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The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.
/*
* 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.direct;
import java.util.Comparator;
import org.apache.commons.math3.optimization.PointValuePair;
import org.apache.commons.math3.analysis.MultivariateFunction;
/**
* This class implements the Nelder-Mead simplex algorithm.
*
* @deprecated As of 3.1 (to be removed in 4.0).
* @since 3.0
*/
@Deprecated
public class NelderMeadSimplex extends AbstractSimplex {
/** Default value for {@link #rho}: {@value}. */
private static final double DEFAULT_RHO = 1;
/** Default value for {@link #khi}: {@value}. */
private static final double DEFAULT_KHI = 2;
/** Default value for {@link #gamma}: {@value}. */
private static final double DEFAULT_GAMMA = 0.5;
/** Default value for {@link #sigma}: {@value}. */
private static final double DEFAULT_SIGMA = 0.5;
/** Reflection coefficient. */
private final double rho;
/** Expansion coefficient. */
private final double khi;
/** Contraction coefficient. */
private final double gamma;
/** Shrinkage coefficient. */
private final double sigma;
/**
* Build a Nelder-Mead simplex with default coefficients.
* The default coefficients are 1.0 for rho, 2.0 for khi and 0.5
* for both gamma and sigma.
*
* @param n Dimension of the simplex.
*/
public NelderMeadSimplex(final int n) {
this(n, 1d);
}
/**
* Build a Nelder-Mead simplex with default coefficients.
* The default coefficients are 1.0 for rho, 2.0 for khi and 0.5
* for both gamma and sigma.
*
* @param n Dimension of the simplex.
* @param sideLength Length of the sides of the default (hypercube)
* simplex. See {@link AbstractSimplex#AbstractSimplex(int,double)}.
*/
public NelderMeadSimplex(final int n, double sideLength) {
this(n, sideLength,
DEFAULT_RHO, DEFAULT_KHI, DEFAULT_GAMMA, DEFAULT_SIGMA);
}
/**
* Build a Nelder-Mead simplex with specified coefficients.
*
* @param n Dimension of the simplex. See
* {@link AbstractSimplex#AbstractSimplex(int,double)}.
* @param sideLength Length of the sides of the default (hypercube)
* simplex. See {@link AbstractSimplex#AbstractSimplex(int,double)}.
* @param rho Reflection coefficient.
* @param khi Expansion coefficient.
* @param gamma Contraction coefficient.
* @param sigma Shrinkage coefficient.
*/
public NelderMeadSimplex(final int n, double sideLength,
final double rho, final double khi,
final double gamma, final double sigma) {
super(n, sideLength);
this.rho = rho;
this.khi = khi;
this.gamma = gamma;
this.sigma = sigma;
}
/**
* Build a Nelder-Mead simplex with specified coefficients.
*
* @param n Dimension of the simplex. See
* {@link AbstractSimplex#AbstractSimplex(int)}.
* @param rho Reflection coefficient.
* @param khi Expansion coefficient.
* @param gamma Contraction coefficient.
* @param sigma Shrinkage coefficient.
*/
public NelderMeadSimplex(final int n,
final double rho, final double khi,
final double gamma, final double sigma) {
this(n, 1d, rho, khi, gamma, sigma);
}
/**
* Build a Nelder-Mead simplex with default coefficients.
* The default coefficients are 1.0 for rho, 2.0 for khi and 0.5
* for both gamma and sigma.
*
* @param steps Steps along the canonical axes representing box edges.
* They may be negative but not zero. See
*/
public NelderMeadSimplex(final double[] steps) {
this(steps, DEFAULT_RHO, DEFAULT_KHI, DEFAULT_GAMMA, DEFAULT_SIGMA);
}
/**
* Build a Nelder-Mead simplex with specified coefficients.
*
* @param steps Steps along the canonical axes representing box edges.
* They may be negative but not zero. See
* {@link AbstractSimplex#AbstractSimplex(double[])}.
* @param rho Reflection coefficient.
* @param khi Expansion coefficient.
* @param gamma Contraction coefficient.
* @param sigma Shrinkage coefficient.
* @throws IllegalArgumentException if one of the steps is zero.
*/
public NelderMeadSimplex(final double[] steps,
final double rho, final double khi,
final double gamma, final double sigma) {
super(steps);
this.rho = rho;
this.khi = khi;
this.gamma = gamma;
this.sigma = sigma;
}
/**
* Build a Nelder-Mead simplex with default coefficients.
