Uses of Class
calhoun.analysis.crf.io.TrainingSequence

Packages that use TrainingSequence

calhoun.analysis.crf	the interface, main Conrad class, and solver for the Conrad engine.
calhoun.analysis.crf.executables.viewer	prototype of a viewing utility for examiining the results of inference.
calhoun.analysis.crf.features.generic	features useful across different models
calhoun.analysis.crf.features.interval13	mdoel definition and setup for the interval13 model
calhoun.analysis.crf.features.interval29
calhoun.analysis.crf.features.supporting	utility classes used by feature managers in gene calling models
calhoun.analysis.crf.features.supporting.phylogenetic	utility classes for phylogenetic analysis
calhoun.analysis.crf.features.tricycle13	basic features and model for the tricycle13 gene calling model
calhoun.analysis.crf.io	handles input and output of gene calling formats
calhoun.analysis.crf.scoring	local similarity functions used in gene calling models
calhoun.analysis.crf.solver	training and inference algorithms used in the CRF engine
calhoun.analysis.crf.solver.semimarkov
calhoun.analysis.crf.test

Uses of TrainingSequence in calhoun.analysis.crf

Methods in calhoun.analysis.crf with parameters of type TrainingSequence

double

LocalPathSimilarityScore.evaluate(int yprev, int y, TrainingSequence<?> seq, int pos) compute a real-valued score between a given path and the true path at a given position.

Method parameters in calhoun.analysis.crf with type arguments of type TrainingSequence

double[]	CRFTraining.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data) find the set of weights which maximizes the value of the objective function.
void	CRFObjectiveFunctionGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data) sets the training data that will be used for evaluation of the objective function.
void	Conrad.test(java.util.List<? extends TrainingSequence<?>> data)
void	Conrad.test(java.util.List<? extends TrainingSequence<?>> data, java.lang.String location) runs a trained model against a set of input data with known results and evaluates the performance.
void	FeatureManager.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends InputType>> data) Provides access to the entire training set so that FeatureManager can compute global properties and assign feature indices.
void	Conrad.train(java.util.List<? extends TrainingSequence<?>> data) fully trains this Conrad engine with this training data.
void	Conrad.trainFeatures(java.util.List<? extends TrainingSequence<?>> data) trains only the features in the current model with this training data.
void	Conrad.trainWeights(java.util.List<? extends TrainingSequence<?>> data) optimizes the feature weights for the current model with this training data.

Uses of TrainingSequence in calhoun.analysis.crf.executables.viewer

Constructors in calhoun.analysis.crf.executables.viewer with parameters of type TrainingSequence

ViterbiTableModel(Conrad crfModel, TrainingSequence seq)

Uses of TrainingSequence in calhoun.analysis.crf.features.generic

Method parameters in calhoun.analysis.crf.features.generic with type arguments of type TrainingSequence

void	WeightedStateChanges.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<?>> data)
void	WeightedEdges.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<?>> data)

Uses of TrainingSequence in calhoun.analysis.crf.features.interval13

Method parameters in calhoun.analysis.crf.features.interval13 with type arguments of type TrainingSequence

void	StateTransitionsInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	StateLengthLogprobInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ReferenceBasePredictorInterval13Base.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	PWMInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	GeneConstraintsInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ESTInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	BlastInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	PhylogeneticLogprobInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	GapFeaturesInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	FootprintsInterval13.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of TrainingSequence in calhoun.analysis.crf.features.interval29

Method parameters in calhoun.analysis.crf.features.interval29 with type arguments of type TrainingSequence

void	StateTransitionsInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	StateLengthLogprobInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ReferenceBasePredictorInterval29Base.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	PWMInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	GeneConstraintsInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	ESTInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	GapFeaturesInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	FootprintsInterval29.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of TrainingSequence in calhoun.analysis.crf.features.supporting

Method parameters in calhoun.analysis.crf.features.supporting with type arguments of type TrainingSequence

void	MarkovPredictorLogprob.train(java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)

Uses of TrainingSequence in calhoun.analysis.crf.features.supporting.phylogenetic

Method parameters in calhoun.analysis.crf.features.supporting.phylogenetic with type arguments of type TrainingSequence

void	ColumnConditionalLogProbability.train(ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of TrainingSequence in calhoun.analysis.crf.features.tricycle13

Method parameters in calhoun.analysis.crf.features.tricycle13 with type arguments of type TrainingSequence

void	PositionWeightMatrixFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	MaxentMotifFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	KmerFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data) Computes the P(label | kmer) for each kmer across all of the training data.
void	GeneConstraints.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data) Set up the matrix Depends on states starting with the words 'intergenic, intron, and exon'.
void	EmissionMarkovFeature.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	CodingStopFeature.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	PWM_evolution.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	PfamPhase.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	PfamGenic.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	ESTIntron.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	ESTExon.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	ESTEdge.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends CompositeInput>> data)
void	IntervalPresenceFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends IntervalInputSequence.IntervalPosition>> data)
void	GapConjunctionFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)
void	FelsensteinFeatures.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends MultipleAlignmentInputSequence.MultipleAlignmentColumn>> data)

Uses of TrainingSequence in calhoun.analysis.crf.io

Methods in calhoun.analysis.crf.io that return TrainingSequence

TrainingSequence	OutputHandlerGeneCallStats.getLabeled(int i)
TrainingSequence	OutputHandlerGeneCallPredict.getLabeled(int i)
TrainingSequence	TrainingSequence.getTrainingComponent(java.lang.String name) returns a new TrainingSequence created by taking a single component of the input sequence and pairing it with the hidden states for this Training Sequence.
TrainingSequence<A>	TrainingSequence.subSequence(int start, int end)

Methods in calhoun.analysis.crf.io that return types with arguments of type TrainingSequence

static java.util.List<? extends TrainingSequence<java.lang.Character>>	StringInput.prepareData(java.lang.String str) Convenience function for creating training sequences in test data.
static java.util.List<? extends TrainingSequence<?>>	IntInput.prepareData(java.lang.String str) Convenience function for creating training sequences in test data.
java.util.List<? extends TrainingSequence<?>>	InputHandlerInterleaved.readTrainingData(java.lang.String location)
java.util.List<? extends TrainingSequence<?>>	InputHandlerFile.readTrainingData(java.lang.String location)
java.util.List<? extends TrainingSequence<?>>	InputHandlerDirectory.readTrainingData(java.lang.String location)
java.util.List<? extends TrainingSequence<?>>	InputHandler.readTrainingData(java.lang.String location)
java.util.List<? extends TrainingSequence<?>>	CompositeInput.LegacyInputHandler.readTrainingData(java.lang.String location)
java.util.List<? extends TrainingSequence<?>>	InputHandlerInterleaved.readTrainingData(java.lang.String location, boolean predict)
java.util.List<? extends TrainingSequence<?>>	InputHandlerFile.readTrainingData(java.lang.String location, boolean predict)
java.util.List<? extends TrainingSequence<?>>	InputHandlerDirectory.readTrainingData(java.lang.String location, boolean predict)
java.util.List<? extends TrainingSequence<?>>	InputHandler.readTrainingData(java.lang.String location, boolean predict) returns the training data read from the specified location.
java.util.List<? extends TrainingSequence<?>>	CompositeInput.LegacyInputHandler.readTrainingData(java.lang.String inputLocation, boolean predict)

Methods in calhoun.analysis.crf.io with parameters of type TrainingSequence

void	OutputHandlerGeneCallStats.calcResultIncrement(TrainingSequence training, int[] predictedHiddenSequence) calculates statstics and output for results on a given test sequence
void	OutputHandlerGeneCallPredict.calcResultIncrement(TrainingSequence training, int[] predictedHiddenSequence) calculates statstics and output for results on a given test sequence
static void	SequenceConverter.convertSeqFrom13To39(TrainingSequence<java.lang.Character> seq)
static void	SequenceConverter.convertSeqFrom39To13(TrainingSequence<java.lang.Character> seq)
static void	SequenceConverter.convertSeqFromInterval13ToTricycle13(TrainingSequence<java.lang.Character> seq)
static void	SequenceConverter.convertSeqFromTricycle13ToInterval13(TrainingSequence<java.lang.Character> seq)
void	SequenceConverter.writeHiddenSequence39GFF(TrainingSequence<java.lang.Character> refStates, java.lang.String filename)
static void	SequenceConverter.writeHiddenSequenceGFF(TrainingSequence<java.lang.Character> refStates, java.lang.String filename)

Method parameters in calhoun.analysis.crf.io with type arguments of type TrainingSequence

void	TrainingSequenceIO.readTrainingSequences(java.lang.Object location, java.util.List<TrainingSequence<java.util.Map<java.lang.String,java.lang.Object>>> seqs) reads training sequences from the specified location.
void	IntInput.readTrainingSequences(java.lang.Object location, java.util.List<TrainingSequence<java.util.Map<java.lang.String,java.lang.Object>>> seqs)
void	GTFInputInterval29.readTrainingSequences(java.lang.Object location, java.util.List<TrainingSequence<java.util.Map<java.lang.String,java.lang.Object>>> seqs)
void	GTFInputInterval13.readTrainingSequences(java.lang.Object location, java.util.List<TrainingSequence<java.util.Map<java.lang.String,java.lang.Object>>> seqs)
void	AllIntergenicHiddenStateReader.readTrainingSequences(java.lang.Object location, java.util.List<TrainingSequence<java.util.Map<java.lang.String,java.lang.Object>>> seqs)
static java.util.ArrayList<java.util.ArrayList<java.lang.Integer>>	SequenceConverter.stateVector2StateLengths(java.util.List<? extends TrainingSequence<?>> data, int nStates)
void	OutputHandlerGeneCallStats.writeGTF(java.util.List<? extends TrainingSequence<?>> refStates, java.lang.String filename)
void	OutputHandlerGeneCallPredict.writeGTF(java.util.List<? extends TrainingSequence<?>> refStates, java.lang.String filename)
void	InputHandlerInterleaved.writeTrainingData(java.lang.String location, java.util.List<? extends TrainingSequence<?>> data)
void	InputHandlerFile.writeTrainingData(java.lang.String location, java.util.List<? extends TrainingSequence<?>> data)
void	InputHandlerDirectory.writeTrainingData(java.lang.String location, java.util.List<? extends TrainingSequence<?>> data)
void	InputHandler.writeTrainingData(java.lang.String location, java.util.List<? extends TrainingSequence<?>> data) writes training data to the specified location.

Constructor parameters in calhoun.analysis.crf.io with type arguments of type TrainingSequence

IteratorAdapterTrainingSequenceInput(java.util.Iterator<? extends TrainingSequence<T>> trainingIterator)
constructs a new iterator which will extract the input sequence from the training sequences

Uses of TrainingSequence in calhoun.analysis.crf.scoring

Methods in calhoun.analysis.crf.scoring with parameters of type TrainingSequence

double	SimScoreStateAndExonBoundariesInt13.evaluate(int yprev, int y, TrainingSequence<?> seq, int pos)
double	SimScoreMinExonBoundaryMiscallsSV13.evaluate(int yprev, int y, TrainingSequence<?> seq, int pos)
double	SimScoreMinCodingMiscallsSV13.evaluate(int yprev, int y, TrainingSequence<?> seq, int pos)
double	SimScoreMaxStateAgreement.evaluate(int yprev, int y, TrainingSequence<?> seq, int pos)

Uses of TrainingSequence in calhoun.analysis.crf.solver

Methods in calhoun.analysis.crf.solver that return types with arguments of type TrainingSequence

java.util.List<? extends TrainingSequence<?>>	CacheProcessorBasic.getData()
java.util.List<? extends TrainingSequence<?>>	CacheProcessor.getData()

Method parameters in calhoun.analysis.crf.solver with type arguments of type TrainingSequence

double[]	TwoPassOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	StandardOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	SimplexOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	SeededOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
double[]	FixedWeightOptimizer.optimize(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	NoCachingCacheProcessor.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	MaximumLikelihoodSemiMarkovGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	MaximumLikelihoodGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessorDeluxe.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessorBasic.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessor.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CacheProcessor.SolverSetup.setup(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data, boolean allPaths, short[] maxStateLengths2, boolean ignoreSemiMarkovSelfTransitions)

Uses of TrainingSequence in calhoun.analysis.crf.solver.semimarkov

Method parameters in calhoun.analysis.crf.solver.semimarkov with type arguments of type TrainingSequence

void	CleanMaximumLikelihoodSemiMarkovGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)
void	CleanLocalScoreSemiMarkovGradient.setTrainingData(ModelManager fm, java.util.List<? extends TrainingSequence<?>> data)

Uses of TrainingSequence in calhoun.analysis.crf.test

Method parameters in calhoun.analysis.crf.test with type arguments of type TrainingSequence

void	TestFeatures.TestFeature.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)
void	GeneConstraintsToy.train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data) Set up the matrix Depends on states starting with the words 'intergenic, intron, and exon'.