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Use single file for test cases and rename file

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Johannes Schönberger
2012-11-10 11:23:43 +01:00
parent c9f95db67f
commit f5ad204aca
2 changed files with 92 additions and 100 deletions
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skimage/filter/rank/tests/test_histo.py
-100
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@@ -1,100 +0,0 @@
import numpy as np
from numpy.testing import run_module_suite, assert_array_equal
from skimage.filter.rank import _crank8, _crank16
def test_trivial_selem8():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint8)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[0, 0, 0], [0, 1, 0],[0, 0, 0]], dtype=np.uint8)
_crank8.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
def test_trivial_selem16():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint16)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[0, 0, 0], [0, 1, 0],[0, 0, 0]], dtype=np.uint8)
_crank16.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
def test_smallest_selem8():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint8)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[1]], dtype=np.uint8)
_crank8.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
def test_smallest_selem16():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint16)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[1]], dtype=np.uint8)
_crank16.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
if __name__ == "__main__":
run_module_suite()
skimage/filter/rank/tests/test_suite.py → skimage/filter/rank/tests/test_rank.py
+92
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@@ -198,5 +198,97 @@ def test_compare_8bit_vs_16bit():
assert_array_equal(f8, f16)
def test_trivial_selem8():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint8)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[0, 0, 0], [0, 1, 0],[0, 0, 0]], dtype=np.uint8)
_crank8.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
def test_trivial_selem16():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint16)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[0, 0, 0], [0, 1, 0],[0, 0, 0]], dtype=np.uint8)
_crank16.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
def test_smallest_selem8():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint8)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[1]], dtype=np.uint8)
_crank8.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank8.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
def test_smallest_selem16():
# check that min, max and mean returns identity if structuring element
# contains only central pixel
image = np.zeros((5, 5), dtype=np.uint16)
out = np.zeros_like(image)
mask = np.ones_like(image, dtype=np.uint8)
image[2,2] = 255
image[2,3] = 128
image[1,2] = 16
elem = np.array([[1]], dtype=np.uint8)
_crank16.mean(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.minimum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
_crank16.maximum(image=image, selem=elem, out=out, mask=mask,
shift_x=0, shift_y=0)
assert_array_equal(image, out)
if __name__ == "__main__":
run_module_suite()