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

M

mapDataSet(DataSet[]) - Method in class de.jstacs.classifiers.MappingClassifier

This method maps the given DataSets to the internal classes.

MappedDiscreteSequence - Class in de.jstacs.data.sequences

This class allows to map a discrete Sequence to an new Sequence using some DiscreteAlphabetMappings.

MappedDiscreteSequence(AlphabetContainer, SequenceAnnotation[], DiscreteAlphabetMapping...) - Constructor for class de.jstacs.data.sequences.MappedDiscreteSequence

This method allows to create an empty MappedDiscreteSequence.

MappedDiscreteSequence(SimpleDiscreteSequence, DiscreteAlphabetMapping...) - Constructor for class de.jstacs.data.sequences.MappedDiscreteSequence

This method allows to create a MappedDiscreteSequence from a given Sequence and some given DiscreteAlphabetMappings.

MappingClassifier - Class in de.jstacs.classifiers

This class allows the user to train the classifier on a given number of classes and to evaluate the classifier on a smaller number of classes by mapping classes together.

MappingClassifier(AbstractScoreBasedClassifier, int...) - Constructor for class de.jstacs.classifiers.MappingClassifier

Creates a new MappingClassifier from a given classifier and a class mapping.

MappingClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.MappingClassifier

The standard constructor for the interface Storable.

MappingDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable

This class implements a DifferentiableStatisticalModel that works on mapped Sequences.

MappingDiffSM(AlphabetContainer, DifferentiableStatisticalModel, DiscreteAlphabetMapping...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM

The main constructor creating a MappingDiffSM.

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

This is the constructor for Storable.

mapWeights(double[][]) - Method in class de.jstacs.classifiers.MappingClassifier

This method maps the given Sequence weights to the internal classes.

MarkovModelDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

This class implements a AbstractDifferentiableStatisticalModel for an inhomogeneous Markov model.

MarkovModelDiffSM(AlphabetContainer, int, double, boolean, int, DurationDiffSM) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM

This constructor creates an instance with an prior for the modeled length.

MarkovModelDiffSM(AlphabetContainer, int, double, boolean, InhomogeneousMarkov) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM

This constructor creates an instance without any prior for the modeled length.

MarkovModelDiffSM(AlphabetContainer, int, double, boolean, InhomogeneousMarkov, DurationDiffSM) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM

This constructor creates an instance with an prior for the modeled length.

MarkovModelDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM

The standard constructor for the interface Storable.

MarkovRandomFieldDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable

This class implements the scoring function for any MRF (Markov Random Field).

MarkovRandomFieldDiffSM(AlphabetContainer, int, String) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM

This constructor creates an instance of a MarkovRandomFieldDiffSM with equivalent sample size (ess) 0.

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

This is the main constructor that creates an instance of a MarkovRandomFieldDiffSM.

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

This is the constructor for the interface Storable.

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

This method allows to answer the question whether there is a similar pattern find a match with a given maximal number of mismatches.

MatrixCosts - Class in de.jstacs.algorithms.alignment.cost

Class for matrix costs, i.e., the cost of any match/mismatch is stored in a matrix allowing a huge degree of freedom.

MatrixCosts(double[][], double, double) - Constructor for class de.jstacs.algorithms.alignment.cost.MatrixCosts

Creates a new instance of MatrixCosts where the costs for mismatch and match are given in matrix.

MatrixCosts(double[][], double) - Constructor for class de.jstacs.algorithms.alignment.cost.MatrixCosts

Creates a new instance of MatrixCosts where the costs for mismatch and match are given in matrix.

MatrixCosts(StringBuffer) - Constructor for class de.jstacs.algorithms.alignment.cost.MatrixCosts

Restores MatrixCosts object from its XML representation.

matrixToString(double[][]) - Static method in class de.jstacs.utils.PFMComparator

Returns a string representation of the matrix, where each row of the matrix is printed on one line and columns are separated by tabstops.

max - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

The maximal value.

max(double[], int, int) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method returns the index of a maximal entry in the array w between index start and end.

max - Variable in class de.jstacs.utils.DefaultProgressUpdater

The maximal number of steps.

max(int, int) - Method in class de.jstacs.utils.DoubleList

This method computes the maximum of a part of the list.

max(double...) - Static method in class de.jstacs.utils.ToolBox

This method returns the maximum of the elements of an array.

