Hi Jonathan,
please apologize the delayed response.
> I was trying to use the random number generator in the tools namespace.
I can generate individual scalars but not random matrices.
Yeah, the interface currently only scalars, indicating that the
implementation is in no way parallelized.
The code I
used is something like this (trying to fill a matrix<float> with random
numbers)
float m = 0.0; float stddev = 1.0;
matrix<float> temp(10,10);
matrix<float> mean(temp.size1(), temp.size2()); mean =
scalar_matrix<float>(temp.size1(), temp.size2(), m);
matrix<float> SD(temp.size1(), temp.size2()); SD =
scalar_matrix<float>(temp.size1(), temp.size2(), stddev);
viennacl::tools::normal_random_numbers<matrix<float>> x;
x = viennacl::tools::normal_random_numbers<matrix<float>>(mean, SD);
temp = x();
Please find an example of initializing a matrix with normally
distributed numbers attached. It is by no means a high-performance
implementation, but is often sufficient. There are a few tweaks one can
apply to make it faster (approx. 3x); let me know if that would make a
big difference for your needs.
Best regards,
Karli
#include <iostream>
#include "viennacl/vector.hpp"
#include "viennacl/compressed_matrix.hpp"
#include "viennacl/linalg/prod.hpp"
#include "viennacl/tools/random.hpp"
template<typename T>
void init_matrix_random(viennacl::matrix<T> & A)
{
std::vector<std::vector<T> > tmp(A.size1(), std::vector<T>(A.size2()));
T mu = 0;
T sigma = 1;
viennacl::tools::normal_random_numbers<T> normal_rand(mu, sigma);
for (std::size_t i=0; i<A.size1(); ++i)
for (std::size_t j=0; j<A.size2(); ++j)
tmp[i][j] = normal_rand();
viennacl::copy(tmp, A);
}
int main()
{
viennacl::matrix<float> A(3,2);
srand(4);
init_matrix_random(A);
std::cout << A << std::endl;
}
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