"""Write trained GMM model"""
from gmmClassifier import train_model, load_data, get_train_data
import sys
import os
import numpy as np
if __name__=='__main__':
npzdir = sys.argv[1]
modeldir = sys.argv[2]
n_components = sys.argv[3]
covar = sys.argv[4]
lang = sys.argv[5]
data = load_data(npzdir, [lang])
train_lang_list = get_train_data(data, lang)
model = train_model(train_lang_list, int(n_components), covar)
print 'Trained', covar, 'model for', lang, 'with', n_components
if not os.path.isdir(modeldir):
os.mkdir(modeldir)
if not os.path.isdir(os.path.join(modeldir, lang)):
os.mkdir(os.path.join(modeldir, lang))
model.weights_.dump(os.path.join(modeldir, lang,
covar+'-'+n_components+'-'+lang+'.weights'))
model.means_.dump(os.path.join(modeldir, lang,
covar+'-'+n_components+'-'+lang+'.means'))
model.covars_.dump(os.path.join(modeldir, lang,
covar+'-'+n_components+'-'+lang+'.covars'))
import os
import numpy as np
if __name__=='__main__':
npzdir = sys.argv[1]
modeldir = sys.argv[2]
n_components = sys.argv[3]
covar = sys.argv[4]
#load models
models = {}
# langlist = ['MA', 'KO', 'IN', 'AR', 'HI', 'CZ', 'FR']
langlist = sys.argv[5:]
for lang in langlist:
if os.path.exists(os.path.join(modeldir, lang,
covar+'-'+n_components+'-'+lang+'.weights')):
models[lang] = GMM(n_components=int(n_components), covariance_type=covar)
models[lang].weights_ = np.load(os.path.join(modeldir, lang,
covar+'-'+n_components+'-'+lang+'.weights'))
models[lang].means_ = np.load(os.path.join(modeldir, lang,
covar+'-'+n_components+'-'+lang+'.means'))
models[lang].covars_ = np.load(os.path.join(modeldir, lang,
covar+'-'+n_components+'-'+lang+'.covars'))
else:
print 'Error: model not trained with these parameters for', lang
#load data
#langlist = models.keys()
data = load_data(npzdir, langlist)
run_test(models, data)
