale_with_the_square_of_the_bulk_speed(self):
         """Doubling the bulk speed quadruples both window edges, since the edges
         are fixed multiples of a kinetic energy."""
         lower_edge, upper_edge = calculate_pickup_ion_fit_energy_range(350.0)
-        doubled_lower_edge, doubled_upper_edge = calculate_pickup_ion_fit_energy_range(
-            700.0
-        )
+        doubled_lower_edge, doubled_upper_edge = calculate_pickup_ion_fit_energy_range(700.0)
 
         self.assertAlmostEqual(doubled_lower_edge / lower_edge, 4.0)
         self.assertAlmostEqual(doubled_upper_edge / upper_edge, 4.0)
diff --git a/tests/swapi/l3a/science/pickup_ion/test_density_of_neutral_helium_lookup_table.py b/tests/swapi/l3a/science/pickup_ion/test_density_of_neutral_helium_lookup_table.py
index 60a36790..5c30023f 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_density_of_neutral_helium_lookup_table.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_density_of_neutral_helium_lookup_table.py
@@ -48,9 +48,7 @@ def test_scalar_distance_returns_scalar_density(self):
 
     def test_negative_angle_wraps_via_modulo(self):
         lut = _table_with_360_anchor()
-        np.testing.assert_array_equal(
-            lut.density(np.array([-180.0]), np.array([0.2])), [0.0225]
-        )
+        np.testing.assert_array_equal(lut.density(np.array([-180.0]), np.array([0.2])), [0.0225])
 
     def test_table_extension_to_360_when_input_only_reaches_180(self):
         lut = _table_without_360_anchor()
@@ -59,21 +57,15 @@ def test_table_extension_to_360_when_input_only_reaches_180(self):
 
     def test_distance_above_grid_returns_fill(self):
         lut = _table_with_360_anchor()
-        np.testing.assert_array_equal(
-            lut.density(np.array([0.0]), np.array([5.0])), [0.0]
-        )
+        np.testing.assert_array_equal(lut.density(np.array([0.0]), np.array([5.0])), [0.0])
 
     def test_density_at_grid_point(self):
         lut = _table_with_360_anchor()
-        np.testing.assert_allclose(
-            lut.density(np.array([0.0]), np.array([0.1])), [0.01]
-        )
+        np.testing.assert_allclose(lut.density(np.array([0.0]), np.array([0.1])), [0.01])
 
     def test_density_below_lower_limit(self):
         lut = _table_with_360_anchor()
-        np.testing.assert_allclose(
-            lut.density(np.array([0.0]), np.array([0.1 / 2])), [0.01 / 2]
-        )
+        np.testing.assert_allclose(lut.density(np.array([0.0]), np.array([0.1 / 2])), [0.01 / 2])
 
 
 class TestTableExtension(TestCase):
diff --git a/tests/swapi/l3a/science/pickup_ion/test_goodness_of_fit.py b/tests/swapi/l3a/science/pickup_ion/test_goodness_of_fit.py
index 81cdd175..1fb6942d 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_goodness_of_fit.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_goodness_of_fit.py
@@ -4,12 +4,12 @@
 
 from imap_l3_processing.swapi.constants import SWAPI_BACKGROUND_RATE
 from imap_l3_processing.swapi.l3a.science.pickup_ion.goodness_of_fit import (
+    CUTOFF_DROP_RATIO,
     MAX_CUTOFF_SPEED_KMS,
     MAX_CUTOFF_SPEED_RATIO,
     MAX_IONIZATION_RATE,
     MIN_CUTOFF_SPEED_RATIO,
     MIN_IONIZATION_RATE,
-    CUTOFF_DROP_RATIO,
     is_good_fit,
 )
 
@@ -47,14 +47,14 @@ def test_fit_acceptance_criteria(self):
         observed_rates = model_rates + SWAPI_BACKGROUND_RATE
 
         max_cutoff = MAX_CUTOFF_SPEED_KMS
-        defaults = dict(
-            esa_energies=esa_energies,
-            model_rates=model_rates,
-            observed_rates=observed_rates,
-            cutoff_speed_kms=max_cutoff - 50.0,
-            sw_speed_kms=400.0,
-            ionization_rate=1e-7,
-        )
+        defaults = {
+            "esa_energies": esa_energies,
+            "model_rates": model_rates,
+            "observed_rates": observed_rates,
+            "cutoff_speed_kms": max_cutoff - 50.0,
+            "sw_speed_kms": 400.0,
+            "ionization_rate": 1e-7,
+        }
 
         chunk_mean_model_rates = model_rates.mean(axis=0)
         peak_model_rate = chunk_mean_model_rates.max()
@@ -62,41 +62,34 @@ def test_fit_acceptance_criteria(self):
             chunk_mean_model_rates >= peak_model_rate * CUTOFF_DROP_RATIO
         ].max()
         past_cutoff_mask = esa_energies > cutoff_mask_energy
-        assert (
-            past_cutoff_mask.sum() == 4
-        )  # 4 points by construction: three zero, one nonzero
+        assert past_cutoff_mask.sum() == 4  # 4 points by construction: three zero, one nonzero
 
         def extra_counts_past_cutoff(fraction: float) -> dict:
-            return dict(
-                observed_rates=model_rates
-                + past_cutoff_mask * peak_model_rate * fraction
-            )
+            return {"observed_rates": model_rates + past_cutoff_mask * peak_model_rate * fraction}
 
         def poisson_sampled_observed_rates() -> dict:
             livetime = 0.145
             expected_counts = observed_rates * livetime
             sampled_counts = np.random.default_rng(0).poisson(expected_counts)
-            return dict(observed_rates=sampled_counts / livetime)
+            return {"observed_rates": sampled_counts / livetime}
 
         cases = {
             "all good": (True, {}),
             "cutoff just below maximum": (
                 True,
-                dict(cutoff_speed_kms=max_cutoff - 1.0),
+                {"cutoff_speed_kms": max_cutoff - 1.0},
             ),
-            "cutoff at maximum": (True, dict(cutoff_speed_kms=max_cutoff)),
-            "cutoff above maximum": (False, dict(cutoff_speed_kms=max_cutoff + 1.0)),
-            "model underpredicts a little": (True, dict(model_rates=model_rates * 0.9)),
-            "model underpredicts a lot": (False, dict(model_rates=model_rates * 0.8)),
+            "cutoff at maximum": (True, {"cutoff_speed_kms": max_cutoff}),
+            "cutoff above maximum": (False, {"cutoff_speed_kms": max_cutoff + 1.0}),
+            "model underpredicts a little": (True, {"model_rates": model_rates * 0.9}),
+            "model underpredicts a lot": (False, {"model_rates": model_rates * 0.8}),
             "small extra counts bit past cutoff": (True, extra_counts_past_cutoff(0.3)),
             "too much past cutoff": (False, extra_counts_past_cutoff(0.5)),
             "counting noise only": (True, poisson_sampled_observed_rates()),
         }
         for case_name, (expected, overrides) in cases.items():
             with self.subTest(case_name):
-                self.assertEqual(
-                    expected, is_good_fit(**{**defaults, **overrides}), msg=case_name
-                )
+                self.assertEqual(expected, is_good_fit(**{**defaults, **overrides}), msg=case_name)
 
     def test_fitted_parameter_range_criteria(self):
         """A fit whose cutoff speed leaves the allowed multiple of the bulk
@@ -106,14 +99,14 @@ def test_fitted_parameter_range_criteria(self):
 
         # 300 km/s keeps 1.5 * v_sw under MAX_CUTOFF_SPEED_KMS
         sw_speed = 300.0
-        defaults = dict(
-            esa_energies=esa_energies,
-            model_rates=model_rates,
-            observed_rates=model_rates + SWAPI_BACKGROUND_RATE,
-            cutoff_speed_kms=sw_speed,
-            sw_speed_kms=sw_speed,
-            ionization_rate=1e-7,
-        )
+        defaults = {
+            "esa_energies": esa_energies,
+            "model_rates": model_rates,
+            "observed_rates": model_rates + SWAPI_BACKGROUND_RATE,
+            "cutoff_speed_kms": sw_speed,
+            "sw_speed_kms": sw_speed,
+            "ionization_rate": 1e-7,
+        }
 
         min_cutoff_speed = sw_speed * MIN_CUTOFF_SPEED_RATIO
         max_cutoff_speed = sw_speed * MAX_CUTOFF_SPEED_RATIO
@@ -121,55 +114,53 @@ def test_fitted_parameter_range_criteria(self):
             "all good": (True, {}),
             "cutoff speed below the lowest allowed multiple": (
                 False,
-                dict(cutoff_speed_kms=min_cutoff_speed - 1.0),
+                {"cutoff_speed_kms": min_cutoff_speed - 1.0},
             ),
             "cutoff speed at the lowest allowed multiple of the bulk speed": (
                 True,
-                dict(cutoff_speed_kms=min_cutoff_speed),
+                {"cutoff_speed_kms": min_cutoff_speed},
             ),
             "cutoff speed above the lowest allowed multiple": (
                 True,
-                dict(cutoff_speed_kms=min_cutoff_speed + 1.0),
+                {"cutoff_speed_kms": min_cutoff_speed + 1.0},
             ),
             "cutoff speed below the highest allowed multiple": (
                 True,
-                dict(cutoff_speed_kms=max_cutoff_speed - 1.0),
+                {"cutoff_speed_kms": max_cutoff_speed - 1.0},
             ),
             "cutoff speed at the highest allowed multiple of the bulk speed": (
                 True,
-                dict(cutoff_speed_kms=max_cutoff_speed),
+                {"cutoff_speed_kms": max_cutoff_speed},
             ),
             "cutoff speed above the highest allowed multiple": (
                 False,
-                dict(cutoff_speed_kms=max_cutoff_speed + 1.0),
+                {"cutoff_speed_kms": max_cutoff_speed + 1.0},
             ),
             "ionization rate below the lower limit": (
                 False,
-                dict(ionization_rate=MIN_IONIZATION_RATE * 0.99),
+                {"ionization_rate": MIN_IONIZATION_RATE * 0.99},
             ),
             "ionization rate at the lower limit": (
                 True,
-                dict(ionization_rate=MIN_IONIZATION_RATE),
+                {"ionization_rate": MIN_IONIZATION_RATE},
             ),
             "ionization rate above the lower limit": (
                 True,
-                dict(ionization_rate=MIN_IONIZATION_RATE * 1.01),
+                {"ionization_rate": MIN_IONIZATION_RATE * 1.01},
             ),
             "ionization rate below the upper limit": (
                 True,
-                dict(ionization_rate=MAX_IONIZATION_RATE * 0.99),
+                {"ionization_rate": MAX_IONIZATION_RATE * 0.99},
             ),
             "ionization rate at the upper limit": (
                 True,
-                dict(ionization_rate=MAX_IONIZATION_RATE),
+                {"ionization_rate": MAX_IONIZATION_RATE},
             ),
             "ionization rate above the upper limit": (
                 False,
-                dict(ionization_rate=MAX_IONIZATION_RATE * 1.01),
+                {"ionization_rate": MAX_IONIZATION_RATE * 1.01},
             ),
         }
         for case_name, (expected, overrides) in cases.items():
             with self.subTest(case_name):
-                self.assertEqual(
-                    expected, is_good_fit(**{**defaults, **overrides}), msg=case_name
-                )
+                self.assertEqual(expected, is_good_fit(**{**defaults, **overrides}), msg=case_name)
diff --git a/tests/swapi/l3a/science/pickup_ion/test_moments.py b/tests/swapi/l3a/science/pickup_ion/test_moments.py
index 301be7d7..ded0e906 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_moments.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_moments.py
@@ -42,15 +42,11 @@ def _quad_discontinuity_points(
     cutoff_speed: float, lut: DensityOfNeutralHeliumLookupTable
 ) -> tuple[float, float, float]:
     radius_au = _DISTANCE_KM / ONE_AU_IN_KM
-    lower = (lut.grid[1][0] / radius_au) ** (
-        1.0 / SWAPI_PUI_COOLING_INDEX
-    ) * cutoff_speed
+    lower = (lut.grid[1][0] / radius_au) ** (1.0 / SWAPI_PUI_COOLING_INDEX) * cutoff_speed
     return (0.0, lower, cutoff_speed)
 
 
-def _quad_density_reference(
-    cutoff_speed: float, lut: DensityOfNeutralHeliumLookupTable
-) -> float:
+def _quad_density_reference(cutoff_speed: float, lut: DensityOfNeutralHeliumLookupTable) -> float:
     integral, _ = scipy.integrate.quad(
         lambda v: _reference_vdf(v, cutoff_speed, lut) * v * v,
         0.0,
@@ -115,8 +111,8 @@ def setUp(self) -> None:
             / "swapi"
             / "imap_swapi_l2_density-of-neutral-helium-lut-text-not-cdf_20241023_v002.cdf"
         )
-        self.density_of_neutral_helium_lookup_table = (
-            DensityOfNeutralHeliumLookupTable.from_file(density_lut_path)
+        self.density_of_neutral_helium_lookup_table = DensityOfNeutralHeliumLookupTable.from_file(
+            density_lut_path
         )
 
     def _calculate_density(self, cutoff_speed):
diff --git a/tests/swapi/l3a/science/pickup_ion/test_utils.py b/tests/swapi/l3a/science/pickup_ion/test_utils.py
index 1ce8b3a6..cf1ede5c 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_utils.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_utils.py
@@ -63,12 +63,8 @@ def test_adds_imap_inertial_velocity_to_rotated_input(self, mock_spice):
             ]
         )
         np.testing.assert_array_almost_equal(output_velocity, expected)
-        mock_spice.sxform.assert_called_with(
-            "INPUT_FRAME", "OUTPUT_FRAME", ephemeris_time
-        )
-        mock_spice.spkezr.assert_called_with(
-            "IMAP", ephemeris_time, "OUTPUT_FRAME", "NONE", "SUN"
-        )
+        mock_spice.sxform.assert_called_with("INPUT_FRAME", "OUTPUT_FRAME", ephemeris_time)
+        mock_spice.spkezr.assert_called_with("IMAP", ephemeris_time, "OUTPUT_FRAME", "NONE", "SUN")
 
 
 class ConvertVelocityToReferenceFrameTest(SpiceTestCase):
@@ -78,9 +74,7 @@ def test_applies_state_block_of_sxform_to_velocity(self, mock_spice):
         ephemeris_time = 10_000_000
 
         input_2d = np.array([[1, 2, 3], [1, 2, 3]])
-        result_2d = convert_velocity_to_reference_frame(
-            input_2d, ephemeris_time, "FROM", "TO"
-        )
+        result_2d = convert_velocity_to_reference_frame(input_2d, ephemeris_time, "FROM", "TO")
         expected_row = (
             1 * _FAKE_SXFORM_ROTATION[3:6, 3]
             + 2 * _FAKE_SXFORM_ROTATION[3:6, 4]
@@ -89,7 +83,5 @@ def test_applies_state_block_of_sxform_to_velocity(self, mock_spice):
         np.testing.assert_array_almost_equal([expected_row, expected_row], result_2d)
         mock_spice.sxform.assert_called_with("FROM", "TO", ephemeris_time)
 
-        result_1d = convert_velocity_to_reference_frame(
-            input_2d[0], ephemeris_time, "FROM", "TO"
-        )
+        result_1d = convert_velocity_to_reference_frame(input_2d[0], ephemeris_time, "FROM", "TO")
         np.testing.assert_array_almost_equal(expected_row, result_1d)
diff --git a/tests/swapi/l3a/science/pickup_ion/test_vasyliunas_siscoe_distribution.py b/tests/swapi/l3a/science/pickup_ion/test_vasyliunas_siscoe_distribution.py
index c8fd14e2..ddbe4ad7 100644
--- a/tests/swapi/l3a/science/pickup_ion/test_vasyliunas_siscoe_distribution.py
+++ b/tests/swapi/l3a/science/pickup_ion/test_vasyliunas_siscoe_distribution.py
@@ -39,8 +39,8 @@ def setUp(self) -> None:
             / "swapi"
             / "imap_swapi_l2_density-of-neutral-helium-lut-text-not-cdf_20241023_v002.cdf"
         )
-        self.density_of_neutral_helium_lookup_table = (
-            DensityOfNeutralHeliumLookupTable.from_file(density_lut_path)
+        self.density_of_neutral_helium_lookup_table = DensityOfNeutralHeliumLookupTable.from_file(
+            density_lut_path
         )
 
     def _evaluate(self, cutoff_speed: float) -> np.ndarray:
@@ -75,8 +75,7 @@ def test_scales_the_cutoff_cell_by_the_fraction_below_it_and_zeros_the_cells_abo
         cutoff_index = 300
         fraction_below_cutoff = 0.3
         cutoff_speed = float(
-            _SPEED_GRID.centers[cutoff_index]
-            + (fraction_below_cutoff - 0.5) * _SPEED_GRID.spacing
+            _SPEED_GRID.centers[cutoff_index] + (fraction_below_cutoff - 0.5) * _SPEED_GRID.spacing
         )
 
         result = self._evaluate(cutoff_speed)
@@ -107,9 +106,7 @@ def test_treats_a_cutoff_on_the_last_node_as_a_half_cell(self, mock_density):
         np.testing.assert_allclose(result, expected, rtol=1e-12)
 
     @patch(f"{_VASYLIUNAS_SISCOE_MODULE}.DensityOfNeutralHeliumLookupTable.density")
-    def test_returns_the_uncut_filled_shell_when_the_cutoff_is_above_the_grid(
-        self, mock_density
-    ):
+    def test_returns_the_uncut_filled_shell_when_the_cutoff_is_above_the_grid(self, mock_density):
         mock_density.return_value = 1
         cutoff_speed = float(_SPEED_GRID.centers[-1] + _SPEED_GRID.spacing)
 
diff --git a/tests/swapi/l3a/science/solar_wind/alpha/test_fit_solar_wind_alpha_model.py b/tests/swapi/l3a/science/solar_wind/alpha/test_fit_solar_wind_alpha_model.py
index 48b09e13..eeb0b0fb 100644
--- a/tests/swapi/l3a/science/solar_wind/alpha/test_fit_solar_wind_alpha_model.py
+++ b/tests/swapi/l3a/science/solar_wind/alpha/test_fit_solar_wind_alpha_model.py
@@ -10,10 +10,13 @@
     PROTON_CHARGE_COULOMBS,
     PROTON_MASS_KG,
 )
+from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.l3a.science.solar_wind.alpha import (
-    fit_solar_wind_alpha_model as alpha_module,
     calculate_initial_guess as alpha_initial_guess_module,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.alpha import (
+    fit_solar_wind_alpha_model as alpha_module,
+)
 from imap_l3_processing.swapi.l3a.science.solar_wind.alpha.fit_solar_wind_alpha_model import (
     MIN_TOLERABLE_ALPHA_SPEED_RATIO,
     AlphaSolarWindFitResult,
@@ -27,18 +30,16 @@
 from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
     model_solar_wind_ideal_coincidence_rates,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
     ProtonSolarWindFitResult,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
 from imap_l3_processing.swapi.response.deadtime import deadtime_factor
-from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
 from imap_l3_processing.swapi.species import Species
 from tests.swapi._helpers import NOMINAL_TEST_EPOCH_TT2000, load_swapi_response
 
-
 # ----- module-level fixture constants --------------------------------------
 
 # 5-sweep coarse-only voltage axis: 62 bins/sweep × 5 sweeps = 310 measurements,
@@ -50,9 +51,7 @@
 _N_BINS_PER_SWEEP = 62
 _N_SWEEPS = 5
 _ONE_SWEEP_VOLTAGE = np.logspace(np.log10(3500.0), np.log10(140.0), _N_BINS_PER_SWEEP)
-_FIVE_SWEEP_VOLTAGE = np.broadcast_to(
-    _ONE_SWEEP_VOLTAGE, (_N_SWEEPS, _N_BINS_PER_SWEEP)
-).copy()
+_FIVE_SWEEP_VOLTAGE = np.broadcast_to(_ONE_SWEEP_VOLTAGE, (_N_SWEEPS, _N_BINS_PER_SWEEP)).copy()
 _N_MEAS = _FIVE_SWEEP_VOLTAGE.size
 
 # Slow-wind ground-truth moments. RTN +R points sunward, so a sunward solar
@@ -230,9 +229,7 @@ def _synthesize_proton_plus_alpha_count_rate(
             species=Species.ALPHA,
             rotation_matrices=rotation_matrices,
         )
-        alpha_true, _ = model_solar_wind_ideal_coincidence_rates(
-            alpha_params, alpha_ctx
-        )
+        alpha_true, _ = model_solar_wind_ideal_coincidence_rates(alpha_params, alpha_ctx)
         total_true = proton_true + alpha_true
     else:
         total_true = proton_true
@@ -334,9 +331,7 @@ def test_nan_magnetic_field_direction_returns_nan_filled_moments(self):
 # ----- fit_solar_wind_alpha_model — end-to-end recovery -----------------
 
 
-class TestFitAlphaMomentsRecoversTruth(
-    _SyntheticAlphaSpectrumFixture, unittest.TestCase
-):
+class TestFitAlphaMomentsRecoversTruth(_SyntheticAlphaSpectrumFixture, unittest.TestCase):
     """Tests for `fit_solar_wind_alpha_model` — end-to-end Stage-2 recovery: synthesize a proton+alpha spectrum from known truth, hand the fitter the exact proton moments, and verify it recovers (n_α, T_α, Δv) and the field-aligned alpha velocity."""
 
     @classmethod
@@ -378,16 +373,12 @@ def test_recovers_alpha_temperature(self):
 
     def test_recovers_signed_delta_v(self):
         """The fitted Δv matches the truth in magnitude and sign — LM recovers the correct basin from the Δv=0 seed."""
-        np.testing.assert_allclose(
-            self.result.delta_v.nominal_value, _TRUE_DELTA_V_KM_S, atol=0.5
-        )
+        np.testing.assert_allclose(self.result.delta_v.nominal_value, _TRUE_DELTA_V_KM_S, atol=0.5)
 
     def test_alpha_velocity_equals_proton_velocity_plus_delta_v_along_bhat(self):
         """The post-fit `velocity_rtn` satisfies the algebraic identity v_α = v_p* + Δv·B̂ exactly (not approximately) — the dataclass stores the constraint, not a free vector."""
         v_alpha = self.result.velocity_rtn_nominal()
-        expected = (
-            _TRUE_PROTON_VELOCITY_RTN + self.result.delta_v.nominal_value * _B_HAT_RTN
-        )
+        expected = _TRUE_PROTON_VELOCITY_RTN + self.result.delta_v.nominal_value * _B_HAT_RTN
         np.testing.assert_allclose(v_alpha, expected, atol=1e-9)
 
     def test_alpha_velocity_recovers_truth(self):
@@ -452,9 +443,7 @@ def setUpClass(cls):
             b_hat=cls.b_hat,
         )
         cls.alpha_velocity_truth = alpha_v
-        cls.proton_moments = _build_proton_fit_result(
-            velocity_rtn=cls.proton_velocity_rtn
-        )
+        cls.proton_moments = _build_proton_fit_result(velocity_rtn=cls.proton_velocity_rtn)
         proton_ctx, alpha_ctx = _build_proton_and_alpha_contexts(
             response=cls.response,
             count_rate=observed,
@@ -480,9 +469,7 @@ def test_recovered_delta_v_matches_dot_product_of_velocity_offset(self):
                 self.b_hat,
             )
         )
-        np.testing.assert_allclose(
-            self.result.delta_v.nominal_value, delta_along, atol=1e-9
-        )
+        np.testing.assert_allclose(self.result.delta_v.nominal_value, delta_along, atol=1e-9)
 
     def test_alpha_velocity_recovers_truth_under_tilted_bhat(self):
         """With a 10° tilted B̂, the recovered alpha velocity matches the synthesis truth vector to ~1 km/s."""
@@ -518,9 +505,7 @@ def setUp(self):
                 [0.5, 0.25, 16.0],
             ]
         )
-        velocity_triple = make_correlated_velocity(
-            self.expected_nominal, self.expected_covariance
-        )
+        velocity_triple = make_correlated_velocity(self.expected_nominal, self.expected_covariance)
         self.moments = AlphaSolarWindFitResult(
             density=ufloat(0.2, 0.01),
             temperature=ufloat(4.0e5, 1.0e3),
@@ -531,9 +516,7 @@ def setUp(self):
 
     def test_velocity_rtn_nominal_returns_per_component_nominals(self):
         """The nominal-vector accessor returns the per-component nominal_values as a length-3 ndarray."""
-        np.testing.assert_array_equal(
-            self.moments.velocity_rtn_nominal(), self.expected_nominal
-        )
+        np.testing.assert_array_equal(self.moments.velocity_rtn_nominal(), self.expected_nominal)
 
     def test_velocity_rtn_covariance_is_three_by_three(self):
         """The covariance accessor returns a 3×3 matrix matching the RTN velocity dimensionality."""
@@ -756,9 +739,7 @@ def setUpClass(cls):
 
     def test_jacobian_shape_is_n_residuals_by_three(self):
         """The analytic Jacobian has shape (N_residuals, 3) — one row per measurement bin, one column per fit parameter (log n_α, log T_α, Δv)."""
-        self.assertEqual(
-            self.analytic_jacobian.shape, (self.alpha_ctx.count_rate.size, 3)
-        )
+        self.assertEqual(self.analytic_jacobian.shape, (self.alpha_ctx.count_rate.size, 3))
 
     def test_log_density_column_equals_alpha_only_rate_times_deadtime_squared(self):
         """Because the rate is linear in n_α, the analytic ∂(observable)/∂(log n_α) column equals 𝒟²(R_total) · R_α exactly with no quadrature slack — an identity check independent of finite-difference noise."""
@@ -772,9 +753,7 @@ def test_log_density_column_equals_alpha_only_rate_times_deadtime_squared(self):
             temperature=_TRUE_ALPHA_TEMPERATURE_K,
             mass=ALPHA_PARTICLE_MASS_KG,
         )
-        alpha_rate, _ = model_solar_wind_ideal_coincidence_rates(
-            alpha_only_params, self.alpha_ctx
-        )
+        alpha_rate, _ = model_solar_wind_ideal_coincidence_rates(alpha_only_params, self.alpha_ctx)
         total_rate = self.proton_true_rate + alpha_rate
         deadtime_squared = deadtime_factor(total_rate) ** 2
         np.testing.assert_allclose(
@@ -803,9 +782,7 @@ def test_delta_v_column_matches_finite_difference(self):
         )
 
 
-class TestAlphaEvaluatorCachesEvaluation(
-    _SyntheticAlphaSpectrumFixture, unittest.TestCase
-):
+class TestAlphaEvaluatorCachesEvaluation(_SyntheticAlphaSpectrumFixture, unittest.TestCase):
     """Tests for `_AlphaEvaluator._refresh` — caches the last (residuals, jacobian) so scipy.least_squares' separate `fun` and `jac` callbacks share one forward-model evaluation per state."""
 
     @classmethod
diff --git a/tests/swapi/l3a/science/solar_wind/proton/test_calculate_initial_guess.py b/tests/swapi/l3a/science/solar_wind/proton/test_calculate_initial_guess.py
index a9d1890a..5eda8f6f 100644
--- a/tests/swapi/l3a/science/solar_wind/proton/test_calculate_initial_guess.py
+++ b/tests/swapi/l3a/science/solar_wind/proton/test_calculate_initial_guess.py
@@ -8,25 +8,24 @@
     PROTON_CHARGE_COULOMBS,
     PROTON_MASS_KG,
 )
+from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     build_solar_wind_fit_context,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.forward_model import (
     model_solar_wind_ideal_coincidence_rates,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
+    SolarWindParams,
+)
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.calculate_initial_guess import (
     INITIAL_TEMPERATURE_FLOOR_K,
     calculate_initial_guess,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
-    SolarWindParams,
-)
 from imap_l3_processing.swapi.l3a.utils import optimal_density_scale
-from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.species import Species
 from tests.swapi._helpers import NOMINAL_TEST_EPOCH_TT2000, load_swapi_response
 
-
 # RTN → SWAPI rotation. Body +Y (the SWAPI boresight / spin axis) in RTN is
 # column 1 of the transpose, i.e. -R̂_RTN. The solar wind direction (anti-
 # parallel to the spin axis) is therefore +R̂.
@@ -130,9 +129,7 @@ def test_temperature_seed_uses_documented_speed_squared_formula(self):
 
         temperature_seed_arg = patched_refine.call_args.args[3]
         expected_temperature = 60_000.0 * (peak_speed / 400.0) ** 2
-        np.testing.assert_allclose(
-            temperature_seed_arg, expected_temperature, rtol=1e-12
-        )
+        np.testing.assert_allclose(temperature_seed_arg, expected_temperature, rtol=1e-12)
 
     def test_temperature_seed_floors_at_one_ev(self):
         """At a low peak speed where 60_000·(v/400)² is below 1 eV, the temperature seed handed to the refiner is clamped to `INITIAL_TEMPERATURE_FLOOR_K`."""
@@ -213,9 +210,7 @@ def test_density_is_optimal_scale_of_unit_density_forward_model(self):
             temperature=guess.temperature,
             mass=ctx.mass_kg,
         )
-        unit_rates, _ = model_solar_wind_ideal_coincidence_rates(
-            unit_density_params, ctx
-        )
+        unit_rates, _ = model_solar_wind_ideal_coincidence_rates(unit_density_params, ctx)
         expected_density = optimal_density_scale(unit_rates, ctx.count_rate)
         np.testing.assert_allclose(guess.density, expected_density, rtol=1e-10)
 
diff --git a/tests/swapi/l3a/science/solar_wind/proton/test_escape_local_minimum.py b/tests/swapi/l3a/science/solar_wind/proton/test_escape_local_minimum.py
index 3fa41fc2..574590db 100644
--- a/tests/swapi/l3a/science/solar_wind/proton/test_escape_local_minimum.py
+++ b/tests/swapi/l3a/science/solar_wind/proton/test_escape_local_minimum.py
@@ -7,6 +7,7 @@
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     SolarWindFitContext,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton import (
     escape_local_minimum as escape_local_minimum_module,
 )
@@ -18,7 +19,6 @@
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.optimize_solar_wind_proton_params import (
     OptimizeSolarWindProtonParamsResult,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.params import SolarWindParams
 from tests.swapi._helpers import proton_params as _shared_proton_params
 
 
@@ -37,10 +37,12 @@ def _proton_params(
 
 
 def _single_sweep_ctx(
-    spin_axis_column=np.array([0.0, 1.0, 0.0]),
+    spin_axis_column: np.ndarray | None = None,
 ) -> SolarWindFitContext:
     """Single-sweep context whose +Y_inst column equals `spin_axis_column`,
     so `average_spin_axis_rtn(ctx.rotation_matrices)` returns that axis."""
+    if spin_axis_column is None:
+        spin_axis_column = np.array([0.0, 1.0, 0.0])
     rotation = np.eye(3)
     rotation[:, 1] = spin_axis_column
     return SolarWindFitContext(
@@ -109,9 +111,7 @@ def test_returns_lm1_unchanged_whenflipped_seed_exactly_at_gate(self):
                 "flipped_seed",
                 return_value=(flipped_mse_at_gate, _proton_params()),
             ),
-            patch.object(
-                escape_local_minimum_module, "_restart_from_flipped_params"
-            ) as mock_opt,
+            patch.object(escape_local_minimum_module, "_restart_from_flipped_params") as mock_opt,
         ):
             out = escape_local_minimum(lm1, ctx)
 
diff --git a/tests/swapi/l3a/science/solar_wind/proton/test_fit_solar_wind_proton_model.py b/tests/swapi/l3a/science/solar_wind/proton/test_fit_solar_wind_proton_model.py
index f11e6f1b..d8eec2b0 100644
--- a/tests/swapi/l3a/science/solar_wind/proton/test_fit_solar_wind_proton_model.py
+++ b/tests/swapi/l3a/science/solar_wind/proton/test_fit_solar_wind_proton_model.py
@@ -9,16 +9,16 @@
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     build_solar_wind_fit_context,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
+    N_STATE,
+    SolarWindParams,
+)
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.fit_solar_wind_proton_model import (
     fit_solar_wind_proton_model,
 )
 from imap_l3_processing.swapi.l3a.science.solar_wind.proton.optimize_solar_wind_proton_params import (
     OptimizeSolarWindProtonParamsResult,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
-    N_STATE,
-    SolarWindParams,
-)
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
 from imap_l3_processing.swapi.species import Species
 from tests.swapi._helpers import (
@@ -149,13 +149,9 @@ def _per_bin_rotation_matrices() -> np.ndarray:
     details don't affect what's being tested."""
     sweep_index = np.repeat(np.arange(_N_SWEEPS), _N_BINS_PER_SWEEP)
     bin_index_in_sweep = np.tile(np.arange(1, _N_BINS_PER_SWEEP + 1), _N_SWEEPS)
-    sample_times_s = (
-        sweep_index * _SWEEP_DURATION_S + bin_index_in_sweep * _SAMPLE_TIME_PER_BIN_S
-    )
+    sample_times_s = sweep_index * _SWEEP_DURATION_S + bin_index_in_sweep * _SAMPLE_TIME_PER_BIN_S
 
-    spin_axis = _ANCHOR_ROTATION_MATRIX[:, 1] / np.linalg.norm(
-        _ANCHOR_ROTATION_MATRIX[:, 1]
-    )
+    spin_axis = _ANCHOR_ROTATION_MATRIX[:, 1] / np.linalg.norm(_ANCHOR_ROTATION_MATRIX[:, 1])
     delta_phi = _SPIN_OMEGA_RAD_S * (sample_times_s - _ANCHOR_TIME_S)
 
     ax, ay, az = spin_axis
diff --git a/tests/swapi/l3a/science/solar_wind/proton/test_optimize_solar_wind_proton_params.py b/tests/swapi/l3a/science/solar_wind/proton/test_optimize_solar_wind_proton_params.py
index 99bfde20..e05ca197 100644
--- a/tests/swapi/l3a/science/solar_wind/proton/test_optimize_solar_wind_proton_params.py
+++ b/tests/swapi/l3a/science/solar_wind/proton/test_optimize_solar_wind_proton_params.py
@@ -7,18 +7,18 @@
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     build_solar_wind_fit_context,
 )
-from imap_l3_processing.swapi.l3a.science.solar_wind.proton.optimize_solar_wind_proton_params import (
-    OptimizeSolarWindProtonParamsResult,
-    optimize_solar_wind_proton_params,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
     N_STATE,
     SolarWindParams,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.proton.optimize_solar_wind_proton_params import (
+    OptimizeSolarWindProtonParamsResult,
+    optimize_solar_wind_proton_params,
+)
 from imap_l3_processing.swapi.species import Species
 from tests.swapi._helpers import (
-    NOMINAL_TEST_EPOCH_TT2000,
     NOMINAL_SWAPI_TO_RTN_ROTATION,
+    NOMINAL_TEST_EPOCH_TT2000,
     REALISTIC_ESA_VOLTAGES,
     load_swapi_response,
     proton_params,
@@ -29,9 +29,7 @@
 def _build_proton_fit_context(count_rate: np.ndarray):
     response = load_swapi_response(warm_cache_voltages=REALISTIC_ESA_VOLTAGES)
     n_sweeps = len(REALISTIC_ESA_VOLTAGES)
-    rotation_matrices = np.broadcast_to(
-        NOMINAL_SWAPI_TO_RTN_ROTATION, (n_sweeps, 3, 3)
-    ).copy()
+    rotation_matrices = np.broadcast_to(NOMINAL_SWAPI_TO_RTN_ROTATION, (n_sweeps, 3, 3)).copy()
     return build_solar_wind_fit_context(
         count_rate=count_rate,
         esa_voltage=REALISTIC_ESA_VOLTAGES,
@@ -151,9 +149,7 @@ def test_residuals_length_matches_ctx_count_rate(self):
 
     def test_jacobian_shape_is_n_residuals_by_n_state(self):
         """The jacobian has shape (n_residuals, N_STATE) — one row per residual, one column per fit parameter."""
-        self.assertEqual(
-            self.result.jacobian.shape, (self.ctx.count_rate.size, N_STATE)
-        )
+        self.assertEqual(self.result.jacobian.shape, (self.ctx.count_rate.size, N_STATE))
 
     def test_success_is_bool(self):
         """The success field is a plain Python bool rather than numpy's bool-like wrapper."""
diff --git a/tests/swapi/l3a/science/solar_wind/test_fit_context.py b/tests/swapi/l3a/science/solar_wind/test_fit_context.py
index c03ebd22..8728fa64 100644
--- a/tests/swapi/l3a/science/solar_wind/test_fit_context.py
+++ b/tests/swapi/l3a/science/solar_wind/test_fit_context.py
@@ -32,9 +32,7 @@ def _build_response_grid(time_as_tt2000, voltage, species):
             oa_passband=None,
             central_speed=float(voltage),
             central_effective_area=0.0,
-            azimuthal_transmission=AzimuthalTransmissionGrid(
-                values=np.zeros(1), spacing=0.1
-            ),
+            azimuthal_transmission=AzimuthalTransmissionGrid(values=np.zeros(1), spacing=0.1),
         )
 
     response.get_response_grid.side_effect = _build_response_grid
@@ -73,17 +71,13 @@ def test_subset_with_all_bin_indices_returns_equivalent_context(self):
         # `subset` rebuilds response_grids as a numba.typed.List; cast to a
         # plain list for value-level comparison.
         self.assertEqual(list(kept.response_grids), self.full_ctx.response_grids)
-        np.testing.assert_array_equal(
-            kept.rotation_matrices, self.full_ctx.rotation_matrices
-        )
+        np.testing.assert_array_equal(kept.rotation_matrices, self.full_ctx.rotation_matrices)
 
     def test_subset_picks_bin_axis_at_the_given_indices_preserving_sweeps(self):
         """Selecting bin indices [0, 2] yields a context with those two bin columns from each sweep; count_rate and esa_voltage stay 2D as (n_sweeps, n_kept_bins)."""
         kept = self.full_ctx.subset(np.array([0, 2]))
         np.testing.assert_array_equal(kept.count_rate, [[10.0, 30.0], [40.0, 60.0]])
-        np.testing.assert_array_equal(
-            kept.esa_voltage, [[100.0, 300.0], [400.0, 600.0]]
-        )
+        np.testing.assert_array_equal(kept.esa_voltage, [[100.0, 300.0], [400.0, 600.0]])
         # Flat sweep-major bin-minor order: s0b0, s0b2, s1b0, s1b2
         self.assertEqual(list(kept.response_grids), ["s0b0", "s0b2", "s1b0", "s1b2"])
         np.testing.assert_array_equal(
@@ -118,9 +112,7 @@ def test_keeps_all_inputs_unchanged_when_voltages_are_finite_and_positive(self):
         """When every voltage is finite and positive, the context preserves count_rate and esa_voltage verbatim and builds one ResponseGrid per bin."""
         count_rate = np.array([10.0, 20.0, 30.0])
         esa_voltage = np.array([100.0, 200.0, 300.0])
-        ctx, response = self._call_factory(
-            count_rate=count_rate, esa_voltage=esa_voltage
-        )
+        ctx, _response = self._call_factory(count_rate=count_rate, esa_voltage=esa_voltage)
         np.testing.assert_array_equal(ctx.count_rate, count_rate)
         np.testing.assert_array_equal(ctx.esa_voltage, esa_voltage)
         self.assertEqual(len(ctx.response_grids), 3)
@@ -169,9 +161,7 @@ def test_creates_response_grid_for_each_bin_in_input_order(self):
         """The factory calls `get_response_grid` once per voltage (in ravel order) and stores the resulting grids in the same order."""
         count_rate = np.array([10.0, 20.0])
         esa_voltage = np.array([100.0, 200.0])
-        ctx, response = self._call_factory(
-            count_rate=count_rate, esa_voltage=esa_voltage
-        )
+        ctx, response = self._call_factory(count_rate=count_rate, esa_voltage=esa_voltage)
         self.assertEqual(response.get_response_grid.call_count, 2)
         self.assertEqual(ctx.response_grids[0].central_speed, 100.0)
         self.assertEqual(ctx.response_grids[1].central_speed, 200.0)
diff --git a/tests/swapi/l3a/science/solar_wind/test_forward_model.py b/tests/swapi/l3a/science/solar_wind/test_forward_model.py
index 515594eb..42251c8e 100644
--- a/tests/swapi/l3a/science/solar_wind/test_forward_model.py
+++ b/tests/swapi/l3a/science/solar_wind/test_forward_model.py
@@ -7,6 +7,7 @@
     PROTON_CHARGE_COULOMBS,
     PROTON_MASS_KG,
 )
+from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     build_solar_wind_fit_context,
 )
@@ -18,16 +19,14 @@
     LOG_DENSITY_IDX,
     LOG_TEMPERATURE_IDX,
     N_STATE,
-    SolarWindParams,
     VELOCITY_SLICE,
+    SolarWindParams,
 )
-from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
 from imap_l3_processing.swapi.species import Species
 from tests.swapi._helpers import NOMINAL_TEST_EPOCH_TT2000, proton_params
 from tests.test_helpers import get_test_data_path, get_test_instrument_team_data_path
 
-
 # Reference bulk speed for the slow-wind fixture state shared by every test
 # in this module (5 cm⁻³, 100 kK protons under the default `proton_params`).
 _REF_BULK_SPEED_KM_S = 450.0
@@ -48,13 +47,7 @@
 def _esa_voltage_at_speed(speed_km_s: float) -> float:
     """ESA voltage (V) whose central proton speed equals `speed_km_s`. The
     relation is `V = ½ m_p v² / (e · k_SWAPI)`."""
-    return (
-        0.5
-        * PROTON_MASS_KG
-        * (speed_km_s * 1e3) ** 2
-        / PROTON_CHARGE_COULOMBS
-        / SWAPI_K_FACTOR
-    )
+    return 0.5 * PROTON_MASS_KG * (speed_km_s * 1e3) ** 2 / PROTON_CHARGE_COULOMBS / SWAPI_K_FACTOR
 
 
 # Putting the bulk speed at the passband center maximizes the rate and
@@ -157,9 +150,7 @@ def setUp(self):
 
     def test_rate_is_positive_when_velocity_aligns_with_boresight(self):
         """With bulk speed at the passband center and the flow aimed along boresight, the predicted rate is strictly positive."""
-        rate, _ = calculate_integral(
-            proton_params(), self.response_grid, self.rotation_matrix
-        )
+        rate, _ = calculate_integral(proton_params(), self.response_grid, self.rotation_matrix)
         self.assertGreater(rate, 0.0)
 
     def test_rate_is_linear_in_density(self):
@@ -257,12 +248,8 @@ def setUp(self):
 
     def test_log_temperature_jacobian_is_correct(self):
         """At an off-axis bulk state, the analytic log-temperature Jacobian column matches a central finite difference of the rate to within GL quadrature noise."""
-        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(
-            self.sw, self.ctx
-        )
-        fd_column = _finite_difference_jacobian_column(
-            self.state, self.ctx, LOG_TEMPERATURE_IDX
-        )
+        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(self.sw, self.ctx)
+        fd_column = _finite_difference_jacobian_column(self.state, self.ctx, LOG_TEMPERATURE_IDX)
         np.testing.assert_allclose(
             analytic_jacobian[:, LOG_TEMPERATURE_IDX],
             fd_column,
@@ -272,12 +259,8 @@ def test_log_temperature_jacobian_is_correct(self):
 
     def test_velocity_r_jacobian_is_correct(self):
         """At an off-axis bulk state, the analytic v_R Jacobian column matches a central finite difference of the rate to within GL quadrature noise."""
-        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(
-            self.sw, self.ctx
-        )
-        fd_column = _finite_difference_jacobian_column(
-            self.state, self.ctx, _VELOCITY_R_IDX
-        )
+        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(self.sw, self.ctx)
+        fd_column = _finite_difference_jacobian_column(self.state, self.ctx, _VELOCITY_R_IDX)
         np.testing.assert_allclose(
             analytic_jacobian[:, _VELOCITY_R_IDX],
             fd_column,
@@ -287,12 +270,8 @@ def test_velocity_r_jacobian_is_correct(self):
 
     def test_velocity_t_jacobian_is_correct(self):
         """At an off-axis bulk state, the analytic v_T Jacobian column matches a central finite difference of the rate to within GL quadrature noise."""
-        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(
-            self.sw, self.ctx
-        )
-        fd_column = _finite_difference_jacobian_column(
-            self.state, self.ctx, _VELOCITY_T_IDX
-        )
+        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(self.sw, self.ctx)
+        fd_column = _finite_difference_jacobian_column(self.state, self.ctx, _VELOCITY_T_IDX)
         np.testing.assert_allclose(
             analytic_jacobian[:, _VELOCITY_T_IDX],
             fd_column,
@@ -302,12 +281,8 @@ def test_velocity_t_jacobian_is_correct(self):
 
     def test_velocity_n_jacobian_is_correct(self):
         """At an off-axis bulk state, the analytic v_N Jacobian column matches a central finite difference of the rate to within GL quadrature noise."""
-        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(
-            self.sw, self.ctx
-        )
-        fd_column = _finite_difference_jacobian_column(
-            self.state, self.ctx, _VELOCITY_N_IDX
-        )
+        _, analytic_jacobian = model_solar_wind_ideal_coincidence_rates(self.sw, self.ctx)
+        fd_column = _finite_difference_jacobian_column(self.state, self.ctx, _VELOCITY_N_IDX)
         np.testing.assert_allclose(
             analytic_jacobian[:, _VELOCITY_N_IDX],
             fd_column,
diff --git a/tests/swapi/l3a/science/solar_wind/test_integration_limits.py b/tests/swapi/l3a/science/solar_wind/test_integration_limits.py
index d1981387..1dcf7349 100644
--- a/tests/swapi/l3a/science/solar_wind/test_integration_limits.py
+++ b/tests/swapi/l3a/science/solar_wind/test_integration_limits.py
@@ -3,6 +3,7 @@
 import numpy as np
 
 from imap_l3_processing.constants import PROTON_MASS_KG
+from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.l3a.science.solar_wind.azimuthal_regions import (
     REGION_OPEN_APERTURE_NEG,
     REGION_OPEN_APERTURE_POS,
@@ -23,7 +24,6 @@
     interpolate_passband,
     speed_ratio_range_at_elevation,
 )
-from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.species import Species
 from tests.swapi._helpers import (
     NOMINAL_SWAPI_TO_RTN_ROTATION,
@@ -78,9 +78,7 @@ def test_window_overlaps_passband_when_k_sigma_exceeds_offset_above_edge(self):
         bulk = v_passband_hi + 30.0
         sigma_overlap = 50.0 / SPEED_HALF_WIDTH_VTH
         T_overlap = thermal_speed_to_temperature(sigma_overlap, PROTON_MASS_KG)
-        sw_overlap = proton_params(
-            velocity_rtn=(0.0, -bulk, 0.0), temperature=T_overlap
-        )
+        sw_overlap = proton_params(velocity_rtn=(0.0, -bulk, 0.0), temperature=T_overlap)
         self.assertFalse(speed_window_misses_passband(sw_overlap, self.response_grid))
 
     def test_window_detaches_from_passband_when_k_sigma_falls_below_offset(self):
@@ -89,9 +87,7 @@ def test_window_detaches_from_passband_when_k_sigma_falls_below_offset(self):
         bulk = v_passband_hi + 30.0
         sigma_detached = 5.0 / SPEED_HALF_WIDTH_VTH
         T_detached = thermal_speed_to_temperature(sigma_detached, PROTON_MASS_KG)
-        sw_detached = proton_params(
-            velocity_rtn=(0.0, -bulk, 0.0), temperature=T_detached
-        )
+        sw_detached = proton_params(velocity_rtn=(0.0, -bulk, 0.0), temperature=T_detached)
         self.assertTrue(speed_window_misses_passband(sw_detached, self.response_grid))
 
