/* Random objects */ /* ------------------------------------------------------------------ The code in this module was based on a download from: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/emt19937ar.html It was modified in 2002 by Raymond Hettinger as follows: * the principal computational lines untouched. * renamed genrand_res53() to random_random() and wrapped in python calling/return code. * genrand_uint32() and the helper functions, init_genrand() and init_by_array(), were declared static, wrapped in Python calling/return code. also, their global data references were replaced with structure references. * unused functions from the original were deleted. new, original C python code was added to implement the Random() interface. The following are the verbatim comments from the original code: A C-program for MT19937, with initialization improved 2002/1/26. Coded by Takuji Nishimura and Makoto Matsumoto. Before using, initialize the state by using init_genrand(seed) or init_by_array(init_key, key_length). Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The names of its contributors may not be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Any feedback is very welcome. http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space) */ /* ---------------------------------------------------------------*/ #ifndef Py_BUILD_CORE_BUILTIN #define Py_BUILD_CORE_MODULE … #endif #include "Python.h" #include "pycore_long.h" // _PyLong_NumBits() #include "pycore_modsupport.h" // _PyArg_NoKeywords() #include "pycore_moduleobject.h" // _PyModule_GetState() #include "pycore_pylifecycle.h" // _PyOS_URandomNonblock() #ifdef HAVE_UNISTD_H # include <unistd.h> // getpid() #endif #ifdef HAVE_PROCESS_H # include <process.h> // getpid() #endif #ifdef MS_WINDOWS # include <windows.h> // GetCurrentProcessId() #endif /* Period parameters -- These are all magic. Don't change. */ #define N … #define M … #define MATRIX_A … #define UPPER_MASK … #define LOWER_MASK … _randomstate; static inline _randomstate* get_random_state(PyObject *module) { … } static struct PyModuleDef _randommodule; #define _randomstate_type(type) … RandomObject; #include "clinic/_randommodule.c.h" /*[clinic input] module _random class _random.Random "RandomObject *" "_randomstate_type(type)->Random_Type" [clinic start generated code]*/ /*[clinic end generated code: output=da39a3ee5e6b4b0d input=70a2c99619474983]*/ /* Random methods */ /* generates a random number on [0,0xffffffff]-interval */ static uint32_t genrand_uint32(RandomObject *self) { … } /* random_random is the function named genrand_res53 in the original code; * generates a random number on [0,1) with 53-bit resolution; note that * 9007199254740992 == 2**53; I assume they're spelling "/2**53" as * multiply-by-reciprocal in the (likely vain) hope that the compiler will * optimize the division away at compile-time. 67108864 is 2**26. In * effect, a contains 27 random bits shifted left 26, and b fills in the * lower 26 bits of the 53-bit numerator. * The original code credited Isaku Wada for this algorithm, 2002/01/09. */ /*[clinic input] @critical_section _random.Random.random self: self(type="RandomObject *") random() -> x in the interval [0, 1). [clinic start generated code]*/ static PyObject * _random_Random_random_impl(RandomObject *self) /*[clinic end generated code: output=117ff99ee53d755c input=26492e52d26e8b7b]*/ { … } /* initializes mt[N] with a seed */ static void init_genrand(RandomObject *self, uint32_t s) { … } /* initialize by an array with array-length */ /* init_key is the array for initializing keys */ /* key_length is its length */ static void init_by_array(RandomObject *self, uint32_t init_key[], size_t key_length) { … } /* * The rest is Python-specific code, neither part of, nor derived from, the * Twister download. */ static int random_seed_urandom(RandomObject *self) { … } static int random_seed_time_pid(RandomObject *self) { … } static int random_seed(RandomObject *self, PyObject *arg) { … } /*[clinic input] @critical_section _random.Random.seed self: self(type="RandomObject *") n: object = None / seed([n]) -> None. Defaults to use urandom and falls back to a combination of the current time and the process identifier. [clinic start generated code]*/ static PyObject * _random_Random_seed_impl(RandomObject *self, PyObject *n) /*[clinic end generated code: output=0fad1e16ba883681 input=46d01d2ba938c7b1]*/ { … } /*[clinic input] @critical_section _random.Random.getstate self: self(type="RandomObject *") getstate() -> tuple containing the current state. [clinic start generated code]*/ static PyObject * _random_Random_getstate_impl(RandomObject *self) /*[clinic end generated code: output=bf6cef0c092c7180 input=b6621f31eb639694]*/ { … } /*[clinic input] @critical_section _random.Random.setstate self: self(type="RandomObject *") state: object / setstate(state) -> None. Restores generator state. [clinic start generated code]*/ static PyObject * _random_Random_setstate_impl(RandomObject *self, PyObject *state) /*[clinic end generated code: output=babfc2c2eac6b027 input=358e898ec07469b7]*/ { … } /*[clinic input] @critical_section _random.Random.getrandbits self: self(type="RandomObject *") k: int / getrandbits(k) -> x. Generates an int with k random bits. [clinic start generated code]*/ static PyObject * _random_Random_getrandbits_impl(RandomObject *self, int k) /*[clinic end generated code: output=b402f82a2158887f input=87603cd60f79f730]*/ { … } static int random_init(RandomObject *self, PyObject *args, PyObject *kwds) { … } static PyMethodDef random_methods[] = …; PyDoc_STRVAR(random_doc, "Random() -> create a random number generator with its own internal state."); static PyType_Slot Random_Type_slots[] = …; static PyType_Spec Random_Type_spec = …; PyDoc_STRVAR(module_doc, "Module implements the Mersenne Twister random number generator."); static int _random_exec(PyObject *module) { … } static PyModuleDef_Slot _random_slots[] = …; static int _random_traverse(PyObject *module, visitproc visit, void *arg) { … } static int _random_clear(PyObject *module) { … } static void _random_free(void *module) { … } static struct PyModuleDef _randommodule = …; PyMODINIT_FUNC PyInit__random(void) { … }
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