Uses of Interface
pal.substmodel.SubstitutionModel

Packages that use SubstitutionModel
pal.distance Classes for reading and generating distance matrices, including computation of pairwise distances for sequence data (maximum-likelihood and observed distances). 
pal.eval Classes for evaluating evolutionary hypothesis (chi-square and likelihood criteria) and estimating model parameters. 
pal.statistics Classes with useful for statistics (normal distribution, Gamma distribution, chi-square distribution, exponential distribution, likelihood-ratio test, chi-square test, descriptive statistics, bootstrap estimators etc.) 
pal.substmodel Classes describing substitution models, i.e. 
pal.supgma   
pal.tree Classes for providing the data structure of trees, for constructing and modifying trees, and for parameterizing trees (e.g., clock constraint). 
pal.treesearch   
 

Uses of SubstitutionModel in pal.distance
 

Methods in pal.distance with parameters of type SubstitutionModel
static DistanceMatrix DistanceTool.constructEvolutionaryDistances(Alignment a, SubstitutionModel sm)
          Construct a distance matrix object such that the distance between sequence A, and sequence B, is the evolutionary distance by a given substitution model.
static DistanceMatrixGenerator DistanceMatrixGenerator.Utils.createEvolutionary(Alignment a, SubstitutionModel sm)
           
static DistanceMatrixAccess DistanceMatrixAccess.Utils.createEvolutionary(Alignment a, SubstitutionModel sm)
           
static DistanceMatrixGenerator DistanceMatrixGenerator.Utils.createParametric(Tree baseTree, SubstitutionModel sm, int numberOfSites)
          Silly idea stuff
 void AlignmentDistanceMatrix.recompute(SitePattern sp, SubstitutionModel model)
          recompute maximum-likelihood distances under new site pattern
 void AlignmentDistanceMatrix.recompute(SitePattern sp, SubstitutionModel model, AlgorithmCallback callback)
          recompute maximum-likelihood distances under new site pattern
 void SequencePairLikelihood.updateModel(SubstitutionModel m)
          update model of substitution
 void PairwiseDistance.updateModel(SubstitutionModel m)
          update model of substitution
 

Constructors in pal.distance with parameters of type SubstitutionModel
AlignmentDistanceMatrix(SitePattern sp, SubstitutionModel m)
          compute maximum-likelihood distances
AlignmentDistanceMatrix(SitePattern sp, SubstitutionModel m, AlgorithmCallback callback)
          compute maximum-likelihood distances
PairwiseDistance(SitePattern sp, SubstitutionModel m)
          Constructor 2 (uses evolutionary model)
SequencePairLikelihood(SitePattern sp, SubstitutionModel m)
          initialisation
 

Uses of SubstitutionModel in pal.eval
 

Methods in pal.eval that return SubstitutionModel
 SubstitutionModel LikelihoodValue.getModel()
          Returns the model of this likelihood value.
 SubstitutionModel SiteDetails.getRelatedModel()
           
 

Methods in pal.eval with parameters of type SubstitutionModel
protected abstract  void LHCalculator.AbstractExternal.calculateCategoryPatternProbabilities(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftFlatConditionalProbabilities, ConditionalProbabilityStore rightFlatConditionalProbabilities, ConditionalProbabilityStore tempStore, double[][] categoryPatternLogLikelihoodStore)
           
protected abstract  void LHCalculator.AbstractExternal.calculateCategoryPatternProbabilities(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, double[][] categoryPatternLikelihoodStore)
           
 ConditionalProbabilityStore LHCalculator.Internal.calculateExtended(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, boolean modelChangedSinceLastCall)
           
 void LHCalculator.External.calculateExtended(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, ConditionalProbabilityStore resultStore)
           
 double LHCalculator.External.calculateLogLikelihood(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftFlatConditionalProbabilities, ConditionalProbabilityStore rightFlatConditionalProbabilities, ConditionalProbabilityStore tempStore)
          Calculate the likelihood given two sub trees (left, right) and their flat (unextend) likeihood probabilities
 double LHCalculator.External.calculateLogLikelihood(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities)
          Calculate the likelihood given two sub trees (left, right) and their extended likeihood probabilities
static double LikelihoodTool.calculateLogLikelihood(Tree tree, Alignment alignment, SubstitutionModel model)
          Calculate the log likelihood of a particular set of phylogenetic data
 double LHCalculator.External.calculateLogLikelihoodSingle(SubstitutionModel model, int[] patternWeights, int numberOfPatterns, ConditionalProbabilityStore conditionalProbabilityStore)
          Calculate the likelihood given the conditional probabilites at the root
 ConditionalProbabilityStore LHCalculator.Internal.calculatePostExtendedFlat(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, boolean modelChangedSinceLastCall)
           
