111 lines
4.6 KiB
Python
111 lines
4.6 KiB
Python
import numpy as np
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import pytest
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from skimage.measure import (
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intersection_coeff,
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manders_coloc_coeff,
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manders_overlap_coeff,
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pearson_corr_coeff,
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)
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def test_invalid_input():
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# images are not same size
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img1 = np.array([[i + j for j in range(4)] for i in range(4)])
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img2 = np.ones((3, 5, 6))
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mask = np.array([[i <= 1 for i in range(5)] for _ in range(5)])
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non_binary_mask = np.array([[2 for __ in range(4)] for _ in range(4)])
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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pearson_corr_coeff(img1, img1, mask)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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pearson_corr_coeff(img1, img2)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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pearson_corr_coeff(img1, img1, mask)
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with pytest.raises(ValueError, match=". array is not of dtype boolean"):
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pearson_corr_coeff(img1, img1, non_binary_mask)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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manders_coloc_coeff(img1, mask)
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with pytest.raises(ValueError, match=". array is not of dtype boolean"):
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manders_coloc_coeff(img1, non_binary_mask)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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manders_coloc_coeff(img1, img1 > 0, mask)
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with pytest.raises(ValueError, match=". array is not of dtype boolean"):
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manders_coloc_coeff(img1, img1 > 0, non_binary_mask)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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manders_overlap_coeff(img1, img1, mask)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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manders_overlap_coeff(img1, img2)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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manders_overlap_coeff(img1, img1, mask)
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with pytest.raises(ValueError, match=". array is not of dtype boolean"):
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manders_overlap_coeff(img1, img1, non_binary_mask)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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intersection_coeff(img1 > 2, img2 > 1, mask)
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with pytest.raises(ValueError, match=". array is not of dtype boolean"):
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intersection_coeff(img1, img2)
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with pytest.raises(ValueError, match=". must have the same dimensions"):
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intersection_coeff(img1 > 2, img1 > 1, mask)
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with pytest.raises(ValueError, match=". array is not of dtype boolean"):
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intersection_coeff(img1 > 2, img1 > 1, non_binary_mask)
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def test_pcc():
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# simple example
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img1 = np.array([[i + j for j in range(4)] for i in range(4)])
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np.testing.assert_almost_equal(
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pearson_corr_coeff(img1, img1), (1.0, 0.0), decimal=14
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)
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img2 = np.where(img1 <= 2, 0, img1)
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np.testing.assert_almost_equal(
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pearson_corr_coeff(img1, img2), (0.944911182523068, 3.5667540654536515e-08)
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)
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# change background of roi and see if values are same
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roi = np.where(img1 <= 2, 0, 1)
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np.testing.assert_almost_equal(
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pearson_corr_coeff(img1, img1, roi), pearson_corr_coeff(img1, img2, roi)
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)
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def test_mcc():
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img1 = np.array([[j for j in range(4)] for i in range(4)])
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mask = np.array([[i <= 1 for j in range(4)] for i in range(4)])
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assert manders_coloc_coeff(img1, mask) == 0.5
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# test negative values
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img_negativeint = np.where(img1 == 1, -1, img1)
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img_negativefloat = img_negativeint / 2.0
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with pytest.raises(ValueError):
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manders_coloc_coeff(img_negativeint, mask)
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with pytest.raises(ValueError):
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manders_coloc_coeff(img_negativefloat, mask)
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def test_moc():
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img1 = np.ones((4, 4))
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img2 = 2 * np.ones((4, 4))
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assert manders_overlap_coeff(img1, img2) == 1
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# test negative values
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img_negativeint = np.where(img1 == 1, -1, img1)
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img_negativefloat = img_negativeint / 2.0
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with pytest.raises(ValueError):
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manders_overlap_coeff(img_negativeint, img2)
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with pytest.raises(ValueError):
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manders_overlap_coeff(img1, img_negativeint)
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with pytest.raises(ValueError):
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manders_overlap_coeff(img_negativefloat, img2)
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with pytest.raises(ValueError):
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manders_overlap_coeff(img1, img_negativefloat)
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with pytest.raises(ValueError):
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manders_overlap_coeff(img_negativefloat, img_negativefloat)
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def test_intersection_coefficient():
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img1_mask = np.array([[j <= 1 for j in range(4)] for i in range(4)])
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img2_mask = np.array([[i <= 1 for j in range(4)] for i in range(4)])
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img3_mask = np.array([[1 for j in range(4)] for i in range(4)])
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assert intersection_coeff(img1_mask, img2_mask) == 0.5
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assert intersection_coeff(img1_mask, img3_mask) == 1
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