public code v1
This commit is contained in:
Francisco Jesús Martínez Mimbrera
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package flintstones.method.promethee.phase.result;
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import java.util.ArrayList;
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/**
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* @author Alex
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*/
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public class Promethee {
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//----------------- DATOS INICIALES DEL PROBLEMA ----------------------
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float[][] initMatrix;
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int[] MinMax; //0 --> Min || 1 --> Max
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float[] weights;
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int[] typeFunc;
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String[] alternatives;
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String[] criteria;
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//--------------------- VARIABLES INTERNAS ----------------------------
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ArrayList<float[][]> preferencesDegrees;
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ArrayList<float[][]> flowMatrix;
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float[][] globalFlowMatrix;
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float[] p;
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float[] q;
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float[] s;
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public Promethee(String[] alternatives, String[] criterions) {
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this.alternatives = alternatives;
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this.criteria = criterions;
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}
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//-------------------- GETTERS AND SETTERS ---------------------------
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public float[][] getMAtrixFlow(int indexCriterion){
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return flowMatrix.get(indexCriterion);
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}
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public float[][] getGlobalFLow(){
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return globalFlowMatrix;
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}
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//-------------------- PROMETHEE FUNCTIONS ---------------------------
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public void init() {
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preferencesDegrees = new ArrayList<float[][]>();
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flowMatrix = new ArrayList<float[][]>();
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globalFlowMatrix = new float[alternatives.length][3];
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//Inicializamos el vector de matrices para cada criterio enfrentando alternativas con alternativas.
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for (int i = 0; i < criteria.length; ++i) {
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preferencesDegrees.add(new float[alternatives.length][alternatives.length]);
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flowMatrix.add(new float[alternatives.length][3]);
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}
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}
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public void Execute(float[][] initMatrix, float[] weights, int[] MinMax, int[] typeFunc, float[] p, float[] q, float[] s) {
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//Iniciamos los valores
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this.initMatrix = initMatrix;
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this.weights = weights;
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this.MinMax = MinMax;
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this.typeFunc = typeFunc;
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this.p = p;
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this.q = q;
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this.s = s;
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init();
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//Calculamos las matrices.
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calculatePreferences();
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//Calculamos el flujo
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calculateFlow();
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//Calculamos el flujo global según sus pesos.
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calculateGlobalsFlow();
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}
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//Calcula las matrices de preferencia según la función especificada.
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private void calculatePreferences() {
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float d = 0.0f;
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//Nos recorremos los criteros para calcular cada matriz
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for (int iCriterion = 0; iCriterion < criteria.length; iCriterion++) {
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//Enfrentamos las alternativas según el criterio (iCriterion) que estamos calculando.
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for (int iAlternative = 0; iAlternative < alternatives.length; iAlternative++) {
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for (int jAlternative = 0; jAlternative < alternatives.length; jAlternative++) {
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if (iAlternative != jAlternative) {
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//Comprobamos si es de beneficio o de coste.
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d = (MinMax[iCriterion] == 0)
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? -(initMatrix[iAlternative][iCriterion] - initMatrix[jAlternative][iCriterion])
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: (initMatrix[iAlternative][iCriterion] - initMatrix[jAlternative][iCriterion]);
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preferencesDegrees.get(iCriterion)[iAlternative][jAlternative] = getResultFunction(d, iCriterion);
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} else {
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preferencesDegrees.get(iCriterion)[iAlternative][jAlternative] = 0.0f;
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}
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}
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}
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}
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}
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//Calculamos el flujo positivo y negativo de cada matriz según sus criterios.
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private void calculateFlow() {
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float positive = 0, negative = 0;
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for (int i = 0; i < preferencesDegrees.size(); i++) {
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//Caculamos el flujo positivo, negativo y neto.
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for (int iAlt = 0; iAlt < alternatives.length; iAlt++) {
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for (int jAlternative = 0; jAlternative < alternatives.length; jAlternative++) {
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positive += preferencesDegrees.get(i)[iAlt][jAlternative];
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negative += preferencesDegrees.get(i)[jAlternative][iAlt];
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}
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flowMatrix.get(i)[iAlt][0] = positive / (alternatives.length - 1);
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flowMatrix.get(i)[iAlt][1] = negative / (alternatives.length - 1);
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flowMatrix.get(i)[iAlt][2] = flowMatrix.get(i)[iAlt][0] - flowMatrix.get(i)[iAlt][1];
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positive = 0;
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negative = 0;
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}
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}
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}
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//Calculamos el flujo positivo y negativo de cada matriz según sus criterios.
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private void calculateGlobalsFlow() {
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float positive = 0, negative = 0;
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//Caculamos el flujo global positivo, negativo y neto.
