from numpy import *

import jieba

import copy

with open('content', 'r', encoding = 'utf-8') as f:

content = f.read()

with open('stopwords', 'r', encoding = 'utf-8') as f:

sw = f.readlines()

sw = map(lambda x: x.replace('\n', ''), sw)#停词

word_list = jieba.cut(content)

word_list = list(word_list)

word_list_vice = copy.deepcopy(word_list)#备份

set_sw = set(sw)

for word in word_list:#迭代消耗

if word in set_sw:

word_list_vice.remove(word)

word_list = copy.deepcopy(word_list_vice)#备份

word_set_list = list(set(word_list_vice))#转换类型消耗

aa = zeros((len(word_set_list), len(word_set_list)), dtype = float)

word_list_vice = copy.deepcopy(list(word_list))#备份

for i, word in enumerate(word_list):#迭代消耗

if i == len(word_list_vice) - 1:

break

sindex = word_set_list.index(word)

eindex = word_set_list.index(word_list_vice[i + 1])

aa[sindex][eindex] = aa[sindex][eindex] + 1

aa[eindex][sindex] = aa[eindex][sindex] + 1

def graph_init(a):#初始化转移矩阵

row, column = a.shape

c = zeros((row, column),dtype = float)

for i in range(row):

for j in range(column):

c[i][j] = a[i][j] / (sum(a[i]))

return c

def pr_init(c):#pageRank向量初始化

row, column = c.shape

pr = zeros(row,dtype = float)

for i in range(row):

pr[i] = float(1) / row

return pr

def pageRank(s, pr, p):#迭代计算pageRank向量

while(array_equal(pr, p * dot(pr, s) + (1 - p) * pr) == False):#判断pr矩阵是否收敛

pr = p * dot(pr, s) + (1 - p) * pr

return pr

if __name__=="__main__":

s = graph_init(aa)

pr = pr_init(s)

p = 0.8 #浏览当前网页的概率p

r = pageRank(s, pr, p)

result_list = []

for i, j in zip(word_set_list, r):

result_dict = {}

result_dict['word'] = i

result_dict['score'] = j

result_list.append(result_dict)

rl = sorted(result_list, key = lambda x: x['score'])