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Jul 23rd, 2019
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  1. import numpy as np
  2. from scipy import signal
  3.  
  4. def gaussian_kernel(n, std, normalised=False):
  5. '''
  6. Generates a n x n matrix with a centered gaussian
  7. of standard deviation std centered on it. If normalised,
  8. its volume equals 1.'''
  9. gaussian1D = signal.gaussian(n, std)
  10. gaussian2D = np.outer(gaussian1D, gaussian1D)
  11. if normalised:
  12. gaussian2D /= (2*np.pi*(std**2))
  13. return gaussian2D
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