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 * https://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
18 /*
19 * This is not the original file distributed by the Apache Software Foundation
20 * It has been modified by the Hipparchus project
21 */
22 package org.hipparchus.analysis.differentiation;
23
24 import org.hipparchus.analysis.MultivariateMatrixFunction;
25
26 /** Class representing the Jacobian of a multivariate vector function.
27 * <p>
28 * The rows iterate on the model functions while the columns iterate on the parameters; thus,
29 * the numbers of rows is equal to the dimension of the underlying function vector
30 * value and the number of columns is equal to the number of free parameters of
31 * the underlying function.
32 * </p>
33 */
34 public class JacobianFunction implements MultivariateMatrixFunction {
35
36 /** Underlying vector-valued function. */
37 private final MultivariateDifferentiableVectorFunction f;
38
39 /** Simple constructor.
40 * @param f underlying vector-valued function
41 */
42 public JacobianFunction(final MultivariateDifferentiableVectorFunction f) {
43 this.f = f;
44 }
45
46 /** {@inheritDoc} */
47 @Override
48 public double[][] value(double[] point) {
49
50 // set up parameters
51 final DSFactory factory = new DSFactory(point.length, 1);
52 final DerivativeStructure[] dsX = new DerivativeStructure[point.length];
53 for (int i = 0; i < point.length; ++i) {
54 dsX[i] = factory.variable(i, point[i]);
55 }
56
57 // compute the derivatives
58 final DerivativeStructure[] dsY = f.value(dsX);
59
60 // extract the Jacobian
61 final double[][] y = new double[dsY.length][point.length];
62 final int[] orders = new int[point.length];
63 for (int i = 0; i < dsY.length; ++i) {
64 for (int j = 0; j < point.length; ++j) {
65 orders[j] = 1;
66 y[i][j] = dsY[i].getPartialDerivative(orders);
67 orders[j] = 0;
68 }
69 }
70
71 return y;
72
73 }
74
75 }