- AbsoluteValueCondition - Class in de.jstacs.algorithms.optimization.termination
-
- 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! If you set the value too low the minimization will not terminate.
- 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.
- AbsoluteValueConditionParameterSet() - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
-
Deprecated.
This constructor creates an empty parameter set.
- AbsoluteValueConditionParameterSet(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
-
Deprecated.
The standard constructor for the interface
Storable
.
- AbsoluteValueConditionParameterSet(double) - Constructor for class de.jstacs.algorithms.optimization.termination.AbsoluteValueCondition.AbsoluteValueConditionParameterSet
-
Deprecated.
This constructor creates a filled instance of a parameters set.
- AbstractAlphabetContainerParameterSet(Class<? extends T>) - Constructor for class de.jstacs.data.AlphabetContainer.AbstractAlphabetContainerParameterSet
-
- AbstractAlphabetContainerParameterSet(StringBuffer) - Constructor for class de.jstacs.data.AlphabetContainer.AbstractAlphabetContainerParameterSet
-
The standard constructor for the interface
Storable
.
- 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
-
- AbstractBurnInTestParameterSet(Class<? extends AbstractBurnInTest>) - Constructor for class de.jstacs.sampling.AbstractBurnInTestParameterSet
-
- AbstractBurnInTestParameterSet(Class<? extends AbstractBurnInTest>, int) - Constructor for class de.jstacs.sampling.AbstractBurnInTestParameterSet
-
- 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
-
- AbstractConditionalDiscreteEmission(AlphabetContainer, double[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- AbstractConditionalDiscreteEmission(AlphabetContainer, double[][], double[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- AbstractConditionalDiscreteEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- AbstractDifferentiableSequenceScore - Class in de.jstacs.sequenceScores.differentiable
-
- AbstractDifferentiableSequenceScore(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
-
The main constructor.
- AbstractDifferentiableSequenceScore(StringBuffer) - Constructor for class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore
-
- AbstractDifferentiableStatisticalModel - Class in de.jstacs.sequenceScores.statisticalModels.differentiable
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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.
- AbstractNumericalTwoClassPerformanceMeasure - Class in de.jstacs.classifiers.performanceMeasures
-
This class is the abstract super class of any performance measure that can only be computed for binary classifiers.
- AbstractNumericalTwoClassPerformanceMeasure() - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractNumericalTwoClassPerformanceMeasure
-
- AbstractNumericalTwoClassPerformanceMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractNumericalTwoClassPerformanceMeasure
-
The standard constructor for the interface
Storable
.
- AbstractOptimizableFunction - Class in de.jstacs.classifiers.differentiableSequenceScoreBased
-
- 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
-
- AbstractPerformanceMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasure
-
The standard constructor for the interface
Storable
.
- AbstractPerformanceMeasureParameterSet<T extends PerformanceMeasure> - Class in de.jstacs.classifiers.performanceMeasures
-
- AbstractPerformanceMeasureParameterSet(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasureParameterSet
-
The standard constructor for the interface
Storable
.
- AbstractPerformanceMeasureParameterSet(int, boolean, T[]) - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasureParameterSet
-
- AbstractPerformanceMeasureParameterSet(int, SelectionParameter, T...) - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractPerformanceMeasureParameterSet
-
This constructor creates an instance with a given template selection
that can be used for classifiers handling a given number of classes.
- 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.
- AbstractSelectionParameter - Class in de.jstacs.parameters
-
Class for a collection parameter, i.e.
- AbstractSelectionParameter(DataType, String[], Object[], String, String, boolean) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
-
- AbstractSelectionParameter(DataType, String[], Object[], String[], String, String, boolean) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
-
- AbstractSelectionParameter(String, String, boolean, ParameterSet...) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
-
- AbstractSelectionParameter(String, String, boolean, Class<? extends ParameterSet>...) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
-
- AbstractSelectionParameter(StringBuffer) - Constructor for class de.jstacs.parameters.AbstractSelectionParameter
-
The standard constructor for the interface
Storable
.
- AbstractSelectionParameter.InconsistentCollectionException - Exception in de.jstacs.parameters
-
- AbstractStringExtractor - Class in de.jstacs.io
-
This class implements the reader that extracts strings.
- AbstractStringExtractor(char) - Constructor for class de.jstacs.io.AbstractStringExtractor
-
- AbstractTerminationCondition - Class in de.jstacs.algorithms.optimization.termination
-
- 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
-
- AbstractTerminationConditionParameterSet(Class<? extends AbstractTerminationCondition>) - Constructor for class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition.AbstractTerminationConditionParameterSet
-
- 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
.
- AbstractTransitionElement(int[], int[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
- AbstractTransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
This is the main constructor creating a new instance with given context, descendant states, and hyper parameters.
- AbstractTransitionElement(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
The standard constructor for the interface
Storable
.
- AbstractTwoClassPerformanceMeasure - Class in de.jstacs.classifiers.performanceMeasures
-
This class is the abstract super class of any performance measure that can only be computed for binary classifiers.
