Overview  Package  Class  Use  Tree  Deprecated   Index  Help 
 PREV LETTER   NEXT LETTER FRAMES    NO FRAMES    All Classes
A B C D E F G H I J K L M N O P Q R S T U V W X Z

G

GalaxyAdaptor - Class in de.jstacs.utils.galaxy
Adaptor class between the parameter representation of Jstacs in Parameters and ParameterSets and the parameter representation in Galaxy.
GalaxyAdaptor(ParameterSet, String, String, String, String) - Constructor for class de.jstacs.utils.galaxy.GalaxyAdaptor
Creates a new GalaxyAdaptor from a given ParameterSet containing all parameters that are necessary for a program is shall be included in a Galaxy installation.
GalaxyAdaptor.FileResult - Class in de.jstacs.utils.galaxy
Result for files that are results of some computation.
GalaxyAdaptor.FileResult(String, String, String) - Constructor for class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
Creates a new GalaxyAdaptor.FileResult with name, comment, and path to the file.
GalaxyAdaptor.FileResult(String, String, String, String, String) - Constructor for class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
Creates a new GalaxyAdaptor.FileResult with name, comment, path to the file, filename and extension.
GalaxyAdaptor.FileResult(StringBuffer) - Constructor for class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
Creates a new GalaxyAdaptor.FileResult from its XML-representation
GalaxyAdaptor.LinkedImageResult - Class in de.jstacs.utils.galaxy
Class for an ImageResult that is linked to a file that can be downloaded.
GalaxyAdaptor.LinkedImageResult(String, String, BufferedImage, GalaxyAdaptor.FileResult) - Constructor for class de.jstacs.utils.galaxy.GalaxyAdaptor.LinkedImageResult
Create a new ImageResult with linked GalaxyAdaptor.FileResult link
GalaxyAdaptor.LinkedImageResult(StringBuffer) - Constructor for class de.jstacs.utils.galaxy.GalaxyAdaptor.LinkedImageResult
Creates a new GalaxyAdaptor.LinkedImageResult from its XML-representation
GalaxyAdaptor.Protocol - Class in de.jstacs.utils.galaxy
Class for a Protocol writer.
GalaxyConvertible - Interface in de.jstacs.parameters
Interface for Parameters that can be converted to and extracted from Galaxy representations.
GaussianEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous
Emission for continuous values following a Gaussian distribution.
GaussianEmission(AlphabetContainer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
Creates a GaussianEmission which can be used for maximum likelihood.
GaussianEmission(AlphabetContainer, double, double, double, double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
Creates a GaussianEmission with normal-gamma prior by directly defining the hyper-parameters of the prior.
GaussianEmission(double, AlphabetContainer, double, double, double, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
Creates a GaussianEmission with normal-gamma prior by defining the expected precision and the expected standard deviation of the precision, i.e. via the expectation and variance of the gamma part of the normal-gamma prior.
GaussianEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
Creates a GaussianEmission from its XML representation.
GaussianLikePositionPrior - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior
This class implements a gaussian like discrete truncated prior.
GaussianLikePositionPrior(int, double, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
This constructor creates an instance with given sequence length, maximal value and sigma for the Gaussian.
GaussianLikePositionPrior(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
The standard constructor for the interface Storable.
GenDisMixClassifier - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix
This class implements a classifier the optimizes the following function
\[f(\underline{\lambda}|C,D,\underline{\alpha},\underline{\beta})
The weights $\beta_i$ have to sum to 1.
GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double[], DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
This constructor creates an instance and sets the value of the last (external) optimization.
GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double[], DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
This constructor creates an instance and sets the value of the last (external) optimization.
GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double[], DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
The main constructor.
GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, double, double, double, DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
This convenience constructor agglomerates the genBeta, disBeta, and priorBeta into an array and calls the main constructor.
GenDisMixClassifier(GenDisMixClassifierParameterSet, LogPrior, LearningPrinciple, DifferentiableStatisticalModel...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
This convenience constructor creates an array of weights for an elementary learning principle and calls the main constructor.
GenDisMixClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
This is the constructor for Storable.
GenDisMixClassifierParameterSet - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix
This class contains the parameters for the GenDisMixClassifier.
GenDisMixClassifierParameterSet(StringBuffer) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet
The standard constructor for the interface Storable.
GenDisMixClassifierParameterSet(AlphabetContainer, int, byte, double, double, double, boolean, OptimizableFunction.KindOfParameter, boolean, int) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet
The default constructor that constructs a new GenDisMixClassifierParameterSet.
GenDisMixClassifierParameterSet(Class<? extends ScoreClassifier>, AlphabetContainer, int, byte, double, double, double, boolean, OptimizableFunction.KindOfParameter, boolean, int) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet
The default constructor that constructs a new GenDisMixClassifierParameterSet.
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.DirichletMRG
 
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.EqualParts
 
generate(int) - Method in class de.jstacs.utils.random.EqualParts
Returns an array of length n with entries 1/n.
generate(double[], int, int) - Method in class de.jstacs.utils.random.EqualParts
Modifies a given number of array entries to 1/number.
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.ErlangMRG
 
generate(int, MRGParams) - Method in class de.jstacs.utils.random.MultivariateRandomGenerator
Generates a n-dimensional random array.
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.MultivariateRandomGenerator
Generates a n-dimensional random array as part of the array d beginning at start.
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.SoftOneOfN
 
generate(int) - Method in class de.jstacs.utils.random.SoftOneOfN
Generates an array of length number with one entry getting the value 1-epsilon and all the others equal parts of epsilon.
generate(double[], int, int) - Method in class de.jstacs.utils.random.SoftOneOfN
Generates an array of length number as part of the array d beginning at index start with one entry getting the value 1-epsilon and all the others equal parts of epsilon.
generateLog(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.DirichletMRG
Fills a part of the array d beginning at start with n logarithmic values.
GenericComplementableDiscreteAlphabet - Class in de.jstacs.data.alphabets
This class implements an generic complementable discrete alphabet.
GenericComplementableDiscreteAlphabet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet
The standard constructor for the interface Storable.
GenericComplementableDiscreteAlphabet(GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet
This constructor creates a GenericComplementableDiscreteAlphabet from a parameter set.
GenericComplementableDiscreteAlphabet(boolean, String[], int[]) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet
The main constructor.
GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet - Class in de.jstacs.data.alphabets
This class is used as container for the parameters of a GenericComplementableDiscreteAlphabet.
GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet() - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet
This constructor creates an empty parameter set the has to be filled before it can be used to create a GenericComplementableDiscreteAlphabet.
GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet(String[], boolean, int[]) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet
The main constructor.
GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet
The standard constructor for the interface Storable.
GEQ - Static variable in interface de.jstacs.parameters.validation.Constraint
The condition is greater or equal
get(int) - Method in class de.jstacs.AnnotatedEntityList
Returns the AnnotatedEntity at index index in the list.
get(String) - Method in class de.jstacs.AnnotatedEntityList
Returns the AnnotatedEntity with name name in the list.
get(int) - Method in class de.jstacs.utils.DoubleList
Returns the element with the specified index.
get(int) - Method in class de.jstacs.utils.IntList
Returns the element with the specified index.
getAbsoluteKMereFrequencies(DataSet, int, boolean) - Static method in class de.jstacs.motifDiscovery.KMereStatistic
This method enables the user to get a statistic over all k-mers in the data.
getAbsoluteKMereFrequencies(DataSet, int, boolean, DataSet.WeightedDataSetFactory.SortOperation) - Static method in class de.jstacs.motifDiscovery.KMereStatistic
This method enables the user to get a statistic over all k-mers in the data.
getAcceptedMimeType() - Method in class de.jstacs.parameters.FileParameter
Returns the MIME-type of the allowed files.
getAdaptVariance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet
Returns true if the sampling variance shall be adapted to the size of the event space of a random variable
getAdditionalInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
 
getAdditionalInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
This method returns a StringBuffer containing additional information for the XML representation.
getAdditionalInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior
 
getAlgorithm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet
This method returns a byte encoding for the algorithm that should be used for optimization.
getAlignedString(int) - Method in class de.jstacs.algorithms.alignment.StringAlignment
Returns the aligned String with index index.
getAlignment(Sequence, Sequence) - Method in class de.jstacs.algorithms.alignment.Alignment
Computes and returns the alignment of s1 and s2 (Alignment.Alignment(AlignmentType, Costs)).
getAlignment(Sequence, int, int, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.Alignment
Computes and returns the alignment of s1 and s2 (Alignment.Alignment(AlignmentType, Costs)).
getAllConditionalStationaryDistributions() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
This method returns the stationary conditional distributions.
getAllConditionalStationaryDistributions(double[], int) - Static method in class de.jstacs.utils.StationaryDistribution
This method returns the conditional stationary distributions, i.e. 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.
getAllElements() - Method in class de.jstacs.data.DataSet
Returns an array of Sequences containing all elements of this DataSet.
getAllLeafs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
This method returns a list of PhyloNodes that are leafs in the subtree starting from this instance
getAllLeafs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
This method returns a list of PhyloNodes that represent the leafs of the tree
getAllMeasures() - Method in class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
Returns an array of all contained performance measures.
getAllowedNumberOfClasses() - Method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
This method returns the allowed number of classes.
getAllowedNumberOfClasses() - Method in class de.jstacs.classifiers.performanceMeasures.ClassificationRate
 
getAllowedNumberOfClasses() - Method in class de.jstacs.classifiers.performanceMeasures.ConfusionMatrix
 
getAllowedNumberOfClasses() - Method in class de.jstacs.classifiers.performanceMeasures.TwoClassAbstractPerformanceMeasure
 
getAllParameterNames() - Method in class de.jstacs.parameters.ParameterSet
Returns the names of all Parameters in this ParameterSet.
getAlphabetAt(int) - Method in class de.jstacs.data.AlphabetContainer
Returns the underlying Alphabet of position pos.
getAlphabetContainer() - Method in class de.jstacs.classifiers.AbstractClassifier
This method returns the container of alphabets that is used in the classifier.
getAlphabetContainer() - Method in class de.jstacs.data.DataSet
Returns the AlphabetContainer of this DataSet.
getAlphabetContainer() - Method in class de.jstacs.data.sequences.Sequence
Return the alphabets, i.e. the AlphabetContainer, used in this Sequence.
getAlphabetContainer() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
Returns the AlphabetContainer of the current instance.
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getAlphabetContainer() - Method in interface de.jstacs.sequenceScores.SequenceScore
Returns the container of alphabets that were used when constructing the instance.
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner
This method returns the AlphabetContainer of the StructureLearner.
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getAlphabetContainer() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission
This method returns the AlphabetContainer of this emission.
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getAlphabetContainer() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getAlphabetIndexForPosition(int) - Method in class de.jstacs.data.AlphabetContainer
This method returns the index of the Alphabet that is used for the given position.
getAlphabetLengthAt(int) - Method in class de.jstacs.data.AlphabetContainer
Returns the length of the underlying Alphabet of position pos.
getAnnotation() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet
Returns a Collection of parameters containing informations about this ClassifierAssessmentAssessParameterSet.
getAnnotation() - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet
 
getAnnotation() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet
 
getAnnotation() - Method in class de.jstacs.classifiers.assessment.RepeatedSubSamplingAssessParameterSet
 
