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TST: enforce proper sklearn __init__ for classifiers #112

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Merged
sdtemple merged 1 commit into from
Aug 12, 2026
Merged

TST: enforce proper sklearn __init__ for classifiers #112

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21 changes: 21 additions & 0 deletions src/gfdl/tests/test_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -440,6 +440,27 @@ def test_sklearn_api_conformance(estimator, check):
check(estimator)


@pytest.mark.parametrize("estimator", [
GFDLClassifier, EnsembleGFDLClassifier
])
def test_preserve_class_inputs(estimator):
# see: gh-111
clf = estimator(seed=0)
actual = clf.get_params()
expected = {"activation": "identity",
"hidden_layer_sizes": (100,),
"reg_alpha": None,
"rtol": None,
"seed": 0,
"voting": "soft",
"weight_scheme": "uniform",
"direct_links": True}
for k, v in actual.items():
if k in expected:
assert v == expected[k]
assert isinstance(v, type(expected[k]))
Comment on lines +458 to +461

@greptile-apps greptile-apps Bot Jun 8, 2026

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P2 Shared expected dict silently skips class-specific params

The loop iterates over actual.items() and only validates a key when it appears in both actual and expected. Because the same dict is used for both estimators, direct_links (present in GFDLClassifier but not in EnsembleGFDLClassifier) and voting (present in EnsembleGFDLClassifier but not in GFDLClassifier) each sit as a "dead" entry in expected for the other estimator — they will never be reached in that estimator's test run. This means a reader scanning expected cannot tell which keys are actually validated for which estimator without checking both __init__ signatures. Consider using per-estimator expected dicts, or iterating over expected.items() and guarding with if k in actual, so that omissions are explicit rather than silent.



@pytest.mark.parametrize("reg_alpha, rtol, expected_acc, expected_roc", [
(0.1, 1e-15, 0.9083333333333333, 0.9893414717354735),
(None, 1e-15, 0.2222222222222222, 0.5518850599798965),
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