multivariate_gaussian.h

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/* Author: Mrinal Kalakrishnan */
 
#pragma once
 
#include <random>
#include <cstdlib>
#include <eigen3/Eigen/Cholesky>
#include <eigen3/Eigen/Core>
#include <rsl/random.hpp>
 
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::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)
{
  size_ = mean.rows();
}
 
template <typename Derived>
void MultivariateGaussian::sample(Eigen::MatrixBase<Derived>& output)
{
  for (int i = 0; i < size_; ++i)
    output(i) = gaussian_(rsl::rng());
  output = mean_ + covariance_cholesky_ * output;
}
}  // namespace chomp