142 lines
4.9 KiB
Python
142 lines
4.9 KiB
Python
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"""
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These tests are originally part of CellProfiler, code licensed under both GPL and BSD licenses.
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Website: http://www.cellprofiler.org
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Copyright (c) 2003-2009 Massachusetts Institute of Technology
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Copyright (c) 2009-2011 Broad Institute
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All rights reserved.
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Original author: Lee Kamentsky
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"""
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import numpy as np
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from skimage.morphology.greyreconstruct import reconstruction
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from skimage._shared import testing
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from skimage._shared.testing import assert_array_almost_equal
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def test_zeros():
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"""Test reconstruction with image and mask of zeros"""
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assert_array_almost_equal(
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reconstruction(np.zeros((5, 7)), np.zeros((5, 7))), 0)
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def test_image_equals_mask():
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"""Test reconstruction where the image and mask are the same"""
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assert_array_almost_equal(
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reconstruction(np.ones((7, 5)), np.ones((7, 5))), 1)
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def test_image_less_than_mask():
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"""Test reconstruction where the image is uniform and less than mask"""
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image = np.ones((5, 5))
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mask = np.ones((5, 5)) * 2
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assert_array_almost_equal(reconstruction(image, mask), 1)
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def test_one_image_peak():
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"""Test reconstruction with one peak pixel"""
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image = np.ones((5, 5))
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image[2, 2] = 2
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mask = np.ones((5, 5)) * 3
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assert_array_almost_equal(reconstruction(image, mask), 2)
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def test_two_image_peaks():
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"""Test reconstruction with two peak pixels isolated by the mask"""
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image = np.array([[1, 1, 1, 1, 1, 1, 1, 1],
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[1, 2, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 3, 1],
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[1, 1, 1, 1, 1, 1, 1, 1]])
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mask = np.array([[4, 4, 4, 1, 1, 1, 1, 1],
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[4, 4, 4, 1, 1, 1, 1, 1],
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[4, 4, 4, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 4, 4, 4],
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[1, 1, 1, 1, 1, 4, 4, 4],
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[1, 1, 1, 1, 1, 4, 4, 4]])
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expected = np.array([[2, 2, 2, 1, 1, 1, 1, 1],
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[2, 2, 2, 1, 1, 1, 1, 1],
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[2, 2, 2, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 3, 3, 3],
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[1, 1, 1, 1, 1, 3, 3, 3],
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[1, 1, 1, 1, 1, 3, 3, 3]])
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assert_array_almost_equal(reconstruction(image, mask), expected)
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def test_zero_image_one_mask():
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"""Test reconstruction with an image of all zeros and a mask that's not"""
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result = reconstruction(np.zeros((10, 10)), np.ones((10, 10)))
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assert_array_almost_equal(result, 0)
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def test_fill_hole():
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"""Test reconstruction by erosion, which should fill holes in mask."""
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seed = np.array([0, 8, 8, 8, 8, 8, 8, 8, 8, 0])
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mask = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
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result = reconstruction(seed, mask, method='erosion')
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assert_array_almost_equal(result, np.array([0, 3, 6, 4, 4, 4, 4, 4, 2, 0]))
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def test_invalid_seed():
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seed = np.ones((5, 5))
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mask = np.ones((5, 5))
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with testing.raises(ValueError):
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reconstruction(seed * 2, mask,
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method='dilation')
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with testing.raises(ValueError):
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reconstruction(seed * 0.5, mask,
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method='erosion')
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def test_invalid_selem():
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seed = np.ones((5, 5))
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mask = np.ones((5, 5))
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with testing.raises(ValueError):
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reconstruction(seed, mask,
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selem=np.ones((4, 4)))
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with testing.raises(ValueError):
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reconstruction(seed, mask,
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selem=np.ones((3, 4)))
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reconstruction(seed, mask, selem=np.ones((3, 3)))
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def test_invalid_method():
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seed = np.array([0, 8, 8, 8, 8, 8, 8, 8, 8, 0])
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mask = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
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with testing.raises(ValueError):
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reconstruction(seed, mask, method='foo')
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def test_invalid_offset_not_none():
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"""Test reconstruction with invalid not None offset parameter"""
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image = np.array([[1, 1, 1, 1, 1, 1, 1, 1],
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[1, 2, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 1, 3, 1],
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[1, 1, 1, 1, 1, 1, 1, 1]])
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mask = np.array([[4, 4, 4, 1, 1, 1, 1, 1],
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[4, 4, 4, 1, 1, 1, 1, 1],
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[4, 4, 4, 1, 1, 1, 1, 1],
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[1, 1, 1, 1, 1, 4, 4, 4],
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[1, 1, 1, 1, 1, 4, 4, 4],
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[1, 1, 1, 1, 1, 4, 4, 4]])
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with testing.raises(ValueError):
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reconstruction(image, mask, method='dilation',
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selem=np.ones((3, 3)), offset=np.array([3, 0]))
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def test_offset_not_none():
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"""Test reconstruction with valid offset parameter"""
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seed = np.array([0, 3, 6, 2, 1, 1, 1, 4, 2, 0])
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mask = np.array([0, 8, 6, 8, 8, 8, 8, 4, 4, 0])
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expected = np.array([0, 3, 6, 6, 6, 6, 6, 4, 4, 0])
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assert_array_almost_equal(
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reconstruction(seed, mask, method='dilation',
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selem=np.ones(3), offset=np.array([0])), expected)
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