de.jstacs.scoringFunctions
Class IndependentProductScoringFunction

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

All Implemented Interfaces:

MotifDiscoverer, MutableMotifDiscoverer, NormalizableScoringFunction, ScoringFunction, Storable, Cloneable

public class IndependentProductScoringFunction
extends AbstractNormalizableScoringFunction
implements MutableMotifDiscoverer

This class enables the user to model parts of a sequence independent of each other. The first part of the sequence is modeled by the first NormalizableScoringFunction and has the length of the first NormalizableScoringFunction, the second part starts directly after the first part, is modeled by the second NormalizableScoringFunction ... etc.

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.scoringFunctions.AbstractNormalizableScoringFunction

alphabets, length, r

Fields inherited from interface de.jstacs.scoringFunctions.ScoringFunction

UNKNOWN

Constructor Summary

IndependentProductScoringFunction(NormalizableScoringFunction... functions)
This constructor creates an instance of an IndependentProductScoringFunction from a given series of independent NormalizableScoringFunctions.

IndependentProductScoringFunction(NormalizableScoringFunction[] functions, int[] length)
This constructor creates an instance of an IndependentProductScoringFunction from given series of independent NormalizableScoringFunctions and lengths.

IndependentProductScoringFunction(StringBuffer source)
This is the constructor for the interface Storable.

Method Summary

void	addGradientOfLogPriorTerm(double[] grad, int start) This method computes the gradient of NormalizableScoringFunction.getLogPriorTerm() for each parameter of this model.
IndependentProductScoringFunction	clone() Creates a clone (deep copy) of the current ScoringFunction instance.
int[]	determineNotSignificantPositionsFor(int motif, Sample[] data, double[][] weights, int classIdx) This method determines the number of not significant positions from each side of the motif with index motif.
protected void	fromXML(StringBuffer rep) This method is called in the constructor for the Storable interface to create a scoring function from a StringBuffer.
double[]	getCurrentParameterValues() Returns a double array of dimension ScoringFunction.getNumberOfParameters() containing the current parameter values.
double	getEss() Returns the equivalent sample size (ess) of this model, i.e. the equivalent sample size for the class or component that is represented by this model.
int	getGlobalIndexOfMotifInComponent(int component, int motif) Returns the global index of the motif used in component.
int	getIndexOfMaximalComponentFor(Sequence sequence) Returns the index of the component with the maximal score for the sequence sequence.
String	getInstanceName() Returns a short instance name.
double	getLogPriorTerm() This method computes a value that is proportional to NormalizableScoringFunction.getEss() * Math.log( NormalizableScoringFunction.getNormalizationConstant() ) + Math.log( prior ).
double	getLogScore(Sequence seq, int start) Returns the logarithmic score for the Sequence seq beginning at position start in the Sequence.
double	getLogScoreAndPartialDerivation(Sequence seq, int start, 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.
int	getMotifLength(int motif) This method returns the length of the motif with index motif .
double	getNormalizationConstant() Returns the sum of the scores over all sequences of the event space.
int	getNumberOfComponents() Returns the number of components in this MotifDiscoverer.
int	getNumberOfMotifs() Returns the number of motifs for this MotifDiscoverer.
int	getNumberOfMotifsInComponent(int component) Returns the number of motifs that are used in the component component of this MotifDiscoverer.
int	getNumberOfParameters() Returns the number of parameters in this ScoringFunction.
int	getNumberOfRecommendedStarts() This method returns the number of recommended optimization starts.
double	getPartialNormalizationConstant(int parameterIndex) Returns the partial normalization constant for the parameter with index parameterIndex.
double[]	getProfileOfScoresFor(int component, int motif, Sequence sequence, int startpos, MotifDiscoverer.KindOfProfile dist) Returns the profile of the scores for component component and motif motif at all possible start positions of the motif in the sequence sequence beginning at startpos.
int	getSizeOfEventSpaceForRandomVariablesOfParameter(int index) Returns the size of the event space of the random variables that are affected by parameter no.
StrandedLocatedSequenceAnnotationWithLength.Strand	getStrandFor(int component, int motif, Sequence sequence, int startpos) This method returns the strand for a given subsequence if it is considered as site of the motif model in a specific component.
void	initializeFunction(int index, boolean freeParams, Sample[] data, double[][] weights) This method creates the underlying structure of the ScoringFunction.
void	initializeFunctionRandomly(boolean freeParams) This method initializes the ScoringFunction randomly.
void	initializeMotif(int motifIndex, Sample data, double[] weights) This method allows to initialize the model of a motif manually using a weighted sample.
boolean	isInitialized() This method can be used to determine whether the model is initialized.
boolean	modifyMotif(int motifIndex, double[] weightsLeft, double[] weightsRight, double[][][][] replacementLeft, double[][][][] replacementRight, int offsetLeft, int offsetRight) Manually modifies the motif model with index motifIndex.
boolean	modifyMotif(int motifIndex, int offsetLeft, int offsetRight) Manually modifies the motif model with index motifIndex.
void	setParameters(double[] params, int start) This method sets the internal parameters to the values of params between start and start + ScoringFunction.getNumberOfParameters() - 1
String	toString()
StringBuffer	toXML() This method returns an XML representation as StringBuffer of an instance of the implementing class.

