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LatAnalyze/lib/Statistics/Random.cpp

57 lines
1.7 KiB
C++

/*
* Random.cpp, part of LatAnalyze 3
*
* Copyright (C) 2013 - 2020 Antonin Portelli
*
* LatAnalyze 3 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LatAnalyze 3 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
*/
#include <LatAnalyze/Core/Plot.hpp>
#include <LatAnalyze/includes.hpp>
#include <LatAnalyze/Statistics/Random.hpp>
using namespace std;
using namespace Latan;
RandomNormal::RandomNormal(const DVec &mean, const DMat &var, const SeedType seed)
: mean_(mean), buf_(mean.size()), var_(var), gen_(seed)
{
if (var_.rows() != var_.cols())
{
LATAN_ERROR(Size, "variance matrix not square");
}
if (mean_.size() != var_.rows())
{
LATAN_ERROR(Size, "variance matrix and mean vector size mismatch");
}
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXd> esolver(var);
Eigen::VectorXd ev = esolver.eigenvalues();
ev = ev.unaryExpr([](const double x){return (x > 0.) ? x : 0.;});
transform_ = esolver.eigenvectors()*ev.cwiseSqrt().asDiagonal();
}
DVec RandomNormal::operator()(void)
{
std::normal_distribution<> dist;
FOR_VEC(buf_, i)
{
buf_(i) = dist(gen_);
}
return mean_ + transform_*buf_;
}