Package org.apache.commons.math3.optimization

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

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                { 0, 0, 0, 2, 0, 0 },
                { 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 });
        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1, 1, 1, 1 },
                               new double[] { 0, 0, 0, 0, 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        for (int i = 0; i < problem.target.length; ++i) {
            Assert.assertEquals(0.55 * i, optimum.getPoint()[i], 1.0e-10);
        }
    }
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                {  1,  0, 0 },
                { -1,  1, 0 },
                {  0, -1, 1 }
        }, new double[] { 1, 1, 1});
        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 0, 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        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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                {  0,  0,   0,  0, epsilon, 1 },
                {  0,  0,   0,  0,       1, 1 }
        }, new double[] { 2, -9, 2, 2, 1 + epsilon * epsilon, 2});

        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1, 1, 1, 1 },
                               new double[] { 0, 0, 0, 0, 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals( 3.0, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals( 4.0, optimum.getPoint()[1], 1.0e-10);
        Assert.assertEquals(-1.0, optimum.getPoint()[2], 1.0e-10);
        Assert.assertEquals(-2.0, optimum.getPoint()[3], 1.0e-10);
        Assert.assertEquals( 1.0 + epsilon, optimum.getPoint()[4], 1.0e-10);
        Assert.assertEquals( 1.0 - epsilon, optimum.getPoint()[5], 1.0e-10);
    }
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                {  7.0, 5.0,  6.0,  5.0 },
                {  8.0, 6.0, 10.0,  9.0 },
                {  7.0, 5.0,  9.0, 10.0 }
        }, new double[] { 32, 23, 33, 31 });
        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum1 =
            optimizer.optimize(100, problem1, problem1.target, new double[] { 1, 1, 1, 1 },
                               new double[] { 0, 1, 2, 3 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(1.0, optimum1.getPoint()[0], 1.0e-10);
        Assert.assertEquals(1.0, optimum1.getPoint()[1], 1.0e-10);
        Assert.assertEquals(1.0, optimum1.getPoint()[2], 1.0e-10);
        Assert.assertEquals(1.0, optimum1.getPoint()[3], 1.0e-10);

        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 });
        PointVectorValuePair optimum2 =
            optimizer.optimize(100, problem2, problem2.target, new double[] { 1, 1, 1, 1 },
                               new double[] { 0, 1, 2, 3 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(-81.0, optimum2.getPoint()[0], 1.0e-8);
        Assert.assertEquals(137.0, optimum2.getPoint()[1], 1.0e-8);
        Assert.assertEquals(-34.0, optimum2.getPoint()[2], 1.0e-8);
        Assert.assertEquals( 22.0, optimum2.getPoint()[3], 1.0e-8);
    }
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                { 0.0, 0.0, -1.0,  1.0, 0.0,  1.0 },
                { 0.0, 0.0,  0.0, -1.0, 1.0,  0.0 }
       }, new double[] { 3.0, 12.0, -1.0, 7.0, 1.0 });

        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1, 1, 1 },
                               new double[] { 2, 2, 2, 2, 2, 2 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(3.0, optimum.getPointRef()[2], 1.0e-10);
        Assert.assertEquals(4.0, optimum.getPointRef()[3], 1.0e-10);
        Assert.assertEquals(5.0, optimum.getPointRef()[4], 1.0e-10);
        Assert.assertEquals(6.0, optimum.getPointRef()[5], 1.0e-10);
    }
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                { 1.0, -1.0 },
                { 1.0,  3.0 }
        }, new double[] { 3.0, 1.0, 5.0 });

        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1 },
                               new double[] { 1, 1 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(2.0, optimum.getPointRef()[0], 1.0e-10);
        Assert.assertEquals(1.0, optimum.getPointRef()[1], 1.0e-10);
    }
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    public void testInconsistentSizes() {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 1, 0 }, { 0, 1 } }, new double[] { -1, 1 });
        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();

        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1 }, new double[] { 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(-1, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(+1, optimum.getPoint()[1], 1.0e-10);

        try {
            optimizer.optimize(100, problem, problem.target,
                               new double[] { 1 },
                               new double[] { 0, 0 });
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        circle.addPoint( 50.0,  -6.0);
        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);
        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, circle, new double[] { 0, 0, 0, 0, 0 }, new double[] { 1, 1, 1, 1, 1 },
                               new double[] { 98.680, 47.345 });
        Assert.assertTrue(optimizer.getEvaluations() < 10);
        Assert.assertTrue(optimizer.getJacobianEvaluations() < 10);
        double rms = optimizer.getRMS();
        Assert.assertEquals(1.768262623567235,  FastMath.sqrt(circle.getN()) * rms,  1.0e-10);
        Point2D.Double center = new Point2D.Double(optimum.getPointRef()[0], optimum.getPointRef()[1]);
        Assert.assertEquals(69.96016176931406, circle.getRadius(center), 1.0e-10);
        Assert.assertEquals(96.07590211815305, center.x,      1.0e-10);
        Assert.assertEquals(48.13516790438953, center.y,      1.0e-10);
        double[][] cov = optimizer.getCovariances();
        Assert.assertEquals(1.839, cov[0][0], 0.001);
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        for (int i = 0; i < points.length; ++i) {
            circle.addPoint(points[i][0], points[i][1]);
        }
        LevenbergMarquardtOptimizer optimizer
            = new LevenbergMarquardtOptimizer(new SimpleVectorValueChecker(1.0e-8, 1.0e-8));
        PointVectorValuePair optimum =
            optimizer.optimize(100, circle, target, weights, new double[] { -12, -12 });
        Point2D.Double center = new Point2D.Double(optimum.getPointRef()[0], optimum.getPointRef()[1]);
        Assert.assertTrue(optimizer.getEvaluations() < 25);
        Assert.assertTrue(optimizer.getJacobianEvaluations() < 20);
        Assert.assertEquals( 0.043, optimizer.getRMS(), 1.0e-3);
        Assert.assertEquals( 0.292235,  circle.getRadius(center), 1.0e-6);
        Assert.assertEquals(-0.151738,  center.x,      1.0e-6);
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     * @param checker Convergence checker.
     */
    protected BaseOptimizer(ConvergenceChecker<PAIR> checker) {
        this.checker = checker;

        evaluations = new Incrementor(0, new MaxEvalCallback());
        iterations = new Incrementor(0, new MaxIterCallback());
    }
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Related Classes of org.apache.commons.math3.optimization.PointVectorValuePair

  • 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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