Methods inherited from class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

getAlphabetContainer, getInitialClassParam, getLength, getLogScore, getLogScoreAndPartialDerivation, isNormalized, isNormalized

Methods inherited from class java.lang.Object

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

Constructor Detail

IndependentProductScoringFunction

public IndependentProductScoringFunction(NormalizableScoringFunction... functions)
                                  throws CloneNotSupportedException,
                                         IllegalArgumentException

This constructor creates an instance of an IndependentProductScoringFunction from a given series of independent NormalizableScoringFunctions. The length that is modeled by each component is determined by ScoringFunction.getLength(). So the length should not be 0.

Parameters:

functions - the components, i.e. the given series of independent NormalizableScoringFunctions

Throws:

CloneNotSupportedException - if at least one element of functions could not be cloned

IllegalArgumentException - if at least one component has length 0 or the components do not have the same equivalent sample size (ess)

See Also:

IndependentProductScoringFunction(NormalizableScoringFunction[], int[])

IndependentProductScoringFunction

public IndependentProductScoringFunction(NormalizableScoringFunction[] functions,
                                         int[] length)
                                  throws CloneNotSupportedException,
                                         IllegalArgumentException

This constructor creates an instance of an IndependentProductScoringFunction from given series of independent NormalizableScoringFunctions and lengths.

Parameters:

functions - the components, i.e. the given series of independent NormalizableScoringFunctions

length - the lengths, one for each component

Throws:

CloneNotSupportedException - if at least one component could not be cloned

IllegalArgumentException - if the lengths and the components are not matching or the components do not have the same equivalent sample size (ess)

See Also:

IndependentProductScoringFunction(NormalizableScoringFunction[], int[])

IndependentProductScoringFunction

public IndependentProductScoringFunction(StringBuffer source)
                                  throws NonParsableException

This is the constructor for the interface Storable. Creates a new IndependentProductScoringFunction out of a StringBuffer as returned by toXML().

Parameters:

source - the XML representation as StringBuffer

Throws:

NonParsableException - if the XML representation could not be parsed

Method Detail

clone

public IndependentProductScoringFunction clone()
                                        throws CloneNotSupportedException

Description copied from interface: ScoringFunction

Creates a clone (deep copy) of the current ScoringFunction instance.

Specified by:

clone in interface ScoringFunction

Overrides:

clone in class AbstractNormalizableScoringFunction

Returns:

the cloned instance of the current ScoringFunction

Throws:

CloneNotSupportedException - if something went wrong while cloning the ScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter

public int getSizeOfEventSpaceForRandomVariablesOfParameter(int index)

Description copied from interface: NormalizableScoringFunction

Returns the size of the event space of the random variables that are affected by parameter no. index, i.e. the product of the sizes of the alphabets at the position of each random variable affected by parameter index. For DNA alphabets this corresponds to 4 for a PWM, 16 for a WAM except position 0, ...

Specified by:

getSizeOfEventSpaceForRandomVariablesOfParameter in interface NormalizableScoringFunction

Parameters:

index - the index of the parameter

Returns:

the size of the event space

getNormalizationConstant

public double getNormalizationConstant()

Description copied from interface: NormalizableScoringFunction

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

Specified by:

getNormalizationConstant in interface NormalizableScoringFunction

Returns:

the normalization constant Z

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, in LaTex notation: \frac{\partial Z(\lambda)}{\partial \lambda_{index}}.

