[SciPy-dev] scipy.signal.convolve2d significantly slower than matlab

[Joel Schaerer]

Hi all,

I've found that the 2D convolution code in scipy is significantly slower than
matlab's. The following code:

--------------------------------------------------------------------
#!/usr/bin/python

import scipy.io as io
import scipy.signal

aa=io.loadmat('input.mat')
seq=aa["seq"]

seq_f=[]

kernel=scipy.randn(21,21)
for k in xrange(seq.shape[2]):
    seq_f.append(scipy.signal.convolve2d(seq[:,:,k],kernel,'same'))
--------------------------------------------------------------------

Executes about 8 times slower than the following matlab code (executed with
matlab7 on 32bit linux):

--------------------------------------------------------------------
clear all
close all
clc

load input.mat

g=randn(21,21);

seq_f=zeros(size(seq));
for p=1:size(seq,3),
    seq_f(:,:,p)=conv2(seq(:,:,p),g,'same');
end
--------------------------------------------------------------------

I've traced the convolve code in scipy to the pylab_convolve2D function in
firfilter.c. It contains the nice following warning:

/* This could definitely be more optimized... */

...

Anyways, convolution is crucial for some applications, 
so I wanted to report this. I also tried to look for 
some good open source convolution code so that it
might be incorporated into scipy, but couldn't find any.
Would anyone know of one?

Totally unrelated question to the scipy devs: do you plan
 to add a hierarchical data structure such as kd-trees to
 scipy? With a nice API, it would be a great feature.