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

G

GaussianLikePositionPrior - Class in de.jstacs.models.mixture.motif.positionprior

This class implements a gaussian like discrete truncated prior.

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

The standard constructor for the interface Storable.

GenDisMixClassifier - Class in de.jstacs.classifier.scoringFunctionBased.gendismix

This class implements a classifier the optimizes the following function

The weights have to sum to 1.

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double[], ScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

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

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double[], NormalizableScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

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

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double[], NormalizableScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

The main constructor.

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double, double, NormalizableScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

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

GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, LearningPrinciple, NormalizableScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.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.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

This is the constructor for Storable.

GenDisMixClassifierParameterSet - Class in de.jstacs.classifier.scoringFunctionBased.gendismix

This class contains the parameters for the GenDisMixClassifier.

GenDisMixClassifierParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.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.classifier.scoringFunctionBased.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.classifier.scoringFunctionBased.gendismix.GenDisMixClassifierParameterSet

The default constructor that constructs a new GenDisMixClassifierParameterSet.

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.

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

The condition is greater or equal

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(Sample, 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(Sample, int, boolean, Sample.WeightedSampleFactory.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 MIME-type of the allowed files.

getAdditionalInformation() - Method in class de.jstacs.models.mixture.motif.positionprior.GaussianLikePositionPrior

getAdditionalInformation() - Method in class de.jstacs.models.mixture.motif.positionprior.PositionPrior

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

getAdditionalInformation() - Method in class de.jstacs.models.mixture.motif.positionprior.UniformPositionPrior

getAlignment() - Method in class de.jstacs.algorithms.Alignment

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

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

This method returns the conditional stationary distributions, i.e. for a homogeneous Markov model of order 2 it returns an array containing the stationary symbol distribution as first entry, the conditional stationary distribution of order 1 as second entry and the conditional distribution of order 2 as third entry.

getAllConditionalStationaryDistributions() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

This method returns the stationary conditional distributions.

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

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

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

Returns the underlying Alphabet of position pos.

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

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

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

Returns the AlphabetContainer of this Sample.

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

Return the alphabets, i.e. the AlphabetContainer, used in this Sequence.CompositeSequence.

getAlphabetContainer() - Method in class de.jstacs.models.AbstractModel

getAlphabetContainer() - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner

This method returns the AlphabetContainer of the StructureLearner.

getAlphabetContainer() - Method in interface de.jstacs.models.Model

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

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

Returns the AlphabetContainer of the current instance.

getAlphabetContainer() - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

getAlphabetContainer() - Method in interface de.jstacs.scoringFunctions.ScoringFunction

Returns the AlphabetContainer for this ScoringFunction.

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

Returns the length of the underlying Alphabet of position pos.

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

Returns a Collection of parameters containing informations about this ClassifierAssessmentAssessParameterSet.

getAnnotation() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet

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

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

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

getAnnotation() - Method in class de.jstacs.classifier.MeasureParameters

Returns the selected parameters and their values as a LinkedList of Results.

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

Returns the annotation for an array of Samples.

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

Returns some annotation of the Sample.

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

Returns the annotation of the Sequence.CompositeSequence.

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.

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

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

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

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

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

Returns the index for an asymmetric tensor.

getAUC_PR(double[], double[], AbstractList<double[]>) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method computes the area under the precision recall curve.

getAUC_ROC(double[], double[], AbstractList<double[]>) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method computes the area under the receiver operator characteristics curve.

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.

getBeta(LearningPrinciple) - Static method in enum de.jstacs.classifier.scoringFunctionBased.gendismix.LearningPrinciple

This method returns the standard weights for a predefined key.

getBindingSites(Sample) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method returns a Sample containing the predicted binding sites.

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

This method returns a Sample containing the predicted binding sites.

getBooleanArrayWithTags(boolean[]) - Static method in class de.jstacs.io.XMLParser

Encodes a boolean array.

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.classifier.utils.PValueComputation

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

getByteArrayWithTags(byte[]) - Static method in class de.jstacs.io.XMLParser

Encodes a byte array.

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

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

getBytesFromFileOnServer(String, RConnection) - Static method in class de.jstacs.utils.RUtils

This method returns the content of a file on the server as byte array.

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

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

getCharacteristics() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getCharacteristics() - Method in class de.jstacs.models.AbstractModel

getCharacteristics() - Method in class de.jstacs.models.CompositeModel

getCharacteristics() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

getCharacteristics() - Method in interface de.jstacs.models.Model

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

getClassificationRate(Sample[]) - Method in class de.jstacs.classifier.AbstractClassifier

This method computes the classification rate for a given array of samples.

getClassificationRate() - Method in class de.jstacs.classifier.ConfusionMatrix

This method returns the classification rate.

getClassificationRateFor2Classes(double[], double[]) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method computes the classification rate for two classes.

getClassifier() - Method in class de.jstacs.classifier.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.classifier.AbstractClassifier

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

getClassifierAnnotation() - Method in class de.jstacs.classifier.MappingClassifier

getClassifierAnnotation() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getClassifierAnnotation() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

getClassifierAnnotation() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier

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.

getClassOfParameterSet() - Method in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

getClassOfParameterSet() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

This method returns the class of the parameters that is used during restoring a classifier from XML.

getClassParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.SFBasedOptimizableFunction

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

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

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

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

Returns the specific class weights of a AbstractScoreBasedClassifier.

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

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

getCMI(double[][][][][][], double[][][][][][], double) - Static method in class de.jstacs.scoringFunctions.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.scoringFunctions.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.

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

This method creates an CollectionParameter that contains InstanceParameterSet for each possible class.

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

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

getCombination() - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator

Returns a clone of the internal combination.

getComment() - Method in class de.jstacs.parameters.CollectionParameter

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

getComment() - Method in class de.jstacs.parameters.Parameter

Returns a comment on this Parameter that tells something about useful values, domains, usage of this parameter, etc.

getComment() - Method in class de.jstacs.parameters.ParameterSetContainer

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

getComment() - Method in class de.jstacs.parameters.SimpleParameter

getComment() - Method in class de.jstacs.results.Result

Returns the comment on the Result.

getCommentString() - Method in enum de.jstacs.classifier.MeasureParameters.Measure

Returns a comment on the MeasureParameters.Measure.

