Uses of Class
de.jstacs.data.AlphabetContainer

Packages that use AlphabetContainer

Package	Description
de.jstacs.classifiers	This package provides the framework for any classifier.
de.jstacs.classifiers.differentiableSequenceScoreBased	Provides the classes for Classifiers that are based on SequenceScores. It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior.
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix	Provides an implementation of a classifier that allows to train the parameters of a set of DifferentiableStatisticalModels by a unified generative-discriminative learning principle.
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling	Provides the classes for AbstractScoreBasedClassifiers that are based on SamplingDifferentiableStatisticalModels and that sample parameters using the Metropolis-Hastings algorithm.
de.jstacs.data	Provides classes for the representation of data. The base classes to represent data are Alphabet and AlphabetContainer for representing alphabets, Sequence and its sub-classes to represent continuous and discrete sequences, and DataSet to represent data sets comprising a set of sequences.
de.jstacs.data.alphabets	Provides classes for the representation of discrete and continuous alphabets, including a DNAAlphabet for the most common case of DNA-sequences.
de.jstacs.data.bioJava	Provides an adapter between the representation of data in BioJava and the representation used in Jstacs.
de.jstacs.data.sequences	Provides classes for representing sequences. The implementations of sequences currently include DiscreteSequences prepared for alphabets of different sizes, and ArbitrarySequences that may contain continuous values as well. As sub-package provides the facilities to annotate Sequences.
de.jstacs.data.sequences.annotation	Provides the facilities to annotate Sequences using a number of pre-defined annotation types, or additional implementations of the SequenceAnnotation class.
de.jstacs.io	Provides classes for reading data from and writing to a file and storing a number of datatypes, including all primitives, arrays of primitives, and Storables to an XML-representation.
de.jstacs.parameters	This package provides classes for parameters that establish a general convention for the description of parameters as defined in the Parameter-interface.
de.jstacs.sequenceScores	Provides all SequenceScores, which can be used to score a Sequence, typically using some model assumptions.
de.jstacs.sequenceScores.differentiable
de.jstacs.sequenceScores.differentiable.logistic
de.jstacs.sequenceScores.statisticalModels.differentiable	Provides all DifferentiableStatisticalModels, which can compute the gradient with respect to their parameters for a given input Sequence.
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels	Provides DifferentiableStatisticalModels that are directed graphical models.
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous	Provides DifferentiableStatisticalModels that are homogeneous, i.e.
de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif
de.jstacs.sequenceScores.statisticalModels.trainable	Provides all TrainableStatisticalModels, which can be learned from a single DataSet.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous	This package contains various inhomogeneous models.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
de.jstacs.sequenceScores.statisticalModels.trainable.hmm	The package provides all interfaces and classes for a hidden Markov model (HMM).
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete
de.jstacs.utils	This package contains a bundle of useful classes and interfaces like ...

Uses of AlphabetContainer in de.jstacs.classifiers

Methods in de.jstacs.classifiers that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	AbstractClassifier.getAlphabetContainer() This method returns the container of alphabets that is used in the classifier.

Constructors in de.jstacs.classifiers with parameters of type AlphabetContainer

Constructor and Description
AbstractClassifier(AlphabetContainer abc) The constructor for a homogeneous classifier.
AbstractClassifier(AlphabetContainer abc, int length) The constructor for an inhomogeneous classifier.
AbstractScoreBasedClassifier(AlphabetContainer abc, int classes) The constructor for a homogeneous classifier.
AbstractScoreBasedClassifier(AlphabetContainer abc, int classes, double classWeight) The constructor for a homogeneous classifier.
AbstractScoreBasedClassifier(AlphabetContainer abc, int length, int classes) The constructor for an inhomogeneous classifier.
AbstractScoreBasedClassifier(AlphabetContainer abc, int length, int classes, double classWeight) The constructor for an inhomogeneous classifier.

Uses of AlphabetContainer in de.jstacs.classifiers.differentiableSequenceScoreBased

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased with parameters of type AlphabetContainer

Constructor and Description
ScoreClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, AbstractTerminationCondition tc, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind) The constructor for a simple, instantiated parameter set.
ScoreClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind) The constructor for a simple, instantiated parameter set.

Uses of AlphabetContainer in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix with parameters of type AlphabetContainer

Constructor and Description
GenDisMixClassifierParameterSet(AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind, boolean norm, int threads) The default constructor that constructs a new GenDisMixClassifierParameterSet.
GenDisMixClassifierParameterSet(Class<? extends ScoreClassifier> instanceClass, AlphabetContainer alphabet, int length, byte algo, double eps, double lineps, double startD, boolean free, OptimizableFunction.KindOfParameter kind, boolean norm, int threads) The default constructor that constructs a new GenDisMixClassifierParameterSet.

