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        "author": "Craig McQueen",
        "author_email": "python@craig.mcqueen.id.au",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Cython",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.1",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Topic :: Scientific/Engineering :: Mathematics"
        ],
        "description": "=============\nSimple Random\n=============\n\n:Author: Craig McQueen\n:Contact: http://craig.mcqueen.id.au/\n:Copyright: 2010 Craig McQueen\n\n\nSimple pseudo-random number generators.\n\n-----\nIntro\n-----\n\nThe ``simplerandom`` package is provided, which contains modules containing\nclasses for various simple pseudo-random number generators.\n\nOne module provides Python iterators, which generate simple unsigned 32-bit\nintegers identical to their C counterparts.\n\nAnother module provides random classes that are sub-classed from the class\n``Random`` in the ``random`` module of the standard Python library.\n\nWhy use this package? These random number generators are very simple, which\nhas two main advantages:\n\n* It is easy to port them to a different platform and/or language. It can be\n  useful to be able to implement the identical algorithm on multiple\n  platforms and/or languages.\n* Small and simple generators can be more appropriate for small embedded\n  systems, with limited RAM and ROM.\n\nAn equivalent C implementation (of the Python ``simplerandom.iterators``\nmodule) has been created. See:\n\n    http://github.com/cmcqueen/simplerandom\n\nAlgorithms\n``````````\n\nMost algorithms were obtained from two newsgroup posts by George Marsaglia\n[#marsaglia1999]_ [#marsaglia2003]_. However, some modifications have been\nmade. From [#rose]_, it seems that the SHR3 algorithm defined in\n[#marsaglia1999]_ is flawed and should not be used. It doesn't actually have a\nperiod of 2**32-1 as expected, but has 64 different cycles, some with very\nshort periods. The SHR3 in the 2003 post is very similar, but with two shift\nvalues swapped. It has a period of 2**32-1 as expected.\n\nWe still find KISS from [#marsaglia1999]_ useful mainly because it uses 32-bit\ncalculations for MWC, which can be more suitable for small embedded systems.\nSo we define KISS that uses a MWC based on [#marsaglia1999]_, but the Cong and\nSHR3 from [#marsaglia2003]_.\n\nFrom Pierre L'Ecuyer [#lecuyer1999]_ [#lecuyer1996]_, the Combined LFSR\n(Tausworthe) LFSR113 algorithm [#lfsr113]_ and LFSR88 (aka Taus88) have been\nimplemented.\n\n\nReferences\n``````````\n\n.. [#marsaglia1999] | `Random Numbers for C\\: End, at last?`__\n                    | George Marsaglia\n                    | Newsgroup post, sci.stat.math and others, Thu, 21 Jan 1999\n\n.. __:\n.. _Random Numbers for C\\: End, at last?:\n    http://www.cse.yorku.ca/~oz/marsaglia-rng.html\n\n.. [#marsaglia2003] | `RNGs`__\n                    | George Marsaglia\n                    | Newsgroup post, sci.math, 26 Feb 2003\n\n.. __:\n.. _RNGs:\n    http://groups.google.com/group/sci.math/msg/9959175f66dd138f\n\n.. [#rose]          | `KISS: A Bit Too Simple`__\n                    | Greg Rose\n                    | Qualcomm Inc.\n\n.. __:\n.. _KISS\\: A Bit Too Simple:\n    http://eprint.iacr.org/2011/007.pdf\n\n.. [#lecuyer1999]   | `Tables of Maximally-Equidistributed Combined LFSR Generators`__\n                    | Pierre L'Ecuyer\n                    | Mathematics of Computation, 68, 225 (1999), 261\u2013269.\n\n.. __:\n.. _Tables of Maximally-Equidistributed Combined LFSR Generators:\n    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.3639\n\n.. [#lfsr113]       | `LFSR113 C double implementation`__\n                    | Pierre L'Ecuyer\n\n.. __:\n.. _LFSR113 C double implementation:\n    http://www.iro.umontreal.ca/~simardr/rng/lfsr113.c\n\n.. [#lecuyer1996]   | `Maximally Equidistributed Combined Tausworthe Generators`__\n                    | P. L'Ecuyer\n                    | Mathematics of Computation, 65, 213 (1996), 203\u2013213. \n\n.. __:\n.. _Maximally Equidistributed Combined Tausworthe Generators:\n    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.4155\n\n\n----------------\nModules Provided\n----------------\n\n==========================  ===========================================================================\nModule                      Description\n==========================  ===========================================================================\n``simplerandom.iterators``  Iterator classes, which generate unsigned 32-bit integers.\n``simplerandom.random``     Classes that conform to standard Python ``random.Random`` API.\n==========================  ===========================================================================\n\n\nRandom Number Generators Provided\n`````````````````````````````````\n\nIn ``simplerandom.iterators``, the following pseudo-random number generators are provided:\n\n==========================  ===========================================================================\nGenerator                   Notes\n==========================  ===========================================================================\n``MWC1``                    Two 32-bit MWCs combined. From [#marsaglia1999]_.