def test_invalid_seed():
seed = np.ones((5, 5))
mask = np.ones((5, 5))
with testing.raises(ValueError):
reconstruction(seed * 2, mask, method='dilation')
with testing.raises(ValueError):
reconstruction(seed * 0.5, mask, method='erosion')
def test_invalid_selem():
seed = np.ones((5, 5))
mask = np.ones((5, 5))
assert_raises(ValueError, reconstruction, seed, mask,
selem=np.ones((4, 4)))
assert_raises(ValueError, reconstruction, seed, mask,
selem=np.ones((3, 4)))
reconstruction(seed, mask, selem=np.ones((3, 3)))
def test_invalid_selem():
seed = np.ones((5, 5))
mask = np.ones((5, 5))
assert_raises(ValueError, reconstruction, seed, mask,
selem=np.ones((4, 4)))
assert_raises(ValueError, reconstruction, seed, mask,
selem=np.ones((3, 4)))
reconstruction(seed, mask, selem=np.ones((3, 3)))
def test_invalid_seed():
seed = np.ones((5, 5))
mask = np.ones((5, 5))
with pytest.raises(ValueError):
reconstruction(seed * 2, mask,
method='dilation')
with pytest.raises(ValueError):
reconstruction(seed * 0.5, mask,
method='erosion')
def test_invalid_offset_not_none():
"""Test reconstruction with invalid not None offset parameter"""
image = np.array([[1, 1, 1, 1, 1, 1, 1, 1], [1, 2, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 3, 1], [1, 1, 1, 1, 1, 1, 1, 1]])
mask = np.array([[4, 4, 4, 1, 1, 1, 1, 1], [4, 4, 4, 1, 1, 1, 1, 1],
[4, 4, 4, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 4, 4, 4],
[1, 1, 1, 1, 1, 4, 4, 4], [1, 1, 1, 1, 1, 4, 4, 4]])
with testing.raises(ValueError):
reconstruction(image,
mask,
method='dilation',
selem=np.ones((3, 3)),
offset=np.array([3, 0]))
def h_minima(image, h, selem=None):
shifted_img = image + h
rec_img = greyreconstruct.reconstruction(shifted_img, image,
method='erosion', selem=selem) #grey_reconstruction_erosion(shifted_img, image)
residue_img = rec_img - image
return residue_img > 0
def fill_spots2(img, size=5):
med = morph.dilation(img, selem=np.ones([size, size]))
fm = img.copy()
fm[1:-2, 1:-2] = med[1:-2, 1:-2]
res = rec.reconstruction(fm, img, method='erosion')
return res
def test_invalid_offset_not_none():
"""Test reconstruction with invalid not None offset parameter"""
image = np.array([[1, 1, 1, 1, 1, 1, 1, 1],
[1, 2, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 3, 1],
[1, 1, 1, 1, 1, 1, 1, 1]])
mask = np.array([[4, 4, 4, 1, 1, 1, 1, 1],
[4, 4, 4, 1, 1, 1, 1, 1],
[4, 4, 4, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 4, 4, 4],
[1, 1, 1, 1, 1, 4, 4, 4],
[1, 1, 1, 1, 1, 4, 4, 4]])
with testing.raises(ValueError):
reconstruction(image, mask, method='dilation',
selem=np.ones((3, 3)), offset=np.array([3, 0]))
def test_offset_not_none():
"""Test reconstruction with valid offset parameter"""
seed = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
mask = np.array([0, 8, 6, 8, 8, 8, 8, 4, 4, 0])
expected = np.array([0, 3, 6, 6, 6, 6, 6, 4, 4, 0])
assert_array_almost_equal(
reconstruction(seed, mask, method='dilation',
selem=np.ones(3), offset=np.array([0])), expected)
def fill_spots(img, size=5):
med = flt.median(img, selem=np.ones([size, 1]))
med = flt.median(med, selem=np.ones([1, size]))
fm = img.copy()
fm[1:-2, 1:-2] = med[1:-2, 1:-2]
fm = np.maximum(fm, img)
res = rec.reconstruction(fm, img, method='erosion')
return res
def test_offset_not_none():
"""Test reconstruction with valid offset parameter"""
seed = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
mask = np.array([0, 8, 6, 8, 8, 8, 8, 4, 4, 0])
expected = np.array([0, 3, 6, 6, 6, 6, 6, 4, 4, 0])
assert_array_almost_equal(
reconstruction(seed,
mask,
method='dilation',
selem=np.ones(3),
offset=np.array([0])), expected)
def test_invalid_selem():
seed = np.ones((5, 5))
mask = np.ones((5, 5))
with testing.raises(ValueError):
reconstruction(seed, mask, selem=np.ones((4, 4)))
with testing.raises(ValueError):
reconstruction(seed, mask, selem=np.ones((3, 4)))
reconstruction(seed, mask, selem=np.ones((3, 3)))
def test_two_image_peaks():
"""Test reconstruction with two peak pixels isolated by the mask"""
image = np.array([[1, 1, 1, 1, 1, 1, 1, 1], [1, 2, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 3, 1], [1, 1, 1, 1, 1, 1, 1, 1]])
mask = np.array([[4, 4, 4, 1, 1, 1, 1, 1], [4, 4, 4, 1, 1, 1, 1, 1],
[4, 4, 4, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 4, 4, 4],
[1, 1, 1, 1, 1, 4, 4, 4], [1, 1, 1, 1, 1, 4, 4, 4]])
expected = np.array([[2, 2, 2, 1, 1, 1, 1, 1], [2, 2, 2, 1, 1, 1, 1, 1],
[2, 2, 2, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 3, 3, 3],
[1, 1, 1, 1, 1, 3, 3, 3], [1, 1, 1, 1, 1, 3, 3, 3]])
assert_array_almost_equal(reconstruction(image, mask), expected)
def test_invalid_selem():
