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If it is much faster than the n-dimensional fft convolution
For me it is about 60(!) times faster, see the attached graph (mind the log scaling). I had NxN data with NxN kernels convolved.
This is interesting.
be worth writing a fftconvolve2 What remains to be checked is the ratio for the case where the kernel is a lot smaller than the data. If that turns out to be equally fast, I don't see any reason to keep the current implementation of scipy.signal.fftconvolve.
Anyway, this may also be related to that other discussion going on about FFTW. I'm not sure what the current status about FFT implementations in SciPy is, but at first glance there seem to be quite a few really, which to me seems redundant and unhelpful.
On this point, I can echo. A quick look turns up: scipy.fftpack.convolve scipy.signal.convolve scipy.signal.fftconvolve scipy.stsci.convolve numpy.convolve I've used scipy.signal.fftconvolve as that's where other signal processing tools useful to me have been found. IMHO, ideally, there would be one 'fast' convolve that does the right thing. I can understand that different convolves in different name spaces exist for historical and practical reasons. So, maybe there's an argument to keep all these numerous convolves. (Some appear to be direct, rather than fft convolves--reason enough to keep those.) Maybe a thing to do would be a page someplace clarifying which are the fastest? Or... 'rewrite' so that all use a fast convolution routine, but preserve the separate interfaces (if they exist) as necessary? ****** My regards, ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Dr Joseph Anderson Lecturer in Music School of Arts and New Media University of Hull, Scarborough Campus, Scarborough, North Yorkshire, YO11 3AZ, UK T: +44.(0)1723.362392 T: +44.(0)1723.357370 F: +44.(0)1723.350815 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ***************************************************************************************** To view the terms under which this email is distributed, please go to http://www.hull.ac.uk/legal/email_disclaimer.html *****************************************************************************************