-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathtemp.py
108 lines (52 loc) · 2.79 KB
/
temp.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
import numpy as np
import pandas as pd
from math import sqrt
import time
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
# print(data_1.describe())
data_1 = pd.read_csv(open('c:/data/mm/2.csv'))
tim = data_1.ix[:, '时间'] # 2018042910515071 ,整型
tim = [int(time.mktime(time.strptime(str(t)[0:14], "%Y%m%d%H%M%S"))) for t in tim] # 时间戳
print(tim)
head = ['时间戳']
df = pd.DataFrame(tim, columns=head)
df.to_csv("c:/data/mm/time.csv", encoding="utf-8", index = False)
# 处理R信息数据， 61.csv
data_61 = pd.read_csv(open('c:/data/mm/61.csv'))
#data_61.as_matrix(columns=None)
array_61 = np.asarray(data_61)
head = ['时间', '经度', '纬度', '传感器类型', 'RA_1_1', 'RA_1_2', 'RA_2_1', 'RA_2_2', 'RA_3_1', 'RA_3_2', 'RA_4_1', 'RA_4_2', '信号源批号 ']
df = pd.DataFrame(array_61, columns=head)
df.to_csv('c:/data/mm/test.csv', index=False)
# 遍历各单元格，将多项数据求和处理
for i in range(len(array_61)):
for j in range(len(array_61[i])):
try:
array_61[i][j] = float(sum(list([float(k) for k in array_61[i][j].split(',')])))
except:
pass
target_number = array_61[:, 13]
signal_number = array_61[:, 12]
start_list = []
end_list = []
start_list.append(0)
for i in range(len(signal_number) - 1):
if signal_number[i] != signal_number[i + 1]:
end_list.append(i)
start_list.append(i + 1)
end_list.append(len(signal_number) - 1)
name_dic_r = {array_61[start_list[i], 12]: array_61[start_list[i], 13] for i in range(len(start_list))}
temp_r = [] # 按列求均
for i in range(len(start_list)):
r_list = [sum(array_61[start_list[i]:end_list[i], 4]) / len(array_61[start_list[i]:end_list[i], 4]),
sum(array_61[start_list[i]:end_list[i], 5]) / len(array_61[start_list[i]:end_list[i], 5]),
sum(array_61[start_list[i]:end_list[i], 6]) / len(array_61[start_list[i]:end_list[i], 6]),
sum(array_61[start_list[i]:end_list[i], 7]) / len(array_61[start_list[i]:end_list[i], 7]),
sum(array_61[start_list[i]:end_list[i], 8]) / len(array_61[start_list[i]:end_list[i], 8]),
sum(array_61[start_list[i]:end_list[i], 9]) / len(array_61[start_list[i]:end_list[i], 9]),
sum(array_61[start_list[i]:end_list[i], 10]) / len(array_61[start_list[i]:end_list[i], 10]),
sum(array_61[start_list[i]:end_list[i], 11]) / len(array_61[start_list[i]:end_list[i], 11])]
temp_r.append(r_list)
target_R = {array_61[start_list[i], 12]: sum(temp_r[i]) for i in range(len(start_list))}