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scipy.ndimage.

# morphological_laplace

scipy.ndimage.morphological_laplace(input, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0, *, axes=None)

  Multidimensional morphological laplace.

  Parameters:
    input array_like

      Input.

    size tuple of ints

      Shape of a flat and full structuring element used for the mathematical morphology operations. Optional if footprint or structure is provided.

    footprint array of ints, optional

      Positions of non-infinite elements of a flat structuring element used for the morphology operations.

    structure array of ints, optional

      Structuring element used for the morphology operations. structure may be a non-flat structuring element. The structure array applies offsets to the pixels in a neighborhood (the offset is additive during dilation and subtractive during erosion)

    output ndarray, optional

      An output array can optionally be provided.

    mode{‘reflect’,’constant’,’nearest’,’mirror’, ‘wrap’}, optional

      The mode parameter determines how the array borders are handled. For ‘constant’ mode, values beyond borders are set to be cval. Default is ‘reflect’.

    cval scalar, optional

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

    origin origin, optional

      The origin parameter controls the placement of the filter.

    axes tuple of int or None

      The axes over which to apply the filter. If None, input is filtered along all axes. If an origin tuple is provided, its length must match the number of axes.

  Returns:
    morphological_laplace ndarray

      Output

  Notes

  Array API Standard Support

  `morphological_laplace` has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable `SCIPY_ARRAY_API=1` and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

  Library | CPU | GPU
  --- | --- | ---
  NumPy | ✅ | n/a
  CuPy | n/a | ✅
  PyTorch | ✅ | ⛔
  JAX | ⚠️ no JIT | ⛔
  Dask | ⚠️ computes graph | n/a

  See Support for the array API standard for more information.