def main():
datafs = []
if (len(sys.argv) < 2):
chowderPath = '/home/avanroi1/messages/inbox/chowder_g03zkk7sug'
weirdPathName = '/home/avanroi1/messages/inbox/mualphanugammaomicron_baafcd34pg'
groupmePathName = '/home/avanroi1/groupmeData/theboys'
#groupmePathName = '/home/avanroi1/groupmeData/allupcs'
datafs = [chowderPath, weirdPathName, groupmePathName]
else:
counter = 1
while (counter < len(sys.argv)):
datafs.append(sys.argv[counter])
counter += 1
for f in datafs:
data = getJson(f)
#gmdata = getJson(groupmePathName)
#gcids,gcnames = startGroupMe(gmdata)
args = parseArgs()
#numMessages = getNumMessages(data)
username = args.username
nameVec = data[0]["participants"]
print(nameVec)
nameVec = [x['name'] for x in nameVec]
#nameVec.append(username)
if (debug is True):
print(nameVec)
c2 = Chat(nameVec, data)
#c2= Chat(gcids,gmdata,isGM=True)
c2.popSelfDict()
c2.updateUserStats()
#c2.updateNames(gcnames)
c2.printStats()
corpus, vocab, userOrder = c2.createCorpusAndTokens()
pdb.set_trace()
with open('./conversation.pk', 'wb') as f:
pk.dump(corpus, f)
with open('./vocab.pk', 'wb') as f:
pk.dump(vocab, f)
with open('./userOrder.pk', 'wb') as f:
pk.dump(userOrder, f)
pdb.set_trace()
#print(corpus)
#model = Word2Vec(corpus, size=100, window=5, min_count=1, workers=4)
#model.save("word2vec.model")
if (doModel):
bestmodel, data, targs = doHTBasic(c2)
model, train, test = tryBagOfWords(c2, bestModel=bestmodel)
#pdb.set_trace()
whatevs = bestmodel.predict(["Miss you mangos"])
print(whatevs)
print(bestmodel.best_score_)
print(doPipeLineAcc(bestmodel, data, targs))
print(bestmodel.best_params_)
trainAcc = testAcc(model, train)
trainAcc = testAcc(model, test)
multiClassAcc(model, train)
print("Test set results")
multiClassAcc(model, test)
