66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
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import numpy as np
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from skimage.restoration import inpaint
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from skimage._shared import testing
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from skimage._shared.testing import assert_allclose
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def test_inpaint_biharmonic_2d():
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img = np.tile(np.square(np.linspace(0, 1, 5)), (5, 1))
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mask = np.zeros_like(img)
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mask[2, 2:] = 1
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mask[1, 3:] = 1
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mask[0, 4:] = 1
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img[np.where(mask)] = 0
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out = inpaint.inpaint_biharmonic(img, mask)
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ref = np.array(
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[[0., 0.0625, 0.25000000, 0.5625000, 0.73925058],
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[0., 0.0625, 0.25000000, 0.5478048, 0.76557821],
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[0., 0.0625, 0.25842878, 0.5623079, 0.85927796],
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[0., 0.0625, 0.25000000, 0.5625000, 1.00000000],
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[0., 0.0625, 0.25000000, 0.5625000, 1.00000000]]
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)
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assert_allclose(ref, out)
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def test_inpaint_biharmonic_3d():
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img = np.tile(np.square(np.linspace(0, 1, 5)), (5, 1))
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img = np.dstack((img, img.T))
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mask = np.zeros_like(img)
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mask[2, 2:, :] = 1
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mask[1, 3:, :] = 1
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mask[0, 4:, :] = 1
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img[np.where(mask)] = 0
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out = inpaint.inpaint_biharmonic(img, mask)
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ref = np.dstack((
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np.array(
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[[0.0000, 0.0625, 0.25000000, 0.56250000, 0.53752796],
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[0.0000, 0.0625, 0.25000000, 0.44443780, 0.53762210],
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[0.0000, 0.0625, 0.23693666, 0.46621112, 0.68615592],
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[0.0000, 0.0625, 0.25000000, 0.56250000, 1.00000000],
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[0.0000, 0.0625, 0.25000000, 0.56250000, 1.00000000]]),
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np.array(
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[[0.0000, 0.0000, 0.00000000, 0.00000000, 0.19621902],
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[0.0625, 0.0625, 0.06250000, 0.17470756, 0.30140091],
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[0.2500, 0.2500, 0.27241289, 0.35155440, 0.43068654],
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[0.5625, 0.5625, 0.56250000, 0.56250000, 0.56250000],
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[1.0000, 1.0000, 1.00000000, 1.00000000, 1.00000000]])
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))
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assert_allclose(ref, out)
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def test_invalid_input():
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img, mask = np.zeros([]), np.zeros([])
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with testing.raises(ValueError):
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inpaint.inpaint_biharmonic(img, mask)
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img, mask = np.zeros((2, 2)), np.zeros((4, 1))
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with testing.raises(ValueError):
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inpaint.inpaint_biharmonic(img, mask)
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img = np.ma.array(np.zeros((2, 2)), mask=[[0, 0], [0, 0]])
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mask = np.zeros((2, 2))
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with testing.raises(TypeError):
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inpaint.inpaint_biharmonic(img, mask)
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