Hi all,
I have been using numpy.correlate and was finding something weird. I now think
that there might be a bug.
Correlations should be order dependent eg. correlate(x,y) != correlate(y,x) in
general (whereas convolutions are symmetric)
>>> import numpy as N
>>> x = N.array([1,0,0])
>>> y = N.array([0,0,1])
>>> N.correlate(x,y,'full')
array([1, 0, 0, 0, 0])
>>> N.correlate(y,x,'full')
array([0, 0, 0, 0, 1])
This works fine. However, if the arrays have different lengths, we get a
problem.
>>> y2=N.array([0,0,0,1])
>>> N.correlate(x,y2,'full')
array([0, 0, 0, 0, 0, 1])
>>> N.correlate(y2,x,'full')
array([0, 0, 0, 0, 0, 1])
I believe that somewhere in the code, the arrays are re-ordered by their
length. Initially I thought that this was because
correlate was deriving from convolution but looking at numpy.core, I can see
that in fact convolution derives from correlate.
After that, it becomes C code which I haven't managed to look at yet.
Am I correct, is this a bug?
regards
Rob Steed
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