685 lines
17 KiB
C
685 lines
17 KiB
C
/* Implementation of the RANDOM intrinsics
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Copyright 2002, 2004 Free Software Foundation, Inc.
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Contributed by Lars Segerlund <seger@linuxmail.org>
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and Steve Kargl.
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This file is part of the GNU Fortran 95 runtime library (libgfortran).
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Libgfortran is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public
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License as published by the Free Software Foundation; either
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version 2 of the License, or (at your option) any later version.
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In addition to the permissions in the GNU General Public License, the
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Free Software Foundation gives you unlimited permission to link the
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compiled version of this file into combinations with other programs,
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and to distribute those combinations without any restriction coming
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from the use of this file. (The General Public License restrictions
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do apply in other respects; for example, they cover modification of
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the file, and distribution when not linked into a combine
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executable.)
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Ligbfortran is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public
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License along with libgfortran; see the file COPYING. If not,
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write to the Free Software Foundation, Inc., 59 Temple Place - Suite 330,
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Boston, MA 02111-1307, USA. */
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#include "libgfortran.h"
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extern void random_r4 (GFC_REAL_4 *);
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iexport_proto(random_r4);
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extern void random_r8 (GFC_REAL_8 *);
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iexport_proto(random_r8);
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extern void arandom_r4 (gfc_array_r4 *);
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export_proto(arandom_r4);
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extern void arandom_r8 (gfc_array_r8 *);
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export_proto(arandom_r8);
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#if 0
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/* The Mersenne Twister code is currently commented out due to
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(1) Simple user specified seeds lead to really bad sequences for
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nearly 100000 random numbers.
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(2) open(), read(), and close() are not properly declared via header
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files.
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(3) The global index i is abused and causes unexpected behavior with
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GET and PUT.
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(4) See PR 15619.
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The algorithm was taken from the paper :
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Mersenne Twister: 623-dimensionally equidistributed
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uniform pseudorandom generator.
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by: Makoto Matsumoto
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Takuji Nishimura
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Which appeared in the: ACM Transactions on Modelling and Computer
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Simulations: Special Issue on Uniform Random Number
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Generation. ( Early in 1998 ). */
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#include <stdio.h>
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#include <stdlib.h>
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#include <sys/types.h>
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#include <sys/stat.h>
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#include <fcntl.h>
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#ifdef HAVE_UNISTD_H
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#include <unistd.h>
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#endif
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/*Use the 'big' generator by default ( period -> 2**19937 ). */
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#define MT19937
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/* Define the necessary constants for the algorithm. */
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#ifdef MT19937
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enum constants
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{
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N = 624, M = 397, R = 19, TU = 11, TS = 7, TT = 15, TL = 17
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};
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#define M_A 0x9908B0DF
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#define T_B 0x9D2C5680
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#define T_C 0xEFC60000
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#else
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enum constants
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{
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N = 351, M = 175, R = 19, TU = 11, TS = 7, TT = 15, TL = 17
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};
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#define M_A 0xE4BD75F5
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#define T_B 0x655E5280
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#define T_C 0xFFD58000
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#endif
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static int i = N;
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static unsigned int seed[N];
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/* This is the routine which handles the seeding of the generator,
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and also reading and writing of the seed. */
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void
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random_seed (GFC_INTEGER_4 *size, gfc_array_i4 *put, gfc_array_i4 *get)
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{
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/* Initialize the seed in system dependent manner. */
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if (get == NULL && put == NULL && size == NULL)
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{
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int fd;
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fd = open ("/dev/urandom", O_RDONLY);
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if (fd == 0)
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{
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/* We dont have urandom. */
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GFC_UINTEGER_4 s = (GFC_UINTEGER_4) seed;
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for (i = 0; i < N; i++)
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{
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s = s * 29943829 - 1;
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seed[i] = s;
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}
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}
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else
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{
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/* Using urandom, might have a length issue. */
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read (fd, &seed[0], sizeof (GFC_UINTEGER_4) * N);
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close (fd);
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}
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return;
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}
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/* Return the size of the seed */
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if (size != NULL)
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{
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*size = N;
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return;
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}
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/* if we have gotten to this pount we have a get or put
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* now we check it the array fulfills the demands in the standard .
