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Enhance ROC Curve Display Tests for Improved Clarity and Maintainability #31254

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Enhance ROC Curve Display Tests for Improved Clarity and Maintainability #31254

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61b9e1f
Replace filtered data fixture with synthetic binary dataset
NEREUScode Apr 25, 2025
e299bf6
Update test_roc_curve_display.py
NEREUScode Apr 25, 2025
7ab9430
Update test_roc_curve_display.py
NEREUScode Apr 25, 2025
4cfe688
Replace filtered data fixture with synthetic binary dataset
NEREUScode Apr 25, 2025
e8b1e45
update the data_binary and delete the data()
NEREUScode Apr 28, 2025
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25 changes: 12 additions & 13 deletions sklearn/metrics/_plot/tests/test_roc_curve_display.py
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Original file line number Diff line number Diff line change
@@ -1,11 +1,11 @@
import numpy as np
import pytest
from numpy.testing import assert_allclose
from scipy.integrate import trapezoid
from scipy.integrate import trapz as trapezoid

from sklearn import clone
from sklearn.compose import make_column_transformer
from sklearn.datasets import load_breast_cancer, load_iris
from sklearn.datasets import load_breast_cancer, make_classification
from sklearn.exceptions import NotFittedError
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import RocCurveDisplay, auc, roc_curve
Expand All @@ -16,20 +16,19 @@


@pytest.fixture(scope="module")
def data():
X, y = load_iris(return_X_y=True)
# Avoid introducing test dependencies by mistake.
X.flags.writeable = False
y.flags.writeable = False
def data_binary():
X, y = make_classification(
n_samples=200,
n_features=20,
n_informative=5,
Comment on lines +22 to +23
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Not sure if we need that many features (and so many uninformative ones), but I will leave to another maintainer to determine.

n_redundant=2,
flip_y=0.1,
class_sep=0.8,
random_state=42,
)
return X, y


@pytest.fixture(scope="module")
def data_binary(data):
X, y = data
return X[y < 2], y[y < 2]


@pytest.mark.parametrize("response_method", ["predict_proba", "decision_function"])
@pytest.mark.parametrize("with_sample_weight", [True, False])
@pytest.mark.parametrize("drop_intermediate", [True, False])
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