- target - Variable in class de.jstacs.algorithms.graphs.Edge
-
The target node.
- template - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
-
The default history
- template - Variable in class de.jstacs.parameters.ExpandableParameterSet
-
- tensor - Variable in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
-
The internal tensor.
- Tensor - Class in de.jstacs.algorithms.graphs.tensor
-
This is the super class for any tensor.
- Tensor(int, byte) - Constructor for class de.jstacs.algorithms.graphs.tensor.Tensor
-
Creates a new
Tensor
for
n
nodes and order
k
.
- TerminationCondition - Interface in de.jstacs.algorithms.optimization.termination
-
This interface can be used in any iterative algorithm for determining the end of the algorithm.
- TerminationException - Exception in de.jstacs.algorithms.optimization
-
This class is for an
Exception
that is thrown if something with a
termination was not correct.
- TerminationException() - Constructor for exception de.jstacs.algorithms.optimization.TerminationException
-
Creates a new
TerminationException
with standard error message
("The termination mode was incorrect, please check your
choice.").
- test(NumericalPerformanceMeasureParameterSet, boolean, DataSet[], double[][]) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
-
Uses the given test data sets to call the evaluate( ...
- TextResult - Class in de.jstacs.results
-
Class for a result that is basically a text file (or its contents).
- TextResult(String, String, FileParameter.FileRepresentation, String, String, String, boolean) - Constructor for class de.jstacs.results.TextResult
-
Creates a new
TextResult
with given name, comment, content, mime type, and additional info.
- TextResult(StringBuffer) - Constructor for class de.jstacs.results.TextResult
-
- TextResultSaver - Class in de.jstacs.results.savers
-
- threads - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
The number of threads that is internally used.
- Time - Class in de.jstacs.utils
-
This interface is the framework for stopping the time of anything.
- Time() - Constructor for class de.jstacs.utils.Time
-
Creates a new time object and starts the clock.
- TimeCondition - Class in de.jstacs.algorithms.optimization.termination
-
This class implements a
TerminationCondition
that stops the optimization if the elapsed time in seconds is
greater than a given value.
- TimeCondition(double) - Constructor for class de.jstacs.algorithms.optimization.termination.TimeCondition
-
This constructor creates an instance that does not allow any further iteration after s
seconds
- TimeCondition(TimeCondition.TimeConditionParameterSet) - Constructor for class de.jstacs.algorithms.optimization.termination.TimeCondition
-
This is the main constructor creating an instance from a given parameter set.
- TimeCondition(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.TimeCondition
-
The standard constructor for the interface
Storable
.
- TimeCondition.TimeConditionParameterSet - Class in de.jstacs.algorithms.optimization.termination
-
- TimeConditionParameterSet() - Constructor for class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
-
This constructor creates an empty parameter set.
- TimeConditionParameterSet(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
-
The standard constructor for the interface
Storable
.
- TimeConditionParameterSet(double) - Constructor for class de.jstacs.algorithms.optimization.termination.TimeCondition.TimeConditionParameterSet
-
This constructor creates a filled instance of a parameters set.
- TimeLimitedProgressUpdater - Class in de.jstacs.utils
-
- TimeLimitedProgressUpdater(Time, int, int, int, int) - Constructor for class de.jstacs.utils.TimeLimitedProgressUpdater
-
- toArray(E[]) - Method in class de.jstacs.AnnotatedEntityList
-
- toArray() - Method in class de.jstacs.utils.DoubleList
-
This method returns a double
array containing all elements
of the list.
- toArray(double[]) - Method in class de.jstacs.utils.DoubleList
-
This method returns a double
array containing all elements
of the list.
- toArray(int, int) - Method in class de.jstacs.utils.DoubleList
-
This method returns a double
array containing all elements
of the list between start and end (exclusive).
- toArray() - Method in class de.jstacs.utils.IntList
-
This method returns an int
array containing all elements of
the list.
- toDirectedGraphvizFormat(int[][]) - Static method in class de.jstacs.algorithms.graphs.DAG
-
This method returns a directed
String
representation of the
structure that can be used in
Graphviz to create an image.
