Package org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer

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

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        LinearProblem problem
                = new LinearProblem(new double[][]{{2}},
                new double[]{3});
        LeastSquaresProblem ls = problem.getBuilder().build();

        Optimum optimum = optimizer.optimize(ls);

        Assert.assertEquals(0, optimum.getRMS(), TOl);
        assertEquals(TOl, optimum.getPoint(), 1.5);
        Assert.assertEquals(0.0, optimum.getResiduals().getEntry(0), TOl);
    }
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    public void testQRColumnsPermutation() {
        LinearProblem problem
                = new LinearProblem(new double[][]{{1, -1}, {0, 2}, {1, -2}},
                new double[]{4, 6, 1});

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

        Assert.assertEquals(0, optimum.getRMS(), TOl);
        assertEquals(TOl, optimum.getPoint(), 7, 3);
        assertEquals(TOl, optimum.getResiduals(), 0, 0, 0);
    }
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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, 1.1, 2.2, 3.3, 4.4, 5.5});

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

        Assert.assertEquals(0, optimum.getRMS(), TOl);
        for (int i = 0; i < problem.target.length; ++i) {
            Assert.assertEquals(0.55 * i, optimum.getPoint().getEntry(i), TOl);
        }
    }
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                {1, 0, 0},
                {-1, 1, 0},
                {0, -1, 1}
        }, new double[]{1, 1, 1});

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

        Assert.assertEquals(0, optimum.getRMS(), TOl);
        assertEquals(TOl, optimum.getPoint(), 1, 2, 3);
    }
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                {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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                {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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                {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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                {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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                {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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                {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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Related Classes of org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum

  • 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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