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Diffstat (limited to 'doc/source/reference/random/generator.rst')
| -rw-r--r-- | doc/source/reference/random/generator.rst | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/doc/source/reference/random/generator.rst b/doc/source/reference/random/generator.rst index a359d2253..7934be98a 100644 --- a/doc/source/reference/random/generator.rst +++ b/doc/source/reference/random/generator.rst @@ -71,13 +71,13 @@ By default, `Generator.permuted` returns a copy. To operate in-place with `Generator.permuted`, pass the same array as the first argument *and* as the value of the ``out`` parameter. For example, - >>> rg = np.random.default_rng() + >>> rng = np.random.default_rng() >>> x = np.arange(0, 15).reshape(3, 5) >>> x array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14]]) - >>> y = rg.permuted(x, axis=1, out=x) + >>> y = rng.permuted(x, axis=1, out=x) >>> x array([[ 1, 0, 2, 4, 3], # random [ 6, 7, 8, 9, 5], @@ -97,13 +97,13 @@ which dimension of the input array to use as the sequence. In the case of a two-dimensional array, ``axis=0`` will, in effect, rearrange the rows of the array, and ``axis=1`` will rearrange the columns. For example - >>> rg = np.random.default_rng() + >>> rng = np.random.default_rng() >>> x = np.arange(0, 15).reshape(3, 5) >>> x array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14]]) - >>> rg.permutation(x, axis=1) + >>> rng.permutation(x, axis=1) array([[ 1, 3, 2, 0, 4], # random [ 6, 8, 7, 5, 9], [11, 13, 12, 10, 14]]) @@ -116,7 +116,7 @@ how `numpy.sort` treats it. Each slice along the given axis is shuffled independently of the others. Compare the following example of the use of `Generator.permuted` to the above example of `Generator.permutation`: - >>> rg.permuted(x, axis=1) + >>> rng.permuted(x, axis=1) array([[ 1, 0, 2, 4, 3], # random [ 5, 7, 6, 9, 8], [10, 14, 12, 13, 11]]) @@ -131,9 +131,9 @@ Shuffling non-NumPy sequences a sequence that is not a NumPy array, it shuffles that sequence in-place. For example, - >>> rg = np.random.default_rng() + >>> rng = np.random.default_rng() >>> a = ['A', 'B', 'C', 'D', 'E'] - >>> rg.shuffle(a) # shuffle the list in-place + >>> rng.shuffle(a) # shuffle the list in-place >>> a ['B', 'D', 'A', 'E', 'C'] # random |