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

This method returns the maximum of the elements of an array between start and end.

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

This class is the super class for any HMMTrainingParameterSet that is used for a maximizing training algorithm of a hidden Markov model.

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

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

MaxHMMTrainingParameterSet(int, AbstractTerminationCondition) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MaxHMMTrainingParameterSet

This constructor can be used to create an instance with specified parameters.

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

The standard constructor for the interface Storable.

MAXIMALBRANCHING - Static variable in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds

Compute the branching yielding the maximum sum of weights.

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

The maximal Markov order of the transition.

MaximumCorrelationCoefficient - Class in de.jstacs.classifiers.performanceMeasures

This class implements the maximum of the correlation coefficient .

MaximumCorrelationCoefficient() - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient

Constructs a new instance of the performance measure MaximumCorrelationCoefficient.

MaximumCorrelationCoefficient(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumCorrelationCoefficient

The standard constructor for the interface Storable.

MaximumFMeasure - Class in de.jstacs.classifiers.performanceMeasures

Computes the maximum of the general F-measure given a positive real parameter .

MaximumFMeasure() - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure

Constructs a new instance of the performance measure MaximumFMeasure with empty parameters.

MaximumFMeasure(double) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure

Constructs a new instance of the performance measure MaximumFMeasure with given beta.

MaximumFMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumFMeasure

The standard constructor for the interface Storable.

MaximumNumericalTwoClassMeasure - Class in de.jstacs.classifiers.performanceMeasures

This class prepares everything for an easy implementation of a maximum of any numerical performance measure.

MaximumNumericalTwoClassMeasure() - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure

Constructs a new instance of the performance measure MaximumNumericalTwoClassMeasure.

MaximumNumericalTwoClassMeasure(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.MaximumNumericalTwoClassMeasure

The standard constructor for the interface Storable.

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

The maximal in-degree of any state.

mean(int, int) - Method in class de.jstacs.utils.DoubleList

This method computes the mean of a part of the list.

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

This method returns the mean of the elements of an array between start and end.

MeanResultSet - Class in de.jstacs.results

Class that computes the mean and the standard error of a series of NumericalResultSets.

MeanResultSet(boolean, SimpleResult...) - Constructor for class de.jstacs.results.MeanResultSet

Constructs a new MeanResultSet with an empty set of NumericalResultSets and allows to collect all values via the switch aggregateAll.

MeanResultSet(SimpleResult...) - Constructor for class de.jstacs.results.MeanResultSet

Constructs a new MeanResultSet with an empty set of NumericalResultSets.

MeanResultSet() - Constructor for class de.jstacs.results.MeanResultSet

Constructs a new MeanResultSet with an empty set of NumericalResultSets and no further information.

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

The standard constructor for the interface Storable.

MeanResultSet.AdditionImpossibleException - Exception in de.jstacs.results

Class for the exception that is thrown if two MeanResultSets should be added that do not match.

MeanResultSet.InconsistentResultNumberException - Exception in de.jstacs.results

Class for the exception that is thrown if a NumericalResultSet is added to the MeanResultSet that has a number of results which is not equal to the number of results of the previously added results.

MeanSmoothing(int) - Constructor for class de.jstacs.data.DinucleotideProperty.MeanSmoothing

Creates a new DinucleotideProperty.MeanSmoothing that averages over windows of width width.

meanValue - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission

Initial mean value.

Measure - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures

Class for structure measures that derive an optimal structure with respect to some criterion within a class of possible structures from data.

Measure(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Creates a new Measure from its XML-representation.

Measure(Measure.MeasureParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Creates a new Measure from its Measure.MeasureParameterSet.

Measure() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure

Default constructor.

