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java.lang.Objectde.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
public class MultivariateGaussianEmission
Multivariate Gaussian emission density for a Hidden Markov Model.
Field Summary | |
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protected HashMap<Sequence,double[]> |
gammas
Contains the emission sequences and corresponding gammas (state-posteriors) required for the estimation of the standard deviation. |
Constructor Summary | |
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MultivariateGaussianEmission(double[] mean,
double[] sds,
double[][] correlation,
double scaleMean,
double[] aprioriMean,
double shapeSd,
double[][] scaleSd)
Creates a Multivariate Gaussian emission density. |
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MultivariateGaussianEmission(StringBuffer xml)
Creates a MultivariateGaussianEmission from its XML representation. |
Method Summary | |
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void |
addToStatistic(boolean forward,
int startPos,
int endPos,
double weight,
Sequence seq)
This method adds the weight to the internal sufficient statistic. |
MultivariateGaussianEmission |
clone()
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void |
estimateFromStatistic()
This method estimates the parameters from the internal sufficient statistic. |
protected void |
fromXML(StringBuffer xml)
|
AlphabetContainer |
getAlphabetContainer()
This method returns the AlphabetContainer of this emission. |
double |
getLogPriorTerm()
Returns a value that is proportional to the log of the prior. |
double |
getLogProbFor(boolean forward,
int startPos,
int endPos,
Sequence seq)
This method computes the logarithm of the likelihood. |
String |
getNodeLabel(double weight,
String name,
NumberFormat nf)
Returns the graphviz label of the node containing this emission. |
String |
getNodeShape(boolean forward)
Returns the graphviz string for the shape of the node. |
void |
initializeFunctionRandomly()
This method initializes the emission randomly. |
void |
joinStatistics(Emission... emissions)
This method joins the statistics of different instances and sets this joined statistic as statistic of each instance. |
void |
resetStatistic()
This method resets the internal sufficient statistic. |
void |
setParameters(Emission t)
Set values of parameters of the instance to the value of the parameters of the given instance. |
String |
toString(NumberFormat nf)
This method returns a String representation of the instance. |
StringBuffer |
toXML()
This method returns an XML representation as StringBuffer of an
instance of the implementing class. |
Methods inherited from class java.lang.Object |
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equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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protected HashMap<Sequence,double[]> gammas
Constructor Detail |
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public MultivariateGaussianEmission(double[] mean, double[] sds, double[][] correlation, double scaleMean, double[] aprioriMean, double shapeSd, double[][] scaleSd)
mean
- mean vectorsds
- standard deviation vectorcorrelation
- correlation matrixscaleMean
- scale of a priori meanaprioriMean
- a priori meanshapeSd
- scale for scaleSd (a covariance matrix)scaleSd
- a priori covariance matrixpublic MultivariateGaussianEmission(StringBuffer xml) throws NonParsableException
MultivariateGaussianEmission
from its XML representation.
xml
- the XML representation.
NonParsableException
- if the XML representation could not be parsedMethod Detail |
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public void addToStatistic(boolean forward, int startPos, int endPos, double weight, Sequence seq) throws OperationNotSupportedException
Emission
weight
to the internal sufficient statistic.
addToStatistic
in interface Emission
forward
- whether to use the forward or the reverse strandstartPos
- the start positionendPos
- the end positionweight
- the weight of the sequenceseq
- the sequence
OperationNotSupportedException
- if forward=false
and the reverse complement of the sequence seq
is not definedpublic void joinStatistics(Emission... emissions)
Emission
joinStatistics
in interface Emission
emissions
- the emissions to be joinedpublic void estimateFromStatistic()
Emission
estimateFromStatistic
in interface Emission
public AlphabetContainer getAlphabetContainer()
Emission
AlphabetContainer
of this emission.
getAlphabetContainer
in interface Emission
AlphabetContainer
of this emissionpublic double getLogPriorTerm()
Emission
getLogPriorTerm
in interface Emission
StatisticalModel.getLogPriorTerm()
public double getLogProbFor(boolean forward, int startPos, int endPos, Sequence seq) throws OperationNotSupportedException
Emission
getLogProbFor
in interface Emission
forward
- whether to use the forward or the reverse strandstartPos
- the start positionendPos
- the end positionseq
- the sequence
OperationNotSupportedException
- if forward=false
and the reverse complement of the sequence seq
is not definedpublic String getNodeLabel(double weight, String name, NumberFormat nf)
Emission
getNodeLabel
in interface Emission
weight
- the weight of the node which is represented by
the color of the node, or -1 for no representation, i.e.,
white backgroundname
- the name of the state using this emissionnf
- the NumberFormat
for formatting the textual representation of this emission
public String getNodeShape(boolean forward)
Emission
getNodeShape
in interface Emission
forward
- if this emission is used on the forward strand
public void initializeFunctionRandomly()
Emission
initializeFunctionRandomly
in interface Emission
public void resetStatistic()
Emission
resetStatistic
in interface Emission
public StringBuffer toXML()
Storable
StringBuffer
of an
instance of the implementing class.
toXML
in interface Storable
protected void fromXML(StringBuffer xml) throws NonParsableException
NonParsableException
public String toString(NumberFormat nf)
Emission
String
representation of the instance.
toString
in interface Emission
nf
- the NumberFormat
for the String
representation of parameters or probabilities
String
representation of the instancepublic MultivariateGaussianEmission clone() throws CloneNotSupportedException
clone
in class Object
CloneNotSupportedException
public void setParameters(Emission t) throws IllegalArgumentException
Emission
setParameters
in interface Emission
t
- the emission with the parameters to be set
IllegalArgumentException
- if the assumption about the same class for given and current instance is wrong
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