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