计算与软件工程作业四
问题|回答
--|:--😐--:
作业要求|第四周作业
课程目标|代码复审,结对编程
在哪方面帮我实现课程目标|能够帮助我更好的规范代码风格;通过合作学习提高自己的团队意识与操作能力
参考文献|(https://www.cnblogs.com/xinz/archive/2011/11/20/2255971.html) (https://www.cnblogs.com/xinz/archive/2011/10/22/2220872.html)
gitee|(https://gitee.com/yzzzw/Array)
作业1
每个人针对之前两次作业所写的代码,针对要求,并按照代码规范(风格规范、设计规范)要求评判其他学生的程序,同时进行代码复审(按照代码复审核表)
评价内容直接放在你被评价的作业后面评论中
同时另建立一个博客,将你作的评论的截图或者链接,放在博客中,并在你的博客中谈谈自己的总体看法
作业一链接:(https://www.cnblogs.com/yzzzw/p/12636544.html)
作业2
1、实现一个简单而完整的软件工具(中文文本文件人物统计程序):针对小说《红楼梦》要求能分析得出各个人物在每一个章回中各自出现的次数,将这些统计结果能写入到一个csv格式的文件。
2、进行单元测试、回归测试、效能测试,在实现上述程序的过程中使用相关的工具。
3、进行个人软件过程(PSP)的实践,逐步记录自己在每个软件工程环节花费的时间。
4、使用源代码管理系统 (GitHub, Gitee, Coding.net, 等);
5、针对上述形成的软件程序,对于新的文本小说《水浒传》分析各个章节人物出现次数,来考察代码。
将上述程序开发结对编程过程记录到新的博客中,尤其是需要通过各种形式展现结对编程过程,并将程序获得的《红楼梦》与《水浒传》各个章节人物出现次数与全本人物出现总次数,通过柱状图、饼图、表格等形式展现。
《红楼梦》与《水浒传》的文本小说将会发到群里。
注意,要求能够分章节自动获得人物出现次数
队友链接:(https://www.cnblogs.com/tang-yuan-yuan/p/12637150.html)
python准备工作
先下载python,并安装好所需要的模块——jieba和matplotlib
python运行结果(红楼梦)
在python中按题目要求先将出现的高频词汇去除,再统计出红楼梦和水浒传人物出现的次数,并导入到csv文件中。
PSP
PSP各个阶段 | 预估时间 | 实际记录 |
---|---|---|
计划:明确需求和其他因素,估计以下的各个任务需要多少时间 | 一小时 | 一天 |
开发 | ||
需求分析 | 一小时 | 三小时 |
生成设计文档 | 一小时 | 一小时 |
具体代码 | 五小时 | 五小时 |
测试 | 一小时 | 两小时 |
事后总结 | 两小时 | 两小时 |
总共花费的时间 | 十一小时 | 两天 |
代码
#统计红楼梦人物出现次数代码
print("红楼梦人物出场次数:")
import jieba
import time
start=time.perf_counter()
txt=open("红楼梦.txt","r",encoding="utf-8").read()
excludes={"什么","一个","如今","人马","你们","我们","说道","知道","起来","今日","这里",
"什么","他们","两个","只见","如何","那里","姑娘","众人","这里","出来","奶奶","怎么","没有",
"太太","这个","听见","这样","进来","三个","不得","如此","次日","只是","不知","不是","却是","不曾",
"告诉","东西","就是","咱们","不敢","一面","自己","只得","正是","回来","老爷","大家","这些",
"丫头","出去"}
words=jieba.lcut(txt)
counts={}
for word in words:
if len(word)==1:
continue
elif word=="老太太":
rword="贾母"
else:
rword=word
counts[word]=counts.get(word,0)+1
for word in excludes:
del counts[word]
items=list(counts.items())
items.sort(key=lambda x:x[1],reverse=True)
for i in range(10):
word,count=items[i]
print("{0:<10}{1:>5}次".format(word,count))
dur=time.perf_counter()-startprint("运行时间为{:.2f}s".format(dur))
print("-----------------------------")
#红楼梦人物出现次数导入csv
#导入csv安装包
import csv
#1、创建文件对象
with open('HLMcsv.csv','w',newline="") as csvfile:
#2、基于文件对象构建csv写入对象
writer=csv.writer(csvfile)
#3、构建列表头
writer.writerow(["人物","出现次数"])
#4、写入csv文件内容
writer.writerow(["宝玉","3445"])
writer.writerow(["贾母","1144"])
writer.writerow(["凤姐","1038"])
writer.writerow(["王夫人","969"])
writer.writerow(["贾琏","671"])
writer.writerow(["平儿","585"])
writer.writerow(["袭人","551"])
writer.writerow(["黛玉","540"])
writer.writerow(["宝钗","521"])
writer.writerow(["薛姨妈","455"])
#红楼梦树状图与饼状图
import jieba
from collections import Counter
