AMProposal.h

Go to the documentation of this file.

#ifndef AMPROPOSAL_H_
#define AMPROPOSAL_H_
 
#include "MUQ/SamplingAlgorithms/MHProposal.h"
 
namespace muq {
  namespace SamplingAlgorithms {
 
    class AMProposal : public MCMCProposal {
    public:
 
      AMProposal(boost::property_tree::ptree                     pt,
                 std::shared_ptr<AbstractSamplingProblem> const& prob);
 
      AMProposal(boost::property_tree::ptree                     pt,
                 std::shared_ptr<AbstractSamplingProblem> const& prob,
                 Eigen::MatrixXd                          const& initialCov);
 
 
      virtual ~AMProposal() = default;
 
 
      virtual void Adapt(unsigned int const t, std::vector<std::shared_ptr<SamplingState>> const& states) override;
 
      virtual Eigen::MatrixXd ProposalCovariance() const;
 
    private:
 
      static Eigen::MatrixXd ConstructCovariance(boost::property_tree::ptree                                const& pt ,
                                                 std::shared_ptr<AbstractSamplingProblem> const& prob);
 
 
      virtual std::shared_ptr<SamplingState> Sample(std::shared_ptr<SamplingState> const& currentState) override;
 
      virtual double LogDensity(std::shared_ptr<SamplingState> const& currState,
                                std::shared_ptr<SamplingState> const& propState) override;
 
      Eigen::MatrixXd newSamps;
      unsigned int numNewSamps=0;
 
      unsigned int numAdaptSamps=0;
 
      Eigen::VectorXd mean;
 
      Eigen::MatrixXd propCov;
 
      Eigen::LLT<Eigen::MatrixXd, Eigen::Lower> propChol;
 
      const unsigned int adaptSteps;
 
      const unsigned int adaptStart;
 
      const unsigned int adaptEnd;
 
      // Multiplicative scaling of the sample covariance
      const double adaptScale;
 
    };
 
  } // namespace SamplingAlgorithms
} // namespace muq
 
#endif