docs: add point density maps example - #19
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New examples/point_density.ipynb documenting render_points(density=, density_how=) (#679), previously undocumented. Uses the full 10x Xenium breast-cancer sample (~43M transcripts, SpatialData sandbox), fetched via pooch and read with sd.read_zarr. Covers: - the overplotting problem (markers on a cropped 2 mm^2 window) - density=True -> a datashader count-density heatmap of all transcripts - density_how (linear/log/eq_hist) reshaping the intensity mapping - per-category density via a categorical color + groups - the parameters density ignores (size/transfunc/norm limits/datashader_reduction) Executed against spatialdata-plot v0.4.1; committed with outputs. Adds the examples gallery card + toctree + thumbnail. Closes P0.2 of the doc-coverage analysis. Note: this notebook downloads ~3.6 GB (the Xenium zarr). Consider excluding it from the weekly execute-all cron, or gating it, to keep CI light.
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Summary
Adds
examples/point_density.ipynbdocumentingrender_points(density=, density_how=)(#679) — a v0.4.0 feature with no prior tutorial.Uses the full 10x Xenium breast-cancer sample (Janesick et al., SpatialData sandbox) — ~43 million transcripts — so the density maps are dense, smooth surfaces that resolve ducts and tumour nests (the small
squidpy.datasets.cellscrop, only 19k transcripts, was too sparse to show the feature).Covers:
density=True→ a datashader count-density heatmap of all transcriptsdensity_how(linear/log/eq_hist) reshaping the intensity mappingcolor+groupssize,transfunc,normlimits,datashader_reduction)Data is fetched via
pooch.retrieve(hash-pinned) +sd.read_zarr. Executed against spatialdata-plot v0.4.1, committed with outputs. Adds the examples gallery card + toctree + thumbnail.Part of the documentation-expansion series from the 0.4.0/0.4.1 gap analysis (P0.2).