- toDiscrete(int, double) - Method in class de.jstacs.data.AlphabetContainer
-
- toDiscrete(int, double) - Method in class de.jstacs.data.sequences.Sequence
-
This method converts a continuous value at position
pos
of
the
Sequence
into a discrete one.
- toDouble3DArray() - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
-
Creates a three-dimensional
double
array representation of
the
Tensor
.
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.AbstractSelectionParameter
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.ExpandableParameterSet
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.FileParameter
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in interface de.jstacs.parameters.GalaxyConvertible
-
Creates an Galaxy XML-representation of the parameters and appends it to descBuffer
and variable configuration and appends it to configBuffer
.
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.ParameterSet
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.ParameterSetContainer
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.RangeParameter
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.SimpleParameter
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean[]) - Method in class de.jstacs.parameters.SimpleParameterSet
-
Creates an Galaxy XML-representation of the parameters and appends it to descBuffer
and variable configuration and appends it to configBuffer
.
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.validation.NumberValidator
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.parameters.validation.RegExpValidator
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.tools.DataColumnParameter
-
- toGalaxy(String, String, int, StringBuffer, StringBuffer, boolean) - Method in class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter
-
- toGalaxyConfig(boolean) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor
-
Creates the contents of a Galaxy configuration file from all the information
provided to this
GalaxyAdaptor
.
- toGraphvizFormat(int[][], String) - Static method in class de.jstacs.algorithms.graphs.DAG
-
This method returns a
String
representation of the structure that
can be used in
Graphviz to create an image.
- toHtml(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
- toHtml(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
-
Returns an HTML representation of this tree.
- tokenize() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.parser.NewickParser
-
This method construct a
PhyloTree
from the given input stream
- toNewick() - Method in class de.jstacs.clustering.hierachical.ClusterTree
-
Returns a string representation of this cluster tree in newick format.
- ToolBox - Class in de.jstacs.utils
-
This class is a collection of methods which might be useful for the programmer.
- ToolBox() - Constructor for class de.jstacs.utils.ToolBox
-
- ToolBox.TiedRanks - Enum in de.jstacs.utils
-
- ToolResult - Class in de.jstacs.tools
-
- ToolResult(String, String, ResultSet, ResultSet, ParameterSet, String, Date) - Constructor for class de.jstacs.tools.ToolResult
-
- ToolResult(StringBuffer) - Constructor for class de.jstacs.tools.ToolResult
-
The standard constructor for the interface
Storable
.
- toParents(int[], byte) - Static method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
-
- TopSort - Class in de.jstacs.algorithms.graphs
-
Class for a topological sort.
- TopSort() - Constructor for class de.jstacs.algorithms.graphs.TopSort
-
- toString() - Method in class de.jstacs.algorithms.alignment.StringAlignment
-
- toString(int, int, List<String>) - Method in class de.jstacs.algorithms.alignment.StringAlignment
-
This method returns a String representation of the alignment with a given chunk size.
- toString() - Method in class de.jstacs.algorithms.graphs.Edge
-
- toString() - Method in class de.jstacs.algorithms.optimization.QuadraticFunction
-
- toString() - Method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
-
- toString() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
-
- toString() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
-
- toString() - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
-
- toString() - Method in class de.jstacs.clustering.hierachical.ClusterTree
-
- toString() - Method in class de.jstacs.data.AlphabetContainer
-
- toString() - Method in class de.jstacs.data.alphabets.Alphabet
-
- toString() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
-
- toString() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
-
- toString() - Method in class de.jstacs.data.DataSet
-
- toString() - Method in class de.jstacs.data.DataSet.WeightedDataSetFactory
-
- toString() - Method in class de.jstacs.data.DinucleotideProperty.MeanSmoothing
-
- toString() - Method in class de.jstacs.data.DinucleotideProperty.MedianSmoothing
-
- toString() - Method in class de.jstacs.data.DinucleotideProperty.NoSmoothing
-
- toString() - Method in class de.jstacs.data.DinucleotideProperty.Smoothing
-
Returns a
String
representation of this smoothing method.
