-
Notifications
You must be signed in to change notification settings - Fork 0
/
InsertData.py
172 lines (158 loc) · 6.95 KB
/
InsertData.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
# -*- coding: UTF-8 -*-
import random
import cx_Oracle as cx
import numpy as np
import matplotlib.pyplot as plt
Imaginary = {
"table": "GRACEFULGOODS_SHOW_INFO",
"text": "Weapons"
}
# 拟合数据控制器
FittingData = {
# 生成文本文件的名字
"text": "DailyLifeGoods",
# 数量曲线待拟合点的横纵坐标(纵坐标最好为整数)
"num_point_x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
"num_point_y": [100, 120, 150, 160, 140, 120, 110, 108, 113, 125, 133, 145, 155, 178, 190],
# 重量曲线待拟合点的横纵坐标
"weight_point_x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15],
"weight_point_y": [100, 120, 150, 160, 140, 120, 110, 108, 113, 125, 133, 145, 155, 178, 190],
# 重量数据小数点位数(单位:kg)
"weight_digit": 3,
# 拟合区间(-1对应最后一个点)
"num_fit_range": [0, -1],
"weight_fit_range": [0, -1],
# 拟合系数
"num_fitLevel": 8.5,
"weight_fitLevel": 8.5,
# 扰动系数
"num_floatLevel": 5,
"weight_floatLevel": 1,
# 收缩系数
"num_shrinkLevel": 1,
"weight_shrinkLevel": 1,
# 数据条数
"linesNum": 10000,
# 显示
"num_curve": 1,
"weight_curve": 1,
}
def generateFittingData():
if FittingData["num_curve"] == 1:
# 待拟合点排序
index = 0
num_point_list = []
for i in FittingData["num_point_x"]:
num_point_list.append([])
num_point_list[index].append(i)
index += 1
index = 0
for i in FittingData["num_point_y"]:
num_point_list[index].append(i)
index += 1
num_point_list.sort(key=lambda x: x[0])
num_point = {}
for i in num_point_list:
num_point[i[0]] = i[1]
num_x = np.array(list(num_point.keys()))
num_y = np.array(list(num_point.values()))
fit = np.polyfit(num_x, num_y, FittingData["num_fitLevel"])
num_fun = np.poly1d(fit)
plt.plot(num_x, num_y, "r*", label="num_point")
num_x_fit = np.linspace(num_x[FittingData["num_fit_range"][0]], num_x[FittingData["num_fit_range"][1]],
FittingData["linesNum"])
num_r_normal = np.random.normal(0, FittingData["num_floatLevel"], FittingData["linesNum"]) / \
FittingData[
"num_shrinkLevel"]
# 数量 整数化处理
num_y_fit = num_fun(num_x_fit) + num_r_normal
for i in range(len(num_y_fit)):
num_y_fit[i] = int(num_y_fit[i])
plt.plot(num_x_fit, num_y_fit, "b", label="num_curve")
if FittingData["weight_curve"]:
# 待拟合点排序
index = 0
weight_point_list = []
for i in FittingData["weight_point_x"]:
weight_point_list.append([])
weight_point_list[index].append(i)
index += 1
index = 0
for i in FittingData["weight_point_y"]:
weight_point_list[index].append(i)
index += 1
weight_point_list.sort(key=lambda x: x[0])
weight_point = {}
for i in weight_point_list:
weight_point[i[0]] = i[1]
weight_x = np.array(list(weight_point.keys()))
weight_y = np.array(list(weight_point.values()))
fit = np.polyfit(weight_x, weight_y, FittingData["weight_fitLevel"])
weight_fun = np.poly1d(fit)
plt.plot(weight_x, weight_y, "g*", label="weight_point")
weight_x_fit = np.linspace(weight_x[FittingData["weight_fit_range"][0]],
weight_x[FittingData["weight_fit_range"][1]], FittingData["linesNum"])
weight_r_normal = np.random.normal(0, FittingData["weight_floatLevel"], FittingData["linesNum"]) / \
FittingData[
"weight_shrinkLevel"]
# 重量 小数位控制
weight_y_fit = weight_fun(weight_x_fit) + weight_r_normal
for i in range(len(weight_y_fit)):
weight_y_fit[i] = round(weight_y_fit[i], FittingData["weight_digit"])
plt.plot(weight_x_fit, weight_y_fit, "y", label="weight_curve")
if FittingData["num_curve"] == 1 or FittingData["weight_curve"] == 1:
plt.xlabel('time')
plt.ylabel('value')
plt.title('Fitting result')
plt.legend()
plt.show()
if FittingData["num_curve"] == 1 and FittingData["weight_curve"] == 1:
fp = open("FITTING_DATA/{}.txt".format(FittingData["text"]), "w")
for i in range(1, FittingData["linesNum"] + 1):
fp.write("{order} {num} {weight}\n".format(order=i, num=int(num_y_fit[i - 1]),
weight=round(weight_y_fit[i - 1], FittingData["weight_digit"])))
def insertSql(Id, GOODS_TYPE, GOODS_NUM, GOODS_WEIGHT, DEPARTURE_TIME, SEND_LONGTITUDE, SEND_LATITUDE, TO_LONGTITUDE,
TO_LATITUDE, TRANSPORT_TYPE, SEND_CITYNAME, TO_CITYNAME):
DEPARTURE_TIME = "to_date(\'{}\', \'yyyy-mm-dd\')".format(DEPARTURE_TIME)
sql = "insert into {table} " \
"values({id}, \'{goods_type}\', {goods_num}, {goods_weight}, {departure_time}, {send_long}, {send_la}, {to_long}, {to_la}, {transport_type}, \'{send_cityName}\', \'{to_cityName}\')" \
.format(table=Imaginary["table"], id=Id, goods_type=GOODS_TYPE, goods_num=GOODS_NUM, goods_weight=GOODS_WEIGHT,
departure_time=DEPARTURE_TIME, send_long=SEND_LONGTITUDE, send_la=SEND_LATITUDE, to_long=TO_LONGTITUDE,
to_la=TO_LATITUDE, transport_type=TRANSPORT_TYPE, send_cityName=SEND_CITYNAME, to_cityName=TO_CITYNAME)
return sql
def InsertImaginaryData():
con = cx.connect('temptest', 'temptest', '81.70.76.251/helowin')
cursor = con.cursor()
fp = open("GRACEFULGOODS_NEW_INFO/{}.txt".format(Imaginary["text"]), "r")
insertData = []
line = 0
while True:
content = fp.readline()
if content:
insertData.append(content.split(' '))
id = int(insertData[line][0])
goods_type = insertData[line][1]
goods_num = int(insertData[line][2])
goods_weight = int(insertData[line][3])
departure_time = insertData[line][4]
send_long = float(insertData[line][5])
send_la = float(insertData[line][6])
to_long = float(insertData[line][7])
to_la = float(insertData[line][8])
transport_type = int(insertData[line][9])
send_cityName = insertData[line][10].split('\n')[0]
to_cityName = insertData[line][11].split('\n')[0]
sql = insertSql(id, goods_type, goods_num, goods_weight, departure_time, send_long, send_la, to_long, to_la,
transport_type, send_cityName, to_cityName)
print(sql)
cursor.execute(sql)
line += 1
# print(content)
else:
break
fp.close()
con.commit()
cursor.close()
con.close()
# InsertImaginaryData()
generateFittingData()