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

This method returns an array of strings of length motifLength so that each String is contained in all sequences of the sample respectively in the sample and the reverse complementary sample.

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

getComponents() - Method in class de.jstacs.algorithms.graphs.UnionFind

Returns the connected components of the graph.

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

Returns an AlphabetContainer of Alphabets e.g. for composite motifs/sequences.

getCompositeSample(int[], int[]) - Method in class de.jstacs.data.Sample

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

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

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

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

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

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.

getCorrectedPosition(int) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint

Returns the value of the corrected position index.

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

Returns the costs.

getCostFor(Sequence, Sequence, int, int, Alignment.Costs.Direction) - Method in interface de.jstacs.algorithms.Alignment.Costs

Returns the costs for the alignment if s1(i) and s2(j) coming from from.

getCostFor(Sequence, Sequence, int, int, Alignment.Costs.Direction) - Method in class de.jstacs.algorithms.Alignment.SimpleCosts

getCount(int) - Method in class de.jstacs.models.discrete.Constraint

Returns the current count with index index.

getCounts() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

Returns the current counts for this parameter.

getCountsFor(int, int) - Method in class de.jstacs.classifier.ConfusionMatrix

This method returns the specific entry of the ConfusionMatrix.

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.data.AlphabetContainer

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

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.DNAAlphabet

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.models.discrete.DiscreteGraphicalModel

getCurrentParameterSet() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getCurrentParameterSet() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual

getCurrentParameterSet() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation

getCurrentParameterSet() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov

getCurrentParameterSet() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual

getCurrentParameterSet() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getCurrentParameterValues() - Method in interface de.jstacs.scoringFunctions.ScoringFunction

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

getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

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.classifier.scoringFunctionBased.AbstractOptimizableFunction

getData() - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction

Returns the data for each class used in this OptimizableFunction.

getDataSplitMethod() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet

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

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

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

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

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

getDatatype() - Method in class de.jstacs.parameters.CollectionParameter

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

getDatatype() - Method in class de.jstacs.parameters.Parameter

Returns the data type of the Parameter.

getDatatype() - Method in class de.jstacs.parameters.ParameterSetContainer

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

getDatatype() - Method in class de.jstacs.parameters.SimpleParameter

getDatatype() - Method in class de.jstacs.results.Result

Returns the data type of the Result.

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

Returns the index of the default selected value.

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

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

getDepth() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

Returns the depth of the tree, i.e. the number of parents of this parameter.

getDescription() - Method in class de.jstacs.io.RegExFilenameFilter

getDescription(AlphabetContainer, int) - Method in class de.jstacs.models.discrete.Constraint

Returns the decoded symbol for the encoded symbol i.

getDescription() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel

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.models.discrete.homogeneous.HomogeneousModel.HomCondProb

getDescription(AlphabetContainer, int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb

getDescription(AlphabetContainer, int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhConstraint

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.OneDimensionalFunction

getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.CompositeLogPrior

getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.DoesNothingLogPrior

getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior

getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior

getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior

getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.SFBasedOptimizableFunction

getDoubleArrayWithTags(double[]) - Static method in class de.jstacs.io.XMLParser

Encodes a double array.

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

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

getEAR(double[][][][][][], double[][][][][][], double, double) - Static method in class de.jstacs.scoringFunctions.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.scoringFunctions.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.Sample

This method returns the element, i.e. the Sequence, with index i.

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

Returns the Sequence with index index.

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

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

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

Returns the length of the elements, i.e. the Sequences, in this Sample.

getElongateCosts() - Method in interface de.jstacs.algorithms.Alignment.Costs

Returns the costs to elongate a gap by one position.

getElongateCosts() - Method in class de.jstacs.algorithms.Alignment.SimpleCosts

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

Returns the end of this LocatedSequenceAnnotationWithLength, i.e.

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.models.discrete.ConstraintManager

Tries to compute the entropy of a Constraint as exact as possible.

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

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.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.ReferenceConstraint

getErrorMessage() - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint

getErrorMessage() - Method in class de.jstacs.parameters.validation.StorableValidator

getESS() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel

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

getEss() - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner

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

getEss() - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet

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

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

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

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

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

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

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

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

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

getEss() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getEss() - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getEss() - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction

Returns the equivalent sample size (ess) of this model, i.e. the equivalent sample size for the class or component that is represented by this model.

getEss() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getEss() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

getExceptionIfMPNotComputable() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet

Returns the flag defined by this ClassifierAssessmentAssessParameterSet.

getExpLambda(int) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint

Returns the exponential value of at position index: .

getExpValue() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

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

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.

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

Returns the content of the file.

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

Returns the filename.

getFirst() - Method in class de.jstacs.algorithms.Alignment.StringAlignment

Returns the first String.

getFirstParent() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree

Returns the first parent of the random variable of this ParameterTree in the topological ordering of the network structure of the enclosing BayesianNetworkScoringFunction.

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

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

getFPRForSensitivity(double[], double[], double) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method computes the false positive rate (FPR) for a given sensitivity.

getFreq(int) - Method in class de.jstacs.models.discrete.Constraint

Returns the current frequency with index index.

getFreq(Sequence, int) - Method in class de.jstacs.models.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.models.discrete.inhomogeneous.MEMConstraint

getFreqInfo(AlphabetContainer) - Method in class de.jstacs.models.discrete.Constraint

Returns an information about the stored frequencies.

getFunction(Sample[], double[][]) - Method in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

getFunction(Sample[], double[][]) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

Returns the function that should be optimized.

getFunction() - Method in class de.jstacs.models.NormalizableScoringFunctionModel

Returns a copy of the internally used NormalizableScoringFunction.

getFunction(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

This method returns a specific internal function.

getFunction() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

This method returns the internal function.

getFunctions() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

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

getFunctions() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

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

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

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

getFurtherClassifierInfos() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier

getFurtherClassifierInfos() - Method in class de.jstacs.classifier.MappingClassifier

getFurtherClassifierInfos() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getFurtherClassifierInfos() - Method in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

getFurtherClassifierInfos() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

getFurtherClassifierInfos() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier

getFurtherInformation() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

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

getFurtherInformation() - Method in class de.jstacs.models.mixture.gibbssampling.AbstractBurnInTest

This method returns further information for the AbstractBurnInTest.