Measure.MeasureParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures

This class is the super class of any ParameterSet that can be used to instantiate a Measure.

MeasureParameterSet(Class<? extends Measure>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure.MeasureParameterSet

Creates a new empty Measure.MeasureParameterSet for the given sub-class of Measure,

MeasureParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure.MeasureParameterSet

The standard constructor for the interface Storable.

median(int, int) - Method in class de.jstacs.utils.DoubleList

This method computes the median of a part of the list.

median(double...) - Static method in class de.jstacs.utils.ToolBox

This method returns the median of the elements of array.

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

This method returns the median of the elements of an array between start and end.

MedianSmoothing(int) - Constructor for class de.jstacs.data.DinucleotideProperty.MedianSmoothing

Creates a new DinucleotideProperty.MedianSmoothing that computes the median over windows of width width.

MEM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

This class represents a maximum entropy model.

MEM(AbstractList<int[]>, int[], int[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM

The main constructor of a MEM.

MEM(int[], int[], int[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM

The main constructor of a MEM.

MEM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEM

The constructor for the Storable interface.

MEManager - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

This class is the super class for all maximum entropy models

MEManager(MEManagerParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager

Creates a new MEManager from a given MEManagerParameterSet.

MEManager(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEManager

The standard constructor for the interface Storable.

MEManagerParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters

The ParameterSet for any MEManager.

MEManagerParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.MEManagerParameterSet

The constructor for the Storable interface.

MEManagerParameterSet(Class<? extends MEManager>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.MEManagerParameterSet

The constructor an empty constructor of extended class.

MEManagerParameterSet(Class<? extends MEManager>, AlphabetContainer, int, double, String, ConstraintManager.Decomposition, boolean, byte, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters.MEManagerParameterSet

The fast constructor.

MEMConstraint - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

This constraint can be used for any maximum entropy model (MEM) application.

MEMConstraint(int[], int[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint

Creates a MEMConstraint as part of a (whole) model.

MEMConstraint(int[], int[], int[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint

Creates a MEMConstraint as part of a model.

MEMConstraint(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint

The standard constructor for the interface Storable.

MEMTools - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

MEMTools() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMTools

MEMTools.DualFunction - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

The dual function to the constraint problem of learning MEM's.

merge(Hashtable<Sequence, BitSet[]>, int, boolean) - Static method in class de.jstacs.motifDiscovery.KMereStatistic

This method allows to merge the statistics of k-mers by allowing mismatches.

min - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

The minimal value.

min(int, int) - Method in class de.jstacs.utils.DoubleList

This method computes the minimum of a part of the list.

min(double...) - Static method in class de.jstacs.utils.ToolBox

This method returns the minimum of the elements of an array.

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

This method returns the minimum of the elements of an array between start and end.

MINIMALBRANCHING - Static variable in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds

Compute the branching yielding the minimum sum of weights.

minStepSize - Static variable in class de.jstacs.classifiers.performanceMeasures.PRCurve

The minimum step size between supporting points

MixtureDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture

This class implements a real mixture model.

MixtureDiffSM(int, boolean, DifferentiableStatisticalModel...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM

This constructor creates a new MixtureDiffSM.

MixtureDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM

This is the constructor for the interface Storable.

MixtureDurationDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif

This class implements a mixture of DurationDiffSMs.

MixtureDurationDiffSM(int, DurationDiffSM...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM

The main constructor of a MixtureDurationDiffSM.

MixtureDurationDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM

This is the constructor for Storable.

MixtureEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions

This class implements a mixture of Emissions.

MixtureEmission(Emission[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission

The main constructor creating a MixtureEmission from a set of emissions.

MixtureEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.MixtureEmission

The standard constructor for the interface Storable.

MixtureTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture

The class for a mixture model of any TrainableStatisticalModels.

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

Creates a new MixtureTrainSM.

MixtureTrainSM(int, TrainableStatisticalModel[], int, double[], double, TerminationCondition, AbstractMixtureTrainSM.Parameterization) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM

Creates an instance using EM and estimating the component probabilities.