getAnnotation() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet
 
getAnnotation(DataSet...) - Static method in class de.jstacs.data.DataSet
Returns the annotation for an array of DataSets.
getAnnotation() - Method in class de.jstacs.data.DataSet
Returns some annotation of the DataSet.
getAnnotation() - Method in class de.jstacs.data.sequences.Sequence
Returns the annotation of the Sequence.
getAnnotation() - Method in class de.jstacs.io.AbstractStringExtractor
Returns the annotation of the source.
getAnnotation() - Method in class de.jstacs.results.ListResult
Returns a reference to the annotation of this ListResult.
getAnnotations() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
Returns the additional annotations of this SequenceAnnotation as given in the constructor.
getAnnotations() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
This method returns the SequenceAnnotation[] for each dimension of this multidimensional sequence.
getAnnotationTypesAndIdentifier() - Method in class de.jstacs.data.DataSet
This method returns all SequenceAnnotation types and the corresponding identifier which occur in this DataSet.
getArrowOption(NumberFormat, double, double, String, boolean) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the option for an edge in Graphviz.
getAsymIndex(int, int[], byte) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Returns the index for an asymmetric tensor.
getAverageElementLength() - Method in class de.jstacs.data.DataSet
Returns the average length of all Sequences in this DataSet.
getBest(int, int[], byte) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
Returns the maximal weight which can be reached for an edge from k nodes from the (encoded) set par to the node child.
getBestParameters() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
Returns the sampled parameter values with the maximum value of the objective function
getBeta(LearningPrinciple) - Static method in enum de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple
This method returns the standard weights for a predefined key.
getBindingSites(DataSet, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This method returns a DataSet containing the predicted binding sites.
getBindingSites(int, DataSet, int, int, int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This method returns a DataSet containing the predicted binding sites.
getBooleanFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
Returns the boolean which is the value of the Parameter par.
getBorder(double[], double) - Static method in class de.jstacs.classifiers.utils.PValueComputation
This method finds the first index that has a significant score.
getBurnInTest() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.SamplingHMMTrainingParameterSet
This method return the burn in test to be used during sampling.
getByteFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
Returns the byte which is the value of the Parameter par.
getCharacteristics() - Method in class de.jstacs.classifiers.AbstractClassifier
Returns some information characterizing or describing the current instance of the classifier.
getCharacteristics() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getCharacteristics() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getCharacteristics() - Method in interface de.jstacs.sequenceScores.SequenceScore
Returns some information characterizing or describing the current instance.
getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getChild(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the state index encoded by the child index.
getChildIdx(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getChildIdx(int, int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns the child index of the state, if this state is no child of the context -1 is returned
getChildrenNodes() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
This method returns a list of PhyloNodes that are children of this instance
getClassifier() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
Returns a deep copy of all classifiers that have been or will be used in this assessment.
getClassifierAnnotation() - Method in class de.jstacs.classifiers.AbstractClassifier
Returns an array of Results of dimension AbstractClassifier.getNumberOfClasses() that contains information about the classifier and for each class.
getClassifierAnnotation() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.classifiers.MappingClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getClassifierAnnotation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureClassifier
 
getClassifierForBestParameters(GenDisMixClassifierParameterSet) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
Returns a standard, i.e., non-sampling, GenDisMixClassifier, where the parameters are set to those that yielded the maximum value of the objective functions among all sampled parameter values.
getClassifierForMeanParameters(GenDisMixClassifierParameterSet, boolean, int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
Returns a standard, i.e., non-sampling, GenDisMixClassifier, where the parameters are set to the mean values over all sampled parameter values in the stationary phase.
getClassName() - Method in class de.jstacs.results.StorableResult
Returns the name of the class of the Storable corresponding to the XML representation stored in this StorableResult.
getClassParams(double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
Returns from the complete vector of parameters those that are for the classes.
getClassWeight(int) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
Returns the class weight for the class with a given index.
getClassWeights() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
Returns the specific class weights of a AbstractScoreBasedClassifier.
getClazz() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
Returns the source of the data to compute the mutual information as defined by this set of parameters.
getClazz() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
Returns the source of the data to compute the mutual information as defined by this set of parameters.
getCMI(double[][][][][][], double[][][][][][], double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Computes the conditional mutual information from fgStats and bgStats counted on sequences with a total weight of n.
getCMI(double[][][][], double[][][][], double, double, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Computes the conditional mutual information from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.
getCode(int, String) - Method in class de.jstacs.data.AlphabetContainer
Returns the encoded symbol for sym of the Alphabet of position pos of this AlphabetContainer.
getCode(String) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
Returns the code of a given symbol.
getCollectionOfAllMeasures(int, boolean) - Static method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
This method creates an instance of an SelectionParameter that can be used to create an instance of PerformanceMeasureParameterSet or NumericalPerformanceMeasureParameterSet.
getCollectionOfScales() - Static method in class de.jstacs.parameters.RangeParameter
Returns a EnumParameter that allows the user to choose between different scales.
getColor(int) - Static method in class de.jstacs.utils.galaxy.GalaxyAdaptor
Returns the color for a specified depth within the parameter hierarchy.
getCombination() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.CombinationIterator
Returns a clone of the internal combination.
getComment() - Method in class de.jstacs.AnnotatedEntity
Returns the comment on the AnnotatedEntity.
getComment(Class<? extends ParameterSet>) - Static method in class de.jstacs.parameters.ParameterSet
Returns a comment for the class.
getComment(ParameterSet) - Static method in class de.jstacs.parameters.ParameterSet
Returns a comment for the ParameterSet.
getComments() - Method in enum de.jstacs.data.DinucleotideProperty
Returns additional comments on this property.
getCommonString(DataSet, int, boolean) - Static method in class de.jstacs.motifDiscovery.KMereStatistic
This method returns an array of 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
 
getComplementaryCode(int) - Method in class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet
 
getComponents() - Method in class de.jstacs.algorithms.graphs.UnionFind
Returns the connected components of the graph.
getCompositeContainer(int[], int[]) - Method in class de.jstacs.data.AlphabetContainer
Returns an AlphabetContainer of Alphabets e.g. for composite motifs/sequences.
getCompositeDataSet(int[], int[]) - Method in class de.jstacs.data.DataSet
This method enables you to use only composite Sequences of all elements in the current DataSet.
getCompositeSequence(AlphabetContainer, int[], int[]) - Method in class de.jstacs.data.sequences.Sequence
This method should be used if one wants to create a DataSet of Sequence.CompositeSequences.
getCompositeSequence(int[], int[]) - Method in class de.jstacs.data.sequences.Sequence
This is a very efficient way to create a Sequence.CompositeSequence for sequences with a simple AlphabetContainer.
getConditionIndex(boolean, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
This method returns an index encoding the condition.
getConditionIndex(boolean, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.DiscreteEmission
 
getConditionIndex(boolean, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.ReferenceSequenceDiscreteEmission
 
getConservedPatterns(Hashtable<Sequence, BitSet[]>, int, int) - Static method in class de.jstacs.motifDiscovery.KMereStatistic
This method returns a list of Sequences.
getContent() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation
Returns the content of the file.
getContext(String[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns a String representation of the context.
getCorrectedPosition(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
Returns the value of the corrected position index.
getCost() - Method in class de.jstacs.algorithms.alignment.StringAlignment
Returns the costs.
getCostFor(Sequence, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
 
getCostFor(Sequence, Sequence, int, int) - Method in interface de.jstacs.algorithms.alignment.cost.Costs
Returns the costs for the alignment of s1(i) and s2(j).
getCostFor(Sequence, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.cost.MatrixCosts
 
getCostFor(Sequence, Sequence, int, int) - Method in class de.jstacs.algorithms.alignment.cost.SimpleCosts
 
getCount(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns the current count with index index.
getCounts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the current counts for this parameter.
getCurrentAnnotation() - Method in class de.jstacs.data.sequences.annotation.NullSequenceAnnotationParser
 
getCurrentAnnotation() - Method in interface de.jstacs.data.sequences.annotation.SequenceAnnotationParser
This method returns the current SequenceAnnotation.
getCurrentAnnotation() - Method in class de.jstacs.data.sequences.annotation.SimpleSequenceAnnotationParser
 
getCurrentAnnotation() - Method in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
 
getCurrentParameterSet() - Method in class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
 
getCurrentParameterSet() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
This method returns the current ParameterSet of the classifier.
getCurrentParameterSet() - Method in class de.jstacs.data.AlphabetContainer
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.Alphabet
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
 
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet
 
getCurrentParameterSet() - Method in interface de.jstacs.InstantiableFromParameterSet
Returns the InstanceParameterSet that has been used to instantiate the current instance of the implementing class.
getCurrentParameterSet() - Method in class de.jstacs.sampling.AbstractBurnInTest
 
getCurrentParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getCurrentParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
 
getCurrentParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
 
getCurrentParameterValues() - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore
Returns a double array of dimension DifferentiableSequenceScore.getNumberOfParameters() containing the current parameter values.
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MultiDimensionalSequenceWrapperDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getCurrentParameterValues() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getCurrentSequenceAnnotations() - Method in class de.jstacs.io.AbstractStringExtractor
Returns the SequenceAnnotation or null if no SequenceAnnotation is available.
getCurrentSequenceAnnotations() - Method in class de.jstacs.io.InfixStringExtractor
 
getCurrentSequenceAnnotations() - Method in class de.jstacs.io.LimitedStringExtractor
 
getCurrentSequenceAnnotations() - Method in class de.jstacs.io.SparseStringExtractor
 
getData() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
 
getData() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.OneDataSetLogGenDisMixFunction
 
getData() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction
Returns the data for each class used in this OptimizableFunction.
getDataSet() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory
Returns the DataSet, where each Sequence occurs only once.
getDataSet(AlphabetContainer, String, SequenceAnnotationParser) - Static method in class de.jstacs.data.sequences.ArbitraryFloatSequence
This method allows to create a DataSet containing ArbitraryFloatSequences using a file name.
getDataSet(AlphabetContainer, String) - Static method in class de.jstacs.data.sequences.ArbitraryFloatSequence
This method allows to create a DataSet containing ArbitraryFloatSequences using a file name.
getDataSet(AlphabetContainer, AbstractStringExtractor...) - Static method in class de.jstacs.data.sequences.ArbitraryFloatSequence
This method allows to create a DataSet containing ArbitraryFloatSequences.
getDataSet(AlphabetContainer, String, SequenceAnnotationParser) - Static method in class de.jstacs.data.sequences.SparseSequence
This method allows to create a DataSet containing SparseSequences using a file name.
getDataSet(AlphabetContainer, String) - Static method in class de.jstacs.data.sequences.SparseSequence
This method allows to create a DataSet containing SparseSequences using a file name.
getDataSet(AlphabetContainer, AbstractStringExtractor...) - Static method in class de.jstacs.data.sequences.SparseSequence
This method allows to create a DataSet containing SparseSequences.
getDataSetForProperty(DataSet, DinucleotideProperty) - Static method in enum de.jstacs.data.DinucleotideProperty
Creates a new DataSet by converting each Sequence in original to the DinucleotideProperty property.
getDataSetForProperty(DataSet, DinucleotideProperty.Smoothing, boolean, DinucleotideProperty) - Static method in enum de.jstacs.data.DinucleotideProperty
Creates a new DataSet by converting each Sequence in original to the DinucleotideProperty property using the DinucleotideProperty.Smoothing smoothing.
getDataSetForProperty(DataSet, DinucleotideProperty...) - Static method in enum de.jstacs.data.DinucleotideProperty
Creates a new DataSet by converting each Sequence in original to the DinucleotidePropertys properties and setting these as ReferenceSequenceAnnotation of each original sequence.
getDataSetForProperty(DataSet, DinucleotideProperty.Smoothing, boolean, DinucleotideProperty...) - Static method in enum de.jstacs.data.DinucleotideProperty
Creates a new DataSet by converting each Sequence in original to the DinucleotidePropertys properties and adding or setting these as ReferenceSequenceAnnotation of each original sequence.
getDataSplitMethod() - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet
Returns the DataSet.PartitionMethod defining how the mutually exclusive random-splits of user supplied data are generated.
getDataSplitMethod() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet
Returns the DataSet.PartitionMethod defining how the mutually exclusive random-splits of user supplied data are generated.
getDataSplitMethod() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet
Returns the DataSet.PartitionMethod defining how the mutually exclusive random-splits of user supplied data are generated.
getDatatype() - Method in class de.jstacs.AnnotatedEntity
Returns the data type of the AnnotatedEntity.
getDefault() - Method in class de.jstacs.parameters.SelectionParameter
Returns the index of the default selected value.
getDeleteOnExit() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
Returns true if the temporary parameter files shall be deleted on exit of the program.
getDelim() - Method in class de.jstacs.data.AlphabetContainer
Returns the delimiter that should be used (for writing e.g. a sequence).
getDepth() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the depth of the tree, i.e. the number of parents of this parameter.
getDescendant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the index of the descendant transition element when following the child with index index
getDescription() - Method in class de.jstacs.io.RegExFilenameFilter
 
getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns the decoded symbol for the encoded symbol i.
getDescription() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
Returns a short description of the model that was given by the user in the parameter set.
getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
 
getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
 
getDescription(AlphabetContainer, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhConstraint
 
getDifferentiableSequenceScore(int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
Returns the internally used DifferentiableSequenceScore with index i.
getDifferentiableSequenceScores() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
Returns all internally used DifferentiableSequenceScores in the internal order.
getDifferentiableStatisticalModels() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
Returns a deep copy of all internal used DifferentiableStatisticalModels.
getDimension() - Method in enum de.jstacs.data.DinucleotideProperty
Returns the dimension of this property, e.g. kcal/mol or angstroem.
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.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLaplaceLogPrior
 
getDimensionOfScope() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
 
getDinucleotideParameters() - Method in enum de.jstacs.data.DinucleotideProperty
Returns the dinucleotide parameters of this DinucleotideProperty as a two-dimensional double array, where the rows correspond to the first nucleotide and the columns correspond to the second nucleotide in the dinucleotide in order A, C, G, and T.
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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Computes the explaining away residual from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.
getEAR(double[][][][], double[][][][], double, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Computes the explaining away residual from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.
getEdgeFromIndex(int, int) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
This method decodes an index in an edge.
getElapsedTime() - Method in class de.jstacs.utils.RealTime
 