 
@@ -131,12 +127,8 @@ def test_sg_azimuth_window_clamps_to_plus_minus_20_for_broad_distribution(self):
             sw, self.response_grid, REGION_SUNGLASSES, self.identity, 0.0
         )
         # GL nodes lie strictly inside the band.
-        np.testing.assert_array_less(
-            quadrature.azimuth_points, _SG_AZIMUTH_HI_DEG + 1e-9
-        )
-        np.testing.assert_array_less(
-            _SG_AZIMUTH_LO_DEG - 1e-9, quadrature.azimuth_points
-        )
+        np.testing.assert_array_less(quadrature.azimuth_points, _SG_AZIMUTH_HI_DEG + 1e-9)
+        np.testing.assert_array_less(_SG_AZIMUTH_LO_DEG - 1e-9, quadrature.azimuth_points)
         # The outermost 21-node GL node sits ≈0.125° inside the edge of a 40°
         # window (analytically `20°·(1 - x_GL[-1])` ≈ 0.125°). 1.5° is a loose
         # cushion above that — only meant to catch the case where the window
@@ -254,9 +246,7 @@ def setUpClass(cls):
         )
         cls.identity = np.eye(3)
         # Bulk at az=-90°: v_inst = (+v, 0, 0) ⇒ az = atan2(-v, 0) = -90°.
-        cls.sw_bulk_at_minus_90 = proton_params(
-            velocity_rtn=(+_BULK_SPEED_KM_S, 0.0, 0.0)
-        )
+        cls.sw_bulk_at_minus_90 = proton_params(velocity_rtn=(+_BULK_SPEED_KM_S, 0.0, 0.0))
 
     def test_oa_negative_region_is_active_for_bulk_at_minus_90_deg_azimuth(self):
         """A bulk at az ≈ -90° lies inside the OA- band, so the region is active and a quadrature is returned."""
@@ -308,12 +298,8 @@ def setUpClass(cls):
     def test_speed_window_lies_inside_per_elevation_passband(self):
         """For warm plasma the passband binds the window, so every GL node lies inside `[r_min(θ)·v0, r_max(θ)·v0]` at the given elevation."""
         sw = proton_params()
-        _, speed_quadrature = get_speed_quadrature(
-            sw, self.response_grid, REGION_SUNGLASSES, 0.0
-        )
-        ratio_lo, ratio_hi = speed_ratio_range_at_elevation(
-            self.response_grid.sg_passband, 0.0
-        )
+        _, speed_quadrature = get_speed_quadrature(sw, self.response_grid, REGION_SUNGLASSES, 0.0)
+        ratio_lo, ratio_hi = speed_ratio_range_at_elevation(self.response_grid.sg_passband, 0.0)
         passband_lo = self.response_grid.central_speed * ratio_lo
         passband_hi = self.response_grid.central_speed * ratio_hi
         self.assertGreaterEqual(speed_quadrature.points.min(), passband_lo)
@@ -327,9 +313,7 @@ def test_cold_plasma_window_lies_inside_bulk_plus_minus_k_vth(self):
         )
         sigma = thermal_speed(sw)
         speed = bulk_speed(sw)
-        _, speed_quadrature = get_speed_quadrature(
-            sw, self.response_grid, REGION_SUNGLASSES, 0.0
-        )
+        _, speed_quadrature = get_speed_quadrature(sw, self.response_grid, REGION_SUNGLASSES, 0.0)
         window_lo = speed - SPEED_HALF_WIDTH_VTH * sigma
         window_hi = speed + SPEED_HALF_WIDTH_VTH * sigma
         self.assertGreaterEqual(speed_quadrature.points.min(), window_lo)
@@ -343,9 +327,7 @@ def test_cold_plasma_outer_gl_nodes_sit_close_to_window_edges(self):
         )
         sigma = thermal_speed(sw)
         speed = bulk_speed(sw)
-        _, speed_quadrature = get_speed_quadrature(
-            sw, self.response_grid, REGION_SUNGLASSES, 0.0
-        )
+        _, speed_quadrature = get_speed_quadrature(sw, self.response_grid, REGION_SUNGLASSES, 0.0)
         window_lo = speed - SPEED_HALF_WIDTH_VTH * sigma
         window_hi = speed + SPEED_HALF_WIDTH_VTH * sigma
         self.assertLess(window_hi - speed_quadrature.points.max(), 2.0)
@@ -354,9 +336,7 @@ def test_cold_plasma_outer_gl_nodes_sit_close_to_window_edges(self):
     def test_speed_quadrature_arrays_are_all_15_long(self):
         """Each array on the returned `SpeedQuadrature` (points, weights, `speed_cubed_times_passband`) has the doc-prescribed Nv = 15 nodes."""
         sw = proton_params()
-        _, speed_quadrature = get_speed_quadrature(
-            sw, self.response_grid, REGION_SUNGLASSES, 0.0
-        )
+        _, speed_quadrature = get_speed_quadrature(sw, self.response_grid, REGION_SUNGLASSES, 0.0)
         self.assertEqual(speed_quadrature.points.shape, (15,))
         self.assertEqual(speed_quadrature.weights.shape, (15,))
         self.assertEqual(speed_quadrature.speed_cubed_times_passband.shape, (15,))
@@ -373,18 +353,10 @@ def test_returns_skip_when_bulk_speed_window_does_not_overlap_passband(self):
     def test_uses_region_specific_passband(self):
         """With a hot plasma so the passband binds the window in both regions, the SG and OA quadratures land on their own region's passband edge and the two windows are distinct."""
         sw = proton_params(temperature=1_000_000.0)
-        _, sg_quad = get_speed_quadrature(
-            sw, self.response_grid, REGION_SUNGLASSES, 0.0
-        )
-        _, oa_quad = get_speed_quadrature(
-            sw, self.response_grid, REGION_OPEN_APERTURE_POS, 0.0
-        )
-        sg_ratio_lo, _ = speed_ratio_range_at_elevation(
-            self.response_grid.sg_passband, 0.0
-        )
-        oa_ratio_lo, _ = speed_ratio_range_at_elevation(
-            self.response_grid.oa_passband, 0.0
-        )
+        _, sg_quad = get_speed_quadrature(sw, self.response_grid, REGION_SUNGLASSES, 0.0)
+        _, oa_quad = get_speed_quadrature(sw, self.response_grid, REGION_OPEN_APERTURE_POS, 0.0)
+        sg_ratio_lo, _ = speed_ratio_range_at_elevation(self.response_grid.sg_passband, 0.0)
+        oa_ratio_lo, _ = speed_ratio_range_at_elevation(self.response_grid.oa_passband, 0.0)
         sg_lo = self.response_grid.central_speed * sg_ratio_lo
         oa_lo = self.response_grid.central_speed * oa_ratio_lo
         # Each quadrature's lower edge sits at its own region's passband edge.
@@ -400,9 +372,7 @@ def test_speed_cubed_times_passband_is_v3_times_normalized_passband_at_each_node
     ):
         """The `speed_cubed_times_passband` array equals `v³ · P(θ, v/v0) / P(0, 1)` reconstructed from `interpolate_passband` at every GL node."""
         sw = proton_params()
-        _, speed_quadrature = get_speed_quadrature(
-            sw, self.response_grid, REGION_SUNGLASSES, 0.0
-        )
+        _, speed_quadrature = get_speed_quadrature(sw, self.response_grid, REGION_SUNGLASSES, 0.0)
         on_axis_peak = interpolate_passband(self.response_grid.sg_passband, 0.0, 1.0)
         expected = np.array(
             [
@@ -416,9 +386,7 @@ def test_speed_cubed_times_passband_is_v3_times_normalized_passband_at_each_node
                 for v in speed_quadrature.points
             ]
         )
-        np.testing.assert_allclose(
-            speed_quadrature.speed_cubed_times_passband, expected
-        )
+        np.testing.assert_allclose(speed_quadrature.speed_cubed_times_passband, expected)
 
 
 if __name__ == "__main__":
diff --git a/tests/swapi/l3a/science/solar_wind/test_params.py b/tests/swapi/l3a/science/solar_wind/test_params.py
index e1c834e3..136c9102 100644
--- a/tests/swapi/l3a/science/solar_wind/test_params.py
+++ b/tests/swapi/l3a/science/solar_wind/test_params.py
@@ -52,9 +52,7 @@ def test_from_vector_inverts_to_vector(self):
         original = proton_params(
             density=3.7, velocity_rtn=(-420.0, 5.0, -2.0), temperature=85_000.0
         )
-        round_tripped = SolarWindParams.from_vector(
-            original.to_vector(), mass=original.mass
-        )
+        round_tripped = SolarWindParams.from_vector(original.to_vector(), mass=original.mass)
         self.assertAlmostEqual(round_tripped.density, original.density)
         self.assertAlmostEqual(round_tripped.temperature, original.temperature)
         np.testing.assert_array_equal(round_tripped.velocity_rtn, original.velocity_rtn)
diff --git a/tests/swapi/l3a/science/solar_wind/test_trim_open_aperture.py b/tests/swapi/l3a/science/solar_wind/test_trim_open_aperture.py
index 0588609d..f5fe01ee 100644
--- a/tests/swapi/l3a/science/solar_wind/test_trim_open_aperture.py
+++ b/tests/swapi/l3a/science/solar_wind/test_trim_open_aperture.py
@@ -3,16 +3,16 @@
 
 import numpy as np
 
-from imap_l3_processing.swapi.l3a.science.solar_wind.trim_open_aperture import (
-    OA_SCAN_RESOLUTION,
-    OA_SCAN_THRESHOLD,
-    trim_open_aperture,
-)
 from imap_l3_processing.swapi.l3a.science.solar_wind.params import (
     SolarWindParams,
     bulk_speed,
     thermal_speed,
 )
+from imap_l3_processing.swapi.l3a.science.solar_wind.trim_open_aperture import (
+    OA_SCAN_RESOLUTION,
+    OA_SCAN_THRESHOLD,
+    trim_open_aperture,
+)
 from imap_l3_processing.swapi.response.azimuthal_transmission import (
     AzimuthalTransmissionGrid,
 )
@@ -21,7 +21,6 @@
 from tests.swapi._helpers import NOMINAL_SWAPI_TO_RTN_ROTATION, proton_params
 from tests.swapi.response.test_passband_grid import _gaussian_values_df
 
-
 # --- fixtures ---------------------------------------------------------------
 
 
@@ -57,9 +56,7 @@ def _proton_params_at_elevation(
     v_x_swapi = -speed * math.cos(math.radians(bulk_el_deg))
     v_z_swapi = -speed * math.sin(math.radians(bulk_el_deg))
     v_rtn = NOMINAL_SWAPI_TO_RTN_ROTATION @ np.array([v_x_swapi, 0.0, v_z_swapi])
-    return proton_params(
-        velocity_rtn=tuple(v_rtn), density=density, temperature=temperature
-    )
+    return proton_params(velocity_rtn=tuple(v_rtn), density=density, temperature=temperature)
 
 
 def _trim(
@@ -191,9 +188,7 @@ def test_endpoints_expand_one_node_past_threshold_crossings(self):
         # interior. The integrand reduces to the Maxwellian centered at the
         # bulk azimuth, which we recompute here.
         rg = _make_response_grid()
-        sw = proton_params(
-            velocity_rtn=(0.0, -450.0, 0.0)
-        )  # bulk_az = +90°, bulk_el = 0°
+        sw = proton_params(velocity_rtn=(0.0, -450.0, 0.0))  # bulk_az = +90°, bulk_el = 0°
 
         lo, hi = _trim(rg, sw, azimuth_lo=20.0, azimuth_hi=150.0, sg_rate=0.0)
 
@@ -202,9 +197,7 @@ def test_endpoints_expand_one_node_past_threshold_crossings(self):
         speed = bulk_speed(sw)
         central = rg.central_speed
         delta_v_sq = (
-            central**2
-            + speed**2
-            - 2.0 * central * speed * np.cos(np.radians(scan - 90.0))
+            central**2 + speed**2 - 2.0 * central * speed * np.cos(np.radians(scan - 90.0))
         )
         integrand = np.exp(-delta_v_sq / (2.0 * sigma**2))
         above_idx = np.where(integrand > OA_SCAN_THRESHOLD * integrand.max())[0]
@@ -228,13 +221,9 @@ def test_mirror_symmetric_bulk_yields_mirror_symmetric_windows(self):
         sw_pos = proton_params(velocity_rtn=(0.0, -450.0, 0.0))
         sw_neg = proton_params(velocity_rtn=(0.0, +450.0, 0.0))
 
-        lo_pos, hi_pos = _trim(
-            rg, sw_pos, azimuth_lo=20.0, azimuth_hi=150.0, sg_rate=0.0
-        )
+        lo_pos, hi_pos = _trim(rg, sw_pos, azimuth_lo=20.0, azimuth_hi=150.0, sg_rate=0.0)
         # OA-: same magnitudes, mirrored around 0.
-        lo_neg, hi_neg = _trim(
-            rg, sw_neg, azimuth_lo=-150.0, azimuth_hi=-20.0, sg_rate=0.0
-        )
+        lo_neg, hi_neg = _trim(rg, sw_neg, azimuth_lo=-150.0, azimuth_hi=-20.0, sg_rate=0.0)
 
         # The implementation picks scan-grid nodes by index, and
         # `linspace(20, 150, N)` mirrors `linspace(-150, -20, N)` up to a
diff --git a/tests/swapi/l3a/science/solar_wind/test_uncertainty_calibration.py b/tests/swapi/l3a/science/solar_wind/test_uncertainty_calibration.py
index 2dd22a74..edaace23 100644
--- a/tests/swapi/l3a/science/solar_wind/test_uncertainty_calibration.py
+++ b/tests/swapi/l3a/science/solar_wind/test_uncertainty_calibration.py
@@ -47,13 +47,12 @@
 from imap_l3_processing.swapi.response.deadtime import deadtime_factor
 from imap_l3_processing.swapi.species import Species
 from tests.swapi._helpers import (
-    NOMINAL_TEST_EPOCH_TT2000,
     NOMINAL_SWAPI_TO_RTN_ROTATION,
+    NOMINAL_TEST_EPOCH_TT2000,
     load_swapi_response,
 )
 from tests.test_helpers import run_periodically
 
-
 _N_BINS_PER_SWEEP = 62
 _N_SWEEPS = 5
 _VOLTAGE_AXIS = np.broadcast_to(
@@ -75,14 +74,10 @@ def _per_bin_rotation_matrices() -> np.ndarray:
     bins and breaks that degeneracy."""
     sweep_index = np.repeat(np.arange(_N_SWEEPS), _N_BINS_PER_SWEEP)
     bin_index_in_sweep = np.tile(np.arange(1, _N_BINS_PER_SWEEP + 1), _N_SWEEPS)
-    sample_times_s = (
-        sweep_index * _SWEEP_DURATION_S + bin_index_in_sweep * _SAMPLE_TIME_PER_BIN_S
-    )
+    sample_times_s = sweep_index * _SWEEP_DURATION_S + bin_index_in_sweep * _SAMPLE_TIME_PER_BIN_S
     spin_axis = NOMINAL_SWAPI_TO_RTN_ROTATION[:, 1]
     spin_axis = spin_axis / np.linalg.norm(spin_axis)
-    delta_phi = (-2.0 * np.pi / _SPIN_PERIOD_S) * (
-        sample_times_s - 0.5 * _SWEEP_DURATION_S
-    )
+    delta_phi = (-2.0 * np.pi / _SPIN_PERIOD_S) * (sample_times_s - 0.5 * _SWEEP_DURATION_S)
     ax, ay, az = spin_axis
     K = np.array([[0.0, -az, ay], [az, 0.0, -ax], [-ay, ax, 0.0]])
     sin_dp = np.sin(delta_phi)[:, None, None]
@@ -141,9 +136,7 @@ def _build_truth_count_rates(response, *, with_alpha: bool) -> np.ndarray:
         species=Species.PROTON,
         rotation_matrices=_ROTATION_MATRICES,
     )
-    proton_rates, _ = model_solar_wind_ideal_coincidence_rates(
-        proton_params, proton_ctx
-    )
+    proton_rates, _ = model_solar_wind_ideal_coincidence_rates(proton_params, proton_ctx)
     total_rates = proton_rates
     if with_alpha:
         alpha_velocity = _TRUE_PROTON_VELOCITY_RTN + _TRUE_DELTA_V_KM_S * _B_HAT_RTN
@@ -161,9 +154,7 @@ def _build_truth_count_rates(response, *, with_alpha: bool) -> np.ndarray:
             species=Species.ALPHA,
             rotation_matrices=_ROTATION_MATRICES,
         )
-        alpha_rates, _ = model_solar_wind_ideal_coincidence_rates(
-            alpha_params, alpha_ctx
-        )
+        alpha_rates, _ = model_solar_wind_ideal_coincidence_rates(alpha_params, alpha_ctx)
         total_rates = proton_rates + alpha_rates
     deadtime_applied = total_rates * deadtime_factor(total_rates)
     return deadtime_applied.reshape(_VOLTAGE_AXIS.shape)
@@ -180,9 +171,7 @@ def _inject_noise(truth_rates: np.ndarray, rng: np.random.Generator) -> np.ndarr
 
 
 def _velocity_component_truth(base: str, velocity_rtn: np.ndarray) -> dict:
-    return {
-        f"{base}_{axis}": float(velocity_rtn[i]) for i, axis in enumerate(_RTN_AXES)
-    }
+    return {f"{base}_{axis}": float(velocity_rtn[i]) for i, axis in enumerate(_RTN_AXES)}
 
 
 def _proton_truth_values() -> dict:
@@ -193,9 +182,7 @@ def _proton_truth_values() -> dict:
         "proton_sw_temperature": _TRUE_PROTON_TEMPERATURE_K,
         "proton_sw_speed": float(np.linalg.norm(_TRUE_PROTON_VELOCITY_RTN)),
         "proton_sw_speed_sun": float(np.linalg.norm(velocity_sun)),
-        **_velocity_component_truth(
-            "proton_sw_velocity_rtn", _TRUE_PROTON_VELOCITY_RTN
-        ),
+        **_velocity_component_truth("proton_sw_velocity_rtn", _TRUE_PROTON_VELOCITY_RTN),
     }
 
 
@@ -249,15 +236,11 @@ def _assert_calibration(
 ) -> None:
     label = species.name.lower()
     if n_good < _N_TRIALS * 0.9:
-        raise AssertionError(
-            f"{label}: only {n_good}/{_N_TRIALS} trials produced a good fit"
-        )
+        raise AssertionError(f"{label}: only {n_good}/{_N_TRIALS} trials produced a good fit")
     failures = []
     for name, samples in sorted(accumulator.items()):
         assert name in truth_values, f"no truth value declared for {name!r}"
-        values, reported_sigmas = (
-            np.asarray(column, dtype=float) for column in zip(*samples)
-        )
+        values, reported_sigmas = (np.asarray(column, dtype=float) for column in zip(*samples))
         if not np.all(np.isfinite(reported_sigmas) & (reported_sigmas > 0)):
             failures.append(f"  {name}: non-positive or non-finite reported σ")
             continue
@@ -350,9 +333,7 @@ def _run_trial(trial_seed: int) -> dict | None:
         b_hat_rtn=_B_HAT_RTN.copy(),
         quality_flag=int(alpha_moments.quality_flag),
     )
-    return _alpha_moments_from_fit(
-        chunk_result, epoch=0, sc_velocity_rtn=_SC_VELOCITY_RTN
-    )
+    return _alpha_moments_from_fit(chunk_result, epoch=0, sc_velocity_rtn=_SC_VELOCITY_RTN)
 
 
 def _run_mc_in_parallel(n_trials: int) -> tuple[dict, int]:
diff --git a/tests/swapi/l3a/science/solar_wind/test_utils.py b/tests/swapi/l3a/science/solar_wind/test_utils.py
index bfa99f8f..941d5384 100644
--- a/tests/swapi/l3a/science/solar_wind/test_utils.py
+++ b/tests/swapi/l3a/science/solar_wind/test_utils.py
@@ -24,9 +24,7 @@ class TestAverageSpinAxisRtn(unittest.TestCase):
     def test_single_rotation_returns_its_y_axis(self):
         """A single identity rotation yields +Y_RTN since column 1 of the identity is (0, 1, 0)."""
         rotation = np.eye(3)
-        np.testing.assert_array_equal(
-            average_spin_axis_rtn(rotation[np.newaxis]), [0.0, 1.0, 0.0]
-        )
+        np.testing.assert_array_equal(average_spin_axis_rtn(rotation[np.newaxis]), [0.0, 1.0, 0.0])
 
     def test_constant_axis_across_sweeps_returns_that_axis(self):
         """Five identical identity rotations average to the same +Y_RTN unit vector, confirming the mean is over the sweep axis."""
@@ -97,9 +95,7 @@ def test_matches_closed_form_formula(self):
             * deg_to_rad_squared
             * km_to_cm
         )
-        np.testing.assert_allclose(
-            count_rate_conversion_factor(sw, rg), expected, rtol=1e-12
-        )
+        np.testing.assert_allclose(count_rate_conversion_factor(sw, rg), expected, rtol=1e-12)
 
 
 if __name__ == "__main__":
diff --git a/tests/swapi/l3a/science/test_inflow_vector.py b/tests/swapi/l3a/science/test_inflow_vector.py
index 23869583..32bac309 100644
--- a/tests/swapi/l3a/science/test_inflow_vector.py
+++ b/tests/swapi/l3a/science/test_inflow_vector.py
@@ -7,9 +7,7 @@
 class TestInflowVector(unittest.TestCase):
     def test_from_file(self):
         vector = InflowVector.from_file(
-            get_test_data_path(
-                "swapi/imap_swapi_hydrogen-inflow-vector_20100101_v001.dat"
-            )
+            get_test_data_path("swapi/imap_swapi_hydrogen-inflow-vector_20100101_v001.dat")
         )
         self.assertIsInstance(vector, InflowVector)
         self.assertEqual(22, vector.speed_km_per_s)
diff --git a/tests/swapi/l3a/test_chunk_fits.py b/tests/swapi/l3a/test_chunk_fits.py
index 76a8d5b8..e57b7822 100644
--- a/tests/swapi/l3a/test_chunk_fits.py
+++ b/tests/swapi/l3a/test_chunk_fits.py
@@ -1,7 +1,7 @@
+import platform
 import unittest
 from datetime import datetime
-from unittest.mock import Mock, patch, create_autospec
-import platform
+from unittest.mock import Mock, create_autospec, patch
 
 import numpy as np
 from imap_processing.spice.time import str_yyyymmdd_to_ttj2000ns
@@ -16,7 +16,15 @@
     THIRTY_SECONDS_IN_NANOSECONDS,
 )
 from imap_l3_processing.models import InputMetadata, MagData
-from imap_l3_processing.swapi.swapi_processor import SwapiProcessor
+from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
+from imap_l3_processing.swapi.constants import (
+    SWAPI_BIN_PERIOD_S,
+    SWAPI_COARSE_SWEEP_BINS,
+    SWAPI_FINE_SWEEP_BINS,
+    SWAPI_L2_K_FACTOR,
+    SWAPI_LIVETIME_CENTER_OFFSET_S,
+    SWAPI_SCIENCE_BINS,
+)
 from imap_l3_processing.swapi.l3a import chunk_fits
 from imap_l3_processing.swapi.l3a.chunk_fits import (
     AlphaChunkFitter,
@@ -25,15 +33,11 @@
     ProtonChunkFitter,
     PuiChunkFitter,
 )
-from imap_l3_processing.swapi.l3a.utils import pickup_ion_chunk_epoch
+from imap_l3_processing.swapi.l3a.models import SwapiL2Data
 from imap_l3_processing.swapi.l3a.science.pickup_ion.calculate_pickup_ion_values import (
     PickupIonFitInputData,
     PickupIonFitResult,
 )
-from imap_l3_processing.swapi.response.efficiency_calibration_table import (
-    EfficiencyCalibrationTable,
-)
-from imap_l3_processing.swapi.l3a.models import SwapiL2Data
 from imap_l3_processing.swapi.l3a.science.solar_wind.fit_context import (
     build_solar_wind_fit_context,
 )
@@ -45,21 +49,17 @@
     ProtonSolarWindFitResult,
 )
 from imap_l3_processing.swapi.l3a.utils import (
-    get_swapi_geometry,
     get_spacecraft_velocity_rtn,
+    get_swapi_geometry,
+    pickup_ion_chunk_epoch,
 )
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
 from imap_l3_processing.swapi.response.deadtime import deadtime_factor
-from imap_l3_processing.swapi.constants import (
-    SWAPI_BIN_PERIOD_S,
-    SWAPI_COARSE_SWEEP_BINS,
-    SWAPI_FINE_SWEEP_BINS,
-    SWAPI_L2_K_FACTOR,
-    SWAPI_LIVETIME_CENTER_OFFSET_S,
-    SWAPI_SCIENCE_BINS,
+from imap_l3_processing.swapi.response.efficiency_calibration_table import (
+    EfficiencyCalibrationTable,
 )
-from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
 from imap_l3_processing.swapi.species import Species
+from imap_l3_processing.swapi.swapi_processor import SwapiProcessor
 from tests.spice_test_case import SpiceTestCase
 from tests.swapi._helpers import (
     REALISTIC_ESA_VOLTAGES,
@@ -130,9 +130,7 @@ def _spice_rotations(bin_slice):
     """SPICE-derived SWAPI→RTN rotations at the synthetic chunk's measurement
     times over `bin_slice`."""
     bin_indices = np.arange(bin_slice.start, bin_slice.stop)
-    seconds_into_sweep = (
-        bin_indices * SWAPI_BIN_PERIOD_S + SWAPI_LIVETIME_CENTER_OFFSET_S
-    )
+    seconds_into_sweep = bin_indices * SWAPI_BIN_PERIOD_S + SWAPI_LIVETIME_CENTER_OFFSET_S
     measurement_times = (
         _SCI_START_TIME[:, np.newaxis] + seconds_into_sweep * ONE_SECOND_IN_NANOSECONDS
     ).flatten()
@@ -331,9 +329,7 @@ def _predicted_ephemeris_kernel_paths():
         "imap_2025_105_2026_105_01.ah.bc",
         "imap_2026_189_2026_189_001.ah.bc",
     ]
-    return [
-        str(get_integration_test_spice_data_path(name)) for name in spice_file_names
-    ]
+    return [str(get_integration_test_spice_data_path(name)) for name in spice_file_names]
 
 
 # ----- ProtonChunkFitter ----------------------------------------------------
@@ -378,8 +374,7 @@ def test_flags_chunks_that_need_predicted_ephemeris(self):
             "imap_2026_189_2026_189_001.ah.bc",
         ]
         spice_test_paths = [
-            str(get_integration_test_spice_data_path(file_name))
-            for file_name in spice_file_names
+            str(get_integration_test_spice_data_path(file_name)) for file_name in spice_file_names
         ]
 
         chunk_needing_predict = _chunk_at_time(
@@ -392,8 +387,8 @@ def test_flags_chunks_that_need_predicted_ephemeris(self):
 
         with KernelPool(spice_test_paths):
             [geom1, geom2] = ProtonChunkFitter().precompute_geometry(chunks)
-            epoch1, rotation_matrices1, spacecraft_velocity1, flags1 = geom1
-            epoch2, rotation_matrices2, spacecraft_velocity2, flags2 = geom2
+            _epoch1, _rotation_matrices1, _spacecraft_velocity1, flags1 = geom1
+            _epoch2, _rotation_matrices2, _spacecraft_velocity2, flags2 = geom2
 
             self.assertEqual(SwapiL3Flags.PREDICTIVE_EPHEMERIS, flags1)
             self.assertEqual(SwapiL3Flags.NONE, flags2)
@@ -421,20 +416,12 @@ def test_uses_predicted_ephemeris_tracker(self, mock_tracker_class):
         ProtonChunkFitter().precompute_geometry(chunks)
         self.assertEqual(2, mock_tracker_class.call_count)
         self.assertEqual(2, mock_tracker_1.run.call_count)
-        self.assertEqual(
-            get_swapi_geometry, mock_tracker_1.run.call_args_list[0].args[0]
-        )
-        self.assertEqual(
-            get_spacecraft_velocity_rtn, mock_tracker_1.run.call_args_list[1].args[0]
-        )
+        self.assertEqual(get_swapi_geometry, mock_tracker_1.run.call_args_list[0].args[0])
+        self.assertEqual(get_spacecraft_velocity_rtn, mock_tracker_1.run.call_args_list[1].args[0])
 
         self.assertEqual(2, mock_tracker_2.run.call_count)
-        self.assertEqual(
-            get_swapi_geometry, mock_tracker_2.run.call_args_list[0].args[0]
-        )
-        self.assertEqual(
-            get_spacecraft_velocity_rtn, mock_tracker_2.run.call_args_list[1].args[0]
-        )
+        self.assertEqual(get_swapi_geometry, mock_tracker_2.run.call_args_list[0].args[0])
+        self.assertEqual(get_spacecraft_velocity_rtn, mock_tracker_2.run.call_args_list[1].args[0])
 
 
 class TestProtonChunkFitterFitChunk(SpiceTestCase):
@@ -556,9 +543,7 @@ def test_missing_sc_velocity_fills_only_sun_frame_outputs(self):
             self.true_proton_velocity_rtn,
             atol=5.0,
         )
-        self.assertTrue(
-            np.all(np.isfinite(result["proton_sw_velocity_rtn_covariance"]))
-        )
+        self.assertTrue(np.all(np.isfinite(result["proton_sw_velocity_rtn_covariance"])))
         self.assertTrue(np.isfinite(result["proton_sw_speed"]))
 
     def test_uses_quality_flag_from_geometry(self):
@@ -600,9 +585,7 @@ def test_success_returns_rotations_sc_velocity_and_b_hat(self):
 
     def test_spice_failure_yields_none_rotations_and_sc_velocity_but_keeps_b_hat(self):
         """When the chunk falls outside SPICE coverage, alpha precompute returns None rotations and None spacecraft velocity, but B̂ is still computed from MAG since that path is independent."""
-        out_of_coverage_chunk_epoch = (
-            _OUT_OF_COVERAGE_START_TIME + THIRTY_SECONDS_IN_NANOSECONDS
-        )
+        out_of_coverage_chunk_epoch = _OUT_OF_COVERAGE_START_TIME + THIRTY_SECONDS_IN_NANOSECONDS
         [(_, rotation_matrices, sc_velocity, b_hat, _)] = AlphaChunkFitter(
             self._mag_centered_on(out_of_coverage_chunk_epoch)
         ).precompute_geometry([_out_of_coverage_chunk()])
@@ -635,8 +618,7 @@ def test_flags_chunks_that_need_predicted_ephemeris(self, _):
             "imap_2026_189_2026_189_001.ah.bc",
         ]
         spice_test_paths = [
-            str(get_integration_test_spice_data_path(file_name))
-            for file_name in spice_file_names
+            str(get_integration_test_spice_data_path(file_name)) for file_name in spice_file_names
         ]
 
         chunk_needing_predict = _chunk_at_time(
@@ -649,8 +631,8 @@ def test_flags_chunks_that_need_predicted_ephemeris(self, _):
 
         with KernelPool(spice_test_paths):
             [geom1, geom2] = AlphaChunkFitter(None).precompute_geometry(chunks)
-            epoch1, rotation_matrices1, spacecraft_velocity1, bhat1, flags1 = geom1
-            epoch2, rotation_matrices2, spacecraft_velocity2, bhat2, flags2 = geom2
+            _epoch1, _rotation_matrices1, _spacecraft_velocity1, _bhat1, flags1 = geom1
+            _epoch2, _rotation_matrices2, _spacecraft_velocity2, _bhat2, flags2 = geom2
 
             self.assertEqual(SwapiL3Flags.PREDICTIVE_EPHEMERIS, flags1)
             self.assertEqual(SwapiL3Flags.NONE, flags2)
@@ -681,20 +663,12 @@ def test_uses_predicted_ephemeris_tracker(self, mock_tracker_class, _):
         AlphaChunkFitter(None).precompute_geometry(chunks)
         self.assertEqual(2, mock_tracker_class.call_count)
         self.assertEqual(2, mock_tracker_1.run.call_count)
-        self.assertEqual(
-            get_swapi_geometry, mock_tracker_1.run.call_args_list[0].args[0]
-        )
-        self.assertEqual(
-            get_spacecraft_velocity_rtn, mock_tracker_1.run.call_args_list[1].args[0]
-        )
+        self.assertEqual(get_swapi_geometry, mock_tracker_1.run.call_args_list[0].args[0])
+        self.assertEqual(get_spacecraft_velocity_rtn, mock_tracker_1.run.call_args_list[1].args[0])
 
         self.assertEqual(2, mock_tracker_2.run.call_count)
-        self.assertEqual(
-            get_swapi_geometry, mock_tracker_2.run.call_args_list[0].args[0]
-        )
-        self.assertEqual(
-            get_spacecraft_velocity_rtn, mock_tracker_2.run.call_args_list[1].args[0]
-        )
+        self.assertEqual(get_swapi_geometry, mock_tracker_2.run.call_args_list[0].args[0])
+        self.assertEqual(get_spacecraft_velocity_rtn, mock_tracker_2.run.call_args_list[1].args[0])
 
 
 class TestAlphaChunkFitterFitChunk(SpiceTestCase):
@@ -786,9 +760,7 @@ def test_missing_sc_velocity_fills_only_sun_frame_outputs(self):
 
     def test_quality_flag_none_on_clean_chunk(self):
         """A clean chunk yields a NONE quality flag (both Stage 1 and Stage 2 converged)."""
-        self.assertEqual(
-            int(self.happy_result["quality_flags"]), int(SwapiL3Flags.NONE)
-        )
+        self.assertEqual(int(self.happy_result["quality_flags"]), int(SwapiL3Flags.NONE))
 
     def test_uses_quality_flag_from_geometry(self):
         result = AlphaChunkFitter(None).fit_chunk(
@@ -857,9 +829,7 @@ def test_dispatches_per_chunk_and_stacks_outputs_in_chunk_order(self):
             _make_chunk_with_start_time(_EPOCH_TT2000 + 12_000_000_000),
         ]
         runner = ParallelChunkRunner(
-            swapi_response=load_swapi_response(
-                np.tile(REALISTIC_ESA_VOLTAGES, _N_SWEEPS)
-            ),
+            swapi_response=load_swapi_response(np.tile(REALISTIC_ESA_VOLTAGES, _N_SWEEPS)),
             efficiency_table=_efficiency_table(),
         )
 
@@ -878,17 +848,13 @@ def test_workers_see_parent_warm_cache_under_fork(self):
         parent_cache_size = len(response._passband_grid_cache)
         self.assertEqual(parent_cache_size, len(voltages))
 
-        runner = ParallelChunkRunner(
-            swapi_response=response, efficiency_table=_efficiency_table()
-        )
+        runner = ParallelChunkRunner(swapi_response=response, efficiency_table=_efficiency_table())
 
         result = runner.run(
             [_make_chunk_with_start_time(_EPOCH_TT2000)], _WarmCacheProbeChunkFitter()
         )
 
-        np.testing.assert_array_equal(
-            result["worker_cache_size"], np.array([parent_cache_size])
-        )
+        np.testing.assert_array_equal(result["worker_cache_size"], np.array([parent_cache_size]))
 
 
 # ----- Proton quality flags -------------------------------------------------
@@ -1040,9 +1006,7 @@ def tearDownClass(cls):
     def test_bad_fit_when_alpha_bump_does_not_match_maxwellian(self):
         """Scrambling and amplifying the alpha-bump bins leaves the proton peak intact but yields a Stage-2 residual the alpha LM cannot describe (the BAD_FIT quality guard fires); the chunk fitter surfaces `BAD_FIT` with every alpha moment NaN-filled."""
         rng = np.random.default_rng(0)
-        permuted = rng.permutation(
-            np.arange(_ALPHA_BUMP_BINS.start, _ALPHA_BUMP_BINS.stop)
-        )
+        permuted = rng.permutation(np.arange(_ALPHA_BUMP_BINS.start, _ALPHA_BUMP_BINS.stop))
         corrupted = self.chunk.coincidence_count_rate.copy()
         corrupted[:, _ALPHA_BUMP_BINS] = corrupted[:, permuted] * 3.0
 
@@ -1090,9 +1054,7 @@ def test_preliminary_mag_bit_set_iff_mag_is_preliminary(
 
                 SwapiProcessor(Mock(), metadata).process_l3a_alpha(data, dependencies)
 
-                passed_quality_flags = mock_alpha_data_class.call_args.kwargs[
-                    "quality_flags"
-                ]
+                passed_quality_flags = mock_alpha_data_class.call_args.kwargs["quality_flags"]
                 np.testing.assert_array_equal(passed_quality_flags, [expected_flag])
 
     def test_no_flag_when_rotations_missing(self):
@@ -1193,8 +1155,7 @@ def _pui_chunk(start_time, count_rates=None):
     if count_rates is None:
         count_rates = np.full((n_sweeps, _N_BINS), 5.0)
     sci_start_time = (
-        start_time
-        + np.arange(n_sweeps, dtype=np.int64) * 12 * ONE_SECOND_IN_NANOSECONDS
+        start_time + np.arange(n_sweeps, dtype=np.int64) * 12 * ONE_SECOND_IN_NANOSECONDS
     )
     return SwapiL2Data(
         sci_start_time=sci_start_time,
@@ -1231,9 +1192,7 @@ def _stub_chunk_position(mock_spiceypy, distance_km=1.5e8, longitude_deg=75.0):
         )
 
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.get_spacecraft_velocity_rtn")
-    @patch(
-        "imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin"
-    )
+    @patch("imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin")
     @patch.object(PuiChunkFitter, "_calculate_ten_minute_velocities")
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.spiceypy")
     def test_returns_one_geometry_per_chunk(
@@ -1277,17 +1236,13 @@ def test_returns_one_geometry_per_chunk(
         np.testing.assert_array_equal(
             fit_input.bulk_sw_per_bin_swapi_kms, per_bin[:, SWAPI_COARSE_SWEEP_BINS, :]
         )
-        np.testing.assert_array_equal(
-            fit_input.solar_wind_velocity_rtn_sun, ten_minute_rtn_sun
-        )
+        np.testing.assert_array_equal(fit_input.solar_wind_velocity_rtn_sun, ten_minute_rtn_sun)
         self.assertEqual(fit_input.distance, 1.5e8)
         self.assertEqual(fit_input.inflow_angle, 75.0)
         mock_get_spacecraft_velocity_rtn.assert_not_called()
 
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.get_spacecraft_velocity_rtn")
-    @patch(
-        "imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin"
-    )
+    @patch("imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin")
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.spiceypy")
     def test_averages_the_proton_fits_over_each_ten_minute_window(
         self,
@@ -1314,9 +1269,7 @@ def test_averages_the_proton_fits_over_each_ten_minute_window(
         per_fit_flags[3] = int(SwapiL3Flags.FIT_ERROR)
         per_fit_flags[13] = int(SwapiL3Flags.BAD_FIT)
         per_fit_flags[14] = int(SwapiL3Flags.PRELIMINARY_MAG)
-        mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full(
-            (50, 72, 3), 0.5
-        )
+        mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full((50, 72, 3), 0.5)
         self._stub_chunk_position(mock_spiceypy)
         fitter = self._make_fitter(
             {
@@ -1348,9 +1301,7 @@ def test_averages_the_proton_fits_over_each_ten_minute_window(
         ):
             np.testing.assert_array_equal(call.args[1], expected_window.mean(axis=0))
 
-    @patch(
-        "imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin"
-    )
+    @patch("imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin")
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.spiceypy")
     def test_drops_unusable_proton_fits_until_too_few_remain(
         self,
@@ -1372,14 +1323,12 @@ def test_drops_unusable_proton_fits_until_too_few_remain(
             with self.subTest(usable_minutes=10 - len(failed_minutes)):
                 per_fit_velocities = original_velocities.copy()
                 per_fit_velocities[failed_minutes] = np.nan
-                expected_velocity = np.delete(
-                    original_velocities, failed_minutes, axis=0
-                ).mean(axis=0)
+                expected_velocity = np.delete(original_velocities, failed_minutes, axis=0).mean(
+                    axis=0
+                )
                 per_fit_flags = np.full(10, int(SwapiL3Flags.NONE))
                 per_fit_flags[failed_minutes] = int(SwapiL3Flags.BAD_FIT)
-                mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full(
-                    (50, 72, 3), 0.5
-                )
+                mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full((50, 72, 3), 0.5)
                 self._stub_chunk_position(mock_spiceypy)
                 fitter = self._make_fitter(
                     {
@@ -1393,6 +1342,7 @@ def test_drops_unusable_proton_fits_until_too_few_remain(
                     [_pui_chunk(_EPOCH_TT2000)]
                 )
 
+                self.assertEqual(0, quality_flag)
                 if len(failed_minutes) > 2:
                     self.assertIsNone(fit_input)
                 else:
@@ -1401,9 +1351,7 @@ def test_drops_unusable_proton_fits_until_too_few_remain(
                     )
 
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.spiceypy")
-    @patch(
-        "imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin"
-    )
+    @patch("imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin")
     @patch.object(PuiChunkFitter, "_calculate_ten_minute_velocities")
     def test_spice_gap_on_rotate_yields_no_fit_input(
         self,
@@ -1433,9 +1381,7 @@ def test_spice_gap_on_rotate_yields_no_fit_input(
 
         self.assertIsNone(fit_input)
 
-    @patch(
-        "imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin"
-    )
+    @patch("imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin")
     @patch.object(PuiChunkFitter, "_calculate_ten_minute_velocities")
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.spiceypy")
     def test_nan_ten_minute_velocity_skips_spice_state(
@@ -1450,9 +1396,7 @@ def test_nan_ten_minute_velocity_skips_spice_state(
             np.array([[np.nan, np.nan, np.nan]]),
             np.array([int(SwapiL3Flags.NONE)]),
         )
-        mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full(
-            (50, 72, 3), 0.0
-        )
+        mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full((50, 72, 3), 0.0)
         fitter = self._make_fitter(
             {
                 "proton_sw_velocity_rtn": np.array([[1.0, 2.0, 3.0]]),
@@ -1468,9 +1412,7 @@ def test_nan_ten_minute_velocity_skips_spice_state(
         mock_spiceypy.spkezr.assert_not_called()
 
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.spiceypy")
-    @patch(
-        "imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin"
-    )
+    @patch("imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin")
     @patch.object(PuiChunkFitter, "_calculate_ten_minute_velocities")
     def test_spice_gap_on_precompute_spice_state_yields_none(
         self,
@@ -1486,9 +1428,7 @@ def test_spice_gap_on_precompute_spice_state_yields_none(
             np.array([[400.0, 40.0, 5.0]]),
             np.array([int(SwapiL3Flags.NONE)]),
         )
-        mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full(
-            (50, 72, 3), 0.0
-        )
+        mock_rotate_rtn_velocity_to_swapi_per_bin.return_value = np.full((50, 72, 3), 0.0)
         mock_spiceypy.spkezr.side_effect = _SpiceyError("gap")
         fitter = self._make_fitter(
             {
@@ -1513,9 +1453,7 @@ def test_flags_chunks_that_need_predicted_ephemeris(
             np.array([int(SwapiL3Flags.NONE), int(SwapiL3Flags.NONE)]),
         )
 
-        chunk_needing_predict = _pui_chunk(
-            str_yyyymmdd_to_ttj2000ns("20260708") + 12 * 3600 * 1e9
-        )
+        chunk_needing_predict = _pui_chunk(str_yyyymmdd_to_ttj2000ns("20260708") + 12 * 3600 * 1e9)
         chunk_not_needing_predict = _pui_chunk(
             str_yyyymmdd_to_ttj2000ns("20260120") + 12 * 3600 * 1e9
         )
@@ -1530,9 +1468,7 @@ def test_flags_chunks_that_need_predicted_ephemeris(
                 }
             )
 
-            [(_, quality_flag1), (_, quality_flag2)] = fitter.precompute_geometry(
-                chunks
-            )
+            [(_, quality_flag1), (_, quality_flag2)] = fitter.precompute_geometry(chunks)
 
             self.assertEqual(SwapiL3Flags.PREDICTIVE_EPHEMERIS, quality_flag1)
             self.assertEqual(SwapiL3Flags.NONE, quality_flag2)
@@ -1548,9 +1484,7 @@ def test_combines_upstream_proton_and_predicted_ephemeris_flags(
             np.array([int(SwapiL3Flags.BAD_FIT), int(SwapiL3Flags.BAD_FIT)]),
         )
 
-        chunk_needing_predict = _pui_chunk(
-            str_yyyymmdd_to_ttj2000ns("20260708") + 12 * 3600 * 1e9
-        )
+        chunk_needing_predict = _pui_chunk(str_yyyymmdd_to_ttj2000ns("20260708") + 12 * 3600 * 1e9)
         chunk_not_needing_predict = _pui_chunk(
             str_yyyymmdd_to_ttj2000ns("20260120") + 12 * 3600 * 1e9
         )
@@ -1565,9 +1499,7 @@ def test_combines_upstream_proton_and_predicted_ephemeris_flags(
                 }
             )
 
-            [(_, quality_flag1), (_, quality_flag2)] = fitter.precompute_geometry(
-                chunks
-            )
+            [(_, quality_flag1), (_, quality_flag2)] = fitter.precompute_geometry(chunks)
 
             self.assertEqual(
                 SwapiL3Flags.BAD_FIT | SwapiL3Flags.PREDICTIVE_EPHEMERIS,
@@ -1576,9 +1508,7 @@ def test_combines_upstream_proton_and_predicted_ephemeris_flags(
             self.assertEqual(SwapiL3Flags.BAD_FIT, quality_flag2)
 
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.get_spacecraft_velocity_rtn")
-    @patch(
-        "imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin"
-    )
+    @patch("imap_l3_processing.swapi.l3a.chunk_fits.rotate_rtn_velocity_to_swapi_per_bin")
     @patch.object(PuiChunkFitter, "_calculate_ten_minute_velocities")
     @patch("imap_l3_processing.swapi.l3a.chunk_fits.PredictedEphemerisTracker")
     def test_uses_predicted_ephemeris_tracker(
@@ -1605,9 +1535,7 @@ def test_uses_predicted_ephemeris_tracker(
             mock_tracker_1,
             mock_tracker_2,
         ]
-        chunk_needing_predict = _pui_chunk(
-            str_yyyymmdd_to_ttj2000ns("20260308") + 12 * 3600 * 1e9
-        )
+        chunk_needing_predict = _pui_chunk(str_yyyymmdd_to_ttj2000ns("20260308") + 12 * 3600 * 1e9)
         chunk_not_needing_predict = _pui_chunk(
             str_yyyymmdd_to_ttj2000ns("20260120") + 12 * 3600 * 1e9
         )
@@ -1635,9 +1563,7 @@ def test_uses_predicted_ephemeris_tracker(
             )
 
 
-def _pui_fit_result(
-    ionization_rate, cutoff_speed, flags, density=None, temperature=None
-):
+def _pui_fit_result(ionization_rate, cutoff_speed, flags, density=None, temperature=None):
     nan = ufloat(np.nan, np.nan)
     return PickupIonFitResult(
         ionization_rate=ionization_rate,
@@ -1679,15 +1605,9 @@ def _fit_input(self, chunk):
         return PickupIonFitInputData(
             time_as_tt2000=self.epoch,
             esa_energies=chunk.energy[:, SWAPI_COARSE_SWEEP_BINS].mean(axis=0),
-            coincidence_count_rates=chunk.coincidence_count_rate[
-                :, SWAPI_COARSE_SWEEP_BINS
-            ],
-            bulk_sw_per_bin_swapi_kms=self.bulk_sw_per_bin_swapi[
-                :, SWAPI_COARSE_SWEEP_BINS, :
-            ],
-            solar_wind_velocity_rtn_sun=(
-                self.sw_velocity_rtn + self.imap_velocity_rtn_sun
-            ),
+            coincidence_count_rates=chunk.coincidence_count_rate[:, SWAPI_COARSE_SWEEP_BINS],
+            bulk_sw_per_bin_swapi_kms=self.bulk_sw_per_bin_swapi[:, SWAPI_COARSE_SWEEP_BINS, :],
+            solar_wind_velocity_rtn_sun=(self.sw_velocity_rtn + self.imap_velocity_rtn_sun),
             distance=self.distance,
             inflow_angle=self.inflow_angle,
         )
@@ -1706,9 +1626,7 @@ def test_clean_chunk_passes_through_the_fit_result(self, mock_calculate_pickup_i
 
         chunk = _pui_chunk(_EPOCH_TT2000)
 
-        result = self.fitter.fit_chunk(
-            chunk, self._fit_input(chunk), int(SwapiL3Flags.NONE)
-        )
+        result = self.fitter.fit_chunk(chunk, self._fit_input(chunk), int(SwapiL3Flags.NONE))
 
         self.assertEqual(result["epoch"], self.epoch)
         self.assertEqual(result["ionization_rate"], 1e-7)
@@ -1717,9 +1635,7 @@ def test_clean_chunk_passes_through_the_fit_result(self, mock_calculate_pickup_i
         self.assertIs(result["temperature"], temperature_result)
         self.assertEqual(result["quality_flags"], int(SwapiL3Flags.NONE))
 
-    def test_combines_pui_fit_flag_with_upstream_proton_flag(
-        self, mock_calculate_pickup_ion
-    ):
+    def test_combines_pui_fit_flag_with_upstream_proton_flag(self, mock_calculate_pickup_ion):
         """The output quality flag is the bitwise OR of the per-fit flag returned by `calculate_pickup_ion_values` and the upstream proton-SW quality flag."""
         nan = ufloat(np.nan, np.nan)
         mock_calculate_pickup_ion.return_value = _pui_fit_result(
@@ -1728,26 +1644,20 @@ def test_combines_pui_fit_flag_with_upstream_proton_flag(
 
         chunk = _pui_chunk(_EPOCH_TT2000)
 
-        result = self.fitter.fit_chunk(
-            chunk, self._fit_input(chunk), int(SwapiL3Flags.FIT_ERROR)
-        )
+        result = self.fitter.fit_chunk(chunk, self._fit_input(chunk), int(SwapiL3Flags.FIT_ERROR))
 
         self.assertEqual(
             result["quality_flags"],
             int(SwapiL3Flags.BAD_FIT) | int(SwapiL3Flags.FIT_ERROR),
         )
 
-    def test_nan_in_count_rates_fills_outputs_and_skips_fit(
-        self, mock_calculate_pickup_ion
-    ):
+    def test_nan_in_count_rates_fills_outputs_and_skips_fit(self, mock_calculate_pickup_ion):
         """A NaN in the coarse-bin count rate slice short-circuits the fit: every scalar output is NaN, no science helper is called, and the only flag in the result is the upstream proton flag."""
         count_rates = np.full((50, _N_BINS), 5.0)
         count_rates[3, 30] = np.nan
         chunk = _pui_chunk(_EPOCH_TT2000, count_rates=count_rates)
 
-        result = self.fitter.fit_chunk(
-            chunk, self._fit_input(chunk), int(SwapiL3Flags.NONE)
-        )
+        result = self.fitter.fit_chunk(chunk, self._fit_input(chunk), int(SwapiL3Flags.NONE))
 
         mock_calculate_pickup_ion.assert_not_called()
         for key in ("ionization_rate", "cutoff_speed", "density", "temperature"):
@@ -1755,9 +1665,7 @@ def test_nan_in_count_rates_fills_outputs_and_skips_fit(
             self.assertTrue(np.isnan(result[key].std_dev), msg=key)
         self.assertEqual(result["quality_flags"], int(SwapiL3Flags.NONE))
 
