How to use Java Math Commons CurveFitter?

, , i80and , ( SO-), Apache Math ( ). DerivativeStructure.

i80and DerivativeStructure class:

//Everything stays the same except for the Jacobian Matrix

import java.util.*;
import org.apache.commons.math3.analysis.ParametricUnivariateFunction;
import org.apache.commons.math3.fitting.AbstractCurveFitter;
import org.apache.commons.math3.fitting.leastsquares.LeastSquaresBuilder;
import org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem;
import org.apache.commons.math3.fitting.WeightedObservedPoint;
import org.apache.commons.math3.linear.DiagonalMatrix;
import org.apache.commons.math3.analysis.differentiation.DerivativeStructure;

class MyFunc implements ParametricUnivariateFunction {
    public double value(double t, double... parameters) {
        return parameters[0] * Math.pow(t, parameters[1]) * Math.exp(-parameters[2] * t);
    }

    // Jacobian matrix of the above. In this case, this is just an array of
    // partial derivatives of the above function, with one element for each parameter.
    public double[] gradient(double t, double... parameters) {
        final double a = parameters[0];
        final double b = parameters[1];
        final double c = parameters[2];

        // Jacobian Matrix Edit

        // Using Derivative Structures...
        // constructor takes 4 arguments - the number of parameters in your
        // equation to be differentiated (3 in this case), the order of
        // differentiation for the DerivativeStructure, the index of the
        // parameter represented by the DS, and the value of the parameter itself
        DerivativeStructure aDev = new DerivativeStructure(3, 1, 0, a);
        DerivativeStructure bDev = new DerivativeStructure(3, 1, 1, b);
        DerivativeStructure cDev = new DerivativeStructure(3, 1, 2, c);

        // define the equation to be differentiated using another DerivativeStructure
        DerivativeStructure y = aDev.multiply(DerivativeStructure.pow(t, bDev))
                .multiply(cDev.negate().multiply(t).exp());

        // then return the partial derivatives required
        // notice the format, 3 arguments for the method since 3 parameters were
        // specified first order derivative of the first parameter, then the second, 
        // then the third
        return new double[] {
                y.getPartialDerivative(1, 0, 0),
                y.getPartialDerivative(0, 1, 0),
                y.getPartialDerivative(0, 0, 1)
        };

    }
}

public class MyFuncFitter extends AbstractCurveFitter {
    protected LeastSquaresProblem getProblem(Collection<WeightedObservedPoint> points) {
        final int len = points.size();
        final double[] target  = new double[len];
        final double[] weights = new double[len];
        final double[] initialGuess = { 1.0, 1.0, 1.0 };

        int i = 0;
        for(WeightedObservedPoint point : points) {
            target[i]  = point.getY();
            weights[i] = point.getWeight();
            i += 1;
        }

        final AbstractCurveFitter.TheoreticalValuesFunction model = new
                AbstractCurveFitter.TheoreticalValuesFunction(new MyFunc(), points);

        return new LeastSquaresBuilder().
                maxEvaluations(Integer.MAX_VALUE).
                maxIterations(Integer.MAX_VALUE).
                start(initialGuess).
                target(target).
                weight(new DiagonalMatrix(weights)).
                model(model.getModelFunction(), model.getModelFunctionJacobian()).
                build();
    }

    public static void main(String[] args) {
        MyFuncFitter fitter = new MyFuncFitter();
        ArrayList<WeightedObservedPoint> points = new ArrayList<WeightedObservedPoint>();

        // Add points here; for instance,
        WeightedObservedPoint point = new WeightedObservedPoint(1.0,
                1.0,
                1.0);
        points.add(point);

        final double coeffs[] = fitter.fit(points);
        System.out.println(Arrays.toString(coeffs));
    }
}

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// specify the required order as the second argument, say second order so 2
DerivativeStructure aDev = new DerivativeStructure(3, 2, 0, a);        
DerivativeStructure bDev = new DerivativeStructure(3, 2, 1, b);
DerivativeStructure cDev = new DerivativeStructure(3, 2, 2, c);

// and then specify the order again here
y.getPartialDerivative(2, 0, 0),
y.getPartialDerivative(0, 2, 0),
y.getPartialDerivative(0, 0, 2)

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