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## A

AbsoluteValueCondition - Class in de.jstacs.algorithms.optimization.termination
  Deprecated. use of the absolute value condition is not recommended and it may be removed in future releases
AbsoluteValueCondition(double) - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition
  Deprecated. This constructor creates an instance that stops an minimization when the value of the function is below the given `threshold`
  Be careful!
AbsoluteValueCondition(AbsoluteValueCondition.AbsoluteValueConditionParameterSet) - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition
  Deprecated. This is the main constructor creating an instance from a given parameter set.
AbsoluteValueCondition(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition
  Deprecated. The standard constructor for the interface `Storable`.
AbsoluteValueCondition.AbsoluteValueConditionParameterSet - Class in de.jstacs.algorithms.optimization.termination
  Deprecated. This class implements the parameter set for a `AbsoluteValueCondition`.
AbsoluteValueCondition.AbsoluteValueConditionParameterSet() - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
  Deprecated. This constructor creates an empty parameter set.
AbsoluteValueCondition.AbsoluteValueConditionParameterSet(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
  Deprecated. The standard constructor for the interface `Storable`.
AbsoluteValueCondition.AbsoluteValueConditionParameterSet(double) - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
  Deprecated. This constructor creates a filled instance of a parameters set.
AbstractBurnInTest - Class in de.jstacs.sampling
  This abstract class implements some of the methods of `BurnInTest` to alleviate the implementation of efficient and new burn-in tests.
AbstractBurnInTest(AbstractBurnInTestParameterSet) - Constructor for class de.jstacs.sampling.AbstractBurnInTest
  This is the main constructor that creates a burn-in test given a specified set of parameters
AbstractBurnInTest(StringBuffer) - Constructor for class de.jstacs.sampling.AbstractBurnInTest
  This is the constructor for the `Storable` interface.
AbstractBurnInTestParameterSet - Class in de.jstacs.sampling
  Class for the parameters of a `AbstractBurnInTest`.
AbstractBurnInTestParameterSet(Class<? extends AbstractBurnInTest>) - Constructor for class de.jstacs.sampling.AbstractBurnInTestParameterSet
  Creates a new `AbstractBurnInTestParameterSet` with empty parameter values.
AbstractBurnInTestParameterSet(Class<? extends AbstractBurnInTest>, int) - Constructor for class de.jstacs.sampling.AbstractBurnInTestParameterSet
  Creates a new `AbstractBurnInTestParameterSet` with pre-defined parameter values.
AbstractBurnInTestParameterSet(StringBuffer) - Constructor for class de.jstacs.sampling.AbstractBurnInTestParameterSet
  The standard constructor for the interface `Storable`.
AbstractClassifier - Class in de.jstacs.classifiers
  The super class for any classifier.
AbstractClassifier(AlphabetContainer) - Constructor for class de.jstacs.classifiers.AbstractClassifier
  The constructor for a homogeneous classifier.
AbstractClassifier(AlphabetContainer, int) - Constructor for class de.jstacs.classifiers.AbstractClassifier
  The constructor for an inhomogeneous classifier.
AbstractClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.AbstractClassifier
  The standard constructor for the interface `Storable`.
AbstractConditionalDiscreteEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete
  The abstract super class of discrete emissions.
AbstractConditionalDiscreteEmission(AlphabetContainer, int, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  This is a simple constructor for a `AbstractConditionalDiscreteEmission` based on the equivalent sample size.
AbstractConditionalDiscreteEmission(AlphabetContainer, double[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  This is a simple constructor for a `AbstractConditionalDiscreteEmission` defining the individual hyper parameters.
AbstractConditionalDiscreteEmission(AlphabetContainer, double[][], double[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  This constructor creates a `AbstractConditionalDiscreteEmission` defining the individual hyper parameters for the prior used during training and initialization.
AbstractConditionalDiscreteEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  Creates a `AbstractConditionalDiscreteEmission` from its XML representation.
AbstractDifferentiableSequenceScore - Class in de.jstacs.sequenceScores.differentiable
  This class is the main part of any `ScoreClassifier`.
AbstractDifferentiableSequenceScore(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
  The main constructor.
AbstractDifferentiableSequenceScore(StringBuffer) - Constructor for class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
  This is the constructor for `Storable`.
AbstractDifferentiableStatisticalModel - Class in de.jstacs.sequenceScores.statisticalModels.differentiable
  This class is the main part of any `ScoreClassifier`.
AbstractDifferentiableStatisticalModel(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
  The main constructor.
AbstractDifferentiableStatisticalModel(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractDifferentiableStatisticalModel
  This is the constructor for `Storable`.
AbstractHMM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
  This class is the super class of all implementations hidden Markov models (HMMs) in Jstacs.
AbstractHMM(HMMTrainingParameterSet, String[], int[], boolean[], Emission[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
  This is the main constructor for an HMM.