getFurtherInformation() - Method in class de.jstacs.models.mixture.gibbssampling.VarianceRatioBurnInTest

getFurtherInformation() - Method in class de.jstacs.models.mixture.motif.HiddenMotifMixture

getFurtherInformation() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

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

getFurtherInformation() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getFurtherInformation() - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

getFurtherModelInfos() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel

Returns further model information as a StringBuffer.

getFurtherModelInfos() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM

getFurtherModelInfos() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel

getFurtherModelInfos() - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling

getGapCostsFor(int) - Method in interface de.jstacs.algorithms.Alignment.Costs

Returns the costs for a gap of length length.

getGapCostsFor(int) - Method in class de.jstacs.algorithms.Alignment.SimpleCosts

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

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

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

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

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

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

getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

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.scoringFunctions.IndependentProductScoringFunction

getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

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

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

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.scoringFunctions.mix.AbstractMixtureScoringFunction

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

getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

getId() - Method in class de.jstacs.parameters.Parameter

Returns the id of this Parameter.

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

Returns the id of this ParameterSet.

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.models.discrete.inhomogeneous.TwoPointEvaluater

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

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.classifier.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.classifier.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.Sequence.CompositeSequence

getIndex(int) - Method in class de.jstacs.data.Sequence.SubSequence

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

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

Returns the index in the internal sequence.

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

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

getIndex(String[], Object[], Comparable, boolean) - Static method in class de.jstacs.parameters.SequenceScoringParameterSet

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

getIndex() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

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

getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

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

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.scoringFunctions.IndependentProductScoringFunction

getIndexOfMaximalComponentFor(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

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.scoringFunctions.mix.MixtureScoringFunction

getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getIndices() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

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

getIndices(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

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

getInfixSample(int, int) - Method in class de.jstacs.data.Sample

This method enables you to use only an infix of all elements, i.e. the Sequences, in the current Sample.

getInfos() - Method in class de.jstacs.results.MeanResultSet

Returns some information for this MeanResultSet.

getInitialClassParam(double) - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

getInitialClassParam(double) - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction

getInitialClassParam(double) - Method in interface de.jstacs.scoringFunctions.ScoringFunction

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

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.classifier.scoringFunctionBased.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.models.discrete.homogeneous.parameters.HomMMParameterSet

getInstanceComment() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet

getInstanceComment() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.FSDAGMParameterSet

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.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet

getInstanceComment() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet

getInstanceComment() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet

getInstanceComment() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet

getInstanceComment() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet

getInstanceComment() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet

getInstanceFromParameterSet(InstanceParameterSet) - 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) - 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.classifier.AbstractClassifier

Returns a short description of the classifier.

getInstanceName() - Method in class de.jstacs.classifier.MappingClassifier

getInstanceName() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.CompositeLogPrior

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.DoesNothingLogPrior

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior

Returns a short instance name.

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.msp.MSPClassifier

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet

getInstanceName() - Method in class de.jstacs.data.Alphabet.AlphabetParameterSet

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.models.CompositeModel

getInstanceName() - Method in class de.jstacs.models.discrete.DGMParameterSet

getInstanceName() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM

getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel

getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel

getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier

getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture

getInstanceName() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

getInstanceName() - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest

Returns a short description of the burn-in test.

getInstanceName() - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest

getInstanceName() - Method in class de.jstacs.models.mixture.gibbssampling.VarianceRatioBurnInTest

getInstanceName() - Method in class de.jstacs.models.mixture.motif.HiddenMotifMixture

getInstanceName() - Method in class de.jstacs.models.mixture.motif.positionprior.GaussianLikePositionPrior

getInstanceName() - Method in class de.jstacs.models.mixture.motif.positionprior.PositionPrior

Returns the instance name.

getInstanceName() - Method in class de.jstacs.models.mixture.motif.positionprior.UniformPositionPrior

getInstanceName() - Method in interface de.jstacs.models.Model

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

getInstanceName() - Method in class de.jstacs.models.NormalizableScoringFunctionModel

getInstanceName() - Method in class de.jstacs.models.UniformModel

getInstanceName() - Method in class de.jstacs.models.VariableLengthWrapperModel

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 class de.jstacs.scoringFunctions.CMMScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet

getInstanceName() - Method in class de.jstacs.scoringFunctions.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.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation

getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet

getInstanceName() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getInstanceName() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getInstanceName() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getInstanceName() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getInstanceName() - Method in interface de.jstacs.scoringFunctions.ScoringFunction

Returns a short instance name.

getInstanceName() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

getIntArrayWithTags(int[]) - Static method in class de.jstacs.io.XMLParser

Encodes an int array.

getInternalPosition(int[]) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction

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.

getK() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet

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

getKLDivergence(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester

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

getKLDivergence(double[][][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree

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

getKLDivergence(double[], double[][][][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree

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

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

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

getLambda(int) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint

Returns the value of .

getLastScore() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

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

getLength() - Method in class de.jstacs.classifier.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.Sequence.CompositeSequence

getLength() - Method in class de.jstacs.data.Sequence

Returns the length of the Sequence.CompositeSequence.

getLength() - Method in class de.jstacs.data.Sequence.SubSequence

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.ArbitrarySequence

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

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

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

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

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

getLength() - Method in class de.jstacs.models.AbstractModel

getLength() - Method in class de.jstacs.models.mixture.motif.positionprior.GaussianLikePositionPrior

getLength() - Method in class de.jstacs.models.mixture.motif.positionprior.PositionPrior

Returns the length that is supported by this prior.

getLength() - Method in class de.jstacs.models.mixture.motif.positionprior.UniformPositionPrior

getLength() - Method in interface de.jstacs.models.Model

Returns the length of sequences this model can classify.

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.scoringFunctions.AbstractNormalizableScoringFunction

getLength() - Method in interface de.jstacs.scoringFunctions.ScoringFunction

Returns the length of this ScoringFunction, i.e. the length of the Sequences this ScoringFunction can handle.

getLengthOfBurnIn() - Method in class de.jstacs.models.mixture.gibbssampling.AbstractBurnInTest

getLengthOfBurnIn() - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest

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

getLengthOfBurnIn() - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest

getLengthOfModels() - Method in class de.jstacs.models.CompositeModel

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

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

Return the line with a given index from the table.

