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

S

SafeOutputStream - Class in de.jstacs.utils
This class is for any output.
SafeOutputStream(OutputStream) - Constructor for class de.jstacs.utils.SafeOutputStream
Creates a new SafeOutputStream.
sameLength() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
Returns true if for test and train dataset the sequences of the non-reference classes have the same length as the corresponding sequence of the reference class.
Sample - Class in de.jstacs.data
This is the class for any sample of Sequences.
Sample(AlphabetContainer, AbstractStringExtractor) - Constructor for class de.jstacs.data.Sample
Creates a new Sample from a StringExtractor using the given AlphabetContainer.
Sample(AlphabetContainer, AbstractStringExtractor, int) - Constructor for class de.jstacs.data.Sample
Creates a new Sample from a StringExtractor using the given AlphabetContainer and all overlapping windows of length subsequenceLength.
Sample(AlphabetContainer, AbstractStringExtractor, String) - Constructor for class de.jstacs.data.Sample
Creates a new Sample from a StringExtractor using the given AlphabetContainer and a delimiter delim.
Sample(AlphabetContainer, AbstractStringExtractor, String, int) - Constructor for class de.jstacs.data.Sample
Creates a new Sample from a StringExtractor using the given AlphabetContainer, the given delimiter delim and all overlapping windows of length subsequenceLength.
Sample(Sample, int) - Constructor for class de.jstacs.data.Sample
Creates a new Sample from a given Sample and a given length subsequenceLength.
Sample(String, Sequence...) - Constructor for class de.jstacs.data.Sample
Creates a new Sample from an array of Sequences and a given annotation.
sample - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The sample that was used in the last training.
Sample.ElementEnumerator - Class in de.jstacs.data
This class can be used to have a fast sequential access to a Sample.
Sample.ElementEnumerator(Sample) - Constructor for class de.jstacs.data.Sample.ElementEnumerator
Creates a new Sample.ElementEnumerator on the given Sample data.
Sample.PartitionMethod - Enum in de.jstacs.data
This enum defines different partition methods for a Sample.
Sample.WeightedSampleFactory - Class in de.jstacs.data
This class enables you to eliminate Sequences that occur more than once in one or more Samples.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample...) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
Creates a new Sample.WeightedSampleFactory on the given Sample(s) with Sample.WeightedSampleFactory.SortOperation sort.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample, double[]) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
Creates a new Sample.WeightedSampleFactory on the given Sample and an array of weights with Sample.WeightedSampleFactory.SortOperation sort.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample, double[], int) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
Creates a new Sample.WeightedSampleFactory on the given Sample and an array of weights with a given length and Sample.WeightedSampleFactory.SortOperation sort.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation, Sample[], double[][], int) - Constructor for class de.jstacs.data.Sample.WeightedSampleFactory
Creates a new Sample.WeightedSampleFactory on the given array of Samples and an array of weights with a given length and Sample.WeightedSampleFactory.SortOperation sort.
Sample.WeightedSampleFactory.SortOperation - Enum in de.jstacs.data
This enum defines the different types of sort operations that can be performed while creating a Sample.WeightedSampleFactory.
Sampled_RepeatedHoldOutAssessParameterSet - Class in de.jstacs.classifier.assessment
This class implements a ClassifierAssessmentAssessParameterSet that must be used to call the method assess( ... ) of a Sampled_RepeatedHoldOutExperiment.
Sampled_RepeatedHoldOutAssessParameterSet() - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
Constructs a new Sampled_RepeatedHoldOutAssessParameterSet with empty parameter values.
Sampled_RepeatedHoldOutAssessParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
The standard constructor for the interface Storable.
Sampled_RepeatedHoldOutAssessParameterSet(Sample.PartitionMethod, int, boolean, int, int, double, boolean) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
Constructs a new Sampled_RepeatedHoldOutAssessParameterSet with given parameter values.
Sampled_RepeatedHoldOutExperiment - Class in de.jstacs.classifier.assessment
This class is a special ClassifierAssessment that partitions the data of a user-specified reference class (typically the smallest class) and samples non-overlapping for all other classes, so that one gets the same number of sequences (and the same lengths of the sequences) in each train and test dataset.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier[], Model[][], boolean, boolean) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
Creates a new Sampled_RepeatedHoldOutExperiment from an array of AbstractClassifiers and a two-dimensional array of Model s, which are combined to additional classifiers.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier...) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
Creates a new Sampled_RepeatedHoldOutExperiment from a set of AbstractClassifiers.
Sampled_RepeatedHoldOutExperiment(boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
Creates a new Sampled_RepeatedHoldOutExperiment from a set of Models.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier[], boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutExperiment
This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given AbstractModels by a Sampled_RepeatedHoldOutExperiment.
SampleResult - Class in de.jstacs.results
Result that contains a Sample.
SampleResult(String, String, Sample) - Constructor for class de.jstacs.results.SampleResult
Creates a new SampleResult from a Sample with the annotation name and comment.
SampleResult(StringBuffer) - Constructor for class de.jstacs.results.SampleResult
The standard constructor for the interface Storable.
sampleToSequenceIterator(Sample, boolean) - Static method in class de.jstacs.data.bioJava.BioJavaAdapter
Creates a SequenceIterator from the Sample sample preserving as much annotation as possible.
samplingIndex - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The current index of the sampling.
samplingIndex - Variable in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
The index of the current sampling.
samplingStopped() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method is the opposite of the method AbstractMixtureModel.initModelForSampling(int).
samplingStopped() - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
 
samplingStopped() - Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
This method is the opposite of the method GibbsSamplingComponent.extendSampling(int, boolean).
satisfiesSpecificConstraint(Sequence, int) - Method in class de.jstacs.models.discrete.Constraint
This method returns the index of the specific constraint that is fulfilled by the Sequence seq beginning at position start.
satisfiesSpecificConstraint(Sequence, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel.HomCondProb
 
satisfiesSpecificConstraint(Sequence, int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhConstraint
 
satisfiesSpecificConstraint(SequenceIterator) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Returns the index of the constraint that is satisfied by sequence.
save(String, File) - Method in class de.jstacs.data.Sample
This method writes a message msg and the Sample to a file f.
score - Variable in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
The internally used scoring functions.
ScoreBasedPerformanceMeasureDefinitions - Class in de.jstacs.classifier
This class contains the methods that are needed to evaluate a score based 2-class-classifier.
ScoreBasedPerformanceMeasureDefinitions() - Constructor for class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
 
ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair - Class in de.jstacs.classifier
This class is used as a container that allows to store a threshold and the result of a measure together.
ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair(double, double) - Constructor for class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair
Creates a filled instance of a ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair.
ScoreClassifier - Class in de.jstacs.classifier.scoringFunctionBased
This abstract class implements the main functionality of a ScoringFunction based classifier.
ScoreClassifier(ScoreClassifierParameterSet, ScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
Creates a new ScoreClassifier from a given ScoreClassifierParameterSet and ScoringFunctions .
ScoreClassifier(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
The standard constructor for the interface Storable.
ScoreClassifierParameterSet - Class in de.jstacs.classifier.scoringFunctionBased
A set of Parameters for any ScoreClassifier.
ScoreClassifierParameterSet(Class<? extends ScoreClassifier>, boolean, AlphabetContainer.AlphabetContainerType, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
Creates a new ScoreClassifierParameterSet with empty parameter values.
ScoreClassifierParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
The standard constructor for the interface Storable.
ScoreClassifierParameterSet(Class<? extends ScoreClassifier>, AlphabetContainer, int, byte, double, double, double, boolean, OptimizableFunction.KindOfParameter) - Constructor for class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
The constructor for a simple, instantiated parameter set.
ScoringFunction - Interface in de.jstacs.scoringFunctions
This interface is the main part of any ScoreClassifier.
SeparateGaussianLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
Class for a LogPrior that defines a Gaussian prior on the parameters of a set of NormalizableScoringFunctions and a set of class parameters.
SeparateGaussianLogPrior(double[], double[], double[]) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior
Creates a new SeparateGaussianLogPrior from a set of base variances vars, a set of class variances classVars and a set of class means classMus.
SeparateGaussianLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior
The standard constructor for the interface Storable.
SeparateLaplaceLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
Class for a LogPrior that defines a Laplace prior on the parameters of a set of NormalizableScoringFunctions and a set of class parameters.
SeparateLaplaceLogPrior(double[], double[], double[]) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior
Creates a new SeparateLaplaceLogPrior from a set of base variances vars, a set of class variances classVars and a set of class means classMus.
SeparateLaplaceLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior
The standard constructor for the interface Storable.
SeparateLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
Abstract class for priors that penalize each parameter value independently and have some variances (and possible means) as hyperparameters.
SeparateLogPrior(double[], double[], double[]) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
Creates a new SeparateLogPrior using the class-specific base variances vars, the variances classVars and the means classMus for the class parameters.
SeparateLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
The standard constructor for the interface Storable.
Sequence - Class in de.jstacs.data
This is the main class for all sequences.
Sequence(AlphabetContainer, SequenceAnnotation[]) - Constructor for class de.jstacs.data.Sequence
Creates a new Sequence.CompositeSequence with the given AlphabetContainer and the given annotation, but without the content.
Sequence.CompositeSequence - Class in de.jstacs.data
The class handles composite Sequences.
Sequence.CompositeSequence(Sequence, int[], int[]) - Constructor for class de.jstacs.data.Sequence.CompositeSequence
This is a very efficient way to create a Sequence.CompositeSequence for Sequences with a simple AlphabetContainer.
Sequence.CompositeSequence(AlphabetContainer, Sequence, int[], int[]) - Constructor for class de.jstacs.data.Sequence.CompositeSequence
This constructor should be used if one wants to create a Sample of Sequence.CompositeSequences.
Sequence.SubSequence - Class in de.jstacs.data
This class handles subsequences.
Sequence.SubSequence(AlphabetContainer, Sequence, int, int) - Constructor for class de.jstacs.data.Sequence.SubSequence
This constructor should be used if one wants to create a Sample of Sequence.SubSequences of defined length.
Sequence.SubSequence(Sequence, int, int) - Constructor for class de.jstacs.data.Sequence.SubSequence
This is a very efficient way to create a Sequence.SubSequence of defined length for Sequences with a simple AlphabetContainer.
SequenceAnnotation - Class in de.jstacs.data.sequences.annotation
Class for a general annotation of a Sequence.
SequenceAnnotation(String, String, Result) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as a Result result.
SequenceAnnotation(String, String, Result[]...) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results results.
SequenceAnnotation(String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotation.
SequenceAnnotation(String, String, Collection<? extends Result>) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
Creates a new SequenceAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as a Collection of Results results.
SequenceAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.SequenceAnnotation
The standard constructor for the interface Storable.
SequenceIterator - Class in de.jstacs.models.discrete.inhomogeneous
This class is used to iterate over a discrete sequence.
SequenceIterator(int) - Constructor for class de.jstacs.models.discrete.inhomogeneous.SequenceIterator
Creates a new SequenceIterator with maximal length.
sequenceIteratorToSample(SequenceIterator, FeatureFilter) - Static method in class de.jstacs.data.bioJava.BioJavaAdapter
This method creates a new Sample from a SequenceIterator.
SequenceScoringParameterSet - Class in de.jstacs.parameters
Abstract class for a ParameterSet containing all parameters necessary to construct an Object that implements InstantiableFromParameterSet.
SequenceScoringParameterSet(Class, AlphabetContainer.AlphabetContainerType, boolean) - Constructor for class de.jstacs.parameters.SequenceScoringParameterSet
Constructs an InstanceParameterSet having empty parameter values.
SequenceScoringParameterSet(Class, AlphabetContainer.AlphabetContainerType, boolean, boolean) - Constructor for class de.jstacs.parameters.SequenceScoringParameterSet
Constructs a SequenceScoringParameterSet having empty parameter values.
SequenceScoringParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.SequenceScoringParameterSet
The standard constructor for the interface Storable.
SequenceScoringParameterSet(Class, AlphabetContainer, int, boolean) - Constructor for class de.jstacs.parameters.SequenceScoringParameterSet
Constructs a SequenceScoringParameterSet from an AlphabetContainer and the length of a sequence.
SequenceScoringParameterSet(Class, AlphabetContainer) - Constructor for class de.jstacs.parameters.SequenceScoringParameterSet
Constructs a SequenceScoringParameterSet for an object that can handle sequences of variable length and with the AlphabetContainer alphabet.
set(boolean, ScoringFunction...) - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.CompositeLogPrior
 
