def run_gen(full_path, dur_path, lf0_path, start, stop):
for sett in Utility.char_range(start, stop):
dur_set_path = '{}/{}/'.format(dur_path, sett)
full_set_path = '{}/{}/'.format(full_path, sett)
lf0_set_path = '{}/{}/'.format(lf0_path, sett)
if not (Utility.is_dir_exists(dur_set_path)
& Utility.is_dir_exists(full_set_path)
& Utility.is_dir_exists(lf0_set_path)):
print 'No set : ', sett
continue
for f in Utility.list_file(full_set_path):
if f.startswith('.'): continue
print f
base = Utility.get_basefilename(f)
dur_list = '{}/{}.dur'.format(dur_set_path, base)
lf0_list = '{}/{}/'.format(lf0_set_path, base)
full_list = '{}/{}.lab'.format(full_set_path, base)
run_make_obj_for_an_utterance(full_list, dur_list, lf0_list)
# sys.exit(0)
pass
for ch in Utility.char_range('a', 'z'):
if ch == 'j' : continue
set_stress_path = '{}/{} lab/'.format(stress_path, ch)
set_utt_base_path = '{}/{}/'.format(utt_base_path, ch)
set_syllable_full_path = '{}/{}/'.format(syllable_full_path, ch)
set_out_path = '{}/{}/'.format(out_path, ch)
Utility.make_directory(set_out_path)
if Utility.is_dir_exists(set_stress_path) & Utility.is_dir_exists(set_utt_base_path):
print ch
for i in xrange(1, 51):
name = 'tscsd{}{}'.format(ch, Utility.fill_zero(i, 2))
yaml_filename = '{}/{}.utt.yaml'.format(set_utt_base_path, name )
if not Utility.is_file_exist(yaml_filename):
continue
full_file = '{}/{}.lab'.format(set_syllable_full_path, name)
count = [0]
yaml = Utility.yaml_load(yaml_filename)
add_stress(yaml, count, name)
out_path = '/work/w2/decha/Data/GPR_speccom_data/lf0_in_syllable/'
plot_out_path = '/work/w2/decha/Data/GPR_speccom_data/f0_in_syllable_plot/'
start = 'k'
stop = 'z'
Utility.make_directory(plot_out_path)
for sett in Utility.char_range(start, stop):
print sett
set_path = '{}/{} lab/'.format(stress_data_path, sett)
if not Utility.is_dir_exists(set_path):
print 'Inexist : {}'.format(set_path)
continue
lf0_set_path = '{}/{}/'.format(lf0_path, sett)
out_set_path = '{}/{}/'.format(out_path, sett)
plot_set_out = '{}/{}/'.format(plot_out_path, sett)
Utility.make_directory(plot_set_out)
for f in Utility.list_file(set_path):
if f.startswith('.'):
continue
n_clusters = xrange(2, 6)
n_neighbor = [0.025, 0.05, 0.075, 0.1, 0.2]
# base_path = '/work/w23/decha/decha_w23/Second_Journal/Unsupervised_learning_result/15_Agglomerative_clustering/'
base_path = '/work/w23/decha/decha_w23/Second_Journal/Unsupervised_learning_result/15_Agglomerative_clustering_pca/'
tex_file = []
tex_file.append('\\documentclass{article}')
tex_file.append('\\usepackage{geometry}')
tex_file.append('\\usepackage[usenames, dvipsnames]{color}')
tex_file.append('\\geometry{margin=1cm}')
tex_file.append('\\usepackage[english]{babel}')
tex_file.append('\\usepackage{graphicx}')
tex_file.append('\\begin{document}')
for t in xrange(5):
for f in ['nasal', 'no', 'non-nasal']:
# for v in ['long', 'short']:
name = '{}_{}'.format(t, f)
name_path = '{}/{}/'.format(base_path, name)
if Utility.is_dir_exists(name_path):
print name
gen_latex(name_path, n_clusters, n_neighbor, name)
tex_file.append('\\end{document}')
Utility.write_to_file_line_by_line('{}/all.tex'.format(base_path), tex_file)
pass
alpha, beta, rmse, l)
pass
if __name__ == '__main__':
predictive = '/work/w21/decha/Interspeech_2017/Result/03_Given_syllable_dct_with_weigth/num_dct_cov_7/'
org_path = '/work/w2/decha/Data/GPR_speccom_data/data_before_remove_silence/lf0/tsc/sd/j/'
tmp_path = './tmp/'
Utility.make_directory(tmp_path)
basename = 'tscsdj'
vuv_path = '/work/w21/decha/Interspeech_2017/GPR_data/450/param_align/lf0/param_mean/'
for alpha in np.arange(0.1, 2, 0.1):
for beta in np.arange(0.1, 2, 0.1):
alpha_beta_path = '{}/alpha_{}_beta_{}/'.format(
predictive, alpha, beta)
if Utility.is_dir_exists(alpha_beta_path):
run_cal_distortion(basename, tmp_path, alpha_beta_path, alpha,
beta)
pass
