src/biascorrection.h

#ifndef BIASCORRECTION_H
#define BIASCORRECTION_H

#include <string>
#include <vector>

#include "lengthdistribution.h"
#include "frequencymatrix.h"
#include "markovmodel.h"

class BiasBoss;
class FragHit;
class Target;

class SeqWeightTable {
  size_t _order;
  MarkovModel _observed;
  MarkovModel _expected;
public:
  SeqWeightTable(size_t window_size, size_t order, double alpha);
  SeqWeightTable(size_t window_size, size_t order, std::string param_file_name,
                 std::string identifier);
  void copy_observed(const SeqWeightTable& other);
  void copy_expected(const SeqWeightTable& other);
  void increment_expected(const Sequence& seq, double mass,
                          const std::vector<double>& fl_cdf);
  void normalize_expected();
   void increment_observed(const Sequence& seq, size_t i, double mass);
   double get_weight(const Sequence& seq, size_t i) const;
  void append_output(std::ofstream& outfile) const;
};

class BiasBoss
{
  size_t _order;
  SeqWeightTable _5_seq_bias;
  SeqWeightTable _3_seq_bias;

public:
  BiasBoss(size_t order, double alpha);  //TODO: Detect order from file.
  BiasBoss(size_t order, std::string param_file_name);
  size_t order() const { return _order; }
  void copy_observations(const BiasBoss& other);
  void copy_expectations(const BiasBoss& other);
   void update_expectations(const Target& targ,
                            double mass = 0,
                            const std::vector<double>& fl_cdf = std::vector<double>());
  void normalize_expectations();
  void update_observed(const FragHit& hit, double mass);
  double get_target_bias(std::vector<float>& start_bias,
                         std::vector<float>& end_bias,
                         const Target& targ) const;
  void append_output(std::ofstream& outfile) const;
};

#endif