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

Packages that use Sequence
de.jstacs.algorithms | Provides classes for algorithms on graphs.
de.jstacs.classifier | This package provides the framework for any classifier.
de.jstacs.classifier.modelBased | Provides the classes for `Classifier`s that are based on `Model`s
de.jstacs.classifier.scoringFunctionBased | Provides the classes for `Classifier`s that are based on `ScoringFunction`s.
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.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.mixture | This package is the super package for any mixture model.
de.jstacs.models.utils |
de.jstacs.scoringFunctions | Provides `ScoringFunction`s that can be used in a `ScoreClassifier`.
de.jstacs.scoringFunctions.directedGraphicalModels | Provides `ScoringFunction`s that are equivalent to directed graphical models.
de.jstacs.scoringFunctions.homogeneous | Provides `ScoringFunction`s that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence
de.jstacs.scoringFunctions.mix | Provides `ScoringFunction`s that are mixtures of other `ScoringFunction`s.

Uses of Sequence in de.jstacs.algorithms

Methods in de.jstacs.algorithms with parameters of type Sequence
`double` | `Alignment.SimpleCosts.getCostFor(Sequence s1, Sequence s2, int i, int j, Alignment.Costs.Direction from)`
`double` | `Alignment.Costs.getCostFor(Sequence s1, Sequence s2, int i, int j, Alignment.Costs.Direction from)` Returns the costs for the alignment if s1(i) and s2(j) coming from `from`.

Constructors in de.jstacs.algorithms with parameters of type Sequence
`Alignment(Sequence s1, Sequence s2, Alignment.Costs costs)` Creates a new `Alignment.StringAlignment` instance that aligns the sequences `s1` and `s2` using the costs defined in `costs`.

Uses of Sequence in de.jstacs.classifier

Methods in de.jstacs.classifier with parameters of type Sequence
`protected void` | `AbstractScoreBasedClassifier.check(Sequence seq)` This method checks if the given sequence can be used.
`byte` | `AbstractScoreBasedClassifier.classify(Sequence seq)`
`abstract byte` | `AbstractClassifier.classify(Sequence seq)` This method classifies a sequence and returns the index `i`, with `0 < i < getNumberOfClasses()`, of the class to which the sequence is assigned.
`protected byte` | `AbstractScoreBasedClassifier.classify(Sequence seq, boolean check)` This method classifies a sequence.
`double` | `AbstractScoreBasedClassifier.getPValue(Sequence candidate, Sample bg)` Returns the p-value for a sequence `candidate` with respect to a given background sample.
`double` | `AbstractScoreBasedClassifier.getScore(Sequence seq, int i)` This method returns the score for a given sequence and a given class.
`protected double` | `MappingClassifier.getScore(Sequence seq, int i, boolean check)`
`protected abstract double` | `AbstractScoreBasedClassifier.getScore(Sequence seq, int i, boolean check)` This method returns the score for a given sequence and a given class.

Uses of Sequence in de.jstacs.classifier.modelBased

Methods in de.jstacs.classifier.modelBased with parameters of type Sequence
`protected double` | `ModelBasedClassifier.getScore(Sequence seq, int i, boolean check)`

Uses of Sequence in de.jstacs.classifier.scoringFunctionBased

Methods in de.jstacs.classifier.scoringFunctionBased with parameters of type Sequence
`protected double` | `ScoreClassifier.getScore(Sequence seq, int i, boolean check)`

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

Methods in de.jstacs.classifier.scoringFunctionBased.cll with parameters of type Sequence
`protected double` | `CLLClassifier.getScore(Sequence seq, int i, boolean check)`

Uses of Sequence in de.jstacs.data

Subclasses of Sequence in de.jstacs.data
`protected static class` | `Sequence.CompositeSequence` The class handles composite sequences.
`protected static class` | `Sequence.SubSequence` This class handles subsequences.

Fields in de.jstacs.data declared as Sequence
`protected Sequence` | `Sequence.rc` The pointer to the reverse complement

