001/* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017package org.apache.commons.math3.analysis.differentiation; 018 019import org.apache.commons.math3.analysis.MultivariateMatrixFunction; 020 021/** Class representing the Jacobian of a multivariate vector function. 022 * <p> 023 * The rows iterate on the model functions while the columns iterate on the parameters; thus, 024 * the numbers of rows is equal to the dimension of the underlying function vector 025 * value and the number of columns is equal to the number of free parameters of 026 * the underlying function. 027 * </p> 028 * @since 3.1 029 */ 030public class JacobianFunction implements MultivariateMatrixFunction { 031 032 /** Underlying vector-valued function. */ 033 private final MultivariateDifferentiableVectorFunction f; 034 035 /** Simple constructor. 036 * @param f underlying vector-valued function 037 */ 038 public JacobianFunction(final MultivariateDifferentiableVectorFunction f) { 039 this.f = f; 040 } 041 042 /** {@inheritDoc} */ 043 public double[][] value(double[] point) { 044 045 // set up parameters 046 final DerivativeStructure[] dsX = new DerivativeStructure[point.length]; 047 for (int i = 0; i < point.length; ++i) { 048 dsX[i] = new DerivativeStructure(point.length, 1, i, point[i]); 049 } 050 051 // compute the derivatives 052 final DerivativeStructure[] dsY = f.value(dsX); 053 054 // extract the Jacobian 055 final double[][] y = new double[dsY.length][point.length]; 056 final int[] orders = new int[point.length]; 057 for (int i = 0; i < dsY.length; ++i) { 058 for (int j = 0; j < point.length; ++j) { 059 orders[j] = 1; 060 y[i][j] = dsY[i].getPartialDerivative(orders); 061 orders[j] = 0; 062 } 063 } 064 065 return y; 066 067 } 068 069}