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530f506ac9
Automatically replace tp_print -> tp_vectorcall_offset tp_compare -> tp_as_async tp_reserved -> tp_as_async
604 lines
18 KiB
C
604 lines
18 KiB
C
/* Random objects */
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/* ------------------------------------------------------------------
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The code in this module was based on a download from:
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http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/emt19937ar.html
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It was modified in 2002 by Raymond Hettinger as follows:
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* the principal computational lines untouched.
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* renamed genrand_res53() to random_random() and wrapped
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in python calling/return code.
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* genrand_int32() and the helper functions, init_genrand()
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and init_by_array(), were declared static, wrapped in
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Python calling/return code. also, their global data
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references were replaced with structure references.
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* unused functions from the original were deleted.
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new, original C python code was added to implement the
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Random() interface.
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The following are the verbatim comments from the original code:
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A C-program for MT19937, with initialization improved 2002/1/26.
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Coded by Takuji Nishimura and Makoto Matsumoto.
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Before using, initialize the state by using init_genrand(seed)
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or init_by_array(init_key, key_length).
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Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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1. Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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3. The names of its contributors may not be used to endorse or promote
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products derived from this software without specific prior written
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permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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Any feedback is very welcome.
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http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
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email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
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*/
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/* ---------------------------------------------------------------*/
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#include "Python.h"
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#include <time.h> /* for seeding to current time */
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#ifdef HAVE_PROCESS_H
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# include <process.h> /* needed for getpid() */
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#endif
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/* Period parameters -- These are all magic. Don't change. */
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#define N 624
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#define M 397
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#define MATRIX_A 0x9908b0dfU /* constant vector a */
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#define UPPER_MASK 0x80000000U /* most significant w-r bits */
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#define LOWER_MASK 0x7fffffffU /* least significant r bits */
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typedef struct {
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PyObject_HEAD
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int index;
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uint32_t state[N];
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} RandomObject;
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static PyTypeObject Random_Type;
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#define RandomObject_Check(v) (Py_TYPE(v) == &Random_Type)
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#include "clinic/_randommodule.c.h"
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/*[clinic input]
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module _random
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class _random.Random "RandomObject *" "&Random_Type"
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[clinic start generated code]*/
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/*[clinic end generated code: output=da39a3ee5e6b4b0d input=f79898ae7847c321]*/
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/* Random methods */
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/* generates a random number on [0,0xffffffff]-interval */
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static uint32_t
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genrand_int32(RandomObject *self)
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{
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uint32_t y;
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static const uint32_t mag01[2] = {0x0U, MATRIX_A};
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/* mag01[x] = x * MATRIX_A for x=0,1 */
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uint32_t *mt;
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mt = self->state;
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if (self->index >= N) { /* generate N words at one time */
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int kk;
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for (kk=0;kk<N-M;kk++) {
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y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
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mt[kk] = mt[kk+M] ^ (y >> 1) ^ mag01[y & 0x1U];
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}
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for (;kk<N-1;kk++) {
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y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
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mt[kk] = mt[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1U];
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}
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y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK);
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mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1U];
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self->index = 0;
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}
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y = mt[self->index++];
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y ^= (y >> 11);
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y ^= (y << 7) & 0x9d2c5680U;
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y ^= (y << 15) & 0xefc60000U;
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y ^= (y >> 18);
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return y;
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}
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/* random_random is the function named genrand_res53 in the original code;
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* generates a random number on [0,1) with 53-bit resolution; note that
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* 9007199254740992 == 2**53; I assume they're spelling "/2**53" as
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* multiply-by-reciprocal in the (likely vain) hope that the compiler will
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* optimize the division away at compile-time. 67108864 is 2**26. In
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* effect, a contains 27 random bits shifted left 26, and b fills in the
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* lower 26 bits of the 53-bit numerator.
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* The original code credited Isaku Wada for this algorithm, 2002/01/09.
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*/
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/*[clinic input]
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_random.Random.random
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self: self(type="RandomObject *")
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random() -> x in the interval [0, 1).