-    def test_missing_fit_input_fills_outputs_and_skips_fit(
-        self, mock_calculate_pickup_ion
-    ):
+    def test_missing_fit_input_fills_outputs_and_skips_fit(self, mock_calculate_pickup_ion):
         """A chunk whose geometry `precompute_geometry` could not build (an upstream proton fit failure, or a SPICE gap) short-circuits the fit the same way as a missing count rate."""
         chunk = _pui_chunk(_EPOCH_TT2000)
 
diff --git a/tests/swapi/l3a/test_models.py b/tests/swapi/l3a/test_models.py
index 4a178bde..2edaa8dd 100644
--- a/tests/swapi/l3a/test_models.py
+++ b/tests/swapi/l3a/test_models.py
@@ -1,5 +1,5 @@
 from datetime import datetime
-from unittest.mock import Mock, sentinel, patch
+from unittest.mock import Mock, patch, sentinel
 
 import imap_data_access
 import numpy as np
@@ -7,64 +7,64 @@
 from uncertainties.unumpy import uarray
 
 from imap_l3_processing.constants import (
-    THIRTY_SECONDS_IN_NANOSECONDS,
     FIVE_MINUTES_IN_NANOSECONDS,
+    THIRTY_SECONDS_IN_NANOSECONDS,
 )
 from imap_l3_processing.models import InputMetadata, VersionMap
 from imap_l3_processing.swapi.l3a.models import (
-    SwapiL3ProtonSolarWindData,
+    ALPHA_SOLAR_WIND_DENSITY_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_DENSITY_UNCERTAINTY_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_SPEED_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_SPEED_SUN_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_SPEED_SUN_UNCERTAINTY_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_SPEED_UNCERTAINTY_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_TEMPERATURE_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_TEMPERATURE_UNCERTAINTY_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_VELOCITY_RTN_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_VELOCITY_RTN_SUN_CDF_VAR_NAME,
+    ALPHA_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME,
+    ALPHA_VELOCITY_GSE_LABEL_CDF_VAR_NAME,
+    ALPHA_VELOCITY_RTN_LABEL_CDF_VAR_NAME,
+    ALPHA_VELOCITY_RTN_SUN_LABEL_CDF_VAR_NAME,
     EPOCH_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_SPEED_UNCERTAINTY_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_SPEED_CDF_VAR_NAME,
     EPOCH_DELTA_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_DENSITY_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_DENSITY_UNCERTAINTY_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_SPEED_CDF_VAR_NAME,
     PROTON_SOLAR_WIND_SPEED_SUN_CDF_VAR_NAME,
     PROTON_SOLAR_WIND_SPEED_SUN_UNCERTAINTY_CDF_VAR_NAME,
-    SwapiL3AlphaSolarWindData,
+    PROTON_SOLAR_WIND_SPEED_UNCERTAINTY_CDF_VAR_NAME,
     PROTON_SOLAR_WIND_TEMPERATURE_CDF_VAR_NAME,
     PROTON_SOLAR_WIND_TEMPERATURE_UNCERTAINTY_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_DENSITY_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_DENSITY_UNCERTAINTY_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_VELOCITY_RTN_SUN_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_VELOCITY_GSE_LABEL_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME,
     PROTON_SOLAR_WIND_VELOCITY_RTN_CDF_VAR_NAME,
     PROTON_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_VELOCITY_RTN_LABEL_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_VELOCITY_RTN_SUN_CDF_VAR_NAME,
+    PROTON_SOLAR_WIND_VELOCITY_RTN_SUN_LABEL_CDF_VAR_NAME,
     PROTON_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_SPEED_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_SPEED_UNCERTAINTY_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_SPEED_SUN_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_SPEED_SUN_UNCERTAINTY_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_DENSITY_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_DENSITY_UNCERTAINTY_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_TEMPERATURE_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_TEMPERATURE_UNCERTAINTY_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_VELOCITY_RTN_SUN_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_VELOCITY_RTN_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_VELOCITY_RTN_UNCERTAINTY_CDF_VAR_NAME,
-    SwapiL3PickupIonData,
-    PUI_IONIZATION_RATE_CDF_VAR_NAME,
     PUI_CUTOFF_SPEED_CDF_VAR_NAME,
-    PUI_DENSITY_CDF_VAR_NAME,
-    PUI_TEMPERATURE_CDF_VAR_NAME,
-    PUI_IONIZATION_RATE_UNCERTAINTY_CDF_VAR_NAME,
     PUI_CUTOFF_SPEED_UNCERTAINTY_CDF_VAR_NAME,
+    PUI_DENSITY_CDF_VAR_NAME,
     PUI_DENSITY_UNCERTAINTY_CDF_VAR_NAME,
+    PUI_IONIZATION_RATE_CDF_VAR_NAME,
+    PUI_IONIZATION_RATE_UNCERTAINTY_CDF_VAR_NAME,
+    PUI_TEMPERATURE_CDF_VAR_NAME,
     PUI_TEMPERATURE_UNCERTAINTY_CDF_VAR_NAME,
     SWAPI_QUALITY_FLAGS_CDF_VAR_NAME,
+    VELOCITY_GSE_LABEL_CDF_VAR_NAME,
     VELOCITY_RTN_LABEL_CDF_VAR_NAME,
-    ALPHA_VELOCITY_RTN_SUN_LABEL_CDF_VAR_NAME,
-    ALPHA_VELOCITY_RTN_LABEL_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_VELOCITY_RTN_SUN_LABEL_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_VELOCITY_RTN_LABEL_CDF_VAR_NAME,
+    SwapiL3AlphaSolarWindData,
     SwapiL3aProtonDataFromCDF,
-    VELOCITY_GSE_LABEL_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME,
-    PROTON_SOLAR_WIND_VELOCITY_GSE_LABEL_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_VELOCITY_GSE_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_VELOCITY_GSE_COVARIANCE_CDF_VAR_NAME,
-    ALPHA_SOLAR_WIND_VELOCITY_GSE_UNCERTAINTY_CDF_VAR_NAME,
-    ALPHA_VELOCITY_GSE_LABEL_CDF_VAR_NAME,
+    SwapiL3PickupIonData,
+    SwapiL3ProtonSolarWindData,
 )
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
 from imap_l3_processing.utils import save_data
@@ -135,9 +135,7 @@ def test_getting_proton_sw_data_product_variables(self):
             speed_sun_uncert,
             PROTON_SOLAR_WIND_SPEED_SUN_UNCERTAINTY_CDF_VAR_NAME,
         )
-        self.assert_variable_attributes(
-            next(var_iter), epoch_delta, EPOCH_DELTA_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(var_iter), epoch_delta, EPOCH_DELTA_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(var_iter), temperature, PROTON_SOLAR_WIND_TEMPERATURE_CDF_VAR_NAME
         )
@@ -167,9 +165,7 @@ def test_getting_proton_sw_data_product_variables(self):
             bulk_v_rtn_cov,
             PROTON_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME,
         )
-        expected_velocity_uncert = np.sqrt(
-            np.diagonal(bulk_v_rtn_cov, axis1=1, axis2=2)
-        )
+        expected_velocity_uncert = np.sqrt(np.diagonal(bulk_v_rtn_cov, axis1=1, axis2=2))
         self.assert_variable_attributes(
             next(var_iter),
             expected_velocity_uncert,
@@ -261,9 +257,7 @@ def test_getting_alpha_sw_data_product_variables(self):
 
         var_iter = iter(variables)
         self.assert_variable_attributes(next(var_iter), epoch_data, EPOCH_CDF_VAR_NAME)
-        self.assert_variable_attributes(
-            next(var_iter), speed, ALPHA_SOLAR_WIND_SPEED_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(var_iter), speed, ALPHA_SOLAR_WIND_SPEED_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(var_iter),
             speed_uncert,
@@ -277,9 +271,7 @@ def test_getting_alpha_sw_data_product_variables(self):
             speed_sun_uncert,
             ALPHA_SOLAR_WIND_SPEED_SUN_UNCERTAINTY_CDF_VAR_NAME,
         )
-        self.assert_variable_attributes(
-            next(var_iter), epoch_delta, EPOCH_DELTA_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(var_iter), epoch_delta, EPOCH_DELTA_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(var_iter), density, ALPHA_SOLAR_WIND_DENSITY_CDF_VAR_NAME
         )
@@ -309,9 +301,7 @@ def test_getting_alpha_sw_data_product_variables(self):
             velocity_rtn_cov,
             ALPHA_SOLAR_WIND_VELOCITY_RTN_COVARIANCE_CDF_VAR_NAME,
         )
-        expected_velocity_uncert = np.sqrt(
-            np.diagonal(velocity_rtn_cov, axis1=1, axis2=2)
-        )
+        expected_velocity_uncert = np.sqrt(np.diagonal(velocity_rtn_cov, axis1=1, axis2=2))
         self.assert_variable_attributes(
             next(var_iter),
             expected_velocity_uncert,
@@ -380,9 +370,7 @@ def test_getting_pui_data_product_variables(self):
 
         expected_temperature_nominal = np.arange(1e5, step=10000.0)
         expected_temperature_std_dev = np.arange(100, step=10.0)
-        expected_temperature = uarray(
-            expected_temperature_nominal, expected_temperature_std_dev
-        )
+        expected_temperature = uarray(expected_temperature_nominal, expected_temperature_std_dev)
 
         expected_quality_flags = np.full(20, 0)
 
@@ -479,15 +467,11 @@ def test_reads_data_into_model(self, tempdir):
             path = save_data(initial_data)
             loaded = SwapiL3aProtonDataFromCDF.from_file(path)
             np.testing.assert_equal(loaded.l2_parent_file_name, l2_parent_file_name)
-            np.testing.assert_equal(
-                loaded.velocity_rtn, initial_data.proton_sw_velocity_rtn
-            )
+            np.testing.assert_equal(loaded.velocity_rtn, initial_data.proton_sw_velocity_rtn)
             np.testing.assert_equal(
                 loaded.velocity_rtn_covariance,
                 initial_data.proton_sw_velocity_rtn_covariance,
             )
             np.testing.assert_equal(loaded.density, initial_data.proton_sw_density)
-            np.testing.assert_equal(
-                loaded.temperature, initial_data.proton_sw_temperature
-            )
+            np.testing.assert_equal(loaded.temperature, initial_data.proton_sw_temperature)
             np.testing.assert_equal(loaded.quality_flags, initial_data.quality_flags)
diff --git a/tests/swapi/l3a/test_swapi_l3a_dependencies.py b/tests/swapi/l3a/test_swapi_l3a_dependencies.py
index 0ff33b08..14ecf0bd 100644
--- a/tests/swapi/l3a/test_swapi_l3a_dependencies.py
+++ b/tests/swapi/l3a/test_swapi_l3a_dependencies.py
@@ -1,24 +1,24 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, call, sentinel
+from unittest.mock import call, patch, sentinel
 
 import imap_data_access
 from imap_data_access.processing_input import (
-    ScienceInput,
-    ProcessingInputCollection,
     AncillaryInput,
+    ProcessingInputCollection,
+    ScienceInput,
 )
 
 from imap_l3_processing.swapi.descriptors import (
-    SWAPI_L2_DESCRIPTOR,
+    AZIMUTHAL_TRANSMISSION_DESCRIPTOR,
+    CENTRAL_EFFECTIVE_AREA_DESCRIPTOR,
     DENSITY_OF_NEUTRAL_HELIUM_DESCRIPTOR,
     EFFICIENCY_LOOKUP_TABLE_DESCRIPTOR,
-    HYDROGEN_INFLOW_VECTOR_DESCRIPTOR,
     HELIUM_INFLOW_VECTOR_DESCRIPTOR,
-    AZIMUTHAL_TRANSMISSION_DESCRIPTOR,
-    CENTRAL_EFFECTIVE_AREA_DESCRIPTOR,
-    PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR,
+    HYDROGEN_INFLOW_VECTOR_DESCRIPTOR,
     MAG_RTN_DESCRIPTOR,
+    PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR,
+    SWAPI_L2_DESCRIPTOR,
 )
 from imap_l3_processing.swapi.l3a.swapi_l3a_dependencies import SwapiL3ADependencies
 
@@ -29,9 +29,7 @@ class TestSwapiL3ADependencies(unittest.TestCase):
         "imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.SwapiL3ADependencies.from_file_paths"
     )
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.download")
-    def test_fetch_dependencies(
-        self, mock_download, mock_from_file_paths, mock_select_mag_path
-    ):
+    def test_fetch_dependencies(self, mock_download, mock_from_file_paths, mock_select_mag_path):
         input_collection = ProcessingInputCollection()
 
         start_date = "20100105"
@@ -52,11 +50,15 @@ def test_fetch_dependencies(
         ]
         mock_select_mag_path.return_value = (sentinel.mag_path, "l2")
 
-        swapi_science_file_download_path = f"{mission}_{instrument}_{data_level}_{SWAPI_L2_DESCRIPTOR}_{start_date}_{version}.cdf"
+        swapi_science_file_download_path = (
+            f"{mission}_{instrument}_{data_level}_{SWAPI_L2_DESCRIPTOR}_{start_date}_{version}.cdf"
+        )
         swapi_efficiency_file_name = f"{mission}_{instrument}_{EFFICIENCY_LOOKUP_TABLE_DESCRIPTOR}_{start_date}_{version}.cdf"
         swapi_density_of_neutral_helium_lookup = f"{mission}_{instrument}_{DENSITY_OF_NEUTRAL_HELIUM_DESCRIPTOR}_{start_date}_{version}.cdf"
         swapi_hydrogen_inflow_filename = f"{mission}_{instrument}_{HYDROGEN_INFLOW_VECTOR_DESCRIPTOR}_{start_date}_{version}.cdf"
-        swapi_helium_inflow_filename = f"{mission}_{instrument}_{HELIUM_INFLOW_VECTOR_DESCRIPTOR}_{start_date}_{version}.cdf"
+        swapi_helium_inflow_filename = (
+            f"{mission}_{instrument}_{HELIUM_INFLOW_VECTOR_DESCRIPTOR}_{start_date}_{version}.cdf"
+        )
         swapi_azimuthal_transmission_filename = f"{mission}_{instrument}_{AZIMUTHAL_TRANSMISSION_DESCRIPTOR}_{start_date}_{version}.cdf"
         swapi_central_effective_area_filename = f"{mission}_{instrument}_{CENTRAL_EFFECTIVE_AREA_DESCRIPTOR}_{start_date}_{version}.cdf"
         swapi_passband_fit_coefficients_filename = f"{mission}_{instrument}_{PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR}_{start_date}_{version}.cdf"
@@ -68,12 +70,8 @@ def test_fetch_dependencies(
         )
         hydrogen_inflow_ancillary = AncillaryInput(swapi_hydrogen_inflow_filename)
         helium_inflow_ancillary = AncillaryInput(swapi_helium_inflow_filename)
-        azimuthal_transmission_ancillary = AncillaryInput(
-            swapi_azimuthal_transmission_filename
-        )
-        central_effective_area_ancillary = AncillaryInput(
-            swapi_central_effective_area_filename
-        )
+        azimuthal_transmission_ancillary = AncillaryInput(swapi_azimuthal_transmission_filename)
+        central_effective_area_ancillary = AncillaryInput(swapi_central_effective_area_filename)
         passband_fit_coefficients_ancillary = AncillaryInput(
             swapi_passband_fit_coefficients_filename
         )
@@ -91,21 +89,12 @@ def test_fetch_dependencies(
             ]
         )
 
-        actual_swapi_l3_dependencies = SwapiL3ADependencies.fetch_dependencies(
-            input_collection
-        )
+        actual_swapi_l3_dependencies = SwapiL3ADependencies.fetch_dependencies(input_collection)
 
         science_data_dir = (
-            imap_data_access.config["DATA_DIR"]
-            / "imap"
-            / "swapi"
-            / "l2"
-            / "2010"
-            / "01"
-        )
-        ancillary_data_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "swapi"
+            imap_data_access.config["DATA_DIR"] / "imap" / "swapi" / "l2" / "2010" / "01"
         )
+        ancillary_data_dir = imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "swapi"
 
         mock_download.assert_has_calls(
             [
@@ -120,9 +109,7 @@ def test_fetch_dependencies(
             ]
         )
 
-        mock_select_mag_path.assert_called_once_with(
-            input_collection, MAG_RTN_DESCRIPTOR
-        )
+        mock_select_mag_path.assert_called_once_with(input_collection, MAG_RTN_DESCRIPTOR)
 
         mock_from_file_paths.assert_called_with(
             sentinel.swapi_l2_data,
@@ -137,9 +124,7 @@ def test_fetch_dependencies(
             False,
         )
 
-        self.assertEqual(
-            mock_from_file_paths.return_value, actual_swapi_l3_dependencies
-        )
+        self.assertEqual(mock_from_file_paths.return_value, actual_swapi_l3_dependencies)
 
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.select_mag_path")
     @patch(
@@ -180,20 +165,15 @@ def test_fetch_dependencies_with_l1d_mag(
 
         SwapiL3ADependencies.fetch_dependencies(input_collection)
 
-        _, kwargs = mock_from_file_paths.call_args
         args = mock_from_file_paths.call_args.args
         self.assertEqual(sentinel.mag_path, args[8])
         self.assertEqual(True, args[9])
 
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.read_mag_rtn_data")
-    @patch(
-        "imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.SwapiResponse.from_files"
-    )
+    @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.SwapiResponse.from_files")
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.CDF")
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.InflowVector.from_file")
-    @patch(
-        "imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.EfficiencyCalibrationTable"
-    )
+    @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.EfficiencyCalibrationTable")
     @patch(
         "imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.DensityOfNeutralHeliumLookupTable.from_file"
     )
@@ -213,12 +193,8 @@ def test_from_file_paths(
         neutral_helium_path = Path("imap_swapi_neutral_he_20100105_v010.cdf")
         hydrogen_vector_path = Path("imap_swapi_h_inflow_20100105_v010.dat")
         helium_vector_path = Path("imap_swapi_he_inflow_20100105_v010.dat")
-        azimuthal_transmission_path = Path(
-            "imap_swapi_azimuthal_transmission_20100105_v010.cdf"
-        )
-        central_effective_area_path = Path(
-            "imap_swapi_central_effective_area_20100105_v010.cdf"
-        )
+        azimuthal_transmission_path = Path("imap_swapi_azimuthal_transmission_20100105_v010.cdf")
+        central_effective_area_path = Path("imap_swapi_central_effective_area_20100105_v010.cdf")
         passband_fit_coefficients_path = Path(
             "imap_swapi_passband_fit_coefficients_20100105_v010.cdf"
         )
@@ -276,14 +252,10 @@ def test_from_file_paths(
         self.assertEqual(expected_dependencies, actual_dependencies)
 
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.read_mag_rtn_data")
-    @patch(
-        "imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.SwapiResponse.from_files"
-    )
+    @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.SwapiResponse.from_files")
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.CDF")
     @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.InflowVector.from_file")
-    @patch(
-        "imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.EfficiencyCalibrationTable"
-    )
+    @patch("imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.EfficiencyCalibrationTable")
     @patch(
         "imap_l3_processing.swapi.l3a.swapi_l3a_dependencies.DensityOfNeutralHeliumLookupTable.from_file"
     )
diff --git a/tests/swapi/l3a/test_utils.py b/tests/swapi/l3a/test_utils.py
index 16ba2dd4..6f579e38 100644
--- a/tests/swapi/l3a/test_utils.py
+++ b/tests/swapi/l3a/test_utils.py
@@ -27,18 +27,18 @@
 )
 from imap_l3_processing.swapi.l3a.models import SwapiL2Data
 from imap_l3_processing.swapi.l3a.utils import (
-    velocity_components_to_angles_in_instrument_frame,
     calculate_sw_speed,
     chunk_l2_data,
+    convert_sun_velocity_rtn_to_gse,
     esa_voltage_to_alpha_speed,
     esa_voltage_to_proton_speed,
     get_spacecraft_velocity_rtn,
-    convert_sun_velocity_rtn_to_gse,
     get_swapi_geometry,
     measurement_times,
     pickup_ion_chunk_epoch,
     read_l2_swapi_data,
     read_mag_rtn_data,
+    velocity_components_to_angles_in_instrument_frame,
     velocity_to_angles_in_instrument_frame,
 )
 from tests.spice_test_case import SpiceTestCase
@@ -47,8 +47,7 @@
 
 def _analytic_speed_km_per_s(voltage: float, mass_kg: float, charge_c: float) -> float:
     return float(
-        np.sqrt(2 * SWAPI_K_FACTOR * charge_c * abs(voltage) / mass_kg)
-        / METERS_PER_KILOMETER
+        np.sqrt(2 * SWAPI_K_FACTOR * charge_c * abs(voltage) / mass_kg) / METERS_PER_KILOMETER
     )
 
 
@@ -111,9 +110,7 @@ def test_chunk_l2_data(self):
             first_chunk.coincidence_count_rate_uncertainty,
         )
 
-        expected_count_rate_chunk_2 = np.array(
-            [[14, 15, 16, 17, 18], [19, 20, 21, 22, 23]]
-        )
+        expected_count_rate_chunk_2 = np.array([[14, 15, 16, 17, 18], [19, 20, 21, 22, 23]])
         expected_count_rate_uncertainty_chunk_2 = np.array(
             [[0.1, 0.2, 0.3, 0.4, 0.5], [0.1, 0.2, 0.3, 0.4, 0.5]]
         )
@@ -153,9 +150,7 @@ def test_each_bin_is_offset_from_its_sweep_start_by_the_livetime_center(self):
         times = measurement_times(sci_start_time)
 
         def expected(sweep_start, bin_index):
-            seconds_into_sweep = (
-                bin_index * SWAPI_BIN_PERIOD_S + SWAPI_LIVETIME_CENTER_OFFSET_S
-            )
+            seconds_into_sweep = bin_index * SWAPI_BIN_PERIOD_S + SWAPI_LIVETIME_CENTER_OFFSET_S
             return sweep_start + seconds_into_sweep * ONE_SECOND_IN_NANOSECONDS
 
         self.assertEqual(times.shape, (2, SWAPI_SWEEP_BIN_COUNT))
@@ -166,9 +161,7 @@ def expected(sweep_start, bin_index):
     def test_offset_is_the_livetime_center_not_its_start(self):
         """The per-bin offset lands half a livetime past the end of the ramp-up, i.e. at the center of the livetime window rather than its start."""
         ramp_up_s = SWAPI_BIN_PERIOD_S - SWAPI_LIVETIME_S
-        self.assertAlmostEqual(
-            SWAPI_LIVETIME_CENTER_OFFSET_S, ramp_up_s + SWAPI_LIVETIME_S / 2
-        )
+        self.assertAlmostEqual(SWAPI_LIVETIME_CENTER_OFFSET_S, ramp_up_s + SWAPI_LIVETIME_S / 2)
         self.assertAlmostEqual(
             SWAPI_LIVETIME_CENTER_OFFSET_S, SWAPI_BIN_PERIOD_S - SWAPI_LIVETIME_S / 2
         )
@@ -208,9 +201,7 @@ def test_reading_l2_data_into_model(self):
         np.testing.assert_array_equal(
             np.array(epoch_as_tt2000), actual_swapi_l2_data.sci_start_time
         )
-        np.testing.assert_array_equal(
-            np.array([1, np.nan, 3, 4]), actual_swapi_l2_data.energy
-        )
+        np.testing.assert_array_equal(np.array([1, np.nan, 3, 4]), actual_swapi_l2_data.energy)
         np.testing.assert_array_equal(
             np.array([5, 6, 7, np.nan]), actual_swapi_l2_data.coincidence_count_rate
         )
@@ -226,10 +217,7 @@ class TestCalculateSwSpeed(TestCase):
     def test_2d_array_matches_analytic_formula_per_element(self):
         """calculate_sw_speed on a 2D energy array matches the analytic v = sqrt(2qE/m) (in km/s) element-by-element."""
         E = np.array([[1.0e-16, 2.0e-16], [4.0e-16, 8.0e-16]])
-        expected = (
-            np.sqrt(2 * E * PROTON_CHARGE_COULOMBS / PROTON_MASS_KG)
-            / METERS_PER_KILOMETER
-        )
+        expected = np.sqrt(2 * E * PROTON_CHARGE_COULOMBS / PROTON_MASS_KG) / METERS_PER_KILOMETER
         result = calculate_sw_speed(PROTON_MASS_KG, PROTON_CHARGE_COULOMBS, E)
         np.testing.assert_allclose(result, expected)
 
@@ -241,9 +229,7 @@ def test_2d_array_input_preserves_shape(self):
 
     def test_empty_array_input_returns_empty_array(self):
         """calculate_sw_speed returns an empty array when given one, without errors."""
-        result = calculate_sw_speed(
-            PROTON_MASS_KG, PROTON_CHARGE_COULOMBS, np.array([])
-        )
+        result = calculate_sw_speed(PROTON_MASS_KG, PROTON_CHARGE_COULOMBS, np.array([]))
         self.assertEqual(result.size, 0)
 
     def test_ufloat_scalar_propagates_uncertainty(self):
@@ -272,9 +258,7 @@ def test_ufloat_array_input_propagates_uncertainty_per_element(self):
                 / METERS_PER_KILOMETER
             )
             self.assertAlmostEqual(r.nominal_value, expected_nom)
-            self.assertAlmostEqual(
-                r.std_dev, expected_nom * E.std_dev / (2 * E.nominal_value)
-            )
+            self.assertAlmostEqual(r.std_dev, expected_nom * E.std_dev / (2 * E.nominal_value))
 
 
 class TestReadMagRtnData(TestCase):
@@ -291,9 +275,7 @@ def tearDown(self) -> None:
 
     def test_reads_b_rtn_and_epoch_into_mag_data(self):
         """read_mag_rtn_data converts CDF epochs to TT2000 and keeps only the leading three vector components of b_rtn (dropping the magnitude column)."""
-        epochs = np.array(
-            [datetime(2026, 1, 1, 0, 0, 0), datetime(2026, 1, 1, 0, 0, 1)]
-        )
+        epochs = np.array([datetime(2026, 1, 1, 0, 0, 0), datetime(2026, 1, 1, 0, 0, 1)])
         b_rtn = np.array(
             [[1.0, 2.0, 3.0, 0.0], [4.0, 5.0, 6.0, 0.0]],
         )
@@ -317,9 +299,7 @@ class TestSwapiSpiceHelpers(SpiceTestCase):
 
     # 2025-06-06 12:00 UTC — inside the IMAP SPK and attitude coverage windows
     # used by the shipped `spice_kernels/` set.
-    _EPOCH_TT2000_NS = spacepy.pycdf.lib.datetime_to_tt2000(
-        datetime(2025, 6, 6, 12, 0, 0)
-    )
+    _EPOCH_TT2000_NS = spacepy.pycdf.lib.datetime_to_tt2000(datetime(2025, 6, 6, 12, 0, 0))
 
     def test_get_swapi_geometry_returns_orthonormal_rotation_per_time(self):
         """get_swapi_geometry returns one proper-orthogonal (right-handed) rotation matrix per input time across a 30 s window."""
@@ -359,12 +339,10 @@ def test_convert_sun_velocity_rtn_to_gse_matches_spice_state_of_imap(self):
             covariance_rtn,
         )
 
-        imap_velocity_from_earth_gse = spiceypy.spkezr(
-            "IMAP", et, "IMAP_GSE", "NONE", "EARTH"
-        )[0][3:]
-        np.testing.assert_allclose(
-            imap_velocity_from_earth_gse, velocity_gse, atol=1e-9
-        )
+        imap_velocity_from_earth_gse = spiceypy.spkezr("IMAP", et, "IMAP_GSE", "NONE", "EARTH")[0][
+            3:
+        ]
+        np.testing.assert_allclose(imap_velocity_from_earth_gse, velocity_gse, atol=1e-9)
 
         gse_from_rtn = spiceypy.pxform("IMAP_RTN", "IMAP_GSE", et)
         np.testing.assert_allclose(
@@ -384,12 +362,10 @@ def test_convert_sun_velocity_rtn_to_gse_matches_full_state_transform(self):
 
         eclipj2000_from_rtn = spiceypy.pxform("IMAP_RTN", "ECLIPJ2000", et)
         gse_from_eclipj2000 = spiceypy.sxform("ECLIPJ2000", "IMAP_GSE", et)
-        imap_position_from_earth = spiceypy.spkezr(
-            "IMAP", et, "ECLIPJ2000", "NONE", "EARTH"
-        )[0][:3]
-        earth_velocity_from_sun = spiceypy.spkezr(
-            "EARTH", et, "ECLIPJ2000", "NONE", "SUN"
-        )[0][3:]
+        imap_position_from_earth = spiceypy.spkezr("IMAP", et, "ECLIPJ2000", "NONE", "EARTH")[0][
+            :3
+        ]
+        earth_velocity_from_sun = spiceypy.spkezr("EARTH", et, "ECLIPJ2000", "NONE", "SUN")[0][3:]
         state_from_earth = np.concatenate(
             [
                 imap_position_from_earth,
@@ -408,54 +384,40 @@ class TestVelocityComponentsToAnglesInInstrumentFrame(TestCase):
 
     def test_flow_along_minus_y_returns_zero_angles(self):
         """A flow along -Y means SWAPI looks toward +Y, which is the (azimuth=0, elevation=0) bore-sight in the instrument frame."""
-        azimuth, elevation = velocity_components_to_angles_in_instrument_frame(
-            0.0, -450.0, 0.0
-        )
+        azimuth, elevation = velocity_components_to_angles_in_instrument_frame(0.0, -450.0, 0.0)
         self.assertAlmostEqual(azimuth, 0.0)
         self.assertAlmostEqual(elevation, 0.0)
 
     def test_positive_x_flow_yields_negative_azimuth(self):
         """A flow with a positive X component (look direction in -X) gives a negative azimuth, since azimuth = atan2(-vx, -vy) < 0 when vx > 0 and vy < 0."""
-        azimuth, _ = velocity_components_to_angles_in_instrument_frame(
-            50.0, -450.0, 0.0
-        )
+        azimuth, _ = velocity_components_to_angles_in_instrument_frame(50.0, -450.0, 0.0)
         self.assertLess(azimuth, 0.0)
 
     def test_positive_z_flow_yields_negative_elevation(self):
         """A flow with a positive Z component (look direction in -Z) gives a negative elevation, since elevation = asin(-vz/|v|) < 0 when vz > 0."""
-        _, elevation = velocity_components_to_angles_in_instrument_frame(
-            0.0, -450.0, 50.0
-        )
+        _, elevation = velocity_components_to_angles_in_instrument_frame(0.0, -450.0, 50.0)
         self.assertLess(elevation, 0.0)
 
     def test_negative_z_flow_yields_positive_elevation(self):
         """A flow with a negative Z component (look direction in +Z) gives a positive elevation."""
-        _, elevation = velocity_components_to_angles_in_instrument_frame(
-            0.0, -450.0, -50.0
-        )
+        _, elevation = velocity_components_to_angles_in_instrument_frame(0.0, -450.0, -50.0)
         self.assertGreater(elevation, 0.0)
 
     def test_pure_plus_x_flow_yields_azimuth_minus_90_elevation_zero(self):
         """A pure +X flow has look direction along -X; azimuth = atan2(-450, 0) = -90 deg, elevation = 0."""
-        azimuth, elevation = velocity_components_to_angles_in_instrument_frame(
-            450.0, 0.0, 0.0
-        )
+        azimuth, elevation = velocity_components_to_angles_in_instrument_frame(450.0, 0.0, 0.0)
         self.assertAlmostEqual(azimuth, -90.0)
         self.assertAlmostEqual(elevation, 0.0)
 
     def test_pure_plus_y_flow_yields_azimuth_180(self):
         """A pure +Y flow (away from SWAPI) has look direction along -Y; azimuth = atan2(0, -450) = +/-180 deg, elevation = 0."""
-        azimuth, elevation = velocity_components_to_angles_in_instrument_frame(
-            0.0, 450.0, 0.0
-        )
+        azimuth, elevation = velocity_components_to_angles_in_instrument_frame(0.0, 450.0, 0.0)
         self.assertAlmostEqual(abs(azimuth), 180.0)
         self.assertAlmostEqual(elevation, 0.0)
 
     def test_pure_plus_z_flow_yields_elevation_minus_90(self):
         """A pure +Z flow has look direction along -Z; elevation = asin(-1) = -90 deg."""
-        _, elevation = velocity_components_to_angles_in_instrument_frame(
-            0.0, 0.0, 450.0
-        )
+        _, elevation = velocity_components_to_angles_in_instrument_frame(0.0, 0.0, 450.0)
         self.assertAlmostEqual(elevation, -90.0)
 
 
@@ -486,9 +448,7 @@ def test_velocity_with_positive_z_inst_component_yields_negative_elevation(self)
 
     def test_uses_rotation_argument_to_transform_into_instrument_frame(self):
         """When the rotation maps +Y_inst to -X_RTN, an RTN flow along -X_RTN lands along +Y_inst and produces azimuth = atan2(0, -1) = +/-180 deg, catching regressions that drop the rotation."""
-        rotation_xyz_to_rtn = np.array(
-            [[0.0, -1.0, 0.0], [1.0, 0.0, 0.0], [0.0, 0.0, 1.0]]
-        )
+        rotation_xyz_to_rtn = np.array([[0.0, -1.0, 0.0], [1.0, 0.0, 0.0], [0.0, 0.0, 1.0]])
         sw = proton_params(velocity_rtn=(-450.0, 0.0, 0.0))
         azimuth, _ = velocity_to_angles_in_instrument_frame(sw, rotation_xyz_to_rtn)
         self.assertAlmostEqual(abs(azimuth), 180.0, places=10)
@@ -509,9 +469,7 @@ def test_matches_analytical_formula(self):
 
     def test_matches_hardcoded_reference_value_at_1000_volts(self):
         """At V = 1000 V the function returns ~601.730748 km/s, the value pre-computed offline from `sqrt(2 · 1.89 · q_p · 1000 / m_p) / 1000`. This pins the absolute magnitude against a manually verifiable number, not just the live formula."""
-        np.testing.assert_allclose(
-            esa_voltage_to_proton_speed(1000.0), 601.7307477647, rtol=1e-9
-        )
+        np.testing.assert_allclose(esa_voltage_to_proton_speed(1000.0), 601.7307477647, rtol=1e-9)
 
     def test_handles_negative_voltage(self):
         """A negative ESA voltage yields the same proton speed as its positive counterpart, since the conversion depends on magnitude."""
@@ -537,9 +495,7 @@ def test_matches_analytical_formula(self):
 
     def test_matches_hardcoded_reference_value_at_1000_volts(self):
         """At V = 1000 V the function returns ~426.952735 km/s, the value pre-computed offline from `sqrt(2 · 1.89 · 2·q_p · 1000 / m_alpha) / 1000`. This pins the absolute magnitude against a manually verifiable number, not just the live formula."""
-        np.testing.assert_allclose(
-            esa_voltage_to_alpha_speed(1000.0), 426.9527347202, rtol=1e-9
-        )
+        np.testing.assert_allclose(esa_voltage_to_alpha_speed(1000.0), 426.9527347202, rtol=1e-9)
 
     def test_handles_negative_voltage(self):
         """A negative ESA voltage yields the same alpha speed as its positive counterpart, since the conversion depends on magnitude."""
diff --git a/tests/swapi/l3b/science/test_calculate_solar_wind_differential_flux.py b/tests/swapi/l3b/science/test_calculate_solar_wind_differential_flux.py
index 1b03ae14..7b83faa2 100644
--- a/tests/swapi/l3b/science/test_calculate_solar_wind_differential_flux.py
+++ b/tests/swapi/l3b/science/test_calculate_solar_wind_differential_flux.py
@@ -24,8 +24,6 @@ def test_calculate_combined_differential_flux(self):
         differential_flux = calculate_combined_solar_wind_differential_flux(
             energies, count_rates, efficiency, mock_geometric_factor_table
         )
-        expected_flux = np.array(
-            [11.337868480725623, 302.3431594860166, 6802.721088435374]
-        )
+        expected_flux = np.array([11.337868480725623, 302.3431594860166, 6802.721088435374])
         np.testing.assert_array_almost_equal(expected_flux, differential_flux)
         mock_geometric_factor_table.lookup_geometric_factor.assert_called_with(energies)
diff --git a/tests/swapi/l3b/science/test_calculate_solar_wind_vdf.py b/tests/swapi/l3b/science/test_calculate_solar_wind_vdf.py
index 0d5d8cab..b671d798 100644
--- a/tests/swapi/l3b/science/test_calculate_solar_wind_vdf.py
+++ b/tests/swapi/l3b/science/test_calculate_solar_wind_vdf.py
@@ -4,11 +4,11 @@
 import numpy as np
 
 from imap_l3_processing.swapi.l3b.science.calculate_solar_wind_vdf import (
-    calculate_proton_solar_wind_vdf,
     GeometricFactorCalibrationTable,
     calculate_alpha_solar_wind_vdf,
-    calculate_pui_solar_wind_vdf,
     calculate_delta_minus_plus,
+    calculate_proton_solar_wind_vdf,
+    calculate_pui_solar_wind_vdf,
 )
 
 
diff --git a/tests/swapi/l3b/science/test_geometric_factor_calibration_table.py b/tests/swapi/l3b/science/test_geometric_factor_calibration_table.py
index d83605c1..f578e5e7 100644
--- a/tests/swapi/l3b/science/test_geometric_factor_calibration_table.py
+++ b/tests/swapi/l3b/science/test_geometric_factor_calibration_table.py
@@ -8,9 +8,7 @@
 
 class TestGeometricFactorTable(unittest.TestCase):
     def test_geometric_factor_table_from_file(self):
-        file_path = get_test_data_path(
-            "swapi/imap_swapi_energy-gf-sw-lut_20100101_v001.csv"
-        )
+        file_path = get_test_data_path("swapi/imap_swapi_energy-gf-sw-lut_20100101_v001.csv")
 
         calibration_table = GeometricFactorCalibrationTable.from_file(file_path)
 
diff --git a/tests/swapi/l3b/test_models.py b/tests/swapi/l3b/test_models.py
index e51718f2..580ece5b 100644
--- a/tests/swapi/l3b/test_models.py
+++ b/tests/swapi/l3b/test_models.py
@@ -11,13 +11,13 @@
     EPOCH_DELTA_CDF_VAR_NAME,
 )
 from imap_l3_processing.swapi.l3b.models import (
-    SwapiL3BCombinedVDF,
     COMBINED_SOLAR_WIND_DIFFERENTIAL_FLUX_CDF_VAR_NAME,
     COMBINED_SOLAR_WIND_DIFFERENTIAL_FLUX_DELTA_CDF_VAR_NAME,
-    SOLAR_WIND_ENERGY_CDF_VAR_NAME,
     SOLAR_WIND_COMBINED_ENERGY_DELTA_MINUS_CDF_VAR_NAME,
     SOLAR_WIND_COMBINED_ENERGY_DELTA_PLUS_CDF_VAR_NAME,
+    SOLAR_WIND_ENERGY_CDF_VAR_NAME,
     SOLAR_WIND_ENERGY_LABEL_CDF_VAR_NAME,
+    SwapiL3BCombinedVDF,
 )
 from tests.swapi.cdf_model_test_case import CdfModelTestCase
 
@@ -70,9 +70,7 @@ def test_combined_vdf_data_products(self):
             ]
         )
 
-        expected_combined_energy_labels = np.array(
-            ["ESA 01", "ESA 02", "ESA 03", "ESA 04"]
-        )
+        expected_combined_energy_labels = np.array(["ESA 01", "ESA 02", "ESA 03", "ESA 04"])
 
         vdf = SwapiL3BCombinedVDF(
             input_metadata=input_metadata,
@@ -103,9 +101,7 @@ def test_combined_vdf_data_products(self):
         self.assert_variable_attributes(
             variables[0], epoch, EPOCH_CDF_VAR_NAME, pycdf.const.CDF_TIME_TT2000
         )
-        self.assert_variable_attributes(
-            variables[1], epoch_delta, EPOCH_DELTA_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(variables[1], epoch_delta, EPOCH_DELTA_CDF_VAR_NAME)
 
         self.assert_variable_attributes(
             variables[2], combined_energies, SOLAR_WIND_ENERGY_CDF_VAR_NAME
diff --git a/tests/swapi/l3b/test_swapi_l3b_dependencies.py b/tests/swapi/l3b/test_swapi_l3b_dependencies.py
index 3fd283f7..4eb8dcfd 100644
--- a/tests/swapi/l3b/test_swapi_l3b_dependencies.py
+++ b/tests/swapi/l3b/test_swapi_l3b_dependencies.py
@@ -1,19 +1,19 @@
 import unittest
 from datetime import datetime
 from pathlib import Path
-from unittest.mock import patch, call, sentinel
+from unittest.mock import call, patch, sentinel
 
 import imap_data_access
 from imap_data_access.processing_input import (
-    ScienceInput,
-    ProcessingInputCollection,
     AncillaryInput,
+    ProcessingInputCollection,
+    ScienceInput,
 )
 
 from imap_l3_processing.swapi.descriptors import (
-    SWAPI_L2_DESCRIPTOR,
-    GEOMETRIC_FACTOR_SW_LOOKUP_TABLE_DESCRIPTOR,
     EFFICIENCY_LOOKUP_TABLE_DESCRIPTOR,
+    GEOMETRIC_FACTOR_SW_LOOKUP_TABLE_DESCRIPTOR,
+    SWAPI_L2_DESCRIPTOR,
 )
 from imap_l3_processing.swapi.l3b.swapi_l3b_dependencies import SwapiL3BDependencies
 
@@ -35,9 +35,15 @@ def test_fetch_dependencies(self, mock_download, mock_from_file_paths):
         version = "v002"
         start_date = datetime(2025, 1, 1).strftime("%Y%m%d")
 
-        science_file_path = f"imap_swapi_{incoming_data_level}_{SWAPI_L2_DESCRIPTOR}_{start_date}_{version}.cdf"
-        geometric_calibration_path = f"imap_swapi_{GEOMETRIC_FACTOR_SW_LOOKUP_TABLE_DESCRIPTOR}_{start_date}_{version}.cdf"
-        efficiency_table_path = f"imap_swapi_{EFFICIENCY_LOOKUP_TABLE_DESCRIPTOR}_{start_date}_{version}.cdf"
+        science_file_path = (
+            f"imap_swapi_{incoming_data_level}_{SWAPI_L2_DESCRIPTOR}_{start_date}_{version}.cdf"
+        )
+        geometric_calibration_path = (
+            f"imap_swapi_{GEOMETRIC_FACTOR_SW_LOOKUP_TABLE_DESCRIPTOR}_{start_date}_{version}.cdf"
+        )
+        efficiency_table_path = (
+            f"imap_swapi_{EFFICIENCY_LOOKUP_TABLE_DESCRIPTOR}_{start_date}_{version}.cdf"
+        )
 
         science_input = ScienceInput(science_file_path)
         geometric_calibration_input = AncillaryInput(geometric_calibration_path)
@@ -46,26 +52,15 @@ def test_fetch_dependencies(self, mock_download, mock_from_file_paths):
             science_input, geometric_calibration_input, efficiency_table_input
         )
 
-        actual_swapi_l3b_dependencies = SwapiL3BDependencies.fetch_dependencies(
-            dependencies
-        )
+        actual_swapi_l3b_dependencies = SwapiL3BDependencies.fetch_dependencies(dependencies)
 
         sci_data_dir = (
-            imap_data_access.config["DATA_DIR"]
-            / "imap"
-            / "swapi"
-            / "l2"
-            / "2025"
-            / "01"
-        )
-        ancillary_data_dir = (
-            imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "swapi"
+            imap_data_access.config["DATA_DIR"] / "imap" / "swapi" / "l2" / "2025" / "01"
         )
+        ancillary_data_dir = imap_data_access.config["DATA_DIR"] / "imap" / "ancillary" / "swapi"
 
         expected_download_science_path = sci_data_dir / science_file_path
-        expected_geometric_calibration_path = (
-            ancillary_data_dir / geometric_calibration_path
-        )
+        expected_geometric_calibration_path = ancillary_data_dir / geometric_calibration_path
         expected_efficiency_table_path = ancillary_data_dir / efficiency_table_path
 
         mock_download.assert_has_calls(
@@ -82,14 +77,10 @@ def test_fetch_dependencies(self, mock_download, mock_from_file_paths):
             expected_efficiency_table_path,
         )
 
-        self.assertEqual(
-            mock_from_file_paths.return_value, actual_swapi_l3b_dependencies
-        )
+        self.assertEqual(mock_from_file_paths.return_value, actual_swapi_l3b_dependencies)
 
     @patch("imap_l3_processing.swapi.l3b.swapi_l3b_dependencies.CDF")
-    @patch(
-        "imap_l3_processing.swapi.l3b.swapi_l3b_dependencies.EfficiencyCalibrationTable"
-    )
+    @patch("imap_l3_processing.swapi.l3b.swapi_l3b_dependencies.EfficiencyCalibrationTable")
     @patch(
         "imap_l3_processing.swapi.l3b.swapi_l3b_dependencies.GeometricFactorCalibrationTable.from_file"
     )
@@ -137,9 +128,7 @@ def test_from_file_paths(
         mock_read_geometric_factor.assert_called_once_with(
             swapi_geometric_factor_calibration_file_path
         )
-        mock_efficiency_calibration.assert_called_once_with(
-            swapi_efficiency_calibration_file_path
-        )
+        mock_efficiency_calibration.assert_called_once_with(swapi_efficiency_calibration_file_path)
 
         mock_cdf.assert_called_once_with(str(swapi_science_file_download_path))
 
diff --git a/tests/swapi/response/test_azimuthal_transmission.py b/tests/swapi/response/test_azimuthal_transmission.py
index 20c6e6a9..3431493b 100644
--- a/tests/swapi/response/test_azimuthal_transmission.py
+++ b/tests/swapi/response/test_azimuthal_transmission.py
@@ -6,17 +6,17 @@
 import pandas as pd
 
 from imap_l3_processing.swapi.response.azimuthal_transmission import (
-    AzimuthalTransmissionGrid,
     OA_PLATEAU_AZIMUTH_MAX_DEG,
     OA_PLATEAU_AZIMUTH_MIN_DEG,
     OA_PLATEAU_TRANSMISSION,
     SG_PLATEAU_AZIMUTH_MAX_DEG,
     SG_PLATEAU_TRANSMISSION,
+    AzimuthalTransmissionGrid,
     interpolate_azimuthal_transmission,
     validate_azimuthal_transmission_values,
 )
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
-from tests.test_helpers import get_test_instrument_team_data_path, get_test_data_path
+from tests.test_helpers import get_test_data_path, get_test_instrument_team_data_path
 
 _TRANSMISSION_CSV = get_test_instrument_team_data_path(
     "swapi/imap_swapi_azimuthal-transmission_20260425_v001.csv"
@@ -79,9 +79,7 @@ def test_linear_interpolation_off_center_between_grid_points(self):
         for fraction in [0.25, 0.7, 0.9]:
             with self.subTest(fraction=fraction):
                 az = az_lower + fraction * _SPACING_DEG
-                expected = (1 - fraction) * self.values[idx] + fraction * self.values[
-                    idx + 1
-                ]
+                expected = (1 - fraction) * self.values[idx] + fraction * self.values[idx + 1]
                 got = interpolate_azimuthal_transmission(self.grid, az)
                 self.assertAlmostEqual(got, float(expected))
 
@@ -120,10 +118,10 @@ def test_wraps_arguments_into_canonical_180_interval(self):
           - multi-period inputs (±541°) wrap into the canonical interval
             (541 mod 360 = 181 → wraps to -179° → |az| = 179°)
         """
-        idx_at_1deg = int(round(1.0 / _SPACING_DEG))
+        idx_at_1deg = round(1.0 / _SPACING_DEG)
         expected_at_1deg = float(self.values[idx_at_1deg])
         last_value = float(self.values[-1])
-        idx_at_179deg = int(round(179.0 / _SPACING_DEG))
+        idx_at_179deg = round(179.0 / _SPACING_DEG)
         expected_at_179deg = float(self.values[idx_at_179deg])
 
         for label, az, expected in [
@@ -172,9 +170,7 @@ def test_csv_layout_matches_production_spacing(self):
         self.assertAlmostEqual(float(grid.values[0]), 1e-3)
 
 
-def _build_grid_satisfying_invariants(
-    spacing: float = 0.1, n: int = 1801
-) -> np.ndarray:
+def _build_grid_satisfying_invariants(spacing: float = 0.1, n: int = 1801) -> np.ndarray:
     """Build a synthetic values array that respects the SG-floor and OA-plateau
     invariants the interpolator's short-circuit branches assume. Cells outside
     those two ranges are set to a neutral 0.5 so a test can corrupt a single
@@ -225,7 +221,7 @@ def test_raises_when_oa_plateau_value_is_wrong(self):
     def test_raises_when_sg_plateau_endpoint_is_wrong(self):
         # |az| = 9.0° (= SG_PLATEAU_AZIMUTH_MAX_DEG) is inclusive.
         values = _build_grid_satisfying_invariants()
-        endpoint_index = int(round(SG_PLATEAU_AZIMUTH_MAX_DEG / 0.1))
+        endpoint_index = round(SG_PLATEAU_AZIMUTH_MAX_DEG / 0.1)
         values[endpoint_index] = 0.5
         with self.assertRaises(ValueError):
             validate_azimuthal_transmission_values(values, 0.1)
@@ -233,7 +229,7 @@ def test_raises_when_sg_plateau_endpoint_is_wrong(self):
     def test_raises_when_oa_plateau_endpoint_is_wrong(self):
         # The 115° endpoint is inclusive — corrupt it and validation must trip.
         values = _build_grid_satisfying_invariants()
-        endpoint_index = int(round(OA_PLATEAU_AZIMUTH_MAX_DEG / 0.1))
+        endpoint_index = round(OA_PLATEAU_AZIMUTH_MAX_DEG / 0.1)
         values[endpoint_index] = 0.5
         with self.assertRaises(ValueError):
             validate_azimuthal_transmission_values(values, 0.1)
diff --git a/tests/swapi/response/test_efficiency_calibration_table.py b/tests/swapi/response/test_efficiency_calibration_table.py
index 9ce85a64..4a01916a 100644
--- a/tests/swapi/response/test_efficiency_calibration_table.py
+++ b/tests/swapi/response/test_efficiency_calibration_table.py
@@ -104,15 +104,9 @@ def test_relative_efficiency_handles_float_input(self):
         )
         efficiency_table = EfficiencyCalibrationTable(calibration_table_path)
 
-        time_as_float = float(
-            pycdf.lib.datetime_to_tt2000(datetime(year=2001, month=2, day=1))
-        )
-        self.assertEqual(
-            efficiency_table.relative_efficiency(time_as_float, Species.ALPHA), 0.9
-        )
-        self.assertEqual(
-            efficiency_table.relative_efficiency(time_as_float, Species.PROTON), 0.1
-        )
+        time_as_float = float(pycdf.lib.datetime_to_tt2000(datetime(year=2001, month=2, day=1)))
+        self.assertEqual(efficiency_table.relative_efficiency(time_as_float, Species.ALPHA), 0.9)
+        self.assertEqual(efficiency_table.relative_efficiency(time_as_float, Species.PROTON), 0.1)
 
     def test_raises_exception_if_ask_for_time_before_the_table_starts(self):
         """A time earlier than every row raises rather than falling back to the first row."""
@@ -127,9 +121,7 @@ def test_raises_exception_if_ask_for_time_before_the_table_starts(self):
                 pycdf.lib.datetime_to_tt2000(time), Species.PROTON
             )
 
-        self.assertEqual(
-            (f"No efficiency data for {time}",), content_manager.exception.args
-        )
+        self.assertEqual((f"No efficiency data for {time}",), content_manager.exception.args)
 
     def test_loads_calibration_table_with_single_row(self):
         """A one-row table still parses and serves both species for any later time."""
@@ -140,12 +132,6 @@ def test_loads_calibration_table_with_single_row(self):
 
         # file has one row, with 0.1 for H, 0.9 for He.
 
-        time_after_row = pycdf.lib.datetime_to_tt2000(
-            datetime(year=2001, month=2, day=1)
-        )
-        self.assertEqual(
-            efficiency_table.relative_efficiency(time_after_row, Species.PROTON), 0.1
-        )
-        self.assertEqual(
-            efficiency_table.relative_efficiency(time_after_row, Species.ALPHA), 0.9
-        )
+        time_after_row = pycdf.lib.datetime_to_tt2000(datetime(year=2001, month=2, day=1))
+        self.assertEqual(efficiency_table.relative_efficiency(time_after_row, Species.PROTON), 0.1)
+        self.assertEqual(efficiency_table.relative_efficiency(time_after_row, Species.ALPHA), 0.9)
diff --git a/tests/swapi/response/test_passband_grid.py b/tests/swapi/response/test_passband_grid.py
index bd6c8568..f241258b 100644
--- a/tests/swapi/response/test_passband_grid.py
+++ b/tests/swapi/response/test_passband_grid.py
@@ -3,6 +3,7 @@
 import numpy as np
 import pandas as pd
 
+from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.response.passband_grid import (
     _PASSBAND_BOUNDARY_THRESHOLD,
     _TARGET_ELEVATIONS,
@@ -11,7 +12,6 @@
     interpolate_passband,
     speed_ratio_range_at_elevation,
 )
-from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 
 
 def _gaussian_values_df(
@@ -55,7 +55,7 @@ def _gaussian_values_df(
 
 def _row_index_for_elevation(grid, elevation: float) -> int:
     """Index into `grid.values` for the row at the given target elevation."""
-    return int(round((elevation - grid.min_elevation) / grid.elevation_spacing))
+    return round((elevation - grid.min_elevation) / grid.elevation_spacing)
 
 
 class TestBuildPassbandGrid(unittest.TestCase):
@@ -95,15 +95,11 @@ def test_boundary_marks_cutoff_crossing(self):
                 continue
             with self.subTest(row=i):
                 np.testing.assert_allclose(
-                    np.interp(
-                        grid.min_boundary[i], _TARGET_SPEED_RATIOS, grid.values[i]
-                    ),
+                    np.interp(grid.min_boundary[i], _TARGET_SPEED_RATIOS, grid.values[i]),
                     cutoff,
                 )
                 np.testing.assert_allclose(
-                    np.interp(
-                        grid.max_boundary[i], _TARGET_SPEED_RATIOS, grid.values[i]
-                    ),
+                    np.interp(grid.max_boundary[i], _TARGET_SPEED_RATIOS, grid.values[i]),
                     cutoff,
                 )
 
