- Pair<E1,E2> - Class in de.jstacs.utils
-
A very simple container.
- Pair(E1, E2) - Constructor for class de.jstacs.utils.Pair
-
This constructor creates a pair of element1
and element2
.
- PairwiseStringAlignment - Class in de.jstacs.algorithms.alignment
-
Class for the representation of an alignment of two
String
s.
- PairwiseStringAlignment(String, String, double, int, int, int) - Constructor for class de.jstacs.algorithms.alignment.PairwiseStringAlignment
-
Creates the instance for the two (extended)
String
s and the
edit-costs.
- PairwiseStringAlignment(StringBuffer) - Constructor for class de.jstacs.algorithms.alignment.PairwiseStringAlignment
-
The standard constructor for the interface
Storable
.
- parabolicInterpolation(OneDimensionalFunction, double, double, double, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
-
Approximates a minimum (not necessary the global) in the interval
[lower,upper]
.
- parabolicInterpolation(OneDimensionalFunction, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
-
Approximates a minimum (not necessary the global) in the interval
[lower,upper]
.
- parameter - Variable in class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
-
The internally used parameters.
- Parameter - Class in de.jstacs.parameters
-
Abstract class for a parameter that shall be used as the parameter of some
method, constructor, etc.
- Parameter(String, String, DataType) - Constructor for class de.jstacs.parameters.Parameter
-
The main constructor which takes the main information of a
Parameter
.
- Parameter(StringBuffer) - Constructor for class de.jstacs.parameters.Parameter
-
The standard constructor for the interface
Storable
.
- parameter - Variable in class de.jstacs.sequenceScores.differentiable.logistic.LogisticDiffSS
-
the parameters of the logistic regression
- ParameterException - Exception in de.jstacs.parameters
-
Class for an exception that is thrown if some error occurs while setting a
parameter's value or constructing a parameter.
- ParameterException(String) - Constructor for exception de.jstacs.parameters.ParameterException
-
- ParameterException() - Constructor for exception de.jstacs.parameters.ParameterException
-
- ParameterList() - Constructor for class de.jstacs.parameters.ParameterSet.ParameterList
-
- ParameterList(int) - Constructor for class de.jstacs.parameters.ParameterSet.ParameterList
-
- parameterRemovable() - Method in class de.jstacs.parameters.ExpandableParameterSet
-
Returns
true
if there is still a
Parameter
that can
be removed from the set.
- parameters - Variable in class de.jstacs.data.AlphabetContainer
-
The parameters for this instance.
- parameters - Variable in class de.jstacs.data.alphabets.DiscreteAlphabet
-
- parameters - Variable in class de.jstacs.parameters.AbstractSelectionParameter
-
- parameters - Variable in class de.jstacs.parameters.ParameterSet
-
The set of parameters
- parameters - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
The parameters of the scoring function.
- parameters - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
-
The parameters of this measure
- parameters - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
The parameters defining the distribution over all states that can be visited.
- ParameterSet - Class in de.jstacs.parameters
-
- ParameterSet() - Constructor for class de.jstacs.parameters.ParameterSet
-
- ParameterSet(Parameter...) - Constructor for class de.jstacs.parameters.ParameterSet
-
- ParameterSet(ArrayList<Parameter>) - Constructor for class de.jstacs.parameters.ParameterSet
-
- ParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.ParameterSet
-
The standard constructor for the interface
Storable
.
- ParameterSet.ParameterList - Class in de.jstacs.parameters
-
- ParameterSetContainer - Class in de.jstacs.parameters
-
- ParameterSetContainer(ParameterSet) - Constructor for class de.jstacs.parameters.ParameterSetContainer
-
- ParameterSetContainer(String, String, ParameterSet) - Constructor for class de.jstacs.parameters.ParameterSetContainer
-
- ParameterSetContainer(Class<? extends ParameterSet>) - Constructor for class de.jstacs.parameters.ParameterSetContainer
-
- ParameterSetContainer(String, String, Class<? extends ParameterSet>) - Constructor for class de.jstacs.parameters.ParameterSetContainer
-
- ParameterSetContainer(StringBuffer) - Constructor for class de.jstacs.parameters.ParameterSetContainer
-
The standard constructor for the interface
Storable
.