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.models.discrete.homogeneous.HomogeneousModel.HomCondProb

Returns the logarithmic frequency at a given position index.

getLnFreq(int) - Method in class de.jstacs.models.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.models.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.

getLogCDF(double) - Static method in class de.jstacs.scoringFunctions.mix.motifSearch.CDFOfNormal

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

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

Computes the sum of the differences between the logarithmic values of the prior knowledge and all counts of a Constraint c.

getLogLikelihood(Model, Sample) - Static method in class de.jstacs.models.utils.ModelTester

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

getLogLikelihood(Model, Sample, double[]) - Static method in class de.jstacs.models.utils.ModelTester

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

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.AbstractVariableLengthScoringFunction

getLogNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getLogNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getLogNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getLogNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

getLogNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.mix.VariableLengthMixtureScoringFunction

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getLogNormalizationConstant() - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction

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

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getLogNormalizationConstant() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

getLogNormalizationConstant(int) - Method in interface de.jstacs.scoringFunctions.VariableLengthScoringFunction

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

getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

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

getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.AbstractVariableLengthScoringFunction

getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.mix.VariableLengthMixtureScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getLogPartialNormalizationConstant(int) - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction

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

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getLogPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

getLogPartialNormalizationConstant(int, int) - Method in interface de.jstacs.scoringFunctions.VariableLengthScoringFunction

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

getLogPartialNormalizer() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

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

getLogPriorForPositions(int, int...) - Method in class de.jstacs.models.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.models.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.models.mixture.motif.positionprior.UniformPositionPrior

getLogPriorTerm() - Method in class de.jstacs.models.CompositeModel

getLogPriorTerm() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM

getLogPriorTerm() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel

getLogPriorTerm() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel

getLogPriorTerm() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

getLogPriorTerm() - Method in interface de.jstacs.models.Model

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

getLogPriorTerm() - Method in class de.jstacs.models.NormalizableScoringFunctionModel

getLogPriorTerm() - Method in class de.jstacs.models.UniformModel

getLogPriorTerm() - Method in class de.jstacs.models.VariableLengthWrapperModel

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.MutableMarkovModelScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getLogPriorTerm() - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction

This method computes a value that is proportional to NormalizableScoringFunction.getEss() * NormalizableScoringFunction.getLogNormalizationConstant() + Math.log( prior ) where prior is the prior for the parameters of this model.

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

getLogPriorTermForComponentProbs() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

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

getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.AbstractModel

getLogProbFor(Sequence, int) - Method in class de.jstacs.models.AbstractModel

getLogProbFor(Sequence) - Method in class de.jstacs.models.AbstractModel

getLogProbFor(Sample) - Method in class de.jstacs.models.AbstractModel

getLogProbFor(Sample, double[]) - Method in class de.jstacs.models.AbstractModel

getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.CompositeModel

getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel

getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel

getLogProbFor(int, Sequence) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

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

getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

getLogProbFor(Sample) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

getLogProbFor(Sequence, int, int) - Method in interface de.jstacs.models.Model

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

getLogProbFor(Sequence, int) - Method in interface de.jstacs.models.Model

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

getLogProbFor(Sequence) - Method in interface de.jstacs.models.Model

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

getLogProbFor(Sample) - Method in interface de.jstacs.models.Model

This method computes the logarithm of the probabilities of all sequences in the given sample.

getLogProbFor(Sample, double[]) - Method in interface de.jstacs.models.Model

This method computes and stores the logarithm of the probabilities for any sequence in the sample in the given double-array.

getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.NormalizableScoringFunctionModel

getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

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.models.mixture.MixtureModel

getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.models.mixture.StrandModel

getLogScore(Sequence) - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

Returns the logarithmic score for a given Sequence.

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.AbstractVariableLengthScoringFunction

getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getLogScore(int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getLogScore(int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction

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

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction

getLogScore(int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getLogScore(int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction

getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.mix.VariableLengthMixtureScoringFunction

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getLogScore(Sequence) - Method in interface de.jstacs.scoringFunctions.ScoringFunction

Returns the logarithmic score for the Sequence seq.

getLogScore(Sequence, int) - Method in interface de.jstacs.scoringFunctions.ScoringFunction

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

getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

getLogScore(Sequence, int, int) - Method in interface de.jstacs.scoringFunctions.VariableLengthScoringFunction

This method computes the logarithm of the score for a given subsequence.

getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.AbstractVariableLengthScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction

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.scoringFunctions.mix.motifSearch.PositionScoringFunction

getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.mix.VariableLengthMixtureScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in interface de.jstacs.scoringFunctions.ScoringFunction

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.scoringFunctions.ScoringFunction

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.scoringFunctions.UniformScoringFunction

getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in interface de.jstacs.scoringFunctions.VariableLengthScoringFunction

This method computes the logarithm of the score and the partial derivations for a given subsequence.

getLogScoreAndPartialDerivationForInternal(IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction

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

getLogScoreForInternal() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction

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

getLogSum(double...) - Static method in class de.jstacs.utils.Normalisation

Returns the logarithm of the sum of values 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 given as lnVal[i] = Math.log( val[i] ) between a start and end index.

getLogT() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

Returns the part of the normalization constant of parameters before this parameter in the structure of the network.

getLogZ() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

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(Model, int[]) - Static method in class de.jstacs.models.utils.ModelTester

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.models.discrete.Constraint

Returns the marginal order, i.e. the number of used random variables.

getMatrix() - Method in class de.jstacs.classifier.ConfusionMatrix

This method returns the confusion matrix as a two dimensional int-array.

getMax() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet

Returns the maximal value of this alphabet.

getMax(double[][]) - Static method in class de.jstacs.models.discrete.inhomogeneous.TwoPointEvaluater

This method can be used to determine the maximal value of the matrix of mutual informations.

getMax() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

Returns the maximal value that can be scored.

