Package org.apache.commons.math3.optimization

Examples of org.apache.commons.math3.optimization.InitialGuess

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        final double[] uB = boundaries == null ? null : boundaries[1];
        final int numIterpolationPoints = 2 * dim + 1 + additionalInterpolationPoints;
        BOBYQAOptimizer optim = new BOBYQAOptimizer(numIterpolationPoints);
        PointValuePair result = boundaries == null ?
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint)) :
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint),
                           new SimpleBounds(lB, uB));
//        System.out.println(func.getClass().getName() + " = "
//              + optim.getEvaluations() + " f(");
//        for (double x: result.getPoint())  System.out.print(x + " ");
//        System.out.println(") = " +  result.getValue());
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                                                  0, new MersenneTwister(), false, null);
        final double[] lB = boundaries == null ? null : boundaries[0];
        final double[] uB = boundaries == null ? null : boundaries[1];
        PointValuePair result = boundaries == null ?
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint),
                           new CMAESOptimizer.Sigma(inSigma),
                           new CMAESOptimizer.PopulationSize(lambda)) :
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint),
                           new SimpleBounds(lB, uB),
                           new CMAESOptimizer.Sigma(inSigma),
                           new CMAESOptimizer.PopulationSize(lambda));
        // System.out.println("sol=" + Arrays.toString(result.getPoint()));
        Assert.assertEquals(expected.getValue(), result.getValue(), fTol);
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        }

        return optimizeInternal(maxEval, f,
                                new Target(t),
                                new Weight(w),
                                new InitialGuess(startPoint));
    }
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     * {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
     * @throws NotStrictlyPositiveException if {@code mean <= 0}.
     * @since 2.1
     */
    public ExponentialDistribution(double mean, double inverseCumAccuracy) {
        this(new Well19937c(), mean, inverseCumAccuracy);
    }
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     * @param upper Upper bound (inclusive) of this distribution.
     * @throws NumberIsTooLargeException if {@code lower >= upper}.
     */
    public UniformIntegerDistribution(int lower, int upper)
        throws NumberIsTooLargeException {
        this(new Well19937c(), lower, upper);
    }
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     * @throws NumberIsTooLargeException if {@code a >= b} or if {@code c > b}.
     * @throws NumberIsTooSmallException if {@code c < a}.
     */
    public TriangularDistribution(double a, double c, double b)
        throws NumberIsTooLargeException, NumberIsTooSmallException {
        this(new Well19937c(), a, c, b);
    }
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            dest.meanImpl = new Mean(dest.secondMoment);
        } else {
            dest.meanImpl = source.meanImpl.copy();
        }
        if (source.getGeoMeanImpl() instanceof GeometricMean) {
            dest.geoMeanImpl = new GeometricMean((SumOfLogs) dest.sumLogImpl);
        } else {
            dest.geoMeanImpl = source.geoMeanImpl.copy();
        }

        // Make sure that if stat == statImpl in source, same
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        for (int i = 0; i < k; ++i) {
            sumImpl[i]     = new Sum();
            sumSqImpl[i]   = new SumOfSquares();
            minImpl[i]     = new Min();
            maxImpl[i]     = new Max();
            sumLogImpl[i]  = new SumOfLogs();
            geoMeanImpl[i] = new GeometricMean();
            meanImpl[i]    = new Mean();
        }

        covarianceImpl =
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        geoMeanImpl = new StorelessUnivariateStatistic[k];
        meanImpl    = new StorelessUnivariateStatistic[k];

        for (int i = 0; i < k; ++i) {
            sumImpl[i]     = new Sum();
            sumSqImpl[i]   = new SumOfSquares();
            minImpl[i]     = new Min();
            maxImpl[i]     = new Max();
            sumLogImpl[i]  = new SumOfLogs();
            geoMeanImpl[i] = new GeometricMean();
            meanImpl[i]    = new Mean();
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     * @param checker Convergence checker.
     */
    protected BaseOptimizer(ConvergenceChecker<PAIR> checker) {
        this.checker = checker;

        evaluations = new Incrementor(0, new MaxEvalCallback());
        iterations = new Incrementor(0, new MaxIterCallback());
    }
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Related Classes of org.apache.commons.math3.optimization.InitialGuess

  • org.apache.commons.math3.analysis.differentiation.DerivativeStructure
  • org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction
  • org.apache.commons.math3.analysis.function.HarmonicOscillator
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
  • org.apache.commons.math3.analysis.solvers.BrentSolver
  • org.apache.commons.math3.analysis.UnivariateFunction
  • org.apache.commons.math3.complex.Complex
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