getElapsedTime() - Method in class de.jstacs.utils.Time
Returns the elapsed time since invoking the constructor.
getElapsedTime() - Method in class de.jstacs.utils.UserTime
 
getElement(int) - Method in class de.jstacs.io.StringExtractor
Returns String number idx that has been extracted.
getElement() - Method in class de.jstacs.utils.ComparableElement
This method returns the element.
getElementAt(int) - Method in class de.jstacs.data.DataSet
This method returns the element, i.e. the Sequence, with index i.
getElementAt(int) - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory
Returns the Sequence with index index.
getElementLength() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet
Returns the length of elements (sequences) defined by this ClassifierAssessmentAssessParameterSet.
getElementLength() - Method in class de.jstacs.data.DataSet
Returns the length of the elements, i.e. the Sequences, in this DataSet.
getElongateCosts() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
Returns the costs to elongate a gap by one position.
getEmptyContainer() - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.MultiDimensionalArbitrarySequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.MultiDimensionalDiscreteSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.Sequence
The method returns a container that can be used for accessing the symbols for each position.
getEmptyContainer() - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
 
getEmptyContainer() - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.Sequence
Returns an empty representation which is used to create the String representation of this instance in the method Sequence.toString(String, int, int).
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
 
getEmptyRepresentation() - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
 
getEnd() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
Returns the end of this LocatedSequenceAnnotationWithLength, i.e.
getEndIndexOfAlignmentForFirst() - Method in class de.jstacs.algorithms.alignment.PairwiseStringAlignment
This method returns the end index of the alignment in the first sequence.
getEndNode() - Method in class de.jstacs.algorithms.graphs.Edge
Returns the end node of the edge.
getEndValue() - Method in class de.jstacs.parameters.RangeParameter
Returns the last value of a range of parameter values or null if no range was specified.
getEntropy(Constraint) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.ConstraintManager
Tries to compute the entropy of a Constraint as exact as possible.
getErrorMessage() - Method in class de.jstacs.parameters.AbstractSelectionParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.FileParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.Parameter
If a value could not be set successfully this method returns the corresponding error message.
getErrorMessage() - Method in class de.jstacs.parameters.ParameterSet
Returns the message of the last error that occurred.
getErrorMessage() - Method in class de.jstacs.parameters.ParameterSetContainer
 
getErrorMessage() - Method in class de.jstacs.parameters.RangeParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.SelectionParameter
 
getErrorMessage() - Method in class de.jstacs.parameters.SimpleParameter
 
getErrorMessage() - Method in interface de.jstacs.parameters.validation.Constraint
Returns the message of the last error (missed constraint) or null if the constraint was fulfilled by the last checked value.
getErrorMessage() - Method in class de.jstacs.parameters.validation.ConstraintValidator
 
getErrorMessage() - Method in class de.jstacs.parameters.validation.NumberValidator
 
getErrorMessage() - Method in interface de.jstacs.parameters.validation.ParameterValidator
Returns the error message if ParameterValidator.checkValue(Object) returned false.
getErrorMessage() - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint
 
getErrorMessage() - Method in class de.jstacs.parameters.validation.StorableValidator
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getESS() - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel
Returns the equivalent sample size (ess) of this model, i.e. the equivalent sample size for the class or component that is represented by this model.
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
Returns the equivalent samples size (ess) defined in this set of parameters.
getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
Returns the equivalent sample sizes (ess) defined by this set of parameters.
getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
Returns the equivalent sample sizes (ess) defined by this set of parameters.
getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
Returns the equivalent sample sizes (ess) defined by this set of parameters.
getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
Returns the equivalent sample sizes (ess) defined by this set of parameters.
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
This method returns the ess (equivalent sample size) that is used in this model.
getEss() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner
This method returns the ess (equivalent sample size) of the StructureLearner.
getESS() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getExceptionIfMPNotComputable() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessmentAssessParameterSet
Returns the flag defined by this ClassifierAssessmentAssessParameterSet.
getExpLambda(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
Returns the exponential value of $\lambda_{index}$ at position index: $\exp(\lambda_{index})$.
getExpValue() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns Math.exp(BNDiffSMParameter.getValue()), which is pre-computed.
getExtension() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
Returns the filename extension
getExtremum() - Method in class de.jstacs.algorithms.optimization.QuadraticFunction
This method returns the extremum of the QuadraticFunction.
getFactorForAucPR() - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This method returns a factor that must be multiplied to scores for computing PR curves.
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.
getFilename() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
Returns the filename.
getFinalStatePosterioriMatrix(double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method is used if AbstractHMM.fillLogStatePosteriorMatrix(double[][], int, int, Sequence, boolean) is used with code>silentZero==true to eliminate the first row.
getFirstElement() - Method in class de.jstacs.utils.Pair
This method returns the first element.
getFirstParent() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
Returns the first parent of the random variable of this BNDiffSMParameterTree in the topological ordering of the network structure of the enclosing BayesianNetworkDiffSM.
getFloatFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
Returns the float which is the value of the Parameter par.
getForwardProbability() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
This methoth returns the a-priori probability for the forward strand.
getFreeParameters() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet
Returns true if only free parameters shall be used
getFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns the current frequency with index index.
getFreq(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
This method determines the specific constraint that is fulfilled by the Sequence seq beginning at position start.
getFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
 
getFreqInfo(AlphabetContainer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns an information about the stored frequencies.
getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
 
getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
Returns the function that should be sampled from.
getFunction(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
Returns the function that should be optimized.
getFunction() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
This method return the internal function.
getFunction(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This method returns a specific internal function.
getFunction() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
This method returns the internal function.
getFunction() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
Returns a copy of the internally used DifferentiableStatisticalModel.
getFunctions() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
This method returns a deep copy of the internally used DifferentiableSequenceScore.
getFunctions() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This method returns an array of clones of the internal used functions.
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.AbstractClassifier
This method returns further information of a classifier as a StringBuffer.
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.MappingClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getFurtherClassifierInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureClassifier
 
getFurtherInformation() - Method in class de.jstacs.sampling.AbstractBurnInTest
This method returns further information for the AbstractBurnInTest.
getFurtherInformation() - Method in class de.jstacs.sampling.VarianceRatioBurnInTest
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
This method is used to append further information of the instance to the XML representation.
getFurtherInformation() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
This method is used to append further information of the instance to the XML representation.
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This method is used to append further information of the instance to the XML representation.
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method is used in the subclasses to append further information to the XML representation.
getFurtherInformation() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
 
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
Returns further model information as a StringBuffer.
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getFurtherModelInfos() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
 
getGapCosts() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
 
getGapCosts() - Method in interface de.jstacs.algorithms.alignment.cost.Costs
Returns the costs for a gap.
getGapCosts() - Method in class de.jstacs.algorithms.alignment.cost.MatrixCosts
 
getGapCosts() - Method in class de.jstacs.algorithms.alignment.cost.SimpleCosts
 
getGapCostsFor(int) - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
Returns the costs for a gap of length length.
getGeneralizedDivergence(double[][], double[][], double) - Static method in class de.jstacs.utils.StatisticalTest
Computes the generalized divergence for two given stochastic matrices over the same domain, i.e. the matrices have to have the same dimensionality.
getGeneralizedDivergence(double[][], double[], double[], double) - Static method in class de.jstacs.utils.StatisticalTest
Computes the generalized divergence for two stochastic matrices over the same domain, i.e. the matrices have to have the same dimensionality.
getGeneralizedDivergence(double[][], double) - Static method in class de.jstacs.utils.StatisticalTest
Computes the generalized divergence for two stochastic matrices over the same domain, i.e. the matrices have to have the same dimensionality.
getGlobalIndexOfMotifInComponent(int, int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
Returns the global index of the motif used in component.
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getGlobalIndexOfMotifInComponent(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getGraphizNetworkRepresentation(NumberFormat, String, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getGraphizNetworkRepresentation(NumberFormat, String, boolean) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns a String representation of the structure that can be used in Graphviz to create an image.
getGraphvizEdgeWeight(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the edge weight for plotting the edge with Graphviz.
getGraphvizNodeOptions(double, double, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState
 
getGraphvizNodeOptions(double, double, NumberFormat) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.State
This method returns a String representation of the node options that can be used in Graphviz to create the node for this state.
getGraphvizRepresentation(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns a String representation of the structure that can be used in Graphviz to create an image.
getGraphvizRepresentation(NumberFormat, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns a String representation of the structure that can be used in Graphviz to create an image.
getGraphvizRepresentation(NumberFormat, DataSet, double[], boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns a String representation of the structure that can be used in Graphviz to create an image.
getGraphvizRepresentation(NumberFormat, DataSet, double[], HashMap<String, String>) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns a String representation of the structure that can be used in Graphviz to create an image.
getHammingDistance(Sequence) - Method in class de.jstacs.data.sequences.Sequence
This method returns the Hamming distance between the current Sequence and seq.
getHashMap() - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory
This method returns a HashMap that can be used in AbstractHMM.getGraphvizRepresentation(java.text.NumberFormat, de.jstacs.data.DataSet, double[], HashMap) to create a Graphviz representation of the AbstractHMM
getHowCreated() - Method in enum de.jstacs.data.DinucleotideProperty
Returns how this property has been determined.
getHtmlFilesPath() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor
Returns the path where files, e.g. images, that shall be linked from the HTML summary shall be stored in.
getHtmlId() - Static method in class de.jstacs.utils.galaxy.GalaxyAdaptor
Gets a unique id that can be used, e.g. to create unique filenames.
getHyperparameter(int) - Method in class de.jstacs.utils.random.DiMRGParams
Returns the value at position i of the hyperparameter vector of the underlying Dirichlet distribution.
getHyperparameter(int) - Method in class de.jstacs.utils.random.DirichletMRGParams
 
getHyperparameter(int) - Method in class de.jstacs.utils.random.ErlangMRGParams
Returns the value at position i of the hyperparameter vector of the underlying Erlang distribution.
getHyperparameter(int) - Method in class de.jstacs.utils.random.FastDirichletMRGParams
 
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This method returns the hyperparameter for the hidden parameter with index index.
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getHyperParams(int, int, double, double[], double[][][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
This method returns the hyper-parameters for a model given some a-priori probabilities.
getHyperParams(double, int, int) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
Returns the hyper-parameters for all parameters and a given ess.
getId() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
This method returns the ID of the current PhyloNode
getIdentifier() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
Returns the identifier of this SequenceAnnotation as given in the constructor.
getImage(double[][], REnvironment) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater
This method can be used to create an image of a mutual information matrix.
getImmutableInstance() - Static method in class de.jstacs.utils.NullProgressUpdater
Returns a reference to the same NullProgressUpdater that is immutable.
getIndex(double[], double) - Static method in class de.jstacs.classifiers.utils.PValueComputation
This method searches in sortedScores for the index i so that sortedScores[i-1] < myScore <= sortedScores[i].
getIndex(double[], double, int) - Static method in class de.jstacs.classifiers.utils.PValueComputation
This method searches in sortedScores beginning at start for the index i so that sortedScores[i-1] < myScore <= sortedScores[i].
getIndex(int) - Method in class de.jstacs.data.sequences.PermutedSequence
 
getIndex(int) - Method in class de.jstacs.data.sequences.Sequence.CompositeSequence
 
getIndex(int) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
Returns the index in the internal sequence.
getIndex(int) - Method in class de.jstacs.data.sequences.Sequence.SubSequence
 
getIndex(String[], Object[], Comparable, boolean) - Static method in class de.jstacs.parameters.ParameterSet
This method tries to find the correct name (String) for your choice.
getIndex() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the index of this parameter as defined in the constructor.
getIndex(int[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.CombinationIterator
This method returns an index for the sorted entries of a combination combi.
getIndex(int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
Returns the distance integrated into the transition from pos - 1 to pos in sequences seq.
getIndex(int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
Returns the index of the transition matrix used for the transition from pos - 1 to pos in sequences seq.
getIndexForAlphabets() - Method in class de.jstacs.data.AlphabetContainer
This method returns an object that is used for assigning the positions of the Sequences to specific Alphabets.
getIndexOfMaximalComponentFor(Sequence) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
Returns the index of the component with the maximal score for the sequence sequence.
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getIndexOfMaximalComponentFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
Returns the index of the component that has the greatest impact on the complete score for a Sequence.
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns the index i of the component with P(i|s) maximal.
getIndices() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
This method returns a deep copy of the internally used indices of the DifferentiableSequenceScore for the parts.
getIndices(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This array is used to compute the relative indices of a parameter index.
getInfixDataSet(int, int) - Method in class de.jstacs.data.DataSet
This method enables you to use only an infix of all elements, i.e. the Sequences, in the current DataSet.
getInfos() - Method in class de.jstacs.results.MeanResultSet
Returns some information for this MeanResultSet.
getInitialClassParam(double) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getInitialClassParam(double) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore
Returns the initial class parameter for the class this DifferentiableSequenceScore is responsible for, based on the class probability classProb.
getInitialClassParam(double) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getInitialClassParam(double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getInstance(SequenceAnnotation[], Sequence...) - Method in class de.jstacs.data.sequences.MultiDimensionalArbitrarySequence
 
