Uses of Interface pal.util.AlgorithmCallback

Packages that use AlgorithmCallback
Package	Description
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
Modifier and Type	Method	Description
`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
Modifier and Type Method Description

Alignment AlignmentGenerator.getNextAlignment(AlgorithmCallback callback)

Uses of AlgorithmCallback in pal.coalescent

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

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

Uses of AlgorithmCallback in pal.statistics

Methods in pal.statistics with parameters of type AlgorithmCallback
Modifier and Type	Method	Description
`LikelihoodEvaluator.MLResult`	LikelihoodEvaluator.`getMLOptimised(Tree tree, Alignment alignment, AlgorithmCallback callback)`
`double[]`	GeneralTopologyPool.`getNewReplicateLogLikelihoods(AlgorithmCallback callback)`
`double[]`	RELLTopologyPool.`getNewReplicateLogLikelihoods(AlgorithmCallback callback)`
`double[]`	TopologyTestEngine.TopologyPool.`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
Modifier and Type	Method	Description
`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(DistanceMatrixAccess alternativeSource, AlgorithmCallback callback, LMSSolver solver)`
`SUPGMABase.PopulationParameters`	SUPGMABase.`process(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
Modifier and Type	Method	Description
`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
Modifier and Type	Method	Description
`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
Modifier and Type	Method	Description
`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
Modifier and Type	Method	Description
`static AlgorithmCallback`	AlgorithmCallback.Utils.`getSubCallback(AlgorithmCallback parent, java.lang.String id, double minProgress, double maxProgress)`