Specified by:

getPartialNormalizationConstant in interface NormalizableScoringFunction

Parameters:

parameterIndex - the index of the parameter

Returns:

the partial normalization constant

Throws:

Exception - if something went wrong with the normalization

See Also:

NormalizableScoringFunction.getNormalizationConstant()

getEss

public double getEss()

Description copied from interface: NormalizableScoringFunction

Returns the equivalent sample size (ess) of this model, i.e. the equivalent sample size for the class or component that is represented by this model.

Specified by:

getEss in interface NormalizableScoringFunction

Returns:

the equivalent sample size.

initializeFunction

public void initializeFunction(int index,
                               boolean freeParams,
                               Sample[] data,
                               double[][] weights)
                        throws Exception

Description copied from interface: ScoringFunction

This method creates the underlying structure of the ScoringFunction.

Specified by:

initializeFunction in interface ScoringFunction

Parameters:

index - the index of the class the ScoringFunction models

freeParams - indicates whether the (reduced) parameterization is used

data - the samples

weights - the weights of the sequences in the samples

Throws:

Exception - if something went wrong

fromXML

protected void fromXML(StringBuffer rep)
                throws NonParsableException

Description copied from class: AbstractNormalizableScoringFunction

This method is called in the constructor for the Storable interface to create a scoring function from a StringBuffer.

Specified by:

fromXML in class AbstractNormalizableScoringFunction

Parameters:

rep - the XML representation as StringBuffer

Throws:

NonParsableException - if the StringBuffer could not be parsed

See Also:

AbstractNormalizableScoringFunction.AbstractNormalizableScoringFunction(StringBuffer)

getInstanceName

public String getInstanceName()

Description copied from interface: ScoringFunction

Returns a short instance name.

Specified by:

getInstanceName in interface ScoringFunction

Returns:

a short instance name

getCurrentParameterValues

public double[] getCurrentParameterValues()
                                   throws Exception

Description copied from interface: ScoringFunction

Returns a double array of dimension ScoringFunction.getNumberOfParameters() containing the current parameter values. If one likes to use these parameters to start an optimization it is highly recommended to invoke ScoringFunction.initializeFunction(int, boolean, Sample[], double[][]) before. After an optimization this method can be used to get the current parameter values.

Specified by:

getCurrentParameterValues in interface ScoringFunction

Returns:

the current parameter values

Throws:

Exception - if no parameters exist (yet)

getLogScore

public double getLogScore(Sequence seq,
                          int start)

Description copied from interface: ScoringFunction

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

Specified by:

getLogScore in interface ScoringFunction

Parameters:

seq - the Sequence

start - the start position in the Sequence

Returns:

the logarithmic score for the Sequence

getLogScoreAndPartialDerivation

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

Description copied from interface: ScoringFunction

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 ScoringFunction

Parameters:

seq - the Sequence

start - the start position in the Sequence

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

partialDer - a DoubleList of partial derivations, after method invocation the list should contain the corresponding \frac{\partial \log score(seq)}{\partial \lambda_i}

Returns:

the logarithmic score for the Sequence

getNumberOfParameters

public int getNumberOfParameters()

Description copied from interface: ScoringFunction

Returns the number of parameters in this ScoringFunction. If the number of parameters is not known yet, the method returns ScoringFunction.UNKNOWN.

Specified by:

getNumberOfParameters in interface ScoringFunction

Returns:

the number of parameters in this ScoringFunction

See Also:

ScoringFunction.UNKNOWN

getNumberOfRecommendedStarts

public int getNumberOfRecommendedStarts()

Description copied from interface: ScoringFunction

This method returns the number of recommended optimization starts. The standard implementation returns 1.

Specified by:

getNumberOfRecommendedStarts in interface ScoringFunction

Overrides:

getNumberOfRecommendedStarts in class AbstractNormalizableScoringFunction

Returns:

the number of recommended optimization starts

setParameters

public void setParameters(double[] params,
                          int start)

Description copied from interface: ScoringFunction

This method sets the internal parameters to the values of params between start and start + ScoringFunction.getNumberOfParameters() - 1

Specified by:

setParameters in interface ScoringFunction

Parameters:

params - the new parameters

start - the start index in params

toXML

public StringBuffer toXML()

Description copied from interface: Storable

This method returns an XML representation as StringBuffer of an instance of the implementing class.

Specified by:

toXML in interface Storable

Returns:

the XML representation

toString

public String toString()

Overrides:

toString in class Object

getLogPriorTerm

public double getLogPriorTerm()

Description copied from interface: NormalizableScoringFunction

This method computes a value that is proportional to

NormalizableScoringFunction.getEss() * Math.log( NormalizableScoringFunction.getNormalizationConstant() ) + Math.log( prior ).

where prior is the prior for the parameters of this model.

