from datahandler import DataHandler
from HMM import unsupervised_HMM
import pickle
import networkx as nx
import matplotlib.pyplot as plt
import pylab
VERSES = ['2quatrain', 'volta', 'couplet']
READ_FOLDER = 'modelsToLoad/'
WRITE_FOLDER = 'modelsSaved/'
dh = DataHandler()
X = {}
X[VERSES[0]], X[VERSES[1]], X[VERSES[2]] = dh.get_data()
topN = 10
for verse in VERSES:
if verse is not '2quatrain':
continue
X_processed, X_conversion = dh.quantify_observations(X[verse])
#HMM = pickle.load(open(READ_FOLDER+'600_30states/HMM_'+verse+'.p', 'rb'))
HMM = pickle.load(open(READ_FOLDER + 'HMM_' + verse + '.p', 'rb'))
G = nx.DiGraph()
for state in range(HMM.L):
# for nxt in range(HMM.L):
# if HMM.A[state][nxt] > 0.1:
# weight = '%.2f' % HMM.A[state][nxt]