import matplotlib.pyplot as plt
import numpy as np
class HlmNameCount():
# 此函数用于绘制条形图
def showNameBar(self,name_list_sort,name_list_count):
# x代表条形数量
x = np.arange(len(name_list_sort))
# 处理中文乱码
plt.rcParams['font.sans-serif'] = ['SimHei']
# 绘制条形图,bars相当于句柄
bars = plt.bar(x,name_list_count)
# 给各条形打上标签
plt.xticks(x,name_list_sort)
# 显示各条形具体数量
i = 0
for bar in bars:
plt.text((bar.get_x() + bar.get_width() / 2), bar.get_height(), '%d' % name_list_count[i], ha='center', va='bottom')
i += 1
# 显示图形
plt.show()
# 此函数用于绘制饼状图
def showNamePie(self, name_list_sort, name_list_fracs):
# 处理中文乱码
plt.rcParams['font.sans-serif'] = ['SimHei']
# 绘制饼状图
plt.pie(name_list_fracs, labels=name_list_sort, autopct='%1.2f%%', shadow=True)
# 显示图形
plt.show()
def getNameTimesSort(self,name_list,txt_path):
# 将所有人名临时添加到jieba所用字典,以使jieba能识别所有人名
for k in name_list:
jieba.add_word(k)
# 打开并读取txt文件
file_obj = open(txt_path, 'rb').read()
# jieba分词
jieba_cut = jieba.cut(file_obj)
# Counter重新组装以方便读取
book_counter = Counter(jieba_cut)
# 人名列表,因为要处理凤姐所以不直接用name_list
name_dict ={}
# 人名出现的总次数,用于后边计算百分比
name_total_count = 0
for k in name_list:
if k == '熙凤':
# 将熙凤出现的次数合并到凤姐
name_dict['凤姐'] += book_counter[k]
else:
name_dict[k] = book_counter[k]
name_total_count += book_counter[k]
# Counter重新组装以使用most_common排序
name_counter = Counter(name_dict)
# 按出现次数排序后的人名列表
name_list_sort = []
# 按出现次数排序后的人名百分比列表
name_list_fracs = []
# 按出现次数排序后的人名次数列表
name_list_count = []
for k,v in name_counter.most_common():
name_list_sort.append(k)
name_list_fracs.append(round(v/name_total_count,2)*100)
name_list_count.append(v)
# print(k+':'+str(v))
# 绘制条形图
self.showNameBar(name_list_sort, name_list_count)
# 绘制饼状图
self.showNamePie(name_list_sort,name_list_fracs)
if __name__ == '__main__':
# 参与统计的人名列表,可修改成自己想要的列表
name_list = ['宝玉', '贾母', '凤姐', '王夫人', '贾琏', '平儿', '袭人', '黛玉', '宝钗', '薛姨妈']
# 红楼梦txt文件所在路径,修改成自己文件所在路径
txt_path = 'F:/Python/红楼梦.txt'
hnc = HlmNameCount()
hnc.getNameTimesSort(name_list,txt_path)
#水浒传人物出现次数
print("水浒传人物出场次数:")
import jieba
import time
start=time.perf_counter()
txt=open("水浒传.txt","r",encoding="utf-8").read()
excludes={"二人","一个","来到","人马","你们","我们","好汉","军马","小人","今日","这个","先锋","宋江道",
"知府","什么","他们","银子","梁山","两个","只见","如何","那里","说道","众人","这里","兄弟","出来",
"妇人","便是","起来","问道","因此","三个","不得","如此","次日","只是","不知","不是","却是","呼延","不曾",
"梁山泊","一面","且说","看时","不敢","如今","原来","将军","山寨","只得","正是","喝道","一齐","当下",
"兄长"}
words=jieba.lcut(txt)
counts={}
for word in words:
if len(word)==1:
continue
elif word=="哥哥":
rword="宋江"
elif word=="头领":
rword="林冲"
else:
rword=word
counts[word]=counts.get(word,0)+1
for word in excludes:
del counts[word]
items=list(counts.items())
items.sort(key=lambda x:x[1],reverse=True)