@@ -186,12 +182,8 @@ def test_matches_corner_weighted_sum(self):
         ]
         for elevation, speed_ratio, label in cases:
             with self.subTest(label=label):
-                i_float = (
-                    elevation - self.grid.min_elevation
-                ) / self.grid.elevation_spacing
-                j_float = (
-                    speed_ratio - self.grid.min_speed_ratio
-                ) / self.grid.speed_ratio_spacing
+                i_float = (elevation - self.grid.min_elevation) / self.grid.elevation_spacing
+                j_float = (speed_ratio - self.grid.min_speed_ratio) / self.grid.speed_ratio_spacing
                 i_lo, j_lo = int(i_float), int(j_float)
                 i_weight, j_weight = i_float - i_lo, j_float - j_lo
 
@@ -241,12 +233,8 @@ def test_returns_cutoff_crossing_for_on_grid_elevation(self):
             with self.subTest(elevation=elevation):
                 lo, hi = speed_ratio_range_at_elevation(grid, float(elevation))
                 row = grid.values[_row_index_for_elevation(grid, float(elevation))]
-                self.assertAlmostEqual(
-                    np.interp(lo, _TARGET_SPEED_RATIOS, row), cutoff, places=2
-                )
-                self.assertAlmostEqual(
-                    np.interp(hi, _TARGET_SPEED_RATIOS, row), cutoff, places=2
-                )
+                self.assertAlmostEqual(np.interp(lo, _TARGET_SPEED_RATIOS, row), cutoff, places=2)
+                self.assertAlmostEqual(np.interp(hi, _TARGET_SPEED_RATIOS, row), cutoff, places=2)
 
     def test_returns_union_of_bracketing_rows_for_off_grid_elevation(self):
         """For an elevation between two grid rows, the returned (lo, hi)
@@ -256,12 +244,8 @@ def test_returns_union_of_bracketing_rows_for_off_grid_elevation(self):
         between_elevation = 0.25
         lower_row = _row_index_for_elevation(self.grid, lower_elevation)
         upper_row = _row_index_for_elevation(self.grid, upper_elevation)
-        expected_lo = min(
-            self.grid.min_boundary[lower_row], self.grid.min_boundary[upper_row]
-        )
-        expected_hi = max(
-            self.grid.max_boundary[lower_row], self.grid.max_boundary[upper_row]
-        )
+        expected_lo = min(self.grid.min_boundary[lower_row], self.grid.min_boundary[upper_row])
+        expected_hi = max(self.grid.max_boundary[lower_row], self.grid.max_boundary[upper_row])
         lo, hi = speed_ratio_range_at_elevation(self.grid, between_elevation)
         self.assertAlmostEqual(lo, expected_lo)
         self.assertAlmostEqual(hi, expected_hi)
@@ -271,9 +255,7 @@ def test_min_is_no_greater_than_max(self):
         active_lo, active_hi = self.grid.elevation_range
         for elevation in np.linspace(active_lo, active_hi, 7):
             with self.subTest(elevation=elevation):
-                lower, upper = speed_ratio_range_at_elevation(
-                    self.grid, float(elevation)
-                )
+                lower, upper = speed_ratio_range_at_elevation(self.grid, float(elevation))
                 self.assertLessEqual(lower, upper)
 
     def test_nan_row_handling_at_active_range_edges(self):
@@ -309,13 +291,11 @@ def test_nan_row_handling_at_active_range_edges(self):
         past_upper_edge = min_el + spacing * n_rows + 100.0
         past_lower_edge = min_el - 100.0
 
-        with self.subTest(case="both NaN past upper edge"):
-            with self.assertRaises(ValueError):
-                speed_ratio_range_at_elevation(grid, float(past_upper_edge))
+        with self.subTest(case="both NaN past upper edge"), self.assertRaises(ValueError):
+            speed_ratio_range_at_elevation(grid, float(past_upper_edge))
 
-        with self.subTest(case="both NaN past lower edge"):
-            with self.assertRaises(ValueError):
-                speed_ratio_range_at_elevation(grid, float(past_lower_edge))
+        with self.subTest(case="both NaN past lower edge"), self.assertRaises(ValueError):
+            speed_ratio_range_at_elevation(grid, float(past_lower_edge))
 
         with self.subTest(case="only upper row NaN at top of active range"):
             lo, hi = speed_ratio_range_at_elevation(grid, float(upper_edge_one_nan))
diff --git a/tests/swapi/response/test_swapi_response.py b/tests/swapi/response/test_swapi_response.py
index fa5b398f..6abfc8f8 100644
--- a/tests/swapi/response/test_swapi_response.py
+++ b/tests/swapi/response/test_swapi_response.py
@@ -9,7 +9,7 @@
 from imap_l3_processing.swapi.constants import SWAPI_K_FACTOR
 from imap_l3_processing.swapi.response.swapi_response import SwapiResponse
 from imap_l3_processing.swapi.species import Species
-from tests.test_helpers import get_test_instrument_team_data_path, get_test_data_path
+from tests.test_helpers import get_test_data_path, get_test_instrument_team_data_path
 
 
 def _load_response() -> SwapiResponse:
@@ -49,9 +49,7 @@ def test_populates_cache_with_unique_finite_voltages(self):
         """Duplicates collapse, NaN/inf are skipped."""
         voltages = np.array([100.0, 100.0, 200.0, 300.0, np.nan, np.inf])
         self.response.warm_cache(voltages)
-        self.assertEqual(
-            set(self.response._passband_grid_cache.keys()), {100.0, 200.0, 300.0}
-        )
+        self.assertEqual(set(self.response._passband_grid_cache.keys()), {100.0, 200.0, 300.0})
         self.assertEqual(len(self.response._passband_grid_cache), 3)
 
     def test_warming_twice_at_same_voltage_is_a_noop(self):
@@ -59,8 +57,7 @@ def test_warming_twice_at_same_voltage_is_a_noop(self):
         PassbandGrid objects — it does not rebuild them."""
         self.response.warm_cache([750.0])
         first_grids = {
-            region: self.response._passband_grid_cache[750.0][region]
-            for region in ("SG", "OA")
+            region: self.response._passband_grid_cache[750.0][region] for region in ("SG", "OA")
         }
         self.response.warm_cache([750.0])
 
@@ -75,9 +72,7 @@ def test_accepts_2d_voltage_array(self):
         """Multidimensional voltage inputs are flattened."""
         voltages = np.array([[100.0, 200.0], [200.0, 300.0]])
         self.response.warm_cache(voltages)
-        self.assertEqual(
-            set(self.response._passband_grid_cache.keys()), {100.0, 200.0, 300.0}
-        )
+        self.assertEqual(set(self.response._passband_grid_cache.keys()), {100.0, 200.0, 300.0})
 
 
 class TestPassbandInterpolation(_RealResponseFixture):
@@ -101,24 +96,18 @@ def test_values_match_manual_polyval(self):
 
                 returned = self.response._get_passband_values(voltage, region)
 
-                coeffs = self.response._passband_fit_coefficients.xs(
-                    region, level="region"
-                )
+                coeffs = self.response._passband_fit_coefficients.xs(region, level="region")
                 log_beam_energy = np.log(SWAPI_K_FACTOR * voltage)
                 n_degrees = coeffs.shape[1]
                 degrees = np.arange(n_degrees - 1, -1, -1)
-                expected_exponent = (coeffs.values * log_beam_energy**degrees).sum(
-                    axis=1
-                )
+                expected_exponent = (coeffs.values * log_beam_energy**degrees).sum(axis=1)
                 expected = np.exp(expected_exponent)
 
                 npt.assert_allclose(returned["value"].to_numpy(), expected, rtol=1e-12)
 
     def _assert_grid_value_bounds(self, esa_voltage):
         self.response.warm_cache([esa_voltage])
-        cached = self.response._passband_grid_cache[
-            self.response._cache_key(esa_voltage)
-        ]
+        cached = self.response._passband_grid_cache[self.response._cache_key(esa_voltage)]
         for region in ("SG", "OA"):
             grid = cached[region]
             self.assertGreaterEqual(
@@ -149,15 +138,9 @@ def test_get_response_grid(self):
         response = _load_response()
         response.warm_cache(esa_voltage)
 
-        response_grid = response.get_response_grid(
-            time_as_tt2000, esa_voltage, Species.PROTON
-        )
-        self.assertAlmostEqual(
-            response_grid.central_effective_area, 0.37553722631276887
-        )
-        self.assertIs(
-            response_grid.azimuthal_transmission, response._azimuthal_transmission_grid
-        )
+        response_grid = response.get_response_grid(time_as_tt2000, esa_voltage, Species.PROTON)
+        self.assertAlmostEqual(response_grid.central_effective_area, 0.37553722631276887)
+        self.assertIs(response_grid.azimuthal_transmission, response._azimuthal_transmission_grid)
         self.assertIs(
             response_grid.oa_passband,
             response._passband_grid_cache[round(esa_voltage, 3)]["OA"],
@@ -176,13 +159,9 @@ def test_get_response_grid(self):
             )
             / constants.METERS_PER_KILOMETER
         )
-        self.assertAlmostEqual(
-            response_grid.central_speed, expected_central_speed_km_per_s
-        )
+        self.assertAlmostEqual(response_grid.central_speed, expected_central_speed_km_per_s)
 
-        response_grid2 = response.get_response_grid(
-            time_as_tt2000, esa_voltage, Species.PROTON
-        )
+        response_grid2 = response.get_response_grid(time_as_tt2000, esa_voltage, Species.PROTON)
         self.assertIs(response_grid, response_grid2, "cache miss")
 
         for species, mass_per_charge in [
diff --git a/tests/swapi/test_constants.py b/tests/swapi/test_constants.py
index 29f4f87d..26865c0d 100644
--- a/tests/swapi/test_constants.py
+++ b/tests/swapi/test_constants.py
@@ -26,9 +26,7 @@ def test_coarse_and_fine_partition_science_bins(self):
         self.assertEqual(SWAPI_FINE_SWEEP_BINS.stop, SWAPI_SCIENCE_BINS.stop)
 
     def test_coarse_sweep_has_62_bins_and_fine_has_9(self):
-        self.assertEqual(
-            SWAPI_COARSE_SWEEP_BINS.stop - SWAPI_COARSE_SWEEP_BINS.start, 62
-        )
+        self.assertEqual(SWAPI_COARSE_SWEEP_BINS.stop - SWAPI_COARSE_SWEEP_BINS.start, 62)
         self.assertEqual(SWAPI_FINE_SWEEP_BINS.stop - SWAPI_FINE_SWEEP_BINS.start, 9)
 
     def test_simion_k_factor(self):
diff --git a/tests/swapi/test_swapi_processor.py b/tests/swapi/test_swapi_processor.py
index ecda6663..72033268 100644
--- a/tests/swapi/test_swapi_processor.py
+++ b/tests/swapi/test_swapi_processor.py
@@ -1,31 +1,31 @@
 from dataclasses import replace
-from datetime import datetime, timedelta, date
+from datetime import date, datetime, timedelta
 from unittest import TestCase
-from unittest.mock import patch, sentinel, call, Mock
+from unittest.mock import Mock, call, patch, sentinel
 
 import numpy as np
 from imap_data_access import config
 from imap_data_access.file_validation import Version
 from imap_data_access.processing_input import (
+    AncillaryInput,
     ProcessingInputCollection,
     ScienceInput,
-    AncillaryInput,
 )
-from uncertainties.unumpy import uarray, nominal_values, std_devs
+from uncertainties.unumpy import nominal_values, std_devs, uarray
 
 from imap_l3_processing.constants import (
-    THIRTY_SECONDS_IN_NANOSECONDS,
     FIVE_MINUTES_IN_NANOSECONDS,
+    THIRTY_SECONDS_IN_NANOSECONDS,
 )
 from imap_l3_processing.models import InputMetadata, VersionMap
 from imap_l3_processing.swapi.descriptors import (
+    AZIMUTHAL_TRANSMISSION_DESCRIPTOR,
+    CENTRAL_EFFECTIVE_AREA_DESCRIPTOR,
     DENSITY_OF_NEUTRAL_HELIUM_DESCRIPTOR,
     EFFICIENCY_LOOKUP_TABLE_DESCRIPTOR,
     GEOMETRIC_FACTOR_SW_LOOKUP_TABLE_DESCRIPTOR,
-    HYDROGEN_INFLOW_VECTOR_DESCRIPTOR,
     HELIUM_INFLOW_VECTOR_DESCRIPTOR,
-    AZIMUTHAL_TRANSMISSION_DESCRIPTOR,
-    CENTRAL_EFFECTIVE_AREA_DESCRIPTOR,
+    HYDROGEN_INFLOW_VECTOR_DESCRIPTOR,
     PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR,
 )
 from imap_l3_processing.swapi.l3a.models import SwapiL2Data
@@ -80,11 +80,11 @@ def test_process_l3a_pui(
         returned_chunk_epoch = 10 + THIRTY_SECONDS_IN_NANOSECONDS
         returned_velocity_rtn_sc = np.array([370.0, 10.0, 5.0])
 
-        proton_runner_result = dict(
-            epoch=np.array([returned_chunk_epoch]),
-            proton_sw_velocity_rtn=np.array([returned_velocity_rtn_sc]),
-            quality_flags=np.array([SwapiL3Flags.NONE]),
-        )
+        proton_runner_result = {
+            "epoch": np.array([returned_chunk_epoch]),
+            "proton_sw_velocity_rtn": np.array([returned_velocity_rtn_sc]),
+            "quality_flags": np.array([SwapiL3Flags.NONE]),
+        }
 
         initial_epoch = 10
 
@@ -122,14 +122,14 @@ def test_process_l3a_pui(
             coincidence_count_rate_uncertainty_fifty,
         )
 
-        pui_runner_result = dict(
-            epoch=np.array([initial_epoch + FIVE_MINUTES_IN_NANOSECONDS]),
-            ionization_rate=np.array([2]),
-            cutoff_speed=np.array([3]),
-            density=np.array([5]),
-            temperature=np.array([6]),
-            quality_flags=np.array([SwapiL3Flags.NONE]),
-        )
+        pui_runner_result = {
+            "epoch": np.array([initial_epoch + FIVE_MINUTES_IN_NANOSECONDS]),
+            "ionization_rate": np.array([2]),
+            "cutoff_speed": np.array([3]),
+            "density": np.array([5]),
+            "temperature": np.array([6]),
+            "quality_flags": np.array([SwapiL3Flags.NONE]),
+        }
         mock_runner = mock_parallel_chunk_runner_class.return_value
         mock_runner.run.side_effect = [proton_runner_result, pui_runner_result]
 
@@ -142,9 +142,7 @@ def test_process_l3a_pui(
             f"imap_{instrument}_{DENSITY_OF_NEUTRAL_HELIUM_DESCRIPTOR}_{dependency_start_date}_{version}.cdf",
         ]
 
-        ancillary_inputs = [
-            AncillaryInput(file_name) for file_name in input_file_names[1:]
-        ]
+        ancillary_inputs = [AncillaryInput(file_name) for file_name in input_file_names[1:]]
 
         dependencies = ProcessingInputCollection(science_input, *ancillary_inputs)
 
@@ -173,9 +171,7 @@ def test_process_l3a_pui(
             [chunk_of_fifty],
         ]
 
-        mock_l3a_dependencies = (
-            mock_swapi_l3_dependencies_class.fetch_dependencies.return_value
-        )
+        mock_l3a_dependencies = mock_swapi_l3_dependencies_class.fetch_dependencies.return_value
         mock_l3a_dependencies.data = Mock(energy=energy_1d)
 
         mock_manager = mock_imap_attribute_manager.return_value
@@ -189,9 +185,7 @@ def test_process_l3a_pui(
             dependency_start_date,
         )
 
-        mock_swapi_l3_dependencies_class.fetch_dependencies.assert_called_once_with(
-            dependencies
-        )
+        mock_swapi_l3_dependencies_class.fetch_dependencies.assert_called_once_with(dependencies)
 
         mock_swapi_response = mock_l3a_dependencies.swapi_response
         mock_efficiency_lut = mock_l3a_dependencies.efficiency_calibration_table
@@ -225,12 +219,8 @@ def test_process_l3a_pui(
             pui_fitter_kwargs["density_of_neutral_helium_lookup_table"],
             mock_density_of_neutral_helium_calibration_table,
         )
-        self.assertIs(
-            pui_fitter_kwargs["hydrogen_inflow_vector"], mock_hydrogen_inflow_vector
-        )
-        self.assertIs(
-            pui_fitter_kwargs["helium_inflow_vector"], mock_helium_inflow_vector
-        )
+        self.assertIs(pui_fitter_kwargs["hydrogen_inflow_vector"], mock_hydrogen_inflow_vector)
+        self.assertIs(pui_fitter_kwargs["helium_inflow_vector"], mock_helium_inflow_vector)
         self.assertIs(pui_fitter_kwargs["proton_sw_results"], proton_runner_result)
 
         mock_manager.add_global_attribute.assert_has_calls(
@@ -238,9 +228,7 @@ def test_process_l3a_pui(
                 call("Data_version", outgoing_version),
                 call("Generation_date", date.today().strftime("%Y%m%d")),
                 call("Logical_source", "imap_swapi_l3a_pui-he"),
-                call(
-                    "Logical_file_id", f"imap_swapi_l3a_pui-he_{start_date_as_str}_v123"
-                ),
+                call("Logical_file_id", f"imap_swapi_l3a_pui-he_{start_date_as_str}_v123"),
             ]
         )
 
@@ -250,9 +238,7 @@ def test_process_l3a_pui(
         for key, expected_val in pui_runner_result.items():
             np.testing.assert_array_equal(expected_val, actual_kwargs[key])
 
-        mock_manager.add_instrument_attrs.assert_called_once_with(
-            "swapi", "l3a", descriptor
-        )
+        mock_manager.add_instrument_attrs.assert_called_once_with("swapi", "l3a", descriptor)
 
         self.assertEqual(input_file_names, pickup_ion_data.parent_file_names)
         mock_write_cdf.assert_called_once_with(
@@ -322,25 +308,25 @@ def test_process_l3a_proton(
             f"imap_{instrument}_{incoming_data_level}_{SWAPI_L2_DESCRIPTOR}_{dependency_start_date}_{version}.cdf"
         )
 
-        runner_result = dict(
-            epoch=np.array([initial_epoch + THIRTY_SECONDS_IN_NANOSECONDS]),
-            proton_sw_speed=np.array([400000.0]),
-            proton_sw_speed_uncert=np.array([2.0]),
-            proton_sw_speed_sun=np.array([401000.0]),
-            proton_sw_speed_sun_uncert=np.array([2.5]),
-            proton_sw_temperature=np.array([99000.0]),
-            proton_sw_temperature_uncert=np.array([1000.0]),
-            proton_sw_density=np.array([4.97]),
-            proton_sw_density_uncert=np.array([0.25]),
-            proton_sw_clock_angle=np.array([200.0]),
-            proton_sw_clock_angle_uncert=np.array([0.25]),
-            proton_sw_deflection_angle=np.array([5.0]),
-            proton_sw_deflection_angle_uncert=np.array([0.001]),
-            proton_sw_velocity_rtn_sun=np.array([[400.0, 10.0, 5.0]]),
-            proton_sw_velocity_rtn=np.array([[370.0, 10.0, 5.0]]),
-            proton_sw_velocity_rtn_covariance=np.array([np.eye(3)]),
-            quality_flags=np.array([SwapiL3Flags.NONE]),
-        )
+        runner_result = {
+            "epoch": np.array([initial_epoch + THIRTY_SECONDS_IN_NANOSECONDS]),
+            "proton_sw_speed": np.array([400000.0]),
+            "proton_sw_speed_uncert": np.array([2.0]),
+            "proton_sw_speed_sun": np.array([401000.0]),
+            "proton_sw_speed_sun_uncert": np.array([2.5]),
+            "proton_sw_temperature": np.array([99000.0]),
+            "proton_sw_temperature_uncert": np.array([1000.0]),
+            "proton_sw_density": np.array([4.97]),
+            "proton_sw_density_uncert": np.array([0.25]),
+            "proton_sw_clock_angle": np.array([200.0]),
+            "proton_sw_clock_angle_uncert": np.array([0.25]),
+            "proton_sw_deflection_angle": np.array([5.0]),
+            "proton_sw_deflection_angle_uncert": np.array([0.001]),
+            "proton_sw_velocity_rtn_sun": np.array([[400.0, 10.0, 5.0]]),
+            "proton_sw_velocity_rtn": np.array([[370.0, 10.0, 5.0]]),
+            "proton_sw_velocity_rtn_covariance": np.array([np.eye(3)]),
+            "quality_flags": np.array([SwapiL3Flags.NONE]),
+        }
         mock_runner = mock_parallel_chunk_runner_class.return_value
         mock_runner.run.return_value = runner_result
 
@@ -355,9 +341,7 @@ def test_process_l3a_proton(
             f"imap_{instrument}_{PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR}_{dependency_start_date}_{version}.cdf",
         ]
 
-        ancillary_inputs = [
-            AncillaryInput(file_name) for file_name in input_file_names[1:]
-        ]
+        ancillary_inputs = [AncillaryInput(file_name) for file_name in input_file_names[1:]]
 
         dependencies = ProcessingInputCollection(science_input, *ancillary_inputs)
 
@@ -386,18 +370,14 @@ def test_process_l3a_proton(
 
         swapi_l3a_dependencies = create_swapi_l3a_dependencies_with_mocks()
         swapi_l3a_dependencies.data = Mock(energy=energy)
-        mock_swapi_l3_dependencies_class.fetch_dependencies.return_value = (
-            swapi_l3a_dependencies
-        )
+        mock_swapi_l3_dependencies_class.fetch_dependencies.return_value = swapi_l3a_dependencies
 
         mock_manager = mock_imap_attribute_manager.return_value
 
         swapi_processor = SwapiProcessor(dependencies, input_metadata)
         product = swapi_processor.process()
 
-        mock_swapi_l3_dependencies_class.fetch_dependencies.assert_called_once_with(
-            dependencies
-        )
+        mock_swapi_l3_dependencies_class.fetch_dependencies.assert_called_once_with(dependencies)
 
         swapi_l3a_dependencies.swapi_response.warm_cache.assert_called_once()
 
@@ -431,9 +411,7 @@ def test_process_l3a_proton(
             ]
         )
 
-        mock_manager.add_instrument_attrs.assert_called_once_with(
-            "swapi", "l3a", descriptor
-        )
+        mock_manager.add_instrument_attrs.assert_called_once_with("swapi", "l3a", descriptor)
 
         self.assertEqual(input_file_names, proton_solar_wind_data.parent_file_names)
         mock_write_cdf.assert_called_once_with(
@@ -468,9 +446,7 @@ def test_process_l3a_alpha(
         outgoing_data_level = "l3a"
         start_date = datetime(2025, 8, 28)
         l3a_descriptor = "alpha-sw"
-        input_version = create_mock_version_map(
-            descriptor=l3a_descriptor, minor_version=123
-        )
+        input_version = create_mock_version_map(descriptor=l3a_descriptor, minor_version=123)
         outgoing_version = "123"
         start_date_as_str = datetime.strftime(start_date, "%Y%m%d")
 
@@ -493,21 +469,21 @@ def test_process_l3a_alpha(
             epoch, energy, coincidence_count_rate, coincidence_count_rate_uncertainty
         )
 
-        runner_result = dict(
-            epoch=np.array([initial_epoch + THIRTY_SECONDS_IN_NANOSECONDS]),
-            alpha_sw_speed=np.array([450.0]),
-            alpha_sw_speed_uncert=np.array([1.0]),
-            alpha_sw_speed_sun=np.array([480.0]),
-            alpha_sw_speed_sun_uncert=np.array([1.4]),
-            alpha_sw_density=np.array([0.15]),
-            alpha_sw_density_uncert=np.array([0.01]),
-            alpha_sw_temperature=np.array([400000.0]),
-            alpha_sw_temperature_uncert=np.array([2000.0]),
-            alpha_sw_velocity_rtn_sun=np.array([[480.0, 5.0, 1.0]]),
-            alpha_sw_velocity_rtn=np.array([[450.0, 5.0, 1.0]]),
-            alpha_sw_velocity_rtn_covariance=np.array([np.eye(3)]),
-            quality_flags=np.array([int(SwapiL3Flags.NONE)]),
-        )
+        runner_result = {
+            "epoch": np.array([initial_epoch + THIRTY_SECONDS_IN_NANOSECONDS]),
+            "alpha_sw_speed": np.array([450.0]),
+            "alpha_sw_speed_uncert": np.array([1.0]),
+            "alpha_sw_speed_sun": np.array([480.0]),
+            "alpha_sw_speed_sun_uncert": np.array([1.4]),
+            "alpha_sw_density": np.array([0.15]),
+            "alpha_sw_density_uncert": np.array([0.01]),
+            "alpha_sw_temperature": np.array([400000.0]),
+            "alpha_sw_temperature_uncert": np.array([2000.0]),
+            "alpha_sw_velocity_rtn_sun": np.array([[480.0, 5.0, 1.0]]),
+            "alpha_sw_velocity_rtn": np.array([[450.0, 5.0, 1.0]]),
+            "alpha_sw_velocity_rtn_covariance": np.array([np.eye(3)]),
+            "quality_flags": np.array([int(SwapiL3Flags.NONE)]),
+        }
         mock_runner = mock_parallel_chunk_runner_class.return_value
         mock_runner.run.return_value = runner_result
 
@@ -523,9 +499,7 @@ def test_process_l3a_alpha(
             f"imap_{instrument}_{PASSBAND_FIT_COEFFICIENTS_DESCRIPTOR}_{dependency_start_date}_{version}.cdf",
         ]
 
-        ancillary_inputs = [
-            AncillaryInput(file_name) for file_name in input_file_names[1:]
-        ]
+        ancillary_inputs = [AncillaryInput(file_name) for file_name in input_file_names[1:]]
         dependencies = ProcessingInputCollection(science_input, *ancillary_inputs)
 
         input_metadata = InputMetadata(
@@ -554,18 +528,14 @@ def test_process_l3a_alpha(
         swapi_l3a_dependencies.data = Mock(energy=energy)
         swapi_l3a_dependencies.mag_data = Mock()
         swapi_l3a_dependencies.mag_is_preliminary = False
-        mock_swapi_l3_dependencies_class.fetch_dependencies.return_value = (
-            swapi_l3a_dependencies
-        )
+        mock_swapi_l3_dependencies_class.fetch_dependencies.return_value = swapi_l3a_dependencies
 
         mock_manager = mock_imap_attribute_manager.return_value
 
         swapi_processor = SwapiProcessor(dependencies, input_metadata)
         product = swapi_processor.process()
 
-        mock_swapi_l3_dependencies_class.fetch_dependencies.assert_called_once_with(
-            dependencies
-        )
+        mock_swapi_l3_dependencies_class.fetch_dependencies.assert_called_once_with(dependencies)
 
         swapi_l3a_dependencies.swapi_response.warm_cache.assert_called_once()
 
@@ -598,9 +568,7 @@ def test_process_l3a_alpha(
                 ),
             ]
         )
-        mock_manager.add_instrument_attrs.assert_called_once_with(
-            "swapi", "l3a", l3a_descriptor
-        )
+        mock_manager.add_instrument_attrs.assert_called_once_with("swapi", "l3a", l3a_descriptor)
 
         self.assertEqual(input_file_names, alpha_solar_wind_data.parent_file_names)
         mock_write_cdf.assert_called_once_with(
@@ -690,9 +658,7 @@ def test_process_l3b(
                 sentinel.alpha_velocity_delta_minus1,
                 sentinel.alpha_velocity_delta_plus1,
             ),
-            DeltaMinusPlus(
-                sentinel.pui_velocity_delta_minus1, sentinel.pui_velocity_delta_plus1
-            ),
+            DeltaMinusPlus(sentinel.pui_velocity_delta_minus1, sentinel.pui_velocity_delta_plus1),
             DeltaMinusPlus(sentinel.energy_delta_minus1, sentinel.energy_delta_plus1),
             DeltaMinusPlus(
                 sentinel.proton_velocity_delta_minus2,
@@ -702,9 +668,7 @@ def test_process_l3b(
                 sentinel.alpha_velocity_delta_minus2,
                 sentinel.alpha_velocity_delta_plus2,
             ),
-            DeltaMinusPlus(
-                sentinel.pui_velocity_delta_minus2, sentinel.pui_velocity_delta_plus2
-            ),
+            DeltaMinusPlus(sentinel.pui_velocity_delta_minus2, sentinel.pui_velocity_delta_plus2),
             DeltaMinusPlus(sentinel.energy_delta_minus2, sentinel.energy_delta_plus2),
         ]
 
@@ -723,8 +687,8 @@ def test_process_l3b(
 
         average_coincident_count_rates = coarse_count_rates
         # σ propagation through Σ/N over n independent sweeps shrinks the per-sweep σ by √n.
-        average_coincident_count_rate_uncertainties = (
-            coarse_count_rate_uncertainties / np.sqrt(n_sweeps)
+        average_coincident_count_rate_uncertainties = coarse_count_rate_uncertainties / np.sqrt(
+            n_sweeps
         )
         energy = coarse_energies
 
@@ -763,9 +727,7 @@ def test_process_l3b(
         swapi_processor = SwapiProcessor(dependencies, input_metadata)
         product = swapi_processor.process()
 
-        mock_swapi_l3b_dependencies_class.fetch_dependencies.assert_called_once_with(
-            dependencies
-        )
+        mock_swapi_l3b_dependencies_class.fetch_dependencies.assert_called_once_with(dependencies)
 
         mock_geometric_factor_calibration_table = mock_swapi_l3b_dependencies_class.fetch_dependencies.return_value.geometric_factor_calibration_table
         mock_efficiency_table = mock_swapi_l3b_dependencies_class.fetch_dependencies.return_value.efficiency_calibration_table
@@ -799,9 +761,7 @@ def test_process_l3b(
 
         np.testing.assert_array_equal(
             nominal_count_rates,
-            nominal_values(
-                mock_calculate_proton_solar_wind_vdf.call_args_list[0].args[1]
-            ),
+            nominal_values(mock_calculate_proton_solar_wind_vdf.call_args_list[0].args[1]),
         )
         np.testing.assert_array_equal(
             std_devs_count_rates,
@@ -821,9 +781,7 @@ def test_process_l3b(
         )
         np.testing.assert_array_equal(
             nominal_count_rates,
-            nominal_values(
-                mock_calculate_alpha_solar_wind_vdf.call_args_list[0].args[1]
-            ),
+            nominal_values(mock_calculate_alpha_solar_wind_vdf.call_args_list[0].args[1]),
         )
         np.testing.assert_array_equal(
             std_devs_count_rates,
@@ -861,37 +819,27 @@ def test_process_l3b(
 
         np.testing.assert_array_equal(
             energy,
-            mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[
-                0
-            ],
+            mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[0],
         )
         np.testing.assert_array_equal(
             nominal_count_rates,
             nominal_values(
-                mock_calculate_combined_solar_wind_differential_flux.call_args_list[
-                    0
-                ].args[1]
+                mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[1]
             ),
         )
         np.testing.assert_array_equal(
             std_devs_count_rates,
             std_devs(
-                mock_calculate_combined_solar_wind_differential_flux.call_args_list[
-                    0
-                ].args[1]
+                mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[1]
             ),
         )
         self.assertEqual(
             mock_efficiency_table.relative_efficiency.return_value,
-            mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[
-                2
-            ],
+            mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[2],
         )
         self.assertEqual(
             mock_geometric_factor_calibration_table,
-            mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[
-                3
-            ],
+            mock_calculate_combined_solar_wind_differential_flux.call_args_list[0].args[3],
         )
         delta_calls = mock_calculate_delta_minus_plus.call_args_list
         self.assertEqual(sentinel.proton_calculated_velocities1, delta_calls[0].args[0])
@@ -939,18 +887,14 @@ def test_process_l3b(
                 sentinel.proton_velocity_delta_minus1,
                 sentinel.proton_velocity_delta_minus2,
             ],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "proton_sw_velocities_delta_minus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["proton_sw_velocities_delta_minus"],
         )
         np.testing.assert_array_equal(
             [
                 sentinel.proton_velocity_delta_plus1,
                 sentinel.proton_velocity_delta_plus2,
             ],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "proton_sw_velocities_delta_plus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["proton_sw_velocities_delta_plus"],
         )
         np.testing.assert_array_equal(
             [
@@ -972,15 +916,11 @@ def test_process_l3b(
                 sentinel.alpha_velocity_delta_minus1,
                 sentinel.alpha_velocity_delta_minus2,
             ],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "alpha_sw_velocities_delta_minus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["alpha_sw_velocities_delta_minus"],
         )
         np.testing.assert_array_equal(
             [sentinel.alpha_velocity_delta_plus1, sentinel.alpha_velocity_delta_plus2],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "alpha_sw_velocities_delta_plus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["alpha_sw_velocities_delta_plus"],
         )
         np.testing.assert_array_equal(
             [
@@ -996,15 +936,11 @@ def test_process_l3b(
         )
         np.testing.assert_array_equal(
             [sentinel.pui_velocity_delta_minus1, sentinel.pui_velocity_delta_minus2],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "pui_sw_velocities_delta_minus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["pui_sw_velocities_delta_minus"],
         )
         np.testing.assert_array_equal(
             [sentinel.pui_velocity_delta_plus1, sentinel.pui_velocity_delta_plus2],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "pui_sw_velocities_delta_plus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["pui_sw_velocities_delta_plus"],
         )
         np.testing.assert_array_equal(
             [
@@ -1020,29 +956,21 @@ def test_process_l3b(
         )
         np.testing.assert_array_equal(
             [sentinel.energy_delta_minus1, sentinel.energy_delta_minus2],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "combined_energy_delta_minus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["combined_energy_delta_minus"],
         )
         np.testing.assert_array_equal(
             [sentinel.energy_delta_plus1, sentinel.energy_delta_plus2],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "combined_energy_delta_plus"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["combined_energy_delta_plus"],
         )
         np.testing.assert_array_equal(
             [
                 sentinel.calculated_diffential_flux1,
                 sentinel.calculated_diffential_flux2,
             ],
-            mock_combined_vdf_data.call_args_list[0].kwargs[
-                "combined_differential_flux"
-            ],
+            mock_combined_vdf_data.call_args_list[0].kwargs["combined_differential_flux"],
         )
 
-        self.assertEqual(
-            input_file_names, mock_combined_vdf_data.return_value.parent_file_names
-        )
+        self.assertEqual(input_file_names, mock_combined_vdf_data.return_value.parent_file_names)
         mock_save_data.assert_called_once_with(mock_combined_vdf_data.return_value)
         self.assertEqual([mock_save_data.return_value], product)
 
@@ -1064,9 +992,7 @@ def test_process_l3a_raises_for_unknown_descriptor(
         swapi_processor = SwapiProcessor(Mock(), input_metadata)
         with self.assertRaises(NotImplementedError) as cm:
             swapi_processor.process()
-        self.assertEqual(
-            ("unknown descriptor", "not-a-real-descriptor"), cm.exception.args
-        )
+        self.assertEqual(("unknown descriptor", "not-a-real-descriptor"), cm.exception.args)
 
     def test_process_l3a_alpha_raises_when_mag_data_missing(self):
         input_metadata = InputMetadata(
@@ -1110,15 +1036,9 @@ def test_adds_converted_velocity_and_covariance(self, mock_convert):
         self.assertEqual(10, epoch)
         np.testing.assert_array_equal([400.0, 1.0, 2.0], velocity)
         np.testing.assert_array_equal(np.eye(3), covariance)
-        np.testing.assert_array_equal(
-            [[-400.0, 29.0, 2.0]], result["proton_sw_velocity_gse"]
-        )
-        np.testing.assert_array_equal(
-            [2 * np.eye(3)], result["proton_sw_velocity_gse_covariance"]
-        )
-        self.assertEqual(
-            int(SwapiL3Flags.PREDICTIVE_EPHEMERIS), result["quality_flags"][0]
-        )
+        np.testing.assert_array_equal([[-400.0, 29.0, 2.0]], result["proton_sw_velocity_gse"])
+        np.testing.assert_array_equal([2 * np.eye(3)], result["proton_sw_velocity_gse_covariance"])
+        self.assertEqual(int(SwapiL3Flags.PREDICTIVE_EPHEMERIS), result["quality_flags"][0])
 
     def test_conversion_failure_gives_fill_and_fit_error(self, mock_convert):
         result = self._result([400.0, 1.0, 2.0])
@@ -1139,9 +1059,7 @@ def test_missing_rtn_velocity_gives_fill_without_new_flag(self, mock_convert):
 
         mock_convert.assert_not_called()
         self._assert_all_fill(result)
-        self.assertEqual(
-            int(SwapiL3Flags.PREDICTIVE_EPHEMERIS), result["quality_flags"][0]
-        )
+        self.assertEqual(int(SwapiL3Flags.PREDICTIVE_EPHEMERIS), result["quality_flags"][0])
 
 
 def create_swapi_l3a_dependencies_with_mocks():
diff --git a/tests/swe/l3/science/test_models.py b/tests/swe/l3/science/test_models.py
index a086ae03..37ddb66b 100644
--- a/tests/swe/l3/science/test_models.py
+++ b/tests/swe/l3/science/test_models.py
@@ -4,104 +4,104 @@
 import numpy as np
 
 from imap_l3_processing.swe.l3.models import (
-    SweL3Data,
-    EPOCH_CDF_VAR_NAME,
-    EPOCH_DELTA_CDF_VAR_NAME,
-    ENERGY_CDF_VAR_NAME,
-    ENERGY_DELTA_PLUS_CDF_VAR_NAME,
-    ENERGY_DELTA_MINUS_CDF_VAR_NAME,
-    PITCH_ANGLE_CDF_VAR_NAME,
-    PITCH_ANGLE_DELTA_CDF_VAR_NAME,
-    PHASE_SPACE_DENSITY_BY_PITCH_ANGLE_CDF_VAR_NAME,
-    PHASE_SPACE_DENSITY_1D_CDF_VAR_NAME,
-    PHASE_SPACE_DENSITY_OUTWARD_CDF_VAR_NAME,
-    PHASE_SPACE_DENSITY_INWARD_CDF_VAR_NAME,
-    SPACECRAFT_POTENTIAL_CDF_VAR_NAME,
-    CORE_HALO_BREAKPOINT_CDF_VAR_NAME,
-    CORE_FIT_NUM_POINTS_CDF_VAR_NAME,
     CHISQ_C_CDF_VAR_NAME,
     CHISQ_H_CDF_VAR_NAME,
     CORE_DENSITY_FIT_CDF_VAR_NAME,
-    HALO_DENSITY_FIT_CDF_VAR_NAME,
+    CORE_DENSITY_INTEGRATED_CDF_VAR_NAME,
+    CORE_FIT_NUM_POINTS_CDF_VAR_NAME,
+    CORE_HALO_BREAKPOINT_CDF_VAR_NAME,
+    CORE_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME,
+    CORE_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME,
+    CORE_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME,
+    CORE_SPEED_FIT_CDF_VAR_NAME,
+    CORE_SPEED_INTEGRATED_CDF_VAR_NAME,
     CORE_T_PARALLEL_FIT_CDF_VAR_NAME,
-    HALO_T_PARALLEL_FIT_CDF_VAR_NAME,
+    CORE_T_PARALLEL_INTEGRATED_CDF_VAR_NAME,
     CORE_T_PERPENDICULAR_FIT_CDF_VAR_NAME,
-    HALO_T_PERPENDICULAR_FIT_CDF_VAR_NAME,
+    CORE_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME,
+    CORE_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME,
+    CORE_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME,
+    CORE_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
     CORE_TEMPERATURE_PHI_RTN_FIT_CDF_VAR_NAME,
-    HALO_TEMPERATURE_PHI_RTN_FIT_CDF_VAR_NAME,
+    CORE_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME,
+    CORE_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
+    CORE_TEMPERATURE_TENSOR_INTEGRATED_CDF_VAR_NAME,
+    CORE_TEMPERATURE_TENSOR_INTEGRATED_LABEL,
     CORE_TEMPERATURE_THETA_RTN_FIT_CDF_VAR_NAME,
-    HALO_TEMPERATURE_THETA_RTN_FIT_CDF_VAR_NAME,
-    CORE_SPEED_FIT_CDF_VAR_NAME,
-    HALO_SPEED_FIT_CDF_VAR_NAME,
+    CORE_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME,
     CORE_VELOCITY_VECTOR_RTN_FIT_CDF_VAR_NAME,
-    HALO_VELOCITY_VECTOR_RTN_FIT_CDF_VAR_NAME,
-    INTENSITY_BY_PITCH_ANGLE_CDF_VAR_NAME,
-    INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME,
-    CORE_DENSITY_INTEGRATED_CDF_VAR_NAME,
-    HALO_DENSITY_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_DENSITY_INTEGRATED_CDF_VAR_NAME,
-    CORE_SPEED_INTEGRATED_CDF_VAR_NAME,
-    HALO_SPEED_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_SPEED_INTEGRATED_CDF_VAR_NAME,
+    CORE_VELOCITY_VECTOR_RTN_FIT_LABEL,
     CORE_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME,
-    HALO_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME,
-    CORE_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME,
-    CORE_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME,
-    CORE_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME,
+    CORE_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL,
+    ENERGY_CDF_VAR_NAME,
+    ENERGY_DELTA_MINUS_CDF_VAR_NAME,
+    ENERGY_DELTA_PLUS_CDF_VAR_NAME,
+    ENERGY_LABEL,
+    EPOCH_CDF_VAR_NAME,
+    EPOCH_DELTA_CDF_VAR_NAME,
+    GYROPHASE_BINS_CDF_VAR_NAME,
+    GYROPHASE_DELTA_CDF_VAR_NAME,
+    GYROPHASE_LABEL,
+    HALO_DENSITY_FIT_CDF_VAR_NAME,
+    HALO_DENSITY_INTEGRATED_CDF_VAR_NAME,
     HALO_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME,
-    HALO_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME,
     HALO_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME,
-    CORE_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME,
-    CORE_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME,
-    HALO_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME,
-    HALO_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME,
-    CORE_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME,
-    CORE_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
+    HALO_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME,
+    HALO_SPEED_FIT_CDF_VAR_NAME,
+    HALO_SPEED_INTEGRATED_CDF_VAR_NAME,
+    HALO_T_PARALLEL_FIT_CDF_VAR_NAME,
+    HALO_T_PARALLEL_INTEGRATED_CDF_VAR_NAME,
+    HALO_T_PERPENDICULAR_FIT_CDF_VAR_NAME,
+    HALO_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME,
+    HALO_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME,
     HALO_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME,
     HALO_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
-    TOTAL_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME,
-    TOTAL_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
-    SweL3MomentData,
-    CORE_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME,
-    CORE_T_PARALLEL_INTEGRATED_CDF_VAR_NAME,
-    HALO_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME,
-    HALO_T_PARALLEL_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_T_PARALLEL_INTEGRATED_CDF_VAR_NAME,
-    CORE_TEMPERATURE_TENSOR_INTEGRATED_CDF_VAR_NAME,
+    HALO_TEMPERATURE_PHI_RTN_FIT_CDF_VAR_NAME,
+    HALO_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME,
+    HALO_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
     HALO_TEMPERATURE_TENSOR_INTEGRATED_CDF_VAR_NAME,
-    TOTAL_TEMPERATURE_TENSOR_INTEGRATED_CDF_VAR_NAME,
-    PHASE_SPACE_DENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME,
-    GYROPHASE_DELTA_CDF_VAR_NAME,
-    GYROPHASE_BINS_CDF_VAR_NAME,
+    HALO_TEMPERATURE_TENSOR_INTEGRATED_LABEL,
+    HALO_TEMPERATURE_THETA_RTN_FIT_CDF_VAR_NAME,
+    HALO_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME,
+    HALO_VELOCITY_VECTOR_RTN_FIT_CDF_VAR_NAME,
+    HALO_VELOCITY_VECTOR_RTN_FIT_LABEL,
+    HALO_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME,
+    HALO_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL,
+    INTENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME,
+    INTENSITY_BY_PITCH_ANGLE_CDF_VAR_NAME,
     INTENSITY_UNCERTAINTY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME,
     INTENSITY_UNCERTAINTY_BY_PITCH_ANGLE_CDF_VAR_NAME,
-    ENERGY_LABEL,
+    PHASE_SPACE_DENSITY_1D_CDF_VAR_NAME,
+    PHASE_SPACE_DENSITY_BY_PITCH_ANGLE_AND_GYROPHASE_CDF_VAR_NAME,
+    PHASE_SPACE_DENSITY_BY_PITCH_ANGLE_CDF_VAR_NAME,
+    PHASE_SPACE_DENSITY_INWARD_CDF_VAR_NAME,
+    PHASE_SPACE_DENSITY_OUTWARD_CDF_VAR_NAME,
+    PITCH_ANGLE_CDF_VAR_NAME,
+    PITCH_ANGLE_DELTA_CDF_VAR_NAME,
     PITCH_ANGLE_LABEL,
-    GYROPHASE_LABEL,
     RTN_LABEL,
-    CORE_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME,
-    HALO_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME,
+    SPACECRAFT_POTENTIAL_CDF_VAR_NAME,
+    SWE_FLAGS_VAR_NAME,
+    TENSOR_ID,
+    TOTAL_DENSITY_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_HEAT_FLUX_MAGNITUDE_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_HEAT_FLUX_PHI_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_HEAT_FLUX_THETA_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_SPEED_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_T_PARALLEL_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_T_PERPENDICULAR_INTEGRATED_CDF_VAR_NAME,
     TOTAL_T_PERPENDICULAR_RATIO_INTEGRATED_CDF_VAR_NAME,
-    CORE_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
-    HALO_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
+    TOTAL_TEMPERATURE_PARALLEL_TO_MAG_CDF_VAR_NAME,
+    TOTAL_TEMPERATURE_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
+    TOTAL_TEMPERATURE_PHI_RTN_INTEGRATED_CDF_VAR_NAME,
     TOTAL_TEMPERATURE_RATIO_PERPENDICULAR_TO_MAG_CDF_VAR_NAME,
-    TENSOR_ID,
-    SWE_FLAGS_VAR_NAME,
-    CORE_VELOCITY_VECTOR_RTN_FIT_LABEL,
-    HALO_VELOCITY_VECTOR_RTN_FIT_LABEL,
-    CORE_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL,
-    HALO_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL,
-    TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL,
-    CORE_TEMPERATURE_TENSOR_INTEGRATED_LABEL,
-    HALO_TEMPERATURE_TENSOR_INTEGRATED_LABEL,
+    TOTAL_TEMPERATURE_TENSOR_INTEGRATED_CDF_VAR_NAME,
     TOTAL_TEMPERATURE_TENSOR_INTEGRATED_LABEL,
+    TOTAL_TEMPERATURE_THETA_RTN_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_CDF_VAR_NAME,
+    TOTAL_VELOCITY_VECTOR_RTN_INTEGRATED_LABEL,
+    SweL3Data,
+    SweL3MomentData,
 )
 from tests.swapi.cdf_model_test_case import CdfModelTestCase
 
@@ -213,9 +213,7 @@ def test_data_to_product_variables(self):
 
         variables = iter(variables)
         # @formatter:off
-        self.assert_variable_attributes(
-            next(variables), sentinel.epoch, EPOCH_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), sentinel.epoch, EPOCH_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), sentinel.epoch_delta, EPOCH_DELTA_CDF_VAR_NAME
         )
@@ -228,9 +226,7 @@ def test_data_to_product_variables(self):
             sentinel.energy_delta_minus,
             ENERGY_DELTA_MINUS_CDF_VAR_NAME,
         )
-        self.assert_variable_attributes(
-            next(variables), pitch_angle, PITCH_ANGLE_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), pitch_angle, PITCH_ANGLE_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), sentinel.pitch_angle_delta, PITCH_ANGLE_DELTA_CDF_VAR_NAME
         )
@@ -300,12 +296,8 @@ def test_data_to_product_variables(self):
             sentinel.core_fit_num_points,
             CORE_FIT_NUM_POINTS_CDF_VAR_NAME,
         )
-        self.assert_variable_attributes(
-            next(variables), sentinel.chisq_c, CHISQ_C_CDF_VAR_NAME
-        )
-        self.assert_variable_attributes(
-            next(variables), sentinel.chisq_h, CHISQ_H_CDF_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), sentinel.chisq_c, CHISQ_C_CDF_VAR_NAME)
+        self.assert_variable_attributes(next(variables), sentinel.chisq_h, CHISQ_H_CDF_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), sentinel.core_density_fit, CORE_DENSITY_FIT_CDF_VAR_NAME
         )
@@ -583,9 +575,7 @@ def test_data_to_product_variables(self):
             sentinel.total_temperature_tensor_integrated,
             TOTAL_TEMPERATURE_TENSOR_INTEGRATED_CDF_VAR_NAME,
         )
-        self.assert_variable_attributes(
-            next(variables), sentinel.swp_flags, SWE_FLAGS_VAR_NAME
-        )
+        self.assert_variable_attributes(next(variables), sentinel.swp_flags, SWE_FLAGS_VAR_NAME)
         self.assert_variable_attributes(
             next(variables), sentinel.raw_1d_psd_rebinned, "raw_1d_psd_rebinned"
         )
@@ -674,12 +664,8 @@ def test_data_to_product_variables(self):
             ],
             TOTAL_TEMPERATURE_TENSOR_INTEGRATED_LABEL,
         )
-        self.assert_variable_attributes(
-            next(variables), sentinel.inst_az_label, "inst_az_label"
-        )
-        self.assert_variable_attributes(
-            next(variables), sentinel.inst_el_label, "inst_el_label"
-        )
+        self.assert_variable_attributes(next(variables), sentinel.inst_az_label, "inst_az_label")
+        self.assert_variable_attributes(next(variables), sentinel.inst_el_label, "inst_el_label")
         self.assert_variable_attributes(next(variables), [1, 2, 3, 4, 5, 6], TENSOR_ID)
 
         self.assertEqual([], list(variables), "unexpected variable found")
diff --git a/tests/swe/l3/science/test_moments_calculation.py b/tests/swe/l3/science/test_moments_calculation.py
index 822743b9..005a5765 100644
--- a/tests/swe/l3/science/test_moments_calculation.py
+++ b/tests/swe/l3/science/test_moments_calculation.py
@@ -1,9 +1,9 @@
 import dataclasses
+import math
 import unittest
 from datetime import datetime
-from unittest.mock import patch, call, sentinel, create_autospec
+from unittest.mock import call, create_autospec, patch, sentinel
 
