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java.lang.Objectde.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
de.jstacs.scoringFunctions.IndependentProductScoringFunction
public class IndependentProductScoringFunction
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.
Nested Class Summary |
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Nested classes/interfaces inherited from interface de.jstacs.motifDiscovery.MotifDiscoverer |
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MotifDiscoverer.KindOfProfile |
Field Summary |
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Fields inherited from class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction |
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alphabets, length, r |
Fields inherited from interface de.jstacs.scoringFunctions.ScoringFunction |
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UNKNOWN |
Constructor Summary | |
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IndependentProductScoringFunction(NormalizableScoringFunction... functions)
This constructor creates an instance of an IndependentProductScoringFunction from a given series of
independent NormalizableScoringFunction s. |
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IndependentProductScoringFunction(NormalizableScoringFunction[] functions,
int[] length)
This constructor creates an instance of an IndependentProductScoringFunction from given series of
independent NormalizableScoringFunction s and lengths. |
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IndependentProductScoringFunction(StringBuffer source)
This is the constructor for the interface Storable . |
Method Summary | |
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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( |
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 + |
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 |
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getAlphabetContainer, getInitialClassParam, getLength, getLogScore, getLogScoreAndPartialDerivation, isNormalized, isNormalized |
Methods inherited from class java.lang.Object |
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equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public IndependentProductScoringFunction(NormalizableScoringFunction... functions) throws CloneNotSupportedException, IllegalArgumentException
IndependentProductScoringFunction
from a given series of
independent NormalizableScoringFunction
s. The length that is
modeled by each component is determined by
ScoringFunction.getLength()
. So the length should not be 0.
functions
- the components, i.e. the given series of independent
NormalizableScoringFunction
s
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)IndependentProductScoringFunction(NormalizableScoringFunction[],
int[])
public IndependentProductScoringFunction(NormalizableScoringFunction[] functions, int[] length) throws CloneNotSupportedException, IllegalArgumentException
IndependentProductScoringFunction
from given series of
independent NormalizableScoringFunction
s and lengths.
functions
- the components, i.e. the given series of independent
NormalizableScoringFunction
slength
- the lengths, one for each component
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)IndependentProductScoringFunction(NormalizableScoringFunction[],
int[])
public IndependentProductScoringFunction(StringBuffer source) throws NonParsableException
Storable
.
Creates a new IndependentProductScoringFunction
out of a
StringBuffer
as returned by toXML()
.
source
- the XML representation as StringBuffer
NonParsableException
- if the XML representation could not be parsedMethod Detail |
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public IndependentProductScoringFunction clone() throws CloneNotSupportedException
ScoringFunction
ScoringFunction
instance.
clone
in interface ScoringFunction
clone
in class AbstractNormalizableScoringFunction
ScoringFunction
CloneNotSupportedException
- if something went wrong while cloning the
ScoringFunction
public int getSizeOfEventSpaceForRandomVariablesOfParameter(int index)
NormalizableScoringFunction
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, ...
getSizeOfEventSpaceForRandomVariablesOfParameter
in interface NormalizableScoringFunction
index
- the index of the parameter
public double getNormalizationConstant()
NormalizableScoringFunction
getNormalizationConstant
in interface NormalizableScoringFunction
public double getPartialNormalizationConstant(int parameterIndex) throws Exception
NormalizableScoringFunction
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}}
.
getPartialNormalizationConstant
in interface NormalizableScoringFunction
parameterIndex
- the index of the parameter
Exception
- if something went wrong with the normalizationNormalizableScoringFunction.getNormalizationConstant()
public double getEss()
NormalizableScoringFunction
getEss
in interface NormalizableScoringFunction
public void initializeFunction(int index, boolean freeParams, Sample[] data, double[][] weights) throws Exception
ScoringFunction
ScoringFunction
.
initializeFunction
in interface ScoringFunction
index
- the index of the class the ScoringFunction
modelsfreeParams
- indicates whether the (reduced) parameterization is useddata
- the samplesweights
- the weights of the sequences in the samples
Exception
- if something went wrongprotected void fromXML(StringBuffer rep) throws NonParsableException
AbstractNormalizableScoringFunction
Storable
interface to create a scoring function from a StringBuffer
.
