Package org.apache.commons.math3.optim

Examples of org.apache.commons.math3.optim.MaxEval

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        NonLinearConjugateGradientOptimizer optimizer
            = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                      new SimpleValueChecker(1e-6, 1e-6),
                                                      1e-3, 1e-3, 1);
        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(new double[] { 1, 1 }));
        Assert.assertTrue(optimum.getValue() > 0.1);
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        NonLinearConjugateGradientOptimizer optimizer
           = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                     new SimpleValueChecker(1e-30, 1e-30),
                                                     1e-15, 1e-13, 1);
        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(new double[] { 98.680, 47.345 }));
        Vector2D center = new Vector2D(optimum.getPointRef()[0], optimum.getPointRef()[1]);
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        return new LevenbergMarquardtOptimizer();
    }

    @Test(expected=MathUnsupportedOperationException.class)
    public void testConstraintsUnsupported() {
        createOptimizer().optimize(new MaxEval(100),
                                   new Target(new double[] { 2 }),
                                   new Weight(new double[] { 1 }),
                                   new InitialGuess(new double[] { 1, 2 }),
                                   new SimpleBounds(new double[] { -10, 0 },
                                                    new double[] { 20, 30 }));
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                { -3, 0, -9 }
        }, new double[] { 1, 1, 1 });

        AbstractLeastSquaresOptimizer optimizer = createOptimizer();
        PointVectorValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getModelFunction(),
                                 problem.getModelFunctionJacobian(),
                                 problem.getTarget(),
                                 new Weight(new double[] { 1, 1, 1 }),
                                 new InitialGuess(new double[] { 0, 0, 0 }));
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                = new LevenbergMarquardtOptimizer(initialStepBoundFactor,
                                                  costRelativeTolerance,
                                                  parRelativeTolerance,
                                                  orthoTolerance,
                                                  Precision.SAFE_MIN);
            optimizer.optimize(new MaxEval(maxCostEval),
                               problem,
                               problemJacobian,
                               new Target(new double[] { 0, 0, 0, 0, 0 }),
                               new Weight(new double[] { 1, 1, 1, 1, 1 }),
                               new InitialGuess(new double[] { 98.680, 47.345 }));
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        final LevenbergMarquardtOptimizer optimizer
            = new LevenbergMarquardtOptimizer();

        final PointVectorValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getModelFunction(),
                                 problem.getModelFunctionJacobian(),
                                 new Target(dataPoints[1]),
                                 new Weight(weights),
                                 new InitialGuess(new double[] { 10, 900, 80, 27, 225 }));
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        // First guess for the center's coordinates and radius.
        final double[] init = { 90, 659, 115 };

        final LevenbergMarquardtOptimizer optimizer
            = new LevenbergMarquardtOptimizer();
        final PointVectorValuePair optimum = optimizer.optimize(new MaxEval(100),
                                                                circle.getModelFunction(),
                                                                circle.getModelFunctionJacobian(),
                                                                new Target(circle.target()),
                                                                new Weight(circle.weight()),
                                                                new InitialGuess(init));
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    @Test
    public void testSinMin() {
        UnivariateFunction f = new Sin();
        UnivariateOptimizer optimizer = new BrentOptimizer(1e-10, 1e-14);
        Assert.assertEquals(3 * Math.PI / 2, optimizer.optimize(new MaxEval(200),
                                                                new UnivariateObjectiveFunction(f),
                                                                GoalType.MINIMIZE,
                                                                new SearchInterval(4, 5)).getPoint(), 1e-8);
        Assert.assertTrue(optimizer.getEvaluations() <= 50);
        Assert.assertEquals(200, optimizer.getMaxEvaluations());
        Assert.assertEquals(3 * Math.PI / 2, optimizer.optimize(new MaxEval(200),
                                                                new UnivariateObjectiveFunction(f),
                                                                GoalType.MINIMIZE,
                                                                new SearchInterval(1, 5)).getPoint(), 1e-8);
        Assert.assertTrue(optimizer.getEvaluations() <= 100);
        Assert.assertTrue(optimizer.getEvaluations() >= 15);
        try {
            optimizer.optimize(new MaxEval(10),
                               new UnivariateObjectiveFunction(f),
                               GoalType.MINIMIZE,
                               new SearchInterval(4, 5));
            Assert.fail("an exception should have been thrown");
        } catch (TooManyEvaluationsException fee) {
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        final ConvergenceChecker<UnivariatePointValuePair> checker = new SimpleUnivariateValueChecker(1e-5, 1e-14);
        // The default stopping criterion of Brent's algorithm should not
        // pass, but the search will stop at the given relative tolerance
        // for the function value.
        final UnivariateOptimizer optimizer = new BrentOptimizer(1e-10, 1e-14, checker);
        final UnivariatePointValuePair result = optimizer.optimize(new MaxEval(200),
                                                                   new UnivariateObjectiveFunction(f),
                                                                   GoalType.MINIMIZE,
                                                                   new SearchInterval(4, 5));
        Assert.assertEquals(3 * Math.PI / 2, result.getPoint(), 1e-3);
    }
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                }
            }
        };
        UnivariateOptimizer optimizer = new BrentOptimizer(1e-10, 1e-14);
        Assert.assertEquals(lower,
                            optimizer.optimize(new MaxEval(100),
                                               new UnivariateObjectiveFunction(f),
                                               GoalType.MINIMIZE,
                                               new SearchInterval(lower, upper)).getPoint(),
                            1.0e-8);
        Assert.assertEquals(upper,
                            optimizer.optimize(new MaxEval(100),
                                               new UnivariateObjectiveFunction(f),
                                               GoalType.MAXIMIZE,
                                               new SearchInterval(lower, upper)).getPoint(),
                            1.0e-8);
    }
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Related Classes of org.apache.commons.math3.optim.MaxEval

  • 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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