Uses of Class
de.jstacs.WrongAlphabetException

Packages that use WrongAlphabetException
de.jstacs.classifier.assessment This package allows to assess classifiers. 
de.jstacs.classifier.scoringFunctionBased Provides the classes for Classifiers that are based on ScoringFunctions. 
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.homogeneous   
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.mixture.motif   
de.jstacs.scoringFunctions.mix Provides ScoringFunctions that are mixtures of other ScoringFunctions. 
 

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)
          Assesses the contained classifiers.
 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, in addition, classifiers that will be 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 Model s, 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 Model s, 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 Model s, 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 Model s, 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 Model s, 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
 

Constructors in de.jstacs.classifier.scoringFunctionBased that throw WrongAlphabetException
AbstractOptimizableFunction(Sample[] data, double[][] weights, boolean norm, boolean freeParams)
          The constructor creates an instance using the given weighted data.
 

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 NormConditionalLogLikelihood.
NormConditionalLogLikelihood(ScoringFunction[] score, Sample[] data, double[][] weights, LogPrior prior, boolean norm, boolean freeParams)
          The constructor creates an instance of the NormConditionalLogLikelihood 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.CompositeSequence from a String based on the given AlphabetContainer using the given delimiter delim and some annotation for the Sequence.CompositeSequence.
static Sequence Sequence.create(AlphabetContainer con, String sequence)
          Creates a Sequence.CompositeSequence 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.CompositeSequence from a String based on the given AlphabetContainer using the given delimiter delim.
 double AlphabetContainer.getCode(int pos, String sym)
          Returns the encoded symbol for sym of the Alphabet of position pos of this AlphabetContainer.
 

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

Uses of WrongAlphabetException in de.jstacs.data.alphabets
 

Methods in de.jstacs.data.alphabets that throw WrongAlphabetException
 int DiscreteAlphabet.getCode(String symbol)
          Returns the code of a given 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 the Sample 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)
          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.
DiscreteSequence(AlphabetContainer container, SequenceAnnotation[] annotation)
          This constructor creates a new DiscreteSequence with the AlphabetContainer container and the annotation annotation but without the content.
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.
PermutedSequence(Sequence seq)
          Creates a new PermutedSequence by shuffling the symbols of a given Sequence.
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.
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 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)
          Creates a new CompositeModel.
 

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) Constraint constr with the weighted absolute frequencies of the Sample data.
 

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

Methods in de.jstacs.models.discrete.homogeneous that throw WrongAlphabetException
 Sample HomogeneousModel.emitSample(int no, int... length)
          Creates a Sample of a given number of Sequences from a trained homogeneous model.
protected abstract  Sequence HomogeneousModel.getRandomSequence(Random r, int length)
          This method creates a random Sequence from a trained homogeneous model.
protected  Sequence HomogeneousMM.getRandomSequence(Random r, int length)
           
 

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)
          Creates a new SharedStructureMixture instance with all relevant values.
SharedStructureMixture(FSDAGModel[] m, StructureLearner.ModelType model, byte order, int starts, double[] weights, double alpha, double epsilon)
          Creates a new SharedStructureMixture instance with fixed component weights.
SharedStructureMixture(FSDAGModel[] m, StructureLearner.ModelType model, byte order, int starts, double alpha, double epsilon)
          Creates a new SharedStructureMixture instance which estimates the component probabilities/weights.
 

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.mixture.motif
 

Constructors in de.jstacs.models.mixture.motif that throw WrongAlphabetException
HiddenMotifMixture(Model[] models, boolean[] optimzeArray, int components, int starts, boolean estimateComponentProbs, double[] componentHyperParams, double[] weights, PositionPrior posPrior, AbstractMixtureModel.Algorithm algorithm, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates a new HiddenMotifMixture.
SingleHiddenMotifMixture(Model motif, Model bg, boolean trainOnlyMotifModel, int starts, double[] componentHyperParams, double[] weights, PositionPrior posPrior, AbstractMixtureModel.Algorithm algorithm, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization, int initialIteration, int stationaryIteration, BurnInTest burnInTest)
          Creates a new SingleHiddenMotifMixture.
SingleHiddenMotifMixture(Model motif, Model bg, boolean trainOnlyMotifModel, int starts, double[] componentHyperParams, PositionPrior posPrior, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization)
          Creates a new SingleHiddenMotifMixture using EM and estimating the probability for finding a motif.
SingleHiddenMotifMixture(Model motif, Model bg, boolean trainOnlyMotifModel, int starts, double motifProb, PositionPrior posPrior, double alpha, double eps, AbstractMixtureModel.Parameterization parametrization)
          Creates a new SingleHiddenMotifMixture using EM and fixed probability for finding a motif.
 

Uses of WrongAlphabetException in de.jstacs.scoringFunctions.mix
 

Constructors in de.jstacs.scoringFunctions.mix that throw WrongAlphabetException
StrandScoringFunction(NormalizableScoringFunction function, double forwardPartOfESS, int starts, boolean plugIn, StrandScoringFunction.InitMethod initMethod)
          This constructor creates a StrandScoringFunction that optimizes the usage of each strand.
StrandScoringFunction(NormalizableScoringFunction function, int starts, boolean plugIn, StrandScoringFunction.InitMethod initMethod, double forward)
          This constructor creates a StrandScoringFunction that has a fixed frequency for the strand usage.