def extract_sentences(word):
folder_name = word.encode("GBK")
list_dirs = os.walk(folder_name)
i = 0
for root, dirs, files in list_dirs:
outfile = open('Extraction/' + folder_name + '.txt', 'w')
for f in files:
file_path = os.path.join(root, f)
infile = codecs.open(file_path, 'r', 'utf-8')
lines = infile.readlines()
full_text = ''
for line in lines:
full_text += line.strip()
infile.close()
bs = BeautifulSoup(full_text, "lxml")
for tag in bs(['script', 'img', 'a', 'head', 'li', 'style']):
tag.extract()
full_text = bs.get_text()
cut_list = '\s\t\f\r\n。！？ '.decode('utf-8')
sentences = functions.cut(cut_list, full_text)
for s in sentences:
if string.find(s, word) != -1:
i += 1
print 's:' + str(i)
s = s.encode('utf-8')
outfile.write(s + '\n')
outfile.close()
return
def search(word):
word_url_encoded = urllib.quote(word.encode('utf-8'))
request_url = "http://www.baidu.com/s?wd=" + word_url_encoded
out_file_name = (macro.BDNEWS_DOCS_ORG_DIR + '/' + word + '.txt').encode('GBK')
# 文件已经存在，说明已经爬取过，直接跳过
if os.path.isfile(out_file_name):
return 0
print word
outfile = codecs.open(out_file_name, 'w', 'utf-8')
try:
response = requests.get(request_url)
except requests.exceptions.RequestException:
outfile.close()
print -1
return -1
soup = BeautifulSoup(response.text, 'html.parser')
divs = soup.find_all('div',class_='c-abstract')
if len(divs)>0:
for div in divs:
text = div.text
cutlist = '\s\t\f\r\n。！？ '.decode('utf-8')
sens = functions.cut(cutlist,text)
for s in sens:
if s.find(word)!=-1:
outfile.write(s+'\r\n')
else:
outfile.close()
print -2
return -2
outfile.close()
def write_data(word_list_file, num, outfilename):
infile = codecs.open(word_list_file, 'r', 'utf-8')
outfile = codecs.open(outfilename, 'w', 'utf-8')
line = infile.readline()
outfile.write(
'ID\tWord1\tWord2\tweb-jaccard\tweb-overlap\tweb-dice\tweb-pmi\tIsSubString\tSharedCharNum\r\n'
)
i = 0
while i < num:
infile.readline()
i += 1
while line != '\n':
line = infile.readline()
cutlist = ',\t\r'.decode('utf-8')
i += 1
words = functions.cut(cutlist, line)
if len(words) == 0:
break
word1 = words[0].strip()
word2 = words[1].strip()
features = sk_LR.get_all_features(word1, word2)
if i % 100 == 0:
time.sleep(1)
if len(features) == 0:
print i
break
outfile.write(word1 + '\t' + word2 + '\t')
for f in features:
outfile.write(str(f) + '\t')
outfile.write('\r\n')
outfile.close()
infile.close()
def extract(word):
out_file_name = (macro.BDNEWS_DOCS_ORG_DIR + '/' + word +
'.txt').encode('GBK')
# 文件已经存在，说明已经爬取过，直接跳过
if os.path.isfile(out_file_name):
return 0
outfile = codecs.open(out_file_name, 'w', 'utf-8')
word_url_encoded = urllib.quote(word.encode('utf-8'))
# 向百度新闻发起搜索请求的URL
request_url = "http://news.baidu.com/ns?word=" + word_url_encoded + "&tn=news&from=news&cl=2&rn=50&ct=1"
try:
response = requests.get(request_url)
except requests.exceptions.RequestException:
outfile.close()
return -1
soup = BeautifulSoup(response.text, 'html.parser')
# 找到所有h3标签，读取内容
result_heads = soup.find_all('h3')
for head in result_heads:
# 有时因为网络问题会导致返回的结果页面异常
if head['class'] == 'norsTitle':
return -1
a_temp = head.contents[0]
link = ''
try:
link = a_temp.attrs['href']
except AttributeError:
continue
else:
pass
try:
article = requests.get(link, timeout=3)
except requests.exceptions.RequestException:
print 'failed:' + link
continue
else:
pass
# 检测并转换编码
if article.encoding == 'ISO-8859-1':
encodings = requests.utils.get_encodings_from_content(
article.content)
if len(encodings) == 0:
article.encoding = 'utf-8'
else:
article.encoding = encodings[0]
article = article.text.encode('utf-8').decode('utf-8')
full_text = functions.remove_useless_tags(article)
# 分句
cut_list = '\s\t\f\r\n。！？ '.decode('utf-8')
sentences = functions.cut(cut_list, full_text)
for s in sentences:
# 含有关键词则写文件
if string.find(s, word) != -1:
outfile.write(s + '\r\n')
outfile.close()
return 1
def extract_from_html(word, html, pagenum):
text = functions.remove_useless_tags(html)
cut_list = '!?.\t\r\n。！？'.decode('utf-8')
# 含有关键词的句子列表
sentences = []
for s in functions.cut(cut_list, text):
if string.find(s, word) != -1:
sentences.append(s)
if len(sentences) > 0:
sentences.remove(sentences[0])
return sentences
itime = getfitskeywords(filename, 'ITIME', HEADER='SCI')
# print('target, itime', target,itime)
qphi = np.nan_to_num(qphi)
vu = np.quantile(qphi, 0.99)
vl = np.quantile(qphi, 0.01)
# print("upper =",vu, " lower=",vl)
### HYPERBOLIC FUNCTION
# qphi = hyperbolic(qphi, 10, vu, vl)
### PLOTTING IMAGE AND BEST FIT ELLIPSE
# qphi = deproject(qphi, 31)
qphi = cut(35, 0, 0, 141, 141, 0, qphi)
plt.figure(figsize=(12, 12))
plt.imshow(qphi, cmap='seismic', origin='lower', vmin=vl, vmax=vu)
# t = test_map(55.37, 24.36, 23.32, 98.48, 140.2, 141.2, 9.954, 0, 282)
# t = test_map_mie(55, 24, 23, 97, 141, 142, 7, 5, 35, 0, 282)
# t = hg_map(50, 20, 45, 45, 141, 141, 0.5, 20, 0, 282)
# t = hg_map(54.41, 23.87, 18.19, -517.70, 140.49, 142.39, -0.2524, 149.09, -2.03275376e-06, 282)
# t = add_noise(t, 1)
# plt.imshow(t, cmap='seismic', origin='lower')
plt.colorbar(shrink=0.8)
### ELLIPSE FITTING
# e = e_best(55, 65, 30, 35, 90, 110, 141, 142, 141, 142, qphi)
# Set header of table. ws_cut = functions.set_cutted_header(ws_raw, ws_cut) ws_cor = functions.set_common_header(ws_raw, ws_cor) ws_cor_temp = functions.set_cutted_header(ws_raw, ws_cor_temp) ws_rearr = functions.set_cutted_header(ws_raw, ws_rearr) ws_rearr_temp = functions.set_cutted_header(ws_raw, ws_rearr_temp) ws_fit = functions.set_cutted_header(ws_raw, ws_fit) ws_fit_uc = functions.set_cutted_header(ws_raw, ws_fit_uc) # Calculate resistance. resistance_res = functions.resistor(ws_raw) resistance = resistance_res[0][0] peaks = resistance_res[1] # Cut the CV curve. cut = functions.cut(ws_raw, ws_cut) ws_cut = cut[0] voltage_range_cut = cut[1] # Calculate the result vol-cur after corrected. ws_cor_res = functions.correct(ws_raw, ws_cor, resistance) ws_cor_temp_res = functions.correct(ws_cut, ws_cor_temp, resistance) ws_cor = ws_cor_res[0] ws_cor_temp = ws_cor_temp_res[0] # Set voltage range. voltage_range = [max(ws_cor_temp_res[2]), min(ws_cor_temp_res[1])] # Rearrangements of data. ws_rearr = functions.rearrangement(ws_cor_temp, ws_rearr, voltage_range) ws_rearr_temp = functions.rearrangement(ws_cut, ws_rearr_temp,
change = False
print(Fore.YELLOW + "> WANT SOME RANDOM ? :)")
#endregion
if run:
game.draw_matrix()
im2 = game.draw_image()
cv2.imshow("frame2", im2)
game.init_matrix()
start = time.time()
frame = capture.force_update() # uh oh
im = functions.cut(frame)
if tried != -1:
tried, last = functions.test(im, p_bot, game, last, mode, change,
tried, random)
random = False
if tried >= 15:
change = False
if mode == "tree":
print("> I'M SORRY, BACK TO CHOPPING")
else:
print("> I'M SORRY, BACK TO MINING")
tried = 0