Methods in de.jstacs.data that return Sequence
`Sequence` | `Sequence.annotate(boolean add, SequenceAnnotation... annotation)` This method allows to append annotation to a sequence.
`Sequence` | `Sequence.complement()` This method returns a new instance of sequence containing the complementary current sequence.
`Sequence` | `Sequence.complement(int start, int end)` This method returns a new instance of sequence containing a part of the complementary current sequence.
`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.
`protected abstract Sequence` | `Sequence.flatCloneWithoutAnnotation()` Works in analogy to `Object.clone()`, but does not clone the annotation.
`protected Sequence` | `Sequence.CompositeSequence.flatCloneWithoutAnnotation()`
`protected Sequence` | `Sequence.SubSequence.flatCloneWithoutAnnotation()`
`Sequence[]` | `Sample.getAllElements()` Returns an array of sequences containing all elements of this Sample.
`Sequence` | `Sequence.getCompositeSequence(AlphabetContainer abc, int[] starts, int[] lengths)` This constructor should be used if one wants to create a sample of composite sequences.
`Sequence` | `Sequence.getCompositeSequence(int[] starts, int[] lengths)` This is an very efficient way to create a composite sequence for sequences with a simple AlphabetContainer.
`Sequence` | `Sample.getElementAt(int i)` This method returns the element with index `i`.
`Sequence` | `Sample.WeightedSampleFactory.getElementAt(int index)` Returns the sequence with index `index`.
`Sequence` | `Sequence.getSubSequence(AlphabetContainer abc, int start)` This method should be used if one wants to create a sample 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 sample of subsequences of defined length.
`Sequence` | `Sequence.getSubSequence(int start)` This is an very efficient way to create a subsequence/suffix for sequences with a simple AlphabetContainer.
`Sequence` | `Sequence.getSubSequence(int start, int length)` This is an very efficient way to create a subsequence of defined length for sequences with a simple AlphabetContainer.
`Sequence` | `Sample.ElementEnumerator.nextElement()`
`Sequence` | `DiscreteSequenceEnumerator.nextElement()`
`Sequence` | `Sequence.reverse()` This method returns a new instance of sequence containing the reverse current sequence.
`Sequence` | `Sequence.reverse(int start, int end)` This method returns a new instance of sequence containing a part of the reverse current sequence.
`Sequence` | `Sequence.reverseComplement()` This method returns a new sequence instance containing the complementary current sequence.
`Sequence` | `Sequence.reverseComplement(int start, int end)` This method returns a new sequence instance containing a part of the complementary current sequence.
`Sequence` | `Sequence.SubSequence.reverseComplement(int start, int end)`

Methods in de.jstacs.data with parameters of type Sequence
`int` | `Sequence.compareTo(Sequence s)`

Constructors in de.jstacs.data with parameters of type Sequence
`Sample(String annotation, Sequence... seqs)` This constructor is specially designed for the method `Model.emitSample(int, int...)`.
`Sequence.CompositeSequence(AlphabetContainer abc, Sequence seq, int[] starts, int[] lengths)` This constructor should be used if one wants to create a sample of composite sequences.
`Sequence.CompositeSequence(Sequence seq, int[] starts, int[] lengths)` This is an very effient way to create a composite sequence for sequences with a simple AlphabetContainer.
`Sequence.SubSequence(AlphabetContainer abc, Sequence seq, int start, int length)` This constructor should be used if one wants to create a sample of subsequences of defined length.
`Sequence.SubSequence(Sequence seq, int start, int length)` This is an very efficient way to create a subsequence of defined length for sequences with a simple AlphabetContainer.

Uses of Sequence in de.jstacs.data.sequences

Subclasses of Sequence in de.jstacs.data.sequences
`class` | `ArbitrarySequence` The class for any continuous or hybrid sequence.
`class` | `ByteSequence` This class can be used for discrete AlphabetContainer with alphabets that use only few symbols.
`class` | `DiscreteSequence` The main class for any discrete sequence.
`class` | `IntSequence` This class can be used for discrete AlphabetContainer with alphabets that use a huge number of symbols.
`class` | `PermutedSequence` Class for a permuted sequence.
`class` | `RecursiveSequence` This is the main class for subsequences, composite sequences, ... .
`class` | `ShortSequence` This class can be used for discrete AlphabetContainer with alphabets that use many different symbols.
`class` | `SparseSequence` This class is an implementation for sequence on one alphabet with length 4.

Fields in de.jstacs.data.sequences declared as Sequence
`protected Sequence` | `RecursiveSequence.content` The internal sequence

Methods in de.jstacs.data.sequences that return Sequence
`protected Sequence` | `SparseSequence.flatCloneWithoutAnnotation()`
`protected Sequence` | `ShortSequence.flatCloneWithoutAnnotation()`
`protected Sequence` | `PermutedSequence.flatCloneWithoutAnnotation()`
`protected Sequence` | `IntSequence.flatCloneWithoutAnnotation()`
`protected Sequence` | `ByteSequence.flatCloneWithoutAnnotation()`
`protected Sequence` | `ArbitrarySequence.flatCloneWithoutAnnotation()`

Constructors in de.jstacs.data.sequences with parameters of type Sequence
`PermutedSequence(Sequence seq)` This constructor creates an instance by shuffling the symbols.
`RecursiveSequence(AlphabetContainer alphabet, Sequence seq)` This constructor creates a recursive sequence using the annotation of the given sequence.
`RecursiveSequence(AlphabetContainer alphabet, SequenceAnnotation[] annotation, Sequence seq)` This constructor creates a recursive sequence.

