Package org.biojava.nbio.alignment.template

Interface Scorer

All Known Subinterfaces:
Aligner<S,C>, MatrixAligner<S,C>, PairInProfileScorer<S,C>, PairwiseSequenceAligner<S,C>, PairwiseSequenceScorer<S,C>, PartitionRefiner<S,C>, ProfileProfileAligner<S,C>, ProfileProfileScorer<S,C>, RescoreRefiner<S,C>
All Known Implementing Classes:
AbstractMatrixAligner, AbstractPairwiseSequenceAligner, AbstractProfileProfileAligner, AbstractScorer, AnchoredPairwiseSequenceAligner, FractionalIdentityInProfileScorer, FractionalIdentityScorer, FractionalSimilarityInProfileScorer, FractionalSimilarityScorer, GuanUberbacher, NeedlemanWunsch, SimpleProfileProfileAligner, SmithWaterman, StandardRescoreRefiner, SubstitutionMatrixScorer
public interface Scorer
Defines an algorithm which computes a score.
Author:
Mark Chapman

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    getDistance()
    Returns score as a distance between 0.0 and 1.0.
    double
    getDistance(double scale)
    Returns score as a distance between 0.0 and scale.
    double
    getMaxScore()
    Returns maximum possible score.
    double
    getMinScore()
    Returns minimum possible score.
    double
    getScore()
    Returns score resulting from algorithm.
    double
    getSimilarity()
    Returns score as a similarity between 0.0 and 1.0.
    double
    getSimilarity(double scale)
    Returns score as a similarity between 0.0 and scale.

  • Method Details

    • getDistance

      double getDistance()
      Returns score as a distance between 0.0 and 1.0. This equals (getMaxScore() - getScore()) / (getMaxScore() - getMinScore()).
      Returns:
      score as a distance between 0.0 and 1.0

    • getDistance

      double getDistance(double scale)
      Returns score as a distance between 0.0 and scale. This equals scale * (getMaxScore() - getScore()) / (getMaxScore() - getMinScore()).
      Parameters:
      scale - maximum distance
      Returns:
      score as a distance between 0.0 and scale

    • getMaxScore

      double getMaxScore()
      Returns maximum possible score.
      Returns:
      maximum possible score

    • getMinScore

      double getMinScore()
      Returns minimum possible score.
      Returns:
      minimum possible score

    • getScore

      double getScore()
      Returns score resulting from algorithm. This should normalize between 0 and 1 by calculating (getScore() - getMinScore()) / (getMaxScore() - getMinScore()).
      Returns:
      score resulting from algorithm

    • getSimilarity

      double getSimilarity()
      Returns score as a similarity between 0.0 and 1.0. This equals (getScore() - getMinScore()) / (getMaxScore() - getMinScore()).
      Returns:
      score as a similarity between 0.0 and 1.0

    • getSimilarity

      double getSimilarity(double scale)
      Returns score as a similarity between 0.0 and scale. This equals scale * (getScore() - getMinScore()) / (getMaxScore() - getMinScore()).
      Parameters:
      scale - maximum similarity
      Returns:
      score as a similarity between 0.0 and scale