rm CondaPkg environment

2023-04-06 13:53:47 +07:00
parent 0a57ed7884
commit c43d949309
3329 changed files with 5725 additions and 447022 deletions
--- a/.CondaPkg/env/Lib/site-packages/skimage/measure/tests/test_colocalization.py
+++ b/.CondaPkg/env/Lib/site-packages/skimage/measure/tests/test_colocalization.py
@@ -1,100 +0,0 @@
-import numpy as np
-import pytest
-from skimage.measure import (intersection_coeff, manders_coloc_coeff,
-                             manders_overlap_coeff, pearson_corr_coeff)
-
-
-def test_invalid_input():
-    # images are not same size
-    img1 = np.array([[i + j for j in range(4)] for i in range(4)])
-    img2 = np.ones((3, 5, 6))
-    mask = np.array([[i <= 1 for i in range(5)] for _ in range(5)])
-    non_binary_mask = np.array([[2 for __ in range(4)] for _ in range(4)])
-
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        pearson_corr_coeff(img1, img1, mask)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        pearson_corr_coeff(img1, img2)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        pearson_corr_coeff(img1, img1, mask)
-    with pytest.raises(ValueError, match=". array is not of dtype boolean"):
-        pearson_corr_coeff(img1, img1, non_binary_mask)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        manders_coloc_coeff(img1, mask)
-    with pytest.raises(ValueError, match=". array is not of dtype boolean"):
-        manders_coloc_coeff(img1, non_binary_mask)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        manders_coloc_coeff(img1, img1 > 0, mask)
-    with pytest.raises(ValueError, match=". array is not of dtype boolean"):
-        manders_coloc_coeff(img1, img1 > 0, non_binary_mask)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        manders_overlap_coeff(img1, img1, mask)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        manders_overlap_coeff(img1, img2)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        manders_overlap_coeff(img1, img1, mask)
-    with pytest.raises(ValueError, match=". array is not of dtype boolean"):
-        manders_overlap_coeff(img1, img1, non_binary_mask)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        intersection_coeff(img1 > 2, img2 > 1, mask)
-    with pytest.raises(ValueError, match=". array is not of dtype boolean"):
-        intersection_coeff(img1, img2)
-    with pytest.raises(ValueError, match=". must have the same dimensions"):
-        intersection_coeff(img1 > 2, img1 > 1, mask)
-    with pytest.raises(ValueError, match=". array is not of dtype boolean"):
-        intersection_coeff(img1 > 2, img1 > 1, non_binary_mask)
-
-
-def test_pcc():
-    # simple example
-    img1 = np.array([[i + j for j in range(4)] for i in range(4)])
-    assert pearson_corr_coeff(img1, img1) == (1.0, 0.0)
-
-    img2 = np.where(img1 <= 2, 0, img1)
-    np.testing.assert_almost_equal(pearson_corr_coeff(img1, img2), (0.944911182523068, 3.5667540654536515e-08))
-
-    # change background of roi and see if values are same
-    roi = np.where(img1 <= 2, 0, 1)
-    np.testing.assert_almost_equal(pearson_corr_coeff(img1, img1, roi), pearson_corr_coeff(img1, img2, roi))
-
-
-def test_mcc():
-    img1 = np.array([[j for j in range(4)] for i in range(4)])
-    mask = np.array([[i <= 1 for j in range(4)]for i in range(4)])
-    assert manders_coloc_coeff(img1, mask) == 0.5
-
-    # test negative values
-    img_negativeint = np.where(img1 == 1, -1, img1)
-    img_negativefloat = img_negativeint / 2.0
-    with pytest.raises(ValueError):
-        manders_coloc_coeff(img_negativeint, mask)
-    with pytest.raises(ValueError):
-        manders_coloc_coeff(img_negativefloat, mask)
-
-
-def test_moc():
-    img1 = np.ones((4, 4))
-    img2 = 2 * np.ones((4, 4))
-    assert manders_overlap_coeff(img1, img2) == 1
-
-    # test negative values
-    img_negativeint = np.where(img1 == 1, -1, img1)
-    img_negativefloat = img_negativeint / 2.0
-    with pytest.raises(ValueError):
-        manders_overlap_coeff(img_negativeint, img2)
-    with pytest.raises(ValueError):
-        manders_overlap_coeff(img1, img_negativeint)
-    with pytest.raises(ValueError):
-        manders_overlap_coeff(img_negativefloat, img2)
-    with pytest.raises(ValueError):
-        manders_overlap_coeff(img1, img_negativefloat)
-    with pytest.raises(ValueError):
-        manders_overlap_coeff(img_negativefloat, img_negativefloat)
-
-
-def test_intersection_coefficient():
-    img1_mask = np.array([[j <= 1 for j in range(4)] for i in range(4)])
-    img2_mask = np.array([[i <= 1 for j in range(4)] for i in range(4)])
-    img3_mask = np.array([[1 for j in range(4)] for i in range(4)])
-    assert intersection_coeff(img1_mask, img2_mask) == 0.5
-    assert intersection_coeff(img1_mask, img3_mask) == 1