def testRankingRules():
print('*-------- Testing Ranking Rules -------')
t = RandomPerformanceTableau(numberOfActions=5)
t.save()
t.showPerformanceTableau()
scores = t.computeWeightedAveragePerformances(isNormalized=True,
lowValue=0.0,
highValue=20.0)
ranking = []
for x in t.actions:
ranking.append((scores[x], x))
ranking.sort(reverse=True)
print(ranking)
g = BipolarOutrankingDigraph(t)
g.exportGraphViz()
gcd = CoDualDigraph(g)
gcd.exportGraphViz()
#gcd._computeRankedPairsOrder(Debug=True)
#print(gcd._computeRankedPairsOrder())
gcd.computeKemenyOrder(Debug=True)
print(gcd.computeKemenyRanking(seed=1, sampleSize=500))
gcd.computeSlaterOrder(Debug=True)
print(gcd.computeSlaterOrder(isProbabilistic=False, seed=1,
sampleSize=500))
def testCBPerformanceTableau():
print('*==>> random CB Performance Tableaux ------------*')
t = RandomCBPerformanceTableau(numberOfActions=10,\
commonPercentiles={'ind':5,'pref':10,'veto':95},\
weightDistribution="random",\
weightScale=[1,2],\
IntegerWeights=True,\
commonMode=["normal",50.0,25.0])
t.showCriteria(Debug=False)
g = BipolarOutrankingDigraph(t)
g.exportGraphViz()
#t.showPerformanceTableau()
g.showRelationTable()
