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())