MultiStartMultivariateOptimizer.java
/*
* 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
*
* https://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.
*/
/*
* This is not the original file distributed by the Apache Software Foundation
* It has been modified by the Hipparchus project
*/
package org.hipparchus.optim.nonlinear.scalar;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import org.hipparchus.exception.MathIllegalArgumentException;
import org.hipparchus.exception.NullArgumentException;
import org.hipparchus.optim.BaseMultiStartMultivariateOptimizer;
import org.hipparchus.optim.PointValuePair;
import org.hipparchus.random.RandomVectorGenerator;
/**
* Multi-start optimizer.
*
* This class wraps an optimizer in order to use it several times in
* turn with different starting points (trying to avoid being trapped
* in a local extremum when looking for a global one).
*
*/
public class MultiStartMultivariateOptimizer
extends BaseMultiStartMultivariateOptimizer<PointValuePair> {
/** Underlying optimizer. */
private final MultivariateOptimizer optimizer;
/** Found optima. */
private final List<PointValuePair> optima;
/**
* Create a multi-start optimizer from a single-start optimizer.
*
* @param optimizer Single-start optimizer to wrap.
* @param starts Number of starts to perform.
* If {@code starts == 1}, the result will be same as if {@code optimizer}
* is called directly.
* @param generator Random vector generator to use for restarts.
* @throws NullArgumentException if {@code optimizer} or {@code generator}
* is {@code null}.
* @throws MathIllegalArgumentException if {@code starts < 1}.
*/
public MultiStartMultivariateOptimizer(final MultivariateOptimizer optimizer,
final int starts,
final RandomVectorGenerator generator)
throws MathIllegalArgumentException, NullArgumentException {
super(optimizer, starts, generator);
this.optimizer = optimizer;
this.optima = new ArrayList<>();
}
/**
* {@inheritDoc}
*/
@Override
public PointValuePair[] getOptima() {
Collections.sort(optima, getPairComparator());
return optima.toArray(new PointValuePair[0]);
}
/**
* {@inheritDoc}
*/
@Override
protected void store(PointValuePair optimum) {
optima.add(optimum);
}
/**
* {@inheritDoc}
*/
@Override
protected void clear() {
optima.clear();
}
/**
* @return a comparator for sorting the optima.
*/
private Comparator<PointValuePair> getPairComparator() {
return new Comparator<PointValuePair>() {
/** {@inheritDoc} */
@Override
public int compare(final PointValuePair o1,
final PointValuePair o2) {
if (o1 == null) {
return (o2 == null) ? 0 : 1;
} else if (o2 == null) {
return -1;
}
final double v1 = o1.getValue();
final double v2 = o2.getValue();
return (optimizer.getGoalType() == GoalType.MINIMIZE) ?
Double.compare(v1, v2) : Double.compare(v2, v1);
}
};
}
}