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Reformat code to comply with PEP8

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Johannes Schönberger
2013-04-13 20:11:22 +02:00
parent 0238e388ac
commit 3c038f8db3
1 changed files with 17 additions and 17 deletions
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skimage/morphology/_skeletonize.py
+17 -17
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@@ -84,14 +84,14 @@ def skeletonize(image):
# look up table - there is one entry for each of the 2^8=256 possible
# combinations of 8 binary neighbours. 1's, 2's and 3's are candidates
# for removal at each iteration of the algorithm.
lut = [ 0,0,0,1,0,0,1,3,0,0,3,1,1,0,1,3,0,0,0,0,0,0,0,0,2,0,2,0,3,0,3,3,
0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,3,0,2,2,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
2,0,0,0,0,0,0,0,2,0,0,0,2,0,0,0,3,0,0,0,0,0,0,0,3,0,0,0,3,0,2,0,
0,0,3,1,0,0,1,3,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,
3,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
2,3,1,3,0,0,1,3,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
2,3,0,1,0,0,0,1,0,0,0,0,0,0,0,0,3,3,0,1,0,0,0,0,2,2,0,0,2,0,0,0]
lut = [0,0,0,1,0,0,1,3,0,0,3,1,1,0,1,3,0,0,0,0,0,0,0,0,2,0,2,0,3,0,3,3,
0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,3,0,2,2,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
2,0,0,0,0,0,0,0,2,0,0,0,2,0,0,0,3,0,0,0,0,0,0,0,3,0,0,0,3,0,2,0,
0,0,3,1,0,0,1,3,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,
3,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
2,3,1,3,0,0,1,3,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
2,3,0,1,0,0,0,1,0,0,0,0,0,0,0,0,3,3,0,1,0,0,0,0,2,2,0,0,2,0,0,0]
# convert to unsigned int (this should work for boolean values)
skeleton = np.array(image).astype(np.uint8)
@@ -106,13 +106,13 @@ def skeletonize(image):
# create the mask that will assign a unique value based on the
# arrangement of neighbouring pixels
mask = np.array([[1, 2, 4],
mask = np.array([[ 1, 2, 4],
[128, 0, 8],
[64, 32, 16]], np.uint8)
[ 64, 32, 16]], np.uint8)
pixelRemoved = True
while pixelRemoved:
pixelRemoved = False
pixel_removed = True
while pixel_removed:
pixel_removed = False
# assign each pixel a unique value based on its foreground neighbours
neighbours = ndimage.correlate(skeleton, mask, mode='constant')
@@ -126,11 +126,11 @@ def skeletonize(image):
# pass 1 - remove the 1's and 3's
code_mask = (codes == 1)
if np.any(code_mask):
pixelRemoved = True
pixel_removed = True
skeleton[code_mask] = 0
code_mask = (codes == 3)
if np.any(code_mask):
pixelRemoved = True
pixel_removed = True
skeleton[code_mask] = 0
# pass 2 - remove the 2's and 3's
@@ -139,11 +139,11 @@ def skeletonize(image):
codes = np.take(lut, neighbours)
code_mask = (codes == 2)
if np.any(code_mask):
pixelRemoved = True
pixel_removed = True
skeleton[code_mask] = 0
code_mask = (codes == 3)
if np.any(code_mask):
pixelRemoved = True
pixel_removed = True
skeleton[code_mask] = 0
return skeleton.astype(bool)