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

All Methods Instance Methods Abstract Methods
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 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
```
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

Interface Scorer

Method Summary

Method Detail

getDistance

getDistance

getMaxScore

getMinScore

getScore

getSimilarity

getSimilarity