def testEquiSignificanceMajorityOutrankingDigraph():
print('*---- test equi-significance majority outranking digraphs ---*')
t = FullRandomPerformanceTableau(numberOfActions=7, numberOfCriteria=13)
g = EquiSignificanceMajorityOutrankingDigraph(t)
print(g.computeWeightPreorder())
g.showRelationTable()
gr = RobustOutrankingDigraph(t)
gr.showRelationTable()
def testPolarisedOutrankingDigraph():
print('==>> Testing PolarisedOutrankingDigraph instantiation')
t = FullRandomPerformanceTableau()
g = BipolarOutrankingDigraph(t)
print(g.valuationdomain)
ch = PolarisedOutrankingDigraph(g,
level=50,
AlphaCut=False,
KeepValues=True)
ch.showAll()
ch.showStatistics()
def testFullRandomPerformanceTableau():
print('==>> Testing Full Random Performance Tableau instantiation')
t = FullRandomPerformanceTableau(numberOfActions=10,
numberOfCriteria=7,
seed=100)
t.showAll()
print(t)
print(
t.computeWeightedAveragePerformances(isNormalized=True,
lowValue=0.0,
highValue=20.0))
t = FullRandomPerformanceTableau(weightScale=(1, 10),
commonMode=('triangular', 30, 0.5),
seed=None)
t.showStatistics()
t = FullRandomPerformanceTableau(weightScale=(1, 10),
commonScale=(0.0, 50),
commonMode=('beta', None, None),
seed=None)
t.showStatistics()
def testFullRandomOutrankingDigraph():
print('*==>> testing full random outranking Digraphs ----*')
t = FullRandomPerformanceTableau()
#t = RandomCBPerformanceTableau()
t.showAll()
g = BipolarOutrankingDigraph(t)
g.showCriteria()
g.showPerformanceTableau()
g.showEvaluationStatistics()
## g.showStatistics()
g.showVetos(realVetosOnly=True)
print('criteria significance concentration: ',
g.computeWeightsConcentrationIndex())
def testPerformanceTableauStatistics():
print('*==>> performanceTableau statistics ---------*')
t = FullRandomPerformanceTableau(commonScale=(0.0, 100.0),
numberOfCriteria=10,
numberOfActions=10,
commonMode=('triangular', 30.0, 0.7))
t.showStatistics()
print(
t.computeNormalizedDiffEvaluations(lowValue=0.0,
highValue=100.0,
withOutput=True,
Debug=True))
t = RandomCBPerformanceTableau()
t.showStatistics()
t.showEvaluationStatistics()
def testRobustoutranking():
print('*==>> robust outranking ------------------*')
t0 = FullRandomPerformanceTableau(numberOfActions=7, numberOfCriteria=5)
t0.saveXMCDA2('testXMLRubis')
t = XMCDA2PerformanceTableau('testXMLRubis')
g = BipolarOutrankingDigraph(t)
g.showRelationTable()
go = OrdinalOutrankingDigraph(t)
go.showRelationTable()
gu = UnanimousOutrankingDigraph(t)
gu.showRelationTable()
gc = BipolarOutrankingDigraph(t)
gc.showRelationTable()
gor = OldRobustOutrankingDigraph(t)
gor.showRelationTable()
def testForcedBestSingleChoice():
print('*==>> testing forced best single choice ----*')
t = FullRandomPerformanceTableau(numberOfActions=15)
g = BipolarOutrankingDigraph(t)
g.showRubyChoice()
print(g.forcedBestSingleChoice())