- AbstractTwoClassPerformanceMeasure() - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractTwoClassPerformanceMeasure
-
- AbstractTwoClassPerformanceMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.AbstractTwoClassPerformanceMeasure
-
The standard constructor for the interface
Storable
.
- AbstractVariableLengthDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable
-
- 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
-
- aCosts - Variable in class de.jstacs.algorithms.alignment.Alignment
-
The affine alignment costs
- actionPerformed(ActionEvent) - Method in class de.jstacs.utils.GUIProgressUpdater
-
- add(int, T) - Method in class de.jstacs.AnnotatedEntityList
-
- add(T...) - Method in class de.jstacs.AnnotatedEntityList
-
- add(String, int, int, StrandedLocatedSequenceAnnotationWithLength.Strand) - Method in class de.jstacs.data.sequences.annotation.MotifAnnotationParser
-
- add(String, String) - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotationParser
-
- add(String, String) - Method in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
-
- 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.tools.ProgressUpdater
-
Increases the internal current value.
- 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
-
- 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
-
- 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
-
- 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
-
- addGradientForLogPriorTerm(double[], int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
- 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
-
- 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.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder
-
- 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
-
- 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
-
- AdditionImpossibleException() - Constructor for exception de.jstacs.results.MeanResultSet.AdditionImpossibleException
-
- addParameters(int, IntList, MEMConstraint[], double[], int[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint
-
This method implements a heuristic to modify a constraint if a number of constraints should be delete.
- addParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.FSMEMParameterSet
-
- addParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.MEManagerParameterSet
-
Adds the parameter template in the constructor.
- addParameterToSet() - Method in class de.jstacs.parameters.ExpandableParameterSet
-
- addResult(Result, boolean, boolean) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor
-
Adds a result to the results of a program run.
- addResult(Result, boolean, boolean, String) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor
-
Adds a result to the results of a program run.
- addResults(MeanResultSet, MeanResultSet) - Static method in class de.jstacs.results.MeanResultSet
-
- addResults(NumericalResultSet...) - Method in class de.jstacs.results.MeanResultSet
-
- addResultSet(ResultSet, boolean, boolean) - Method in class de.jstacs.tools.ui.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
-
- 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.CyclicSequenceAdaptor
-
- 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.continuous.MultivariateGaussianEmission
-
- 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.
- addToValues(int, int, int) - Method in class de.jstacs.utils.IntList
-
Adds a constant to all internal values between start and end
- 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.
- AffineCosts(double, double, Costs) - Constructor for class de.jstacs.algorithms.alignment.cost.AffineCosts
-
This constructor creates a new instance of cost using affine gap costs.
- AffineCosts(StringBuffer) - Constructor for class de.jstacs.algorithms.alignment.cost.AffineCosts
-
Restores
AffineCosts
object from its XML representation.
- 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(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(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.
- Alphabet() - Constructor for class de.jstacs.data.alphabets.Alphabet
-
- alphabet - Variable in class de.jstacs.data.alphabets.DiscreteAlphabet
-
- 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
-
- AlphabetArrayParameterSet(AlphabetContainer.AlphabetContainerType) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
-
- AlphabetArrayParameterSet() - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
-
- AlphabetArrayParameterSet(StringBuffer) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
-
The standard constructor for the interface
Storable
.
- AlphabetArrayParameterSet(Alphabet[], AlphabetContainer.AlphabetContainerType) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
-
- alphabetCon - Variable in class de.jstacs.data.sequences.Sequence
-
The underlying alphabets.
- AlphabetContainer - Class in de.jstacs.data
-
- AlphabetContainer(Alphabet) - Constructor for class de.jstacs.data.AlphabetContainer
-
- AlphabetContainer(Alphabet...) - Constructor for class de.jstacs.data.AlphabetContainer
-
- AlphabetContainer(AlphabetContainer[], int[]) - Constructor for class de.jstacs.data.AlphabetContainer
-
- AlphabetContainer(Alphabet[], int[]) - Constructor for class de.jstacs.data.AlphabetContainer
-
- AlphabetContainer(AlphabetContainerParameterSet) - Constructor for class de.jstacs.data.AlphabetContainer
-
- 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
-
- AlphabetContainer.AlphabetContainerType - Enum in de.jstacs.data
-
- AlphabetContainerParameterSet - Class in de.jstacs.data
-
- AlphabetContainerParameterSet(AlphabetContainer.AlphabetContainerType, boolean) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
-
- AlphabetContainerParameterSet() - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
-
- 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
-
- AlphabetContainerParameterSet(Alphabet[]) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
-
- AlphabetContainerParameterSet(Class<? extends AlphabetContainer>, Alphabet...) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
-
- AlphabetContainerParameterSet(Alphabet[], int[]) - Constructor for class de.jstacs.data.AlphabetContainerParameterSet
-
- AlphabetContainerParameterSet.AlphabetArrayParameterSet - Class in de.jstacs.data
-
Class for the parameters of an array of
Alphabet
s of defined
length.
