gaussian.hpp

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//  GAMBIT: Global and Modular BSM Inference Tool
//  *********************************************

#ifndef __PRIOR_GAUSSIAN_HPP__
#define __PRIOR_GAUSSIAN_HPP__

#include <algorithm>
#include <cmath>
#include <string>
#include <unordered_map>
#include <vector>

#include "gambit/ScannerBit/cholesky.hpp"
#include "gambit/ScannerBit/priors.hpp"
#include "gambit/Utils/yaml_options.hpp"

#include <boost/math/special_functions/erf.hpp>

namespace Gambit
{
  namespace Priors
  {
    class Gaussian : public BasePrior
    {
     private:
      std::vector <double> mu;
      mutable Cholesky col;

     public:
      // Constructor defined in gaussian.cpp
      Gaussian(const std::vector<std::string>&, const Options&);

      // Transformation from unit interval to the Gaussian
      void transform(const std::vector <double> &unitpars, std::unordered_map<std::string, double> &outputMap) const
      {
        std::vector<double> vec(unitpars.size());

        auto v_it = vec.begin();
        for (auto elem_it = unitpars.begin(), elem_end = unitpars.end(); elem_it != elem_end; elem_it++, v_it++)
        {
          *v_it = M_SQRT2 * boost::math::erf_inv(2. * (*elem_it) - 1.);
        }

        col.ElMult(vec);

        v_it = vec.begin();
        auto m_it = mu.begin();
        for (auto str_it = param_names.begin(), str_end = param_names.end(); str_it != str_end; str_it++)
        {
          outputMap[*str_it] = *(v_it++) + *(m_it++);
        }
      }

      double operator()(const std::vector<double> &vec) const
      {
        static double norm = 0.5 * std::log(2. * M_PI * std::pow(col.DetSqrt(), 2));
        return -0.5 * col.Square(vec, mu) - norm;
      }
    };

    LOAD_PRIOR(gaussian, Gaussian)

  }  // namespace Priors
}  // namespace Gambit

#endif  // __PRIOR_GAUSSIAN_HPP__