Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/skimage/measure/tests/test_find_contours.py

@@ -0,0 +1,132 @@
+import numpy as np
+from skimage.measure import find_contours
+
+from skimage._shared import testing
+from skimage._shared.testing import assert_array_equal
+from pytest import raises
+
+
+a = np.ones((8, 8), dtype=np.float32)
+a[1:-1, 1] = 0
+a[1, 1:-1] = 0
+
+x, y = np.mgrid[-1:1:5j, -1:1:5j]
+r = np.sqrt(x**2 + y**2)
+
+
+def test_binary():
+    ref = [[6. ,  1.5],
+           [5. ,  1.5],
+           [4. ,  1.5],
+           [3. ,  1.5],
+           [2. ,  1.5],
+           [1.5,  2. ],
+           [1.5,  3. ],
+           [1.5,  4. ],
+           [1.5,  5. ],
+           [1.5,  6. ],
+           [1. ,  6.5],
+           [0.5,  6. ],
+           [0.5,  5. ],
+           [0.5,  4. ],
+           [0.5,  3. ],
+           [0.5,  2. ],
+           [0.5,  1. ],
+           [1. ,  0.5],
+           [2. ,  0.5],
+           [3. ,  0.5],
+           [4. ,  0.5],
+           [5. ,  0.5],
+           [6. ,  0.5],
+           [6.5,  1. ],
+           [6. ,  1.5]]
+
+    contours = find_contours(a, 0.5, positive_orientation='high')
+    assert len(contours) == 1
+    assert_array_equal(contours[0][::-1], ref)
+
+
+# target contour for mask tests
+mask_contour = [
+    [6. ,  0.5],
+    [5. ,  0.5],
+    [4. ,  0.5],
+    [3. ,  0.5],
+    [2. ,  0.5],
+    [1. ,  0.5],
+    [0.5,  1. ],
+    [0.5,  2. ],
+    [0.5,  3. ],
+    [0.5,  4. ],
+    [0.5,  5. ],
+    [0.5,  6. ],
+    [1. ,  6.5],
+    [1.5,  6. ],
+    [1.5,  5. ],
+    [1.5,  4. ],
+    [1.5,  3. ],
+    [1.5,  2. ],
+    [2. ,  1.5],
+    [3. ,  1.5],
+    [4. ,  1.5],
+    [5. ,  1.5],
+    [6. ,  1.5],
+]
+
+mask = np.ones((8, 8), dtype=bool)
+# Some missing data that should result in a hole in the contour:
+mask[7, 0:3] = False
+
+
+def test_nodata():
+    # Test missing data via NaNs in input array
+    b = np.copy(a)
+    b[~mask] = np.nan
+    contours = find_contours(b, 0.5, positive_orientation='high')
+    assert len(contours) == 1
+    assert_array_equal(contours[0], mask_contour)
+
+
+def test_mask():
+    # Test missing data via explicit masking
+    contours = find_contours(a, 0.5, positive_orientation='high', mask=mask)
+    assert len(contours) == 1
+    assert_array_equal(contours[0], mask_contour)
+
+
+def test_mask_shape():
+    bad_mask = np.ones((8, 7), dtype=bool)
+    with raises(ValueError, match='shape'):
+        find_contours(a, 0, mask=bad_mask)
+
+
+def test_mask_dtype():
+    bad_mask = np.ones((8,8), dtype=np.uint8)
+    with raises(TypeError, match='binary'):
+        find_contours(a, 0, mask=bad_mask)
+
+
+def test_float():
+    contours = find_contours(r, 0.5)
+    assert len(contours) == 1
+    assert_array_equal(contours[0],
+                    [[ 2.,  3.],
+                     [ 1.,  2.],
+                     [ 2.,  1.],
+                     [ 3.,  2.],
+                     [ 2.,  3.]])
+
+
+def test_memory_order():
+    contours = find_contours(np.ascontiguousarray(r), 0.5)
+    assert len(contours) == 1
+
+    contours = find_contours(np.asfortranarray(r), 0.5)
+    assert len(contours) == 1
+
+
+def test_invalid_input():
+    with testing.raises(ValueError):
+        find_contours(r, 0.5, 'foo', 'bar')
+    with testing.raises(ValueError):
+        find_contours(r[..., None], 0.5)