de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models

Class SamplingPhyloHMM

java.lang.Object

de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingPhyloHMM

All Implemented Interfaces:

SequenceScore, StatisticalModel, TrainableStatisticalModel, Storable, Cloneable

public class SamplingPhyloHMM
extends SamplingHigherOrderHMM

This class implements an (higher order) HMM that contains multi-dimensional emissions described by a phylogenetic tree. The model is trained by a Metropolis-Hastings algorithm.

Author:

Michael Scharfe

Nested Class Summary

Nested classes/interfaces inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

SamplingHigherOrderHMM.ViterbiComputation

Nested classes/interfaces inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

HigherOrderHMM.Type

Field Summary

Fields inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

burnInTest, hasSampled

Fields inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

backwardIntermediate, container, logEmission, numberOfSummands, skipInit, stateList

Fields inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

bwdMatrix, emission, emissionIdx, finalState, forward, fwdMatrix, name, sostream, START_NODE, states, threads, trainingParameter, transition

Fields inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

alphabets, length

Constructor Summary

Constructors

Constructor and Description
SamplingPhyloHMM(SamplingHMMTrainingParameterSet trainingParameterSet, String[] name, int[] emissionIdx, boolean[] forward, PhyloDiscreteEmission[] emission, TransitionElement... te) This is the main constructor for a hidden markov model with phylogenetic emission(s) This model can be trained using a metropolis hastings algorithm
SamplingPhyloHMM(StringBuffer xml) The standard constructor for the interface Storable.

Method Summary

Modifier and Type	Method and Description
String	getInstanceName() Should return a short instance name such as iMM(0), BN(2), ...
protected void	getNewParameters() This method set all parameters for the next sampling step

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

acceptParameters, appendFurtherInformation, clone, createStates, drawFromStatistics, extractFurtherInformation, furtherInits, getLogPosteriorFromStatistic, getLogProbForPath, getLogStatePosteriorMatrixFor, getViterbiPath, getViterbiPathFor, getXMLTag, gibbsSampling, gibbsSamplingStep, initTraining, isInitialized, logProb, parseNextParameterSet, parseParameterSet, train

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

baumWelch, createHelperVariables, estimateFromStatistics, fillBwdMatrix, fillBwdOrViterbiMatrix, fillFwdMatrix, fillLogStatePosteriorMatrix, finalize, getCharacteristics, getEmissionIndexes, getEmissions, getLogPriorTerm, getLogScoreFor, getLogScoreFor, getMaximalMarkovOrder, getNames, getNumericalCharacteristics, getTrainingParams, getTransisionElements, initialize, initializeRandomly, resetStatistics, samplePath, setSkiptInit, viterbi

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

createMatrixForStatePosterior, decodePath, decodeStatePosterior, determineFinalStates, fromXML, getFinalStatePosterioriMatrix, getGraphvizRepresentation, getGraphvizRepresentation, getGraphvizRepresentation, getGraphvizRepresentation, getLogProbFor, getLogStatePosteriorMatrixFor, getNumberOfStates, getNumberOfThreads, getRunTimeException, getStatePosteriorMatrixFor, getStatePosteriorMatrixFor, getViterbiPathFor, getViterbiPathsFor, initTransition, provideMatrix, setOutputStream, toString, toXML, train

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

check, emitDataSet, getAlphabetContainer, getLength, getLogProbFor, getLogProbFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, toString

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

SamplingPhyloHMM

public SamplingPhyloHMM(SamplingHMMTrainingParameterSet trainingParameterSet,
                        String[] name,
                        int[] emissionIdx,
                        boolean[] forward,
                        PhyloDiscreteEmission[] emission,
                        TransitionElement... te)
                 throws CloneNotSupportedException,
                        IllegalArgumentException,
                        WrongAlphabetException,
                        Exception

This is the main constructor for a hidden markov model with phylogenetic emission(s) This model can be trained using a metropolis hastings algorithm

Parameters:

trainingParameterSet - the ParameterSet that determines the training algorithm and contains the necessary Parameters

name - the names of the states

emissionIdx - the indices of the emissions that should be used for each state

forward - a boolean array that indicates whether the symbol on the forward or the reverse complementary strand should be used

emission - the emissions

te - the TransitionElements building a transition

Throws:

CloneNotSupportedException - if the parameters or the emissions or transition elements could not be cloned

IllegalArgumentException - if one of the parameters is not allowed

WrongAlphabetException - if the alphabet does not fit the model

Exception - if something else went wrong

SamplingPhyloHMM

public SamplingPhyloHMM(StringBuffer xml)
                 throws NonParsableException

The standard constructor for the interface Storable. Constructs an SamplingPhyloHMM out of an XML representation.

Parameters:

xml - the XML representation as StringBuffer

Throws:

NonParsableException - if the SamplingPhyloHMM could not be reconstructed out of the StringBuffer xml

Method Detail

getInstanceName

public String getInstanceName()

Description copied from interface: SequenceScore

Should return a short instance name such as iMM(0), BN(2), ...

Specified by:

getInstanceName in interface SequenceScore

Overrides:

getInstanceName in class SamplingHigherOrderHMM

Returns:

a short instance name

getNewParameters

protected void getNewParameters()
                         throws Exception

Description copied from class: SamplingHigherOrderHMM

This method set all parameters for the next sampling step

Overrides:

getNewParameters in class SamplingHigherOrderHMM

Throws:

Exception - if something went wrong