Hidden Markov Model implementation of PILIS. More...

#include <OpenMS/ANALYSIS/ID/HiddenMarkovModel.h>

Collaboration diagram for HiddenMarkovModel:

Constructors and destructors
Map< HMMState , Map< HMMState , double > >	trans_

Map< HMMState , Map< HMMState , double > >	count_trans_

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

Map< HMMState , Map< HMMState , std::vector< double > > >	train_count_trans_all_

Map< HMMState , Map< HMMState , Size > >	training_steps_count_

Map< HMMState *, double >	forward_

Map< HMMState *, double >	backward_

Map< String, HMMState * >	name_to_state_

Map< HMMState *, double >	train_emission_prob_

Map< HMMState *, double >	init_prob_

std::set< HMMState * >	states_

std::set< std::pair< HMMState , HMMState > >	trained_trans_

Map< String, Map< String, std::pair< String, String > > >	synonym_trans_names_

Map< HMMState , Map< HMMState , std::pair< HMMState , HMMState > > >	synonym_trans_

Map< HMMState , std::set< HMMState > >	enabled_trans_

double	pseudo_counts_

StringList	var_modifications_

	HiddenMarkovModel ()
	default constructor More...

	HiddenMarkovModel (const HiddenMarkovModel &hmm_new)
	copy constructor More...

virtual	~HiddenMarkovModel ()
	destructor More...

HiddenMarkovModel &	operator= (const HiddenMarkovModel &)
	assignment operator More...

void	writeGraphMLFile (const String &filename)
	writes the HMM into a file in GraphML format More...

void	write (std::ostream &out) const
	writes the HMM into an outstream More...

double	getTransitionProbability (const String &s1, const String &s2) const
	returns the transition probability of the given state names More...

void	setTransitionProbability (const String &s1, const String &s2, double prob)
	sets the transition probability of the given state names to prob More...

Size	getNumberOfStates () const
	return the number of states More...

void	addNewState (HMMState *state)
	registers a new state to the HMM More...

void	addNewState (const String &name)
	registers a new state to the HMM More...

void	addSynonymTransition (const String &name1, const String &name2, const String &synonym1, const String &synonym2)
	add a new synonym transition to the given state names More...

void	evaluate ()
	evaluate the HMM, estimates the transition probabilities from the training More...

void	train ()
	trains the HMM; initial probabilities and emission probabilities of the emitting states should be set More...

void	setInitialTransitionProbability (const String &state, double prob)
	sets the initial transition probability of the given state to prob More...

void	clearInitialTransitionProbabilities ()
	clears the initial probabilities More...

void	setTrainingEmissionProbability (const String &state, double prob)
	sets the emission probability of the given state to prob More...

void	clearTrainingEmissionProbabilities ()
	clear the emission probabilities More...

void	enableTransition (const String &s1, const String &s2)
	enables a transition; adds s1 to the predecessor list of s2 and s2 to the successor list of s1 More...

void	disableTransition (const String &s1, const String &s2)
	disables the transition; deletes the nodes from the predecessor/successor list respectively More...

void	disableTransitions ()
	disables all transitions More...

void	calculateEmissionProbabilities (Map< HMMState *, double > &emission_probs)
	calculates the emission probabilities of the HMM (of course only of the non-hidden states) More...

void	dump ()
	writes some stats to cerr More...

void	forwardDump ()
	writes some info of the forward "matrix" to cerr More...

void	estimateUntrainedTransitions ()
	builds a synonyms structure, needed when synonyms are used More...

HMMState *	getState (const String &name)
	returns the state with the given name More...

const HMMState *	getState (const String &name) const
	returns the state with the given name More...

void	clear ()
	clears all data More...

void	setPseudoCounts (double pseudo_counts)
	sets the pseudo count that are added instead of zero More...

double	getPseudoCounts () const
	returns the pseudo counts More...

void	setVariableModifications (const StringList &modifications)

void	disableTransition_ (HMMState s1, HMMState s2)
	disables the transition; deletes the nodes from the predecessor/successor list respectively More...

void	enableTransition_ (HMMState s1, HMMState s2)
	enables a transition; adds s1 to the predecessor list of s2 and s2 to the successor list of s1 More...

void	setTrainingEmissionProbability_ (HMMState *state, double prob)
	sets the emission probability of the given state to prob More...

void	setTransitionProbability_ (HMMState s1, HMMState s2, double prob)
	sets the transition probability of the given states to prob More...

double	getTransitionProbability_ (HMMState s1, HMMState s2) const
	returns the transition probability of the given states More...

void	calculateForwardPart_ ()
	performs the forward algorithm More...

void	calculateBackwardPart_ ()
	performs the backward algorithm More...

double	getForwardVariable_ (HMMState *)
	returns the forward variable More...

double	getBackwardVariable_ (HMMState *)
	returns the backward variable More...

void	copy_ (const HiddenMarkovModel &source)

Detailed Description

Hidden Markov Model implementation of PILIS.