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],...

getMaximalElementLength() - Method in class de.jstacs.data.Sample

Returns the maximal length of an element, i.e. a Sequence, in this Sample.

getMaximalMarkovOrder() - Method in class de.jstacs.models.AbstractModel

getMaximalMarkovOrder() - Method in class de.jstacs.models.CompositeModel

getMaximalMarkovOrder() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel

getMaximalMarkovOrder() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel

getMaximalMarkovOrder() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel

getMaximalMarkovOrder() - Method in interface de.jstacs.models.Model

This method returns the maximal used Markov order, if possible.

getMaximalMarkovOrder() - Method in class de.jstacs.models.UniformModel

getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.HomogeneousScoringFunction

Returns the maximal used markov oder.

getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

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

Returns the length of the longest "symbol" in the alphabet.

getMaxIndex(double[]) - Static method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

Returns the index with maximal value in a double array.

getMaxOfCC(double[], double[]) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method computes the maximal correlation coefficient (CC_max).

getMaxOfDeviation(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester

This method computes the maximum deviation between the probabilities for all sequences of length for discrete models m1 and m2.

getMeasure() - Method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair

This method returns the value of the measure.

getMeasure() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet

Returns the structure Measure defined by this set of parameters.

getMeasuresForEvaluate() - Static method in class de.jstacs.classifier.AbstractClassifier

Returns an object of the parameters for the method AbstractClassifier.evaluate(MeasureParameters, boolean, Sample...).

getMeasuresForEvaluateAll() - Static method in class de.jstacs.classifier.AbstractClassifier

Returns an object of the parameters for the method AbstractClassifier.evaluateAll(MeasureParameters, boolean, Sample...).

getMI(double[][][][][][], double) - Static method in class de.jstacs.scoringFunctions.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.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure

Computes the mutual information from counts counted on sequences with a total weight of n.

getMIInBits(Sample, double[]) - Static method in class de.jstacs.models.discrete.inhomogeneous.TwoPointEvaluater

This method computes the pairwise mutual information (in bits) between the sequence positions.

getMin() - Method in class de.jstacs.data.Alphabet

Returns the minimal value of theAlphabet.

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.ContinuousAlphabet

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

getMin() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

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.Sample

Returns the minimal length of an element, i.e. a Sequence, in this Sample.

getMinimalSequenceLength() - Method in class de.jstacs.models.mixture.motif.HiddenMotifMixture

Returns the minimal length a sequence respectively a sample has to have.

getMinimalSequenceLength() - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

getMisclassificationRate() - Method in class de.jstacs.classifier.ConfusionMatrix

This method returns the misclassification rate.

getModel(int) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

Returns a clone of the Model for a specified class.

getModel(int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

Returns a deep copy of the i-th model.

getModelInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet

This method returns a short description of the model.

getModelInstanceName(StructureLearner.ModelType, byte, StructureLearner.LearningType, double) - Static method in class de.jstacs.models.discrete.inhomogeneous.parameters.IDGMParameterSet

This method returns a short textual representation of the model instance.

getModels() - Method in class de.jstacs.models.CompositeModel

Returns the a deep copy of the models.

getModels() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

Returns a deep copy of the models.

getMostProbableSequence(Model, int) - Static method in class de.jstacs.models.utils.ModelTester

Returns one most probable sequence for the discrete model m.

getMotifLength(int) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

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.scoringFunctions.IndependentProductScoringFunction

getMotifLength(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getMotifLength(int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getMRG() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

This method creates the multivariate random generator that will be used during initialization.

getMRGParams() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

This method creates the parameters used in a multivariate random generator while initialization.

getName() - Method in class de.jstacs.parameters.CollectionParameter

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

getName() - Method in class de.jstacs.parameters.Parameter

Returns the name of the Parameter.

getName() - Method in class de.jstacs.parameters.ParameterSetContainer

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

getName() - Method in class de.jstacs.parameters.SimpleParameter

getName() - Method in class de.jstacs.results.Result

Returns the name of the Result.

getNameOfAlgorithm() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

Returns the name of the used algorithm.

getNameOfAssessment() - Method in class de.jstacs.classifier.assessment.ClassifierAssessment

Returns the name of this class.

getNameString() - Method in enum de.jstacs.classifier.MeasureParameters.Measure

Returns the name of the MeasureParameters.Measure.

getNeededReference() - Method in class de.jstacs.parameters.Parameter

Returns a reference to a ParameterSet whose ParameterSet.hasDefaultOrIsSet()-method depends on the value of this Parameter.

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

getNeededReferenceId() - Method in class de.jstacs.parameters.Parameter

Returns the id of the ParameterSet that would be returned by Parameter.getNeededReference().

getNewComponentProbs(double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

Estimates the weights of each component.

getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.CompositeLogPrior

getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.DoesNothingLogPrior

getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior

This method returns an empty new instance of the current prior.

getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior

getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior

getNewParameters(int, double[][], double[]) - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture

getNewParameters(int, double[][], double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

This method trains the internal models on the internal sample and the given weights.

getNewParameters(int, double[][], double[]) - Method in class de.jstacs.models.mixture.motif.HiddenMotifMixture

getNewParametersForModel(int, int, int, double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

This method trains the internal model with index modelIndex on the internal sample 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.models.mixture.AbstractMixtureModel

Computes sequence weights and returns the score.

getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.models.mixture.MixtureModel

Computes sequence weights and returns the score.

getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.models.mixture.StrandModel

Computes sequence weights and returns the score.

getNormalizedVersion(NormalizableScoringFunction, int) - Static method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

This method returns a normalized version of a NormalizableScoringFunction.

getNumberOfAvailableProcessors() - Static method in class de.jstacs.classifier.scoringFunctionBased.AbstractMultiThreadedOptimizableFunction

This method returns the number of available processors.

getNumberOfBoundSequences(Sample, 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.

getNumberOfClasses() - Method in class de.jstacs.classifier.AbstractClassifier

Returns the number of classes that can be distinguished.

getNumberOfClasses() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier

getNumberOfCombinations(int) - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator

Returns the number of possible combinations.

getNumberOfComponents() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

Returns the number of components the are modeled by this AbstractMixtureModel.

getNumberOfComponents() - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the number of components in this MotifDiscoverer.

getNumberOfComponents() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getNumberOfComponents() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

Returns the number of different components of this AbstractMixtureScoringFunction.

getNumberOfElements() - Method in class de.jstacs.data.Sample

Returns the number of elements, i.e. the Sequences, in this Sample.

getNumberOfElements() - Method in class de.jstacs.data.Sample.WeightedSampleFactory

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.Sample

Returns the number of overlapping elements that can be extracted.

getNumberOfElementsWithLength(int, double[]) - Method in class de.jstacs.data.Sample

Returns the weighted number of overlapping elements that can be extracted.

getNumberOfLines() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult

Returns the number of lines in this table.

getNumberOfModels() - Method in class de.jstacs.models.CompositeModel

This method returns the number of models in the CompositeModel.

getNumberOfMotifs() - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

getNumberOfMotifs() - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer

Returns the number of motifs for this MotifDiscoverer.

getNumberOfMotifs() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getNumberOfMotifs() - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getNumberOfMotifs() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getNumberOfMotifsInComponent(int) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

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.scoringFunctions.IndependentProductScoringFunction

getNumberOfMotifsInComponent(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getNumberOfMotifsInComponent(int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getNumberOfNexts(int) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

Returns the number of calls of MultiSelectionCollectionParameter.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.