set(boolean, ScoringFunction...) - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior
Resets all pre-computed values to their initial values using the ScoringFunctions funs.
set(boolean, ScoringFunction...) - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
 
set(AlphabetContainer) - Method in class de.jstacs.models.AbstractModel
This method should only be invoked by the method AbstractModel.setNewAlphabetContainerInstance(AlphabetContainer) and not be made public.
set(AlphabetContainer) - Method in class de.jstacs.models.CompositeModel
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
Sets the parameters as internal parameters and does some essential computations.
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel
 
set(DGMParameterSet, boolean) - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
 
set(AlphabetContainer) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
 
setAlpha(double) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the parameter of the Dirichlet distribution which is used when you invoke train to init the gammas.
setBounds(int[]) - Method in class de.jstacs.models.discrete.inhomogeneous.SequenceIterator
This method sets the bounds for each position.
setClassWeights(boolean, double...) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
Sets new class weights.
setCurrentLength(int) - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator
This method sets the current used number of selected elements.
setCurrentSamplingIndex(int) - Method in class de.jstacs.models.mixture.gibbssampling.AbstractBurnInTest
 
setCurrentSamplingIndex(int) - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest
This method sets the value of the current sampling.
setCurrentSamplingIndex(int) - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
 
setDefault(Object) - Method in class de.jstacs.parameters.CollectionParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.EnumParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.FileParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.Parameter
Sets the default value of the Parameter to defaultValue.
setDefault(Object) - Method in class de.jstacs.parameters.ParameterSetContainer
 
setDefault(Object) - Method in class de.jstacs.parameters.RangeParameter
 
setDefault(Object) - Method in class de.jstacs.parameters.SimpleParameter
 
setEss(double) - Method in class de.jstacs.models.discrete.DGMParameterSet
This method can be used to set the ess (equivalent sample size) of this parameter set.
setESS(double) - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner
This method sets the ess (equivalent sample size) of the StructureLearner.
setExpLambda(int, double) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Sets the exponential value of \lambda at position index to val: exp(\lambda_{index}) = val.
setForwardProb(double) - Method in class de.jstacs.scoringFunctions.mix.StrandScoringFunction
This method can be used to set the forward strand probability.
setFreqs(String[], int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb
This method is used to restore the values of a Gibbs Sampling run.
setFurtherInformation(StringBuffer) - Method in class de.jstacs.models.mixture.gibbssampling.AbstractBurnInTest
This method sets further information for the AbstractBurnInTest.
setFurtherInformation(StringBuffer) - Method in class de.jstacs.models.mixture.gibbssampling.VarianceRatioBurnInTest
 
setFurtherModelInfos(StringBuffer) - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
This method replaces the internal model information with those from a StringBuffer.
setFurtherModelInfos(StringBuffer) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM
 
setFurtherModelInfos(StringBuffer) - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
 
setFurtherModelInfos(StringBuffer) - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
 
setHiddenParameters(double[], int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method sets the hidden parameters of the model.
setLambda(int, double) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
Sets the value of \lambda at position index to val: \lambda_{index} = val.
setLastDistance(double) - Method in class de.jstacs.algorithms.optimization.ConstantStartDistance
 
setLastDistance(double) - Method in class de.jstacs.algorithms.optimization.LimitedMedianStartDistance
 
setLastDistance(double) - Method in interface de.jstacs.algorithms.optimization.StartDistanceForecaster
Sets the last used distance.
setMax(int) - Method in class de.jstacs.utils.DefaultProgressUpdater
 
setMax(int) - Method in class de.jstacs.utils.GUIProgressUpdater
 
setMax(int) - Method in class de.jstacs.utils.NullProgressUpdater
 
setMax(int) - Method in interface de.jstacs.utils.ProgressUpdater
Sets the maximal value that will be set by ProgressUpdater.setValue(int), so a value of max indicates the end of the supervised method call.
setModelType(String) - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
This method allows a simple change of the model type.
setMotifLength(int) - Method in class de.jstacs.models.mixture.motif.positionprior.GaussianLikePositionPrior
 
setMotifLength(int) - Method in class de.jstacs.models.mixture.motif.positionprior.PositionPrior
Sets the length of the current motif.
setNeededReference(ParameterSet) - Method in class de.jstacs.parameters.Parameter
Sets an internal reference to a ParameterSet whose validity depends on the value of this Parameter.
setNeededReference(ParameterSet) - Method in class de.jstacs.parameters.RangeParameter
 
setNewAlphabetContainerInstance(AlphabetContainer) - Method in class de.jstacs.classifier.AbstractClassifier
This method tries to set a new instance of an AlphabetContainer for the current classifier.
setNewAlphabetContainerInstance(AlphabetContainer) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
 
setNewAlphabetContainerInstance(AlphabetContainer) - Method in class de.jstacs.models.AbstractModel
 
setNewAlphabetContainerInstance(AlphabetContainer) - Method in interface de.jstacs.models.Model
This method tries to set a new instance of an AlphabetContainer for the current model.
setOffset() - Method in class de.jstacs.utils.NullProgressUpdater
After NullProgressUpdater.setOffset() is called the current value will be added to every value set by NullProgressUpdater.setValue(int).
setOutputStream(OutputStream) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
Sets the OutputStream that is used e.g. for writing information during training.
setOutputStream(OutputStream) - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
Sets the OutputStream for the model.
setOutputStream(OutputStream) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the OutputStream that is used e.g. for writing information while training.
setParameterFor(int, int[][], Parameter) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Sets the instance of the Parameter for symbol symbol and context context to Parameter par.
setParameterOptimization(boolean) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
This method allows the user to specify whether the parameters should be optimized or not.
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction
 
setParameters(double, double, double) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction
this method can be used to set the parameters even if the parameters are not allowed to be optimized.
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.UniformDurationScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
 