\n``MWC2``                    Very similar to ``MWC1``, but slightly modified to improve its statistical properties.\n``Cong``                    From [#marsaglia2003]_.\n``SHR3``                    From [#marsaglia2003]_.\n``MWC64``                   A single 64-bit multiply-with-carry calculation. From [#marsaglia2003]_.\n``KISS``                    Combination of MWC2, Cong and SHR3. Based on [#marsaglia1999]_ but using Cong and SHR3 from [#marsaglia2003]_, and the modified MWC.\n``KISS2``                   Combination of MWC64, Cong and SHR3. From [#marsaglia2003]_.\n``LFSR113``                 Combined LFSR (Tausworthe) random number generator by L'Ecuyer. From [#lecuyer1999]_ [#lfsr113]_.\n``LFSR88``                  Combined LFSR (Tausworthe) random number generator by L'Ecuyer. From [#lecuyer1996]_.\n==========================  ===========================================================================\n\nThese generators are Python iterators, of infinite length (they never raise\n``StopIteration``). They implement the ``next()`` method (``__next__()`` in\nPython 3.x) to generate the next random integer. All the generators output\n32-bit unsigned values, and take one or more 32-bit seed values during\ninitialisation/seeding.\n\n\nIn ``simplerandom.random``, pseudo-random number generators are provided which\nhave the same names as those in ``simplerandom.iterators``, but these\ngenerators implement the standard Python ``random.Random`` API. Each generator\nuses the iterator of the same name in ``simplerandom.iterators`` to generate\nthe random bits used to produce the random floats. The ``jumpahead()`` function\n(Python 2.x) is implemented in all cases, and is also supported in Python 3.x,\neven though ``jumpahead()`` has officially been removed from the Python 3.x\n``random`` API. \n\n\n-----\nUsage\n-----\n\nIterators\n`````````\n\n    >>> import simplerandom.iterators as sri\n    >>> rng = sri.KISS(123958, 34987243, 3495825239, 2398172431)\n    >>> next(rng)\n    702862187L\n    >>> next(rng)\n    13888114L\n    >>> next(rng)\n    699722976L\n\nRandom class API\n````````````````\n\n    >>> import simplerandom.random as srr\n    >>> rng = srr.KISS(258725234)\n    >>> rng.random()\n    0.0925917826051541\n    >>> rng.random()\n    0.02901686453730415\n    >>> rng.random()\n    0.9024972981686489\n\n\n-------------------------\nSupported Python Versions\n-------------------------\n\nCurrently this has had basic testing on Ubuntu 13.04 64-bit and\nWindows XP 32-bit. It passes the ``simplerandom.iterators.test`` unit\ntests, as well as basic manual testing of ``simplerandom.random``. A more\nthorough unit test suite is needed.\n\nIn Ubuntu, it has been tested on Python 2.7 and 3.3, and passes.\n\nIn Windows, it has been tested on Python 2.6, 2.7, 3.1, 3.2 and 3.3. It\npasses under these versions.\n\n\n-------------\nUse of Cython\n-------------\n\n`Cython`_ is used to make a fast implementation of ``simplerandom.iterators``.\nCython creates a ``.c`` file that can be compiled into a Python binary\nextension module.\n\nThe ``simplerandom`` source distribution package includes a ``.c`` file that\nwas created with Cython, so it is not necessary to have Cython installed to\ninstall ``simplerandom``.\n\nThe Cython ``.pyx`` file is also included, if you want to modify the Cython\nsource code, in which case you do need to have Cython installed. But by\ndefault, ``setup.py`` builds the extension from the ``.c`` file (to ensure\nthat the build doesn't fail due to particular Cython version issues). If you\nwish to build using Cython from the included ``.pyx`` file, you must set\n``USE_CYTHON=True`` in ``setup.py``.\n\n.. _Cython:\n    http://cython.org/\n\n\n------------\nInstallation\n------------\n\nThe simplerandom package is installed using ``distutils``.  If you have the tools\ninstalled to build a Python extension module, run the following command::\n\n    python setup.py install\n\nIf you cannot build the C extension, you may install just the pure Python\nimplementation, using the following command::\n\n    python setup.py build_py install --skip-build\n\n\n------------\nUnit Testing\n------------\n\nUnit testing of the iterators is in ``simplerandom.iterators.test``. It\nduplicates the tests of the C algorithms given in the original newsgroup post\n[#marsaglia1999]_, as well as other unit tests.\n\nTo run unit tests::\n\n    python -m simplerandom.iterators.test\n\nA more thorough unit test suite is needed. A unit test suite for\n``simplerandom.random`` is needed.\n\n\n-------\nLicense\n-------\n\nThe code is released under the MIT license. See LICENSE.txt for details.",
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