getInstance(SequenceAnnotation[], Sequence...) - Method in class de.jstacs.data.sequences.MultiDimensionalDiscreteSequence
 
getInstance(SequenceAnnotation[], Sequence...) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
getInstance() - Method in class de.jstacs.parameters.InstanceParameterSet
Returns a new instance of the class of InstanceParameterSet.getInstanceClass() that was created using this ParameterSet.
getInstanceClass() - Method in class de.jstacs.parameters.InstanceParameterSet
Returns the class of the instances that can be constructed using this set.
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
Deprecated.  
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.CombinedCondition.CombinedConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.IterationCondition.IterationConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition.SmallDifferenceOfFunctionEvaluationsConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.SmallGradientConditon.SmallGradientConditonParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.SmallStepCondition.SmallStepConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
 
getInstanceComment() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifierParameterSet
 
getInstanceComment() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifierParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
Returns a descriptive comment on this AlphabetContainerParameterSet.AlphabetArrayParameterSet.
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
Returns a descriptive comment on this AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet.
getInstanceComment() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet.DiscreteAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.DNAAlphabet.DNAAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.DNAAlphabetContainer.DNAAlphabetContainerParameterSet
 
getInstanceComment() - Method in class de.jstacs.data.alphabets.ProteinAlphabet.ProteinAlphabetParameterSet
 
getInstanceComment() - Method in class de.jstacs.parameters.InstanceParameterSet
Returns a comment (a textual description) of the class that can be constructed using this ParameterSet.
getInstanceComment() - Method in class de.jstacs.sampling.VarianceRatioBurnInTestParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet
 
getInstanceComment() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSDAGTrainSMParameterSet
 
getInstanceFromParameterSet(InstanceParameterSet<T>) - Static method in class de.jstacs.io.ParameterSetParser
Returns an instance of a subclass of InstantiableFromParameterSet that can be instantiated by the InstanceParameterSet pars.
getInstanceFromParameterSet(ParameterSet, Class<T>) - Static method in class de.jstacs.io.ParameterSetParser
Returns an instance of a subclass of InstantiableFromParameterSet that can be instantiated by the ParameterSet pars.
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
Deprecated.  
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.CombinedCondition.CombinedConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.IterationCondition.IterationConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition.SmallDifferenceOfFunctionEvaluationsConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.SmallGradientConditon.SmallGradientConditonParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.SmallStepCondition.SmallStepConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
 
getInstanceName() - Method in class de.jstacs.classifiers.AbstractClassifier
Returns a short description of the classifier.
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior
Returns a short instance name.
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLaplaceLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifierParameterSet
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifierParameterSet
 
getInstanceName() - Method in class de.jstacs.classifiers.MappingClassifier
 
getInstanceName() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
Returns a descriptive name for this AlphabetContainerParameterSet.AlphabetArrayParameterSet .
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
Returns a descriptive name for this AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet.
getInstanceName() - Method in class de.jstacs.data.alphabets.Alphabet.AlphabetParameterSet
 
getInstanceName() - Method in class de.jstacs.data.alphabets.DNAAlphabetContainer.DNAAlphabetContainerParameterSet
 
getInstanceName() - Method in class de.jstacs.parameters.InstanceParameterSet
Returns the name of an instance of the class that can be constructed using this ParameterSet.
getInstanceName() - Method in interface de.jstacs.sampling.BurnInTest
Returns a short description of the burn-in test.
getInstanceName() - Method in class de.jstacs.sampling.SimpleBurnInTest
Deprecated.  
getInstanceName() - Method in class de.jstacs.sampling.VarianceRatioBurnInTest
 
getInstanceName() - Method in class de.jstacs.sampling.VarianceRatioBurnInTestParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getInstanceName() - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getInstanceName() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getInstanceName() - Method in interface de.jstacs.sequenceScores.SequenceScore
Should return a short instance name such as iMM(0), BN(2), ...
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation.BTMutualInformationParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Returns the name of the Measure and possibly some additional information about the current instance.
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MultiDimensionalSequenceWrapperDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DGTrainSMParameterSet
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureClassifier
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingPhyloHMM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
Returns the instance name.
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getInstanceParameterSets() - Method in enum de.jstacs.data.AlphabetContainer.AlphabetContainerType
This method returns a LinkedList of InstanceParameterSets which can be used to create Alphabets that can be used in a AlphabetContainer of the given AlphabetContainer.AlphabetContainerType.
getInstanceParameterSets(Class<T>, String) - Static method in class de.jstacs.utils.SubclassFinder
This method returns a list of InstanceParameterSets that can be used to create a subclass of clazz.
getInternalPosition(int[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
Copies the current value of the internal iterator in the given array.
getIntFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
Returns the int which is the value of the Parameter par.
getK() - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet
Returns the number of mutually exclusive random-splits of user supplied data defined by this KFoldCrossValidationAssessParameterSet.
getKLDivergence(double[][][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
Returns the KL-divergence of the distribution of this BNDiffSMParameterTree and the distribution given by ds.
getKLDivergence(double[], double[][][][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
Returns the KL-divergence of the distribution of this BNDiffSMParameterTree and a number of distribution given by ds and weighted by weight
getKLDivergence(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester
Returns the Kullback-Leibler-divergence D(p_m1||p_m2).
getKmereSequenceStatistic(int, boolean, int, DataSet...) - Static method in class de.jstacs.motifDiscovery.KMereStatistic
This method enables the user to get a statistic over all k-mers in the sequences.
getKmereSequenceStatistic(boolean, int, HashSet<Sequence>, DataSet...) - Static method in class de.jstacs.motifDiscovery.KMereStatistic
This method enables the user to get a statistic for a set of k-mers.
getLabel(String[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns a label for the state.
getLambda(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
Returns the value of $\lambda_{index}$.
getLastContextState(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLastContextState(int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
The method returns the index of the state of the context, if there is no context -1 is returned.
getLastScore() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
Returns the score that was computed in the last optimization of the parameters.
getLegalName(String) - Static method in class de.jstacs.utils.galaxy.GalaxyAdaptor
Returns a legal variable name in Galaxy
getLength() - Method in class de.jstacs.algorithms.alignment.StringAlignment
This method return the length of the alignment.
getLength() - Method in class de.jstacs.classifiers.AbstractClassifier
Returns the length of the sequences this classifier can handle or 0 for sequences of arbitrary length.
getLength() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
Returns the length of this LocatedSequenceAnnotationWithLength as given in the constructor.
getLength() - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getLength() - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getLength() - Method in class de.jstacs.data.sequences.ByteSequence
 
getLength() - Method in class de.jstacs.data.sequences.IntSequence
 
getLength() - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
 
getLength() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
getLength() - Method in class de.jstacs.data.sequences.PermutedSequence
 
getLength() - Method in class de.jstacs.data.sequences.Sequence.CompositeSequence
 
getLength() - Method in class de.jstacs.data.sequences.Sequence
Returns the length of the Sequence.
getLength() - Method in class de.jstacs.data.sequences.Sequence.SubSequence
 
getLength() - Method in class de.jstacs.data.sequences.ShortSequence
 
getLength() - Method in class de.jstacs.data.sequences.SparseSequence
 
getLength() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
Returns the length of the sequences the model can work on.
getLength() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLength() - Method in interface de.jstacs.sequenceScores.SequenceScore
Returns the length of sequences this instance can score.
getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
 
getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
Returns the length that is supported by this prior.
getLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior
 
getLengthArray(DifferentiableSequenceScore...) - Static method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
This method provides an array of lengths that can be used for instance as IndependentProductDiffSS.partialLength.
getLengthOfBurnIn() - Method in class de.jstacs.sampling.AbstractBurnInTest
 
getLengthOfBurnIn() - Method in interface de.jstacs.sampling.BurnInTest
Computes and returns the length of the burn-in phase using the values from BurnInTest.setValue(double).
getLengthOfBurnIn() - Method in class de.jstacs.sampling.SimpleBurnInTest
Deprecated.  
getLengthOfModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
This method returns the length of the models in the CompositeTrainSM.
getLine(int) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
Return the line with a given index from the table.
getLineEps() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet
This method returns the threshold that should be used for stopping the line search during the optimization.
getLink() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.LinkedImageResult
Returns the linked file
getList() - Method in class de.jstacs.parameters.RangeParameter
Returns a list of all parameter values as a String or null if no parameter values have been set.
getLnFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
Returns the logarithmic frequency at a given position index.
getLnFreq(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
Returns the logarithm of the relative frequency (=probability) at position index in the distribution.
getLnFreq(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
Returns the logarithm of the relative frequency (=probability) with the position in the distribution given by the index of the specific constraint that is fulfilled by the Sequence s beginning at start.
getLogCDF(double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.CDFOfNormal
This method computes the logarithm of the cumulative density function of a standard normal distribution.
getLogGammaScoreForCurrentStatistic() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SamplingState
This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics
getLogGammaScoreForCurrentStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogGammaScoreFromStatistic() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SamplingEmission
This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLogGammaScoreFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
 
getLogGammaScoreFromStatistic() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.TransitionWithSufficientStatistic
This method calculates a score for the current statistics, which is independent from the current parameters In general the gamma-score is a product of gamma-functions parameterized with the current statistics
getLogGammaSum(Constraint, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.ConstraintManager
Computes the sum of the differences between the logarithmic values of the prior knowledge and all counts of a Constraint c.
getLogLikelihood(StatisticalModel, DataSet) - Static method in class de.jstacs.utils.StatisticalModelTester
Returns the log-likelihood of a DataSet data for a given model m.
getLogLikelihood(StatisticalModel, DataSet, double[]) - Static method in class de.jstacs.utils.StatisticalModelTester
Returns the log-likelihood of a DataSet data for a given model m.
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogNormalizationConstant() - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel
Returns the logarithm of the sum of the scores over all sequences of the event space.
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getLogNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogNormalizationConstant(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM
This method returns the logarithm of the normalization constant for a given sequence length.
getLogNormalizationConstant() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
Computes the logarithm of the normalization constant for the component i.
getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogNormalizationConstantForComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getLogNumberOfPossibleOriginalSequences() - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
This method returns the logarithm of the number of original Sequences that yield the same mapped Sequence.
getLogNumberOfPossibleOriginalSequences(int, int) - Method in class de.jstacs.data.sequences.MappedDiscreteSequence
This method returns the logarithm of the number of original Sequences that yield the same mapped Sequence.
getLogNumberOfSimilarSymbols(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabetMapping
This method returns the logarithm of the number of old values that yield the same new value.
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogPartialNormalizationConstant(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel
Returns the logarithm of the partial normalization constant for the parameter with index parameterIndex.
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogPartialNormalizationConstant(int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM
This method returns the logarithm of the partial normalization constant for a given parameter index and a sequence length.
getLogPartialNormalizationConstant(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogPartialNormalizer() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the partial derivative of the normalization constant with respect to this parameter.
getLogPosteriorFromStatistic() - Method in interface de.jstacs.sampling.SamplingFromStatistic
This method calculates the a-posteriori probability for the current statistics
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
This method calculates the a posteriori probability for the current statistics
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
 
