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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.
/*
* 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.univariate;
import org.apache.commons.math3.analysis.UnivariateFunction;
import org.apache.commons.math3.optim.BaseOptimizer;
import org.apache.commons.math3.optim.OptimizationData;
import org.apache.commons.math3.optim.nonlinear.scalar.GoalType;
import org.apache.commons.math3.optim.ConvergenceChecker;
import org.apache.commons.math3.exception.TooManyEvaluationsException;
/**
* Base class for a univariate scalar function optimizer.
*
* @since 3.1
*/
public abstract class UnivariateOptimizer
extends BaseOptimizer {
/** Objective function. */
private UnivariateFunction function;
/** Type of optimization. */
private GoalType goal;
/** Initial guess. */
private double start;
/** Lower bound. */
private double min;
/** Upper bound. */
private double max;
/**
* @param checker Convergence checker.
*/
protected UnivariateOptimizer(ConvergenceChecker checker) {
super(checker);
}
/**
* {@inheritDoc}
*
* @param optData Optimization data. In addition to those documented in
* {@link BaseOptimizer#parseOptimizationData(OptimizationData[])
* BaseOptimizer}, this method will register the following data:
*
* - {@link GoalType}
* - {@link SearchInterval}
* - {@link UnivariateObjectiveFunction}
*
* @return {@inheritDoc}
* @throws TooManyEvaluationsException if the maximal number of
* evaluations is exceeded.
*/
@Override
public UnivariatePointValuePair optimize(OptimizationData... optData)
throws TooManyEvaluationsException {
// Perform computation.
return super.optimize(optData);
}
/**
* @return the optimization type.
*/
public GoalType getGoalType() {
return goal;
}
/**
* 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 GoalType}
* - {@link SearchInterval}
* - {@link UnivariateObjectiveFunction}
*
*/
@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 SearchInterval) {
final SearchInterval interval = (SearchInterval) data;
min = interval.getMin();
max = interval.getMax();
start = interval.getStartValue();
continue;
}
if (data instanceof UnivariateObjectiveFunction) {
function = ((UnivariateObjectiveFunction) data).getObjectiveFunction();
continue;
}
if (data instanceof GoalType) {
goal = (GoalType) data;
continue;
}
}
}
/**
* @return the initial guess.
*/
public double getStartValue() {
return start;
}
/**
* @return the lower bounds.
*/
public double getMin() {
return min;
}
/**
* @return the upper bounds.
*/
public double getMax() {
return max;
}
/**
* Computes the objective function value.
* This method must be called by subclasses to enforce the
* evaluation counter limit.
*
* @param x Point at which the objective function must be evaluated.
* @return the objective function value at the specified point.
* @throws TooManyEvaluationsException if the maximal number of
* evaluations is exceeded.
*/
protected double computeObjectiveValue(double x) {
super.incrementEvaluationCount();
return function.value(x);
}
}