AbstractHMM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
  The standard constructor for the interface `Storable`.
AbstractMixtureDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture
  This main abstract class for any mixture scoring function (e.g.
AbstractMixtureDiffSM(int, int, int, boolean, boolean, DifferentiableStatisticalModel...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
  This constructor creates a new `AbstractMixtureDiffSM`.
AbstractMixtureDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
  This is the constructor for the interface `Storable`.
AbstractMixtureTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture
  This is the abstract class for all kinds of mixture models.
AbstractMixtureTrainSM(int, TrainableStatisticalModel[], boolean[], int, int, boolean, double[], double[], AbstractMixtureTrainSM.Algorithm, double, TerminationCondition, AbstractMixtureTrainSM.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  Creates a new `AbstractMixtureTrainSM`.
AbstractMixtureTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  The standard constructor for the interface `Storable`.
AbstractMixtureTrainSM.Algorithm - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.mixture
  This `enum` defines the different types of algorithms that can be used in an `AbstractMixtureTrainSM`.
AbstractMixtureTrainSM.Parameterization - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.mixture
  This `enum` defines the different types of parameterization for a probability that can be used in an `AbstractMixtureTrainSM`.
AbstractMultiThreadedOptimizableFunction - Class in de.jstacs.classifiers.differentiableSequenceScoreBased
  This class enables the user to exploit all CPUs of an computer by using threads.
AbstractMultiThreadedOptimizableFunction(int, DataSet[], double[][], boolean, boolean) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction
  The constructor for an multi-threaded instance.
AbstractOptimizableFunction - Class in de.jstacs.classifiers.differentiableSequenceScoreBased
  This class extends `OptimizableFunction` and implements some common methods.
AbstractOptimizableFunction(DataSet[], double[][], boolean, boolean) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction
  The constructor creates an instance using the given weighted data.
AbstractPerformanceMeasure - Class in de.jstacs.classifiers.performanceMeasures
  This class is the abstract super class of any performance measure used to evaluate an `AbstractClassifier`.
AbstractPerformanceMeasure() - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
  Constructs a new `AbstractPerformanceMeasure` with empty parameter values.
AbstractPerformanceMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
  The standard constructor for the interface `Storable`.
AbstractScoreBasedClassifier - Class in de.jstacs.classifiers
  This class is the main class for all score based classifiers.
AbstractScoreBasedClassifier(AlphabetContainer, int) - Constructor for class de.jstacs.classifiers.AbstractScoreBasedClassifier
  The constructor for a homogeneous classifier.
AbstractScoreBasedClassifier(AlphabetContainer, int, double) - Constructor for class de.jstacs.classifiers.AbstractScoreBasedClassifier
  The constructor for a homogeneous classifier.
AbstractScoreBasedClassifier(AlphabetContainer, int, int) - Constructor for class de.jstacs.classifiers.AbstractScoreBasedClassifier
  The constructor for an inhomogeneous classifier.
AbstractScoreBasedClassifier(AlphabetContainer, int, int, double) - Constructor for class de.jstacs.classifiers.AbstractScoreBasedClassifier
  The constructor for an inhomogeneous classifier.
AbstractScoreBasedClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.AbstractScoreBasedClassifier
  The standard constructor for the interface `Storable`.
AbstractScoreBasedClassifier.DoubleTableResult - Class in de.jstacs.classifiers
  This class is for `Result`s given as a table of `double` s.
AbstractScoreBasedClassifier.DoubleTableResult(String, String, AbstractList<double[]>) - Constructor for class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
  This is the default constructor that creates an instance based on the results given in `list`
AbstractScoreBasedClassifier.DoubleTableResult(StringBuffer) - Constructor for class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
  The standard constructor for the interface `Storable` .
AbstractSelectionParameter - Class in de.jstacs.parameters
  Class for a collection parameter, i.e. a parameter that provides some collection of possible values the user can choose from.
AbstractSelectionParameter(DataType, String[], Object[], String, String, boolean) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
  Constructor for a `AbstractSelectionParameter` of `SimpleParameter`s.
AbstractSelectionParameter(DataType, String[], Object[], String[], String, String, boolean) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
  Constructor for a `AbstractSelectionParameter`.
AbstractSelectionParameter(String, String, boolean, ParameterSet...) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
  Constructor for a `AbstractSelectionParameter` from an array of `ParameterSet`s.
AbstractSelectionParameter(String, String, boolean, Class<? extends ParameterSet>...) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
  Constructor for a `AbstractSelectionParameter` from an array of `Class`es of `ParameterSet`s.
AbstractSelectionParameter(StringBuffer) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
  The standard constructor for the interface `Storable`.
AbstractSelectionParameter.InconsistentCollectionException - Exception in de.jstacs.parameters
  This exception is thrown if the `AbstractSelectionParameter` is inconsistent for some reason.
