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A Java's Collaborative Filtering library to carry out experiments in research of Collaborative Filtering based Recommender Systems. The library has been designed from researchers to researchers.
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/*
 * 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.analysis.MultivariateFunction;
import org.apache.commons.math3.optimization.PointValuePair;

/**
 * This class implements the multi-directional direct search method.
 *
 * @deprecated As of 3.1 (to be removed in 4.0).
 * @since 3.0
 */
@Deprecated
public class MultiDirectionalSimplex extends AbstractSimplex {
    /** 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;
    /** Expansion coefficient. */
    private final double khi;
    /** 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.
     *
     * @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.
     *
     * @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.
     *
     * @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.
     *
     * @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.
     *
     * @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.
     *
     * @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.
     *
     * @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.
     *
     * @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} */
    @Override
    public void iterate(final MultivariateFunction evaluationFunction,
                        final Comparator 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.
     *
     * @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 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);
    }
}