/* mpfr_erandom (rop, state, rnd_mode) -- Generate an exponential deviate with mean 1 and round it to the precision of rop according to the given rounding mode. Copyright 2013-2019 Free Software Foundation, Inc. Contributed by Charles Karney , SRI International. This file is part of the GNU MPFR Library. The GNU MPFR Library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version. The GNU MPFR Library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with the GNU MPFR Library; see the file COPYING.LESSER. If not, see https://www.gnu.org/licenses/ or write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301, USA. */ /* * Sampling from the exponential distribution with unit mean using the method * given in John von Neumann, Various techniques used in connection with random * digits, in A. S. Householder, G. E. Forsythe, and H. H. Germond, editors, * "Monte Carlo Method", number 12 in Applied Mathematics Series, pp. 36-38 * (NBS, Washington, DC, 1951), Proceedings of a symposium held June 29-July 1, * 1949, in Los Angeles. * * A modification to this algorithm is given in: * Charles F. F. Karney, * "Sampling exactly from the normal distribution", * ACM Trans. Math. Software 42(1), 3:1-14 (Jan. 2016). * https://dx.doi.org/10.1145/2710016 * http://arxiv.org/abs/1303.6257 * Although this improves the bit efficiency, in practice, it results in * a slightly slower algorithm for MPFR. So here the original von Neumann * algorithm is used. * * There are a few "weasel words" regarding the accuracy of this * implementation. The algorithm produces exactly rounded exponential deviates * provided that gmp's random number engine delivers truly random bits. If it * did, the algorithm would be perfect; however, this implementation would have * problems, e.g., in that the integer part of the exponential deviate is * represented by an unsigned long, whereas in reality the integer part in * unbounded. In this implementation, asserts catch overflow in the integer * part and similar (very, very) unlikely events. In reality, of course, gmp's * random number engine has a finite internal state (19937 bits in the case of * the MT19937 method). This means that these unlikely events in fact won't * occur. If the asserts are triggered, then this is an indication that the * random number engine is defective. (Even if a hardware random number * generator were used, the most likely explanation for the triggering of the * asserts would be that the hardware generator was broken.) */ #include "random_deviate.h" /* true with prob exp(-x) */ static int E (mpfr_random_deviate_t x, gmp_randstate_t r, mpfr_random_deviate_t p, mpfr_random_deviate_t q) { /* p and q are temporaries */ mpfr_random_deviate_reset (p); if (!mpfr_random_deviate_less (p, x, r)) return 1; for (;;) { mpfr_random_deviate_reset (q); if (!mpfr_random_deviate_less (q, p, r)) return 0; mpfr_random_deviate_reset (p); if (!mpfr_random_deviate_less (p, q, r)) return 1; } } /* return an exponential random deviate with mean 1 as a MPFR */ int mpfr_erandom (mpfr_t z, gmp_randstate_t r, mpfr_rnd_t rnd) { mpfr_random_deviate_t x, p, q; int inex; unsigned long k = 0; mpfr_random_deviate_init (x); mpfr_random_deviate_init (p); mpfr_random_deviate_init (q); while (!E(x, r, p, q)) { ++k; /* Catch k wrapping around to 0; for a 32-bit unsigned long, the * probability of this is exp(-2^32)). */ MPFR_ASSERTN (k != 0UL); mpfr_random_deviate_reset (x); } mpfr_random_deviate_clear (q); mpfr_random_deviate_clear (p); inex = mpfr_random_deviate_value (0, k, x, z, r, rnd); mpfr_random_deviate_clear (x); return inex; }