- ParameterSetParser - Class in de.jstacs.io
-
- ParameterSetParser() - Constructor for class de.jstacs.io.ParameterSetParser
-
- ParameterSetParser.NotInstantiableException - Exception in de.jstacs.io
-
An
Exception
that is thrown if an instance of some class could
not be created.
- ParameterSetParser.WrongParameterTypeException - Exception in de.jstacs.io
-
- ParameterSetTagger - Class in de.jstacs.parameters
-
- ParameterSetTagger(String[], ParameterSet...) - Constructor for class de.jstacs.parameters.ParameterSetTagger
-
The constructor creates an new instance by collecting and tagging all parameters of the
ParameterSet
s.
- ParameterSetTagger.KeyEntryComparator<K extends Comparable<K>,V> - Class in de.jstacs.parameters
-
- ParameterSetTagger.RankEntryComparator<K,V> - Class in de.jstacs.parameters
-
- parametersLoaded() - Method in class de.jstacs.parameters.ParameterSet
-
Returns
true
if the parameters of this
ParameterSet
have been loaded.
- ParameterValidator - Interface in de.jstacs.parameters.validation
-
Interface for a parameter validator, i.e.
- paramRef - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
This array contains the references/indices for the parameters.
- params - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction
-
This is a pointer for the current parameters.
- params - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
-
Parameters
- params - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
-
The parameter set for the classifier.
- params - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
-
The current parameter set of the model.
- params - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
The parameters of the emission
- paramsFile - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
The files for saving the parameters during the sampling.
- paramsFile - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
The files for saving the parameters during the sampling.
- paramsFile - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
-
The files for saving the parameters during the sampling.
- parent - Variable in class de.jstacs.parameters.Parameter
-
- parent - Variable in class de.jstacs.parameters.ParameterSet
-
- parse(String[], boolean) - Method in class de.jstacs.tools.ui.galaxy.GalaxyAdaptor
-
Parses the command line.
- parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.MotifAnnotationParser
-
- parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.NullSequenceAnnotationParser
-
- parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotationParser
-
- parseAnnotationToComment(char, SequenceAnnotation...) - Method in interface de.jstacs.data.sequences.annotation.SequenceAnnotationParser
-
This method returns a
String
representation of the given
SequenceAnnotation
s that can be used as comment line in a file.
- parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.SimpleSequenceAnnotationParser
-
- parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
-
- parseAttributes(Map<String, String>) - Static method in class de.jstacs.io.XMLParser
-
This method parses a map of attribute, i.e.
- parseHashSet2IndexHashtable(HashSet<K>) - Static method in class de.jstacs.utils.ToolBox
-
This method converts a
HashSet
in a
Hashtable
with unique indices starting at 0.
- parseNextParameterSet() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier.DiffSMSamplingComponent
-
- parseNextParameterSet() - Method in interface de.jstacs.sampling.SamplingComponent
-
This method allows the user to parse the next set of parameters (from a
file).
- parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
- parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
-
This method parse a parameter set stored in file during sampling
- parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
-
- parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
-
- parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
-
- parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
This method allows the user to parse the next set of parameters (from a
file).
- parseParameterSet(int, int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier.DiffSMSamplingComponent
-
- parseParameterSet(int, int) - Method in interface de.jstacs.sampling.SamplingComponent
-
This method allows the user to parse the set of parameters with index
n
of a certain sampling
(from a file).
- parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
-
- parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
-
This method allows the user to parse the set of parameters with index
idx
of a certain sampling
(from a file).
- parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
- parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
-
- parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
-
- parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
-
- parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
-
This method allows the user to parse the set of parameters with index
burnInIteration
of a specific sampling
(from a
file).
- parseProfileHMMFromHMMer(Reader, StringBuffer, LinkedList<Integer>, LinkedList<Integer>) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory
-
Parses a profile HMM from the textual HMMer representation.
- parseSections(String) - Static method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
-
Parses the sections as defined in
sections
to a
LinkedList
of
Integer
s.
- parseString(String) - Static method in class de.jstacs.io.XMLParser
-
This method parses the
original
String
to
null
if
original
equals "null".
- partDerState - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
-
Help array for the derivatives of the parameters of the states
- partDerTransition - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
-
Help array for the derivatives of the parameters of the transition
- partialLength - Variable in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
-
This array specifies the lengths of the specific parts.
- partition(DataSet.PartitionMethod, double...) - Method in class de.jstacs.data.DataSet
-
This method partitions the elements, i.e.
