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

xarray_like, at least one-dimensional: Array to be shuffled.
axisint, 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.
outndarray, 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

numpy.random.Generator.permutation

numpy.random.Generator.beta