chompMultivariateGaussian.hpp

/*********************************************************************
 * Software License Agreement (BSD License)
 *
 *  Copyright (c) 2009, Willow Garage, Inc.
 *  All rights reserved.
 *
 *  Redistribution and use in source and binary forms, with or without
 *  modification, are permitted provided that the following conditions
 *  are met:
 *
 *   * Redistributions of source code must retain the above copyright
 *     notice, this list of conditions and the following disclaimer.
 *   * Redistributions in binary form must reproduce the above
 *     copyright notice, this list of conditions and the following
 *     disclaimer in the documentation and/or other materials provided
 *     with the distribution.
 *   * Neither the name of the Willow Garage nor the names of its
 *     contributors may be used to endorse or promote products derived
 *     from this software without specific prior written permission.
 *
 *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
 *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
 *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
 *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
 *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
 *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
 *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
 *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
 *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 *  POSSIBILITY OF SUCH DAMAGE.
 *********************************************************************/

#ifndef MULTIVARIATE_GAUSSIAN_H_
#define MULTIVARIATE_GAUSSIAN_H_


#include <Eigen/Core>
#include <Eigen/Cholesky>
#include <boost/random/variate_generator.hpp>
#include <boost/random/normal_distribution.hpp>
#include <boost/random/mersenne_twister.hpp>
#include <cstdlib>
#include <iostream>

//namespace chomp
//{
  
  class MultivariateGaussian
  {
  public:
    template <typename Derived1, typename Derived2>
    MultivariateGaussian(const Eigen::MatrixBase<Derived1>& mean, const Eigen::MatrixBase<Derived2>& covariance);
    
    template <typename Derived>
    void sample(Eigen::MatrixBase<Derived>& output);
    
  private:
    Eigen::VectorXd mean_;                
    Eigen::MatrixXd covariance_;          
    Eigen::MatrixXd covariance_cholesky_; 
    int size_;
    boost::mt19937 rng_;
    boost::normal_distribution<> normal_dist_;
    boost::variate_generator<boost::mt19937, boost::normal_distribution<> > gaussian_;
  };
  
  
  template <typename Derived1, typename Derived2>
  MultivariateGaussian::MultivariateGaussian(const Eigen::MatrixBase<Derived1>& mean, const Eigen::MatrixBase<Derived2>& covariance):
  mean_(mean),
  covariance_(covariance),
  covariance_cholesky_(covariance_.llt().matrixL()),
  rng_(rand()), 
  gaussian_(rng_, normal_dist_)
  {
    //int seed_nb = rand();
    //std::cout << "MultivariateGaussian::MultivariateGaussian seed(" << seed_nb << ") = "<< std::endl;
    
    //rng_.seed( seed_nb );
    size_ = mean.rows();
    
    //gaussian_ = boost::variate_generator<boost::mt19937, boost::normal_distribution<> >(rng_, normal_dist_);
  }
  
  template <typename Derived>
  void MultivariateGaussian::sample(Eigen::MatrixBase<Derived>& output)
  {
    for (int i=0; i<size_; ++i)
      output(i) = gaussian_();
    output = mean_ + covariance_cholesky_*output;
  }
  
//}

#endif /* MULTIVARIATE_GAUSSIAN_H_ */