Uses of Class
de.jstacs.WrongAlphabetException

Packages that use WrongAlphabetException
de.jstacs.classifier.assessment This package allows to assess classifiers. 
de.jstacs.classifier.scoringFunctionBased.cll Provides the implementation of the log conditional likelihood as an OptimizableFunction and a classifier that uses log conditional likelihood or supervised posterior to learn the parameters of a set of ScoringFunctions 
de.jstacs.data Provides classes for the representation of data. 
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. 
de.jstacs.models Provides the interface Model and its abstract implementation AbstractModel, which is the super class of all other models. 
de.jstacs.models.discrete   
de.jstacs.models.discrete.inhomogeneous This package contains various inhomogeneous models. 
de.jstacs.models.discrete.inhomogeneous.shared   
de.jstacs.models.mixture This package is the super package for any mixture model. 
de.jstacs.models.utils   
 

Uses of WrongAlphabetException in de.jstacs.classifier.assessment
 

Methods in de.jstacs.classifier.assessment that throw WrongAlphabetException
 ListResult ClassifierAssessment.assess(MeasureParameters mp, ClassifierAssessmentAssessParameterSet assessPS, ProgressUpdater pU, Sample... s)
          Assesses the contained classifiers.
 ListResult ClassifierAssessment.assess(MeasureParameters mp, ClassifierAssessmentAssessParameterSet assessPS, ProgressUpdater pU, Sample[][]... s)
           
 ListResult ClassifierAssessment.assess(MeasureParameters mp, ClassifierAssessmentAssessParameterSet assessPS, Sample... s)
          Assesses the contained classifiers.
protected  void ClassifierAssessment.prepareAssessment(Sample... s)
          Prepares an assessment.
 

Constructors in de.jstacs.classifier.assessment that throw WrongAlphabetException
ClassifierAssessment(AbstractClassifier... aCs)
          Creates a new ClassifierAssessment from a set of AbstractClassifiers.
ClassifierAssessment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)
          This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given AbstractModels.
ClassifierAssessment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
          Creates a new ClassifierAssessment from an array of AbstractClassifiers and a two-dimensional array of Models, which are combined to additional classifiers.
ClassifierAssessment(boolean buildClassifiersByCrossProduct, Model[]... aMs)
          Creates a new ClassifierAssessment from a set of Models.
KFoldCrossValidation(AbstractClassifier... aCs)
          Creates a new KFoldCrossValidation from a set of AbstractClassifiers.
KFoldCrossValidation(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)
          This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given AbstractModels by a KFoldCrossValidation.
KFoldCrossValidation(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
          Creates a new KFoldCrossValidation from an array of AbstractClassifiers and a two-dimensional array of Models, which are combined to additional classifiers.
KFoldCrossValidation(boolean buildClassifiersByCrossProduct, Model[]... aMs)
          Creates a new KFoldCrossValidation from a set of Models.
RepeatedHoldOutExperiment(AbstractClassifier... aCs)
          Creates a new RepeatedHoldOutExperiment from a set of AbstractClassifiers.
RepeatedHoldOutExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)
          This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given AbstractModels by a RepeatedHoldOutExperiment.
RepeatedHoldOutExperiment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
          Creates a new RepeatedHoldOutExperiment from an array of AbstractClassifiers and a two-dimensional array of Models, which are combined to additional classifiers.
RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct, Model[]... aMs)
          Creates a new RepeatedHoldOutExperiment from a set of Models.
RepeatedSubSamplingExperiment(AbstractClassifier... aCs)
          Creates a new RepeatedSubSamplingExperiment from a set of AbstractClassifiers.
RepeatedSubSamplingExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)
          This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given AbstractModels by a RepeatedSubSamplingExperiment.
RepeatedSubSamplingExperiment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
          Creates a new RepeatedSubSamplingExperiment from an array of AbstractClassifiers and a two-dimensional array of Models, which are combined to additional classifiers.
RepeatedSubSamplingExperiment(boolean buildClassifiersByCrossProduct, Model[]... aMs)
          Creates a new RepeatedSubSamplingExperiment from a set of Models.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier... aCs)
          Creates a new Sampled_RepeatedHoldOutExperiment from a set of AbstractClassifiers.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)
          This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given AbstractModels by a Sampled_RepeatedHoldOutExperiment.
Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
          Creates a new Sampled_RepeatedHoldOutExperiment from an array of AbstractClassifiers and a two-dimensional array of Models, which are combined to additional classifiers.
Sampled_RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct, Model[]... aMs)
          Creates a new Sampled_RepeatedHoldOutExperiment from a set of Models.
 

