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Github Actions doc build after commit eabbc99
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bashtage committed Sep 20, 2024
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15 changes: 7 additions & 8 deletions devel/_modules/index.html
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<title>Overview: module code - RandomGen 1.26.1</title>
<title>Overview: module code - RandomGen v1.26.2 (+53)</title>



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<style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style>


<link rel="stylesheet" type="text/css" href="../_static/sphinx_immaterial_theme.af531f03affe68837.min.css?v=2410bb73" />
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<header class="md-header" data-md-component="header">
<nav class="md-header__inner md-grid" aria-label="Header">
<a href="../index.html" title="RandomGen 1.26.1" class="md-header__button md-logo" aria-label="RandomGen 1.26.1" data-md-component="logo">
<a href="../index.html" title="RandomGen v1.26.2 (+53)" class="md-header__button md-logo" aria-label="RandomGen v1.26.2 (+53)" data-md-component="logo">
<img src="../_static/casino.svg" alt="logo">
</a>
<label class="md-header__button md-icon" for="__drawer">
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<div class="md-header__ellipsis">
<div class="md-header__topic">
<span class="md-ellipsis">
RandomGen 1.26.1
RandomGen v1.26.2 (+53)
</span>
</div>
<div class="md-header__topic" data-md-component="header-topic">
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<nav class="md-nav md-nav--primary" aria-label="Navigation" data-md-level="0">
<label class="md-nav__title" for="__drawer">
<a href="../index.html" title="RandomGen 1.26.1" class="md-nav__button md-logo" aria-label="RandomGen 1.26.1" data-md-component="logo">
<a href="../index.html" title="RandomGen v1.26.2 (+53)" class="md-nav__button md-logo" aria-label="RandomGen v1.26.2 (+53)" data-md-component="logo">
<img src="../_static/casino.svg" alt="logo">
</a>
RandomGen 1.26.1
RandomGen v1.26.2 (+53)
</label>

<div class="md-nav__source">
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<li><a href="randomgen/lxm.html">randomgen.lxm</a></li>
<li><a href="randomgen/mt19937.html">randomgen.mt19937</a></li>
<li><a href="randomgen/mt64.html">randomgen.mt64</a></li>
<li><a href="randomgen/mtrand.html">randomgen.mtrand</a></li>
<li><a href="randomgen/pcg32.html">randomgen.pcg32</a></li>
<li><a href="randomgen/pcg64.html">randomgen.pcg64</a></li>
<li><a href="randomgen/philox.html">randomgen.philox</a></li>
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Created using
<a href="https://www.sphinx-doc.org/" target="_blank" rel="noopener">Sphinx</a>
7.2.6.
8.0.2.
and
<a href="https://github.com/jbms/sphinx-immaterial/" target="_blank" rel="noopener">Sphinx-Immaterial</a>

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4 changes: 2 additions & 2 deletions devel/_sources/change-log.rst.txt
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- ``choice`` pulled in upstream performance improvement that
use a hash set when choosing without replacement and without user-provided probabilities.
- Added support for :class:`~randomgen.seed_sequence.SeedSequence` (and NumPy's ``SeedSequence``).
- Fixed a bug that affected both :class:`~randomgen.generator.Generator.randint`
- Fixed a bug that affected both ``randomgen.generator.Generator.randint``
in ``Generator`` and ``randint``
in ``RandomState`` when ``high=2**32``. This value is inbounds for
a 32-bit unsigned closed interval generator, and so should have been redirected to
a 32-bit generator. It was erroneously sent to the 64-bit path. The random values produced
are fully random but inefficient. This fix breaks the stream in :class:`~randomgen.generator.Generator
are fully random but inefficient. This fix breaks the stream in ``randomgen.generator.Generator``
is the value for ``high`` is used. The fix restores ``RandomState`` to
NumPy 1.16 compatibility.
only affects the output if ``dtype`` is ``'int64'``
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7 changes: 2 additions & 5 deletions devel/_sources/generator.rst.txt
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.. danger::

``Generator`` has been **removed**. You should be using :class:`numpy.random.Generator`.
``Generator`` has been completely **removed** in randomgen 2.0.0.
You should be using :class:`numpy.random.Generator`.

.. currentmodule:: randomgen.generator

.. autoclass::
Generator
2 changes: 1 addition & 1 deletion devel/_sources/index.rst.txt
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.. code-block:: python
rg = Generator(AESCounter(12345, mode="sequence"))
rg = Generator(AESCounter(12345))
rg.random()
History
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11 changes: 4 additions & 7 deletions devel/_sources/legacy.rst.txt
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.. danger::

``RandomState`` has been **removed**. You should be using :class:`numpy.random.Generator`,
or if you must have backward compatibility with NumPy before 1.17, :class:`numpy.random.RandomState`.

.. currentmodule:: randomgen.mtrand

.. autoclass::
RandomState
``RandomState`` has been completely **removed** in randomgen 2.0.0.
You should be using :class:`numpy.random.Generator`, or if you must
have full stability (e.g., for writing tests) or backward compatibility
with NumPy before 1.17, :class:`numpy.random.RandomState`.
19 changes: 10 additions & 9 deletions devel/_sources/multithreading.rst.txt
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Multithreaded Generation
========================

The four core distributions all allow existing arrays to be filled using the
``out`` keyword argument. Existing arrays need to be contiguous and
well-behaved (writable and aligned). Under normal circumstances, arrays
created using the common constructors such as :meth:`numpy.empty` will satisfy
these requirements.
The four core distributions in :class:`~numpy.random.Generator` all allow
existing arrays to be filled using the ``out`` keyword argument.
Existing arrays need to be contiguous and well-behaved (writable and aligned).
Under normal circumstances, arrays created using the common constructors such
as :meth:`numpy.empty` will satisfy 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 PRNG is
xorshift2014 which is fast, has a long period and supports using ``jumped`` to
xorshift256 which is fast, has a long period and supports using ``jumped`` to
advance the state. The random numbers generated are reproducible in the sense
that the same seed will produce the same outputs.

.. code-block:: ipython
from randomgen import Xoshiro256
import multiprocessing
import concurrent.futures
import numpy as np
import warnings
warnings.filterwarnings("ignore", "Generator", FutureWarning)
from numpy.random import Generator
from randomgen import Xoshiro256
class MultithreadedRNG(object):
def __init__(self, n, seed=None, threads=None):
last_bg = Xoshiro256(seed, mode="sequence")
last_bg = Xoshiro256(seed)
if threads is None:
threads = multiprocessing.cpu_count()
self.threads = threads
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