Uses of Interface
pal.util.AlgorithmCallback

Packages that use AlgorithmCallback
pal.algorithmics   
pal.alignment Classes dealing with sequence alignments, including methods for reading and printing in several possible formats, as well as rearranging and concatenating. 
pal.coalescent Classes to model population genetic processes using the coalescent. 
pal.distance Classes for reading and generating distance matrices, including computation of pairwise distances for sequence data (maximum-likelihood and observed distances). 
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.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   
pal.util Utility classes for sorting etc. 
 

Uses of AlgorithmCallback in pal.algorithmics
 

Methods in pal.algorithmics with parameters of type AlgorithmCallback
 void StoppingCriteria.newIteration(double currentScore, double bestScore, boolean maximising, boolean externalStablized, AlgorithmCallback callback)
           
 void SearchEngine.run(AlgorithmCallback callback, double initialScore, ObjectState subject, StoppingCriteria.Factory stoppingCriteria, Ranker ranker)
           
 

Uses of AlgorithmCallback in pal.alignment
 

Methods in pal.alignment with parameters of type AlgorithmCallback
 Alignment AlignmentGenerator.getNextAlignment(AlgorithmCallback callback)
           
 

Uses of AlgorithmCallback in pal.coalescent
 

Methods in pal.coalescent with parameters of type AlgorithmCallback
 SerialCoalescentGenerator.Results SerialCoalescentGenerator.generateResults(AlgorithmCallback callback)
           
 Tree[] SerialCoalescentGenerator.generateTrees(AlgorithmCallback callback)
          If callback request stop then returns trees creating thus far
 

Uses of AlgorithmCallback in pal.distance
 

Methods in pal.distance with parameters of type AlgorithmCallback
 DistanceMatrix DistanceMatrixGenerator.generateNextMatrix(AlgorithmCallback callback)
           
 DistanceMatrix DistanceMatrixAccess.obtainMatrix(AlgorithmCallback callback)
           
 void AlignmentDistanceMatrix.recompute(SitePattern sp, AlgorithmCallback callback)
          recompute observed distances under new site pattern
 void AlignmentDistanceMatrix.recompute(SitePattern sp, SubstitutionModel model, AlgorithmCallback callback)
          recompute maximum-likelihood distances under new site pattern
 

Constructors in pal.distance with parameters of type AlgorithmCallback
AlignmentDistanceMatrix(SitePattern sp, AlgorithmCallback callback)
          compute observed distances
AlignmentDistanceMatrix(SitePattern sp, SubstitutionModel m, AlgorithmCallback callback)
          compute maximum-likelihood distances
 

Uses of AlgorithmCallback in pal.statistics
 

Methods in pal.statistics with parameters of type AlgorithmCallback
 LikelihoodEvaluator.MLResult LikelihoodEvaluator.getMLOptimised(Tree tree, Alignment alignment, AlgorithmCallback callback)
           
 double[] GeneralTopologyPool.getNewReplicateLogLikelihoods(AlgorithmCallback callback)
           
 double[] TopologyTestEngine.TopologyPool.getNewReplicateLogLikelihoods(AlgorithmCallback callback)
           
 double[] RELLTopologyPool.getNewReplicateLogLikelihoods(AlgorithmCallback callback)
           
 void GeneralTopologyPool.optimiseOriginalTopologies(AlgorithmCallback callback)
           
 TopologyTestEngine.TestResult TopologyTestEngine.performTest(TopologyTestEngine.TopologyPool topologyPool, int numberOfReplicates, AlgorithmCallback callback)
           
 

Uses of AlgorithmCallback in pal.supgma
 

Methods in pal.supgma with parameters of type AlgorithmCallback
 Tree SUPGMABase.generateAlignmentBootstrappedSUPGMATree(AlgorithmCallback callback, ClusterTree.ClusteringMethod cm, SUPGMABase.PopulationParameters pp, int numberOfReplicates, LMSSolver solver)
           
 Tree SUPGMABase.PopulationParameters.generateSUPGMATree(AlgorithmCallback callback, ClusterTree.ClusteringMethod cm, DistanceMatrixGenerator replicateSource, int numberOfAlignmentBootstrapReplicates, LMSSolver solver)
           
