def translate(config_path, input_path, output_path):
print('Loading config ... ', end='', flush=True)
with open(config_path, 'r') as f:
config = json.load(f)
print('done !')
dic = Dic()
dic.read_dict(config['dic'], config['word'], True)
translater = Translater(dic, config['model'])
if input_path == '':
translater.shell()
else:
translater.translate_file(input_path, output_path)
return
def train(config_path):
jieba.initialize() # init jieba
print('Loading training config ... ', end='', flush=True)
with open(config_path, 'r') as f:
config = json.load(f)
print('done !')
dic = Dic()
dic.read_dict(config['dic'], config['word'])
trainer = Trainer(dic)
# trainer.feed(config['word'], True)
for data in config['data']:
trainer.feed(data)
trainer.build()
trainer.write_into_file(config['model'])
def main(args):
stats = Stats()
transactions = TransactionsList(args.infile)
if args.algorithm == 'apriori':
algorithm = Apriori(transactions, args.minsup)
else:
algorithm = Dic(transactions, args.minsup, args.m)
large_sets, counter = algorithm.get_large_sets_and_counter()
stats.record_post_large_sets()
rules = RulesGenerator.generate_rules(large_sets, args.minconf, counter, transactions)
stats.record_post_rules()
writer = Writer(args.outfile)
writer.add_args(args)
writer.add_stats(stats)
writer.add_rules(rules)
writer.write()
