Package org.apache.commons.math3.optim

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

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            = optimizer.optimize(new MaxEval(100),
                                 problem.getModelFunction(),
                                 problem.getModelFunctionJacobian(),
                                 new Target(data[1]),
                                 new Weight(w),
                                 new InitialGuess(initial));

        final double[] actual = optimum.getPoint();
        for (int i = 0; i < actual.length; i++) {
            double expected = dataset.getParameter(i);
            double delta = FastMath.abs(errParams * expected);
 
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                                                      1e-3, 1e-3, 1);
        optimizer.optimize(new MaxEval(100),
                           problem.getObjectiveFunction(),
                           problem.getObjectiveFunctionGradient(),
                           GoalType.MINIMIZE,
                           new InitialGuess(new double[] { 0 }),
                           new SimpleBounds(new double[] { -1 },
                                            new double[] { 1 }));
    }
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        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(new double[] { 0 }));
        Assert.assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(0.0, optimum.getValue(), 1.0e-10);

        // Check that the number of iterations is updated (MATH-949).
        Assert.assertTrue(optimizer.getIterations() > 0);
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        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(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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        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(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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        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(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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        PointValuePair optimum
            = optimizer.optimize(new MaxEval(100),
                                 problem.getObjectiveFunction(),
                                 problem.getObjectiveFunctionGradient(),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(new double[] { 0, 0, 0, 0, 0, 0 }));

        final double[] result = optimum.getPoint();
        final double[] expected = {3, 4, -1, -2, 1 + epsilon, 1 - epsilon};

        Assert.assertEquals(expected[0], result[0], 1.0e-7);
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        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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        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 }));

        final double[] result2 = optimum2.getPoint();
        final double[] expected2 = {-81, 137, -34, 22};

        Assert.assertEquals(expected2[0], result2[0], 2);
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        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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Related Classes of org.apache.commons.math3.optim.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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