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*/
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/* Set the seed to PUT data */
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if (put != NULL)
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{
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/* if the rank of the array is not 1 abort */
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if (GFC_DESCRIPTOR_RANK (put) != 1)
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abort ();
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/* if the array is too small abort */
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if (((put->dim[0].ubound + 1 - put->dim[0].lbound)) < N)
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abort ();
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/* If this is the case the array is a temporary */
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if (put->dim[0].stride == 0)
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return;
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/* This code now should do correct strides. */
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for (i = 0; i < N; i++)
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seed[i] = put->data[i * put->dim[0].stride];
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}
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/* Return the seed to GET data */
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if (get != NULL)
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{
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/* if the rank of the array is not 1 abort */
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if (GFC_DESCRIPTOR_RANK (get) != 1)
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abort ();
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/* if the array is too small abort */
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if (((get->dim[0].ubound + 1 - get->dim[0].lbound)) < N)
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abort ();
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/* If this is the case the array is a temporary */
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if (get->dim[0].stride == 0)
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return;
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/* This code now should do correct strides. */
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for (i = 0; i < N; i++)
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get->data[i * get->dim[0].stride] = seed[i];
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}
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}
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iexport(random_seed);
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/* Here is the internal routine which generates the random numbers
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in 'batches' based upon the need for a new batch.
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It's an integer based routine known as 'Mersenne Twister'.
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This implementation still lacks 'tempering' and a good verification,
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but gives very good metrics. */
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static void
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random_generate (void)
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{
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/* 32 bits. */
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GFC_UINTEGER_4 y;
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/* Generate batch of N. */
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int k, m;
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for (k = 0, m = M; k < N - 1; k++)
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{
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y = (seed[k] & (-1 << R)) | (seed[k + 1] & ((1u << R) - 1));
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seed[k] = seed[m] ^ (y >> 1) ^ (-(GFC_INTEGER_4) (y & 1) & M_A);
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if (++m >= N)
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m = 0;
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}
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y = (seed[N - 1] & (-1 << R)) | (seed[0] & ((1u << R) - 1));
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seed[N - 1] = seed[M - 1] ^ (y >> 1) ^ (-(GFC_INTEGER_4) (y & 1) & M_A);
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i = 0;
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}
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/* A routine to return a REAL(KIND=4). */
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void
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random_r4 (GFC_REAL_4 * harv)
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{
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/* Regenerate if we need to. */
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if (i >= N)
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random_generate ();
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/* Convert uint32 to REAL(KIND=4). */
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*harv = (GFC_REAL_4) ((GFC_REAL_4) (GFC_UINTEGER_4) seed[i++] /
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(GFC_REAL_4) (~(GFC_UINTEGER_4) 0));
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}
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iexport(random_r4);
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/* A routine to return a REAL(KIND=8). */
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void
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random_r8 (GFC_REAL_8 * harv)
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{
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/* Regenerate if we need to, may waste one 32-bit value. */
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if ((i + 1) >= N)
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random_generate ();
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/* Convert two uint32 to a REAL(KIND=8). */
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*harv = ((GFC_REAL_8) ((((GFC_UINTEGER_8) seed[i+1]) << 32) + seed[i])) /
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(GFC_REAL_8) (~(GFC_UINTEGER_8) 0);
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i += 2;
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}
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iexport(random_r8);
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/* Code to handle arrays will follow here. */
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/* REAL(KIND=4) REAL array. */
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void
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arandom_r4 (gfc_array_r4 * harv)
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{
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index_type count[GFC_MAX_DIMENSIONS];
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index_type extent[GFC_MAX_DIMENSIONS];
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index_type stride[GFC_MAX_DIMENSIONS];
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index_type stride0;
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index_type dim;
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GFC_REAL_4 *dest;
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int n;
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dest = harv->data;
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if (harv->dim[0].stride == 0)
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harv->dim[0].stride = 1;
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dim = GFC_DESCRIPTOR_RANK (harv);
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for (n = 0; n < dim; n++)
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{
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count[n] = 0;
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stride[n] = harv->dim[n].stride;
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extent[n] = harv->dim[n].ubound + 1 - harv->dim[n].lbound;
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if (extent[n] <= 0)
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return;
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}
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stride0 = stride[0];
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while (dest)
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{
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/* Set the elements. */
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/* regenerate if we need to */
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if (i >= N)
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random_generate ();
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/* Convert uint32 to float in a hopefully g95 compiant manner */
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*dest = (GFC_REAL_4) ((GFC_REAL_4) (GFC_UINTEGER_4) seed[i++] /
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(GFC_REAL_4) (~(GFC_UINTEGER_4) 0));
