org.biojava.bio.dist

Interface Distribution

All Superinterfaces:

Changeable

All Known Subinterfaces:

OrderNDistribution

All Known Implementing Classes:

AbstractDistribution, AbstractOrderNDistribution, GapDistribution, PairDistribution, SimpleDistribution, TranslatedDistribution, UniformDistribution, UntrainableDistribution

public interface Distribution
extends Changeable

An encapsulation of a probability distribution over the Symbols within an alphabet.

A distribution can be implemented as a map from symbol to probability. It is more correct to think of them as being integrals or sums over probability dencity funcitons. In this world view, getWeight should look at the getMatches of the symbol it is given and then perform the apropreate sum or integral to return the probability of something within that set of symbols being emitted.

This interface should handle the case of emitting an ambiguity symbol. This should be just the sum of the probabiltiy of emitting each matching symbol. It is up to the code using the Distribution instance to divide out the null model appropreately.

Since:

1.0

Author:

Matthew Pocock

Nested Class Summary

Nested Classes

Modifier and Type	Interface and Description
static class	Distribution.NullModelForwarder Deprecated. use new ChangeForwarder.Retyper(this, cs, Annotation.PROPERTY) instead

Field Summary

Fields

Modifier and Type	Field and Description
static ChangeType	NULL_MODEL Whenever the null model distribution changes the values that would be returned by getWeight, either by being edited or by being replaced, a ChangeEvent with this object as the type should be thrown.
static ChangeType	WEIGHTS Whenever a distribution changes the values that would be returned by getWeight, they should fire a ChangeEvent with this object as the type.

Method Summary

Methods

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.
double	getWeight(Symbol s) Return the probability that Symbol s is emitted by this spectrum.
void	registerWithTrainer(DistributionTrainerContext dtc) Register this distribution with a training context.
Symbol	sampleSymbol() Sample a symbol from this state's probability distribution.
void	setNullModel(Distribution nullDist) Set the null model Distribution that this Distribution recognizes.
void	setWeight(Symbol s, double w) Set the probability or odds that Symbol s is emitted by this state.

Methods inherited from interface org.biojava.utils.Changeable

addChangeListener, addChangeListener, isUnchanging, removeChangeListener, removeChangeListener

Field Detail

WEIGHTS

static final ChangeType WEIGHTS

Whenever a distribution changes the values that would be returned by getWeight, they should fire a ChangeEvent with this object as the type.

If the whole distribution changes, then the change and previous fields of the ChangeEvent should be left null. If only a single weight is modified, then change should be of the form Object[] { symbol, new Double(newVal) } and previous should be of the form Object[] { symbol, new Double(oldVal) }

NULL_MODEL

static final ChangeType NULL_MODEL

Whenever the null model distribution changes the values that would be returned by getWeight, either by being edited or by being replaced, a ChangeEvent with this object as the type should be thrown.

If the null model has changed its weights, then the ChangeEvent should refer back to the ChangeEvent from the null model.

Method Detail

getAlphabet

Alphabet getAlphabet()

The alphabet from which this spectrum emits symbols.

Returns:

the Alphabet associated with this spectrum

getWeight

double getWeight(Symbol s)
                 throws IllegalSymbolException

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.

Parameters:

s - the Symbol emitted

Returns:

the probability of emitting that symbol

Throws:

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

setWeight

void setWeight(Symbol s,
             double w)
               throws IllegalSymbolException,
                      ChangeVetoException

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

Parameters:

s - the Symbol emitted

w - the probability of emitting that symbol

Throws:

IllegalSymbolException - if s is not from this state's alphabet, or if it is an ambiguity symbol and the implementation can't handle this case

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

sampleSymbol

Symbol sampleSymbol()

Sample a symbol from this state's probability distribution.

Returns:

the symbol sampled

getNullModel

Distribution getNullModel()

Retrieve the null model Distribution that this Distribution recognizes.

Returns:

the apropriate null model

setNullModel

void setNullModel(Distribution nullDist)
                  throws IllegalAlphabetException,
                         ChangeVetoException

Set the null model Distribution that this Distribution recognizes.

Parameters:

nullDist - 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

void registerWithTrainer(DistributionTrainerContext dtc)

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.

Parameters:

dtc - the DistributionTrainerContext with witch to register a trainer