| Name | simplerandom JSON |
| Version |
0.13.6
JSON |
| download |
| home_page | |
| Summary | Simple random number generators |
| upload_time | 2023-10-16 10:53:53 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.6 |
| license | ---------------------------------------------------------------------------- Copyright (c) 2011 Craig McQueen Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ---------------------------------------------------------------------------- |
| keywords |
simple
random
pseudorandom
rng
prng
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
=============
Simple Random
=============
:Author: Craig McQueen
:Contact: http://craig.mcqueen.id.au/
:Copyright: 2010 Craig McQueen
Simple pseudo-random number generators.
-----
Intro
-----
The ``simplerandom`` package is provided, which contains modules containing
classes for various simple pseudo-random number generators.
One module provides Python iterators, which generate simple unsigned 32-bit
integers identical to their C counterparts.
Another module provides random classes that are sub-classed from the class
``Random`` in the ``random`` module of the standard Python library.
Why use this package? These random number generators are very simple, which
has two main advantages:
* It is easy to port them to a different platform and/or language. It can be
useful to be able to implement the identical algorithm on multiple
platforms and/or languages.
* Small and simple generators can be more appropriate for small embedded
systems, with limited RAM and ROM.
An equivalent C implementation (of the Python ``simplerandom.iterators``
module) has been created. See:
http://github.com/cmcqueen/simplerandom
Algorithms
``````````
Most algorithms were obtained from two newsgroup posts by George Marsaglia
[#marsaglia1999]_ [#marsaglia2003]_. However, some modifications have been
made. From [#rose]_, it seems that the SHR3 algorithm defined in
[#marsaglia1999]_ is flawed and should not be used. It doesn't actually have a
period of 2**32-1 as expected, but has 64 different cycles, some with very
short periods. The SHR3 in the 2003 post is very similar, but with two shift
values swapped. It has a period of 2**32-1 as expected.
We still find KISS from [#marsaglia1999]_ useful mainly because it uses 32-bit
calculations for MWC, which can be more suitable for small embedded systems.
So we define KISS that uses a MWC based on [#marsaglia1999]_, but the Cong and
SHR3 from [#marsaglia2003]_.
From Pierre L'Ecuyer [#lecuyer1999]_ [#lecuyer1996]_, the Combined LFSR
(Tausworthe) LFSR113 algorithm [#lfsr113]_ and LFSR88 (aka Taus88) have been
implemented.
References
``````````
.. [#marsaglia1999] | `Random Numbers for C\: End, at last?`__
| George Marsaglia
| Newsgroup post, sci.stat.math and others, Thu, 21 Jan 1999
.. __:
.. _Random Numbers for C\: End, at last?:
http://www.cse.yorku.ca/~oz/marsaglia-rng.html
.. [#marsaglia2003] | `RNGs`__
| George Marsaglia
| Newsgroup post, sci.math, 26 Feb 2003
.. __:
.. _RNGs:
http://groups.google.com/group/sci.math/msg/9959175f66dd138f
.. [#rose] | `KISS: A Bit Too Simple`__
| Greg Rose
| Qualcomm Inc.
.. __:
.. _KISS\: A Bit Too Simple:
http://eprint.iacr.org/2011/007.pdf
.. [#lecuyer1999] | `Tables of Maximally-Equidistributed Combined LFSR Generators`__
| Pierre L'Ecuyer
| Mathematics of Computation, 68, 225 (1999), 261–269.
.. __:
.. _Tables of Maximally-Equidistributed Combined LFSR Generators:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.3639
.. [#lfsr113] | `LFSR113 C double implementation`__
| Pierre L'Ecuyer
.. __:
.. _LFSR113 C double implementation:
http://www.iro.umontreal.ca/~simardr/rng/lfsr113.c
.. [#lecuyer1996] | `Maximally Equidistributed Combined Tausworthe Generators`__
| P. L'Ecuyer
| Mathematics of Computation, 65, 213 (1996), 203–213.
.. __:
.. _Maximally Equidistributed Combined Tausworthe Generators:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.4155
----------------
Modules Provided
----------------
========================== ===========================================================================
Module Description
========================== ===========================================================================
``simplerandom.iterators`` Iterator classes, which generate unsigned 32-bit integers.
``simplerandom.random`` Classes that conform to standard Python ``random.Random`` API.
========================== ===========================================================================
Random Number Generators Provided
`````````````````````````````````
In ``simplerandom.iterators``, the following pseudo-random number generators are provided:
========================== ===========================================================================
Generator Notes
========================== ===========================================================================
``MWC1`` Two 32-bit MWCs combined. From [#marsaglia1999]_.
``MWC2`` Very similar to ``MWC1``, but slightly modified to improve its statistical properties.