* The default coefficients are 1.0 for rho, 2.0 for khi and 0.5
* for both gamma and sigma.
*
* @param referenceSimplex Reference simplex. See
* {@link AbstractSimplex#AbstractSimplex(double[][])}.
*/
public NelderMeadSimplex(final double[][] referenceSimplex) {
this(referenceSimplex, DEFAULT_RHO, DEFAULT_KHI, DEFAULT_GAMMA, DEFAULT_SIGMA);
}
/**
* Build a Nelder-Mead simplex with specified coefficients.
*
* @param referenceSimplex Reference simplex. See
* {@link AbstractSimplex#AbstractSimplex(double[][])}.
* @param rho Reflection coefficient.
* @param khi Expansion coefficient.
* @param gamma Contraction coefficient.
* @param sigma Shrinkage coefficient.
* @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
* if the reference simplex does not contain at least one point.
* @throws org.apache.commons.math3.exception.DimensionMismatchException
* if there is a dimension mismatch in the reference simplex.
*/
public NelderMeadSimplex(final double[][] referenceSimplex,
final double rho, final double khi,
final double gamma, final double sigma) {
super(referenceSimplex);
this.rho = rho;
this.khi = khi;
this.gamma = gamma;
this.sigma = sigma;
}
/** {@inheritDoc} */
@Override
public void iterate(final MultivariateFunction evaluationFunction,
final Comparator comparator) {
// The simplex has n + 1 points if dimension is n.
final int n = getDimension();
// Interesting values.
final PointValuePair best = getPoint(0);
final PointValuePair secondBest = getPoint(n - 1);
final PointValuePair worst = getPoint(n);
final double[] xWorst = worst.getPointRef();
// Compute the centroid of the best vertices (dismissing the worst
// point at index n).
final double[] centroid = new double[n];
for (int i = 0; i < n; i++) {
final double[] x = getPoint(i).getPointRef();
for (int j = 0; j < n; j++) {
centroid[j] += x[j];
}
}
final double scaling = 1.0 / n;
for (int j = 0; j < n; j++) {
centroid[j] *= scaling;
}
// compute the reflection point
final double[] xR = new double[n];
for (int j = 0; j < n; j++) {
xR[j] = centroid[j] + rho * (centroid[j] - xWorst[j]);
}
final PointValuePair reflected
= new PointValuePair(xR, evaluationFunction.value(xR), false);
if (comparator.compare(best, reflected) <= 0 &&
comparator.compare(reflected, secondBest) < 0) {
// Accept the reflected point.
replaceWorstPoint(reflected, comparator);
} else if (comparator.compare(reflected, best) < 0) {
// Compute the expansion point.
final double[] xE = new double[n];
for (int j = 0; j < n; j++) {
xE[j] = centroid[j] + khi * (xR[j] - centroid[j]);
}
final PointValuePair expanded
= new PointValuePair(xE, evaluationFunction.value(xE), false);
if (comparator.compare(expanded, reflected) < 0) {
// Accept the expansion point.
replaceWorstPoint(expanded, comparator);
} else {
// Accept the reflected point.
replaceWorstPoint(reflected, comparator);
}
} else {
if (comparator.compare(reflected, worst) < 0) {
// Perform an outside contraction.
final double[] xC = new double[n];
for (int j = 0; j < n; j++) {
xC[j] = centroid[j] + gamma * (xR[j] - centroid[j]);
}
final PointValuePair outContracted
= new PointValuePair(xC, evaluationFunction.value(xC), false);
if (comparator.compare(outContracted, reflected) <= 0) {
// Accept the contraction point.
replaceWorstPoint(outContracted, comparator);
return;
}
} else {
// Perform an inside contraction.
final double[] xC = new double[n];
for (int j = 0; j < n; j++) {
xC[j] = centroid[j] - gamma * (centroid[j] - xWorst[j]);
}
final PointValuePair inContracted
= new PointValuePair(xC, evaluationFunction.value(xC), false);
if (comparator.compare(inContracted, worst) < 0) {
// Accept the contraction point.
replaceWorstPoint(inContracted, comparator);
return;
}
}
// Perform a shrink.
final double[] xSmallest = getPoint(0).getPointRef();
for (int i = 1; i <= n; i++) {
final double[] x = getPoint(i).getPoint();
for (int j = 0; j < n; j++) {
x[j] = xSmallest[j] + sigma * (x[j] - xSmallest[j]);
}
setPoint(i, new PointValuePair(x, Double.NaN, false));
}
evaluate(evaluationFunction, comparator);
}
}
}