def test_crop_mask():
rng = np.random.RandomState(42)
mask = np.zeros((3, 4, 5), dtype=np.bool)
box = mask[:2, :3, :4]
box[rng.rand(*box.shape) < 3.] = 1 # mask covers 30% of brain
idx = np.where(mask)
assert_true(idx[1].max() < 3)
tight_mask = _crop_mask(mask)
assert_equal(mask.sum(), tight_mask.sum())
assert_true(np.prod(tight_mask.shape) <= np.prod(box.shape))
def test_crop_mask():
rng = np.random.RandomState(42)
mask = np.zeros((3, 4, 5), dtype=np.bool)
box = mask[:2, :3, :4]
box[rng.rand(*box.shape) < 3.] = 1 # mask covers 30% of brain
idx = np.where(mask)
assert_true(idx[1].max() < 3)
tight_mask = _crop_mask(mask)
assert_equal(mask.sum(), tight_mask.sum())
assert_true(np.prod(tight_mask.shape) <= np.prod(box.shape))
def test_crop_mask_empty_mask():
with pytest.raises(ValueError, match="Empty mask:."):
_crop_mask(np.array([]))
with pytest.raises(ValueError, match="Empty mask:"):
_crop_mask(np.zeros((2, 2, 2)))