``Cong`` From [#marsaglia2003]_.
``SHR3`` From [#marsaglia2003]_.
``MWC64`` A single 64-bit multiply-with-carry calculation. From [#marsaglia2003]_.
``KISS`` Combination of MWC2, Cong and SHR3. Based on [#marsaglia1999]_ but using Cong and SHR3 from [#marsaglia2003]_, and the modified MWC.
``KISS2`` Combination of MWC64, Cong and SHR3. From [#marsaglia2003]_.
``LFSR113`` Combined LFSR (Tausworthe) random number generator by L'Ecuyer. From [#lecuyer1999]_ [#lfsr113]_.
``LFSR88`` Combined LFSR (Tausworthe) random number generator by L'Ecuyer. From [#lecuyer1996]_.
========================== ===========================================================================
These generators are Python iterators, of infinite length (they never raise
``StopIteration``). They implement the ``__next__()`` function to generate the
next random integer. All the generators output 32-bit unsigned values, and
take one or more 32-bit seed values during initialisation/seeding.
In ``simplerandom.random``, pseudo-random number generators are provided which
have the same names as those in ``simplerandom.iterators``, but these
generators implement the standard Python ``random.Random`` API. Each generator
uses the iterator of the same name in ``simplerandom.iterators`` to generate
the random bits used to produce the random floats. The ``jumpahead()`` function
(in the style of the Python 2.x API) is implemented in all cases, even though
``jumpahead()`` has officially been removed from the Python 3.x ``random`` API.
-----
Usage
-----
Iterators
`````````
>>> import simplerandom.iterators as sri
>>> rng = sri.KISS(123958, 34987243, 3495825239, 2398172431)
>>> next(rng)
702862187
>>> next(rng)
13888114
>>> next(rng)
699722976
Random class API
````````````````
>>> import simplerandom.random as srr
>>> rng = srr.KISS(258725234)
>>> rng.random()
0.0925917826051541
>>> rng.random()
0.02901686453730415
>>> rng.random()
0.9024972981686489
-------------------------
Supported Python Versions
-------------------------
Python >= 3.10 are supported.
Python versions < 3.10 might work, but have not been tested.
-------------
Use of Cython
-------------
`Cython`_ is used to make a fast implementation of ``simplerandom.iterators``.
Cython creates a ``.c`` file that can be compiled into a Python binary
extension module.
The ``simplerandom`` source distribution package includes a ``.c`` file that
was created with Cython, so it is not necessary to have Cython installed to
install ``simplerandom``.
The Cython ``.pyx`` file is also included, if you want to modify the Cython
source code, in which case you do need to have Cython installed. But by
default, ``setup.py`` builds the extension from the ``.c`` file (to ensure
that the build doesn't fail due to particular Cython version issues). If you
wish to build using Cython from the included ``.pyx`` file, you must set
``USE_CYTHON=True`` in ``setup.py``.
.. _Cython:
http://cython.org/
------------
Installation
------------
The simplerandom package is installed using ``distutils``. If you have the tools
installed to build a Python extension module, run the following command::
python setup.py install
If you cannot build the C extension, you may install just the pure Python
implementation, using the following command::
python setup.py build_py install --skip-build
------------
Unit Testing
------------
Unit testing of the iterators is in ``simplerandom.iterators.test``. It
duplicates the tests of the C algorithms given in the original newsgroup post
[#marsaglia1999]_, as well as other unit tests.
To run unit tests::
python -m simplerandom.iterators.test
A more thorough unit test suite is needed. A unit test suite for
``simplerandom.random`` is needed.
-------
License
-------
The code is released under the MIT license. See LICENSE.txt for details.
