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running sum optimizations

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git-svn-id: https://callirhoe.googlecode.com/svn/trunk@157 81c8bb96-aa45-f2e2-0eef-c4fa4a15c6df
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geortz@gmail.com 2014-10-03 10:43:48 +00:00
parent df191c2917
commit 97bcec2027
1 changed files with 15 additions and 3 deletions
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18
calmagick.py
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@ -70,9 +70,10 @@ class PNMImage(object):
@ivar data: image data as 2-dimensional array (list of lists)
@ivar size: tuple M{(width,height)} of image dimensions
@ivar maxval: maximum grayscale value
@ivar _rsum_cache: used by L{_rsum()} to remember results
@ivar xsum: 2-dimensional array of running x-sums for each line, used for efficient
computation of block averages, resulting in M{O(sqrt(A))} complexity, instead of M{O(A)},
where M{A} the image area
computation of block averages, resulting in M{O(H)} complexity, instead of M{O(W*H)},
where M{W,H} the image dimensions
"""
def __init__(self, strlist):
self.data = [];
@ -105,7 +106,18 @@ class PNMImage(object):
self.data = [intlist[x:x+w] for x in range(0, len(intlist), w)]
break
self.xsum = [map(lambda x: sum(self.data[y][0:x]), range(w+1)) for y in range(0,h)]
self._rsum_cache=(-1,-1,0) # y,x,s
# self.xsum = [map(lambda x: sum(self.data[y][0:x]), range(w+1)) for y in range(0,h)]
self.xsum = [map(lambda x: self._rsum(y,x), range(w+1)) for y in range(0,h)]
def _rsum(self,y,x):
"""running sum with cache"""
if self._rsum_cache[0] == y and self._rsum_cache[1] == x:
s = self._rsum_cache[2] + self.data[y][x-1]
else:
s = sum(self.data[y][0:x])
self._rsum_cache = (y,x+1,s)
return s
def block_avg(self, x, y, szx, szy):
"""returns the average intensity of a block of size M{(szx,szy)} at pos (top-left) M{(x,y)}"""