AbstractSelectionParameter.InconsistentCollectionException(String) - Constructor for exception de.jstacs.parameters.AbstractSelectionParameter.InconsistentCollectionException
  Constructs a new `AbstractSelectionParameter.InconsistentCollectionException` with message `message`.
AbstractStringExtractor - Class in de.jstacs.io
  This class implements the reader that extracts strings.
AbstractStringExtractor(char) - Constructor for class de.jstacs.io.AbstractStringExtractor
  Creates a new `AbstractStringExtractor` with the specified character as start of each comment line.
AbstractTerminationCondition - Class in de.jstacs.algorithms.optimization.termination
  This class is the abstract super class of many `TerminationCondition`s.
AbstractTerminationCondition(AbstractTerminationCondition.AbstractTerminationConditionParameterSet) - Constructor for class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
  This is the main constructor creating an instance from a given parameter set.
AbstractTerminationCondition(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
  The standard constructor for the interface `Storable`.
AbstractTerminationCondition.AbstractTerminationConditionParameterSet - Class in de.jstacs.algorithms.optimization.termination
  This class implements the super class of all parameter sets of instances from `AbstractTerminationCondition`.
AbstractTerminationCondition.AbstractTerminationConditionParameterSet(Class<? extends AbstractTerminationCondition>) - Constructor for class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition.AbstractTerminationConditionParameterSet
  Constructs an `AbstractTerminationCondition.AbstractTerminationConditionParameterSet` from the class that can be instantiated using this `AbstractTerminationCondition.AbstractTerminationConditionParameterSet`.
AbstractTerminationCondition.AbstractTerminationConditionParameterSet(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition.AbstractTerminationConditionParameterSet
  The standard constructor for the interface `Storable`.
AbstractTrainableStatisticalModel - Class in de.jstacs.sequenceScores.statisticalModels.trainable
  Abstract class for a model for pattern recognition.
AbstractTrainableStatisticalModel(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
  Constructor that sets the length of the model to `length` and the `AlphabetContainer` to `alphabets`.
AbstractTrainableStatisticalModel(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
  The standard constructor for the interface `Storable`.
AbstractVariableLengthDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable
  This abstract class implements some methods declared in `DifferentiableStatisticalModel` based on the declaration of methods in `VariableLengthDiffSM`.
AbstractVariableLengthDiffSM(AlphabetContainer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
  This is the main constructor that creates an instance of a `VariableLengthDiffSM` that models sequences of arbitrary length.
AbstractVariableLengthDiffSM(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
  This is the main constructor that creates an instance of a `VariableLengthDiffSM` that models sequences of a given length.
AbstractVariableLengthDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM
  This is the constructor for the interface `Storable`.
accept(File) - Method in class de.jstacs.io.CombinedFileFilter
accept(File) - Method in class de.jstacs.io.DateFileFilter
accept(File) - Method in class de.jstacs.io.RegExFilenameFilter
accept(File, String) - Method in class de.jstacs.io.RegExFilenameFilter
acceptParameters() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier.DiffSMSamplingComponent
acceptParameters() - Method in interface de.jstacs.sampling.SamplingComponent
  This methods accepts the drawn parameters.
acceptParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
acceptParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
  This method can be used to accept the current parameters (and save them into a file)
acceptParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
acceptParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
acceptParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
acceptParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
actionPerformed(ActionEvent) - Method in class de.jstacs.utils.GUIProgressUpdater
add(int, T) - Method in class de.jstacs.AnnotatedEntityList
  Adds the `AnnotatedEntity` `entity` at index `idx` to the list.
add(T...) - Method in class de.jstacs.AnnotatedEntityList
  Adds all `AnnotatedEntity`s in `entities` to the list.
add(String, int, int, StrandedLocatedSequenceAnnotationWithLength.Strand) - Method in class de.jstacs.data.sequences.annotation.MotifAnnotationParser
  Adds the motif with identifier `identifier` at position `position` with length `length` and `StrandedLocatedSequenceAnnotationWithLength.Strand` `strandedness`
add(String, String) - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotationParser
add(String, String) - Method in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
  This method actually adds a `SequenceAnnotation` to the internal list.
add(int, Parameter) - Method in class de.jstacs.parameters.ParameterSet.ParameterList
add(Parameter...) - Method in class de.jstacs.parameters.ParameterSet.ParameterList
add(int, double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
  Adds the given `weight` to the count with index `index`.
add(Sequence, int, double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
  This method determines the specific constraint that is fulfilled by the `Sequence` `seq` and adds the `weight` to the specific counter.
add(double) - Method in class de.jstacs.utils.DoubleList
  Adds the element `val` at the end of the list.
add(double, int, int) - Method in class de.jstacs.utils.DoubleList
  Adds the element `val` from `fromIndex` to `toIndex` (exclusive).
