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test: Add data_source parameter tests for ROC curve and ComparisonReport #1817

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test: Add data_source parameter tests for ROC curve and ComparisonReport
sobiya-22 Jun 9, 2025
7c08f39
removed unnecessary comments, fixed lint errors
sobiya-22 Jun 11, 2025
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76 changes: 76 additions & 0 deletions skore/tests/unit/sklearn/plot/roc_curve/test_comparison_cross_validation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -232,3 +232,79 @@ def test_multiclass_classification_kwargs(pyplot, multiclass_classification_repo
display.plot(despine=False)
assert display.ax_[0].spines["top"].get_visible()
assert display.ax_[0].spines["right"].get_visible()


def test_data_source_binary_classification(pyplot, binary_classification_data_no_split):
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@MarieSacksick MarieSacksick Jun 26, 2025

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Can you check that the results when changing the data_source do change please?
For instance, you can use a subsample of X and y when giving the data source X_y so you don't have to create a new one, and then check that the dataframes display.frame() outputed are different with assert not and the equals function.

"""
Test passing data_source to ROC plot in ComparisonReport with CrossValidationReport
"""
estimator, X, y = binary_classification_data_no_split
estimator_1 = LogisticRegression()
estimator_2 = LogisticRegression(C=10)

report = ComparisonReport(
reports={
"estimator_1": CrossValidationReport(estimator_1, X, y),
"estimator_2": CrossValidationReport(estimator_2, X, y),
}
)

display = report.metrics.roc(data_source="X_y", X=X, y=y)
assert display.data_source == "X_y"
display.plot()

display = report.metrics.roc(data_source="train")
assert display.data_source == "train"
display.plot()

display = report.metrics.roc(data_source="test")
assert display.data_source == "test"
display.plot()

n_reports = len(report.reports_)
n_splits = report.reports_[0]._cv_splitter.n_splits
expected_auc_entries = n_reports * n_splits

assert len(display.roc_auc) == expected_auc_entries
auc_values = display.roc_auc["roc_auc"].values
assert all(0 <= auc <= 1 for auc in auc_values)


def test_data_source_multiclass_classification(
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@MarieSacksick MarieSacksick Jun 26, 2025

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Same as above, can you check that the outputs are different please?

pyplot, multiclass_classification_data_no_split
):
"Test data_source in ROC plot for ComparisonReport with multiclass and CV report"
estimator, X, y = multiclass_classification_data_no_split
estimator_1 = LogisticRegression()
estimator_2 = LogisticRegression(C=10)

report = ComparisonReport(
reports={
"estimator_1": CrossValidationReport(estimator_1, X, y),
"estimator_2": CrossValidationReport(estimator_2, X, y),
}
)

class_labels = np.unique(y)

display = report.metrics.roc(data_source="X_y", X=X, y=y)
assert display.data_source == "X_y"
display.plot()

display = report.metrics.roc(data_source="train")
assert display.data_source == "train"
display.plot()

display = report.metrics.roc(data_source="test")
assert display.data_source == "test"
display.plot()

n_reports = len(report.reports_)
n_splits = report.reports_[0]._cv_splitter.n_splits
n_classes = len(class_labels)
expected_combinations = n_reports * n_classes * n_splits

assert len(display.roc_auc) == expected_combinations

auc_values = display.roc_auc["roc_auc"].values
assert all(0 <= auc <= 1 for auc in auc_values)
86 changes: 86 additions & 0 deletions skore/tests/unit/sklearn/plot/roc_curve/test_comparison_estimator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -141,6 +141,92 @@ def test_multiclass_classification(pyplot, multiclass_classification_data):
assert display.ax_.get_title() == "ROC Curve"


def test_data_source_binary_classification(pyplot, binary_classification_data):
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@MarieSacksick MarieSacksick Jun 26, 2025

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same as in previous file: checking that the outputs are different.

