de.jstacs.scoringFunctions
Interface VariableLengthScoringFunction

All Superinterfaces:

Cloneable, NormalizableScoringFunction, ScoringFunction, Storable

All Known Implementing Classes:

AbstractVariableLengthScoringFunction, CMMScoringFunction, HMM0ScoringFunction, HMMScoringFunction, HomogeneousScoringFunction, UniformHomogeneousScoringFunction, VariableLengthMixtureScoringFunction

public interface VariableLengthScoringFunction
extends NormalizableScoringFunction

This is an interface for all NormalizableScoringFunctions that allow to score subsequences of arbitrary length. This NormalizableScoringFunction should be the super class for non-motif NormalizableScoringFunctions like homogeneous Markov models, cyclic Markov models, ... etc.

Author:

Jens Keilwagen

Field Summary

Fields inherited from interface de.jstacs.scoringFunctions.ScoringFunction

UNKNOWN

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	getLogScore(Sequence seq, int start, int length) This method computes the logarithm of the score for a given subsequence.
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.
void	setStatisticForHyperparameters(int[] length, double[] weight) This method sets the hyperparameters for the model parameters by evaluating the given statistic.

Methods inherited from interface de.jstacs.scoringFunctions.NormalizableScoringFunction

addGradientOfLogPriorTerm, getEss, getInitialClassParam, getLogNormalizationConstant, getLogPartialNormalizationConstant, getLogPriorTerm, getSizeOfEventSpaceForRandomVariablesOfParameter, isNormalized

Methods inherited from interface de.jstacs.scoringFunctions.ScoringFunction

clone, getAlphabetContainer, getCurrentParameterValues, getInstanceName, getLength, getLogScore, getLogScore, getLogScoreAndPartialDerivation, getLogScoreAndPartialDerivation, getNumberOfParameters, getNumberOfRecommendedStarts, initializeFunction, initializeFunctionRandomly, isInitialized, setParameters

Methods inherited from interface de.jstacs.Storable

toXML

Method Detail

getLogNormalizationConstant

double getLogNormalizationConstant(int length)

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

Parameters:

length - the sequence length

Returns:

the logarithm of the normalization constant

See Also:

NormalizableScoringFunction.getLogNormalizationConstant()

getLogPartialNormalizationConstant

double getLogPartialNormalizationConstant(int parameterIndex,
                                          int length)
                                          throws Exception

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

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:

NormalizableScoringFunction.getLogPartialNormalizationConstant(int)

getLogScore

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 in the Sequence

length - the length of the Sequence beginning at start

Returns:

the logarithm of the score for the subsequence

See Also:

ScoringFunction.getLogScore(Sequence, int)

getLogScoreAndPartialDerivation

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 in the Sequence

length - the end index in the Sequence

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

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

Returns:

the logarithm of the score

See Also:

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

setStatisticForHyperparameters

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