Package 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:

  • Constructor Details

    • 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 Details

    • 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