def read_position_excel(config):
position_path = curPath.mainPath() + config.get_filename("position_file")
workbook = load_workbook(position_path)
sheets = workbook.get_sheet_names() # #四个sheet对应有四个维度,标签
data = {} #存罪犯数据
table = [] #存属性
booksheet = workbook.get_sheet_by_name(sheets[0])
rows = booksheet.rows
# 迭代所有的行
num_row = 0
for row in rows:
if num_row == 0:
line = [col.value for col in row]
table = table + line
else:
line = [col.value for col in row]
data[line[0]] = line
num_row = num_row + 1
# 不满足条件的罪犯数据删掉,此处数据很好,完备
new_data = {}
for key in data:
if (len(data[key]) == len(table)):
new_data[key] = data[key]
return table, new_data
def process(type, code):
con = db.DB()
sql = "select * from {} where id={}".format(type, code)
data = con.select(sql)
res = {}
if len(data) == 1:
# 查询到一个
adata = data[0]
# 导出table
if type == "thieves":
table = np.load(curPath.mainPath() + "/thieves_dq/thieves.npy",
allow_pickle=True)
elif type == "position":
table = np.load(curPath.mainPath() + "/position_zw/position.npy",
allow_pickle=True)
elif type == "fraudsters":
table = np.load(curPath.mainPath() +
"/fraudsters_zp/fraudsters.npy",
allow_pickle=True)
elif type == "drug":
table = np.load(curPath.mainPath() + "/drug/drug.npy",
allow_pickle=True)
elif type == "traffic":
table = np.load(curPath.mainPath() + "/traffic/traffic.npy",
allow_pickle=True)
elif type == "rape":
table = np.load(curPath.mainPath() + "/violence/rape.npy",
allow_pickle=True)
elif type == "rob":
table = np.load(curPath.mainPath() + "/violence/rob.npy",
allow_pickle=True)
elif type == "damage":
table = np.load(curPath.mainPath() + "/violence/damage.npy",
allow_pickle=True)
elif type == "intentkill":
table = np.load(curPath.mainPath() + "/violence/intentkill.npy",
allow_pickle=True)
else:
return {"err": "参数错误!"}
assert len(table) == len(adata) - 2
table = np.hstack((np.array(["id", "data_type"]), table))
for i in range(len(table)):
res[table[i]] = adata[i]
return res
elif len(data) == 0:
res["status"] = "id is not found!"
return res
return res
def read_thieves_excel(config):
thieves_path=curPath.mainPath()+config.get_filename("thieves_file")
workbook = load_workbook(thieves_path)
sheets = workbook.get_sheet_names() # #四个sheet对应有四个维度,标签
# print(sheets)
sheet_size=len(sheets)
data={}
table=[]
for i in range(sheet_size): #145列/289列/433列/577列
booksheet = workbook.get_sheet_by_name(sheets[i])
rows = booksheet.rows
# 迭代所有的行
num_row = 0
for row in rows:
if num_row == 0:
line = [col.value for col in row]
if i==0:
table=table+line
else:
table=table+line[1:]
num_row =num_row +1
else:
line = [col.value for col in row]
if line[0] not in data:
data[line[0]]=line
else:
data[line[0]]=data[line[0]]+line[1:]
num_row = num_row + 1
if i==3:
# print(table)
# print(data)
# print(len(table))
# print(len(data["14637李芸"]))
break
# 不满足条件的罪犯数据删掉
new_data={}
for key in data:
if (len(data[key]) == len(table)):
new_data[key]=data[key]
return table,new_data
def read_fraudsters_excel(config):
thieves_path=curPath.mainPath()+config.get_filename("fraudsters_file")
workbook = load_workbook(thieves_path)
sheets = workbook.get_sheet_names() # #四个sheet对应有四个维度,标签
# print(sheets)
sheet_size=len(sheets)
data={}
table=[]
for i in range(sheet_size): #先算好标签
booksheet = workbook.get_sheet_by_name(sheets[i])
rows = booksheet.rows
# 迭代所有的行,得到所有的标签
num_row = 0
for row in rows:
if num_row == 0:
line = [col.value for col in row]
if i==0:
