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