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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (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
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math3.analysis.differentiation;

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

/** Class representing the gradient of a multivariate function.
 * 

* The vectorial components of the function represent the derivatives * with respect to each function parameters. *

* @since 3.1 */ public class GradientFunction implements MultivariateVectorFunction { /** Underlying real-valued function. */ private final MultivariateDifferentiableFunction f; /** Simple constructor. * @param f underlying real-valued function */ public GradientFunction(final MultivariateDifferentiableFunction f) { this.f = f; } /** {@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 gradient final double[] y = new double[point.length]; final int[] orders = new int[point.length]; for (int i = 0; i < point.length; ++i) { orders[i] = 1; y[i] = dsY.getPartialDerivative(orders); orders[i] = 0; } return y; } }




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