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## 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 `Sequence`s 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 `Result`s.
getAnnotation(Sample...) - Static method in class de.jstacs.data.Sample
  Returns the annotation for an array of `Sample`s.
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 `Result`s 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 `Alphabet`s e.g. for composite motifs/sequences.
getCompositeSample(int[], int[]) - Method in class de.jstacs.data.Sample
  This method enables you to use only composite `Sequence`s 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.CompositeSequence`s.
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 `Sequence`s.
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 `Sequence`s, 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 `Sequence`s, 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 `Sequence`s 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 the`Alphabet`.
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 `Sequence`s, 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 `String`s 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 `Result`s in this `ResultSet`
getNumberOfSequenceAnnotationsByType(String) - Method in class de.jstacs.data.Sequence
  Returns the number of `SequenceAnnotation`s 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 `InstanceParameterSet`s 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 `Model`s.
getPossibleLength() - Method in class de.jstacs.data.AlphabetContainer
  Returns the possible length for `Sequence`s 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 `Sequence`s 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 `ResultSet`s.
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 `Result`s.
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 `SparseSequence`s.
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 `ScoringFunction`s in the internal order.
getScoringFunctions() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Returns a deep copy of all internal used `ScoringFunction`s.
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 `Alphabet`s 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 `Alphabet`s 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.CompositeSequence`s 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.CompositeSequence`s 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`.

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