 void LHCalculator.External.calculateSingleExtendedDirect(double distance, SubstitutionModel model, int numberOfPatterns, ConditionalProbabilityStore conditionalProbabilities)
          Extend the conditionals back in time by some distance, with some model
 void LHCalculator.External.calculateSingleExtendedIndirect(double distance, SubstitutionModel model, int numberOfPatterns, ConditionalProbabilityStore baseConditionalProbabilities, ConditionalProbabilityStore resultConditionalProbabilities)
          Extend the conditionals back in time by some distance, with some model
 SiteDetails LHCalculator.External.calculateSiteDetailsRooted(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilitiesStore, ConditionalProbabilityStore rightConditionalProbabilitiesStore)
          Calculate the conditional probabilities of each pattern for each category
 SiteDetails LHCalculator.AbstractExternal.calculateSiteDetailsRooted(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilitiesStore, ConditionalProbabilityStore rightConditionalProbabilitiesStore)
           
 SiteDetails LHCalculator.External.calculateSiteDetailsUnrooted(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilitiesStore, ConditionalProbabilityStore rightConditionalProbabilitiesStore, ConditionalProbabilityStore tempStore)
          Calculate the conditional probabilities of each pattern for each category
 SiteDetails LHCalculator.AbstractExternal.calculateSiteDetailsUnrooted(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftFlatConditionalProbabilities, ConditionalProbabilityStore rightFlatConditionalProbabilities, ConditionalProbabilityStore tempStore)
           
static SiteDetails SiteDetails.Utils.create(double[][] categoryPatternConditionalProbabilities, boolean isLoggedConditionals, SubstitutionModel model, int numberOfPatterns, int[] sitePatternMatchup, int numberOfSites, double[] siteLikelihoods)
          Create a Postriors object
static MolecularClockLikelihoodModel.Instance SimpleMolecularClockLikelihoodModel.createInstance(LHCalculator.Factory baseFactory, SubstitutionModel model)
           
static UnconstrainedLikelihoodModel.Instance SimpleUnconstrainedLikelihoodModel.createInstance(LHCalculator.Factory base, SubstitutionModel model)
          Create a SimpleUnconstrainedLikelihoodModel instance
static UnconstrainedLikelihoodModel.Instance SimpleUnconstrainedLikelihoodModel.createInstance(LHCalculator.Generator base, SubstitutionModel model)
          Create a SimpleUnconstrainedLikelihoodModel instance
static MolecularClockLikelihoodModel.Instance SimpleMolecularClockLikelihoodModel.createInstance(SubstitutionModel model)
           
 ConditionalProbabilityStore LHCalculator.Leaf.getExtendedConditionalProbabilities(double distance, SubstitutionModel model, boolean modelChanged)
           
 ConditionalProbabilityStore SimpleLeafCalculator.getExtendedConditionalProbabilities(double distance, SubstitutionModel model, boolean modelChanged)
           
static Alignment LikelihoodTool.getMatchingDataType(Alignment alignment, SubstitutionModel model)
          Creates a new alignment that has a compatible data type with a substution model (needed for likelihood stuff)
static double LikelihoodOptimiser.optimiseAlternate(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
          Optimise parameters to acheive maximum likelihood using an alternating stategy.
static double LikelihoodOptimiser.optimiseAlternate(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
          Optimise parameters to acheive maximum likelihood using an alternating stategy.
static Tree LikelihoodTool.optimiseClockConstrained(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel)
          Optimise the branches of a tree with regard to maximum likelihood, with a molecular clock assumption, that is, constrained such that all tips are contemporaneous, the tree is treated as rooted.
static double LikelihoodOptimiser.optimiseCombined(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
          Optimise parameters to acheive maximum likelihood using a combined stategy.
static double LikelihoodOptimiser.optimiseCombined(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
          Optimise parameters to acheive maximum likelihood using a combined stategy.
static double LikelihoodOptimiser.optimiseModel(Tree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
          Optimise model parameters only to acheive maximum likelihood using a combined stategy.
static Tree LikelihoodTool.optimiseMRDT(Tree tree, Alignment alignment, SubstitutionModel model, TimeOrderCharacterData tocd, boolean optimiseModel, double[] rateStore)
          Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and multiple mutation rate parameters, mu - one for each sampling interval.
static Tree LikelihoodTool.optimiseMRDT(Tree tree, Alignment alignment, SubstitutionModel model, TimeOrderCharacterData tocd, boolean optimiseModel, double[] rateChangeTimes, double[] rateStore)
          Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and multiple mutation rate parameters, mu, over general time intervals.
static Tree LikelihoodTool.optimiseSRDT(Tree tree, Alignment alignment, SubstitutionModel model, TimeOrderCharacterData tocd, boolean optimiseModel, double[] rateStore)
          Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and a single mutation rate parameter.
static double LikelihoodOptimiser.optimiseTree(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits)
          Optimise tree branchlengths only to acheive maximum likelihood using a combined stategy.
static double LikelihoodOptimiser.optimiseTree(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
          Optimise tree branchlengths only to acheive maximum likelihood using a combined stategy.
static Tree LikelihoodTool.optimiseUnrooted(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel)
          Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree).
 void LikelihoodValue.setModel(SubstitutionModel m)
          define model (a site pattern must have been set before calling this method)
 void GeneralLikelihoodCalculator.setup(Tree t, SubstitutionModel model)
           