add(int) - Method in class de.jstacs.utils.IntList
  Adds the element `val` at the end of the list.
addAll(Collection<? extends T>) - Method in class de.jstacs.AnnotatedEntityList
  Adds all `AnnotatedEntity`s in `entities` to the list.
addAll(Sequence, double, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
  Adds the given `weight` to the counts corresponding to the `Sequence` `seq` from `start` to the end of the `Sequence`.
addAll(DoubleList) - Method in class de.jstacs.utils.DoubleList
  This method adds all elements of `DoubleList` `list2` to the current list.
addChild(PhyloNode) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
  This method adds a children node to the current instance
addConditional(int) - Method in class de.jstacs.utils.IntList
  Adds `val` to the list only if it is not already contained in the list.
addConstraint(Constraint) - Method in class de.jstacs.parameters.validation.ConstraintValidator
  Adds an additional `Constraint` to the list of `Constraint`s.
addCount(double) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
  Adds `count2` to the counts of this parameter.
addCount(Sequence, int, double) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
  Adds `count` to the parameter as returned by `BNDiffSMParameterTree.getParameterFor(Sequence, int)`.
addGradientFor(double[], double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
addGradientFor(double[], double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
addGradientFor(double[], double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior
  Adds the gradient of the log-prior using the current parameters to a given vector.
addGradientFor(double[], double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior
addGradientFor(double[], double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLaplaceLogPrior
addGradientFor(double[], double[]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
addGradientForLogPriorTerm(double[], int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.DifferentiableTransition
  This method computes the gradient of `Transition.getLogPriorTerm()` for each parameter of this transition.
addGradientForLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
  This method computes the gradient of `BasicHigherOrderTransition.AbstractTransitionElement.getLogPriorTerm()` for each parameter of this transition element.
addGradientForLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in interface de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel
  This method computes the gradient of `DifferentiableStatisticalModel.getLogPriorTerm()` for each parameter of this model.
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
addGradientOfLogPriorTerm(double[], int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.DifferentiableEmission
  This method computes the gradient of `Emission.getLogPriorTerm()` for each parameter of this model.
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
addGradientOfLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
addMeasure(AbstractPerformanceMeasure) - Method in class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
  Deprecated.
addParameters(int, IntList, MEMConstraint[], double[], int[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
addParameterToSet() - Method in class de.jstacs.parameters.ExpandableParameterSet
  Adds a new `ParameterSetContainer` containing a clone of the `ParameterSet`-template to the set of `Parameter`s.
addResult(Result, boolean, boolean) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor
  Adds a result to the results of a program run.
addResults(MeanResultSet, MeanResultSet) - Static method in class de.jstacs.results.MeanResultSet
  Adds two `MeanResultSet`s together.
addResults(NumericalResultSet...) - Method in class de.jstacs.results.MeanResultSet
  Adds `NumericalResultSet`s to this `MeanResultSet`.
addResultSet(ResultSet, boolean, boolean) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor
  Adds a set of results to the results of a program run.
addTags(StringBuffer, String) - Static method in class de.jstacs.io.XMLParser
  Frames the `StringBuffer` `source` with equal tags "< `tag`>" and "<`/tag` >".
addTagsAndAttributes(StringBuffer, String, String) - Static method in class de.jstacs.io.XMLParser
  Frames the `StringBuffer` `source` with "< `tag attributes`>" and "<`/tag` >".
addTermToClassParameter(int, double) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
  This method adds the `term` to the class parameter of the class with index `classIndex`.
addTo(int, int, double) - Method in class de.jstacs.utils.DoubleList
  Adds to all values in the list from index `start` to `end` the value `summand`.
addToAnnotation(String) - Method in class de.jstacs.data.sequences.annotation.MotifAnnotationParser
addToAnnotation(String) - Method in class de.jstacs.data.sequences.annotation.NullSequenceAnnotationParser
addToAnnotation(String) - Method in interface de.jstacs.data.sequences.annotation.SequenceAnnotationParser
  This method adds the `unparsed` `String` in some way to the `SequenceAnnotation`.
addToAnnotation(String) - Method in class de.jstacs.data.sequences.annotation.SimpleSequenceAnnotationParser
addToAnnotation(String) - Method in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
addToRepresentation(Object, int, String) - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
addToRepresentation(Object, int, String) - Method in class de.jstacs.data.sequences.ArbitrarySequence
addToRepresentation(Object, int, String) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
addToRepresentation(Object, int, String) - Method in class de.jstacs.data.sequences.Sequence
  This method adds the information of one position to the representation using the specified delimiter
addToRepresentation(Object, int, String) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
addToRepresentation(Object, int, String) - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
addToStatistic(boolean, int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
addToStatistic(boolean, int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
addToStatistic(boolean, int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
addToStatistic(boolean, int, int, double, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission
  This method adds the `weight` to the internal sufficient statistic.
addToStatistic(boolean, int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
addToStatistic(boolean, int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
addToStatistic(boolean, int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
addToStatistic(int, int, double, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState
addToStatistic(int, int, double, Sequence) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.TrainableState
  This method allows to add a certain `weight` to the sufficient statistic of the parameters that are used for scoring the specific subsequence(s).
addToStatistic(int, double, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  This method adds a given weight to the sufficient statistic for the parameters.
addToStatistic(int, int, int, double, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
addToStatistic(int, double, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
addToStatistic(int, double, Sequence, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
addToStatistic(int, int, int, double, Sequence, int) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.TransitionWithSufficientStatistic
  This method allows to add a certain `weight` to the sufficient statistic of a specific transition.
adjust(int[], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
  This method adjust the parameter based on the given statistic.
adjust(int[], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
adjust(int[], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
adjust(int[], double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM
adjustHiddenParameters(int, DataSet[], double[][]) - Method in interface de.jstacs.motifDiscovery.MutableMotifDiscoverer
  Adjusts all hidden parameters including duration and mixture parameters according to the current values of the remaining parameters.
adjustHiddenParameters(int, DataSet[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM
adjustHiddenParameters(int, DataSet[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
adjustHiddenParameters(int, DataSet[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
  Adjusts all hidden parameters including duration and mixture parameters according to the current values of the remaining parameters.
adjustHiddenParameters(int, DataSet[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
AffineCosts - Class in de.jstacs.algorithms.alignment.cost
  This class implements affine gap costs, i.e., the costs for starting a new gap are given by `start`, and the costs for elongating a gap by one position are given by `elong`.
AffineCosts(double, Costs) - Constructor for class de.jstacs.algorithms.alignment.cost.AffineCosts
  This constructor creates a new instance of cost using affine gap costs.
algorithm - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  The type of algorithm.
algorithmHasBeenRun - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  A switch which indicates that the algorithm for determining the parameters has been run.
algorithmHasBeenRun() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  This method indicates whether the parameters of the model has been determined by the internal algorithm.
Alignment - Class in de.jstacs.algorithms.alignment
  Class for computing optimal alignments using Needleman-Wunsch algorithm of for affine gap costs Gotohs algorithm.
Alignment(Alignment.AlignmentType, Costs) - Constructor for class de.jstacs.algorithms.alignment.Alignment
  Creates a new `Alignment` instance that aligns the sequences `s1` and `s2` using the costs defined in `costs`.
Alignment(Alignment.AlignmentType, Costs, int) - Constructor for class de.jstacs.algorithms.alignment.Alignment
  Creates a new `Alignment` instance that aligns the sequences `s1` and `s2` using the costs defined in `costs` and a banded version of the alignment algorithm.
Alignment.AlignmentType - Enum in de.jstacs.algorithms.alignment
Alphabet - Class in de.jstacs.data.alphabets
  Class for a set of symbols, i.e. an `Alphabet`.
Alphabet() - Constructor for class de.jstacs.data.alphabets.Alphabet
alphabet - Variable in class de.jstacs.data.alphabets.DiscreteAlphabet
  The alphabet as `String` array.
alphabet - Variable in class de.jstacs.parameters.SequenceScoringParameterSet
  The alphabet the model works on
Alphabet.AlphabetParameterSet<T extends Alphabet> - Class in de.jstacs.data.alphabets
  The super class for the `InstanceParameterSet` of any `Alphabet`.
Alphabet.AlphabetParameterSet(Class<T>) - Constructor for class de.jstacs.data.alphabets.Alphabet.AlphabetParameterSet
  Creates a new `Alphabet.AlphabetParameterSet` from the class that can be instantiated using this `Alphabet.AlphabetParameterSet`.
Alphabet.AlphabetParameterSet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.Alphabet.AlphabetParameterSet
  The standard constructor for the interface `Storable` .
alphabetCon - Variable in class de.jstacs.data.sequences.Sequence
  The underlying alphabets.
AlphabetContainer - Class in de.jstacs.data
  The container for `Alphabet`s used in a `Sequence`, `DataSet`, `AbstractTrainableStatisticalModel` or ... .
AlphabetContainer(Alphabet) - Constructor for class de.jstacs.data.AlphabetContainer
  Creates a new simple `AlphabetContainer`.
AlphabetContainer(Alphabet...) - Constructor for class de.jstacs.data.AlphabetContainer
  Creates a new `AlphabetContainer` with different `Alphabet`s for each position.
AlphabetContainer(AlphabetContainer[], int[]) - Constructor for class de.jstacs.data.AlphabetContainer
  Creates an new sparse `AlphabetContainer` based on given `AlphabetContainer`s.
AlphabetContainer(Alphabet[], int[]) - Constructor for class de.jstacs.data.AlphabetContainer
  Creates a new `AlphabetContainer` that uses different `Alphabet`s.
