All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.apache.commons.math3.optim.BaseOptimizer Maven / Gradle / Ivy

Go to download

The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.

There is a newer version: 62
Show newest version
/*
 * 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;

import org.apache.commons.math3.util.Incrementor;
import org.apache.commons.math3.exception.TooManyEvaluationsException;
import org.apache.commons.math3.exception.TooManyIterationsException;

/**
 * Base class for implementing optimizers.
 * It contains the boiler-plate code for counting the number of evaluations
 * of the objective function and the number of iterations of the algorithm,
 * and storing the convergence checker.
 * It is not a "user" class.
 *
 * @param  Type of the point/value pair returned by the optimization
 * algorithm.
 *
 * @since 3.1
 */
public abstract class BaseOptimizer {
    /** Evaluations counter. */
    protected final Incrementor evaluations;
    /** Iterations counter. */
    protected final Incrementor iterations;
    /** Convergence checker. */
    private final ConvergenceChecker checker;

    /**
     * @param checker Convergence checker.
     */
    protected BaseOptimizer(ConvergenceChecker checker) {
        this(checker, 0, Integer.MAX_VALUE);
    }

    /**
     * @param checker Convergence checker.
     * @param maxEval Maximum number of objective function evaluations.
     * @param maxIter Maximum number of algorithm iterations.
     */
    protected BaseOptimizer(ConvergenceChecker checker,
                            int maxEval,
                            int maxIter) {
        this.checker = checker;

        evaluations = new Incrementor(maxEval, new MaxEvalCallback());
        iterations = new Incrementor(maxIter, new MaxIterCallback());
    }

    /**
     * Gets the maximal number of function evaluations.
     *
     * @return the maximal number of function evaluations.
     */
    public int getMaxEvaluations() {
        return evaluations.getMaximalCount();
    }

    /**
     * Gets the number of evaluations of the objective function.
     * The number of evaluations corresponds to the last call to the
     * {@code optimize} method. It is 0 if the method has not been
     * called yet.
     *
     * @return the number of evaluations of the objective function.
     */
    public int getEvaluations() {
        return evaluations.getCount();
    }

    /**
     * Gets the maximal number of iterations.
     *
     * @return the maximal number of iterations.
     */
    public int getMaxIterations() {
        return iterations.getMaximalCount();
    }

    /**
     * Gets the number of iterations performed by the algorithm.
     * The number iterations corresponds to the last call to the
     * {@code optimize} method. It is 0 if the method has not been
     * called yet.
     *
     * @return the number of evaluations of the objective function.
     */
    public int getIterations() {
        return iterations.getCount();
    }

    /**
     * Gets the convergence checker.
     *
     * @return the object used to check for convergence.
     */
    public ConvergenceChecker getConvergenceChecker() {
        return checker;
    }

    /**
     * Stores data and performs the optimization.
     * 

* The list of parameters is open-ended so that sub-classes can extend it * with arguments specific to their concrete implementations. *

* When the method is called multiple times, instance data is overwritten * only when actually present in the list of arguments: when not specified, * data set in a previous call is retained (and thus is optional in * subsequent calls). *

* Important note: Subclasses must override * {@link #parseOptimizationData(OptimizationData[])} if they need to register * their own options; but then, they must also call * {@code super.parseOptimizationData(optData)} within that method. * * @param optData Optimization data. * This method will register the following data: *

    *
  • {@link MaxEval}
  • *
  • {@link MaxIter}
  • *
* @return a point/value pair that satisfies the convergence criteria. * @throws TooManyEvaluationsException if the maximal number of * evaluations is exceeded. * @throws TooManyIterationsException if the maximal number of * iterations is exceeded. */ public PAIR optimize(OptimizationData... optData) throws TooManyEvaluationsException, TooManyIterationsException { // Parse options. parseOptimizationData(optData); // Reset counters. evaluations.resetCount(); iterations.resetCount(); // Perform optimization. return doOptimize(); } /** * Performs the optimization. * * @return a point/value pair that satisfies the convergence criteria. * @throws TooManyEvaluationsException if the maximal number of * evaluations is exceeded. * @throws TooManyIterationsException if the maximal number of * iterations is exceeded. */ public PAIR optimize() throws TooManyEvaluationsException, TooManyIterationsException { // Reset counters. evaluations.resetCount(); iterations.resetCount(); // Perform optimization. return doOptimize(); } /** * Performs the bulk of the optimization algorithm. * * @return the point/value pair giving the optimal value of the * objective function. */ protected abstract PAIR doOptimize(); /** * Increment the evaluation count. * * @throws TooManyEvaluationsException if the allowed evaluations * have been exhausted. */ protected void incrementEvaluationCount() throws TooManyEvaluationsException { evaluations.incrementCount(); } /** * Increment the iteration count. * * @throws TooManyIterationsException if the allowed iterations * have been exhausted. */ protected void incrementIterationCount() throws TooManyIterationsException { iterations.incrementCount(); } /** * 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 MaxEval}
  • *
  • {@link MaxIter}
  • *
*/ protected void parseOptimizationData(OptimizationData... 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 MaxEval) { evaluations.setMaximalCount(((MaxEval) data).getMaxEval()); continue; } if (data instanceof MaxIter) { iterations.setMaximalCount(((MaxIter) data).getMaxIter()); continue; } } } /** * Defines the action to perform when reaching the maximum number * of evaluations. */ private static class MaxEvalCallback implements Incrementor.MaxCountExceededCallback { /** * {@inheritDoc} * @throws TooManyEvaluationsException */ public void trigger(int max) { throw new TooManyEvaluationsException(max); } } /** * Defines the action to perform when reaching the maximum number * of evaluations. */ private static class MaxIterCallback implements Incrementor.MaxCountExceededCallback { /** * {@inheritDoc} * @throws TooManyIterationsException */ public void trigger(int max) { throw new TooManyIterationsException(max); } } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy