G-Index

A B C D E F G H I J K L M N O P Q R S T U V W X Z

G

Galaxy - Class in de.jstacs.tools.ui.galaxy

Class for generating a generic Galaxy interface for a set of JstacsTools.

Galaxy(String, boolean, JstacsTool...) - Constructor for class de.jstacs.tools.ui.galaxy.Galaxy

Creates a new Galaxy interface from a set of JstacsTools.

GalaxyAdaptor - Class in de.jstacs.tools.ui.galaxy

Adaptor class between the parameter representation of Jstacs in Parameters and ParameterSets and the parameter representation in Galaxy.

GalaxyAdaptor(ParameterSet, JstacsTool.ResultEntry[], boolean[], String, String, String, String, String) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Creates a new GalaxyAdaptor from a given ParameterSet containing all parameters that are necessary for a program is shall be included in a Galaxy installation.

GalaxyAdaptor.FileResult - Class in de.jstacs.tools.ui.galaxy

Result for files that are results of some computation.

GalaxyAdaptor.HeadResult - Class in de.jstacs.tools.ui.galaxy

Class for a result that is basically a CategoricalResult, but has its own name for checking purposes.

GalaxyAdaptor.LineBasedResult - Class in de.jstacs.tools.ui.galaxy

Superclass for all Result that may be saved line by line.

GalaxyAdaptor.LinkedImageResult - Class in de.jstacs.tools.ui.galaxy

Class for an ImageResult that is linked to a file that can be downloaded.

GalaxyAdaptor.Protocol - Class in de.jstacs.tools.ui.galaxy

Class for a Protocol writer.

GalaxyConvertible - Interface in de.jstacs.parameters

Interface for Parameters that can be converted to and extracted from Galaxy representations.

gammas - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission

Contains the emission sequences and corresponding gammas (state-posteriors) required for the estimation of the standard deviation.

GaussianEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous

Emission for continuous values following a Gaussian distribution.

GaussianEmission(AlphabetContainer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission

Creates a GaussianEmission which can be used for maximum likelihood.

GaussianEmission(AlphabetContainer, double, double, double, double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission

Creates a GaussianEmission with normal-gamma prior by directly defining the hyper-parameters of the prior.

GaussianEmission(double, AlphabetContainer, double, double, double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission

Creates a GaussianEmission with normal-gamma prior by defining the expected precision and the expected standard deviation of the precision, i.e.

GaussianEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission

Creates a GaussianEmission from its XML representation.

GaussianLikePositionPrior - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior

This class implements a gaussian like discrete truncated prior.

GaussianLikePositionPrior(int, double, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior

This constructor creates an instance with given sequence length, maximal value and sigma for the Gaussian.

GaussianLikePositionPrior(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior

The standard constructor for the interface Storable.

GenDisMixClassifier - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

This class implements a classifier the optimizes the following function

$\[f(\underline{\lambda}|C,D,\underline{\alpha},\underline{\beta})$

The weights $\beta_i$ have to sum to 1.

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double[], DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier

This constructor creates an instance and sets the value of the last (external) optimization.

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double[], DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier

This constructor creates an instance and sets the value of the last (external) optimization.

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double[], DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier

The main constructor.

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double, double, DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier

This convenience constructor agglomerates the genBeta, disBeta, and priorBeta into an array and calls the main constructor.

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, LearningPrinciple, DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier

This convenience constructor creates an array of weights for an elementary learning principle and calls the main constructor.

GenDisMixClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier

This is the constructor for Storable.

GenDisMixClassifierParameterSet - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

This class contains the parameters for the GenDisMixClassifier.

GenDisMixClassifierParameterSet(StringBuffer) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet

The standard constructor for the interface Storable.

GenDisMixClassifierParameterSet(AlphabetContainer, int, byte, double, double, double, boolean, OptimizableFunction.KindOfParameter, boolean, int) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet

The default constructor that constructs a new GenDisMixClassifierParameterSet.

GenDisMixClassifierParameterSet(Class<? extends ScoreClassifier>, AlphabetContainer, int, byte, double, double, double, boolean, OptimizableFunction.KindOfParameter, boolean, int) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet

The default constructor that constructs a new GenDisMixClassifierParameterSet.

generate(DiscreteAlphabet, int) - Static method in class de.jstacs.data.DeBruijnGraphSequenceGenerator

Generates a De Bruijn sequence of length $|A|^n$

, where A denotes the alphabet.

generate(DiscreteAlphabet, int, int) - Static method in class de.jstacs.data.DeBruijnGraphSequenceGenerator

Generates a De Bruijn sequence using the supplied alphabet and the given alphabet shift, i.e., for a cyclic shift of the symbols of the alphabet.

generate(DiscreteAlphabet, int) - Static method in class de.jstacs.data.DeBruijnSequenceGenerator

Generates a De Bruijn sequence of length $|A|^n$

, where A denotes the alphabet.

generate(DiscreteAlphabet, int, int) - Static method in class de.jstacs.data.DeBruijnSequenceGenerator

Generates a De Bruijn sequence using the supplied alphabet and the given alphabet shift, i.e., for a cyclic shift of the symbols of the alphabet.

generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.DirichletMRG

generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.EqualParts

generate(int) - Method in class de.jstacs.utils.random.EqualParts

Returns an array of length n with entries 1/n.

generate(double[], int, int) - Method in class de.jstacs.utils.random.EqualParts

Modifies a given number of array entries to 1/number.

generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.ErlangMRG

generate(int, MRGParams) - Method in class de.jstacs.utils.random.MultivariateRandomGenerator

Generates a n-dimensional random array.

generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.MultivariateRandomGenerator

Generates a n-dimensional random array as part of the array d beginning at start.

generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.SoftOneOfN

generate(int) - Method in class de.jstacs.utils.random.SoftOneOfN

Generates an array of length number with one entry getting the value 1-epsilon and all the others equal parts of epsilon.

generate(double[], int, int) - Method in class de.jstacs.utils.random.SoftOneOfN

Generates an array of length number as part of the array d beginning at index start with one entry getting the value 1-epsilon and all the others equal parts of epsilon.

generateLog(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.DirichletMRG

Fills a part of the array d beginning at start with n logarithmic values.

generateOutput(File) - Method in class de.jstacs.utils.graphics.EPSAdaptor

generateOutput(String) - Method in class de.jstacs.utils.graphics.GraphicsAdaptor

Generates the outputs and saves the results to a file with the supplied name.

generateOutput(File) - Method in class de.jstacs.utils.graphics.GraphicsAdaptor

Generates the outputs and saves the results to the supplied file.

generateOutput(File) - Method in class de.jstacs.utils.graphics.PDFAdaptor

generateOutput(File) - Method in class de.jstacs.utils.graphics.RasterizedAdaptor

generateOutput(File) - Method in class de.jstacs.utils.graphics.SVGAdaptor

generatePlot(GraphicsAdaptor) - Method in interface de.jstacs.results.PlotGeneratorResult.PlotGenerator

Generates the plot using the Graphics2D device of the supplied GraphicsAdaptor.

generatePlot(GraphicsAdaptor) - Method in class de.jstacs.utils.SeqLogoPlotter.SeqLogoPlotGenerator

GenericComplementableDiscreteAlphabet - Class in de.jstacs.data.alphabets

This class implements an generic complementable discrete alphabet.

GenericComplementableDiscreteAlphabet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet

The standard constructor for the interface Storable.

GenericComplementableDiscreteAlphabet(GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet

This constructor creates a GenericComplementableDiscreteAlphabet from a parameter set.

GenericComplementableDiscreteAlphabet(boolean, String[], int[]) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet

The main constructor.

GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet - Class in de.jstacs.data.alphabets

This class is used as container for the parameters of a GenericComplementableDiscreteAlphabet.

GenericComplementableDiscreteAlphabetParameterSet() - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet

This constructor creates an empty parameter set the has to be filled before it can be used to create a GenericComplementableDiscreteAlphabet.

GenericComplementableDiscreteAlphabetParameterSet(String[], boolean, int[]) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet

The main constructor.

GenericComplementableDiscreteAlphabetParameterSet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet

The standard constructor for the interface Storable.

GEQ - Static variable in interface de.jstacs.parameters.validation.Constraint

The condition is greater or equal

get(int) - Method in class de.jstacs.AnnotatedEntityList

Returns the AnnotatedEntity at index index in the list.

get(String) - Method in class de.jstacs.AnnotatedEntityList

Returns the AnnotatedEntity with name name in the list.

get(int) - Method in class de.jstacs.utils.DoubleList

Returns the element with the specified index.

get(int) - Method in class de.jstacs.utils.IntList

Returns the element with the specified index.

getAbsoluteKMereFrequencies(DataSet, int, boolean) - Static method in class de.jstacs.motifDiscovery.KMereStatistic

This method enables the user to get a statistic over all k-mers in the data.

getAbsoluteKMereFrequencies(DataSet, int, boolean, DataSet.WeightedDataSetFactory.SortOperation) - Static method in class de.jstacs.motifDiscovery.KMereStatistic

This method enables the user to get a statistic over all k-mers in the data.

getAcceptedMimeType() - Method in class de.jstacs.parameters.FileParameter

Returns the type(s) of the allowed files as list of file extensions, separated by commas

getAdaptor(GraphicsAdaptorFactory.OutputFormat) - Static method in class de.jstacs.utils.graphics.GraphicsAdaptorFactory

Returns an appropriat GraphicsAdaptor for the given format

getAdaptVariance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet

Returns true if the sampling variance shall be adapted to the size of the event space of a random variable

getAdditionalInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior

getAdditionalInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior

This method returns a StringBuffer containing additional information for the XML representation.

getAdditionalInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior

getAlgorithm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet

This method returns a byte encoding for the algorithm that should be used for optimization.

getAlignedString(int) - Method in class de.jstacs.algorithms.alignment.StringAlignment

Returns the aligned String with index index.

getAlignment(Alignment.AlignmentType, Sequence, Sequence) - Method in class de.jstacs.algorithms.alignment.Alignment

Computes and returns the alignment of s1 and s2 (Alignment.Alignment(Costs)).

getAlignment(Alignment.AlignmentType, Sequence, int, int, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.Alignment

Computes and returns the alignment of s1 and s2 (Alignment.Alignment(Costs)).

getAlignment(int[]) - Method in class de.jstacs.algorithms.alignment.Alignment

Returns the optimal alignment (backtrace) according to matrix index[0] until positions index[1] and index[2] in the first and second sequence, respectively.

getAllConditionalStationaryDistributions() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM

This method returns the stationary conditional distributions.

getAllConditionalStationaryDistributions(double[], int) - Static method in class de.jstacs.utils.StationaryDistribution

This method returns the conditional stationary distributions, i.e.

getAllElements() - Method in class de.jstacs.data.DataSet

Returns an array of Sequences containing all elements of this DataSet.

getAllLeafs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode

This method returns a list of PhyloNodes that are leafs in the subtree starting from this instance

getAllLeafs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree

This method returns a list of PhyloNodes that represent the leafs of the tree

getAllMeasures() - Method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasureParameterSet

Returns an array of all contained performance measures.

getAllowedNumberOfClasses() - Method in class de.jstacs.classifiers.performanceMeasures.AbstractTwoClassPerformanceMeasure

getAllowedNumberOfClasses() - Method in class de.jstacs.classifiers.performanceMeasures.ClassificationRate

getAllowedNumberOfClasses() - Method in class de.jstacs.classifiers.performanceMeasures.ConfusionMatrix

getAllowedNumberOfClasses() - Method in interface de.jstacs.classifiers.performanceMeasures.PerformanceMeasure

This method returns the allowed number of classes.

getAllParameterNames() - Method in class de.jstacs.parameters.ParameterSet

Returns the names of all Parameters in this ParameterSet.

getAllValues(int) - Method in class de.jstacs.results.MeanResultSet

Returns all values of the result with index index if available otherwise null.

getAlphabetAt(int) - Method in class de.jstacs.data.AlphabetContainer

Returns the underlying Alphabet of position pos.

getAlphabetContainer() - Method in class de.jstacs.classifiers.AbstractClassifier

This method returns the container of alphabets that is used in the classifier.

getAlphabetContainer() - Method in class de.jstacs.data.DataSet

Returns the AlphabetContainer of this DataSet.

getAlphabetContainer() - Method in class de.jstacs.data.sequences.Sequence

Return the alphabets, i.e.

getAlphabetContainer() - Method in class de.jstacs.parameters.SequenceScoringParameterSet

Returns the AlphabetContainer of the current instance.

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore

getAlphabetContainer() - Method in interface de.jstacs.sequenceScores.SequenceScore

Returns the container of alphabets that were used when constructing the instance.

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner

This method returns the AlphabetContainer of the StructureLearner.

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission

getAlphabetContainer() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission

This method returns the AlphabetContainer of this emission.

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission

getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission

getAlphabetIndexForPosition(int) - Method in class de.jstacs.data.AlphabetContainer

This method returns the index of the Alphabet that is used for the given position.

getAlphabetLengthAt(int) - Method in class de.jstacs.data.AlphabetContainer

Returns the length of the underlying Alphabet of position pos.

getAncestorProbabilities(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Returns the probabilities that the preceding positions considered are used as context.

getAnnotation() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet

Returns a Collection of parameters containing informations about this ClassifierAssessmentAssessParameterSet.

getAnnotation() - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet

getAnnotation() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet

getAnnotation() - Method in class de.jstacs.classifiers.assessment.RepeatedSubSamplingAssessParameterSet

getAnnotation() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet

getAnnotation(DataSet...) - Static method in class de.jstacs.data.DataSet

Returns the annotation for an array of DataSets.

getAnnotation() - Method in class de.jstacs.data.DataSet

Returns some annotation of the DataSet.

getAnnotation() - Method in class de.jstacs.data.sequences.Sequence

Returns the annotation of the Sequence.

getAnnotation() - Method in class de.jstacs.io.AbstractStringExtractor

Returns the annotation of the source.

getAnnotation() - Method in class de.jstacs.results.ListResult

Returns a reference to the annotation of this ListResult.

getAnnotationResult() - Method in class de.jstacs.algorithms.alignment.StringAlignment

Returns the annotation result.

getAnnotations() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation

Returns the additional annotations of this SequenceAnnotation as given in the constructor.

getAnnotations() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence

This method returns the SequenceAnnotation[] for each dimension of this multidimensional sequence.

getAnnotationTypesAndIdentifier() - Method in class de.jstacs.data.DataSet

This method returns all SequenceAnnotation types and the corresponding identifier which occur in this DataSet.

getAPrioriMixtureProbabilities() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

Returns the mixture probabilities (i.e., the a-priori probabilities of the different components).

getArrowOption(NumberFormat, double, double, String, boolean) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the option for an edge in Graphviz.

getAssessParameterSet() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment

This method returns an instance of ClassifierAssessmentAssessParameterSet that can be used in the assess methods.

getAssessParameterSet() - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidation

getAssessParameterSet() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutExperiment

getAssessParameterSet() - Method in class de.jstacs.classifiers.assessment.RepeatedSubSamplingExperiment

getAssessParameterSet() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutExperiment

getAsymIndex(int, int[], byte) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor

Returns the index for an asymmetric tensor.

getAverageElementLength() - Method in class de.jstacs.data.DataSet

Returns the average length of all Sequences in this DataSet.

getBest(int, int[], byte) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor

Returns the maximal weight which can be reached for an edge from k nodes from the (encoded) set par to the node child.

getBestParameters() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Returns the sampled parameter values with the maximum value of the objective function

getBeta(LearningPrinciple) - Static method in enum de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple

This method returns the standard weights for a predefined key.

getBindingSites(DataSet, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method returns a DataSet containing the predicted binding sites.

getBindingSites(int, DataSet, int, int, int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method returns a DataSet containing the predicted binding sites.

getBooleanFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the boolean which is the value of the Parameter par.

getBorder(double[], double) - Static method in class de.jstacs.classifiers.utils.PValueComputation

This method finds the first index that has a significant score.

getBufferedImageAndGraphics(int, double[][]) - Static method in class de.jstacs.utils.SeqLogoPlotter