- toString() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
-
- toString() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
-
- toString() - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotation
-
- toString() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
-
- toString() - Method in enum de.jstacs.data.sequences.annotation.SinglePositionSequenceAnnotation.Type
-
- toString() - Method in class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
-
- toString() - Method in class de.jstacs.data.sequences.Sequence
-
- toString(int) - Method in class de.jstacs.data.sequences.Sequence
-
Returns a
String
representation of the
Sequence
(normally
the
Sequence
in its original
Alphabet
) beginning at
position
start
with a default delimiter as separator.
- toString(int, int) - Method in class de.jstacs.data.sequences.Sequence
-
Returns a
String
representation of the
Sequence
(normally
the
Sequence
in its original
Alphabet
) between
start
and
end
with a default delimiter as
separator.
- toString(String, int, int) - Method in class de.jstacs.data.sequences.Sequence
-
Returns a
String
representation of the
Sequence
(normally
the
Sequence
in its original alphabet) between
start
and
end
with
delim
as separator.
- toString() - Method in class de.jstacs.io.CombinedFileFilter
-
- toString() - Method in class de.jstacs.io.DateFileFilter
-
- toString() - Method in class de.jstacs.io.RegExFilenameFilter
-
- toString() - Method in class de.jstacs.parameters.FileParameter
-
- toString(Comparator<Map.Entry<String, ComparableElement<Parameter, Integer>>>) - Method in class de.jstacs.parameters.ParameterSetTagger
-
This method allows to get a String representation where the tagged parameters are sorted in some specific way.
- toString() - Method in class de.jstacs.parameters.ParameterSetTagger
-
- toString() - Method in class de.jstacs.parameters.SelectionParameter
-
- toString() - Method in class de.jstacs.parameters.SimpleParameter
-
- toString() - Method in class de.jstacs.parameters.validation.NumberValidator
-
- toString() - Method in class de.jstacs.results.ImageResult
-
- toString() - Method in class de.jstacs.results.ListResult
-
- toString() - Method in class de.jstacs.results.NumericalResult
-
- toString() - Method in class de.jstacs.results.ResultSet
-
- toString() - Method in class de.jstacs.results.SimpleResult
-
- toString() - Method in class de.jstacs.results.StorableResult
-
- toString() - Method in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
-
- toString() - Method in class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
-
- toString(NumberFormat) - Method in interface de.jstacs.sequenceScores.SequenceScore
-
This method returns a
String
representation of the instance.
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
-
Returns a string representation of this tree using the provided
NumberFormat
.
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.UniformDiffSM
-
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
-
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
-
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.DAGTrainSM
-
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhCondProb
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
-
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory.PseudoTransitionElement
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
-
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.DiscreteEmission
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.ReferenceSequenceDiscreteEmission
-
- toString(NumberFormat) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.Emission
-
This method returns a
String
representation of the instance.
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleState
-
- toString(NumberFormat) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.State
-
This method returns a
String
representation of the instance.
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
- toString(String[], NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
This method returns a
String
representation of the transition element using the given names of the states.
- toString() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
-
- toString(String[], NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
-
- toString(String[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.DistanceBasedScaledTransitionElement
-
Returns a string representation of the transition probabilities.
- toString(String[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ScaledTransitionElement
-
Returns a string representation of the transition probabilities.
- toString(String[], NumberFormat) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
-
This method returns a
String
representation of the
Transition
using the given names of the states.
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.StrandTrainSM
-
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
-
- toString() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModel
-
Should give a simple representation (text) of the model as
String
.
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
-
Returns the String "".
- toString(NumberFormat) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
-
- toString() - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol
-
Returns the current version of the protocol as
String
.
- toString() - Method in class de.jstacs.utils.ComparableElement
-
- toString() - Method in class de.jstacs.utils.DoubleList
-
- toString() - Method in class de.jstacs.utils.IntList
-
- toString() - Method in class de.jstacs.utils.Pair
-
- toString() - Method in class de.jstacs.utils.TimeLimitedProgressUpdater
-
- toString(double[], NumberFormat) - Static method in class de.jstacs.utils.ToolBox
-
This methods returns a
String
representation of a double array using the specified
NumberFormat
.
- toUndirectedGraphvizFormat(int[][]) - Static method in class de.jstacs.algorithms.graphs.DAG
-
This method returns an undirected
String
representation of the
structure that can be used in
Graphviz to create an image.