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[clinic start generated code]*/
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static PyObject *
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_random_Random_random_impl(RandomObject *self)
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/*[clinic end generated code: output=117ff99ee53d755c input=afb2a59cbbb00349]*/
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{
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uint32_t a=genrand_int32(self)>>5, b=genrand_int32(self)>>6;
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return PyFloat_FromDouble((a*67108864.0+b)*(1.0/9007199254740992.0));
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}
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/* initializes mt[N] with a seed */
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static void
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init_genrand(RandomObject *self, uint32_t s)
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{
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int mti;
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uint32_t *mt;
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mt = self->state;
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mt[0]= s;
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for (mti=1; mti<N; mti++) {
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mt[mti] =
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(1812433253U * (mt[mti-1] ^ (mt[mti-1] >> 30)) + mti);
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/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
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/* In the previous versions, MSBs of the seed affect */
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/* only MSBs of the array mt[]. */
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/* 2002/01/09 modified by Makoto Matsumoto */
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}
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self->index = mti;
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return;
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}
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/* initialize by an array with array-length */
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/* init_key is the array for initializing keys */
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/* key_length is its length */
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static void
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init_by_array(RandomObject *self, uint32_t init_key[], size_t key_length)
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{
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size_t i, j, k; /* was signed in the original code. RDH 12/16/2002 */
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uint32_t *mt;
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mt = self->state;
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init_genrand(self, 19650218U);
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i=1; j=0;
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k = (N>key_length ? N : key_length);
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for (; k; k--) {
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mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525U))
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+ init_key[j] + (uint32_t)j; /* non linear */
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i++; j++;
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if (i>=N) { mt[0] = mt[N-1]; i=1; }
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if (j>=key_length) j=0;
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}
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for (k=N-1; k; k--) {
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mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941U))
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- (uint32_t)i; /* non linear */
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i++;
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if (i>=N) { mt[0] = mt[N-1]; i=1; }
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}
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mt[0] = 0x80000000U; /* MSB is 1; assuring non-zero initial array */
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}
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/*
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* The rest is Python-specific code, neither part of, nor derived from, the
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* Twister download.
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*/
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static int
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random_seed_urandom(RandomObject *self)
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{
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PY_UINT32_T key[N];
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if (_PyOS_URandomNonblock(key, sizeof(key)) < 0) {
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return -1;
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}
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init_by_array(self, key, Py_ARRAY_LENGTH(key));
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return 0;
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}
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static void
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random_seed_time_pid(RandomObject *self)
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{
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_PyTime_t now;
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uint32_t key[5];
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now = _PyTime_GetSystemClock();
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key[0] = (PY_UINT32_T)(now & 0xffffffffU);
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key[1] = (PY_UINT32_T)(now >> 32);
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key[2] = (PY_UINT32_T)getpid();
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now = _PyTime_GetMonotonicClock();
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key[3] = (PY_UINT32_T)(now & 0xffffffffU);
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key[4] = (PY_UINT32_T)(now >> 32);
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init_by_array(self, key, Py_ARRAY_LENGTH(key));
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}
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static PyObject *
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random_seed(RandomObject *self, PyObject *arg)
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{
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PyObject *result = NULL; /* guilty until proved innocent */
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PyObject *n = NULL;
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uint32_t *key = NULL;
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size_t bits, keyused;
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int res;
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if (arg == NULL || arg == Py_None) {
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if (random_seed_urandom(self) < 0) {
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PyErr_Clear();
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/* Reading system entropy failed, fall back on the worst entropy:
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use the current time and process identifier. */
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random_seed_time_pid(self);
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}
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Py_RETURN_NONE;
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}
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/* This algorithm relies on the number being unsigned.
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* So: if the arg is a PyLong, use its absolute value.
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* Otherwise use its hash value, cast to unsigned.
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*/
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if (PyLong_Check(arg)) {
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/* Calling int.__abs__() prevents calling arg.__abs__(), which might
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return an invalid value. See issue #31478. */
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n = PyLong_Type.tp_as_number->nb_absolute(arg);
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}
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else {
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Py_hash_t hash = PyObject_Hash(arg);
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if (hash == -1)
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goto Done;
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n = PyLong_FromSize_t((size_t)hash);
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}
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if (n == NULL)
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goto Done;
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/* Now split n into 32-bit chunks, from the right. */
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bits = _PyLong_NumBits(n);
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if (bits == (size_t)-1 && PyErr_Occurred())
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goto Done;
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/* Figure out how many 32-bit chunks this gives us. */
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keyused = bits == 0 ? 1 : (bits - 1) / 32 + 1;
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/* Convert seed to byte sequence. */
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key = (uint32_t *)PyMem_Malloc((size_t)4 * keyused);
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if (key == NULL) {
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PyErr_NoMemory();
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goto Done;
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}
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res = _PyLong_AsByteArray((PyLongObject *)n,
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(unsigned char *)key, keyused * 4,
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PY_LITTLE_ENDIAN,
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0); /* unsigned */
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if (res == -1) {
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goto Done;
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}
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#if PY_BIG_ENDIAN
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{
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size_t i, j;
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/* Reverse an array. */
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for (i = 0, j = keyused - 1; i < j; i++, j--) {
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uint32_t tmp = key[i];
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key[i] = key[j];
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key[j] = tmp;
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}
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}
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#endif
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init_by_array(self, key, keyused);
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Py_INCREF(Py_None);
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result = Py_None;
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Done:
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Py_XDECREF(n);
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PyMem_Free(key);
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return result;
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}
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/*[clinic input]
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_random.Random.seed
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self: self(type="RandomObject *")
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n: object = None
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/
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seed([n]) -> None.