Creates a new BufferedImage with given height and width chosen automatically according to the number of rows of ps, and returns this BufferedImage and its Graphics2D object.

getBurnInTest() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.SamplingHMMTrainingParameterSet

This method return the burn in test to be used during sampling.

getByteFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the byte which is the value of the Parameter par.

getCharacteristics() - Method in class de.jstacs.classifiers.AbstractClassifier

Returns some information characterizing or describing the current instance of the classifier.

getCharacteristics() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier

getCharacteristics() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore

getCharacteristics() - Method in interface de.jstacs.sequenceScores.SequenceScore

Returns some information characterizing or describing the current instance.

getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM

getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

getChild(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the state index encoded by the child index.

getChildIdx(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition

getChildIdx(int, int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns the child index of the state, if this state is no child of the context -1 is returned

getChildrenNodes() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode

This method returns a list of PhyloNodes that are children of this instance

getClassifier() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment

Returns a deep copy of all classifiers that have been or will be used in this assessment.

getClassifierAnnotation() - Method in class de.jstacs.classifiers.AbstractClassifier

Returns an array of Results of dimension AbstractClassifier.getNumberOfClasses() that contains information about the classifier and for each class.


 res[0] = new CategoricalResult( "classifier", "the kind of classifier", getInstanceName() );

 res[1] = new CategoricalResult( "class info 0", "some information about the class", "info0" );

 res[2] = new CategoricalResult( "class info 1", "some information about the class", "info1" );

 ...


getClassifierAnnotation() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.classifiers.MappingClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureClassifier
 
getClassifierForBestParameters(GenDisMixClassifierParameterSet) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier

Returns a standard, i.e., non-sampling, GenDisMixClassifier, where the parameters
 are set to those that yielded the maximum value of the objective functions among all sampled
 parameter values.

getClassifierForMeanParameters(GenDisMixClassifierParameterSet, boolean, int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier

Returns a standard, i.e., non-sampling, GenDisMixClassifier, where the parameters
 are set to the mean values over all sampled
 parameter values in the stationary phase.

getClassName() - Method in class de.jstacs.results.StorableResult

Returns the name of the class of the Storable corresponding to
 the XML representation stored in this StorableResult.

getClassParams(double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction

Returns from the complete vector of parameters those that are for the
 classes.

getClassWeight(int) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier

Returns the class weight for the class with a given index.

getClassWeights() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier

Returns the specific class weights of a
 AbstractScoreBasedClassifier.

getClazz() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet

Returns the source of the data to compute the mutual information as
 defined by this set of parameters.

getClazz() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet

Returns the source of the data to compute the mutual information as
 defined by this set of parameters.

getClusterElements() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the elements at all leaves in this cluster tree, in the order
 of the leaves, from left to right.

getClusterRepresentative(ClusterTree<StatisticalModel>, int) - Static method in class de.jstacs.clustering.distances.DeBruijnMotifComparison

Returns a position weight matrix (PWM) representation of the root node of the given cluster tree and
 also computed the relative shifts of the motifs such that they align best with the consensus motif at the root.

getCMI(double[][][][][][], double[][][][][][], double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Computes the conditional mutual information from fgStats and
 bgStats counted on sequences with a total weight of
 n.

getCMI(double[][][][], double[][][][], double, double, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Computes the conditional mutual information from fgStats and
 bgStats counted on sequences with a total weight of
 nFg and nBg, respectively.

getCode(int, String) - Method in class de.jstacs.data.AlphabetContainer

Returns the encoded symbol for sym of the Alphabet
 of position pos of this AlphabetContainer.

getCode(String) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet

Returns the code of a given symbol.

getCode(String) - Method in class de.jstacs.data.alphabets.DNAAlphabet
 
getCollectionOfAllMeasures(int, boolean) - Static method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure

This method creates an instance of an SelectionParameter that can be used to create
 an instance of PerformanceMeasureParameterSet or NumericalPerformanceMeasureParameterSet.

getCollectionOfScales() - Static method in class de.jstacs.parameters.RangeParameter

Returns a EnumParameter that allows the user to choose
 between different scales.

getColor(int) - Static method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Returns the color for a specified depth within the parameter hierarchy.

getColumnWidth(int) - Static method in class de.jstacs.utils.SeqLogoPlotter

Returns the width of one column in the sequence logo of the given height for a PWM with the given number of columns.

getCombination() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.CombinationIterator

Returns a clone of the internal combination.

getComment() - Method in class de.jstacs.AnnotatedEntity

Returns the comment on the AnnotatedEntity.

getComment(Class<? extends ParameterSet>) - Static method in class de.jstacs.parameters.ParameterSet

Returns a comment for the class.

getComment(ParameterSet) - Static method in class de.jstacs.parameters.ParameterSet

Returns a comment for the ParameterSet.

getComments() - Method in enum de.jstacs.data.DinucleotideProperty

Returns additional comments on this property.

getCommonString(DataSet, int, boolean) - Static method in class de.jstacs.motifDiscovery.KMereStatistic

This method returns an array of sequences of length
 motifLength so that each string is contained in all
 sequences of the data set, more precisely in the data set or the reverse
 complementary data set.

getComplementaryCode(int) - Method in class de.jstacs.data.alphabets.ComplementableDiscreteAlphabet

This method returns the code of the symbol that is the complement of the
 symbol encoded by code.

getComplementaryCode(int) - Method in class de.jstacs.data.alphabets.DNAAlphabet
 
getComplementaryCode(int) - Method in class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet
 
getComplementaryCode(int) - Method in class de.jstacs.data.alphabets.IUPACDNAAlphabet
 
getComponents() - Method in class de.jstacs.algorithms.graphs.UnionFind

Returns the connected components of the graph.

getComponentScores(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

Return the scores for the individual components.

getCompositeContainer(int[], int[]) - Method in class de.jstacs.data.AlphabetContainer

Returns an AlphabetContainer of Alphabets e.g.

getCompositeDataSet(int[], int[]) - Method in class de.jstacs.data.DataSet

This method enables you to use only composite Sequences of all
 elements in the current DataSet.

getCompositeSequence(AlphabetContainer, int[], int[]) - Method in class de.jstacs.data.sequences.Sequence

This method should be used if one wants to create a DataSet of
 Sequence.CompositeSequences.

getCompositeSequence(int[], int[]) - Method in class de.jstacs.data.sequences.Sequence

This is a very efficient way to create a Sequence.CompositeSequence for
 sequences with a simple AlphabetContainer.

getConditionalProbabilities(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Returns the conditional probabilities for the specified component.

getConditionIndex(boolean, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission

This method returns an index encoding the condition.

getConditionIndex(boolean, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.DiscreteEmission
 
getConditionIndex(boolean, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.ReferenceSequenceDiscreteEmission
 
getConsensus(AlphabetContainer, double[][]) - Static method in class de.jstacs.utils.PFMComparator

This method extracts the 
 The method does not use any degenerated IUPAC code.

getConservedPatterns(Hashtable<Sequence, BitSet[]>, int, int) - Static method in class de.jstacs.motifDiscovery.KMereStatistic

This method returns a list of Sequences.

getContent() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation

Returns the content of the file.

getContext(String[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns a String representation of the context.

getCorrectedPosition(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint

Returns the value of the corrected position index.

getCost(int, int) - Method in class de.jstacs.algorithms.alignment.Alignment

Returns the costs until positions end1 and end2 of the last alignment computed using
 Alignment.computeAlignment(AlignmentType, Sequence, Sequence).

getCost() - Method in class de.jstacs.algorithms.alignment.StringAlignment

Returns the costs.

getCostFor(Sequence, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
 
getCostFor(Sequence, Sequence, int, int) - Method in interface de.jstacs.algorithms.alignment.cost.Costs

Returns the costs for the alignment of s1(i) and
 s2(j).

getCostFor(Sequence, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.cost.MatrixCosts
 
getCostFor(Sequence, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.cost.SimpleCosts
 
getCount(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns the current count with index index.

getCounts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the current counts for this parameter.

getCounts(DataSet...) - Static method in class de.jstacs.utils.PFMComparator

This method counts the occurrences of symbols in the given data sets.

getCum_Complex(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getCum_Naive(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getCurrentAnnotation() - Method in class de.jstacs.data.sequences.annotation.NullSequenceAnnotationParser
 
getCurrentAnnotation() - Method in interface de.jstacs.data.sequences.annotation.SequenceAnnotationParser

This method returns the current SequenceAnnotation.

getCurrentAnnotation() - Method in class de.jstacs.data.sequences.annotation.SimpleSequenceAnnotationParser
 
getCurrentAnnotation() - Method in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
 
getCurrentParameterSet() - Method in class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
 
getCurrentParameterSet() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

This method returns the current ParameterSet of the classifier.

getCurrentParameterSet() - Method in class de.jstacs.data.AlphabetContainer
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.Alphabet
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet
 
getCurrentParameterSet() - Method in interface de.jstacs.InstantiableFromParameterSet

Returns the InstanceParameterSet that has been used to
 instantiate the current instance of the implementing class.

getCurrentParameterSet() - Method in class de.jstacs.sampling.AbstractBurnInTest
 
getCurrentParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getCurrentParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
 
getCurrentParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
 
getCurrentParameterValues() - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

Returns a double array of dimension
 DifferentiableSequenceScore.getNumberOfParameters() containing the current parameter values.

getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getCurrentSequenceAnnotations() - Method in class de.jstacs.io.AbstractStringExtractor

Returns the SequenceAnnotation or null if no SequenceAnnotation is available.

getCurrentSequenceAnnotations() - Method in class de.jstacs.io.InfixStringExtractor
 
getCurrentSequenceAnnotations() - Method in class de.jstacs.io.LimitedStringExtractor
 
getCurrentSequenceAnnotations() - Method in class de.jstacs.io.SparseStringExtractor
 
getData() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
 
getData() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.OneDataSetLogGenDisMixFunction
 
getData() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction

Returns the data for each class used in this OptimizableFunction.

getDataRef() - Method in class de.jstacs.tools.DataColumnParameter

Returns the  ID of the referenced parameter (tabular) in Galaxy.

getDataSet() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory

Returns the DataSet, where each Sequence occurs only
 once.

getDataSet(AlphabetContainer, String, SequenceAnnotationParser) - Static method in class de.jstacs.data.sequences.ArbitraryFloatSequence

This method allows to create a DataSet containing ArbitraryFloatSequences using
 a file name.

getDataSet(AlphabetContainer, String) - Static method in class de.jstacs.data.sequences.ArbitraryFloatSequence

This method allows to create a DataSet containing ArbitraryFloatSequences using
 a file name.

getDataSet(AlphabetContainer, AbstractStringExtractor...) - Static method in class de.jstacs.data.sequences.ArbitraryFloatSequence

This method allows to create a DataSet containing ArbitraryFloatSequences.

getDataSet(AlphabetContainer, String, SequenceAnnotationParser) - Static method in class de.jstacs.data.sequences.SparseSequence

This method allows to create a DataSet containing SparseSequences using
 a file name.

getDataSet(AlphabetContainer, String) - Static method in class de.jstacs.data.sequences.SparseSequence

This method allows to create a DataSet containing SparseSequences using
 a file name.

getDataSet(AlphabetContainer, AbstractStringExtractor...) - Static method in class de.jstacs.data.sequences.SparseSequence

This method allows to create a DataSet containing SparseSequences.

getDataSetForProperty(DataSet, DinucleotideProperty) - Static method in enum de.jstacs.data.DinucleotideProperty

Creates a new DataSet by converting each Sequence in original to the DinucleotideProperty property.

getDataSetForProperty(DataSet, DinucleotideProperty.Smoothing, boolean, DinucleotideProperty) - Static method in enum de.jstacs.data.DinucleotideProperty

Creates a new DataSet by converting each Sequence in original to the DinucleotideProperty property using the DinucleotideProperty.Smoothing smoothing.

getDataSetForProperty(DataSet, DinucleotideProperty...) - Static method in enum de.jstacs.data.DinucleotideProperty

Creates a new DataSet by converting each Sequence in original to the DinucleotidePropertys properties and setting these as ReferenceSequenceAnnotation of each original sequence.

getDataSetForProperty(DataSet, DinucleotideProperty.Smoothing, boolean, DinucleotideProperty...) - Static method in enum de.jstacs.data.DinucleotideProperty

Creates a new DataSet by converting each Sequence in original to the DinucleotidePropertys properties and adding or setting these as ReferenceSequenceAnnotation of each original sequence.

getDataSplitMethod() - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet

Returns the DataSet.PartitionMethod defining how the mutually exclusive
 random-splits of user supplied data are generated.

getDataSplitMethod() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet

Returns the DataSet.PartitionMethod defining how the mutually exclusive
 random-splits of user supplied data are generated.

getDataSplitMethod() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet

Returns the DataSet.PartitionMethod defining how the mutually exclusive
 random-splits of user supplied data are generated.

getDatatype() - Method in class de.jstacs.AnnotatedEntity

Returns the data type of the AnnotatedEntity.

getDeclaredClass() - Method in class de.jstacs.tools.JstacsTool.ResultEntry

Returns the class declared for the default result.

getDefault() - Method in class de.jstacs.parameters.SelectionParameter

Returns the index of the default selected value.

getDefaultExtension(Class<? extends Result>) - Static method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Returns the default extension (Galaxy format) for a given result class.

getDefaultResultInfos() - Method in interface de.jstacs.tools.JstacsTool

Returns JstacsTool.ResultEntrys for the default results of this JstacsTool.

getDeleteCosts() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
 
getDeleteCosts() - Method in interface de.jstacs.algorithms.alignment.cost.Costs

Returns the costs for a delete gap, i.e., a gap in the second string.

getDeleteCosts() - Method in class de.jstacs.algorithms.alignment.cost.MatrixCosts
 
getDeleteCosts() - Method in class de.jstacs.algorithms.alignment.cost.SimpleCosts
 
getDeleteCostsFor(int) - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts

Returns the costs for a delete gap of length length.

getDeleteOnExit() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Returns true if the temporary parameter files shall
 be deleted on exit of the program.

getDelim() - Method in class de.jstacs.data.AlphabetContainer

Returns the delimiter that should be used (for writing e.g.

getDepth() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the depth of the tree, i.e.

getDescendant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the index of the descendant transition element when following the child with index index

getDescription() - Method in class de.jstacs.io.RegExFilenameFilter
 
getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns the decoded symbol for the encoded symbol i.

getDescription() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

Returns a short description of the model that was given by the user in
 the parameter set.

getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
 
getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
 
getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhConstraint
 
getDescription() - Method in interface de.jstacs.tools.JstacsTool

Returns a short description (half a sentence) on what this tool does.

getDifferentiableSequenceScore(int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

Returns the internally used DifferentiableSequenceScore with index
 i.

getDifferentiableSequenceScores() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

Returns all internally used DifferentiableSequenceScores in the internal
 order.

getDifferentiableStatisticalModels() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

Returns a deep copy of all internal used
 DifferentiableStatisticalModels.

getDimension() - Method in enum de.jstacs.data.DinucleotideProperty

Returns the dimension of this property, e.g.

getDimension() - Method in class de.jstacs.utils.random.DiMRGParams

Returns the dimension of the hyperparameter vector of the underlying
 Dirichlet distribution and therefore the dimension of the generated
 random array.

getDimension() - Method in class de.jstacs.utils.random.DirichletMRGParams
 
getDimension() - Method in class de.jstacs.utils.random.ErlangMRGParams

Returns the dimension of the hyperparameter vector of the underlying
 Erlang distribution.

getDimension() - Method in class de.jstacs.utils.random.FastDirichletMRGParams
 
getDimensionOfScope() - Method in interface de.jstacs.algorithms.optimization.Function

Returns the dimension of the scope of the Function.

