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TST use global_random_seed in sklearn/feature_extraction/tests/test_image.py #31310

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Merged
merged 3 commits into from
Jun 13, 2025
Merged

TST use global_random_seed in sklearn/feature_extraction/tests/test_image.py #31310

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ee0f591
tests: use global_random_seed in sklearn/feature_extraction/tests/tes…
TheAyos May 5, 2025
d74af20
fix linting errors
TheAyos May 5, 2025
a99ee25
[all random seeds]
jeremiedbb Jun 13, 2025
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26 changes: 15 additions & 11 deletions sklearn/feature_extraction/tests/test_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -223,21 +223,23 @@ def test_reconstruct_patches_perfect_color(orange_face):
np.testing.assert_array_almost_equal(face, face_reconstructed)


def test_patch_extractor_fit(downsampled_face_collection):
def test_patch_extractor_fit(downsampled_face_collection, global_random_seed):
faces = downsampled_face_collection
extr = PatchExtractor(patch_size=(8, 8), max_patches=100, random_state=0)
extr = PatchExtractor(
patch_size=(8, 8), max_patches=100, random_state=global_random_seed
)
assert extr == extr.fit(faces)


def test_patch_extractor_max_patches(downsampled_face_collection):
def test_patch_extractor_max_patches(downsampled_face_collection, global_random_seed):
faces = downsampled_face_collection
i_h, i_w = faces.shape[1:3]
p_h, p_w = 8, 8

max_patches = 100
expected_n_patches = len(faces) * max_patches
extr = PatchExtractor(
patch_size=(p_h, p_w), max_patches=max_patches, random_state=0
patch_size=(p_h, p_w), max_patches=max_patches, random_state=global_random_seed
)
patches = extr.transform(faces)
assert patches.shape == (expected_n_patches, p_h, p_w)
Expand All @@ -247,35 +249,37 @@ def test_patch_extractor_max_patches(downsampled_face_collection):
(i_h - p_h + 1) * (i_w - p_w + 1) * max_patches
)
extr = PatchExtractor(
patch_size=(p_h, p_w), max_patches=max_patches, random_state=0
patch_size=(p_h, p_w), max_patches=max_patches, random_state=global_random_seed
)
patches = extr.transform(faces)
assert patches.shape == (expected_n_patches, p_h, p_w)


def test_patch_extractor_max_patches_default(downsampled_face_collection):
def test_patch_extractor_max_patches_default(
downsampled_face_collection, global_random_seed
):
faces = downsampled_face_collection
extr = PatchExtractor(max_patches=100, random_state=0)
extr = PatchExtractor(max_patches=100, random_state=global_random_seed)
patches = extr.transform(faces)
assert patches.shape == (len(faces) * 100, 19, 25)


def test_patch_extractor_all_patches(downsampled_face_collection):
def test_patch_extractor_all_patches(downsampled_face_collection, global_random_seed):
faces = downsampled_face_collection
i_h, i_w = faces.shape[1:3]
p_h, p_w = 8, 8
expected_n_patches = len(faces) * (i_h - p_h + 1) * (i_w - p_w + 1)
extr = PatchExtractor(patch_size=(p_h, p_w), random_state=0)
extr = PatchExtractor(patch_size=(p_h, p_w), random_state=global_random_seed)
patches = extr.transform(faces)
assert patches.shape == (expected_n_patches, p_h, p_w)


def test_patch_extractor_color(orange_face):
def test_patch_extractor_color(orange_face, global_random_seed):
faces = _make_images(orange_face)
i_h, i_w = faces.shape[1:3]
p_h, p_w = 8, 8
expected_n_patches = len(faces) * (i_h - p_h + 1) * (i_w - p_w + 1)
extr = PatchExtractor(patch_size=(p_h, p_w), random_state=0)
extr = PatchExtractor(patch_size=(p_h, p_w), random_state=global_random_seed)
patches = extr.transform(faces)
assert patches.shape == (expected_n_patches, p_h, p_w, 3)

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