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
This method computes the log posterior from the internal sufficient statistic.
getLogPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getLogPriorForPositions(int, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.GaussianLikePositionPrior
Returns only the important part and leaving the logarithm of the normalization constant out.
getLogPriorForPositions(int, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
The logarithmic value of the prior for specified start positions of the part motifs.
getLogPriorForPositions(int, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.UniformPositionPrior
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel
This method computes a value that is proportional to DifferentiableStatisticalModel.getESS() * DifferentiableStatisticalModel.getLogNormalizationConstant() + Math.log( prior ) where prior is the prior for the parameters of this model.
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel
Returns a value that is proportional to the log of the prior.
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission
Returns a value that is proportional to the log of the prior.
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
Returns a value that is proportional to the log of the prior.
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
 
getLogPriorTerm() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
Returns a value that is proportional to the log of the prior.
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getLogPriorTerm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getLogPriorTermForComponentProbs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method computes the part of the prior that comes from the component probabilities.
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission
Returns the logarithmic score for a Sequence beginning at position start in the Sequence and fills lists with the indices and the partial derivations.
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogProbAndPartialDerivationFor(boolean, int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogProbFor(Sequence, int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel
Returns the logarithm of the probability of (a part of) the given sequence given the model.
getLogProbFor(Sequence, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel
Returns the logarithm of the probability of (a part of) the given sequence given the model.
getLogProbFor(Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel
Returns the logarithm of the probability of the given sequence given the model.
getLogProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogProbFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission
This method computes the logarithm of the likelihood.
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getLogProbFor(boolean, int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getLogProbFor(int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns the logarithmic probability for the sequence and the given component.
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getLogProbForPath(IntList, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getLogProbForPath(IntList, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogProbForPath(IntList, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns the logarithmic probability for the sequence and the given component using the current parameter set.
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
 
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.StrandTrainSM
 
getLogProposalPosteriorFromStatistic() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
Returns the log posterior of the proposal distribution for the current statistic
getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
This method enables the user to get the log-score without using a sequence object.
getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getLogScore(int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore
Returns the logarithmic score for a Sequence seq and fills lists with the indices and the partial derivations.
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore
Returns the logarithmic score for a Sequence beginning at position start in the Sequence and fills lists with the indices and the partial derivations.
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore
Returns the logarithmic score for a Sequence beginning at position start in the Sequence and fills lists with the indices and the partial derivations.
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
This method enables the user to get the log-score and the partial derivations without using a sequence object.
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getLogScoreAndPartialDerivation(IntList, DoubleList, int...) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MultiDimensionalSequenceWrapperDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM
 
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreAndPartialDerivation(int, int, IntList, DoubleList, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.DifferentiableState
This method allows to compute the logarithm of the score and the gradient for the given subsequences.
getLogScoreAndPartialDerivation(int, int, IntList, DoubleList, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleDifferentiableState
 
getLogScoreAndPartialDerivation(int, int, int, IntList, DoubleList, Sequence, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.DifferentiableTransition
This method allows to compute the logarithm of the score and the gradient for a specific transition.
getLogScoreAndPartialDerivation(int, IntList, DoubleList, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
Returns the logarithmic score and fills lists with the indices and the partial derivations.
getLogScoreAndPartialDerivation(int, int, int, IntList, DoubleList, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getLogScoreAndPartialDerivationForInternal(IntList, DoubleList) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
This method enables the user to get the log-score and the partial derivations without using a sequence object by using the internal iterator.
getLogScoreFor(Sequence) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getLogScoreFor(Sequence) - Method in interface de.jstacs.sequenceScores.SequenceScore
Returns the logarithmic score for the Sequence seq.
getLogScoreFor(Sequence, int) - Method in interface de.jstacs.sequenceScores.SequenceScore
Returns the logarithmic score for the Sequence seq beginning at position start in the Sequence.
getLogScoreFor(Sequence, int, int) - Method in interface de.jstacs.sequenceScores.SequenceScore
Returns the logarithmic score for the Sequence seq beginning at position start in the Sequence.
getLogScoreFor(DataSet) - Method in interface de.jstacs.sequenceScores.SequenceScore
This method computes the logarithm of the scores of all sequences in the given sample.
getLogScoreFor(DataSet, double[]) - Method in interface de.jstacs.sequenceScores.SequenceScore
This method computes and stores the logarithm of the scores for any sequence in the sample in the given double-array.
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.VariableLengthMixtureDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MultiDimensionalSequenceWrapperDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getLogScoreFor(Sequence, int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.VariableLengthDiffSM
 
getLogScoreFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getLogScoreFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreFor(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogScoreFor(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getLogScoreFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState
 
getLogScoreFor(int, int, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.State
This method returns the logarithm of the score for a given sequence with given start and end position.
getLogScoreFor(int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the score for the transition from the current context to the state with index index.
getLogScoreFor(int, int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getLogScoreFor(int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
 
getLogScoreFor(int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
 
getLogScoreFor(int, int, int, Sequence, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns the logarithm of the score for the transition.
getLogScoreFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getLogScoreForInternal() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
This method enables the user to get the log-score without using a sequence object by using the internal iterator.
getLogStatePosteriorMatrixFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns the log state posterior of all states for a sequence.
getLogStatePosteriorMatrixFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns the log state posteriors for all sequences of the sample data.
getLogStatePosteriorMatrixFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getLogSum(double...) - Static method in class de.jstacs.utils.Normalisation
Returns the logarithm of the sum of values val[i] given as lnVal[i] = Math.log( val[i] ).
getLogSum(int, int, double...) - Static method in class de.jstacs.utils.Normalisation
Returns the logarithm of the sum of values v[i] given as lnVal[i] = Math.log( val[i] ) between a start and end index.
getLogT() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the part of the normalization constant of parameters before this parameter in the structure of the network.
getLogZ() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the part of the normalization constant of parameters after this parameter in the structure of the network.
getLongFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
Returns the long which is the value of the Parameter par.
getLowerBound() - Method in class de.jstacs.parameters.validation.NumberValidator
Returns the lower bound of the NumberValidator.
getMarginalDistribution(StatisticalModel, int[]) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the marginal distribution for any discrete model m and all sequences that fulfill the constraint , if possible.
getMarginalOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns the marginal order, i.e. the number of used random variables.
getMax() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
Returns the maximal value of this alphabet.
getMax() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
Returns the maximal value that can be scored.
getMax(double[][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater
This method can be used to determine the maximal value of the matrix of mutual informations.
getMaximalAlphabetLength() - Method in class de.jstacs.data.AlphabetContainer
Returns the maximal Alphabet length of this AlphabetContainer.
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SubTensor
 
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Returns the edge permute(parents[0],...
getMaximalElementLength() - Method in class de.jstacs.data.DataSet
Returns the maximal length of an element, i.e. a Sequence, in this DataSet.
getMaximalInDegree() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getMaximalInDegree() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns the maximal out degree of any context used in this transition instance.
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM
Returns the maximal used markov oder.
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getMaximalMarkovOrder() - Method in interface de.jstacs.sequenceScores.statisticalModels.StatisticalModel
This method returns the maximal used Markov order, if possible.
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getMaximalMarkovOrder() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns the maximal used Markov order.
getMaximalMarkovOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getMaximalNumberOfChildren() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getMaximalNumberOfChildren() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns the maximal number of children for any context used in this transition instance.
getMaximalSymbolLength() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
Returns the length of the longest "symbol" in the alphabet.
getMaxIndex(double[]) - Static method in class de.jstacs.utils.ToolBox
Returns the index with maximal value in a double array.
getMaxIndex(int, int, double[]) - Static method in class de.jstacs.utils.ToolBox
Returns the index with maximal value in a double array.
getMaxOfDeviation(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the maximum deviation between the probabilities for all sequences of length for discrete models m1 and m2.
getMeanParameters(boolean, int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
Returns the mean parameters over all samplings of all stationary phases.
getMeasure(double, double, double, double) - Method in class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
 
getMeasure(double, double, double, double) - Method in class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
 
getMeasure(double, double, double, double) - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure
This measure compute the measure for a given confusion matrix
getMeasure() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
Returns the structure Measure defined by this set of parameters.
getMeasureName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
 
getMeasureName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
 
getMeasureName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure
This method returns a short name of the measure without any parameters.
getMI(double[][][][][][], double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Computes the mutual information from counts counted on sequences with a total weight of n.
getMI(double[][][][], double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Computes the mutual information from counts counted on sequences with a total weight of n.
getMIInBits(DataSet, double[]) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater
This method computes the pairwise mutual information (in bits) between the sequence positions.
getMin(int) - Method in class de.jstacs.data.AlphabetContainer
Returns the minimal value of the underlying Alphabet of position pos.
getMin() - Method in class de.jstacs.data.alphabets.Alphabet
Returns the minimal value of theAlphabet.
getMin() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
 
getMin() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
 
getMin() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
Returns the minimal value that can be scored.
getMinimalAlphabetLength() - Method in class de.jstacs.data.AlphabetContainer
Returns the minimal Alphabet length of this AlphabetContainer.
getMinimalElementLength() - Method in class de.jstacs.data.DataSet
Returns the minimal length of an element, i.e. a Sequence, in this DataSet.
getMinimalHyperparameter() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
This method returns the minimal hyper parameters of this TransitionElement.
getMinimalSequenceLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
Returns the minimal length a sequence respectively a sample has to have.
getMinimalSequenceLength() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getModel(int) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
Returns a clone of the TrainableStatisticalModel for a specified class.
getModel(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns a deep copy of the i-th model.
getModelInstanceName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.BayesianNetworkTrainSMParameterSet
This method returns a short description of the model.
getModelInstanceName(StructureLearner.ModelType, byte, StructureLearner.LearningType, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.IDGTrainSMParameterSet
This method returns a short textual representation of the model instance.
getModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
Returns the a deep copy of the models.
getModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns a deep copy of the models.
getMostProbableSequence(SequenceScore, int) - Static method in class de.jstacs.utils.StatisticalModelTester
Returns one most probable sequence for the discrete model m.
getMotifDiscoverer() - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This method returns a clone of the internally used MotifDiscoverer.
getMotifLength(int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
This method returns the length of the motif with index motif .
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getMotifLength(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getMRG() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method creates the multivariate random generator that will be used during initialization.
getMRGParams() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method creates the parameters used in a multivariate random generator while initialization.
getMultiClassScores(DataSet[]) - Method in class de.jstacs.classifiers.AbstractClassifier
This method returns a multidimensional array with class specific scores.
getMultiClassScores(DataSet[]) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getName() - Method in class de.jstacs.AnnotatedEntity
Returns the name of the AnnotatedEntity.
getName() - Method in class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
The method returns the name of the performance measure.
getName() - Method in class de.jstacs.classifiers.performanceMeasures.AucPR
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.AucROC
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.ClassificationRate
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.ConfusionMatrix
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.FalsePositiveRateForFixedSensitivity
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.PRCurve
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.ROCCurve
 
getName() - Method in class de.jstacs.classifiers.performanceMeasures.SensitivityForFixedSpecificity
 
getName(Class<? extends ParameterSet>) - Static method in class de.jstacs.parameters.ParameterSet
Returns a name for the class.
getName(ParameterSet) - Static method in class de.jstacs.parameters.ParameterSet
Returns a name for the ParameterSet.
getName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
This method returns the name of the current instance
getName() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
This method returns the name of the PhyloTree
getNameOfAlgorithm() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns the name of the used algorithm.
getNameOfAssessment() - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
Returns the name of this class.
getNames() - Method in class de.jstacs.AnnotatedEntityList
Returns the names of all AnnotatedEntitys in the list.
getNewAlphabet() - Method in class de.jstacs.data.alphabets.DiscreteAlphabetMapping
Returns the new Alphabet that is used for mapping.
getNewAlphabetContainer(AlphabetContainer, DiscreteAlphabetMapping...) - Static method in class de.jstacs.data.sequences.MappedDiscreteSequence
This method allows to create a new AlphabetContainer given an old AlphabetContainer and some DiscreteAlphabetMappings.
getNewComponentProbs(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Estimates the weights of each component.
getNewDiscreteValue(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabetMapping
This method implements the main transformation of the values.
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
 
