Hi!
...I have found a good enough solution, although it only works if the
number of patterns (clusters) is not very big:
def classify(f):
THERESHOLD=0.1
patterns={}
for l in enumerate(f):
found = False
for p,c in patterns.items():
if dist(l,p) < THERESHOLD:
>Find out which pattern is being used on the second iteration and then try it
>on the first iteration. Is it just as slow?
You were right, the second pattern was 1891 bytes but the first was
just 142 :P
I will need to put more thought than I expect in the "small script".
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ne knows the reson of this behavior? How
should I write a program that deals with large data sets in python?
Thanks a lot!
marc magrans de abril
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Hi,
I was a trying to profile a small script and after shrinking the code
to the minimum I got a interesting profile difference.
Given two test functions test1 and test2, that only differs from an
extra level of indirection (i.e. find_substr), I wonder why I got a
timming difference >50%? What is