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Defaults to use urandom and falls back to a combination
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of the current time and the process identifier.
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[clinic start generated code]*/
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static PyObject *
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_random_Random_seed_impl(RandomObject *self, PyObject *n)
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/*[clinic end generated code: output=0fad1e16ba883681 input=78d6ef0d52532a54]*/
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{
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return random_seed(self, n);
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}
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/*[clinic input]
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_random.Random.getstate
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self: self(type="RandomObject *")
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getstate() -> tuple containing the current state.
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[clinic start generated code]*/
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static PyObject *
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_random_Random_getstate_impl(RandomObject *self)
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/*[clinic end generated code: output=bf6cef0c092c7180 input=b937a487928c0e89]*/
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{
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PyObject *state;
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PyObject *element;
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int i;
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state = PyTuple_New(N+1);
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if (state == NULL)
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return NULL;
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for (i=0; i<N ; i++) {
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element = PyLong_FromUnsignedLong(self->state[i]);
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if (element == NULL)
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goto Fail;
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PyTuple_SET_ITEM(state, i, element);
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}
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element = PyLong_FromLong((long)(self->index));
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if (element == NULL)
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goto Fail;
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PyTuple_SET_ITEM(state, i, element);
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return state;
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Fail:
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Py_DECREF(state);
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return NULL;
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}
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/*[clinic input]
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_random.Random.setstate
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self: self(type="RandomObject *")
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state: object
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/
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setstate(state) -> None. Restores generator state.
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[clinic start generated code]*/
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static PyObject *
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_random_Random_setstate(RandomObject *self, PyObject *state)
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/*[clinic end generated code: output=fd1c3cd0037b6681 input=b3b4efbb1bc66af8]*/
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{
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int i;
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unsigned long element;
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long index;
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uint32_t new_state[N];
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if (!PyTuple_Check(state)) {
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PyErr_SetString(PyExc_TypeError,
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"state vector must be a tuple");
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return NULL;
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}
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if (PyTuple_Size(state) != N+1) {
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PyErr_SetString(PyExc_ValueError,
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"state vector is the wrong size");
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return NULL;
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}
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for (i=0; i<N ; i++) {
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element = PyLong_AsUnsignedLong(PyTuple_GET_ITEM(state, i));
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if (element == (unsigned long)-1 && PyErr_Occurred())
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return NULL;
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new_state[i] = (uint32_t)element;
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}
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index = PyLong_AsLong(PyTuple_GET_ITEM(state, i));
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if (index == -1 && PyErr_Occurred())
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return NULL;
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if (index < 0 || index > N) {
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PyErr_SetString(PyExc_ValueError, "invalid state");
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return NULL;
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}
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self->index = (int)index;
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for (i = 0; i < N; i++)
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self->state[i] = new_state[i];
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Py_RETURN_NONE;
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}
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/*[clinic input]
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_random.Random.getrandbits
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self: self(type="RandomObject *")
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k: int
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/
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getrandbits(k) -> x. Generates an int with k random bits.