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 class de.jstacs.scoringFunctions.CMMScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getNumberOfParameters() - Method in interface de.jstacs.scoringFunctions.ScoringFunction

Returns the number of parameters in this ScoringFunction.

getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

getNumberOfParents() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree

Returns the number of parents for the random variable of this ParameterTree in the network structure of the enclosing BayesianNetworkScoringFunction.

getNumberOfPossibilities() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

Returns the number of different possibilities that can be scored.

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getNumberOfRecommendedStarts() - Method in interface de.jstacs.scoringFunctions.ScoringFunction

This method returns the number of recommended optimization starts.

getNumberOfResults() - Method in class de.jstacs.results.ResultSet

Returns the number of Results in this ResultSet

getNumberOfSequenceAnnotationsByType(String) - Method in class de.jstacs.data.Sequence

Returns the number of SequenceAnnotations of type type for this Sequence.CompositeSequence.

getNumberOfSpecificConstraints() - Method in class de.jstacs.models.discrete.Constraint

Returns the number of specific constraints.

getNumberOfStarts(ScoringFunction[]) - Static method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction

Returns the number of recommended starts in a numerical optimization.

getNumberOfThreads() - Method in class de.jstacs.classifier.scoringFunctionBased.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.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

This method returns the number of used threads while optimization.

getNumberOfThreads() - Method in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifierParameterSet

This method returns the number of threads that should be used during optimization.

getNumberOfValues() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

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

getNumberOfValues() - Method in class de.jstacs.parameters.ParameterSetContainer

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.classifier.AbstractClassifier

Returns the subset of numerical values that are also returned by AbstractClassifier.getCharacteristics().

getNumericalCharacteristics() - Method in class de.jstacs.classifier.MappingClassifier

getNumericalCharacteristics() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getNumericalCharacteristics() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

getNumericalCharacteristics() - Method in class de.jstacs.models.CompositeModel

getNumericalCharacteristics() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel

getNumericalCharacteristics() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel

getNumericalCharacteristics() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

getNumericalCharacteristics() - Method in interface de.jstacs.models.Model

Returns the subset of numerical values that are also returned by Model.getCharacteristics().

getNumericalCharacteristics() - Method in class de.jstacs.models.NormalizableScoringFunctionModel

getNumericalCharacteristics() - Method in class de.jstacs.models.UniformModel

getNumericalCharacteristics() - Method in class de.jstacs.models.VariableLengthWrapperModel

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.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov

Returns the order of the Markov model as defined in the constructor

getOrder() - Method in class de.jstacs.scoringFunctions.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.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet

Returns the order defined by this set of parameters.

getOrder() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet

Returns the order defined by this set of parameters.

getOutput(byte[], double) - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb

This method is used to create random sequences.

getOutputStream() - Method in class de.jstacs.utils.SafeOutputStream

Returns the internal used OutputStream.

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.scoringFunctions.directedGraphicalModels.ParameterTree

Returns the Parameter that is responsible for the suffix of sequence seq starting at position start.

getParameterFromTag(String) - Method in class de.jstacs.parameters.ParameterSetTagger

This method returns the Parameter specified by the tag

getParameters(OptimizableFunction.KindOfParameter, double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction

This method enables the user to get the parameters without creating a new array.

getParameters(OptimizableFunction.KindOfParameter) - Method in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction

getParameters(OptimizableFunction.KindOfParameter) - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction

Returns some parameters that can be used for instance as start parameters.

getParameters(OptimizableFunction.KindOfParameter, double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.SFBasedOptimizableFunction

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.CollectionParameter

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 ParameterSetContainer of this ParameterSet or null if none exists.

getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual

getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation

getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov

getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure

Returns the optimal parents for the given data and weights.

getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual

getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation

getPartialLengths() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

This method returns a deep copy of the internally used partial lengths of the parts.

getPartialROC(double[], double[], RangeParameter) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method allows to compute a partial ROC curve.

getPercent() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet

Returns the percentage of user supplied data that is used in each iteration as test dataset.

getPercents() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet

Returns an array containing for each class the percentage of user supplied data that is used in each iteration as test dataset.

getPlotCommands(REnvironment, String, AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifier.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.classifier.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.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunctionParameterSet

Returns true if plug-in parameters shall be used when creating a BayesianNetworkScoringFunction 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(int) - Method in class de.jstacs.models.discrete.Constraint

Returns the position with index index.

getPosition() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

Returns the position of the symbol this parameter is responsible for as defined in the constructor.

getPositionDependentKMerProb(Sequence) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

Returns the probability of kmer for all possible positions in this BayesianNetworkScoringFunction starting at position kmer.getLength()-1.

getPositionForParameter(int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

Returns the position in the sequence the parameter index is responsible for.

getPositions() - Method in class de.jstacs.models.discrete.Constraint

Returns a clone of the array of used positions.

getPossibleLength(Model...) - Static method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

This method returns the possible length of a classifier that would use the given Models.