table=table+line
else:
table=table+line[5:]
num_row =num_row +1
for i in range(sheet_size): #再计算里面的数据
booksheet = workbook.get_sheet_by_name(sheets[i])
rows = booksheet.rows
num_row=0
for row in rows:
if num_row != 0:
line = [col.value for col in row]
# print(line)
if line[0] not in data:
data[line[0]]=[]
if i==0:
data[line[0]]+=(line+[-1 for _ in range(len(table)-len(line))])
else:
data[line[0]]+=(line[:5]+[-1 for _ in range(len(table)-len(line))]+line[5:])
else:
data[line[0]]=data[line[0]][:17]+line[5:]
num_row = num_row + 1
return table,data
data_json.append(adata_json)
name_set.add(name)
if table == "intentkill":
qid_start = 8000
# 故意杀人
for j in range(1000):
adata = data[j]
id = adata[0]
name = adata[2]
age = adata[4]
type = adata[7]
note = name + "," + str(age) + "岁," + type + "," + kill_note()
# print(desc)
sql_updata = "update {} set note=\"{}\" where id={};".format(
table, note, int(id))
# print(sql_updata)
con.updata(sql_updata)
adata_json = {}
adata_json["qid"] = qid_start + int(id)
adata_json["type"] = table
adata_json["note"] = note
data_json.append(adata_json)
name_set.add(name)
sava_to_json.save_json(data_json,
curPath.mainPath() + "/bert/data/data.json")
save_to_txt(
name_set,
curPath.mainPath() +
"/bert/stopwords/姓名年龄岁.txt") #bert里面进行用的时候,去掉这些姓名等词语,所以提前保存停止词
# 5.建表
traffic_table_name = config.get_tablename("traffic_name")
sql_createTb = "create table {} (id int primary key auto_increment,data_type int(1) ,`{}`char(20) not null default ''," + "`{}` char(20) not null default ''," * (
len(table) - 2) + "{} text(1000))CHARSET=utf8;"
sql_createTb = sql_createTb.format(traffic_table_name, *table)
print(table)
print(sql_createTb)
con = db.DB()
con.chech_table_exit(traffic_table_name, sql_createTb)
# 6.数据写入
data_arr = []
for key in data:
adata = data[key]
sql_insert = "insert into {} values(default,0," + "'{}'," * (
len(adata)) + "'{}');"
try:
sql_insert = sql_insert.format(traffic_table_name, *adata,
p.join(flag_map[key]))
except:
sql_insert = sql_insert.format(traffic_table_name, *adata, "无")
print(sql_insert)
con.insert(sql_insert)
# print(data) # {key(编号),value:数据}
# 7.保存table用于提供web接口
np.save(curPath.mainPath() + "/traffic/traffic.npy", table)
# 3.5+4步骤中的数据static_map进行保存
sava_to_json.save_json(
static_map,
curPath.mainPath() + "/temp_file/traffic_static_map")
"适用人群": "暂时没有",
"单元": ["虚拟单元1(00017)", "虚拟单元2(00018)"]},
"虚拟疗法(20)": {
"age": "暂时没有",
"edu": "暂时没有",
"适用人群": "暂时没有",
"单元": ["虚拟单元1(00017)", "虚拟单元2(00018)"]},
"虚拟疗法(21)": {
"age": "暂时没有",
"edu": "暂时没有",
"适用人群": "暂时没有",
"单元": ["虚拟单元1(00017)", "虚拟单元2(00018)"]},
"虚拟疗法(22)": {
"age": "暂时没有",
"edu": "暂时没有",
"适用人群": "暂时没有",
"单元": ["虚拟单元1(00017)", "虚拟单元2(00018)"]},
"虚拟疗法(23)": {
"age": "暂时没有",
"edu": "暂时没有",
"适用人群": "暂时没有",
"单元": ["虚拟单元1(00017)", "虚拟单元2(00018)"]},
"虚拟疗法(24)": {
"age": "暂时没有",
"edu": "暂时没有",
"适用人群": "暂时没有",
"单元": ["虚拟单元1(00017)", "虚拟单元2(00018)"]},
}
s.save_json(flag_method,curPath.mainPath()+"/temp_file/flag_method.json")
s.save_json(method_plan,curPath.mainPath()+"/temp_file/method_plan.json")
flag_map = {}
for key in data:
dim = data[key].tolist()[-n:] #后面的维度项目总分
table2 = table.tolist()[-n - 1:-1] #后面的维度项目标签
flag_map[key] = []
for i in range(len(dim)):
if dim[i] > arr[i]:
flag_map[key].append(table2[i])
return flag_map
if __name__ == '__main__':
# 生成1k条虚拟数据
N = 1100
# 1.读取统计文件position_static_map.json
static_map = sava_to_json.load_json(curPath.mainPath() +
"/temp_file/thieves_static_map")
