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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;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.NumberIsTooSmallException;
import org.apache.commons.math3.exception.NumberIsTooLargeException;
/**
* Base class for implementing optimizers for multivariate functions.
* It contains the boiler-plate code for initial guess and bounds
* specifications.
* It is not a "user" class.
*
* @param Type of the point/value pair returned by the optimization
* algorithm.
*
* @since 3.1
*/
public abstract class BaseMultivariateOptimizer
extends BaseOptimizer {
/** Initial guess. */
private double[] start;
/** Lower bounds. */
private double[] lowerBound;
/** Upper bounds. */
private double[] upperBound;
/**
* @param checker Convergence checker.
*/
protected BaseMultivariateOptimizer(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 InitialGuess}
* - {@link SimpleBounds}
*
* @return {@inheritDoc}
*/
@Override
public PAIR optimize(OptimizationData... optData) {
// Perform optimization.
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 InitialGuess}
* - {@link SimpleBounds}
*
*/
@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 InitialGuess) {
start = ((InitialGuess) data).getInitialGuess();
continue;
}
if (data instanceof SimpleBounds) {
final SimpleBounds bounds = (SimpleBounds) data;
lowerBound = bounds.getLower();
upperBound = bounds.getUpper();
continue;
}
}
// Check input consistency.
checkParameters();
}
/**
* Gets the initial guess.
*
* @return the initial guess, or {@code null} if not set.
*/
public double[] getStartPoint() {
return start == null ? null : start.clone();
}
/**
* @return the lower bounds, or {@code null} if not set.
*/
public double[] getLowerBound() {
return lowerBound == null ? null : lowerBound.clone();
}
/**
* @return the upper bounds, or {@code null} if not set.
*/
public double[] getUpperBound() {
return upperBound == null ? null : upperBound.clone();
}
/**
* Check parameters consistency.
*/
private void checkParameters() {
if (start != null) {
final int dim = start.length;
if (lowerBound != null) {
if (lowerBound.length != dim) {
throw new DimensionMismatchException(lowerBound.length, dim);
}
for (int i = 0; i < dim; i++) {
final double v = start[i];
final double lo = lowerBound[i];
if (v < lo) {
throw new NumberIsTooSmallException(v, lo, true);
}
}
}
if (upperBound != null) {
if (upperBound.length != dim) {
throw new DimensionMismatchException(upperBound.length, dim);
}
for (int i = 0; i < dim; i++) {
final double v = start[i];
final double hi = upperBound[i];
if (v > hi) {
throw new NumberIsTooLargeException(v, hi, true);
}
}
}
}
}
}