getDimensionOfScope() - Method in class de.jstacs.algorithms.optimization.NegativeDifferentiableFunction
 
getDimensionOfScope() - Method in class de.jstacs.algorithms.optimization.NegativeFunction
 
getDimensionOfScope() - Method in class de.jstacs.algorithms.optimization.NumericalDifferentiableFunction
 
getDimensionOfScope() - Method in class de.jstacs.algorithms.optimization.OneDimensionalFunction
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLaplaceLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools.DualFunction
 
getDinucleotideParameters() - Method in enum de.jstacs.data.DinucleotideProperty

Returns the dinucleotide parameters of this DinucleotideProperty as a two-dimensional double array, where the rows correspond to the first nucleotide
 and the columns correspond to the second nucleotide in the dinucleotide in order A, C, G, and T.

getDistance(T, T) - Method in class de.jstacs.clustering.distances.DistanceMetric

Returns the distance according to the metric of the two supplied objects.

getDistance(double[], double[]) - Method in class de.jstacs.clustering.distances.PearsonCorrelationDistanceMetric
 
getDistance(double[][], double[][], double[][], int) - Method in class de.jstacs.clustering.distances.SequenceScoreDistance

Returns the distance between the two score profiles.

getDistance(double[][], double[][], StatisticalModel, int) - Method in class de.jstacs.clustering.distances.SequenceScoreDistance

Returns the distance between a score profile and a model.

getDistance(StatisticalModel, StatisticalModel) - Method in class de.jstacs.clustering.distances.SequenceScoreDistance
 
getDistance() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the distance between the child trees of this cluster tree root node.

getDistance(double[][], ClusterTree<Integer>, ClusterTree<Integer>) - Method in class de.jstacs.clustering.hierachical.Hclust

Returns the distance between the two supplied trees using the linkage method of this Hclust object
 and the given distance matrix.

getDistance() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Returns the maximum distance of preceding positions considered in the LSlim model.

getDistance(double[][], double[][], int, int) - Method in class de.jstacs.utils.PFMComparator.NormalizedEuclideanDistance
 
getDistance(double[][], double[][], int, int) - Method in class de.jstacs.utils.PFMComparator.OneMinusPearsonCorrelationCoefficient
 
getDistance(double[][], double[][], int) - Method in class de.jstacs.utils.PFMComparator.PFMDistance

This method computes the distance between two PFMs.

getDistance(double[][], double[][], int, int) - Method in class de.jstacs.utils.PFMComparator.PFMDistance

Computes the mean distance between the overlapping parts of pfm1 and pfm2 starting at the offsets
 l1 and l2, respectively.

getDistance(double[][], double[][], int, int) - Method in class de.jstacs.utils.PFMComparator.SymmetricKullbackLeiblerDivergence
 
getDistance(double[][], double[][], int, int) - Method in class de.jstacs.utils.PFMComparator.UniformBorderWrapper
 
getDoubleFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the double which is the value of the
 Parameter par.

getEAR(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual

Returns the explaining away residual (EAR) between all pairs of positions
 as a matrix.

getEAR(double[][][][][][], double[][][][][][], double, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Computes the explaining away residual from fgStats and
 bgStats counted on sequences with a total weight of
 nFg and nBg, respectively.

getEAR(double[][][][], double[][][][], double, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Computes the explaining away residual from fgStats and
 bgStats counted on sequences with a total weight of
 nFg and nBg, respectively.

getEdgeFromIndex(int, int) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor

This method decodes an index in an edge.

getElapsedTime() - Method in class de.jstacs.utils.RealTime
 
getElapsedTime() - Method in class de.jstacs.utils.Time

Returns the elapsed time since invoking the constructor.

getElapsedTime() - Method in class de.jstacs.utils.UserTime
 
getElement(int) - Method in class de.jstacs.io.StringExtractor

Returns String number idx that has been extracted.

getElement() - Method in class de.jstacs.utils.ComparableElement

This method returns the element.

getElementAt(int) - Method in class de.jstacs.data.DataSet

This method returns the element, i.e.

getElementAt(int) - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory

Returns the Sequence with index index.

getElementLength() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet

Returns the length of elements (sequences) defined by this
 ClassifierAssessmentAssessParameterSet.

getElementLength() - Method in class de.jstacs.data.DataSet

Returns the length of the elements, i.e.

getElongateDeleteCosts() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts

Returns the costs for elongating a delete gap by one position.

getElongateInsertCosts() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts

Returns the costs for elongating an insert gap by one position.

getEmissionIndexes() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

Returns a clone of the internal array of emission indexes that represent which emission is used in which state.

getEmissions() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

Returns a clone of the internal emissions.

getEmptyContainer() - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.MultiDimensionalArbitrarySequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.MultiDimensionalDiscreteSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.Sequence

The method returns a container that can be used for accessing the symbols for each position.

getEmptyContainer() - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.Sequence

Returns an empty representation which is used to create the String representation of this instance in the method Sequence.toString(String, int, int).

getEmptyRepresentation() - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
 
getEnd() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength

Returns the end of this LocatedSequenceAnnotationWithLength, i.e.

getEndIndexOfAlignmentForFirst() - Method in class de.jstacs.algorithms.alignment.PairwiseStringAlignment

This method returns the end index of the alignment in the first sequence.

getEndNode() - Method in class de.jstacs.algorithms.graphs.Edge

Returns the end node of the edge.

getEndValue() - Method in class de.jstacs.parameters.RangeParameter

Returns the last value of a range of parameter values or
 null if no range was specified.

getEntropy(Constraint) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.ConstraintManager

Tries to compute the entropy as exact as possible.

getErrorMessage() - Method in class de.jstacs.parameters.AbstractSelectionParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.FileParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.Parameter

If a value could not be set successfully this method returns the
 corresponding error message.

getErrorMessage() - Method in class de.jstacs.parameters.ParameterSet

Returns the message of the last error that occurred.

getErrorMessage() - Method in class de.jstacs.parameters.ParameterSetContainer
 
getErrorMessage() - Method in class de.jstacs.parameters.RangeParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.SelectionParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.SimpleParameter
 
getErrorMessage() - Method in interface de.jstacs.parameters.validation.Constraint

Returns the message of the last error (missed constraint) or
 null if the constraint was fulfilled by the last checked
 value.

getErrorMessage() - Method in class de.jstacs.parameters.validation.ConstraintValidator
 
getErrorMessage() - Method in class de.jstacs.parameters.validation.NumberValidator
 
getErrorMessage() - Method in interface de.jstacs.parameters.validation.ParameterValidator

Returns the error message if ParameterValidator.checkValue(Object) returned false.

getErrorMessage() - Method in class de.jstacs.parameters.validation.RegExpValidator
 
getErrorMessage() - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint
 
getErrorMessage() - Method in class de.jstacs.parameters.validation.StorableValidator
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getESS() - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel

Returns the equivalent sample size (ess) of this model, i.e.

getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet

Returns the equivalent samples size (ess) defined in this set of
 parameters.

getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet

Returns the equivalent sample sizes (ess) defined by this set of
 parameters.

getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet

Returns the equivalent sample sizes (ess) defined by this set of
 parameters.

getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet

Returns the equivalent sample sizes (ess) defined by this set of
 parameters.

getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet

Returns the equivalent sample sizes (ess) defined by this set of parameters.

getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

This method returns the ess (equivalent sample size)
 that is used in this model.

getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner

This method returns the ess (equivalent sample size)
 of the StructureLearner.

getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getExceptionIfMPNotComputable() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet

Returns the flag defined by this
 ClassifierAssessmentAssessParameterSet.

getExpLambda(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint

Returns the exponential value of  at position
 index: .

getExport() - Method in class de.jstacs.results.ListResult

Returns if this ListResult is exported in Galaxy.

getExport() - Method in class de.jstacs.results.TextResult

Returns true if the contents are saved to a separate file in Galaxy.

getExpPartOfProb(MEMConstraint[], int[], SequenceIterator) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools

This method computes the exponential part of the probability, i.e., everything except the normalization constant.

getExpValue() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns Math.exp(BNDiffSMParameter.getValue()), which is pre-computed.

getExtendedType() - Method in class de.jstacs.parameters.FileParameter

Returns the extended type (or null if not set) of this FileParameter.

getExtendedType() - Method in class de.jstacs.results.TextResult

Returns the extended type of this TextResult.

getExtension() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation

Returns the extension of this FileParameter.

getExtension() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult

Returns the filename extension

getExtremum() - Method in class de.jstacs.algorithms.optimization.QuadraticFunction

This method returns the extremum of the QuadraticFunction.

getFactorForAucPR() - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method returns a factor that must be multiplied to scores for computing PR curves.

getFactors(String, boolean, ConstraintManager.Decomposition) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager

This method returns an array of independent maximum entropy models parsed from the given constraints.

getFactors(ArrayList<int[]>, boolean, ConstraintManager.Decomposition) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager

This method returns an array of independent maximum entropy models parsed from the given constraints.

getFancyScatterplot(AbstractScoreBasedClassifier, AbstractScoreBasedClassifier, REnvironment, DataSet...) - Static method in class de.jstacs.classifiers.utils.ClassificationVisualizer

Scatters the classification scores of two binary classifiers for given data.

getFileContents() - Method in class de.jstacs.parameters.FileParameter

Returns the content of the file.

getFileExtensions(DataSetResult) - Method in class de.jstacs.results.savers.DataSetResultSaver
 
getFileExtensions(ListResult) - Method in class de.jstacs.results.savers.ListResultSaver
 
getFileExtensions(PlotGeneratorResult) - Method in class de.jstacs.results.savers.PlotGeneratorResultSaver
 
getFileExtensions(T) - Method in interface de.jstacs.results.savers.ResultSaver

Returns the file extensions (in descending preference) for storing the given Result

getFileExtensions(ResultSetResult) - Method in class de.jstacs.results.savers.ResultSetResultSaver
 
getFileExtensions(StorableResult) - Method in class de.jstacs.results.savers.StorableResultSaver
 
getFileExtensions(TextResult) - Method in class de.jstacs.results.savers.TextResultSaver
 
getFilename() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation

Returns the filename.

getFilename() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult

Returns the filename.

getFilesize() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation

Returns the size of the file of the FileParameter.FileRepresentation
 as specified in the constructor.

getFinalStatePosterioriMatrix(double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method is used if AbstractHMM.fillLogStatePosteriorMatrix(double[][], int, int, Sequence, boolean) is used with silentZero==true
 to eliminate the first row.

getFinishedDate() - Method in class de.jstacs.tools.ToolResult

Returns the date and time, when the tool's run resulting in this ToolResult finished.

getFirstElement() - Method in class de.jstacs.utils.Pair

This method returns the first element.

getFirstParent() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the first parent of the random variable of this
 BNDiffSMParameterTree in the topological ordering of the network
 structure of the enclosing BayesianNetworkDiffSM.

getFloatFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the float which is the value of the
 Parameter par.

getFormat() - Method in class de.jstacs.tools.JstacsTool.ResultEntry

Returns the format of the result.

getForwardProbability() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM

This methoth returns the a-priori probability for the forward strand.

getFreeParameters() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet

Returns true if only free parameters shall be used

getFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns the current frequency with index index.

getFreq(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

This method determines the specific constraint that is fulfilled by the
 Sequence seq beginning at position
 start.

getFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
 
getFreqInfo(AlphabetContainer, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns an information about the stored frequencies.

getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
 
getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Returns the function that should be sampled from.

getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

Returns the function that should be optimized.

getFunction() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM

This method return the internal function.

getFunction(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This method returns a specific internal function.

getFunction() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM

This method returns the internal function.

getFunction() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM

Returns a copy of the internally used DifferentiableStatisticalModel.

getFunctions() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS

This method returns a deep copy of the internally used DifferentiableSequenceScore.

getFunctions() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This method returns an array of clones of the internal used functions.

getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.AbstractClassifier

This method returns further information of a classifier as a
 StringBuffer.

getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.MappingClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureClassifier
 
getFurtherInformation() - Method in class de.jstacs.sampling.AbstractBurnInTest

This method returns further information for the
 AbstractBurnInTest.

getFurtherInformation() - Method in class de.jstacs.sampling.VarianceRatioBurnInTest
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS

This method is used to append further information of the instance to the
 XML representation.

getFurtherInformation() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS

This method is used to append further information of the instance to the
 XML representation.

getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This method is used to append further information of the instance to the
 XML representation.

getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method is used in the subclasses to append further information to
 the XML representation.

getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
 
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

Returns further model information as a StringBuffer.

getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
 
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
 
getGapCostsFor(int) - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts

Returns the costs for a gap of length length.

getGeneralizedDivergence(double[][], double[][], double) - Static method in class de.jstacs.utils.StatisticalTest

Computes the generalized divergence for two given stochastic matrices
 over the same domain, i.e.

getGeneralizedDivergence(double[][], double[], double[], double) - Static method in class de.jstacs.utils.StatisticalTest

Computes the generalized divergence for two stochastic matrices over the
 same domain, i.e.

getGeneralizedDivergence(double[][], double) - Static method in class de.jstacs.utils.StatisticalTest

Computes the generalized divergence for two stochastic matrices over the
 same domain, i.e.

getGlobalIndexOfMotifInComponent(int, int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the global index of the motif used in
 component.

getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getGraphics(int, int) - Method in class de.jstacs.utils.graphics.EPSAdaptor
 
getGraphics(int, int) - Method in class de.jstacs.utils.graphics.GraphicsAdaptor

Returns a Graphics2D object for this GraphicsAdaptor of the given width and height.

getGraphics(int, int) - Method in class de.jstacs.utils.graphics.PDFAdaptor
 
getGraphics(int, int) - Method in class de.jstacs.utils.graphics.RasterizedAdaptor
 
getGraphics(int, int) - Method in class de.jstacs.utils.graphics.SVGAdaptor
 
getGraphicsExtension() - Method in class de.jstacs.utils.graphics.EPSAdaptor
 
getGraphicsExtension() - Method in class de.jstacs.utils.graphics.GraphicsAdaptor

Returns the file extension for the graphics file format of this GraphicsAdaptor.

getGraphicsExtension() - Method in class de.jstacs.utils.graphics.PDFAdaptor
 
getGraphicsExtension() - Method in class de.jstacs.utils.graphics.RasterizedAdaptor
 
getGraphicsExtension() - Method in class de.jstacs.utils.graphics.SVGAdaptor
 
getGraphizNetworkRepresentation(NumberFormat, String, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getGraphizNetworkRepresentation(NumberFormat, String, boolean) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns a String representation of the structure that
 can be used in Graphviz to create an image.

getGraphviz() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Returns a Graphviz (dot) representation of the Slim model.

getGraphvizEdgeWeight(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the edge weight for plotting the edge with Graphviz.

getGraphvizNodeOptions(double, double, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState
 
getGraphvizNodeOptions(double, double, NumberFormat) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.State

This method returns a String representation of the node options that
 can be used in Graphviz to create the node for this state.

getGraphvizRepresentation(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns a String representation of the structure that
 can be used in Graphviz to create an image.

getGraphvizRepresentation(NumberFormat, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns a String representation of the structure that
 can be used in Graphviz to create an image.

getGraphvizRepresentation(NumberFormat, DataSet, double[], boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns a String representation of the structure that
 can be used in Graphviz to create an image.

getGraphvizRepresentation(NumberFormat, DataSet, double[], HashMap<String, String>) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns a String representation of the structure that
 can be used in Graphviz to create an image.

getHammingDistance(Sequence) - Method in class de.jstacs.data.sequences.Sequence

This method returns the Hamming distance between the current Sequence and seq.

getHashMap() - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory

This method returns a HashMap that can be used in
 AbstractHMM.getGraphvizRepresentation(java.text.NumberFormat, de.jstacs.data.DataSet, double[], HashMap)
 to create a Graphviz representation of the AbstractHMM

getHeight(int, double[][]) - Static method in class de.jstacs.utils.SeqLogoPlotter

Returns the automatically chosen height for a given width and position weight matrix.

getHeightForDependencyLogo(int, int, int[], int, int) - Static method in class de.jstacs.utils.SeqLogoPlotter

Returns the height for a dependency logos of the given sequence length and chunks.

getHelpText() - Method in interface de.jstacs.tools.JstacsTool

Returns a detailed help text for this tool, describing the purpose of the tool, all parameters and results.

getHowCreated() - Method in enum de.jstacs.data.DinucleotideProperty

Returns how this property has been determined.

getHtmlFilesPath() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Returns the path where files, e.g.

getHtmlId() - Static method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Gets a unique id that can be used, e.g.

getHyperparameter(int) - Method in class de.jstacs.utils.random.DiMRGParams

Returns the value at position i of the hyperparameter vector
 of the underlying Dirichlet distribution.

getHyperparameter(int) - Method in class de.jstacs.utils.random.DirichletMRGParams
 
getHyperparameter(int) - Method in class de.jstacs.utils.random.ErlangMRGParams

Returns the value at position i of the hyperparameter vector
 of the underlying Erlang distribution.

getHyperparameter(int) - Method in class de.jstacs.utils.random.FastDirichletMRGParams
 
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This method returns the hyperparameter for the hidden parameter with
 index index.

getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getHyperParams(int, int, double, double[], double[][][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM

This method returns the hyper-parameters for a model given some a-priori probabilities.

getHyperParams(double, int, int) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission

Returns the hyper-parameters for all parameters and a given ess.

getICScale(double[]) - Static method in class de.jstacs.utils.SeqLogoPlotter

Returns the information content scaled to [0,1].

getId() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode

This method returns the ID of the current PhyloNode

getIdentifier() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation

Returns the identifier of this SequenceAnnotation as given in the
 constructor.

getImage(double[][], REnvironment) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater

This method can be used to create an image of a mutual information
 matrix.

getImage(DataSet, double[], REnvironment, double, int...) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater
 
getImage() - Method in class de.jstacs.utils.graphics.RasterizedAdaptor

Returns the internal image as a BufferedImage

getImmutableInstance() - Static method in class de.jstacs.utils.NullProgressUpdater

Returns a reference to the same NullProgressUpdater that is
 immutable.

getIndex(double[], double) - Static method in class de.jstacs.classifiers.utils.PValueComputation

This method searches in sortedScores for the index
 i so that
 sortedScores[i-1] < myScore <= sortedScores[i].

getIndex(double[], double, int) - Static method in class de.jstacs.classifiers.utils.PValueComputation

This method searches in sortedScores beginning at
 start for the index i so that
 sortedScores[i-1] < myScore <= sortedScores[i].

getIndex(int) - Method in class de.jstacs.data.sequences.PermutedSequence
 
getIndex(int) - Method in class de.jstacs.data.sequences.Sequence.CompositeSequence
 
getIndex(int) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence

Returns the index in the internal sequence.

getIndex(int) - Method in class de.jstacs.data.sequences.Sequence.SubSequence
 
getIndex(String[], Object[], Comparable, boolean) - Static method in class de.jstacs.parameters.ParameterSet

This method tries to find the correct name (String) for your
 choice.

getIndex() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the index of this parameter as defined in the constructor.

getIndex(int[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.CombinationIterator

This method returns an index for the sorted entries of a combination
 combi.

getIndex(int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission

Returns the index for position seqPos in sequence seq.

getIndex(int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement

Returns the distance integrated into the transition from pos - 1  to pos in sequences seq.

getIndex(int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement

Returns the index of the transition matrix used for the transition from pos - 1  to pos in sequences seq.

getIndexForAlphabets() - Method in class de.jstacs.data.AlphabetContainer

This method returns an object that is used for assigning the positions of the Sequences to specific Alphabets.

getIndexOfMaximalComponentFor(Sequence) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the index of the component with the maximal score for the
 sequence sequence.

getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getIndexOfMaximalComponentFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

Returns the index of the component that has the greatest impact on the
 complete score for a Sequence.

getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns the index i of the component with
 P(i|s) maximal.

getIndexTree() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns a cluster tree with identical structure as this cluster tree but with all leaves replaced by
 integer leaves holding the corresponding original indices.

getIndices() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS

This method returns a deep copy of the internally used indices of the DifferentiableSequenceScore for the parts.

getIndices(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This array is used to compute the relative indices of a parameter index.

getInfixDataSet(int, int) - Method in class de.jstacs.data.DataSet

This method enables you to use only an infix of all elements, i.e.

getInfixFilter(int, double, int...) - Method in interface de.jstacs.sequenceScores.QuickScanningSequenceScore

Computes arrays that indicate, for a given set of starting positions and a given k-mer length, if a sequence
 containing this k-mer may yield a score above threshold, choosing the best-scoring option among
 all non-specified positions (i.e., those outside the k-mer).

getInfixFilter(int, double, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getInfixFilter(int, double, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getInfixScores(int, int, int, int, int[], double[][], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getInfos() - Method in class de.jstacs.results.MeanResultSet

Returns some information for this MeanResultSet.

getInitialClassParam(double) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getInitialClassParam(double) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

Returns the initial class parameter for the class this
 DifferentiableSequenceScore is responsible for, based on the class
 probability classProb.

getInitialClassParam(double) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getInitialClassParam(double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getInsertCosts() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
 
getInsertCosts() - Method in interface de.jstacs.algorithms.alignment.cost.Costs

Returns the costs for an insert gap, i.e., a gap in the first string.

getInsertCosts() - Method in class de.jstacs.algorithms.alignment.cost.MatrixCosts
 
getInsertCosts() - Method in class de.jstacs.algorithms.alignment.cost.SimpleCosts
 
getInsertCostsFor(int) - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts

Returns the costs for an insert gap of length length.

getInstance(SequenceAnnotation[], Sequence...) - Method in class de.jstacs.data.sequences.MultiDimensionalArbitrarySequence
 
getInstance(SequenceAnnotation[], Sequence...) - Method in class de.jstacs.data.sequences.MultiDimensionalDiscreteSequence
 
getInstance(SequenceAnnotation[], Sequence...) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence

Returns a new instance of a MultiDimensionalSequence with given SequenceAnnotations and given Sequences.

getInstance() - Method in class de.jstacs.parameters.InstanceParameterSet

Returns a new instance of the class of InstanceParameterSet.getInstanceClass() that
 was created using this ParameterSet.

getInstanceClass() - Method in class de.jstacs.parameters.InstanceParameterSet

Returns the class of the instances that can be constructed using this
 set.

getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet

Deprecated.
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.CombinedCondition.CombinedConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.IterationCondition.IterationConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition.SmallDifferenceOfFunctionEvaluationsConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.SmallGradientConditon.SmallGradientConditonParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.SmallStepCondition.SmallStepConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifierParameterSet
 
getInstanceComment() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifierParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet

Returns a descriptive comment on this
 AlphabetContainerParameterSet.AlphabetArrayParameterSet.

getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet

Returns a descriptive comment on this
 AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet.

getInstanceComment() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet.DiscreteAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.DNAAlphabet.DNAAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.DNAAlphabetContainer.DNAAlphabetContainerParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.IUPACDNAAlphabet.IUPACDNAAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.ProteinAlphabet.ProteinAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.parameters.InstanceParameterSet

Returns a comment (a textual description) of the class that can be
 constructed using this ParameterSet.

getInstanceComment() - Method in class de.jstacs.sampling.VarianceRatioBurnInTestParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGTrainSMParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSMEMParameterSet
 
getInstanceFromParameterSet(InstanceParameterSet<T>) - Static method in class de.jstacs.io.ParameterSetParser

Returns an instance of a subclass of InstantiableFromParameterSet
 that can be instantiated by the InstanceParameterSet
 pars.

getInstanceFromParameterSet(ParameterSet, Class<T>) - Static method in class de.jstacs.io.ParameterSetParser

Returns an instance of a subclass of InstantiableFromParameterSet
 that can be instantiated by the ParameterSet pars.

getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet

Deprecated.
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.CombinedCondition.CombinedConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.IterationCondition.IterationConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition.SmallDifferenceOfFunctionEvaluationsConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.SmallGradientConditon.SmallGradientConditonParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.SmallStepCondition.SmallStepConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.classifiers.AbstractClassifier

Returns a short description of the classifier.

getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior

Returns a short instance name.

getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLaplaceLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifierParameterSet
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifierParameterSet
 
getInstanceName() - Method in class de.jstacs.classifiers.MappingClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet

Returns a descriptive name for this AlphabetContainerParameterSet.AlphabetArrayParameterSet
 .

getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet

Returns a descriptive name for this
 AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet.

getInstanceName() - Method in class de.jstacs.data.alphabets.Alphabet.AlphabetParameterSet
 
getInstanceName() - Method in class de.jstacs.data.alphabets.DNAAlphabetContainer.DNAAlphabetContainerParameterSet
 
getInstanceName() - Method in class de.jstacs.parameters.InstanceParameterSet

Returns the name of an instance of the class that can be constructed
 using this ParameterSet.

getInstanceName() - Method in interface de.jstacs.sampling.BurnInTest

Returns a short description of the burn-in test.

getInstanceName() - Method in class de.jstacs.sampling.SimpleBurnInTest

Deprecated.
 
getInstanceName() - Method in class de.jstacs.sampling.VarianceRatioBurnInTest
 
getInstanceName() - Method in class de.jstacs.sampling.VarianceRatioBurnInTestParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getInstanceName() - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getInstanceName() - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
 
getInstanceName() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getInstanceName() - Method in interface de.jstacs.sequenceScores.SequenceScore

Should return a short instance name such as iMM(0), BN(2), ...

getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Returns the name of the Measure and possibly some additional
 information about the current instance.

getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DGTrainSMParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSMEManager
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureClassifier
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingPhyloHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior

Returns the instance name.

getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getInstanceParameterSets() - Method in enum de.jstacs.data.AlphabetContainer.AlphabetContainerType

This method returns a LinkedList of
 InstanceParameterSets which can be used to create
 Alphabets that can be used in a AlphabetContainer of
 the given AlphabetContainer.AlphabetContainerType.

getInstanceParameterSets(Class<T>, String) - Static method in class de.jstacs.utils.SubclassFinder

This method returns a list of InstanceParameterSets that can be used to create a subclass of clazz.

getInternalCosts() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts

Returns the internal costs (supplied as c to AffineCosts.AffineCosts(double, Costs)) used for matches and mismatches.

getInternalPosition(int[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM

Copies the current value of the internal iterator in the given array.

getIntFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the int which is the value of the Parameter
 par.

getIterations() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

Returns the number of independent re-starts in the training.

getK() - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet

Returns the number of mutually exclusive random-splits of user supplied
 data defined by this KFoldCrossValidationAssessParameterSet.

getKLDivergence(double[][][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the KL-divergence of the distribution of this BNDiffSMParameterTree and the distribution given by
 ds.

getKLDivergence(double[], double[][][][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the KL-divergence of the distribution of this BNDiffSMParameterTree and a number of distribution given by
 ds and weighted by weight

getKLDivergence(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester

Returns the Kullback-Leibler-divergence D(p_m1||p_m2).

getKmereSequenceStatistic(int, boolean, int, DataSet...) - Static method in class de.jstacs.motifDiscovery.KMereStatistic

This method enables the user to get a statistic over all k-mers
 in the sequences.

getKmereSequenceStatistic(boolean, int, HashSet<Sequence>, DataSet...) - Static method in class de.jstacs.motifDiscovery.KMereStatistic

This method enables the user to get a statistic for a set of k-mers.

getLabel(String[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns a label for the state.

getLambda(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint

Returns the value of .

getLastContextState() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

Returns the last state of the context

getLastContextState(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLastContextState(int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

The method returns the index of the state of the context, if there is no context -1 is returned.

getLastScore() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

Returns the score that was computed in the last optimization of the
 parameters.

getLeaves() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns all leaves of this cluster tree as ClusterTree objects comprising just the corresponding
 leaf element

getLegalName(String) - Static method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Returns a legal variable name in Galaxy

getLength() - Method in class de.jstacs.algorithms.alignment.StringAlignment

This method return the length of the alignment.

getLength() - Method in class de.jstacs.classifiers.AbstractClassifier

Returns the length of the sequences this classifier can handle or
 0 for sequences of arbitrary length.

getLength() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength

Returns the length of this LocatedSequenceAnnotationWithLength as
 given in the constructor.

getLength() - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getLength() - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getLength() - Method in class de.jstacs.data.sequences.ByteSequence
 
getLength() - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor
 
getLength() - Method in class de.jstacs.data.sequences.IntSequence
 
getLength() - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
 
getLength() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
getLength() - Method in class de.jstacs.data.sequences.PermutedSequence
 
getLength() - Method in class de.jstacs.data.sequences.Sequence.CompositeSequence
 
getLength() - Method in class de.jstacs.data.sequences.Sequence

Returns the length of the Sequence.

getLength() - Method in class de.jstacs.data.sequences.Sequence.SubSequence
 
getLength() - Method in class de.jstacs.data.sequences.ShortSequence
 
getLength() - Method in class de.jstacs.data.sequences.SparseSequence
 
getLength() - Method in class de.jstacs.parameters.SequenceScoringParameterSet

Returns the length of the sequences the model can work on.

getLength() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLength() - Method in interface de.jstacs.sequenceScores.SequenceScore

Returns the length of sequences this instance can score.

getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
 
getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior

Returns the length that is supported by this prior.

getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior
 
getLengthArray(DifferentiableSequenceScore...) - Static method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS

This method provides an array of lengths that can be used for instance as IndependentProductDiffSS.partialLength.

getLengthOfBurnIn() - Method in class de.jstacs.sampling.AbstractBurnInTest
 
getLengthOfBurnIn() - Method in interface de.jstacs.sampling.BurnInTest

Computes and returns the length of the burn-in phase using the values
 from BurnInTest.setValue(double).

getLengthOfBurnIn() - Method in class de.jstacs.sampling.SimpleBurnInTest

Deprecated.
 
getLengthOfModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM

This method returns the length of the models in the
 CompositeTrainSM.

getLine(int) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult

Return the line with a given index from the table.

getLineEps() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet

This method returns the threshold that should be used for stopping the line search during the optimization.

getLink() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.LinkedImageResult

Returns the linked file

getList() - Method in class de.jstacs.parameters.RangeParameter

Returns a list of all parameter values as a String or
 null if no parameter values have been set.

getLnFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb

Returns the logarithmic frequency at a given position
 index.

getLnFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb

Returns the logarithm of the relative frequency (=probability) at
 position index in the distribution.

getLnFreq(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb

Returns the logarithm of the relative frequency (=probability) with the
 position in the distribution given by the index of the specific
 constraint that is fulfilled by the Sequence s
 beginning at start.

getLocalScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the score for the symbol at this BNDiffSMParameterTree starting
 from offset i

getLog() - Method in class de.jstacs.tools.ui.cli.CLI.SysProtocol

Returns the StringBuffer containing all messages since the creation of this
 object.

getLogCDF(double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.CDFOfNormal

This method computes the logarithm of the cumulative density function of a standard normal distribution.

getLogGammaScoreForCurrentStatistic() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SamplingState

This method calculates a score for the current statistics, which is independent from the current parameters

 In general the gamma-score is a product of gamma-functions parameterized with the current statistics

getLogGammaScoreForCurrentStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogGammaScoreFromStatistic() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SamplingEmission

This method calculates a score for the current statistics, which is independent from the current parameters

 In general the gamma-score is a product of gamma-functions parameterized with the current statistics

getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method calculates a score for the current statistics, which is independent from the current parameters

 In general the gamma-score is a product of gamma-functions parameterized with the current statistics

getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
 
getLogGammaScoreFromStatistic() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.TransitionWithSufficientStatistic

This method calculates a score for the current statistics, which is independent from the current parameters

 In general the gamma-score is a product of gamma-functions parameterized with the current statistics

getLogGammaSum(Constraint, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.ConstraintManager

Computes the sum of differences of the logarithmic values of the prior knowledge and all counts.

getLogLikelihood(StatisticalModel, DataSet) - Static method in class de.jstacs.utils.StatisticalModelTester

Returns the log-likelihood of a DataSet data for a
 given model m.

getLogLikelihood(StatisticalModel, DataSet, double[]) - Static method in class de.jstacs.utils.StatisticalModelTester

Returns the log-likelihood of a DataSet data for a
 given model m.

getLogLikelihoodRatio(Sequence) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier

Returns the log likelihood ratios along the sequence seq for all
 sliding windows of length AbstractClassifier.getLength().

getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogNormalizationConstant() - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel

Returns the logarithm of the sum of the scores over all sequences of the event space.

getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogNormalizationConstant(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM

This method returns the logarithm of the normalization constant for a given sequence
 length.

getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

Computes the logarithm of the normalization constant for the component i.

getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getLogNumberOfPossibleOriginalSequences() - Method in class de.jstacs.data.sequences.MappedDiscreteSequence

This method returns the logarithm of the number of original Sequences that yield the same mapped Sequence.

getLogNumberOfPossibleOriginalSequences(int, int) - Method in class de.jstacs.data.sequences.MappedDiscreteSequence

This method returns the logarithm of the number of original Sequences that yield the same mapped Sequence.

getLogNumberOfSimilarSymbols(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabetMapping

This method returns the logarithm of the number of old values that yield the same new value.

