HiddenMarkovModel.h

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//                   OpenMS -- Open-Source Mass Spectrometry
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// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
// ETH Zurich, and Freie Universitaet Berlin 2002-2017.
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// $Maintainer: Timo Sachsenberg $
// $Authors: Andreas Bertsch $
// --------------------------------------------------------------------------


#ifndef OPENMS_ANALYSIS_ID_HIDDENMARKOVMODEL_H
#define OPENMS_ANALYSIS_ID_HIDDENMARKOVMODEL_H

#include <vector>
#include <set>

#include <OpenMS/DATASTRUCTURES/Map.h>
#include <OpenMS/CONCEPT/Types.h>
#include <OpenMS/DATASTRUCTURES/StringListUtils.h>
#include <OpenMS/DATASTRUCTURES/String.h>

#include <utility>

namespace OpenMS
{
  class OPENMS_DLLAPI HMMState
  {
public:

    HMMState();

    HMMState(const HMMState & state);

    HMMState(const String & name, bool hidden = true);

    virtual ~HMMState();

    HMMState & operator=(const HMMState &);

    void setName(const String & name);

    const String & getName() const;

    void setHidden(bool hidden);

    bool isHidden() const;

    void addPredecessorState(HMMState * state);

    void deletePredecessorState(HMMState * state);

    void addSuccessorState(HMMState * state);

    void deleteSuccessorState(HMMState * state);

    const std::set<HMMState *> & getPredecessorStates() const;

    const std::set<HMMState *> & getSuccessorStates() const;

protected:

    bool hidden_;

    String name_;

    std::set<HMMState *> pre_states_;

    std::set<HMMState *> succ_states_;
  };


  class OPENMS_DLLAPI HiddenMarkovModel
  {
public:

    HiddenMarkovModel();

    HiddenMarkovModel(const HiddenMarkovModel & hmm_new);

    virtual ~HiddenMarkovModel();

    HiddenMarkovModel & operator=(const HiddenMarkovModel &);

    void writeGraphMLFile(const String & filename);

    void write(std::ostream & out) const;

    double getTransitionProbability(const String & s1, const String & s2) const;

    void setTransitionProbability(const String & s1, const String & s2, double prob);

    Size getNumberOfStates() const;

    void addNewState(HMMState * state);

    void addNewState(const String & name);

    void addSynonymTransition(const String & name1, const String & name2, const String & synonym1, const String & synonym2);

    void evaluate();

    void train();

    void setInitialTransitionProbability(const String & state, double prob);

    void clearInitialTransitionProbabilities();

    void setTrainingEmissionProbability(const String & state, double prob);

    void clearTrainingEmissionProbabilities();

    void enableTransition(const String & s1, const String & s2);

    void disableTransition(const String & s1, const String & s2);

    void disableTransitions();

    void calculateEmissionProbabilities(Map<HMMState *, double> & emission_probs);

    void dump();

    void forwardDump();

    //void buildSynonyms();

    void estimateUntrainedTransitions();

    HMMState * getState(const String & name);

    const HMMState * getState(const String & name) const;

    void clear();

    void setPseudoCounts(double pseudo_counts);

    double getPseudoCounts() const;

    void setVariableModifications(const StringList & modifications);

protected:

    void disableTransition_(HMMState * s1, HMMState * s2);

    void enableTransition_(HMMState * s1, HMMState * s2);

    void setTrainingEmissionProbability_(HMMState * state, double prob);

    void setTransitionProbability_(HMMState * s1, HMMState * s2, double prob);

    double getTransitionProbability_(HMMState * s1, HMMState * s2) const;


    void calculateForwardPart_();

    void calculateBackwardPart_();

    double getForwardVariable_(HMMState *);

    double getBackwardVariable_(HMMState *);

private:

    // transition probs
    Map<HMMState *, Map<HMMState *, double> > trans_;

    // transition prob counts
    Map<HMMState *, Map<HMMState *, double> > count_trans_;

    Map<HMMState *, Map<HMMState *, std::vector<double> > > count_trans_all_;

    // all transition probs of all training steps (for model checking)
    Map<HMMState *, Map<HMMState *, std::vector<double> > > train_count_trans_all_;

    // number of training steps of the transitions
    Map<HMMState *, Map<HMMState *, Size> > training_steps_count_;

    // forward variables
    Map<HMMState *, double> forward_;

    // backward variables
    Map<HMMState *, double> backward_;

    // name to state Mapping
    Map<String, HMMState *> name_to_state_;

    // emission probabilities
    Map<HMMState *, double> train_emission_prob_;

    // initial transition probabilities
    Map<HMMState *, double> init_prob_;

    // all states of the HMM
    std::set<HMMState *> states_;

    // trained transitions
    std::set<std::pair<HMMState *, HMMState *> > trained_trans_;

    // synonym transitions Mapping
    Map<String, Map<String, std::pair<String, String> > > synonym_trans_names_;

    // synonym transitions
    Map<HMMState *, Map<HMMState *, std::pair<HMMState *, HMMState *> > > synonym_trans_;

    // transitions which are enabled
    Map<HMMState *, std::set<HMMState *> > enabled_trans_;

    // pseudocounts used in this instance
    double pseudo_counts_;

    // copy all the stuff from one HMM to this
    void copy_(const HiddenMarkovModel & source);

    StringList var_modifications_;
  };
}
#endif