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

H

hasAnySelfTransitions() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition

hasAnySelfTransitions() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition

This method answers the question whether the instance models any self transitions.

hasBeenOptimized - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

This boolean indicates whether the classifier has been optimized with the method AbstractClassifier.train(DataSet[]) or the weighted version.

hasBeenOptimized() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier

This method indicates if the classifier has been optimized by a train-method.

hasDefault() - Method in class de.jstacs.parameters.AbstractSelectionParameter

Returns true, if this AbstractSelectionParameter has a default value.

hasDefault() - Method in class de.jstacs.parameters.MultiSelectionParameter

hasDefault() - Method in class de.jstacs.parameters.SelectionParameter

Returns true, if this SelectionParameter has a default value.

hasDefaultOrIsSet() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet

hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ArrayParameterSet

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

hasDefaultOrIsSet() - Method in class de.jstacs.parameters.MultiSelectionParameter

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

Returns true if the parameter either has a default value or the value was set by the user, false otherwise.

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

Returns true if all parameters in this ParameterSet are either set by the user or have default values.

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

hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ParameterSetTagger

This method allows to check whether all tagged parameters that require a value also have some value.

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

hasDefaultOrIsSet() - Method in class de.jstacs.parameters.SelectionParameter

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

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

hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DGTrainSMParameterSet

hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet

hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.BaumWelchParameterSet

hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.ViterbiParameterSet

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

hashCode() - Method in class de.jstacs.data.sequences.Sequence

hashCodeForPos(int) - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence

hashCodeForPos(int) - Method in class de.jstacs.data.sequences.ArbitrarySequence

hashCodeForPos(int) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence

hashCodeForPos(int) - Method in class de.jstacs.data.sequences.Sequence

This method is used in Sequence.hashCode() and the hash code for one specific position.

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

hashCodeForPos(int) - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence

hasMoreElements() - Method in class de.jstacs.data.DataSet.ElementEnumerator

hasMoreElements() - Method in class de.jstacs.data.DataSetKMerEnumerator

hasMoreElements() - Method in class de.jstacs.data.DiscreteSequenceEnumerator

hasMoreElements() - Method in class de.jstacs.data.SequenceEnumeration

hasMoreElements() - Method in class de.jstacs.io.InfixStringExtractor

hasMoreElements() - Method in class de.jstacs.io.LimitedStringExtractor

hasMoreElements() - Method in class de.jstacs.io.SimpleStringExtractor

hasMoreElements() - Method in class de.jstacs.io.SparseStringExtractor

hasMoreElements() - Method in class de.jstacs.io.StringExtractor

hasMoreElements() - Method in class de.jstacs.io.SymbolExtractor

hasNext() - Method in class de.jstacs.data.bioJava.SimpleSequenceIterator

hasNext() - Method in class de.jstacs.data.DataSet.ElementEnumerator

hasSampled - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

This boolean indicates if the parameters for the model were sampled

hasTag(StringBuffer, String, Map<String, String>, Map<String, String>) - Static method in class de.jstacs.io.XMLParser

This method allows to check whether an XML contains a tagged entry.

helpArray - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LogGenDisMixFunction

General temporary array

HiddenMotifMixture - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif

This is the main class that every generative motif discoverer should implement.

HiddenMotifMixture(TrainableStatisticalModel[], boolean[], int, int, boolean, double[], double[], PositionPrior, AbstractMixtureTrainSM.Algorithm, double, TerminationCondition, AbstractMixtureTrainSM.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture

Creates a new HiddenMotifMixture.

HiddenMotifMixture(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture

The standard constructor for the interface Storable.

hiddenParameter - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This array contains the hidden parameters of the instance.

hiddenPotential - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM

This array contains the hidden potentials of the instance.

HigherOrderHMM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models

This class implements a higher order hidden Markov model.

HigherOrderHMM(HMMTrainingParameterSet, String[], Emission[], BasicHigherOrderTransition.AbstractTransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

This is a convenience constructor.

HigherOrderHMM(HMMTrainingParameterSet, String[], int[], boolean[], Emission[], BasicHigherOrderTransition.AbstractTransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

This is the main constructor.

HigherOrderHMM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

The standard constructor for the interface Storable.

HigherOrderHMM.Type - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models

This enum defined different types of computations that will be done using the backward algorithm.

HigherOrderTransition - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions

This class can be used in any AbstractHMM allowing to use gradient based or sampling training algorithm.

HigherOrderTransition(boolean[], TransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition

The main constructor.

