Example usage for org.apache.commons.math3.optim.nonlinear.scalar.noderiv SimplexOptimizer SimplexOptimizer

Introduction

In this page you can find the example usage for org.apache.commons.math3.optim.nonlinear.scalar.noderiv SimplexOptimizer SimplexOptimizer.

Prototype

public SimplexOptimizer(ConvergenceChecker<PointValuePair> checker) 

Source Link

Usage

From source file:de.bund.bfr.math.MultivariateOptimization.java

@Override
public Result optimize(int nParameterSpace, int nOptimizations, boolean stopWhenSuccessful,
        Map<String, Double> minStartValues, Map<String, Double> maxStartValues, int maxIterations,
        DoubleConsumer progessListener, ExecutionContext exec) throws CanceledExecutionException {
    if (exec != null) {
        exec.checkCanceled();//from  w  w  w . jav  a2s.co m
    }

    progessListener.accept(0.0);

    List<ParamRange> ranges = MathUtils.getParamRanges(parameters, minStartValues, maxStartValues,
            nParameterSpace);

    ranges.set(parameters.indexOf(sdParam), new ParamRange(1.0, 1, 1.0));

    List<StartValues> startValuesList = MathUtils.createStartValuesList(ranges, nOptimizations,
            values -> optimizerFunction.value(Doubles.toArray(values)),
            progress -> progessListener.accept(0.5 * progress), exec);
    Result result = new Result();
    AtomicInteger currentIteration = new AtomicInteger();
    SimplexOptimizer optimizer = new SimplexOptimizer(new SimpleValueChecker(1e-10, 1e-10) {

        @Override
        public boolean converged(int iteration, PointValuePair previous, PointValuePair current) {
            if (super.converged(iteration, previous, current)) {
                return true;
            }

            return currentIteration.incrementAndGet() >= maxIterations;
        }
    });
    int count = 0;

    for (StartValues startValues : startValuesList) {
        if (exec != null) {
            exec.checkCanceled();
        }

        progessListener.accept(0.5 * count++ / startValuesList.size() + 0.5);

        try {
            PointValuePair optimizerResults = optimizer.optimize(new MaxEval(Integer.MAX_VALUE),
                    new MaxIter(maxIterations), new InitialGuess(Doubles.toArray(startValues.getValues())),
                    new ObjectiveFunction(optimizerFunction), GoalType.MAXIMIZE,
                    new NelderMeadSimplex(parameters.size()));
            double logLikelihood = optimizerResults.getValue() != null ? optimizerResults.getValue()
                    : Double.NaN;

            if (result.logLikelihood == null || logLikelihood > result.logLikelihood) {
                result = getResults(optimizerResults);

                if (result.logLikelihood == 0.0 || stopWhenSuccessful) {
                    break;
                }
            }
        } catch (TooManyEvaluationsException | TooManyIterationsException | ConvergenceException e) {
        }
    }

    return result;
}

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From source file:com.insightml.math.optimization.AbstractOptimizable.java

private PointValuePair simplex(final AbstractSimplex simplex, final double[] initialValues) {
    return optimize(new SimplexOptimizer(conv()), initialValues, simplex);
}

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From source file:com.wwidesigner.optimization.ObjectiveFunctionOptimizer.java

protected static PointValuePair runSimplex(BaseObjectiveFunction objective, double[] startPoint)
        throws TooManyEvaluationsException {
    // Rely on relative difference to test convergence,
    // to allow for vast differences in absolute error scale
    // between objective functions.
    ConvergenceChecker<PointValuePair> convergenceChecker = new SimpleValueChecker(1.e-6, 1.e-14);
    SimplexOptimizer optimizer = new SimplexOptimizer(convergenceChecker);
    MultiDirectionalSimplex simplex = new MultiDirectionalSimplex(objective.getSimplexStepSize());

    return optimizer.optimize(GoalType.MINIMIZE, new ObjectiveFunction(objective),
            new MaxEval(objective.getMaxEvaluations()), MaxIter.unlimited(), new InitialGuess(startPoint),
            simplex);/*from w  w w . jav a2s.  c o m*/
}

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From source file:uk.ac.diamond.scisoft.analysis.diffraction.FittingUtils.java

/**
 * @param opt//  w w  w  .j a va  2  s  .co  m
 * @param n
 * @return optimizer
 */
public static MultivariateOptimizer createOptimizer(Optimizer opt, int n) {
    switch (opt) {
    case BOBYQA:
        return new BOBYQAOptimizer(n + 2);
    case CMAES:
        return new CMAESOptimizer(MAX_ITER, 0., true, 0, 10,
                seed == null ? new Well19937c() : new Well19937c(seed), false,
                new SimplePointChecker<PointValuePair>(REL_TOL, ABS_TOL));
    case Simplex:
    default:
        return new SimplexOptimizer(new SimplePointChecker<PointValuePair>(REL_TOL * 1e3, ABS_TOL * 1e3));
    }
}

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From source file:uk.ac.diamond.scisoft.analysis.optimize.ApacheOptimizer.java

private MultivariateOptimizer createOptimizer() {
    SimplePointChecker<PointValuePair> checker = new SimplePointChecker<PointValuePair>(REL_TOL, ABS_TOL);
    switch (optimizer) {
    case CONJUGATE_GRADIENT:
        return new NonLinearConjugateGradientOptimizer(Formula.POLAK_RIBIERE, checker);
    case BOBYQA:// w  ww  .ja  v a 2 s  .  c  o m
        return new BOBYQAOptimizer(n + 2);
    case CMAES:
        return new CMAESOptimizer(MAX_ITER, 0., true, 0, 10,
                seed == null ? new Well19937c() : new Well19937c(seed), false,
                new SimplePointChecker<PointValuePair>(REL_TOL, ABS_TOL));
    case POWELL:
        return new PowellOptimizer(REL_TOL, ABS_TOL, checker);
    case SIMPLEX_MD:
    case SIMPLEX_NM:
        return new SimplexOptimizer(checker);
    default:
        throw new IllegalStateException("Should not be called");
    }
}

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