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for (int iAlt = 0; iAlt < alternatives.length; iAlt++) {
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for (int j = 0; j < flowMatrix.size(); j++) {
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positive += flowMatrix.get(j)[iAlt][0] * weights[j];
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negative += flowMatrix.get(j)[iAlt][1] * weights[j];
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}
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globalFlowMatrix[iAlt][0] = positive;
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globalFlowMatrix[iAlt][1] = negative;
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globalFlowMatrix[iAlt][2] = positive - negative;
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positive = 0;
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negative = 0;
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}
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}
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//Según la función especificada, te devuelve el valor P(d) correspondiente
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private float getResultFunction(float d, int iCriterion) {
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switch (typeFunc[iCriterion]) {
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case 1:
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if(d > 0 ) return 1;
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else return 0;
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case 2:
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if(d > q[iCriterion] ) return 1;
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else return 0;
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case 3:
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if(d > p[iCriterion] ) return 1;
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else if (d <= 0) return 0;
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else return d / p[iCriterion];
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case 4:
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if(d > p[iCriterion] ) return 1;
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else if (d <= q[iCriterion]) return 0;
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else return 1/2;
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case 5:
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if (d <= q[iCriterion]) {
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return 0.0f;
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} else if (d > p[iCriterion]) {
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return 1.0f;
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} else {
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return ((d - q[iCriterion]) / (p[iCriterion] - q[iCriterion]));
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}
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case 6:
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if(d <= 0 ) return 0;
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else {
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float exponentialFunc = (float) java.lang.Math.exp((-1) * (Math.pow(d, 2) / (2 * Math.pow(s[iCriterion], 2))));
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return 1 - exponentialFunc;
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}
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}
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return -1;
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}
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}
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+148
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package flintstones.method.promethee.phase.result;
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import java.util.HashMap;
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import java.util.Map.Entry;
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import javax.inject.Inject;
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import flintstones.entity.method.phase.PhaseMethod;
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import flintstones.entity.problemelement.ProblemElementKey;
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import flintstones.entity.problemelement.entities.Alternative;
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import flintstones.entity.problemelement.entities.Criterion;
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import flintstones.entity.problemelement.entities.Expert;
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import flintstones.entity.problemelement.entities.ProblemElement;
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import flintstones.entity.problemelement.entities.ProblemElementHelper;
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import flintstones.entity.valuation.Valuation;
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import flintstones.model.problemelement.service.IProblemElementService;
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import flintstones.model.valuation.service.IValuationService;
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import flintstones.valuation.numeric.NumericValuation;
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public class PrometheeResult extends PhaseMethod {
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@Inject
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IProblemElementService problemService;
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@Inject
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IValuationService valuationService;
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// Atributos
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HashMap<ProblemElementKey, Valuation> mapVAluations;
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Alternative[] allAlternatives;
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Criterion[] allCriterion;
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Expert[] Allexperts;
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String[] rowHeaderPromethee;
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Promethee promethee;
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float[] weights;
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float[][] values;
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int[] MinMax;
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public PrometheeResult() {
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}
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@Override
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public String getName() {
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return "Phase Promethee Result";
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}
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//------------------------------- GETS AND SETTERS ---------------------------------
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public void cargarDatos() {
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rowHeaderPromethee = new String[3];
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rowHeaderPromethee[0] = "Positive Flow";
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rowHeaderPromethee[1] = "Negative Flow";
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rowHeaderPromethee[2] = "Neto Flow";
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allAlternatives = ProblemElementHelper.asAlternatives(problemService.getAll(Alternative.Type));
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allCriterion = ProblemElementHelper.asCriterions(problemService.getAll(Criterion.Type));
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Allexperts = ProblemElementHelper.asExperts(problemService.getAll(Expert.Type));
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promethee = new Promethee(getAlternativesNames(), getCriterionNames());
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values = this.getValuations(Allexperts[0]);
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float[] p = (float[]) this.importData("arrayP");
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float[] q = (float[]) this.importData("arrayQ");
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float[] s = (float[]) this.importData("arrayS");
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float[] w = (float[]) this.importData("arrayWeights");
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int[] MinMax = (int[]) this.importData("arrayMinMax");
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int[] typeFunc = (int[]) this.importData("arrayTypeFunc");
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this.promethee.Execute(this.values, w, MinMax, typeFunc, p, q, s);
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}
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public float[][] getValuations(Expert e) {
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String[] alternatives = getAlternativesNames();
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String[] criterions = getCriterionNames();
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float[][] valuation = new float[allAlternatives.length][allCriterion.length];
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//Obtenemos el hashmap
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ProblemElement pE = problemService.getByCanonicalName(Expert.Type, e.getCanonicalName());
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mapVAluations = valuationService.getAllValuationsKVWith(pE);
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//Para cada elemento, introducirlo ordenado en el array
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int a = 0, b = 0;
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for(Entry<ProblemElementKey, Valuation> entry : mapVAluations.entrySet()){
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NumericValuation nV = (NumericValuation) entry.getValue();
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for(int i = 0; i < allAlternatives.length; i++) {
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if(entry.getKey().getAlternative().getName().equals( alternatives[i] )) {
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a = i;
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break;
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}
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}
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for(int i = 0; i < allCriterion.length; i++) {
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if(entry.getKey().getCriterion().getName().equals( criterions[i])) {
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b = i;
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break;
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}
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}
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double number = Double.valueOf(nV.getValue());
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valuation[a][b] = (float) number;
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a = 0;
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b = 0;
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}
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return valuation;
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}
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public float[][] getResult() {
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return promethee.getGlobalFLow();
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}
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public float[][] getCriterionMatrixFlow(int indexCriterion){
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return promethee.getMAtrixFlow(indexCriterion);
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}
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public void executePromethee() {
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}
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public String[] getRowHeaderPromethee() {
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return rowHeaderPromethee;
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}
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public String[] getAlternativesNames() {
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String[] str = new String[allAlternatives.length];
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for(int i = 0; i < allAlternatives.length; i++)
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str[i] = allAlternatives[i].getName();
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return str;
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}
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public String[] getCriterionNames() {
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String[] str = new String[allCriterion.length];
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for(int i = 0; i < allCriterion.length; i++) {
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str[i] = allCriterion[i].getName();
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}
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return str;
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}
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public int numberCriterions() {
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return allCriterion.length;
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}
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}
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