-import math
 import numpy as np
 import spiceypy
 from spiceypy import SpiceyError
@@ -11,29 +11,28 @@
 from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
 from imap_l3_processing.swe.l3.science import moment_calculations
 from imap_l3_processing.swe.l3.science.moment_calculations import (
-    compute_maxwellian_weight_factors,
-    filter_and_flatten_regress_parameters,
-    regress,
-    calculate_fit_temperature_density_velocity,
-    rotate_temperature,
-    apply_rotation_matrix,
+    MomentFitResults,
     Moments,
-    halotrunc,
+    apply_rotation_matrix,
+    calculate_fit_temperature_density_velocity,
+    calculate_primary_eigenvector,
     compute_density_scale,
+    compute_maxwellian_weight_factors,
     core_fit_moments_retrying_on_failure,
+    filter_and_flatten_regress_parameters,
     halo_fit_moments_retrying_on_failure,
-    scale_halo_density,
+    halotrunc,
+    regress,
+    rotate_rtn_vectors_to_dps,
+    rotate_temperature,
+    rotate_temperature_tensor_to_mag,
     rotate_vector_to_rtn_spherical_coordinates,
-    calculate_primary_eigenvector,
     rotation_matrix_builder,
-    rotate_temperature_tensor_to_mag,
-    MomentFitResults,
-    rotate_rtn_vectors_to_dps,
+    scale_halo_density,
 )
-from tests.test_helpers import create_dataclass_mock
-from tests.test_helpers import get_test_data_path
-from imap_l3_processing.swe.swe_processor import check_temperature_outlier_flag
 from imap_l3_processing.swe.quality_flags import SweL3Flags
+from imap_l3_processing.swe.swe_processor import check_temperature_outlier_flag
+from tests.test_helpers import create_dataclass_mock, get_test_data_path
 
 MODULE = "imap_l3_processing.swe.l3.science.moment_calculations"
 
@@ -54,16 +53,12 @@ def test_halo_fit_moments_retrying_on_failure(
         density_history = np.array([100, 89, 72])
 
         negative_density_value = -1
-        density_greater_than_rolling_average_of_history = (
-            np.average(density_history) * 1.35 + 1
-        )
+        density_greater_than_rolling_average_of_history = np.average(density_history) * 1.35 + 1
 
         valid_density = 13
         moments_1 = create_dataclass_mock(Moments, density=sentinel.density1)
         moments_2 = create_dataclass_mock(Moments, density=sentinel.density2)
-        moments_3_with_valid_density = create_dataclass_mock(
-            Moments, density=sentinel.density3
-        )
+        moments_3_with_valid_density = create_dataclass_mock(Moments, density=sentinel.density3)
         mock_calculate_fit_temp_dens_velocity.side_effect = [
             moments_1,
             moments_2,
@@ -207,14 +202,10 @@ def test_fit_moments_retrying_on_failure(
         density_history = np.array([100, 89, 72])
 
         negative_density_value = -1
-        density_greater_than_rolling_average_of_history = (
-            np.average(density_history) * 1.85 + 1
-        )
+        density_greater_than_rolling_average_of_history = np.average(density_history) * 1.85 + 1
 
         valid_density = 13
-        moments_with_valid_density = create_dataclass_mock(
-            Moments, density=valid_density
-        )
+        moments_with_valid_density = create_dataclass_mock(Moments, density=valid_density)
         mock_calculate_fit_temp_dens_velocity.side_effect = [
             create_dataclass_mock(Moments, density=negative_density_value),
             create_dataclass_mock(
@@ -507,9 +498,7 @@ def test_compute_maxwellian_weight_factors_reproduces_heritage_results(self):
         counts = np.array([[[536.0, 20000, 536.0], [1.2, 3072.0000001359296, 1.2]]])
         acquisition_duration = np.array([[80000.0, 40000.0]])
         count_rates = counts / acquisition_duration[:, :, np.newaxis]
-        weight_factors = compute_maxwellian_weight_factors(
-            count_rates, acquisition_duration
-        )
+        weight_factors = compute_maxwellian_weight_factors(count_rates, acquisition_duration)
 
         first_weight = np.sqrt(21.25 + 536) / 536
         second_weight = np.sqrt(87381.25 + 20000.0) / 20000
@@ -537,9 +526,7 @@ def test_regress_reproduces_heritage_results_given_all_test_data(self):
         weights = np.loadtxt(
             get_test_data_path("swe/fake_weights.csv"), delimiter=",", dtype=np.float64
         )
-        yreg = np.loadtxt(
-            get_test_data_path("swe/fake_yreg.csv"), delimiter=",", dtype=np.float64
-        )
+        yreg = np.loadtxt(get_test_data_path("swe/fake_yreg.csv"), delimiter=",", dtype=np.float64)
 
         regression_values, chisq = regress(velocity_vectors, weights, yreg)
 
@@ -579,9 +566,7 @@ def test_calculate_fit_temperature_density_velocity_is_consistent_with_heritage_
             ],
             dtype=np.float64,
         )
-        moments = calculate_fit_temperature_density_velocity(
-            regress_output_of_full_fake_data
-        )
+        moments = calculate_fit_temperature_density_velocity(regress_output_of_full_fake_data)
 
         self.assertAlmostEqual(1.958299, moments.alpha, places=5)
         self.assertAlmostEqual(1.729684, moments.beta, places=5)
@@ -640,9 +625,7 @@ def test_filter_and_flatten_regress_parameters(self):
             vectors, [[3, 0, 0], [4, 0, 0], [10, 0, 0], [10, 0, 0], [0, 0, 0]]
         )
         np.testing.assert_array_equal(actual_weights, [3, 1e-36, 10, 11, 12])
-        np.testing.assert_array_equal(
-            yreg, [np.log(3), -80.6, np.log(10), np.log(11), np.log(12)]
-        )
+        np.testing.assert_array_equal(yreg, [np.log(3), -80.6, np.log(10), np.log(11), np.log(12)])
 
     def test_rotate_dps_vector_to_rtn(self):
         dsp_vector = np.array([0, 1, 0])
@@ -667,13 +650,9 @@ def test_get_dps_to_rtn_rotation_matrix_returns_pxform_result(
         rotation_matrix = np.array([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
         mock_pxform.return_value = rotation_matrix
 
-        actual_rotation_matrix = moment_calculations.get_dps_to_rtn_rotation_matrix(
-            epoch
-        )
+        actual_rotation_matrix = moment_calculations.get_dps_to_rtn_rotation_matrix(epoch)
         mock_datetime2et.assert_called_once_with(epoch)
-        mock_pxform.assert_called_once_with(
-            "IMAP_DPS", "IMAP_RTN", mock_datetime2et.return_value
-        )
+        mock_pxform.assert_called_once_with("IMAP_DPS", "IMAP_RTN", mock_datetime2et.return_value)
         np.testing.assert_array_equal(actual_rotation_matrix, rotation_matrix)
 
     @patch(f"{MODULE}.spiceypy.pxform")
@@ -690,9 +669,7 @@ def test_get_dps_to_rtn_rotation_matrix_propagates_spice_errors(
             moment_calculations.get_dps_to_rtn_rotation_matrix(epoch)
 
         mock_datetime2et.assert_called_once_with(epoch)
-        mock_pxform.assert_called_once_with(
-            "IMAP_DPS", "IMAP_RTN", mock_datetime2et.return_value
-        )
+        mock_pxform.assert_called_once_with("IMAP_DPS", "IMAP_RTN", mock_datetime2et.return_value)
 
     def test_rotate_temperature(self):
         temperature_alpha = math.pi / 4
@@ -714,9 +691,7 @@ def test_rotate_temperature(self):
                 np.array(
                     [
                         np.asin(expected_rtn_temperature[2]),
-                        np.atan2(
-                            expected_rtn_temperature[1], expected_rtn_temperature[0]
-                        ),
+                        np.atan2(expected_rtn_temperature[1], expected_rtn_temperature[0]),
                     ]
                 ),
             ),
@@ -754,9 +729,7 @@ def test_momscale(self):
                     core_halo_break - spacecraft_potential, speed, temperature
                 )
 
-                self.assertAlmostEqual(
-                    expected_density_scale, dscale, delta=allowable_difference
-                )
+                self.assertAlmostEqual(expected_density_scale, dscale, delta=allowable_difference)
 
     def test_halotrunc(self):
         density = 130
@@ -840,9 +813,7 @@ def test_halotrunc(self):
                     moments, t_parallel=t_parallel, t_perpendicular=t_perpendicular
                 )
 
-                scaled_density = halotrunc(
-                    moments, core_halo_breakpoint, spacecraft_potential
-                )
+                scaled_density = halotrunc(moments, core_halo_breakpoint, spacecraft_potential)
 
                 self.assertAlmostEqual(expected_density, scaled_density, places=3)
 
@@ -860,9 +831,9 @@ def test_integrate(self):
         ).reshape(20, 7, 30)
         phase_space_density_expected_shape = np.moveaxis(phase_space_density, 2, 1)
 
-        energy = np.loadtxt(
-            get_test_data_path("swe/energies.csv"), delimiter=","
-        ).reshape(20, 7, 30)[:, 0, 0]
+        energy = np.loadtxt(get_test_data_path("swe/energies.csv"), delimiter=",").reshape(
+            20, 7, 30
+        )[:, 0, 0]
 
         sintheta = np.array(
             [
@@ -912,9 +883,7 @@ def test_integrate(self):
         np.testing.assert_allclose(
             np.array([-1053.53, 327.55, 1919.34]), integrate_outputs.velocity, rtol=1e-4
         )
-        np.testing.assert_allclose(
-            np.array(-10.7911), integrate_outputs.base_energy, rtol=1e-4
-        )
+        np.testing.assert_allclose(np.array(-10.7911), integrate_outputs.base_energy, rtol=1e-4)
         np.testing.assert_allclose(
             np.array([48.1855, -1.06466, 62.4149, -1.06081, -37.8901, -8.58049]),
             integrate_outputs.temperature,
@@ -940,9 +909,9 @@ def test_integrate_returns_early_when_density_is_negative(self):
         ).reshape(20, 7, 30)
         phase_space_density_expected_shape = np.moveaxis(phase_space_density, 2, 1)
 
-        energy = np.loadtxt(
-            get_test_data_path("swe/energies.csv"), delimiter=","
-        ).reshape(20, 7, 30)[:, 0, 0]
+        energy = np.loadtxt(get_test_data_path("swe/energies.csv"), delimiter=",").reshape(
+            20, 7, 30
+        )[:, 0, 0]
 
         sintheta = np.array(
             [
@@ -995,9 +964,9 @@ def test_integrate_with_nonzero_cdelnv_and_cdelt(self):
         inst_az_data_energy_spin = inst_az_data[:, 0, :]
         phase_space_density_energy_spin_cem = np.moveaxis(phase_space_density, 2, 1)
 
-        energy = np.loadtxt(
-            get_test_data_path("swe/energies.csv"), delimiter=","
-        ).reshape(20, 7, 30)[:, 0, 0]
+        energy = np.loadtxt(get_test_data_path("swe/energies.csv"), delimiter=",").reshape(
+            20, 7, 30
+        )[:, 0, 0]
 
         artificial_all_positive_sintheta = np.array(
             [
@@ -1042,13 +1011,9 @@ def test_integrate_with_nonzero_cdelnv_and_cdelt(self):
             rtol=1e-4,
         )
 
+        np.testing.assert_allclose(np.array(-10.7911), integrate_outputs.base_energy, rtol=1e-4)
         np.testing.assert_allclose(
-            np.array(-10.7911), integrate_outputs.base_energy, rtol=1e-4
-        )
-        np.testing.assert_allclose(
-            np.array(
-                [5.13448e13, 1.0269e14, 1.54034e14, 2.05379e14, 2.56724e14, 3.08069e14]
-            ),
+            np.array([5.13448e13, 1.0269e14, 1.54034e14, 2.05379e14, 2.56724e14, 3.08069e14]),
             integrate_outputs.temperature,
             rtol=2e-4,
         )
@@ -1173,9 +1138,7 @@ def test_scale_core_density(self):
             core_density_output.cdelt,
             rtol=5e-5,
         )
-        np.testing.assert_allclose(
-            5718525.41685336, core_density_output.density, rtol=1e-5
-        )
+        np.testing.assert_allclose(5718525.41685336, core_density_output.density, rtol=1e-5)
         np.testing.assert_allclose(
             np.array(
                 [
@@ -1499,9 +1462,7 @@ def test_scale_halo_density_difference_in_breakpoints_is_greater_than_base_energ
             rtol=1e-5,
         )
         np.testing.assert_allclose(
-            np.array(
-                [-67.071986, 60.433456, -14.211044, 129.49805, 161.93695, 72.622535]
-            ),
+            np.array([-67.071986, 60.433456, -14.211044, 129.49805, 161.93695, 72.622535]),
             scaled_density.temperature,
             rtol=3e-5,
         )
@@ -1874,9 +1835,7 @@ def test_rotate_rtn_vectors_to_dps(
             pred_tracker_3,
         ]
 
-        epochs = np.array(
-            [datetime(2020, 1, 1), datetime(2020, 1, 2), datetime(2020, 1, 3)]
-        )
+        epochs = np.array([datetime(2020, 1, 1), datetime(2020, 1, 2), datetime(2020, 1, 3)])
         rtn_vectors = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
         mock_datetime2et.side_effect = (sentinel.et_1, sentinel.et_2, sentinel.et_3)
 
@@ -1898,9 +1857,7 @@ def test_rotate_rtn_vectors_to_dps(
             mock_pxform, "IMAP_RTN", "IMAP_DPS", sentinel.et_3
         )
 
-        expected_dps_vectors = np.array(
-            [[2, 4, 6], [12, 15, 18], [np.nan, np.nan, np.nan]]
-        )
+        expected_dps_vectors = np.array([[2, 4, 6], [12, 15, 18], [np.nan, np.nan, np.nan]])
 
         np.testing.assert_array_equal(dps_vectors, expected_dps_vectors)
         np.testing.assert_array_equal(used_predict, [False, True, False])
diff --git a/tests/swe/l3/science/test_pitch_calculations.py b/tests/swe/l3/science/test_pitch_calculations.py
index 82597593..32661e5d 100644
--- a/tests/swe/l3/science/test_pitch_calculations.py
+++ b/tests/swe/l3/science/test_pitch_calculations.py
@@ -1,24 +1,23 @@
 import unittest
-from unittest.mock import Mock, patch, call, sentinel
+from unittest.mock import Mock, call, patch, sentinel
 
 import numpy as np
 
 from imap_l3_processing.swe.l3.science.pitch_calculations import (
-    mec_breakpoint_finder,
     average_over_look_directions,
-    calculate_velocity_in_dsp_frame_km_s,
+    calculate_energy_in_ev_from_velocity_in_km_per_second,
     calculate_look_directions,
-    rebin_by_pitch_angle,
+    calculate_velocity_in_dsp_frame_km_s,
     correct_and_rebin,
-    calculate_energy_in_ev_from_velocity_in_km_per_second,
     integrate_distribution_to_get_1d_spectrum,
     integrate_distribution_to_get_inbound_and_outbound_1d_spectrum,
+    mec_breakpoint_finder,
+    rebin_by_pitch_angle,
     rebin_by_pitch_angle_and_gyrophase,
     swe_rebin_intensity_by_pitch_angle_and_gyrophase,
 )
-from tests.test_helpers import build_swe_configuration, NumpyArrayMatcher
-
 from imap_l3_processing.swe.quality_flags import SweL3Flags
+from tests.test_helpers import NumpyArrayMatcher, build_swe_configuration
 
 
 class TestPitchCalculations(unittest.TestCase):
@@ -90,18 +89,14 @@ def test_look_direction(self):
         )
 
         actual_look_direction = calculate_look_directions(inst_el, inst_az)
-        np.testing.assert_array_almost_equal(
-            actual_look_direction, expected_look_direction
-        )
+        np.testing.assert_array_almost_equal(actual_look_direction, expected_look_direction)
 
     def test_compute_velocity(self):
         energy = np.array([1, 2])  # 2 -- energy
         inst_el = np.array([0, 90])
         inst_az = np.array([[0], [90]])  # 2, 1  --  energy, spin sector
 
-        scalar_speeds = (
-            np.sqrt(energy * 1.602176634e-19 * 2 / 9.109_383_7139e-31) / 1000
-        )
+        scalar_speeds = np.sqrt(energy * 1.602176634e-19 * 2 / 9.109_383_7139e-31) / 1000
         expected_velocity = np.array(
             [
                 [  # energy 1
@@ -130,10 +125,7 @@ def test_compute_velocity_and_confirm_energy_calculation(self):
         velocity = calculate_velocity_in_dsp_frame_km_s(energy, inst_el, inst_az)
         scalar_velocity = np.linalg.norm(velocity, axis=-1)
         calculated_energy = (
-            0.5
-            * 9.109_383_7139e-31
-            * np.square(scalar_velocity * 1000)
-            / 1.602176634e-19
+            0.5 * 9.109_383_7139e-31 * np.square(scalar_velocity * 1000) / 1.602176634e-19
         )
 
         np.testing.assert_almost_equal(calculated_energy[0], energy[0])
@@ -406,9 +398,7 @@ def test_calculate_energy(self):
     )
     @patch("imap_l3_processing.swe.l3.science.pitch_calculations.rebin_by_pitch_angle")
     @patch("imap_l3_processing.swe.l3.science.pitch_calculations.calculate_pitch_angle")
-    @patch(
-        "imap_l3_processing.swe.l3.science.pitch_calculations.calculate_velocity_in_sw_frame"
-    )
+    @patch("imap_l3_processing.swe.l3.science.pitch_calculations.calculate_velocity_in_sw_frame")
     def test_correct_and_rebin(
         self,
         mock_calculate_velocity_in_sw_frame,
@@ -469,9 +459,7 @@ def test_correct_and_rebin(
             NumpyArrayMatcher(expected_mag_vectors_with_cem_axis),
         )
 
-        mock_calculate_energy.assert_called_with(
-            mock_calculate_velocity_in_sw_frame.return_value
-        )
+        mock_calculate_energy.assert_called_with(mock_calculate_velocity_in_sw_frame.return_value)
         mock_rebin_by_pitch_angle.assert_called_with(
             flux_data,
             mock_calculate_pitch_angle.return_value,
@@ -521,9 +509,7 @@ def test_integrate_distribution_to_get_1d_spectrum(self):
             5 * bin1_factor + 10 * bin2_factor,
             7 * bin1_factor + 15 * bin2_factor,
         ]
-        np.testing.assert_allclose(
-            actual_integrated_spectrum, expected_integrated_spectrum
-        )
+        np.testing.assert_allclose(actual_integrated_spectrum, expected_integrated_spectrum)
 
     def test_integrate_distribution_to_get_1d_spectrum_ignores_nan_values(self):
         pitch_angle_bins = [30, 90]
@@ -553,9 +539,7 @@ def test_integrate_distribution_to_get_1d_spectrum_ignores_nan_values(self):
             5 * bin1_factor + 10 * bin2_factor,
             15 * bin2_factor,
         ]
-        np.testing.assert_allclose(
-            actual_integrated_spectrum, expected_integrated_spectrum
-        )
+        np.testing.assert_allclose(actual_integrated_spectrum, expected_integrated_spectrum)
 
     def test_integrate_distribution_decides_inbound_and_outbound_based_on_config_energy_index(
         self,
@@ -642,10 +626,8 @@ def test_integrate_distribution_to_get_inbound_and_outbound_ignores_fill(self):
             in_vs_out_energy_index=0,
         )
 
-        in_spectrum, out_spectrum = (
-            integrate_distribution_to_get_inbound_and_outbound_1d_spectrum(
-                psd_by_pitch_angles, configuration
-            )
+        in_spectrum, out_spectrum = integrate_distribution_to_get_inbound_and_outbound_1d_spectrum(
+            psd_by_pitch_angles, configuration
         )
 
         np.testing.assert_allclose(in_spectrum, expected_A_spectrum)
@@ -763,9 +745,7 @@ def test_rebin_swe_intensity(
             actual_intensity_uncertainty_by_pa_and_gyro,
             actual_intensity_uncertainty_by_pa,
         ) = rebinned_data
-        np.testing.assert_equal(
-            actual_rebinned_by_pa_and_gyro, expected_intensity_by_pa_and_gyro
-        )
+        np.testing.assert_equal(actual_rebinned_by_pa_and_gyro, expected_intensity_by_pa_and_gyro)
         np.testing.assert_equal(actual_rebinned_by_pa, expected_intensity_by_pa)
         np.testing.assert_array_almost_equal(
             actual_intensity_uncertainty_by_pa_and_gyro, expected_uncertainty_by_pa_gyro
diff --git a/tests/swe/l3/test_swe_l3_dependencies.py b/tests/swe/l3/test_swe_l3_dependencies.py
index 268276b3..67b5da70 100644
--- a/tests/swe/l3/test_swe_l3_dependencies.py
+++ b/tests/swe/l3/test_swe_l3_dependencies.py
@@ -1,11 +1,11 @@
 import unittest
 from pathlib import Path
-from unittest.mock import patch, Mock, call
+from unittest.mock import Mock, call, patch
 
 from imap_data_access.processing_input import (
-    ScienceInput,
     AncillaryInput,
     ProcessingInputCollection,
+    ScienceInput,
 )
 
 from imap_l3_processing.swe.l3.swe_l3_dependencies import SweL3Dependencies
@@ -46,9 +46,7 @@ def test_from_file_paths(
         self.assertEqual(mock_read_l1b_swe_data.return_value, result.swe_l1b_data)
         self.assertEqual(mock_read_swe_data.return_value, result.swe_l2_data)
         self.assertEqual(mock_read_mag_data.return_value, result.mag_data)
-        self.assertEqual(
-            mock_read_swapi_data.return_value, result.swapi_l3a_proton_data
-        )
+        self.assertEqual(mock_read_swapi_data.return_value, result.swapi_l3a_proton_data)
         self.assertEqual(mock_read_swe_config.return_value, result.configuration)
         self.assertFalse(result.mag_is_preliminary)
 
diff --git a/tests/swe/l3/test_utils.py b/tests/swe/l3/test_utils.py
index 40687faa..5cfb5a10 100644
--- a/tests/swe/l3/test_utils.py
+++ b/tests/swe/l3/test_utils.py
@@ -9,13 +9,13 @@
 from imap_processing.quality_flags import SweL1bFlags
 from spacepy.pycdf import CDF
 
-from imap_l3_processing.swe.l3.models import SweL2Data, SwapiL3aProtonData, SweL1bData
+from imap_l3_processing.swe.l3.models import SwapiL3aProtonData, SweL1bData, SweL2Data
 from imap_l3_processing.swe.l3.utils import (
-    read_swe_config,
+    compute_epoch_delta_in_ns,
+    read_l1b_swe_data,
     read_l2_swe_data,
     read_l3a_swapi_proton_data,
-    read_l1b_swe_data,
-    compute_epoch_delta_in_ns,
+    read_swe_config,
 )
 from tests.spice_test_case import SpiceTestCase
 from tests.test_helpers import get_test_data_path
@@ -115,9 +115,7 @@ def test_read_l2_swe_data(self):
         self.assertTrue(np.all(np.isnan(result.inst_az_spin_sector[1])))
         spiceypy.sct2e(-43, 0.1)
         self.assertEqual(result.phase_space_density.shape, (6, 24, 30, 7))
-        self.assertEqual(
-            result.phase_space_density[3][11][8][4], 3.1664245168848865e-28
-        )
+        self.assertEqual(result.phase_space_density[3][11][8][4], 3.1664245168848865e-28)
         self.assertTrue(np.all(np.isnan(result.phase_space_density[1])))
 
         self.assertEqual(result.acquisition_time.shape, (6, 24, 30))
@@ -132,9 +130,7 @@ def test_read_l2_swe_data(self):
         self.assertTrue(np.all(result.acquisition_duration[1] == 0))
 
         self.assertEqual(result.phase_space_density_rebinned.shape, (6, 24, 30, 7))
-        self.assertEqual(
-            result.phase_space_density_rebinned[3][11][8][4], 1.2744421815220178e-27
-        )
+        self.assertEqual(result.phase_space_density_rebinned[3][11][8][4], 1.2744421815220178e-27)
         self.assertTrue(np.isnan(result.phase_space_density_rebinned[0][0][0][0]))
         self.assertTrue(np.all(np.isnan(result.phase_space_density_rebinned[1])))
 
@@ -177,9 +173,7 @@ def test_read_l3a_swapi_proton_data_with_fill_values(self):
     def test_compute_epoch_delta_in_ns(self):
         acq_duration_microseconds = np.full((4, 24, 30), 80_000)
         settle_duration_microseconds = np.full((4, 4), 10000 / 3)
-        result = compute_epoch_delta_in_ns(
-            acq_duration_microseconds, settle_duration_microseconds
-        )
+        result = compute_epoch_delta_in_ns(acq_duration_microseconds, settle_duration_microseconds)
         expected = np.full(4, 30 * 1e9)
         np.testing.assert_array_equal(expected, result)
 
diff --git a/tests/swe/test_swe_processor.py b/tests/swe/test_swe_processor.py
index 11723396..a8719aac 100644
--- a/tests/swe/test_swe_processor.py
+++ b/tests/swe/test_swe_processor.py
@@ -1,28 +1,32 @@
 import unittest
 from dataclasses import replace
 from datetime import datetime, timedelta, timezone
-from unittest.mock import patch, call, Mock, sentinel, create_autospec
+from unittest.mock import Mock, call, create_autospec, patch, sentinel
 
 import numpy as np
 from imap_data_access.processing_input import (
-    ScienceInput,
-    ProcessingInputCollection,
     AncillaryInput,
+    ProcessingInputCollection,
+    ScienceInput,
 )
 from imap_processing.quality_flags import SweL1bFlags
 from spiceypy import SpiceyError
 
 from imap_l3_processing.data_utils import NearestInterpolator
-from imap_l3_processing.models import MagData, InputMetadata
+from imap_l3_processing.models import InputMetadata, MagData
 from imap_l3_processing.predicted_ephemeris_tracker import PredictedEphemerisTracker
-from imap_l3_processing.swe.l3.models import SweL2Data, SwapiL3aProtonData, SweL1bData
-from imap_l3_processing.swe.l3.models import SweL3MomentData
+from imap_l3_processing.swe.l3.models import (
+    SwapiL3aProtonData,
+    SweL1bData,
+    SweL2Data,
+    SweL3MomentData,
+)
 from imap_l3_processing.swe.l3.science.moment_calculations import (
     IntegrateOutputs,
     MomentFitResults,
+    Moments,
     ScaleDensityOutput,
 )
-from imap_l3_processing.swe.l3.science.moment_calculations import Moments
 from imap_l3_processing.swe.l3.swe_l3_dependencies import SweL3Dependencies
 from imap_l3_processing.swe.quality_flags import SweL3Flags
 from imap_l3_processing.swe.swe_processor import (
@@ -32,11 +36,11 @@
 )
 from tests.test_helpers import (
     NumpyArrayMatcher,
-    build_swe_configuration,
-    create_dataclass_mock,
-    build_moments,
     build_moment_fit_results,
+    build_moments,
+    build_swe_configuration,
     build_swe_moment_data,
+    create_dataclass_mock,
 )
 
 MODULE = "imap_l3_processing.swe.swe_processor"
@@ -64,9 +68,7 @@ def test_process(
 
         mock_spiceypy.ktotal.return_value = 0
 
-        science_inputs = [
-            ScienceInput(file_name) for file_name in input_file_names[0:4]
-        ]
+        science_inputs = [ScienceInput(file_name) for file_name in input_file_names[0:4]]
         config_input = AncillaryInput(input_file_names[4])
         mock_dependencies = ProcessingInputCollection(*science_inputs, config_input)
 
@@ -79,9 +81,7 @@ def test_process(
         self.assertEqual(calculate_products_return.parent_file_names, input_file_names)
 
         mock_fetch_dependencies.assert_called_once_with(mock_dependencies)
-        mock_calculate_products.assert_called_once_with(
-            mock_fetch_dependencies.return_value
-        )
+        mock_calculate_products.assert_called_once_with(mock_fetch_dependencies.return_value)
         mock_save_data.assert_called_once_with(mock_calculate_products.return_value)
         self.assertEqual([mock_save_data.return_value], product)
 
@@ -89,12 +89,8 @@ def test_process(
     @patch("imap_l3_processing.swe.swe_processor.compute_epoch_delta_in_ns")
     @patch("imap_l3_processing.swe.swe_processor.average_over_look_directions")
     @patch("imap_l3_processing.swe.swe_processor.mec_breakpoint_finder")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.SweProcessor.calculate_pitch_angle_products"
-    )
-    @patch(
-        "imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.SweProcessor.calculate_pitch_angle_products")
+    @patch("imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products")
     def test_calculate_products(
         self,
         mock_calculate_moment_products,
@@ -107,16 +103,13 @@ def test_calculate_products(
         mock_compute_epoch_delta_in_ns.return_value = [30e9, 40e9]
         epochs = datetime.now() + np.arange(7) * timedelta(minutes=1)
         swapi_epochs = (
-            datetime.now()
-            - timedelta(seconds=15)
-            + np.arange(2) * timedelta(minutes=0.5)
+            datetime.now() - timedelta(seconds=15) + np.arange(2) * timedelta(minutes=0.5)
         )
         mock_breakpoint_finder.side_effect = [
             (
                 1,
                 2,
-                SweL3Flags.FALLBACK_POTENTIAL_ESTIMATE
-                | SweL3Flags.POTENTIAL_FIT_UNCONVERGED,
+                SweL3Flags.FALLBACK_POTENTIAL_ESTIMATE | SweL3Flags.POTENTIAL_FIT_UNCONVERGED,
             ),
             (3, 4, SweL3Flags.NONE),
             (5, 6, SweL3Flags.NONE),
@@ -218,21 +211,15 @@ def test_calculate_products(
 
         mock_calculate_moment_products.return_value = mock_moment_data
 
-        negative_moment_flags_return = np.array(
-            [SweL3Flags.NONE] * len(epochs), dtype=np.uint16
-        )
+        negative_moment_flags_return = np.array([SweL3Flags.NONE] * len(epochs), dtype=np.uint16)
         negative_moment_flags_return[4] = SweL3Flags.NEGATIVE_MOMENT
         mock_check_and_mask_negative_moments.return_value = negative_moment_flags_return
 
-        calculate_pitch_angle_flags = np.array(
-            [SweL3Flags.NONE] * len(epochs), dtype=np.uint16
-        )
+        calculate_pitch_angle_flags = np.array([SweL3Flags.NONE] * len(epochs), dtype=np.uint16)
         calculate_pitch_angle_flags[0] = SweL3Flags.FALLBACK_SWAPI_SPEED
         calculate_pitch_angle_flags[2] = SweL3Flags.FALLBACK_SWAPI_SPEED
 
-        expected_phase_space_density_by_pitch_angle = np.full(
-            (7, 3, 3), physical_psd_value
-        )
+        expected_phase_space_density_by_pitch_angle = np.full((7, 3, 3), physical_psd_value)
         expected_phase_space_density_by_pitch_angle[1, 0, 0] = unphysical_psd_value
         expected_phase_space_density_by_pitch_angle_and_gyrophase = np.full(
             (7, 3, 3, 3), physical_psd_value
@@ -350,27 +337,13 @@ def test_calculate_products(
 
         mock_breakpoint_finder.assert_has_calls(
             [
-                call(
-                    swe_l2_data.energy, mock_average_over_look_directions.return_value
-                ),
-                call(
-                    swe_l2_data.energy, mock_average_over_look_directions.return_value
-                ),
-                call(
-                    swe_l2_data.energy, mock_average_over_look_directions.return_value
-                ),
-                call(
-                    swe_l2_data.energy, mock_average_over_look_directions.return_value
-                ),
-                call(
-                    swe_l2_data.energy, mock_average_over_look_directions.return_value
-                ),
-                call(
-                    swe_l2_data.energy, mock_average_over_look_directions.return_value
-                ),
-                call(
-                    swe_l2_data.energy, mock_average_over_look_directions.return_value
-                ),
+                call(swe_l2_data.energy, mock_average_over_look_directions.return_value),
+                call(swe_l2_data.energy, mock_average_over_look_directions.return_value),
+                call(swe_l2_data.energy, mock_average_over_look_directions.return_value),
+                call(swe_l2_data.energy, mock_average_over_look_directions.return_value),
+                call(swe_l2_data.energy, mock_average_over_look_directions.return_value),
+                call(swe_l2_data.energy, mock_average_over_look_directions.return_value),
+                call(swe_l2_data.energy, mock_average_over_look_directions.return_value),
             ]
         )
 
@@ -399,18 +372,14 @@ def test_calculate_products(
         self.assertEqual(swe_config, mock_calculate_moment_products.call_args[0][6])
 
         mock_calculate_pitch_angle_products.assert_called_once()
-        self.assertEqual(
-            swe_l3_dependency, mock_calculate_pitch_angle_products.call_args[0][0]
-        )
+        self.assertEqual(swe_l3_dependency, mock_calculate_pitch_angle_products.call_args[0][0])
         np.testing.assert_array_equal(
             mock_calculate_pitch_angle_products.call_args[0][1],
             expected_corrected_energy_bins,
         )
 
         # @formatter:off
-        self.assertEqual(
-            swe_l3_data.input_metadata, replace(input_metadata, descriptor="sci")
-        )
+        self.assertEqual(swe_l3_data.input_metadata, replace(input_metadata, descriptor="sci"))
         # pass through from l2
         np.testing.assert_array_equal(swe_l3_data.epoch, swe_l2_data.epoch)
         np.testing.assert_array_equal(
@@ -429,18 +398,12 @@ def test_calculate_products(
         np.testing.assert_array_equal(
             swe_l3_data.energy_delta_minus, swe_config["energy_delta_minus"]
         )
-        np.testing.assert_array_equal(
-            swe_l3_data.pitch_angle, swe_config["pitch_angle_bins"]
-        )
+        np.testing.assert_array_equal(swe_l3_data.pitch_angle, swe_config["pitch_angle_bins"])
         np.testing.assert_array_equal(
             swe_l3_data.pitch_angle_delta, swe_config["pitch_angle_deltas"]
         )
-        np.testing.assert_array_equal(
-            swe_l3_data.gyrophase_bins, swe_config["gyrophase_bins"]
-        )
-        np.testing.assert_array_equal(
-            swe_l3_data.gyrophase_delta, swe_config["gyrophase_deltas"]
-        )
+        np.testing.assert_array_equal(swe_l3_data.gyrophase_bins, swe_config["gyrophase_bins"])
+        np.testing.assert_array_equal(swe_l3_data.gyrophase_delta, swe_config["gyrophase_deltas"])
         np.testing.assert_array_equal(
             swe_l3_data.intensity_by_pitch_angle_and_gyrophase,
             sentinel.intensity_by_pitch_angle_and_gyrophase,
@@ -470,9 +433,7 @@ def test_calculate_products(
             swe_l3_data.phase_space_density_by_pitch_angle,
             expected_phase_space_density_by_pitch_angle,
         )
-        np.testing.assert_array_equal(
-            swe_l3_data.phase_space_density_1d, expected_energy_spectrum
-        )
+        np.testing.assert_array_equal(swe_l3_data.phase_space_density_1d, expected_energy_spectrum)
         np.testing.assert_array_equal(
             swe_l3_data.phase_space_density_inward, expected_energy_spectrum_inbound
         )
@@ -491,23 +452,15 @@ def test_calculate_products(
 
         expected_psd_by_phi = np.full((7, 3, 5), physical_psd_value)
         expected_psd_by_phi[6, 0, 0] = expected_phi_avg_at_unphysical_cell
-        np.testing.assert_allclose(
-            swe_l3_data.raw_psd_by_phi_rebinned, expected_psd_by_phi
-        )
+        np.testing.assert_allclose(swe_l3_data.raw_psd_by_phi_rebinned, expected_psd_by_phi)
 
         expected_1d_psd = np.full((7, 3), physical_psd_value)
-        expected_1d_psd[6, 0] = (
-            expected_phi_avg_at_unphysical_cell + 4 * physical_psd_value
-        ) / 5
+        expected_1d_psd[6, 0] = (expected_phi_avg_at_unphysical_cell + 4 * physical_psd_value) / 5
         np.testing.assert_allclose(swe_l3_data.raw_1d_psd_rebinned, expected_1d_psd)
 
         expected_psd_by_theta = np.full((7, 3, 7), physical_psd_value)
-        expected_psd_by_theta[6, 0, 0] = (
-            unphysical_psd_value + 4 * physical_psd_value
-        ) / 5
-        np.testing.assert_allclose(
-            swe_l3_data.raw_psd_by_theta_rebinned, expected_psd_by_theta
-        )
+        expected_psd_by_theta[6, 0, 0] = (unphysical_psd_value + 4 * physical_psd_value) / 5
+        np.testing.assert_allclose(swe_l3_data.raw_psd_by_theta_rebinned, expected_psd_by_theta)
 
         expected_quality_flags = np.array(
             [
@@ -539,21 +492,15 @@ def test_calculate_products(
         np.testing.assert_array_equal(swe_l3_data.swe_flags, expected_quality_flags)
 
         mock_check_and_mask_negative_moments.assert_called_once()
-        self.assertIs(
-            mock_moment_data, mock_check_and_mask_negative_moments.call_args[0][0]
-        )
+        self.assertIs(mock_moment_data, mock_check_and_mask_negative_moments.call_args[0][0])
 
     @patch("imap_l3_processing.swe.swe_processor.check_temperature_outlier_flag")
     @patch("imap_l3_processing.swe.swe_processor.check_and_mask_negative_moments")
     @patch("imap_l3_processing.swe.swe_processor.compute_epoch_delta_in_ns")
     @patch("imap_l3_processing.swe.swe_processor.average_over_look_directions")
     @patch("imap_l3_processing.swe.swe_processor.mec_breakpoint_finder")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.SweProcessor.calculate_pitch_angle_products"
-    )
-    @patch(
-        "imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.SweProcessor.calculate_pitch_angle_products")
+    @patch("imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products")
     def test_negative_moment_mask_runs_before_temperature_outlier_checks(
         self,
         mock_calculate_moment_products,
@@ -604,12 +551,8 @@ def test_negative_moment_mask_runs_before_temperature_outlier_checks(
 
         moment_data = build_swe_moment_data(num_epochs)
         mock_calculate_moment_products.return_value = moment_data
-        mock_check_and_mask_negative_moments.return_value = np.zeros(
-            num_epochs, dtype=np.uint16
-        )
-        mock_check_temperature_outlier_flag.return_value = np.zeros(
-            num_epochs, dtype=np.uint16
-        )
+        mock_check_and_mask_negative_moments.return_value = np.zeros(num_epochs, dtype=np.uint16)
+        mock_check_temperature_outlier_flag.return_value = np.zeros(num_epochs, dtype=np.uint16)
         mock_calculate_pitch_angle_products.return_value = (
             np.zeros((num_epochs, 3, 3)),
             np.zeros((num_epochs, 3, 3, 3)),
@@ -645,17 +588,13 @@ def test_negative_moment_mask_runs_before_temperature_outlier_checks(
         self.assertEqual("mask", method_call_order[0])
         self.assertEqual(["outlier"] * 8, method_call_order[1:])
 
-    @patch(
-        "imap_l3_processing.swe.swe_processor.swe_rebin_intensity_by_pitch_angle_and_gyrophase"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.swe_rebin_intensity_by_pitch_angle_and_gyrophase")
     @patch("imap_l3_processing.swe.swe_processor.calculate_velocity_in_dsp_frame_km_s")
     @patch("imap_l3_processing.swe.swe_processor.average_over_look_directions")
     @patch("imap_l3_processing.swe.swe_processor.mec_breakpoint_finder")
     @patch("imap_l3_processing.swe.swe_processor.rotate_rtn_vectors_to_dps")
     @patch("imap_l3_processing.swe.swe_processor.correct_and_rebin")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.integrate_distribution_to_get_1d_spectrum"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.integrate_distribution_to_get_1d_spectrum")
     @patch(
         "imap_l3_processing.swe.swe_processor.integrate_distribution_to_get_inbound_and_outbound_1d_spectrum"
     )
@@ -674,21 +613,15 @@ def test_calculate_pitch_angle_and_gyrophase_products(
     ):
         epochs = np.arange(3) * timedelta(minutes=1) + datetime.now()
         mag_epochs = (
-            np.arange(10) * timedelta(minutes=0.5)
-            + datetime.now()
-            - timedelta(seconds=15)
+            np.arange(10) * timedelta(minutes=0.5) + datetime.now() - timedelta(seconds=15)
         )
         swapi_epochs = (
-            np.arange(10) * timedelta(minutes=0.5)
-            + datetime.now()
-            - timedelta(seconds=15)
+            np.arange(10) * timedelta(minutes=0.5) + datetime.now() - timedelta(seconds=15)
         )
         spacecraft_potential = np.array([12, 16, 19])
         energies = np.array([2, 4, 6])
 
-        corrected_energy_bins = energies.reshape(1, -1) - spacecraft_potential.reshape(
-            -1, 1
-        )
+        corrected_energy_bins = energies.reshape(1, -1) - spacecraft_potential.reshape(-1, 1)
 
         pitch_angle_bins = [0, 90, 180]
         gyrophase_bins = [0, 360]
@@ -735,9 +668,7 @@ def test_calculate_pitch_angle_and_gyrophase_products(
             sentinel.solar_wind_uses_pred_ephem_flags,
         )
         counts = (
-            swe_l1b_data.count_rates
-            * swe_l2_data.acquisition_duration[:, :, np.newaxis]
-            / 1e6
+            swe_l1b_data.count_rates * swe_l2_data.acquisition_duration[:, :, np.newaxis] / 1e6
         )
         mock_average_over_look_directions.return_value = np.array([5, 10, 15])
         closest_mag_data = np.arange(9).reshape(3, 3)
@@ -770,9 +701,7 @@ def test_calculate_pitch_angle_and_gyrophase_products(
             i
             + np.arange(
                 len(swe_l2_data.energy) * len(pitch_angle_bins) * len(gyrophase_bins)
-            ).reshape(
-                len(swe_l2_data.energy), len(pitch_angle_bins), len(gyrophase_bins)
-            )
+            ).reshape(len(swe_l2_data.energy), len(pitch_angle_bins), len(gyrophase_bins))
             for i in range(len(epochs))
         ]
 
@@ -867,18 +796,14 @@ def test_calculate_pitch_angle_and_gyrophase_products(
             actual_uncertainty_by_pa_and_gyro,
             actual_uncertainty_by_pa,
             actual_swe_flags,
-        ) = swe_processor.calculate_pitch_angle_products(
-            swel3_dependency, corrected_energy_bins
-        )
+        ) = swe_processor.calculate_pitch_angle_products(swel3_dependency, corrected_energy_bins)
 
         self.assertEqual(3, mock_correct_and_rebin.call_count)
         self.assertEqual(3, mock_integrate_distribution_to_get_1d_spectrum.call_count)
         mock_rotate_rtn_vectors_to_dps.assert_called_once()
         rotate_args = mock_rotate_rtn_vectors_to_dps.call_args[0]
         np.testing.assert_array_equal(rotate_args[0], swapi_epochs)
-        np.testing.assert_array_equal(
-            rotate_args[1], swapi_l3a_proton_data.proton_sw_velocity_rtn
-        )
+        np.testing.assert_array_equal(rotate_args[1], swapi_l3a_proton_data.proton_sw_velocity_rtn)
         expected_dps_vectors_after_speed_fallback = rotated_dps_vectors.copy()
         expected_dps_vectors_after_speed_fallback[3] = [0.0, 0.0, -400.0]
         expected_dps_vectors_after_speed_fallback[4] = [0.0, 0.0, -400.0]
@@ -892,9 +817,7 @@ def test_calculate_pitch_angle_and_gyrophase_products(
                 ),
                 call(
                     from_epoch=swapi_epochs,
-                    from_data=NumpyArrayMatcher(
-                        expected_dps_vectors_after_speed_fallback
-                    ),
+                    from_data=NumpyArrayMatcher(expected_dps_vectors_after_speed_fallback),
                     to_epoch=epochs,
                     maximum_distance=np.timedelta64(5, "m"),
                 ),
@@ -941,15 +864,9 @@ def test_calculate_pitch_angle_and_gyrophase_products(
             rebinned_by_pitch_and_gyrophase_list,
         )
         np.testing.assert_array_equal(actual_energy_spectrum, integrated_spectrum)
-        np.testing.assert_array_equal(
-            actual_energy_spectrum_inbound, expected_inbound_spectrum
-        )
-        np.testing.assert_array_equal(
-            actual_energy_spectrum_outbound, expected_outbound_spectrum
-        )
-        np.testing.assert_array_equal(
-            actual_energy_spectrum_outbound, expected_outbound_spectrum
-        )
+        np.testing.assert_array_equal(actual_energy_spectrum_inbound, expected_inbound_spectrum)
+        np.testing.assert_array_equal(actual_energy_spectrum_outbound, expected_outbound_spectrum)
+        np.testing.assert_array_equal(actual_energy_spectrum_outbound, expected_outbound_spectrum)
         np.testing.assert_array_equal(
             actual_intensity_by_pa_and_gyro, expected_intensity_by_pa_and_gyro
         )
@@ -957,9 +874,7 @@ def test_calculate_pitch_angle_and_gyrophase_products(
         np.testing.assert_array_equal(
             actual_uncertainty_by_pa_and_gyro, expected_uncertainty_by_pa_and_gyro
         )
-        np.testing.assert_array_equal(
-            actual_uncertainty_by_pa, expected_uncertainty_by_pa
-        )
+        np.testing.assert_array_equal(actual_uncertainty_by_pa, expected_uncertainty_by_pa)
         np.testing.assert_array_equal(actual_swe_flags, expected_flags)
 
         def call_with_array_matchers(*args):
@@ -1010,9 +925,7 @@ def call_with_array_matchers(*args):
                 swe_config,
             ),
         ]
-        self.assertEqual(
-            correct_and_rebin_expected_calls, correct_and_rebin_actual_calls
-        )
+        self.assertEqual(correct_and_rebin_expected_calls, correct_and_rebin_actual_calls)
 
         mock_rebin_intensity_expected_calls = [
             call_with_array_matchers(
@@ -1057,9 +970,7 @@ def call_with_array_matchers(*args):
         )
 
     @patch("imap_l3_processing.swe.swe_processor.rotate_rtn_vectors_to_dps")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products")
     def test_calculate_pitch_angle_products_makes_nan_if_no_mag_close_enough(
         self, mock_calculate_moments, mock_rotate_rtn_vectors_to_dps
     ):
@@ -1168,14 +1079,10 @@ def test_calculate_pitch_angle_products_makes_nan_if_no_mag_close_enough(
         swel3_dependency = SweL3Dependencies(
             swe_l2_data, swe_l1b_data, mag_l1d_data, swapi_l3a_proton_data, swe_config
         )
-        swe_processor = SweProcessor(
-            ProcessingInputCollection(), input_metadata=input_metadata
-        )
+        swe_processor = SweProcessor(ProcessingInputCollection(), input_metadata=input_metadata)
         swe_l3_data = swe_processor.calculate_products(swel3_dependency)
 
-        self.assertEqual(
-            replace(input_metadata, descriptor="sci"), swe_l3_data.input_metadata
-        )
+        self.assertEqual(replace(input_metadata, descriptor="sci"), swe_l3_data.input_metadata)
         self.assertEqual(
             swe_l3_data.pitch_angle, swel3_dependency.configuration["pitch_angle_bins"]
         )
@@ -1183,9 +1090,7 @@ def test_calculate_pitch_angle_products_makes_nan_if_no_mag_close_enough(
             swe_l3_data.pitch_angle_delta,
             swel3_dependency.configuration["pitch_angle_deltas"],
         )
-        self.assertEqual(
-            swe_l3_data.energy, swel3_dependency.configuration["energy_bins"]
-        )
+        self.assertEqual(swe_l3_data.energy, swel3_dependency.configuration["energy_bins"])
         self.assertEqual(
             swe_l3_data.energy_delta_plus,
             swel3_dependency.configuration["energy_delta_plus"],
@@ -1235,17 +1140,13 @@ def test_calculate_pitch_angle_products_makes_nan_if_no_mag_close_enough(
         )
 
     @patch("imap_l3_processing.swe.swe_processor.rotate_rtn_vectors_to_dps")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.SweProcessor.calculate_moment_products")
     def test_calculate_pitch_angle_products_without_mocks(
         self, mock_calculate_moments, mock_rotate_rtn_vectors_to_dps
     ):
         epochs = np.array([datetime(2025, 3, 6)])
         mag_start_time = datetime(2025, 3, 6, 0, 1, 0)
-        mag_epochs = np.array(
-            [mag_start_time + i * timedelta(seconds=1) for i in range(10)]
-        )
+        mag_epochs = np.array([mag_start_time + i * timedelta(seconds=1) for i in range(10)])
         swapi_epochs = np.array([datetime(2025, 3, 6), datetime(2025, 3, 10)])
         swp_flags = np.zeros(2)
         mock_calculate_moments.return_value = build_swe_moment_data(len(epochs))
@@ -1340,14 +1241,10 @@ def test_calculate_pitch_angle_products_without_mocks(
         swel3_dependency = SweL3Dependencies(
             swe_l2_data, swe_l1b_data, mag_l1d_data, swapi_l3a_proton_data, swe_config
         )
-        swe_processor = SweProcessor(
-            ProcessingInputCollection(), input_metadata=input_metadata
-        )
+        swe_processor = SweProcessor(ProcessingInputCollection(), input_metadata=input_metadata)
         swe_l3_data = swe_processor.calculate_products(swel3_dependency)
 
-        self.assertEqual(
-            replace(input_metadata, descriptor="sci"), swe_l3_data.input_metadata
-        )
+        self.assertEqual(replace(input_metadata, descriptor="sci"), swe_l3_data.input_metadata)
         self.assertEqual(
             swe_l3_data.pitch_angle, swel3_dependency.configuration["pitch_angle_bins"]
         )
@@ -1355,9 +1252,7 @@ def test_calculate_pitch_angle_products_without_mocks(
             swe_l3_data.pitch_angle_delta,
             swel3_dependency.configuration["pitch_angle_deltas"],
         )
-        self.assertEqual(
-            swe_l3_data.energy, swel3_dependency.configuration["energy_bins"]
-        )
+        self.assertEqual(swe_l3_data.energy, swel3_dependency.configuration["energy_bins"])
         self.assertEqual(
             swe_l3_data.energy_delta_plus,
             swel3_dependency.configuration["energy_delta_plus"],
@@ -1398,9 +1293,7 @@ def test_calculate_pitch_angle_products_without_mocks(
             swe_l3_data.phase_space_density_outward,
             np.array([[253.074453, 305.115485, 379.073531]]),
         )
-        self.assertEqual(
-            (1, 9, 3, 3), swe_l3_data.intensity_by_pitch_angle_and_gyrophase.shape
-        )
+        self.assertEqual((1, 9, 3, 3), swe_l3_data.intensity_by_pitch_angle_and_gyrophase.shape)
         self.assertEqual((1, 9, 3), swe_l3_data.intensity_by_pitch_angle.shape)
         np.testing.assert_allclose(
             swe_l3_data.intensity_by_pitch_angle[0, 1, 1:3], np.array([49.5, 53.0])
@@ -1416,9 +1309,7 @@ def test_calculate_pitch_angle_products_without_mocks(
             atol=1e-6,
         )
         np.testing.assert_allclose(
-            swe_l3_data.intensity_uncertainty_by_pitch_angle_and_gyrophase[
-                0, 0, 1:3, 2
-            ],
+            swe_l3_data.intensity_uncertainty_by_pitch_angle_and_gyrophase[0, 0, 1:3, 2],
             np.array([0.000717, 0.000762]),
             atol=1e-6,
         )
@@ -1436,9 +1327,7 @@ def test_calculate_pitch_angle_products_without_mocks(
     @patch(f"{MODULE}.get_dps_to_rtn_rotation_matrix")
     @patch("imap_l3_processing.swe.swe_processor.rotate_temperature_tensor_to_mag")
     @patch("imap_l3_processing.swe.swe_processor.calculate_primary_eigenvector")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.rotate_vector_to_rtn_spherical_coordinates"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.rotate_vector_to_rtn_spherical_coordinates")
     @patch("imap_l3_processing.swe.swe_processor.scale_halo_density")
     @patch("imap_l3_processing.swe.swe_processor.scale_core_density")
     @patch("imap_l3_processing.swe.swe_processor.integrate")
@@ -1508,9 +1397,9 @@ def test_calculate_moment_products(
         spacecraft_potential = np.array([12, 14, 16])
         core_halo_breakpoint = np.array([96, 54, 103])
 