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/* Advance to the next element. */
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dest += stride0;
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count[0]++;
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/* Advance to the next source element. */
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n = 0;
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while (count[n] == extent[n])
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{
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/* When we get to the end of a dimension,
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reset it and increment
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the next dimension. */
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count[n] = 0;
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/* We could precalculate these products,
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but this is a less
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frequently used path so proabably not worth it. */
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dest -= stride[n] * extent[n];
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n++;
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if (n == dim)
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{
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dest = NULL;
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break;
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}
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else
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{
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count[n]++;
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dest += stride[n];
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}
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}
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}
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}
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/* REAL(KIND=8) array. */
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void
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arandom_r8 (gfc_array_r8 * harv)
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{
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index_type count[GFC_MAX_DIMENSIONS];
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index_type extent[GFC_MAX_DIMENSIONS];
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index_type stride[GFC_MAX_DIMENSIONS];
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index_type stride0;
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index_type dim;
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GFC_REAL_8 *dest;
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int n;
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dest = harv->data;
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if (harv->dim[0].stride == 0)
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harv->dim[0].stride = 1;
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dim = GFC_DESCRIPTOR_RANK (harv);
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for (n = 0; n < dim; n++)
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{
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count[n] = 0;
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stride[n] = harv->dim[n].stride;
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extent[n] = harv->dim[n].ubound + 1 - harv->dim[n].lbound;
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if (extent[n] <= 0)
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return;
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}
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stride0 = stride[0];
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while (dest)
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{
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/* Set the elements. */
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/* regenerate if we need to, may waste one 32-bit value */
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if ((i + 1) >= N)
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random_generate ();
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/* Convert two uint32 to a REAL(KIND=8). */
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*dest = ((GFC_REAL_8) ((((GFC_UINTEGER_8) seed[i+1]) << 32) + seed[i])) /
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(GFC_REAL_8) (~(GFC_UINTEGER_8) 0);
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i += 2;
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/* Advance to the next element. */
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dest += stride0;
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count[0]++;
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/* Advance to the next source element. */
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n = 0;
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while (count[n] == extent[n])
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{
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/* When we get to the end of a dimension,
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reset it and increment
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the next dimension. */
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count[n] = 0;
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/* We could precalculate these products,
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but this is a less
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frequently used path so proabably not worth it. */
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dest -= stride[n] * extent[n];
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n++;
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if (n == dim)
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{
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dest = NULL;
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break;
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}
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else
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{
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count[n]++;
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dest += stride[n];
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}
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}
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}
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}
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#else
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/* George Marsaglia's KISS (Keep It Simple Stupid) random number generator.
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This PRNG combines:
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(1) The congruential generator x(n)=69069*x(n-1)+1327217885 with a period
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of 2^32,
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(2) A 3-shift shift-register generator with a period of 2^32-1,
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(3) Two 16-bit multiply-with-carry generators with a period of
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597273182964842497 > 2^59.
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The overall period exceeds 2^123.
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http://www.ciphersbyritter.com/NEWS4/RANDC.HTM#369F6FCA.74C7C041@stat.fsu.edu
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The above web site has an archive of a newsgroup posting from George
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Marsaglia with the statement:
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Subject: Random numbers for C: Improvements.
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Date: Fri, 15 Jan 1999 11:41:47 -0500
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From: George Marsaglia <geo@stat.fsu.edu>
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Message-ID: <369F6FCA.74C7C041@stat.fsu.edu>
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References: <369B5E30.65A55FD1@stat.fsu.edu>
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Newsgroups: sci.stat.math,sci.math,sci.math.numer-analysis
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Lines: 93
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As I hoped, several suggestions have led to
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improvements in the code for RNG's I proposed for
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use in C. (See the thread "Random numbers for C: Some
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suggestions" in previous postings.) The improved code
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is listed below.
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A question of copyright has also been raised. Unlike
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DIEHARD, there is no copyright on the code below. You
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are free to use it in any way you want, but you may
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wish to acknowledge the source, as a courtesy.
