multivariate_gaussian.h

Go to the documentation of this file.

/*********************************************************************
 * 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 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.
 *********************************************************************/
 
/* Author: Mrinal Kalakrishnan */
 
#pragma once
 
#include <random>
#include <cstdlib>
#include <eigen3/Eigen/Cholesky>
#include <eigen3/Eigen/Core>
 
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_;
  std::mt19937 rng_;
  std::normal_distribution<double> 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()), gaussian_(0.0, 1.0)
{
  rng_ = std::mt19937(std::random_device{}());
  size_ = mean.rows();
}
 
template <typename Derived>
void MultivariateGaussian::sample(Eigen::MatrixBase<Derived>& output)
{
  for (int i = 0; i < size_; ++i)
    output(i) = gaussian_(rng_);
  output = mean_ + covariance_cholesky_ * output;
}
}  // namespace chomp