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
 
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior
This method returns an empty new instance of the current prior.
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior
 
getNewInstance() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
 
getNewParameters(int, double[][], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture
 
getNewParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
This method set all parameters for the next sampling step
getNewParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingPhyloHMM
 
getNewParameters(int, double[][], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method trains the internal models on the internal sample and the given weights.
getNewParameters(int, double[][], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
 
getNewParametersForModel(int, int, int, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method trains the internal model with index modelIndex on the internal 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.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Computes sequence weights and returns the score.
getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
Computes sequence weights and returns the score.
getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.StrandTrainSM
Computes sequence weights and returns the score.
getNextContext(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the next context that will be visited when visiting the child with index index.
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getNodeLabel(double, String, NumberFormat) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission
Returns the graphviz label of the node containing this emission.
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getNodeLabel(double, String, NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getNodeShape(boolean) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission
Returns the graphviz string for the shape of the node.
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getNodeShape(boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getNormalizedVersion(DifferentiableStatisticalModel, int) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
This method returns a normalized version of a DifferentiableStatisticalModel.
getNucleicAcid() - Method in enum de.jstacs.data.DinucleotideProperty
Returns the kind of nucleic acid, e.g.
getNumberOfAlignedSequences() - Method in class de.jstacs.algorithms.alignment.StringAlignment
Returns the number of sequences in this alignment.
getNumberOfAllNodesBelow() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
This method returns the total number of PhyloNodes in the subtree starting from this instance
getNumberOfAlphabets() - Method in class de.jstacs.data.AlphabetContainer
This method returns the number of Alphabets used in the current AlphabetContainer.
getNumberOfAvailableProcessors() - Static method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction
This method returns the number of available processors.
getNumberOfBoundSequences(DataSet, double[], int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
Returns the number of sequences in data that are predicted to be bound at least once by motif no.
getNumberOfChildren() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the number of states that can be visited.
getNumberOfChildren(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getNumberOfChildren(int, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns the number of children states for given index, i.e. context, and a given layer of the matrix.
getNumberOfClasses() - Method in class de.jstacs.classifiers.AbstractClassifier
Returns the number of classes that can be distinguished.
getNumberOfClasses() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getNumberOfCombinations(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.CombinationIterator
Returns the number of possible combinations.
getNumberOfComponents() - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
Returns the number of components in this MotifDiscoverer.
getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
Returns the number of different components of this AbstractMixtureDiffSM.
getNumberOfComponents() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns the number of components the are modeled by this AbstractMixtureTrainSM.
getNumberOfElements() - Method in class de.jstacs.data.DataSet
Returns the number of elements, i.e. the Sequences, in this DataSet.
getNumberOfElements() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory
Returns the number of elements, i.e.
getNumberOfElements() - Method in class de.jstacs.io.StringExtractor
Returns the number of Strings that have been read.
getNumberOfElementsWithLength(int) - Method in class de.jstacs.data.DataSet
Returns the number of overlapping elements that can be extracted.
getNumberOfElementsWithLength(int, double[]) - Method in class de.jstacs.data.DataSet
Returns the weighted number of overlapping elements that can be extracted.
getNumberOfIndexes(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getNumberOfIndexes(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method computes the number of different indexes for a given layer of the matrix.
getNumberOfLines() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
Returns the number of lines in this table.
getNumberOfModels() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
This method returns the number of models in the CompositeTrainSM.
getNumberOfMotifs() - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
Returns the number of motifs for this MotifDiscoverer.
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getNumberOfMotifs() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getNumberOfMotifsInComponent(int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
Returns the number of motifs that are used in the component component of this MotifDiscoverer.
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getNumberOfMotifsInComponent(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getNumberOfNexts(int) - Method in class de.jstacs.parameters.MultiSelectionParameter
Returns the number of calls of MultiSelectionParameter.next() that can be called before false is returned.
getNumberOfNexts(int) - Method in class de.jstacs.parameters.RangeParameter
Returns the number of calls of RangeParameter.next() that can be done before obtaining false.
getNumberOfNodes() - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Returns the number of nodes.
getNumberOfNodes() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
This method returns the total number of nodes in the tree
getNumberOfParameters() - Method in class de.jstacs.parameters.ArrayParameterSet
 
getNumberOfParameters() - Method in class de.jstacs.parameters.ParameterSet
Returns the number of parameters in the ParameterSet.
getNumberOfParameters() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
 
getNumberOfParameters() - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore
Returns the number of parameters in this DifferentiableSequenceScore.
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MultiDimensionalSequenceWrapperDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getNumberOfParameters() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission
Returns the number of parameters of this emission.
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getNumberOfParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the number of parameters in this transition element.
getNumberOfParents() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
Returns the number of parents for the random variable of this BNDiffSMParameterTree in the network structure of the enclosing BayesianNetworkDiffSM.
getNumberOfPossibilities() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
Returns the number of different possibilities that can be scored.
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getNumberOfRecommendedStarts() - Method in interface de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore
This method returns the number of recommended optimization starts.
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getNumberOfRecommendedStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getNumberOfResults() - Method in class de.jstacs.results.ResultSet
Returns the number of Results in this ResultSet
getNumberOfSequenceAnnotationsByType(String) - Method in class de.jstacs.data.sequences.Sequence
Returns the number of SequenceAnnotations of type type for this Sequence.
getNumberOfSequences() - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
This method returns the number of internal sequences.
getNumberOfSequences() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.SequenceIterator
This method returns the number of sequences in this iterator, i.e., the number of times SequenceIterator.next() returns true after using SequenceIterator.reset().
getNumberOfSpecificConstraints() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns the number of specific constraints.
getNumberOfStarts() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet
Returns the number of independent sampling starts
getNumberOfStarts() - Method in class de.jstacs.sampling.AbstractBurnInTestParameterSet
Returns the number of starts.
getNumberOfStarts(DifferentiableSequenceScore[]) - Static method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
Returns the number of recommended starts in a numerical optimization.
getNumberOfStarts() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet
The method returns the number of different starts.
getNumberOfStates() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns the number of the (hidden) states
getNumberOfStates() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
 
getNumberOfStates() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
This method returns the number of states underlying this transition instance.
getNumberOfStationarySamplings() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet
Returns the number of samplings steps in the stationary phase
getNumberOfStepsInStationaryPhase() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.SamplingHMMTrainingParameterSet
The method returns the number of steps to be done in the stationary phase.
getNumberOfStepsPerIteration() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.SamplingHMMTrainingParameterSet
This method returns the number of steps to be done in each start before testing for the end of the burn in phase (again).
getNumberOfTestSamplings() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet
Returns the number of samplings between checks for the stationary phase
getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction
Returns the number of used threads for evaluating the function and for determining the gradient of the function.
getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
This method returns the number of used threads while optimization.
getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet
This method returns the number of threads that should be used during optimization.
getNumberOfThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifierParameterSet
Returns the number of threads for evaluating the LogGenDisMixFunction
getNumberOfThreads() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns the number of threads that is internally used.
getNumberOfThreads() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MultiThreadedTrainingParameterSet
This method returns the number of threads that should be used during optimization.
getNumberOfValues() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
getNumberOfValues() - Method in interface de.jstacs.parameters.RangeIterator
Returns the number of values in the collection.
getNumberOfValues() - Method in class de.jstacs.parameters.RangeParameter
Returns the number of values in a list or range of parameter values.
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.AbstractClassifier
Returns the subset of numerical values that are also returned by AbstractClassifier.getCharacteristics().
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.MappingClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
 
getNumericalCharacteristics() - Method in interface de.jstacs.sequenceScores.SequenceScore
Returns the subset of numerical values that are also returned by SequenceScore.getCharacteristics().
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
 
getNumericalCharacteristics() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
 
getOffsetForAucPR() - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This method returns an offset that must be added to scores for computing PR curves.
getOptimalBranching(double[][], double[][], byte) - Static method in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds
Returns an optimal branching.
getOrder() - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Returns the order.
getOrder() - Method in enum de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder.RandomSeqType
This method returns the Markov order.
getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
Returns the order of the inhomogeneous Markov model.
getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
Returns the order of the Markov model as defined in the constructor
getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov.InhomogeneousMarkovParameterSet
Returns the order of the InhomogeneousMarkov structure measure as defined by this set of parameters.
getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
Returns the order defined by this set of parameters.
getOrder() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
Returns the order defined by this set of parameters.
getOutfilePrefix() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet
Returns the prefix of the temporary files for storing sampled parameter values
getOutput(byte[], double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
This method is used to create random sequences.
getOutputStream() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.Protocol
Returns the ByteArrayOutputStream of this protocol
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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
Returns the BNDiffSMParameter that is responsible for the suffix of sequence seq starting at position start.
getParameterForName(String) - Method in class de.jstacs.parameters.ParameterSet
Returns the Parameter with name name.
getParameterFromTag(String) - Method in class de.jstacs.parameters.ParameterSetTagger
This method returns the Parameter specified by the tag
getParameterIndexesForSamplingStep(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
Returns the indexes of the parameters, incremented by offset, that shall be sampled in step step of a grouped sampling process.
getParameters(OptimizableFunction.KindOfParameter, double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
This method enables the user to get the parameters without creating a new array.
getParameters(OptimizableFunction.KindOfParameter) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
 
getParameters(OptimizableFunction.KindOfParameter, double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
 
getParameters(OptimizableFunction.KindOfParameter) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction
Returns some parameters that can be used for instance as start parameters.
getParameterSetContainingASingleDoubleValue(double) - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet
Creates a new ParameterSet containing a single double-SimpleParameter.
getParameterSetFor(Class<? extends InstantiableFromParameterSet>) - Static method in class de.jstacs.utils.SubclassFinder
Returns a LinkedList of the classes of the InstanceParameterSets that can be used to instantiate the sub-class of InstantiableFromParameterSet that is given by clazz
getParametersInCollection() - Method in class de.jstacs.parameters.AbstractSelectionParameter
Returns the possible values in this collection.
getParent() - Method in class de.jstacs.parameters.Parameter
Returns a reference to the ParameterSet enclosing this Parameter.
getParent() - Method in class de.jstacs.parameters.ParameterSet
Returns the enclosing ParameterSetContainer of this ParameterSet or null if none exists.
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Returns the optimal parents for the given data and weights.
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
 
getParents(DataSet, DataSet, double[], double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
 
getParser() - Method in class de.jstacs.results.DataSetResult
Returns the SequenceAnnotationParser that can be used to write this DataSetResult including annotations on the contained Sequences to a file.
getPartialLengths() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
This method returns a deep copy of the internally used partial lengths of the parts.
getPath() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
Returns the path of the directory containing the file
getPercent() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet
Returns the percentage of user supplied data that is used in each iteration as test dataset.
getPercents() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet
Returns an array containing for each class the percentage of user supplied data that is used in each iteration as test dataset.
getPlotCommands(REnvironment, String, AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
This method copies the data to the server side and creates a StringBuffer containing the plot commands.
getPlotCommands(REnvironment, String, int[], AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
This method copies the data to the server side and creates a StringBuffer containing the plot commands.
getPlotCommands(REnvironment, String, String[], AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
This method copies the data to the server side and creates a StringBuffer containing the plot commands.
getPlugInParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSMParameterSet
Returns true if plug-in parameters shall be used when creating a BayesianNetworkDiffSM from this set of parameters.
getPosition() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
Returns the position of this LocatedSequenceAnnotation on the sequence.
getPosition() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the position of the symbol this parameter is responsible for as defined in the constructor.
getPosition(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns the position with index index.
getPositionDependentKMerProb(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
Returns the probability of kmer for all possible positions in this BayesianNetworkDiffSM starting at position kmer.getLength()-1.
getPositionForParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
Returns the position in the sequence the parameter index is responsible for.
getPositions() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns a clone of the array of used positions.
getPossibleLength(TrainableStatisticalModel...) - Static method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
This method returns the possible length of a classifier that would use the given TrainableStatisticalModels.
getPossibleLength() - Method in class de.jstacs.data.AlphabetContainer.AbstractAlphabetContainerParameterSet
Returns the length of the AlphabetContainer that can be instantiated using this ParameterSet.
getPossibleLength() - Method in class de.jstacs.data.AlphabetContainer
Returns the possible length for Sequences using this AlphabetContainer.
getPossibleLength() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
getPossibleLength() - Method in class de.jstacs.data.alphabets.DNAAlphabetContainer.DNAAlphabetContainerParameterSet
 
getProbFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
Returns the probability of Sequence sequence in this BNDiffSMParameterTree.
getProbsForComponent(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
Returns the probabilities for each component given a Sequence.
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
Returns the profile of the scores for component component and motif motif at all possible start positions of the motif in the sequence sequence beginning at startpos.
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getProfileOfScoresFor(int, int, Sequence, int, MotifDiscoverer.KindOfProfile) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getProperty(Sequence, DinucleotideProperty.Smoothing) - Method in enum de.jstacs.data.DinucleotideProperty
Computes this dinucleotide property for all overlapping twomers in original, smoothes the result using smoothing, and returns the smoothed property as a double array.
getProperty(Sequence) - Method in enum de.jstacs.data.DinucleotideProperty
Computes this dinucleotide property for all overlapping twomers in original and returns the result as a double array of length original.getLength()-1
getPropertyAsSequence(Sequence) - Method in enum de.jstacs.data.DinucleotideProperty
Computes this dinucleotide property for all overlapping twomers in original and returns the result as a Sequence of length original.getLength()-1
getPropertyAsSequence(Sequence, DinucleotideProperty.Smoothing) - Method in enum de.jstacs.data.DinucleotideProperty
Computes this dinucleotide property for all overlapping twomers in original, smoothes the result using smoothing, and returns the smoothed property as a Sequence.
getPropertyImage(Sequence, DinucleotideProperty, DinucleotideProperty.Smoothing, REnvironment, int, String, int, int) - Static method in enum de.jstacs.data.DinucleotideProperty
 
