de.jstacs.sequenceScores.statisticalModels.differentiable.mixture
Class VariableLengthMixtureDiffSM

java.lang.Object
  de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
      de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
          de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
              de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
                  de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM

All Implemented Interfaces:

MotifDiscoverer, MutableMotifDiscoverer, DifferentiableSequenceScore, SequenceScore, DifferentiableStatisticalModel, SamplingDifferentiableStatisticalModel, VariableLengthDiffSM, StatisticalModel, Storable, Cloneable

public class VariableLengthMixtureDiffSM
extends MixtureDiffSM
implements VariableLengthDiffSM

This class implements a mixture of VariableLengthDiffSM by extending MixtureDiffSM and implementing the methods of VariableLengthDiffSM.

Author:

Jens Keilwagen

Nested Class Summary

Nested classes/interfaces inherited from interface de.jstacs.motifDiscovery.MotifDiscoverer

MotifDiscoverer.KindOfProfile

Field Summary

Fields inherited from class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

componentScore, dList, freeParams, function, hiddenParameter, hiddenPotential, iList, logGammaSum, logHiddenNorm, logHiddenPotential, norm, optimizeHidden, paramRef, partNorm

Fields inherited from class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore

alphabets, length, r

Fields inherited from interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

UNKNOWN

Constructor Summary

VariableLengthMixtureDiffSM(int starts, boolean plugIn, VariableLengthDiffSM... component)
This constructor creates a new VariableLengthMixtureDiffSM.

VariableLengthMixtureDiffSM(StringBuffer xml)
This is the constructor for the interface Storable.

Method Summary

double	getLogNormalizationConstant(int length) This method returns the logarithm of the normalization constant for a given sequence length.
double	getLogPartialNormalizationConstant(int parameterIndex, int length) This method returns the logarithm of the partial normalization constant for a given parameter index and a sequence length.
double	getLogScoreAndPartialDerivation(Sequence seq, int start, int end, IntList indices, DoubleList partialDer) Returns the logarithmic score for a Sequence beginning at position start in the Sequence and fills lists with the indices and the partial derivations.
double	getLogScoreFor(Sequence seq, int start, int end) Returns the logarithmic score for the Sequence seq beginning at position start in the Sequence.
void	setStatisticForHyperparameters(int[] length, double[] weight) This method sets the hyperparameters for the model parameters by evaluating the given statistic.

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM

adjustHiddenParameters, clone, fillComponentScores, getESS, getGlobalIndexOfMotifInComponent, getHyperparameterForHiddenParameter, getIndexOfMaximalComponentFor, getInstanceName, getLogNormalizationConstantForComponent, getLogPartialNormalizationConstant, getLogScoreAndPartialDerivation, getMotifLength, getNumberOfMotifs, getNumberOfMotifsInComponent, getProfileOfScoresFor, getStrandProbabilitiesFor, initializeMotif, initializeMotifRandomly, initializeUsingPlugIn, modifyMotif, toString

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

addGradientOfLogPriorTerm, cloneFunctions, computeHiddenParameter, computeLogGammaSum, determineIsNormalized, extractFurtherInformation, fromXML, getCurrentParameterValues, getDifferentiableStatisticalModels, getFunction, getFunctions, getFurtherInformation, getIndexOfMaximalComponentFor, getIndices, getLogNormalizationConstant, getLogPriorTerm, getLogScoreFor, getNumberOfComponents, getNumberOfParameters, getNumberOfRecommendedStarts, getProbsForComponent, getSamplingGroups, getSizeOfEventSpaceForRandomVariablesOfParameter, getXMLTag, init, initializeFunction, initializeFunctionRandomly, initializeHiddenPotentialRandomly, initializeHiddenUniformly, initWithLength, isInitialized, isNormalized, precomputeNorm, setHiddenParameters, setParameters, setParametersForFunction, toXML

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel

emitDataSet, getInitialClassParam, getLogProbFor, getLogProbFor, getLogProbFor, getLogScoreFor, getLogScoreFor, getMaximalMarkovOrder, isNormalized

Methods inherited from class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore

getAlphabetContainer, getCharacteristics, getLength, getLogScoreAndPartialDerivation, getLogScoreFor, getNumberOfStarts, getNumericalCharacteristics

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel

addGradientOfLogPriorTerm, getESS, getLogNormalizationConstant, getLogPartialNormalizationConstant, getLogPriorTerm, getSizeOfEventSpaceForRandomVariablesOfParameter, isNormalized

Methods inherited from interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

clone, getCurrentParameterValues, getInitialClassParam, getLogScoreAndPartialDerivation, getLogScoreAndPartialDerivation, getNumberOfParameters, getNumberOfRecommendedStarts, initializeFunction, initializeFunctionRandomly, setParameters

