using for loop to install conda package

.CondaPkg/env/Lib/site-packages/skimage/feature/tests/test_censure.py

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+import numpy as np
+from skimage._shared.testing import assert_array_equal
+from skimage.data import moon
+from skimage.feature import CENSURE
+from skimage._shared.testing import test_parallel
+from skimage._shared import testing
+from skimage.transform import rescale
+
+
+img = moon()
+np.random.seed(0)
+
+
+def test_censure_on_rectangular_images():
+    """Censure feature detector should work on 2D image of any shape."""
+    rect_image = np.random.rand(300, 200)
+    square_image = np.random.rand(200, 200)
+    CENSURE().detect(square_image)
+    CENSURE().detect(rect_image)
+
+
+def test_keypoints_censure_color_image_unsupported_error():
+    """Censure keypoints can be extracted from gray-scale images only."""
+    with testing.raises(ValueError):
+        CENSURE().detect(np.zeros((20, 20, 3)))
+
+
+def test_keypoints_censure_mode_validity_error():
+    """Mode argument in keypoints_censure can be either DoB, Octagon or
+    STAR."""
+    with testing.raises(ValueError):
+        CENSURE(mode='dummy')
+
+
+def test_keypoints_censure_scale_range_error():
+    """Difference between the the max_scale and min_scale parameters in
+    keypoints_censure should be greater than or equal to two."""
+    with testing.raises(ValueError):
+        CENSURE(min_scale=1, max_scale=2)
+
+
+def test_keypoints_censure_moon_image_dob():
+    """Verify the actual Censure keypoints and their corresponding scale with
+    the expected values for DoB filter."""
+    detector = CENSURE()
+    detector.detect(img)
+    expected_keypoints = np.array([[ 21, 497],
+                                   [ 36,  46],
+                                   [119, 350],
+                                   [185, 177],
+                                   [287, 250],
+                                   [357, 239],
+                                   [463, 116],
+                                   [464, 132],
+                                   [467, 260]])
+    expected_scales = np.array([3, 4, 4, 2, 2, 3, 2, 2, 2])
+
+    assert_array_equal(expected_keypoints, detector.keypoints)
+    assert_array_equal(expected_scales, detector.scales)
+
+
+@test_parallel()
+def test_keypoints_censure_moon_image_octagon():
+    """Verify the actual Censure keypoints and their corresponding scale with
+    the expected values for Octagon filter."""
+
+    detector = CENSURE(mode='octagon')
+    # quarter scale image for speed
+    detector.detect(rescale(img, 0.25,
+                            anti_aliasing=False,
+                            mode='constant'))
+    expected_keypoints = np.array([[ 23,  27],
+                                   [ 29,  89],
+                                   [ 31,  87],
+                                   [106,  59],
+                                   [111,  67]])
+
+    expected_scales = np.array([3, 2, 5, 2, 4])
+
+    assert_array_equal(expected_keypoints, detector.keypoints)
+    assert_array_equal(expected_scales, detector.scales)
+
+
+def test_keypoints_censure_moon_image_star():
+    """Verify the actual Censure keypoints and their corresponding scale with
+    the expected values for STAR filter."""
+    detector = CENSURE(mode='star')
+    # quarter scale image for speed
+    detector.detect(rescale(img, 0.25,
+                            anti_aliasing=False,
+                            mode='constant'))
+    expected_keypoints = np.array([[ 23,  27],
+                                   [ 29,  89],
+                                   [ 30,  86],
+                                   [107,  59],
+                                   [109,  64],
+                                   [111,  67],
+                                   [113,  70]])
+
+    expected_scales = np.array([3, 2, 4, 2, 5, 3, 2])
+
+    assert_array_equal(expected_keypoints, detector.keypoints)
+    assert_array_equal(expected_scales, detector.scales)