create a n dimensional gaussian kernel for the given shape

n dimensional gaus kernel

import numpy as np


def gaussian(shape, sigma=1.0, mu=0.0):
    """ create a n dimensional gaussian kernel for the given shape """
    m = np.meshgrid(*[np.linspace(-1,1,s) for s in shape])
    d = np.sqrt(np.sum([x*x for x in m], axis=0))
    g = np.exp(-( (d-mu)**2 / ( 2.0 * sigma**2 ) ) )
    return g / np.sum(g)


if __name__ == "__main__":
    from matplotlib import pyplot as plt
    fig, ax = plt.subplots(2)
    ax[0].imshow(gaussian([20,10]))
    ax[1].plot(gaussian([100]))
    plt.show()