getPropertyImage(DataSet, DinucleotideProperty, DinucleotideProperty.Smoothing, REnvironment, int, String, int, int) - Static method in enum de.jstacs.data.DinucleotideProperty
 
getProtocol(boolean) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor
Returns an object for writing a protocol of a program run
getPseudoCount() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the pseudocount as given in the constructor.
getPubMedID() - Method in enum de.jstacs.data.DinucleotideProperty
Returns the PubMed ID of the publication where the parameters of this property has been published.
getPValue(Sequence, DataSet) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
Returns the p-value for a Sequence candidate with respect to a given background DataSet.
getPValue(DataSet, DataSet) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
Returns the p-values for all Sequences in the DataSet candidates with respect to a given background DataSet .
getPValue(double[], double) - Static method in class de.jstacs.classifiers.utils.PValueComputation
This method searches for the insertion point of the score in a given sorted array of scores and returns the p-value for this score.
getPValue(double[], double, int) - Static method in class de.jstacs.classifiers.utils.PValueComputation
This method searches for the insertion point of the score in a given sorted array of scores from index start and returns the p-value for this score.
getPWM() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
If this BayesianNetworkDiffSM is a PWM, i.e.
getRandomSequence(Random, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getRandomSequence(Random, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
This method creates a random Sequence from a trained homogeneous model.
getRangedInstance() - Method in class de.jstacs.parameters.AbstractSelectionParameter
 
getRangedInstance() - Method in interface de.jstacs.parameters.Rangeable
Returns an instance of RangeIterator that has the same properties as the current instance, but accepts a range or list of values.
getRangedInstance() - Method in class de.jstacs.parameters.SimpleParameter
 
getRawResult() - Method in class de.jstacs.results.ListResult
Returns a copy of the internal list of ResultSets.
getReference() - Method in enum de.jstacs.data.DinucleotideProperty
Returns the reference of the publication where the parameters of this property has been published.
getReferenceClass() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet
Returns the index of the reference class.
getReferenceSequence() - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotation
Returns the reference sequence.
getRegEx() - Method in class de.jstacs.io.RegExFilenameFilter
Returns a representation of all used regular expressions.
getRepeats() - Method in class de.jstacs.classifiers.assessment.RepeatedHoldOutAssessParameterSet
Returns the repeats defined by this RepeatedHoldOutAssessParameterSet (repeats define how many iterations (train and test classifiers) of that RepeatedHoldOutExperiment this RepeatedHoldOutAssessParameterSet is used with are performed).
getRepeats() - Method in class de.jstacs.classifiers.assessment.RepeatedSubSamplingAssessParameterSet
Returns the repeats defined by this RepeatedSubSamplingAssessParameterSet (repeats defines how many iterations (train and test classifiers) of that RepeatedSubSamplingExperiment this RepeatedSubSamplingAssessParameterSet is used with are performed).
getRepeats() - Method in class de.jstacs.classifiers.assessment.Sampled_RepeatedHoldOutAssessParameterSet
Returns the repeats defined by this Sampled_RepeatedHoldOutAssessParameterSet (repeats defines how many iterations (train and test classifiers) of that Sampled_RepeatedHoldOutExperiment this Sampled_RepeatedHoldOutAssessParameterSet is used with are performed).
getResultAt(int) - Method in class de.jstacs.results.NumericalResultSet
 
getResultAt(int) - Method in class de.jstacs.results.ResultSet
Returns Result number index in this ResultSet.
getResultForName(String) - Method in class de.jstacs.results.ResultSet
Returns Result with name name in this ResultSet.
getResultInstance() - Method in class de.jstacs.results.StorableResult
Returns the instance of the Storable that is the result of this StorableResult.
getResults(LinkedList, DataSet[], PerformanceMeasureParameterSet, boolean) - Method in class de.jstacs.classifiers.AbstractClassifier
This method computes the results for any evaluation of the classifier.
getResults(LinkedList, DataSet[], PerformanceMeasureParameterSet, boolean) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
 
getResults(LinkedList, DataSet[], PerformanceMeasureParameterSet, boolean) - Method in class de.jstacs.classifiers.MappingClassifier
 
getResults() - Method in class de.jstacs.results.ResultSet
Returns all internal results as an array of Results.
getReverseComplementaryDataSet() - Method in class de.jstacs.data.DataSet
Returns a DataSet that contains the reverse complement of all Sequences in this DataSet.
getReverseComplementDistributions(ComplementableDiscreteAlphabet, double[][][]) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
This method computes the reverse complement distributions for given conditional distributions.
getReverseSwitches() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
This method returns a deep copy of the internally used switches for the parts whether to use the corresponding DifferentiableSequenceScore forward or as reverse complement.
getRNotation(String) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
This method returns the distribution in R notation.
getRNotation(String) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
 
getRNotation(String) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
 
getRNotation(String) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
 
getRoot() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
This method returns the root node of the tree
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.SubTensor
 
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Returns the value for child as root.
getRunTimeException(Exception) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method creates an RuntimeException from any other Exception
getSafeOutputStream(OutputStream) - Static method in class de.jstacs.utils.SafeOutputStream
This method returns an instance of SafeOutputStream for a given OutputStream.
getSamplingComponent() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
Returns a sampling component suited for this SamplingScoreBasedClassifier
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getSamplingGroups(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.SamplingDifferentiableStatisticalModel
Returns groups of indexes of parameters that shall be drawn together in a sampling procedure
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getSamplingGroups(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getSamplingScheme() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifierParameterSet
Returns the sampling scheme
getScale() - Method in class de.jstacs.parameters.RangeParameter
Returns a description of the the scale of a range of parameter values.
getScatterplot(AbstractScoreBasedClassifier, AbstractScoreBasedClassifier, DataSet, DataSet, REnvironment, boolean) - Static method in class de.jstacs.classifiers.utils.ClassificationVisualizer
This method returns an ImageResult containing a scatter plot of the scores for the given classifiers cl1 and cl2.
getScore(Tensor, int[][]) - Static method in class de.jstacs.algorithms.graphs.DAG
Returns the score for any graph.
getScore(Sequence, int) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
This method returns the score for a given Sequence and a given class.
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
This method returns the score for a given Sequence and a given class.
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.MappingClassifier
 
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getScoreForBestRun() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
Returns the value of the optimized function from the best run of the last training.
getScoreForPath(Tensor, int, byte, int[]) - Static method in class de.jstacs.algorithms.graphs.DAG
Returns the score for a given path path using the first l nodes and dependencies of order k.
getScores(DataSet) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier
This method returns the scores of the classifier for any Sequence in the DataSet.
getScores(DataSet) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
 
getScores(DataSet) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getSecondElement() - Method in class de.jstacs.utils.Pair
This method returns the second element.
getSelected() - Method in class de.jstacs.parameters.MultiSelectionParameter
Returns the indexes of the selected options.
getSelected() - Method in class de.jstacs.parameters.SelectionParameter
Returns the index of the selected value.
getSelectionParameter(Class<? extends ParameterSet>, String, String, String, boolean) - Static method in class de.jstacs.utils.SubclassFinder
This method creates an SelectionParameter that contains InstanceParameterSet for each possible class.
getSequence(int) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
This method returns the internal sequence with index index.
getSequenceAnnotationByType(String, int) - Method in class de.jstacs.data.sequences.Sequence
Returns the SequenceAnnotation no.
getSequenceAnnotationByTypeAndIdentifier(String, String) - Method in class de.jstacs.data.sequences.Sequence
Returns the SequenceAnnotation of this Sequence that has type type and identifier identifier.
getSequenceAnnotationIndexMatrix(String, Hashtable<String, Integer>, String, Hashtable<String, Integer>) - Method in class de.jstacs.data.DataSet
This method creates a matrix which contains the index of the Sequence with specific SequenceAnnotation combination or -1 if the DataSet does not contain any Sequence with such a combination.
getSequenceWeights() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
 
getSequenceWeights() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction
Returns the weights for each Sequence for each class used in this OptimizableFunction.
getShannonEntropy(StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the Shannon entropy for any discrete model m and all sequences of length, if possible.
getShannonEntropyInBits(StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the Shannon entropy in bits for any discrete model m and all sequences of length, if possible.
getShortFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
Returns the short which is the value of the Parameter par.
getSimplifiedAlphabetContainer(Alphabet[], int[]) - Static method in class de.jstacs.data.AlphabetContainer
This method creates a new AlphabetContainer that uses as less as possible Alphabets to describe the container.
getSingelton(Class<? extends Singleton>) - Static method in class de.jstacs.Singleton.SingletonHandler
This method helps to retrieve the single instance of a Singleton singletonClass.
getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
 
getSizeOfEventSpace() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission
Returns the size of the event space, i.e., the number of possible outcomes, for the random variables of this emission
getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
 
getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
 
getSizeOfEventSpace() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
 
getSizeOfEventSpace(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.DifferentiableTransition
Returns the size of the event space, i.e., the number of possible outcomes, for the random variable of parameter index
getSizeOfEventSpace(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel
Returns the size of the event space of the random variables that are affected by parameter no.
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
 
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
 
getSmoothedProfile(int, String...) - Method in class de.jstacs.motifDiscovery.KMereStatistic
This method returns an array of smoothed profiles.
getSmoothedProfile(int, Sequence...) - Method in class de.jstacs.motifDiscovery.KMereStatistic
This method returns an array of smoothed profiles.
getSortedInitialParameters(DifferentiableSequenceScore[], MutableMotifDiscovererToolbox.InitMethodForDiffSM[], DiffSSBasedOptimizableFunction, int, OutputStream, int) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
This method allows to initialize the DifferentiableSequenceScore using different MutableMotifDiscovererToolbox.InitMethodForDiffSM.
getSortedScoresForMotifAndFlanking(DataSet, DataSet, String) - Static method in class de.jstacs.motifDiscovery.MotifDiscoveryAssessment
Returns the scores read from the prediction pred for the motif with identifier identifier and flanking sequences as annotated in the DataSet data.
getSortedValuesForMotifAndFlanking(DataSet, double[][], double, double, String) - Static method in class de.jstacs.motifDiscovery.MotifDiscoveryAssessment
This method provides some score arrays that can be used in AbstractPerformanceMeasure to determine some curves or area under curves based on the values of the predictions.
getSpecificName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient
 
getSpecificName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure
 
getSpecificName() - Method in class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure
This method returns a specific name of the measure including any parameters.
getStartDistance() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.NumericalHMMTrainingParameterSet
This method returns the start distance that should be used in the line search during the optimization.
getStartIndexOfAlignmentForFirst() - Method in class de.jstacs.algorithms.alignment.PairwiseStringAlignment
This method returns the start index of the alignment in the first sequence.
getStartNode() - Method in class de.jstacs.algorithms.graphs.Edge
Returns the start node of the edge.
getStartPositions(int, DataSet, int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This method returns a list of start positions of binding sites.
getStartValue() - Method in class de.jstacs.parameters.RangeParameter
Returns the start value of a range of parameter values or null if no range was specified.
getStatePosteriorMatrixFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns the log state posterior of all states for a sequence.
getStatePosteriorMatrixFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns the state posteriors for all sequences of the sample data.
getStationaryDistribution(double[], int) - Static method in class de.jstacs.utils.StationaryDistribution
This method return the stationary distribution.
getStatistics() - Method in class de.jstacs.results.MeanResultSet
Returns the means and (if possible the) standard errors of the results in this MeanResultSet as a new NumericalResultSet.
getStatistics(DataSet, double[], int, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Counts the occurrences of symbols of the AlphabetContainer of DataSet s using weights.
getStatisticsOrderTwo(DataSet, double[], int, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Counts the occurrences of symbols of the AlphabetContainer of DataSet s using weights.
getSteps() - Method in class de.jstacs.parameters.RangeParameter
Returns the number of steps of a range of parameter values or 0 if no range was specified.
getStrand(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
This method returns the preferred StrandedLocatedSequenceAnnotationWithLength.Strand for a given subsequence.
getStrand(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
This method return the preferred StrandedLocatedSequenceAnnotationWithLength.Strand for a Sequence beginning at startPos.
getStrandedness() - Method in class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Returns the strandedness, i.e the orientation of this annotation.
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in interface de.jstacs.motifDiscovery.MotifDiscoverer
This method returns the probabilities of the strand orientations for a given subsequence if it is considered as site of the motif model in a specific component.
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
 
getStrandProbabilitiesFor(int, int, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
 
getStringFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
Returns the String which is the value of the Parameter par.
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.Sequence
This method creates a String representation from the given representation.
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
 
getStringRepresentation(Object) - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
 
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
 
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhomogeneousDGTrainSM
Returns a String representation of the underlying graph.
getStructure() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture
Returns a String representation of the structure of the used models.
getStructure(DataSet, double[], StructureLearner.ModelType, byte, StructureLearner.LearningType) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner
This method finds the optimal structure of a model by using a given learning method (in some sense).
getStructure(Tensor, StructureLearner.ModelType, byte) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner
This method can be used to determine the optimal structure of a model.
getStructureFromPath(int[], Tensor) - Static method in class de.jstacs.algorithms.graphs.DAG
Extracts the structure from a given path path and score-"function".
getSubAnnotations() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
Returns the sub-annotations of this SequenceAnnotation as given in the constructor.
getSubContainer(int, int) - Method in class de.jstacs.data.AlphabetContainer
Returns a sub-container with the Alphabets for the positions starting at start and with length length.
getSubSequence(AlphabetContainer, int) - Method in class de.jstacs.data.sequences.Sequence
This method should be used if one wants to create a DataSet of subsequences of defined length.
getSubSequence(AlphabetContainer, int, int) - Method in class de.jstacs.data.sequences.Sequence
This method should be used if one wants to create a DataSet of subsequences of defined length.
getSubSequence(int) - Method in class de.jstacs.data.sequences.Sequence
This is a very efficient way to create a subsequence/suffix for Sequences with a simple AlphabetContainer.
getSubSequence(int, int) - Method in class de.jstacs.data.sequences.Sequence
This is a very efficient way to create a subsequence of defined length for Sequences with a simple AlphabetContainer.
getSuffixDataSet(int) - Method in class de.jstacs.data.DataSet
This method enables you to use only a suffix of all elements, i.e. the Sequence, in the current DataSet.
getSumOfDeviation(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the sum of deviations between the probabilities for all sequences of length for discrete models m1 and m2.
getSumOfDistribution(StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the marginal distribution for any discrete model m and all sequences of length, if possible.
getSumOfHyperparameter() - Method in class de.jstacs.utils.random.DirichletMRGParams
Returns the sum of the hyperparameters (entries of the hyperparameter vector) of the underlying Dirichlet distribution.
getSumOfHyperparameter() - Method in class de.jstacs.utils.random.ErlangMRGParams
Returns the sum of the hyperparameters (entries of the hyperparameter vector) of the underlying Erlang distribution.
getSumOfHyperParameters(int, int, double) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
This method returns an array that can be used in the constructor HomogeneousMMDiffSM.HomogeneousMMDiffSM(AlphabetContainer, int, double, double[], boolean, boolean, int) containing the sums of the specific hyperparameters.
getSumOfWeights() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory
Returns the sum of all weights.
getSuperClassOf(T...) - Static method in class de.jstacs.io.ArrayHandler
This method returns the deepest class in the class hierarchy that is the class or a superclass of all instances in the array.
getSymbol(int, double) - Method in class de.jstacs.data.AlphabetContainer
Returns a String representation of the encoded symbol val of the Alphabet of position pos of this AlphabetContainer.
getSymbolAt(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
Returns the symbol at position i in the alphabet.
getSymKLDivergence(StatisticalModel, StatisticalModel, int) - Static method in class de.jstacs.utils.StatisticalModelTester
Returns the difference of the Kullback-Leibler-divergences, i.e.
getTempDir() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
Returns the directory for parameter files set in this SamplingScoreBasedClassifier.
getTensor(DataSet, double[], byte, StructureLearner.LearningType) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.StructureLearner
This method can be used to compute a Tensor that can be used to determine the optimal structure.
getTerminantionCondition() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifierParameterSet
This method returns the AbstractTerminationCondition for stopping the training, e.g., if the difference of the scores between two iterations is smaller than a given threshold the training is stopped.
getTerminationCondition() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MaxHMMTrainingParameterSet
This method returns the AbstractTerminationCondition for stopping the training, e.g., if the difference of the scores between two iterations is smaller than a given threshold the training is stopped.
getThreshold(double[], int) - Static method in class de.jstacs.classifiers.utils.PValueComputation
This method returns the threshold that determines if an observed score is significant.
getThreshold() - Method in class de.jstacs.sampling.VarianceRatioBurnInTestParameterSet
Returns the threshold used in the VarianceRatioBurnInTestParameterSet.
getTimeInstance(OutputStream) - Static method in class de.jstacs.utils.Time
This method tries to return a UserTime instance, if not possible (due to native code) it returns a RealTime instance.
getTopologicalOrder(int[][]) - Static method in class de.jstacs.algorithms.graphs.TopSort
Returns the topological order of indexes according to parents2.
getTopologicalOrder2(byte[][]) - Static method in class de.jstacs.algorithms.graphs.TopSort
Computes a topological ordering for a given graph.
getTrain_TestNumbers(boolean) - Method in class de.jstacs.classifiers.assessment.RepeatedSubSamplingAssessParameterSet
Returns an array containing the number of elements the subsampled (train | test) datasets should consist of.
getTransitionElementIndex(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
This method return the index of the BasicHigherOrderTransition.AbstractTransitionElement using the BasicHigherOrderTransition.lookup table.
getTrueIndexForLastGetBest() - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
Returns the edge from SymmetricTensor.getBest(int, int[], byte) in an encoded index.
getType() - Method in class de.jstacs.data.AlphabetContainer
Returns the type of this AlphabetContainer.
getType() - Method in enum de.jstacs.data.DinucleotideProperty
Returns the type of this property.
getType() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
Returns the type of this SequenceAnnotation as given in the constructor.
getUniqueHueValues(int) - Static method in class de.jstacs.utils.ToolBox
Creates an array of hue values that can be used for the representation of probabilities.
getValidator() - Method in class de.jstacs.parameters.SimpleParameter
Returns the ParameterValidator used in this SimpleParameter.
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SubTensor
 
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Returns the value for the edge parents[0],...
getValue() - Method in class de.jstacs.AnnotatedEntity
Returns the value of the AnnotatedEntity.
getValue() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
 
getValue() - Method in class de.jstacs.parameters.EnumParameter
 
getValue() - Method in class de.jstacs.parameters.FileParameter
 
getValue() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
getValue() - Method in class de.jstacs.parameters.ParameterSetContainer
 
getValue() - Method in class de.jstacs.parameters.RangeParameter
 
getValue() - Method in class de.jstacs.parameters.SelectionParameter
 
getValue() - Method in class de.jstacs.parameters.SimpleParameter
 
getValue() - Method in class de.jstacs.results.DataSetResult
 
getValue() - Method in class de.jstacs.results.ImageResult
 
getValue() - Method in class de.jstacs.results.ListResult
 
getValue() - Method in class de.jstacs.results.SimpleResult
 
getValue() - Method in class de.jstacs.results.StorableResult
 
getValue(Sequence, int) - Method in interface de.jstacs.sequenceScores.differentiable.logistic.LogisticConstraint
This method returns the value f(seq) used in LogisticDiffSS
getValue(Sequence, int) - Method in class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
 
getValue() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
Returns the current value of this parameter.
getValue() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
 
getValueFor(String) - Method in class de.jstacs.parameters.MultiSelectionParameter
Returns the value for the option with key key.
getValueFor(int) - Method in class de.jstacs.parameters.MultiSelectionParameter
Returns the value of the option with no.
getValueFromTag(String) - Method in class de.jstacs.parameters.ParameterSetTagger
This method returns the value of the Parameter specified by the tag.
getValueFromTag(String, Class<T>) - Method in class de.jstacs.parameters.ParameterSetTagger
This method returns the casted value of the Parameter specified by the tag.
getValueOfAIC(StatisticalModel, DataSet, int) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the value of Akaikes Information Criterion (AIC).
getValueOfBIC(StatisticalModel, DataSet, int) - Static method in class de.jstacs.utils.StatisticalModelTester
This method computes the value of the Bayesian Information Criterion (BIC).
getValues() - Method in class de.jstacs.parameters.MultiSelectionParameter
Returns the values of all selected options as an array.
getValuesForEachNucleotide(DataSet, int, boolean) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This method determines a score for each possible starting position in each of the sequences in data that this position is covered by at least one motif occurrence of the motif with index index.
getValuesFromSequence(Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
This method extracts the values form a sequence.
getVersionInformation() - Method in class de.jstacs.utils.REnvironment
Returns information about the version of R that is used.
getViterbiPath(int, int, Sequence, SamplingHigherOrderHMM.ViterbiComputation) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
This method returns a viterbi path that is the optimum for the choosen ViterbiComputation method
getViterbiPathFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getViterbiPathFor(Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
 
getViterbiPathFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getViterbiPathFor(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getViterbiPathsFor(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
This method returns the viterbi paths and scores for all sequences of the sample data.
getWeight() - Method in class de.jstacs.algorithms.graphs.Edge
Returns the weight of the edge.
getWeight(int) - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory
Returns the weight for the Sequence with index index.
getWeight() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
This method return the weight (length, rate ...) for the incoming edge
getWeight() - Method in class de.jstacs.utils.ComparableElement
This method returns the weight of the element.
getWeights() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory
Returns a copy of the weights for the DataSet.
getWeights() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
This method returns a deep copy of the weights for each component.
getWriter() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.Protocol
Returns the PrintWriter of this protocol
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition
Deprecated.  
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
This method returns the xml tag that is used in the method AbstractTerminationCondition.toXML() and in the constructor AbstractTerminationCondition.AbstractTerminationCondition(StringBuffer).
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.CombinedCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.IterationCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.SmallGradientConditon
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.SmallStepCondition
 
getXmlTag() - Method in class de.jstacs.algorithms.optimization.termination.TimeCondition
 
getXMLTag() - Method in class de.jstacs.AnnotatedEntity
This method returns a tag used as outer tag of the XML description.
getXMLTag() - Method in class de.jstacs.classifiers.AbstractClassifier
Returns the String that is used as tag for the XML representation of the classifier.
getXMLTag() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.MappingClassifier
 
getXMLTag() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
 
getXMLTag() - Method in class de.jstacs.parameters.FileParameter
 
getXMLTag() - Method in class de.jstacs.parameters.MultiSelectionParameter
 
getXMLTag() - Method in class de.jstacs.parameters.ParameterSetContainer
 
getXMLTag() - Method in class de.jstacs.parameters.RangeParameter
 
getXMLTag() - Method in class de.jstacs.parameters.SelectionParameter
 
getXMLTag() - Method in class de.jstacs.parameters.SimpleParameter
 
getXMLTag() - Method in class de.jstacs.results.CategoricalResult
 
getXMLTag() - Method in class de.jstacs.results.DataSetResult
 
getXMLTag() - Method in class de.jstacs.results.ImageResult
 
getXMLTag() - Method in class de.jstacs.results.ListResult
 
getXMLTag() - Method in class de.jstacs.results.NumericalResult
 
getXMLTag() - Method in class de.jstacs.results.StorableResult
 
getXMLTag() - Method in class de.jstacs.sampling.AbstractBurnInTest
This method returns the XML tag that is used in AbstractBurnInTest.toXML() and AbstractBurnInTest.AbstractBurnInTest(StringBuffer).
getXMLTag() - Method in class de.jstacs.sampling.VarianceRatioBurnInTest
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
Returns the XML-tag for storing this measure
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This method returns the XML tag of the instance that is used to build a XML representation.
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
Returns the XML tag that is used for the class to en- or decode.
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
Returns the XML tag that is used for this model in DiscreteGraphicalTrainSM.fromXML(StringBuffer) and DiscreteGraphicalTrainSM.toXML().
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
Returns the tag for the XML representation.
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
This method returns the xml tag used in BasicHigherOrderTransition.AbstractTransitionElement.toXML().
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
The method returns the XML tag used during saving and loading the transition.
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicPluginTransitionElement
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
 
getXMLTag() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
 
getXMLTag() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
 
getXMLTag() - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.LinkedImageResult
 
gibbsSampling(int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
This method implements a sampling step in the sampling procedure
GibbsSamplingModel - Interface in de.jstacs.sampling
This is the interface that any AbstractTrainableStatisticalModel has to implement if it should be used in a sampling.
gibbsSamplingStep(int, int, boolean, DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
This method implements the next step(s) in the sampling procedure
goldenRatio(OneDimensionalFunction, double, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
Approximates a minimum (not necessary the global) in the interval [lower,upper].
goldenRatio(OneDimensionalFunction, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
Approximates a minimum (not necessary the global) in the interval [lower,upper].
grad - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
The array for storing the gradients for each parameter
gradient - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
Help array for the gradient
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.
Overview  Package  Class  Use  Tree  Deprecated   Index  Help 
 PREV LETTER   NEXT LETTER FRAMES    NO FRAMES    All Classes
A B C D E F G H I J K L M N O P Q R S T U V W X Z