Uses of AlphabetContainer in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling

Constructors in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling with parameters of type AlphabetContainer

Constructor and Description
SamplingGenDisMixClassifierParameterSet(AlphabetContainer alphabet, int length, int numStarts, int testSamplings, int stationarySamplings, String outfilePrefix, int threads) Create a new SamplingGenDisMixClassifierParameterSet with a grouped sampling scheme, sampling all parameters (and not only the free ones), and adaption of the variance.
SamplingGenDisMixClassifierParameterSet(AlphabetContainer alphabet, int length, int numStarts, SamplingScoreBasedClassifier.SamplingScheme scheme, int testSamplings, int stationarySamplings, boolean freeParameters, boolean adaptVariance, String outfilePrefix, int threads) Create a new SamplingGenDisMixClassifierParameterSet.
SamplingGenDisMixClassifierParameterSet(Class<? extends SamplingScoreBasedClassifier> instanceClass, AlphabetContainer alphabet, int length, int numStarts, SamplingScoreBasedClassifier.SamplingScheme scheme, int testSamplings, int stationarySamplings, boolean freeParameters, boolean adaptVariance, String outfilePrefix, int threads) Create a new SamplingGenDisMixClassifierParameterSet.
SamplingScoreBasedClassifierParameterSet(Class<? extends SamplingScoreBasedClassifier> instanceClass, AlphabetContainer alphabet, int length, int numStarts, int testSamplings, int stationarySamplings, String outfilePrefix) Create a new SamplingScoreBasedClassifierParameterSet with a grouped sampling scheme, sampling all parameters (and not only the free ones), and adaption of the variance.
SamplingScoreBasedClassifierParameterSet(Class<? extends SamplingScoreBasedClassifier> instanceClass, AlphabetContainer alphabet, int length, int numStarts, SamplingScoreBasedClassifier.SamplingScheme scheme, int testSamplings, int stationarySamplings, boolean freeParameters, boolean adaptVariance, String outfilePrefix) Create a new SamplingScoreBasedClassifierParameterSet.

Uses of AlphabetContainer in de.jstacs.data

Classes in de.jstacs.data with type parameters of type AlphabetContainer

Modifier and Type	Class and Description
static class	AlphabetContainer.AbstractAlphabetContainerParameterSet<T extends AlphabetContainer> This class is the super class of any InstanceParameterSet for AlphabetContainer.

Fields in de.jstacs.data declared as AlphabetContainer

Modifier and Type	Field and Description
static AlphabetContainer	DinucleotideProperty.continuousAlphabet

Methods in de.jstacs.data that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	DataSet.getAlphabetContainer() Returns the AlphabetContainer of this DataSet.
AlphabetContainer	AlphabetContainer.getCompositeContainer(int[] start, int[] length) Returns an AlphabetContainer of Alphabets e.g.
static AlphabetContainer	AlphabetContainer.getSimplifiedAlphabetContainer(Alphabet[] abc, int[] assignment) This method creates a new AlphabetContainer that uses as less as possible Alphabets to describe the container.
AlphabetContainer	AlphabetContainer.getSubContainer(int start, int length) Returns a sub-container with the Alphabets for the positions starting at start and with length length.
static AlphabetContainer	AlphabetContainer.insertAlphabet(AlphabetContainer aC, Alphabet a, boolean[] useNewAlphabet) This method may be used to construct a new AlphabetContainer by incorporating additional Alphabets into an existing AlphabetContainer.

Methods in de.jstacs.data that return types with arguments of type AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer.AbstractAlphabetContainerParameterSet<? extends AlphabetContainer>	AlphabetContainer.getCurrentParameterSet()

Methods in de.jstacs.data with parameters of type AlphabetContainer

Modifier and Type	Method and Description
boolean	AlphabetContainer.checkConsistency(AlphabetContainer abc) Checks if this AlphabetContainer is consistent consistent with another AlphabetContainer.
int	AlphabetContainer.compareTo(AlphabetContainer abc)
static AlphabetContainer	AlphabetContainer.insertAlphabet(AlphabetContainer aC, Alphabet a, boolean[] useNewAlphabet) This method may be used to construct a new AlphabetContainer by incorporating additional Alphabets into an existing AlphabetContainer.

Constructors in de.jstacs.data with parameters of type AlphabetContainer

Constructor and Description
AlphabetContainer(AlphabetContainer[] cons, int[] lengths) Creates an new sparse AlphabetContainer based on given AlphabetContainers.
DataSet(AlphabetContainer abc, AbstractStringExtractor se) Creates a new DataSet from a StringExtractor using the given AlphabetContainer.
DataSet(AlphabetContainer abc, AbstractStringExtractor se, int subsequenceLength) Creates a new DataSet from a StringExtractor using the given AlphabetContainer and all overlapping windows of length subsequenceLength.
DataSet(AlphabetContainer abc, AbstractStringExtractor se, String delim) Creates a new DataSet from a StringExtractor using the given AlphabetContainer and a delimiter delim.
DataSet(AlphabetContainer abc, AbstractStringExtractor se, String delim, int subsequenceLength) Creates a new DataSet from a StringExtractor using the given AlphabetContainer, the given delimiter delim and all overlapping windows of length subsequenceLength.
DataSet(AlphabetContainer abc, AbstractStringExtractor se, String delim, int subsequenceLength, double percentage) Creates a new DataSet from a StringExtractor using the given AlphabetContainer, the given delimiter delim and all overlapping windows of length subsequenceLength.
DiscreteSequenceEnumerator(AlphabetContainer con, int length, boolean sparse) Creates a new DiscreteSequenceEnumerator from a given AlphabetContainer and a length.

