mirror of
https://github.com/wassname/scikit-image.git
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Olivia
176 lines
7.1 KiB
Python
176 lines
7.1 KiB
Python
import numpy as np
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from numpy.testing import (assert_array_equal, assert_equal, assert_raises,
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assert_warns)
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from skimage.morphology import remove_small_objects, remove_small_holes
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from ..._shared._warnings import expected_warnings
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test_image = np.array([[0, 0, 0, 1, 0],
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[1, 1, 1, 0, 0],
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[1, 1, 1, 0, 1]], bool)
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def test_one_connectivity():
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expected = np.array([[0, 0, 0, 0, 0],
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[1, 1, 1, 0, 0],
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[1, 1, 1, 0, 0]], bool)
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observed = remove_small_objects(test_image, min_size=6)
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assert_array_equal(observed, expected)
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def test_two_connectivity():
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expected = np.array([[0, 0, 0, 1, 0],
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[1, 1, 1, 0, 0],
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[1, 1, 1, 0, 0]], bool)
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observed = remove_small_objects(test_image, min_size=7, connectivity=2)
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assert_array_equal(observed, expected)
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def test_in_place():
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observed = remove_small_objects(test_image, min_size=6, in_place=True)
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assert_equal(observed is test_image, True,
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"remove_small_objects in_place argument failed.")
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def test_labeled_image():
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labeled_image = np.array([[2, 2, 2, 0, 1],
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[2, 2, 2, 0, 1],
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[2, 0, 0, 0, 0],
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[0, 0, 3, 3, 3]], dtype=int)
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expected = np.array([[2, 2, 2, 0, 0],
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[2, 2, 2, 0, 0],
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[2, 0, 0, 0, 0],
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[0, 0, 3, 3, 3]], dtype=int)
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observed = remove_small_objects(labeled_image, min_size=3)
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assert_array_equal(observed, expected)
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def test_uint_image():
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labeled_image = np.array([[2, 2, 2, 0, 1],
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[2, 2, 2, 0, 1],
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[2, 0, 0, 0, 0],
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[0, 0, 3, 3, 3]], dtype=np.uint8)
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expected = np.array([[2, 2, 2, 0, 0],
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[2, 2, 2, 0, 0],
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[2, 0, 0, 0, 0],
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[0, 0, 3, 3, 3]], dtype=np.uint8)
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observed = remove_small_objects(labeled_image, min_size=3)
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assert_array_equal(observed, expected)
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def test_single_label_warning():
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image = np.array([[0, 0, 0, 1, 0],
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[1, 1, 1, 0, 0],
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[1, 1, 1, 0, 0]], int)
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with expected_warnings(['use a boolean array?']):
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remove_small_objects(image, min_size=6)
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def test_float_input():
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float_test = np.random.rand(5, 5)
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assert_raises(TypeError, remove_small_objects, float_test)
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def test_negative_input():
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negative_int = np.random.randint(-4, -1, size=(5, 5))
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assert_raises(ValueError, remove_small_objects, negative_int)
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test_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,0,0,1,1,0,0,0,0],
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[0,1,1,1,0,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,0,1],
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[0,0,0,0,0,0,0,1,1,1]], bool)
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def test_one_connectivity_holes():
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expected = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1]], bool)
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observed = remove_small_holes(test_holes_image, min_size=3)
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assert_array_equal(observed, expected)
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def test_two_connectivity_holes():
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expected = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,0,0,1,1,0,0,0,0],
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[0,1,1,1,0,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1]], bool)
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observed = remove_small_holes(test_holes_image, min_size=3, connectivity=2)
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assert_array_equal(observed, expected)
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def test_in_place_holes():
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observed = remove_small_holes(test_holes_image, min_size=3, in_place=True)
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assert_equal(observed is test_holes_image, True,
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"remove_small_holes in_place argument failed.")
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def test_labeled_image_holes():
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labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,0,0,1,1,0,0,0,0],
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[0,1,1,1,0,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,2,2,2],
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[0,0,0,0,0,0,0,2,0,2],
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[0,0,0,0,0,0,0,2,2,2]], dtype=int)
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expected = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1]], dtype=bool)
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observed = remove_small_holes(labeled_holes_image, min_size=3)
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assert_array_equal(observed, expected)
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def test_uint_image_holes():
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labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,0,0,1,1,0,0,0,0],
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[0,1,1,1,0,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,2,2,2],
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[0,0,0,0,0,0,0,2,0,2],
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[0,0,0,0,0,0,0,2,2,2]], dtype=np.uint8)
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expected = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1],
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[0,0,0,0,0,0,0,1,1,1]], dtype=bool)
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observed = remove_small_holes(labeled_holes_image, min_size=3)
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assert_array_equal(observed, expected)
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def test_label_warning_holes():
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labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,1,0,0,1,1,0,0,0,0],
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[0,1,1,1,0,1,0,0,0,0],
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[0,1,1,1,1,1,0,0,0,0],
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[0,0,0,0,0,0,0,2,2,2],
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[0,0,0,0,0,0,0,2,0,2],
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[0,0,0,0,0,0,0,2,2,2]], dtype=int)
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with expected_warnings(['use a boolean array?']):
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remove_small_holes(labeled_holes_image, min_size=3)
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def test_float_input_holes():
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float_test = np.random.rand(5, 5)
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assert_raises(TypeError, remove_small_holes, float_test)
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if __name__ == "__main__":
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np.testing.run_module_suite()
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