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

Introduction

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

Prototype

public Sigma(double[] s) throws NotPositiveException 

Source Link

Usage

From source file:edu.cmu.tetrad.sem.GeneralizedSemEstimator.java

private double[] optimize(MultivariateFunction function, double[] values, int optimizer) {
    PointValuePair pair = null;/*  w w  w  . j a v a2  s  . c  o m*/

    if (optimizer == 1) {
        //            0.01, 0.000001
        //2.0D * FastMath.ulp(1.0D), 1e-8
        MultivariateOptimizer search = new PowellOptimizer(1e-7, 1e-7);
        pair = search.optimize(new InitialGuess(values), new ObjectiveFunction(function), GoalType.MINIMIZE,
                new MaxEval(100000));
    } else if (optimizer == 2) {
        MultivariateOptimizer search = new SimplexOptimizer(1e-7, 1e-7);
        pair = search.optimize(new InitialGuess(values), new ObjectiveFunction(function), GoalType.MINIMIZE,
                new MaxEval(100000), new NelderMeadSimplex(values.length));
    } else if (optimizer == 3) {
        int dim = values.length;
        int additionalInterpolationPoints = 0;
        final int numIterpolationPoints = 2 * dim + 1 + additionalInterpolationPoints;

        BOBYQAOptimizer search = new BOBYQAOptimizer(numIterpolationPoints);
        pair = search.optimize(new MaxEval(100000), new ObjectiveFunction(function), GoalType.MINIMIZE,
                new InitialGuess(values), SimpleBounds.unbounded(dim));
    } else if (optimizer == 4) {
        MultivariateOptimizer search = new CMAESOptimizer(3000000, .05, false, 0, 0, new MersenneTwister(),
                false, new SimplePointChecker<PointValuePair>(0.5, 0.5));
        pair = search.optimize(new MaxEval(30000), new ObjectiveFunction(function), GoalType.MINIMIZE,
                new InitialGuess(values), new CMAESOptimizer.Sigma(new double[values.length]),
                new CMAESOptimizer.PopulationSize(1000));
    } else if (optimizer == 5) {
        //            0.01, 0.000001
        //2.0D * FastMath.ulp(1.0D), 1e-8
        MultivariateOptimizer search = new PowellOptimizer(.05, .05);
        pair = search.optimize(new InitialGuess(values), new ObjectiveFunction(function), GoalType.MINIMIZE,
                new MaxEval(100000));
    } else if (optimizer == 6) {
        MultivariateOptimizer search = new PowellOptimizer(1e-7, 1e-7);
        pair = search.optimize(new InitialGuess(values), new ObjectiveFunction(function), GoalType.MAXIMIZE,
                new MaxEval(10000));
    }

    return pair.getPoint();
}

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