Constructor parameters in de.jstacs.data with type arguments of type AlphabetContainer

Constructor and Description
AlphabetContainerParameterSet(Class<? extends AlphabetContainer> instanceClass, Alphabet... alphabets) /** Creates a new AlphabetContainerParameterSet from an array of Alphabets for a given sub-class of AlphabetContainer.

Uses of AlphabetContainer in de.jstacs.data.alphabets

Subclasses of AlphabetContainer in de.jstacs.data.alphabets

Modifier and Type	Class and Description
class	DNAAlphabetContainer This class implements a singleton for an AlphabetContainer that can be used for DNA.

Uses of AlphabetContainer in de.jstacs.data.bioJava

Methods in de.jstacs.data.bioJava with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static DataSet	BioJavaAdapter.sequenceIteratorToDataSet(SequenceIterator it, FeatureFilter filter, AlphabetContainer con) This method creates a new DataSet from a SequenceIterator.

Uses of AlphabetContainer in de.jstacs.data.sequences

Fields in de.jstacs.data.sequences declared as AlphabetContainer

Modifier and Type	Field and Description
protected AlphabetContainer	Sequence.alphabetCon The underlying alphabets.
protected AlphabetContainer	MappedDiscreteSequence.originalAlphabetContainer The original AlphabetContainer.

Methods in de.jstacs.data.sequences that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	Sequence.getAlphabetContainer() Return the alphabets, i.e.
static AlphabetContainer	MappedDiscreteSequence.getNewAlphabetContainer(AlphabetContainer original, DiscreteAlphabetMapping... transformation) This method allows to create a new AlphabetContainer given an old AlphabetContainer and some DiscreteAlphabetMappings.

Methods in de.jstacs.data.sequences with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static Sequence	Sequence.create(AlphabetContainer con, SequenceAnnotation[] annotation, String sequence, String delim) Creates a Sequence from a String based on the given AlphabetContainer using the given delimiter delim and some annotation for the Sequence.
static Sequence	Sequence.create(AlphabetContainer con, String sequence) Creates a Sequence from a String based on the given AlphabetContainer using the standard delimiter for this AlphabetContainer.
static Sequence	Sequence.create(AlphabetContainer con, String sequence, String delim) Creates a Sequence from a String based on the given AlphabetContainer using the given delimiter delim.
Sequence<T>	Sequence.getCompositeSequence(AlphabetContainer abc, int[] starts, int[] lengths) This method should be used if one wants to create a DataSet of Sequence.CompositeSequences.
static DataSet	SparseSequence.getDataSet(AlphabetContainer con, AbstractStringExtractor... se) This method allows to create a DataSet containing SparseSequences.
static DataSet	ArbitraryFloatSequence.getDataSet(AlphabetContainer con, AbstractStringExtractor... se) This method allows to create a DataSet containing ArbitraryFloatSequences.
static DataSet	SparseSequence.getDataSet(AlphabetContainer con, String filename) This method allows to create a DataSet containing SparseSequences using a file name.
static DataSet	ArbitraryFloatSequence.getDataSet(AlphabetContainer con, String filename) This method allows to create a DataSet containing ArbitraryFloatSequences using a file name.
static DataSet	SparseSequence.getDataSet(AlphabetContainer con, String filename, SequenceAnnotationParser parser) This method allows to create a DataSet containing SparseSequences using a file name.
static DataSet	ArbitraryFloatSequence.getDataSet(AlphabetContainer con, String filename, SequenceAnnotationParser parser) This method allows to create a DataSet containing ArbitraryFloatSequences using a file name.
static AlphabetContainer	MappedDiscreteSequence.getNewAlphabetContainer(AlphabetContainer original, DiscreteAlphabetMapping... transformation) This method allows to create a new AlphabetContainer given an old AlphabetContainer and some DiscreteAlphabetMappings.
Sequence	Sequence.getSubSequence(AlphabetContainer abc, int start) This method should be used if one wants to create a DataSet of subsequences of defined length.
Sequence	Sequence.getSubSequence(AlphabetContainer abc, int start, int length) This method should be used if one wants to create a DataSet of subsequences of defined length.

Constructors in de.jstacs.data.sequences with parameters of type AlphabetContainer

Constructor and Description
ArbitraryFloatSequence(AlphabetContainer alphabetContainer, float[] content) Creates a new ArbitraryFloatSequence from an array of float-encoded alphabet symbols.
ArbitraryFloatSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim) Creates a new ArbitraryFloatSequence from a String representation using the delimiter delim.
ArbitraryFloatSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor) Creates a new ArbitraryFloatSequence from a SymbolExtractor.
ArbitraryFloatSequence(AlphabetContainer alphabetContainer, String sequence) Creates a new ArbitraryFloatSequence from a String representation using the default delimiter.
ArbitrarySequence(AlphabetContainer alphabetContainer, double... content) Creates a new ArbitrarySequence from an array of double-encoded alphabet symbols.
ArbitrarySequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim) Creates a new ArbitrarySequence from a String representation using the delimiter delim.
ArbitrarySequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor) Creates a new ArbitrarySequence from a SymbolExtractor.
ArbitrarySequence(AlphabetContainer alphabetContainer, String sequence) Creates a new ArbitrarySequence from a String representation using the default delimiter.
ByteSequence(AlphabetContainer alphabetContainer, byte[] content) Creates a new ByteSequence from an array of byte- encoded alphabet symbols.
ByteSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim) Creates a new ByteSequence from a String representation using the delimiter delim.
ByteSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor) Creates a new ByteSequence from a SymbolExtractor.
ByteSequence(AlphabetContainer alphabetContainer, String sequence) Creates a new ByteSequence from a String representation using the default delimiter.
IntSequence(AlphabetContainer alphabetContainer, int... content) Creates a new IntSequence from an array of int- encoded alphabet symbols.
IntSequence(AlphabetContainer alphabetContainer, int[] content, int start, int length) Creates a new IntSequence from a part of the array of int- encoded alphabet symbols.
IntSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim) Creates a new IntSequence from a String representation using the delimiter delim.
IntSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor) Creates a new IntSequence from a SymbolExtractor.
IntSequence(AlphabetContainer alphabetContainer, String sequence) Creates a new IntSequence from a String representation using the default delimiter.
MappedDiscreteSequence(AlphabetContainer originalAlphabetContainer, SequenceAnnotation[] seqAn, DiscreteAlphabetMapping... transformation) This method allows to create an empty MappedDiscreteSequence.
Sequence.CompositeSequence(AlphabetContainer abc, Sequence<T> seq, int[] starts, int[] lengths) This constructor should be used if one wants to create a DataSet of Sequence.CompositeSequences.
Sequence.RecursiveSequence(AlphabetContainer alphabet, Sequence<T> seq) Creates a new Sequence.RecursiveSequence on the Sequence seq with the AlphabetContainer alphabet using the annotation of the given Sequence.
Sequence.RecursiveSequence(AlphabetContainer alphabet, SequenceAnnotation[] annotation, Sequence<T> seq) Creates a new Sequence.RecursiveSequence on the Sequence seq with the AlphabetContainer alphabet and the annotation annotation.
Sequence.SubSequence(AlphabetContainer abc, Sequence seq, int start, int length) This constructor should be used if one wants to create a DataSet of Sequence.SubSequences of defined length.
Sequence(AlphabetContainer container, SequenceAnnotation[] annotation) Creates a new Sequence with the given AlphabetContainer and the given annotation, but without the content.
ShortSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim) Creates a new ShortSequence from a String representation using the delimiter delim.
ShortSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor) Creates a new ShortSequence from a SymbolExtractor.
ShortSequence(AlphabetContainer alphabetContainer, short[] content) Creates a new ShortSequence from an array of short- encoded alphabet symbols.
ShortSequence(AlphabetContainer alphabetContainer, String sequence) Creates a new ShortSequence from a String representation using the default delimiter.
SimpleDiscreteSequence(AlphabetContainer container, SequenceAnnotation[] annotation) This constructor creates a new SimpleDiscreteSequence with the AlphabetContainer container and the annotation annotation but without the content.
SparseSequence(AlphabetContainer alphCon, String seq) Creates a new SparseSequence from a String representation.
SparseSequence(AlphabetContainer alphCon, SymbolExtractor se) Creates a new SparseSequence from a SymbolExtractor.

Uses of AlphabetContainer in de.jstacs.data.sequences.annotation

Constructors in de.jstacs.data.sequences.annotation with parameters of type AlphabetContainer

Constructor and Description
ReferenceSequenceAnnotationParser(String key, AlphabetContainer alphabet, String keyValueDelimiter, String annotationDelimiter) Creates a new ReferenceSequenceAnnotationParser with user-specified delimiters.
ReferenceSequenceAnnotationParser(String key, AlphabetContainer alphabet, String keyValueDelimiter, String annotationDelimiter, String delim) Creates a new ReferenceSequenceAnnotationParser with user-specified delimiters.

Uses of AlphabetContainer in de.jstacs.io

Methods in de.jstacs.io with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static int	SymbolExtractor.filter(String inFile, char ignore, AlphabetContainer con, int minLength, String outFile) This method allows the user to filter the content of a File using a given AlphabetContainer and a minimal sequence length.

Uses of AlphabetContainer in de.jstacs.parameters

Methods in de.jstacs.parameters that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	SequenceScoringParameterSet.getAlphabetContainer() Returns the AlphabetContainer of the current instance.

Constructors in de.jstacs.parameters with parameters of type AlphabetContainer

Constructor and Description
SequenceScoringParameterSet(Class<T> instanceClass, AlphabetContainer alphabet) Constructs a SequenceScoringParameterSet for an object that can handle sequences of variable length and with the AlphabetContainer alphabet.
SequenceScoringParameterSet(Class<T> instanceClass, AlphabetContainer alphabet, int length, boolean variableLength) Constructs a SequenceScoringParameterSet from an AlphabetContainer and the length of a sequence.