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogPartialNormalizationConstant(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel

Returns the logarithm of the partial normalization constant for the parameter with index
 parameterIndex.

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM

This method returns the logarithm of the partial normalization constant for a given
 parameter index and a sequence length.

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogPartialNormalizer() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the partial derivative of the normalization constant with respect
 to this parameter.

getLogPosteriorFromStatistic() - Method in interface de.jstacs.sampling.SamplingFromStatistic

This method calculates the a-posteriori probability for the current statistics

getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

This method calculates the a posteriori probability for the current statistics

getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement

This method computes the log posterior from the internal sufficient statistic.

getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getLogPriorForPositions(int, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior

Returns only the important part and leaving the logarithm of the
 normalization constant out.

getLogPriorForPositions(int, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior

The logarithmic value of the prior for specified start positions of the
 part motifs.

getLogPriorForPositions(int, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior
 
getLogPriorPart(double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM

This method compute the prior for the current parameter ignoring some constants.

getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel

This method computes a value that is proportional to

getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel

Returns a value that is proportional to the log of the prior.

getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission

Returns a value that is proportional to the log of the prior.

getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

Returns a value that is proportional to the log of the prior.

getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

Returns a value that is proportional to the log of the prior.

getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getLogPriorTermForComponentProbs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method computes the part of the prior that comes from the component
 probabilities.

getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission

Returns the logarithmic score for a Sequence beginning at
 position start in the Sequence and fills lists with
 the indices and the partial derivations.

getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogProbFor(Sequence, int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel

Returns the logarithm of the probability of (a part of) the given
 sequence given the model.

getLogProbFor(Sequence, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel

Returns the logarithm of the probability of (a part of) the given
 sequence given the model.

getLogProbFor(Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel

Returns the logarithm of the probability of the given sequence given the
 model.

getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission

This method computes the logarithm of the likelihood.

getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getLogProbFor(int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns the logarithmic probability for the sequence and the given
 component.

getLogProbFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns the logarithmic probability for the sequence between start and end and the given
 component.

getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getLogProbForPath(IntList, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getLogProbForPath(IntList, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogProbForPath(IntList, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns the logarithmic probability for the sequence and the given
 component using the current parameter set.

getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
 
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.StrandTrainSM
 
getLogProposalPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission

Returns the log posterior of the proposal distribution for the current statistic

getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM

This method enables the user to get the log-score without using a sequence object.

getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

Returns the logarithmic score for a Sequence seq and
 fills lists with the indices and the partial derivations.

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

Returns the logarithmic score for a Sequence beginning at
 position start in the Sequence and fills lists with
 the indices and the partial derivations.

getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

Returns the logarithmic score for a Sequence beginning at
 position start in the Sequence and fills lists with
 the indices and the partial derivations.

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM

This method enables the user to get the log-score and the partial derivations without using a sequence object.

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM
 
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreAndPartialDerivation(int, int, IntList, DoubleList, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.DifferentiableState

This method allows to compute the logarithm of the score and the gradient for the given subsequences.

getLogScoreAndPartialDerivation(int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleDifferentiableState
 
getLogScoreAndPartialDerivation(int, int, int, IntList, DoubleList, Sequence, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.DifferentiableTransition

This method allows to compute the logarithm of the score and the gradient for a specific transition.

getLogScoreAndPartialDerivation(int, IntList, DoubleList, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement

Returns the logarithmic score and fills lists with
 the indices and the partial derivations.

getLogScoreAndPartialDerivation(int, int, int, IntList, DoubleList, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getLogScoreAndPartialDerivationForInternal(IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM

This method enables the user to get the log-score and the partial derivations without using a sequence object by using the internal iterator.

getLogScoreFor(Sequence) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getLogScoreFor(Sequence) - Method in interface de.jstacs.sequenceScores.SequenceScore

Returns the logarithmic score for the Sequence seq.

getLogScoreFor(Sequence, int) - Method in interface de.jstacs.sequenceScores.SequenceScore

Returns the logarithmic score for the Sequence seq
 beginning at position start in the Sequence.

getLogScoreFor(Sequence, int, int) - Method in interface de.jstacs.sequenceScores.SequenceScore

Returns the logarithmic score for the Sequence seq
 beginning at position start in the Sequence.

getLogScoreFor(DataSet) - Method in interface de.jstacs.sequenceScores.SequenceScore

This method computes the logarithm of the scores of all sequences
 in the given data set.

getLogScoreFor(DataSet, double[]) - Method in interface de.jstacs.sequenceScores.SequenceScore

This method computes and stores the logarithm of the scores for
 any sequence in the data set in the given double-array.

getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM
 
getLogScoreFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM

Returns the logarithmic score for the sequence beginning at start.

getLogScoreFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogScoreFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState
 
getLogScoreFor(int, int, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.State

This method returns the logarithm of the score for a given sequence with given start and end position.

getLogScoreFor(int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the score for the transition from the current context to the state with index index.

getLogScoreFor(int, int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLogScoreFor(int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
 
getLogScoreFor(int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
 
getLogScoreFor(int, int, int, Sequence, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns the logarithm of the score for the transition.

getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getLogScoreForInternal() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM

This method enables the user to get the log-score without using a sequence object by using the internal iterator.

getLogStatePosteriorMatrixFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns the log state posterior of all states for a sequence.

getLogStatePosteriorMatrixFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns the log state posteriors for all sequences of the data set data.

getLogStatePosteriorMatrixFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getLogSum(double...) - Static method in class de.jstacs.utils.Normalisation

Returns the logarithm of the sum of values val[i] given as
 lnVal[i] = Math.log( val[i] ).

getLogSum(int, int, double...) - Static method in class de.jstacs.utils.Normalisation

Returns the logarithm of the sum of values v[i] given as
 lnVal[i] = Math.log( val[i] ) between a start and end index.

getLogT() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the part of the normalization constant of parameters before this
 parameter in the structure of the network.

getLogZ() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the part of the normalization constant of parameters after this
 parameter in the structure of the network.

getLongFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the long which is the value of the Parameter
 par.

getLowerBound() - Method in class de.jstacs.parameters.validation.NumberValidator

Returns the lower bound of the NumberValidator.

getMarginalDistribution(StatisticalModel, int[]...) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the marginal distribution for any discrete model
 m and all sequences that fulfill the constraint
 , if possible.

getMarginalOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns the marginal order, i.e.

getMatrixForKruskal(double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Prepares a matrix of pairwise association measures for the implementation of Kruskal's algorithm.

getMax() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet

Returns the maximal value of this alphabet.

getMax() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

Returns the maximal value that can be scored.

getMax(double[][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater

This method can be used to determine the maximal value of the matrix of
 mutual informations.

getMaximalAlphabetLength() - Method in class de.jstacs.data.AlphabetContainer

Returns the maximal Alphabet length of this
 AlphabetContainer.

getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SubTensor
 
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor

Returns the edge
 permute(parents[0],...,parents[k-1]) -> child that maximizes
 the score.

getMaximalElementLength() - Method in class de.jstacs.data.DataSet

Returns the maximal length of an element, i.e.

getMaximalInDegree() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getMaximalInDegree() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns the maximal out degree of any context used in this transition instance.

getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the maximal Markov order of this tree.

getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM

Returns the maximal used markov oder.

getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getMaximalMarkovOrder() - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel

This method returns the maximal used Markov order, if possible.

getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getMaximalMarkovOrder() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns the maximal used Markov order.

getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getMaximalNumberOfChildren() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getMaximalNumberOfChildren() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns the maximal number of children for any context used in this transition instance.

getMaximalSymbolLength() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet

Returns the length of the longest "symbol" in the alphabet.

getMaximumDistance() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the maximum distance of trees under this root node.

getMaximumScore() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

Returns the maximum score of this BayesianNetworkDiffSM returned for a
 admissible input sequence.

getMaximumScore() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the maximum score in this tree.

getMaxIndex() - Method in class de.jstacs.utils.DoubleList

Returns the index of the first value that is equal to the maximal value.

getMaxIndex(double[]) - Static method in class de.jstacs.utils.ToolBox

Returns the index with maximal value in a double array.

getMaxIndex(int, int, double[]) - Static method in class de.jstacs.utils.ToolBox

Returns the index with maximal value in a double array.

getMaxOfDeviation(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the maximum deviation between the probabilities for
 all sequences of length for discrete models m1
 and m2.

getMeanParameters(boolean, int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Returns the mean parameters over all samplings of all stationary phases.

getMeasure(double, double, double, double) - Method in class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
 
getMeasure(double, double, double, double) - Method in class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
 
getMeasure(double, double, double, double) - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure

This measure compute the measure for a given confusion matrix

getMeasure() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet

Returns the structure Measure defined by this set of parameters.

getMeasureName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
 
getMeasureName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
 
getMeasureName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure

This method returns a short name of the measure without any parameters.

getMI(double[][][][][][], double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Computes the mutual information from counts counted on
 sequences with a total weight of n.

getMI(double[][][][], double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Computes the mutual information from counts counted on
 sequences with a total weight of n.

getMI(DataSet, double[]) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater

This method computes the pairwise mutual information between
 the sequence positions.

getMIInBits(DataSet, double[]) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater

This method computes the pairwise mutual information (in bits) between
 the sequence positions.

getMime() - Method in class de.jstacs.results.TextResult

Returns the mime type of this TextResult.

getMin(int) - Method in class de.jstacs.data.AlphabetContainer

Returns the minimal value of the underlying Alphabet of position
 pos.

getMin() - Method in class de.jstacs.data.alphabets.Alphabet

Returns the minimal value of theAlphabet.

getMin() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
 
getMin() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
 
getMin() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

Returns the minimal value that can be scored.

getMinimalAlphabetLength() - Method in class de.jstacs.data.AlphabetContainer

Returns the minimal Alphabet length of this
 AlphabetContainer.

getMinimalElementLength() - Method in class de.jstacs.data.DataSet

Returns the minimal length of an element, i.e.

getMinimalHyperparameter() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement

This method returns the minimal hyper parameters of this TransitionElement.

getMinimalSequenceLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture

Returns the minimal length a sequence respectively a data set has to have.

getMinimalSequenceLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getMinimumDistance() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the minimum distance of trees under this root node.

getMinimumOriginalIndex() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the minimum original index in this cluster tree.

getMinIndex() - Method in class de.jstacs.utils.DoubleList

Returns the index of the first value that is equal to the minimal value.

getMinIndex(double[]) - Static method in class de.jstacs.utils.ToolBox

Returns the index with minimum value in a double array.

getMinIndex(int, int, double[]) - Static method in class de.jstacs.utils.ToolBox

Returns the index with minimum value in a double array.

getMixtureProbabilities() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Returns the probabilities of the mixture components.

getModel(int) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier

Returns a clone of the TrainableStatisticalModel for a specified class.

getModel(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns a deep copy of the i-th model.

getModelInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet

This method returns a short description of the model.

getModelInstanceName(StructureLearner.ModelType, byte, StructureLearner.LearningType, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.IDGTrainSMParameterSet

This method returns a short textual representation of the model instance.

getModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM

Returns the a deep copy of the models.

getModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns a deep copy of the models.

getMostProbableSequence(SequenceScore, int) - Static method in class de.jstacs.utils.StatisticalModelTester

Returns one most probable sequence for the discrete model m.

getMotifDiscoverer() - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method returns a clone of the internally used MotifDiscoverer.

getMotifLength(int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

This method returns the length of the motif with index motif
 .

getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getMRG() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method creates the multivariate random generator that will be used
 during initialization.

getMRGParams() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method creates the parameters used in a multivariate random
 generator while initialization.

getMultiClassScores(DataSet[]) - Method in class de.jstacs.classifiers.AbstractClassifier

This method returns a multidimensional array with class specific scores.

getMultiClassScores(DataSet[]) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getName() - Method in class de.jstacs.AnnotatedEntity

Returns the name of the AnnotatedEntity.

getName() - Method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.AucPR
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.AucROC
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.ClassificationRate
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.ConfusionMatrix
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.CorrelationCoefficient
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.FalsePositiveRateForFixedSensitivity
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure
 
getName() - Method in interface de.jstacs.classifiers.performanceMeasures.PerformanceMeasure

The method returns the name of the performance measure.

getName() - Method in class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.PRCurve
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.ROCCurve
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.SensitivityForFixedSpecificity
 
getName() - Method in interface de.jstacs.clustering.hierachical.PWMSupplier

Returns a name (e.g., an identifier from a database) for the PWM.

getName(Class<? extends ParameterSet>) - Static method in class de.jstacs.parameters.ParameterSet

Returns a name for the class.

getName(ParameterSet) - Static method in class de.jstacs.parameters.ParameterSet

Returns a name for the ParameterSet.

getName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState

Returns the name of the state.

getName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
 
getName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode

This method returns the name of the current instance

getName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree

This method returns the name of the PhyloTree

getName() - Method in class de.jstacs.tools.JstacsTool.ResultEntry

Returns the name of the result.

getNameOfAlgorithm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns the name of the used algorithm.

getNameOfAssessment() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment

Returns the name of this class.

getNames() - Method in class de.jstacs.AnnotatedEntityList

Returns the names of all AnnotatedEntitys in the list.

getNames() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

Returns a clone of the state names.

getNewAlphabet() - Method in class de.jstacs.data.alphabets.DiscreteAlphabetMapping

Returns the new Alphabet that is used for mapping.

getNewAlphabetContainer(AlphabetContainer, DiscreteAlphabetMapping...) - Static method in class de.jstacs.data.sequences.MappedDiscreteSequence

This method allows to create a new AlphabetContainer given an old AlphabetContainer and some DiscreteAlphabetMappings.

getNewComponentProbs(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Estimates the weights of each component.

getNewDiscreteValue(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabetMapping

This method implements the main transformation of the values.

getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
 
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
 
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior

This method returns an empty new instance of the current prior.

getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior
 
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
 
getNewParameters(int, double[][], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture
 
getNewParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

This method set all parameters for the next sampling step

getNewParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingPhyloHMM
 
getNewParameters(int, double[][], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method trains the internal models on the internal data set and the
 given weights.

getNewParameters(int, double[][], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
 
getNewParametersForModel(int, int, int, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method trains the internal model with index modelIndex
 on the internal data set and the given weights.

getNewStartDistance() - Method in class de.jstacs.algorithms.optimization.ConstantStartDistance
 
getNewStartDistance() - Method in class de.jstacs.algorithms.optimization.LimitedMedianStartDistance
 
getNewStartDistance() - Method in interface de.jstacs.algorithms.optimization.StartDistanceForecaster

This method returns the new positive start distance.

getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Computes sequence weights and returns the score.

getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM

Computes sequence weights and returns the score.

getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.StrandTrainSM

Computes sequence weights and returns the score.

getNextContext(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the next context that will be visited when visiting the child with index index.

getNextLine(boolean) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.LineBasedResult

Returns the next line of the result

getNiceMax() - Method in class de.jstacs.utils.NiceScale

Returns the "nice" maximum value

getNiceMin() - Method in class de.jstacs.utils.NiceScale

Returns the "nice" minimum value

getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
 
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getNodeLabel(double, String, NumberFormat) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission

Returns the graphviz label of the node containing this emission.

getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getNodeShape(boolean) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission

Returns the graphviz string for the shape of the node.

getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getNormalizedVersion(DifferentiableStatisticalModel, int) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM

This method returns a normalized version of a DifferentiableStatisticalModel.

getNucleicAcid() - Method in enum de.jstacs.data.DinucleotideProperty

Returns the kind of nucleic acid, e.g.

getNumberOfAlignedSequences() - Method in class de.jstacs.algorithms.alignment.StringAlignment

Returns the number of sequences in this alignment.

getNumberOfAllNodesBelow() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode

This method returns the total number of PhyloNodes in the subtree starting from this instance

getNumberOfAlphabets() - Method in class de.jstacs.data.AlphabetContainer

This method returns the number of Alphabets used in the current AlphabetContainer.

getNumberOfAvailableProcessors() - Static method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction

This method returns the number of available processors.

getNumberOfBoundSequences(DataSet, double[], int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

Returns the number of sequences in data that are predicted to be bound at least once by motif no.

getNumberOfChildren() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the number of states that can be visited.

getNumberOfChildren(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getNumberOfChildren(int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns the number of children states for given index, i.e.

getNumberOfClasses() - Method in class de.jstacs.classifiers.AbstractClassifier

Returns the number of classes that can be distinguished.

getNumberOfClasses() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getNumberOfClasses(PerformanceMeasure[]) - Static method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasureParameterSet

Returns the number of classes the PerformanceMeasures in measures
 can be applied to.

getNumberOfCombinations(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.CombinationIterator

Returns the number of possible combinations.

getNumberOfComponents() - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the number of components in this MotifDiscoverer.

getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

Returns the number of different components of this
 AbstractMixtureDiffSM.

getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns the number of components the are modeled by this
 AbstractMixtureTrainSM.

getNumberOfElements() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the number of leaves in this cluster tree.

getNumberOfElements() - Method in class de.jstacs.data.DataSet

Returns the number of elements, i.e.

getNumberOfElements() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory

Returns the number of elements, i.e.

getNumberOfElements() - Method in class de.jstacs.io.StringExtractor

Returns the number of Strings that have been read.

getNumberOfElementsWithLength(int) - Method in class de.jstacs.data.DataSet

Returns the number of overlapping elements that can be extracted.

getNumberOfElementsWithLength(int, double[]) - Method in class de.jstacs.data.DataSet

Returns the weighted number of overlapping elements that can be extracted.

getNumberOfIndexes(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getNumberOfIndexes(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method computes the number of different indexes for a given layer of the matrix.

getNumberOfLines() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult

Returns the number of lines in this table.

getNumberOfMatches() - Method in class de.jstacs.algorithms.alignment.PairwiseStringAlignment

Returns the number of matches in this alignment.

getNumberOfModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM

This method returns the number of models in the CompositeTrainSM.

getNumberOfMotifs() - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the number of motifs for this MotifDiscoverer.

getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getNumberOfMotifsInComponent(int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the number of motifs that are used in the component
 component of this MotifDiscoverer.

getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getNumberOfNexts(int) - Method in class de.jstacs.parameters.MultiSelectionParameter

Returns the number of calls of
 MultiSelectionParameter.next() that can be called
 before false is returned.

getNumberOfNexts(int) - Method in class de.jstacs.parameters.RangeParameter

Returns the number of calls of RangeParameter.next() that can be done before
 obtaining false.

getNumberOfNodes() - Method in class de.jstacs.algorithms.graphs.tensor.Tensor

Returns the number of nodes.

getNumberOfNodes() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree

This method returns the total number of nodes in the tree

getNumberOfParameters() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Returns the number of parameters of all internal SamplingDifferentiableStatisticalModels.

getNumberOfParameters() - Method in class de.jstacs.parameters.ArrayParameterSet
 
getNumberOfParameters() - Method in class de.jstacs.parameters.ParameterSet

Returns the number of parameters in the ParameterSet.

getNumberOfParameters() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
 
getNumberOfParameters() - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

Returns the number of parameters in this DifferentiableSequenceScore.

getNumberOfParameters() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getNumberOfParameters() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission

Returns the number of parameters of this emission.

getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the number of parameters in this transition element.

getNumberOfParameterSets(int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier.DiffSMSamplingComponent

Returns the number of parameters set that can be retrieved from an internal file which has been creating while previous training.

getNumberOfParents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the number of parents for the random variable of this
 BNDiffSMParameterTree in the network structure of the enclosing
 BayesianNetworkDiffSM.

getNumberOfPossibilities() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

Returns the number of different possibilities that can be scored.

getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getNumberOfRecommendedStarts() - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore

This method returns the number of recommended optimization starts.

getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getNumberOfResults() - Method in class de.jstacs.results.ResultSet

Returns the number of Results in this ResultSet

getNumberOfResultSets() - Method in class de.jstacs.results.ListResult

Returns the number of ResultSets in this ListResult

getNumberOfSequenceAnnotationsByType(String) - Method in class de.jstacs.data.sequences.Sequence

Returns the number of SequenceAnnotations of type type for this Sequence.

getNumberOfSequences() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence

This method returns the number of internal sequences.

getNumberOfSequences() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.SequenceIterator

This method returns the number of sequences in this iterator,
 i.e., the number of times SequenceIterator.next() returns true after using SequenceIterator.reset().

getNumberOfSpecificConstraints() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns the number of specific constraints.

getNumberOfStarts() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet

Returns the number of independent sampling starts

getNumberOfStarts() - Method in class de.jstacs.sampling.AbstractBurnInTestParameterSet

Returns the number of starts.

getNumberOfStarts(DifferentiableSequenceScore[]) - Static method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore

Returns the number of recommended starts in a numerical optimization.

getNumberOfStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet

The method returns the number of different starts.

getNumberOfStates() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns the number of the (hidden) states

getNumberOfStates() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getNumberOfStates() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method returns the number of states underlying this transition
 instance.

getNumberOfStationarySamplings() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet

Returns the number of samplings steps in the stationary phase

getNumberOfStepsInStationaryPhase() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.SamplingHMMTrainingParameterSet

The method returns the number of steps to be done in the stationary phase.

getNumberOfStepsPerIteration() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.SamplingHMMTrainingParameterSet

This method returns the number of steps to be done in each start before testing for the end of the burn in phase (again).

getNumberOfTestSamplings() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet

Returns the number of samplings between checks for the stationary phase

getNumberOfThreads() - Method in interface de.jstacs.algorithms.optimization.MultiThreadedFunction

Returns the number of used threads for evaluating the function and for determining the gradient of the function.

getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction

Returns the number of used threads for evaluating the function and for determining the gradient of the function.

getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier

This method returns the number of used threads while optimization.

getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet

This method returns the number of threads that should be used during optimization.

getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifierParameterSet

Returns the number of threads for evaluating the LogGenDisMixFunction

getNumberOfThreads() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns the number of threads that is internally used.

getNumberOfThreads() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MultiThreadedTrainingParameterSet

This method returns the number of threads that should be used during optimization.

getNumberOfValues() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
getNumberOfValues() - Method in interface de.jstacs.parameters.RangeIterator

Returns the number of values in the collection.

getNumberOfValues() - Method in class de.jstacs.parameters.RangeParameter

Returns the number of values in a list or range of parameter values.

getNumericalCharacteristics() - Method in class de.jstacs.classifiers.AbstractClassifier

Returns the subset of numerical values that are also returned by
 AbstractClassifier.getCharacteristics().

getNumericalCharacteristics() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.MappingClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getNumericalCharacteristics() - Method in interface de.jstacs.sequenceScores.SequenceScore

Returns the subset of numerical values that are also returned by
 SequenceScore.getCharacteristics().

getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getOffsetForAucPR() - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method returns an offset that must be added to scores for computing PR curves.

getOptimalBranching(double[][], double[][], byte) - Static method in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds

Returns an optimal branching.

getOrder() - Method in class de.jstacs.algorithms.graphs.tensor.Tensor

Returns the order.

getOrder() - Method in enum de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder.RandomSeqType

This method returns the Markov order.

getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM

Returns the order of the inhomogeneous Markov model.

getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov

Returns the order of the Markov model as defined in the constructor

getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet

Returns the order of the InhomogeneousMarkov structure
 measure as defined by this set of parameters.

getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet

Returns the order defined by this set of parameters.

getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet

Returns the order defined by this set of parameters.

getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Returns the order of the Slim model

getOriginal() - Method in class de.jstacs.data.sequences.Sequence.SubSequence

Returns the original sequence, this sequence is a sub-sequence of.

getOriginalIndex() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the original index of the root node of this cluster tree

getOriginalName() - Method in class de.jstacs.results.Result

Returns the original name (i.e., the name upon object creation) of this Result, 
 which may be just the name if Result.rename(String) has not been called on this object, yet.

getOutfilePrefix() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet

Returns the prefix of the temporary files for storing sampled
 parameter values

getOutput(byte[], double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb

This method is used to create random sequences.

getOutputStream() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol

Returns the ByteArrayOutputStream of this protocol

getOutputStream() - Method in class de.jstacs.utils.SafeOutputStream

Returns the internal used OutputStream.

getPairwiseDistanceMatrix(DistanceMetric<T>, T...) - Static method in class de.jstacs.clustering.distances.DistanceMetric

Returns the matrix of all pairwise distance of the supplied objects, where rows and colums are indexed in the order
 of the supplied objects.

getPairwiseDistanceMatrix(int, StatisticalModel...) - Method in class de.jstacs.clustering.distances.SequenceScoreDistance

Multi-threaded computation of the pairwise distance matrix.

getParameterAt(int) - Method in class de.jstacs.parameters.ArrayParameterSet
 
getParameterAt(int) - Method in class de.jstacs.parameters.ParameterSet

Returns the Parameter at position i.

getParameterAt(int) - Method in class de.jstacs.parameters.SequenceScoringParameterSet
 
getParameterFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the BNDiffSMParameter that is responsible for the suffix of
 sequence seq starting at position start.

getParameterFor(int[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the BNDiffSMParameter that is responsible for the suffix of
 sequence seq starting at position start.

getParameterForName(String) - Method in class de.jstacs.parameters.ParameterSet

Returns the Parameter with name name.

getParameterFromTag(String) - Method in class de.jstacs.parameters.ParameterSetTagger

This method returns the Parameter specified by the tag

getParameterIndexesForSamplingStep(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the indexes of the parameters, incremented by offset, that
 shall be sampled in step step of a grouped sampling process.

getParameters(OptimizableFunction.KindOfParameter, double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction

This method enables the user to get the parameters without creating a new
 array.

getParameters(OptimizableFunction.KindOfParameter) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
 
getParameters(OptimizableFunction.KindOfParameter, double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
 
getParameters(OptimizableFunction.KindOfParameter) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction

Returns some parameters that can be used for instance as start
 parameters.

getParameterSetContainingASingleDoubleValue(double) - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet

Creates a new ParameterSet containing a single
 double-SimpleParameter.

getParameterSetFor(Class<? extends InstantiableFromParameterSet>) - Static method in class de.jstacs.utils.SubclassFinder

Returns a LinkedList of the classes of the
 InstanceParameterSets that can be used to instantiate the
 sub-class of InstantiableFromParameterSet that is given by
 clazz

getParametersInCollection() - Method in class de.jstacs.parameters.AbstractSelectionParameter

Returns the possible values in this collection.

getParent() - Method in class de.jstacs.parameters.Parameter

Returns a reference to the ParameterSet enclosing this
 Parameter.

getParent() - Method in class de.jstacs.parameters.ParameterSet

Returns the enclosing Parameter of this
 ParameterSet or null if none exists.

getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Returns the optimal parents for the given data and weights.

getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
 
getParser() - Method in class de.jstacs.results.DataSetResult

Returns the SequenceAnnotationParser that can be used to
 write this DataSetResult including annotations on the contained Sequences
 to a file.

getPartialDataSet(int, int) - Method in class de.jstacs.data.DataSet

Returns a new DataSet that contains all elements of this DataSet that are specified
 by the supplied start (inclusive) and end (exclusive) indexes.

getPartialDataSet(int[]...) - Method in class de.jstacs.data.DataSet

Returns a new DataSet that contains all elements of this DataSet that are specified
 by the supplied pairs of start and end indexes in indexes.

getPartialLengths() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS

This method returns a deep copy of the internally used partial lengths of the parts.

getPath() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult

Returns the path of the directory containing the file

getPercent() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet

Returns the percentage of user supplied data that is used in each
 iteration as test data set.

getPercentage() - Method in class de.jstacs.tools.ProgressUpdater

Returns the percentage of a tool's work that has been completed so far.

getPercents() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet

Returns an array containing for each class the percentage of user
 supplied data that is used in each iteration as test dataset.

getPFM() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM

Returns a deep copy of the internal PFM.

getPFM(DataSet) - Static method in class de.jstacs.utils.PFMComparator

This method creates a PFM from a DataSet of Sequences.

getPFM(DataSet, int, int) - Static method in class de.jstacs.utils.PFMComparator

Returns a position frequency matrix (PFM, rows=positions, columns=symbols) for the given subset of DataSet.

getPFM(DataSet, double[]) - Static method in class de.jstacs.utils.PFMComparator

This method creates a PFM from a DataSet of Sequences.

getPlotCommands(REnvironment, String, AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult

This method copies the data to the server side and creates a
 StringBuffer containing the plot commands.

getPlotCommands(REnvironment, String, int[], AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult

This method copies the data to the server side and creates a
 StringBuffer containing the plot commands.

getPlotCommands(REnvironment, String, String[], AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult

This method copies the data to the server side and creates a
 StringBuffer containing the plot commands.

getPlugInParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet

Returns true if plug-in parameters shall be used when creating a
 BayesianNetworkDiffSM from this set of parameters.

getPosition() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation

Returns the position of this LocatedSequenceAnnotation on the
 sequence.

getPosition() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the position of the symbol this parameter is responsible for as
 defined in the constructor.

getPosition(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns the position with index index.

getPositionDependentKMerProb(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

Returns the probability of kmer for all possible positions in this BayesianNetworkDiffSM starting at position kmer.getLength()-1.

getPositionForParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

Returns the position in the sequence the parameter index is
 responsible for.

getPositions() - Method in class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint

Returns a clone of the internal positions.

getPositions() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns a clone of the array of used positions.

getPossibleLength(TrainableStatisticalModel...) - Static method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier

This method returns the possible length of a classifier that would use
 the given TrainableStatisticalModels.

getPossibleLength() - Method in class de.jstacs.data.AlphabetContainer.AbstractAlphabetContainerParameterSet

Returns the length of the AlphabetContainer that can be instantiated using
 this ParameterSet.

getPossibleLength() - Method in class de.jstacs.data.AlphabetContainer

Returns the possible length for Sequences using this
 AlphabetContainer.

getPossibleLength() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
getPossibleLength() - Method in class de.jstacs.data.alphabets.DNAAlphabetContainer.DNAAlphabetContainerParameterSet
 
getProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Returns the probability of Sequence sequence in this BNDiffSMParameterTree.

getProbsForComponent(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

Returns the probabilities for each component given a Sequence.

getProducer() - Method in class de.jstacs.results.TextResult

Returns the producer (i.e., the tool/application/program) that created this TextResult.

getProfile(StatisticalModel, boolean) - Method in class de.jstacs.clustering.distances.RandomSequenceScoreDistance
 
getProfile(StatisticalModel, boolean) - Method in class de.jstacs.clustering.distances.SequenceScoreDistance

Returns the score profile for the model.

getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the profile of the scores for component component
 and motif motif at all possible start positions of the motif
 in the sequence sequence beginning at startpos.

getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getProfilesForMotif(StatisticalModel, int, boolean, boolean) - Static method in class de.jstacs.clustering.distances.DeBruijnMotifComparison

Returns the score profile on a De Bruin sequence for a De Bruijn sequence.

getProfilesForMotif(CyclicSequenceAdaptor[], StatisticalModel, boolean, boolean) - Static method in class de.jstacs.clustering.distances.DeBruijnMotifComparison

Returns the score profile on a De Bruin sequence for a De Bruijn sequence.

