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https://github.com/wassname/scikit-image.git
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arokem
152 lines
5.1 KiB
Python
152 lines
5.1 KiB
Python
import numpy as np
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from numpy.testing import assert_array_equal, assert_raises
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from numpy.testing.decorators import skipif
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from skimage.morphology import convex_hull_image, convex_hull_object
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from skimage.morphology._convex_hull import possible_hull
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try:
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import scipy.spatial
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scipy_spatial = True
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except ImportError:
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scipy_spatial = False
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@skipif(not scipy_spatial)
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def test_basic():
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image = np.array(
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[[0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 0, 0, 0, 0],
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[0, 0, 0, 1, 0, 1, 0, 0, 0],
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[0, 0, 1, 0, 0, 0, 1, 0, 0],
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[0, 1, 0, 0, 0, 0, 0, 1, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=bool)
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expected = np.array(
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[[0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 0, 0, 0, 0],
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[0, 0, 0, 1, 1, 1, 0, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=bool)
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assert_array_equal(convex_hull_image(image), expected)
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# Test that an error is raised on passing a 3D image:
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image3d = np.empty((5, 5, 5))
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assert_raises(ValueError, convex_hull_image, image3d)
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@skipif(not scipy_spatial)
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def test_qhull_offset_example():
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nonzeros = (([1367, 1368, 1368, 1368, 1369, 1369, 1369, 1369, 1369, 1370,
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1370, 1370, 1370, 1370, 1370, 1370, 1371, 1371, 1371, 1371,
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1371, 1371, 1371, 1371, 1371, 1372, 1372, 1372, 1372, 1372,
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1372, 1372, 1372, 1372, 1373, 1373, 1373, 1373, 1373, 1373,
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1373, 1373, 1373, 1374, 1374, 1374, 1374, 1374, 1374, 1374,
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1375, 1375, 1375, 1375, 1375, 1376, 1376, 1376, 1377]),
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([151, 150, 151, 152, 149, 150, 151, 152, 153, 148, 149, 150,
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151, 152, 153, 154, 147, 148, 149, 150, 151, 152, 153, 154,
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155, 146, 147, 148, 149, 150, 151, 152, 153, 154, 146, 147,
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148, 149, 150, 151, 152, 153, 154, 147, 148, 149, 150, 151,
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152, 153, 148, 149, 150, 151, 152, 149, 150, 151, 150]))
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image = np.zeros((1392, 1040), dtype=bool)
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image[nonzeros] = True
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expected = image.copy()
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assert_array_equal(convex_hull_image(image), expected)
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@skipif(not scipy_spatial)
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def test_pathological_qhull_example():
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image = np.array(
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[[0, 0, 0, 0, 1, 0, 0],
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[0, 0, 1, 1, 1, 1, 1],
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[1, 1, 1, 0, 0, 0, 0]], dtype=bool)
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expected = np.array(
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[[0, 0, 0, 1, 1, 1, 0],
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[0, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 0, 0, 0]], dtype=bool)
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assert_array_equal(convex_hull_image(image), expected)
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@skipif(not scipy_spatial)
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def test_possible_hull():
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image = np.array(
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[[0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 0, 0, 0, 0],
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[0, 0, 0, 1, 0, 1, 0, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.uint8)
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expected = np.array([[1, 4],
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[2, 3],
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[3, 2],
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[4, 1],
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[4, 1],
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[3, 2],
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[2, 3],
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[1, 4],
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[2, 5],
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[3, 6],
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[4, 7],
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[2, 5],
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[3, 6],
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[4, 7],
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[4, 2],
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[4, 3],
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[4, 4],
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[4, 5],
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[4, 6]])
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ph = possible_hull(image)
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assert_array_equal(ph, expected)
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@skipif(not scipy_spatial)
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def test_object():
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image = np.array(
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[[0, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 1, 1, 1, 0, 0, 1, 0, 1],
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[1, 0, 0, 0, 0, 0, 0, 1, 0],
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[1, 0, 0, 0, 0, 0, 1, 0, 1],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=bool)
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expected4 = np.array(
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[[0, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 1, 0, 0, 0, 0, 0, 0, 0],
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[1, 1, 1, 0, 0, 0, 0, 0, 0],
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[1, 1, 1, 1, 0, 0, 1, 0, 1],
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[1, 1, 1, 0, 0, 0, 0, 1, 0],
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[1, 1, 0, 0, 0, 0, 1, 0, 1],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=bool)
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assert_array_equal(convex_hull_object(image, 4), expected4)
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expected8 = np.array(
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[[0, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[1, 1, 0, 0, 0, 0, 0, 0, 0],
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[1, 1, 1, 0, 0, 0, 0, 0, 0],
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[1, 1, 1, 1, 0, 0, 1, 1, 1],
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[1, 1, 1, 0, 0, 0, 1, 1, 1],
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[1, 1, 0, 0, 0, 0, 1, 1, 1],
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[1, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=bool)
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assert_array_equal(convex_hull_object(image, 8), expected8)
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assert_raises(ValueError, convex_hull_object, image, 7)
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# Test that an error is raised on passing a 3D image:
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image3d = np.empty((5, 5, 5))
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assert_raises(ValueError, convex_hull_object, image3d)
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if __name__ == "__main__":
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np.testing.run_module_suite()
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