/*
* 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.vector;
import java.util.Collections;
import java.util.List;
import java.util.ArrayList;
import java.util.Comparator;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NullArgumentException;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.linear.RealVector;
import org.apache.commons.math3.linear.ArrayRealVector;
import org.apache.commons.math3.random.RandomVectorGenerator;
import org.apache.commons.math3.optim.BaseMultiStartMultivariateOptimizer;
import org.apache.commons.math3.optim.PointVectorValuePair;
/**
* Multi-start optimizer for a (vector) model function.
*
* 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).
*
* @since 3.0
*/
@Deprecated
public class MultiStartMultivariateVectorOptimizer
extends BaseMultiStartMultivariateOptimizer<PointVectorValuePair> {
/** Underlying optimizer. */
private final MultivariateVectorOptimizer optimizer;
/** Found optima. */
private final List<PointVectorValuePair> optima = new ArrayList<PointVectorValuePair>();
/**
* 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 NotStrictlyPositiveException if {@code starts < 1}.
*/
public MultiStartMultivariateVectorOptimizer(final MultivariateVectorOptimizer optimizer,
final int starts,
final RandomVectorGenerator generator)
throws NullArgumentException,
NotStrictlyPositiveException {
super(optimizer, starts, generator);
this.optimizer = optimizer;
}
/**
* {@inheritDoc}
*/
@Override
public PointVectorValuePair[] getOptima() {
Collections.sort(optima, getPairComparator());
return optima.toArray(new PointVectorValuePair[0]);
}
/**
* {@inheritDoc}
*/
@Override
protected void store(PointVectorValuePair optimum) {
optima.add(optimum);
}
/**
* {@inheritDoc}
*/
@Override
protected void clear() {
optima.clear();
}
/**
* @return a comparator for sorting the optima.
*/
private Comparator<PointVectorValuePair> getPairComparator() {
return new Comparator<PointVectorValuePair>() {
private final RealVector target = new ArrayRealVector(optimizer.getTarget(), false);
private final RealMatrix weight = optimizer.getWeight();
public int compare(final PointVectorValuePair o1,
final PointVectorValuePair o2) {
if (o1 == null) {
return (o2 == null) ? 0 : 1;
} else if (o2 == null) {
return -1;
}
return Double.compare(weightedResidual(o1),
weightedResidual(o2));
}
private double weightedResidual(final PointVectorValuePair pv) {
final RealVector v = new ArrayRealVector(pv.getValueRef(), false);
final RealVector r = target.subtract(v);
return r.dotProduct(weight.operate(r));
}
};
}
}