Package org.apache.commons.math3.optimization

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


     * The convergence check is set to a {@link SimpleValueChecker}.
     * @deprecated See {@link SimpleValueChecker#SimpleValueChecker()}
     */
    @Deprecated
    protected BaseAbstractMultivariateOptimizer() {
        this(new SimpleValueChecker());
    }
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    public void testTrivial() {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0 });
        Assert.assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(0.0, optimum.getValue(), 1.0e-10);
    }
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            new LinearProblem(new double[][] { { 1.0, -1.0 }, { 0.0, 2.0 }, { 1.0, -2.0 } },
                              new double[] { 4.0, 6.0, 1.0 });

        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0 });
        Assert.assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
        Assert.assertEquals(0.0, optimum.getValue(), 1.0e-10);
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                { 0, 0, 0, 0, 2, 0 },
                { 0, 0, 0, 0, 0, 2 }
        }, new double[] { 0.0, 1.1, 2.2, 3.3, 4.4, 5.5 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0, 0, 0, 0, 0 });
        for (int i = 0; i < problem.target.length; ++i) {
            Assert.assertEquals(0.55 * i, optimum.getPoint()[i], 1.0e-10);
        }
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                { -11, 0 },
                0, -1, 1 }
        }, new double[] { 1, 1, 1});
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0, 0 });
        Assert.assertEquals(1.0, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(2.0, optimum.getPoint()[1], 1.0e-10);
        Assert.assertEquals(3.0, optimum.getPoint()[2], 1.0e-10);
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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 });
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                2, 13 },
                { -3, 0, -9 }
        }, new double[] { 1, 1, 1 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
                optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0, 0, 0 });
        Assert.assertTrue(optimum.getValue() > 0.5);
    }
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                8.0, 6.0, 10.09.0 },
                7.0, 5.09.0, 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);
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                { 2.0, 0.01.0, 0.0 }
        }, new double[] { 7.0, 3.0, 5.0 });

        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 7, 6, 5, 4 });
        Assert.assertEquals(0, optimum.getValue(), 1.0e-10);

    }
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                 { 0.0, 0.0, -1.01.0, 0.01.0 },
                 { 0.0, 0.00.0, -1.0, 1.00.0 }
        }, new double[] { 3.0, 12.0, -1.0, 7.0, 1.0 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 2, 2, 2, 2, 2, 2 });
        Assert.assertEquals(0, optimum.getValue(), 1.0e-10);
    }
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