#### Previous topic

scipy.ndimage.generic_gradient_magnitude

#### Next topic

scipy.ndimage.laplace

# 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