org.biojava.bio.dist

Class PairDistribution

java.lang.Object

org.biojava.utils.AbstractChangeable

org.biojava.bio.dist.PairDistribution

All Implemented Interfaces:

Serializable, Distribution, Changeable

public class PairDistribution
extends AbstractChangeable
implements Serializable, Distribution

Class for pairing up two independant distributions.

Since:

1.1

Author:

Matthew Pocock, Thomas Down, Samiul Hasan

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.biojava.bio.dist.Distribution

Distribution.NullModelForwarder

Field Summary

Fields inherited from interface org.biojava.bio.dist.Distribution

NULL_MODEL, WEIGHTS

Constructor Summary

Constructors

Constructor and Description
PairDistribution(Distribution first, Distribution second) Create a new PairDistribution that represents the product of two other distributions.

Method Summary

Modifier and Type	Method and Description
Alphabet	getAlphabet() The alphabet from which this spectrum emits symbols.
Distribution	getNullModel() Retrieve the null model Distribution that this Distribution recognizes.
protected static Distribution	getNullModel(Distribution first, Distribution second) Get a uniform null model over a PairDistribution over [first,second].
double	getWeight(Symbol sym) Return the probability that Symbol s is emitted by this spectrum.
void	registerWithTrainer(DistributionTrainerContext dtc) Register this distribution with a training context.
void	registerWithTrainer(ModelTrainer trainer) Register this paired distribution with a model trainer.
Symbol	sampleSymbol() Sample a symbol from this state's probability distribution.
void	setNullModel(Distribution nullModel) Set the null model Distribution that this Distribution recognizes.
void	setWeight(Symbol sym, double weight) Set the probability or odds that Symbol s is emitted by this state.

Methods inherited from class org.biojava.utils.AbstractChangeable

addChangeListener, addChangeListener, generateChangeSupport, getChangeSupport, hasListeners, hasListeners, isUnchanging, removeChangeListener, removeChangeListener

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.biojava.utils.Changeable

addChangeListener, addChangeListener, isUnchanging, removeChangeListener, removeChangeListener

Constructor Detail

PairDistribution

public PairDistribution(Distribution first,
                        Distribution second)

Create a new PairDistribution that represents the product of two other distributions. The alphabet will be the product of the first and seccond distribution's alphabets, and the weights will be the products of the weights for the first and seccond distributions given the first and second component of the symbol respectively.

Parameters:

first - the first distribution

second - the second distribution

Method Detail

getNullModel

protected static Distribution getNullModel(Distribution first,
                                           Distribution second)

Get a uniform null model over a PairDistribution over [first,second].

Parameters:

first - the first Alphabet

second - the second Alphabet

Returns:

a Distribution that is a uniform distribution over the product of first and second

getAlphabet

public Alphabet getAlphabet()

Description copied from interface: Distribution

The alphabet from which this spectrum emits symbols.

Specified by:

getAlphabet in interface Distribution

Returns:

the Alphabet associated with this spectrum

getNullModel

public Distribution getNullModel()

Description copied from interface: Distribution

Retrieve the null model Distribution that this Distribution recognizes.

Specified by:

getNullModel in interface Distribution

Returns:

the apropriate null model

setNullModel

public void setNullModel(Distribution nullModel)
                  throws IllegalAlphabetException,
                         ChangeVetoException

Description copied from interface: Distribution

Set the null model Distribution that this Distribution recognizes.

Specified by:

setNullModel in interface Distribution

Parameters:

nullModel - the new null model Distribution

Throws:

IllegalAlphabetException - if the null model has the wrong alphabet

ChangeVetoException - if this Distirbution doesn't support setting the null model, or if one of its listeners objects

registerWithTrainer

public void registerWithTrainer(ModelTrainer trainer)

Register this paired distribution with a model trainer.

Parameters:

trainer - the trainer to register this distribution with.

getWeight

public double getWeight(Symbol sym)
                 throws IllegalSymbolException

Description copied from interface: Distribution

Return the probability that Symbol s is emitted by this spectrum.

If the symbol is ambiguou, then it is the sum of the probability that each one of the matching symbols was emitted.

Specified by:

getWeight in interface Distribution

Parameters:

sym - the Symbol emitted

Returns:

the probability of emitting that symbol

Throws:

IllegalSymbolException - if s is not from this state's alphabet

setWeight

public void setWeight(Symbol sym,
                      double weight)
               throws ChangeVetoException

Description copied from interface: Distribution

Set the probability or odds that Symbol s is emitted by this state.

Specified by:

setWeight in interface Distribution

Parameters:

sym - the Symbol emitted

weight - the probability of emitting that symbol

Throws:

ChangeVetoException - if this state does not allow weights to be tampered with, or if one of the listeners vetoed this change

registerWithTrainer

public void registerWithTrainer(DistributionTrainerContext dtc)

Description copied from interface: Distribution

Register this distribution with a training context.

This should be invoked from within dtc.addDistribution(). This method is responsible for constructing a suitable DistributionTrainer instance and registering it by calling dtc.registerDistributionTrainer(this, trainer). If the distribution is a view onto another distribution, it can force the other to be registered by calling dtc.addDistribution(other), and can then get on with registering it's own trainer.

Specified by:

registerWithTrainer in interface Distribution

Parameters:

dtc - the DistributionTrainerContext with witch to register a trainer

sampleSymbol

public Symbol sampleSymbol()

Description copied from interface: Distribution

Sample a symbol from this state's probability distribution.

Specified by:

sampleSymbol in interface Distribution

Returns:

the symbol sampled