# print(len(static_map))
# 2.根据文件生成基本数据,根据文件的均值和标准差按照正太分布生成随机的问卷分数
data = {}
for i in range(N):
#编号
id = 20000 + i
sex = random.choice(range(2)) #1表示男,0表示女
name = random_name(sex)
start_id = str(id) + name
data[start_id] = []
data[start_id].append(start_id)
#性别 sex
data[start_id].append(sex)
flag_map = {}
for key in data:
dim = data[key].tolist()[-n:] #后面的维度项目总分
table2 = table.tolist()[-n - 1:-1] #后面的维度项目标签
flag_map[key] = []
for i in range(len(dim)):
if float(dim[i]) > float(arr[i]):
flag_map[key].append(table2[i])
return flag_map
if __name__ == '__main__':
# 生成1k条虚拟数据
N = 1100
# 1.读取统计文件position_static_map.json
static_map = sava_to_json.load_json(curPath.mainPath() +
"/temp_file/position_static_map")
print(len(static_map))
# 2.根据文件生成基本数据,根据文件的均值和标准差按照正太分布生成随机的问卷分数
data = {}
for i in range(N):
my_id = static_map["自编号"][-1] + 1 + i
name = random_name()
prison_room = random.choice(static_map["监狱"])
prison_area = random.choice(static_map["监区"])
r_id = 4500000000 + i
birth = randomtimes('1956-01-01-0-0', '1985-12-30-0-0')
birth2 = birth.strftime("%Y-%m-%d %H:%M:%S")
survey_data = randomtimes(
'2019-01-01-0-0', '2020-12-30-0-0').strftime("%Y-%m-%d %H:%M:%S")
import copy
import time
import random
import datetime
import position_zw.position as p
import position_zw.random_generate as pr
import violence.read_excel as v
if __name__ == '__main__':
N = 1100
# N=1
tablename = ["rape", "rob", "damage", "intentkill"]
for j in range(len(tablename)):
data = {}
static_map = sava_to_json.load_json(
curPath.mainPath() +
"/temp_file/{}_static_map".format(tablename[j]))
for i in range(N):
name = pr.random_name()
data[name] = []
data[name].append(name)
birth = pr.randomtimes('1956-01-01-0-0', '1985-12-30-0-0')
age = 2021 - birth.year
birth2 = birth.strftime("%Y-%m-%d")
data[name].append(birth2)
data[name].append(age)
data[name].append(random.choice(static_map["受教育程度"]))
data[name].append(random.choice(static_map["刑期"]))
data[name].append(random.choice(static_map["组别"]))
# 添加问卷量表数据
for key in static_map:
txt[m] = method_plan[m]
else:
txt["status"] = "flag is not found!"
return web.json_response(txt)
async def handle_greeting(self, request):
type = request.match_info.get('type')
code = request.match_info.get('code')
assert type in table
txt = process(type, code)
# print(txt)
return web.json_response(txt)
handler = Handler()
app = web.Application()
table = [
"thieves", "position", "fraudsters", "drug", "traffic", "rape", "rob",
"damage", "intentkill"
]
flag_method = s.load_json(curPath.mainPath() + "/temp_file/flag_method.json")
print(flag_method.keys())
method_plan = s.load_json(curPath.mainPath() + "/temp_file/method_plan.json")
app.add_routes([
web.get('/prisoners', handler.handle_intro),
web.get('/prisoners/flag={flag}', handler.handle_plan),
web.get('/prisoners/type={type}&code={code}', handler.handle_greeting)
])
# print(config)
app['config'] = config
web.run_app(app)
# print("每个犯人的标签:",flag_map)
#5.建表
thieves_table_name=config.get_tablename("thieves_name")
sql_createTb="create table {} (id int primary key auto_increment,data_type int(1) ,`{}`char(10) not null default '',"+"`{}` char(8) not null default '',"*(len(table)-2) +"{} text(1000))CHARSET=utf8;"
sql_createTb=sql_createTb.format(thieves_table_name,*table)
# print(sql_createTb)
con=db.DB()
con.chech_table_exit(thieves_table_name,sql_createTb)
#6.数据写入
data_arr=[]
# print(len(table))
# print(flag_map)
for key in data:
