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package org.apache.commons.math3.optim.nonlinear.scalar.noderiv;

import java.util.Comparator;

import org.apache.commons.math3.analysis.MultivariateFunction;
import org.apache.commons.math3.optim.PointValuePair;

This class implements the multi-directional direct search method.
Since:3.0
/** * This class implements the multi-directional direct search method. * * @since 3.0 */
public class MultiDirectionalSimplex extends AbstractSimplex {
Default value for khi: 2.0.
/** Default value for {@link #khi}: {@value}. */
private static final double DEFAULT_KHI = 2;
Default value for gamma: 0.5.
/** Default value for {@link #gamma}: {@value}. */
private static final double DEFAULT_GAMMA = 0.5;
Expansion coefficient.
/** Expansion coefficient. */
private final double khi;
Contraction coefficient.
/** Contraction coefficient. */
private final double gamma;
Build a multi-directional simplex with default coefficients. The default values are 2.0 for khi and 0.5 for gamma.
Params:
  • n – Dimension of the simplex.
/** * Build a multi-directional simplex with default coefficients. * The default values are 2.0 for khi and 0.5 for gamma. * * @param n Dimension of the simplex. */
public MultiDirectionalSimplex(final int n) { this(n, 1d); }
Build a multi-directional simplex with default coefficients. The default values are 2.0 for khi and 0.5 for gamma.
Params:
/** * Build a multi-directional simplex with default coefficients. * The default values are 2.0 for khi and 0.5 for gamma. * * @param n Dimension of the simplex. * @param sideLength Length of the sides of the default (hypercube) * simplex. See {@link AbstractSimplex#AbstractSimplex(int,double)}. */
public MultiDirectionalSimplex(final int n, double sideLength) { this(n, sideLength, DEFAULT_KHI, DEFAULT_GAMMA); }
Build a multi-directional simplex with specified coefficients.
Params:
/** * Build a multi-directional simplex with specified coefficients. * * @param n Dimension of the simplex. See * {@link AbstractSimplex#AbstractSimplex(int,double)}. * @param khi Expansion coefficient. * @param gamma Contraction coefficient. */
public MultiDirectionalSimplex(final int n, final double khi, final double gamma) { this(n, 1d, khi, gamma); }
Build a multi-directional simplex with specified coefficients.
Params:
/** * Build a multi-directional 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 khi Expansion coefficient. * @param gamma Contraction coefficient. */
public MultiDirectionalSimplex(final int n, double sideLength, final double khi, final double gamma) { super(n, sideLength); this.khi = khi; this.gamma = gamma; }
Build a multi-directional simplex with default coefficients. The default values are 2.0 for khi and 0.5 for gamma.
Params:
  • steps – Steps along the canonical axes representing box edges. They may be negative but not zero. See
/** * Build a multi-directional simplex with default coefficients. * The default values are 2.0 for khi and 0.5 for gamma. * * @param steps Steps along the canonical axes representing box edges. * They may be negative but not zero. See */
public MultiDirectionalSimplex(final double[] steps) { this(steps, DEFAULT_KHI, DEFAULT_GAMMA); }
Build a multi-directional simplex with specified coefficients.
Params:
  • steps – Steps along the canonical axes representing box edges. They may be negative but not zero. See AbstractSimplex(double[]).
  • khi – Expansion coefficient.
  • gamma – Contraction coefficient.
/** * Build a multi-directional 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 khi Expansion coefficient. * @param gamma Contraction coefficient. */
public MultiDirectionalSimplex(final double[] steps, final double khi, final double gamma) { super(steps); this.khi = khi; this.gamma = gamma; }
Build a multi-directional simplex with default coefficients. The default values are 2.0 for khi and 0.5 for gamma.
Params:
/** * Build a multi-directional simplex with default coefficients. * The default values are 2.0 for khi and 0.5 for gamma. * * @param referenceSimplex Reference simplex. See * {@link AbstractSimplex#AbstractSimplex(double[][])}. */
public MultiDirectionalSimplex(final double[][] referenceSimplex) { this(referenceSimplex, DEFAULT_KHI, DEFAULT_GAMMA); }
Build a multi-directional simplex with specified coefficients.
Params:
  • referenceSimplex – Reference simplex. See AbstractSimplex(double[][]).
  • khi – Expansion coefficient.
  • gamma – Contraction coefficient.
Throws:
/** * Build a multi-directional simplex with specified coefficients. * * @param referenceSimplex Reference simplex. See * {@link AbstractSimplex#AbstractSimplex(double[][])}. * @param khi Expansion coefficient. * @param gamma Contraction 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 MultiDirectionalSimplex(final double[][] referenceSimplex, final double khi, final double gamma) { super(referenceSimplex); this.khi = khi; this.gamma = gamma; }
{@inheritDoc}
/** {@inheritDoc} */
@Override public void iterate(final MultivariateFunction evaluationFunction, final Comparator<PointValuePair> comparator) { // Save the original simplex. final PointValuePair[] original = getPoints(); final PointValuePair best = original[0]; // Perform a reflection step. final PointValuePair reflected = evaluateNewSimplex(evaluationFunction, original, 1, comparator); if (comparator.compare(reflected, best) < 0) { // Compute the expanded simplex. final PointValuePair[] reflectedSimplex = getPoints(); final PointValuePair expanded = evaluateNewSimplex(evaluationFunction, original, khi, comparator); if (comparator.compare(reflected, expanded) <= 0) { // Keep the reflected simplex. setPoints(reflectedSimplex); } // Keep the expanded simplex. return; } // Compute the contracted simplex. evaluateNewSimplex(evaluationFunction, original, gamma, comparator); }
Compute and evaluate a new simplex.
Params:
  • evaluationFunction – Evaluation function.
  • original – Original simplex (to be preserved).
  • coeff – Linear coefficient.
  • comparator – Comparator to use to sort simplex vertices from best to poorest.
Throws:
Returns:the best point in the transformed simplex.
/** * Compute and evaluate a new simplex. * * @param evaluationFunction Evaluation function. * @param original Original simplex (to be preserved). * @param coeff Linear coefficient. * @param comparator Comparator to use to sort simplex vertices from best * to poorest. * @return the best point in the transformed simplex. * @throws org.apache.commons.math3.exception.TooManyEvaluationsException * if the maximal number of evaluations is exceeded. */
private PointValuePair evaluateNewSimplex(final MultivariateFunction evaluationFunction, final PointValuePair[] original, final double coeff, final Comparator<PointValuePair> comparator) { final double[] xSmallest = original[0].getPointRef(); // Perform a linear transformation on all the simplex points, // except the first one. setPoint(0, original[0]); final int dim = getDimension(); for (int i = 1; i < getSize(); i++) { final double[] xOriginal = original[i].getPointRef(); final double[] xTransformed = new double[dim]; for (int j = 0; j < dim; j++) { xTransformed[j] = xSmallest[j] + coeff * (xSmallest[j] - xOriginal[j]); } setPoint(i, new PointValuePair(xTransformed, Double.NaN, false)); } // Evaluate the simplex. evaluate(evaluationFunction, comparator); return getPoint(0); } }