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction
 
setParameters(double[], int) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
This method sets the internal parameters to the values of params between start and start + ScoringFunction.getNumberOfParameters() - 1
setParameters(double[], int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
 
setParametersForFunction(int, double[], int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method allows to set the parameters for specific functions.
setParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction
Checks the dimension and sets the class parameters.
setParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood
 
setParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction
Sets the current values as parameters.
setParent(ParameterSet) - Method in class de.jstacs.parameters.Parameter
Sets the reference of the enclosing ParameterSet of this Parameter to parent.
setParent(ParameterSetContainer) - Method in class de.jstacs.parameters.ParameterSet
Sets the enclosing ParameterSetContainer of this ParameterSet to parent.
setPlugInParameters(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Computes and sets the plug-in parameters (MAP estimated parameters) from data using weights.
setPrior(LogPrior) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
This method sets a new prior that should be used for optimization.
setRangeable(boolean) - Method in class de.jstacs.parameters.CollectionParameter
Sets the value returned by CollectionParameter.isRangeable() to rangeable.
setRangeable(boolean) - Method in class de.jstacs.parameters.SimpleParameter
Sets the value returned by SimpleParameter.isRangeable() to rangeable.
setRootValue(int, double) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
setRootValue(int, double) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
 
setRootValue(int, double) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Sets the value val for the root node child.
setSeed(long) - Method in class de.jstacs.utils.random.RandomNumberGenerator
 
setSelected(MeasureParameters.Measure, boolean) - Method in class de.jstacs.classifier.MeasureParameters
Selects or deselects an option sel depending on the new selection b.
setSelected(String, boolean) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
Sets the selection of the option with key key to the value of selected.
setSelected(int, boolean) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
Sets the selection of option with no.
setShallBeRanged(RangeParameter.RangeType) - Method in class de.jstacs.parameters.RangeParameter
Sets the type of this RangeParameter to one of LIST, RANGE or NO.
setSign(double) - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture
This method set the sign that is used in shift, shrink and expand.
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
setStatisticForHyperparameters(int[], double[]) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
This method sets the hyperparameters for the model parameters by evaluating the given statistic.
setStringToBeParsed(String) - Method in class de.jstacs.io.SymbolExtractor
Sets a new String to be parsed.
setThreshold(double) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the threshold for terminating the train algorithm.
setThresholdClassWeights(boolean, double) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
Sets a new threshold for 2-class-classifiers.
setTrainData(Sample) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method is invoked by the train-method and sets for a given sample the sample that should be used for train.
setTrainData(Sample) - Method in class de.jstacs.models.mixture.MixtureModel
 
setTrainData(Sample) - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
 
setTrainData(Sample) - Method in class de.jstacs.models.mixture.StrandModel
 
setValidator(ParameterValidator) - Method in class de.jstacs.parameters.SimpleParameter
Sets a new ParameterValidator for this SimpleParameter.
setValue(byte, double, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
 
setValue(byte, double, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
Sets the value if it is bigger than the current value and keeps the parents information.
setValue(byte, double, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
Sets the value for the edge parents[0],...
setValue(double) - Method in class de.jstacs.models.mixture.gibbssampling.AbstractBurnInTest
 
setValue(double) - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest
This method can be used to fill the internal memory with the values that will be used to determine the length of the burn-in phase.
setValue(double) - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
 
setValue(Object) - Method in class de.jstacs.parameters.CollectionParameter
Sets the selected value to the one that is specified by the key value.
setValue(Object) - Method in class de.jstacs.parameters.EnumParameter
 
setValue(Object) - Method in class de.jstacs.parameters.FileParameter
 
setValue(Object) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
setValue(Object) - Method in class de.jstacs.parameters.Parameter
Sets the value of this Parameter to value.
setValue(Object) - Method in class de.jstacs.parameters.ParameterSetContainer
 
setValue(Object) - Method in class de.jstacs.parameters.RangeParameter
 
setValue(Object) - Method in class de.jstacs.parameters.SimpleParameter
 
setValue(double) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
Sets the current value of this parameter.
setValue(int) - Method in class de.jstacs.utils.DefaultProgressUpdater
 
setValue(int) - Method in class de.jstacs.utils.GUIProgressUpdater
 
setValue(int) - Method in class de.jstacs.utils.NullProgressUpdater
 
setValue(int) - Method in interface de.jstacs.utils.ProgressUpdater
Sets the current value the supervised process has reached.
setValue(int) - Method in class de.jstacs.utils.TimeLimitedProgressUpdater
 
