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scipy.signal.

# medfilt

scipy.signal.medfilt(volume, kernel_size=None)

  Perform a median filter on an N-dimensional array.

  Apply a median filter to the input array using a local window-size given by kernel_size. The array will automatically be zero-padded.

  Parameters:
    volume array_like

      An N-dimensional input array.

    kernel_size array_like, optional

      A scalar or an N-length list giving the size of the median filter window in each dimension. Elements of kernel_size should be odd. If kernel_size is a scalar, then this scalar is used as the size in each dimension. Default size is 3 for each dimension.

  Returns:
    out ndarray

      An array the same size as input containing the median filtered result.

  Warns:
    UserWarning

      If array size is smaller than kernel size along any dimension

  See also

  `scipy.ndimage.median_filter`
  `scipy.signal.medfilt2d`

  Notes

  Array API Standard Support

  `medfilt` 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.