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scipy.signal.

# order_filter

scipy.signal.order_filter(a, domain, rank)

  Perform an order filter on an N-D array.

  Perform an order filter on the array in. The domain argument acts as a mask centered over each pixel. The non-zero elements of domain are used to select elements surrounding each input pixel which are placed in a list. The list is sorted, and the output for that pixel is the element corresponding to rank in the sorted list.

  Parameters:
    a ndarray

      The N-dimensional input array.

    domain array_like

      A mask array with the same number of dimensions as a. Each dimension should have an odd number of elements.

    rank int

      A non-negative integer which selects the element from the sorted list (0 corresponds to the smallest element, 1 is the next smallest element, etc.).

  Returns:
    out ndarray

      The results of the order filter in an array with the same shape as a.

  Notes

  Array API Standard Support

  `order_filter` 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.

  Examples

      >>> import numpy as np
      >>> from scipy import signal
      >>> x = np.arange(25).reshape(5, 5)
      >>> domain = np.identity(3)
      >>> x
      array([[ 0,  1,  2,  3,  4],
             [ 5,  6,  7,  8,  9],
             [10, 11, 12, 13, 14],
             [15, 16, 17, 18, 19],
             [20, 21, 22, 23, 24]])
      >>> signal.order_filter(x, domain, 0)
      array([[  0,   0,   0,   0,   0],
             [  0,   0,   1,   2,   0],
             [  0,   5,   6,   7,   0],
             [  0,  10,  11,  12,   0],
             [  0,   0,   0,   0,   0]])
      >>> signal.order_filter(x, domain, 2)
      array([[  6,   7,   8,   9,   4],
             [ 11,  12,  13,  14,   9],
             [ 16,  17,  18,  19,  14],
             [ 21,  22,  23,  24,  19],
             [ 20,  21,  22,  23,  24]])