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

Returns the length of the AlphabetContainer that can be instantiated using this AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet.

getPPVForSensitivity(double[], double[], double) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method computes the positive predictive value (PPV) for a given sensitivity.

getPriorTerm() - Method in class de.jstacs.models.AbstractModel

getPriorTerm() - Method in interface de.jstacs.models.Model

Returns a value that is proportional to the prior.

getProbFor(Sequence) - Method in class de.jstacs.models.AbstractModel

getProbFor(Sequence, int) - Method in class de.jstacs.models.AbstractModel

getProbFor(Sequence, int, int) - Method in class de.jstacs.models.CompositeModel

getProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel

getProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel

getProbFor(Sequence, int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel

getProbFor(Sequence) - Method in interface de.jstacs.models.Model

Returns the probability of the given sequence given the model.

getProbFor(Sequence, int) - Method in interface de.jstacs.models.Model

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

getProbFor(Sequence, int, int) - Method in interface de.jstacs.models.Model

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

getProbFor(Sequence, int, int) - Method in class de.jstacs.models.NormalizableScoringFunctionModel

getProbFor(Sequence, int, int) - Method in class de.jstacs.models.UniformModel

getProbFor(Sequence, int, int) - Method in class de.jstacs.models.VariableLengthWrapperModel

getProbFor(Sequence) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree

Returns the probability of Sequence sequence in this ParameterTree.

getProbsForComponent(Sequence) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

Returns the probabilities for each component given a Sequence.

getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

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.scoringFunctions.IndependentProductScoringFunction

getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getPseudoCount() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

Returns the pseudocount as given in the constructor.

getPValue(Sequence, Sample) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier

Returns the p-value for a Sequence candidate with respect to a given background Sample.

getPValue(Sample, Sample) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier

Returns the p-values for all Sequences in the Sample candidates with respect to a given background Sample .

getPValue(double[], double) - Static method in class de.jstacs.classifier.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.classifier.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 class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

If this BayesianNetworkScoringFunction is a PWM, i.e.

getRandomSequence(Random, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM

getRandomSequence(Random, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel

This method creates a random Sequence from a trained homogeneous model.

getRangedInstance() - Method in class de.jstacs.parameters.CollectionParameter

getRangedInstance() - Method in class de.jstacs.parameters.ParameterSetContainer

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.

getReferenceClass() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet

Returns the index of the reference class.

getRegEx() - Method in class de.jstacs.io.RegExFilenameFilter

Returns a representation of all used regular expressions.

getRepeats() - Method in class de.jstacs.classifier.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.classifier.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.classifier.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).

getResult() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult

getResult() - Method in class de.jstacs.results.ImageResult

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

getResult() - Method in class de.jstacs.results.Result

Returns the value of the Result.

getResult() - Method in class de.jstacs.results.SampleResult

getResult() - Method in class de.jstacs.results.SimpleResult

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

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.

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

Returns the instance of the Storable that is the result of this StorableResult.

getResults(Sample[], MeasureParameters, boolean, boolean) - Method in class de.jstacs.classifier.AbstractClassifier

This method computes the results for any evaluation of the classifier.

getResults(Sample[], MeasureParameters, boolean, boolean) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier

getResults(Sample[], MeasureParameters, boolean, boolean) - Method in class de.jstacs.classifier.MappingClassifier

getResults() - Method in class de.jstacs.results.ResultSet

Returns all internal results as an array of Results.

getReverseComplementDistributions(ComplementableDiscreteAlphabet, double[][][]) - Static method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

This method computes the reverse complement distributions for given conditional distributions.

getReverseSwitches() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

This method returns a deep copy of the internally used switches for the parts whether to use the corresponding NormalizableScoringFunction forward or as reverse complement.

getRNotation(String) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

This method returns the distribution in R notation.

getRNotation(String) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.MixtureDuration

getRNotation(String) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction

getRNotation(String) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction

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.

getSafeOutputStream(OutputStream) - Static method in class de.jstacs.utils.SafeOutputStream

This method returns an instance of SafeOutputStream for a given OutputStream.

getSample() - Method in class de.jstacs.data.Sample.WeightedSampleFactory

Returns the Sample, where each Sequence occurs only once.

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

This method allows to create a Sample containing SparseSequences.

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

Returns a description of the the scale of a range of parameter values.

getScatterplot(AbstractScoreBasedClassifier, AbstractScoreBasedClassifier, Sample, Sample, REnvironment, boolean) - Static method in class de.jstacs.classifier.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.classifier.AbstractScoreBasedClassifier

This method returns the score for a given Sequence and a given class.

getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier

This method returns the score for a given Sequence and a given class.

getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.MappingClassifier

getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

getScoreForBestRun() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

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(Sample) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier

This method returns the scores of the classifier for any Sequence in the Sample.

getScores(Sample) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getScoringFunction(int) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

Returns the internally used ScoringFunction with index i.

getScoringFunctions() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

Returns all internally used ScoringFunctions in the internal order.

getScoringFunctions() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

Returns a deep copy of all internal used ScoringFunctions.

getSecond() - Method in class de.jstacs.algorithms.Alignment.StringAlignment

Returns the second String.

getSelected() - Method in class de.jstacs.parameters.CollectionParameter

Returns the index of the selected value.

getSelected() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

getSensitivityForSpecificity(double[], double[], double) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions

This method computes the sensitivity for a given specificity.

getSequenceAnnotationByType(String, int) - Method in class de.jstacs.data.Sequence

Returns the SequenceAnnotation no.

getSequenceAnnotationIndexMatrix(String, Hashtable<String, Integer>, String, Hashtable<String, Integer>) - Method in class de.jstacs.data.Sample

This method creates a matrix which contains the index of the Sequence with specific SequenceAnnotation combination or -1 if the Sample does not contain any Sequence with such a combination.

getSequenceWeights() - Method in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction

getSequenceWeights() - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction

Returns the weights for each Sequence for each class used in this OptimizableFunction.

getShannonEntropy(Model, int) - Static method in class de.jstacs.models.utils.ModelTester

This method computes the Shannon entropy for any discrete model m and all sequences of length, if possible.

getShannonEntropyInBits(Model, int) - Static method in class de.jstacs.models.utils.ModelTester

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.

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.

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.CMMScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.DurationScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction

Returns the size of the event space of the random variables that are affected by parameter no.

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction

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(ScoringFunction[], MutableMotifDiscovererToolbox.InitMethodForScoringFunction[], SFBasedOptimizableFunction, int, SafeOutputStream, int) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox

This method allows to initialize the MutableMotifDiscovererToolbox.InitMethodForScoringFunction using different MutableMotifDiscovererToolbox.InitMethodForScoringFunction.

getSortedScoresForMotifAndFlanking(Sample, Sample, 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 Sample data.

getSortedValuesForMotifAndFlanking(Sample, double[][], double, double, String) - Static method in class de.jstacs.motifDiscovery.MotifDiscoveryAssessment

This method provides some score arrays that can be used in ScoreBasedPerformanceMeasureDefinitions to determine some curves or area under curves based on the p-values of the predictions.

