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

Multi-dimensional Laplace filter using Gaussian second 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.