de.jstacs.scoringFunctions
Class VariableLengthScoringFunction

java.lang.Object
  de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
      de.jstacs.scoringFunctions.VariableLengthScoringFunction

All Implemented Interfaces:

NormalizableScoringFunction, ScoringFunction, Storable, Cloneable

Direct Known Subclasses:

HomogeneousScoringFunction

public abstract class VariableLengthScoringFunction
extends AbstractNormalizableScoringFunction

This is the main class for all ScoringFunctions that allow to score subsequences of arbitrary length. This ScoringFunction should be the super class for non-motif ScoringFunctions like homogeneous Markov models, cyclic Markov models, ...

Author:

Jens Keilwagen

Field Summary

Fields inherited from class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

alphabets, length, r

Fields inherited from interface de.jstacs.scoringFunctions.ScoringFunction

UNKNOWN

Constructor Summary

protected	VariableLengthScoringFunction(AlphabetContainer alphabets) This is the main constructor that creates an instance that models sequence s of arbitrary length.
protected	VariableLengthScoringFunction(AlphabetContainer alphabets, int length) This is the main constructor that creates an instance that models sequence s of a given length.
protected	VariableLengthScoringFunction(StringBuffer source) This is the constructor for Storable.

Method Summary

double	getLogScore(Sequence seq, int start) Returns the log score for the sequence
abstract double	getLogScore(Sequence seq, int start, int length) This method computes the logarithm of the score for a given subsequence.
abstract double	getLogScoreAndPartialDerivation(Sequence seq, int start, int length, IntList indices, DoubleList dList) This method computes the logarithm of the score and the partial derivations for a given subsequence.
double	getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList dList) Returns the log score for the sequence and fills the list with the indices and the partial derivations.
double	getNormalizationConstant() Returns the sum of the scores over all sequences of the event space.
abstract double	getNormalizationConstant(int length) This method returns the normalization constant for a given sequence length.
double	getPartialNormalizationConstant(int parameterIndex) Returns the partial normalization constant for the parameter with index parameterIndex.
abstract double	getPartialNormalizationConstant(int parameterIndex, int length) This method returns the partial normalization constant for a given parameter index and sequence length.
abstract double[]	getStationarySymbolDistribution() This method returns the stationary symbol distribution.
abstract 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.scoringFunctions.AbstractNormalizableScoringFunction

clone, fromXML, getAlphabetContainer, getInitialClassParam, getLength, getLogScore, getLogScoreAndPartialDerivation, getNumberOfRecommendedStarts, isNormalized, isNormalized

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.jstacs.scoringFunctions.NormalizableScoringFunction

addGradientOfLogPriorTerm, getEss, getLogPriorTerm, getSizeOfEventSpaceForRandomVariablesOfParameter

Methods inherited from interface de.jstacs.scoringFunctions.ScoringFunction

getCurrentParameterValues, getInstanceName, getNumberOfParameters, initializeFunction, initializeFunctionRandomly, isInitialized, setParameters

Methods inherited from interface de.jstacs.Storable

toXML

Constructor Detail

VariableLengthScoringFunction

protected VariableLengthScoringFunction(AlphabetContainer alphabets)

This is the main constructor that creates an instance that models sequence s of arbitrary length.

Parameters:

alphabets - the AlphabetContainer

VariableLengthScoringFunction

protected VariableLengthScoringFunction(AlphabetContainer alphabets,
                                        int length)

This is the main constructor that creates an instance that models sequence s of a given length.

Parameters:

alphabets - the AlphabetContainer

length - the length of the modeled sequences

VariableLengthScoringFunction

protected VariableLengthScoringFunction(StringBuffer source)
                                 throws NonParsableException

This is the constructor for Storable.

Parameters:

source - the xml representation

Throws:

NonParsableException - if the representation could not be parsed.

Method Detail

getNormalizationConstant

public double getNormalizationConstant()

Description copied from interface: NormalizableScoringFunction

Returns the sum of the scores over all sequences of the event space.

Returns:

the normalization constant Z

getNormalizationConstant

public abstract double getNormalizationConstant(int length)

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

Parameters:

length - the sequence length

Returns:

the normalization constant

See Also:

NormalizableScoringFunction.getNormalizationConstant()

getPartialNormalizationConstant

public double getPartialNormalizationConstant(int parameterIndex)
                                       throws Exception

Description copied from interface: NormalizableScoringFunction

Returns the partial normalization constant for the parameter with index parameterIndex. This is the partial derivation of the normalization constant for the parameter with index parameterIndex \frac{\partial Z(\lambda)}{\partial \lambda_{index}}.

Parameters:

parameterIndex - the index of the parameter

Returns:

the partial normalization constant

Throws:

Exception - if something went wrong with the Normalization

getPartialNormalizationConstant

public abstract double getPartialNormalizationConstant(int parameterIndex,
                                                       int length)
                                                throws Exception

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

Parameters:

parameterIndex - the index of the parameter

length - the sequence length

Returns:

the partial normalization constant

Throws:

Exception - if something went wrong

See Also:

NormalizableScoringFunction.getPartialNormalizationConstant(int)

getLogScore

public double getLogScore(Sequence seq,
                          int start)

Description copied from interface: ScoringFunction

Returns the log score for the sequence

Parameters:

seq - the sequence

start - the startposition in the sequence

Returns:

the log score for the sequence

getLogScore

public abstract double getLogScore(Sequence seq,
                                   int start,
                                   int length)

This method computes the logarithm of the score for a given subsequence.

Parameters:

seq - the sequence

start - the start index

length - the end index

Returns:

the logarithm of the score

See Also:

ScoringFunction.getLogScore(Sequence, int)

getLogScoreAndPartialDerivation

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

Description copied from interface: ScoringFunction

Returns the log score for the sequence and fills the list with the indices and the partial derivations.

Parameters:

seq - the sequence

start - the startposition in the sequence

indices - after method invocation the list should contain the indices i where \frac{\partial \log score(seq)}{\partial \lambda_i} is not zero

dList - after method invocation the list should contain the corresponding \frac{\partial \log score(seq)}{\partial \lambda_i}

Returns:

the log score

getLogScoreAndPartialDerivation

public abstract double getLogScoreAndPartialDerivation(Sequence seq,
                                                       int start,
                                                       int length,
                                                       IntList indices,
                                                       DoubleList dList)

This method computes the logarithm of the score and the partial derivations for a given subsequence.

Parameters:

seq - the sequence

start - the start index

length - the end index

indices - the list for the indices of the parameters

dList - the list for the partial derivations

Returns:

the logarithm of the score

See Also:

ScoringFunction.getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList)

getStationarySymbolDistribution

public abstract double[] getStationarySymbolDistribution()

This method returns the stationary symbol distribution. For DNA this is the stationary mono nucleotide distribution. This method is used to determine the contrast for de.jstacs.motifDiscovery.Mutable#expand(int, double[], double[], double), de.jstacs.motifDiscovery.Mutable#shift(double[], double[], double) and de.jstacs.motifDiscovery.Mutable#shrink(double[], double[], double).

Returns:

the stationary symbol distribution

See Also:

Mutable

setStatisticForHyperparameters

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

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.

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