scipy.ndimage.filters.gaussian_gradient_magnitude(input, sigma, output=None, mode='reflect', cval=0.0)[source]

Calculate a multidimensional gradient magnitude using gaussian derivatives.

Parameters :

input : array-like

input array to filter

sigma : scalar or sequence of scalars

The standard deviations of the Gaussian filter are given for each axis as a sequence, or as a single number, in which case it is equal for all axes..

output : array, optional

The output parameter passes an array in which to store the filter output.

mode : {‘reflect’,’constant’,’nearest’,’mirror’, ‘wrap’}, optional

The mode parameter determines how the array borders are handled, where cval is the value when mode is equal to ‘constant’. Default is ‘reflect’

cval : scalar, optional

Value to fill past edges of input if mode is ‘constant’. Default is 0.0

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