def test_mask_from_collection_single_image():
"""Test that mask_from_collection works even if input
is a single array"""
images = np.zeros((64, 64))
mask = mask_from_collection(images)
assert not np.any(mask)
def test_mask_from_collection_trivial():
""" Test on set of images with value zero """
images = [np.zeros((64, 64)) for _ in range(5)]
mask = mask_from_collection(images)
assert images[0].shape == mask.shape
assert not np.any(mask)
def test_single_image(self):
""" Test that mask_from_collection works even if input
is a single array """
images = np.zeros((64, 64))
mask = mask_from_collection(images)
self.assertFalse(np.any(mask))
def test_trivial(self):
""" Test on set of images with value zero """
images = [np.zeros((64, 64)) for _ in range(5)]
mask = mask_from_collection(images)
self.assertSequenceEqual(images[0].shape, mask.shape)
self.assertFalse(np.any(mask))
def test_mask_from_collection_std_threshold():
""" Test that std threshold is respected """
images = [np.ones((64, 64)) for _ in range(5)]
images[0][5, 12] = 1000
mask = mask_from_collection(images, px_thresh=10000, std_thresh=1)
assert np.sum(mask) == 1 # only one pixels is masked
assert mask[5, 12] == True
def test_mask_from_collection_intensity_threshold_with_lower_bound():
""" Test that intensity threshold is respected """
images = [np.ones((64, 64)) for _ in range(5)]
images[2][32, 4] = -10
mask = mask_from_collection(images, px_thresh=(0, np.inf))
assert np.sum(mask) == 1 # only one pixels is masked
assert mask[32, 4] == True
def test_std_threshold(self):
""" Test that std threshold is respected """
images = [np.ones((64, 64)) for _ in range(5)]
images[0][5, 12] = 1000
mask = mask_from_collection(images, px_thresh=10000, std_thresh=1)
self.assertEqual(np.sum(mask), 1) # only one pixels is masked
self.assertEqual(mask[5, 12], True)
def test_intensity_threshold_with_lower_bound(self):
""" Test that intensity threshold is respected """
images = [np.ones((64, 64)) for _ in range(5)]
images[2][32, 4] = -10
mask = mask_from_collection(images, px_thresh=(0, np.inf))
self.assertEqual(np.sum(mask), 1) # only one pixels is masked
self.assertEqual(mask[32, 4], True)