MixtureTrainSM(int, TrainableStatisticalModel[], double[], int, double, TerminationCondition, AbstractMixtureTrainSM.Parameterization) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM

Creates an instance using EM and fixed component probabilities.

MixtureTrainSM(int, TrainableStatisticalModel[], int, double[], int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM

Creates an instance using Gibbs Sampling and sampling the component probabilities.

MixtureTrainSM(int, TrainableStatisticalModel[], double[], int, int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.MixtureTrainSM

Creates an instance using Gibbs Sampling and fixed component probabilities.

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

The constructor for the interface Storable.

model - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

The model for the sequences.

models - Variable in class de.jstacs.classifiers.trainSMBased.TrainSMBasedClassifier

The internal TrainableStatisticalModels.

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

The models for the components

modify(int, int) - Method in interface de.jstacs.motifDiscovery.Mutable

Manually modifies the model.

modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM

modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture.LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder

modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM

modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MarkovRandomFieldDiffSM

modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.DurationDiffSM

This method modifies the underlying AlphabetContainer.

modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.MixtureDurationDiffSM

modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.SkewNormalLikeDurationDiffSM

modify(int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.UniformDurationDiffSM

modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.StrandDiffSM

modify(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.NormalizedDiffSM

modify(double[], double[], int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.ZOOPSTrainSM

This method modifies the computed weights for one sequence and returns the score.

modifyFunctionValue(double) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingGenDisMixClassifier

modifyFunctionValue(double) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier

Allows for a modification of the value returned by the function obtained by SamplingScoreBasedClassifier.getFunction(DataSet[], double[][]).

modifyMotif(int, int, int) - Method in interface de.jstacs.motifDiscovery.MutableMotifDiscoverer

Manually modifies the motif model with index motifIndex.

modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.IndependentProductDiffSM

modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.MappingDiffSM

modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.MixtureDiffSM

modifyMotif(int, int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.ExtendedZOOPSDiffSM

modifyWeights(double[]) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM

This method modifies the computed weights for one sequence and returns the score.

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

Class for a StrandedLocatedSequenceAnnotationWithLength that is a motif.

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

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

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

The standard constructor for the interface Storable.

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

Annotation parser for MotifAnnotations.

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

Creates a new MotifAnnotationParser with default delimiters.

MotifAnnotationParser(String, String) - Constructor for class de.jstacs.data.sequences.annotation.MotifAnnotationParser

Creates a new MotifAnnotationParser with the supplied delimiters

MotifDiscoverer - Interface in de.jstacs.motifDiscovery

This is the interface that any tool for de-novo motif discovery should implement.

MotifDiscoverer.KindOfProfile - Enum in de.jstacs.motifDiscovery

This enum can be used to determine which kind of profile should be returned.

MotifDiscovererToolBox - Class in de.jstacs.motifDiscovery

This class contains static methods for the MotifDiscoverer.

MotifDiscovererToolBox() - Constructor for class de.jstacs.motifDiscovery.MotifDiscovererToolBox

MotifDiscoveryAssessment - Class in de.jstacs.motifDiscovery

This class enables the user to assess the prediction of motif occurrences

MotifDiscoveryAssessment() - Constructor for class de.jstacs.motifDiscovery.MotifDiscoveryAssessment

motifLength - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior

The length of the motif.

MRGParams - Class in de.jstacs.utils.random

The super container for parameter of multivariate random generators.

MRGParams() - Constructor for class de.jstacs.utils.random.MRGParams

MSPClassifier - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.msp

This class implements a classifier that allows the training via MCL or MSP principle.

MSPClassifier(GenDisMixClassifierParameterSet, DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier

This convenience constructor creates an MSPClassifier that used MCL principle for training.

MSPClassifier(GenDisMixClassifierParameterSet, LogPrior, DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier

The default constructor that creates a new MSPClassifier from a given parameter set, a prior and DifferentiableSequenceScores for the classes.