Raw data
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"description": "=============\r\nSimple Random\r\n=============\r\n\r\n:Author: Craig McQueen\r\n:Contact: http://craig.mcqueen.id.au/\r\n:Copyright: 2010 Craig McQueen\r\n\r\n\r\nSimple pseudo-random number generators.\r\n\r\n-----\r\nIntro\r\n-----\r\n\r\nThe ``simplerandom`` package is provided, which contains modules containing\r\nclasses for various simple pseudo-random number generators.\r\n\r\nOne module provides Python iterators, which generate simple unsigned 32-bit\r\nintegers identical to their C counterparts.\r\n\r\nAnother module provides random classes that are sub-classed from the class\r\n``Random`` in the ``random`` module of the standard Python library.\r\n\r\nWhy use this package? These random number generators are very simple, which\r\nhas two main advantages:\r\n\r\n* It is easy to port them to a different platform and/or language. It can be\r\n useful to be able to implement the identical algorithm on multiple\r\n platforms and/or languages.\r\n* Small and simple generators can be more appropriate for small embedded\r\n systems, with limited RAM and ROM.\r\n\r\nAn equivalent C implementation (of the Python ``simplerandom.iterators``\r\nmodule) has been created. See:\r\n\r\n http://github.com/cmcqueen/simplerandom\r\n\r\nAlgorithms\r\n``````````\r\n\r\nMost algorithms were obtained from two newsgroup posts by George Marsaglia\r\n[#marsaglia1999]_ [#marsaglia2003]_. However, some modifications have been\r\nmade. From [#rose]_, it seems that the SHR3 algorithm defined in\r\n[#marsaglia1999]_ is flawed and should not be used. It doesn't actually have a\r\nperiod of 2**32-1 as expected, but has 64 different cycles, some with very\r\nshort periods. The SHR3 in the 2003 post is very similar, but with two shift\r\nvalues swapped. It has a period of 2**32-1 as expected.\r\n\r\nWe still find KISS from [#marsaglia1999]_ useful mainly because it uses 32-bit\r\ncalculations for MWC, which can be more suitable for small embedded systems.\r\nSo we define KISS that uses a MWC based on [#marsaglia1999]_, but the Cong and\r\nSHR3 from [#marsaglia2003]_.\r\n\r\nFrom Pierre L'Ecuyer [#lecuyer1999]_ [#lecuyer1996]_, the Combined LFSR\r\n(Tausworthe) LFSR113 algorithm [#lfsr113]_ and LFSR88 (aka Taus88) have been\r\nimplemented.\r\n\r\n\r\nReferences\r\n``````````\r\n\r\n.. [#marsaglia1999] | `Random Numbers for C\\: End, at last?`__\r\n | George Marsaglia\r\n | Newsgroup post, sci.stat.math and others, Thu, 21 Jan 1999\r\n\r\n.. __:\r\n.. _Random Numbers for C\\: End, at last?:\r\n http://www.cse.yorku.ca/~oz/marsaglia-rng.html\r\n\r\n.. [#marsaglia2003] | `RNGs`__\r\n | George Marsaglia\r\n | Newsgroup post, sci.math, 26 Feb 2003\r\n\r\n.. __:\r\n.. _RNGs:\r\n http://groups.google.com/group/sci.math/msg/9959175f66dd138f\r\n\r\n.. [#rose] | `KISS: A Bit Too Simple`__\r\n | Greg Rose\r\n | Qualcomm Inc.\r\n\r\n.. __:\r\n.. _KISS\\: A Bit Too Simple:\r\n http://eprint.iacr.org/2011/007.pdf\r\n\r\n.. [#lecuyer1999] | `Tables of Maximally-Equidistributed Combined LFSR Generators`__\r\n | Pierre L'Ecuyer\r\n | Mathematics of Computation, 68, 225 (1999), 261\u2013269.\r\n\r\n.. __:\r\n.. _Tables of Maximally-Equidistributed Combined LFSR Generators:\r\n http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.3639\r\n\r\n.. [#lfsr113] | `LFSR113 C double implementation`__\r\n | Pierre L'Ecuyer\r\n\r\n.. __:\r\n.. _LFSR113 C double implementation:\r\n http://www.iro.umontreal.ca/~simardr/rng/lfsr113.c\r\n\r\n.. [#lecuyer1996] | `Maximally Equidistributed Combined Tausworthe Generators`__\r\n | P. L'Ecuyer\r\n | Mathematics of Computation, 65, 213 (1996), 203\u2013213.\r\n\r\n.. __:\r\n.. _Maximally Equidistributed Combined Tausworthe Generators:\r\n http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.4155\r\n\r\n\r\n----------------\r\nModules Provided\r\n----------------\r\n\r\n========================== ===========================================================================\r\nModule Description\r\n========================== ===========================================================================\r\n``simplerandom.iterators`` Iterator classes, which generate unsigned 32-bit integers.\r\n``simplerandom.random`` Classes that conform to standard Python ``random.Random`` API.\r\n========================== ===========================================================================\r\n\r\n\r\nRandom Number Generators Provided\r\n`````````````````````````````````\r\n\r\nIn ``simplerandom.iterators``, the following pseudo-random number generators are provided:\r\n\r\n========================== ===========================================================================\r\nGenerator Notes\r\n========================== ===========================================================================\r\n``MWC1`` Two 32-bit MWCs combined. From [#marsaglia1999]_.