Hidden Markov Model implementation suitable for forward connected HMMs. The HMM is mostly used within PILIS. For further details have a look at the docs of PILIS.

Constructor & Destructor Documentation

◆ HiddenMarkovModel() [1/2]

HiddenMarkovModel ( )

default constructor

◆ HiddenMarkovModel() [2/2]

HiddenMarkovModel ( const HiddenMarkovModel & hmm_new )

copy constructor

◆ ~HiddenMarkovModel()

virtual ~HiddenMarkovModel ( )

virtual

destructor

Member Function Documentation

◆ addNewState() [1/2]

void addNewState ( const String & name )

registers a new state to the HMM

◆ addNewState() [2/2]

void addNewState ( HMMState * state )

registers a new state to the HMM

◆ addSynonymTransition()

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

add a new synonym transition to the given state names

◆ calculateBackwardPart_()

void calculateBackwardPart_ ( )

protected

performs the backward algorithm

◆ calculateEmissionProbabilities()

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

calculates the emission probabilities of the HMM (of course only of the non-hidden states)

◆ calculateForwardPart_()

void calculateForwardPart_ ( )

protected

performs the forward algorithm

◆ clear()

void clear ( )

clears all data

◆ clearInitialTransitionProbabilities()

void clearInitialTransitionProbabilities ( )

clears the initial probabilities

◆ clearTrainingEmissionProbabilities()

void clearTrainingEmissionProbabilities ( )

clear the emission probabilities

◆ copy_()

void copy_ ( const HiddenMarkovModel & source )

private

◆ disableTransition()

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

disables the transition; deletes the nodes from the predecessor/successor list respectively

◆ disableTransition_()

void disableTransition_	(	HMMState *	s1,
		HMMState *	s2
	)

protected

disables the transition; deletes the nodes from the predecessor/successor list respectively

◆ disableTransitions()

void disableTransitions ( )

disables all transitions

◆ dump()

void dump ( )

writes some stats to cerr

◆ enableTransition()

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

enables a transition; adds s1 to the predecessor list of s2 and s2 to the successor list of s1

◆ enableTransition_()

void enableTransition_	(	HMMState *	s1,
		HMMState *	s2
	)

protected

enables a transition; adds s1 to the predecessor list of s2 and s2 to the successor list of s1

◆ estimateUntrainedTransitions()

void estimateUntrainedTransitions ( )

builds a synonyms structure, needed when synonyms are used

estimates the transition probabilities of not trained transitions by averages similar trained ones

◆ evaluate()

void evaluate ( )

evaluate the HMM, estimates the transition probabilities from the training

◆ forwardDump()

void forwardDump ( )

writes some info of the forward "matrix" to cerr

◆ getBackwardVariable_()

double getBackwardVariable_ ( HMMState * )

protected

returns the backward variable

◆ getForwardVariable_()

double getForwardVariable_ ( HMMState * )

protected

returns the forward variable

◆ getNumberOfStates()

Size getNumberOfStates ( ) const

return the number of states

◆ getPseudoCounts()

double getPseudoCounts ( ) const

returns the pseudo counts

◆ getState() [1/2]

HMMState* getState ( const String & name )

returns the state with the given name

◆ getState() [2/2]

const HMMState* getState ( const String & name ) const

returns the state with the given name

◆ getTransitionProbability()

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

returns the transition probability of the given state names

◆ getTransitionProbability_()

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

protected

returns the transition probability of the given states

◆ operator=()