MSPClassifier(GenDisMixClassifierParameterSet, LogPrior, double, DifferentiableSequenceScore...) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier

This constructor that creates a new MSPClassifier from a given parameter set, a prior and DifferentiableSequenceScores for the classes.

MSPClassifier(StringBuffer) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.msp.MSPClassifier

This is the constructor for Storable.

MST - Class in de.jstacs.algorithms.graphs

This class enables you to compute the maximal spanning forest for an undirected, weighted graph.

MST() - Constructor for class de.jstacs.algorithms.graphs.MST

MultiDimensionalArbitrarySequence - Class in de.jstacs.data.sequences

This class is for multidimensional arbitrary sequences.

MultiDimensionalArbitrarySequence(SequenceAnnotation[], ArbitrarySequence...) - Constructor for class de.jstacs.data.sequences.MultiDimensionalArbitrarySequence

This constructor creates an MultiDimensionalDiscreteSequence from a set of individual Sequences.

MultiDimensionalDiscreteSequence - Class in de.jstacs.data.sequences

This class is for multidimensional discrete sequences that can be used, for instance, for phylogenetic footprinting.

MultiDimensionalDiscreteSequence(SequenceAnnotation[], SimpleDiscreteSequence...) - Constructor for class de.jstacs.data.sequences.MultiDimensionalDiscreteSequence

This constructor creates an MultiDimensionalDiscreteSequence from a set of individual Sequences.

MultiDimensionalSequence<T> - Class in de.jstacs.data.sequences

This class is for multidimensional sequences that can be used, for instance, for phylogenetic footprinting.

MultiDimensionalSequence(SequenceAnnotation[], Sequence...) - Constructor for class de.jstacs.data.sequences.MultiDimensionalSequence

This constructor creates an MultiDimensionalSequence from a set of individual Sequences.

MultiDimensionalSequenceWrapperDiffSS - Class in de.jstacs.sequenceScores.differentiable

This class implements a simple wrapper for multidimensional sequences.

MultiDimensionalSequenceWrapperDiffSS(DifferentiableSequenceScore) - Constructor for class de.jstacs.sequenceScores.differentiable.MultiDimensionalSequenceWrapperDiffSS

The main constructor.

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

This is the constructor for Storable.

MultilineSimpleParameter - Class in de.jstacs.tools.ui.galaxy

An extension of SimpleParameter that renders as a textarea in Galaxy, which is only suitable for DataType.STRINGs.

MultilineSimpleParameter(String, String, boolean, Object) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter

Creates a new MultilineSimpleParameter with given default value.

MultilineSimpleParameter(String, String, boolean, ParameterValidator, Object) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter

Creates a new MultilineSimpleParameter with given default value and a ParameterValidator.

MultilineSimpleParameter(String, String, boolean, ParameterValidator) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter

Creates a new MultilineSimpleParameter with no default value and a ParameterValidator.

MultilineSimpleParameter(String, String, boolean) - Constructor for class de.jstacs.tools.ui.galaxy.MultilineSimpleParameter

Creates a new MultilineSimpleParameter with no default value.

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

The standard constructor for the interface Storable.

MultipleIterationsCondition - Class in de.jstacs.algorithms.optimization.termination

This TerminationCondition requires another provided TerminationCondition to fail a contiguous specified number of times before the optimization is terminated.

MultipleIterationsCondition(int, AbstractTerminationCondition) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition

This constructor creates an instance that stops the optimization if provided termination condition fails a contiguously a specified number of times.

MultipleIterationsCondition(MultipleIterationsCondition.MultipleIterationsConditionParameterSet) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition

This is the main constructor creating an instance from a given parameter set.

MultipleIterationsCondition(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition

The standard constructor for the interface Storable.

MultipleIterationsCondition.MultipleIterationsConditionParameterSet - Class in de.jstacs.algorithms.optimization.termination

This class implements the parameter set for a MultipleIterationsCondition.

MultipleIterationsConditionParameterSet() - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet

This constructor creates an empty parameter set.