Methods inherited from interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel

emitDataSet, getLogProbFor, getLogProbFor, getLogProbFor, getMaximalMarkovOrder

Methods inherited from interface de.jstacs.sequenceScores.SequenceScore

getAlphabetContainer, getCharacteristics, getInstanceName, getLength, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getNumericalCharacteristics, isInitialized

Methods inherited from interface de.jstacs.Storable

toXML

Methods inherited from interface de.jstacs.motifDiscovery.MotifDiscoverer

getNumberOfComponents

Constructor Detail

VariableLengthMixtureDiffSM

public VariableLengthMixtureDiffSM(int starts,
                                   boolean plugIn,
                                   VariableLengthDiffSM... component)
                            throws CloneNotSupportedException

This constructor creates a new VariableLengthMixtureDiffSM.

Parameters:

starts - the number of starts that should be done in an optimization

plugIn - indicates whether the initial parameters for an optimization should be related to the data or randomly drawn

component - the VariableLengthDiffSMs

Throws:

CloneNotSupportedException - if an element of component could not be cloned

VariableLengthMixtureDiffSM

public VariableLengthMixtureDiffSM(StringBuffer xml)
                            throws NonParsableException

This is the constructor for the interface Storable. Creates a new VariableLengthMixtureDiffSM out of a StringBuffer.

Parameters:

xml - the XML representation as StringBuffer

Throws:

NonParsableException - if the XML representation could not be parsed

Method Detail

getLogScoreFor

public double getLogScoreFor(Sequence seq,
                             int start,
                             int end)

Description copied from interface: SequenceScore

Returns the logarithmic score for the Sequence seq beginning at position start in the Sequence.

Specified by:

getLogScoreFor in interface SequenceScore

Specified by:

getLogScoreFor in interface VariableLengthDiffSM

Overrides:

getLogScoreFor in class AbstractDifferentiableSequenceScore

Parameters:

seq - the Sequence

start - the start position in the Sequence

end - the end position (inclusive) in the Sequence

Returns:

the logarithmic score for the Sequence

getLogScoreAndPartialDerivation

public double getLogScoreAndPartialDerivation(Sequence seq,
                                              int start,
                                              int end,
                                              IntList indices,
                                              DoubleList partialDer)

Description copied from interface: DifferentiableSequenceScore

Returns the logarithmic score for a Sequence beginning at position start in the Sequence and fills lists with the indices and the partial derivations.

Specified by:

getLogScoreAndPartialDerivation in interface DifferentiableSequenceScore

Specified by:

getLogScoreAndPartialDerivation in interface VariableLengthDiffSM

Overrides:

getLogScoreAndPartialDerivation in class AbstractDifferentiableSequenceScore

Parameters:

seq - the Sequence

start - the start position in the Sequence

end - the end position (inclusive) in the Sequence

indices - an IntList of indices, after method invocation the list should contain the indices i where is not zero

partialDer - a DoubleList of partial derivations, after method invocation the list should contain the corresponding that are not zero

Returns:

the logarithmic score for the Sequence

getLogNormalizationConstant

public double getLogNormalizationConstant(int length)

Description copied from interface: VariableLengthDiffSM

This method returns the logarithm of the normalization constant for a given sequence length.

Specified by:

getLogNormalizationConstant in interface VariableLengthDiffSM

Parameters:

length - the sequence length

Returns:

the logarithm of the normalization constant

See Also:

DifferentiableStatisticalModel.getLogNormalizationConstant()

getLogPartialNormalizationConstant

public double getLogPartialNormalizationConstant(int parameterIndex,
                                                 int length)
                                          throws Exception

Description copied from interface: VariableLengthDiffSM

This method returns the logarithm of the partial normalization constant for a given parameter index and a sequence length.

Specified by:

getLogPartialNormalizationConstant in interface VariableLengthDiffSM

Parameters:

parameterIndex - the index of the parameter

length - the sequence length

Returns:

the logarithm of the partial normalization constant

Throws:

Exception - if something went wrong

See Also:

DifferentiableStatisticalModel.getLogPartialNormalizationConstant(int)

setStatisticForHyperparameters

public void setStatisticForHyperparameters(int[] length,
                                           double[] weight)
                                    throws Exception

Description copied from interface: VariableLengthDiffSM

This method sets the hyperparameters for the model parameters by evaluating the given statistic. The statistic can be interpreted as follows: The model has seen a number of sequences. From these sequences it is only known how long (length) and how often ( weight) they have been seen.

Specified by:

setStatisticForHyperparameters in interface VariableLengthDiffSM

Parameters:

length - the non-negative lengths of the sequences

weight - the non-negative weight for the corresponding sequence

Throws:

Exception - if something went wrong

See Also:

Mutable