 SUPGMABase.CISummary SUPGMABase.PopulationParameters.inferCI(AlgorithmCallback callback, int numberOfReplicates, SimulatedAlignment.Factory alignmentFactory, SubstitutionModel evolutionaryModel, LMSSolver solver)
           
 SUPGMABase.PopulationParameters SUPGMABase.process(AlgorithmCallback callback, LMSSolver solver)
           
 SUPGMABase.PopulationParameters SUPGMABase.process(DistanceMatrixAccess alternativeSource, AlgorithmCallback callback, LMSSolver solver)
           
 Tree[] SUPGMABase.PopulationParameters.simulateTrees(int numberOfTreesToSimulate, AlgorithmCallback callback, LMSSolver solver)
           
 Tree SUPGMABase.solve(AlgorithmCallback callback, ClusterTree.ClusteringMethod cm, LMSSolver solver)
           
 

Uses of AlgorithmCallback in pal.tree
 

Methods in pal.tree with parameters of type AlgorithmCallback
 SimulatedAlignment[] SimulatedAlignment.Factory.generateAlignments(Tree[] trees, AlgorithmCallback callback)
          Generate an array of simulated alignments based on an array of input trees
 Tree TreeGenerator.getNextTree(AlgorithmCallback callback)
           
static Tree TreeUtils.getReplicateCladeSupport(java.lang.String attributeName, Tree baseTree, TreeGenerator treeGenerator, int numberOfReplicates, AlgorithmCallback callback)
          Generates a tree which is identical to baseTree but has attributes (defined by attributeName) at all internal nodes excluding the root node signifying (as a value between 0 and 100) the replicate support by clade (that is the proportion of replicates that produce the sub clade under that node)
 

Uses of AlgorithmCallback in pal.treesearch
 

Methods in pal.treesearch with parameters of type AlgorithmCallback
 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, AlgorithmCallback callback)
          Do a basic tree search using maximum likelihood on an unrooted tree space, with a given starting tree
 double GeneralLikelihoodSearcher.optimiseAllFullHeirarchy(StoppingCriteria mainStopper, StoppingCriteria subStopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor)
           
 double GeneralLikelihoodSearcher.optimiseAllPlusSubstitutionModel(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, MultivariateMinimum substitutionModelMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, int substitutionModelOptimiseFrequency, MinimiserMonitor substitutionModelMonitor, MinimiserMonitor rateMonitor)
           
 double GeneralLikelihoodSearcher.optimiseAllSimple(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback)
           
 double GeneralLikelihoodSearcher.optimiseAllSimple(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor)
           
 double GeneralLikelihoodSearcher.optimiseAllSimple(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor, int groupOptimistionType)
           
 double GeneralLikelihoodSearcher.optimiseAllSimpleHeirarchy(StoppingCriteria stopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor)
           
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.
 double GeneralLikelihoodSearcher.optimiseGeneral(StoppingCriteria stopper, int fracDigits, AlgorithmCallback callback)
           
 double GeneralLikelihoodSearcher.optimiseGeneral(StoppingCriteria stopper, int fracDigits, AlgorithmCallback callback, SearchMonitor monitor)
           
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).
 double UnrootedMLSearcher.simpleOptimiseLikelihood(double epsilon, AlgorithmCallback callback)
          Optimise the branch lengths of the tree to obtain the maximum likelihood.
 double UnrootedMLSearcher.simpleOptimiseLikelihood(StoppingCriteria stopper, AlgorithmCallback callback)
          Optimise the branch lengths of the tree to obtain the maximum likelihood.
 

Uses of AlgorithmCallback in pal.util
 

Methods in pal.util that return AlgorithmCallback
static AlgorithmCallback AlgorithmCallback.Utils.getNullCallback()
           
static AlgorithmCallback AlgorithmCallback.Utils.getPrintWriterCallback(java.io.PrintWriter pw)
          Construct an algorithm callback that redirects status reports to a print writer
static AlgorithmCallback AlgorithmCallback.Utils.getSubCallback(AlgorithmCallback parent, java.lang.String id, double minProgress, double maxProgress)
           
static AlgorithmCallback AlgorithmCallback.Utils.getSystemOutCallback()
           
 

Methods in pal.util with parameters of type AlgorithmCallback
static AlgorithmCallback AlgorithmCallback.Utils.getSubCallback(AlgorithmCallback parent, java.lang.String id, double minProgress, double maxProgress)