2D Convolution in Python similar to Matlab's conv2

Question

I have been trying to do Convolution of a 2D Matrix using SciPy, and Numpy but have failed. For SciPy I tried, sepfir2d and scipy.signal.convolve and Convolve2D for Numpy. I

Answer 1

scipy's convolved1d() does what you want, just treats the edges a bit differently:

sp.ndimage.filters.convolve1d(A,[0.707,0.707],axis=1,mode='constant')

will give you:

array([[ 6.363,  6.363,  6.363,  2.828],
       [ 3.535,  3.535,  3.535,  1.414],
       [ 6.363,  6.363,  6.363,  2.828],
       [ 3.535,  3.535,  3.535,  1.414]])

If you want the exact same result, just add a column of zeros to A like this:

sp.ndimage.filters.convolve1d(np.c_[np.zeros((4,1)),A],[0.707,0.707],axis=1,mode='constant')

and you will get:

array([[ 3.535,  6.363,  6.363,  6.363,  2.828],
       [ 2.121,  3.535,  3.535,  3.535,  1.414],
       [ 3.535,  6.363,  6.363,  6.363,  2.828],
       [ 2.121,  3.535,  3.535,  3.535,  1.414]])

From my experience you can do in scipy/numpy most of what you do in Matlab very easily (and more).