1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.apache.commons.math4.legacy.analysis.differentiation;
18
19 import org.apache.commons.math4.legacy.analysis.MultivariateVectorFunction;
20
21 /** Class representing the gradient of a multivariate function.
22 * <p>
23 * The vectorial components of the function represent the derivatives
24 * with respect to each function parameters.
25 * </p>
26 * @since 3.1
27 */
28 public class GradientFunction implements MultivariateVectorFunction {
29
30 /** Underlying real-valued function. */
31 private final MultivariateDifferentiableFunction f;
32
33 /** Simple constructor.
34 * @param f underlying real-valued function
35 */
36 public GradientFunction(final MultivariateDifferentiableFunction f) {
37 this.f = f;
38 }
39
40 /** {@inheritDoc} */
41 @Override
42 public double[] value(double[] point) {
43
44 // set up parameters
45 final DerivativeStructure[] dsX = new DerivativeStructure[point.length];
46 for (int i = 0; i < point.length; ++i) {
47 dsX[i] = new DerivativeStructure(point.length, 1, i, point[i]);
48 }
49
50 // compute the derivatives
51 final DerivativeStructure dsY = f.value(dsX);
52
53 // extract the gradient
54 final double[] y = new double[point.length];
55 final int[] orders = new int[point.length];
56 for (int i = 0; i < point.length; ++i) {
57 orders[i] = 1;
58 y[i] = dsY.getPartialDerivative(orders);
59 orders[i] = 0;
60 }
61
62 return y;
63 }
64 }