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.