setValues(String) - Method in class de.jstacs.parameters.RangeParameter
Sets a list of values from a String containing a space separated list of values.
setValues(Object, int, Object, RangeParameter.Scale) - Method in class de.jstacs.parameters.RangeParameter
Sets the values of this RangeParameter as a range of values, specified by a start value, a last value, a number of steps between these values (without the last value) and a scale in that the values between the first and the last value are chosen.
setValuesInLogScale(boolean, double, Object, int, Object) - Method in class de.jstacs.parameters.RangeParameter
This method enables you to set a list of values in an easy manner.
setWeights(double...) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Sets the weights of each component.
shallBeRanged() - Method in class de.jstacs.parameters.RangeParameter
Returns one of LIST, RANGE or NO depending on the input used to specify this RangeParameter.
SharedStructureClassifier - Class in de.jstacs.models.discrete.inhomogeneous.shared
This class enables you to learn the structure on all classes of the classifier together.
SharedStructureClassifier(int, StructureLearner.ModelType, byte, StructureLearner.LearningType, FSDAGModel...) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
Creates a new SharedStructureClassifier from given FSDAGModels.
SharedStructureClassifier(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
The standard constructor for the interface Storable.
SharedStructureMixture - Class in de.jstacs.models.discrete.inhomogeneous.shared
This class handles a mixture of models with the same structure that is learned via EM.
SharedStructureMixture(FSDAGModel[], StructureLearner.ModelType, byte, int, double, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
Creates a new SharedStructureMixture instance which estimates the component probabilities/weights.
SharedStructureMixture(FSDAGModel[], StructureLearner.ModelType, byte, int, double[], double, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
Creates a new SharedStructureMixture instance with fixed component weights.
SharedStructureMixture(FSDAGModel[], StructureLearner.ModelType, byte, int, boolean, double[], double, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
Creates a new SharedStructureMixture instance with all relevant values.
SharedStructureMixture(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
The standard constructor for the interface Storable.
shortcut - Variable in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction
These shortcuts indicate the beginning of a new part in the parameter vector.
ShortSequence - Class in de.jstacs.data.sequences
This class is for sequences with the alphabet symbols encoded as shortss and can therefore be used for discrete AlphabetContainers with alphabets that use many different symbols.
ShortSequence(AlphabetContainer, short[]) - Constructor for class de.jstacs.data.sequences.ShortSequence
Creates a new ShortSequence from an array of short- encoded alphabet symbols.
ShortSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ShortSequence
Creates a new ShortSequence from a String representation using the default delimiter.
ShortSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ShortSequence
Creates a new ShortSequence from a String representation using the delimiter delim.
ShortSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ShortSequence
Creates a new ShortSequence from a SymbolExtractor.
shouldBeNormalized() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifierParameterSet
This method indicates if a normalization shall be used while optimization.
showImage(String, BufferedImage) - Static method in class de.jstacs.utils.REnvironment
Enables you to show an image.
showImage(String, BufferedImage, int) - Static method in class de.jstacs.utils.REnvironment
Enables you to show an image.
SignificantMotifOccurrencesFinder - Class in de.jstacs.motifDiscovery
This class enables the user to predict motif occurrences given a specific significance level.
SignificantMotifOccurrencesFinder(MotifDiscoverer, SignificantMotifOccurrencesFinder.RandomSeqType, int, double) - Constructor for class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This constructor creates an instance of SignificantMotifOccurrencesFinder that uses the given SignificantMotifOccurrencesFinder.RandomSeqType to determine the siginificance level.
SignificantMotifOccurrencesFinder(MotifDiscoverer, Sample, double) - Constructor for class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
This constructor creates an instance of SignificantMotifOccurrencesFinder that uses a Sample to determine the siginificance level.
SignificantMotifOccurrencesFinder.RandomSeqType - Enum in de.jstacs.motifDiscovery
 
SimpleBurnInTest - Class in de.jstacs.models.mixture.gibbssampling
This is a very simple test for the length of the burn-in phase.
SimpleBurnInTest(int) - Constructor for class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
This is the main constructor that creates an instance of SimpleBurnInTest with fixed burn-in length.
SimpleBurnInTest(StringBuffer) - Constructor for class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
The standard constructor for the interface Storable.
SimpleGaussianSumLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter.
SimpleGaussianSumLogPrior(double) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior
Creates a new SimpleGaussianSumLogPrior with mean 0 and variance sigma for all parameters, including the class parameters.
SimpleGaussianSumLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior
The standard constructor for the interface Storable.
SimpleParameter - Class in de.jstacs.parameters
Class for a "simple" parameter.
SimpleParameter(StringBuffer) - Constructor for class de.jstacs.parameters.SimpleParameter
The standard constructor for the interface Storable.
SimpleParameter(DataType, String, String, boolean) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter without ParameterValidator.
SimpleParameter(DataType, String, String, boolean, Object) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter without ParameterValidator but with a default value.
SimpleParameter(DataType, String, String, boolean, ParameterValidator) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter with a ParameterValidator.
SimpleParameter(DataType, String, String, boolean, ParameterValidator, Object) - Constructor for class de.jstacs.parameters.SimpleParameter
Constructor for a SimpleParameter with validator and default value.
SimpleParameter.DatatypeNotValidException - Exception in de.jstacs.parameters
Class for an Exception that can be thrown if the provided int-value that represents a data type is not one of the values defined in DataType.
SimpleParameter.DatatypeNotValidException(String) - Constructor for exception de.jstacs.parameters.SimpleParameter.DatatypeNotValidException
Creates a new SimpleParameter.DatatypeNotValidException with an error message.
SimpleParameter.IllegalValueException - Exception in de.jstacs.parameters
This exception is thrown if a parameter is not valid.
SimpleParameter.IllegalValueException(String) - Constructor for exception de.jstacs.parameters.SimpleParameter.IllegalValueException
Creates a new SimpleParameter.IllegalValueException with the reason of the exception reason as error message.
SimpleParameterSet - Class in de.jstacs.parameters
Class for a ParameterSet that is constructed from an array of Parameters and thus does nothing in the method SimpleParameterSet.loadParameters().
SimpleParameterSet(Parameter[]) - Constructor for class de.jstacs.parameters.SimpleParameterSet
Creates a new SimpleParameterSet from an array of Parameters.
SimpleParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.SimpleParameterSet
The standard constructor for the interface Storable.
SimpleReferenceConstraint - Class in de.jstacs.parameters.validation
Class for a ReferenceConstraint that checks for "simple" conditions as defined in the interface Constraint.
SimpleReferenceConstraint(SimpleParameter, int) - Constructor for class de.jstacs.parameters.validation.SimpleReferenceConstraint
Creates a new SimpleReferenceConstraint from a reference SimpleParameter and a comparison operator, which is one of the values defined in the Constraint interface.
SimpleReferenceConstraint(StringBuffer) - Constructor for class de.jstacs.parameters.validation.SimpleReferenceConstraint
The standard constructor for the interface Storable.
SimpleResult - Class in de.jstacs.results
Abstract class for a Result with a value of a primitive data type or String.
SimpleResult(String, String, DataType) - Constructor for class de.jstacs.results.SimpleResult
The main constructor which takes the main information of a result.
SimpleResult(StringBuffer) - Constructor for class de.jstacs.results.SimpleResult
This is the constructor for Storable.
SimpleSequenceIterator - Class in de.jstacs.data.bioJava
Class that implements the SequenceIterator interface of BioJava in a simple way, backed by an array of Sequences.
SimpleSequenceIterator(Sequence...) - Constructor for class de.jstacs.data.bioJava.SimpleSequenceIterator
Creates a new SimpleSequenceIterator from an array of Sequences.
SimpleStaticConstraint - Class in de.jstacs.parameters.validation
Class for a Constraint that checks values against static values using the comparison operators defined in the interface Constraint.
SimpleStaticConstraint(Number, int) - Constructor for class de.jstacs.parameters.validation.SimpleStaticConstraint
Creates a new SimpleStaticConstraint from a Number -reference and a comparison operator as defined in Constraint.
SimpleStaticConstraint(String, int) - Constructor for class de.jstacs.parameters.validation.SimpleStaticConstraint
Creates a new SimpleStaticConstraint from a String -reference and a comparison operator as defined in Constraint.
SimpleStaticConstraint(StringBuffer) - Constructor for class de.jstacs.parameters.validation.SimpleStaticConstraint
The standard constructor for the interface Storable.
SimpleStringExtractor - Class in de.jstacs.io
This is a simple class that extracts Strings.
SimpleStringExtractor(String...) - Constructor for class de.jstacs.io.SimpleStringExtractor
This constructor packs the Strings in an instance of SimpleStringExtractor.
simplify() - Method in class de.jstacs.parameters.CollectionParameter
 
