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/*
 * 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.math3.optim.nonlinear.scalar;

import org.apache.commons.math3.analysis.MultivariateVectorFunction;
import org.apache.commons.math3.optim.ConvergenceChecker;
import org.apache.commons.math3.optim.OptimizationData;
import org.apache.commons.math3.optim.PointValuePair;
import org.apache.commons.math3.exception.TooManyEvaluationsException;

/**
 * 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 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:
     * 
    *
  • {@link ObjectiveFunctionGradient}
  • *
* @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: *
    *
  • {@link ObjectiveFunctionGradient}
  • *
*/ @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; } } } }




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