- toWeightedGraphvizFormat(int[][], String, Tensor) - Static method in class de.jstacs.algorithms.graphs.DAG
-
This method returns a
String
representation of the weighted
structure that can be used in
Graphviz to create an image.
- toXML() - Method in class de.jstacs.algorithms.alignment.cost.AffineCosts
-
- toXML() - Method in class de.jstacs.algorithms.alignment.cost.MatrixCosts
-
- toXML() - Method in class de.jstacs.algorithms.alignment.cost.SimpleCosts
-
- toXML() - Method in class de.jstacs.algorithms.alignment.PairwiseStringAlignment
-
- toXML() - Method in class de.jstacs.algorithms.alignment.StringAlignment
-
- toXML() - Method in class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
-
- toXML() - Method in class de.jstacs.AnnotatedEntity
-
- toXML() - Method in class de.jstacs.classifiers.AbstractClassifier
-
- toXML() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.CompositeLogPrior
-
- toXML() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.DoesNothingLogPrior
-
Deprecated.
- toXML() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior
-
Encodes the prior as an XML representation.
- toXML() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior
-
- toXML() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SimpleGaussianSumLogPrior
-
- toXML() - Method in class de.jstacs.clustering.hierachical.ClusterTree
-
- toXML() - Method in class de.jstacs.data.AlphabetContainer
-
- toXML() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
-
- toXML() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
-
- toXML() - Method in class de.jstacs.data.AlphabetContainerParameterSet
-
- toXML() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
-
- toXML() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
-
- toXML() - Method in class de.jstacs.data.alphabets.DiscreteAlphabetMapping
-
- toXML() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
-
- toXML() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
-
- toXML() - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotation
-
- toXML() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
-
- toXML() - Method in class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
-
- toXML() - Method in class de.jstacs.motifDiscovery.history.CappedHistory
-
- toXML() - Method in class de.jstacs.motifDiscovery.history.NoRevertHistory
-
- toXML() - Method in class de.jstacs.motifDiscovery.history.RestrictedRepeatHistory
-
- toXML() - Method in class de.jstacs.motifDiscovery.history.SimpleHistory
-
- toXML() - Method in class de.jstacs.parameters.ArrayParameterSet
-
- toXML() - Method in class de.jstacs.parameters.ExpandableParameterSet
-
- toXML() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation
-
- toXML() - Method in class de.jstacs.parameters.InstanceParameterSet
-
- toXML() - Method in class de.jstacs.parameters.ParameterSet
-
- toXML() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
-
- toXML() - Method in class de.jstacs.parameters.validation.ConstraintValidator
-
- toXML() - Method in class de.jstacs.parameters.validation.NumberValidator
-
- toXML() - Method in class de.jstacs.parameters.validation.RegExpValidator
-
- toXML() - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint
-
- toXML() - Method in class de.jstacs.parameters.validation.StorableValidator
-
- toXML() - Method in class de.jstacs.results.MeanResultSet
-
- toXML() - Method in class de.jstacs.results.ResultSet
-
- toXML() - Method in class de.jstacs.sampling.AbstractBurnInTest
-
- toXML() - Method in class de.jstacs.sampling.SimpleBurnInTest
-
Deprecated.
- toXML() - Method in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
-
- toXML() - Method in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
-
- toXML() - Method in class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
-
- toXML() - Method in class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS
-
- toXML() - Method in class de.jstacs.sequenceScores.differentiable.UniformDiffSS
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.CyclicMarkovModelDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree.TreeElement
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.UniformHomogeneousDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.Constraint
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureMixture
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.UniformEmission
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
-
- toXML() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
-
- toXML() - Method in interface de.jstacs.Storable
-
This method returns an XML representation as
StringBuffer
of an
instance of the implementing class.
- toXML() - Method in class de.jstacs.utils.DoubleList
-
- toXML() - Method in class de.jstacs.utils.SeqLogoPlotter.SeqLogoPlotGenerator
-
- train(DataSet...) - Method in class de.jstacs.classifiers.AbstractClassifier
-
- train(DataSet[], double[][]) - Method in class de.jstacs.classifiers.AbstractClassifier
-
This method trains a classifier over an array of weighted
DataSet
s.
- train(DataSet[], double[][]) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
-
Trains the local classifiers using the given training data sets.
