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Packages that use Pair | |
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de.jstacs.data | Provides classes for the representation of data. |
de.jstacs.motifDiscovery | This package provides the framework including the interface for any de novo motif discoverer |
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.models | The package provides different implementations of hidden Markov models based on AbstractHMM |
Uses of Pair in de.jstacs.data |
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Methods in de.jstacs.data that return Pair | |
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Pair<DataSet[],double[][]> |
DataSet.partition(double[] sequenceWeights,
DataSet.PartitionMethod method,
double... percentage)
This method partitions the elements, i.e. the Sequence s, of the
DataSet and the corresponding weights in distinct parts where each part holds the corresponding
percentage given in the array percentage . |
Pair<DataSet[],double[][]> |
DataSet.partition(double[] sequenceWeights,
int k,
DataSet.PartitionMethod method)
This method partitions the elements, i.e. the Sequence s, of the
DataSet and the corresponding weights in k distinct parts. |
Uses of Pair in de.jstacs.motifDiscovery |
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Methods in de.jstacs.motifDiscovery that return Pair | |
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static Pair<Sequence,BitSet[]>[] |
KMereStatistic.getKmereSequenceStatistic(boolean bothStrands,
int maxMismatch,
HashSet<Sequence> filter,
DataSet... data)
This method enables the user to get a statistic for a set of k -mers. |
Uses of Pair in de.jstacs.sequenceScores.statisticalModels.trainable.hmm |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm that return Pair | |
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abstract Pair<IntList,Double> |
AbstractHMM.getViterbiPathFor(int startPos,
int endPos,
Sequence seq)
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Pair<IntList,Double> |
AbstractHMM.getViterbiPathFor(Sequence seq)
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Pair<IntList,Double>[] |
AbstractHMM.getViterbiPathsFor(DataSet data)
This method returns the viterbi paths and scores for all sequences of the sample data . |
static Pair<double[][],double[]> |
HMMFactory.propagateESS(double ess,
ArrayList<HMMFactory.PseudoTransitionElement> list)
Propagates the ess for an HMM with absorbing states. |
Uses of Pair in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models that return Pair | |
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Pair<IntList,Double> |
SamplingHigherOrderHMM.getViterbiPath(int startPos,
int endPos,
Sequence seq,
SamplingHigherOrderHMM.ViterbiComputation compute)
This method returns a viterbi path that is the optimum for the choosen ViterbiComputation method |
Pair<IntList,Double> |
SamplingHigherOrderHMM.getViterbiPathFor(int startPos,
int endPos,
Sequence seq)
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Pair<IntList,Double> |
HigherOrderHMM.getViterbiPathFor(int startPos,
int endPos,
Sequence seq)
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