Examples of org.apache.commons.math3.analysis.solvers.BrentSolver

Package org.apache.commons.math3.analysis.solvers

Examples of org.apache.commons.math3.analysis.solvers.BrentSolver

org.apache.commons.math3.exception.DimensionMismatchException
orld.wolfram.com/BrentsMethod.html"> Brent algorithm for finding zeros of real univariate functions. The function should be continuous but not necessarily smooth. The {@code solve} method returns a zero {@code x} of the function {@code f}in the given interval {@code [a, b]} to within a tolerance{@code 6 eps abs(x) + t} where {@code eps} is the relative accuracy and{@code t} is the absolute accuracy.The given interval must bracket the root.

        };


        final double tolerance = 0.1;
        EventState es = new EventState(closeEventsGenerator, 1.5 * gap,
                                       tolerance, 100,
                                       new BrentSolver(tolerance));


        AbstractStepInterpolator interpolator =
            new DummyStepInterpolator(new double[0], new double[0], true);
        interpolator.storeTime(r1 - 2.5 * gap);
        interpolator.shift();

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                };


        NonLinearConjugateGradientOptimizer optimizer
           = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                     new SimpleValueChecker(1e-13, 1e-13),
                                                     new BrentSolver(),
                                                     preconditioner);


        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),

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                {  7.0, 5.0,  9.0, 10.0 }
        }, new double[] { 32, 23, 33, 31 });
        NonLinearConjugateGradientOptimizer optimizer
            = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                      new SimpleValueChecker(1e-13, 1e-13),
                                                      new BrentSolver(1e-15, 1e-15));
        PointValuePair optimum1
            = optimizer.optimize(new MaxEval(200),
                                 problem1.getObjectiveFunction(),
                                 problem1.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,

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        problem.addPoint( 35.0,  15.0);
        problem.addPoint( 45.0,  97.0);
        NonLinearConjugateGradientOptimizer optimizer
           = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                     new SimpleValueChecker(1e-30, 1e-30),
                                                     new BrentSolver(1e-15, 1e-13));
        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,

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        };


        final double tolerance = 0.1;
        EventState es = new EventState(closeEventsGenerator, 1.5 * gap,
                                       tolerance, 100,
                                       new BrentSolver(tolerance));


        AbstractStepInterpolator interpolator =
            new DummyStepInterpolator(new double[0], new double[0], true);
        interpolator.storeTime(r1 - 2.5 * gap);
        interpolator.shift();

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                };


        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-13, 1e-13),
                                                    new BrentSolver(),
                                                    preconditioner);
                                                    
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0, 0, 0, 0, 0 });
        Assert.assertEquals( 3.0, optimum.getPoint()[0], 1.0e-10);

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                {  7.0, 5.0,  9.0, 10.0 }
        }, new double[] { 32, 23, 33, 31 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-13, 1e-13),
                                                    new BrentSolver(1e-15, 1e-15));
        PointValuePair optimum1 =
            optimizer.optimize(200, problem1, GoalType.MINIMIZE, new double[] { 0, 1, 2, 3 });
        Assert.assertEquals(1.0, optimum1.getPoint()[0], 1.0e-4);
        Assert.assertEquals(1.0, optimum1.getPoint()[1], 1.0e-4);
        Assert.assertEquals(1.0, optimum1.getPoint()[2], 1.0e-4);

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        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-30, 1e-30),
                                                    new BrentSolver(1e-15, 1e-13));
        PointValuePair optimum =
            optimizer.optimize(100, circle, GoalType.MINIMIZE, new double[] { 98.680, 47.345 });
        Point2D.Double center = new Point2D.Double(optimum.getPointRef()[0], optimum.getPointRef()[1]);
        Assert.assertEquals(69.960161753, circle.getRadius(center), 1.0e-8);
        Assert.assertEquals(96.075902096, center.x, 1.0e-8);

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                        final double baseRoot = forward ?
                                                solver.solve(maxIterationCount, f, ta, tb) :
                                                solver.solve(maxIterationCount, f, tb, ta);
                        final int remainingEval = maxIterationCount - solver.getEvaluations();
                        BracketedUnivariateSolver<UnivariateFunction> bracketing =
                                new PegasusSolver(solver.getRelativeAccuracy(), solver.getAbsoluteAccuracy());
                        root = forward ?
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, ta, tb, AllowedSolution.RIGHT_SIDE) :
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, tb, ta, AllowedSolution.LEFT_SIDE);

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     * length.
     */
    protected double[] computeResiduals(double[] objectiveValue) {
        final double[] target = getTarget();
        if (objectiveValue.length != target.length) {
            throw new DimensionMismatchException(target.length,
                                                 objectiveValue.length);
        }


        final double[] residuals = new double[target.length];
        for (int i = 0; i < target.length; i++) {

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Related Classes of org.apache.commons.math3.analysis.solvers.BrentSolver

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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