"""Test data_source in ROC plot for ComparisonReport."""
estimator, X_train, X_test, y_train, y_test = binary_classification_data
estimator_2 = clone(estimator).set_params(C=10).fit(X_train, y_train)

report = ComparisonReport(
reports={
"estimator_1": EstimatorReport(
estimator,
X_train=X_train,
y_train=y_train,
X_test=X_test,
y_test=y_test,
),
"estimator_2": EstimatorReport(
estimator_2,
X_train=X_train,
y_train=y_train,
X_test=X_test,
y_test=y_test,
),
}
)

display = report.metrics.roc(data_source="X_y", X=X_train, y=y_train)
assert display.data_source == "X_y"
display.plot()

display = report.metrics.roc(data_source="train")
assert display.data_source == "train"
display.plot()

display = report.metrics.roc(data_source="test")
assert display.data_source == "test"
display.plot()

train_auc = display.roc_auc["roc_auc"].values
assert len(train_auc) == 2
assert all(0 <= auc <= 1 for auc in train_auc)


def test_data_source_multiclass_classification(pyplot, multiclass_classification_data):
"""Test data_source in ROC plot for ComparisonReport with multiclass data"""
estimator, X_train, X_test, y_train, y_test = multiclass_classification_data
estimator_2 = clone(estimator).set_params(C=10).fit(X_train, y_train)

report = ComparisonReport(
reports={
"estimator_1": EstimatorReport(
estimator,
X_train=X_train,
y_train=y_train,
X_test=X_test,
y_test=y_test,
),
"estimator_2": EstimatorReport(
estimator_2,
X_train=X_train,
y_train=y_train,
X_test=X_test,
y_test=y_test,
),
}
)

class_labels = report.reports_[0].estimator_.classes_

display = report.metrics.roc(data_source="X_y", X=X_train, y=y_train)
assert display.data_source == "X_y"
display.plot()

display = report.metrics.roc(data_source="train")
assert display.data_source == "train"
display.plot()

display = report.metrics.roc(data_source="test")
assert display.data_source == "test"
display.plot()

expected_combinations = len(report.report_names_) * len(class_labels)
assert len(display.roc_auc) == expected_combinations

auc_values = display.roc_auc["roc_auc"].values
assert all(0 <= auc <= 1 for auc in auc_values)


def test_binary_classification_kwargs(pyplot, binary_classification_data):
"""Check that we can pass keyword arguments to the ROC curve plot for
cross-validation."""
Expand Down
10 changes: 10 additions & 0 deletions skore/tests/unit/sklearn/plot/roc_curve/test_estimator.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,7 @@ def test_binary_classification(pyplot, binary_classification_data):
assert display.ax_.get_aspect() in ("equal", 1.0)
assert display.ax_.get_xlim() == display.ax_.get_ylim() == (-0.01, 1.01)
assert display.ax_.get_title() == "ROC Curve for LogisticRegression"
assert display.data_source == "test"


def test_multiclass_classification(pyplot, multiclass_classification_data):
Expand Down Expand Up @@ -108,6 +109,7 @@ def test_multiclass_classification(pyplot, multiclass_classification_data):
assert display.ax_.get_aspect() in ("equal", 1.0)
assert display.ax_.get_xlim() == display.ax_.get_ylim() == (-0.01, 1.01)
assert display.ax_.get_title() == "ROC Curve for LogisticRegression"
assert display.data_source == "test"


def test_data_source_binary_classification(pyplot, binary_classification_data):
Expand All @@ -116,6 +118,14 @@ def test_data_source_binary_classification(pyplot, binary_classification_data):
report = EstimatorReport(
estimator, X_train=X_train, y_train=y_train, X_test=X_test, y_test=y_test
)
display = report.metrics.roc(data_source="X_y", X=X_train, y=y_train)
assert display.data_source == "X_y"
display.plot()
assert (
display.lines_[0].get_label()
== f"AUC = {display.roc_auc['roc_auc'].item():0.2f}"
)

display = report.metrics.roc(data_source="train")
display.plot()
assert (
Expand Down