-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathex2.py
113 lines (94 loc) · 4.52 KB
/
ex2.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
from math import exp
import netCDF4 as nc
import numpy as np # 调用 numpy
import pandas as pd
upfrist = ['air', 'hgt', 'uv']
var = ['air', 'hgt', 'u', 'v']
frist = ['1000', '925', '850', '700', '600', '500']
second = ['2021052000', '2021052006', '2021052012', '2021052018', '2021052100', '2021052106', '2021052112',
'2021052118', '2021052200', '2021052206', '2021052212', '2021052218', '2021052300', '2021052306',
'2021052312', '2021052318', '2021052400']
a = np.full((len(var), len(second), len(frist), 29, 45), 9.9936 * exp(-36)) # 创建一个五维数组
for k in upfrist:
for i in frist:
for j in second:
filename = 'D:\\python\\tianzhen\\shixi2\\' + k + '\\' + i + '\\' + j + '.txt'
f = open(filename, 'r', encoding='UTF-8')
if k != 'uv': # 读取气温，位势高度
for bb in range(4): # 提前读取，跳过前四行
b = f.readline()
for y_i in range(28, -1, -1):
x_i = 0
for bbb in range(5):
List = f.readline()
list_start = 2 # 字符串截取起始
list_end = 11 # 字符串截取结束
for x in range(10):
a[upfrist.index(k), second.index(j), frist.index(i), y_i, x_i] = float(
List[list_start:list_end:1])
list_start += 10 # 跳到下一个数据的两侧
list_end += 10
x_i += 1
if x_i == 45: # 第五行只有五个数据，设置提前跳出循环
break
else: # 读取 uv 风场
for bb in range(3):
b = f.readline()
for var_i in range(2, 4):
for y_i in range(28, -1, -1):
x_i = 0 # 数据纬向存储（按列）
for bbb in range(5):
List = f.readline()
list_start = 2 # 字符串截取起始
list_end = 11 # 字符串截取结束
for x in range(10):
a[var_i, second.index(j), frist.index(i), y_i, x_i] = float(
List[list_start:list_end:1])
list_start += 10 # 跳到下一个数据的两侧
list_end += 10
x_i += 1
if x_i == 45:
break
print(a[0, 0, 0, 0, 0])
##############################创建 nc 文件
f_w = nc.Dataset('D:\\python\\tianzhen\\shixi2\\al.nc', 'w', format('NETCDF4'))
###创建一个组容纳所有变量
all_var = f_w.createGroup('shixi')
# 定义维度
f_w.createDimension('time', 17)
f_w.createDimension('level', 6)
f_w.createDimension('lat', 29)
f_w.createDimension('lon', 45)
# 给维度设置
f_w.createVariable('time', 'f', 'time')
f_w.createVariable('level', np.int32, 'level')
f_w.createVariable('lat', np.float32, 'lat')
f_w.createVariable('lon', np.float32, 'lon')
# time = np.array([2021052000, 2021052006, 2021052012, 2021052018, 2021052100, 2021052106, 2021052112,
# 2021052118, 2021052200, 2021052206, 2021052212, 2021052218, 2021052300, 2021052306,
# 2021052312, 2021052318, 2021052400])
time = pd.date_range(start='20210520', end='20210524', periods=17)
# time= np.arange(17)
level = np.array([1000, 925, 850, 700, 600, 500])
lat = np.linspace(10, 81, 29)
lon = np.linspace(50, 160, 45)
print(len(time))
f_w.variables['time'][:] = time
f_w.variables['level'][:] = level
f_w.variables['lat'][:] = lat
f_w.variables['lon'][:] = lon
###在组里创建变量
all_var.createVariable('air', np.float32, ('time', 'level', 'lat', 'lon'))
all_var.createVariable('hgt', np.float32, ('time', 'level', 'lat', 'lon'))
all_var.createVariable('u', np.float32, ('time', 'level', 'lat', 'lon'))
all_var.createVariable('v', np.float32, ('time', 'level', 'lat', 'lon'))
###给变量设初值
var_data = np.full((17, 6, 29, 45), -99.9)
all_var.variables['air'][:] = var_data
all_var.variables['hgt'][:] = var_data
all_var.variables['u'][:] = var_data
all_var.variables['v'][:] = var_data
###给变量赋值
all_var.variables['air'][:] = a[0, :, :, :, :]
all_var.close
f_w.close()