de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

Class InhomogeneousDGTrainSM

java.lang.Object

de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhomogeneousDGTrainSM

All Implemented Interfaces:

InstantiableFromParameterSet, SequenceScore, StatisticalModel, TrainableStatisticalModel, Storable, Cloneable

Direct Known Subclasses:

DAGTrainSM, MEManager

public abstract class InhomogeneousDGTrainSM
extends DiscreteGraphicalTrainSM

This class is the main class for all inhomogeneous discrete graphical models (InhomogeneousDGTrainSM).

Author:

Jens Keilwagen

See Also:

IDGTrainSMParameterSet

Field Summary

Fields

Modifier and Type	Field and Description
protected static OutputStream	DEFAULT_STREAM The default OutputStream.
protected SafeOutputStream	sostream This stream is used for comments, computation steps/results or any other kind of output during the training, ...

Fields inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

params, trained

Fields inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

alphabets, length

Constructor Summary

Constructors

Constructor and Description
InhomogeneousDGTrainSM(IDGTrainSMParameterSet params) Creates a new InhomogeneousDGTrainSM from a given IDGTrainSMParameterSet.
InhomogeneousDGTrainSM(StringBuffer representation) The standard constructor for the interface Storable.

Method Summary

Methods

Modifier and Type	Method and Description
protected void	check(Sequence sequence, int startpos, int endpos) Checks some conditions on a Sequence.
InhomogeneousDGTrainSM	clone() Follows the conventions of Object's clone()-method.
abstract String	getStructure() Returns a String representation of the underlying graph.
protected void	set(DGTrainSMParameterSet parameter, boolean trained) Sets the parameters as internal parameters and does some essential computations.
void	setOutputStream(OutputStream stream) Sets the OutputStream for the model.

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

fromXML, getCurrentParameterSet, getDescription, getESS, getFurtherModelInfos, getXMLTag, isInitialized, setFurtherModelInfos, toString, toXML

Methods inherited from class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

emitDataSet, getAlphabetContainer, getCharacteristics, getLength, getLogProbFor, getLogProbFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getLogScoreFor, getMaximalMarkovOrder, toString, train

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModel

train

Methods inherited from interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel

getLogPriorTerm, getLogProbFor

Methods inherited from interface de.jstacs.sequenceScores.SequenceScore

getInstanceName, getNumericalCharacteristics

Field Detail

sostream

protected SafeOutputStream sostream

This stream is used for comments, computation steps/results or any other kind of output during the training, ... etc.

DEFAULT_STREAM

protected static final OutputStream DEFAULT_STREAM

The default OutputStream.

Constructor Detail

InhomogeneousDGTrainSM

public InhomogeneousDGTrainSM(IDGTrainSMParameterSet params)
                       throws CloneNotSupportedException,
                              IllegalArgumentException,
                              NonParsableException

Creates a new InhomogeneousDGTrainSM from a given IDGTrainSMParameterSet.

Parameters:

params - the given parameter set

Throws:

CloneNotSupportedException - if the parameter set could not be cloned

IllegalArgumentException - if the parameter set is not instantiated

NonParsableException - if the parameter set is not parsable

See Also:

DiscreteGraphicalTrainSM.DiscreteGraphicalTrainSM(DGTrainSMParameterSet)

InhomogeneousDGTrainSM

public InhomogeneousDGTrainSM(StringBuffer representation)
                       throws NonParsableException

The standard constructor for the interface Storable. Creates a new InhomogeneousDGTrainSM out of its XML representation.

Parameters:

representation - the XML representation as StringBuffer

Throws:

NonParsableException - if the InhomogeneousDGTrainSM could not be reconstructed out of the XML representation (the StringBuffer could not be parsed)

See Also:

Storable, DiscreteGraphicalTrainSM.DiscreteGraphicalTrainSM(StringBuffer)

Method Detail

clone

public InhomogeneousDGTrainSM clone()
                             throws CloneNotSupportedException

Description copied from class: AbstractTrainableStatisticalModel

Follows the conventions of Object's clone()-method.

Specified by:

clone in interface SequenceScore

Specified by:

clone in interface TrainableStatisticalModel

Overrides:

clone in class DiscreteGraphicalTrainSM

Returns:

an object, that is a copy of the current AbstractTrainableStatisticalModel (the member-AlphabetContainer isn't deeply cloned since it is assumed to be immutable). The type of the returned object is defined by the class X directly inherited from AbstractTrainableStatisticalModel. Hence X's clone()-method should work as:
1. Object o = (X)super.clone();
2. all additional member variables of o defined by X that are not of simple data-types like int, double, ... have to be deeply copied
3. return o

Throws:

CloneNotSupportedException - if something went wrong while cloning

getStructure

public abstract String getStructure()
                             throws NotTrainedException

Returns a String representation of the underlying graph.

Returns:

a String representation of the underlying graph

Throws:

NotTrainedException - if the structure is not set, this can only be the case if the model is not trained

setOutputStream

public void setOutputStream(OutputStream stream)

Sets the OutputStream for the model. This stream will sometimes be used to write some information about the training/progress/computation... etc. to the screen, a file ... etc.

Parameters:

stream - the OutputStream

See Also:

SafeOutputStream

check

protected void check(Sequence sequence,
         int startpos,
         int endpos)
              throws NotTrainedException,
                     IllegalArgumentException

Description copied from class: DiscreteGraphicalTrainSM

Checks some conditions on a Sequence. These are in general conditions on the AlphabetContainer of a (sub) Sequence between startpos und endpos.

Overrides:

check in class DiscreteGraphicalTrainSM

Parameters:

sequence - the Sequence

startpos - the startposition

endpos - the endposition

Throws:

NotTrainedException - if the model is not trained

IllegalArgumentException - if some constraints are not fulfilled

set

protected void set(DGTrainSMParameterSet parameter,
       boolean trained)
            throws CloneNotSupportedException,
                   NonParsableException

Description copied from class: DiscreteGraphicalTrainSM

Sets the parameters as internal parameters and does some essential computations. Used in fromParameterSet-methods.

Overrides:

set in class DiscreteGraphicalTrainSM

Parameters:

parameter - the new ParameterSet

trained - indicates if the model is trained or not

Throws:

CloneNotSupportedException - if the parameter set could not be cloned

NonParsableException - if the parameters of the model could not be parsed