fromXML
in class AbstractNormalizableScoringFunction
rep
- the XML representation as StringBuffer
NonParsableException
- if the StringBuffer
could not be parsedAbstractNormalizableScoringFunction.AbstractNormalizableScoringFunction(StringBuffer)
public String getInstanceName()
ScoringFunction
getInstanceName
in interface ScoringFunction
public double[] getCurrentParameterValues() throws Exception
ScoringFunction
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.
getCurrentParameterValues
in interface ScoringFunction
Exception
- if no parameters exist (yet)public double getLogScore(Sequence seq, int start)
ScoringFunction
Sequence
seq
beginning at position start
in the Sequence
.
getLogScore
in interface ScoringFunction
seq
- the Sequence
start
- the start position in the Sequence
Sequence
public double getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList partialDer)
ScoringFunction
Sequence
beginning at
position start
in the Sequence
and fills lists with
the indices and the partial derivations.
getLogScoreAndPartialDerivation
in interface ScoringFunction
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 zeropartialDer
- a DoubleList
of partial derivations, after method
invocation the list should contain the corresponding
\frac{\partial \log
score(seq)}{\partial \lambda_i}
Sequence
public int getNumberOfParameters()
ScoringFunction
ScoringFunction
. If the
number of parameters is not known yet, the method returns
ScoringFunction.UNKNOWN
.
getNumberOfParameters
in interface ScoringFunction
ScoringFunction
ScoringFunction.UNKNOWN
public int getNumberOfRecommendedStarts()
ScoringFunction
getNumberOfRecommendedStarts
in interface ScoringFunction
getNumberOfRecommendedStarts
in class AbstractNormalizableScoringFunction
public void setParameters(double[] params, int start)
ScoringFunction
params
between start
and
start + ScoringFunction.getNumberOfParameters()
- 1
setParameters
in interface ScoringFunction
params
- the new parametersstart
- the start index in params
public StringBuffer toXML()
Storable
StringBuffer
of an
instance of the implementing class.
toXML
in interface Storable
public String toString()
toString
in class Object
public double getLogPriorTerm()
NormalizableScoringFunction
NormalizableScoringFunction.getEss()
* Math.log(
NormalizableScoringFunction.getNormalizationConstant()
) + Math.log( prior ).
prior
is the prior for the parameters of this model.
getLogPriorTerm
in interface NormalizableScoringFunction
NormalizableScoringFunction.getEss()
* Math.log( NormalizableScoringFunction.getNormalizationConstant()
) + Math.log( prior ).
NormalizableScoringFunction.getEss()
,
NormalizableScoringFunction.getNormalizationConstant()
public void addGradientOfLogPriorTerm(double[] grad, int start) throws Exception
NormalizableScoringFunction
NormalizableScoringFunction.getLogPriorTerm()
for each
parameter of this model. The results are added to the array
grad
beginning at index start
.
addGradientOfLogPriorTerm
in interface NormalizableScoringFunction
grad
- the array of gradientsstart
- the start index in the grad
array, where the
partial derivations for the parameters of this models shall be
entered
Exception
- if something went wrong with the computing of the gradientsNormalizableScoringFunction.getLogPriorTerm()
public boolean isInitialized()
ScoringFunction
ScoringFunction.initializeFunction(int, boolean, Sample[], double[][])
.
isInitialized
in interface ScoringFunction
true
if the model is initialized, false
otherwisepublic void initializeFunctionRandomly(boolean freeParams) throws Exception
ScoringFunction
ScoringFunction
randomly. It has to
create the underlying structure of the ScoringFunction
.
initializeFunctionRandomly
in interface ScoringFunction
freeParams
- indicates whether the (reduced) parameterization is used
Exception
- if something went wrongpublic void initializeMotif(int motifIndex, Sample data, double[] weights) throws Exception
MutableMotifDiscoverer
initializeMotif
in interface MutableMotifDiscoverer
motifIndex
- the index of the motif in the motif discovererdata
- the sample of sequencesweights
- either null
or an array of length data.getNumberofElements()
with non-negative weights.
