Gaussian.h

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#ifndef GAUSSIAN_H_
#define GAUSSIAN_H_
 
#include "MUQ/Modeling/Distributions/GaussianBase.h"
 
namespace muq {
  namespace Modeling {
 
    class Gaussian : public GaussianBase {
    public:
 
      enum Mode {
 
        Covariance,
 
          Precision
      };
 
      enum ExtraInputs {
        None           = 1 << 0,
        Mean           = 1 << 1,
        DiagCovariance = 1 << 2,
        DiagPrecision  = 1 << 3,
        FullCovariance = 1 << 4,
        FullPrecision  = 1 << 5,
      };
      typedef uint8_t InputMask;
 
      Gaussian(unsigned int dim,
               InputMask    extraInputs = ExtraInputs::None);
 
 
      Gaussian(Eigen::VectorXd const& mu,
               InputMask              extraInputs = ExtraInputs::None);
 
 
      Gaussian(Eigen::VectorXd const& mu,
               Eigen::MatrixXd const& obj,
               Gaussian::Mode         mode = Gaussian::Mode::Covariance,
               InputMask              extraInputs = ExtraInputs::None);
 
 
      virtual ~Gaussian() = default;
 
      Mode GetMode() const{return mode;};
 
      virtual Eigen::MatrixXd ApplyCovariance(Eigen::Ref<const Eigen::MatrixXd> const& x) const override;
      virtual Eigen::MatrixXd ApplyPrecision(Eigen::Ref<const Eigen::MatrixXd> const& x) const override;
 
      virtual Eigen::MatrixXd ApplyCovSqrt(Eigen::Ref<const Eigen::MatrixXd> const& x) const override;
      virtual Eigen::MatrixXd ApplyPrecSqrt(Eigen::Ref<const Eigen::MatrixXd> const& x) const override;
 
 
      Eigen::MatrixXd GetCovariance() const;
      Eigen::MatrixXd GetPrecision() const;
 
 
      void SetCovariance(Eigen::MatrixXd const& newCov);
 
 
      void SetPrecision(Eigen::MatrixXd const& newPrec);
 
      Gaussian::InputMask GetInputTypes() const{return inputTypes;};
 
      std::shared_ptr<Gaussian> Condition(Eigen::MatrixXd const& obsMat,
                                          Eigen::VectorXd const& data,
                                          Eigen::MatrixXd const& obsCov) const;
 
      void ResetHyperparameters(ref_vector<Eigen::VectorXd> const& params) override;
 
      virtual double LogDeterminant() const override{return logDet;};
 
    protected:
 
 
      void ComputeNormalization();
 
      static Eigen::VectorXi GetExtraSizes(unsigned dim, InputMask extraInputs);
 
      static Gaussian::Mode ModeFromExtras(InputMask extraInputs);
      static void CheckInputTypes(InputMask extraInputs, Mode mode);
 
      Gaussian::Mode mode;
 
      Gaussian::InputMask inputTypes;
 
      // Space to store either the covariance or precision matrix (depending on mode)
      Eigen::MatrixXd covPrec;
 
      // Space to tore the matrix square root of the covariance or precision
      Eigen::LLT<Eigen::MatrixXd> sqrtCovPrec;
 
      double logDet;
 
    };
  } // namespace Modeling
} // namespace muq
 
#endif