# setting paths
fname_text = 'texts/article.txt'            #你需要生成词云的文件地址
fname_stop = 'hit_stopwords.txt'                #分词文件地址，不能动
fname_mask = 'owl.jpeg'             #生成词云所用的背景地址
fname_font = 'simhei.ttf'           #生成词云文字的字体地址，可更改自己需要的字体

import numpy as np
from wordcloud import WordCloud, ImageColorGenerator  # , STOPWORDS
import matplotlib.pyplot as plt
from PIL import Image
import jieba  # cutting Chinese sentences into words
def plt_imshow(x, ax=None, show=True):
  if ax is None:
    fig, ax = plt.subplots()
  ax.imshow(x)
  ax.axis("off")
  if show: plt.show()
  return ax
def count_frequencies(word_list):
  freq = dict()
  for w in word_list:
    if w not in freq.keys():
      freq[w] = 1
    else:
      freq[w] += 1
  return freq
if __name__ == '__main__':
  # setting paths
  fname_text = '商务英语特征与翻译难点探讨.txt'
  fname_stop = 'hit_stopwords.txt'
  fname_mask = 'touxiang.JPG'
  fname_font = 'simhei.ttf'
  # read in texts (an article)
  text = open(fname_text, encoding='utf8').read()
  # Chinese stop words
  STOPWORDS_CH = open(fname_stop, encoding='utf8').read().split()
  # processing texts: cutting words, removing stop-words and single-charactors
  word_list = [
    w for w in jieba.cut(text)
    if w not in set(STOPWORDS_CH) and len(w) > 1
  ]
  freq = count_frequencies(word_list)
  # processing image
  im_mask = np.array(Image.open(fname_mask))
  im_colors = ImageColorGenerator(im_mask)
  # generate word cloud
  wcd = WordCloud(font_path=fname_font,  # font for Chinese charactors
                  background_color='white',
                  mode="RGBA",
                  mask=im_mask,
                  )
  # wcd.generate(text) # for English words
  wcd.generate_from_frequencies(freq)
  wcd.recolor(color_func=im_colors)
  # visualization
  ax = plt_imshow(wcd, )
  ax.figure.savefig(f'single_wcd.png', bbox_inches='tight', dpi=150)
  fig, axs = plt.subplots(1, 2)
  plt_imshow(im_mask, axs[0], show=False)
  plt_imshow(wcd, axs[1])
  fig.savefig(f'conbined_wcd.png', bbox_inches='tight', dpi=150)