-
Notifications
You must be signed in to change notification settings - Fork 0
/
plotstreamflow.py
109 lines (99 loc) · 4.09 KB
/
plotstreamflow.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
# -*- coding: utf-8 -*-
"""
Created on Mon Dec 6 21:53:46 2021
@author: dingxj
"""
# import os
# import matplotlib.pyplot as plt
# import pandas as pd
# import numpy as np
# import matplotlib.dates as mdate
# mopex_path=r'\\192.168.0.110\d\dingxinjun\mopex\mopex_data\trans_data'
# pic_path=r'\\192.168.0.110\d\dingxinjun\mopex\mopex_data\pic_test'
# file_list=os.listdir(mopex_path)
# for filename in file_list:
# print(filename)
# file=os.path.join(mopex_path,filename)
# df=pd.read_csv(file,index_col=0)
# Q=df['daily streamflow discharge (mm)']
# Q[Q<0]=np.nan
# figure, ax = plt.subplots(figsize=(12,8))
# pic_name=filename[:-8]+'.png'
# ax.plot(df.index,Q)
# ax.set_xlim([df.index[0], df.index[-1]])
# ax.set_xticks(df.index[::3650],)
# ax.xaxis.set_major_formatter(mdate.DateFormatter('%d/%m/%Y'))
# ax.set_ylim(ymin=0)
# plt.savefig(os.path.join(pic_path,pic_name))
# plt.close()
#%%
#plot the mopex_camel data set
#这次plot按照camel数据文件夹一样存放数据的图片，所以加了一项，如果没有这样一个文件夹就创建一个文件夹并且存放图片
# import os
# import matplotlib.pyplot as plt
# import pandas as pd
# import numpy as np
# import matplotlib.dates as mdate
# camel_path=r'C:\F\code_notebook\Priestly_taylor\hydrological_input_data\camel_mopex'
# data_save_path=r'\\192.168.0.110\d\dingxinjun\mopex\Q-pic\mopex_camel'
# Folders=['01','02','03','04','05','06','07','08','09','10','11','12','13',
# '14','15','16','17','18']
# # for num in Folders[:2]:
# for num in Folders:
# folder_path=os.path.join(camel_path,num)
# list_of_file=os.listdir(folder_path)
# for file in list_of_file:
# file_path= os.path.join(camel_path,num,file)
# df=pd.read_csv(file_path,index_col=0)
# df.index=pd.to_datetime(df.index)
# Q=df['daily streamflow discharge (mm)']
# Q[Q<0]=np.nan
# figure, ax = plt.subplots(figsize=(12,8))
# pic_name=file[:-4]+'.png'
# ax.plot(df.index,Q)
# ax.set_xlim([df.index[0], df.index[-1]])
# ax.set_xticks(df.index[::3650])
# ax.xaxis.set_major_formatter(mdate.DateFormatter('%d/%m/%Y'))
# ax.set_ylim(ymin=0)
# #如果不存在num path就创建文件夹
# # data_save_path=r'\\192.168.0.110\d\dingxinjun\mopex\Q-pic\camel'
# save_folder_path=os.path.join(data_save_path,num)
# if not os.path.exists(save_folder_path):
# os.makedirs(save_folder_path)
# plt.savefig(os.path.join(save_folder_path,pic_name))
# plt.close()
#%%
#plot the camel data set
import os
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.dates as mdate
camel_path=r'C:\F\code_notebook\Priestly_taylor\hydrological_input_data\day_met'
data_save_path=r'\\192.168.0.110\d\dingxinjun\mopex\Q-pic\camel'
Folders=['01','02','03','04','05','06','07','08','09','10','11','12','13',
'14','15','16','17','18']
# for num in Folders[:2]:
for num in Folders:
folder_path=os.path.join(camel_path,num)
list_of_file=os.listdir(folder_path)
for file in list_of_file:
file_path= os.path.join(camel_path,num,file)
df=pd.read_csv(file_path,index_col=0)
df.index=pd.to_datetime(df.index)
Q=df['OBS_RUN']
Q[Q<0]=np.nan
figure, ax = plt.subplots(figsize=(12,8))
pic_name=file[:-4]+'.png'
ax.plot(df.index,Q)
ax.set_xlim([df.index[0], df.index[-1]])
ax.set_xticks(df.index[::3650])
ax.xaxis.set_major_formatter(mdate.DateFormatter('%d/%m/%Y'))
ax.set_ylim(ymin=0)
#如果不存在num path就创建文件夹
# data_save_path=r'\\192.168.0.110\d\dingxinjun\mopex\Q-pic\camel'
save_folder_path=os.path.join(data_save_path,num)
if not os.path.exists(save_folder_path):
os.makedirs(save_folder_path)
plt.savefig(os.path.join(save_folder_path,pic_name))
plt.close()