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+/**
+ * Description: provide the information for the search space (S)
+ *
+ * @ Author Create/Modi Note
+ * Xiaofeng Xie Mar 2, 2003
+ * Xiaofeng Xie May 11, 2004
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * Please acknowledge the author(s) if you use this code in any way.
+ *
+ * @References:
+ * [1] Zhang W J, Xie X F, Bi D C. Handling boundary constraints for numerical
+ * optimization by particle swarm flying in periodic search space. Congress
+ * on Evolutionary Computation, Oregon, USA, 2004
+ * @ especially for particle swarm agent
+ */
+
+package net.adaptivebox.space;
+import net.adaptivebox.global.*;
+
+public class DesignSpace {
+ //The information of all the dimension
+ private DesignDim[] dimProps;
+
+ public DesignSpace(int dim) {
+ dimProps = new DesignDim[dim];
+ }
+
+ public DesignDim getDimAt(int index) {
+ return dimProps[index];
+ }
+
+ public void setElemAt(DesignDim elem, int index) {
+ dimProps[index] = elem;
+ }
+
+ public int getDimension() {
+ if (dimProps==null) {
+ return -1;
+ }
+ return dimProps.length;
+ }
+
+ public double boundAdjustAt(double val, int dim){
+ return dimProps[dim].paramBound.boundAdjust(val);
+ }
+
+ public void annulusAdjust (double[] location){
+ for (int i=0; i<getDimension(); i++) {
+ location[i] = dimProps[i].paramBound.annulusAdjust(location[i]);
+ }
+ }
+
+ public void randomAdjust (double[] location){
+ for (int i=0; i<getDimension(); i++) {
+ location[i] = dimProps[i].paramBound.randomAdjust(location[i]);
+ }
+ }
+
+ public boolean satisfyCondition(double[] location){
+ for (int i=0; i<getDimension(); i++) {
+ if (!dimProps[i].paramBound.isSatisfyCondition(location[i])) {
+ return false;
+ }
+ }
+ /*If the limits are not violated, return TRUE*/
+ return(true);
+ }
+
+ public void mutationAt(double[] location, int i){
+ location[i] = dimProps[i].paramBound.getRandomValue();
+ }
+
+ public double mutationUniformAtPointAsCenter (double pointX, int i){
+ double length = this.getMagnitudeIn(i)/2;
+ pointX += RandomGenerator.doubleRangeRandom(-1*length, length);
+
+ return pointX;
+ }
+
+ public double getUpValueAt(int dimensionIndex) {
+ return dimProps[dimensionIndex].paramBound.maxValue;
+ }
+
+ public double getLowValueAt(int dimensionIndex) {
+ return dimProps[dimensionIndex].paramBound.minValue;
+ }
+
+ public double getMagnitudeIn(int dimensionIndex) {
+ return dimProps[dimensionIndex].paramBound.getLength();
+ }
+
+
+ public boolean initilizeGeneAtPointAsCenter(double[] tempX){
+ if (tempX.length!=this.getDimension()) {
+ return false;
+ }
+ for(int i=0;i<tempX.length;i++) {
+ double length = this.getMagnitudeIn(i)/2;
+ tempX[i]+=RandomGenerator.doubleRangeRandom(-1*length, length);
+ }
+ return true;
+ }
+
+ public void initializeGene(double[] tempX){
+ for(int i=0;i<tempX.length;i++) tempX[i] = dimProps[i].paramBound.getRandomValue(); //Global.RandomGenerator.doubleRangeRandom(9.8, 10);
+ }
+
+ public double[] getFreshGene() {
+ double[] tempX = new double[this.getDimension()];
+ initializeGene(tempX);
+ return tempX;
+ }
+ public void getMappingPoint(double[] point) {
+ for(int i=0; i<getDimension(); i++) {
+ point[i] = dimProps[i].paramBound.annulusAdjust(point[i]);
+ if(dimProps[i].isDiscrete()) {
+ point[i] = dimProps[i].getGrainedValue(point[i]);
+ }
+ }
+ }
+
+ public double[] getRealLoc(double[] imageLoc) {
+ double[] realLoc = new double[imageLoc.length];
+ for (int i=0; i<imageLoc.length; i++) {
+ realLoc[i] = imageLoc[i];
+ }
+ annulusAdjust(realLoc);
+ return realLoc;
+ }
+}
+