-        corrected_energy_bins = swe_l2_data.energy.reshape(
-            1, -1
-        ) - spacecraft_potential.reshape(-1, 1)
+        corrected_energy_bins = swe_l2_data.energy.reshape(1, -1) - spacecraft_potential.reshape(
+            -1, 1
+        )
 
         velocity_in_dsp_frame_km_s = [
             np.full(shape=(24, 30, 7, 3), fill_value=1),
@@ -1518,9 +1407,7 @@ def test_calculate_moment_products(
             np.full(shape=(24, 30, 7, 3), fill_value=3),
         ]
 
-        mock_calculate_velocity_in_dsp_frame_km_s.side_effect = (
-            velocity_in_dsp_frame_km_s
-        )
+        mock_calculate_velocity_in_dsp_frame_km_s.side_effect = velocity_in_dsp_frame_km_s
 
         maxwellian_weight_factors = [
             np.full(shape=(24, 30, 7), fill_value=1),
@@ -1661,9 +1548,7 @@ def test_calculate_moment_products(
         mock_scale_core_density.side_effect = [scale_core_density_output]
 
         scaled_halo_velocity = [2000, 1800, 1700]
-        scaled_halo_temperature = np.array(
-            [180000, 190000, 200000, 201000, 202000, 203000]
-        )
+        scaled_halo_temperature = np.array([180000, 190000, 200000, 201000, 202000, 203000])
         scale_halo_density_output = ScaleDensityOutput(
             density=500,
             velocity=scaled_halo_velocity,
@@ -1730,41 +1615,23 @@ def test_calculate_moment_products(
             config,
         )
 
-        calculate_velocity_call_1 = (
-            mock_calculate_velocity_in_dsp_frame_km_s.mock_calls[0]
-        )
-        np.testing.assert_array_equal(
-            corrected_energy_bins[0], calculate_velocity_call_1.args[0]
-        )
-        np.testing.assert_array_equal(
-            swe_l2_data.inst_el, calculate_velocity_call_1.args[1]
-        )
+        calculate_velocity_call_1 = mock_calculate_velocity_in_dsp_frame_km_s.mock_calls[0]
+        np.testing.assert_array_equal(corrected_energy_bins[0], calculate_velocity_call_1.args[0])
+        np.testing.assert_array_equal(swe_l2_data.inst_el, calculate_velocity_call_1.args[1])
         np.testing.assert_array_equal(
             swe_l2_data.inst_az_spin_sector[0], calculate_velocity_call_1.args[2]
         )
 
-        calculate_velocity_call_2 = (
-            mock_calculate_velocity_in_dsp_frame_km_s.mock_calls[1]
-        )
-        np.testing.assert_array_equal(
-            corrected_energy_bins[1], calculate_velocity_call_2.args[0]
-        )
-        np.testing.assert_array_equal(
-            swe_l2_data.inst_el, calculate_velocity_call_2.args[1]
-        )
+        calculate_velocity_call_2 = mock_calculate_velocity_in_dsp_frame_km_s.mock_calls[1]
+        np.testing.assert_array_equal(corrected_energy_bins[1], calculate_velocity_call_2.args[0])
+        np.testing.assert_array_equal(swe_l2_data.inst_el, calculate_velocity_call_2.args[1])
         np.testing.assert_array_equal(
             swe_l2_data.inst_az_spin_sector[1], calculate_velocity_call_2.args[2]
         )
 
-        calculate_velocity_call_3 = (
-            mock_calculate_velocity_in_dsp_frame_km_s.mock_calls[2]
-        )
-        np.testing.assert_array_equal(
-            corrected_energy_bins[2], calculate_velocity_call_3.args[0]
-        )
-        np.testing.assert_array_equal(
-            swe_l2_data.inst_el, calculate_velocity_call_3.args[1]
-        )
+        calculate_velocity_call_3 = mock_calculate_velocity_in_dsp_frame_km_s.mock_calls[2]
+        np.testing.assert_array_equal(corrected_energy_bins[2], calculate_velocity_call_3.args[0])
+        np.testing.assert_array_equal(swe_l2_data.inst_el, calculate_velocity_call_3.args[1])
         np.testing.assert_array_equal(
             swe_l2_data.inst_az_spin_sector[2], calculate_velocity_call_3.args[2]
         )
@@ -1781,12 +1648,8 @@ def test_calculate_moment_products(
         self.assertEqual(3, mock_core_fit_moments_retrying_on_failure.call_count)
         self.assertEqual(3, mock_halo_fit_moments_retrying_on_failure.call_count)
 
-        core_fit_moments_call_1 = mock_core_fit_moments_retrying_on_failure.mock_calls[
-            0
-        ]
-        np.testing.assert_array_equal(
-            core_fit_moments_call_1.args[0], corrected_energy_bins[0]
-        )
+        core_fit_moments_call_1 = mock_core_fit_moments_retrying_on_failure.mock_calls[0]
+        np.testing.assert_array_equal(core_fit_moments_call_1.args[0], corrected_energy_bins[0])
         np.testing.assert_array_equal(
             velocity_in_dsp_frame_km_s[0] * 100000, core_fit_moments_call_1.args[1]
         )
@@ -1800,12 +1663,8 @@ def test_calculate_moment_products(
         self.assertEqual(7, core_fit_moments_call_1.args[5])
         np.testing.assert_array_equal(core_fit_moments_call_1.args[6], [100, 100, 100])
 
-        halo_fit_moments_call_1 = mock_halo_fit_moments_retrying_on_failure.mock_calls[
-            0
-        ]
-        np.testing.assert_array_equal(
-            corrected_energy_bins[0], halo_fit_moments_call_1.args[0]
-        )
+        halo_fit_moments_call_1 = mock_halo_fit_moments_retrying_on_failure.mock_calls[0]
+        np.testing.assert_array_equal(corrected_energy_bins[0], halo_fit_moments_call_1.args[0])
         np.testing.assert_array_equal(
             velocity_in_dsp_frame_km_s[0] * 100000, halo_fit_moments_call_1.args[1]
         )
@@ -1822,18 +1681,14 @@ def test_calculate_moment_products(
         self.assertEqual(core_halo_breakpoint[0], halo_fit_moments_call_1.args[8])
 
         core_fit_moments_2 = mock_core_fit_moments_retrying_on_failure.mock_calls[1]
-        np.testing.assert_array_equal(
-            corrected_energy_bins[1], core_fit_moments_2.args[0]
-        )
+        np.testing.assert_array_equal(corrected_energy_bins[1], core_fit_moments_2.args[0])
         np.testing.assert_array_equal(
             velocity_in_dsp_frame_km_s[1] * 100000, core_fit_moments_2.args[1]
         )
         np.testing.assert_array_equal(
             swe_l2_data.phase_space_density[1], core_fit_moments_2.args[2]
         )
-        np.testing.assert_array_equal(
-            maxwellian_weight_factors[1], core_fit_moments_2.args[3]
-        )
+        np.testing.assert_array_equal(maxwellian_weight_factors[1], core_fit_moments_2.args[3])
         self.assertEqual(4, core_fit_moments_2.args[4])
         self.assertEqual(6, core_fit_moments_2.args[5])
         np.testing.assert_array_equal(
@@ -1841,39 +1696,29 @@ def test_calculate_moment_products(
         )
 
         halo_fit_moments_2 = mock_halo_fit_moments_retrying_on_failure.mock_calls[1]
-        np.testing.assert_array_equal(
-            corrected_energy_bins[1], halo_fit_moments_2.args[0]
-        )
+        np.testing.assert_array_equal(corrected_energy_bins[1], halo_fit_moments_2.args[0])
         np.testing.assert_array_equal(
             velocity_in_dsp_frame_km_s[1] * 100000, halo_fit_moments_2.args[1]
         )
         np.testing.assert_array_equal(
             swe_l2_data.phase_space_density[1], halo_fit_moments_2.args[2]
         )
-        np.testing.assert_array_equal(
-            maxwellian_weight_factors[1], halo_fit_moments_2.args[3]
-        )
+        np.testing.assert_array_equal(maxwellian_weight_factors[1], halo_fit_moments_2.args[3])
         self.assertEqual(5, halo_fit_moments_2.args[4])
         self.assertEqual(10, halo_fit_moments_2.args[5])
-        np.testing.assert_array_equal(
-            halo_fit_moments_2.args[6], [25, 25, halo_moments1.density]
-        )
+        np.testing.assert_array_equal(halo_fit_moments_2.args[6], [25, 25, halo_moments1.density])
         self.assertEqual(spacecraft_potential[1], halo_fit_moments_2.args[7])
         self.assertEqual(core_halo_breakpoint[1], halo_fit_moments_2.args[8])
 
         core_fit_moments_3 = mock_core_fit_moments_retrying_on_failure.mock_calls[2]
-        np.testing.assert_array_equal(
-            corrected_energy_bins[2], core_fit_moments_3.args[0]
-        )
+        np.testing.assert_array_equal(corrected_energy_bins[2], core_fit_moments_3.args[0])
         np.testing.assert_array_equal(
             velocity_in_dsp_frame_km_s[2] * 100000, core_fit_moments_3.args[1]
         )
         np.testing.assert_array_equal(
             swe_l2_data.phase_space_density[2], core_fit_moments_3.args[2]
         )
-        np.testing.assert_array_equal(
-            maxwellian_weight_factors[2], core_fit_moments_3.args[3]
-        )
+        np.testing.assert_array_equal(maxwellian_weight_factors[2], core_fit_moments_3.args[3])
         self.assertEqual(5, core_fit_moments_3.args[4])
         self.assertEqual(9, core_fit_moments_3.args[5])
         np.testing.assert_array_equal(
@@ -1882,18 +1727,14 @@ def test_calculate_moment_products(
         )
 
         halo_fit_moments_3 = mock_halo_fit_moments_retrying_on_failure.mock_calls[2]
-        np.testing.assert_array_equal(
-            corrected_energy_bins[2], halo_fit_moments_3.args[0]
-        )
+        np.testing.assert_array_equal(corrected_energy_bins[2], halo_fit_moments_3.args[0])
         np.testing.assert_array_equal(
             velocity_in_dsp_frame_km_s[2] * 100000, halo_fit_moments_3.args[1]
         )
         np.testing.assert_array_equal(
             swe_l2_data.phase_space_density[2], halo_fit_moments_3.args[2]
         )
-        np.testing.assert_array_equal(
-            maxwellian_weight_factors[2], halo_fit_moments_3.args[3]
-        )
+        np.testing.assert_array_equal(maxwellian_weight_factors[2], halo_fit_moments_3.args[3])
         self.assertEqual(8, halo_fit_moments_3.args[4])
         self.assertEqual(11, halo_fit_moments_3.args[5])
         np.testing.assert_array_equal(
@@ -2397,9 +2238,7 @@ def call_with_array_matchers(*args):
         # @formatter:on
 
     @patch(f"{MODULE}.get_dps_to_rtn_rotation_matrix")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.rotate_vector_to_rtn_spherical_coordinates"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.rotate_vector_to_rtn_spherical_coordinates")
     @patch("imap_l3_processing.swe.swe_processor.scale_halo_density")
     @patch("imap_l3_processing.swe.swe_processor.scale_core_density")
     @patch("imap_l3_processing.swe.swe_processor.rotate_temperature")
@@ -2487,9 +2326,9 @@ def test_calculate_moment_products_only_integrates_temperatures_in_a_range(
         spacecraft_potential = np.array([12, 14, 16, 18])
         core_halo_breakpoint = np.array([96, 54, 103, 124])
 
-        corrected_energy_bins = swe_l2_data.energy.reshape(
-            1, -1
-        ) - spacecraft_potential.reshape(-1, 1)
+        corrected_energy_bins = swe_l2_data.energy.reshape(1, -1) - spacecraft_potential.reshape(
+            -1, 1
+        )
 
         mock_integrate.return_value.temperature = np.full(6, 0)
 
@@ -2554,9 +2393,7 @@ def test_calculate_moments_products_flags_data_and_uses_fill_based_on_spice_call
         mock_scale_halo_density: Mock,
         mock_predicted_ephemeris_tracker: Mock,
     ):
-        epochs = datetime(2025, 1, 1, tzinfo=timezone.utc) + np.arange(3) * timedelta(
-            minutes=1
-        )
+        epochs = datetime(2025, 1, 1, tzinfo=timezone.utc) + np.arange(3) * timedelta(minutes=1)
 
         mock_predicted_ephemeris_tracker_epoch_1 = create_autospec(
             PredictedEphemerisTracker, used_predict=False
@@ -2586,12 +2423,8 @@ def test_calculate_moments_products_flags_data_and_uses_fill_based_on_spice_call
         mock_compute_maxwellian_weight_factors.return_value = np.full(
             shape=(24, 30, 7), fill_value=1
         )
-        mock_core_fit_moments_retrying_on_failure.return_value = (
-            build_moment_fit_results()
-        )
-        mock_halo_fit_moments_retrying_on_failure.return_value = (
-            build_moment_fit_results()
-        )
+        mock_core_fit_moments_retrying_on_failure.return_value = build_moment_fit_results()
+        mock_halo_fit_moments_retrying_on_failure.return_value = build_moment_fit_results()
         mock_integrate.return_value = IntegrateOutputs(
             100,
             np.array([1, 2, 3]),
@@ -2641,9 +2474,9 @@ def test_calculate_moments_products_flags_data_and_uses_fill_based_on_spice_call
         )
         spacecraft_potential = np.array([12, 14, 16])
         core_halo_breakpoint = np.array([96, 54, 103])
-        corrected_energy_bins = swe_l2_data.energy.reshape(
-            1, -1
-        ) - spacecraft_potential.reshape(-1, 1)
+        corrected_energy_bins = swe_l2_data.energy.reshape(1, -1) - spacecraft_potential.reshape(
+            -1, 1
+        )
 
         input_metadata = InputMetadata(
             "swe",
@@ -2739,9 +2572,7 @@ def test_calculate_moments_products_flags_data_and_uses_fill_based_on_spice_call
 
         np.testing.assert_array_equal(
             swe_moment_data.quality_flags,
-            np.array(
-                [SweL3Flags.NONE, SweL3Flags.NONE, SweL3Flags.PREDICTIVE_EPHEMERIS]
-            ),
+            np.array([SweL3Flags.NONE, SweL3Flags.NONE, SweL3Flags.PREDICTIVE_EPHEMERIS]),
         )
         self.assertEqual(np.uint16, swe_moment_data.quality_flags.dtype)
 
@@ -2771,17 +2602,15 @@ def test_calculate_moment_products_handles_bad_fit_indices_and_continues(self):
         )
         spacecraft_potential = np.array([12, 14])
         core_halo_breakpoint = np.array([12, 54])
-        corrected_energy_bins = swe_l2_data.energy.reshape(
-            1, -1
-        ) - spacecraft_potential.reshape(-1, 1)
+        corrected_energy_bins = swe_l2_data.energy.reshape(1, -1) - spacecraft_potential.reshape(
+            -1, 1
+        )
 
         input_metadata = InputMetadata(
             "swe", "l3", datetime(2025, 2, 21), datetime(2025, 2, 22), "v001"
         )
 
-        swe_processor = SweProcessor(
-            ProcessingInputCollection(), input_metadata=input_metadata
-        )
+        swe_processor = SweProcessor(ProcessingInputCollection(), input_metadata=input_metadata)
         config = build_swe_configuration()
 
         rebinned_mag_data = [sentinel.mag_data_1]
@@ -2807,9 +2636,7 @@ def test_calculate_moment_products_handles_bad_fit_indices_and_continues(self):
 
     @patch("imap_l3_processing.swe.swe_processor.rotate_temperature_tensor_to_mag")
     @patch("imap_l3_processing.swe.swe_processor.calculate_primary_eigenvector")
-    @patch(
-        "imap_l3_processing.swe.swe_processor.rotate_vector_to_rtn_spherical_coordinates"
-    )
+    @patch("imap_l3_processing.swe.swe_processor.rotate_vector_to_rtn_spherical_coordinates")
     @patch("imap_l3_processing.swe.swe_processor.scale_halo_density")
     @patch("imap_l3_processing.swe.swe_processor.scale_core_density")
     @patch("imap_l3_processing.swe.swe_processor.integrate")
@@ -3121,9 +2948,7 @@ def test_negative_core_density_masks_core_and_total_and_flags(self):
             nan_index=1,
             finite_indices=(0, 2),
         )
-        _assert_fields_finite_everywhere(
-            self, moment_data, _HALO_INTEGRATED_FIELD_NAMES
-        )
+        _assert_fields_finite_everywhere(self, moment_data, _HALO_INTEGRATED_FIELD_NAMES)
         _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_core_tensor_diagonal_masks_core_and_total_and_flags(self):
@@ -3160,9 +2985,7 @@ def test_negative_core_tensor_diagonal_masks_core_and_total_and_flags(self):
                     nan_index=1,
                     finite_indices=(0, 2),
                 )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _HALO_INTEGRATED_FIELD_NAMES
-                )
+                _assert_fields_finite_everywhere(self, moment_data, _HALO_INTEGRATED_FIELD_NAMES)
                 _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_core_tensor_off_diagonal_does_not_flag_or_mask(self):
@@ -3184,15 +3007,9 @@ def test_negative_core_tensor_off_diagonal_does_not_flag_or_mask(self):
                 np.testing.assert_array_equal(flags, expected_flags)
                 self.assertEqual(np.uint16, flags.dtype)
 
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _CORE_INTEGRATED_FIELD_NAMES
-                )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _HALO_INTEGRATED_FIELD_NAMES
-                )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _TOTAL_INTEGRATED_FIELD_NAMES
-                )
+                _assert_fields_finite_everywhere(self, moment_data, _CORE_INTEGRATED_FIELD_NAMES)
+                _assert_fields_finite_everywhere(self, moment_data, _HALO_INTEGRATED_FIELD_NAMES)
+                _assert_fields_finite_everywhere(self, moment_data, _TOTAL_INTEGRATED_FIELD_NAMES)
                 _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_halo_density_masks_halo_and_total_and_flags(self):
@@ -3222,9 +3039,7 @@ def test_negative_halo_density_masks_halo_and_total_and_flags(self):
             nan_index=1,
             finite_indices=(0, 2),
         )
-        _assert_fields_finite_everywhere(
-            self, moment_data, _CORE_INTEGRATED_FIELD_NAMES
-        )
+        _assert_fields_finite_everywhere(self, moment_data, _CORE_INTEGRATED_FIELD_NAMES)
         _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_halo_tensor_diagonal_masks_halo_and_total_and_flags(self):
@@ -3261,9 +3076,7 @@ def test_negative_halo_tensor_diagonal_masks_halo_and_total_and_flags(self):
                     nan_index=1,
                     finite_indices=(0, 2),
                 )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _CORE_INTEGRATED_FIELD_NAMES
-                )
+                _assert_fields_finite_everywhere(self, moment_data, _CORE_INTEGRATED_FIELD_NAMES)
                 _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_halo_tensor_off_diagonal_does_not_flag_or_mask(self):
@@ -3285,15 +3098,9 @@ def test_negative_halo_tensor_off_diagonal_does_not_flag_or_mask(self):
                 np.testing.assert_array_equal(flags, expected_flags)
                 self.assertEqual(np.uint16, flags.dtype)
 
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _CORE_INTEGRATED_FIELD_NAMES
-                )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _HALO_INTEGRATED_FIELD_NAMES
-                )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _TOTAL_INTEGRATED_FIELD_NAMES
-                )
+                _assert_fields_finite_everywhere(self, moment_data, _CORE_INTEGRATED_FIELD_NAMES)
+                _assert_fields_finite_everywhere(self, moment_data, _HALO_INTEGRATED_FIELD_NAMES)
+                _assert_fields_finite_everywhere(self, moment_data, _TOTAL_INTEGRATED_FIELD_NAMES)
                 _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_total_density_masks_only_total_and_flags(self):
@@ -3316,12 +3123,8 @@ def test_negative_total_density_masks_only_total_and_flags(self):
             nan_index=1,
             finite_indices=(0, 2),
         )
-        _assert_fields_finite_everywhere(
-            self, moment_data, _CORE_INTEGRATED_FIELD_NAMES
-        )
-        _assert_fields_finite_everywhere(
-            self, moment_data, _HALO_INTEGRATED_FIELD_NAMES
-        )
+        _assert_fields_finite_everywhere(self, moment_data, _CORE_INTEGRATED_FIELD_NAMES)
+        _assert_fields_finite_everywhere(self, moment_data, _HALO_INTEGRATED_FIELD_NAMES)
         _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_total_tensor_diagonal_masks_only_total_and_flags(self):
@@ -3351,12 +3154,8 @@ def test_negative_total_tensor_diagonal_masks_only_total_and_flags(self):
                     nan_index=1,
                     finite_indices=(0, 2),
                 )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _CORE_INTEGRATED_FIELD_NAMES
-                )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _HALO_INTEGRATED_FIELD_NAMES
-                )
+                _assert_fields_finite_everywhere(self, moment_data, _CORE_INTEGRATED_FIELD_NAMES)
+                _assert_fields_finite_everywhere(self, moment_data, _HALO_INTEGRATED_FIELD_NAMES)
                 _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_negative_total_tensor_off_diagonal_does_not_flag_or_mask(self):
@@ -3378,15 +3177,9 @@ def test_negative_total_tensor_off_diagonal_does_not_flag_or_mask(self):
                 np.testing.assert_array_equal(flags, expected_flags)
                 self.assertEqual(np.uint16, flags.dtype)
 
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _CORE_INTEGRATED_FIELD_NAMES
-                )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _HALO_INTEGRATED_FIELD_NAMES
-                )
-                _assert_fields_finite_everywhere(
-                    self, moment_data, _TOTAL_INTEGRATED_FIELD_NAMES
-                )
+                _assert_fields_finite_everywhere(self, moment_data, _CORE_INTEGRATED_FIELD_NAMES)
+                _assert_fields_finite_everywhere(self, moment_data, _HALO_INTEGRATED_FIELD_NAMES)
+                _assert_fields_finite_everywhere(self, moment_data, _TOTAL_INTEGRATED_FIELD_NAMES)
                 _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
 
     def test_combines_negative_sources_correctly(self):
@@ -3450,14 +3243,8 @@ def assert_population_at_epoch(
         )
         for epoch, core_masked, halo_masked, total_masked in epoch_masking_matrix:
             with self.subTest(epoch=epoch):
-                assert_population_at_epoch(
-                    epoch, _CORE_INTEGRATED_FIELD_NAMES, core_masked
-                )
-                assert_population_at_epoch(
-                    epoch, _HALO_INTEGRATED_FIELD_NAMES, halo_masked
-                )
-                assert_population_at_epoch(
-                    epoch, _TOTAL_INTEGRATED_FIELD_NAMES, total_masked
-                )
+                assert_population_at_epoch(epoch, _CORE_INTEGRATED_FIELD_NAMES, core_masked)
+                assert_population_at_epoch(epoch, _HALO_INTEGRATED_FIELD_NAMES, halo_masked)
+                assert_population_at_epoch(epoch, _TOTAL_INTEGRATED_FIELD_NAMES, total_masked)
 
         _assert_fields_finite_everywhere(self, moment_data, _FIT_FIELD_NAMES)
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/archive/map_SCFrame.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/archive/map_SCFrame.py
index c8a8b8c0..17a01d3c 100755
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/archive/map_SCFrame.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/archive/map_SCFrame.py
@@ -1,12 +1,15 @@
+#!/usr/bin/python
+
 # May 18, 2023 - NAS
 # in Version 2 we are adding the TOF3 < 20 ns criterion
-#!/usr/bin/python
-import numpy as np
+
 import argparse
-import pandas as pd
 import os
 from pathlib import Path
 
+import numpy as np
+import pandas as pd
+
 PI = np.pi
 
 # ESA Steps
@@ -35,13 +38,9 @@ def argParsing():
         help="Path to the location of CSV files generated by flight_to_csv.py",
     )
 
-    parser.add_argument(
-        "-se", "--start_esa", required=False, type=int, help="Start ESA Number"
-    )
+    parser.add_argument("-se", "--start_esa", required=False, type=int, help="Start ESA Number")
 
-    parser.add_argument(
-        "-ee", "--end_esa", required=False, type=int, help="End ESA Number"
-    )
+    parser.add_argument("-ee", "--end_esa", required=False, type=int, help="End ESA Number")
 
     return parser.parse_args()
 
@@ -142,7 +141,7 @@ def argParsing():
             counts = df["counts"].values
             expo = df["expo"].values
 
-            for ia in range(0, 60):
+            for ia in range(60):
                 ra = ps_ra[ia]
                 dec = ps_dec[ia]
 
@@ -159,8 +158,8 @@ def argParsing():
                 h_cnts_map[jmap, imap] += counts[ia]
                 exposure[jmap, imap] += expo[ia]
 
-        for imap in range(0, nra):
-            for jmap in range(0, ncolat):
+        for imap in range(nra):
+            for jmap in range(ncolat):
                 expo = exposure[jmap, imap]
                 energy = esa_energy[esa]
                 # if el == 'Hy':
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/crap/new_patch_arc2.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/crap/new_patch_arc2.py
old mode 100755
new mode 100644
index d54b632d..9d9d008b
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/crap/new_patch_arc2.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/crap/new_patch_arc2.py
@@ -1,9 +1,9 @@
+import cartopy.crs as ccrs
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
-import cartopy.crs as ccrs
-from scipy.spatial.transform import Rotation as R
 from matplotlib.colors import LogNorm
+from scipy.spatial.transform import Rotation as R
 
 PI = np.pi
 
@@ -32,9 +32,7 @@ def somewhat_great_circle_centered(rot, lat0, lon0, angle, npts=400):
     t = np.linspace(0, 2 * np.pi, npts)
 
     angle_r = np.radians(angle)
-    pts = np.cos(angle_r) * p + np.sin(angle_r) * (
-        np.outer(np.cos(t), u) + np.outer(np.sin(t), v)
-    )
+    pts = np.cos(angle_r) * p + np.sin(angle_r) * (np.outer(np.cos(t), u) + np.outer(np.sin(t), v))
     # rotate into map frame
     pts_rot = rot.apply(pts)
 
@@ -103,9 +101,7 @@ def make_imap_lo_reference_points(rot, option=1):
         labels = ["Nose", "V1", "V2", "Tail"]
     if option == 2:
         npoints = 7
-        lons = np.array(
-            [259.200622, 255.499300, 289.800000, 79.200622, 221, 150.0, 0.0]
-        )
+        lons = np.array([259.200622, 255.499300, 289.800000, 79.200622, 221, 150.0, 0.0])
         lats = np.array([5.116296, 34.999941, -35.600000, -5.116296, 39, 0.0, 0.0])
         labels = ["Nose", "V1", "V2", "Tail", "Rcen", "Stbd", "Port"]
     if option == 3:
@@ -154,7 +150,7 @@ def make_imap_lo_reference_points(rot, option=1):
         # --- Reference point in ORIGINAL coordinates ---
     lat_points = np.linspace(0.0, 0.0, npoints)
     lon_points = np.linspace(0.0, 0.0, npoints)
-    for i in range(0, npoints):
+    for i in range(npoints):
         ref_lat = lats[i]  # degrees
         ref_lon = lons[i]  # degrees
 
@@ -186,9 +182,7 @@ def make_imap_lo_reference_points(rot, option=1):
 # --- Load data ---
 
 
-def make_imap_lo_map(
-    file, lat_center, lon_center, vmin, vmax, output, opt_points=1, opt_ribbon=0
-):
+def make_imap_lo_map(file, lat_center, lon_center, vmin, vmax, output, opt_points=1, opt_ribbon=0):
 
     data = pd.read_csv(file, header=0).values
     ny, nx = data.shape
@@ -219,9 +213,7 @@ def make_imap_lo_map(
     xyz_rot = rot.apply(xyz)
 
     lat_rot = np.degrees(np.arcsin(xyz_rot[:, 2])).reshape(ny + 1, nx + 1)
-    lon_rot = np.degrees(np.arctan2(xyz_rot[:, 1], xyz_rot[:, 0])).reshape(
-        ny + 1, nx + 1
-    )
+    lon_rot = np.degrees(np.arctan2(xyz_rot[:, 1], xyz_rot[:, 0])).reshape(ny + 1, nx + 1)
     lon_rot = (lon_rot + 180) % 360 - 180
 
     # For the data
@@ -231,11 +223,9 @@ def make_imap_lo_map(
     # lat_edges = compute_edges(lat_rot)
 
     # --- Plot using pcolormesh ---
-    fig, ax = plt.subplots(figsize=(10, 5), subplot_kw={"projection": ccrs.Mollweide()})
+    _fig, ax = plt.subplots(figsize=(10, 5), subplot_kw={"projection": ccrs.Mollweide()})
     ax.set_facecolor("darkblue")
 
-    vmin = vmin
-    vmax = vmax
     data_clipped = np.clip(data, vmin, vmax)
     data_filled = np.copy(data_clipped)
     data_filled[np.isnan(data_clipped)] = vmin
@@ -312,7 +302,7 @@ def make_imap_lo_map(
                     ax.text(
                         lon_here,
                         seg_lat[0],
-                        f"{int(round(lat_orig))}°",
+                        f"{round(lat_orig)}°",
                         transform=ccrs.PlateCarree(),
                         color="orange",
                         fontsize=6,
@@ -426,7 +416,7 @@ def make_imap_lo_map(
     if opt_points > 0:
         labels, lon_points, lat_points = make_imap_lo_reference_points(rot, opt_points)
         npoints = len(labels)
-        for i in range(0, npoints):
+        for i in range(npoints):
             lon_ref_rot = lon_points[i]
             lat_ref_rot = lat_points[i]
             ref_label = labels[i]
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv2yaml.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv2yaml.py
index 5ac0ff47..6ef3b613 100755
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv2yaml.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv2yaml.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 """
 Created on Wed Feb 25 17:06:47 2026
 
@@ -62,9 +61,7 @@ def csv_to_map_yaml(
         reader = csv.reader(f)
         header = next(reader)  # 10–59, not used  # noqa: F841
         for row in reader:
-            formatted_row = [
-                f"{float(x):.3E}" if float(x) != 0 else "0.000E+00" for x in row
-            ]
+            formatted_row = [f"{float(x):.3E}" if float(x) != 0 else "0.000E+00" for x in row]
             data_rows.append(formatted_row)
 
     _, _, tag = latest_monday_tag()
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv_to_soc.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv_to_soc.py
index 26e87258..b909608d 100755
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv_to_soc.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/csv_to_soc.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 """
 Created on Sat Jan  3 21:04:46 2026
 
@@ -7,10 +6,11 @@
 """
 
 import os
+from datetime import datetime
 from pathlib import Path
-import pandas as pd
+
 import numpy as np
-from datetime import datetime
+import pandas as pd
 
 # -----------------------------
 # Configuration
@@ -55,8 +55,10 @@ def build_header(file_type, hmin, hmax):
         " skyframe=ECLIPJ2000 posframe=J2000",
         "",
         " chat=0 smearspread='0/0/0' calc='0/0/0'",
-        " frame_epoch=914561779.587 resp_class=lo_triple "
-        "zaxis_ra_deg=+274.476346 zaxis_dec_deg=-22.782473",
+        (
+            " frame_epoch=914561779.587 resp_class=lo_triple "
+            "zaxis_ra_deg=+274.476346 zaxis_dec_deg=-22.782473"
+        ),
         " ram_ra_deg=+186.7725 ram_dec_deg=-3.2847 mtype_list='40' energy_list='21,41'",
         " check_mt_list='40' check_species='20' rate_factor='1000' e_nominal='0.015'",
         "",
@@ -127,7 +129,6 @@ def build_header(file_type, hmin, hmax):
         # with open(f'/Users/hafijulislam/UNH/csv_to_isoc/converted/map_cnts_esa{esa}.txt', "w") as f:
         with open(out_path, "w") as f:
             f.write("\n".join(header) + "\n")
-            for row in data:
-                f.write("\t".join(f"{val:.6e}" for val in row) + "\n")
+            f.writelines("\t".join(f"{val:.6e}" for val in row) + "\n" for row in data)
 
     print(f"Converted Maps for Pivot {pp}")
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/l1b_to_spin.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/l1b_to_spin.py
index f1432192..5be72a6f 100755
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/l1b_to_spin.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/l1b_to_spin.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 """
 Created on Sat Feb  7 11:53:09 2026
 
@@ -8,15 +7,16 @@
 This code produce spin angle distribution from the l1b histograms.
 """
 
-from spacepy.pycdf import CDF
-import numpy as np
 import os
+import re
+import shutil
 import sys
 from datetime import datetime
 from pathlib import Path
+
+import numpy as np
 import pandas as pd
-import re
-import shutil
+from spacepy.pycdf import CDF
 
 
 def radec2cart(ra, th):
@@ -37,9 +37,7 @@ def equatorial_to_ecliptic(alpha, delta):
     delta_rad = np.radians(delta)
     epsilon_rad = np.radians(epsilon_0)
 
-    numerator = np.sin(alpha_rad) * np.cos(epsilon_rad) + np.tan(delta_rad) * np.sin(
-        epsilon_rad
-    )
+    numerator = np.sin(alpha_rad) * np.cos(epsilon_rad) + np.tan(delta_rad) * np.sin(epsilon_rad)
     denominator = np.cos(alpha_rad)
 
     # Calculate ecliptic longitude
@@ -226,13 +224,11 @@ def route_by_pivot(data_dir, pivot_csv):
         cdf = CDF(file_path)
 
         for ESA in range(1, 8):
-            nep_cnts = np.zeros((60))
-            nep_expo = np.zeros((60))
+            nep_cnts = np.zeros(60)
+            nep_expo = np.zeros(60)
 
             ## Filter through Goodtime, create masking
-            start_arr, end_arr, expo = estimate_exposure_time(
-                goodtime_file, int_YD, ESA
-            )
+            start_arr, end_arr, expo = estimate_exposure_time(goodtime_file, int_YD, ESA)
 
             met_epoch = datetime(2010, 1, 1, 0, 0, 0)
             epoch_sec = cdf["epoch"][:]
@@ -291,20 +287,16 @@ def route_by_pivot(data_dir, pivot_csv):
             df_new["date_yyyymmdd"] = yymmdd
             df_new["yd"] = YD
             df_new["repoint"] = (
-                basename.split("-repoint")[1].split("_")[0]
-                if "-repoint" in basename
-                else ""
+                basename.split("-repoint")[1].split("_")[0] if "-repoint" in basename else ""
             )
             df_new["pivot"] = int(pivot)
             df_new["l1b_product"] = "histrates"
             df_new["l1b_filename"] = basename
             df_new["l1b_path"] = str(Path(file_path).resolve())
 
-            df_new.to_csv(
-                f"./outdir/{pivot_str}/daily/data_YD_{YD}_esa{ESA}.csv", index=False
-            )
+            df_new.to_csv(f"./outdir/{pivot_str}/daily/data_YD_{YD}_esa{ESA}.csv", index=False)
 
-    except Exception as e:
+    except Exception as e:  # noqa: BLE001
         print(f"Skipping {file.name}: {e}")
 
 ## Move files into specific directory
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/map_SCFrame.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/map_SCFrame.py
index 8c6197fd..17834f54 100755
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/map_SCFrame.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/map_SCFrame.py
@@ -5,11 +5,12 @@
 
 """
 
-import numpy as np
-import pandas as pd
 import os
 from pathlib import Path
 
+import numpy as np
+import pandas as pd
+
 PI = np.pi
 
 # ESA Steps
@@ -193,7 +194,7 @@ def get_brate(YD, esa):
             counts = df["counts"].values
             expo = df["expo"].values
 
-            for ia in range(0, 60):
+            for ia in range(60):
                 ra = ps_ra[ia]
                 dec = ps_dec[ia]
 
@@ -220,8 +221,8 @@ def get_brate(YD, esa):
                 h_cnts_map[jmap, imap] += counts[ia]
                 exposure[jmap, imap] += expo[ia]
 
-        for imap in range(0, nra):
-            for jmap in range(0, ncolat):
+        for imap in range(nra):
+            for jmap in range(ncolat):
                 expo = exposure[jmap, imap]
                 energy = esa_energy[esa]
 
@@ -236,25 +237,18 @@ def get_brate(YD, esa):
                     back_rate_var[jmap, imap] = brate / expo
                     h_rate_map[jmap, imap] = h_cnts_map[jmap, imap] / expo
                     h_flux_map[jmap, imap] = h_rate_map[jmap, imap] / (geo * energy)
-                    h_fser_map[jmap, imap] = (
-                        h_rate_map[jmap, imap] * dge / (geo * geo * energy)
-                    )
+                    h_fser_map[jmap, imap] = h_rate_map[jmap, imap] * dge / (geo * geo * energy)
                     back_flux_map[jmap, imap] = brate / (geo * energy)
-                    back_flux_var[jmap, imap] = (
-                        back_rate_var[jmap, imap] / (geo * energy) ** 2
-                    )
+                    back_flux_var[jmap, imap] = back_rate_var[jmap, imap] / (geo * energy) ** 2
                     # represent uncertainty in terms of variance (Poisson counts)
                     h_rate_var[jmap, imap] = h_rate_map[jmap, imap] / expo
                     if brate > 0.0:
                         stonoise_map[jmap, imap] = h_rate_map[jmap, imap] / (brate)
                         # Guard against division by zero in stonoise_var components
-                        if (back_rate_map[jmap, imap] > 0.0) and (
-                            h_rate_map[jmap, imap] > 0.0
-                        ):
+                        if (back_rate_map[jmap, imap] > 0.0) and (h_rate_map[jmap, imap] > 0.0):
                             stonoise_var_map[jmap, imap] = (
                                 h_rate_var[jmap, imap] / back_rate_map[jmap, imap] ** 2
-                                + back_rate_var[jmap, imap]
-                                / h_rate_map[jmap, imap] ** 2
+                                + back_rate_var[jmap, imap] / h_rate_map[jmap, imap] ** 2
                             )
                         else:
                             stonoise_var_map[jmap, imap] = 0.0
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2.py
old mode 100755
new mode 100644
index 9a438088..e433e685
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2.py
@@ -1,9 +1,9 @@
+import cartopy.crs as ccrs
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
-import cartopy.crs as ccrs
-from scipy.spatial.transform import Rotation as R
 from matplotlib.colors import LogNorm
+from scipy.spatial.transform import Rotation as R
 
 PI = np.pi
 
@@ -32,9 +32,7 @@ def somewhat_great_circle_centered(rot, lat0, lon0, angle, npts=400):
     t = np.linspace(0, 2 * np.pi, npts)
 
     angle_r = np.radians(angle)
-    pts = np.cos(angle_r) * p + np.sin(angle_r) * (
-        np.outer(np.cos(t), u) + np.outer(np.sin(t), v)
-    )
+    pts = np.cos(angle_r) * p + np.sin(angle_r) * (np.outer(np.cos(t), u) + np.outer(np.sin(t), v))
     # rotate into map frame
     pts_rot = rot.apply(pts)
 
@@ -103,9 +101,7 @@ def make_imap_lo_reference_points(rot, option=1):
         labels = ["Nose", "V1", "V2", "Tail"]
     if option == 2:
         npoints = 7
-        lons = np.array(
-            [259.200622, 255.499300, 289.800000, 79.200622, 221, 150.0, 0.0]
-        )
+        lons = np.array([259.200622, 255.499300, 289.800000, 79.200622, 221, 150.0, 0.0])
         lats = np.array([5.116296, 34.999941, -35.600000, -5.116296, 39, 0.0, 0.0])
         labels = ["Nose", "V1", "V2", "Tail", "Rcen", "Stbd", "Port"]
     if option == 3:
@@ -154,7 +150,7 @@ def make_imap_lo_reference_points(rot, option=1):
         # --- Reference point in ORIGINAL coordinates ---
     lat_points = np.linspace(0.0, 0.0, npoints)
     lon_points = np.linspace(0.0, 0.0, npoints)
-    for i in range(0, npoints):
+    for i in range(npoints):
         ref_lat = lats[i]  # degrees
         ref_lon = lons[i]  # degrees
 
@@ -228,9 +224,7 @@ def make_imap_lo_map(
     xyz_rot = rot.apply(xyz)
 
     lat_rot = np.degrees(np.arcsin(xyz_rot[:, 2])).reshape(ny + 1, nx + 1)
-    lon_rot = np.degrees(np.arctan2(xyz_rot[:, 1], xyz_rot[:, 0])).reshape(
-        ny + 1, nx + 1
-    )
+    lon_rot = np.degrees(np.arctan2(xyz_rot[:, 1], xyz_rot[:, 0])).reshape(ny + 1, nx + 1)
     lon_rot = (lon_rot + 180) % 360 - 180
 
     # For the data
@@ -243,8 +237,6 @@ def make_imap_lo_map(
     fig, ax = plt.subplots(figsize=(10, 5), subplot_kw={"projection": ccrs.Mollweide()})
     ax.set_facecolor("darkblue")
 
-    vmin = vmin
-    vmax = vmax
     data_clipped = np.clip(data, vmin, vmax)
     data_filled = np.copy(data_clipped)
     data_filled[np.isnan(data_clipped)] = vmin
@@ -321,7 +313,7 @@ def make_imap_lo_map(
                     ax.text(
                         lon_here,
                         seg_lat[0],
-                        f"{int(round(lat_orig))}°",
+                        f"{round(lat_orig)}°",
                         transform=ccrs.PlateCarree(),
                         color="orange",
                         fontsize=6,
@@ -435,7 +427,7 @@ def make_imap_lo_map(
     if opt_points > 0:
         labels, lon_points, lat_points = make_imap_lo_reference_points(rot, opt_points)
         npoints = len(labels)
-        for i in range(0, npoints):
+        for i in range(npoints):
             lon_ref_rot = lon_points[i]
             lat_ref_rot = lat_points[i]
             ref_label = labels[i]
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2_linear.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2_linear.py
old mode 100755
new mode 100644
index b163a0d1..35e00e51
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2_linear.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/new_patch_arc2_linear.py
@@ -1,7 +1,7 @@
+import cartopy.crs as ccrs
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
-import cartopy.crs as ccrs
 from scipy.spatial.transform import Rotation as R
 
 PI = np.pi
@@ -31,9 +31,7 @@ def somewhat_great_circle_centered(rot, lat0, lon0, angle, npts=400):
     t = np.linspace(0, 2 * np.pi, npts)
 
     angle_r = np.radians(angle)
-    pts = np.cos(angle_r) * p + np.sin(angle_r) * (
-        np.outer(np.cos(t), u) + np.outer(np.sin(t), v)
-    )
+    pts = np.cos(angle_r) * p + np.sin(angle_r) * (np.outer(np.cos(t), u) + np.outer(np.sin(t), v))
     # rotate into map frame
     pts_rot = rot.apply(pts)
 
@@ -102,9 +100,7 @@ def make_imap_lo_reference_points(rot, option=1):
         labels = ["Nose", "V1", "V2", "Tail"]
     if option == 2:
         npoints = 7
-        lons = np.array(
-            [259.200622, 255.499300, 289.800000, 79.200622, 221, 150.0, 0.0]
-        )
+        lons = np.array([259.200622, 255.499300, 289.800000, 79.200622, 221, 150.0, 0.0])
         lats = np.array([5.116296, 34.999941, -35.600000, -5.116296, 39, 0.0, 0.0])
         labels = ["Nose", "V1", "V2", "Tail", "Rcen", "Stbd", "Port"]
     if option == 3:
@@ -153,7 +149,7 @@ def make_imap_lo_reference_points(rot, option=1):
         # --- Reference point in ORIGINAL coordinates ---
     lat_points = np.linspace(0.0, 0.0, npoints)
     lon_points = np.linspace(0.0, 0.0, npoints)
-    for i in range(0, npoints):
+    for i in range(npoints):
         ref_lat = lats[i]  # degrees
         ref_lon = lons[i]  # degrees
 
@@ -227,9 +223,7 @@ def make_imap_lo_map(
     xyz_rot = rot.apply(xyz)
 
     lat_rot = np.degrees(np.arcsin(xyz_rot[:, 2])).reshape(ny + 1, nx + 1)
-    lon_rot = np.degrees(np.arctan2(xyz_rot[:, 1], xyz_rot[:, 0])).reshape(
-        ny + 1, nx + 1
-    )
+    lon_rot = np.degrees(np.arctan2(xyz_rot[:, 1], xyz_rot[:, 0])).reshape(ny + 1, nx + 1)
     lon_rot = (lon_rot + 180) % 360 - 180
 
     # For the data
@@ -242,8 +236,6 @@ def make_imap_lo_map(
     fig, ax = plt.subplots(figsize=(10, 5), subplot_kw={"projection": ccrs.Mollweide()})
     ax.set_facecolor("darkblue")
 
-    vmin = vmin
-    vmax = vmax
     data_clipped = np.clip(data, vmin, vmax)
     data_filled = np.copy(data_clipped)
     data_filled[np.isnan(data_clipped)] = vmin
@@ -321,7 +313,7 @@ def make_imap_lo_map(
                     ax.text(
                         lon_here,
                         seg_lat[0],
-                        f"{int(round(lat_orig))}°",
+                        f"{round(lat_orig)}°",
                         transform=ccrs.PlateCarree(),
                         color="orange",
                         fontsize=6,
@@ -435,7 +427,7 @@ def make_imap_lo_map(
     if opt_points > 0:
         labels, lon_points, lat_points = make_imap_lo_reference_points(rot, opt_points)
         npoints = len(labels)
-        for i in range(0, npoints):
+        for i in range(npoints):
             lon_ref_rot = lon_points[i]
             lat_ref_rot = lat_points[i]
             ref_label = labels[i]
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/old/csv2yaml.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/old/csv2yaml.py
index 791b1fd8..a7e70425 100755
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/old/csv2yaml.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/old/csv2yaml.py
@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 """
 Created on Wed Feb 25 17:06:47 2026
 
@@ -57,9 +56,7 @@ def csv_to_map_yaml(
         reader = csv.reader(f)
         header = next(reader)  # 10–59, not used  # noqa: F841
         for row in reader:
-            formatted_row = [
-                f"{float(x):.3E}" if float(x) != 0 else "0.000E+00" for x in row
-            ]
+            formatted_row = [f"{float(x):.3E}" if float(x) != 0 else "0.000E+00" for x in row]
             data_rows.append(formatted_row)
 
     tag = latest_monday_tag()
diff --git a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/plot_map_DN.py b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/plot_map_DN.py
index fcae4b7a..4f5e648a 100755
--- a/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/plot_map_DN.py
+++ b/tests/test_data/lo/lo_txt_pipeline/3S5_l1b_ram_maps/plot_map_DN.py
@@ -1,16 +1,16 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 """
 Created on Sun Feb 15 18:14:16 2026
 
 @author: hafijulislam
 """
 
-import numpy as np
 import os
-from scipy.spatial.transform import Rotation as R
+
 import new_patch_arc2 as patch
 import new_patch_arc2_linear as pchlin
+import numpy as np
+from scipy.spatial.transform import Rotation as R
 
 PI = np.pi
 
diff --git a/tests/test_data_utils.py b/tests/test_data_utils.py
index 7da1fd0f..73f974ed 100644
--- a/tests/test_data_utils.py
+++ b/tests/test_data_utils.py
@@ -4,14 +4,12 @@
 
 import numpy as np
 
-from imap_l3_processing.data_utils import rebin, NearestInterpolator
+from imap_l3_processing.data_utils import NearestInterpolator, rebin
 
 
 class TestDataUtils(unittest.TestCase):
     def test_1d_rebin(self):
-        hit_data_epoch = np.array(
-            [datetime(2020, 4, 4, 0, 5), datetime(2020, 4, 4, 0, 15)]
-        )
+        hit_data_epoch = np.array([datetime(2020, 4, 4, 0, 5), datetime(2020, 4, 4, 0, 15)])
         hit_data_delta = np.array([timedelta(seconds=300), timedelta(seconds=300)])
         extra_data_at_beginning = [0, 0.5]
         extra_dates_at_beginning = [
@@ -51,9 +49,7 @@ def test_1d_rebin(self):
         np.testing.assert_array_equal(actual_average, expected_average)
 
     def test_rebin_with_extra_data_at_beginning_and_end(self):
-        hit_data_epoch = np.array(
-            [datetime(2020, 4, 4, 0, 5), datetime(2020, 4, 4, 0, 15)]
-        )
+        hit_data_epoch = np.array([datetime(2020, 4, 4, 0, 5), datetime(2020, 4, 4, 0, 15)])
         hit_data_delta = np.array([timedelta(seconds=300), timedelta(seconds=300)])
         extra_data_at_beginning = [[0.5, 0, 1], [0, 0.5, 1]]
         extra_dates_at_beginning = [
@@ -282,9 +278,7 @@ def test_nearest_interpolator_interpolate(self):
                     from_date_epoch, from_data, to_data_epoch, timedelta(days=1)
                 )
 
-                np.testing.assert_array_equal(
-                    interpolator.interpolate_data(), expected_values
-                )
+                np.testing.assert_array_equal(interpolator.interpolate_data(), expected_values)
                 np.testing.assert_array_equal(
                     interpolator.interpolate_flags(quality_flags),
                     expected_quality_flags,
@@ -309,10 +303,7 @@ def test_find_closest_neighbor_handles_large_dataset(self):
 
         from_data = np.repeat([[1, 0, 0]], 86400 * 2, axis=0)
         from_epoch = np.array(
-            [
-                datetime(2020, 4, 4) + timedelta(seconds=0.5) * i
-                for i in range(86400 * 2)
-            ]
+            [datetime(2020, 4, 4) + timedelta(seconds=0.5) * i for i in range(86400 * 2)]
         )
 
         t0 = time.perf_counter()
@@ -325,13 +316,9 @@ def test_find_closest_neighbor_handles_large_dataset(self):
 
     def test_nearest_interpolator_handles_nan(self):
         to_epoch = np.array([datetime(2020, 4, 4, minute=1)])
-        from_epoch = np.array(
-            [datetime(2020, 4, 4, minute=1), datetime(2020, 4, 4, minute=2)]
-        )
+        from_epoch = np.array([datetime(2020, 4, 4, minute=1), datetime(2020, 4, 4, minute=2)])
 
         from_data = np.array([np.nan, 2])
 
