scikit-image

test_draw3d.py
224 строки · 6.4 Кб
Перенос по словам
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import numpy as np
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from skimage._shared.testing import assert_array_equal, assert_allclose
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from skimage.draw import ellipsoid, ellipsoid_stats, rectangle
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from skimage._shared import testing
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def test_ellipsoid_sign_parameters1():
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    with testing.raises(ValueError):
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        ellipsoid(-1, 2, 2)
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def test_ellipsoid_sign_parameters2():
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    with testing.raises(ValueError):
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        ellipsoid(0, 2, 2)
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def test_ellipsoid_sign_parameters3():
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    with testing.raises(ValueError):
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        ellipsoid(-3, -2, 2)
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def test_ellipsoid_bool():
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    test = ellipsoid(2, 2, 2)[1:-1, 1:-1, 1:-1]
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    test_anisotropic = ellipsoid(2, 2, 4, spacing=(1.0, 1.0, 2.0))
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    test_anisotropic = test_anisotropic[1:-1, 1:-1, 1:-1]
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    expected = np.array(
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        [
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            [
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 1, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 0, 0, 0],
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                [0, 1, 1, 1, 0],
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                [0, 1, 1, 1, 0],
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                [0, 1, 1, 1, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 1, 0, 0],
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                [0, 1, 1, 1, 0],
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                [1, 1, 1, 1, 1],
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                [0, 1, 1, 1, 0],
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                [0, 0, 1, 0, 0],
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            ],
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            [
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                [0, 0, 0, 0, 0],
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                [0, 1, 1, 1, 0],
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                [0, 1, 1, 1, 0],
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                [0, 1, 1, 1, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 1, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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        ]
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    )
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    assert_array_equal(test, expected.astype(bool))
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    assert_array_equal(test_anisotropic, expected.astype(bool))
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def test_ellipsoid_levelset():
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    test = ellipsoid(2, 2, 2, levelset=True)[1:-1, 1:-1, 1:-1]
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    test_anisotropic = ellipsoid(2, 2, 4, spacing=(1.0, 1.0, 2.0), levelset=True)
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    test_anisotropic = test_anisotropic[1:-1, 1:-1, 1:-1]
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    expected = np.array(
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        [
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            [
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                [2.0, 1.25, 1.0, 1.25, 2.0],
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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                [1.0, 0.25, 0.0, 0.25, 1.0],
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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                [2.0, 1.25, 1.0, 1.25, 2.0],
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            ],
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            [
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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                [0.5, -0.25, -0.5, -0.25, 0.5],
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                [0.25, -0.5, -0.75, -0.5, 0.25],
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                [0.5, -0.25, -0.5, -0.25, 0.5],
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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            ],
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            [
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                [1.0, 0.25, 0.0, 0.25, 1.0],
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                [0.25, -0.5, -0.75, -0.5, 0.25],
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                [0.0, -0.75, -1.0, -0.75, 0.0],
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                [0.25, -0.5, -0.75, -0.5, 0.25],
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                [1.0, 0.25, 0.0, 0.25, 1.0],
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            ],
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            [
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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                [0.5, -0.25, -0.5, -0.25, 0.5],
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                [0.25, -0.5, -0.75, -0.5, 0.25],
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                [0.5, -0.25, -0.5, -0.25, 0.5],
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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            ],
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            [
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                [2.0, 1.25, 1.0, 1.25, 2.0],
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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                [1.0, 0.25, 0.0, 0.25, 1.0],
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                [1.25, 0.5, 0.25, 0.5, 1.25],
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                [2.0, 1.25, 1.0, 1.25, 2.0],
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            ],
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        ]
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    )
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    assert_allclose(test, expected)
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    assert_allclose(test_anisotropic, expected)
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def test_ellipsoid_stats():
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    # Test comparison values generated by Wolfram Alpha
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    vol, surf = ellipsoid_stats(6, 10, 16)
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    assert_allclose(1280 * np.pi, vol, atol=1e-6)
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    assert_allclose(1383.2828269179892359787, surf, atol=1e-6)
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    # Test when a <= b <= c does not hold
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    vol, surf = ellipsoid_stats(16, 6, 10)
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    assert_allclose(1280 * np.pi, vol, atol=1e-6)
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    assert_allclose(1383.2828269179892359787, surf, atol=1e-6)
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    # Larger test to ensure reliability over broad range
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    vol, surf = ellipsoid_stats(17, 27, 169)
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    assert_allclose(103428 * np.pi, vol, atol=1e-4)
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    assert_allclose(37426.253635465972897880, surf, atol=1e-6)
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    # For equal a, b, c values
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    vol, surf = ellipsoid_stats(10, 10, 10)
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    assert_allclose(4000 * np.pi / 3, vol, atol=1e-6)
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    assert_allclose(400 * np.pi, surf, atol=1e-6)
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def test_rect_3d_extent():
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    expected = np.array(
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        [
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            [
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                [0, 0, 1, 1, 1],
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                [0, 0, 1, 1, 1],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 1, 1, 1],
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                [0, 0, 1, 1, 1],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 1, 1, 1],
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                [0, 0, 1, 1, 1],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 1, 1, 1],
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                [0, 0, 1, 1, 1],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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        ],
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        dtype=np.uint8,
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    )
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    img = np.zeros((4, 5, 5), dtype=np.uint8)
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    start = (0, 0, 2)
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    extent = (5, 2, 3)
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    pp, rr, cc = rectangle(start, extent=extent, shape=img.shape)
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    img[pp, rr, cc] = 1
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    assert_array_equal(img, expected)
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def test_rect_3d_end():
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    expected = np.array(
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        [
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            [
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 1, 1, 0],
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                [0, 0, 1, 1, 0],
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                [0, 0, 1, 1, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 1, 1, 0],
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                [0, 0, 1, 1, 0],
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                [0, 0, 1, 1, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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            [
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                [0, 0, 1, 1, 0],
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                [0, 0, 1, 1, 0],
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                [0, 0, 1, 1, 0],
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                [0, 0, 0, 0, 0],
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                [0, 0, 0, 0, 0],
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            ],
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        ],
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        dtype=np.uint8,
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    )
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    img = np.zeros((4, 5, 5), dtype=np.uint8)
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    start = (1, 0, 2)
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    end = (3, 2, 3)
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    pp, rr, cc = rectangle(start, end=end, shape=img.shape)
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    img[pp, rr, cc] = 1
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    assert_array_equal(img, expected)
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