scikit-image

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import pytest
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import numpy as np
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from skimage import data
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from skimage.measure._label import _label_bool, label
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from skimage.measure._ccomp import label_cython as clabel
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from skimage._shared import testing
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# In this testsuite, we ensure that the results provided by
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# label_cython are identical to the one from _label_bool,
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# which is based on ndimage.
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def test_no_option():
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    img = data.binary_blobs(length=128, blob_size_fraction=0.15, n_dim=3)
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    l_ndi = _label_bool(img)
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    l_cy = clabel(img)
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    testing.assert_equal(l_ndi, l_cy)
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def test_background():
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    img = data.binary_blobs(length=128, blob_size_fraction=0.15, n_dim=3)
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    l_ndi = _label_bool(img, background=0)
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    l_cy = clabel(img, background=0)
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    testing.assert_equal(l_ndi, l_cy)
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    l_ndi = _label_bool(img, background=1)
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    l_cy = clabel(img, background=1)
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    testing.assert_equal(l_ndi, l_cy)
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def test_return_num():
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    img = data.binary_blobs(length=128, blob_size_fraction=0.15, n_dim=3)
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    l_ndi = _label_bool(img, return_num=True)
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    l_cy = clabel(img, return_num=True)
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    testing.assert_equal(l_ndi, l_cy)
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def test_connectivity():
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    img = data.binary_blobs(length=128, blob_size_fraction=0.15, n_dim=3)
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    for c in (1, 2, 3):
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        l_ndi = _label_bool(img, connectivity=c)
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        l_cy = clabel(img, connectivity=c)
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        testing.assert_equal(l_ndi, l_cy)
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    for c in (0, 4):
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        with pytest.raises(ValueError):
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            l_ndi = _label_bool(img, connectivity=c)
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        with pytest.raises(ValueError):
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            l_cy = clabel(img, connectivity=c)
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@pytest.mark.parametrize("dtype", [bool, int])
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def test_zero_size(dtype):
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    img = np.ones((300, 0, 300), dtype=dtype)
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    lab, num = label(img, return_num=True)
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    assert lab.shape == img.shape
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    assert num == 0
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