Specified by:

getLogPriorTerm in interface NormalizableScoringFunction

Returns:

a value that is proportional to NormalizableScoringFunction.getEss() * Math.log( NormalizableScoringFunction.getNormalizationConstant() ) + Math.log( prior ).

See Also:

NormalizableScoringFunction.getEss(), NormalizableScoringFunction.getNormalizationConstant()

addGradientOfLogPriorTerm

public void addGradientOfLogPriorTerm(double[] grad,
                                      int start)
                               throws Exception

Description copied from interface: NormalizableScoringFunction

This method computes the gradient of NormalizableScoringFunction.getLogPriorTerm() for each parameter of this model. The results are added to the array grad beginning at index start.

Specified by:

addGradientOfLogPriorTerm in interface NormalizableScoringFunction

Parameters:

grad - the array of gradients

start - the start index in the grad array, where the partial derivations for the parameters of this models shall be entered

Throws:

Exception - if something went wrong with the computing of the gradients

See Also:

NormalizableScoringFunction.getLogPriorTerm()

isInitialized

public boolean isInitialized()

Description copied from interface: ScoringFunction

This method can be used to determine whether the model is initialized. If the model is not initialized you should invoke the method ScoringFunction.initializeFunction(int, boolean, Sample[], double[][]).

Specified by:

isInitialized in interface ScoringFunction

Returns:

true if the model is initialized, false otherwise

initializeFunctionRandomly

public void initializeFunctionRandomly(boolean freeParams)
                                throws Exception

Description copied from interface: ScoringFunction

This method initializes the ScoringFunction randomly. It has to create the underlying structure of the ScoringFunction.

Specified by:

initializeFunctionRandomly in interface ScoringFunction

Parameters:

freeParams - indicates whether the (reduced) parameterization is used

Throws:

Exception - if something went wrong

initializeMotif

public void initializeMotif(int motifIndex,
                            Sample data,
                            double[] weights)
                     throws Exception

Description copied from interface: MutableMotifDiscoverer

This method allows to initialize the model of a motif manually using a weighted sample.

Specified by:

initializeMotif in interface MutableMotifDiscoverer

Parameters:

motifIndex - the index of the motif in the motif discoverer

data - the sample of sequences

weights - either null or an array of length data.getNumberofElements() with non-negative weights.

Throws:

Exception - if initialize was not possible

modifyMotif

public boolean modifyMotif(int motifIndex,
                           double[] weightsLeft,
                           double[] weightsRight,
                           double[][][][] replacementLeft,
                           double[][][][] replacementRight,
                           int offsetLeft,
                           int offsetRight)
                    throws Exception

Description copied from interface: MutableMotifDiscoverer

Manually modifies the motif model with index motifIndex. The two offsets offsetLeft and offsetRight define how many positions the left or right border positions shall be moved. Negative numbers indicate moves to the left while positive numbers correspond to moves to the right.

Specified by:

modifyMotif in interface MutableMotifDiscoverer

Parameters:

motifIndex - the index of the motif in the motif discoverer

weightsLeft - the weights for the left contrast distributions

weightsRight - the weights for the right contrast distributions

replacementLeft - the replacement distribution for the left side

replacementRight - the replacement distribution for the right side

offsetLeft - the offset on the left side

offsetRight - the offset on the right side

Returns:

true if the motif model was modified otherwise false

Throws:

Exception

modifyMotif

public boolean modifyMotif(int motifIndex,
                           int offsetLeft,
                           int offsetRight)
                    throws Exception

Description copied from interface: MutableMotifDiscoverer

Manually modifies the motif model with index motifIndex. The two offsets offsetLeft and offsetRight define how many positions the left or right border positions shall be moved. Negative numbers indicate moves to the left while positive numbers correspond to moves to the right. The distribution for sequences to the left and right side of the motif shall be computed internally.

Specified by:

modifyMotif in interface MutableMotifDiscoverer

Parameters:

motifIndex - the index of the motif in the motif discoverer

offsetLeft - the offset on the left side

offsetRight - the offset on the right side

Returns:

true if the motif model was modified otherwise false

Throws:

Exception

See Also:

MutableMotifDiscoverer.modifyMotif(int, double[], double[], double[][][][], double[][][][], int, int)

determineNotSignificantPositionsFor

public int[] determineNotSignificantPositionsFor(int motif,
                                                 Sample[] data,
                                                 double[][] weights,
                                                 int classIdx)

Description copied from interface: MutableMotifDiscoverer

This method determines the number of not significant positions from each side of the motif with index motif.

