# -*- coding: utf-8 -*-
"""created on 2019/5/22 10:18
@author: johnson
@email:[email protected]
@file: wordcloud教程.py
"""from os import path
from scipy.misc import imread
from wordcloud import wordcloud, stopwords
import matplotlib.pyplot as plt
def wordcount(filename):
'''簡單計算詞頻的函式
:param filename: 檔名
:return: 詞頻
'''wordcount = {}
file = open(filename,'r')
while true:
line = file.readline()
if line:
wordlist = line.split(',[')
if len(wordlist) == 1: continue
wordlist = wordlist[1].split('],')[0].split(',')
for word in wordlist:
word = word.replace(' ', '').replace("'", '')
if word in wordcount.keys():
wordcount[word] = wordcount[word]+1
else:
wordcount[word] = 1
else:
break
return [(k, wordcount[k]) for k in wordcount.keys()]
def generatecloud(filename,imagename,cloudname,fontname):
'''生成標籤雲的函式
'''coloring = imread(imagename) # 讀取背景
wc = wordcloud(background_color="white", # 背景顏色max_words=2000,# 詞云顯示的最大詞數
mask=coloring, # 設定背景
stopwords=stopwords, # 停止詞
font_path=fontname, # 相容中文字型
max_font_size=150) # 字型最大值
#計算好詞頻後使用generate_from_frequencies函式生成詞云
#txtfreq例子為[('詞a', 100),('詞b', 90),('詞c', 80)]
txtfreq = wordcount(filename)
wc.generate_from_frequencies(txtfreq)
# 生成
plt.imshow(wc)
plt.axis("off")
# 繪製詞云
plt.figure()
# 儲存詞云
wc.to_file(cloudname)
if __name__ == '__main__':
d = path.dirname(__file__) # 獲取當前檔案路徑
fontname = path.join(d, 'msyh.ttf') # 中文字型路徑
filename = path.join(d, '廣州.txt') # txt檔案路徑
imagename = path.join(d, "circle.jpg") # 背景路徑
cloudname = path.join(d, "cloud.png") # 標籤雲路徑
generatecloud(filename, imagename, cloudname, fontname)
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