Example usage for org.apache.commons.math3.optim.nonlinear.vector.jacobian LevenbergMarquardtOptimizer LevenbergMarquardtOptimizer

Introduction

In this page you can find the example usage for org.apache.commons.math3.optim.nonlinear.vector.jacobian LevenbergMarquardtOptimizer LevenbergMarquardtOptimizer.

Prototype

public LevenbergMarquardtOptimizer(double initialStepBoundFactor,
        ConvergenceChecker<PointVectorValuePair> checker, double costRelativeTolerance,
        double parRelativeTolerance, double orthoTolerance, double threshold) 

Source Link

Document

Constructor that allows the specification of a custom convergence checker, in addition to the standard ones.

Usage

From source file:gdsc.utils.Cell_Outliner.java

/**
 * Find an ellipse that optimises the fit to the polygon detected edges.
 * /*from   ww w.ja  v  a  2  s  .  c  om*/
 * @param roi
 * @param params
 * @param weightMap
 * @param angle
 * @return
 */
private double[] fitPolygonalCell(PolygonRoi roi, double[] params, FloatProcessor weightMap,
        FloatProcessor angle) {
    // Get an estimate of the starting parameters using the current polygon
    double[] startPoint = params;
    startPoint = estimateStartPoint(roi, weightMap.getWidth(), weightMap.getHeight());

    int maxEval = 2000;
    final DifferentiableEllipticalFitFunction func = new DifferentiableEllipticalFitFunction(roi, weightMap);

    double relativeThreshold = 100 * Precision.EPSILON;
    double absoluteThreshold = 100 * Precision.SAFE_MIN;
    ConvergenceChecker<PointVectorValuePair> checker = new SimplePointChecker<PointVectorValuePair>(
            relativeThreshold, absoluteThreshold);
    double initialStepBoundFactor = 10;
    double costRelativeTolerance = 1e-10;
    double parRelativeTolerance = 1e-10;
    double orthoTolerance = 1e-10;
    double threshold = Precision.SAFE_MIN;

    LevenbergMarquardtOptimizer optimiser = new LevenbergMarquardtOptimizer(initialStepBoundFactor, checker,
            costRelativeTolerance, parRelativeTolerance, orthoTolerance, threshold);

    try {
        PointVectorValuePair solution = optimiser.optimize(new MaxIter(maxEval), new MaxEval(Integer.MAX_VALUE),
                new ModelFunctionJacobian(new MultivariateMatrixFunction() {
                    public double[][] value(double[] point) throws IllegalArgumentException {
                        return func.jacobian(point);
                    }
                }), new ModelFunction(func), new Target(func.calculateTarget()),
                new Weight(func.calculateWeights()), new InitialGuess(startPoint));

        if (debug)
            IJ.log(String.format("Eval = %d (Iter = %d), RMS = %f", optimiser.getEvaluations(),
                    optimiser.getIterations(), optimiser.getRMS()));
        return solution.getPointRef();
    } catch (Exception e) {
        IJ.log("Failed to find an elliptical solution, defaulting to polygon");
        e.printStackTrace();
    }

    return null;
}

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