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 onedimensional
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
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 inplace, 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 isout
:>>> y is x True