Examples of Optimum

org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum
Weight matrix of the residuals between model and observations.
Immutable class. @version $Id: Weight.java 1416643 2012-12-03 19:37:14Z tn $ @since 3.1

Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

                {0, -3, -12, -1, 0, 0},
                {0, 0, 0, 0, epsilon, 1},
                {0, 0, 0, 0, 1, 1}
        }, new double[]{2, -9, 2, 2, 1 + epsilon * epsilon, 2});


        Optimum optimum = optimizer.optimize(problem.getBuilder().build());


        Assert.assertEquals(0, optimum.getRMS(), TOl);
        assertEquals(TOl, optimum.getPoint(), 3, 4, -1, -2, 1 + epsilon, 1 - epsilon);
    }

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

                {8, 6, 10, 9},
                {7, 5, 9, 10}
        }, new double[]{32, 23, 33, 31});
        final double[] start = {0, 1, 2, 3};


        Optimum optimum = optimizer
                .optimize(problem1.getBuilder().start(start).build());


        Assert.assertEquals(0, optimum.getRMS(), TOl);
        assertEquals(TOl, optimum.getPoint(), 1, 1, 1, 1);


        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});


        optimum = optimizer.optimize(problem2.getBuilder().start(start).build());


        Assert.assertEquals(0, optimum.getRMS(), TOl);
        assertEquals(1e-8, optimum.getPoint(), -81, 137, -34, 22);
    }

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

                {3, 2, 0, 0},
                {0, 1, -1, 1},
                {2, 0, 1, 0}
        }, new double[]{7, 3, 5});


        Optimum optimum = optimizer
                .optimize(problem.getBuilder().start(new double[]{7, 6, 5, 4}).build());


        Assert.assertEquals(0, optimum.getRMS(), TOl);
    }

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

                {0, 0, 0, 0, 1, -1},
                {0, 0, -1, 1, 0, 1},
                {0, 0, 0, -1, 1, 0}
        }, new double[]{3, 12, -1, 7, 1});


        Optimum optimum = optimizer.optimize(
                problem.getBuilder().start(new double[]{2, 2, 2, 2, 2, 2}).build());


        Assert.assertEquals(0, optimum.getRMS(), TOl);
        RealVector point = optimum.getPoint();
        //the first two elements are under constrained
        //check first two elements obey the constraint: sum to 3
        Assert.assertEquals(3, point.getEntry(0) + point.getEntry(1), TOl);
        //#constrains = #states fro the last 4 elements
        assertEquals(TOl, point.getSubVector(2, 4), 3, 4, 5, 6);

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

                {1, 1},
                {1, -1},
                {1, 3}
        }, new double[]{3, 1, 5});


        Optimum optimum = optimizer
                .optimize(problem.getBuilder().start(new double[]{1, 1}).build());


        Assert.assertEquals(0, optimum.getRMS(), TOl);
        assertEquals(TOl, optimum.getPoint(), 2, 1);
    }

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

                {1, 1},
                {1, -1},
                {1, 3}
        }, new double[]{3, 1, 4});


        Optimum optimum = optimizer
                .optimize(problem.getBuilder().start(new double[]{1, 1}).build());


        //TODO what is this actually testing?
        Assert.assertTrue(optimum.getRMS() > 0.1);
    }

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

                    = new LinearProblem(new double[][]{{1, 0},
                    {0, 1}},
                    new double[]{-1, 1});


            //TODO why is this part here? hasn't it been tested already?
            Optimum optimum = optimizer.optimize(problem.getBuilder().build());


            Assert.assertEquals(0, optimum.getRMS(), TOl);
            assertEquals(TOl, optimum.getPoint(), -1, 1);


            //TODO move to builder test
            optimizer.optimize(
                    problem.getBuilder().weight(new DiagonalMatrix(new double[]{1})).build());

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

        try {
            LinearProblem problem
                    = new LinearProblem(new double[][]{{1, 0}, {0, 1}},
                    new double[]{-1, 1});


            Optimum optimum = optimizer.optimize(problem.getBuilder().build());


            Assert.assertEquals(0, optimum.getRMS(), TOl);
            assertEquals(TOl, optimum.getPoint(), -1, 1);


            //TODO move to builder test
            optimizer.optimize(
                    problem.getBuilder()
                            .target(new double[]{1})

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

        circle.addPoint(110, -20);
        circle.addPoint(35, 15);
        circle.addPoint(45, 97);
        final double[] start = {98.680, 47.345};


        Optimum optimum = optimizer.optimize(builder(circle).start(start).build());


        Assert.assertTrue(optimum.getEvaluations() < 10);


        double rms = optimum.getRMS();
        Assert.assertEquals(1.768262623567235, FastMath.sqrt(circle.getN()) * rms, TOl);


        Vector2D center = new Vector2D(optimum.getPoint().getEntry(0), optimum.getPoint().getEntry(1));
        Assert.assertEquals(69.96016176931406, circle.getRadius(center), 1e-6);
        Assert.assertEquals(96.07590211815305, center.getX(), 1e-6);
        Assert.assertEquals(48.13516790438953, center.getY(), 1e-6);


        double[][] cov = optimum.getCovariances(1e-14).getData();
        Assert.assertEquals(1.839, cov[0][0], 0.001);
        Assert.assertEquals(0.731, cov[0][1], 0.001);
        Assert.assertEquals(cov[0][1], cov[1][0], 1e-14);
        Assert.assertEquals(0.786, cov[1][1], 0.001);


        // add perfect measurements and check formal errors are reduced
        double r = circle.getRadius(center);
        for (double d = 0; d < 2 * FastMath.PI; d += 0.01) {
            circle.addPoint(center.getX() + r * FastMath.cos(d), center.getY() + r * FastMath.sin(d));
        }


        double[] weights = new double[circle.getN()];
        Arrays.fill(weights, 2);


        optimum = optimizer.optimize(
                builder(circle).weight(new DiagonalMatrix(weights)).start(start).build());


        cov = optimum.getCovariances(1e-14).getData();
        Assert.assertEquals(0.0016, cov[0][0], 0.001);
        Assert.assertEquals(3.2e-7, cov[0][1], 1e-9);
        Assert.assertEquals(cov[0][1], cov[1][0], 1e-14);
        Assert.assertEquals(0.0016, cov[1][1], 0.001);
    }

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Examples of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

        Arrays.fill(weights, 2);
        for (int i = 0; i < points.length; ++i) {
            circle.addPoint(points[i][0], points[i][1]);
        }


        Optimum optimum = optimizer.optimize(builder(circle).weight(new DiagonalMatrix(weights)).start(start).build());


        Vector2D center = new Vector2D(optimum.getPoint().getEntry(0), optimum.getPoint().getEntry(1));
        Assert.assertTrue(optimum.getEvaluations() < 25);
        Assert.assertEquals(0.043, optimum.getRMS(), 1e-3);
        Assert.assertEquals(0.292235, circle.getRadius(center), 1e-6);
        Assert.assertEquals(-0.151738, center.getX(), 1e-6);
        Assert.assertEquals(0.2075001, center.getY(), 1e-6);
    }

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