Uses of Sequence in de.jstacs.models

Methods in de.jstacs.models with parameters of type Sequence
`double` | `Model.getLogProbFor(Sequence sequence)` Returns the logarithm of the probability of the given sequence given the model.
`double` | `AbstractModel.getLogProbFor(Sequence sequence)`
`double` | `Model.getLogProbFor(Sequence sequence, int startpos)` Returns the logarithm of the probability of the given sequence given the model.
`double` | `AbstractModel.getLogProbFor(Sequence sequence, int startpos)`
`double` | `Model.getLogProbFor(Sequence sequence, int startpos, int endpos)` Returns the logarithm of the probability of the given sequence given the model.
`double` | `CompositeModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `AbstractModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `Model.getProbFor(Sequence sequence)` Returns the probability of the given sequence given the model.
`double` | `AbstractModel.getProbFor(Sequence sequence)`
`double` | `Model.getProbFor(Sequence sequence, int startpos)` Returns the probability of the given sequence given the model.
`double` | `AbstractModel.getProbFor(Sequence sequence, int startpos)`
`double` | `UniformModel.getProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `Model.getProbFor(Sequence sequence, int startpos, int endpos)` Returns the probability of the given sequence given the model.
`double` | `CompositeModel.getProbFor(Sequence sequence, int startpos, int endpos)`

Uses of Sequence in de.jstacs.models.discrete

Methods in de.jstacs.models.discrete with parameters of type Sequence
`void` | `Constraint.add(Sequence seq, int start, double weight)` This method determines the specific constraint that is fulfilled by the sequence and adds the `weight` to the specific counter.
`protected void` | `DiscreteGraphicalModel.check(Sequence sequence, int startpos, int endpos)` Checks some conditions on a sequence.
`double` | `Constraint.getFreq(Sequence seq, int start)` This method determines the specific constraint that is fullfilled by the sequence beginning at `start`.
`abstract int` | `Constraint.satisfiesSpecificConstraint(Sequence seq, int start)` This method returns the index of the specific constraint that is fullfilled by the sequence beginning at `start`.

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

Methods in de.jstacs.models.discrete.inhomogeneous with parameters of type Sequence
`protected void` | `InhomogeneousDGM.check(Sequence sequence, int startpos, int endpos)`
`double` | `InhCondProb.getLnFreq(Sequence s, int start)` Returns the logarithmic frequency.
`double` | `DAGModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `DAGModel.getProbFor(Sequence sequence, int startpos, int endpos)`
`int` | `InhConstraint.satisfiesSpecificConstraint(Sequence s, int start)`

Uses of Sequence in de.jstacs.models.mixture

Methods in de.jstacs.models.mixture that return Sequence
`protected Sequence[]` | `StrandModel.emitSampleUsingCurrentParameterSet(int n, int... lengths)`
`protected Sequence[]` | `MixtureModel.emitSampleUsingCurrentParameterSet(int n, int... lengths)`
`protected abstract Sequence[]` | `AbstractMixtureModel.emitSampleUsingCurrentParameterSet(int n, int... lengths)` The method returns an array of sequences using the current parameter set.

Methods in de.jstacs.models.mixture with parameters of type Sequence
`int` | `AbstractMixtureModel.getIndexOfMaximalComponentFor(Sequence s)` Returns the index `i` of the component with `P(i|s)`maximal.``
`double` | `AbstractMixtureModel.getLogProbFor(int component, Sequence s)` Returns the log probability for the sequence and the given component.
`double` | `AbstractMixtureModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`protected double` | `StrandModel.getLogProbUsingCurrentParameterSetFor(int component, Sequence s, int start, int end)`
`protected double` | `MixtureModel.getLogProbUsingCurrentParameterSetFor(int component, Sequence s, int start, int end)`
`protected abstract double` | `AbstractMixtureModel.getLogProbUsingCurrentParameterSetFor(int component, Sequence s, int start, int end)` Returns the log probability for the sequence and the given component using the current parameter set.
`double` | `AbstractMixtureModel.getProbFor(Sequence sequence, int startpos, int endpos)`