MultipleIterationsConditionParameterSet(StringBuffer) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet

The standard constructor for the interface Storable.

MultipleIterationsConditionParameterSet(int, AbstractTerminationCondition) - Constructor for class de.jstacs.algorithms.optimization.termination.MultipleIterationsCondition.MultipleIterationsConditionParameterSet

This constructor creates a filled instance of the parameter set.

multiply(int, int, double) - Method in class de.jstacs.utils.DoubleList

Multiplies all values in the list from index start to end with the value factor.

multiplyExpLambdaWith(int, double) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.MEMConstraint

Multiplies the exponential value of with the factor val: .

MultiSelectionParameter - Class in de.jstacs.parameters

Class for a Parameter that provides a collection of possible values.

MultiSelectionParameter(DataType, String[], Object[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionParameter

Constructor for a MultiSelectionParameter.

MultiSelectionParameter(DataType, String[], Object[], String[], String, String, boolean) - Constructor for class de.jstacs.parameters.MultiSelectionParameter

Constructor for a MultiSelectionParameter.

MultiSelectionParameter(String, String, boolean, ParameterSet...) - Constructor for class de.jstacs.parameters.MultiSelectionParameter

Creates a new MultiSelectionParameter from an array of ParameterSets.

MultiSelectionParameter(String, String, boolean, Class<? extends ParameterSet>...) - Constructor for class de.jstacs.parameters.MultiSelectionParameter

Creates a new MultiSelectionParameter from an array of Classes of ParameterSets.

MultiSelectionParameter(StringBuffer) - Constructor for class de.jstacs.parameters.MultiSelectionParameter

The standard constructor for the interface Storable.

MultiThreadedFunction - Interface in de.jstacs.algorithms.optimization

This interface defines methods for functions that are multi-threaded.

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

This class is the super class for any MaxHMMTrainingParameterSet that is used for a multi-threaded maximizing training algorithm of a hidden Markov model.

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

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

MultiThreadedTrainingParameterSet(int, AbstractTerminationCondition, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.MultiThreadedTrainingParameterSet

This constructor can be used to create an instance with specified parameters.

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

The standard constructor for the interface Storable.

MultivariateGaussianEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous

Multivariate Gaussian emission density for a Hidden Markov Model.

MultivariateGaussianEmission(double[], double[], double[][], double, double[], double, double[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission

Creates a Multivariate Gaussian emission density.

MultivariateGaussianEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.MultivariateGaussianEmission

Creates a MultivariateGaussianEmission from its XML representation.

MultivariateRandomGenerator - Class in de.jstacs.utils.random

This class is the abstract super class for any multivariate random generator (MRG).

MultivariateRandomGenerator() - Constructor for class de.jstacs.utils.random.MultivariateRandomGenerator

mus - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior

The means

Mutable - Interface in de.jstacs.motifDiscovery

This interface allows to modify a motif model.

MutableMotifDiscoverer - Interface in de.jstacs.motifDiscovery

This is the interface that any tool for de-novo motif discovery should implement that allows any modify-operations like shift, shrink and expand.

MutableMotifDiscovererToolbox - Class in de.jstacs.motifDiscovery

This class contains some important methods for the initiation and optimization of MutableMotifDiscoverer.

MutableMotifDiscovererToolbox() - Constructor for class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox

MutableMotifDiscovererToolbox.InitMethodForDiffSM - Enum in de.jstacs.motifDiscovery

This enum defines some constants for the method MutableMotifDiscovererToolbox.getSortedInitialParameters(DifferentiableSequenceScore[], InitMethodForDiffSM[], DiffSSBasedOptimizableFunction, int, OutputStream, int).

myAbstractClassifier - Variable in class de.jstacs.classifiers.assessment.ClassifierAssessment

This array contains the internal used classifiers.

myModel - Variable in class de.jstacs.classifiers.assessment.ClassifierAssessment

This array contains for each class the internal used models.

myTempMeanResultSets - Variable in class de.jstacs.classifiers.assessment.ClassifierAssessment

The temporary result set.

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