adata=data[key]
sql_insert = "insert into {} values(default,0," + "'{}'," * (len(adata)) + "'{}');"
try:
sql_insert=sql_insert.format(thieves_table_name,*adata,join(flag_map[key]))
except:
sql_insert=sql_insert.format(thieves_table_name,*adata,"无")
print(sql_insert)
con.insert(sql_insert)
# print(table)
# print(data)
# print(len(table))
# 7.保存table用于提供web接口
np.save(curPath.mainPath()+"/thieves_dq/thieves.npy", table)
# 3.5+4步骤中的数据static_map进行保存
sava_to_json.save_json(static_map,curPath.mainPath()+"/temp_file/thieves_static_map")
table=np.hstack((table, np.array(["标签"])))
flag_map,static_map=cul_flag(data,table,n,0.27,static_map)
# print(flag_map)
# print(data)
# 5.建表
fraudsters_table_name=config.get_tablename("fraudsters_name")
sql_createTb = "create table {} (id int primary key auto_increment,data_type int(1) ,`{}`char(10) not null default ''," + "`{}` char(10) not null default ''," * (
len(table) - 2) + "{} char(255) not null default '')CHARSET=utf8;"
sql_createTb = sql_createTb.format(fraudsters_table_name, *table)
# print(sql_createTb)
con = db.DB()
con.chech_table_exit(fraudsters_table_name, sql_createTb)
# 6.数据写入
data_arr = []
# print(len(table))
# print(flag_map)
for key in data:
adata = data[key]
sql_insert = "insert into {} values(default,0," + "'{}'," * (len(adata)) + "'{}');"
try:
sql_insert = sql_insert.format(fraudsters_table_name, *adata, join(flag_map[key]))
except:
sql_insert = sql_insert.format(fraudsters_table_name, *adata, "无")
print(sql_insert)
con.insert(sql_insert)
#7.保存table用于提供web接口
np.save(curPath.mainPath()+"/fraudsters_zp/fraudsters.npy", table)
sava_to_json.save_json(static_map,curPath.mainPath()+"/temp_file/fraudsters_static_map")
len(table) - 2) + "{} text(1000))CHARSET=utf8;"
sql_createTb = sql_createTb.format(position_table_name, *table)
# print(table)
print(sql_createTb)
con = db.DB()
con.chech_table_exit(position_table_name, sql_createTb)
#6.数据写入
data_arr = []
# print(len(table))
# print(flag_map)
for key in data:
adata = data[key]
sql_insert = "insert into {} values(default,0," + "'{}'," * (
len(adata)) + "'{}');"
try:
sql_insert = sql_insert.format(position_table_name, *adata,
join(flag_map[key]))
except:
sql_insert = sql_insert.format(position_table_name, *adata, "无")
print(sql_insert)
# con.insert(sql_insert)
# print(data) #{key(编号),value:数据}
# print(len(table)) #144条
# 7.保存table用于提供web接口
np.save(curPath.mainPath() + "/position_zw/position.npy", table)
# 3.5+4步骤中的数据static_map进行保存
sava_to_json.save_json(
static_map,
curPath.mainPath() + "/temp_file/position_static_map")
sum = 0
for j in items[i]:
sum += int(float(adata[j]))
inner_arr.append(sum)
data[int(adata[0])] = np.hstack(
(data[int(adata[0])], np.array(inner_arr)))
#处理inner_arr 进行评估是否含有这个标签
return data
if __name__ == '__main__':
# 生成1k条虚拟数据
N = 1100
# 1.读取统计文件drug_static_map.json
static_map = sava_to_json.load_json(curPath.mainPath() +
"/temp_file/drug_static_map")
# 2.根据文件生成基本数据,根据文件的均值和标准差按照正太分布生成随机的问卷分数
data = {}
base_id = int(max(static_map["ID完整"])) + 1
for i in range(N):
my_id = base_id + i
data[my_id] = [my_id]
data[my_id].append(random.choice(static_map["年龄"]))
data[my_id].append(random.choice(static_map["文化程度"]))
data[my_id].append(random.choice(static_map["罪名"]))
for key in static_map:
if len(static_map[key]) == 4:
data[my_id].append(pr.random_normal(static_map, key))
import random
import datetime
import position_zw.position as p
