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TST use global_random_seed in sklearn/metrics/tests/test_classification.py #30851

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Merged
merged 18 commits into from
Mar 3, 2025
Merged

TST use global_random_seed in sklearn/metrics/tests/test_classification.py #30851

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dba519d
add global_random_seed to test_matthews_corrcoef_against_numpy_corrcoef
Rishab260 Feb 18, 2025
f6137f7
add global_random_seed to test_matthews_corrcoef_against_jurman
Rishab260 Feb 18, 2025
81740a3
add global_random_seed to test_matthews_corrcoef
Rishab260 Feb 18, 2025
d8b2584
add global_random_seed to test_matthews_corrcoef_multiclass
Rishab260 Feb 18, 2025
2e14c8f
add global_random_seed to test_matthews_corrcoef_overflow
Rishab260 Feb 18, 2025
459de87
add global_random_seed to test_classification_metric_pos_label_types
Rishab260 Feb 18, 2025
af92257
add global_random_seed to make_prediction
Rishab260 Feb 18, 2025
734ab6c
Undo add global_random_seed to make_prediction
Rishab260 Feb 18, 2025
282b3af
test_classification [all random seeds]
Rishab260 Feb 18, 2025
f0596c4
Merge branch 'scikit-learn:main' into test_classification
Rishab260 Feb 18, 2025
c639742
Merge branch 'main' into test_classification
Rishab260 Feb 20, 2025
3040942
Merge branch 'main' into test_classification
Rishab260 Feb 20, 2025
faea2e5
Merge branch 'main' into test_classification
Rishab260 Feb 22, 2025
05f25e8
Update sklearn/metrics/tests/test_classification.py
Rishab260 Feb 22, 2025
f342409
Update sklearn/metrics/tests/test_classification.py
Rishab260 Feb 22, 2025
025b9c7
test_classification [all random seeds]
Rishab260 Mar 2, 2025
2f154b3
Merge branch 'main' into test_classification
Rishab260 Mar 2, 2025
371d82d
test_classification [all random seeds]
Rishab260 Mar 2, 2025
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20 changes: 10 additions & 10 deletions sklearn/metrics/tests/test_classification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -970,8 +970,8 @@ def test_zero_division_nan_warning(metric, y_true, y_pred):
assert result == 0.0


def test_matthews_corrcoef_against_numpy_corrcoef():
rng = np.random.RandomState(0)
def test_matthews_corrcoef_against_numpy_corrcoef(global_random_seed):
rng = np.random.RandomState(global_random_seed)
y_true = rng.randint(0, 2, size=20)
y_pred = rng.randint(0, 2, size=20)

Expand All @@ -980,11 +980,11 @@ def test_matthews_corrcoef_against_numpy_corrcoef():
)


def test_matthews_corrcoef_against_jurman():
def test_matthews_corrcoef_against_jurman(global_random_seed):
# Check that the multiclass matthews_corrcoef agrees with the definition
# presented in Jurman, Riccadonna, Furlanello, (2012). A Comparison of MCC
# and CEN Error Measures in MultiClass Prediction
rng = np.random.RandomState(0)
rng = np.random.RandomState(global_random_seed)
y_true = rng.randint(0, 2, size=20)
y_pred = rng.randint(0, 2, size=20)
sample_weight = rng.rand(20)
Expand Down Expand Up @@ -1019,8 +1019,8 @@ def test_matthews_corrcoef_against_jurman():
assert_almost_equal(mcc_ours, mcc_jurman, 10)


def test_matthews_corrcoef():
rng = np.random.RandomState(0)
def test_matthews_corrcoef(global_random_seed):
rng = np.random.RandomState(global_random_seed)
y_true = ["a" if i == 0 else "b" for i in rng.randint(0, 2, size=20)]

# corrcoef of same vectors must be 1
Expand Down Expand Up @@ -1054,8 +1054,8 @@ def test_matthews_corrcoef():
assert_almost_equal(matthews_corrcoef(y_1, y_2, sample_weight=mask), 0.0)


def test_matthews_corrcoef_multiclass():
rng = np.random.RandomState(0)
def test_matthews_corrcoef_multiclass(global_random_seed):
rng = np.random.RandomState(global_random_seed)
ord_a = ord("a")
n_classes = 4
y_true = [chr(ord_a + i) for i in rng.randint(0, n_classes, size=20)]
Expand Down Expand Up @@ -1111,9 +1111,9 @@ def test_matthews_corrcoef_multiclass():


@pytest.mark.parametrize("n_points", [100, 10000])
def test_matthews_corrcoef_overflow(n_points):
def test_matthews_corrcoef_overflow(n_points, global_random_seed):
# https://github.com/scikit-learn/scikit-learn/issues/9622
rng = np.random.RandomState(20170906)
rng = np.random.RandomState(global_random_seed)

def mcc_safe(y_true, y_pred):
conf_matrix = confusion_matrix(y_true, y_pred)
Expand Down