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 > numpy/core/tests/test_numeric.py > Please look over the code, my design decisions, and the unit tests I have > written. This is my first time contributing, so I am not confident about any > of these and welcome feedback.
I'll just repeat here what I already said on Github. I think this stems from the need to compute cross-correlograms as used in statistical signal analysis, whereas numpy.correlate and scipy.signal.correlate are better suited for matched filtering. I think the best solution would be to add a function called scipy.signal.correlogram, which would return a cross-correlation and an array of time lags. It could take minlag and maxlag as optional arguments. Adding maxlag and minlag arguments to numpy.convolve makes very little sense, as far as I am concerned. Sturla _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion