normjoin('C:\Experiments\JK302'))
#filehandler = open(dataDir + '\\sc.pickle', 'w')
#pickle.dump(sc, filehandler)
sc.phonTable.to_csv(dataDir + '\\phonTable.csv')
# Make pandas table
sentT = pd.DataFrame(lktable)
#Join the ngram and IPHoD info and "correctness" at the word level
wordT = pd.concat([sc.tngram, sc.tphod], axis=1, join_axes=[sc.tngram.index])
#
#Table with phoneme Level info
phonT = sc.phonTable
bigPhonT = pd.concat([
landkit.IndexFill(sentT, phonT['SentenceCount'], phonT['PhonemeCount']),
landkit.IndexFill(wordT, phonT['WordCount'], phonT['PhonemeCount']), phonT
],
axis=1,
join_axes=[phonT.index])
audioTableTM = pd.DataFrame.from_csv(normjoin(tablePath, 'audioTableTM.csv'))
audioTableTM['PhonemeIndex'] = [int(x) for x in audioTableTM['PhonemeIndex']]
#atm = audioTableTM.groupby(['Talker','SentenceID']).first().reset_index()
bigPhonT = pd.merge(bigPhonT,
audioTableTM,
how='left',
on=['Talker', 'SentenceID', 'PhonemeIndex'])
del bigPhonT['TargetPhoneme_y']
bigPhonT = bigPhonT.rename(columns={'TargetPhoneme_x': 'TargetPhoneme'})
lktable['SourceSentence'] = lktable['SourceSentence'].fillna(" ")
sc = landkit.SentCompare(list(lktable['FullSentence']),list(lktable['SourceSentence']),True,normjoin('C:\Experiments\JK310'))
#filehandler = open(dataDir + '\\sc.pickle', 'w')
#pickle.dump(sc, filehandler)
sc.phonTable.to_csv(dataDir+'\\phonTable.csv')
# Make pandas table
sentT = pd.DataFrame(lktable)
#Join the ngram and IPHoD info and "correctness" at the word level
wordT = pd.concat([sc.tngram, sc.tphod], axis=1, join_axes=[sc.tngram.index])
#
#Table with phoneme Level info
phonT = sc.phonTable
bigPhonT = pd.concat([landkit.IndexFill(sentT,phonT['SentenceCount'],phonT['PhonemeCount']),landkit.IndexFill(wordT,phonT['WordCount'],phonT['PhonemeCount']),phonT], axis=1, join_axes=[phonT.index])
audioTableTM = pd.DataFrame.from_csv(normjoin(tablePath,'audioTableTM.csv'))
audioTableTM['PhonemeIndex']= [int(x) for x in audioTableTM['PhonemeIndex']]
#atm = audioTableTM.groupby(['Talker','SentenceID']).first().reset_index()
bigPhonT = pd.merge(bigPhonT,audioTableTM, how='left', on=['Talker','SentenceID','PhonemeIndex'])
del bigPhonT['TargetPhoneme_y']
bigPhonT=bigPhonT.rename(columns = {'TargetPhoneme_x':'TargetPhoneme'})
#subjectTable = pd.DataFrame.from_csv(normjoin(dataDir,'SubjectInfoJK302.csv')).reset_index()
#bigPhonT = pd.merge(bigPhonT,subjectTable,how='left',on=['Subject'])
POSTable = pd.DataFrame.from_csv(normjoin(tablePath,'posTags_r1.csv')).reset_index()
POSTable=POSTable.rename(columns = {'Subject':'Talker'})
POSTable=POSTable.rename(columns = {'File':'SentenceID'})
POSTable['Talker'] = POSTable['Talker'].apply(lambda x: 's' +x)