def train_save_model(train_time_file):
df = pd.read_csv('./file/' + train_time_file, encoding="utf-8", parse_dates=True, lineterminator="\n")
print "get the dataframe from train_file"
time_interval = time_explore.get_time_interval(train_time_file)
print "train file time interval: " + str(time_interval)
# print "get the time interval"
bm = background_model(new_time_interval = time_interval)
print "initialize the background model"
bm.read_data_frame(df)
print "read in the dataframe"
bm.write_model_to_model_file()
print "write to file"
def train_save_model(train_time_file):
df = pd.read_csv('./file/' + train_time_file,
encoding="utf-8",
parse_dates=True,
lineterminator="\n")
print "get the dataframe from train_file"
time_interval = time_explore.get_time_interval(train_time_file)
print "train file time interval: " + str(time_interval)
# print "get the time interval"
bm = background_model(new_time_interval=time_interval)
print "initialize the background model"
bm.read_data_frame(df)
print "read in the dataframe"
bm.write_model_to_model_file()
print "write to file"
def test_model(test_time_file, threshold = 10):
df = pd.read_csv('./file/' + test_time_file, encoding="utf-8", parse_dates=True, lineterminator="\n")
time_interval = time_explore.get_time_interval(test_time_file)
print "test file time interval: " + str(time_interval)
if time_interval == 0:
time_interval = 1
test_background_model = background_model(new_time_interval = time_interval)
test_background_model.read_data_frame(df)
trained_background_model = background_model()
trained_background_model.read_model_from_model_file()
generator = key_burst(trained_background_model,test_background_model,threshold)
hotwords = generator.detect_hot_words()
hotwords_list = write_hotwords_to_file(hotwords)
return hotwords_list
def test_model(test_time_file, threshold=10):
df = pd.read_csv('./file/' + test_time_file,
encoding="utf-8",
parse_dates=True,
lineterminator="\n")
time_interval = time_explore.get_time_interval(test_time_file)
print "test file time interval: " + str(time_interval)
if time_interval == 0:
time_interval = 1
test_background_model = background_model(new_time_interval=time_interval)
test_background_model.read_data_frame(df)
trained_background_model = background_model()
trained_background_model.read_model_from_model_file()
generator = key_burst(trained_background_model, test_background_model,
threshold)
hotwords = generator.detect_hot_words()
hotwords_list = write_hotwords_to_file(hotwords)
return hotwords_list
