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draw.py
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draw.py
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import json
from connect import ReadBJFU
def YearsData(papers):
""" 保存教授论文发表年份数据
:param papers: (str) 教授论文信息字符串
Author: 王心童
"""
AllYears = []
for paper in papers:
date = paper.split('. ')[1]
if len(date.split('-')) == 3:
AllYears.append(date.split('-')[0])
elif len(date.split('(')) == 2:
AllYears.append(date.split('(')[0])
years = set(AllYears)
clean_years = {}
for item in years:
clean_years.update({item: AllYears.count(item)})
years_list = list(clean_years.keys())
for item in years_list:
if len(item) > 4:
clean_years.pop(item)
if '' in clean_years:
clean_years.pop('')
clean_years = sorted(clean_years.items(), key=lambda e: e[0])
# 将论文发表年份数据按键值对，存为json 文件
years_list = []
for year in clean_years:
years = {}
years['year'] = year[0]
years['num'] = year[1]
years_list.append(years)
with open('C:\code\static\years.json', 'w', encoding='utf-8') as fid:
json.dump(years_list, fid, ensure_ascii=False)
def JournalData(papers):
""" 保存期刊和专利数据
:param papers: (str) 教授论文信息字符串
Author: 李明泽
"""
# 期刊列表
journal_list = []
# 文章列表
artical_list = []
# 专利列表
patent_list = []
for i in range(len(papers)):
if '[J]' in papers[i]:
artical_list.append(papers[i])
if '[P]' in papers[i]:
patent_list.append(papers[i])
# 将题目按专利和文章分类
for i in range(len(artical_list)):
# 从文章中分离出期刊
journal_list.append(artical_list[i].split('\n')[1].split('.')[0])
# 元素去除重复
# journal_list = sorted(list(set(journal_list)))
# 查期刊发表的频度
journal_set = set(journal_list)
journal = {}
for item in journal_set:
journal.update({item: journal_list.count(item)})
journal.update({'中国专利': len(patent_list)})
journal_sorted = sorted(journal.items(), key=lambda e: e[1], reverse=True)
# 新增字典列表
journal_dict = {}
for i in range(min(len(journal_sorted), 10)):
journal_dict[journal_sorted[i][0]] = journal_sorted[i][1]
# 将期刊专利数据按键值对，存为json 文件
with open('C:\code\static\journal.json', 'w', encoding='utf-8') as fid:
json.dump(journal_dict, fid, ensure_ascii=False)
def MapData(rank, name, majors, friends):
""" 保存图谱关系数据
:param rank:(str) 教授的唯一专业
:param name:(str) 教授的姓名
:param majors:(list) 教授的多个专业
:param friends:(str) 教授的合作学者
Author: 李明泽
"""
# 图谱关系 = ['合作', '专业相同', '专业相关']
# author (friends)
# ranking 相同则为专业相同学者peer_list(同行)(majors)
# domain与 ranking 的差值为专业相关学者peer_related_list(猜你想找)
# ranking 增加通配符查找同行
ranking = '%' + rank + '%'
# 基于ranking的同行列表, 定义专业相同学者
peer_list = ReadBJFU(name=name, ranking=ranking, Peer=1)
peer_list = sorted(list(set(peer_list))) # peer_list元素去除重复
tmp_list = []
data_list = ReadBJFU(name=name, domain_list=majors, PeerRelated=1)
for i in range(0, len(data_list)):
for data in data_list[i]:
tmp_list.append(data)
tmp_list = sorted(list(set(tmp_list))) # temp_list元素去除重复
peer_related_list = []
for i in range(len(tmp_list)):
if tmp_list[i] not in peer_list:
peer_related_list.append(tmp_list[i]) # 两表做差，生成peer_related_list列表
map = {}
map['partner_list'] = "".join(friends)
map['peer_list'] = ";".join(peer_list)
map['peer_related_list'] = ";".join(peer_related_list)
with open('C:\code\static\map.json', 'w', encoding='utf-8') as fid:
json.dump(map, fid, ensure_ascii=False)