Specified by:

determineNotSignificantPositionsFor in interface MutableMotifDiscoverer

Parameters:

motif - the index of the motif in the motif discoverer

data - an array Samples, each array-entry represents on class

weights - the weights of each Sequence for each class

classIdx - the index of the current class in classCounts

Returns:

a two dimensional array containing at position 0 the number of not significant positions from the left and at position 1 the number of not significant positions from the right side

See Also:

Mutable.determineNotSignificantPositions(double, double[], double[], double[][][][], double[][][][], double), MutableMotifDiscoverer.modifyMotif(int, int, int), MutableMotifDiscoverer.modifyMotif(int, double[], double[], double[][][][], double[][][][], int, int)

getGlobalIndexOfMotifInComponent

public int getGlobalIndexOfMotifInComponent(int component,
                                            int motif)

Description copied from interface: MotifDiscoverer

Returns the global index of the motif used in component. The index returned must be at least 0 and less than MotifDiscoverer.getNumberOfMotifs().

Specified by:

getGlobalIndexOfMotifInComponent in interface MotifDiscoverer

Parameters:

component - the component index

motif - the motif index in the component

Returns:

the global index of the motif in component

getIndexOfMaximalComponentFor

public int getIndexOfMaximalComponentFor(Sequence sequence)
                                  throws Exception

Description copied from interface: MotifDiscoverer

Returns the index of the component with the maximal score for the sequence sequence.

Specified by:

getIndexOfMaximalComponentFor in interface MotifDiscoverer

Parameters:

sequence - the given sequence

Returns:

the index of the component with the maximal score for the given sequence

Throws:

Exception - if the index could not be computed for any reasons

getMotifLength

public int getMotifLength(int motif)

Description copied from interface: MotifDiscoverer

This method returns the length of the motif with index motif .

Specified by:

getMotifLength in interface MotifDiscoverer

Parameters:

motif - the index of the motif

Returns:

the length of the motif with index motif

getNumberOfComponents

public int getNumberOfComponents()

Description copied from interface: MotifDiscoverer

Returns the number of components in this MotifDiscoverer.

Specified by:

getNumberOfComponents in interface MotifDiscoverer

Returns:

the number of components

getNumberOfMotifs

public int getNumberOfMotifs()

Description copied from interface: MotifDiscoverer

Returns the number of motifs for this MotifDiscoverer.

Specified by:

getNumberOfMotifs in interface MotifDiscoverer

Returns:

the number of motifs

getNumberOfMotifsInComponent

public int getNumberOfMotifsInComponent(int component)

Description copied from interface: MotifDiscoverer

Returns the number of motifs that are used in the component component of this MotifDiscoverer.

Specified by:

getNumberOfMotifsInComponent in interface MotifDiscoverer

Parameters:

component - the component of the MotifDiscoverer

Returns:

the number of motifs

getProfileOfScoresFor

public double[] getProfileOfScoresFor(int component,
                                      int motif,
                                      Sequence sequence,
                                      int startpos,
                                      MotifDiscoverer.KindOfProfile dist)
                               throws Exception

Description copied from interface: MotifDiscoverer

Returns the profile of the scores for component component and motif motif at all possible start positions of the motif in the sequence sequence beginning at startpos. This array should be of length
sequence.length() - startpos - motifs[motif].length() + 1.
A high score should encode for a probable start position.

Specified by:

getProfileOfScoresFor in interface MotifDiscoverer

Parameters:

component - the component index

motif - the index of the motif in the component

sequence - the given sequence

startpos - the start position in the sequence

dist - indicates the kind of profile

Returns:

the profile of scores

Throws:

Exception - if the score could not be computed for any reasons

getStrandFor

public StrandedLocatedSequenceAnnotationWithLength.Strand getStrandFor(int component,
                                                                       int motif,
                                                                       Sequence sequence,
                                                                       int startpos)
                                                                throws Exception

Description copied from interface: MotifDiscoverer

This method returns the strand for a given subsequence if it is considered as site of the motif model in a specific component.

Specified by:

getStrandFor in interface MotifDiscoverer

Parameters:

component - the component index

motif - the index of the motif in the component

sequence - the given sequence

startpos - the start position in the sequence

Returns:

the predicted strand annotation

Throws:

Exception - if the strand could not be computed for any reasons