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[clinic start generated code]*/
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static PyObject *
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_random_Random_getrandbits_impl(RandomObject *self, int k)
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/*[clinic end generated code: output=b402f82a2158887f input=8c0e6396dd176fc0]*/
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{
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int i, words;
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uint32_t r;
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uint32_t *wordarray;
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PyObject *result;
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if (k <= 0) {
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PyErr_SetString(PyExc_ValueError,
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"number of bits must be greater than zero");
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return NULL;
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}
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if (k <= 32) /* Fast path */
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return PyLong_FromUnsignedLong(genrand_int32(self) >> (32 - k));
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words = (k - 1) / 32 + 1;
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wordarray = (uint32_t *)PyMem_Malloc(words * 4);
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if (wordarray == NULL) {
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PyErr_NoMemory();
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return NULL;
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}
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/* Fill-out bits of long integer, by 32-bit words, from least significant
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to most significant. */
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#if PY_LITTLE_ENDIAN
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for (i = 0; i < words; i++, k -= 32)
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#else
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for (i = words - 1; i >= 0; i--, k -= 32)
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#endif
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{
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r = genrand_int32(self);
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if (k < 32)
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r >>= (32 - k); /* Drop least significant bits */
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wordarray[i] = r;
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}
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result = _PyLong_FromByteArray((unsigned char *)wordarray, words * 4,
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PY_LITTLE_ENDIAN, 0 /* unsigned */);
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PyMem_Free(wordarray);
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return result;
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}
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static PyObject *
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random_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
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{
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RandomObject *self;
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PyObject *tmp;
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if (type == &Random_Type && !_PyArg_NoKeywords("Random", kwds))
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return NULL;
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self = (RandomObject *)type->tp_alloc(type, 0);
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if (self == NULL)
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return NULL;
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tmp = random_seed(self, args);
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if (tmp == NULL) {
|
|
Py_DECREF(self);
|
|
return NULL;
|
|
}
|
|
Py_DECREF(tmp);
|
|
return (PyObject *)self;
|
|
}
|
|
|
|
static PyMethodDef random_methods[] = {
|
|
_RANDOM_RANDOM_RANDOM_METHODDEF
|
|
_RANDOM_RANDOM_SEED_METHODDEF
|
|
_RANDOM_RANDOM_GETSTATE_METHODDEF
|
|
_RANDOM_RANDOM_SETSTATE_METHODDEF
|
|
_RANDOM_RANDOM_GETRANDBITS_METHODDEF
|
|
{NULL, NULL} /* sentinel */
|
|
};
|
|
|
|
PyDoc_STRVAR(random_doc,
|
|
"Random() -> create a random number generator with its own internal state.");
|
|
|
|
static PyTypeObject Random_Type = {
|
|
PyVarObject_HEAD_INIT(NULL, 0)
|
|
"_random.Random", /*tp_name*/
|
|
sizeof(RandomObject), /*tp_basicsize*/
|
|
0, /*tp_itemsize*/
|
|
/* methods */
|
|
0, /*tp_dealloc*/
|
|
0, /*tp_vectorcall_offset*/
|
|
0, /*tp_getattr*/
|
|
0, /*tp_setattr*/
|
|
0, /*tp_as_async*/
|
|
0, /*tp_repr*/
|
|
0, /*tp_as_number*/
|
|
0, /*tp_as_sequence*/
|
|
0, /*tp_as_mapping*/
|
|
0, /*tp_hash*/
|
|
0, /*tp_call*/
|
|
0, /*tp_str*/
|
|
PyObject_GenericGetAttr, /*tp_getattro*/
|
|
0, /*tp_setattro*/
|
|
0, /*tp_as_buffer*/
|
|
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /*tp_flags*/
|
|
random_doc, /*tp_doc*/
|
|
0, /*tp_traverse*/
|
|
0, /*tp_clear*/
|
|
0, /*tp_richcompare*/
|
|
0, /*tp_weaklistoffset*/
|
|
0, /*tp_iter*/
|
|
0, /*tp_iternext*/
|
|
random_methods, /*tp_methods*/
|
|
0, /*tp_members*/
|
|
0, /*tp_getset*/
|
|
0, /*tp_base*/
|
|
0, /*tp_dict*/
|
|
0, /*tp_descr_get*/
|
|
0, /*tp_descr_set*/
|
|
0, /*tp_dictoffset*/
|
|
0, /*tp_init*/
|
|
0, /*tp_alloc*/
|
|
random_new, /*tp_new*/
|
|
PyObject_Free, /*tp_free*/
|
|
0, /*tp_is_gc*/
|
|
};
|
|
|
|
PyDoc_STRVAR(module_doc,
|
|
"Module implements the Mersenne Twister random number generator.");
|
|
|
|
|
|
static struct PyModuleDef _randommodule = {
|
|
PyModuleDef_HEAD_INIT,
|
|
"_random",
|
|
module_doc,
|
|
-1,
|
|
NULL,
|
|
NULL,
|
|
NULL,
|
|
NULL,
|
|
NULL
|
|
};
|
|
|
|
PyMODINIT_FUNC
|
|
PyInit__random(void)
|
|
{
|
|
PyObject *m;
|
|
|
|
if (PyType_Ready(&Random_Type) < 0)
|
|
return NULL;
|
|
m = PyModule_Create(&_randommodule);
|
|
if (m == NULL)
|
|
return NULL;
|
|
Py_INCREF(&Random_Type);
|
|
PyModule_AddObject(m, "Random", (PyObject *)&Random_Type);
|
|
return m;
|
|
}
|