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

Returns the start node of the edge.

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.

getStationaryDistribution(double[], int) - Static method in class de.jstacs.models.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(Sample, double[], int, double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure

Counts the occurrences of symbols of the AlphabetContainer of Sample s using weights.

getStatisticsOrderTwo(Sample, double[], int, double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure

Counts the occurrences of symbols of the AlphabetContainer of Sample 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.

getStorableArrayWithTags(Storable[]) - Static method in class de.jstacs.io.XMLParser

Encodes a Storable array.

getStrand(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction

This method returns the preferred StrandedLocatedSequenceAnnotationWithLength.Strand for a given subsequence.

getStrand(Sequence, int) - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction

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.

getStrandFor(int, int, Sequence, int) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture

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

This method returns the strand for a given subsequence if it is considered as site of the motif model in a specific component.

getStrandFor(int, int, Sequence, int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction

getStrandFor(int, int, Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction

getStrandFor(int, int, Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture

getStringArrayWithTags(String[]) - Static method in class de.jstacs.io.XMLParser

Encodes a String array.

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

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

getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel

getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel

getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM

Returns a String representation of the underlying graph.

getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture

Returns a String representation of the structure of the used models.

getStructure(Sample, double[], StructureLearner.ModelType, byte, StructureLearner.LearningType) - Method in class de.jstacs.models.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.models.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.Sequence

This method should be used if one wants to create a Sample of subsequences of defined length.

getSubSequence(AlphabetContainer, int, int) - Method in class de.jstacs.data.Sequence

This method should be used if one wants to create a Sample of subsequences of defined length.

getSubSequence(int) - Method in class de.jstacs.data.Sequence

This is a very efficient way to create a subsequence/suffix for Sequence.CompositeSequences with a simple AlphabetContainer.

getSubSequence(int, int) - Method in class de.jstacs.data.Sequence

This is a very efficient way to create a subsequence of defined length for Sequence.CompositeSequences with a simple AlphabetContainer.

getSuffixSample(int) - Method in class de.jstacs.data.Sample

This method enables you to use only a suffix of all elements, i.e. the Sequence, in the current Sample.

getSumOfDeviation(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester

This method computes the sum of deviations between the probabilities for all sequences of length for discrete models m1 and m2.

getSumOfDistribution(Model, int) - Static method in class de.jstacs.models.utils.ModelTester

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.

getSumOfWeights() - Method in class de.jstacs.data.Sample.WeightedSampleFactory

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.

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(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester

Returns the difference of the Kullback-Leibler-divergences, i.e.

getTensor(Sample, double[], byte, StructureLearner.LearningType) - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner

This method can be used to compute a Tensor that can be used to determine the optimal structure.

getThreshold() - Method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair

This method returns the value of threshold.

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

This method returns the threshold that determines if an observed score is significant.

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.classifier.assessment.RepeatedSubSamplingAssessParameterSet

Returns an array containing the number of elements the subsampled (train | test) datasets should consist of.

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 class de.jstacs.data.sequences.annotation.SequenceAnnotation

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

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],...

getValue() - Method in class de.jstacs.parameters.CollectionParameter

getValue() - Method in class de.jstacs.parameters.EnumParameter

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

getValue() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

getValue() - Method in class de.jstacs.parameters.Parameter

Returns the current value of this Parameter.

getValue() - Method in class de.jstacs.parameters.ParameterSetContainer

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

getValue() - Method in class de.jstacs.parameters.SimpleParameter

getValue() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter

Returns the current value of this parameter.

getValueFor(String) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

Returns the value for the option with key key.

getValueFor(int) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

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(Model, Sample, int) - Static method in class de.jstacs.models.utils.ModelTester

This method computes the value of Akaikes Information Criterion (AIC).

getValueOfBIC(Model, Sample, int) - Static method in class de.jstacs.models.utils.ModelTester

This method computes the value of the Bayesian Information Criterion (BIC).

getValues() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter

Returns the values of all selected options as an array.

getValuesForEachNucleotide(Sample, int, int, boolean) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder

This method determines a value for each symbol to be annotated at least in one motif occurrence of the motif with index index in the component component.

getValuesFromSequence(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction

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.

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

Returns the weight of the edge.

getWeight(int) - Method in class de.jstacs.data.Sample.WeightedSampleFactory

Returns the weight for the Sequence with index index.

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

This method returns the weight of the element.

getWeights() - Method in class de.jstacs.data.Sample.WeightedSampleFactory

Returns a copy of the weights for the Sample.

getWeights() - Method in class de.jstacs.models.mixture.AbstractMixtureModel

This method returns a deep copy of the weights for each component.

getXMLTag() - Method in class de.jstacs.classifier.AbstractClassifier

Returns the String that is used as tag for the XML representation of the classifier.

getXMLTag() - Method in class de.jstacs.classifier.MappingClassifier

getXMLTag() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier

getXMLTag() - Method in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier

getXMLTag() - Method in class de.jstacs.classifier.scoringFunctionBased.msp.MSPClassifier

getXMLTag() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier

getXMLTag() - Method in class de.jstacs.models.discrete.Constraint

Returns the XML tag that is used for the class to en- or decode.

getXMLTag() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel

Returns the XML tag that is used for this model in DiscreteGraphicalModel.fromXML(StringBuffer) and DiscreteGraphicalModel.toXML().

getXMLTag() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM

getXMLTag() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel.HomCondProb

getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel

getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel

getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb

getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint

getXMLTag() - Method in class de.jstacs.models.mixture.gibbssampling.AbstractBurnInTest

This method returns the XML tag that is used in AbstractBurnInTest.toXML() and AbstractBurnInTest.AbstractBurnInTest(StringBuffer).

getXMLTag() - Method in class de.jstacs.models.mixture.gibbssampling.VarianceRatioBurnInTest

getXMLTag() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

This method returns the XML tag of the instance that is used to build a XML representation.

GibbsSamplingComponent - Interface in de.jstacs.models.mixture.gibbssampling

This is the interface that any AbstractModel has to implement if it should be used in a Gibbs Sampling.

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].

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.