 

Constructors in pal.eval with parameters of type SubstitutionModel
GeneralLikelihoodCalculator(Alignment baseAlignment, Tree tree, SubstitutionModel model)
          Constructor taking site pattern, tree and a general substitution model.
LikelihoodOptimiser(Tree tree, Alignment alignment, SubstitutionModel model)
           
ModelParameters(SitePattern sp, SubstitutionModel m)
          Constructor
SimpleUnconstrainedLikelihoodModel.InternalImpl(LHCalculator.Internal base, SubstitutionModel model)
           
SimpleUnconstrainedLikelihoodModel.LeafImpl(LHCalculator.Leaf base, SubstitutionModel model)
           
 

Uses of SubstitutionModel in pal.statistics
 

Methods in pal.statistics with parameters of type SubstitutionModel
static ReplicateLikelihoodEvaluator ReplicateLikelihoodEvaluator.Utils.createRELLEvaluator(SubstitutionModel model)
          Create a ReplicateLikelihoodEvaluator that based likelihood on original tree (does no optimisation)
static LikelihoodEvaluator LikelihoodEvaluator.Utils.createSimpleEvaluator(SubstitutionModel model)
          Create a simple evaluator that uses UnrootedTreeSearch
 

Uses of SubstitutionModel in pal.substmodel
 

Classes in pal.substmodel that implement SubstitutionModel
 class GeneralRateDistributionSubstitutionModel
           
 class SingleClassSubstitutionModel
           
static class YangCodonModel.SimpleNeutralSelection
          A Substitution Model which can be used to implment the Neutral Model (with out continuous rate stuff) Codon model of [1] which uses the weighted sum of trwo base YangCodon models where omega=0, omega=1 repectively
[1] Nielsen, R., Yang Z., 1998 Likelihood Models for Detecting Positively Selected Amino Acid Sites and Applications to the HIV-1 Envelope Gene.
static class YangCodonModel.SimplePositiveSelection
          A Substitution Model which can be used to implment the Postitive Selection (with out continuous rate stuff) Codon model of [1] which uses the weighted sum of a three base Codon model where omega=0, omega=1 and omega=free
[1] Nielsen, R., Yang Z., 1998 Likelihood Models for Detecting Positively Selected Amino Acid Sites and Applications to the HIV-1 Envelope Gene.
 

Fields in pal.substmodel declared as SubstitutionModel
static SubstitutionModel F81.JC69_MODEL
           
 

Methods in pal.substmodel that return SubstitutionModel
static SubstitutionModel SubstitutionTool.createF81Model(double[] baseFrequencies)
          Create an F81 model of substitution
static SubstitutionModel SubstitutionTool.createF84Model(double expectedTsTv, double[] baseFrequencies)
          Create an F84 model of substitution
static SubstitutionModel SubstitutionTool.createGTRModel(double a, double b, double c, double d, double e, double[] baseFrequencies)
          Create an GTR model of substitution
static SubstitutionModel SubstitutionTool.createJC69Model()
          Create a Jukes-cantor model of substitution
static SubstitutionModel SubstitutionTool.createM0YangCodonModel(double kappa, double omega, double[] baseFrequencies)
          Create an base Yang Codon model (M0) of substitution
static SubstitutionModel SubstitutionTool.createM1YangCodonModel(double kappa, double p0, double[] baseFrequencies)
          Create an neutral Yang Codon model (M1) of substitution
static SubstitutionModel SubstitutionTool.createM2YangCodonModel(double kappa, double p0, double p1, double omega, double[] baseFrequencies)
          Create an Positive Yang Codon model (M2) of substitution
static SubstitutionModel SubstitutionModel.Utils.createSubstitutionModel(NeoRateMatrix rm, DataType dt, double[] equilibriumFrequencies)
           
static SubstitutionModel SubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm)
           
static SubstitutionModel SubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm, RateDistribution rd)
           
static SubstitutionModel SubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm, RateDistribution rd, boolean parameteriseDistribution)
           
static SubstitutionModel SubstitutionTool.createTNModel(double kappa, double r, double[] baseFrequencies)
          Create an Tamura-Nei model of substitution
 SubstitutionModel SingleClassSubstitutionModel.getCopy()
           