Exception
- if initialize was not possiblepublic boolean modifyMotif(int motifIndex, double[] weightsLeft, double[] weightsRight, double[][][][] replacementLeft, double[][][][] replacementRight, int offsetLeft, int offsetRight) throws Exception
MutableMotifDiscoverer
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.
modifyMotif
in interface MutableMotifDiscoverer
motifIndex
- the index of the motif in the motif discovererweightsLeft
- the weights for the left contrast distributionsweightsRight
- the weights for the right contrast distributionsreplacementLeft
- the replacement distribution for the left sidereplacementRight
- the replacement distribution for the right sideoffsetLeft
- the offset on the left sideoffsetRight
- the offset on the right side
true
if the motif model was modified otherwise false
Exception
public boolean modifyMotif(int motifIndex, int offsetLeft, int offsetRight) throws Exception
MutableMotifDiscoverer
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.
modifyMotif
in interface MutableMotifDiscoverer
motifIndex
- the index of the motif in the motif discovereroffsetLeft
- the offset on the left sideoffsetRight
- the offset on the right side
true
if the motif model was modified otherwise false
Exception
MutableMotifDiscoverer.modifyMotif(int, double[], double[], double[][][][], double[][][][], int, int)
public int[] determineNotSignificantPositionsFor(int motif, Sample[] data, double[][] weights, int classIdx)
MutableMotifDiscoverer
motif
.
determineNotSignificantPositionsFor
in interface MutableMotifDiscoverer
motif
- the index of the motif in the motif discovererdata
- an array Sample
s, each array-entry represents on classweights
- the weights of each Sequence
for each classclassIdx
- the index of the current class in classCounts
Mutable.determineNotSignificantPositions(double, double[], double[], double[][][][], double[][][][], double)
,
MutableMotifDiscoverer.modifyMotif(int, int, int)
,
MutableMotifDiscoverer.modifyMotif(int, double[], double[], double[][][][], double[][][][], int, int)
public int getGlobalIndexOfMotifInComponent(int component, int motif)
MotifDiscoverer
motif
used in
component
. The index returned must be at least 0 and less
than MotifDiscoverer.getNumberOfMotifs()
.
getGlobalIndexOfMotifInComponent
in interface MotifDiscoverer
component
- the component indexmotif
- the motif index in the component
motif in component
public int getIndexOfMaximalComponentFor(Sequence sequence) throws Exception
MotifDiscoverer
sequence
.
getIndexOfMaximalComponentFor
in interface MotifDiscoverer
sequence
- the given sequence
Exception
- if the index could not be computed for any reasonspublic int getMotifLength(int motif)
MotifDiscoverer
motif
.
getMotifLength
in interface MotifDiscoverer
motif
- the index of the motif
motif
public int getNumberOfComponents()
MotifDiscoverer
MotifDiscoverer
.
getNumberOfComponents
in interface MotifDiscoverer
public int getNumberOfMotifs()
MotifDiscoverer
MotifDiscoverer
.
getNumberOfMotifs
in interface MotifDiscoverer
public int getNumberOfMotifsInComponent(int component)
MotifDiscoverer
component
of this MotifDiscoverer
.
getNumberOfMotifsInComponent
in interface MotifDiscoverer
component
- the component of the MotifDiscoverer
public double[] getProfileOfScoresFor(int component, int motif, Sequence sequence, int startpos, MotifDiscoverer.KindOfProfile dist) throws Exception
MotifDiscoverer
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
.
getProfileOfScoresFor
in interface MotifDiscoverer
component
- the component indexmotif
- the index of the motif in the componentsequence
- the given sequencestartpos
- the start position in the sequencedist
- indicates the kind of profile
Exception
- if the score could not be computed for any reasonspublic StrandedLocatedSequenceAnnotationWithLength.Strand getStrandFor(int component, int motif, Sequence sequence, int startpos) throws Exception
MotifDiscoverer
getStrandFor
in interface MotifDiscoverer
component
- the component indexmotif
- the index of the motif in the componentsequence
- the given sequencestartpos
- the start position in the sequence
Exception
- if the strand could not be computed for any reasons
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