simplify() - Method in class de.jstacs.parameters.FileParameter
 
simplify() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
simplify() - Method in class de.jstacs.parameters.Parameter
Simplifies the Parameter and its contents to the relevant information.
simplify() - Method in class de.jstacs.parameters.ParameterSet
Simplifies all Parameters in this ParameterSet.
simplify() - Method in class de.jstacs.parameters.ParameterSetContainer
 
simplify() - Method in class de.jstacs.parameters.RangeParameter
 
simplify() - Method in class de.jstacs.parameters.SimpleParameter
 
SingleHiddenMotifMixture - Class in de.jstacs.models.mixture.motif
This class enables the user to search for a single motif in a sequence.
SingleHiddenMotifMixture(Model, Model, boolean, int, double[], double[], PositionPrior, AbstractMixtureModel.Algorithm, double, double, AbstractMixtureModel.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
Creates a new SingleHiddenMotifMixture.
SingleHiddenMotifMixture(Model, Model, boolean, int, double[], PositionPrior, double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
Creates a new SingleHiddenMotifMixture using EM and estimating the probability for finding a motif.
SingleHiddenMotifMixture(Model, Model, boolean, int, double, PositionPrior, double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
Creates a new SingleHiddenMotifMixture using EM and fixed probability for finding a motif.
SingleHiddenMotifMixture(StringBuffer) - Constructor for class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
The standard constructor for the interface Storable.
SinglePositionSequenceAnnotation - Class in de.jstacs.data.sequences.annotation
Class for some annotations that consist mainly of one position on a sequence.
SinglePositionSequenceAnnotation(SinglePositionSequenceAnnotation.Type, String, int) - Constructor for class de.jstacs.data.sequences.annotation.SinglePositionSequenceAnnotation
Creates a new SinglePositionSequenceAnnotation of type type with identifier identifier and position position.
SinglePositionSequenceAnnotation(SinglePositionSequenceAnnotation.Type, String, int, Result...) - Constructor for class de.jstacs.data.sequences.annotation.SinglePositionSequenceAnnotation
Creates a new SinglePositionSequenceAnnotation of type type with identifier identifier, position position and additional annotations additionalAnnotation.
SinglePositionSequenceAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.SinglePositionSequenceAnnotation
The standard constructor for the interface Storable.
SinglePositionSequenceAnnotation.Type - Enum in de.jstacs.data.sequences.annotation
This enum defines possible types of a SinglePositionSequenceAnnotation.
SkewNormalLikeScoringFunction - Class in de.jstacs.scoringFunctions.mix.motifSearch
This class implements a skew normal like discrete truncated distribution.
SkewNormalLikeScoringFunction(int, int, double, double, double, int) - Constructor for class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction
This is the main constructor if the parameters are fixed.
SkewNormalLikeScoringFunction(int, int, boolean, double, double, boolean, double, double, boolean, double, double, int) - Constructor for class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction
This is the constructor that allows the most flexible handling of the parameters.
SkewNormalLikeScoringFunction(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction
This is the constructor for Storable.
skip(int) - Method in class de.jstacs.models.discrete.inhomogeneous.SequenceIterator
This method skips some position.
skipLastClassifiersDuringClassifierTraining - Variable in class de.jstacs.classifier.assessment.ClassifierAssessment
Skip last classifier.
SoftOneOfN - Class in de.jstacs.utils.random
This random generator returns 1-epsilon for one and equal parts for the rest of a random vector.
SoftOneOfN(double) - Constructor for class de.jstacs.utils.random.SoftOneOfN
This constructor can be used for (soft) sampling one of n.
SoftOneOfN() - Constructor for class de.jstacs.utils.random.SoftOneOfN
This constructor can be used for (hard) sampling one of n.
sort(String) - Method in class de.jstacs.results.ListResult
This method enables you to sort the entries of this container by a specified column.
sostream - Variable in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
This stream is used for comments, e.g. during the training, ... .
sostream - Variable in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
This stream is used for comments, computation steps/results or any other kind of output during the training, ... etc.
sostream - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
This is the stream for writing information while training.
source - Variable in class de.jstacs.algorithms.graphs.Edge
The source node.
SparseSequence - Class in de.jstacs.data.sequences
This class is an implementation for sequences on one alphabet with length 4.
SparseSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.SparseSequence
Creates a new SparseSequence from a String representation.
SparseSequence(AlphabetContainer, SymbolExtractor) - Constructor for class de.jstacs.data.sequences.SparseSequence
Creates a new SparseSequence from a SymbolExtractor.
SparseStringExtractor - Class in de.jstacs.io
This StringExtractor reads the Strings from a File as the user asks for the String.
SparseStringExtractor(File) - Constructor for class de.jstacs.io.SparseStringExtractor
A constructor that reads the lines from file.
SparseStringExtractor(File, char) - Constructor for class de.jstacs.io.SparseStringExtractor
A constructor that reads the lines from file and ignores those starting with the comment character ignore.
SparseStringExtractor(File, String) - Constructor for class de.jstacs.io.SparseStringExtractor
A constructor that reads the lines from file and sets the annotation of the source to annotation.
SparseStringExtractor(File, char, String) - Constructor for class de.jstacs.io.SparseStringExtractor
A constructor that reads the lines from file, ignores those starting with the comment character ignore and sets the annotation of the source to annotation.
StartDistanceForecaster - Interface in de.jstacs.algorithms.optimization
This interface is used to determine the next start distance that will be used in a line search.
starts - Variable in class de.jstacs.models.CompositeModel
The start indices.
starts - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The number of starts.
StationaryDistribution - Class in de.jstacs.models.utils
This class can be used to determine the stationary distribution.
StationaryDistribution() - Constructor for class de.jstacs.models.utils.StationaryDistribution
 
