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 * this work for additional information regarding copyright ownership.
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 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.commons.math3.analysis.differentiation;

import org.apache.commons.math3.analysis.MultivariateMatrixFunction;

Class representing the Jacobian of a multivariate vector function.

The rows iterate on the model functions while the columns iterate on the parameters; thus,
the numbers of rows is equal to the dimension of the underlying function vector
value and the number of columns is equal to the number of free parameters of
the underlying function.

Since:
3.1/** Class representing the Jacobian of a multivariate vector function.
 * <p>
 * The rows iterate on the model functions while the columns iterate on the parameters; thus,
 * the numbers of rows is equal to the dimension of the underlying function vector
 * value and the number of columns is equal to the number of free parameters of
 * the underlying function.
 * </p>
 * @since 3.1
 */
public class JacobianFunction implements MultivariateMatrixFunction {

    
Underlying vector-valued function. /** Underlying vector-valued function. */
    private final MultivariateDifferentiableVectorFunction f;

    
Simple constructor.
Params:
f – underlying vector-valued function/** Simple constructor.
     * @param f underlying vector-valued function
     */
    public JacobianFunction(final MultivariateDifferentiableVectorFunction f) {
        this.f = f;
    }

    
{@inheritDoc} /** {@inheritDoc} */
    public double[][] value(double[] point) {

        // set up parameters
        final DerivativeStructure[] dsX = new DerivativeStructure[point.length];
        for (int i = 0; i < point.length; ++i) {
            dsX[i] = new DerivativeStructure(point.length, 1, i, point[i]);
        }

        // compute the derivatives
        final DerivativeStructure[] dsY = f.value(dsX);

        // extract the Jacobian
        final double[][] y = new double[dsY.length][point.length];
        final int[] orders = new int[point.length];
        for (int i = 0; i < dsY.length; ++i) {
            for (int j = 0; j < point.length; ++j) {
                orders[j] = 1;
                y[i][j] = dsY[i].getPartialDerivative(orders);
                orders[j] = 0;
            }
        }

        return y;

    }

}