relationship_find.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

# 基于共现矩阵来确定人物关系

import jieba
jieba.load_userdict('e:/PY/relationship_find/dic.txt') #导入自己的字典，不然分词效果不好
import jieba.posseg as pseg
import Graph_built


# 将剧本进行分词，并将表示人名的词提出，将其他停用词和标点省略
# 提出人名的同时，同name字典记录下来，作为矩阵的行和列
def cut_word(text):
    words=pseg.cut(text)
    L_name=[]
    for x in words :
        if x.flag!='nr' or len(x.word) < 2:
            continue
        if not Names.get(x.word):
            Names[x.word]=1
        else:
            Names[x.word]=Names[x.word]+1
        L_name.append(x.word)
    return L_name


# 建立词频字典和每段中的人物列表
def namedict_built():
    global Names
    with open('e:/PY/relationship_find/test.txt','r') as f:
        for l in f.readlines():
            n=cut_word(l)
            if len(n)>=2: # 由于要计算关系，空list和单元素list没有用
                Lines.append(n)
    Names=dict(sorted(Names.items(),key = lambda x:x[1],reverse = True)[:36])
    # print(Line)


# 通过遍历Lines来构建贡献矩阵
def relation_built():
    for key in Names:
        relationships[key]={}
    for line in Lines:
        for name1 in line:
            if not Names.get(name1):
                continue
            for name2 in line:
                if name1==name2 or (not Names.get(name2)):
                    continue
                if not relationships[name1].get(name2):		
                    relationships[name1][name2]= 1
                else:
                    relationships[name1][name2] = relationships[name1][name2]+ 1
    # print(relationships)

# 生成有向图的节点文件和边文件
def file_built():
    with open('e:/PY/relationship_find/node.txt','w') as fn:
        # windows的换行是\r\n
        for key in Names:
            fn.write(key+' '+str(Names[key])+'\r\n')
    with open('e:/PY/relationship_find/edge.txt','w') as fe:
        for key in relationships:
            for v in relationships[key]:
                fe.write(key+' '+v+' '+str(relationships[key][v])+'\r\n')
    

Names={} # 统计频次
Lines=[] # 每一行的名字的集合
relationships={} # 二维共现矩阵，用二维字典实现
namedict_built() #Names的元素是元组
relation_built()
file_built()
Graph_built.Graph_show()