Uses of Sequence in de.jstacs.models.utils

Methods in de.jstacs.models.utils that return Sequence
`static Sequence` | `ModelTester.getMostProbableSequence(Model m, int length)` Returns one most probable sequence for the discrete model `m`.
`Sequence` | `ModelTester.SeqIterator.getSequence()`

Uses of Sequence in de.jstacs.scoringFunctions

Methods in de.jstacs.scoringFunctions with parameters of type Sequence
`double` | `ScoringFunction.getLogScore(Sequence seq)` Returns the log score for the sequence
`double` | `AbstractNormalizableScoringFunction.getLogScore(Sequence seq)` Returns the log score for the sequence
`double` | `VariableLengthScoringFunction.getLogScore(Sequence seq, int start)`
`double` | `UniformScoringFunction.getLogScore(Sequence seq, int start)`
`double` | `ScoringFunction.getLogScore(Sequence seq, int start)` Returns the log score for the sequence
`double` | `MRFScoringFunction.getLogScore(Sequence seq, int start)`
`double` | `IndependentProductScoringFunction.getLogScore(Sequence seq, int start)`
`abstract double` | `VariableLengthScoringFunction.getLogScore(Sequence seq, int start, int length)` This method computes the logarithm of the score for a given subsequence.
`abstract double` | `VariableLengthScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, int length, IntList indices, DoubleList dList)` This method computes the logarithm of the score and the partial derivations for a given subsequence.
`double` | `VariableLengthScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList dList)`
`double` | `UniformScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList dList)`
`double` | `ScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList partialDer)` Returns the log score for the sequence and fills the list with the indices and the partial derivations.
`double` | `MRFScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList partialDer)`
`double` | `IndependentProductScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList partialDer)`
`double` | `ScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, IntList indices, DoubleList partialDer)` Returns the log score for the sequence and fills the list with the indices and the partial derivations.
`double` | `AbstractNormalizableScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, IntList indices, DoubleList partialDer)`

Uses of Sequence in de.jstacs.scoringFunctions.directedGraphicalModels

Methods in de.jstacs.scoringFunctions.directedGraphicalModels with parameters of type Sequence
`void` | `ParameterTree.addCount(Sequence seq, int start, double count)` Adds `count` to the parameter as returned by `ParameterTree.getParameterFor(Sequence, int)`.
`double` | `Parameter.doesApplyFor(Sequence seq)` Returns true if `seq` fulfills all requirements defined in the context (`Parameter.context`}).
`double` | `BayesianNetworkScoringFunction.getLogScore(Sequence seq, int start)`
`double` | `BayesianNetworkScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList partialDer)`
`Parameter` | `ParameterTree.getParameterFor(Sequence seq, int start)` Returns the `Parameter` that is responsible for the suffix of sequence `seq` starting at position `start`.

Uses of Sequence in de.jstacs.scoringFunctions.homogeneous

Methods in de.jstacs.scoringFunctions.homogeneous with parameters of type Sequence
`double` | `UniformHomogeneousScoringFunction.getLogScore(Sequence seq, int start, int length)`
`double` | `HMMScoringFunction.getLogScore(Sequence seq, int start, int length)`
`double` | `HMM0ScoringFunction.getLogScore(Sequence seq, int start, int length)`
`double` | `UniformHomogeneousScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, int length, IntList indices, DoubleList dList)`
`double` | `HMMScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, int length, IntList indices, DoubleList dList)`
`double` | `HMM0ScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, int length, IntList indices, DoubleList dList)`

Uses of Sequence in de.jstacs.scoringFunctions.mix

Methods in de.jstacs.scoringFunctions.mix with parameters of type Sequence
`protected void` | `MixtureScoringFunction.fillComponentScores(Sequence seq, int start)`
`protected abstract void` | `AbstractMixtureScoringFunction.fillComponentScores(Sequence seq, int start)` Fills the internal array `componentScore` with the log scores of the components.
`int` | `AbstractMixtureScoringFunction.getIndexOfMaximalComponentFor(Sequence seq, int start)` Returns the index of the component that has the greatest impact on the complete score
`double` | `AbstractMixtureScoringFunction.getLogScore(Sequence seq, int start)`
`double` | `MixtureScoringFunction.getLogScoreAndPartialDerivation(Sequence seq, int start, IntList indices, DoubleList partialDer)`
`double[]` | `AbstractMixtureScoringFunction.getProbsForComponent(Sequence seq)` Returns the probabilities for each component

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