seed = np.ones((5, 5))
mask = np.ones((5, 5))
with pytest.raises(ValueError):
reconstruction(seed, mask,
selem=np.ones((4, 4)))
with pytest.raises(ValueError):
reconstruction(seed, mask,
selem=np.ones((3, 4)))
reconstruction(seed, mask, selem=np.ones((3, 3)))
def extended_minima(img, h, selem=None):
if np.issubdtype(img.dtype, 'half'):
resolution = 2 * np.finfo(img.dtype).resolution
if h < resolution:
h = resolution
h_corrected = h - resolution / 2.0
shifted_img = img + h
else:
shifted_img = _add_constant_clip(img, h)
h_corrected = h
rec_img = greyreconstruct.reconstruction(shifted_img, img,
method='erosion', selem=selem)
residue_img = rec_img - img
h_min = np.zeros(img.shape, dtype=np.uint8)
h_min[residue_img > 0] = 1
return h_min
def test_two_image_peaks():
"""Test reconstruction with two peak pixels isolated by the mask"""
image = np.array([[1, 1, 1, 1, 1, 1, 1, 1],
[1, 2, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 3, 1],
[1, 1, 1, 1, 1, 1, 1, 1]])
mask = np.array([[4, 4, 4, 1, 1, 1, 1, 1],
[4, 4, 4, 1, 1, 1, 1, 1],
[4, 4, 4, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 4, 4, 4],
[1, 1, 1, 1, 1, 4, 4, 4],
[1, 1, 1, 1, 1, 4, 4, 4]])
expected = np.array([[2, 2, 2, 1, 1, 1, 1, 1],
[2, 2, 2, 1, 1, 1, 1, 1],
[2, 2, 2, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 3, 3, 3],
[1, 1, 1, 1, 1, 3, 3, 3],
[1, 1, 1, 1, 1, 3, 3, 3]])
assert_close(reconstruction(image, mask), expected)
def test_image_equals_mask():
"""Test reconstruction where the image and mask are the same"""
assert_close(reconstruction(np.ones((7, 5)), np.ones((7, 5))), 1)
def test_zeros():
"""Test reconstruction with image and mask of zeros"""
assert_close(reconstruction(np.zeros((5, 7)), np.zeros((5, 7))), 0)
def test_zeros():
"""Test reconstruction with image and mask of zeros"""
assert_array_almost_equal(
reconstruction(np.zeros((5, 7)), np.zeros((5, 7))), 0)
def test_invalid_method():
seed = np.array([0, 8, 8, 8, 8, 8, 8, 8, 8, 0])
mask = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
with testing.raises(ValueError):
reconstruction(seed, mask, method='foo')
def test_fill_hole():
"""Test reconstruction by erosion, which should fill holes in mask."""
seed = np.array([0, 8, 8, 8, 8, 8, 8, 8, 8, 0])
mask = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
result = reconstruction(seed, mask, method='erosion')
assert_close(result, np.array([0, 3, 6, 4, 4, 4, 4, 4, 2, 0]))
def test_image_less_than_mask():
"""Test reconstruction where the image is uniform and less than mask"""
image = np.ones((5, 5))
mask = np.ones((5, 5)) * 2
assert_close(reconstruction(image, mask), 1)
def test_zeros():
"""Test reconstruction with image and mask of zeros"""
assert_close(reconstruction(np.zeros((5, 7)), np.zeros((5, 7))), 0)
def test_image_less_than_mask():
"""Test reconstruction where the image is uniform and less than mask"""
image = np.ones((5, 5))
mask = np.ones((5, 5)) * 2
assert_array_almost_equal(reconstruction(image, mask), 1)
def test_image_equals_mask():
"""Test reconstruction where the image and mask are the same"""
assert_array_almost_equal(reconstruction(np.ones((7, 5)), np.ones((7, 5))),
1)
def test_zeros():
"""Test reconstruction with image and mask of zeros"""
assert_array_almost_equal(
reconstruction(np.zeros((5, 7)), np.zeros((5, 7))), 0)
def test_one_image_peak():
"""Test reconstruction with one peak pixel"""
image = np.ones((5, 5))
image[2, 2] = 2
mask = np.ones((5, 5)) * 3
assert_close(reconstruction(image, mask), 2)
def test_zero_image_one_mask():
"""Test reconstruction with an image of all zeros and a mask that's not"""
result = reconstruction(np.zeros((10, 10)), np.ones((10, 10)))
assert_array_almost_equal(result, 0)
def test_zero_image_one_mask():
"""Test reconstruction with an image of all zeros and a mask that's not"""
result = reconstruction(np.zeros((10, 10)), np.ones((10, 10)))
assert_close(result, 0)
def test_fill_hole():
"""Test reconstruction by erosion, which should fill holes in mask."""
seed = np.array([0, 8, 8, 8, 8, 8, 8, 8, 8, 0])
mask = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
result = reconstruction(seed, mask, method='erosion')
assert_array_almost_equal(result, np.array([0, 3, 6, 4, 4, 4, 4, 4, 2, 0]))
def test_one_image_peak():
"""Test reconstruction with one peak pixel"""
image = np.ones((5, 5))
image[2, 2] = 2
mask = np.ones((5, 5)) * 3
assert_array_almost_equal(reconstruction(image, mask), 2)
def test_invalid_method():
seed = np.array([0, 8, 8, 8, 8, 8, 8, 8, 8, 0])
mask = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
with pytest.raises(ValueError):
reconstruction(seed, mask, method='foo')
