Skip to content

Fix report crash when a cohort has subgroups and unequal model coverage #3

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
aRealGem wants to merge 2 commits into
base: main
Choose a base branch
from
Draft

Fix report crash when a cohort has subgroups and unequal model coverage #3

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
8519ecd
evaluate: fix coverage_delta duplicating rows when subgroups and ragg…
claude Oct 6, 2026
92359fc
tests: regression test for coverage_delta with subgroups and ragged c…
claude Oct 7, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
11 changes: 8 additions & 3 deletions src/predval/evaluate.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -95,9 +95,14 @@ def coverage_delta(metrics: pd.DataFrame) -> pd.DataFrame:
# As-published only: coverage restriction is a property of rung0, and mixing recalibrated
# rungs into the pivot would compare corrections rather than the effect of the common subset.
primary = metrics[(metrics["ci_method"] != "naive_row_bootstrap") & (metrics["rung"] == RUNG0)]
wide = primary.pivot_table(
index=keys, columns="subset", values="value", aggfunc="first", dropna=False
).reset_index()
# groupby, not pivot_table: pivot_table(dropna=False) takes the cartesian product of the index
# levels, inventing (overall, perturbation=dialect, ...) rows that duplicate each model_id.
wide = (
primary.groupby([*keys, "subset"], dropna=False, observed=True)["value"]
.first()
.unstack("subset")
.reset_index()
)
if "full" not in wide or "common" not in wide:
return pd.DataFrame(columns=[*keys, "cov_delta"])
wide["cov_delta"] = wide["full"] - wide["common"]
Expand Down
16 changes: 16 additions & 0 deletions tests/test_evaluate.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -242,6 +242,22 @@ def test_coverage_delta_is_zero_when_coverage_is_identical(result) -> None:
assert np.allclose(finite, 0.0), "full == common here, so every delta must be zero"


def test_coverage_delta_has_one_overall_row_per_model_with_ragged_coverage(tmp_path: Path) -> None:
"""Subgroups plus unequal coverage must not multiply the overall rows (report.py indexes them).

pivot_table(dropna=False) crossed the index levels, inventing overall rows carrying subgroup
levels; _primary_rows then got a Series back from .get() and crashed rendering the report.
"""
cohort, preds = build(tmp_path, drop_for_weak=40)
delta = coverage_delta(evaluate(cohort, preds).metrics)
overall = delta[(delta["stratum_kind"] == "overall") & (delta["metric"] == "auroc")]
assert sorted(overall["model_id"]) == sorted(MODELS)
assert overall["subgroup_name"].isna().all()
by_model = overall.set_index("model_id")["cov_delta"]
assert by_model["weak"] == 0.0, "weak's own rows define the common subset"
assert np.isfinite(by_model["good"]) and by_model["good"] != 0.0, "good loses rows to common"


# -------------------------------------------------------------------------------- the manifest


Expand Down