def runDE(baselineMin, baselineMax, modelObj, deRunCountParam, runCountParam, constraintFileNameParam):
#import IO_Utility
#print "### Executing D.E. "
out_normscore, out_decVec = de(runCountParam, constraintFileNameParam, modelObj,baselineMin,baselineMax,deRunCountParam)
tempObj = modelObj(constraintFileNameParam, runCountParam)
objByDecVec = tempObj.getobjfromdecision(out_decVec)
print "Normalized Score ...", out_normscore
print "The objective scores after all minimization ....UnAc={}, UnPass={}".format(objByDecVec[0], objByDecVec[1])
def runDE(baselineMin, baselineMax, modelObj, deRunCountParam, runCountParam,
constraintFileNameParam):
#import IO_Utility
#print "### Executing D.E. "
out_normscore, out_decVec = de(runCountParam, constraintFileNameParam,
modelObj, baselineMin, baselineMax,
deRunCountParam)
tempObj = modelObj(constraintFileNameParam, runCountParam)
objByDecVec = tempObj.getobjfromdecision(out_decVec)
print "Normalized Score ...", out_normscore
print "The objective scores after all minimization ....UnAc={}, UnPass={}".format(
objByDecVec[0], objByDecVec[1])
def __init__(self, num):
self.id = num
self.score = 0
self.de = de()
self.nom = ""
self.init_nom()
def tunetest(predict): de() The.option.tuning = False predicttest(predict,"Tuned_WHERE")
def tunetest(predict):
de()
The.option.tuning = False
predicttest(predict, "Tuned_WHERE")
def test_res(self):
for i in range(100):
lance = de().lancer()
self.assertTrue(lance >= 1)
self.assertTrue(lance <= 6)
def test_de(self):
self.assertTrue(len(de().model) == 6)