HiddenMarkovModel& operator= ( const HiddenMarkovModel & )

assignment operator

◆ setInitialTransitionProbability()

void setInitialTransitionProbability	(	const String &	state,
		double	prob
	)

sets the initial transition probability of the given state to prob

◆ setPseudoCounts()

void setPseudoCounts ( double pseudo_counts )

sets the pseudo count that are added instead of zero

◆ setTrainingEmissionProbability()

void setTrainingEmissionProbability	(	const String &	state,
		double	prob
	)

sets the emission probability of the given state to prob

◆ setTrainingEmissionProbability_()

void setTrainingEmissionProbability_	(	HMMState *	state,
		double	prob
	)

protected

sets the emission probability of the given state to prob

◆ setTransitionProbability()

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

sets the transition probability of the given state names to prob

◆ setTransitionProbability_()

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

protected

sets the transition probability of the given states to prob

◆ setVariableModifications()

void setVariableModifications ( const StringList & modifications )

◆ train()

void train ( )

trains the HMM; initial probabilities and emission probabilities of the emitting states should be set

◆ write()

void write ( std::ostream & out ) const

writes the HMM into an outstream

◆ writeGraphMLFile()

void writeGraphMLFile ( const String & filename )

writes the HMM into a file in GraphML format

Accessors A detailed description of the GraphML format can be found under http://graphml.graphdrawing.org/

Member Data Documentation

◆ backward_

Map<HMMState *, double> backward_

private

◆ count_trans_

Map<HMMState *, Map<HMMState *, double> > count_trans_

private

◆ count_trans_all_

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

private

◆ enabled_trans_

Map<HMMState *, std::set<HMMState *> > enabled_trans_

private

◆ forward_

Map<HMMState *, double> forward_

private

◆ init_prob_

Map<HMMState *, double> init_prob_

private

◆ name_to_state_

Map<String, HMMState *> name_to_state_

private

◆ pseudo_counts_

double pseudo_counts_

private

◆ states_

std::set<HMMState *> states_

private

◆ synonym_trans_

Map<HMMState *, Map<HMMState *, std::pair<HMMState *, HMMState *> > > synonym_trans_

private

◆ synonym_trans_names_

Map<String, Map<String, std::pair<String, String> > > synonym_trans_names_

private

◆ train_count_trans_all_

Map<HMMState *, Map<HMMState *, std::vector<double> > > train_count_trans_all_

private

◆ train_emission_prob_

Map<HMMState *, double> train_emission_prob_

private

◆ trained_trans_

std::set<std::pair<HMMState *, HMMState *> > trained_trans_

private

◆ training_steps_count_

Map<HMMState *, Map<HMMState *, Size> > training_steps_count_

private

◆ trans_

Map<HMMState *, Map<HMMState *, double> > trans_

private

◆ var_modifications_

StringList var_modifications_

private

Constructors and destructors

Detailed Description

Constructor & Destructor Documentation

◆ HiddenMarkovModel() [1/2]

◆ HiddenMarkovModel() [2/2]

◆ ~HiddenMarkovModel()

Member Function Documentation

◆ addNewState() [1/2]

◆ addNewState() [2/2]

◆ addSynonymTransition()

◆ calculateBackwardPart_()

◆ calculateEmissionProbabilities()

◆ calculateForwardPart_()

◆ clear()

◆ clearInitialTransitionProbabilities()

◆ clearTrainingEmissionProbabilities()

◆ copy_()

◆ disableTransition()

◆ disableTransition_()

◆ disableTransitions()

◆ dump()

◆ enableTransition()

◆ enableTransition_()

◆ estimateUntrainedTransitions()

◆ evaluate()

◆ forwardDump()

◆ getBackwardVariable_()

◆ getForwardVariable_()

◆ getNumberOfStates()

◆ getPseudoCounts()

◆ getState() [1/2]

◆ getState() [2/2]

◆ getTransitionProbability()

◆ getTransitionProbability_()

◆ operator=()

◆ setInitialTransitionProbability()

◆ setPseudoCounts()

◆ setTrainingEmissionProbability()

◆ setTrainingEmissionProbability_()

◆ setTransitionProbability()

◆ setTransitionProbability_()

◆ setVariableModifications()

◆ train()

◆ write()

◆ writeGraphMLFile()

Member Data Documentation

◆ backward_

◆ count_trans_

◆ count_trans_all_

◆ enabled_trans_

◆ forward_

◆ init_prob_

◆ name_to_state_

◆ pseudo_counts_

◆ states_

◆ synonym_trans_

◆ synonym_trans_names_

◆ train_count_trans_all_

◆ train_emission_prob_

◆ trained_trans_

◆ training_steps_count_

◆ trans_

◆ var_modifications_