- partition(double[], DataSet.PartitionMethod, double...) - Method in class de.jstacs.data.DataSet
-
This method partitions the elements, i.e.
- partition(DataSet.PartitionMethod, int) - Method in class de.jstacs.data.DataSet
-
This method partitions the elements, i.e.
- partition(double[], DataSet.PartitionMethod, int) - Method in class de.jstacs.data.DataSet
-
This method partitions the elements, i.e.
- partNorm - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
This array contains the partial normalization constants, i.e.
- PDFAdaptor - Class in de.jstacs.utils.graphics
-
- PDFAdaptor() - Constructor for class de.jstacs.utils.graphics.PDFAdaptor
-
Creates a new adaptor for plotting to a PDF device.
- pearsonCorrelation(double[], double[]) - Static method in class de.jstacs.utils.ToolBox
-
The method computes the Pearson correlation of two vectors.
- pearsonCorrelation(double[], double[], double[]) - Static method in class de.jstacs.utils.ToolBox
-
Computes the Pearson correlation of two vectors with weights on the individual entries.
- pearsonCorrelation(double[], double[], int, int) - Static method in class de.jstacs.utils.ToolBox
-
The method computes the Pearson correlation of two vectors beginning at specific offsets.
- pearsonCorrelation(double[], double[], int, int, int) - Static method in class de.jstacs.utils.ToolBox
-
The method computes the Pearson correlation of two vectors beginning at specific offsets and using a given number of entries.
- PearsonCorrelationDistanceMetric - Class in de.jstacs.clustering.distances
-
Implements a distance metric based on the Pearson correlation of two double vectors.
- PearsonCorrelationDistanceMetric(boolean) - Constructor for class de.jstacs.clustering.distances.PearsonCorrelationDistanceMetric
-
Creates a new distance based on the Pearson correlation.
- percentile(double[], double) - Static method in class de.jstacs.utils.ToolBox
-
Returns the percent
percentile of the array, i.e.,
returns the element at percent*(array.length)
of the sorted array.
- percentile(int, int, double[], double) - Static method in class de.jstacs.utils.ToolBox
-
Returns the percent
percentile of the array between start and end, i.e.,
returns the element at percent*(end-start)
of the sorted sub-array.
- PerformanceMeasure - Interface in de.jstacs.classifiers.performanceMeasures
-
- PerformanceMeasureParameterSet - Class in de.jstacs.classifiers.performanceMeasures
-
- PerformanceMeasureParameterSet(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
-
The standard constructor for the interface
Storable
.
- PerformanceMeasureParameterSet(int) - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
-
- PerformanceMeasureParameterSet(PerformanceMeasure...) - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
-
- permute(double[]) - Static method in class de.jstacs.utils.ToolBox
-
Creates and returns a permutation of the values in values
.
- permute(double[], double[]) - Static method in class de.jstacs.utils.ToolBox
-
Creates a new permutation of the values in values
.
- PermutedSequence<T> - Class in de.jstacs.data.sequences
-
This class is for permuted sequences.
- PermutedSequence(Sequence<T>) - Constructor for class de.jstacs.data.sequences.PermutedSequence
-
- PermutedSequence(Sequence<T>, int[]) - Constructor for class de.jstacs.data.sequences.PermutedSequence
-
- PFMComparator - Class in de.jstacs.utils
-
This class implements a number of methods for the comparison of position frequency matrices (PFMs) as described in the
Amadeus paper
- PFMComparator() - Constructor for class de.jstacs.utils.PFMComparator
-
- PFMComparator.NormalizedEuclideanDistance - Class in de.jstacs.utils
-
This class implements the normalized Euclidean distance.
- PFMComparator.OneMinusPearsonCorrelationCoefficient - Class in de.jstacs.utils
-
This class implements the Pearson correlation coefficient.
- PFMComparator.PFMDistance - Class in de.jstacs.utils
-
This interface declares a method for comparing different PFMs.
- PFMComparator.SymmetricKullbackLeiblerDivergence - Class in de.jstacs.utils
-
This class implements the symmetric Kullback-Leibler-divergence.
- PFMComparator.UniformBorderWrapper - Class in de.jstacs.utils
-
- PFMDistance() - Constructor for class de.jstacs.utils.PFMComparator.PFMDistance
-
- PFMWrapperTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable
-
A wrapper class for representing position weight matrices or position frequency matrices
from databases as
TrainableStatisticalModel
s.
