import numpy as np
from scipy.ndimage.filters import convolve
def conv2(x,y,mode='same'):
"""
Emulate the function conv2 from Mathworks.
Usage:
z = conv2(x,y,mode='same')
TODO:
- Support other modes than 'same' (see conv2.m)
"""
if not(mode == 'same'):
raise Exception("Mode not supported")
# Add singleton dimensions
if (len(x.shape) < len(y.shape)):
dim = x.shape
for i in range(len(x.shape),len(y.shape)):
dim = (1,) + dim
x = x.reshape(dim)
elif (len(y.shape) < len(x.shape)):
dim = y.shape
for i in range(len(y.shape),len(x.shape)):
dim = (1,) + dim
y = y.reshape(dim)
origin = ()
# Apparently, the origin must be set in a special way to reproduce
# the results of scipy.signal.convolve and Matlab
for i in range(len(x.shape)):
if ( (x.shape[i] - y.shape[i]) % 2 == 0 and
x.shape[i] > 1 and
y.shape[i] > 1):
origin = origin + (-1,)
else:
origin = origin + (0,)
z = convolve(x,y, mode='constant', origin=origin)
return z