\r\n``MWC2`` Very similar to ``MWC1``, but slightly modified to improve its statistical properties.\r\n``Cong`` From [#marsaglia2003]_.\r\n``SHR3`` From [#marsaglia2003]_.\r\n``MWC64`` A single 64-bit multiply-with-carry calculation. From [#marsaglia2003]_.\r\n``KISS`` Combination of MWC2, Cong and SHR3. Based on [#marsaglia1999]_ but using Cong and SHR3 from [#marsaglia2003]_, and the modified MWC.\r\n``KISS2`` Combination of MWC64, Cong and SHR3. From [#marsaglia2003]_.\r\n``LFSR113`` Combined LFSR (Tausworthe) random number generator by L'Ecuyer. From [#lecuyer1999]_ [#lfsr113]_.\r\n``LFSR88`` Combined LFSR (Tausworthe) random number generator by L'Ecuyer. From [#lecuyer1996]_.\r\n========================== ===========================================================================\r\n\r\nThese generators are Python iterators, of infinite length (they never raise\r\n``StopIteration``). They implement the ``__next__()`` function to generate the\r\nnext random integer. All the generators output 32-bit unsigned values, and\r\ntake one or more 32-bit seed values during initialisation/seeding.\r\n\r\n\r\nIn ``simplerandom.random``, pseudo-random number generators are provided which\r\nhave the same names as those in ``simplerandom.iterators``, but these\r\ngenerators implement the standard Python ``random.Random`` API. Each generator\r\nuses the iterator of the same name in ``simplerandom.iterators`` to generate\r\nthe random bits used to produce the random floats. The ``jumpahead()`` function\r\n(in the style of the Python 2.x API) is implemented in all cases, even though\r\n``jumpahead()`` has officially been removed from the Python 3.x ``random`` API.\r\n\r\n\r\n-----\r\nUsage\r\n-----\r\n\r\nIterators\r\n`````````\r\n\r\n >>> import simplerandom.iterators as sri\r\n >>> rng = sri.KISS(123958, 34987243, 3495825239, 2398172431)\r\n >>> next(rng)\r\n 702862187\r\n >>> next(rng)\r\n 13888114\r\n >>> next(rng)\r\n 699722976\r\n\r\nRandom class API\r\n````````````````\r\n\r\n >>> import simplerandom.random as srr\r\n >>> rng = srr.KISS(258725234)\r\n >>> rng.random()\r\n 0.0925917826051541\r\n >>> rng.random()\r\n 0.02901686453730415\r\n >>> rng.random()\r\n 0.9024972981686489\r\n\r\n\r\n-------------------------\r\nSupported Python Versions\r\n-------------------------\r\n\r\nPython >= 3.10 are supported.\r\n\r\nPython versions < 3.10 might work, but have not been tested.\r\n\r\n\r\n-------------\r\nUse of Cython\r\n-------------\r\n\r\n`Cython`_ is used to make a fast implementation of ``simplerandom.iterators``.\r\nCython creates a ``.c`` file that can be compiled into a Python binary\r\nextension module.\r\n\r\nThe ``simplerandom`` source distribution package includes a ``.c`` file that\r\nwas created with Cython, so it is not necessary to have Cython installed to\r\ninstall ``simplerandom``.\r\n\r\nThe Cython ``.pyx`` file is also included, if you want to modify the Cython\r\nsource code, in which case you do need to have Cython installed. But by\r\ndefault, ``setup.py`` builds the extension from the ``.c`` file (to ensure\r\nthat the build doesn't fail due to particular Cython version issues). If you\r\nwish to build using Cython from the included ``.pyx`` file, you must set\r\n``USE_CYTHON=True`` in ``setup.py``.\r\n\r\n.. _Cython:\r\n http://cython.org/\r\n\r\n\r\n------------\r\nInstallation\r\n------------\r\n\r\nThe simplerandom package is installed using ``distutils``. If you have the tools\r\ninstalled to build a Python extension module, run the following command::\r\n\r\n python setup.py install\r\n\r\nIf you cannot build the C extension, you may install just the pure Python\r\nimplementation, using the following command::\r\n\r\n python setup.py build_py install --skip-build\r\n\r\n\r\n------------\r\nUnit Testing\r\n------------\r\n\r\nUnit testing of the iterators is in ``simplerandom.iterators.test``. It\r\nduplicates the tests of the C algorithms given in the original newsgroup post\r\n[#marsaglia1999]_, as well as other unit tests.\r\n\r\nTo run unit tests::\r\n\r\n python -m simplerandom.iterators.test\r\n\r\nA more thorough unit test suite is needed. A unit test suite for\r\n``simplerandom.random`` is needed.\r\n\r\n\r\n-------\r\nLicense\r\n-------\r\n\r\nThe code is released under the MIT license. See LICENSE.txt for details.\r\n\r\n",
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"license": "---------------------------------------------------------------------------- Copyright (c) 2011 Craig McQueen Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ---------------------------------------------------------------------------- ",
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