Package org.apache.commons.math3.optim

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


        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[] { 0, 0, 0 }));
        Assert.assertTrue(optimum.getValue() > 0.5);
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        NonLinearConjugateGradientOptimizer optimizer
            = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                      new SimpleValueChecker(1e-13, 1e-13),
                                                      1e-15, 1e-15, 1);
        PointValuePair optimum1
            = optimizer.optimize(new MaxEval(200),
                                 problem1.getObjectiveFunction(),
                                 problem1.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(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-3);
        Assert.assertEquals(1.0, optimum1.getPoint()[2], 1.0e-4);
        Assert.assertEquals(1.0, optimum1.getPoint()[3], 1.0e-4);

        LinearProblem problem2 = new LinearProblem(new double[][] {
                { 10.00, 7.00, 8.10, 7.20 },
                7.08, 5.04, 6.00, 5.00 },
                8.00, 5.98, 9.89, 9.00 },
                6.99, 4.99, 9.00, 9.98 }
        }, new double[] { 32, 23, 33, 31 });
        PointValuePair optimum2
            = optimizer.optimize(new MaxEval(200),
                                 problem2.getObjectiveFunction(),
                                 problem2.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(new double[] { 0, 1, 2, 3 }));
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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[] { 7, 6, 5, 4 }));
        Assert.assertEquals(0, optimum.getValue(), 1.0e-10);
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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[] { 2, 2, 2, 2, 2, 2 }));
        Assert.assertEquals(0, optimum.getValue(), 1.0e-10);
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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.assertEquals(2.0, optimum.getPoint()[0], 1.0e-8);
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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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