def read_pref(data_folder):
all_score = dict()
all_score['01'] = 0
all_score['10'] = 0
all_score['02'] = 0
all_score['20'] = 0
all_score['12'] = 0
all_score['21'] = 0
met = [
'01_wav_gpr_single_level/', '02_wav_gpr_multi_level/',
'03_wav_gpr_pog/'
]
d = dict()
d[met[0]] = '0'
d[met[1]] = '1'
d[met[2]] = '2'
for score_file in Utility.list_file(data_folder):
if score_file.startswith('.'): continue
if not 'pref' in score_file: continue
# print score_file
score = Utility.load_json('{}/{}'.format(data_folder, score_file))
# print score
for s in score:
# print s, score[s]
for m in score[s]:
# print m, score[s][m]
if (met[0] in m) & (met[1] in m):
if score[s][m] == met[0]:
all_score['01'] = all_score['01'] + 1
else:
all_score['10'] = all_score['10'] + 1
if (met[0] in m) & (met[2] in m):
if score[s][m] == met[0]:
all_score['02'] = all_score['02'] + 1
else:
all_score['20'] = all_score['20'] + 1
if (met[1] in m) & (met[2] in m):
if score[s][m] == met[1]:
all_score['12'] = all_score['12'] + 1
else:
all_score['21'] = all_score['21'] + 1
print '-----------------------------------------'
for k in ['01', '10', '02', '20', '12', '21']:
print k, all_score[k]
def read_mos(data_folder):
all_score = dict()
c_all_score = dict()
count = dict()
for score_file in Utility.list_file(data_folder):
if score_file.startswith('.'): continue
if not 'mos' in score_file: continue
# print score_file
score = Utility.load_json('{}/{}'.format(data_folder, score_file))
for s in score:
# print score[s]
for k in score[s]:
# print k, score[s][k]
if k in all_score:
all_score[k] = all_score[k] + float(score[s][k])
# if k=='01_GPR_single_level/':
# print float(score[s][k]), all_score[k]
count[k] = count[k] + 1
c_all_score[k].append(float(score[s][k]))
else:
all_score[k] = float(score[s][k])
count[k] = 1
c_all_score[k] = []
c_all_score[k].append(float(score[s][k]))
print '-----------------------------------------'
for k in all_score:
print k, all_score[k]
print count[k]
print all_score[k] / count[k]
print 'Mean :', np.average(c_all_score[k]), 'Var :', np.var(
c_all_score[k])
sys.path.append('/home/h1/decha/Dropbox/python_workspace/Utility/')
sys.path.append('../../')
sys.path.append('../')
sys.path.append('/home/h1/decha/Dropbox/python_workspace/Inter_speech_2016/')
import matplotlib.mlab as mlab
from tool_box.util.utility import Utility
import scipy.stats as stats
from DataModel.Syllables.Syllable import Syllable
from DataModel.Syllables.SyllableDatabaseManagement import SyllableDatabaseManagement
import numpy as np
import matplotlib.pyplot as plt
if __name__ == '__main__':
dur_path = '/home/h1/decha/Dropbox/Inter_speech_2016/Syllable_level_prediction/01_single_space/testrun/out/tsc/a-i/speech_param/a-i/demo/seed-00/M-1024/B-1024/num_iters-5/dur/param_mean/tscsdj02.npy'
obj = np.load(dur_path)
# print obj
json = '/home/h1/decha/Dropbox/python_workspace/Inter_speech_2016/playground/generate_json/latent_data/tscsdj02.lab.json'
np.set_printoptions(precision=3)
json = Utility.load_json(json)
for idx, j in enumerate(json):
d = np.array(j['duration'])
print d
print obj[idx]
print '---------------------------'
pass