-        interpolator = NearestInterpolator(
-            from_epoch, from_data, to_epoch, timedelta(minutes=1)
-        )
+        interpolator = NearestInterpolator(from_epoch, from_data, to_epoch, timedelta(minutes=1))
         self.assertEqual(interpolator.interpolate_data(), [2])
diff --git a/tests/test_helpers.py b/tests/test_helpers.py
index 019babe3..0aeb9be4 100644
--- a/tests/test_helpers.py
+++ b/tests/test_helpers.py
@@ -1,26 +1,27 @@
 import json
 import os
 import tempfile
-from dataclasses import fields, dataclass
-from datetime import timedelta, datetime
+from collections.abc import Callable
+from dataclasses import dataclass, fields
+from datetime import datetime, timedelta
 from functools import wraps
 from pathlib import Path
-from typing import Type, Optional, Callable, TypeVar
+from typing import TypeVar
 from unittest import SkipTest
 from unittest.mock import Mock
 
 import imap_data_access
 import numpy as np
-from imap_data_access import ScienceFilePath, AncillaryFilePath, SPICEFilePath
-from imap_data_access.file_validation import generate_imap_file_path, Version
+from imap_data_access import AncillaryFilePath, ScienceFilePath, SPICEFilePath
+from imap_data_access.file_validation import Version, generate_imap_file_path
 
 import imap_l3_processing
 import tests
 from imap_l3_processing.models import VersionMap
 from imap_l3_processing.swe.l3.models import SweConfiguration, SweL3MomentData
 from imap_l3_processing.swe.l3.science.moment_calculations import (
-    Moments,
     MomentFitResults,
+    Moments,
 )
 
 run_local_data_path = Path(tests.__file__).parent.parent / "run_local_input_data"
@@ -57,9 +58,7 @@ def get_spice_data_path(filename: str) -> Path:
 
 
 def get_integration_test_spice_data_path(filename: str) -> Path:
-    return (
-        Path(tests.__file__).parent / "integration" / "test_data" / "spice" / filename
-    )
+    return Path(tests.__file__).parent / "integration" / "test_data" / "spice" / filename
 
 
 def get_test_data_folder() -> Path:
@@ -78,18 +77,18 @@ def build_swe_configuration(**args) -> SweConfiguration:
 
 
 def build_moments(**args) -> Moments:
-    default_moments = dict(
-        alpha=1,
-        beta=2,
-        t_parallel=3e5,
-        t_perpendicular=4e5,
-        velocity_x=500,
-        velocity_y=600,
-        velocity_z=700,
-        density=80,
-        aoo=9,
-        ao=10,
-    )
+    default_moments = {
+        "alpha": 1,
+        "beta": 2,
+        "t_parallel": 3e5,
+        "t_perpendicular": 4e5,
+        "velocity_x": 500,
+        "velocity_y": 600,
+        "velocity_z": 700,
+        "density": 80,
+        "aoo": 9,
+        "ao": 10,
+    }
     default_moments.update(**args)
 
     return Moments(**default_moments)
@@ -181,7 +180,7 @@ def build_swe_moment_data(epoch_len):
 T = TypeVar("T")
 
 
-def create_dataclass_mock(obj: Type[T], **kwargs) -> T:
+def create_dataclass_mock(obj: type[T], **kwargs) -> T:
     return Mock(spec=[field.name for field in fields(obj)], **kwargs)
 
 
@@ -215,9 +214,7 @@ def assert_dict_close(x, y, rtol=1e-7, path=None):
         for k in x:
             assert_dict_close(x[k], y[k], rtol, path.copy() + [k])
     elif isinstance(x, (list, np.ndarray, float)):
-        np.testing.assert_allclose(
-            x, y, rtol=rtol, err_msg=f"path to failure: {path_str}"
-        )
+        np.testing.assert_allclose(x, y, rtol=rtol, err_msg=f"path to failure: {path_str}")
     else:
         assert x == y, f"{x} != {y} at path {path_str}"
 
@@ -249,7 +246,7 @@ def wrapper(*args, **kwargs):
 
             func_result = func(*args, **kwargs)
 
-            for k in env_vars.keys():
+            for k in env_vars:
                 del os.environ[k]
 
             for k, v in old_vars.items():
@@ -263,7 +260,7 @@ def wrapper(*args, **kwargs):
 
 
 def create_mock_query_results(
-    file_names: list[Path | str], ingestion_dates: Optional[list[datetime]] = None
+    file_names: list[Path | str], ingestion_dates: list[datetime] | None = None
 ) -> list[dict]:
     file_paths = []
 
@@ -273,9 +270,7 @@ def create_mock_query_results(
     for fn, ingestion_date in zip(file_names, ingestion_dates):
         imap_file_path = generate_imap_file_path(Path(fn).name)
         file_path = str(
-            imap_file_path.construct_path().relative_to(
-                imap_data_access.config["DATA_DIR"]
-            )
+            imap_file_path.construct_path().relative_to(imap_data_access.config["DATA_DIR"])
         ).replace("\\", "/")
 
         match imap_file_path:
@@ -317,9 +312,9 @@ def create_mock_query_results(
 
 
 def create_mock_version_map(
-    descriptor: Optional[str] = "descriptor",
-    major_version: Optional[int] = None,
-    minor_version: Optional[int] = 1,
+    descriptor: str | None = "descriptor",
+    major_version: int | None = None,
+    minor_version: int | None = 1,
 ):
     return VersionMap({descriptor: Version(major_version, minor_version)})
 
@@ -328,16 +323,14 @@ def create_mock_version_map(
 class PeriodicallyRunTest:
     test_name: str
     frequency: str
-    last_run: Optional[str]
+    last_run: str | None
 
 
 def run_periodically(frequency: timedelta):
     def run_periodically_decorator(test_item):
         @wraps(test_item)
         def test_thing(*args):
-            periodically_run_tests_path = (
-                Path(__file__).parent / "periodically_run_tests.json"
-            )
+            periodically_run_tests_path = Path(__file__).parent / "periodically_run_tests.json"
             periodically_run_tests = json.loads(periodically_run_tests_path.read_text())
 
             last_run = periodically_run_tests.get(test_item.__name__)
@@ -355,12 +348,12 @@ def test_thing(*args):
                 periodically_run_tests_path.write_text(
                     json.dumps(periodically_run_tests, indent=4)
                 )
-            except Exception as e:
+            except Exception:
                 periodically_run_tests[test_item.__name__] = None
                 periodically_run_tests_path.write_text(
                     json.dumps(periodically_run_tests, indent=4)
                 )
-                raise e
+                raise
 
         return test_thing
 
diff --git a/tests/test_imap_l3_data_processor.py b/tests/test_imap_l3_data_processor.py
index 8793010f..be63ebec 100644
--- a/tests/test_imap_l3_data_processor.py
+++ b/tests/test_imap_l3_data_processor.py
@@ -2,13 +2,13 @@
 from datetime import datetime
 from pathlib import Path
 from unittest import TestCase
-from unittest.mock import patch, call, Mock, sentinel
+from unittest.mock import Mock, call, patch, sentinel
 
 from imap_data_access.file_validation import Version
 from imap_data_access.processing_input import (
-    ScienceInput,
-    ProcessingInputCollection,
     AncillaryInput,
+    ProcessingInputCollection,
+    ScienceInput,
     SPICEInput,
 )
 
@@ -120,9 +120,7 @@ def test_invokes_correct_processor(
                     ]
                 )
 
-                mock_processing_input.return_value.deserialize.assert_called_once_with(
-                    "[]"
-                )
+                mock_processing_input.return_value.deserialize.assert_called_once_with("[]")
 
                 expected_processor.assert_called_once_with(
                     mock_processing_input.return_value, expected_input_metadata
@@ -219,9 +217,7 @@ def test_scheduled_map_jobs_invoke_correct_initializer(
                 "version": version_descriptors,
                 "dependency": [],
             }
-            dependency_with_version_info_as_string = json.dumps(
-                dependency_with_version_info
-            )
+            dependency_with_version_info_as_string = json.dumps(dependency_with_version_info)
 
             dependency_cases = [
                 ("old style", "[]", None, VersionMap({descriptor: Version(None, 1)})),
@@ -252,14 +248,10 @@ def test_scheduled_map_jobs_invoke_correct_initializer(
                     mock_argument_parser = mock_argparse.ArgumentParser.return_value
                     mock_argument_parser.parse_args.return_value.instrument = instrument
                     mock_argument_parser.parse_args.return_value.data_level = data_level
-                    mock_argument_parser.parse_args.return_value.dependency = (
-                        dependency_contents
-                    )
+                    mock_argument_parser.parse_args.return_value.dependency = dependency_contents
                     mock_argument_parser.parse_args.return_value.start_date = "20250101"
                     mock_argument_parser.parse_args.return_value.end_date = None
-                    mock_argument_parser.parse_args.return_value.repointing = (
-                        "repoint00022"
-                    )
+                    mock_argument_parser.parse_args.return_value.repointing = "repoint00022"
                     mock_argument_parser.parse_args.return_value.version = "v001"
                     mock_argument_parser.parse_args.return_value.descriptor = descriptor
 
@@ -275,9 +267,7 @@ def test_scheduled_map_jobs_invoke_correct_initializer(
                     mock_initializer = mock_initializer_class.return_value
                     mock_processor = mock_processor_class.return_value
 
-                    possible_map_to_produce = PossibleMapToProduce(
-                        set(), expected_input_metadata
-                    )
+                    possible_map_to_produce = PossibleMapToProduce(set(), expected_input_metadata)
                     mock_initializer.get_maps_that_should_be_produced.return_value = [
                         possible_map_to_produce
                     ]
@@ -293,9 +283,7 @@ def test_scheduled_map_jobs_invoke_correct_initializer(
                         ]
                     )
 
-                    self.assertEqual(
-                        len(expected_descriptors), mock_processor_class.call_count
-                    )
+                    self.assertEqual(len(expected_descriptors), mock_processor_class.call_count)
 
                     self.assertEqual(
                         len(expected_descriptors),
@@ -309,9 +297,7 @@ def test_scheduled_map_jobs_invoke_correct_initializer(
                         possible_map_to_produce.processing_input_collection,
                         expected_input_metadata,
                     )
-                    self.assertEqual(
-                        len(expected_descriptors), mock_processor.process.call_count
-                    )
+                    self.assertEqual(len(expected_descriptors), mock_processor.process.call_count)
 
                     self.assertEqual(len(expected_descriptors), mock_upload.call_count)
                     mock_upload.assert_called_with(sentinel.cdf)
@@ -339,8 +325,7 @@ def test_failing_to_produce_an_sp_map_continues(
         mock_argument_parser.parse_args.return_value.descriptor = descriptor
 
         mock_hi_initializer.get_maps_that_should_be_produced.side_effect = [
-            [PossibleMapToProduce(set(), Mock())]
-            for _ in range(len(HI_SP_MAP_DESCRIPTORS))
+            [PossibleMapToProduce(set(), Mock())] for _ in range(len(HI_SP_MAP_DESCRIPTORS))
         ]
 
         mock_hi_processor.return_value.process.side_effect = [
@@ -399,16 +384,12 @@ def test_get_spice_kernels_based_on_input_collection(
         mock_download.side_effect = [Path("naif0012.tls"), Path("imap_sclk_0012.tls")]
 
         imap_l3_processor()
-        expected_spice_paths = imap_data_access_dependency.get_file_paths(
-            data_type="spice"
-        )
+        expected_spice_paths = imap_data_access_dependency.get_file_paths(data_type="spice")
         self.assertEqual(2, mock_download.call_count)
         mock_download.assert_has_calls(
             [call(expected_spice_paths[0]), call(expected_spice_paths[1])]
         )
-        mock_spicepy.furnsh.assert_has_calls(
-            [call("naif0012.tls"), call("imap_sclk_0012.tls")]
-        )
+        mock_spicepy.furnsh.assert_has_calls([call("naif0012.tls"), call("imap_sclk_0012.tls")])
 
     @patch("imap_l3_data_processor.ProcessingInputCollection")
     @patch("imap_l3_data_processor.imap_data_access.upload")
@@ -651,9 +632,7 @@ def test_upload_fails_tries_all_uploads_and_raises_exception(
 
     @patch("imap_l3_data_processor.argparse")
     @patch("imap_l3_data_processor.imap_data_access.upload")
-    def test_throws_exception_for_unimplemented_instrument(
-        self, mock_upload, mock_argparse
-    ):
+    def test_throws_exception_for_unimplemented_instrument(self, mock_upload, mock_argparse):
         instrument_argument = "new_instrument"
         data_level_argument = "l3a"
         start_date_argument = "20160630"
@@ -814,9 +793,7 @@ def test_version_comes_from_dependency(
         input_end_date, expected_end_date = "20170630", datetime(2017, 6, 30)
         for name, dependency, expected_version_map in cases:
             with self.subTest(name):
-                mock_argument_parser.parse_args.return_value.dependency = json.dumps(
-                    dependency
-                )
+                mock_argument_parser.parse_args.return_value.dependency = json.dumps(dependency)
                 mock_upload.reset_mock()
                 imap_data_access_dependency.deserialize.reset_mock()
 
diff --git a/tests/test_models.py b/tests/test_models.py
index 1f91bf58..dccdc334 100644
--- a/tests/test_models.py
+++ b/tests/test_models.py
@@ -9,9 +9,7 @@
 
 class TestModels(unittest.TestCase):
     def test_calculate_average_mag_data_with_extra_data_at_beginning_and_end(self):
-        hit_data_epoch = np.array(
-            [datetime(2020, 4, 4, 0, 5), datetime(2020, 4, 4, 0, 15)]
-        )
+        hit_data_epoch = np.array([datetime(2020, 4, 4, 0, 5), datetime(2020, 4, 4, 0, 15)])
         hit_data_delta = np.array([timedelta(seconds=300), timedelta(seconds=300)])
         extra_data_at_beginning = [[0.5, 0, 1], [0, 0.5, 1]]
         extra_dates_at_beginning = [
@@ -81,9 +79,7 @@ def test_calculate_average_mag_data_handles_missing_mag_data(self):
         )
 
         mag_data_model = MagData(mag_epoch, mag_data)
-        actual_average = mag_data_model.rebin_to(
-            epoch=hit_data_epoch, epoch_delta=hit_data_delta
-        )
+        actual_average = mag_data_model.rebin_to(epoch=hit_data_epoch, epoch_delta=hit_data_delta)
         np.testing.assert_array_equal(actual_average, expected_average)
 
     def test_version_map(self):
diff --git a/tests/test_pitch_angles.py b/tests/test_pitch_angles.py
index aefbc016..93e52d03 100644
--- a/tests/test_pitch_angles.py
+++ b/tests/test_pitch_angles.py
@@ -3,12 +3,12 @@
 import numpy as np
 
 from imap_l3_processing.pitch_angles import (
+    calculate_gyrophase,
     calculate_pitch_angle,
     calculate_unit_vector,
-    calculate_gyrophase,
+    rebin_by_pitch_angle_and_gyrophase,
     rotate_from_imap_despun_to_hit_despun,
     rotate_particle_vectors_from_hit_despun_to_imap_despun,
-    rebin_by_pitch_angle_and_gyrophase,
 )
 
 
@@ -46,9 +46,7 @@ def test_calculate_unit_vector(self):
 
         many_vectors = np.array([[0.1, 0, 0], [30, 40, 0]])
         unit_vectors = calculate_unit_vector(many_vectors)
-        np.testing.assert_array_almost_equal(
-            [[1, 0, 0], [3 / 5, 4 / 5, 0]], unit_vectors
-        )
+        np.testing.assert_array_almost_equal([[1, 0, 0], [3 / 5, 4 / 5, 0]], unit_vectors)
 
     def test_rotate_from_imap_despun_to_hit_despun(self):
         vector = np.array([1.0, 1.0, 1.0])
@@ -70,8 +68,8 @@ def test_rotate_particle_vectors_from_hit_despun_to_imap_despun(self):
             dtype=float,
         )
 
-        rotated_particle_vectors = (
-            rotate_particle_vectors_from_hit_despun_to_imap_despun(particle_vectors)
+        rotated_particle_vectors = rotate_particle_vectors_from_hit_despun_to_imap_despun(
+            particle_vectors
         )
 
         expected_particle_vectors = np.array(
@@ -83,9 +81,7 @@ def test_rotate_particle_vectors_from_hit_despun_to_imap_despun(self):
             ]
         )
 
-        np.testing.assert_array_almost_equal(
-            rotated_particle_vectors, expected_particle_vectors
-        )
+        np.testing.assert_array_almost_equal(rotated_particle_vectors, expected_particle_vectors)
 
     def test_calculate_gyrophase(self):
         particle_vector = np.array(
@@ -291,9 +287,7 @@ def test_rebin_intensity_by_pitch_angle_and_gyrophase(self):
                 np.testing.assert_array_equal(
                     intensity_pa_and_gyro, expected_intensity_by_pa_gyrophase
                 )
-                np.testing.assert_array_equal(
-                    intensity_pa_only, expected_intensity_by_pa
-                )
+                np.testing.assert_array_equal(intensity_pa_only, expected_intensity_by_pa)
 
     def test_rebin_by_pitch_angle_and_gyrophase_pa_product_only_correctly_weights_when_averaging(
         self,
@@ -359,13 +353,9 @@ def test_rebin_by_pitch_angle_and_gyrophase_includes_uncertainties(self):
             ]
         )
 
-        expected_delta_plus_pa_only = np.array(
-            [[0.084187, 0.252562], [0.43045, 0.60958]]
-        )
+        expected_delta_plus_pa_only = np.array([[0.084187, 0.252562], [0.43045, 0.60958]])
 
-        expected_delta_minus_pa_only = np.array(
-            [[0.102896, 0.308687], [0.526106, 0.745042]]
-        )
+        expected_delta_minus_pa_only = np.array([[0.102896, 0.308687], [0.526106, 0.745042]])
 
         rebinned_data = rebin_by_pitch_angle_and_gyrophase(
             intensity,
@@ -382,12 +372,8 @@ def test_rebin_by_pitch_angle_and_gyrophase_includes_uncertainties(self):
 
         np.testing.assert_allclose(delta_plus_pa_gyro, expected_delta_plus_pa_gyro)
         np.testing.assert_allclose(delta_minus_pa_gyro, expected_delta_minus_pa_gyro)
-        np.testing.assert_allclose(
-            delta_plus_pa_only, expected_delta_plus_pa_only, rtol=1e-5
-        )
-        np.testing.assert_allclose(
-            delta_minus_pa_only, expected_delta_minus_pa_only, rtol=1e-5
-        )
+        np.testing.assert_allclose(delta_plus_pa_only, expected_delta_plus_pa_only, rtol=1e-5)
+        np.testing.assert_allclose(delta_minus_pa_only, expected_delta_minus_pa_only, rtol=1e-5)
 
 
 if __name__ == "__main__":
diff --git a/tests/test_predicted_ephemeris_tracker.py b/tests/test_predicted_ephemeris_tracker.py
index 7cbad336..67a4658a 100644
--- a/tests/test_predicted_ephemeris_tracker.py
+++ b/tests/test_predicted_ephemeris_tracker.py
@@ -24,8 +24,7 @@ def test_predicted_ephemeris_tracker_determines_if_function_needs_predicted_ephe
             "de440.bsp",
         ]
         spice_test_paths = [
-            str(get_integration_test_spice_data_path(file_name))
-            for file_name in spice_file_names
+            str(get_integration_test_spice_data_path(file_name)) for file_name in spice_file_names
         ]
 
         with KernelPool(spice_test_paths):
@@ -41,9 +40,7 @@ def test_predicted_ephemeris_tracker_determines_if_function_needs_predicted_ephe
                 tracker.run(imap_state, et_no_coverage, SpiceFrame.ECLIPJ2000)
             self.assertFalse(tracker.used_predict)
 
-            state2 = tracker.run(
-                imap_state, et_requiring_predict, SpiceFrame.ECLIPJ2000
-            )
+            state2 = tracker.run(imap_state, et_requiring_predict, SpiceFrame.ECLIPJ2000)
             self.assertTrue(tracker.used_predict)
 
             expected_state_no_predict = [
@@ -90,9 +87,7 @@ def requires_predict():
             self.assertEqual(1, mock_spice_function_2.call_count)
 
     def test_predicted_ephemeris_tracker_skips_retry_if_no_predict_kernel(self):
-        other_kernel = get_integration_test_spice_data_path(
-            "imap_2025_105_2026_105_01.ah.bc"
-        )
+        other_kernel = get_integration_test_spice_data_path("imap_2025_105_2026_105_01.ah.bc")
         with KernelPool([str(other_kernel)]):
             mock_spice_function_1 = Mock(side_effect=SpiceyError())
             tracker = PredictedEphemerisTracker()
diff --git a/tests/test_processor.py b/tests/test_processor.py
index 7b7b1e86..4a987bb6 100644
--- a/tests/test_processor.py
+++ b/tests/test_processor.py
@@ -3,9 +3,9 @@
 from unittest.mock import Mock, patch
 
 from imap_data_access.processing_input import (
+    AncillaryInput,
     ProcessingInputCollection,
     ScienceInput,
-    AncillaryInput,
 )
 
 from imap_l3_processing.swapi.swapi_processor import SwapiProcessor
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 8dc3ff14..1e5eb273 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -1,52 +1,52 @@
 import os
 import tempfile
-from datetime import datetime, date
+from datetime import date, datetime
 from pathlib import Path
 from unittest import TestCase
-from unittest.mock import patch, call, Mock, sentinel
+from unittest.mock import Mock, call, patch, sentinel
 
 import imap_data_access
 import numpy as np
 from imap_data_access import config
 from imap_data_access.file_validation import Version
-from imap_data_access.processing_input import ScienceInput, ProcessingInputCollection
+from imap_data_access.processing_input import ProcessingInputCollection, ScienceInput
 from imap_processing.spice.geometry import SpiceFrame
 from requests import RequestException
 from spacepy.pycdf import CDF
 
 from imap_l3_processing.constants import TEMP_CDF_FOLDER_PATH, TT2000_EPOCH
 from imap_l3_processing.maps.map_models import (
-    RectangularSpectralIndexDataProduct,
     RectangularIntensityDataProduct,
+    RectangularSpectralIndexDataProduct,
 )
 from imap_l3_processing.models import InputMetadata, VersionMap
 from imap_l3_processing.swapi.l3a.models import SwapiL3AlphaSolarWindData
 from imap_l3_processing.swapi.quality_flags import SwapiL3Flags
 from imap_l3_processing.utils import (
-    format_time,
-    read_mag_data,
-    save_data,
+    FurnishMetakernelOutput,
+    SpiceKernelTypes,
     download_external_dependency,
+    format_time,
     furnish_local_spice,
-    get_spice_parent_file_names,
     furnish_spice_metakernel,
-    SpiceKernelTypes,
-    FurnishMetakernelOutput,
-    read_cdf_parents,
     get_dependency_paths_by_descriptor,
-    get_version_from_query_result,
+    get_spice_parent_file_names,
     get_temp_cache_dir,
+    get_version_from_query_result,
+    read_cdf_parents,
+    read_mag_data,
+    save_data,
 )
 from imap_l3_processing.version import VERSION
 from tests.cdf.test_cdf_utils import TestDataProduct
 from tests.maps.test_builders import (
-    create_rectangular_spectral_index_map_data,
     create_rectangular_intensity_map_data,
+    create_rectangular_spectral_index_map_data,
 )
 from tests.test_helpers import (
+    create_mock_version_map,
     get_spice_data_path,
     with_tempdir,
-    create_mock_version_map,
 )
 
 
@@ -104,9 +104,7 @@ def test_save_data(
         )
 
         mock_science_file_path = Mock()
-        mock_science_file_path_class.generate_from_inputs.return_value = (
-            mock_science_file_path
-        )
+        mock_science_file_path_class.generate_from_inputs.return_value = mock_science_file_path
 
         expected_file_path = mock_science_file_path.construct_path.return_value
 
@@ -149,9 +147,7 @@ def test_save_data(
     @patch("imap_l3_processing.utils.ImapAttributeManager")
     @patch("imap_l3_processing.utils.date")
     @patch("imap_l3_processing.utils.write_cdf")
-    def test_save_data_adds_global_attrs_if_present(
-        self, _, mock_today, mock_attribute_manager
-    ):
+    def test_save_data_adds_global_attrs_if_present(self, _, mock_today, mock_attribute_manager):
         mock_today.today.return_value = date(2024, 9, 16)
         data_product = TestDataProduct()
         data_product.global_metadata_attrs = {
@@ -268,9 +264,7 @@ def test_save_throws_exception_if_given_cr_and_repointing(self, _, mock_today, _
     @patch("imap_l3_processing.utils.ImapAttributeManager")
     @patch("imap_l3_processing.utils.date")
     @patch("imap_l3_processing.utils.write_cdf")
-    def test_save_data_does_not_add_parent_attribute_if_empty(
-        self, mock_write_cdf, mock_today, _
-    ):
+    def test_save_data_does_not_add_parent_attribute_if_empty(self, mock_write_cdf, mock_today, _):
         mock_today.today.return_value = date(2024, 9, 16)
 
         descriptor = "descriptor"
@@ -369,9 +363,7 @@ def test_save_data_custom_path(self, mock_write_cdf, mock_today, _):
 
     @patch("imap_l3_processing.utils.write_cdf")
     @patch("imap_l3_processing.utils.ImapAttributeManager.add_global_attribute")
-    def test_save_data_procedurally_generates_map_global_metadata(
-        self, mock_add_global_attr, _
-    ):
+    def test_save_data_procedurally_generates_map_global_metadata(self, mock_add_global_attr, _):
         descriptor = "descriptor"
         input_metadata = InputMetadata(
             "ultra",
@@ -383,9 +375,7 @@ def test_save_data_procedurally_generates_map_global_metadata(
         )
 
         epoch_as_datetime = np.array([datetime(2025, 1, 1)])
-        epoch_as_int = np.array(
-            [(datetime(2025, 1, 1) - TT2000_EPOCH).total_seconds() * 1e9]
-        )
+        epoch_as_int = np.array([(datetime(2025, 1, 1) - TT2000_EPOCH).total_seconds() * 1e9])
         epoch_delta = np.array([86400 * 1e9])
 
         cases = [
@@ -396,10 +386,8 @@ def test_save_data_procedurally_generates_map_global_metadata(
         for case, epoch in cases:
             mock_add_global_attr.reset_mock()
             with self.subTest(case=case):
-                rectangular_spectral_index_map_data = (
-                    create_rectangular_spectral_index_map_data(
-                        epoch=epoch, epoch_delta=epoch_delta
-                    )
+                rectangular_spectral_index_map_data = create_rectangular_spectral_index_map_data(
+                    epoch=epoch, epoch_delta=epoch_delta
                 )
                 data_product = RectangularSpectralIndexDataProduct(
                     input_metadata=input_metadata,
@@ -523,9 +511,7 @@ def add_swapi_attrs_from_file(attr_manager, instrument, level, descriptor):
 
                 mock_write_cdf.assert_called_once()
 
-                [_file_path, _data, attribute_manager] = mock_write_cdf.call_args_list[
-                    0
-                ].args
+                [_file_path, _data, attribute_manager] = mock_write_cdf.call_args_list[0].args
 
                 global_metadata = attribute_manager.try_load_global_metadata(
                     input_metadata.logical_source
@@ -546,7 +532,9 @@ def test_format_time(self):
     @patch("imap_l3_processing.utils.requests")
     @patch("builtins.open")
     def test_download_external_dependency(self, mock_open_file, mock_requests):
-        expected_url = "https://www.spaceweather.gc.ca/solar_flux_data/daily_flux_values/fluxtable.txt"
+        expected_url = (
+            "https://www.spaceweather.gc.ca/solar_flux_data/daily_flux_values/fluxtable.txt"
+        )
         expected_filename = "f107_fluxtable.txt"
 
         mock_response = Mock(status_code=200)
@@ -565,7 +553,9 @@ def test_download_external_dependency(self, mock_open_file, mock_requests):
 
     @patch("imap_l3_processing.utils.requests")
     def test_download_external_dependency_error_case(self, mock_requests):
-        expected_url = "https://www.spaceweather.gc.ca/solar_flux_data/daily_flux_values/no_such_file.txt"
+        expected_url = (
+            "https://www.spaceweather.gc.ca/solar_flux_data/daily_flux_values/no_such_file.txt"
+        )
 
         expected_filename = "f107_fluxtable.txt"
         mock_requests.get.side_effect = RequestException
@@ -622,13 +612,7 @@ def test_furnish_local_spice(self, mock_spiceypy):
                 call(str(get_spice_data_path("imap_science_0001.tf"))),
                 call(str(get_spice_data_path("imap_science_draft.tf"))),
                 call(str(get_spice_data_path("imap_sclk_0000.tsc"))),
-                call(
-                    str(
-                        get_spice_data_path(
-                            "imap_sim_ck_2hr_2secsampling_with_nutation.bc"
-                        )
-                    )
-                ),
+                call(str(get_spice_data_path("imap_sim_ck_2hr_2secsampling_with_nutation.bc"))),
                 call(str(get_spice_data_path("imap_spk_demo.bsp"))),
                 call(str(get_spice_data_path("imap_wkcp.tf"))),
                 call(str(get_spice_data_path("pck00011.tpc"))),
@@ -656,13 +640,9 @@ def test_get_spice_parent_file_names(self, mock_spicepy):
     @patch("imap_l3_processing.utils.imap_data_access.download")
     @patch("imap_l3_processing.utils.spiceypy")
     @patch("imap_l3_processing.utils.requests")
-    def test_furnish_spice_metakernel(
-        self, mock_requests, mock_spiceypy, mock_download
-    ):
+    def test_furnish_spice_metakernel(self, mock_requests, mock_spiceypy, mock_download):
 
-        metakernel_bytes = (
-            b"\n\\begintext\n\nThis is the most up to date Metakernel as of ..."
-        )
+        metakernel_bytes = b"\n\\begintext\n\nThis is the most up to date Metakernel as of ..."
 
         mock_requests.get.side_effect = [
             Mock(content=metakernel_bytes),
@@ -692,9 +672,7 @@ def test_furnish_spice_metakernel(
                 "DATA_DIR": mock_data_dir,
                 "DATA_ACCESS_URL": mock_data_access_url,
             }
-            with patch.object(
-                imap_data_access, "config", new=fake_imap_data_access_config
-            ):
+            with patch.object(imap_data_access, "config", new=fake_imap_data_access_config):
                 actual_output = furnish_spice_metakernel(
                     start_date,
                     end_date,
@@ -724,20 +702,12 @@ def test_furnish_spice_metakernel(
                     ]
                 )
 
-                mock_download.assert_has_calls(
-                    [call("naif0012.tls"), call("imap_001.tf")]
-                )
+                mock_download.assert_has_calls([call("naif0012.tls"), call("imap_001.tf")])
 
-                expected_metakernel_path = (
-                    mock_data_dir / "metakernel" / "metakernel_file.txt"
-                )
-                self.assertEqual(
-                    metakernel_bytes, expected_metakernel_path.read_bytes()
-                )
+                expected_metakernel_path = mock_data_dir / "metakernel" / "metakernel_file.txt"
+                self.assertEqual(metakernel_bytes, expected_metakernel_path.read_bytes())
 
-                mock_spiceypy.furnsh.assert_called_once_with(
-                    str(expected_metakernel_path)
-                )
+                mock_spiceypy.furnsh.assert_called_once_with(str(expected_metakernel_path))
 
                 expected_output = FurnishMetakernelOutput(
                     metakernel_path=expected_metakernel_path,
@@ -768,30 +738,22 @@ def test_get_dependency_paths_by_descriptor(self):
             ),
             (
                 "no matching filenames for a descriptor",
-                ProcessingInputCollection(
-                    ScienceInput(filename1), ScienceInput(filename3)
-                ),
+                ProcessingInputCollection(ScienceInput(filename1), ScienceInput(filename3)),
                 ["u90", "u45"],
                 {"u45": [], "u90": [filename1, filename3]},
             ),
             (
                 "extra science file",
-                ProcessingInputCollection(
-                    ScienceInput(filename1), ScienceInput(filename4)
-                ),
+                ProcessingInputCollection(ScienceInput(filename1), ScienceInput(filename4)),
                 ["u90", "u45"],
                 {"u45": [], "u90": [filename1]},
             ),
         ]
         for case_name, input_collection, descriptors, expected_output in cases:
             with self.subTest(case_name):
-                actual_output = get_dependency_paths_by_descriptor(
-                    input_collection, descriptors
-                )
+                actual_output = get_dependency_paths_by_descriptor(input_collection, descriptors)
 
-                self.assertEqual(
-                    sorted(expected_output.keys()), sorted(actual_output.keys())
-                )
+                self.assertEqual(sorted(expected_output.keys()), sorted(actual_output.keys()))
 
                 for i, output_key in enumerate(expected_output.keys()):
                     self.assertEqual(
@@ -842,9 +804,7 @@ def test_get_version_from_query_result(self):
         }
 
         science_file_version = get_version_from_query_result(science_file_query_result)
-        ancillary_file_version = get_version_from_query_result(
-            ancillary_file_query_result
-        )
+        ancillary_file_version = get_version_from_query_result(ancillary_file_query_result)
 
         self.assertIsInstance(science_file_version, Version)
         self.assertIsInstance(ancillary_file_version, Version)
diff --git a/tests/ultra/test_models.py b/tests/ultra/test_models.py
index df4360b7..5fc5d3ff 100644
--- a/tests/ultra/test_models.py
+++ b/tests/ultra/test_models.py
@@ -6,19 +6,19 @@
 
 from imap_l3_processing.glows.l3e.glows_l3e_ultra_model import (
     ENERGY_VAR_NAME,
-    PROBABILITY_OF_SURVIVAL_VAR_NAME,
-    HEALPIX_INDEX_VAR_NAME,
     EPOCH_CDF_VAR_NAME,
     GLOWS_FLAGS_VAR_NAME,
+    HEALPIX_INDEX_VAR_NAME,
+    PROBABILITY_OF_SURVIVAL_VAR_NAME,
 )
 from imap_l3_processing.glows.quality_flags import GlowsL3Flags
 from imap_l3_processing.ultra.models import UltraGlowsL3eData, UltraL1CPSet
 from tests.spice_test_case import SpiceTestCase
 from tests.test_helpers import (
-    get_test_data_folder,
-    with_tempdir,
     get_integration_test_data_path,
+    get_test_data_folder,
     get_test_data_path,
+    with_tempdir,
 )
 
 
@@ -26,8 +26,7 @@ class TestModels(SpiceTestCase):
     @with_tempdir
     def test_glows_l3e_read_from_file(self, temp_dir):
         path_to_cdf = (
-            temp_dir
-            / "imap_glows_l3e_survival-probability-ul_20250415-repoint01000_v001.cdf"
+            temp_dir / "imap_glows_l3e_survival-probability-ul_20250415-repoint01000_v001.cdf"
         )
 
         rng = np.random.RandomState(42)
@@ -80,12 +79,8 @@ def test_ultra_l1c_read_from_file_and_can_convert_to_xarray(self):
             np.testing.assert_array_equal(
                 expected[CoordNames.ENERGY_ULTRA_L1C.value][...], actual.energy
             )
-            np.testing.assert_array_equal(
-                expected["exposure_factor"][...], actual.exposure
-            )
-            np.testing.assert_array_equal(
-                expected["epoch_delta"][...], actual.epoch_delta
-            )
+            np.testing.assert_array_equal(expected["exposure_factor"][...], actual.exposure)
+            np.testing.assert_array_equal(expected["epoch_delta"][...], actual.epoch_delta)
             np.testing.assert_array_equal(
                 expected[CoordNames.HEALPIX_INDEX.value][...], actual.healpix_index
             )
@@ -95,9 +90,7 @@ def test_ultra_l1c_read_from_file_and_can_convert_to_xarray(self):
             np.testing.assert_array_equal(
                 expected[CoordNames.AZIMUTH_L1C.value][0], actual.longitude
             )
-            np.testing.assert_array_equal(
-                expected["sensitivity"][...], actual.sensitivity
-            )
+            np.testing.assert_array_equal(expected["sensitivity"][...], actual.sensitivity)
 
     def test_ultra_l1c_convert_to_xarray(self):
         l1c_path = get_test_data_path(
diff --git a/tests/ultra/test_ultra_combined_nsp_initializer.py b/tests/ultra/test_ultra_combined_nsp_initializer.py
index 43bc6131..31c0e787 100644
--- a/tests/ultra/test_ultra_combined_nsp_initializer.py
+++ b/tests/ultra/test_ultra_combined_nsp_initializer.py
@@ -1,6 +1,6 @@
 import unittest
 from datetime import datetime
-from unittest.mock import patch, call
+from unittest.mock import call, patch
 
 from imap_data_access.file_validation import Version
 
@@ -173,24 +173,12 @@ def test_get_maps_that_should_be_produced(self, mock_read_cdf_parents):
 
                 mock_read_cdf_parents.assert_has_calls(
                     [
-                        call(
-                            "imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"
-                        ),
-                        call(
-                            "imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"
-                        ),
-                        call(
-                            "imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"
-                        ),
-                        call(
-                            "imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v002.cdf"
-                        ),
-                        call(
-                            "imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"
-                        ),
-                        call(
-                            "imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"
-                        ),
+                        call("imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                        call("imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                        call("imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"),
+                        call("imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v002.cdf"),
+                        call("imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"),
+                        call("imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"),
                         call(
                             f"imap_ultra_l3_ulc-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_{Version(major_version, 1)}.cdf"
                         ),
diff --git a/tests/ultra/test_ultra_l3_dependencies.py b/tests/ultra/test_ultra_l3_dependencies.py
index 750921d9..b54706be 100644
--- a/tests/ultra/test_ultra_l3_dependencies.py
+++ b/tests/ultra/test_ultra_l3_dependencies.py
@@ -2,15 +2,15 @@
 import unittest
 from hashlib import sha256
 from pathlib import Path
-from unittest.mock import patch, sentinel, call, Mock
+from unittest.mock import Mock, call, patch, sentinel
 
 import numpy as np
-from imap_data_access import ScienceInput, AncillaryInput, ProcessingInputCollection
+from imap_data_access import AncillaryInput, ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.ultra.ultra_l3_dependencies import (
+    UltraL3CombinedDependencies,
     UltraL3Dependencies,
     UltraL3SpectralIndexDependencies,
-    UltraL3CombinedDependencies,
     load_or_create_healpix_l2,
 )
 from imap_l3_processing.utils import clear_temp_cache, get_temp_cache_dir
@@ -21,9 +21,7 @@ class TestUltraL3Dependencies(unittest.TestCase):
     def setUp(self):
         clear_temp_cache()
 
-    @patch(
-        "imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path"
-    )
+    @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path")
     @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraL1CPSet.read_from_path")
     @patch(
         "imap_l3_processing.ultra.ultra_l3_dependencies.RectangularIntensityMapData.read_from_path"
@@ -56,9 +54,7 @@ def test_fetch_dependencies(
             "imap_glows_l3e_survival-probability-ul-sf_20201003_v003.cdf",
         ]
 
-        l2_energy_bin_group_sizes = (
-            "imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"
-        )
+        l2_energy_bin_group_sizes = "imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"
         l2_energy_bin_group_sizes_path = get_test_data_path(
             "ultra/imap_ultra_l2-energy-bin-group-sizes_20250101_v000.csv"
         )
@@ -83,9 +79,7 @@ def test_fetch_dependencies(
         ]
 
         mock_download.side_effect = returned_download_paths
-        mock_science_input_constructor.return_value = Mock(
-            descriptor="ultra-nsp-descriptor-6deg"
-        )
+        mock_science_input_constructor.return_value = Mock(descriptor="ultra-nsp-descriptor-6deg")
 
         l1c_data = [
             sentinel.ultra_l1c_data_1,
@@ -103,9 +97,7 @@ def test_fetch_dependencies(
 
         mock_ultra_l2.return_value = [sentinel.ultra_l2_healpix_map_dataset]
         mock_read_xarray_healpix.return_value = sentinel.ultra_l2_healpix_data
-        mock_read_from_path_rectangular.return_value = (
-            sentinel.ultra_l2_rectangular_data
-        )
+        mock_read_from_path_rectangular.return_value = sentinel.ultra_l2_rectangular_data
 
         dependencies = UltraL3Dependencies.fetch_dependencies(input_collection)
 
@@ -138,19 +130,13 @@ def test_fetch_dependencies(
             [call(file_path) for file_path in expected_parent_file_paths]
         )
 
-        mock_read_xarray_healpix.assert_called_once_with(
-            sentinel.ultra_l2_healpix_map_dataset
-        )
+        mock_read_xarray_healpix.assert_called_once_with(sentinel.ultra_l2_healpix_map_dataset)
         mock_read_from_path_rectangular.assert_called_once_with(sentinel.l2_map_path)
 
         self.assertEqual(l1c_data, dependencies.ultra_l1c_pset)
         self.assertEqual(glows_l3e_data, dependencies.glows_l3e_sp)
-        self.assertEqual(
-            sentinel.ultra_l2_healpix_data, dependencies.ultra_l2_healpix_map
-        )
-        self.assertEqual(
-            sentinel.ultra_l2_rectangular_data, dependencies.ultra_l2_rectangular_map
-        )
+        self.assertEqual(sentinel.ultra_l2_healpix_data, dependencies.ultra_l2_healpix_map)
+        self.assertEqual(sentinel.ultra_l2_rectangular_data, dependencies.ultra_l2_rectangular_map)
         self.assertEqual(returned_download_paths, dependencies.dependency_file_paths)
         np.testing.assert_array_equal(
             np.array([0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 46], dtype=np.uint8),
@@ -159,9 +145,7 @@ def test_fetch_dependencies(
         )
 
     @patch("imap_l3_processing.ultra.ultra_l3_dependencies.load_or_create_healpix_l2")
-    @patch(
-        "imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path"
-    )
+    @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path")
     @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraL1CPSet.read_from_path")
     @patch(
         "imap_l3_processing.ultra.ultra_l3_dependencies.RectangularIntensityMapData.read_from_path"
@@ -215,9 +199,7 @@ def test_raise_error_for_more_than_one_input_files_paths(self):
     @patch(
         "imap_l3_processing.ultra.ultra_l3_dependencies.RectangularIntensityMapData.read_from_path"
     )
-    @patch(
-        "imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path"
-    )
+    @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path")
     @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraL1CPSet.read_from_path")
     def test_from_file_paths(
         self,
@@ -247,12 +229,8 @@ def test_from_file_paths(
         )
 
         mock_read_l2_from_path.assert_called_with(ultra_l2_input_path)
-        mock_read_l1c.assert_has_calls(
-            [call(file_path) for file_path in ultra_l1c_input_paths]
-        )
-        mock_read_glows.assert_has_calls(
-            [call(file_path) for file_path in glows_input_paths]
-        )
+        mock_read_l1c.assert_has_calls([call(file_path) for file_path in ultra_l1c_input_paths])
+        mock_read_glows.assert_has_calls([call(file_path) for file_path in glows_input_paths])
         mock_load_or_create_healpix_l2.assert_called_with(
             ultra_l2_input_path, ultra_l1c_input_paths
         )
@@ -261,13 +239,9 @@ def test_from_file_paths(
             result.ultra_l1c_pset,
             [sentinel.ultra_data3, sentinel.ultra_data1, sentinel.ultra_data2],
         )
-        self.assertEqual(
-            result.glows_l3e_sp, [sentinel.glows_data1, sentinel.glows_data2]
-        )
+        self.assertEqual(result.glows_l3e_sp, [sentinel.glows_data1, sentinel.glows_data2])
         self.assertEqual(result.ultra_l2_healpix_map, sentinel.ultra_l2_healpix_data)
-        self.assertEqual(
-            result.ultra_l2_rectangular_map, sentinel.ultra_l2_rectangular_data
-        )
+        self.assertEqual(result.ultra_l2_rectangular_map, sentinel.ultra_l2_rectangular_data)
 
     @patch(
         "imap_l3_processing.ultra.ultra_l3_dependencies.HealPixIntensityMapData.read_from_xarray"
@@ -288,9 +262,7 @@ def test_load_or_create_healpix_l2_saves_to_cache(
         ]
         mock_read_l2_xarray.return_value = sentinel.ultra_l2_healpix_data
         l2_ultra_descriptor = "u45-ena-h-hf-nsp-full-hae-6deg"
-        mock_science_input_constructor.return_value = Mock(
-            descriptor=l2_ultra_descriptor
-        )
+        mock_science_input_constructor.return_value = Mock(descriptor=l2_ultra_descriptor)
         mock_ultra_l2.return_value = [sentinel.ultra_l2_healpix_map]
 
         result = load_or_create_healpix_l2(ultra_l2_input_path, ultra_l1c_input_paths)
@@ -312,9 +284,7 @@ def test_load_or_create_healpix_l2_saves_to_cache(
         self.assertEqual(result, sentinel.ultra_l2_healpix_data)
 
         temp_cache_dir = get_temp_cache_dir()
-        raw_cache_key = (
-            "['u_path_1', 'u_path_2', 'u_path_3']u45-ena-h-hf-nsp-full-hae-nside32"
-        )
+        raw_cache_key = "['u_path_1', 'u_path_2', 'u_path_3']u45-ena-h-hf-nsp-full-hae-nside32"
         cached_healpix_filename = sha256(raw_cache_key.encode("utf-8")).hexdigest()
         with open(temp_cache_dir / cached_healpix_filename, "rb") as f:
             cached_healpix = pickle.load(f)
@@ -332,9 +302,7 @@ def test_load_or_create_healpix_l2_loads_from_cache(
         mock_read_l2_xarray: Mock,
     ):
         temp_cache_dir = get_temp_cache_dir()
-        raw_cache_key = (
-            "['l1c_path_1.cdf', 'l1c_path_2.cdf']u45-ena-h-hf-nsp-full-hae-nside32"
-        )
+        raw_cache_key = "['l1c_path_1.cdf', 'l1c_path_2.cdf']u45-ena-h-hf-nsp-full-hae-nside32"
         cached_healpix_filename = sha256(raw_cache_key.encode("utf-8")).hexdigest()
         with open(temp_cache_dir / cached_healpix_filename, "wb") as f:
             pickle.dump(sentinel.ultra_l2_healpix_data, f)
@@ -344,9 +312,7 @@ def test_load_or_create_healpix_l2_loads_from_cache(
             Path("imap/l1c_path_2.cdf"),
         ]
         l2_ultra_descriptor = "u45-ena-h-hf-nsp-full-hae-6deg"
-        mock_science_input_constructor.return_value = Mock(
-            descriptor=l2_ultra_descriptor
-        )
+        mock_science_input_constructor.return_value = Mock(descriptor=l2_ultra_descriptor)
 
         result = load_or_create_healpix_l2(ultra_l2_input_path, ultra_l1c_input_paths)
 
@@ -366,12 +332,16 @@ def test_spectral_index_fetch_dependencies(
         for input_data_type in ["l2", "l3"]:
             mock_rectangular_read_from_path.reset_mock()
             with self.subTest(input_data_type):
-                map_file_name = f"imap_ultra_{input_data_type}_ultra-cool-descriptor_20250601_v000.cdf"
+                map_file_name = (
+                    f"imap_ultra_{input_data_type}_ultra-cool-descriptor_20250601_v000.cdf"
+                )
                 ancillary_file_name = "imap_ultra_spx-energy-ranges_20250601_v000.cdf"
                 pointing_set_file_name = (
                     "imap_ultra_l1c_u90spacecraftpset_20250601-repoint00001_v000.cdf"
                 )
-                glows_file_name = "imap_glows_l3e_survival-probability-ul-hf_20250601-repoint00001_v000.cdf"
+                glows_file_name = (
+                    "imap_glows_l3e_survival-probability-ul-hf_20250601-repoint00001_v000.cdf"
+                )
                 expected_energy_ranges = [[5, 15], [15, 50]]
                 map_input = ScienceInput(map_file_name)
                 ancillary_input = AncillaryInput(ancillary_file_name)
@@ -385,20 +355,14 @@ def test_spectral_index_fetch_dependencies(
 
                 mock_download.side_effect = [
                     "map_file",
-                    get_test_data_path(
-                        "ultra/imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat"
-                    ),
+                    get_test_data_path("ultra/imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat"),
                 ]
 
-                ultra_l3_dependencies = (
-                    UltraL3SpectralIndexDependencies.fetch_dependencies(
-                        processing_input_collection
-                    )
+                ultra_l3_dependencies = UltraL3SpectralIndexDependencies.fetch_dependencies(
+                    processing_input_collection
                 )
 
-                mock_download.assert_has_calls(
-                    [call(map_file_name), call(ancillary_file_name)]
-                )
+                mock_download.assert_has_calls([call(map_file_name), call(ancillary_file_name)])
                 mock_rectangular_read_from_path.assert_called_once_with("map_file")
                 self.assertEqual(
                     ultra_l3_dependencies.map_data,
@@ -409,9 +373,7 @@ def test_spectral_index_fetch_dependencies(
                 )
 
     def test_spectral_index_fetch_dependencies_raises_exception_on_missing_map(self):
-        ancillary_input = AncillaryInput(
-            "imap_ultra_spx-energy-ranges_20250601_v000.dat"
-        )
+        ancillary_input = AncillaryInput("imap_ultra_spx-energy-ranges_20250601_v000.dat")
         with self.assertRaises(ValueError) as context:
             UltraL3SpectralIndexDependencies.fetch_dependencies(
                 ProcessingInputCollection(ancillary_input)
@@ -419,9 +381,7 @@ def test_spectral_index_fetch_dependencies_raises_exception_on_missing_map(self)
         self.assertEqual("Expected 1 input map, got 0: []", str(context.exception))
 
     def test_spectral_index_fetch_dependencies_raises_exception_on_multiple_maps(self):
-        ancillary_input = AncillaryInput(
-            "imap_ultra_spx-energy-ranges_20250601_v000.dat"
-        )
+        ancillary_input = AncillaryInput("imap_ultra_spx-energy-ranges_20250601_v000.dat")
         science_input = ScienceInput("imap_ultra_l3_map_20250601_v000.cdf")
 
         with self.assertRaises(ValueError) as context:
@@ -434,17 +394,13 @@ def test_spectral_index_fetch_dependencies_raises_exception_on_multiple_maps(sel
     def test_spectral_index_fetch_dependencies_raises_exception_on_missing_ancillary_file(
         self,
     ):
-        science_input = ScienceInput(
-            "imap_ultra_l3_ultra-cool-descriptor_20250601_v000.cdf"
-        )
+        science_input = ScienceInput("imap_ultra_l3_ultra-cool-descriptor_20250601_v000.cdf")
 
         with self.assertRaises(ValueError) as context:
             UltraL3SpectralIndexDependencies.fetch_dependencies(
                 ProcessingInputCollection(science_input)
             )
-        self.assertEqual(
-            "Missing fit energy ranges ancillary file", str(context.exception)
-        )
+        self.assertEqual("Missing fit energy ranges ancillary file", str(context.exception))
 
     @patch(
         "imap_l3_processing.ultra.ultra_l3_dependencies.RectangularIntensityMapData.read_from_path"
@@ -452,8 +408,7 @@ def test_spectral_index_fetch_dependencies_raises_exception_on_missing_ancillary
     def test_spectral_index_from_file_paths(self, mock_read_from_path):
         map_file_path = Mock()
         ancillary_file_path = (
-            get_test_data_path("ultra")
-            / "imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat"
+            get_test_data_path("ultra") / "imap_ultra_ulc-spx-energy-ranges_20250407_v000.dat"
         )
         expected_energy_range_values = np.loadtxt(ancillary_file_path)
 
@@ -473,9 +428,7 @@ def test_spectral_index_get_fit_energy_ranges(self):
         )
         actual_fit_energy_ranges = dependencies.get_fit_energy_ranges()
 
