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electre.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# electre.py
#
# Copyright 2011 Fco Javier Lucena <[email protected]>
#
# ReglajesF1 is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# ReglajesF1 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 General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with ReglajesF1; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston,
# MA 02110-1301, USA.
from math import sqrt
class Electre:
def __init__ (self,alternativas, atributos):
self.alternativas = alternativas
self.atributos = atributos
self.pesos = [0] * atributos
self.optimo = [0] * atributos
self.decisional = [] #[[0] * atributos] * alternativas
self.normalizada = [[0] * atributos] * alternativas
self.ponderada = [[0] * atributos] * alternativas
self.concordada = [[0] * atributos] * alternativas
self.discordada = [[0] * atributos] * alternativas
self.dominancia = [[0] * atributos] * alternativas
def establecerPesos(self, prioridad):
total = 0.0
for i in range(0, self.atributos):
total += prioridad[i]
for i in range(0, self.atributos):
self.pesos[i] = prioridad[i]
def establecerOptimo(self, optimo):
for i in range(0, self.atributos):
self.optimo[i] = optimo[i]
def establecerDecisional(self, decisional):
for d in decisional:
self.decisional.append(d)
def establecerNormalizada(self):
for j in range(0, self.atributos):
suma = 0
for i in range(0, self.alternativas):
cuadrado = self.decisional[i][j] * self.decisional[i][j]
suma = suma + cuadrado
suma = sqrt(suma)
for i in range(0, self.alternativas):
self.normalizada[i][j] = (self.decisional[i][j] / suma)
def establecerPonderada(self):
for i in range(0, self.alternativas):
for j in range(0, self.atributos):
self.ponderada[i][j] = self.normalizada[i][j] * self.pesos[j]
def establecerConcordada(self):
for i in range(0, self.alternativas):
self.concordada[i][self.atributos - 1] = self.ponderada[i][self.atributos-1]
media = 0
contador = 0
for i in range(0, self.alternativas):
for k in range(i+1, self.alternativas):
contador = contador + 1
suma = 0
for j in range(0, self.atributos):
if (((self.normalizada[i][j] >= self.ponderada[k][j]) and (self.optimo[j] == 1)) or ((self.ponderada[i][j] <= self.ponderada[k][j]) and (self.optimo[j]==0))):
suma = suma + self.pesos[j]
self.concordada[i][k] = suma
self.concordada[k][i] = 1 - suma
media = media + suma
media = media / contador
for i in range(0, self.alternativas):
for k in range(0, self.alternativas):
if self.concordada[i][k] >= media :
self.concordada[i][k] = 1
else:
self.concordada[i][k] = 0
if i == k:
self.concordada[i][k] = 0
def establecerDiscordada(self):
for i in range(0, self.alternativas):
self.discordada[i][self.atributos - 1] = self.concordada[i][self.atributos-1]
media = 0
for i in range(0, self.alternativas):
for k in range(0, self.alternativas):
maximo = 0
maximo_globlal = 0
if i != k:
for j in range(0, self.atributos):
maximo_actual = self.concordada[i][j] - self.concordada[k][j]
if maximo_actual < 0:
maximo_actual = maximo_actual * (-1.0)
if maximo_actual > maximo_global:
maximo_globlal = maximo_actual
if (((self.concordada[i][j] < self.concordada[k][j]) and (self.optimo[j] == 1)) or ((self.ponderada[i][j] > self.ponderada[k][j]) and (self.optimo[j] == 0))):
maximo_actual = self.concordada[i][j] - self.concordada[k][j]
if maximo_actual < 0:
maximo_actual = maximo_actual * (-1.0)
if maximo_actual > maximo:
maximo = maximo_actual
self.discordada[i][k] = maximo / maximo_global
media = media + self.discordada[i][k]
media = media / ((self.alternativas * self.alternativas) - this.alternativas)
for i in range(0, self.alternativas):
for k in range(0, self.alternativas):
if i != k:
if self.discordada[i][k] <= media:
self.discordada[i][k] = 1
else:
self.discordada[i][k] = 0
else:
self.discordada[i][k] = 0
def establecerDominada(self):
for i in range(0, self.alternativas):
for j in range(0, self.atributos):
self.dominancia[i][j] = 0
for i in range(0, self.alternativas):
self.dominancia[i][self.alternativas - 1] = self.concordada[i][self.alternativas - 1]
for i in range(0, self.alternativas):
for j in range(0, self.alternativas):
if self.concordada[i][j] == self.discordada[i][j]:
self.dominancia[i][j] = self.concordada[i][j]
def resolver(self, decisional, prioridad, optimo):
self.establecerPesos(prioridad)
self.establecerOptimo(optimo)
self.establecerDecisional(decisional)
self.establecerNormalizada()
self.establecerPonderada()
self.establecerConcordada()
self.establecerConcordada()
self.establecerDominada()
print "DECISIONAL"
self.mostrar(self.decisional)
print "NORMALIZADA"
self.mostrar(self.normalizada)
print "PONDERADA"
self.mostrar(self.ponderada)
print "CONCORDADA"
self.mostrar(self.concordada)
print "DISCORDADA"
self.mostrar(self.discordada)
print "DOMINANCIA"
self.mostrar(self.dominancia)
mejor = False
reglaje = 0
j=0
for i in range(0, self.alternativas):
mejor = True
while (j<self.atributos and mejor):
if self.dominancia[i][j] == 1.0:
mejor = False
else:
reglaje = i
j = j+1
return reglaje
def mostrar(self, matriz):
for i in range(0, self.alternativas):
for j in range(0, self.atributos):
print matriz[i][j],
print