def craw_result_process(root=Dir.res + "/data/"):
files = ftools.get_files(root)
data = []
for i in range(len(files)):
filename = files[i]
if len(data) > 10:
break
lines = ftools.read_lines(root + filename)
for line in lines:
tmp = line.split(",")
# print("news",len(tmp[2]))
# print("news",tmp[2])
#
# print("abstract",len(tmp[1]))
# print("abstract",tmp[1])
abstract = tools.seperate_sentences(tmp[1])
news = tools.seperate_sentences(tmp[2])
print(abstract)
print(news)
# input()
jude = data_filter(news, abstract)
if jude > 0.5:
data.append(['\n'.join(abstract), '\n'.join(news)])
return data
def __init__(self):
self.auto = AutoCoder()
self.name = "fast encoder"
self.data ={}
path = Dir.res+"/encoder/cleandata_8700/"
fllist = ftools.get_files(path)
for name in fllist:
self.data[name] = tools.load_object(path+name)
def load(self):
path = Dir.res + "/cleandata_highquality_1640/abstract/"
for name in ftools.get_files(path):
tmp = ftools.read_lines(path + name)
self.answer[name] = []
for var in tmp:
if len(var.strip()) <= 5:
continue
self.answer[name].append(var)
def rouge_detail(self,abstract_processed,save_dir):
flist = tools.get_files(abstract_processed)
save_content = []
for fname in flist:
content = tools.read_lines(abstract_processed+fname)
refence = tools.read_lines(self.ref_processed+fname)
lines =[line.split(" ") for line in content]
refen =[line.split(" ") for line in refence]
rouge1 = self.rouge_1_simple(refen,lines)
rouge2 = self.rouge_2_simple(refen, lines)
save_content.append(fname+","+str(rouge1)+","+str(rouge2))
tools.write_list(save_dir+"/detials.txt",save_content)
def analyze(main_name, compare_index, name="cleandata_small"):
save_path = Dir.res + "/result/judge.txt"
jude_dict = tools.load_object(save_path)
# print(list(jude_dict.keys())[0])
print(len(jude_dict))
entry_path = Dir.res + "/result/" + name + "/EntryBigraph/detials.txt"
entry_data = load_data(entry_path)
first_path = Dir.res + "/result/" + name + "/" + main_name + "/detials.txt"
first_data = load_data(first_path)
textrank_path = Dir.res + "/result/" + name + "/TextRank/detials.txt"
tr_data = load_data(textrank_path)
result = {}
for key in first_data.keys():
a = first_data[key][0] - entry_data[key][0]
b = first_data[key][1] - entry_data[key][1]
c = first_data[key][0] - tr_data[key][0]
d = first_data[key][1] - tr_data[key][1]
e = first_data[key][0] - tr_data[key][0] + entry_data[key][
0] - tr_data[key][0]
f = first_data[key][1] - tr_data[key][1] + entry_data[key][
1] - tr_data[key][1]
result[key] = [a, b, c, d, e, f]
count = 0
news_root = Dir.res + "/" + name + "/news/"
abst_root = Dir.res + "/" + name + "/abstract/"
fname = ftools.get_files(news_root)
new_result = {}
for filename in fname:
# print(filename,count,len(fname))
# news = ftools.read_lines(news_root+filename)
# weibo = ftools.read_lines(abst_root+filename)
# jude = data_filter(news,weibo)
# jude_dict[filename] = jude
jude = jude_dict[filename]
if jude > 0.5:
new_result[filename] = result[filename]
new_result[filename].append(jude)
count += 1
tools.save_object(jude_dict, Dir.res + "/result/judge.txt")
tmp = dict(
sorted(new_result.items(),
key=lambda d: d[1][compare_index],
reverse=True))
save_dict = {}
names = []
for key in tmp.keys():
save_dict[key] = tmp[key]
names.append(key)
save_path = Dir.res + "/result/" + name + "/" + main_name + ".txt"
ftools.write_com_dict(save_path, save_dict)
return names
def get_result(dataname="cleandata_highquality_3500"):
root = Dir.res + "/result/" + dataname + "/"
