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

Multi-dimensional gradient magnitude using Gaussian derivatives.

  • input (cupy.ndarray) – The input array.

  • sigma (scalar or sequence of scalar) – Standard deviations for each axis of Gaussian kernel. A single value applies to all axes.

  • output (cupy.ndarray, dtype or None) – The array in which to place the output. Default is is same dtype as the input.

  • mode (str) – The array borders are handled according to the given mode ('reflect', 'constant', 'nearest', 'mirror', 'wrap'). Default is 'reflect'.

  • cval (scalar) – Value to fill past edges of input if mode is 'constant'. Default is 0.0.

  • kwargs (dict, optional) – dict of extra keyword arguments to pass gaussian_filter().


The result of the filtering.

Return type



When the output data type is integral (or when no output is provided and input is integral) the results may not perfectly match the results from SciPy due to floating-point rounding of intermediate results.