Uses of AlphabetContainer in de.jstacs.sequenceScores

Methods in de.jstacs.sequenceScores that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	SequenceScore.getAlphabetContainer() Returns the container of alphabets that were used when constructing the instance.

Uses of AlphabetContainer in de.jstacs.sequenceScores.differentiable

Fields in de.jstacs.sequenceScores.differentiable declared as AlphabetContainer

Modifier and Type	Field and Description
protected AlphabetContainer	AbstractDifferentiableSequenceScore.alphabets The AlphabetContainer of this AbstractDifferentiableSequenceScore .

Methods in de.jstacs.sequenceScores.differentiable that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	AbstractDifferentiableSequenceScore.getAlphabetContainer()

Constructors in de.jstacs.sequenceScores.differentiable with parameters of type AlphabetContainer

Constructor and Description
AbstractDifferentiableSequenceScore(AlphabetContainer alphabets, int length) The main constructor.
UniformDiffSS(AlphabetContainer alphabets, int length) This is the main constructor that creates an instance of a UniformDiffSS that models each sequence uniformly.

Uses of AlphabetContainer in de.jstacs.sequenceScores.differentiable.logistic

Constructors in de.jstacs.sequenceScores.differentiable.logistic with parameters of type AlphabetContainer

Constructor and Description
LogisticDiffSS(AlphabetContainer con, int length, LogisticConstraint... constraint) This is the main constructor to create LogisticDiffSS instance.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.differentiable

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static HomogeneousMMDiffSM	DifferentiableStatisticalModelFactory.createHomogeneousMarkovModel(AlphabetContainer con, double ess, int order, int priorLength) This method returns a homogeneous Markov model with user-specified order.
static BayesianNetworkDiffSM	DifferentiableStatisticalModelFactory.createInhomogeneousMarkovModel(AlphabetContainer con, int length, double ess, int order) This method returns a inhomogeneous Markov model (IMM) with user-specified order.
static MarkovRandomFieldDiffSM	DifferentiableStatisticalModelFactory.createMarkovRandomField(AlphabetContainer con, int length, String constraintType) This method allows to create a MarkovRandomFieldDiffSM of the specified length and with the given constraint type.
static BayesianNetworkDiffSM	DifferentiableStatisticalModelFactory.createPWM(AlphabetContainer con, int length, double ess) This method returns a position weight matrix (PWM).

Constructors in de.jstacs.sequenceScores.statisticalModels.differentiable with parameters of type AlphabetContainer

Constructor and Description
AbstractDifferentiableStatisticalModel(AlphabetContainer alphabets, int length) The main constructor.
AbstractVariableLengthDiffSM(AlphabetContainer alphabets) This is the main constructor that creates an instance of a VariableLengthDiffSM that models sequences of arbitrary length.
AbstractVariableLengthDiffSM(AlphabetContainer alphabets, int length) This is the main constructor that creates an instance of a VariableLengthDiffSM that models sequences of a given length.
CyclicMarkovModelDiffSM(AlphabetContainer alphabets, double[] frameHyper, double[][][] hyper, boolean plugIn, boolean optimize, int starts, int initFrame) This constructor allows to create an instance with specific hyper-parameters for all conditional distributions.
CyclicMarkovModelDiffSM(AlphabetContainer alphabets, int order, int period, double classEss, double[] sumOfHyperParams, boolean plugIn, boolean optimize, int starts, int initFrame) The main constructor.
MappingDiffSM(AlphabetContainer originalAlphabetContainer, DifferentiableStatisticalModel nsf, DiscreteAlphabetMapping... mapping) The main constructor creating a MappingDiffSM.
MarkovRandomFieldDiffSM(AlphabetContainer alphabets, int length, double ess, String constr) This is the main constructor that creates an instance of a MarkovRandomFieldDiffSM.
MarkovRandomFieldDiffSM(AlphabetContainer alphabets, int length, String constr) This constructor creates an instance of a MarkovRandomFieldDiffSM with equivalent sample size (ess) 0.
UniformDiffSM(AlphabetContainer alphabets, int length, double ess) This is the main constructor that creates an instance of a UniformDiffSM that models each sequence uniformly.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Constructors in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels with parameters of type AlphabetContainer

Constructor and Description
BayesianNetworkDiffSM(AlphabetContainer alphabet, int length, double ess, boolean plugInParameters, Measure structureMeasure) Creates a new BayesianNetworkDiffSM that has neither been initialized nor trained.
BayesianNetworkDiffSMParameterSet(AlphabetContainer alphabet, int length, double ess, boolean plugInParameters, Measure structureMeasure) Creates a new BayesianNetworkDiffSMParameterSet with pre-defined parameter values.
BNDiffSMParameterTree(int pos, int[] contextPoss, AlphabetContainer alphabet, int firstParent, int[] firstChildren) Creates a new BNDiffSMParameterTree for the parameters at position pos using the parent positions in contextPoss.
MarkovModelDiffSM(AlphabetContainer alphabet, int length, double ess, boolean plugInParameters, InhomogeneousMarkov structureMeasure) This constructor creates an instance without any prior for the modeled length.
MarkovModelDiffSM(AlphabetContainer alphabet, int length, double ess, boolean plugInParameters, InhomogeneousMarkov structureMeasure, DurationDiffSM lengthPenalty) This constructor creates an instance with an prior for the modeled length.
MarkovModelDiffSM(AlphabetContainer alphabet, int length, double ess, boolean plugInParameters, int order, DurationDiffSM lengthPenalty) This constructor creates an instance with an prior for the modeled length.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

Constructors in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous with parameters of type AlphabetContainer

Constructor and Description
HomogeneousDiffSM(AlphabetContainer alphabets) This is the main constructor that creates an instance of a HomogeneousDiffSM that models sequences of arbitrary length.
HomogeneousDiffSM(AlphabetContainer alphabets, int length) This is the main constructor that creates an instance of a HomogeneousDiffSM that models sequences of a given length.
HomogeneousMM0DiffSM(AlphabetContainer alphabets, int length, double ess, boolean plugIn, boolean optimize) The main constructor that creates an instance of a homogeneous Markov model of order 0.
HomogeneousMMDiffSM(AlphabetContainer alphabets, int order, double classEss, double[][] hyperParams, boolean plugIn, boolean optimize, int starts) This is the main constructor that creates an instance of a homogeneous Markov model of arbitrary order with given hyper-parameters for the prior.
HomogeneousMMDiffSM(AlphabetContainer alphabets, int order, double classEss, double[] sumOfHyperParams, boolean plugIn, boolean optimize, int starts) This is the main constructor that creates an instance of a homogeneous Markov model of arbitrary order.
HomogeneousMMDiffSM(AlphabetContainer alphabets, int order, double classEss, int length) This is a convenience constructor for creating an instance of a homogeneous Markov model of arbitrary order.
UniformHomogeneousDiffSM(AlphabetContainer alphabets, double ess) This is the main constructor that creates an instance of a UniformHomogeneousDiffSM that models each sequence uniformly.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture

Constructors in de.jstacs.sequenceScores.statisticalModels.differentiable.localMixture with parameters of type AlphabetContainer

Constructor and Description
LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder(AlphabetContainer alphabets, int length, int components, int distance, double ess) Creates a new Slim model with given number of components and maximum distance.
LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder(AlphabetContainer alphabets, int length, int order, int distance, double ess, double q, LimitedSparseLocalInhomogeneousMixtureDiffSM_higherOrder.PriorType t) Creates a new Slim model with given number of components and maximum distance.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif

Constructors in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif with parameters of type AlphabetContainer

Constructor and Description
PositionDiffSM(AlphabetContainer con, int length) This constructor allows create instance with more than one dimension.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable

Fields in de.jstacs.sequenceScores.statisticalModels.trainable declared as AlphabetContainer

Modifier and Type	Field and Description
protected AlphabetContainer	AbstractTrainableStatisticalModel.alphabets The underlying alphabets

Methods in de.jstacs.sequenceScores.statisticalModels.trainable that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	AbstractTrainableStatisticalModel.getAlphabetContainer()

Methods in de.jstacs.sequenceScores.statisticalModels.trainable with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static BayesianNetworkTrainSM	TrainableStatisticalModelFactory.createBayesianNetworkModel(AlphabetContainer con, int length, double ess, byte order) This method returns a Bayesian network model (BN) with user-specified order.
static HomogeneousMM	TrainableStatisticalModelFactory.createHomogeneousMarkovModel(AlphabetContainer con, double ess, byte order) This method returns a homogeneous Markov model with user-specified order.
static FSDAGTrainSM	TrainableStatisticalModelFactory.createInhomogeneousMarkovModel(AlphabetContainer con, int length, double ess, byte order) This method returns a inhomogeneous Markov model (IMM) with user-specified order.
static BayesianNetworkTrainSM	TrainableStatisticalModelFactory.createPermutedMarkovModel(AlphabetContainer con, int length, double ess, byte order) This method returns a permuted Markov model (PMM) with user-specified order.
static FSDAGTrainSM	TrainableStatisticalModelFactory.createPWM(AlphabetContainer con, int length, double ess) This method returns a position weight matrix (PWM).

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable with parameters of type AlphabetContainer

Constructor and Description
AbstractTrainableStatisticalModel(AlphabetContainer alphabets, int length) Constructor that sets the length of the model to length and the AlphabetContainer to alphabets.
CompositeTrainSM(AlphabetContainer alphabets, int[] assignment, TrainableStatisticalModel... models) Creates a new CompositeTrainSM.
PFMWrapperTrainSM(AlphabetContainer alphabets, String name, double[][] pfm, double ess) Creates a new wrapper for a given position frequency matrix.
UniformTrainSM(AlphabetContainer alphabet) Creates a new UniformTrainSM using a given AlphabetContainer.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.discrete

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static double	ConstraintManager.countInhomogeneous(AlphabetContainer alphabets, int length, DataSet data, double[] weights, boolean reset, Constraint... constr) Fills the (inhomogeneous) constr with the weighted absolute frequency of the DataSet data and computes the frequencies will not be computed.
abstract String	Constraint.getDescription(AlphabetContainer con, int i) Returns the decoded symbol for the encoded symbol i.
String	Constraint.getFreqInfo(AlphabetContainer con, NumberFormat nf) Returns an information about the stored frequencies.