- PFMWrapperTrainSM(AlphabetContainer, String, double[][], double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
-
Creates a new wrapper for a given position frequency matrix.
- PFMWrapperTrainSM(AlphabetContainer, String, double[][]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
-
Creates a new wrapper for a given position frequency matrix.
- PFMWrapperTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.PFMWrapperTrainSM
-
Creates a wrapper from its XML representation
- PhyloDiscreteEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete
-
Phylogenetic discrete emission
This class uses a phylogenetic tree to describe multidimensional data
It implements Felsensteins model for nucleotide substitution (F81)
- PhyloDiscreteEmission(AlphabetContainer, double, PhyloTree) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
-
- PhyloDiscreteEmission(AlphabetContainer, double[], PhyloTree) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
-
This is a simple constructor for a
DiscreteEmission
defining the individual hyper parameters.
- PhyloNode - Class in de.jstacs.sequenceScores.statisticalModels.trainable.phylo
-
This class implements a node in a
PhyloTree
A PhyloNode contains some basic informations of itself and the incoming edge
Furthermore it contains a list of
PhyloNode
s that represent the children nodes
- PhyloNode() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
-
Basic constructor
- PhyloNode(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
-
The standard constructor for the interface
Storable
.
- PhyloTree - Class in de.jstacs.sequenceScores.statisticalModels.trainable.phylo
-
This class implements a simple (phylogenetic) tree.
- PhyloTree(String, PhyloNode) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
-
Construct an instance of the class PhyloTree
- PhyloTree(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
-
The standard constructor for the interface
Storable
.
- plot(REnvironment, AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
-
- plot(MotifDiscoverer, int, int, Sequence, int, REnvironment, int, int, MotifDiscoverer.KindOfProfile) - Static method in class de.jstacs.motifDiscovery.MotifDiscovererToolBox
-
This method creates a simple plot of the profile of scores for a sequence
and a start position.
- plot(CharSequence) - Method in class de.jstacs.utils.REnvironment
-
Creates a buffered image from a given plot command.
- plot(CharSequence, double, double) - Method in class de.jstacs.utils.REnvironment
-
Creates a buffered image with given dimension from a given plot command.
- plot(CharSequence, double, double, String, OutputStream) - Method in class de.jstacs.utils.REnvironment
-
This method creates an image with given dimension from a given plot command and pipes it to the output stream.
- plotAndAnnotate(MotifDiscoverer, int, int, Sequence, int, REnvironment, int, int, double, double, double, MotifDiscoverer.KindOfProfile) - Static method in class de.jstacs.motifDiscovery.MotifDiscovererToolBox
-
This method creates a plot of the profile of scores for a sequence and a
start position and annotates bindings sites in the plot that have a higher
score than threshold
.
- plotDefaultDependencyLogoToBufferedImage(DataSet, double[], int) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots a dependency logo using default parameters to a
BufferedImage
.
- plotDefaultDependencyLogoToGraphicsAdaptor(GraphicsAdaptor, DataSet, double[], int) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
- plotDependencyLogo(DataSet, Object[], int, double[][], double[], Graphics2D, int, int, int, int[], int[], double, int, boolean, int, boolean, boolean, boolean, double) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots a dependency logo using the supplied parameters.
- PlotGeneratorResult - Class in de.jstacs.results
-
Class for a
Result
that may be used to generate plots for different output formats using
GraphicsAdaptor
sub-classes.
- PlotGeneratorResult(String, String, PlotGeneratorResult.PlotGenerator, boolean) - Constructor for class de.jstacs.results.PlotGeneratorResult
-
- PlotGeneratorResult(StringBuffer) - Constructor for class de.jstacs.results.PlotGeneratorResult
-
- PlotGeneratorResult.PlotGenerator - Interface in de.jstacs.results
-
Interface for a class that may generate a plot using the specified
GraphicsAdaptor
.
- PlotGeneratorResultSaver - Class in de.jstacs.results.savers
-
- plotLogo(Graphics2D, int, double[][]) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the sequence logo for the position weight matrix given in ps
.
- plotLogo(Graphics2D, int, double[][], String[], String, String) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the sequence logo for the position weight matrix given in ps
.
