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## Uses of Class
de.jstacs.data.WrongLengthException

Packages that use WrongLengthException
de.jstacs.data | Provides classes for the representation of data.
de.jstacs.data.sequences | Provides classes for representing sequences.
de.jstacs.motifDiscovery | This package provides the framework including the interface for any de novo motif discoverer
de.jstacs.sequenceScores.differentiable |
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models | The package provides different implementations of hidden Markov models based on `AbstractHMM`
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states | The package provides all interfaces and classes for states used in hidden Markov models.

Uses of WrongLengthException in de.jstacs.data

Methods in de.jstacs.data that throw WrongLengthException
`int` | `DataSet.getNumberOfElementsWithLength(int len)` Returns the number of overlapping elements that can be extracted.
`double` | `DataSet.getNumberOfElementsWithLength(int len, double[] weights)` Returns the weighted number of overlapping elements that can be extracted.
`DataSet[]` | `DataSet.partition(double p, DataSet.PartitionMethod method, int subsequenceLength)` This method partitions the elements, i.e. the `Sequence`s, of the `DataSet` in two distinct parts.
`static DataSet` | `DataSet.union(DataSet[] s, boolean[] in, int subsequenceLength)` This method unites all `DataSet`s of the array `s` regarding the array `in` and sets the element length in the united `DataSet` to `subsequenceLength`.
`static DataSet` | `DataSet.union(DataSet[] s, int subsequenceLength)` This method unites all `DataSet`s of the array `s` and sets the element length in the united sample to `subsequenceLength`.

Constructors in de.jstacs.data that throw WrongLengthException
`DataSet.WeightedDataSetFactory(DataSet.WeightedDataSetFactory.SortOperation sort, DataSet... data)` Creates a new `DataSet.WeightedDataSetFactory` on the given `DataSet`(s) with `DataSet.WeightedDataSetFactory.SortOperation` `sort`.
`DataSet.WeightedDataSetFactory(DataSet.WeightedDataSetFactory.SortOperation sort, DataSet[] data, double[][] weights, int length)` Creates a new `DataSet.WeightedDataSetFactory` on the given array of `DataSet`s and an array of `weights` with a given `length` and `DataSet.WeightedDataSetFactory.SortOperation` `sort`.
`DataSet.WeightedDataSetFactory(DataSet.WeightedDataSetFactory.SortOperation sort, DataSet data, double[] weights)` Creates a new `DataSet.WeightedDataSetFactory` on the given `DataSet` and an array of `weights` with `DataSet.WeightedDataSetFactory.SortOperation` `sort`.
`DataSet.WeightedDataSetFactory(DataSet.WeightedDataSetFactory.SortOperation sort, DataSet data, double[] weights, int length)` Creates a new `DataSet.WeightedDataSetFactory` on the given `DataSet` and an array of `weights` with a given `length` and `DataSet.WeightedDataSetFactory.SortOperation` `sort`.
`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(DataSet s, int subsequenceLength)` Creates a new `DataSet` from a given `DataSet` and a given length `subsequenceLength`.
`DNADataSet(String fName)` Creates a new sample of DNA sequence from a FASTA file with file name `fName`.
`DNADataSet(String fName, char ignore)` Creates a new sample of DNA sequence from a file with file name `fName`.
`DNADataSet(String fName, char ignore, SequenceAnnotationParser parser)` Creates a new sample of DNA sequence from a file with file name `fName` using the given `parser`.

Uses of WrongLengthException in de.jstacs.data.sequences

Methods in de.jstacs.data.sequences that throw WrongLengthException
`protected abstract MultiDimensionalSequence<T>` | `MultiDimensionalSequence.getInstance(SequenceAnnotation[] seqAn, Sequence... seqs)`
`protected MultiDimensionalDiscreteSequence` | `MultiDimensionalDiscreteSequence.getInstance(SequenceAnnotation[] seqAn, Sequence... seqs)`
`protected MultiDimensionalArbitrarySequence` | `MultiDimensionalArbitrarySequence.getInstance(SequenceAnnotation[] seqAn, Sequence... seqs)`

Constructors in de.jstacs.data.sequences that throw WrongLengthException
`MultiDimensionalArbitrarySequence(SequenceAnnotation[] seqAn, ArbitrarySequence... sequence)` This constructor creates an `MultiDimensionalDiscreteSequence` from a set of individual `Sequence`s.
`MultiDimensionalDiscreteSequence(SequenceAnnotation[] seqAn, SimpleDiscreteSequence... sequence)` This constructor creates an `MultiDimensionalDiscreteSequence` from a set of individual `Sequence`s.
`MultiDimensionalSequence(SequenceAnnotation[] seqAn, Sequence... sequence)` This constructor creates an `MultiDimensionalSequence` from a set of individual `Sequence`s.

Uses of WrongLengthException in de.jstacs.motifDiscovery

Methods in de.jstacs.motifDiscovery that throw WrongLengthException
`static Hashtable<Sequence,BitSet[]>` | `KMereStatistic.merge(Hashtable<Sequence,BitSet[]> statistic, int maximalMissmatch, boolean bothStrands)` This method allows to merge the statistics of k-mers by allowing mismatches.

Uses of WrongLengthException in de.jstacs.sequenceScores.differentiable

Methods in de.jstacs.sequenceScores.differentiable that throw WrongLengthException
`double` | `AbstractDifferentiableSequenceScore.getLogScoreAndPartialDerivation(Sequence seq, int startpos, int endpos, IntList indices, DoubleList partialDer)`
`double` | `AbstractDifferentiableSequenceScore.getLogScoreFor(Sequence seq, int startpos, int endpos)`

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

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif that throw WrongLengthException
`double[]` | `ExtendedZOOPSDiffSM.getProfileOfScoresFor(int component, int motif, Sequence sequence, int startpos, MotifDiscoverer.KindOfProfile dist)`

Uses of WrongLengthException in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models that throw WrongLengthException
`protected void` | `HigherOrderHMM.fillFwdMatrix(int startPos, int endPos, Sequence seq)`

Uses of WrongLengthException in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states that throw WrongLengthException
`double` | `SimpleDifferentiableState.getLogScoreAndPartialDerivation(int startPos, int endPos, IntList indices, DoubleList partDer, Sequence seq)`
`double` | `DifferentiableState.getLogScoreAndPartialDerivation(int startPos, int endPos, IntList indices, DoubleList partDer, Sequence seq)` This method allows to compute the logarithm of the score and the gradient for the given subsequences.
`double` | `State.getLogScoreFor(int startPos, int endPos, Sequence seq)` This method returns the logarithm of the score for a given sequence with given start and end position.
`double` | `SimpleState.getLogScoreFor(int startPos, int endPos, Sequence seq)`

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