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.discrete with parameters of type AlphabetContainer

Constructor and Description
DGTrainSMParameterSet(Class<T> instanceClass, AlphabetContainer alphabet, double ess, String description) The constructor for models that can handle variable lengths.
DGTrainSMParameterSet(Class<T> instanceClass, AlphabetContainer alphabet, int length, double ess, String description) The constructor for models that can handle only sequences of fixed length given by length.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous with parameters of type AlphabetContainer

Modifier and Type	Method and Description
String	HomogeneousTrainSM.HomCondProb.getDescription(AlphabetContainer con, int i)

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters with parameters of type AlphabetContainer

Constructor and Description
HomMMParameterSet(AlphabetContainer alphabet, double ess, String description, byte order) Creates a new HomMMParameterSet with AlphabetContainer, ess (equivalent sample size), description and order of the homogeneous Markov model.
HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM> instanceClass, AlphabetContainer alphabet, double ess, String description, byte order) Creates a new HomogeneousTrainSMParameterSet with AlphabetContainer, ess (equivalent sample size), description and order of the homogeneous Markov model.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	StructureLearner.getAlphabetContainer() This method returns the AlphabetContainer of the StructureLearner.

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous with parameters of type AlphabetContainer

Modifier and Type	Method and Description
String	InhConstraint.getDescription(AlphabetContainer con, int i)
String	InhCondProb.getDescription(AlphabetContainer con, int i)

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous with parameters of type AlphabetContainer

Constructor and Description
StructureLearner(AlphabetContainer con, int length) Creates a StructureLearner with equivalent sample size (ess) = 0.
StructureLearner(AlphabetContainer con, int length, double ess) Creates a new StructureLearner for a given AlphabetContainer, a given length and a given equivalent sample size (ess).

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters with parameters of type AlphabetContainer

Constructor and Description
BayesianNetworkTrainSMParameterSet(AlphabetContainer alphabet, int length, double ess, String description, StructureLearner.ModelType model, byte order, StructureLearner.LearningType method) This is the constructor of a filled BayesianNetworkTrainSMParameterSet for a BayesianNetworkTrainSM.
FSDAGModelForGibbsSamplingParameterSet(AlphabetContainer alphabet, int length, double ess, String description, String graph) This is the constructor that creates a filled parameter set.
FSDAGTrainSMParameterSet(AlphabetContainer alphabet, int length, double ess, String description, String graph) This constructor creates an FSDAGTrainSMParameterSet instance.
FSDAGTrainSMParameterSet(Class<? extends FSDAGTrainSM> clazz, AlphabetContainer alphabet, int length, double ess, String description, String graph) This constructor creates an FSDAGTrainSMParameterSet instance for the specified class.
FSMEMParameterSet(AlphabetContainer alphabet, int length, double ess, String description, ConstraintManager.Decomposition decomposition, boolean reduce, byte algorithm, double epsilon, String constraints) The fast constructor.
IDGTrainSMParameterSet(Class<? extends InhomogeneousDGTrainSM> instanceClass, AlphabetContainer alphabet, int length, double ess, String description) This constructor creates an IDGTrainSMParameterSet instance for the specified class.
MEManagerParameterSet(Class<? extends MEManager> instanceClass, AlphabetContainer alphabet, int length, double ess, String description, ConstraintManager.Decomposition decomposition, boolean reduce, byte algorithm, double epsilon) The fast constructor.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.hmm

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static AbstractHMM	HMMFactory.createProfileHMM(MaxHMMTrainingParameterSet trainingParameterSet, double[][] initFromTo, boolean likelihood, int order, int numLayers, AlphabetContainer con, double ess, boolean conditionalMain, boolean closeCircle, double[][] conditionInitProbs, boolean insertUniform) Creates a new profile HMM for a given architecture and number of layers.
static AbstractHMM	HMMFactory.createProfileHMM(MaxHMMTrainingParameterSet trainingParameterSet, double[][] initFromTo, boolean likelihood, int order, int numLayers, AlphabetContainer con, double ess, boolean conditionalMain, int joiningStates, double[][] conditionInitProbs, boolean insertUniform) Creates a new profile HMM for a given architecture and number of layers.
static AbstractHMM	HMMFactory.createProfileHMM(MaxHMMTrainingParameterSet trainingParameterSet, HMMFactory.HMMType type, boolean likelihood, int order, int numLayers, AlphabetContainer con, double ess, boolean conditionalMain, boolean closeCircle, double[][] conditionInitProbs) Creates a new profile HMM for a given architecture and number of layers.
static AbstractHMM	HMMFactory.createPseudoErgodicHMM(HMMTrainingParameterSet pars, double ess, double selfTranistionPart, double finalTranistionPart, AlphabetContainer con, int numStates, boolean insertUniform) Creates an HMM with numStates+1 states, where numStates emitting build a clique and each of those states is connected to the absorbing silent final state.
static AbstractHMM	HMMFactory.createSunflowerHMM(HMMTrainingParameterSet pars, AlphabetContainer con, double ess, int expectedSequenceLength, boolean startCentral, int... motifLength) This method creates a first order sunflower HMM.
static AbstractHMM	HMMFactory.createSunflowerHMM(HMMTrainingParameterSet pars, AlphabetContainer con, double ess, int expectedSequenceLength, boolean startCentral, PhyloTree[] t, double[] motifProb, int[] motifLength) This method creates a first order sunflower HMM allowing phylogenetic emissions.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	UniformEmission.getAlphabetContainer()
AlphabetContainer	SilentEmission.getAlphabetContainer()
AlphabetContainer	MixtureEmission.getAlphabetContainer()
AlphabetContainer	Emission.getAlphabetContainer() This method returns the AlphabetContainer of this emission.