stationaryIteration - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The number of (stationary) iterations of the Gibbs Sampler.
StatisticalTest - Class in de.jstacs.models.utils
This class enables the user to compute some divergences.
StatisticalTest() - Constructor for class de.jstacs.models.utils.StatisticalTest
 
STEEPEST_DESCENT - Static variable in class de.jstacs.algorithms.optimization.Optimizer
This constant can be used to specify that the steepest descent should be used in the optimize-method.
steepestDescent(DifferentiableFunction, double[], Optimizer.TerminationCondition, double, double, StartDistanceForecaster, SafeOutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
The steepest descent.
Storable - Interface in de.jstacs
This is the root interface for all immutable objects that must be stored in e.g. a file or a database.
StorableArrayWithTags(Storable[]) - Static method in class de.jstacs.io.XMLParser
Encodes a Storable array.
StorableResult - Class in de.jstacs.results
Class for Results that are Storables.
StorableResult(String, String, Storable) - Constructor for class de.jstacs.results.StorableResult
Creates a result for an XML representation of an object.
StorableResult(StringBuffer) - Constructor for class de.jstacs.results.StorableResult
The standard constructor for the interface Storable.
StorableValidator - Class in de.jstacs.parameters.validation
Class for a validator that validates instances and XML representations for the correct class types (e.g.
StorableValidator(Class<? extends Storable>, boolean) - Constructor for class de.jstacs.parameters.validation.StorableValidator
Creates a new StorableValidator for a subclass of AbstractModel or AbstractClassifier.
StorableValidator(Class<? extends Storable>) - Constructor for class de.jstacs.parameters.validation.StorableValidator
Creates a new StorableValidator for a subclass of Storable.
StorableValidator(StringBuffer) - Constructor for class de.jstacs.parameters.validation.StorableValidator
The standard constructor for the interface Storable.
StrandedLocatedSequenceAnnotationWithLength - Class in de.jstacs.data.sequences.annotation
Class for a SequenceAnnotation that has a position, a length and an orientation on the strand of a Sequence.
StrandedLocatedSequenceAnnotationWithLength(int, int, StrandedLocatedSequenceAnnotationWithLength.Strand, String, String, Result...) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results results.
StrandedLocatedSequenceAnnotationWithLength(int, int, StrandedLocatedSequenceAnnotationWithLength.Strand, String, String, Collection<Result>) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as a Collection of Results results.
StrandedLocatedSequenceAnnotationWithLength(int, int, StrandedLocatedSequenceAnnotationWithLength.Strand, String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotations and sub-annotations annotations.
StrandedLocatedSequenceAnnotationWithLength(String, String, StrandedLocatedSequenceAnnotationWithLength.Strand, LocatedSequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
Creates a new StrandedLocatedSequenceAnnotationWithLength of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotations and sub-annotations annotations.
StrandedLocatedSequenceAnnotationWithLength(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
The standard constructor for the interface Storable.
StrandedLocatedSequenceAnnotationWithLength.Strand - Enum in de.jstacs.data.sequences.annotation
This enum defines possible orientations on the strands.
strandedness() - Method in enum de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength.Strand
Returns the strandedness, i.e. the orientation on the strand of the sequence as a String.
StrandModel - Class in de.jstacs.models.mixture
This model handles sequences that can either lie on the forward strand or on the backward strand.
StrandModel(Model, int, boolean, double[], double, AbstractMixtureModel.Algorithm, double, double, AbstractMixtureModel.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates a new StrandModel.
StrandModel(Model, int, double[], double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using EM and estimating the component probabilities.
StrandModel(Model, int, double, double, double, AbstractMixtureModel.Parameterization) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using EM and fixed component probabilities.
StrandModel(Model, int, double[], int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using Gibbs Sampling and sampling the component probabilities.
StrandModel(Model, int, double, int, int, BurnInTest) - Constructor for class de.jstacs.models.mixture.StrandModel
Creates an instance using Gibbs Sampling and fixed component probabilities.
StrandModel(StringBuffer) - Constructor for class de.jstacs.models.mixture.StrandModel
The constructor for the interface Storable.
StrandScoringFunction - Class in de.jstacs.scoringFunctions.mix
This class enables the user to search on both strand.
StrandScoringFunction(NormalizableScoringFunction, double, int, boolean, StrandScoringFunction.InitMethod) - Constructor for class de.jstacs.scoringFunctions.mix.StrandScoringFunction
This constructor creates a StrandScoringFunction that optimizes the usage of each strand.
StrandScoringFunction(NormalizableScoringFunction, int, boolean, StrandScoringFunction.InitMethod, double) - Constructor for class de.jstacs.scoringFunctions.mix.StrandScoringFunction
This constructor creates a StrandScoringFunction that has a fixed frequency for the strand usage.
StrandScoringFunction(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.mix.StrandScoringFunction
This is the constructor for Storable.
StrandScoringFunction.InitMethod - Enum in de.jstacs.scoringFunctions.mix
This enum defines the different types of plug-in initialization of a StrandScoringFunction.
