L-Index

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

L

L - Variable in class de.jstacs.algorithms.graphs.tensor.Tensor

The number of nodes minus 1.

l1 - Variable in class de.jstacs.algorithms.alignment.Alignment

The length of the sub-sequence of the first sequence that is aligned

l2 - Variable in class de.jstacs.algorithms.alignment.Alignment

The length of the sub-sequence of the second sequence that is aligned

LargeSequenceReader - Class in de.jstacs.utils

Class for reading large DNA sequences (e.g.

LargeSequenceReader() - Constructor for class de.jstacs.utils.LargeSequenceReader

lastParameters - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

The last accepted parameters for all samplings, backup for iterative sampling when checking for BurnInTest

lastScore - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

The scores yielded for the parameters in lastParameters

leafOrder(double[][]) - Method in class de.jstacs.clustering.hierachical.ClusterTree

Orders the leaves of this cluster tree such that adjacent nodes have minimal distance.

LearningPrinciple - Enum in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

This enum can be used to obtain the weights for well-known optimization tasks.

length() - Method in class de.jstacs.data.alphabets.Alphabet

Returns the length of the Alphabet.

length() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet

length() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet

Returns the number of symbols in the calling alphabet.

length - Variable in class de.jstacs.parameters.SequenceScoringParameterSet

The length of sequences the model can work on or 0 for arbitrary length

length - Variable in class de.jstacs.sequenceScores.differentiable.AbstractDifferentiableSequenceScore

The length of the modeled sequences.

length - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.AbstractTrainableStatisticalModel

The length of the sequences the model can classify.

length() - Method in class de.jstacs.utils.DoubleList

Returns the number of inserted elements.

length() - Method in class de.jstacs.utils.IntList

Returns the number of inserted elements.

lengths - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.CompositeTrainSM

The length for each component.

LEQ - Static variable in interface de.jstacs.parameters.validation.Constraint

The condition is less or equal

LIKELIHOOD_INDEX - Static variable in enum de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple

This constant is the array index of the weighting factor for the likelihood.

LimitedMedianStartDistance - Class in de.jstacs.algorithms.optimization

This class implements a StartDistanceForecaster that uses the median of a limited memory over the last values.

LimitedMedianStartDistance(int, double) - Constructor for class de.jstacs.algorithms.optimization.LimitedMedianStartDistance

This constructor creates an instance with slots memory slots that will initially be filled with value.

limitedMemoryBFGS(DifferentiableFunction, double[], byte, TerminationCondition, double, StartDistanceForecaster, OutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer

The Broyden-Fletcher-Goldfarb-Shanno version of limited memory quasi-Newton methods.

LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture

Class for a sparse local inhomogeneous mixture (Slim) model.

LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder(AlphabetContainer, int, int, int, double, double, LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder.PriorType) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Creates a new Slim model with given number of components and maximum distance.

LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

Creates a LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder model from its XML representation

LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder.PriorType - Enum in de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture

The type of the prior used by the Slim model

LimitedStringExtractor - Class in de.jstacs.io

This AbstractStringExtractor allows to read only a limited amount of data.

LimitedStringExtractor(AbstractStringExtractor, int) - Constructor for class de.jstacs.io.LimitedStringExtractor

This constructor creates a new instance based on a given AbstractStringExtractor and a maximal number of Strings to be read.

LIN_EPS - Static variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools

The epsilon for the line search in an optimization using the Optimizer.

linearizeParameters() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree

Extracts the BNDiffSMParameters from the leaves of this tree in left-to-right order (as specified by the order of the alphabet) and returns them as a LinkedList.

LineBasedResult(String, String, DataType) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.LineBasedResult

Creates a new GalaxyAdaptor.LineBasedResult with given name, comment, and data type.

LinkedImageResult(String, String, BufferedImage, GalaxyAdaptor.FileResult) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.LinkedImageResult

Create a new ImageResult with linked TextResult link

LinkedImageResult(StringBuffer) - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.LinkedImageResult

Creates a new GalaxyAdaptor.LinkedImageResult from its XML-representation

list - Variable in class de.jstacs.results.ListResult

The internal list of ResultSets that are part of this ListResult

ListResult - Class in de.jstacs.results

Class for a Result that contains a list or a matrix, respectively, of ResultSets.

ListResult(String, String, ResultSet, ResultSet...) - Constructor for class de.jstacs.results.ListResult

Creates a new ListResult from an array of ResultSets and a ResultSet of annotations, which may provide additional information on this ListResult.

ListResult(String, String, ResultSet, Collection<ResultSet>) - Constructor for class de.jstacs.results.ListResult

Creates a new ListResult from a Collection of ResultSets and a ResultSet of annotations, which may provide additional information on this ListResult.

ListResult(StringBuffer) - Constructor for class de.jstacs.results.ListResult

The standard constructor for the interface Storable.

ListResultSaver - Class in de.jstacs.results.savers

ResultSaver for ListResults.

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

Array for the gradient of the log-likelihood

LocatedSequenceAnnotation - Class in de.jstacs.data.sequences.annotation

Class for a SequenceAnnotation that has a position on the sequence, e.g for transcription start sites or intron-exon junctions.

LocatedSequenceAnnotation(int, String, String, Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation

Creates a new LocatedSequenceAnnotation of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results result.

LocatedSequenceAnnotation(int, String, String, Collection<Result>) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation

LocatedSequenceAnnotation(int, String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation

Creates a new LocatedSequenceAnnotation of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotation and sub-annotations annotations.

LocatedSequenceAnnotation(String, String, LocatedSequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation

LocatedSequenceAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation

The standard constructor for the interface Storable.

LocatedSequenceAnnotationWithLength - Class in de.jstacs.data.sequences.annotation

Class for a SequenceAnnotation that has a position on the sequence and a length, e.g.

LocatedSequenceAnnotationWithLength(int, int, String, String, Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength

Creates a new LocatedSequenceAnnotationWithLength of type type with identifier identifier and additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results result.

LocatedSequenceAnnotationWithLength(int, int, String, String, Collection<Result>) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength

LocatedSequenceAnnotationWithLength(int, int, String, String, SequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength

Creates a new LocatedSequenceAnnotationWithLength of type type with identifier identifier, additional annotation (that does not fit the SequenceAnnotation definitions) given as an array of Results additionalAnnotations and sub-annotations annotations.

LocatedSequenceAnnotationWithLength(String, String, LocatedSequenceAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength

LocatedSequenceAnnotationWithLength(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength

The standard constructor for the interface Storable.

logClazz - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractOptimizableFunction

The logarithm of the class parameters.

logEmission - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM

Helper variable = only for internal use.

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

This double contains the sum of the logarithm of the gamma functions used in the prior.

LogGenDisMixFunction - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

This class implements the the following function

$\[f(\underline{\lambda}|C,D,\underline{\alpha},\underline{\beta})$

The weights $\beta_i$ have to sum to 1.

LogGenDisMixFunction(int, DifferentiableSequenceScore[], DataSet[], double[][], LogPrior, double[], boolean, boolean) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LogGenDisMixFunction

The constructor for creating an instance that can be used in an Optimizer.

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

This double contains the logarithm of the normalization constant of hidden parameters of the instance.

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

This array contains the logarithm of the hidden potentials of the instance.

LogisticConstraint - Interface in de.jstacs.sequenceScores.differentiable.logistic

This interface defines the function $f(\underline{x})$ for sequence $\underline{x}$ which can be used in LogisticDiffSS.

LogisticDiffSS - Class in de.jstacs.sequenceScores.differentiable.logistic

This class implements a logistic function.

LogisticDiffSS(AlphabetContainer, int, LogisticConstraint...) - Constructor for class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS

This is the main constructor to create LogisticDiffSS instance.

LogisticDiffSS(StringBuffer) - Constructor for class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS

This is the constructor for Storable.

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

The log-normalization constants for each condition

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

The log normalization constant based on the parameters.

logNormalizationConstant - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

Normalization constant to obtain normalized probabilities.

LogPrior - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior

The abstract class for any log-prior used e.g.

LogPrior() - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior

logProb(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM

This method computes the logarithm of the probability of the corresponding subsequences.

logProb(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM

logProb(int, int, Sequence) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM

logProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM

logProbFor(Sequence, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM

This method computes the logarithm of the probability of the given Sequence in the given interval.

logSumNormalisation(double[]) - Static method in class de.jstacs.utils.Normalisation

The method does a log-sum-normalisation on the array d, where the values of d are assumed to be logarithmised.

logSumNormalisation(double[], int, int) - Static method in class de.jstacs.utils.Normalisation