- train(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
-
- train(DataSet[], double[][]) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
-
- train(DataSet[], double[][]) - Method in class de.jstacs.classifiers.MappingClassifier
-
- train(DataSet[], double[][]) - Method in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
-
- train(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.DifferentiableStatisticalModelWrapperTrainSM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
-
- train(DataSet[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
-
- train(DataSet[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
-
Trains the homogeneous model on all given
DataSet
s.
- train(DataSet[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
-
Trains the homogeneous model using an array of weighted
DataSet
s.
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.BayesianNetworkTrainSM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
- train(DataSet, double[], int[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
-
- train(DataSet, double[], int[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
-
Computes the model with structure graph
.
- train(TrainableStatisticalModel[], int[][], double[][], DataSet...) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGTrainSM
-
Computes the models with structure graph
.
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSMEManager
-
- train(SequenceIterator, byte, TerminationCondition, SafeOutputStream) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM
-
This method approximates the distribution either analytically or numerically.
- train(MEMConstraint[], int[][], SequenceIterator, byte, TerminationCondition, OutputStream, int[]) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools
-
This method approximates the distribution either analytically or numerically.
- train(DataSet[], double[][]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared.SharedStructureClassifier
-
- train(DataSet) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
-
- train(DataSet) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModel
-
- train(DataSet, double[]) - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModel
-
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.UniformTrainSM
-
Deprecated.
- train(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.VariableLengthWrapperTrainSM
-
- TrainableAndDifferentiableTransition - Interface in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
-
- TrainableState - Interface in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states
-
This class implements method that allows to fill a statistic, which is used to estimate the parameters of a state during, for instance, the Baum-Welch training.
- TrainableStatisticalModel - Interface in de.jstacs.sequenceScores.statisticalModels.trainable
-
This interface defines all methods for a probabilistic model.
- TrainableStatisticalModelFactory - Class in de.jstacs.sequenceScores.statisticalModels.trainable
-
This class allows to easily create some frequently used models.
- TrainableStatisticalModelFactory() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModelFactory
-
- TrainableTransition - Interface in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
-
This class declares methods that allow for estimating the parameters from a sufficient statistic,
as for instance done in the (modified) Baum-Welch algorithm, viterbi training, or Gibbs sampling.
- trainBgModel(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
-
This method trains the background model.
- trainBgModel(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM
-
- trained - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
-
Indicates whether the model is trained or not.
- trainFactors(DataSet, double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager
-
This method trains the internal
MEM
array,
i.e., it optimizes the parameters of the underlying
MEMConstraint
s.
- trainingParameter - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
- TrainSMBasedClassifier - Class in de.jstacs.classifiers.trainSMBased
-
- TrainSMBasedClassifier(boolean, TrainableStatisticalModel...) - Constructor for class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
-
- TrainSMBasedClassifier(TrainableStatisticalModel...) - Constructor for class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
-
- TrainSMBasedClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier
-
The standard constructor for the interface
Storable
.
- transformation - Variable in class de.jstacs.data.sequences.MappedDiscreteSequence
-
- transition - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
The transitions between all (hidden) states of the HMM.
- Transition - Interface in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
-
This interface declares the methods of the transition used in a hidden Markov model.
- TransitionElement - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements
-
This class implements an transition element implements method used
for training via sampling or gradient based optimization approach.
- TransitionElement(int[], int[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
- TransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
- TransitionElement(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
The standard constructor for the interface
Storable
.
- transitions - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
-
- TransitionWithSufficientStatistic - Interface in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
-
This interface defines method for reseting and filling an internal sufficient statistic.
- transpose(double[][]) - Static method in class de.jstacs.utils.ToolBox
-
Transpose a double
matrix.
- TreeElement(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree.TreeElement
-
- trees - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
The trees that represent the context of the random variable (i.e.
- TRUE - Static variable in class de.jstacs.results.StorableResult
-
The model/classifier has been trained.
- TwoPointEvaluater - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
-
This class is for visualizing two point dependency between sequence
positions.
- TwoPointEvaluater() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.TwoPointEvaluater
-
- type - Variable in class de.jstacs.algorithms.alignment.Alignment
-
The type of the alignment
- TYPE - Static variable in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotation
-