org.biojava3.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

public interface Scorer

Defines an algorithm which computes a score.

Author:
Mark Chapman

Method Summary
 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.
 int getMaxScore()
          Returns maximum possible score.
 int getMinScore()
          Returns minimum possible score.
 int 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 Detail

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

int getMaxScore()
Returns maximum possible score.

Returns:
maximum possible score

getMinScore

int getMinScore()
Returns minimum possible score.

Returns:
minimum possible score

getScore

int 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