fix(epistemic): return the validated assignment without rounding

src/argumentation/probabilistic/epistemic.py

@@ -944,10 +944,9 @@ def update_assignment(
                 changed = True
     if not belief_assignment_satisfies(graph, assignment):
         raise ValueError("updated assignment cannot satisfy the graph constraints")
-    return {
-        argument: round(assignment[argument], 12)
-        for argument in sorted(graph.arguments)
-    }
+    # Return exactly the validated values: rounding here could move a value
+    # across an exact constraint bound after validation.
+    return {argument: assignment[argument] for argument in sorted(graph.arguments)}
 
 
 def project_to_constellation_praf(graph: EpistemicGraph) -> ProbabilisticAF:

tests/probabilistic/test_epistemic.py

@@ -74,7 +74,11 @@ def test_update_assignment_clamps_evidence_and_propagates_fragment() -> None:
         ),
     )
 
-    assert update_assignment(graph, {"a": 0.8}) == {"a": 0.8, "b": 0.8, "c": 0.2}
+    # Values are returned exactly as validated (issue #16), so c is the float
+    # 1 - 0.8 rather than a rounded 0.2.
+    assert update_assignment(graph, {"a": 0.8}) == pytest.approx(
+        {"a": 0.8, "b": 0.8, "c": 0.2}
+    )
 
 
 def test_update_assignment_respects_explicit_belief_constraints() -> None:

tests/probabilistic/test_epistemic_contracts.py

@@ -20,6 +20,7 @@
 from argumentation.probabilistic.epistemic import (
     AndTerm,
     ArgumentTerm,
+    BeliefConstraint,
     EpistemicGraph,
     Influence,
     InfluenceKind,
@@ -30,6 +31,7 @@
     OrTerm,
     ProbabilityTerm,
     Term,
+    belief_assignment_satisfies,
     least_squares_update_labelling,
     parse_term,
     update_assignment,
@@ -164,6 +166,43 @@ def tracer(frame: FrameType, event: str, arg: object) -> object:
         sys.settrace(None)
 
 
+@pytest.mark.parametrize(
+    "influences",
+    [(), (Influence("a", "b", InfluenceKind.NEGATIVE),)],
+    ids=["exact-bound", "negative-influence-from-exact-bound"],
+)
+def test_update_assignment_returns_values_that_satisfy_exact_bounds(
+    influences: tuple[Influence, ...],
+) -> None:
+    """Issue #16: the returned assignment must satisfy the graph constraints
+    (Hunter & Thimm 2017 epistemic constraints), including an exact bound
+    finer than 12 decimal places and a negative influence ``b <= 1 - a``
+    computed from it."""
+    value = 0.1234567890123
+    graph = EpistemicGraph(
+        frozenset({"a", "b"}),
+        influences=frozenset(influences),
+        constraints=(BeliefConstraint("a", value, value),),
+    )
+
+    result = update_assignment(graph, {})
+
+    assert result["a"] == value
+    assert belief_assignment_satisfies(graph, result)
+
+
+def test_update_assignment_coarse_bound_control() -> None:
+    """Control: a bound with few decimals is returned unchanged."""
+    graph = EpistemicGraph(
+        frozenset({"a"}), constraints=(BeliefConstraint("a", 0.25, 0.25),)
+    )
+
+    result = update_assignment(graph, {})
+
+    assert result == {"a": 0.25}
+    assert belief_assignment_satisfies(graph, result)
+
+
 def test_update_assignment_rejects_contradictory_influences() -> None:
     """Issue #42: with P(a) = 0.8, a positive influence a -> b demands
     P(b) >= 0.8 and a negative one demands P(b) <= 0.2 (Hunter & Thimm 2017