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Java example source code file (MultiStartMultivariateVectorOptimizer.java)

This example Java source code file (MultiStartMultivariateVectorOptimizer.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.

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Java - Java tags/keywords

arraylist, basemultistartmultivariateoptimizer, comparator, deprecated, multistartmultivariatevectoroptimizer, notstrictlypositiveexception, nullargumentexception, override, pointvectorvaluepair, randomvectorgenerator, realmatrix, realvector, util

The MultiStartMultivariateVectorOptimizer.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,
 * 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
public class MultiStartMultivariateVectorOptimizer
    extends BaseMultiStartMultivariateOptimizer<PointVectorValuePair> {
    /** Underlying optimizer. */
    private final MultivariateVectorOptimizer optimizer;
    /** Found optima. */
    private final List<PointVectorValuePair> optima = new ArrayList();

     * 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}
    public PointVectorValuePair[] getOptima() {
        Collections.sort(optima, getPairComparator());
        return optima.toArray(new PointVectorValuePair[0]);

     * {@inheritDoc}
    protected void store(PointVectorValuePair optimum) {

     * {@inheritDoc}
    protected void clear() {

     * @return a comparator for sorting the optima.
    private Comparator<PointVectorValuePair> getPairComparator() {
        return new Comparator<PointVectorValuePair>() {
            /** Observed value to be matched. */
            private final RealVector target = new ArrayRealVector(optimizer.getTarget(), false);
            /** Observations weights. */
            private final RealMatrix weight = optimizer.getWeight();

            /** {@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),

            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));

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