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"There is no copyright on the code below." included the original
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KISS algorithm. */
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#define GFC_SL(k, n) ((k)^((k)<<(n)))
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#define GFC_SR(k, n) ((k)^((k)>>(n)))
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static const GFC_INTEGER_4 kiss_size = 4;
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#define KISS_DEFAULT_SEED {123456789, 362436069, 521288629, 916191069};
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static const GFC_UINTEGER_4 kiss_default_seed[4] = KISS_DEFAULT_SEED;
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static GFC_UINTEGER_4 kiss_seed[4] = KISS_DEFAULT_SEED;
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/* kiss_random_kernel() returns an integer value in the range of
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(0, GFC_UINTEGER_4_HUGE]. The distribution of pseudorandom numbers
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should be uniform. */
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static GFC_UINTEGER_4
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kiss_random_kernel(void)
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{
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GFC_UINTEGER_4 kiss;
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kiss_seed[0] = 69069 * kiss_seed[0] + 1327217885;
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kiss_seed[1] = GFC_SL(GFC_SR(GFC_SL(kiss_seed[1],13),17),5);
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kiss_seed[2] = 18000 * (kiss_seed[2] & 65535) + (kiss_seed[2] >> 16);
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kiss_seed[3] = 30903 * (kiss_seed[3] & 65535) + (kiss_seed[3] >> 16);
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kiss = kiss_seed[0] + kiss_seed[1] + (kiss_seed[2] << 16) + kiss_seed[3];
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return kiss;
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}
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/* This function produces a REAL(4) value from the uniform distribution
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with range [0,1). */
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void
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random_r4 (GFC_REAL_4 *x)
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{
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GFC_UINTEGER_4 kiss;
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kiss = kiss_random_kernel ();
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/* Burn a random number, so the REAL*4 and REAL*8 functions
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produce similar sequences of random numbers. */
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kiss_random_kernel ();
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*x = normalize_r4_i4 (kiss, ~(GFC_UINTEGER_4) 0);
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}
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iexport(random_r4);
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/* This function produces a REAL(8) value from the uniform distribution
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with range [0,1). */
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void
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random_r8 (GFC_REAL_8 *x)
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{
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GFC_UINTEGER_8 kiss;
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kiss = ((GFC_UINTEGER_8)kiss_random_kernel ()) << 32;
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kiss += kiss_random_kernel ();
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*x = normalize_r8_i8 (kiss, ~(GFC_UINTEGER_8) 0);
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}
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iexport(random_r8);
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/* This function fills a REAL(4) array with values from the uniform
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distribution with range [0,1). */
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void
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arandom_r4 (gfc_array_r4 *x)
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{
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index_type count[GFC_MAX_DIMENSIONS];
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index_type extent[GFC_MAX_DIMENSIONS];
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index_type stride[GFC_MAX_DIMENSIONS];
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index_type stride0;
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index_type dim;
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GFC_REAL_4 *dest;