- 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.
- AlphabetParameterSet(Class<T>) - Constructor for class de.jstacs.data.alphabets.Alphabet.AlphabetParameterSet
-
- AlphabetParameterSet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.Alphabet.AlphabetParameterSet
-
The standard constructor for the interface
Storable
.
- alphabets - Variable in class de.jstacs.sequenceScores.differentiable.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
-
- 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
-
- AnnotatedEntityList() - Constructor for class de.jstacs.AnnotatedEntityList
-
- AnnotatedEntityList(int) - Constructor for class de.jstacs.AnnotatedEntityList
-
- annotateMotif(DataSet, int) - Method in class de.jstacs.motifDiscovery.SignificantMotifOccurrencesFinder
-
- 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
-
- 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
-
- annotation - Variable in class de.jstacs.io.AbstractStringExtractor
-
The annotation of the source.
- ANNOTATION_ID - Static variable in class de.jstacs.data.bioJava.BioJavaAdapter
-
A generic annotation ID for new annotations
- 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
-
- annotationParser - Variable in class de.jstacs.io.SparseStringExtractor
-
A parser for the sequence annotation.
- append(String) - Method in interface de.jstacs.tools.Protocol
-
Appends a general message to the protocol
- append(String) - Method in class de.jstacs.tools.ui.cli.CLI.SysProtocol
-
- append(String) - Method in class de.jstacs.tools.ui.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.PlotGeneratorResult
-
- appendFurtherInfos(StringBuffer) - Method in class de.jstacs.results.Result
-
- 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.results.TextResult
-
- appendFurtherInfos(StringBuffer) - Method in class de.jstacs.tools.DataColumnParameter
-
- appendFurtherInfos(StringBuffer) - Method in class de.jstacs.tools.ToolResult
-
- appendFurtherInfos(StringBuffer) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.FileResult
-
- appendFurtherInfos(StringBuffer) - Method in class de.jstacs.tools.ui.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 interface de.jstacs.tools.Protocol
-
Appends a heading to the protocol, which is generally highlighted in some appropriate way.
- appendHeading(String) - Method in class de.jstacs.tools.ui.cli.CLI.SysProtocol
-
- appendHeading(String) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol
-
Append a heading to the protocol
- appendObjectWithTags(StringBuffer, Object, String) - Static method in class de.jstacs.io.XMLParser
-
- appendObjectWithTagsAndAttributes(StringBuffer, Object, String, String) - Static method in class de.jstacs.io.XMLParser
-
- appendObjectWithTagsAndAttributes(StringBuffer, Object, String, String, boolean) - Static method in class de.jstacs.io.XMLParser
-
- appendSequencesWithTags(StringBuffer, String, Sequence...) - Static method in class de.jstacs.io.XMLParser
-
- appendThrowable(Throwable) - Method in interface de.jstacs.tools.Protocol
-
- appendThrowable(Throwable) - Method in class de.jstacs.tools.ui.cli.CLI.SysProtocol
-
- appendThrowable(Throwable) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol
-
- 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
-
- appendVerbatim(String) - Method in interface de.jstacs.tools.Protocol
-
Appends some verbatim text (i.e., text that is displayed "as is" regardless of default formatting) to the protocol.
- appendVerbatim(String) - Method in class de.jstacs.tools.ui.cli.CLI.SysProtocol
-
- appendVerbatim(String) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol
-
- appendWarning(String) - Method in interface de.jstacs.tools.Protocol
-
Appends a warning to the protocol, which is generally highlighted in some appropriate way.
- appendWarning(String) - Method in class de.jstacs.tools.ui.cli.CLI.SysProtocol
-
- appendWarning(String) - Method in class de.jstacs.tools.ui.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
-
- ArbitraryFloatSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ArbitraryFloatSequence
-
- ArbitraryFloatSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ArbitraryFloatSequence
-
- ArbitraryFloatSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ArbitraryFloatSequence
-
- 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
-
- ArbitrarySequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.ArbitrarySequence
-
- ArbitrarySequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.ArbitrarySequence
-
- ArbitrarySequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.ArbitrarySequence
-
- 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
-
- ArrayParameterSet(ParameterSet, String, String, String, String, NumberValidator<Integer>) - Constructor for class de.jstacs.parameters.ArrayParameterSet
-
- ArrayParameterSet(ParameterSet, String, String) - Constructor for class de.jstacs.parameters.ArrayParameterSet
-
- 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, T, DataSet...) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
-
Assesses the contained classifiers.
- assess(NumericalPerformanceMeasureParameterSet, T, ProgressUpdater, DataSet[]) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
-
Assesses the contained classifiers.
- assess(NumericalPerformanceMeasureParameterSet, T, ProgressUpdater, DataSet[], double[][]) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
-
Assesses the contained classifiers.
- assess(NumericalPerformanceMeasureParameterSet, T, 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[][], double[][][]) - 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
.