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions with parameters of type AlphabetContainer

Constructor and Description
UniformEmission(AlphabetContainer con) The main constructor for a UniformEmission.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	MultivariateGaussianEmission.getAlphabetContainer()
AlphabetContainer	GaussianEmission.getAlphabetContainer()

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous with parameters of type AlphabetContainer

Constructor and Description
GaussianEmission(AlphabetContainer con) Creates a GaussianEmission which can be used for maximum likelihood.
GaussianEmission(AlphabetContainer con, double ess, double priorMu, double priorAlpha, double priorBeta, boolean transformed) Creates a GaussianEmission with normal-gamma prior by directly defining the hyper-parameters of the prior.
GaussianEmission(double ess, AlphabetContainer con, double priorMu, double expectedPrecision, double sdPrecision, boolean transformed) Creates a GaussianEmission with normal-gamma prior by defining the expected precision and the expected standard deviation of the precision, i.e.

Uses of AlphabetContainer in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete

Fields in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete declared as AlphabetContainer

Modifier and Type	Field and Description
protected AlphabetContainer	AbstractConditionalDiscreteEmission.con The alphabet of the emissions

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete that return AlphabetContainer

Modifier and Type	Method and Description
AlphabetContainer	AbstractConditionalDiscreteEmission.getAlphabetContainer()

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete with parameters of type AlphabetContainer

Constructor and Description
AbstractConditionalDiscreteEmission(AlphabetContainer con, double[][] hyperParams) This is a simple constructor for a AbstractConditionalDiscreteEmission defining the individual hyper parameters.
AbstractConditionalDiscreteEmission(AlphabetContainer con, double[][] hyperParams, double[][] initHyperParams) This constructor creates a AbstractConditionalDiscreteEmission defining the individual hyper parameters for the prior used during training and initialization.
AbstractConditionalDiscreteEmission(AlphabetContainer con, int numberOfConditions, double ess) This is a simple constructor for a AbstractConditionalDiscreteEmission based on the equivalent sample size.
DiscreteEmission(AlphabetContainer con, double ess) This is a simple constructor for a DiscreteEmission based on the equivalent sample size.
DiscreteEmission(AlphabetContainer con, double[] hyperParams) This is a simple constructor for a DiscreteEmission defining the individual hyper parameters.
PhyloDiscreteEmission(AlphabetContainer con, double[] hyperParams, PhyloTree t) This is a simple constructor for a DiscreteEmission defining the individual hyper parameters.
PhyloDiscreteEmission(AlphabetContainer con, double ess, PhyloTree t) This is a simple constructor for a PhyloDiscreteEmission based on the equivalent sample size.
ReferenceSequenceDiscreteEmission(AlphabetContainer con, AlphabetContainer refCon, int refIdx, double ess) This is a simple constructor for a ReferenceSequenceDiscreteEmission based on the equivalent sample size.
ReferenceSequenceDiscreteEmission(AlphabetContainer con, AlphabetContainer refCon, int refIdx, double[][] hyperParams) This constructor creates a ReferenceSequenceDiscreteEmission defining the individual hyper parameters.
ReferenceSequenceDiscreteEmission(AlphabetContainer con, AlphabetContainer refCon, int refIdx, double[][] hyperParams, double[][] initHyperParams) This constructor creates a ReferenceSequenceDiscreteEmission defining the individual hyper parameters.
ReferenceSequenceDiscreteEmission(AlphabetContainer con, AlphabetContainer refCon, int refIdx, double ess, double[][] initHyperParams) This is a simple constructor for a ReferenceSequenceDiscreteEmission based on the equivalent sample size.

Uses of AlphabetContainer in de.jstacs.utils

Methods in de.jstacs.utils with parameters of type AlphabetContainer

Modifier and Type	Method and Description
static String	PFMComparator.getConsensus(AlphabetContainer con, double[][] pfm) This method extracts the The method does not use any degenerated IUPAC code.