flist = ftools.get_files(root)
content = ""
for name in flist:
if ".txt" in name:
continue
lines = ftools.read_lines(root + name + "/eval_res.txt")
content += name + ", " + lines[1][lines[1].index("[") +
1:lines[1].index("]")] + "\n"
print(content)
ftools.write(Dir.res + "/result/" + dataname + "/result.txt", content)
def load_data(self, path=Dir.res + "/cleandata_604/news/"):
flist = ftools.get_files(path)
data = []
count = 0
for name in flist:
filepath = path + name
lines = ftools.read_lines(filepath)
for line in lines:
words = tools.seperate(line)
data.append(TaggedDocument(words, ["sen_" + str(count)]))
self.sen_dict[''.join(words)] = "sen_" + str(count)
count += 1
return data
def indexlize_data(self,reprocess):
### 建立词到数值的映射
print("start")
word_index_path = self.dir_path + "/words_index.txt"
if not tools.isexists(word_index_path) or \
not tools.isexists(self.ref_processed) or \
not tools.isexists(self.ref_seperate) or \
len(tools.get_files(self.ref_seperate)) ==0 or \
len(tools.get_files(self.ref_processed)) == 0:
reprocess = True
if reprocess:
self.word_index = RP.build_word_index(self.file, word_index_path)
# print("word_index_builded")
### 参考摘要数值化
print(self.file_ref,self.ref_seperate,self.ref_processed)
RP.result_process(self.file_ref, self.ref_seperate)
RP.replace_words_by_num(self.word_index, self.ref_seperate, self.ref_processed)
print("references process done")
else:
self.load_word_index(word_index_path )
print("word index loaded")
def generate_new_data():
npath = Dir.res + "/cleandata_highquality_3500/news/"
# apath = Dir.res+"/cleandata_highquality_3500/abstract/"
new_npath = Dir.res + "/cleandata_highquality_3500_new/news/"
new_apath = Dir.res + "/cleandata_highquality_3500_new/abstract/"
uper = Uper()
for name in ftools.get_files(npath):
path = npath + name
content = ftools.read_lines(path)
new_abstract = uper.summarize(content, num=3, fname=name[:-4])
ftools.copy(path, new_npath + name)
ftools.write_list(new_apath + name, new_abstract)
def get_small_data():
root = Dir.res + "/cleandata_8700/"
saveroot = Dir.res + "/cleandata_small/"
flist = ftools.get_files(root + "news/")
count = 0
for i in range(len(flist)):
name = flist[i]
content = ftools.read_lines(root + "news/" + name)
if len(content) < 80:
print(count, i, len(flist))
ftools.copy(root + "news/" + name, saveroot + "news/" + name)
ftools.copy(root + "abstract/" + name,
saveroot + "abstract/" + name)
count += 1
def load_data(self, path=Dir.res + "/cleandata_604/news/"):
flist = ftools.get_files(path)
data = []
count = 0
for name in flist:
filepath = path + name
lines = ftools.read_lines(filepath)
essay = ""
tmp = []
for line in lines:
words = tools.seperate(line)
tmp.extend(words)
essay += ''.join(words)
data.append(TaggedDocument(tmp, ["text_" + str(count)]))
self.sen_dict[essay] = "text_" + str(count)
count += 1
return data
def update_rouge_details(dataname="cleandata_small", modelname="EntryBigraph"):
ref_root = Dir.res + "/" + dataname + "/ref_processed/"
abs_root = Dir.res + "/result/" + dataname + "/" + modelname + "/abstract_processed/"
detail_path = Dir.res + "/result/" + dataname + "/" + modelname + "/detials.txt"
filelist = ftools.get_files(ref_root)
content = ""
for i in range(len(filelist)):
fname = filelist[i]
print(i, len(filelist))
abstract = ftools.read_lines(abs_root + fname)
refence = ftools.read_lines(ref_root + fname)
lines = [line.split(" ") for line in abstract]
refen = [line.split(" ") for line in refence]
rouge1 = rouge_1_simple(refen, lines)
