def gaussian_kernel ( sigma , truncate = 4.0 ) : sigma = float ( sigma ) radius = int ( truncate * sigma + 0.5 ) x , y = np . mgrid [ - radius : radius + 1 , - radius : radius + 1 ] sigma = sigma ** 2 k = 2 * np . exp ( - 0.5 * ( x ** 2 + y ** 2 ) / sigma ) k = k / np . sum ( k ) return k
gaussian kernel python with sigma and width
Return Gaussian that truncates at the given number of std deviations .
def gaussian_kernel(sigma, truncate=4.0):
    """Return Gaussian that truncates at the given number of std deviations.

    Adapted from https://github.com/nicjhan/gaussian-filter
    """

    sigma = float(sigma)
    radius = int(truncate * sigma + 0.5)

    x, y = np.mgrid[-radius:radius + 1, -radius:radius + 1]
    sigma = sigma ** 2

    k = 2 * np.exp(-0.5 * (x ** 2 + y ** 2) / sigma)
    k = k / np.sum(k)

    return k