 SubstitutionModel YangCodonModel.SimplePositiveSelection.getCopy()
           
 SubstitutionModel YangCodonModel.SimpleNeutralSelection.getCopy()
           
 SubstitutionModel GeneralRateDistributionSubstitutionModel.getCopy()
           
 

Methods in pal.substmodel with parameters of type SubstitutionModel
static double[][][] SubstitutionModel.Utils.generateTransitionProbabilityTables(SubstitutionModel model)
           
 

Constructors in pal.substmodel with parameters of type SubstitutionModel
SequenceSimulator(SubstitutionModel model, int sequenceLength, boolean stochasticDistribution)
          A constructor (with no provided random number generator - a fresh one is created)
SequenceSimulator(SubstitutionModel model, int sequenceLength, MersenneTwisterFast random, boolean stochasticDistribution)
          A constructor (with no provided random number generator - a fresh one is created)
 

Uses of SubstitutionModel in pal.supgma
 

Methods in pal.supgma with parameters of type SubstitutionModel
 SUPGMABase.CISummary SUPGMABase.PopulationParameters.inferCI(AlgorithmCallback callback, int numberOfReplicates, SimulatedAlignment.Factory alignmentFactory, SubstitutionModel evolutionaryModel, LMSSolver solver)
           
 

Uses of SubstitutionModel in pal.tree
 

Constructors in pal.tree with parameters of type SubstitutionModel
SimulatedAlignment.Factory(int sequenceLength, SubstitutionModel model)
           
SimulatedAlignment(int sites, Tree t, SubstitutionModel m)
          Inititalisation
 

Uses of SubstitutionModel in pal.treesearch
 

Methods in pal.treesearch with parameters of type SubstitutionModel
 UnrootedMLSearcher BranchAccess.attach(Node subTree, Alignment fullAlignment, SubstitutionModel model)
          Create a new Tree Searcher with a new sub tree attached
 UnrootedMLSearcher BranchAccess.attach(java.lang.String newSequence, Alignment fullAlignment, SubstitutionModel model)
          Create a new Tree Searcher with a new sub tree attached
 Tree TreeSearchTool.basicUnrootedTreeMLSearch(Alignment a, SubstitutionModel sm, boolean optimiseModel)
          Do a basic tree search using maximum likelihood on an unrooted tree space, without a given starting tree
 Tree TreeSearchTool.basicUnrootedTreeMLSearch(Alignment a, SubstitutionModel sm, boolean optimiseModel, AlgorithmCallback callback)
          Do a basic tree search using maximum likelihood on an unrooted tree space, without a given starting tree
 Tree TreeSearchTool.basicUnrootedTreeMLSearch(Tree baseTree, Alignment a, SubstitutionModel sm, boolean optimiseModel)
          Do a basic tree search using maximum likelihood on an unrooted tree space, with a given starting tree
 Tree TreeSearchTool.basicUnrootedTreeMLSearch(Tree baseTree, Alignment a, SubstitutionModel sm, boolean optimiseModel, AlgorithmCallback callback)
          Do a basic tree search using maximum likelihood on an unrooted tree space, with a given starting tree
static double TreeSearchTool.calculateLogLikelihood(Tree tree, Alignment alignment, SubstitutionModel model)
          Calculate the log likelihood of a particular set of phylogenetic data
static Alignment TreeSearchTool.getMatchingDataType(Alignment alignment, SubstitutionModel model)
          Creates a new alignment that has a compatible data type with a substution model (needed for likelihood stuff)
static Tree TreeSearchTool.optimiseClockConstrainedFixed(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel, AlgorithmCallback callback)
          Optimise the branches of a tree with regard to maximum likelihood, with the contraints of a global molecular clock - that is, all the tips terminate at the same point.
static Tree TreeSearchTool.optimiseUnrootedFixed(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel)
          Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree).
static Tree TreeSearchTool.optimiseUnrootedFixed(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel, AlgorithmCallback callback)
          Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree).
 

Constructors in pal.treesearch with parameters of type SubstitutionModel
UnrootedMLSearcher(Alignment alignment, SubstitutionModel model)
          Build an unconstrained optimiser based on a randomly generated tree.
UnrootedMLSearcher(Alignment alignment, SubstitutionModel model, LHCalculator.Factory calcFactory)
           
UnrootedMLSearcher(Node root, Alignment alignment, SubstitutionModel model)
           
UnrootedMLSearcher(Node root, Alignment alignment, SubstitutionModel model, LHCalculator.Factory calcFactory)
           
UnrootedMLSearcher(Node root, SubstitutionModel model)
          Create a searcher based on a given tree, that has no alignment specified (useful as backbone tree for attaching new nodes)
UnrootedMLSearcher(Tree t, Alignment alignment, SubstitutionModel model)