# 特征
for i in li1:
data1 = re.sub('@[\s\S]*?:','',i)
data1 = re.sub('http://','',data1)
data_1 = re.sub("[^a-zA-Z\u4e00-\u9fa5]","",data1)
if data_1=='':
wordList=[]
jishu+=1
else:
jishu+=1
wordList_2 = ltp(data_1)
list_for_cv.append(n_gram(wordList_2))
print(jishu)
t_bd_p = biaodian(i)
t_fdc_p = fdc(data_1)
tmp1 = zzqgc(list_ai,data_1)
tmp2 = zzqgc(list_e,data_1)
tmp3 = zzqgc(list_hao,data_1)
tmp4= zzqgc(list_jing,data_1)
tmp5 = zzqgc(list_ju,data_1)
tmp6= zzqgc(list_le,data_1)
tmp7 = zzqgc(list_nu,data_1)
numtezheng = [tmp1,tmp2,tmp3,tmp4,tmp5,tmp6,tmp7,len(wordList_2),t_fdc_p,t_bd_p]
list_num_tezheng.append(numtezheng)
tezheng_sadness = tz('sadness',list_for_cv,list_num_tezheng)
tezheng_like = tz('like',list_for_cv,list_num_tezheng)
tezheng_disgust = tz('disgust',list_for_cv,list_num_tezheng)
tezheng_surprise = tz('surprise',list_for_cv,list_num_tezheng)
tezheng_anger = tz('anger',list_for_cv,list_num_tezheng)
# 分词
if data=='':
wordList=[]
jishu+=1
else:
jishu+=1
wordList = ltp(data)
list_ngram.append(n_gram(wordList))
print(jishu)
# 否定词特征
t_fdc = fdc(data)
# 标点特征
t_bd = biaodian(node.firstChild.data)
# 情感词典0&1特征
tmp1 = zzqgc(list_ai,data)
tmp2 = zzqgc(list_e,data)
tmp3 = zzqgc(list_hao,data)
tmp4= zzqgc(list_jing,data)
tmp5 = zzqgc(list_ju,data)
tmp6= zzqgc(list_le,data)
tmp7 = zzqgc(list_nu,data)
numtezheng = [tmp1,tmp2,tmp3,tmp4,tmp5,tmp6,tmp7,len(wordList),t_fdc,t_bd]
