Package org.apache.commons.math.optimization.general

Examples of org.apache.commons.math.optimization.general.GaussNewtonOptimizer

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    @Test
    public void testRedundantUnsolvable() {
        // Gauss-Newton should not be able to solve redundant information
        DifferentiableMultivariateVectorialOptimizer optimizer =
            new GaussNewtonOptimizer(true);
        checkUnsolvableProblem(optimizer, false);
    }
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    @Test
    public void testTrivial() throws FunctionEvaluationException, OptimizationException {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(16069223052l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
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    }

    @Test(expected = OptimizationException.class)
    public void testNoOptimum() throws FunctionEvaluationException, OptimizationException {
        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(12373523445l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
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     * @param yDegree Degree of the polynomial fitting functions along the
     * y-dimension.
     */
    public SmoothingPolynomialBicubicSplineInterpolator(int xDegree,
                                                        int yDegree) {
        xFitter = new PolynomialFitter(xDegree, new GaussNewtonOptimizer(false));
        yFitter = new PolynomialFitter(yDegree, new GaussNewtonOptimizer(false));
    }
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    @Test
    public void testTrivial() throws FunctionEvaluationException, OptimizationException {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(16069223052l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
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    }

    @Test(expected = OptimizationException.class)
    public void testNoOptimum() throws FunctionEvaluationException, OptimizationException {
        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(12373523445l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
View Full Code Here
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    @Test
    public void testRedundantUnsolvable() {
        // Gauss-Newton should not be able to solve redundant information
        DifferentiableMultivariateVectorialOptimizer optimizer =
            new GaussNewtonOptimizer(true);
        checkUnsolvableProblem(optimizer, false);
    }
View Full Code Here
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    @Test
    public void testTrivial() throws FunctionEvaluationException, OptimizationException {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(16069223052l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
View Full Code Here
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    }

    @Test(expected = OptimizationException.class)
    public void testNoOptimum() throws FunctionEvaluationException, OptimizationException {
        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(12373523445l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
View Full Code Here
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    @Test
    public void testRedundantUnsolvable() {
        // Gauss-Newton should not be able to solve redundant information
        DifferentiableMultivariateVectorialOptimizer optimizer =
            new GaussNewtonOptimizer(true);
        checkUnsolvableProblem(optimizer, false);
    }
View Full Code Here
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