Uses of Interface
pal.math.MinimiserMonitor

Packages that use MinimiserMonitor
pal.eval Classes for evaluating evolutionary hypothesis (chi-square and likelihood criteria) and estimating model parameters. 
pal.math Classes for math stuff such as optimisation, numerical derivatives, matrix exponentials, random numbers, special function etc. 
pal.treesearch   
 

Uses of MinimiserMonitor in pal.eval
 

Methods in pal.eval with parameters of type MinimiserMonitor
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 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.
 double LikelihoodOptimiser.optimiseLogLikelihood(Parameterized parameters, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
           
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 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.
 

Uses of MinimiserMonitor in pal.math
 

Methods in pal.math that return MinimiserMonitor
static MinimiserMonitor MinimiserMonitor.Utils.createNullMonitor()
          Creates a MinimiserMonitor that looses all output
static MinimiserMonitor MinimiserMonitor.Utils.createSimpleMonitor(java.io.PrintWriter output)
          Creates a MinimiserMonitor that outputs current minimum to a print stream
static MinimiserMonitor MinimiserMonitor.Utils.createSplitMonitor(MinimiserMonitor a, MinimiserMonitor b)
           
static MinimiserMonitor MinimiserMonitor.Utils.createStringMonitor()
          Creates a MinimiserMonitor that Stores output (use toString() to access current results)
static MinimiserMonitor MinimiserMonitor.Utils.createSystemErrorMonitor()
          Creates a MinimiserMonitor that outputs current minimum to a System.err
static MinimiserMonitor MinimiserMonitor.Utils.createSystemOuptutMonitor()
          Creates a MinimiserMonitor that outputs current minimum to a System.out
 

Methods in pal.math with parameters of type MinimiserMonitor
static MinimiserMonitor MinimiserMonitor.Utils.createSplitMonitor(MinimiserMonitor a, MinimiserMonitor b)
           
 double OrthogonalSearch.RoundOptimiser.doRound(double[] xvec, UnivariateMinimum um, double tolx, double fx, MinimiserMonitor monitor)
           
 double MultivariateMinimum.findMinimum(MultivariateFunction f, double[] xvec, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)
          Find minimum close to vector x (desired fractional digits for each parameter is specified)
 void ConjugateGradientSearch.optimize(MultivariateFunction f, double[] x, double tolfx, double tolx, MinimiserMonitor monitor)
           
 void OrthogonalSearch.optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx, MinimiserMonitor monitor)
           
 void GeneralizedDEOptimizer.optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx, MinimiserMonitor monitor)
          The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
 void ConjugateDirectionSearch.optimize(MultivariateFunction f, double[] xvector, double tolfx, double tolx, MinimiserMonitor monitor)
           
 void DifferentialEvolution.optimize(MultivariateFunction func, double[] xvec, double tolfx, double tolx, MinimiserMonitor monitor)
           
 void MultivariateMinimum.optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx, MinimiserMonitor monitor)
          The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
 

Uses of MinimiserMonitor in pal.treesearch
 

Methods in pal.treesearch with parameters of type MinimiserMonitor
 UndoableAction UnrootedMLSearcher.getModelOptimiseAction(MultivariateMinimum minimiser, MinimiserMonitor monitor, int fxFracDigits, int xFracDigits)
           
 double GeneralLikelihoodSearcher.optimiseAllFullHeirarchy(StoppingCriteria mainStopper, StoppingCriteria subStopper, MultivariateMinimum rateMinimiser, int fxFracDigits, int xFracDigits, AlgorithmCallback callback, SearchMonitor monitor, MinimiserMonitor rateMonitor)
           
 double GeneralConstraintGroupManager.optimiseAllGlobalClockConstraints(MultivariateMinimum minimiser, GeneralConstraintGroupManager.LikelihoodScoreAccess scoreAccess, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
          Optimise all the global clock parameters related to this group
 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, 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)
           
 double GeneralLikelihoodSearcher.optimiseConstraintRateModels(MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
           
 double GeneralConstraintGroupManager.optimisePrimaryGlobalClockConstraints(MultivariateMinimum minimiser, GeneralConstraintGroupManager.LikelihoodScoreAccess scoreAccess, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
          Optimise the global clock parameters marked as primary related to this group
 double GeneralConstraintGroupManager.optimiseSecondaryGlobalClockConstraints(MultivariateMinimum minimiser, GeneralConstraintGroupManager.LikelihoodScoreAccess scoreAccess, int fxFracDigits, int xFracDigits, MinimiserMonitor rateMonitor)
          Optimise the global clock parameters marked as secondary related to this group
 double GeneralLikelihoodSearcher.optimiseSubstitutionModels(MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor)