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Diffstat (limited to 'doc/source/reference/random/multithreading.rst')
| -rw-r--r-- | doc/source/reference/random/multithreading.rst | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/doc/source/reference/random/multithreading.rst b/doc/source/reference/random/multithreading.rst index 7ce90af99..849d64d4e 100644 --- a/doc/source/reference/random/multithreading.rst +++ b/doc/source/reference/random/multithreading.rst @@ -10,21 +10,21 @@ these requirements. This example makes use of Python 3 :mod:`concurrent.futures` to fill an array using multiple threads. Threads are long-lived so that repeated calls do not require any additional overheads from thread creation. The underlying -BitGenerator is `Xoshiro256` which is fast, has a long period and supports -using `Xoshiro256.jumped` to return a new generator while advancing the +BitGenerator is `PCG64` which is fast, has a long period and supports +using `PCG64.jumped` to return a new generator while advancing the state. The random numbers generated are reproducible in the sense that the same seed will produce the same outputs. .. code-block:: ipython - from numpy.random import Generator, Xoshiro256 + from numpy.random import Generator, PCG64 import multiprocessing import concurrent.futures import numpy as np class MultithreadedRNG(object): def __init__(self, n, seed=None, threads=None): - rg = Xoshiro256(seed) + rg = PCG64(seed) if threads is None: threads = multiprocessing.cpu_count() self.threads = threads @@ -89,7 +89,7 @@ The single threaded call directly uses the BitGenerator. .. code-block:: ipython In [5]: values = np.empty(10000000) - ...: rg = Generator(Xoshiro256()) + ...: rg = Generator(PCG64()) ...: %timeit rg.standard_normal(out=values) 99.6 ms ± 222 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) @@ -100,7 +100,7 @@ that does not use an existing array due to array creation overhead. .. code-block:: ipython - In [6]: rg = Generator(Xoshiro256()) + In [6]: rg = Generator(PCG64()) ...: %timeit rg.standard_normal(10000000) 125 ms ± 309 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) |