home | career | drupal | java | mac | mysql | perl | scala | uml | unix  

Java example source code file (BaseMultivariateVectorMultiStartOptimizer.java)

This example Java source code file (BaseMultivariateVectorMultiStartOptimizer.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

basemultivariatevectormultistartoptimizer, basemultivariatevectoroptimizer, comparator, convergencechecker, convergenceexception, deprecated, func, multivariatevectorfunction, notstrictlypositiveexception, nullargumentexception, pointvectorvaluepair, randomvectorgenerator, runtimeexception, util

The BaseMultivariateVectorMultiStartOptimizer.java Java example source code

/*
 * 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.optimization;

import java.util.Arrays;
import java.util.Comparator;

import org.apache.commons.math3.analysis.MultivariateVectorFunction;
import org.apache.commons.math3.exception.ConvergenceException;
import org.apache.commons.math3.exception.MathIllegalStateException;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NullArgumentException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.random.RandomVectorGenerator;

/**
 * Base class for all implementations of a multi-start optimizer.
 *
 * This interface is mainly intended to enforce the internal coherence of
 * Commons-Math. Users of the API are advised to base their code on
 * {@link DifferentiableMultivariateVectorMultiStartOptimizer}.
 *
 * @param <FUNC> Type of the objective function to be optimized.
 *
 * @deprecated As of 3.1 (to be removed in 4.0).
 * @since 3.0
 */
@Deprecated
public class BaseMultivariateVectorMultiStartOptimizer<FUNC extends MultivariateVectorFunction>
    implements BaseMultivariateVectorOptimizer<FUNC> {
    /** Underlying classical optimizer. */
    private final BaseMultivariateVectorOptimizer<FUNC> optimizer;
    /** Maximal number of evaluations allowed. */
    private int maxEvaluations;
    /** Number of evaluations already performed for all starts. */
    private int totalEvaluations;
    /** Number of starts to go. */
    private int starts;
    /** Random generator for multi-start. */
    private RandomVectorGenerator generator;
    /** Found optima. */
    private PointVectorValuePair[] 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 {@link #optimize(int,MultivariateVectorFunction,double[],double[],double[])
     * optimize} will return the same solution as {@code optimizer} would.
     * @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}.
     */
    protected BaseMultivariateVectorMultiStartOptimizer(final BaseMultivariateVectorOptimizer<FUNC> optimizer,
                                                           final int starts,
                                                           final RandomVectorGenerator generator) {
        if (optimizer == null ||
            generator == null) {
            throw new NullArgumentException();
        }
        if (starts < 1) {
            throw new NotStrictlyPositiveException(starts);
        }

        this.optimizer = optimizer;
        this.starts = starts;
        this.generator = generator;
    }

    /**
     * Get all the optima found during the last call to {@link
     * #optimize(int,MultivariateVectorFunction,double[],double[],double[]) optimize}.
     * The optimizer stores all the optima found during a set of
     * restarts. The {@link #optimize(int,MultivariateVectorFunction,double[],double[],double[])
     * optimize} method returns the best point only. This method
     * returns all the points found at the end of each starts, including
     * the best one already returned by the {@link
     * #optimize(int,MultivariateVectorFunction,double[],double[],double[]) optimize} method.
     * <br/>
     * The returned array as one element for each start as specified
     * in the constructor. It is ordered with the results from the
     * runs that did converge first, sorted from best to worst
     * objective value (i.e. in ascending order if minimizing and in
     * descending order if maximizing), followed by and null elements
     * corresponding to the runs that did not converge. This means all
     * elements will be null if the {@link
     * #optimize(int,MultivariateVectorFunction,double[],double[],double[]) optimize} method did
     * throw a {@link ConvergenceException}). This also means that if
     * the first element is not {@code null}, it is the best point found
     * across all starts.
     *
     * @return array containing the optima
     * @throws MathIllegalStateException if {@link
     * #optimize(int,MultivariateVectorFunction,double[],double[],double[]) optimize} has not been
     * called.
     */
    public PointVectorValuePair[] getOptima() {
        if (optima == null) {
            throw new MathIllegalStateException(LocalizedFormats.NO_OPTIMUM_COMPUTED_YET);
        }
        return optima.clone();
    }

    /** {@inheritDoc} */
    public int getMaxEvaluations() {
        return maxEvaluations;
    }

    /** {@inheritDoc} */
    public int getEvaluations() {
        return totalEvaluations;
    }

    /** {@inheritDoc} */
    public ConvergenceChecker<PointVectorValuePair> getConvergenceChecker() {
        return optimizer.getConvergenceChecker();
    }

    /**
     * {@inheritDoc}
     */
    public PointVectorValuePair optimize(int maxEval, final FUNC f,
                                            double[] target, double[] weights,
                                            double[] startPoint) {
        maxEvaluations = maxEval;
        RuntimeException lastException = null;
        optima = new PointVectorValuePair[starts];
        totalEvaluations = 0;

        // Multi-start loop.
        for (int i = 0; i < starts; ++i) {

            // CHECKSTYLE: stop IllegalCatch
            try {
                optima[i] = optimizer.optimize(maxEval - totalEvaluations, f, target, weights,
                                               i == 0 ? startPoint : generator.nextVector());
            } catch (ConvergenceException oe) {
                optima[i] = null;
            } catch (RuntimeException mue) {
                lastException = mue;
                optima[i] = null;
            }
            // CHECKSTYLE: resume IllegalCatch

            totalEvaluations += optimizer.getEvaluations();
        }

        sortPairs(target, weights);

        if (optima[0] == null) {
            throw lastException; // cannot be null if starts >=1
        }

        // Return the found point given the best objective function value.
        return optima[0];
    }

    /**
     * Sort the optima from best to worst, followed by {@code null} elements.
     *
     * @param target Target value for the objective functions at optimum.
     * @param weights Weights for the least-squares cost computation.
     */
    private void sortPairs(final double[] target,
                           final double[] weights) {
        Arrays.sort(optima, new Comparator<PointVectorValuePair>() {
                /** {@inheritDoc} */
                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 double[] value = pv.getValueRef();
                    double sum = 0;
                    for (int i = 0; i < value.length; ++i) {
                        final double ri = value[i] - target[i];
                        sum += weights[i] * ri * ri;
                    }
                    return sum;
                }
            });
    }
}

Other Java examples (source code examples)

Here is a short list of links related to this Java BaseMultivariateVectorMultiStartOptimizer.java source code file:



my book on functional programming

 

new blog posts

 

Copyright 1998-2019 Alvin Alexander, alvinalexander.com
All Rights Reserved.

A percentage of advertising revenue from
pages under the /java/jwarehouse URI on this website is
paid back to open source projects.