StringArrayWithTags(String[]) - Static method in class de.jstacs.io.XMLParser
Encodes a String array.
StringExtractor - Class in de.jstacs.io
This class implements the reader that extracts Strings from either a File or a String.
StringExtractor(File, int) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file.
StringExtractor(File, int, char) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file and ignores those starting with the comment character ignore.
StringExtractor(File, int, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file and sets the annotation of the source to annotation.
StringExtractor(File, int, char, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from file, ignores those starting with the comment character ignore and sets the annotation of the source to annotation.
StringExtractor(String, int, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from a String content and sets the annotation of the source to annotation.
StringExtractor(String, int, char, String) - Constructor for class de.jstacs.io.StringExtractor
A constructor that reads the lines from a String content, ignores those starting with the comment character ignore and sets the annotation of the source to annotation.
StructureLearner - Class in de.jstacs.models.discrete.inhomogeneous
This class can be used to learn the structure of any discrete model.
StructureLearner(AlphabetContainer, int, double) - Constructor for class de.jstacs.models.discrete.inhomogeneous.StructureLearner
Creates a new StructureLearner for a given AlphabetContainer, a given length and a given equivalent sample size (ess).
StructureLearner(AlphabetContainer, int) - Constructor for class de.jstacs.models.discrete.inhomogeneous.StructureLearner
Creates a StructureLearner with equivalent sample size (ess) = 0.
StructureLearner.LearningType - Enum in de.jstacs.models.discrete.inhomogeneous
This enum defines the different types of learning that are possible with the StructureLearner.
StructureLearner.ModelType - Enum in de.jstacs.models.discrete.inhomogeneous
This enum defines the different types of models that can be learned with the StructureLearner.
structureMeasure - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Measure that defines the network structure.
SubclassFinder - Class in de.jstacs.utils
Utility-class with static methods to find all sub-classes of a certain class (or interface) within the scope of the current class-loader find all sub-classes of a certain class (or interface) within the scope of the current class-loader that can be instantiated, i.e. that are neither interfaces nor abstract filter a set of classes by inheritance from a super-class obtain the class of an InstanceParameterSet that can be used to instantiate a sub-class of InstantiableFromParameterSet.
SubclassFinder() - Constructor for class de.jstacs.utils.SubclassFinder
 
subSampling(int) - Method in class de.jstacs.data.Sample
Randomly samples elements, i.e.
SubstringFilenameFilter - Class in de.jstacs.io
A simple filter on Files that accepts Files with a specific substring in the filename.
SubstringFilenameFilter(SubstringFilenameFilter.PartOfName, String, boolean, boolean, String...) - Constructor for class de.jstacs.io.SubstringFilenameFilter
Creates a new SubstringFilenameFilter with given substring(s) of type type to be found in the filename of the Files to be filtered.
SubstringFilenameFilter.PartOfName - Enum in de.jstacs.io
This enum defines the different types of a String that can be part of an other String, i.e. the different types of substrings.
sum - Variable in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction
The sums of the weighted data per class and additional the total weight sum.
sum(double[]) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
Computes the sum of all elements in the array ar.
sumNormalisation(double[]) - Static method in class de.jstacs.utils.Normalisation
The method does a sum-normalisation on d and returns the the sum of the values.
sumNormalisation(double[], double[], int) - Static method in class de.jstacs.utils.Normalisation
The method does a sum-normalisation on d.
swap() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method swaps the current component models with the alternative model.
symbol - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
The symbol (out of some Alphabet) this parameter is responsible for.
SymbolExtractor - Class in de.jstacs.io
This class enables you to extract elements (symbols) from a given String similar to a StringTokenizer.
SymbolExtractor(String) - Constructor for class de.jstacs.io.SymbolExtractor
Creates a new SymbolExtractor using delim as delimiter.
SymbolExtractor(String, String) - Constructor for class de.jstacs.io.SymbolExtractor
Creates a new SymbolExtractor using delim as delimiter and string as the String to be parsed.
SymmetricTensor - Class in de.jstacs.algorithms.graphs.tensor
This class can be used for Tensors with a special symmetry property.
SymmetricTensor(int, byte) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
This constructor creates an empty symmetric tensor with given dimension.
SymmetricTensor(SymmetricTensor[], double[]) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
The constructor can be used creating a new SymmetricTensor as weighted sum of SymmetricTensors.
SymmetricTensor(AsymmetricTensor) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
This constructor creates and checks a filled asymmetric tensor from an AsymmetricTensor instance.
SymmetricTensor(double[][][], int, byte) - Constructor for class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
This constructor creates and checks a filled asymmetric tensor with given dimension.

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