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# scipy.ndimage.gaussian_gradient_magnitude

`scipy.ndimage.``gaussian_gradient_magnitude`(input, sigma, output=None, mode='reflect', cval=0.0, **kwargs)

  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

  Extra keyword arguments will be passed to gaussian_filter().