- plotLogo(Graphics2D, int, int, double[][], String[], String, String) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the sequence logo for the position weight matrix given in ps
.
- plotLogo(Graphics2D, int, int, int, int, double[][], String[], String, String) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the sequence logo for the position weight matrix given in ps
.
- plotLogo(Graphics2D, double, double, double, double, double[]) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots a sequence logo for a single position to a graphics object.
- plotLogoToBufferedImage(int, double[][]) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the sequence logo for the position weight matrix given in ps
.
- plotLogoToPNG(String, int, double[][]) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the sequence logo for the position weight matrix given in ps
.
- plotScores(AbstractScoreBasedClassifier, DataSet, DataSet, REnvironment, int, double, String) - Static method in class de.jstacs.classifiers.utils.ClassificationVisualizer
-
This method returns an
ImageResult
containing a plot of the
histograms of the scores.
- plotScores(AbstractScoreBasedClassifier, DataSet, DataSet, REnvironment, int, double, String, String) - Static method in class de.jstacs.classifiers.utils.ClassificationVisualizer
-
This method creates a pdf containing a plot of the histograms of the
scores.
- plotTALgetterLogo(Graphics2D, int, int, int, int, double[][], double[], String[], String, String, String) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the TALgetter logo for the binding specificities given in ps
.
- plotTALgetterLogoToBufferedImage(int, double[][], double[], String[]) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the TALgetter logo for the binding specificities given in ps
.
- plotTALgetterLogoToPNG(String, int, double[][], double[], String[]) - Static method in class de.jstacs.utils.SeqLogoPlotter
-
Plots the TALgetter logo for the binding specificities given in ps
.
- plotToPDF(CharSequence, String, boolean) - Method in class de.jstacs.utils.REnvironment
-
Creates a pdf file from a given plot command.
- plotToPDF(CharSequence, double, double, String, boolean) - Method in class de.jstacs.utils.REnvironment
-
Creates a pdf file with given dimension from a given plot command.
- plotToTexFile(CharSequence, String, boolean) - Method in class de.jstacs.utils.REnvironment
-
Creates a tex file from a given plot command.
- plotToTexFile(CharSequence, double, double, String, boolean) - Method in class de.jstacs.utils.REnvironment
-
Creates a tex file with given dimension from a given plot command.
- PluginGaussianEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous
-
Basic Gaussian emission distribution without random initialization of parameters.
- PluginGaussianEmission(double, double, double, double, double, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
-
Creates a Gaussian emission density with mean mean
and standard deviation sd
.
- PluginGaussianEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
-
- plugInParameters - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
Indicates if plug-in parameters, i.e.
- PMMExplainingAwayResidual - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
-
Class for the network structure of a
BayesianNetworkDiffSM
that is a permuted Markov model based on the explaining away residual.
- PMMExplainingAwayResidual(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
-
The standard constructor for the interface
Storable
.
- PMMExplainingAwayResidual(byte, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
-
- PMMExplainingAwayResidual(PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
-
- PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
-
- PMMExplainingAwayResidualParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
-
- PMMExplainingAwayResidualParameterSet(byte, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
-
- PMMExplainingAwayResidualParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
-
- PMMMutualInformation - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
-
Class for the network structure of a
BayesianNetworkDiffSM
that is a permuted Markov model based on mutual information.
- PMMMutualInformation(byte, BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
-
- PMMMutualInformation(PMMMutualInformation.PMMMutualInformationParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
-
- PMMMutualInformation(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
-
The standard constructor for the interface
Storable
.
- PMMMutualInformation.PMMMutualInformationParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
-
- PMMMutualInformationParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
-
- PMMMutualInformationParameterSet(byte, BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
-
- PMMMutualInformationParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
-
- pop() - Method in class de.jstacs.utils.IntList
-
Returns the last element and removes it from the list.
- position - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
-
The position of symbol
this parameter is responsible for.
- PositionDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif
-
This class implements a position scoring function that enables the user to get a score without using a Sequence
object.
- PositionDiffSM(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
-
This constructor allows create instance with more than one dimension.
- PositionDiffSM(int, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
-
- PositionDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
-
- PositionPrior - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior
-
This is the main class for any position prior that can be used in a motif
discovery.
- PositionPrior() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
-
This empty constructor creates an instance with motif length -1.
- PositionPrior(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
-
The standard constructor for the interface
Storable
.
