# numpy.random.Generator.permuted

method

random.Generator.permuted(x, axis=None, out=None)

  Randomly permute x along axis axis.

  Unlike `shuffle`, each slice along the given axis is shuffled independently of the others.

  Parameters
    x array_like, at least one-dimensional

      Array to be shuffled.

    axis int, optional

      Slices of x in this axis are shuffled. Each slice is shuffled independently of the others. If axis is None, the flattened array is shuffled.

    out ndarray, optional

      If given, this is the destinaton of the shuffled array. If out is None, a shuffled copy of the array is returned.

  Returns
    ndarray

      If out is None, a shuffled copy of x is returned. Otherwise, the shuffled array is stored in out, and out is returned

  See also

  `shuffle`
  `permutation`

  Examples

  Create a `numpy.random.Generator` instance:

      >>> rng = np.random.default_rng()

  Create a test array:

      >>> x = np.arange(24).reshape(3, 8)
      >>> 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]])

  Shuffle the rows of x:

      >>> y = rng.permuted(x, axis=1)
      >>> y
      array([[ 4,  3,  6,  7,  1,  2,  5,  0],  # random
             [15, 10, 14,  9, 12, 11,  8, 13],
             [17, 16, 20, 21, 18, 22, 23, 19]])

  x has not been modified:

      >>> 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]])

  To shuffle the rows of x in-place, pass x as the out parameter:

      >>> y = rng.permuted(x, axis=1, out=x)
      >>> x
      array([[ 3,  0,  4,  7,  1,  6,  2,  5],  # random
             [ 8, 14, 13,  9, 12, 11, 15, 10],
             [17, 18, 16, 22, 19, 23, 20, 21]])

  Note that when the `out` parameter is given, the return value is `out`:

      >>> y is x
      True

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