HigherOrderTransition(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition

The standard constructor for the interface Storable.

History - Interface in de.jstacs.motifDiscovery.history

This interface is used to manage the history of some process.

HMMFactory - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm

This class allows to create some frequently used HMMs.

HMMFactory() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory

HMMFactory.HMMType - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.hmm

This enum defines some standard architecture of profile HMMs.

HMMFactory.PseudoTransitionElement - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm

This class is used as place holder for a later BasicHigherOrderTransition.AbstractTransitionElement.

HMMFactory.PseudoTransitionElement(int[], int[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory.PseudoTransitionElement

This constructor creates an new HMMFactory.PseudoTransitionElement without edge weights.

HMMFactory.PseudoTransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory.PseudoTransitionElement

This constructor creates an new HMMFactory.PseudoTransitionElement with specific edge weights.

HMMTrainingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training

This class implements an abstract ParameterSet that is used for the training of an AbstractHMM.

HMMTrainingParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet

This is the empty constructor that can be used to fill the parameters after creation.

HMMTrainingParameterSet(int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet

This constructor can be used to create an instance with a specified number of starts.

HMMTrainingParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet

The standard constructor for the interface Storable.

HomMMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters

This class implements a container for all parameters of a homogeneous Markov model.

HomMMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet

The standard constructor for the interface Storable.

HomMMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet

An empty constructor.

HomMMParameterSet(AlphabetContainer, double, String, byte) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet

Creates a new HomMMParameterSet with AlphabetContainer, ess (equivalent sample size), description and order of the homogeneous Markov model.

HomogeneousDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

This is the main class for all homogeneous DifferentiableSequenceScores.

HomogeneousDiffSM(AlphabetContainer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM

This is the main constructor that creates an instance of a HomogeneousDiffSM that models sequences of arbitrary length.

HomogeneousDiffSM(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM

This is the main constructor that creates an instance of a HomogeneousDiffSM that models sequences of a given length.

HomogeneousDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM

This is the constructor for Storable.

HomogeneousMM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

This class implements homogeneous Markov models (hMM) of arbitrary order.

HomogeneousMM(HomMMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM

Creates a new homogeneous Markov model from a parameter set.

HomogeneousMM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM

The standard constructor for the interface Storable.

HomogeneousMM0DiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.

HomogeneousMM0DiffSM(AlphabetContainer, int, double, boolean, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM

The main constructor that creates an instance of a homogeneous Markov model of order 0.

HomogeneousMM0DiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM

This is the constructor for Storable.

HomogeneousMMDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.

HomogeneousMMDiffSM(AlphabetContainer, int, double, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM

This is a convenience constructor for creating an instance of a homogeneous Markov model of arbitrary order.

HomogeneousMMDiffSM(AlphabetContainer, int, double, double[], boolean, boolean, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM

This is the main constructor that creates an instance of a homogeneous Markov model of arbitrary order.

HomogeneousMMDiffSM(AlphabetContainer, int, double, double[][], boolean, boolean, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM

This is the main constructor that creates an instance of a homogeneous Markov model of arbitrary order with given hyper-parameters for the prior.

HomogeneousMMDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM

This is the constructor for Storable.

HomogeneousTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

This class implements homogeneous models of arbitrary order.

HomogeneousTrainSM(HomogeneousTrainSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM

Creates a homogeneous model from a parameter set.

HomogeneousTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM

The standard constructor for the interface Storable.

HomogeneousTrainSM.HomCondProb - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

This class handles the (conditional) probabilities of a homogeneous model in a fast way.

HomogeneousTrainSM.HomCondProb(int[], int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb

The main constructor.

HomogeneousTrainSM.HomCondProb(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb

The standard constructor for the interface Storable .

HomogeneousTrainSM.HomCondProb(HomogeneousTrainSM.HomCondProb) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb

Creates a new HomogeneousTrainSM.HomCondProb instance from a given one.

HomogeneousTrainSMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters

This class implements a container for all parameters of any homogeneous model.

HomogeneousTrainSMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet

The standard constructor for the interface Storable.

HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet

This is the constructor that creates an empty HomogeneousTrainSMParameterSet from the class that can be instantiated using this HomogeneousTrainSMParameterSet.

HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM>, AlphabetContainer, double, String, byte) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet

Creates a new HomogeneousTrainSMParameterSet with AlphabetContainer, ess (equivalent sample size), description and order of the homogeneous Markov model.

hyperParameters - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement

The hyperparameters of the prior over the parameters.

hyperParams - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission

The hyper-parameters for the prior on the parameters