getProperty(Sequence, DinucleotideProperty.Smoothing) - Method in enum de.jstacs.data.DinucleotideProperty

Computes this dinucleotide property for all overlapping twomers in original, smoothes the result using smoothing,
 and returns the smoothed property as a double array.

getProperty(Sequence, int) - Method in enum de.jstacs.data.DinucleotideProperty
 
getProperty(Sequence) - Method in enum de.jstacs.data.DinucleotideProperty

Computes this dinucleotide property for all overlapping twomers in original
 and returns the result as a double array of length original.getLength()-1

getPropertyAsSequence(Sequence) - Method in enum de.jstacs.data.DinucleotideProperty

Computes this dinucleotide property for all overlapping dimers in original
 and returns the result as a Sequence of length original.getLength()-1

getPropertyAsSequence(Sequence, DinucleotideProperty.Smoothing) - Method in enum de.jstacs.data.DinucleotideProperty

Computes this dinucleotide property for all overlapping dimers in original, smoothes the result using smoothing,
 and returns the smoothed property as a Sequence.

getPropertyImage(Sequence, DinucleotideProperty, DinucleotideProperty.Smoothing, REnvironment, int, String, int, int) - Static method in enum de.jstacs.data.DinucleotideProperty
 
getPropertyImage(DataSet, DinucleotideProperty, DinucleotideProperty.Smoothing, REnvironment, int, String, int, int) - Static method in enum de.jstacs.data.DinucleotideProperty
 
getProtocol(boolean) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Returns an object for writing a protocol of a program run

getPseudoCount() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the pseudocount as given in the constructor.

getPubMedID() - Method in enum de.jstacs.data.DinucleotideProperty

Returns the PubMed ID of the publication where the parameters of this property has been published.

getPValue(Sequence, DataSet) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier

Returns the p-value for a Sequence candidate with
 respect to a given background DataSet.

getPValue(DataSet, DataSet) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier

Returns the p-values for all Sequences in the DataSet
 candidates with respect to a given background DataSet
 .

getPValue(double[], double) - Static method in class de.jstacs.classifiers.utils.PValueComputation

This method searches for the insertion point of the score in a given
 sorted array of scores and returns the p-value for this score.

getPValue(double[], double, int) - Static method in class de.jstacs.classifiers.utils.PValueComputation

This method searches for the insertion point of the score in a given
 sorted array of scores from index start and returns the
 p-value for this score.

getPWM() - Method in interface de.jstacs.clustering.hierachical.PWMSupplier

Returns the position weight matrix.

getPWM(int, DataSet, double[], int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

Returns the Position weight matrix (PWM) of the binding sites of motif motif 
 in the data set data of the MotifDiscoverer of this SignificantMotifOccurrencesFinder.

getPWM() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

If this BayesianNetworkDiffSM is a PWM, i.e.

getPWM() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
 
getPWM(DataSet, int, int) - Static method in class de.jstacs.utils.PFMComparator

Returns a position weight matrix (PWM, rows=positions, columns=symbols, containing probabilities) for the given subset of DataSet.

getPWMAndPosDist(int, DataSet, double[], double[], int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

Returns the Position weight matrix (PWM) of the binding sites of motif motif 
 in the data set data of the MotifDiscoverer of this SignificantMotifOccurrencesFinder
 together with standard deviation of binding site positions computed using the provided mean values for each sequence.

getPWMAndPosDist(int, DataSet, double[], double[], int, int, LinkedList<Sequence>, DoubleList, DoubleList) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

Returns the position weight matrix and standard deviation of the position distribution using the given mean.

getPWMAndPositions(int, DataSet, double[], int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

Returns the Position weight matrix (PWM) of the binding sites of motif motif 
 in the data set data of the MotifDiscoverer of this SignificantMotifOccurrencesFinder
 together with the positions of the binding sites within the sequences of data and the corresponding p-values.

getPWMAndPositions(int, DataSet, double[], int, int, int[][], double[][], double[], double[], LinkedList<Sequence>, DoubleList, DoubleList) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

Returns the Position weight matrix (PWM) of the binding sites of motif motif 
 in the data set data of the MotifDiscoverer of this SignificantMotifOccurrencesFinder
 and fills with the positions of the binding sites within the sequences of data and the corresponding p-values into the corresponding arrays.

getPWMParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Returns the unconditional, normalized (PWM) probabilities of this Slim model

getRandomSequence(Random, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getRandomSequence(Random, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM

This method creates a random Sequence from a trained homogeneous
 model.

getRangedInstance() - Method in class de.jstacs.parameters.AbstractSelectionParameter
 
getRangedInstance() - Method in interface de.jstacs.parameters.Rangeable

Returns an instance of RangeIterator that has the same properties
 as the current instance, but accepts a range or list of values.

getRangedInstance() - Method in class de.jstacs.parameters.SimpleParameter
 
getRawResult() - Method in class de.jstacs.results.ListResult

Returns a copy of the internal list of ResultSets.

getReference() - Method in enum de.jstacs.data.DinucleotideProperty

Returns the reference of the publication where the parameters of this property has been published.

getReferenceClass() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet

Returns the index of the reference class.

getReferenceSequence() - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotation

Returns the reference sequence.

getReferenceSequence(Sequence) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.ReferenceSequenceDiscreteEmission

Returns the reference sequence annotated to seq.

getRegEx() - Method in class de.jstacs.io.RegExFilenameFilter

Returns a representation of all used regular expressions.

getRepeats() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet

Returns the repeats defined by this
 RepeatedHoldOutAssessParameterSet (repeats define how many
 iterations (train and test classifiers) of that
 RepeatedHoldOutExperiment this
 RepeatedHoldOutAssessParameterSet is used with are performed).

getRepeats() - Method in class de.jstacs.classifiers.assessment.RepeatedSubSamplingAssessParameterSet

Returns the repeats defined by this
 RepeatedSubSamplingAssessParameterSet (repeats defines how many
 iterations (train and test classifiers) of that
 RepeatedSubSamplingExperiment this
 RepeatedSubSamplingAssessParameterSet is used with are
 performed).

getRepeats() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet

Returns the repeats defined by this
 Sampled_RepeatedHoldOutAssessParameterSet (repeats defines how
 many iterations (train and test classifiers) of that
 Sampled_RepeatedHoldOutExperiment this
 Sampled_RepeatedHoldOutAssessParameterSet is used with are
 performed).

getResultAt(int) - Method in class de.jstacs.results.NumericalResultSet
 
getResultAt(int) - Method in class de.jstacs.results.ResultSet

Returns Result number index in this
 ResultSet.

getResultForName(String) - Method in class de.jstacs.results.ResultSet

Returns Result with name name in this
 ResultSet.

getResultInstance() - Method in class de.jstacs.results.StorableResult

Returns the instance of the Storable that is the result of this
 StorableResult.

getResults(LinkedList, DataSet[], double[][], AbstractPerformanceMeasureParameterSet<? extends PerformanceMeasure>, boolean) - Method in class de.jstacs.classifiers.AbstractClassifier

This method computes the results for any evaluation of the classifier.

getResults(LinkedList, DataSet[], double[][], AbstractPerformanceMeasureParameterSet<? extends PerformanceMeasure>, boolean) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getResults(LinkedList, DataSet[], double[][], AbstractPerformanceMeasureParameterSet<? extends PerformanceMeasure>, boolean) - Method in class de.jstacs.classifiers.MappingClassifier
 
getResults() - Method in class de.jstacs.results.ResultSet

Returns all internal results as an array of Results.

getReverseComplement(ComplementableDiscreteAlphabet, double[][]) - Static method in class de.jstacs.utils.PFMComparator

This method returns the PFM that is the reverse complement of the given PFM.

getReverseComplementaryDataSet() - Method in class de.jstacs.data.DataSet

Returns a DataSet that contains the reverse complement of all Sequences in
 this DataSet.

getReverseComplementDistributions(ComplementableDiscreteAlphabet, double[][][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM

This method computes the reverse complement distributions for given conditional distributions.

getReverseSwitches() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS

This method returns a deep copy of the internally used switches for the parts whether to use the corresponding
 DifferentiableSequenceScore forward or as reverse complement.

getRNotation(String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

This method returns the distribution in R notation.

getRNotation(String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getRNotation(String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getRNotation(String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getRoot() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree

This method returns the root node of the tree

getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.SubTensor
 
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor

Returns the value for child as root.

getRunTimeException(Exception) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method creates an RuntimeException from any other Exception

getSafeOutputStream(OutputStream) - Static method in class de.jstacs.utils.SafeOutputStream

This method returns an instance of SafeOutputStream for a given OutputStream.

getSamplingComponent() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Returns a sampling component suited for this SamplingScoreBasedClassifier

getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getSamplingGroups(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.SamplingDifferentiableStatisticalModel

Returns groups of indexes of parameters that shall be drawn
 together in a sampling procedure

getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getSamplingScheme() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet

Returns the sampling scheme

getSaver(Class<? extends T>) - Static method in class de.jstacs.results.savers.ResultSaverLibrary

Returns the most suitable ResultSaver (if any) currently registered in the library.

getScale() - Method in class de.jstacs.parameters.RangeParameter

Returns a description of the the scale of a range of parameter values.

getScatterplot(AbstractScoreBasedClassifier, AbstractScoreBasedClassifier, DataSet, DataSet, REnvironment, boolean) - Static method in class de.jstacs.classifiers.utils.ClassificationVisualizer

This method returns an ImageResult containing a scatter plot of
 the scores for the given classifiers cl1 and
 cl2.

getScore(Tensor, int[][]) - Static method in class de.jstacs.algorithms.graphs.DAG

Returns the score for any graph.

getScore(Sequence, int) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier

This method returns the score for a given Sequence and a given
 class.

getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier

This method returns the score for a given Sequence and a given
 class.

getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.MappingClassifier
 
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM

Returns the score for the sequence beginning at start.

getScoreForBestRun() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

Returns the value of the optimized function from the best run of the last
 training.

getScoreForPath(Tensor, int, byte, int[]) - Static method in class de.jstacs.algorithms.graphs.DAG

Returns the score for a given path path using the first
 l nodes and dependencies of order k.

getScores(DataSet) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier

This method returns the scores of the classifier for any Sequence
 in the DataSet.

getScores(DataSet) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getScores(DataSet) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getSecondElement() - Method in class de.jstacs.utils.Pair

This method returns the second element.

getSelected() - Method in class de.jstacs.parameters.MultiSelectionParameter

Returns the indexes of the selected options.

getSelected() - Method in class de.jstacs.parameters.SelectionParameter

Returns the index of the selected value.

getSelectionParameter(Class<? extends ParameterSet>, String, String, String, boolean) - Static method in class de.jstacs.utils.SubclassFinder

This method creates an SelectionParameter that contains
 InstanceParameterSet for each possible
 class.

getSequence(int) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence

This method returns the internal sequence with index index.

getSequenceAnnotationByType(String, int) - Method in class de.jstacs.data.sequences.Sequence

Returns the SequenceAnnotation no.

getSequenceAnnotationByTypeAndIdentifier(String, String) - Method in class de.jstacs.data.sequences.Sequence

Returns the SequenceAnnotation of this Sequence that has type type and identifier identifier.

getSequenceAnnotationIndexMatrix(String, Hashtable<String, Integer>, String, Hashtable<String, Integer>) - Method in class de.jstacs.data.DataSet

This method creates a matrix which contains the index of the Sequence with specific SequenceAnnotation
 combination or -1 if the DataSet does not contain any Sequence with such a combination.

getSequenceWeights() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
 
getSequenceWeights() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction

Returns the weights for each Sequence for each
 class used in this OptimizableFunction.

getShannonEntropy(StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the Shannon entropy for any discrete model
 m and all sequences of length, if possible.

getShannonEntropyInBits(StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the Shannon entropy in bits for any discrete model
 m and all sequences of length, if possible.

getShortFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the short which is the value of the
 Parameter par.

getShortName() - Method in interface de.jstacs.tools.JstacsTool

Returns a name (preferably short and without spaces) for referring to this tool on the command line.

getSimplifiedAlphabetContainer(Alphabet[], int[]) - Static method in class de.jstacs.data.AlphabetContainer

This method creates a new AlphabetContainer that uses as less as
 possible Alphabets to describe the container.

getSingelton(Class<? extends Singleton>) - Static method in class de.jstacs.Singleton.SingletonHandler

This method helps to retrieve the single instance of a Singleton singletonClass.

getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getSizeOfEventSpace() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission

Returns the size of the event space, i.e., the number of possible outcomes,
 for the random variables of this emission

getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getSizeOfEventSpace(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.DifferentiableTransition

Returns the size of the event space, i.e., the number of possible outcomes,
 for the random variable of parameter index

getSizeOfEventSpace(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel

Returns the size of the event space of the random variables that are
 affected by parameter no.

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getSmoothedProfile(int, String...) - Method in class de.jstacs.motifDiscovery.KMereStatistic

This method returns an array of smoothed profiles.

getSmoothedProfile(int, Sequence...) - Method in class de.jstacs.motifDiscovery.KMereStatistic

This method returns an array of smoothed profiles.

getSortedInitialParameters(DifferentiableSequenceScore[], MutableMotifDiscovererToolbox.InitMethodForDiffSM[], DiffSSBasedOptimizableFunction, int, OutputStream, int) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox

This method allows to initialize the DifferentiableSequenceScore using different MutableMotifDiscovererToolbox.InitMethodForDiffSM.

getSortedScoresForMotifAndFlanking(DataSet, DataSet, String) - Static method in class de.jstacs.motifDiscovery.MotifDiscoveryAssessment

Returns the scores read from the prediction pred for the motif with identifier identifier and flanking sequences as annotated in
 the DataSet data.

getSortedValuesForMotifAndFlanking(DataSet, double[][], double, double, String) - Static method in class de.jstacs.motifDiscovery.MotifDiscoveryAssessment

This method provides some score arrays that can be used in AbstractPerformanceMeasure to determine some
 curves or area under curves based on the values of the predictions.

getSpecificName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
 
getSpecificName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
 
getSpecificName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure

This method returns a specific name of the measure including any parameters.

getStart() - Method in class de.jstacs.data.sequences.Sequence.SubSequence

Returns the start of this sub-sequence in the original sequence.

getStartDistance() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet

This method returns the start distance that should be used in the line search during the optimization.

getStartIndexOfAlignmentForFirst() - Method in class de.jstacs.algorithms.alignment.PairwiseStringAlignment

This method returns the start index of the alignment in the first sequence.

getStartNode() - Method in class de.jstacs.algorithms.graphs.Edge

Returns the start node of the edge.

getStartPositions(int, DataSet, int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method returns a list of start positions of binding sites.

getStartValue() - Method in class de.jstacs.parameters.RangeParameter

Returns the start value of a range of parameter values or
 null if no range was specified.

getStatePosteriorMatrixFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns the log state posterior of all states for a sequence.

getStatePosteriorMatrixFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns the state posteriors for all sequences of the data set data.

getStationaryDistribution(double[], int) - Static method in class de.jstacs.utils.StationaryDistribution

This method return the stationary distribution.

getStatistics() - Method in class de.jstacs.results.MeanResultSet

Returns the means and (if possible the) standard errors of the results in
 this MeanResultSet as a new NumericalResultSet.

getStatistics(DataSet, double[], int, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Counts the occurrences of symbols of the AlphabetContainer of
 DataSet s using weights.

getStatisticsOrderTwo(DataSet, double[], int, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Counts the occurrences of symbols of the AlphabetContainer of
 DataSet s using weights.

getSteps() - Method in class de.jstacs.parameters.RangeParameter

Returns the number of steps of a range of parameter values or
 0 if no range was specified.

getStoreAll() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet

Returns the flag for storing all performance measures in each iteration defined by this
 ClassifierAssessmentAssessParameterSet.

getStrand(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM

This method returns the preferred StrandedLocatedSequenceAnnotationWithLength.Strand for a given subsequence.

getStrand(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM

This method return the preferred StrandedLocatedSequenceAnnotationWithLength.Strand for a Sequence beginning at startPos.

getStrandedness() - Method in class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength

Returns the strandedness, i.e the orientation of this annotation.

getStrandProbabilitiesFor(int, int, Sequence, int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

This method returns the probabilities of the strand orientations for a given subsequence if it is
 considered as site of the motif model in a specific component.

getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getStringFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser

Returns the String which is the value of the Parameter
 par.

getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.Sequence

This method creates a String representation from the given representation.

getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
 
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhomogeneousDGTrainSM

Returns a String representation of the underlying graph.

getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
 
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture

Returns a String representation of the structure of the used
 models.

getStructure(DataSet, double[], StructureLearner.ModelType, byte, StructureLearner.LearningType) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner

This method finds the optimal structure of a model by using a given
 learning method (in some sense).

getStructure(Tensor, StructureLearner.ModelType, byte) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner

This method can be used to determine the optimal structure of a model.

getStructureFromPath(int[], Tensor) - Static method in class de.jstacs.algorithms.graphs.DAG

Extracts the structure from a given path path and
 score-"function".

getSubAnnotations() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation

Returns the sub-annotations of this SequenceAnnotation as given
 in the constructor.

getSubContainer(int, int) - Method in class de.jstacs.data.AlphabetContainer

Returns a sub-container with the Alphabets for the positions
 starting at start and with length length.

getSubSequence(AlphabetContainer, int) - Method in class de.jstacs.data.sequences.Sequence

This method should be used if one wants to create a DataSet of
 subsequences of defined length.

getSubSequence(AlphabetContainer, int, int) - Method in class de.jstacs.data.sequences.Sequence

This method should be used if one wants to create a DataSet of
 subsequences of defined length.

getSubSequence(int) - Method in class de.jstacs.data.sequences.Sequence

This is a very efficient way to create a subsequence/suffix for
 Sequences with a simple AlphabetContainer.

getSubSequence(int, int) - Method in class de.jstacs.data.sequences.Sequence

This is a very efficient way to create a subsequence of defined length
 for Sequences with a simple AlphabetContainer.

getSubTrees() - Method in class de.jstacs.clustering.hierachical.ClusterTree

Returns the sub-trees of this cluster tree root node

getSuffixDataSet(int) - Method in class de.jstacs.data.DataSet

This method enables you to use only a suffix of all elements, i.e.

getSumOfDeviation(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the sum of deviations between the probabilities for
 all sequences of length for discrete models m1
 and m2.

getSumOfDistribution(StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the marginal distribution for any discrete model
 m and all sequences of length, if possible.

getSumOfHyperparameter() - Method in class de.jstacs.utils.random.DirichletMRGParams

Returns the sum of the hyperparameters (entries of the hyperparameter
 vector) of the underlying Dirichlet distribution.

getSumOfHyperparameter() - Method in class de.jstacs.utils.random.ErlangMRGParams

Returns the sum of the hyperparameters (entries of the hyperparameter
 vector) of the underlying Erlang distribution.

getSumOfHyperParameters(int, int, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM

This method returns an array that can be used in the constructor
 HomogeneousMMDiffSM.HomogeneousMMDiffSM(AlphabetContainer, int, double, double[], boolean, boolean, int)
 containing the sums of the specific hyper-parameters.

getSumOfWeights() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory

Returns the sum of all weights.

getSuperClassOf(T...) - Static method in class de.jstacs.io.ArrayHandler

This method returns the deepest class in the class hierarchy that is the
 class or a superclass of all instances in the array.

getSuperSequence(int) - Method in class de.jstacs.data.sequences.CyclicSequenceAdaptor

Returns a new cyclic sequence using the internal sequence of this CyclicSequenceAdaptor but with 
 the supplied virtual length

getSymbol(int, double) - Method in class de.jstacs.data.AlphabetContainer

Returns a String representation of the encoded symbol
 val of the Alphabet of position pos of
 this AlphabetContainer.

getSymbolAt(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet

Returns the symbol at position i in the alphabet.

getSymKLDivergence(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester

Returns the difference of the Kullback-Leibler-divergences, i.e.

getTempDir() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Returns the directory for parameter files set in this SamplingScoreBasedClassifier.

getTensor(DataSet, double[], byte, StructureLearner.LearningType) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner

This method can be used to compute a Tensor that can be used to
 determine the optimal structure.

getTerminantionCondition() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifierParameterSet

This method returns the AbstractTerminationCondition for stopping the training, e.g., if the
 difference of the scores between two iterations is smaller than a given
 threshold the training is stopped.

getTerminationCondition() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MaxHMMTrainingParameterSet

This method returns the AbstractTerminationCondition for stopping the training, e.g., if the
 difference of the scores between two iterations is smaller than a given
 threshold the training is stopped.

getThreads() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor

Returns the number of threads given by the Galaxy configuration

getThreshold(double[], int) - Static method in class de.jstacs.classifiers.utils.PValueComputation

This method returns the threshold that determines if an observed score is
 significant.

getThreshold() - Method in class de.jstacs.sampling.VarianceRatioBurnInTestParameterSet

Returns the threshold used in the VarianceRatioBurnInTestParameterSet.

getTickSpacing() - Method in class de.jstacs.utils.NiceScale

Returns the spacing between the tick marks

getTimeInstance(OutputStream) - Static method in class de.jstacs.utils.Time

This method tries to return a UserTime instance, if not possible (due to native code) it returns a RealTime instance.

getToolName() - Method in interface de.jstacs.tools.JstacsTool

Returns a descriptive, human readable name for this tool.

getToolName() - Method in class de.jstacs.tools.ToolResult

Returns the name of the tool (see JstacsTool.getToolName()) used to create these results.

getToolParameters() - Method in interface de.jstacs.tools.JstacsTool

Returns the input parameters of this tool.

getToolParameters() - Method in class de.jstacs.tools.ToolResult

Returns the tool's parameters that have been used to create the results stored in this ToolResult.

getToolVersion() - Method in interface de.jstacs.tools.JstacsTool

Returns a descriptive, human readable version for this tool.

getTopologicalOrder(int[][]) - Static method in class de.jstacs.algorithms.graphs.TopSort

Returns the topological order of indexes according to
 parents2.

getTopologicalOrder2(byte[][]) - Static method in class de.jstacs.algorithms.graphs.TopSort

Computes a topological ordering for a given graph.

getTrain_TestNumbers(boolean) - Method in class de.jstacs.classifiers.assessment.RepeatedSubSamplingAssessParameterSet

Returns an array containing the number of elements the subsampled (train
 | test) data sets should consist of.

getTrainingParams() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

Returns a clone of the training parameters

getTransisionElements() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

Returns the transition elements of the internal Transition.

getTransisionElements() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition

Returns a clone of the internal transition elements.

getTransitionElementIndex(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition

This method return the index of the BasicHigherOrderTransition.AbstractTransitionElement using the BasicHigherOrderTransition.lookup table.

getTrueIndexForLastGetBest() - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor

Returns the edge from SymmetricTensor.getBest(int, int[], byte) in an encoded
 index.

getType() - Method in class de.jstacs.data.AlphabetContainer

Returns the type of this AlphabetContainer.

getType() - Method in enum de.jstacs.data.DinucleotideProperty

Returns the type of this property.

getType() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation

Returns the type of this SequenceAnnotation as given in the
 constructor.

getUniqueHueValues(int) - Static method in class de.jstacs.utils.ToolBox

Creates an array of hue values that can be used for the representation
 of probabilities.

getValidator() - Method in class de.jstacs.parameters.SimpleParameter

Returns the ParameterValidator used in this
 SimpleParameter.

getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SubTensor
 
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor

Returns the value for the edge
 parents[0],...,parents[k-1] -> child.

getValue() - Method in class de.jstacs.AnnotatedEntity

Returns the value of the AnnotatedEntity.

getValue() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
 
getValue() - Method in class de.jstacs.parameters.EnumParameter
 
getValue() - Method in class de.jstacs.parameters.FileParameter
 
getValue() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
getValue() - Method in class de.jstacs.parameters.ParameterSetContainer
 
getValue() - Method in class de.jstacs.parameters.RangeParameter
 
getValue() - Method in class de.jstacs.parameters.SelectionParameter
 
getValue() - Method in class de.jstacs.parameters.SimpleParameter
 
getValue() - Method in class de.jstacs.results.DataSetResult
 
getValue() - Method in class de.jstacs.results.ImageResult
 
getValue() - Method in class de.jstacs.results.ListResult
 
getValue() - Method in class de.jstacs.results.PlotGeneratorResult
 
getValue() - Method in class de.jstacs.results.SimpleResult
 
getValue() - Method in class de.jstacs.results.StorableResult
 
getValue() - Method in class de.jstacs.results.TextResult
 
getValue(Sequence, int) - Method in interface de.jstacs.sequenceScores.differentiable.logistic.LogisticConstraint

This method returns the value f(seq) used in LogisticDiffSS

getValue(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
 
getValue() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter

Returns the current value of this parameter.

getValue() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult
 
getValueFor(String) - Method in class de.jstacs.parameters.MultiSelectionParameter

Returns the value for the option with key key.

getValueFor(int) - Method in class de.jstacs.parameters.MultiSelectionParameter

Returns the value of the option with no.

getValueFromTag(String) - Method in class de.jstacs.parameters.ParameterSetTagger

This method returns the value of the Parameter specified by the tag.

getValueFromTag(String, Class<T>) - Method in class de.jstacs.parameters.ParameterSetTagger

This method returns the casted value of the Parameter specified by the tag.

getValueOfAIC(StatisticalModel, DataSet, int) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the value of Akaikes Information Criterion (AIC).

getValueOfBIC(StatisticalModel, DataSet, int) - Static method in class de.jstacs.utils.StatisticalModelTester

This method computes the value of the Bayesian Information Criterion
 (BIC).

getValues() - Method in class de.jstacs.parameters.MultiSelectionParameter

Returns the values of all selected options as an array.

getValuesForEachNucleotide(DataSet, int, boolean) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method determines a score for each possible starting position in each of the sequences in data 
 that this position is covered by at least one motif occurrence of the
 motif with index index.

getValuesFromSequence(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM

This method extracts the values form a sequence.

getVersionInformation() - Method in class de.jstacs.utils.REnvironment

Returns information about the version of R that is used.

getViterbiPath(int, int, Sequence, SamplingHigherOrderHMM.ViterbiComputation) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

This method returns a viterbi path that is the optimum for the choosen ViterbiComputation method

getViterbiPathFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getViterbiPathFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getViterbiPathFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getViterbiPathFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getViterbiPathsFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method returns the viterbi paths and scores for all sequences of the data set data.

getWeight() - Method in class de.jstacs.algorithms.graphs.Edge

Returns the weight of the edge.

getWeight(double[], int) - Static method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure

Returns the weight at index in weight or 1 if weight is null.

getWeight(int) - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory

Returns the weight for the Sequence with index
 index.

getWeight() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode

This method return the weight (length, rate ...) for the incoming edge

getWeight() - Method in class de.jstacs.utils.ComparableElement

This method returns the weight of the element.

getWeights() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory

Returns a copy of the weights for the DataSet.

getWeights() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method returns a deep copy of the weights for each component.

getWidth(int, double[][]) - Static method in class de.jstacs.utils.SeqLogoPlotter

Returns the automatically chosen width for a given height and position weight matrix.

getWidth(int, int) - Static method in class de.jstacs.utils.SeqLogoPlotter

Returns the width of a sequence logo of the given height for a PWM with the given number of columns.

getWriter() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol

Returns the PrintWriter of this protocol

getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition

Deprecated.
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition

This method returns the xml tag that is used in the method AbstractTerminationCondition.toXML() and
 in the constructor AbstractTerminationCondition.AbstractTerminationCondition(StringBuffer).

getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.CombinedCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.IterationCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.SmallGradientConditon
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.SmallStepCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.TimeCondition
 
getXMLTag() - Method in class de.jstacs.AnnotatedEntity

This method returns a tag used as outer tag of the XML description.

getXMLTag() - Method in class de.jstacs.classifiers.AbstractClassifier

Returns the String that is used as tag for the XML representation
 of the classifier.

getXMLTag() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.MappingClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getXMLTag() - Method in class de.jstacs.parameters.FileParameter
 
getXMLTag() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
getXMLTag() - Method in class de.jstacs.parameters.ParameterSetContainer
 
getXMLTag() - Method in class de.jstacs.parameters.RangeParameter
 
getXMLTag() - Method in class de.jstacs.parameters.SelectionParameter
 
getXMLTag() - Method in class de.jstacs.parameters.SimpleParameter
 
getXMLTag() - Method in class de.jstacs.results.CategoricalResult
 
getXMLTag() - Method in class de.jstacs.results.DataSetResult
 
getXMLTag() - Method in class de.jstacs.results.ImageResult
 
getXMLTag() - Method in class de.jstacs.results.ListResult
 
getXMLTag() - Method in class de.jstacs.results.NumericalResult
 
getXMLTag() - Method in class de.jstacs.results.PlotGeneratorResult
 
getXMLTag() - Method in class de.jstacs.results.StorableResult
 
getXMLTag() - Method in class de.jstacs.results.TextResult
 
getXMLTag() - Method in class de.jstacs.sampling.AbstractBurnInTest

This method returns the XML tag that is used in
 AbstractBurnInTest.toXML() and
 AbstractBurnInTest.AbstractBurnInTest(StringBuffer).

getXMLTag() - Method in class de.jstacs.sampling.VarianceRatioBurnInTest
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Returns the XML-tag for storing this measure

getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This method returns the XML tag of the instance that is used to build a
 XML representation.

getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint

Returns the XML tag that is used for the class to en- or decode.

getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM

Returns the XML tag that is used for this model in
 DiscreteGraphicalTrainSM.fromXML(StringBuffer) and DiscreteGraphicalTrainSM.toXML().

getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSMEManager
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

Returns the tag for the XML representation.

getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

This method returns the xml tag used in BasicHigherOrderTransition.AbstractTransitionElement.toXML().

getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition

The method returns the XML tag used during saving and loading the transition.

getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicPluginTransitionElement
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getXMLTag() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult
 
getXMLTag() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.LinkedImageResult
 
gibbsSampling(int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

This method implements a sampling step in the sampling procedure

GibbsSamplingModel - Interface in de.jstacs.sampling

This is the interface that any AbstractTrainableStatisticalModel has to implement if it
 should be used in a sampling.

gibbsSamplingStep(int, int, boolean, DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

This method implements the next step(s) in the sampling procedure

GIS - Static variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools

This constant can be used to specify that the model should use the iterative scaling for
 training.

goldenRatio(OneDimensionalFunction, double, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer

Approximates a minimum (not necessary the global) in the interval
 [lower,upper].

goldenRatio(OneDimensionalFunction, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer

Approximates a minimum (not necessary the global) in the interval
 [lower,upper].

grad - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission

The array for storing the gradients for
 each parameter

gradient - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM

Help array for the gradient

graphics - Variable in class de.jstacs.utils.graphics.EPSAdaptor

The EPS document

graphics - Variable in class de.jstacs.utils.graphics.RasterizedAdaptor

The graphics object used for plotting

graphics - Variable in class de.jstacs.utils.graphics.SVGAdaptor

The internal graphics object

GraphicsAdaptor - Class in de.jstacs.utils.graphics

Generic class for different adaptors for plotting graphics to a file
 using different graphics formats.

GraphicsAdaptor() - Constructor for class de.jstacs.utils.graphics.GraphicsAdaptor
 
GraphicsAdaptorFactory - Class in de.jstacs.utils.graphics

Factory class for GraphicsAdaptors

GraphicsAdaptorFactory() - Constructor for class de.jstacs.utils.graphics.GraphicsAdaptorFactory
 
GraphicsAdaptorFactory.OutputFormat - Enum in de.jstacs.utils.graphics

The allowed output formats

GT - Static variable in interface de.jstacs.parameters.validation.Constraint

The condition is greater than

GUIProgressUpdater - Class in de.jstacs.utils

This class implements a ProgressUpdater with a GUI.

GUIProgressUpdater(boolean) - Constructor for class de.jstacs.utils.GUIProgressUpdater

This is the constructor for a GUIProgressUpdater.


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