de.jstacs.models.hmm.states
Class SimpleSamplingState

java.lang.Object
  de.jstacs.models.hmm.states.SimpleState
      de.jstacs.models.hmm.states.SimpleSamplingState

All Implemented Interfaces:

State, SamplingState, TrainableState, SamplingComponent, SamplingFromStatistic

public class SimpleSamplingState
extends SimpleState
implements SamplingState

This class implements a state that can be used for a HMM that obtains its parameters from sampling.

Author:

Jens Keilwagen

Field Summary

Fields inherited from class de.jstacs.models.hmm.states.SimpleState

e, forward, name

Constructor Summary

SimpleSamplingState(SamplingEmission e, String name, boolean forward)
This constructor creates a state that can be used in a HMM that obtains its parameters from sampling.

Method Summary

void	acceptParameters() This methods accepts the drawn parameters.
void	drawParametersFromStatistic() This method draws the parameters using a sufficient statistic representing a posteriori density.
void	extendSampling(int sampling, boolean append) This method allows to extend a sampling.
double	getLogGammaScoreForCurrentStatistic() This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics
double	getLogPosteriorFromStatistic() This method calculates the a-posteriori probability for the current statistics
void	initForSampling(int starts) This method initializes the instance for the sampling.
boolean	isInSamplingMode() This method returns true if the object is currently used in a sampling, otherwise false.
boolean	parseNextParameterSet() This method allows the user to parse the next set of parameters (from a file).
boolean	parseParameterSet(int sampling, int n) This method allows the user to parse the set of parameters with index n of a certain sampling (from a file).
void	samplingStopped() This method is the opposite of the method SamplingComponent.extendSampling(int, boolean).

Methods inherited from class de.jstacs.models.hmm.states.SimpleState

addToStatistic, getEmissionType, getGraphvizNodeOptions, getLogScoreFor, isSilent, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.jstacs.models.hmm.states.TrainableState

addToStatistic

Methods inherited from interface de.jstacs.models.hmm.State

getEmissionType, getGraphvizNodeOptions, getLogScoreFor, isSilent

Constructor Detail

SimpleSamplingState

public SimpleSamplingState(SamplingEmission e,
                           String name,
                           boolean forward)

This constructor creates a state that can be used in a HMM that obtains its parameters from sampling.

Parameters:

e - the emission

name - the name of the emission (e.g. for the Graphviz representation)

forward - a switch whether to use the forward or the reverse strand

Method Detail

drawParametersFromStatistic

public void drawParametersFromStatistic()
                                 throws Exception

Description copied from interface: SamplingFromStatistic

This method draws the parameters using a sufficient statistic representing a posteriori density. It is recommended to write the parameters to a specific file using SamplingComponent.acceptParameters() so that they can later be parsed using the methods of the interface.

Before using this method the method SamplingComponent.initForSampling(int) should be called.

Specified by:

drawParametersFromStatistic in interface SamplingFromStatistic

Throws:

Exception - if there is a problem with drawing the parameters, the initialization, ...

See Also:

SamplingComponent.initForSampling(int), SamplingComponent.acceptParameters()

extendSampling

public void extendSampling(int sampling,
                           boolean append)
                    throws IOException

Description copied from interface: SamplingComponent

This method allows to extend a sampling.

Specified by:

extendSampling in interface SamplingComponent

Parameters:

sampling - the index of the sampling

append - whether to append the sampled parameters to an existing file or to overwrite the file

Throws:

IOException - if the file could not be handled correctly

initForSampling

public void initForSampling(int starts)
                     throws IOException

Description copied from interface: SamplingComponent

This method initializes the instance for the sampling. For instance this method can be used to create new files where all parameter sets are stored.

Specified by:

initForSampling in interface SamplingComponent

Parameters:

starts - the number of different sampling starts that will be done

Throws:

IOException - if something went wrong

See Also:

File.createTempFile(String, String, java.io.File )

isInSamplingMode

public boolean isInSamplingMode()

Description copied from interface: SamplingComponent

This method returns true if the object is currently used in a sampling, otherwise false.

Specified by:

isInSamplingMode in interface SamplingComponent

Returns:

true if the object is currently used in a sampling, otherwise false

parseNextParameterSet

public boolean parseNextParameterSet()

Description copied from interface: SamplingComponent

This method allows the user to parse the next set of parameters (from a file).

Specified by:

parseNextParameterSet in interface SamplingComponent

Returns:

true if the parameters could be parsed, otherwise false

See Also:

SamplingComponent.parseParameterSet(int, int)

parseParameterSet

public boolean parseParameterSet(int sampling,
                                 int n)
                          throws Exception

Description copied from interface: SamplingComponent

This method allows the user to parse the set of parameters with index n of a certain sampling (from a file). The internal numbering should start with 0. The parameter set with index 0 is the initial (random) parameter set. It is recommended that a series of parameter sets is accessed by the following lines:

for( sampling = 0; sampling < numSampling; sampling++ )
{

boolean b = parseParameterSet( sampling, n );
while( b )
{
//do something
b = parseNextParameterSet();
} }


Specified by:

parseParameterSet in interface SamplingComponent

Parameters:

sampling - the index of the sampling

n - the index of the parameter set

Returns:

true if the parameter set could be parsed

Throws:

Exception - if there is a problem with parsing the parameters

See Also:

SamplingComponent.parseNextParameterSet()

samplingStopped

public void samplingStopped()
                     throws IOException

Description copied from interface: SamplingComponent

This method is the opposite of the method SamplingComponent.extendSampling(int, boolean). It can be used for closing any streams of writer, ...

Specified by:

samplingStopped in interface SamplingComponent

Throws:

IOException - if something went wrong

See Also:

SamplingComponent.extendSampling(int, boolean)

acceptParameters

public void acceptParameters()
                      throws IOException

Description copied from interface: SamplingComponent

This methods accepts the drawn parameters. Internally the drawn parameters should be saved (to a file).

Specified by:

acceptParameters in interface SamplingComponent

Throws:

IOException - if the file could not be handled correctly

getLogGammaScoreForCurrentStatistic

public double getLogGammaScoreForCurrentStatistic()

Description copied from interface: SamplingState

This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics

Specified by:

getLogGammaScoreForCurrentStatistic in interface SamplingState

Returns:

the logarithm of the gamma-score for the current statistics

getLogPosteriorFromStatistic

public double getLogPosteriorFromStatistic()

Description copied from interface: SamplingFromStatistic

This method calculates the a-posteriori probability for the current statistics

Specified by:

getLogPosteriorFromStatistic in interface SamplingFromStatistic

Returns:

the logarithm of the a-posteriori probability