itchat.auto_login(hotReload = True)   
friends = itchat.get_friends(update = True)

def analyseSex(firends):   
  sexs = list(map(lambda x:x['Sex'],friends[1:]))   
 counts = list(map(lambda x:x[1],Counter(sexs).items()))   
 labels = ['Unknow','Male','Female']   
 colors = ['red','yellowgreen','lightskyblue']   
 plt.figure(figsize=(8,5), dpi=80)   
 plt.axes(aspect=1)   
 plt.pie(counts, #性別統計結果   
   labels=labels, #性別展示標籤   
   colors=colors, #餅圖區域配色   
   labeldistance = 1.1, #標籤距離圓點距離   
   autopct = '%3.1f%%', #餅圖區域文本格式   
   shadow = False, #餅圖是否顯示陰影   
   startangle = 90, #餅圖起始角度   
   pctdistance = 0.6 #餅圖區域文本距離圓點距離   
 )   
 plt.legend(loc='upper right',)   
 plt.title(u'%s的微信好友性別組成' % friends[0]['NickName'])   
 plt.show()

def analyseHeadImage(frineds):   
 # Init Path   
 basePath = os.path.abspath('.')   
 baseFolder = basePath + '\\HeadImages\\'  
 if(os.path.exists(baseFolder) == False):   
  os.makedirs(baseFolder)    
 # Analyse Images   
 faceApi = FaceAPI()   
 use_face = 0  
 not_use_face = 0  
 image_tags = ''   
 for index in range(1,len(friends)):   
  friend = friends[index]   
  # Save HeadImages   
  imgFile = baseFolder + '\\Image%s.jpg' % str(index)   
  imgData = itchat.get_head_img(userName = friend['UserName'])   
  if(os.path.exists(imgFile) == False):   
   with open(imgFile,'wb') as file:   
    file.write(imgData)     
  # Detect Faces   
  time.sleep(1)   
  result = faceApi.detectFace(imgFile)   
  if result == True:   
   use_face += 1  
  else:   
   not_use_face += 1    
  # Extract Tags   
  result = faceApi.extractTags(imgFile)   
  image_tags += ','.join(list(map(lambda x:x['tag_name'],result)))    
 labels = [u'使用人臉頭像',u'不使用人臉頭像']   
 counts = [use_face,not_use_face]   
 colors = ['red','yellowgreen','lightskyblue']   
 plt.figure(figsize=(8,5), dpi=80)   
 plt.axes(aspect=1)   
 plt.pie(counts, #性別統計結果   
   labels=labels, #性別展示標籤   
   colors=colors, #餅圖區域配色   
   labeldistance = 1.1, #標籤距離圓點距離   
   autopct = '%3.1f%%', #餅圖區域文本格式   
   shadow = False, #餅圖是否顯示陰影   
   startangle = 90, #餅圖起始角度   
   pctdistance = 0.6 #餅圖區域文本距離圓點距離   
 )   
 plt.legend(loc='upper right',)   
 plt.title(u'%s的微信好友使用人臉頭像情況' % friends[0]['NickName'])   
 plt.show()    
 image_tags = image_tags.encode('iso8859-1').decode('utf-8')   
 back_coloring = np.array(Image.open('face.jpg'))   
 wordcloud = WordCloud(   
  font_path='simfang.ttf',   
  background_color="white",   
  max_words=1200,   
  mask=back_coloring,   
  max_font_size=75,   
  random_state=45,   
  width=800,   
  height=480,   
  margin=15  
 )    
 wordcloud.generate(image_tags)   
 plt.imshow(wordcloud)   
 plt.axis("off")   
 plt.show()

def analyseSignature(friends):   
 signatures = ''   
 emotions = []   
 pattern = re.compile("1f\d.+")   
 for friend in friends:   
  signature = friend['Signature']   
  if(signature != None):   
   signature = signature.strip().replace('span', '').replace('class', '').replace('emoji', '')   
   signature = re.sub(r'1f(\d.+)','',signature)   
   if(len(signature)>0):   
    nlp = SnowNLP(signature)   
    emotions.append(nlp.sentiments)   
    signatures += ' '.join(jieba.analyse.extract_tags(signature,5))   
 with open('signatures.txt','wt',encoding='utf-8') as file:   
   file.write(signatures)   
 # Sinature WordCloud   
 back_coloring = np.array(Image.open('flower.jpg'))   
 wordcloud = WordCloud(   
  font_path='simfang.ttf',   
  background_color="white",   
  max_words=1200,   
  mask=back_coloring,   
  max_font_size=75,   
  random_state=45,   
  width=960,   
  height=720,   
  margin=15  
 )   
 wordcloud.generate(signatures)   
 plt.imshow(wordcloud)   
 plt.axis("off")   
 plt.show()   
 wordcloud.to_file('signatures.jpg')   
 # Signature Emotional Judgment   
 count_good = len(list(filter(lambda x:x>0.66,emotions)))   
 count_normal = len(list(filter(lambda x:x>=0.33 and x<=0.66,emotions)))   
 count_bad = len(list(filter(lambda x:x<0.33,emotions)))   
 labels = [u'負面消極',u'中性',u'正面積極']   
 values = (count_bad,count_normal,count_good)   
 plt.rcParams['font.sans-serif'] = ['simHei']   
 plt.rcParams['axes.unicode_minus'] = False  
 plt.xlabel(u'情感判斷')   
 plt.ylabel(u'頻數')   
 plt.xticks(range(3),labels)   
 plt.legend(loc='upper right',)   
 plt.bar(range(3), values, color = 'rgb')   
 plt.title(u'%s的微信好友簽名信息情感分析' % friends[0]['NickName'])   
 plt.show()

def analyseLocation(friends):   
 headers = ['NickName','Province','City']   
 with open('location.csv','w',encoding='utf-8',newline='',) as csvFile:   
  writer = csv.DictWriter(csvFile, headers)   
  writer.writeheader()   
  for friend in friends[1:]:   
   row = {}   
   row['NickName'] = friend['NickName']   
   row['Province'] = friend['Province']   
   row['City'] = friend['City']   
   writer.writerow(row)