AlphabetContainer(AlphabetContainerParameterSet) - Constructor for class de.jstacs.data.AlphabetContainer
  Creates a new `AlphabetContainer` from an `AlphabetContainerParameterSet` that contains all necessary parameters.
AlphabetContainer(StringBuffer) - Constructor for class de.jstacs.data.AlphabetContainer
  The standard constructor for the interface `Storable`.
AlphabetContainer.AbstractAlphabetContainerParameterSet<T extends AlphabetContainer> - Class in de.jstacs.data
  This class is the super class of any `InstanceParameterSet` for `AlphabetContainer`.
AlphabetContainer.AbstractAlphabetContainerParameterSet(Class<? extends T>) - Constructor for class de.jstacs.data.AlphabetContainer.AbstractAlphabetContainerParameterSet
  Constructs an `AlphabetContainer.AbstractAlphabetContainerParameterSet` from the class that can be instantiated using this `AlphabetContainer.AbstractAlphabetContainerParameterSet`.
AlphabetContainer.AbstractAlphabetContainerParameterSet(StringBuffer) - Constructor for class de.jstacs.data.AlphabetContainer.AbstractAlphabetContainerParameterSet
  The standard constructor for the interface `Storable`.
AlphabetContainer.AlphabetContainerType - Enum in de.jstacs.data
  This `enum` defines types of `AlphabetContainer`s.
AlphabetContainerParameterSet - Class in de.jstacs.data
  Class for the `AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet` of an `AlphabetContainer`.
AlphabetContainerParameterSet(AlphabetContainer.AlphabetContainerType, boolean) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
  Creates a new `AlphabetContainerParameterSet` of an `AlphabetContainer` with `AlphabetContainer.AlphabetContainerType` `type`.
AlphabetContainerParameterSet() - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
  Creates a new `AlphabetContainerParameterSet` of a complex `AlphabetContainer` with `type` `AlphabetContainer.AlphabetContainerType.BOTH`.
AlphabetContainerParameterSet(StringBuffer) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
  The standard constructor for the interface `Storable`.
AlphabetContainerParameterSet(Alphabet) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
  Creates a new `AlphabetContainerParameterSet` of a simple `AlphabetContainer` from a single `Alphabet`.
AlphabetContainerParameterSet(Alphabet[]) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
  Creates a new `AlphabetContainerParameterSet` from an array of `Alphabet`s.
AlphabetContainerParameterSet(Class<? extends AlphabetContainer>, Alphabet...) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
  /** Creates a new `AlphabetContainerParameterSet` from an array of `Alphabet`s for a given sub-class of `AlphabetContainer`.
AlphabetContainerParameterSet(Alphabet[], int[]) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
  Creates a new `AlphabetContainerParameterSet` from an array of `Alphabet`s and an array of `int`s defining the `Alphabet` index `i` in `alphabets` that is used for position `i`.
AlphabetContainerParameterSet.AlphabetArrayParameterSet - Class in de.jstacs.data
  Class for the parameters of an array of `Alphabet`s of defined length.
AlphabetContainerParameterSet.AlphabetArrayParameterSet(AlphabetContainer.AlphabetContainerType) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
  Creates a new `AlphabetContainerParameterSet.AlphabetArrayParameterSet` from the information about the `type` of the `Alphabet`s, e.g. if the array shall contain only the parameters for discrete `Alphabet` s.
AlphabetContainerParameterSet.AlphabetArrayParameterSet() - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
  Creates a new `AlphabetContainerParameterSet.AlphabetArrayParameterSet` with `type` `AlphabetContainer.AlphabetContainerType.BOTH`.
AlphabetContainerParameterSet.AlphabetArrayParameterSet(StringBuffer) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
  The standard constructor for the interface `Storable` .
AlphabetContainerParameterSet.AlphabetArrayParameterSet(Alphabet[], AlphabetContainer.AlphabetContainerType) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
  Creates a new `AlphabetContainerParameterSet.AlphabetArrayParameterSet` from an array of `Alphabet`s and the information about the `type` of the `Alphabet`s.
AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet - Class in de.jstacs.data
  Class for the parameter set of an array of `Alphabet`s where each `Alphabet` may be used for one or more sections of positions.
AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet(AlphabetContainer.AlphabetContainerType) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
  Creates a new `AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet` for a set of discrete or continuous `Alphabet`s.
AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet() - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
  Creates a new `AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet` for a set of discrete and continuous `Alphabet`s.
AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet(Alphabet[], int[]) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
  Creates a new `AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet` from an array of `Alphabet`s and an array of indexes that define the index of the `Alphabet` in `alphabets` belonging to that position in `indexes`.
AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet(StringBuffer) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
  The standard constructor for the interface `Storable` .
alphabets - Variable in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
  The `AlphabetContainer` of this `AbstractDifferentiableSequenceScore` .
alphabets - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
  The underlying alphabets
alternativeModel - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  The alternative models for the EM.
annot - Variable in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
  The internal list of current `SequenceAnnotation`s.
annotate(boolean, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.Sequence
  This method allows to append annotation to a `Sequence`.
AnnotatedEntity - Class in de.jstacs
  Superclass for all Jstacs entities that have a name, a comment, and a data type as annotations.
AnnotatedEntity(String, String, DataType) - Constructor for class de.jstacs.AnnotatedEntity
  The main constructor which takes the main information of a `AnnotatedEntity`.
AnnotatedEntity(StringBuffer) - Constructor for class de.jstacs.AnnotatedEntity
  The standard constructor for the interface `Storable`.
AnnotatedEntityList<T extends AnnotatedEntity> - Class in de.jstacs
  Class for a list of `AnnotatedEntity`s where elements can be accessed either by index or by the name of the `AnnotatedEntity`.
AnnotatedEntityList() - Constructor for class de.jstacs.AnnotatedEntityList
  Creates a new `AnnotatedEntityList` with an initial capacity of 10.
AnnotatedEntityList(int) - Constructor for class de.jstacs.AnnotatedEntityList
  Creates a new `AnnotatedEntityList` with given initial capacity.
annotateMotif(DataSet, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
  This method annotates a `DataSet`.
annotateMotif(int, DataSet, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
  This method annotates a `DataSet` starting in each sequence at `startPos`.
annotateMotif(DataSet, int, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
  This method annotates a `DataSet`.
annotateMotif(int, DataSet, int, int, boolean) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
  This method annotates a `DataSet` starting in each sequence at `startPos`.
annotation - Variable in class de.jstacs.data.sequences.Sequence
  The annotation of the `Sequence`.
annotation - Variable in class de.jstacs.io.AbstractStringExtractor
  The annotation of the source.
annotationDelimiter - Variable in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
  The delimiter between different annotations
annotationID - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
  The annotation id used for determining the transition matrix from the `ReferenceSequenceAnnotation`s.
annotationParser - Variable in class de.jstacs.io.SparseStringExtractor
  A parser for the sequence annotation.
append(String) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.Protocol
  Appends `str` to the protocol.
appendAdditionalInfo(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
  This method appends additional information that is not stored in the base class to the `StringBuffer`.
appendAdditionalInfo(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
appendAdditionalInfo(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
appendAdditionalInfo(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhConstraint
appendAdditionalInfo(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
  This method appends further information to the XML representation.
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  This method appends further information to the XML representation.
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.ReferenceSequenceDiscreteEmission
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  This method appends further information to the XML representation.
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
  This method appends further information to the XML representation.
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicPluginTransitionElement
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.BasicTransitionElement
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
appendFurtherInformation(StringBuffer) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.AnnotatedEntity
  This method can be used in the method `Storable.toXML()` to extract further information (name, comment, datatype).
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.AbstractSelectionParameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.EnumParameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.FileParameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.MultiSelectionParameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.Parameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.ParameterSetContainer
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.RangeParameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.SelectionParameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.parameters.SimpleParameter
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.results.DataSetResult
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.results.ImageResult
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.results.ListResult
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.results.SimpleResult
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.results.StorableResult
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.FileResult
appendFurtherInfos(StringBuffer) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.LinkedImageResult
appendGraphvizDescription(StringBuffer, NumberFormat, String, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  This method appends the current transition element to a Graphviz representation of the structure that can be used to create an image.
appendHeading(String) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.Protocol
  Append a heading to the protocol
appendObjectWithTags(StringBuffer, Object, String) - Static method in class de.jstacs.io.XMLParser
  Appends an `Object` with the tags to the `StringBuffer` `xml`.
appendObjectWithTagsAndAttributes(StringBuffer, Object, String, String) - Static method in class de.jstacs.io.XMLParser
  Appends an `Object` with the tags and attributes to the `StringBuffer` `xml`.
appendObjectWithTagsAndAttributes(StringBuffer, Object, String, String, boolean) - Static method in class de.jstacs.io.XMLParser
  Appends an `Object` with the tags and attributes to the `StringBuffer` `xml`.
appendTransitions(StringBuffer, String, NumberFormat, String, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  This method appends all edges of the transition element to a given Graphviz representation.
appendTransitions(StringBuffer, String, NumberFormat, String, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
appendTransitions(StringBuffer, String, NumberFormat, String, boolean) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
appendWarning(String) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor.Protocol
  Appends a warning to the protocol
ArbitraryFloatSequence - Class in de.jstacs.data.sequences
  This class is for any continuous or hybrid sequence.
ArbitraryFloatSequence(AlphabetContainer, float[]) - Constructor for class de.jstacs.data.sequences.ArbitraryFloatSequence
  Creates a new `ArbitraryFloatSequence` from an array of `float`-encoded alphabet symbols.
ArbitraryFloatSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ArbitraryFloatSequence
  Creates a new `ArbitraryFloatSequence` from a `String` representation using the default delimiter.
ArbitraryFloatSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ArbitraryFloatSequence
  Creates a new `ArbitraryFloatSequence` from a `String` representation using the delimiter `delim`.
ArbitraryFloatSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ArbitraryFloatSequence
  Creates a new `ArbitraryFloatSequence` from a `SymbolExtractor`.
ArbitrarySequence - Class in de.jstacs.data.sequences
  This class is for any continuous or hybrid sequence.
ArbitrarySequence(AlphabetContainer, double[]) - Constructor for class de.jstacs.data.sequences.ArbitrarySequence
  Creates a new `ArbitrarySequence` from an array of `double`-encoded alphabet symbols.
ArbitrarySequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ArbitrarySequence
  Creates a new `ArbitrarySequence` from a `String` representation using the default delimiter.
ArbitrarySequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ArbitrarySequence
  Creates a new `ArbitrarySequence` from a `String` representation using the delimiter `delim`.
ArbitrarySequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ArbitrarySequence
  Creates a new `ArbitrarySequence` from a `SymbolExtractor`.
ArrayHandler - Class in de.jstacs.io
  This class handles arrays with elements of generic type and enables the user to cast, clone, and create arrays easily.
ArrayHandler() - Constructor for class de.jstacs.io.ArrayHandler
ArrayParameterSet - Class in de.jstacs.parameters
  Class for a `ParameterSet` that consists of a length-`Parameter` that defines the length of the array and an array of `ParameterSetContainer`s of this length.
ArrayParameterSet(ParameterSet, String, String, String, String, NumberValidator<Integer>) - Constructor for class de.jstacs.parameters.ArrayParameterSet
  Creates a new `ArrayParameterSet` from a `Class` that can be instantiated using this `ArrayParameterSet` and templates for the `ParameterSet` in each element of the array, the name and the comment that are displayed for the `ParameterSetContainer`s enclosing the `ParameterSet`s.
ArrayParameterSet(ParameterSet, String, String) - Constructor for class de.jstacs.parameters.ArrayParameterSet
  Creates a new `ArrayParameterSet` from a `Class` that can be instantiated using this `ArrayParameterSet` and templates for the `ParameterSet` in each element of the array, the name and the comment that are displayed for the `ParameterSetContainer`s enclosing the `ParameterSet`s.
ArrayParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.ArrayParameterSet
  The standard constructor for the interface `Storable`.
arrowOptions - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
  The Graphviz options for drawing the arrows.
arrowOptions - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
  The Graphviz options for distinguishing the arrows of the different transitions.
assess(NumericalPerformanceMeasureParameterSet, ClassifierAssessmentAssessParameterSet, DataSet...) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
  Assesses the contained classifiers.
assess(NumericalPerformanceMeasureParameterSet, ClassifierAssessmentAssessParameterSet, ProgressUpdater, DataSet...) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
  Assesses the contained classifiers.
assess(NumericalPerformanceMeasureParameterSet, ClassifierAssessmentAssessParameterSet, ProgressUpdater, DataSet[][]...) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
  Assesses the contained classifiers.
assess(DataSet, DataSet, int) - Static method in class de.jstacs.motifDiscovery.MotifDiscoveryAssessment
  This method computes the nucleotide and site measures.
assessWithPredefinedSplits(NumericalPerformanceMeasureParameterSet, ClassifierAssessmentAssessParameterSet, ProgressUpdater, DataSet[]...) - Method in class de.jstacs.classifiers.assessment.KFoldCrossValidation
  This method implements a k-fold crossvalidation on previously split data.
AsymmetricTensor - Class in de.jstacs.algorithms.graphs.tensor
  This class can be used for `Tensor`s which are not symmetric, as opposed to the symmetry defined in `SymmetricTensor`.
AsymmetricTensor(int, byte) - Constructor for class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
  This constructor creates an empty asymmetric tensor with given dimension.
AsymmetricTensor(double[][][], int, byte) - Constructor for class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
  This constructor creates and checks a filled asymmetric tensor with given dimension.
AucPR - Class in de.jstacs.classifiers.performanceMeasures
  This class implements the area under curve of the precision-recall curve.
AucPR() - Constructor for class de.jstacs.classifiers.performanceMeasures.AucPR
  Constructs a new instance of the performance measure `AucPR`.
AucPR(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.AucPR
  The standard constructor for the interface `Storable`.
AucROC - Class in de.jstacs.classifiers.performanceMeasures
  This class implements the area under curve of the Receiver Operating Characteristics curve.
AucROC() - Constructor for class de.jstacs.classifiers.performanceMeasures.AucROC
  Constructs a new instance of the performance measure `AucROC`.
AucROC(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.AucROC
  The standard constructor for the interface `Storable`.

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