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int n;
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dest = x->data;
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if (x->dim[0].stride == 0)
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x->dim[0].stride = 1;
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dim = GFC_DESCRIPTOR_RANK (x);
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for (n = 0; n < dim; n++)
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{
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count[n] = 0;
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stride[n] = x->dim[n].stride;
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extent[n] = x->dim[n].ubound + 1 - x->dim[n].lbound;
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if (extent[n] <= 0)
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return;
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}
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|
|
|
stride0 = stride[0];
|
|
|
|
while (dest)
|
|
{
|
|
random_r4 (dest);
|
|
|
|
/* Advance to the next element. */
|
|
dest += stride0;
|
|
count[0]++;
|
|
/* Advance to the next source element. */
|
|
n = 0;
|
|
while (count[n] == extent[n])
|
|
{
|
|
/* When we get to the end of a dimension, reset it and increment
|
|
the next dimension. */
|
|
count[n] = 0;
|
|
/* We could precalculate these products, but this is a less
|
|
frequently used path so probably not worth it. */
|
|
dest -= stride[n] * extent[n];
|
|
n++;
|
|
if (n == dim)
|
|
{
|
|
dest = NULL;
|
|
break;
|
|
}
|
|
else
|
|
{
|
|
count[n]++;
|
|
dest += stride[n];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/* This function fills a REAL(8) array with values from the uniform
|
|
distribution with range [0,1). */
|
|
|
|
void
|
|
arandom_r8 (gfc_array_r8 *x)
|
|
{
|
|
index_type count[GFC_MAX_DIMENSIONS];
|
|
index_type extent[GFC_MAX_DIMENSIONS];
|
|
index_type stride[GFC_MAX_DIMENSIONS];
|
|
index_type stride0;
|
|
index_type dim;
|
|
GFC_REAL_8 *dest;
|
|
int n;
|
|
|
|
dest = x->data;
|
|
|
|
if (x->dim[0].stride == 0)
|
|
x->dim[0].stride = 1;
|
|
|
|
dim = GFC_DESCRIPTOR_RANK (x);
|
|
|
|
for (n = 0; n < dim; n++)
|
|
{
|
|
count[n] = 0;
|
|
stride[n] = x->dim[n].stride;
|
|
extent[n] = x->dim[n].ubound + 1 - x->dim[n].lbound;
|
|
if (extent[n] <= 0)
|
|
return;
|
|
}
|
|
|
|
stride0 = stride[0];
|
|
|
|
while (dest)
|
|
{
|
|
random_r8 (dest);
|
|
|
|
/* Advance to the next element. */
|
|
dest += stride0;
|
|
count[0]++;
|
|
/* Advance to the next source element. */
|
|
n = 0;
|
|
while (count[n] == extent[n])
|
|
{
|
|
/* When we get to the end of a dimension, reset it and increment
|
|
the next dimension. */
|
|
count[n] = 0;
|
|
/* We could precalculate these products, but this is a less
|
|
frequently used path so probably not worth it. */
|
|
dest -= stride[n] * extent[n];
|
|
n++;
|
|
if (n == dim)
|
|
{
|
|
dest = NULL;
|
|
break;
|
|
}
|
|
else
|
|
{
|
|
count[n]++;
|
|
dest += stride[n];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/* random_seed is used to seed the PRNG with either a default
|
|
set of seeds or user specified set of seeds. random_seed
|
|
must be called with no argument or exactly one argument. */
|
|
|
|
void
|
|
random_seed (GFC_INTEGER_4 *size, gfc_array_i4 *put, gfc_array_i4 *get)
|
|
{
|
|
int i;
|
|
|
|
if (size == NULL && put == NULL && get == NULL)
|
|
{
|
|
/* From the standard: "If no argument is present, the processor assigns
|
|
a processor-dependent value to the seed." */
|
|
kiss_seed[0] = kiss_default_seed[0];
|
|
kiss_seed[1] = kiss_default_seed[1];
|
|
kiss_seed[2] = kiss_default_seed[2];
|
|
kiss_seed[3] = kiss_default_seed[3];
|
|
}
|
|
|
|
if (size != NULL)
|
|
*size = kiss_size;
|
|
|
|
if (put != NULL)
|
|
{
|
|
/* If the rank of the array is not 1, abort. */
|
|
if (GFC_DESCRIPTOR_RANK (put) != 1)
|
|
runtime_error ("Array rank of PUT is not 1.");
|
|
|
|
/* If the array is too small, abort. */
|
|
if (((put->dim[0].ubound + 1 - put->dim[0].lbound)) < kiss_size)
|
|
runtime_error ("Array size of PUT is too small.");
|
|
|
|
if (put->dim[0].stride == 0)
|
|
put->dim[0].stride = 1;
|
|
|
|
/* This code now should do correct strides. */
|
|
for (i = 0; i < kiss_size; i++)
|
|
kiss_seed[i] =(GFC_UINTEGER_4) put->data[i * put->dim[0].stride];
|
|
}
|
|
|
|
/* Return the seed to GET data. */
|
|
if (get != NULL)
|
|
{
|
|
/* If the rank of the array is not 1, abort. */
|
|
if (GFC_DESCRIPTOR_RANK (get) != 1)
|
|
runtime_error ("Array rank of GET is not 1.");
|
|
|
|
/* If the array is too small, abort. */
|
|
if (((get->dim[0].ubound + 1 - get->dim[0].lbound)) < kiss_size)
|
|
runtime_error ("Array size of GET is too small.");
|
|
|
|
if (get->dim[0].stride == 0)
|
|
get->dim[0].stride = 1;
|
|
|
|
/* This code now should do correct strides. */
|
|
for (i = 0; i < kiss_size; i++)
|
|
get->data[i * get->dim[0].stride] = (GFC_INTEGER_4) kiss_seed[i];
|
|
}
|
|
}
|
|
iexport(random_seed);
|
|
|
|
#endif /* mersenne twister */
|