def tokenize_and_output(csv_filename, tokenizers_by_key_of_description, output_filename, key_of_code,
keys_of_descriptions, vocab, delimiter, code_prefix,
use_descriptions=True, stop_words=None):
reader = CSVReader(csv_filename, delimiter)
dataset = reader.read_from_file()
try:
#os.remove(output_filename)
pass
except OSError:
pass
with open(output_filename, 'w+') as out_file:
for record in dataset:
tokenized_record = []
if use_descriptions:
for key_of_description in keys_of_descriptions:
tokenizer = tokenizers_by_key_of_description[key_of_description]
tokenized_record.extend(tokenizer.tokenize(record[key_of_description]))
if stop_words != None:
tokenized_record = [w for w in tokenized_record if w.lower() not in stop_words]
tokenized_record = tokenize_code(record[key_of_code], code_prefix) + tokenized_record
output_line = " ".join(tokenized_record)
vocab.update(tokenized_record)
print(output_line, file=out_file)
exit(-1)
token_file = sys.argv[1]
vector_file = sys.argv[2]
code_type = sys.argv[3]
catalog = sys.argv[4]
phrase = sys.argv[5]
start = time.clock()
if code_type not in ['ICD', 'CHOP', 'DRG']:
print("Code type has to be one of ICD|DRG|CHOP")
exit(-2)
print("Reading catalog")
reader = CSVReader(catalog, ',')
descriptions_de = {}
dataset = reader.read_from_file()
for record in dataset:
descriptions_de[code_type + '_' + record['code'].replace('.', '').upper()] = record['text_de']
print("Reading vectors and tokens..")
vector_by_token = read_vectors(vector_file)
res = read_code_vectors(vector_by_token, token_file)
vectors_by_codes = res['vectors']
tokens_by_codes = res['tokens']
code_vocab = []
for code in vectors_by_codes.keys():
if(code.startswith(code_type)):
exit(-1)
token_file = sys.argv[1]
vector_file = sys.argv[2]
code_type = sys.argv[3]
catalog = sys.argv[4]
phrase = sys.argv[5]
start = time.clock()
if code_type not in ['ICD', 'CHOP', 'DRG']:
print("Code type has to be one of ICD|DRG|CHOP")
exit(-2)
print("Reading catalog")
reader = CSVReader(catalog, ',')
descriptions_de = {}
dataset = reader.read_from_file()
for record in dataset:
descriptions_de[code_type + '_' + record['code'].replace(
'.', '').upper()] = record['text_de']
print("Reading vectors and tokens..")
vector_by_token = read_vectors(vector_file)
res = read_code_vectors(vector_by_token, token_file)
vectors_by_codes = res['vectors']
tokens_by_codes = res['tokens']
code_vocab = []
for code in vectors_by_codes.keys():
