def main():
# Takes in the file and parses into datum's.
D = cData(sys.argv[1])
# Starting points from the pickle or not.
EmAlg = parseCommandLine(D, sys.argv)
prevCons = 0
totalcons = 0
nmiResult = evaluateEM_NMI(D, EmAlg)
print "Initial nmi: ",nmiResult
consobj = Cons.cCons(D)
for numCons in range(1,len(D.data)/4,1):
consobj.constype = Cons.cCons.eConsType.TripCenterChunk
consobj.centerChunkSize = 0.2
cons = consobj.tripCons(EmAlg.mGammas,numCons-prevCons)
prevCons = numCons
totalcons += len(cons)
for i in cons:
EmAlg.mCij[i[0]][i[1]] = i[2]
EmAlg.mCij[i[1]][i[0]] = i[2]
EmAlg.EM(len(D.classlist))
nmiresult = evaluateEM_NMI(D, EmAlg)
print numCons, ",", nmiresult, ",", totalcons
if(nmiresult > 0.999 or len(D.data)==numCons):
break
def TripConsTest(D, sNum, EMStarts, fp):
fp.write("trips,queries,cons,likelihood,NMI\n")
for option in TripConsOptions.lOptions:
optname = TripConsOptions.lOptionNames[option]
fp.write(optname + "\n")
for iOutertrial in range(numOuterTrials):
print "scenario ", sNum, " options ", optname, " outertrial ", iOutertrial
fp.write("outertrial: %d\n" % iOutertrial)
em = copy.deepcopy(EMStarts[iOutertrial])
em.bPPC = True
prevTrips = 0
totalCons = 0
nmiResult = utils.evaluateEM_NMI(D, em)
fp.write("Initial nmi: %f\n" % nmiResult)
consobj = Cons.cCons(D)
for numTrips in range(1,len(D.data)/4,1):
if option == TripConsOptions.CenterChunkCons:
consobj.constype = Cons.cCons.eConsType.TripCenterChunk
elif option == TripConsOptions.MidCons:
consobj.constype = Cons.cCons.eConsType.TripMids
print em.mLikelihood_il
cons = consobj.tripCons(em.mGammas,numTrips-prevTrips)
prevTrips = numTrips
totalCons += len(cons)
for i in cons:
em.mCij[i[0]][i[1]] = i[2]
em.mCij[i[1]][i[0]] = i[2]
em.EM(len(D.classlist))
nmiresult = utils.evaluateEM_NMI(D, em)
fp.write("%d,%d,%d,%f,%f\n" % (numTrips,
numTrips*14,
totalCons,
em.dEMLikelihood,
nmiresult) )
fp.flush()
if (nmiresult > 0.999 or len(D.data)==numTrips):
break
