""" Tests for Morphological footprints (skimage.morphology.footprint) Author: Damian Eads """ import numpy as np import pytest from numpy.testing import assert_equal from skimage._shared.testing import fetch from skimage.morphology import footprints class TestFootprints: def test_square_footprint(self): """Test square footprints""" for k in range(0, 5): actual_mask = footprints.square(k) expected_mask = np.ones((k, k), dtype='uint8') assert_equal(expected_mask, actual_mask) def test_rectangle_footprint(self): """Test rectangle footprints""" for i in range(0, 5): for j in range(0, 5): actual_mask = footprints.rectangle(i, j) expected_mask = np.ones((i, j), dtype='uint8') assert_equal(expected_mask, actual_mask) def test_cube_footprint(self): """Test cube footprints""" for k in range(0, 5): actual_mask = footprints.cube(k) expected_mask = np.ones((k, k, k), dtype='uint8') assert_equal(expected_mask, actual_mask) def strel_worker(self, fn, func): matlab_masks = np.load(fetch(fn)) k = 0 for arrname in sorted(matlab_masks): expected_mask = matlab_masks[arrname] actual_mask = func(k) if expected_mask.shape == (1,): expected_mask = expected_mask[:, np.newaxis] assert_equal(expected_mask, actual_mask) k = k + 1 def strel_worker_3d(self, fn, func): matlab_masks = np.load(fetch(fn)) k = 0 for arrname in sorted(matlab_masks): expected_mask = matlab_masks[arrname] actual_mask = func(k) if expected_mask.shape == (1,): expected_mask = expected_mask[:, np.newaxis] # Test center slice for each dimension. This gives a good # indication of validity without the need for a 3D reference # mask. c = int(expected_mask.shape[0]/2) assert_equal(expected_mask, actual_mask[c, :, :]) assert_equal(expected_mask, actual_mask[:, c, :]) assert_equal(expected_mask, actual_mask[:, :, c]) k = k + 1 def test_footprint_disk(self): """Test disk footprints""" self.strel_worker("data/disk-matlab-output.npz", footprints.disk) def test_footprint_diamond(self): """Test diamond footprints""" self.strel_worker("data/diamond-matlab-output.npz", footprints.diamond) def test_footprint_ball(self): """Test ball footprints""" self.strel_worker_3d("data/disk-matlab-output.npz", footprints.ball) def test_footprint_octahedron(self): """Test octahedron footprints""" self.strel_worker_3d("data/diamond-matlab-output.npz", footprints.octahedron) def test_footprint_octagon(self): """Test octagon footprints""" expected_mask1 = np.array([[0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [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, 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], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0]], dtype=np.uint8) actual_mask1 = footprints.octagon(5, 3) expected_mask2 = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]], dtype=np.uint8) actual_mask2 = footprints.octagon(1, 1) assert_equal(expected_mask1, actual_mask1) assert_equal(expected_mask2, actual_mask2) def test_footprint_ellipse(self): """Test ellipse footprints""" expected_mask1 = np.array([[0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0], [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, 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], [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]], dtype=np.uint8) actual_mask1 = footprints.ellipse(5, 3) expected_mask2 = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], dtype=np.uint8) actual_mask2 = footprints.ellipse(1, 1) assert_equal(expected_mask1, actual_mask1) assert_equal(expected_mask2, actual_mask2) assert_equal(expected_mask1, footprints.ellipse(3, 5).T) assert_equal(expected_mask2, footprints.ellipse(1, 1).T) def test_footprint_star(self): """Test star footprints""" expected_mask1 = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0]], dtype=np.uint8) actual_mask1 = footprints.star(4) expected_mask2 = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], dtype=np.uint8) actual_mask2 = footprints.star(1) assert_equal(expected_mask1, actual_mask1) assert_equal(expected_mask2, actual_mask2) @pytest.mark.parametrize( 'function, args, supports_sequence_decomposition', [ (footprints.disk, (3,), True), (footprints.ball, (3,), True), (footprints.square, (3,), True), (footprints.cube, (3,), True), (footprints.diamond, (3,), True), (footprints.octahedron, (3,), True), (footprints.rectangle, (3, 4), True), (footprints.ellipse, (3, 4), False), (footprints.octagon, (3, 4), True), (footprints.star, (3,), False), ] ) @pytest.mark.parametrize("dtype", [np.uint8, np.float64]) def test_footprint_dtype(function, args, supports_sequence_decomposition, dtype): # make sure footprint dtype matches what was requested footprint = function(*args, dtype=dtype) assert footprint.dtype == dtype if supports_sequence_decomposition: sequence = function(*args, dtype=dtype, decomposition='sequence') assert all([fp_tuple[0].dtype == dtype for fp_tuple in sequence]) @pytest.mark.parametrize("function", ["disk", "ball"]) @pytest.mark.parametrize("radius", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, 75, 100]) def test_nsphere_series_approximation(function, radius): fp_func = getattr(footprints, function) expected = fp_func(radius, strict_radius=False, decomposition=None) footprint_sequence = fp_func(radius, strict_radius=False, decomposition="sequence") approximate = footprints.footprint_from_sequence(footprint_sequence) assert approximate.shape == expected.shape # verify that maximum error does not exceed some fraction of the size error = np.sum(np.abs(expected.astype(int) - approximate.astype(int))) if radius == 1: assert error == 0 else: max_error = 0.1 if function == "disk" else 0.15 assert error / expected.size <= max_error @pytest.mark.parametrize("radius", [1, 2, 3, 4, 5, 10, 20, 50, 75]) @pytest.mark.parametrize("strict_radius", [False, True]) def test_disk_crosses_approximation(radius, strict_radius): fp_func = footprints.disk expected = fp_func(radius, strict_radius=strict_radius, decomposition=None) footprint_sequence = fp_func(radius, strict_radius=strict_radius, decomposition="crosses") approximate = footprints.footprint_from_sequence(footprint_sequence) assert approximate.shape == expected.shape # verify that maximum error does not exceed some fraction of the size error = np.sum(np.abs(expected.astype(int) - approximate.astype(int))) max_error = 0.05 assert error / expected.size <= max_error @pytest.mark.parametrize("width", [3, 8, 20, 50]) @pytest.mark.parametrize("height", [3, 8, 20, 50]) def test_ellipse_crosses_approximation(width, height): fp_func = footprints.ellipse expected = fp_func(width, height, decomposition=None) footprint_sequence = fp_func(width, height, decomposition="crosses") approximate = footprints.footprint_from_sequence(footprint_sequence) assert approximate.shape == expected.shape # verify that maximum error does not exceed some fraction of the size error = np.sum(np.abs(expected.astype(int) - approximate.astype(int))) max_error = 0.05 assert error / expected.size <= max_error def test_disk_series_approximation_unavailable(): # ValueError if radius is too large (only precomputed up to radius=250) with pytest.raises(ValueError): footprints.disk(radius=10000, decomposition="sequence") def test_ball_series_approximation_unavailable(): # ValueError if radius is too large (only precomputed up to radius=100) with pytest.raises(ValueError): footprints.ball(radius=10000, decomposition="sequence")