rouge2 = rouge_2_simple(refen, lines)
print(fname, rouge1, rouge2)
content += fname + "," + str(rouge1) + "," + str(rouge2) + "\n"
ftools.write(detail_path, content)
def clean(data_dir=Dir.res + "/cleandata_8700/news/"):
flist = tools.get_files(data_dir)
# print(data_dir,len(flist))
for fname in flist:
flag = False
content = tools.read(data_dir + fname)
if "3805" in fname:
print(content)
input()
if "您的浏览器不支持video标签\n" in content:
content = content.replace("您的浏览器不支持video标签\n", "")
flag = True
if "新闻 专题 微博" in content:
flag = True
content = content[:content.index("新闻 专题 微博")]
if flag:
print(fname)
tools.write(data_dir + fname, content)
def fill_all(path = Dir.res+"/craw_data/original/",save_path = Dir.res+"/craw_data/data/",fail_save_path = Dir.res+"/craw_data/fail/"):
crawer = Crawer()
files = tools.get_files(path)
for name in files:
content = tools.read_lines(path+name)
fail_content = ""
save_content = ""
crawer.writeIntofile(save_path+name,"")
crawer.writeIntofile(fail_save_path+name,"")
succ_count,fail_count = 0,0
for line in content:
tmp = line.split(",")
article = crawer.get_article(tmp[-1]).strip().replace("\n","")
if len(article)>0:
save_content += tmp[0]+","+tmp[1]+","+article+'\n'
succ_count+=1
else:
fail_content += tmp[0]+","+tmp[1]+","+tmp[2]+'\n'
fail_count+=1
# fail_content.append(tmp)
crawer.writeIntofile(save_path+name,save_content)
crawer.writeIntofile(fail_save_path+name,fail_content)
print(name,succ_count,fail_count)
trainformat_sentences.append(tools.seperate(sen))
return trainformat_sentences
def train(traindata, savepath=Dir.res + "/parameter/words_vector/w2v.model"):
ftools.check_filename(savepath)
model = Word2Vec(sentences=traindata,
size=200,
window=5,
min_count=3,
workers=4)
model.save(savepath)
def load(path=Dir.res + "/parameter/words_vector/w2v.model"):
model = Word2Vec.load(path)
return model
if __name__ == "__main__":
root = Dir.res + "/data/"
flist = ftools.get_files(root)
data = []
count = 0
for name in flist:
path = root + name
print(" %04d" % count, len(flist))
count += 1
data.extend(loaddata(path))
train(data)
def filter_craw_data(data_dir=Dir.res + "/craw_data/data/",
save_dir=Dir.res + "/cleandata_none"):
if os.path.lexists(save_dir):
shutil.rmtree(save_dir)
files = tools.get_files(data_dir)
cleandata = []
count = 0
bad_sample = []
for i in range(len(files)):
print(i, len(files), len(cleandata))
fname = files[i]
path = data_dir + fname
lines = tools.read_lines(path)
for line in lines:
line = line.strip()
# try:
if 1:
last_ = line.rindex(",")
first_ = line.index(",")
if first_ == last_:
continue
tmp = [line[:first_], line[first_ + 1:last_], line[last_ + 1:]]
abstracts = tls.seperate_sentences(tmp[1])
news = tls.seperate_sentences(tmp[2])
tmp = get_abstract_index(news, abstracts)
count += 1
if len(tmp) != len(abstracts):
continue
# print(tmp)
# cmd = input()
# if "1" in cmd:
# print('\n'.join(abstracts))
# print("--------------------")
# print('\n'.join(news))
#
# print("--------------------")
# print("words:",w_count)
w_count = 0
for li in news:
w_count += len(tls.seperate(li))
if w_count < 520:
continue
if sum(tmp[:3]) <= 3:
continue
cleandata.append([abstracts, news])
tools.write(
save_dir + "/abstract/trainning_" + str(len(cleandata)) +
".txt", '\n'.join(abstracts))
tools.write(
save_dir + "/news/trainning_" + str(len(cleandata)) +
".txt", '\n'.join(news))
# except Exception as e:
# print(str(e),e.with_traceback(e.__traceback__))
# print("error",line)
# bad_sample.append(line)
print(count, len(bad_sample), len(cleandata))
