- 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
-
- 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
-
- hasDefault() - Method in class de.jstacs.parameters.MultiSelectionParameter
-
- hasDefault() - Method in class de.jstacs.parameters.SelectionParameter
-
- 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.ReferenceSequenceAnnotation
-
- 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.CyclicSequenceAdaptor
-
- hashCodeForPos(int) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
-
- hashCodeForPos(int) - Method in class de.jstacs.data.sequences.Sequence
-
- 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.
- Hclust<T> - Class in de.jstacs.clustering.hierachical
-
Class for clustering a set of elements of the same kind (T
) hierarchically
using agglomerative clustering with different linkage methods.
- Hclust(DistanceMetric<T>, Hclust.Linkage) - Constructor for class de.jstacs.clustering.hierachical.Hclust
-
Creates a new object for clustering using the supplied distance metric and linkage method.
- Hclust.Linkage - Enum in de.jstacs.clustering.hierachical
-
The linkage method for clustering
- HeadResult(String, String) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.HeadResult
-
Creates a new head result with given name and comment
- 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
-
- 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
-
- HMMTrainingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
-
- 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
.
- HomCondProb(int[], int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
-
The main constructor.
- HomCondProb(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
-
The standard constructor for the interface
Storable
.
- HomCondProb(HomogeneousTrainSM.HomCondProb) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
-
- 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
-
- HomogeneousDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
-
- 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
-
- 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
-
- 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
-
- 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.
- 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
-
- HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM>, AlphabetContainer, double, String, byte) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
-
- 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