mersenne-twister

问题 I'm comparing the mersenne twister in Java and matlab. I'm using the same seed in both. My problem is that when i print out ten numbers from each number generator (Mersenne Twister running in Java and Matlab respectively), the resulting output doesn't seem to match. The output data from the Matlab version prints out every second number from the program in Java. Java prints: 0.417, 0.997, 0.720, 0.932, 0.0001.. Matlab prints: 0.417, 0.720, 0.0001.. Can anyone point me in the right direction to

问题 I want to use one of the Mersenne Twister C libraries (e.g. tinymt, mtwist, or libbrahe) so I can use it as a seed for rand() in a C program. I wasn't able to find a simple minimalistic example on how to do this. I got this far with the mtwist package, but through pjs's comments I've realized that this is the wrong way to do it: #include <stdio.h> #include <stdlib.h> #include "mtwist.h" int main() { uint32_t random_value; random_value = mt_lrand(); srand(random_value); printf("mtwist random:

问题 I have been trying to use the c++ 11 mersenne_twister_engine class( http://www.cplusplus.com/reference/random/mersenne_twister_engine/) to generate numbers in the interval [0,1] however I am continually getting 0 on every number. Here is my code snippet unsigned seed1 = std::chrono::system_clock::now().time_since_epoch().count(); std::mt19937 generator(seed1); for (int i=0; i < WIDTH * HEIGHT; i++) //GENERATES THE MATRIX OF CONNECTIVITY { double random = generator()/generator.max(); if (

问题 I've read that many pseudo-random number generators require many samples in ordered to be "warmed up". Is that the case when using std::random_device to seed std::mt19937, or can we expect that it's ready after construction? The code in question: #include <random> std::random_device rd; std::mt19937 gen(rd()); 回答1: Mersenne Twister is a shift-register based pRNG (pseudo-random number generator) and is therefore subject to bad seeds with long runs of 0s or 1s that lead to relatively

问题 The following code outputs a random number each second: int main () { srand(time(NULL)); // Seeds number generator with execution time. while (true) { int rawRand = rand(); std::cout << rawRand << std::endl; sleep(1); } } How might I size these numbers down so they're always in the range of 0-100? 回答1: If you are using C++ and are concerned about good distribution you can use TR1 C++11 <random> . #include <random> std::random_device rseed; std::mt19937 rgen(rseed()); // mersenne_twister std:

问题 I am trying to find an efficient way to implement a uniform(0,1) distribution. Since I have to generate a very large number of samples, I chose mt19937 as engine. I am using the version from the boost library. My question is: what is the difference between using the output of the engine itself vs using uniform_real_distribution? Option #1 std::random_device rd; boost::mt19937 gen(rd()); boost::random::uniform_real_distribution<double> urand(0, 1); for ( int i = 0; i < 1E8; i++ ) { u = urand

问题 I am attempting to use the Boost multiprecision libraries for C++ to generate large random numbers. I have been unable to create a generator which is seeded by the time or another random number, so my generator produces the same numbers on every run. How do I seed the generator with a changing value to produce different values on each run? Here is the code which works but produces the same values on each run: using namespace boost::multiprecision; using namespace boost::random; typedef

问题 I'm using a Mersenne Twister implementation which provides me numbers with double precision. http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/VERSIONS/FORTRAN/fortran.html (implementation in Fortran 77 by Tsuyoshi Tada, I'm using genrand_real2) However, my application needs, in order to avoid warnings while multiplying numbers with different precisions, a single precision random number. So, I wrote a small function to convert between the two data types: function genrand_real() real genrand

问题 In PHP, we have the choice of mt_rand() and rand() where mt_rand() uses the Mersenne Twister algorithm and rand() uses the libc random generator. I would like to choose a random item out of an array using array_rand. However, does array_rand use the Mersenne Twister algorithm? It is quite simple to implement my own array_rand using mt_rand , but if array_rand uses the Mersenne Twister, then all the better. 回答1: It appears that array_rand uses php_rand() internally, which appears to be the

问题 This is actually a follow up question of a previous one: Rounding of double precision to single precision: Forcing an upper bound After what I thought was the solution of my problems with the answer of previous question, I tried running my program again and found that I had the same problem. The Mersenne Twister implementation I'm using generates a signed 32 bits random integer. The guy who implemented the RNG made this function to generate a random double precision float in the range [0,1):