for i in range(10):
word,count=items[i]
print("{0:<10}{1:>5}次".format(word,count))
dur=time.perf_counter()-startprint("运行时间为{:.2f}s".format(dur))
print("-----------------------------")
#水浒传任务出现次数导入csv
#导入csv安装包
import csv
#1、创建文件对象
with open('SHZcsv.csv','w',newline="") as csvfile:
#2、基于文件对象构建csv写入对象
writer=csv.writer(csvfile)
#3、构建列表头
writer.writerow(["人物","出现次数"])
#4、写入csv文件内容
writer.writerow(["宋江","2447"])
writer.writerow(["李逵","1093"])
writer.writerow(["武松","1027"])
writer.writerow(["林冲","693"])
writer.writerow(["吴用","626"])
writer.writerow(["卢俊义","547"])
writer.writerow(["鲁智深","325"])
writer.writerow(["柴进","305"])
writer.writerow(["戴宗","301"])
writer.writerow(["公孙胜","272"])
#水浒传树状图和饼状图
import jieba
from collections import Counter
import matplotlib.pyplot as plt
import numpy as np
class HlmNameCount():
# 此函数用于绘制条形图
def showNameBar(self,name_list_sort,name_list_count):
# x代表条形数量
x = np.arange(len(name_list_sort))
# 处理中文乱码
plt.rcParams['font.sans-serif'] = ['SimHei']
# 绘制条形图,bars相当于句柄
bars = plt.bar(x,name_list_count)
# 给各条形打上标签
plt.xticks(x,name_list_sort)
# 显示各条形具体数量
i = 0
for bar in bars:
plt.text((bar.get_x() + bar.get_width() / 2), bar.get_height(), '%d' % name_list_count[i], ha='center', va='bottom')
i += 1
# 显示图形
plt.show()
# 此函数用于绘制饼状图
def showNamePie(self, name_list_sort, name_list_fracs):
# 处理中文乱码
plt.rcParams['font.sans-serif'] = ['SimHei']
# 绘制饼状图
plt.pie(name_list_fracs, labels=name_list_sort, autopct='%1.2f%%', shadow=True)
# 显示图形
plt.show()
def getNameTimesSort(self,name_list,txt_path):
# 将所有人名临时添加到jieba所用字典,以使jieba能识别所有人名
for k in name_list:
jieba.add_word(k)
# 打开并读取txt文件
file_obj = open(txt_path, 'rb').read()
# jieba分词
jieba_cut = jieba.cut(file_obj)
# Counter重新组装以方便读取
book_counter = Counter(jieba_cut)
# 人名列表,因为要处理宋江所以不直接用name_list
name_dict ={}
# 人名出现的总次数,用于后边计算百分比
name_total_count = 0
for k in name_list:
if k == '哥哥':
name_dict['宋江'] += book_counter[k]
else:
name_dict[k] = book_counter[k]
name_total_count += book_counter[k]
# Counter重新组装以使用most_common排序
name_counter = Counter(name_dict)
# 按出现次数排序后的人名列表
name_list_sort = []
# 按出现次数排序后的人名百分比列表
name_list_fracs = []
# 按出现次数排序后的人名次数列表
name_list_count = []
for k,v in name_counter.most_common():
name_list_sort.append(k)
name_list_fracs.append(round(v/name_total_count,2)*100)
name_list_count.append(v)
# print(k+':'+str(v))
# 绘制条形图
self.showNameBar(name_list_sort, name_list_count)
# 绘制饼状图
self.showNamePie(name_list_sort,name_list_fracs)
if __name__ == '__main__':
# 参与统计的人名列表,可修改成自己想要的列表
name_list = ['宋江', '李逵', '武松', '林冲', '吴用', '卢俊义', '鲁智深', '柴进', '戴宗', '公孙胜']
# 水浒传txt文件所在路径,修改成自己文件所在路径
txt_path = 'F:/Python/水浒传.txt'
hnc = HlmNameCount()
hnc.getNameTimesSort(name_list,txt_path)
运行结果(水浒传)