import position_zw.random_generate as pr
"""
这部分根据统计信息trafic_static_map完成数据的随机生成,并写入数据库,虚拟数据的data_type=1
1.读取统计文件trafic_static_map.json
2.根据文件生成基本数据,根据文件的均值和标准差按照正太分布生成随机的问卷分数
3.计算总分,按照打标签static_map中最后一项阈值,完成打标签
4.构造sql,写入数据库
"""
if __name__ == '__main__':
# 生成1k条虚拟数据
N = 1100
# 1.读取统计文件drug_static_map.json
static_map = sava_to_json.load_json(curPath.mainPath() +
"/temp_file/traffic_static_map")
print(len(static_map))
# 2.根据文件生成基本数据,根据文件的均值和标准差按照正太分布生成随机的问卷分数
data = {}
base_id = 1
for i in range(N):
name = pr.random_name()
data[name] = [name]
for key in static_map:
if len(static_map[key]) == 4:
data[name].append(pr.random_normal(static_map, key))
# 3.计算总分, 按照打标签static_map中最后一项阈值, 完成打标签
n = 0
import thieves_dq.random_generate as th_random
import position_zw.position as p
import position_zw.random_generate as pr
"""
这部分根据统计信息thieves_static_map完成数据的随机生成,并写入数据库,虚拟数据的data_type=1
1.读取统计文件thieves_static_map.json, -1并未参与到统计中
2.根据文件生成基本数据,根据文件的均值和标准差按照正太分布生成随机的问卷分数
注意的是两个属性只能生成一种属性,所以可以使用一个随机数决定创造力还是马式
3.计算总分,按照打标签static_map中最后一项阈值,完成打标签
4.构造sql,写入数据库
"""
if __name__ == '__main__':
# 生成1k条虚拟数据
N = 1100
# 1.读取统计文件position_static_map.json
static_map = sava_to_json.load_json(curPath.mainPath() +
"/temp_file/fraudsters_static_map")
print(len(static_map))
# 2.根据文件生成基本数据,根据文件的均值和标准差按照正太分布生成随机的问卷分数
data = {}
base_id = max(static_map["罪犯编号"]) + 1
for i in range(N):
id = base_id + i
data[id] = []
data[id].append(id) #"罪犯编号"
data[id].append(random.choice(static_map["队别"]))
data[id].append(pr.random_name())
data[id].append(random.choice(static_map["受教育"]))
data[id].append(random.choice(static_map["年龄"]))
flag = random.choice(range(2))
# print(table)
print(sql_createTb)
con = db.DB()
con.chech_table_exit(position_table_name, sql_createTb)
# 6.数据写入
data_arr = []
# print(len(table))
# print(flag_map)
for key in n_data:
adata = n_data[key]
sql_insert = "insert into {} values(default,0," + "'{}'," * (
len(adata)) + "'{}');"
try:
sql_insert = sql_insert.format(position_table_name, *adata,
p.join(flag_map[key]))
except:
sql_insert = sql_insert.format(position_table_name, *adata,
"无")
print(sql_insert)
con.insert(sql_insert)
# 7.保存table用于提供web接口: 如: data_rape.npy
np.save(curPath.mainPath() + "/violence/{}.npy".format(tablename[i]),
table)
# 3.5+4步骤中的数据static_map进行保存 data_rape_static_map
sava_to_json.save_json(
static_map,
curPath.mainPath() +
"/temp_file/{}_static_map".format(tablename[i]))
# 5.建表
drug_table_name = config.get_tablename("drug_name")
sql_createTb = "create table {} (id int primary key auto_increment,data_type int(1) ,`{}`char(20) not null default ''," + "`{}` char(40) not null default ''," * (
len(table) - 2) + "{} text(1000))CHARSET=utf8;"
sql_createTb = sql_createTb.format(drug_table_name, *table)
print(table)
print(sql_createTb)
con = db.DB()
con.chech_table_exit(drug_table_name, sql_createTb)
# 6.数据写入
data_arr = []
for key in data:
adata = data[key]
sql_insert = "insert into {} values(default,0," + "'{}'," * (
len(adata)) + "'{}');"
try:
sql_insert = sql_insert.format(drug_table_name, *adata,
p.join(flag_map[key]))
except:
sql_insert = sql_insert.format(drug_table_name, *adata, "无")
print(sql_insert)
con.insert(sql_insert)
# print(data) # {key(编号),value:数据}
# 7.保存table用于提供web接口
np.save(curPath.mainPath() + "/drug/drug.npy", table)
# 3.5+4步骤中的数据static_map进行保存
sava_to_json.save_json(static_map,
curPath.mainPath() + "/temp_file/drug_static_map")