PosteriorErrorProbabilityModel.h

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// $Maintainer: Timo Sachsenberg $
// $Authors: David Wojnar $
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#ifndef OPENMS_MATH_STATISTICS_POSTERIORERRORPROBABILITYMODEL_H
#define OPENMS_MATH_STATISTICS_POSTERIORERRORPROBABILITYMODEL_H

#include <OpenMS/DATASTRUCTURES/DPosition.h>
#include <OpenMS/MATH/STATISTICS/GumbelDistributionFitter.h>
#include <OpenMS/MATH/STATISTICS/GaussFitter.h>
#include <OpenMS/DATASTRUCTURES/DefaultParamHandler.h>
#include <vector>

namespace OpenMS
{
  class String;
  class TextFile;
  namespace Math
  {


    class OPENMS_DLLAPI PosteriorErrorProbabilityModel :
      public DefaultParamHandler
    {
public:

      PosteriorErrorProbabilityModel();

      virtual ~PosteriorErrorProbabilityModel();

      bool fit(std::vector<double> & search_engine_scores);

      bool fit(std::vector<double> & search_engine_scores, std::vector<double> & probabilities);

      void fillDensities(std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density);
      double computeMaxLikelihood(std::vector<double> & incorrect_density, std::vector<double> & correct_density);
      double one_minus_sum_post(std::vector<double> & incorrect_density, std::vector<double> & correct_density);
      double sum_post(std::vector<double> & incorrect_density, std::vector<double> & correct_density);
      double sum_pos_x0(std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density);
      double sum_neg_x0(std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density);
      double sum_pos_sigma(std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density, double positive_mean);
      double sum_neg_sigma(std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density, double positive_mean);


      GaussFitter::GaussFitResult getCorrectlyAssignedFitResult() const
      {
        return correctly_assigned_fit_param_;
      }

      GaussFitter::GaussFitResult getIncorrectlyAssignedFitResult() const
      {
        return incorrectly_assigned_fit_param_;
      }

      double getNegativePrior() const
      {
        return negative_prior_;
      }

      double getGauss(double x, const GaussFitter::GaussFitResult & params)
      {
        return params.A * exp(-1.0 * pow(x - params.x0, 2) / (2 * pow(params.sigma, 2)));
      }

      double getGumbel(double x, const GaussFitter::GaussFitResult & params)
      {
        double z = exp((params.x0 - x) / params.sigma);
        return (z * exp(-1 * z)) / params.sigma;
      }

      double computeProbability(double score);

      TextFile initPlots(std::vector<double> & x_scores);

      const String getGumbelGnuplotFormula(const GaussFitter::GaussFitResult & params) const;

      const String getGaussGnuplotFormula(const GaussFitter::GaussFitResult & params) const;

      const String getBothGnuplotFormula(const GaussFitter::GaussFitResult & incorrect, const GaussFitter::GaussFitResult & correct) const;

      void plotTargetDecoyEstimation(std::vector<double> & target, std::vector<double> & decoy);

      inline double getSmallestScore()
      {
        return smallest_score_;
      }

      void tryGnuplot(const String& gp_file);

private:
      PosteriorErrorProbabilityModel & operator=(const PosteriorErrorProbabilityModel & rhs);
      PosteriorErrorProbabilityModel(const PosteriorErrorProbabilityModel & rhs);
      GaussFitter::GaussFitResult incorrectly_assigned_fit_param_;
      GaussFitter::GaussFitResult correctly_assigned_fit_param_;
      double negative_prior_;
      double max_incorrectly_;
      double max_correctly_;
      double smallest_score_;
      double (PosteriorErrorProbabilityModel::* calc_incorrect_)(double x, const GaussFitter::GaussFitResult & params);
      double (PosteriorErrorProbabilityModel::* calc_correct_)(double x, const GaussFitter::GaussFitResult & params);
      const String (PosteriorErrorProbabilityModel::* getNegativeGnuplotFormula_)(const GaussFitter::GaussFitResult & params) const;
      const String (PosteriorErrorProbabilityModel::* getPositiveGnuplotFormula_)(const GaussFitter::GaussFitResult & params) const;

    };
  }
}

#endif // OPENMS_MATH_STATISTICS_POSTERIORERRORPROBABILITYMODEL_H