| /* |
| * 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.math4.optim.nonlinear.scalar; |
| |
| import org.apache.commons.math4.analysis.MultivariateVectorFunction; |
| import org.apache.commons.math4.exception.TooManyEvaluationsException; |
| import org.apache.commons.math4.optim.ConvergenceChecker; |
| import org.apache.commons.math4.optim.OptimizationData; |
| import org.apache.commons.math4.optim.PointValuePair; |
| |
| /** |
| * Base class for implementing optimizers for multivariate scalar |
| * differentiable functions. |
| * It contains boiler-plate code for dealing with gradient evaluation. |
| * |
| * @since 3.1 |
| */ |
| public abstract class GradientMultivariateOptimizer |
| extends MultivariateOptimizer { |
| /** |
| * Gradient of the objective function. |
| */ |
| private MultivariateVectorFunction gradient; |
| |
| /** |
| * @param checker Convergence checker. |
| */ |
| protected GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker) { |
| super(checker); |
| } |
| |
| /** |
| * Compute the gradient vector. |
| * |
| * @param params Point at which the gradient must be evaluated. |
| * @return the gradient at the specified point. |
| */ |
| protected double[] computeObjectiveGradient(final double[] params) { |
| return gradient.value(params); |
| } |
| |
| /** |
| * {@inheritDoc} |
| * |
| * @param optData Optimization data. In addition to those documented in |
| * {@link MultivariateOptimizer#parseOptimizationData(OptimizationData[]) |
| * MultivariateOptimizer}, this method will register the following data: |
| * <ul> |
| * <li>{@link ObjectiveFunctionGradient}</li> |
| * </ul> |
| * @return {@inheritDoc} |
| * @throws TooManyEvaluationsException if the maximal number of |
| * evaluations (of the objective function) is exceeded. |
| */ |
| @Override |
| public PointValuePair optimize(OptimizationData... optData) |
| throws TooManyEvaluationsException { |
| // Set up base class and perform computation. |
| return super.optimize(optData); |
| } |
| |
| /** |
| * Scans the list of (required and optional) optimization data that |
| * characterize the problem. |
| * |
| * @param optData Optimization data. |
| * The following data will be looked for: |
| * <ul> |
| * <li>{@link ObjectiveFunctionGradient}</li> |
| * </ul> |
| */ |
| @Override |
| protected void parseOptimizationData(OptimizationData... optData) { |
| // Allow base class to register its own data. |
| super.parseOptimizationData(optData); |
| |
| // The existing values (as set by the previous call) are reused if |
| // not provided in the argument list. |
| for (OptimizationData data : optData) { |
| if (data instanceof ObjectiveFunctionGradient) { |
| gradient = ((ObjectiveFunctionGradient) data).getObjectiveFunctionGradient(); |
| // If more data must be parsed, this statement _must_ be |
| // changed to "continue". |
| break; |
| } |
| } |
| } |
| } |