Package | Description |
---|---|
org.biojava.bio.dp |
HMM and Dynamic Programming Algorithms.
|
org.biojava.bio.dp.onehead | |
org.biojava.bio.dp.twohead |
Modifier and Type | Class and Description |
---|---|
static class |
ScoreType.NullModel
In this class, calculateScore returns the probability of
a Symbol being emitted by the null model.
|
static class |
ScoreType.Odds
In this class, calculateScore returns the odds ratio
of a symbol being emitted.
|
static class |
ScoreType.Probability
In this class, calculateScore returns the probability
of a Symbol being emitted.
|
Modifier and Type | Field and Description |
---|---|
static ScoreType |
ScoreType.NULL_MODEL |
static ScoreType |
ScoreType.ODDS |
static ScoreType |
ScoreType.PROBABILITY |
Modifier and Type | Method and Description |
---|---|
abstract double |
DP.backward(SymbolList[] symList,
ScoreType scoreType) |
abstract DPMatrix |
DP.backwardMatrix(SymbolList[] symList,
DPMatrix matrix,
ScoreType scoreType) |
abstract DPMatrix |
DP.backwardMatrix(SymbolList[] symList,
ScoreType scoreType) |
static double[][] |
DP.backwardTransitionScores(MarkovModel model,
State[] states,
int[][] transitions,
ScoreType scoreType) |
abstract double |
DP.forward(SymbolList[] symList,
ScoreType scoreType) |
abstract DPMatrix |
DP.forwardMatrix(SymbolList[] symList,
DPMatrix matrix,
ScoreType scoreType) |
abstract DPMatrix |
DP.forwardMatrix(SymbolList[] symList,
ScoreType scoreType) |
DPMatrix |
DP.forwardsBackwards(SymbolList[] symList,
ScoreType scoreType) |
static double[][] |
DP.forwardTransitionScores(MarkovModel model,
State[] states,
int[][] transitions,
ScoreType scoreType)
Compute the log(score) of all transitions
between the specified States.
|
double[][] |
DP.getBackwardTransitionScores(ScoreType scoreType) |
double[][] |
DP.getForwardTransitionScores(ScoreType scoreType) |
static double |
DP.scoreWeightMatrix(WeightMatrix matrix,
SymbolList symList,
ScoreType scoreType,
int start)
Scores the SymbolList from symbol start to symbol (start+columns) with a
weight matrix using a particular ScoreType.
|
protected double |
BaumWelchSampler.singleSequenceIteration(ModelTrainer trainer,
SymbolList symList,
ScoreType scoreType) |
abstract StatePath |
DP.viterbi(SymbolList[] symList,
ScoreType scoreType) |
Constructor and Description |
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WeightMatrixAnnotator(WeightMatrix wm,
ScoreType scoreType,
double threshold)
Create a new annotator that uses a specific score type.
|
WeightMatrixAnnotator(WeightMatrix wm,
ScoreType scoreType,
double threshold,
String wmID)
Create a new annotator that uses the PROBABILITY score type and an ID
for the weight matrix.
|
Modifier and Type | Method and Description |
---|---|
protected void |
SingleDP.backward_initialize(DPCursor dpCursor,
ScoreType scoreType) |
protected void |
SingleDP.backward_recurse(DPCursor dpCursor,
ScoreType scoreType) |
protected double |
SingleDP.backward_termination(DPCursor dpCursor,
ScoreType scoreType) |
protected double |
SingleDP.backward(DPCursor dpCursor,
ScoreType scoreType) |
double |
SingleDP.backward(SymbolList[] seq,
ScoreType scoreType) |
DPMatrix |
SingleDP.backwardMatrix(SymbolList[] seq,
DPMatrix matrix,
ScoreType scoreType) |
DPMatrix |
SingleDP.backwardMatrix(SymbolList[] seq,
ScoreType scoreType) |
protected void |
SingleDP.forward_initialize(DPCursor dpCursor,
ScoreType scoreType) |
protected double |
SingleDP.forward(DPCursor dpCursor,
ScoreType scoreType) |
double |
SingleDP.forward(SymbolList[] seq,
ScoreType scoreType) |
DPMatrix |
SingleDP.forwardMatrix(SymbolList[] seq,
DPMatrix matrix,
ScoreType scoreType) |
DPMatrix |
SingleDP.forwardMatrix(SymbolList[] seq,
ScoreType scoreType) |
double[] |
SingleDP.getEmission(Symbol sym,
ScoreType scoreType)
This method is public for the benefit of training algorithms,
and in the future we should look at a better way of exposing
the emissions cache.
|
StatePath |
SingleDP.viterbi(SymbolList[] symList,
ScoreType scoreType) |
Modifier and Type | Method and Description |
---|---|
double |
PairwiseDP.backward(SymbolList[] seqs,
ScoreType scoreType) |
DPMatrix |
PairwiseDP.backwardMatrix(SymbolList[] seqs,
DPMatrix d,
ScoreType scoreType) |
DPMatrix |
PairwiseDP.backwardMatrix(SymbolList[] seqs,
ScoreType scoreType) |
CellCalculator |
DPInterpreter.backwards(ScoreType scoreType) |
CellCalculator |
CellCalculatorFactory.backwards(ScoreType scoreType) |
double |
PairwiseDP.forward(SymbolList[] seqs,
ScoreType scoreType) |
DPMatrix |
PairwiseDP.forwardMatrix(SymbolList[] seqs,
DPMatrix d,
ScoreType scoreType) |
DPMatrix |
PairwiseDP.forwardMatrix(SymbolList[] seqs,
ScoreType scoreType) |
CellCalculator |
DPInterpreter.forwards(ScoreType scoreType) |
CellCalculator |
CellCalculatorFactory.forwards(ScoreType scoreType) |
CellCalculator |
DPInterpreter.viterbi(ScoreType scoreType,
BackPointer terminal) |
CellCalculator |
CellCalculatorFactory.viterbi(ScoreType scoreType,
BackPointer terminal) |
StatePath |
PairwiseDP.viterbi(SymbolList[] seqs,
ScoreType scoreType) |
Constructor and Description |
---|
EmissionCache(Alphabet alpha,
State[] states,
int dsi,
ScoreType scoreType) |
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