Package org.apache.commons.math3.optimization

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

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        }, new double[] { 1, 1, 1});

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));

        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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        }, new double[] { 2, -9, 2, 2, 1 + epsilon * epsilon, 2});

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));

        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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        }, new double[] { 32, 23, 33, 31 });

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));

        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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        }, new double[] { 3.0, 1.0, 5.0 });

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));

        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.getPoint()[0], 1.0e-8);
        Assert.assertEquals(1.0, optimum.getPoint()[1], 1.0e-8);
    }
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            new LinearProblem(new double[][] { { 1, 0 }, { 0, 1 } }, new double[] { -1, 1 });

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));

        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);

        optimizer.optimize(100, problem, problem.target,
                           new double[] { 1 },
                           new double[] { 0, 0 });
    }
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            new LinearProblem(new double[][] { { 1, 0 }, { 0, 1 } }, new double[] { -1, 1 });

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));

        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);

        optimizer.optimize(100, problem, new double[] { 1 },
                           new double[] { 1 },
                           new double[] { 0, 0 });
    }
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        circle.addPoint( 45.0,  97.0);

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-13, 1.0e-13));

        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.assertEquals(1.768262623567235,  FastMath.sqrt(circle.getN()) * optimizer.getRMS(),  1.0e-10);
        Point2D.Double center = new Point2D.Double(optimum.getPointRef()[0], optimum.getPointRef()[1]);
        Assert.assertEquals(69.96016175359975, circle.getRadius(center), 1.0e-10);
        Assert.assertEquals(96.07590209601095, center.x, 1.0e-10);
        Assert.assertEquals(48.135167894714,   center.y, 1.0e-10);
    }
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        }

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));

        PointVectorValuePair optimum =
            optimizer.optimize(100, circle, target, weights, new double[] { 0, 0 });
        Assert.assertEquals(-0.1517383071957963, optimum.getPointRef()[0], 1.0e-6);
        Assert.assertEquals(0.2074999736353867,  optimum.getPointRef()[1], 1.0e-6);
        Assert.assertEquals(0.04268731682389561, optimizer.getRMS(),       1.0e-8);
    }
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    @Test
    public void testTrivial() {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1 }, new double[] { 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        try {
            optimizer.guessParametersErrors();
            Assert.fail("an exception should have been thrown");
        } catch (NumberIsTooSmallException ee) {
            // expected behavior
        }
        Assert.assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(3.0, optimum.getValue()[0], 1.0e-10);
    }
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        LinearProblem problem =
            new LinearProblem(new double[][] { { 1.0, -1.0 }, { 0.0, 2.0 }, { 1.0, -2.0 } },
                              new double[] { 4.0, 6.0, 1.0 });

        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(3.0, optimum.getPoint()[1], 1.0e-10);
        Assert.assertEquals(4.0, optimum.getValue()[0], 1.0e-10);
        Assert.assertEquals(6.0, optimum.getValue()[1], 1.0e-10);
        Assert.assertEquals(1.0, optimum.getValue()[2], 1.0e-10);
    }
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Related Classes of org.apache.commons.math3.optimization.PointVectorValuePair$DataTransferObject

  • 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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