a guest Jul 23rd, 2019 54 Never
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- 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
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