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DOC: Clarify code comments and docstring

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Tony S Yu
2012-08-18 18:04:01 -04:00
parent 969772c036
commit 7a56a7f35e
1 changed files with 41 additions and 20 deletions
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skimage/morphology/_greyreconstruct.pyx
+41 -20
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@@ -18,26 +18,47 @@ cimport cython
@cython.boundscheck(False)
def reconstruction_loop(np.ndarray[dtype=np.uint32_t, ndim=1,
negative_indices = False,
mode = 'c'] avalues,
negative_indices=False, mode='c'] avalues,
np.ndarray[dtype=np.int32_t, ndim=1,
negative_indices = False,
mode = 'c'] aprev,
negative_indices=False, mode='c'] aprev,
np.ndarray[dtype=np.int32_t, ndim=1,
negative_indices = False,
mode = 'c'] anext,
negative_indices=False, mode='c'] anext,
np.ndarray[dtype=np.int32_t, ndim=1,
negative_indices = False,
mode = 'c'] astrides,
negative_indices=False, mode='c'] astrides,
np.int32_t current,
int image_stride):
"""The inner loop for reconstruction"""
"""The inner loop for reconstruction.
This algorithm uses the rank-order of pixels. If low intensity pixels have
a low rank and high intensity pixels have a high rank, then this loop
performs reconstruction by dilation. If this ranking is reversed, the
result is reconstruction by erosion.
For each pixel in the seed image, check its neighbors. If its neighbor's
rank is below that of the current pixel, replace the neighbor's rank with
the rank of the current pixel. This dilation is limited by the mask, i.e.
the rank at each pixel cannot exceed the mask as that pixel.
Parameters
----------
avalues : array
The rank order of the flattened seed and mask images.
aprev, anext: arrays
Indices of previous and next pixels in rank sorted order.
astrides : array
Strides to neighbors of the current pixel.
current : int
Index of lowest-ranked pixel used as starting point in reconstruction
loop.
image_stride : int
Stride between seed image and mask image in `avalues`.
"""
cdef:
np.int32_t neighbor
np.uint32_t neighbor_value
np.uint32_t current_value
np.uint32_t mask_value
np.int32_t link
np.int32_t current_link
int i
np.int32_t nprev
np.int32_t nnext
@@ -55,18 +76,18 @@ def reconstruction_loop(np.ndarray[dtype=np.uint32_t, ndim=1,
for i in range(nstrides):
neighbor = current + strides[i]
neighbor_value = values[neighbor]
# Only do neighbors less than the current value
# Only propagate neighbors ranked below the current rank
if neighbor_value < current_value:
mask_value = values[neighbor + image_stride]
# Only do neighbors less than the mask value
# Only propagate neighbors ranked below the mask rank
if neighbor_value < mask_value:
# Raise the neighbor to the mask value if
# the mask is less than current
# Raise the neighbor to the mask rank if
# the mask ranked below the current rank
if mask_value < current_value:
link = neighbor + image_stride
current_link = neighbor + image_stride
values[neighbor] = mask_value
else:
link = current
current_link = current
values[neighbor] = current_value
# unlink the neighbor
nprev = prev[neighbor]
@@ -74,12 +95,12 @@ def reconstruction_loop(np.ndarray[dtype=np.uint32_t, ndim=1,
next[nprev] = nnext
if nnext != -1:
prev[nnext] = nprev
# link the neighbor after the link
nnext = next[link]
# link to the neighbor after the current link
nnext = next[current_link]
next[neighbor] = nnext
prev[neighbor] = link
prev[neighbor] = current_link
if nnext >= 0:
prev[nnext] = neighbor
next[link] = neighbor
next[current_link] = neighbor
current = next[current]