-        np.testing.assert_array_equal(
-            actual_fit_energy_ranges, expected_energy_range_values
-        )
+        np.testing.assert_array_equal(actual_fit_energy_ranges, expected_energy_range_values)
 
 
 class TestUltraL3CombinedDependencies(unittest.TestCase):
@@ -702,9 +655,7 @@ def test_fetch_dependencies_without_ancillary_file(
         self.assertIsNone(combined_dependencies.u90_dependencies.energy_bin_group_sizes)
 
     @patch("imap_l3_processing.ultra.ultra_l3_dependencies.load_or_create_healpix_l2")
-    @patch(
-        "imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path"
-    )
+    @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraGlowsL3eData.read_from_path")
     @patch("imap_l3_processing.ultra.ultra_l3_dependencies.UltraL1CPSet.read_from_path")
     @patch("imap_l3_processing.ultra.ultra_l3_dependencies.imap_data_access.download")
     @patch(
@@ -721,12 +672,8 @@ def test_fetch_dependencies_with_glows_files(
         cases = [["sf", "spacecraftpset"], ["hf", "heliopset"]]
         for frame, pset in cases:
             with self.subTest(frame):
-                u45_map_file_name = (
-                    "imap_ultra_l2_u45-cool-descriptor_20250601_v000.cdf"
-                )
-                u90_map_file_name = (
-                    "imap_ultra_l2_u90-cool-descriptor_20250601_v000.cdf"
-                )
+                u45_map_file_name = "imap_ultra_l2_u45-cool-descriptor_20250601_v000.cdf"
+                u90_map_file_name = "imap_ultra_l2_u90-cool-descriptor_20250601_v000.cdf"
                 u45_pset_file_names = [
                     f"imap_ultra_l1c_45sensor-{pset}_20251010_v001.cdf",
                     f"imap_ultra_l1c_45sensor-{pset}_20251011_v001.cdf",
@@ -766,24 +713,14 @@ def test_fetch_dependencies_with_glows_files(
                     Path("imap_ultra_l1c_u90-pset_20251011_v001.cdf"),
                     Path("imap_ultra_l1c_u90-pset_20251012_v001.cdf"),
                 ]
-                u45_l2_path = Path(
-                    "imap_ultra_l2_u45-cool-descriptor_20250601_v000.cdf"
-                )
-                u90_l2_path = Path(
-                    "imap_ultra_l2_u90-cool-descriptor_20250601_v000.cdf"
-                )
+                u45_l2_path = Path("imap_ultra_l2_u45-cool-descriptor_20250601_v000.cdf")
+                u90_l2_path = Path("imap_ultra_l2_u90-cool-descriptor_20250601_v000.cdf")
                 expected_file_paths = [
                     *u45_l1c_paths,
                     *u90_l1c_paths,
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251010_v001.cdf"
-                    ),
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251011_v001.cdf"
-                    ),
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251012_v001.cdf"
-                    ),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251010_v001.cdf"),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251011_v001.cdf"),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251012_v001.cdf"),
                     u45_l2_path,
                     u90_l2_path,
                 ]
@@ -892,18 +829,10 @@ def test_fetch_dependencies_with_glows_files(
                 )
                 u45_deps = combined_dependencies.u45_dependencies
                 u90_deps = combined_dependencies.u90_dependencies
-                self.assertEqual(
-                    u45_deps.ultra_l2_healpix_map, sentinel.u45_healpix_dataset
-                )
-                self.assertEqual(
-                    u90_deps.ultra_l2_healpix_map, sentinel.u90_healpix_dataset
-                )
-                self.assertEqual(
-                    u45_deps.ultra_l2_rectangular_map, sentinel.u45_rectangular_l2
-                )
-                self.assertEqual(
-                    u90_deps.ultra_l2_rectangular_map, sentinel.u90_rectangular_l2
-                )
+                self.assertEqual(u45_deps.ultra_l2_healpix_map, sentinel.u45_healpix_dataset)
+                self.assertEqual(u90_deps.ultra_l2_healpix_map, sentinel.u90_healpix_dataset)
+                self.assertEqual(u45_deps.ultra_l2_rectangular_map, sentinel.u45_rectangular_l2)
+                self.assertEqual(u90_deps.ultra_l2_rectangular_map, sentinel.u90_rectangular_l2)
                 self.assertEqual(
                     u45_deps.ultra_l1c_pset,
                     [sentinel.u45_l1c_1, sentinel.u45_l1c_2, sentinel.u45_l1c_3],
@@ -923,32 +852,16 @@ def test_fetch_dependencies_with_glows_files(
                 expected_u45_file_paths = [
                     u45_l2_path,
                     *u45_l1c_paths,
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251010_v001.cdf"
-                    ),
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251011_v001.cdf"
-                    ),
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251012_v001.cdf"
-                    ),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251010_v001.cdf"),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251011_v001.cdf"),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251012_v001.cdf"),
                 ]
                 expected_u90_file_paths = [
                     u90_l2_path,
                     *u90_l1c_paths,
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251010_v001.cdf"
-                    ),
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251011_v001.cdf"
-                    ),
-                    Path(
-                        f"imap_glows_l3e_survival-probability-ul-{frame}_20251012_v001.cdf"
-                    ),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251010_v001.cdf"),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251011_v001.cdf"),
+                    Path(f"imap_glows_l3e_survival-probability-ul-{frame}_20251012_v001.cdf"),
                 ]
-                self.assertEqual(
-                    u45_deps.dependency_file_paths, expected_u45_file_paths
-                )
-                self.assertEqual(
-                    u90_deps.dependency_file_paths, expected_u90_file_paths
-                )
+                self.assertEqual(u45_deps.dependency_file_paths, expected_u45_file_paths)
+                self.assertEqual(u90_deps.dependency_file_paths, expected_u90_file_paths)
diff --git a/tests/ultra/test_ultra_l3_survival_probabillity.py b/tests/ultra/test_ultra_l3_survival_probabillity.py
index ffb7514b..2db1b01f 100644
--- a/tests/ultra/test_ultra_l3_survival_probabillity.py
+++ b/tests/ultra/test_ultra_l3_survival_probabillity.py
@@ -4,17 +4,17 @@
 
 import numpy as np
 from astropy_healpix import HEALPix
-from imap_processing.ena_maps.ena_maps import UltraPointingSet, HealpixSkyMap
+from imap_processing.ena_maps.ena_maps import HealpixSkyMap, UltraPointingSet
 from imap_processing.spice import geometry
 from imap_processing.ultra.constants import UltraConstants
 
 from imap_l3_processing.constants import (
-    TT2000_EPOCH,
     ONE_SECOND_IN_NANOSECONDS,
     SECONDS_PER_DAY,
+    TT2000_EPOCH,
 )
 from imap_l3_processing.glows.quality_flags import GlowsL3Flags
-from imap_l3_processing.ultra.models import UltraL1CPSet, UltraGlowsL3eData
+from imap_l3_processing.ultra.models import UltraGlowsL3eData, UltraL1CPSet
 from imap_l3_processing.ultra.science.ultra_survival_probability import (
     UltraSurvivalProbability,
     UltraSurvivalProbabilitySkyMap,
@@ -26,12 +26,8 @@ class TestUltraSurvivalProbability(unittest.TestCase):
     @patch(
         "imap_l3_processing.ultra.science.ultra_survival_probability.geometry.frame_transform_az_el"
     )
-    @patch(
-        "imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim"
-    )
-    def test_ultra_survival_probability_pset_calls_super(
-        self, _, mock_frame_transform_az_el
-    ):
+    @patch("imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim")
+    def test_ultra_survival_probability_pset_calls_super(self, _, mock_frame_transform_az_el):
         input_l1c_pset = _create_ultra_l1c_pset(np.array([2]), np.full((1, 1, 12), 1))
         glows = _build_glows_l3e_ultra()
 
@@ -46,9 +42,7 @@ def test_ultra_survival_probability_pset_calls_super(
     @patch(
         "imap_l3_processing.ultra.science.ultra_survival_probability.geometry.frame_transform_az_el"
     )
-    @patch(
-        "imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim"
-    )
+    @patch("imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim")
     @patch.object(UltraConstants, "PSET_ENERGY_BIN_EDGES", new=[0.5, 1.5, 4])
     def test_ultra_survival_probability_rotates_to_glows_frame(
         self, mock_unitim, mock_frame_transform_az_el
@@ -85,17 +79,13 @@ def test_ultra_survival_probability_rotates_to_glows_frame(
                 ]
             ]
         )
-        survival_probability_times_exposure = prod.data[
-            "survival_probability_times_exposure"
-        ]
+        survival_probability_times_exposure = prod.data["survival_probability_times_exposure"]
         np.testing.assert_array_equal(
             survival_probability_times_exposure.values,
             expected_survival_probabilities_values,
         )
 
-    @patch(
-        "imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim"
-    )
+    @patch("imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim")
     @patch(
         "imap_l3_processing.ultra.science.ultra_survival_probability.geometry.frame_transform_az_el"
     )
@@ -115,20 +105,14 @@ def test_ultra_survival_probability_is_multiplied_by_exposure(
 
         prod = UltraSurvivalProbability(input_l1c_pset, glows, bin_groups=[0, 1])
 
-        expected_survival_probabilities_values = np.array(
-            [[[2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0]]]
-        )
-        survival_probability_times_exposure = prod.data[
-            "survival_probability_times_exposure"
-        ]
+        expected_survival_probabilities_values = np.array([[[2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0]]])
+        survival_probability_times_exposure = prod.data["survival_probability_times_exposure"]
         np.testing.assert_array_equal(
             survival_probability_times_exposure.values,
             expected_survival_probabilities_values,
         )
 
-    @patch(
-        "imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim"
-    )
+    @patch("imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim")
     @patch(
         "imap_l3_processing.ultra.science.ultra_survival_probability.geometry.frame_transform_az_el"
     )
@@ -166,8 +150,7 @@ def test_ultra_survival_probability_pset_includes_quality_flags(
                 expected_flagged,
             ),
             (
-                GlowsL3Flags.PREDICTIVE_EPHEMERIS
-                | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
+                GlowsL3Flags.PREDICTIVE_EPHEMERIS | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
                 expected_flagged,
                 expected_flagged,
                 expected_unflagged,
@@ -179,8 +162,7 @@ def test_ultra_survival_probability_pset_includes_quality_flags(
                 expected_flagged,
             ),
             (
-                GlowsL3Flags.PERSISTED_LAST_POINT
-                | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
+                GlowsL3Flags.PERSISTED_LAST_POINT | GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO,
                 expected_unflagged,
                 expected_flagged,
                 expected_flagged,
@@ -212,13 +194,9 @@ def test_ultra_survival_probability_pset_includes_quality_flags(
                     flags=flag,
                 )
 
-                mock_frame_transform_az_el.side_effect = lambda et, az_el, to, _from: (
-                    az_el
-                )
+                mock_frame_transform_az_el.side_effect = lambda et, az_el, to, _from: az_el
 
-                prod = UltraSurvivalProbability(
-                    input_l1c_pset, glows, bin_groups=[0, 1]
-                )
+                prod = UltraSurvivalProbability(input_l1c_pset, glows, bin_groups=[0, 1])
 
                 np.testing.assert_array_equal(
                     prod.data["predicted_ephemeris_flag"], expected_predicted_ephem_flag
@@ -240,9 +218,7 @@ def test_ultra_survival_probability_pset_includes_quality_flags(
                     prod.data["survival_probability_times_exposure"].dims,
                 )
 
-    @patch(
-        "imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim"
-    )
+    @patch("imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim")
     @patch(
         "imap_l3_processing.ultra.science.ultra_survival_probability.geometry.frame_transform_az_el"
     )
@@ -264,17 +240,13 @@ def test_ultra_survival_probability_interpolates_over_energy(
         prod = UltraSurvivalProbability(input_l1c_pset, glows, bin_groups=[0, 1, 2])
 
         expected_survival_probabilities_values = np.array([[[2] * 12, [4] * 12]])
-        survival_probability_times_exposure = prod.data[
-            "survival_probability_times_exposure"
-        ]
+        survival_probability_times_exposure = prod.data["survival_probability_times_exposure"]
         np.testing.assert_array_equal(
             survival_probability_times_exposure.values,
             expected_survival_probabilities_values,
         )
 
-    @patch(
-        "imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim"
-    )
+    @patch("imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim")
     @patch(
         "imap_l3_processing.ultra.science.ultra_survival_probability.geometry.frame_transform_az_el"
     )
@@ -288,9 +260,7 @@ def test_ultra_survival_probability_combines_fine_energy_bins(
     ):
         glows_energies = np.array([1, 100, 10000])
         ultra_energies = np.array([10, 10, 10, 10, 1000, 1000, 1000, 1000])
-        input_l1c_pset = _create_ultra_l1c_pset(
-            ultra_energies, np.full((1, 2 * 4, 12), 1)
-        )
+        input_l1c_pset = _create_ultra_l1c_pset(ultra_energies, np.full((1, 2 * 4, 12), 1))
         glows_surv_prob = np.array([[[1] * 12, [3] * 12, [5] * 12]])
 
         glows = _build_glows_l3e_ultra(
@@ -302,17 +272,13 @@ def test_ultra_survival_probability_combines_fine_energy_bins(
         prod = UltraSurvivalProbability(input_l1c_pset, glows)
 
         expected_survival_probabilities_values = np.array([[[2] * 12, [4] * 12]])
-        survival_probability_times_exposure = prod.data[
-            "survival_probability_times_exposure"
-        ]
+        survival_probability_times_exposure = prod.data["survival_probability_times_exposure"]
         np.testing.assert_array_equal(
             survival_probability_times_exposure.values,
             expected_survival_probabilities_values,
         )
 
-    @patch(
-        "imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim"
-    )
+    @patch("imap_l3_processing.ultra.science.ultra_survival_probability.spiceypy.unitim")
     @patch(
         "imap_l3_processing.ultra.science.ultra_survival_probability.geometry.frame_transform_az_el"
     )
@@ -388,9 +354,7 @@ def test_ultra_survival_probability_handles_different_resolutions(
                 ]
             ]
         )
-        survival_probability_times_exposure = prod.data[
-            "survival_probability_times_exposure"
-        ]
+        survival_probability_times_exposure = prod.data["survival_probability_times_exposure"]
         np.testing.assert_array_almost_equal(
             survival_probability_times_exposure.values,
             expected_survival_probabilities_values,
@@ -406,24 +370,19 @@ def test_ultra_survival_probability_skymap(self):
         l3e_sp_1 = np.full((1, 1, pointing_set_pixels), 0.5)
         l3e_sp_2 = np.full((1, 1, pointing_set_pixels), 0.25)
         glows_energies = np.array([1])
-        l1c_1 = _create_ultra_l1c_pset(
-            energy=np.array([1]), exposure_factor=l1c_exposure_1
-        )
+        l1c_1 = _create_ultra_l1c_pset(energy=np.array([1]), exposure_factor=l1c_exposure_1)
         l3e_glows_1 = _build_glows_l3e_ultra(
             survival_probabilities=l3e_sp_1,
             energies=glows_energies,
             nside=pointing_set_nside,
             flags=GlowsL3Flags.PREDICTIVE_EPHEMERIS,
         )
-        l1c_2 = _create_ultra_l1c_pset(
-            energy=np.array([1]), exposure_factor=l1c_exposure_2
-        )
+        l1c_2 = _create_ultra_l1c_pset(energy=np.array([1]), exposure_factor=l1c_exposure_2)
         l3e_glows_2 = _build_glows_l3e_ultra(
             survival_probabilities=l3e_sp_2,
             energies=glows_energies,
             nside=pointing_set_nside,
-            flags=GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO
-            | GlowsL3Flags.PERSISTED_LAST_POINT,
+            flags=GlowsL3Flags.NOMINAL_ALPHA_PROTON_RATIO | GlowsL3Flags.PERSISTED_LAST_POINT,
         )
 
         pset_1 = UltraSurvivalProbability(l1c_1, l3e_glows_1, bin_groups=[0, 1])
@@ -466,17 +425,13 @@ def test_ultra_survival_probability_skymap_ignores_nan_survival_probabilities(se
         l3e_sp_1 = np.full((1, 1, pointing_set_pixels), 0.5)
         l3e_sp_2 = np.full((1, 1, pointing_set_pixels), np.nan)
         glows_energies = np.array([1])
-        l1c_1 = _create_ultra_l1c_pset(
-            energy=np.array([1]), exposure_factor=l1c_exposure_1
-        )
+        l1c_1 = _create_ultra_l1c_pset(energy=np.array([1]), exposure_factor=l1c_exposure_1)
         l3e_glows_1 = _build_glows_l3e_ultra(
             survival_probabilities=l3e_sp_1,
             energies=glows_energies,
             nside=pointing_set_nside,
         )
-        l1c_2 = _create_ultra_l1c_pset(
-            energy=np.array([1]), exposure_factor=l1c_exposure_2
-        )
+        l1c_2 = _create_ultra_l1c_pset(energy=np.array([1]), exposure_factor=l1c_exposure_2)
         l3e_glows_2 = _build_glows_l3e_ultra(
             survival_probabilities=l3e_sp_2,
             energies=glows_energies,
@@ -521,7 +476,7 @@ def _build_glows_l3e_ultra(
     healpix_pixels = np.arange(num_pixels)
 
     healpix_grid = HEALPix(nside)
-    lon, lat = healpix_grid.healpix_to_lonlat(healpix_pixels)
+    _lon, _lat = healpix_grid.healpix_to_lonlat(healpix_pixels)
 
     return UltraGlowsL3eData(
         epoch=datetime.now(),
@@ -540,7 +495,7 @@ def _create_ultra_l1c_pset(
     counts: np.ndarray = None,
     latitude: np.ndarray = None,
     longitude: np.ndarray = None,
-    epoch: datetime = None,
+    epoch: datetime | None = None,
     epoch_delta: int = ONE_SECOND_IN_NANOSECONDS * SECONDS_PER_DAY,
 ):
     epoch = datetime(2025, 10, 1, 0) if epoch is None else epoch
diff --git a/tests/ultra/test_ultra_l3_to_rectangular_dependencies.py b/tests/ultra/test_ultra_l3_to_rectangular_dependencies.py
index ec2d1be0..124ac9f5 100644
--- a/tests/ultra/test_ultra_l3_to_rectangular_dependencies.py
+++ b/tests/ultra/test_ultra_l3_to_rectangular_dependencies.py
@@ -1,7 +1,7 @@
 import unittest
-from unittest.mock import patch, call
+from unittest.mock import call, patch
 
-from imap_data_access import ScienceInput, ProcessingInputCollection
+from imap_data_access import ProcessingInputCollection, ScienceInput
 
 from imap_l3_processing.ultra.ultra_l3_to_rectangular_dependencies import (
     UltraL3ToRectangularDependencies,
@@ -22,10 +22,8 @@ def test_fetch_dependencies(self, mock_download, mock_healpix_read_from_path):
             "map_file",
         ]
 
-        ultra_l3_to_rectangular_dependencies = (
-            UltraL3ToRectangularDependencies.fetch_dependencies(
-                processing_input_collection
-            )
+        ultra_l3_to_rectangular_dependencies = UltraL3ToRectangularDependencies.fetch_dependencies(
+            processing_input_collection
         )
 
         mock_download.assert_has_calls(
diff --git a/tests/ultra/test_ultra_processor.py b/tests/ultra/test_ultra_processor.py
index 447d4b6e..95b2dec0 100644
--- a/tests/ultra/test_ultra_processor.py
+++ b/tests/ultra/test_ultra_processor.py
@@ -3,41 +3,41 @@
 from datetime import datetime, timedelta
 from hashlib import sha256
 from pathlib import Path
-from unittest.mock import patch, sentinel, call, Mock
+from unittest.mock import Mock, call, patch, sentinel
 
 import numpy as np
 import xarray as xr
 from imap_data_access.processing_input import (
     AncillaryInput,
-    ScienceInput,
     ProcessingInputCollection,
+    ScienceInput,
 )
 from imap_processing.ena_maps.ena_maps import RectangularSkyMap
 from imap_processing.ena_maps.utils.coordinates import CoordNames
 from imap_processing.spice.geometry import SpiceFrame
 
 from imap_l3_processing.maps.map_models import (
+    HealPixCoords,
     HealPixIntensityMapData,
     IntensityMapData,
-    HealPixCoords,
-    SpectralIndexMapData,
     RectangularIntensityDataProduct,
+    RectangularIntensityMapData,
     RectangularSpectralIndexDataProduct,
     RectangularSpectralIndexMapData,
-    RectangularIntensityMapData,
+    SpectralIndexMapData,
 )
 from imap_l3_processing.maps.quality_flags import MapL3Flags
 from imap_l3_processing.models import InputMetadata
 from imap_l3_processing.ultra.ultra_l3_dependencies import (
+    UltraL3CombinedDependencies,
     UltraL3Dependencies,
     UltraL3SpectralIndexDependencies,
-    UltraL3CombinedDependencies,
 )
 from imap_l3_processing.ultra.ultra_processor import (
     UltraProcessor,
     correct_healpix_data_for_survival_probability,
 )
-from imap_l3_processing.utils import get_temp_cache_dir, clear_temp_cache
+from imap_l3_processing.utils import clear_temp_cache, get_temp_cache_dir
 from tests.maps.test_builders import create_rectangular_intensity_map_data
 from tests.test_helpers import get_test_data_path
 
@@ -68,9 +68,7 @@ def test_process_combined_survival_corrected_all_spacings(self):
 
     @patch("imap_l3_processing.ultra.ultra_processor.UltraSurvivalProbabilitySkyMap")
     @patch("imap_l3_processing.ultra.ultra_processor.UltraSurvivalProbability")
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.combine_glows_l3e_with_l1c_pointing"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.combine_glows_l3e_with_l1c_pointing")
     def test_correct_healpix_data_for_survival_probability(
         self,
         mock_combine_glows_l3e_with_l1c_pointing,
@@ -116,9 +114,7 @@ def test_correct_healpix_data_for_survival_probability(
             sentinel.pset_3,
         ]
         computed_survival_probabilities = rng.random((1, 9, healpix_indices.shape[0]))
-        expected_quality_flags = np.full(
-            (1, 9, healpix_indices.shape[0]), MapL3Flags.NONE
-        )
+        expected_quality_flags = np.full((1, 9, healpix_indices.shape[0]), MapL3Flags.NONE)
         expected_quality_flags[rng.random((1, 9, healpix_indices.shape[0])) > 0.8] = (
             MapL3Flags.PREDICTIVE_EPHEMERIS
         )
@@ -209,15 +205,11 @@ def test_correct_healpix_data_for_survival_probability(
             computed_survival_probabilities,
         )
 
-        np.testing.assert_array_equal(
-            actual_intensity_map_data.epoch, intensity_data.epoch
-        )
+        np.testing.assert_array_equal(actual_intensity_map_data.epoch, intensity_data.epoch)
         np.testing.assert_array_equal(
             actual_intensity_map_data.epoch_delta, intensity_data.epoch_delta
         )
-        np.testing.assert_array_equal(
-            actual_intensity_map_data.energy, intensity_data.energy
-        )
+        np.testing.assert_array_equal(actual_intensity_map_data.energy, intensity_data.energy)
         np.testing.assert_array_equal(
             actual_intensity_map_data.energy_delta_plus,
             intensity_data.energy_delta_plus,
@@ -229,18 +221,14 @@ def test_correct_healpix_data_for_survival_probability(
         np.testing.assert_array_equal(
             actual_intensity_map_data.energy_label, intensity_data.energy_label
         )
-        np.testing.assert_array_equal(
-            actual_intensity_map_data.latitude, intensity_data.latitude
-        )
+        np.testing.assert_array_equal(actual_intensity_map_data.latitude, intensity_data.latitude)
         np.testing.assert_array_equal(
             actual_intensity_map_data.longitude, intensity_data.longitude
         )
         np.testing.assert_array_equal(
             actual_intensity_map_data.exposure_factor, intensity_data.exposure_factor
         )
-        np.testing.assert_array_equal(
-            actual_intensity_map_data.obs_date, intensity_data.obs_date
-        )
+        np.testing.assert_array_equal(actual_intensity_map_data.obs_date, intensity_data.obs_date)
         np.testing.assert_array_equal(
             actual_intensity_map_data.obs_date_range, intensity_data.obs_date_range
         )
@@ -251,9 +239,7 @@ def test_correct_healpix_data_for_survival_probability(
             actual_intensity_map_data.quality_flags, expected_quality_flags
         )
         coords = healpix_intensity_map_data.coords
-        np.testing.assert_array_equal(
-            coords.pixel_index, input_l2_healpix_map.coords.pixel_index
-        )
+        np.testing.assert_array_equal(coords.pixel_index, input_l2_healpix_map.coords.pixel_index)
         np.testing.assert_array_equal(
             coords.pixel_index_label, input_l2_healpix_map.coords.pixel_index_label
         )
@@ -261,9 +247,7 @@ def test_correct_healpix_data_for_survival_probability(
     @patch("imap_l3_processing.ultra.ultra_processor.HealPixIntensityMapData")
     @patch("imap_l3_processing.ultra.ultra_processor.UltraSurvivalProbabilitySkyMap")
     @patch("imap_l3_processing.ultra.ultra_processor.UltraSurvivalProbability")
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.combine_glows_l3e_with_l1c_pointing"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.combine_glows_l3e_with_l1c_pointing")
     def test_correct_healpix_data_for_survival_probability_caches_results(
         self,
         mock_combine_glows_l3e_with_l1c_pointing,
@@ -271,9 +255,7 @@ def test_correct_healpix_data_for_survival_probability_caches_results(
         mock_survival_skymap,
         mock_healpix_intensity_map_data,
     ):
-        mock_healpix_intensity_map_data.return_value = (
-            sentinel.healpix_intensity_map_data
-        )
+        mock_healpix_intensity_map_data.return_value = sentinel.healpix_intensity_map_data
         rng = np.random.default_rng()
         healpix_indices = np.arange(12)
 
@@ -345,9 +327,7 @@ def test_correct_healpix_data_for_survival_probability_caches_results(
             f"['{input_glows_l3e_name_1}', '{input_glows_l3e_name_2}']"
             "a-map-descriptor-nside32"
         )
-        expected_cache_path = (
-            cache_dir / sha256(expected_cache_key.encode("utf-8")).hexdigest()
-        )
+        expected_cache_path = cache_dir / sha256(expected_cache_key.encode("utf-8")).hexdigest()
 
         with open(expected_cache_path, "rb") as f:
             cached_data = pickle.load(f)
@@ -357,9 +337,7 @@ def test_correct_healpix_data_for_survival_probability_caches_results(
     @patch("imap_l3_processing.ultra.ultra_processor.HealPixIntensityMapData")
     @patch("imap_l3_processing.ultra.ultra_processor.UltraSurvivalProbabilitySkyMap")
     @patch("imap_l3_processing.ultra.ultra_processor.UltraSurvivalProbability")
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.combine_glows_l3e_with_l1c_pointing"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.combine_glows_l3e_with_l1c_pointing")
     def test_correct_healpix_data_for_survival_probability_uses_cached_result(
         self,
         mock_combine_glows_l3e_with_l1c_pointing,
@@ -379,9 +357,7 @@ def test_correct_healpix_data_for_survival_probability_uses_cached_result(
             f"['{input_glows_l3e_name_1}', '{input_glows_l3e_name_2}']"
             "a-map-descriptor-nside32"
         )
-        expected_cache_path = (
-            cache_dir / sha256(expected_cache_key.encode("utf-8")).hexdigest()
-        )
+        expected_cache_path = cache_dir / sha256(expected_cache_key.encode("utf-8")).hexdigest()
         cached_result = sentinel.healpix_intensity_map_data
 
         with open(expected_cache_path, "wb") as f:
@@ -429,9 +405,7 @@ def test_correct_healpix_data_for_survival_probability_uses_cached_result(
     )
     @patch("imap_l3_processing.utils.spiceypy")
     @patch("imap_l3_processing.ultra.ultra_processor.save_data")
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.UltraL3Dependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.UltraL3Dependencies.fetch_dependencies")
     def _test_process_survival_probability(
         self,
         degree_spacing,
@@ -481,12 +455,8 @@ def _test_process_survival_probability(
         )
 
         rectangular_predicted_ephemeris_data = np.array([0.73, 0.24, 0, 0.99, 1, 0])
-        nominal_alpha_proton_ratio_data = np.full_like(
-            rectangular_predicted_ephemeris_data, 0.0
-        )
-        persisted_last_point_data = np.full_like(
-            rectangular_predicted_ephemeris_data, 0.0
-        )
+        nominal_alpha_proton_ratio_data = np.full_like(rectangular_predicted_ephemeris_data, 0.0)
+        persisted_last_point_data = np.full_like(rectangular_predicted_ephemeris_data, 0.0)
 
         expected_quality_flags = np.array(
             [
@@ -499,9 +469,7 @@ def _test_process_survival_probability(
             ]
         )
 
-        mock_healpix_map_data = (
-            mock_correct_healpix_data_for_survival_probability.return_value
-        )
+        mock_healpix_map_data = mock_correct_healpix_data_for_survival_probability.return_value
         mock_healpix_skymap = Mock()
         mock_healpix_map_data.to_healpix_skymap = Mock(return_value=mock_healpix_skymap)
 
@@ -510,18 +478,10 @@ def _test_process_survival_probability(
             "ena_intensity_stat_uncert": Mock(
                 values=sentinel.rectangular_ena_intensity_stat_uncert
             ),
-            "ena_intensity_sys_err": Mock(
-                values=sentinel.rectangular_ena_intensity_sys_err
-            ),
-            "survival_probability": Mock(
-                values=sentinel.rectangular_survival_probability
-            ),
-            "predicted_ephemeris_flag": Mock(
-                values=rectangular_predicted_ephemeris_data
-            ),
-            "nominal_alpha_proton_ratio_flag": Mock(
-                values=nominal_alpha_proton_ratio_data
-            ),
+            "ena_intensity_sys_err": Mock(values=sentinel.rectangular_ena_intensity_sys_err),
+            "survival_probability": Mock(values=sentinel.rectangular_survival_probability),
+            "predicted_ephemeris_flag": Mock(values=rectangular_predicted_ephemeris_data),
+            "nominal_alpha_proton_ratio_flag": Mock(values=nominal_alpha_proton_ratio_data),
             "persisted_last_point_flag": Mock(values=persisted_last_point_data),
         }
 
@@ -555,9 +515,7 @@ def _test_process_survival_probability(
 
         mock_save_data.assert_called_once()
         actual_rectangular_data_product = mock_save_data.call_args_list[0].args[0]
-        self.assertIsInstance(
-            actual_rectangular_data_product, RectangularIntensityDataProduct
-        )
+        self.assertIsInstance(actual_rectangular_data_product, RectangularIntensityDataProduct)
         self.assertEqual(4, len(actual_rectangular_data_product.parent_file_names))
         self.assertEqual(
             {
@@ -568,13 +526,9 @@ def _test_process_survival_probability(
             },
             set(actual_rectangular_data_product.parent_file_names),
         )
-        self.assertEqual(
-            SpiceFrame.IMAP_GCS, actual_rectangular_data_product.spice_frame_name
-        )
+        self.assertEqual(SpiceFrame.IMAP_GCS, actual_rectangular_data_product.spice_frame_name)
         actual_rectangular_data = actual_rectangular_data_product.data
-        self.assertIsInstance(
-            actual_rectangular_data.intensity_map_data, IntensityMapData
-        )
+        self.assertIsInstance(actual_rectangular_data.intensity_map_data, IntensityMapData)
 
         # @formatter:off
         self.assertEqual(
@@ -600,9 +554,7 @@ def _test_process_survival_probability(
         )
 
         expected_passthrough = input_l2_rectangular_map.intensity_map_data
-        self.assertIs(
-            expected_passthrough.epoch, actual_rectangular_data.intensity_map_data.epoch
-        )
+        self.assertIs(expected_passthrough.epoch, actual_rectangular_data.intensity_map_data.epoch)
         self.assertIs(
             expected_passthrough.epoch_delta,
             actual_rectangular_data.intensity_map_data.epoch_delta,
@@ -669,9 +621,7 @@ def _test_process_survival_probability(
 
         self.assertEqual([mock_save_data.return_value], product)
 
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.MapProcessor.get_parent_file_names"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.MapProcessor.get_parent_file_names")
     @patch("imap_l3_processing.ultra.ultra_processor.ExposureWeightedCombination")
     @patch("imap_l3_processing.ultra.ultra_processor.save_data")
     @patch(
@@ -731,9 +681,7 @@ def _test_process_combined_sensor(
         )
 
         predicted_ephemeris_rectangular_values = np.array([0.243, 0, 1, 0, 0.993, 0])
-        nominal_alpha_proton_ratio_rectangular_values = np.array(
-            [0, 0.34, 0.8, 0, 0, 0]
-        )
+        nominal_alpha_proton_ratio_rectangular_values = np.array([0, 0.34, 0.8, 0, 0, 0])
         persisted_last_point_rectangular_values = np.array([0, 0, 0.4, 0, 0, 1])
 
         expected_quality_flags = np.array(
@@ -753,18 +701,12 @@ def _test_process_combined_sensor(
             "ena_intensity_stat_uncert": Mock(
                 values=sentinel.rectangular_ena_intensity_stat_uncert
             ),
-            "ena_intensity_sys_err": Mock(
-                values=sentinel.rectangular_ena_intensity_sys_err
-            ),
-            "predicted_ephemeris_flag": Mock(
-                values=predicted_ephemeris_rectangular_values
-            ),
+            "ena_intensity_sys_err": Mock(values=sentinel.rectangular_ena_intensity_sys_err),
+            "predicted_ephemeris_flag": Mock(values=predicted_ephemeris_rectangular_values),
             "nominal_alpha_proton_ratio_flag": Mock(
                 values=nominal_alpha_proton_ratio_rectangular_values
             ),
-            "persisted_last_point_flag": Mock(
-                values=persisted_last_point_rectangular_values
-            ),
+            "persisted_last_point_flag": Mock(values=persisted_last_point_rectangular_values),
         }
 
         processor = UltraProcessor(sentinel.dependencies, input_metadata)
@@ -849,9 +791,7 @@ def _test_process_combined_sensor(
     @patch(
         "imap_l3_processing.ultra.ultra_processor.UltraProcessor._process_healpix_intensity_to_rectangular"
     )
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.MapProcessor.get_parent_file_names"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.MapProcessor.get_parent_file_names")
     @patch("imap_l3_processing.ultra.ultra_processor.UncertaintyWeightedCombination")
     @patch("imap_l3_processing.ultra.ultra_processor.save_data")
     @patch(
@@ -984,9 +924,7 @@ def _test_process_combined_sensor_survival_probability(
     )
     @patch("imap_l3_processing.utils.spiceypy")
     @patch("imap_l3_processing.ultra.ultra_processor.save_data")
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.UltraL3Dependencies.fetch_dependencies"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.UltraL3Dependencies.fetch_dependencies")
     def test_defaults_to_ECLIPJ2000_spice_frame(
         self,
         mock_fetch_dependencies,
@@ -1045,15 +983,9 @@ def test_defaults_to_ECLIPJ2000_spice_frame(
 
         mock_rectangular_map_dataset = {
             "ena_intensity": Mock(values=sentinel.rectangular_ena_intensity),
-            "ena_intensity_stat_uncert": Mock(
-                values=sentinel.rectangular_ena_intensity_stat_unc
-            ),
-            "ena_intensity_sys_err": Mock(
-                values=sentinel.rectangular_ena_intensity_sys_err
-            ),
-            "survival_probability": Mock(
-                values=sentinel.rectangular_survival_probability
-            ),
+            "ena_intensity_stat_uncert": Mock(values=sentinel.rectangular_ena_intensity_stat_unc),
+            "ena_intensity_sys_err": Mock(values=sentinel.rectangular_ena_intensity_sys_err),
+            "survival_probability": Mock(values=sentinel.rectangular_survival_probability),
             "predicted_ephemeris_flag": Mock(values=np.array([])),
             "nominal_alpha_proton_ratio_flag": Mock(values=np.array([])),
             "persisted_last_point_flag": Mock(values=np.array([])),
@@ -1075,9 +1007,7 @@ def test_defaults_to_ECLIPJ2000_spice_frame(
 
     @patch("imap_l3_processing.utils.spiceypy")
     @patch("imap_l3_processing.ultra.ultra_processor.save_data")
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.calculate_spectral_index_for_multiple_ranges"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.calculate_spectral_index_for_multiple_ranges")
     @patch(
         "imap_l3_processing.ultra.ultra_processor.UltraL3SpectralIndexDependencies.fetch_dependencies"
     )
@@ -1107,9 +1037,7 @@ def _test_process_spectral_index(
             descriptor=f"u90-spx-h-sf-sp-full-hae-{degree_spacing}deg-6mo",
         )
         input_map_data = RectangularIntensityMapData(Mock(), Mock())
-        dependencies = UltraL3SpectralIndexDependencies(
-            input_map_data, sentinel.energy_ranges
-        )
+        dependencies = UltraL3SpectralIndexDependencies(input_map_data, sentinel.energy_ranges)
         mock_fetch_dependencies.return_value = dependencies
 
         mock_spectral_index_map_data = Mock(spec=SpectralIndexMapData)
@@ -1122,23 +1050,15 @@ def _test_process_spectral_index(
 
         mock_save_data.assert_called_once()
         actual_rectangular_data_product = mock_save_data.call_args_list[0].args[0]
-        self.assertIsInstance(
-            actual_rectangular_data_product, RectangularSpectralIndexDataProduct
-        )
+        self.assertIsInstance(actual_rectangular_data_product, RectangularSpectralIndexDataProduct)
         self.assertEqual(
             expected_parent_file_names,
             actual_rectangular_data_product.parent_file_names,
         )
-        self.assertEqual(
-            processor.input_metadata, actual_rectangular_data_product.input_metadata
-        )
-        self.assertEqual(
-            SpiceFrame.ECLIPJ2000, actual_rectangular_data_product.spice_frame_name
-        )
+        self.assertEqual(processor.input_metadata, actual_rectangular_data_product.input_metadata)
+        self.assertEqual(SpiceFrame.ECLIPJ2000, actual_rectangular_data_product.spice_frame_name)
 
-        self.assertIsInstance(
-            actual_rectangular_data_product, RectangularSpectralIndexDataProduct
-        )
+        self.assertIsInstance(actual_rectangular_data_product, RectangularSpectralIndexDataProduct)
 
         actual_rectangular_data: RectangularSpectralIndexMapData = (
             actual_rectangular_data_product.data
@@ -1160,9 +1080,7 @@ def _test_process_spectral_index(
 
     @patch("imap_l3_processing.ultra.ultra_processor.save_data")
     @patch("imap_l3_processing.utils.spiceypy")
-    @patch(
-        "imap_l3_processing.ultra.ultra_processor.calculate_spectral_index_for_multiple_ranges"
-    )
+    @patch("imap_l3_processing.ultra.ultra_processor.calculate_spectral_index_for_multiple_ranges")
     @patch("imap_l3_processing.ultra.ultra_processor.fit_spectral_index_map")
     @patch("imap_l3_processing.ultra.ultra_processor.slice_energy_range_by_bin")
     @patch(
@@ -1258,17 +1176,15 @@ def test_process_spectral_index_validating_output_values(
         )
         mock_fetch_dependencies.return_value = dependencies
 
-        expected_ena_spectral_index = np.array(
-            [2] * (60 * 30) + [3.5] * (60 * 30)
-        ).reshape(1, 2, 60, 30)
+        expected_ena_spectral_index = np.array([2] * (60 * 30) + [3.5] * (60 * 30)).reshape(
+            1, 2, 60, 30
+        )
 
         processing_input_collection = ProcessingInputCollection()
         processor = UltraProcessor(processing_input_collection, input_metadata)
         product = processor.process()
 
-        actual_data_product: RectangularSpectralIndexDataProduct = (
-            mock_save_data.call_args[0][0]
-        )
+        actual_data_product: RectangularSpectralIndexDataProduct = mock_save_data.call_args[0][0]
 
         np.testing.assert_array_almost_equal(
             actual_data_product.data.spectral_index_map_data.ena_spectral_index,
@@ -1292,18 +1208,14 @@ def _create_ultra_l2_healpix_data(
     lat = lat if lat is not None else np.array([1.0])
     healpix_indices = healpix_indices if healpix_indices is not None else np.arange(12)
     energy = energy if energy is not None else np.array([1.0])
-    energy_delta = (
-        energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
-    )
+    energy_delta = energy_delta if energy_delta is not None else np.full((len(energy), 2), 1)
     flux = (
         flux
         if flux is not None
         else np.full((len(epoch), len(energy), len(healpix_indices)), fill_value=1)
     )
     intensity_stat_uncert = (
-        intensity_stat_unc
-        if intensity_stat_unc is not None
-        else np.full(flux.shape, fill_value=1)
+        intensity_stat_unc if intensity_stat_unc is not None else np.full(flux.shape, fill_value=1)
     )
 
     if isinstance(flux, np.ndarray):
diff --git a/tests/ultra/test_ultra_sp_initializer.py b/tests/ultra/test_ultra_sp_initializer.py
index 0323217e..071f0f3c 100644
--- a/tests/ultra/test_ultra_sp_initializer.py
+++ b/tests/ultra/test_ultra_sp_initializer.py
@@ -1,19 +1,19 @@
 import unittest
 from datetime import datetime
-from unittest.mock import patch, call
+from unittest.mock import call, patch
 
 from imap_data_access.file_validation import Version
 
 from imap_l3_processing.glows.descriptors import (
-    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
     GLOWS_L3E_ULTRA_HF_DESCRIPTOR,
+    GLOWS_L3E_ULTRA_SF_DESCRIPTOR,
 )
 from imap_l3_processing.maps.map_initializer import PossibleMapToProduce
 from imap_l3_processing.maps.sp_map_initializer import SPMapInitializer
 from imap_l3_processing.models import InputMetadata, VersionMap
 from imap_l3_processing.ultra.ultra_sp_initializer import (
-    UltraSPInitializer,
     ULTRA_SP_SPICE_KERNELS,
+    UltraSPInitializer,
 )
 from tests.integration.integration_test_helpers import ImapQueryPatcher
 
@@ -188,9 +188,7 @@ def test_get_maps_that_should_be_produced(self, mock_read_cdf_parents):
                 self.assertEqual(2, len(actual_maps_to_produce))
 
     @patch("imap_l3_processing.maps.map_initializer.read_cdf_parents")
-    def test_get_maps_that_should_be_produced_lists_combined_maps(
-        self, mock_read_cdf_parents
-    ):
+    def test_get_maps_that_should_be_produced_lists_combined_maps(self, mock_read_cdf_parents):
         self.mock_query.side_effect = ImapQueryPatcher(
             [
                 "imap_glows_l3e_survival-probability-ul-sf_20100101-repoint00001_v001.cdf",
@@ -320,36 +318,16 @@ def test_get_maps_that_should_be_produced_lists_combined_maps(
 
         mock_read_cdf_parents.assert_has_calls(
             [
-                call(
-                    "imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l3_ulc-ena-h-sf-sp-full-hae-4deg-3mo_20100101_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l3_ulc-ena-h-sf-sp-full-hae-4deg-3mo_20100401_v001.cdf"
-                ),
+                call("imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                call("imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"),
+                call("imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"),
+                call("imap_ultra_l2_u45-ena-h-sf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-sf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"),
+                call("imap_ultra_l3_ulc-ena-h-sf-sp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                call("imap_ultra_l3_ulc-ena-h-sf-sp-full-hae-4deg-3mo_20100401_v001.cdf"),
             ]
         )
         descriptor = "ulc-ena-h-sf-sp-full-hae-4deg-3mo"
@@ -382,9 +360,7 @@ def test_get_maps_that_should_be_produced_lists_combined_maps(
         self.assertEqual(2, len(actual_maps_to_produce))
 
     @patch("imap_l3_processing.maps.map_initializer.read_cdf_parents")
-    def test_get_maps_that_should_be_produced_lists_cg_corrected_maps(
-        self, mock_read_cdf_parents
-    ):
+    def test_get_maps_that_should_be_produced_lists_cg_corrected_maps(self, mock_read_cdf_parents):
         self.mock_query.side_effect = ImapQueryPatcher(
             [
                 "imap_glows_l3e_survival-probability-ul-hf_20100101-repoint00001_v001.cdf",
@@ -514,36 +490,16 @@ def test_get_maps_that_should_be_produced_lists_cg_corrected_maps(
 
         mock_read_cdf_parents.assert_has_calls(
             [
-                call(
-                    "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l3_ulc-ena-h-hf-sp-full-hae-4deg-3mo_20100101_v001.cdf"
-                ),
-                call(
-                    "imap_ultra_l3_ulc-ena-h-hf-sp-full-hae-4deg-3mo_20100401_v001.cdf"
-                ),
+                call("imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                call("imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20100401_v001.cdf"),
+                call("imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20100701_v001.cdf"),
+                call("imap_ultra_l2_u45-ena-h-hf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"),
+                call("imap_ultra_l2_u90-ena-h-hf-nsp-full-hae-4deg-3mo_20101001_v001.cdf"),
+                call("imap_ultra_l3_ulc-ena-h-hf-sp-full-hae-4deg-3mo_20100101_v001.cdf"),
+                call("imap_ultra_l3_ulc-ena-h-hf-sp-full-hae-4deg-3mo_20100401_v001.cdf"),
             ]
         )
 
diff --git a/uv.lock b/uv.lock
index e7be1f08..7ca5b9b3 100644
--- a/uv.lock
+++ b/uv.lock
@@ -575,6 +575,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/36/41/04e2a649058b0713b00d6c9bd22da35618bb157289e05d068e51fddf8d7e/dunamai-1.25.0-py3-none-any.whl", hash = "sha256:7f9dc687dd3256e613b6cc978d9daabfd2bb5deb8adc541fc135ee423ffa98ab", size = 27022, upload-time = "2025-07-04T19:25:54.863Z" },
 ]
 
+[[package]]
+name = "et-xmlfile"
+version = "2.0.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/d3/38/af70d7ab1ae9d4da450eeec1fa3918940a5fafb9055e934af8d6eb0c2313/et_xmlfile-2.0.0.tar.gz", hash = "sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54", size = 17234, upload-time = "2024-10-25T17:25:40.039Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c1/8b/5fe2cc11fee489817272089c4203e679c63b570a5aaeb18d852ae3cbba6a/et_xmlfile-2.0.0-py3-none-any.whl", hash = "sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa", size = 18059, upload-time = "2024-10-25T17:25:39.051Z" },
+]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.3.1"
@@ -605,15 +614,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/01/a4/9b63d595d748e3aff8812b65eacc1a2c4bd90b7c2012e08e72373b4835eb/filelock-3.32.4-py3-none-any.whl", hash = "sha256:22e58ca3b1ae3b98993b762d7338367ae64fe50252bf78d59da3bfebcdf1cedd", size = 99864, upload-time = "2026-08-23T17:37:53.913Z" },
 ]
 
-[[package]]
-name = "et-xmlfile"
-version = "2.0.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/d3/38/af70d7ab1ae9d4da450eeec1fa3918940a5fafb9055e934af8d6eb0c2313/et_xmlfile-2.0.0.tar.gz", hash = "sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54", size = 17234, upload-time = "2024-10-25T17:25:40.039Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/c1/8b/5fe2cc11fee489817272089c4203e679c63b570a5aaeb18d852ae3cbba6a/et_xmlfile-2.0.0-py3-none-any.whl", hash = "sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa", size = 18059, upload-time = "2024-10-25T17:25:39.051Z" },
-]
-
 [[package]]
 name = "fonttools"
 version = "4.61.1"
@@ -828,7 +828,7 @@ requires-dist = [
     { name = "pytest", marker = "extra == 'test'", specifier = ">=8.3" },
     { name = "pytest-xdist", marker = "extra == 'test'", specifier = ">=3.6" },
     { name = "requests", specifier = "==2.32.3" },
-    { name = "ruff", marker = "extra == 'dev'", specifier = "==0.15.2" },
+    { name = "ruff", marker = "extra == 'dev'", specifier = "==0.16.10" },
     { name = "sammi-cdf", specifier = "==1.0.0" },
     { name = "scikit-learn", specifier = "==1.6.1" },
     { name = "scipy", specifier = ">=1.13.1" },
@@ -1941,27 +1941,27 @@ wheels = [
 
 [[package]]
 name = "ruff"
-version = "0.15.2"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/06/04/eab13a954e763b0606f460443fcbf6bb5a0faf06890ea3754ff16523dce5/ruff-0.15.2.tar.gz", hash = "sha256:14b965afee0969e68bb871eba625343b8673375f457af4abe98553e8bbb98342", size = 4558148, upload-time = "2026-02-19T22:32:20.271Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/2f/70/3a4dc6d09b13cb3e695f28307e5d889b2e1a66b7af9c5e257e796695b0e6/ruff-0.15.2-py3-none-linux_armv6l.whl", hash = "sha256:120691a6fdae2f16d65435648160f5b81a9625288f75544dc40637436b5d3c0d", size = 10430565, upload-time = "2026-02-19T22:32:41.824Z" },
-    { url = "https://files.pythonhosted.org/packages/71/0b/bb8457b56185ece1305c666dc895832946d24055be90692381c31d57466d/ruff-0.15.2-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:a89056d831256099658b6bba4037ac6dd06f49d194199215befe2bb10457ea5e", size = 10820354, upload-time = "2026-02-19T22:32:07.366Z" },
-    { url = "https://files.pythonhosted.org/packages/2d/c1/e0532d7f9c9e0b14c46f61b14afd563298b8b83f337b6789ddd987e46121/ruff-0.15.2-py3-none-macosx_11_0_arm64.whl", hash = "sha256:e36dee3a64be0ebd23c86ffa3aa3fd3ac9a712ff295e192243f814a830b6bd87", size = 10170767, upload-time = "2026-02-19T22:32:13.188Z" },
-    { url = "https://files.pythonhosted.org/packages/47/e8/da1aa341d3af017a21c7a62fb5ec31d4e7ad0a93ab80e3a508316efbcb23/ruff-0.15.2-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a9fb47b6d9764677f8c0a193c0943ce9a05d6763523f132325af8a858eadc2b9", size = 10529591, upload-time = "2026-02-19T22:32:02.547Z" },
-    { url = "https://files.pythonhosted.org/packages/93/74/184fbf38e9f3510231fbc5e437e808f0b48c42d1df9434b208821efcd8d6/ruff-0.15.2-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f376990f9d0d6442ea9014b19621d8f2aaf2b8e39fdbfc79220b7f0c596c9b80", size = 10260771, upload-time = "2026-02-19T22:32:36.938Z" },
-    { url = "https://files.pythonhosted.org/packages/05/ac/605c20b8e059a0bc4b42360414baa4892ff278cec1c91fff4be0dceedefd/ruff-0.15.2-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2dcc987551952d73cbf5c88d9fdee815618d497e4df86cd4c4824cc59d5dd75f", size = 11045791, upload-time = "2026-02-19T22:32:31.642Z" },
-    { url = "https://files.pythonhosted.org/packages/fd/52/db6e419908f45a894924d410ac77d64bdd98ff86901d833364251bd08e22/ruff-0.15.2-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:42a47fd785cbe8c01b9ff45031af875d101b040ad8f4de7bbb716487c74c9a77", size = 11879271, upload-time = "2026-02-19T22:32:29.305Z" },
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