def get_list_name(file_list_name):
file_names = read.textfile2list(file_list_name)
file_simple = [
file_name.split("/")[-1] for file_name in file_names
if "THYMEColonFinal" in file_name
]
read.savein_json(file_list_name.replace(".txt", "_simple"), file_simple)
def get_train():
file_dev = read.readfrom_json("data/dev_file_simple")
train_all_simple = read.readfrom_json("data/train_all_simple")
train = [
train_file for train_file in train_all_simple
if train_file not in file_dev
]
read.savein_json("data/train_simple", train)
def document_level_2_sentence_level(file_dir, raw_data_path, preprocessed_path,
xml_path, file_format):
max_len_all = list()
char_vocab = defaultdict(float)
for data_id in range(0, len(file_dir)):
raw_text_path = os.path.join(raw_data_path, file_dir[data_id],
file_dir[data_id])
preprocessed_file_path = os.path.join(preprocessed_path,
file_dir[data_id],
file_dir[data_id])
raw_text = read.readfrom_txt(raw_text_path)
raw_text = process.text_normalize(raw_text)
sent_span_list_file, max_len_file, char_vocab = split_by_sentence(
raw_text, char_vocab)
max_len_all += max_len_file
read.savein_json(preprocessed_file_path + "_sent", sent_span_list_file)
if xml_path != "":
xml_file_path = os.path.join(xml_path, file_dir[data_id],
file_dir[data_id] + file_format)
posi_info_dict = process.extract_xmltag_anafora(
xml_file_path, raw_text)
sent_tag_list_file = xml_tag_in_sentence(sent_span_list_file,
posi_info_dict)
read.savein_json(preprocessed_file_path + "_tag",
sent_tag_list_file)
max_len_all.sort(reverse=True)
max_len_file_name = "/".join(
preprocessed_path.split('/')[:-1]) + "/max_len_sent"
read.savein_json(max_len_file_name, max_len_all)
def document_level_2_sentence_level(file_dir, raw_data_path, preprocessed_path,
xml_path, file_format):
max_len_all = list()
char_vocab = defaultdict(float)
for data_id in range(0, len(file_dir)):
#raw_text_path = os.path.join(raw_data_path,file_dir[data_id],file_dir[data_id])
#preprocessed_file_path = os.path.join(preprocessed_path,file_dir[data_id],file_dir[data_id])
raw_text_path = os.path.join(raw_data_path, file_dir[data_id])
preprocessed_file_path = os.path.join(preprocessed_path,
file_dir[data_id])
raw_text = read.readfrom_txt(raw_text_path)
raw_text = process.text_normalize(raw_text)
#print('raw_text - %s' % raw_text)
#print('raw_text AFTER NORMALIZE - %s' % raw_text)
sent_span_list_file, max_len_file, char_vocab = split_by_sentence(
raw_text, char_vocab)
#print('sent_span_list_file - %s, max_len_file - %s,char_vocab - %s ' % (sent_span_list_file, max_len_file, char_vocab))
max_len_all += max_len_file
read.savein_json(preprocessed_file_path + "_sent", sent_span_list_file)
if xml_path != "":
xml_file_path = os.path.join(xml_path, file_dir[data_id],
file_dir[data_id] + file_format)
#xml_file_path = os.path.join(xml_path, file_dir[data_id] + file_format)
print('xml_file_path - %s' % xml_file_path)
posi_info_dict = process.extract_xmltag_anafora(
xml_file_path, raw_text)
print('posi_info_dict - ')
for key, value in posi_info_dict.items():
print(key, value)
sent_tag_list_file = xml_tag_in_sentence(sent_span_list_file,
posi_info_dict)
#print('sent_tag_list_file - %s' % sent_tag_list_file)
read.savein_json(preprocessed_file_path + "_tag",
sent_tag_list_file)
print('max_len_all - %s' % max_len_all)
max_len_all.sort(reverse=True)
max_len_file_name = "/".join(
preprocessed_path.split('/')[:-1]) + "/max_len_sent"
read.savein_json(max_len_file_name, max_len_all)
def document_level_2_sentence_level(file_dir, raw_data_path, preprocessed_path,
xml_path, file_format):
max_len_all = list()
char_vocab = defaultdict(float)
pos_vocab = defaultdict(float)
unicode_vocab = defaultdict(float)
word_vocab = defaultdict(float)
for data_id in range(0, len(file_dir)):
raw_text_path = os.path.join(raw_data_path, file_dir[data_id],
file_dir[data_id])
preprocessed_file_path = os.path.join(preprocessed_path,
file_dir[data_id],
file_dir[data_id])
raw_text = read.readfrom_txt(raw_text_path)
raw_text = process.text_normalize(raw_text)
sent_span_list_file, max_len_file, char_vocab = split_by_sentence(
raw_text, char_vocab)
max_len_all += max_len_file
pos_sentences, pos_vocab = process.get_pos_sentence(
sent_span_list_file, pos_vocab)
#pos_sentences = read.readfrom_json("data/pos_sentences")#read.savein_json("data/pos_sentences",pos_sentences)
word_sentences, word_vocab = process.get_words(sent_span_list_file,
word_vocab)
pos_sentences_character = process.word_pos_2_character_pos(
sent_span_list_file, pos_sentences)
unico_sentences_characte, unicode_vocab = process.get_unicode(
sent_span_list_file, unicode_vocab)
read.savein_json(preprocessed_file_path + "_sent", sent_span_list_file)
read.savein_json(preprocessed_file_path + "_pos",
pos_sentences_character)
read.savein_json(preprocessed_file_path + "_unicodecategory",
unico_sentences_characte)
read.savein_json(preprocessed_file_path + "_words", word_sentences)
if xml_path != "":
xml_file_path = os.path.join(xml_path, file_dir[data_id],
file_dir[data_id] + file_format)
posi_info_dict = process.extract_xmltag_anafora(
xml_file_path, raw_text)
sent_tag_list_file = xml_tag_in_sentence(sent_span_list_file,
posi_info_dict)
read.savein_json(preprocessed_file_path + "_tag",
sent_tag_list_file)
#read.savein_json("data/word_vocab", word_vocab)
max_len_all.sort(reverse=True)
max_len_file_name = "/".join(
preprocessed_path.split('/')[:-1]) + "/max_len_sent"
read.savein_json(max_len_file_name, max_len_all)