- PositivePredictiveValueForFixedSensitivity - Class in de.jstacs.classifiers.performanceMeasures
-
This class implements the positive predictive value for a fixed sensitivity.
- PositivePredictiveValueForFixedSensitivity() - Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
-
- PositivePredictiveValueForFixedSensitivity(double) - Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
-
- PositivePredictiveValueForFixedSensitivity(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
-
The standard constructor for the interface
Storable
.
- posPrior - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
-
The prior for the positions.
- powers - Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
-
An array containing the powers for the number of nodes.
- powers - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
-
The powers of the alphabet length.
- PRCurve - Class in de.jstacs.classifiers.performanceMeasures
-
This class implements the precision-recall curve and its area under the curve.
- PRCurve() - Constructor for class de.jstacs.classifiers.performanceMeasures.PRCurve
-
Constructs a new instance of the performance measure
PRCurve
.
- PRCurve(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.PRCurve
-
The standard constructor for the interface
Storable
.
- precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
-
This method precomputes some normalization constant.
- precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
This method precomputes some normalization constant and probabilities.
- precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
-
This method precomputes internal fields as for instance the normalization constant.
- precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
-
- precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
- precomputeBurnInLength(SamplingScoreBasedClassifier.DiffSMSamplingComponent) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
-
Precomputes the length of the burn-in phase, e.g.
- precomputeNorm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
-
Pre-computes the normalization constant.
- precomputeNormalization() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
-
Pre-computes all normalization constants.
- preoptimize(OptimizableFunction) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
-
This method allows to pre-optimize the parameter before the real optimization.
- prepareAssessment(boolean, DataSet...) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
-
Prepares an assessment.
- prepareThreads() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction
-
Assigns parts of the data to the threads
- previousParameters - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
-
The previously accepted parameters, backup for rollbacks
- prGrad - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LogGenDisMixFunction
-
Array for the gradient of the prior
- print(PrintWriter) - Method in class de.jstacs.results.ListResult
-
- print() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
-
Prints the counts and the value of this parameter to
System.out
.
- print() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
-
Prints the structure of this tree.
- prior - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
-
The prior that is used in this function.
- prior - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
-
The prior that is used in this classifier.
- PRIOR_INDEX - Static variable in enum de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple
-
This constant is the array index of the weighting factor for the prior.
- probabilities - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
-
Represents the initial the transition probabilities.
- probs - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
-
The parameters transformed to probabilites
- probs - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
The precomputed probabilities for each possible transition.
- ProductConstraint - Class in de.jstacs.sequenceScores.differentiable.logistic
-
- ProductConstraint(int...) - Constructor for class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
-
This is the main constructor creating an instance from a given set of positions.
- ProductConstraint(StringBuffer) - Constructor for class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
-
- ProgressUpdater - Class in de.jstacs.tools
-
Interface for a progress bar (or similar) indicating a tool's progress.
- ProgressUpdater() - Constructor for class de.jstacs.tools.ProgressUpdater
-
- ProgressUpdater - Interface in de.jstacs.utils
-
Deprecated.
- propagateESS(double, ArrayList<HMMFactory.PseudoTransitionElement>) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory
-
Propagates the ess
for an HMM with absorbing states.
- ProteinAlphabet - Class in de.jstacs.data.alphabets
-
This class implements the discrete alphabet that is used for proteins (one letter code).
- ProteinAlphabet.ProteinAlphabetParameterSet - Class in de.jstacs.data.alphabets
-
- Protocol - Interface in de.jstacs.tools
-
Interface for the protocol of the run of a
JstacsTool
.
- Protocol() - Constructor for class de.jstacs.tools.ui.galaxy.GalaxyAdaptor.Protocol
-
Creates a new Protocol
- provideMatrix(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
-
- pseudoCount - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
-
The pseudocount for this parameter.
- PseudoTransitionElement(int[], int[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory.PseudoTransitionElement
-
- PseudoTransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory.PseudoTransitionElement
-
- PValueComputation - Class in de.jstacs.classifiers.utils
-
This class can be used to compute any p-value from a given statistic.
- PValueComputation() - Constructor for class de.jstacs.classifiers.utils.PValueComputation
-
- PWMSupplier - Interface in de.jstacs.clustering.hierachical
-
Interface for classes that may provide a position weight matrix