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 */ 017 package org.apache.commons.math3.optim.nonlinear.vector; 018 019 import org.apache.commons.math3.analysis.MultivariateMatrixFunction; 020 import org.apache.commons.math3.optim.ConvergenceChecker; 021 import org.apache.commons.math3.optim.OptimizationData; 022 import org.apache.commons.math3.optim.PointVectorValuePair; 023 import org.apache.commons.math3.exception.TooManyEvaluationsException; 024 import org.apache.commons.math3.exception.DimensionMismatchException; 025 026 /** 027 * Base class for implementing optimizers for multivariate vector 028 * differentiable functions. 029 * It contains boiler-plate code for dealing with Jacobian evaluation. 030 * It assumes that the rows of the Jacobian matrix iterate on the model 031 * functions while the columns iterate on the parameters; thus, the numbers 032 * of rows is equal to the dimension of the {@link Target} while the 033 * number of columns is equal to the dimension of the 034 * {@link org.apache.commons.math3.optim.InitialGuess InitialGuess}. 035 * 036 * @version $Id$ 037 * @since 3.1 038 */ 039 public abstract class JacobianMultivariateVectorOptimizer 040 extends MultivariateVectorOptimizer { 041 /** 042 * Jacobian of the model function. 043 */ 044 private MultivariateMatrixFunction jacobian; 045 046 /** 047 * @param checker Convergence checker. 048 */ 049 protected JacobianMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker) { 050 super(checker); 051 } 052 053 /** 054 * Computes the Jacobian matrix. 055 * 056 * @param params Point at which the Jacobian must be evaluated. 057 * @return the Jacobian at the specified point. 058 */ 059 protected double[][] computeJacobian(final double[] params) { 060 return jacobian.value(params); 061 } 062 063 /** 064 * {@inheritDoc} 065 * 066 * @param optData Optimization data. The following data will be looked for: 067 * <ul> 068 * <li>{@link org.apache.commons.math3.optim.MaxEval}</li> 069 * <li>{@link org.apache.commons.math3.optim.InitialGuess}</li> 070 * <li>{@link org.apache.commons.math3.optim.SimpleBounds}</li> 071 * <li>{@link Target}</li> 072 * <li>{@link Weight}</li> 073 * <li>{@link ModelFunction}</li> 074 * <li>{@link ModelFunctionJacobian}</li> 075 * </ul> 076 * @return {@inheritDoc} 077 * @throws TooManyEvaluationsException if the maximal number of 078 * evaluations is exceeded. 079 * @throws DimensionMismatchException if the initial guess, target, and weight 080 * arguments have inconsistent dimensions. 081 */ 082 @Override 083 public PointVectorValuePair optimize(OptimizationData... optData) 084 throws TooManyEvaluationsException, 085 DimensionMismatchException { 086 // Retrieve settings. 087 parseOptimizationData(optData); 088 // Set up base class and perform computation. 089 return super.optimize(optData); 090 } 091 092 /** 093 * Scans the list of (required and optional) optimization data that 094 * characterize the problem. 095 * 096 * @param optData Optimization data. 097 * The following data will be looked for: 098 * <ul> 099 * <li>{@link ModelFunctionJacobian}</li> 100 * </ul> 101 */ 102 private void parseOptimizationData(OptimizationData... optData) { 103 // The existing values (as set by the previous call) are reused if 104 // not provided in the argument list. 105 for (OptimizationData data : optData) { 106 if (data instanceof ModelFunctionJacobian) { 107 jacobian = ((ModelFunctionJacobian) data).getModelFunctionJacobian(); 108 // If more data must be parsed, this statement _must_ be 109 // changed to "continue". 110 break; 111 } 112 } 113 } 114 }