def toTwoLevel(var,data):
newdata = []
for d in data:
if d == "stronglyagree":
newdata.append("agree")
elif d == "stronglydisagree":
newdata.append("disagree")
else:
newdata.append(d)
return newdata
b = ModelBuilder()
for var in ["f","mbsa2","mbsa7","mbsa8","mbsa9"]:
b.addNode(var)
b.setLevels(var,["Disagree","Agree"])
#b.setLevels(var,["StronglyDisagree","Disagree","Agree","StronglyAgree"])
b.setInfluence("f","mbsa2",1)
b.setInfluence("f","mbsa7",1)
b.setInfluence("f","mbsa8",1)
b.setInfluence("f","mbsa9",1)
m = b.consume()
data = dataset.fromCSV("experiments/cnesdata.csv")
data = data.discretiseFunc(toTwoLevel)
lincp = NonLinearCPLogicGenerator()
cpcode = lincp.generate(m)
cc = CPCompiler()
runmodel = cc.compileCode(cpcode,data)
