Example usage for org.apache.commons.math.optimization.general LevenbergMarquardtOptimizer getChiSquare

Introduction

In this page you can find the example usage for org.apache.commons.math.optimization.general LevenbergMarquardtOptimizer getChiSquare.

Prototype

public double getChiSquare() 

Source Link

Document

Get a Chi-Square-like value assuming the N residuals follow N distinct normal distributions centered on 0 and whose variances are the reciprocal of the weights.

Usage

From source file:uk.ac.diamond.scisoft.analysis.fitting.AngleDerivativeFunction.java

/**
 * Fit points given by x, y datasets to an ellipse. If no initial parameters are given, then
 * an algebraic fit is performed then a non-linear least squares fitting routine is used to
 * provide the best geometric fit.//  w  ww.  j  a va 2 s .  c  o  m
 * @param x
 * @param y
 * @param init parameters (can be null)
 */
public void geometricFit(AbstractDataset x, AbstractDataset y, double[] init) {

    if (x.getSize() < PARAMETERS || y.getSize() < PARAMETERS) {
        throw new IllegalArgumentException("Need " + PARAMETERS + " or more points");
    }

    if (init == null)
        init = quickfit(x, y);
    else if (init.length < PARAMETERS)
        throw new IllegalArgumentException("Need " + PARAMETERS + " parameters");

    EllipseCoordinatesFunction f = new EllipseCoordinatesFunction(x, y);
    LevenbergMarquardtOptimizer opt = new LevenbergMarquardtOptimizer();

    try {
        VectorialPointValuePair result = opt.optimize(f, f.getTarget(), f.getWeight(),
                f.calcAllInitValues(init));

        double[] point = result.getPointRef();
        parameters[0] = point[0] * point[0];
        parameters[1] = point[1] * point[1];
        for (int i = 2; i < PARAMETERS; i++)
            parameters[i] = point[i];

        logger.info("Ellipse fit: rms = {}, x^2 = {}", opt.getRMS(), opt.getChiSquare());
    } catch (FunctionEvaluationException e) {
        // cannot happen
    } catch (IllegalArgumentException e) {
        // should not happen!
    } catch (ConvergenceException e) {
        throw new IllegalArgumentException("Problem with optimizer converging");
    }
}

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