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# scipy.ndimage.generic_laplace

`scipy.ndimage.``generic_laplace`(input, derivative2, output=None, mode='reflect', cval=0.0, extra_arguments=(), extra_keywords=None)

  N-dimensional Laplace filter using a provided second derivative function

  Parameters:

  input : array_like

  > Input array to filter.

  derivative2 : callable

  > Callable with the following signature:

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

  > See extra_arguments, extra_keywords below.

  output : array, optional

  > The output parameter passes an array in which to store the filter output. Output array should have different name as compared to input array to avoid aliasing errors.

  mode : str or sequence, optional

  > The mode parameter determines how the array borders are handled. Valid modes are {‘reflect’, ‘constant’, ‘nearest’, ‘mirror’, ‘wrap’}. cval is the value used when mode is equal to ‘constant’. A list of modes with length equal to the number of axes can be provided to specify different modes for different axes. Default is ‘reflect’

  cval : scalar, optional

  > Value to fill past edges of input if mode is ‘constant’. Default is 0.0

  extra_keywords : dict, optional

  > dict of extra keyword arguments to pass to passed function

  extra_arguments : sequence, optional

  > Sequence of extra positional arguments to pass to passed function