cupyx.scipy.ndimage.generic_laplace(input, derivative2, output=None, mode='reflect', cval=0.0, extra_arguments=(), extra_keywords=None)[source]#

Multi-dimensional Laplace filter using a provided second derivative function.

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

  • derivative2 (callable) –

    Function or other callable with the following signature that is called once per axis:

    derivative2(input, axis, output, mode, cval,
                *extra_arguments, **extra_keywords)

    where input and output are cupy.ndarray, axis is an int from 0 to the number of dimensions, and mode, cval, extra_arguments, extra_keywords are the values given to this function.

  • 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.

  • extra_arguments (sequence, optional) – Sequence of extra positional arguments to pass to derivative2.

  • extra_keywords (dict, optional) – dict of extra keyword arguments to pass derivative2.


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.