import numpy as np from scipy import signal def gaussian_kernel(n, std, normalised=False): ''' Generates a n x n matrix with a centered gaussian of standard deviation std centered on it. If normalised, its volume equals 1.''' gaussian1D = signal.gaussian(n, std) gaussian2D = np.outer(gaussian1D, gaussian1D) if normalised: gaussian2D /= (2*np.pi*(std**2)) return gaussian2D