Java tutorial
/* * 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.scalar; 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.random.RandomVectorGenerator; import org.apache.commons.math3.optim.BaseMultiStartMultivariateOptimizer; import org.apache.commons.math3.optim.PointValuePair; /** * 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). * * @version $Id$ * @since 3.0 */ public class MultiStartMultivariateOptimizer extends BaseMultiStartMultivariateOptimizer<PointValuePair> { /** Underlying optimizer. */ private final MultivariateOptimizer optimizer; /** Found optima. */ private final List<PointValuePair> optima = new ArrayList<PointValuePair>(); /** * 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 MultiStartMultivariateOptimizer(final MultivariateOptimizer optimizer, final int starts, final RandomVectorGenerator generator) throws NullArgumentException, NotStrictlyPositiveException { super(optimizer, starts, generator); this.optimizer = optimizer; } /** * {@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>() { 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); } }; } }