Uses of WrongAlphabetException in de.jstacs.classifier.scoringFunctionBased.cll
 

Constructors in de.jstacs.classifier.scoringFunctionBased.cll that throw WrongAlphabetException
NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, boolean norm, boolean freeParams)
          The constructor creates an instance of the log conditional likelihood.
NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, LogPrior prior, boolean norm, boolean freeParams)
          The constructor creates an instance using the given prior.
 

Uses of WrongAlphabetException in de.jstacs.data
 

Methods in de.jstacs.data that throw WrongAlphabetException
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.
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.
 double AlphabetContainer.getCode(int pos, String sym)
          Returns the encoded symbol sym for position pos.
 

Constructors in de.jstacs.data that throw WrongAlphabetException
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation sort, Sample... data)
          This constructor creates a Sample.WeightedSampleFactory on the given Sample(s).
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation sort, Sample[] data, double[][] weights, int length)
          This constructor creates a Sample.WeightedSampleFactory on the given array of Samples and weights.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation sort, Sample data, double[] weights)
          This constructor creates a Sample.WeightedSampleFactory on the given Sample and weights.
Sample.WeightedSampleFactory(Sample.WeightedSampleFactory.SortOperation sort, Sample data, double[] weights, int length)
          This constructor creates a Sample.WeightedSampleFactory on the given Sample and weights.
Sample(AlphabetContainer abc, StringExtractor se)
          Creates a Sample from a StringExctractor using the given AlphabetContainer.
Sample(AlphabetContainer abc, StringExtractor se, int subsequenceLength)
          Creates a Sample from a StringExctractor using the given AlphabetContainer and all overlapping windows of subsequenceLength.
Sample(AlphabetContainer abc, StringExtractor se, String delim)
          Creates a Sample from a StringExctractor using the given AlphabetContainer and delimiter.
Sample(AlphabetContainer abc, StringExtractor se, String delim, int subsequenceLength)
          Creates a Sample from a StringExctractor using the given AlphabetContainer, the given delimiter and all overlapping windows of subsequenceLength.
 

Uses of WrongAlphabetException in de.jstacs.data.alphabets
 

Methods in de.jstacs.data.alphabets that throw WrongAlphabetException
 int DiscreteAlphabet.getCode(String symbol)
           
 

Uses of WrongAlphabetException in de.jstacs.data.bioJava
 

Methods in de.jstacs.data.bioJava that throw WrongAlphabetException
static SequenceIterator BioJavaAdapter.sampleToSequenceIterator(Sample sample, boolean flat)
          Creates a SequenceIterator from sample preserving as much annotation as possible.
 

Uses of WrongAlphabetException in de.jstacs.data.sequences
 

Constructors in de.jstacs.data.sequences that throw WrongAlphabetException
ArbitrarySequence(AlphabetContainer alphabetContainer, double[] content)
          This constructor is designed for the emitSample( int n ) of AbstractModel.
ArbitrarySequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim)
          Creates a new sequence from a string representation using the delimiter delim.
ArbitrarySequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor)
          Creates a new sequence from a SymbolExctractor.
ArbitrarySequence(AlphabetContainer alphabetContainer, String sequence)
          Creates a new sequence from a string representation using the default delimiter.
ByteSequence(AlphabetContainer alphabetContainer, byte[] content)
          This constructor is designed for the emitSample( int n ) of AbstractModel.
ByteSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim)
          Creates a new sequence from a string representation using the delimiter delim.
ByteSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor)
          Creates a new sequence from a SymbolExctractor.
ByteSequence(AlphabetContainer alphabetContainer, String sequence)
          Creates a new sequence from a string representation using the default delimiter.
DiscreteSequence(AlphabetContainer container, SequenceAnnotation[] annotation)
          This constructor creates an instance with the AlphabetContainer and the annotation, but without the content.
IntSequence(AlphabetContainer alphabetContainer, int[] content)
          This constructor is designed for Model.emitSample(int, int...).
IntSequence(AlphabetContainer alphabetContainer, int[] content, int start, int length)
          This constructor creates an instance from a part of the content.
IntSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim)
          Creates a new sequence from a string representation using the delimiter delim.
IntSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor)
          Creates a new sequence from a SymbolExctractor.
IntSequence(AlphabetContainer alphabetContainer, String sequence)
          Creates a new sequence from a string representation using the default delimiter.
PermutedSequence(Sequence seq)
          This constructor creates an instance by shuffling the symbols.
ShortSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, String sequence, String delim)
          Creates a new sequence from a string representation using the delimiter delim.
ShortSequence(AlphabetContainer alphabetContainer, SequenceAnnotation[] annotation, SymbolExtractor extractor)
          Creates a new sequence from a SymbolExctractor.
ShortSequence(AlphabetContainer alphabetContainer, short[] content)
          This constructor is designed for the emitSample( int n ) of AbstractModel.
ShortSequence(AlphabetContainer alphabetContainer, String sequence)
          Creates a new sequence from a string representation using the default delimiter.
SparseSequence(AlphabetContainer alphCon, String seq)
          This constructor creates an instance from a String.
SparseSequence(AlphabetContainer alphCon, SymbolExtractor se)
          This constructor creates an instance from a SymbolExtractor.
 

Uses of WrongAlphabetException in de.jstacs.models
 

Methods in de.jstacs.models that throw WrongAlphabetException
 double UniformModel.getProbFor(Sequence sequence, int startpos, int endpos)
           
 

Constructors in de.jstacs.models that throw WrongAlphabetException
CompositeModel(AlphabetContainer alphabets, int[] assignment, Model... models)
           
 

Uses of WrongAlphabetException in de.jstacs.models.discrete
 

Methods in de.jstacs.models.discrete that throw WrongAlphabetException
static double ConstraintManager.countInhomogeneous(AlphabetContainer alphabets, int length, Sample data, double[] weights, boolean reset, Constraint... constr)
          Fills the (inhomogeneous) constr with the weighted absolute frequency of the sample data and computes the frequencies will not be computed.
 

Uses of WrongAlphabetException in de.jstacs.models.discrete.inhomogeneous
 

Methods in de.jstacs.models.discrete.inhomogeneous that throw WrongAlphabetException
 SymmetricTensor StructureLearner.getTensor(Sample data, double[] weights, byte order, StructureLearner.LearningType method)
          This method can be used to compute a tensor that can be used to determine the optimal structure.
 

Uses of WrongAlphabetException in de.jstacs.models.discrete.inhomogeneous.shared
 

Constructors in de.jstacs.models.discrete.inhomogeneous.shared that throw WrongAlphabetException
SharedStructureMixture(FSDAGModel[] m, StructureLearner.ModelType model, byte order, int starts, boolean estimateComponentProbs, double[] weights, double alpha, double epsilon)
          This constructor is used from the other main constructors.
SharedStructureMixture(FSDAGModel[] m, StructureLearner.ModelType model, byte order, int starts, double[] weights, double alpha, double epsilon)
          This main constructor creates an instance with fixed component weights.
SharedStructureMixture(FSDAGModel[] m, StructureLearner.ModelType model, byte order, int starts, double alpha, double epsilon)
          This main constructor creates an instance which estimates the component probabilities.
 

Uses of WrongAlphabetException in de.jstacs.models.mixture
 

Constructors in de.jstacs.models.mixture that throw WrongAlphabetException
AbstractMixtureModel(int length, Model[] models, boolean[] optimizeModel, int dimension, int starts, boolean estimateComponentProbs, double[] componentHyperParams, double[] weights, AbstractMixtureModel.Algorithm algorithm, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates a new AbstractMixtureModel.
MixtureModel(int length, Model[] models, double[] weights, int starts, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization)
          Creates an instance using EM and fixed component probabilities.
MixtureModel(int length, Model[] models, double[] weights, int starts, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates an instance using Gibbs Sampling and fixed component probabilities.
MixtureModel(int length, Model[] models, int starts, boolean estimateComponentProbs, double[] componentHyperParams, double[] weights, AbstractMixtureModel.Algorithm algorithm, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates a new MixtureModel.
MixtureModel(int length, Model[] models, int starts, double[] componentHyperParams, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization)
          Creates an instance using EM and estimating the component probabilities.
MixtureModel(int length, Model[] models, int starts, double[] componentHyperParams, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates an instance using Gibbs Sampling and sampling the component probabilities.
StrandModel(Model model, int starts, boolean estimateComponentProbs, double[] componentHyperParams, double forwardStrandProb, AbstractMixtureModel.Algorithm algorithm, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates a new StrandModel.
StrandModel(Model model, int starts, double[] componentHyperParams, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization)
          Creates an instance using EM and estimating the component probabilities.
StrandModel(Model model, int starts, double[] componentHyperParams, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates an instance using Gibbs Sampling and sampling the component probabilities.
StrandModel(Model model, int starts, double forwardStrandProb, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization)
          Creates an instance using EM and fixed component probabilities.
StrandModel(Model model, int starts, double forwardStrandProb, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates an instance using Gibbs Sampling and fixed component probabilities.
 

Uses of WrongAlphabetException in de.jstacs.models.utils
 

Methods in de.jstacs.models.utils that throw WrongAlphabetException
 Sequence ModelTester.SeqIterator.getSequence()