On 17/06/15 04:38, Honi Sanders wrote:
I have now implemented this functionality in numpy.correlate() and
numpy.convolve(). https://github.com/bringingheavendown/numpy. The files that
were edited are:
numpy/core/src/multiarray/multiarraymodule.c
numpy/core/numeric.py
I will also repeat what I said in response on Github (discussions at:
https://github.com/scipy/scipy/issues/4940,
https://github.com/numpy/numpy/issues/5954):
I do want a function that computes cross-correlograms, however the
implementation is exactly the same for cross-correlograms as
Hi!
I just finished porting a large code-base to Python 3 (making it work on
2.6, 2.7 and 3.4). It wasn't that difficult, but one thing gave me a
hard time and it was this:
Python 2.7.9 (default, Apr 2 2015, 15:33:21)
[GCC 4.9.2] on linux2
Type help, copyright, credits or license for more
Hi All,
I plan to branch the 1.10 release next Monday. I expect this to be a
difficult release, much time has passed since 1.9 and there have been
significant enhancements/changes to masked arrays, structured array
assigment, and recored arrays. In addition, most ufuncs no longer return
Hello,
There is a simple solution.
The cross-correlation of two arrays of lengths m and n is of length
m + n - 1, where m is usually much larger than n.
If you need to compute the cross-correlation with a bound on the lag
of k, then truncate the longer array to length k - n + 1.
That is,
def
