-
Notifications
You must be signed in to change notification settings - Fork 0
/
plot_station.py
89 lines (74 loc) · 3.02 KB
/
plot_station.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
# -*- coding: utf-8 -*-
"""
@author: bav@geus.dk
tip list:
%matplotlib inline
%matplotlib qt
import pdb; pdb.set_trace()
"""
import matplotlib.pyplot as plt
import pandas as pd
path_l3 = '../aws-l3-dev/stations/'
path_tx = '../aws-l3/tx/'
path_gcn= 'C:/Users/bav/GitHub/PROMICE data/GC-Net-Level-1-data-processing/L1/'
df_meta = pd.read_csv(path_l3+'../AWS_latest_locations.csv')
# var_list = ['gps_geoid']
# var_list = ['t_i_'+str(i) for i in range(1,12)]
# var_list = [
# # 'batt_v', 't_u',
# # 'wspd_u',
# 'z_boom_u',
# 'z_boom_l',
# # 'z_pt_cor',
# # 't_i_all'
# ]
# var_list = ['p_u','p_l','p_i']
# var_list = ['t_u','t_l','t_i']
# var_list = ['rh_l','rh_i','rh_l_cor',]
# var_list = ['t_i','rh_i','p_i','wspd_i','wdir_i','z_boom_u', 'z_boom_l', 'gps_lat','gps_lon','gps_alt']
# var_list = ['gps_geounit']
# var_list = ['t_u', 't_l','ts']
# var_list = ['gps_lat', 'gps_lon','gps_alt']
var_list = ['z_surf_combined','z_ice_surf','snow_height','z_pt_cor']
station_list = df_meta.stid
# station_list = ['KPC_U']
# plt.close('all')
# gps_info=[]
for station in station_list:
print(station)
# if 'level' in path_l3:
df_l3 = pd.read_csv(path_l3+station+'/'+station+'_hour.csv')
# else:
# df_l3 = pd.read_csv(path_l3+station+'/'+station+'_10min.csv')
# gps_info=gps_info.append(df_l3['gps_geoid'].drop_duplicates())
df_l3.time = pd.to_datetime(df_l3.time, utc=True)
df_l3 = df_l3.set_index('time')
var_list_list = [var_list[i:i+6] for i in range(0, len(var_list),6)]
for k, var_list in enumerate(var_list_list):
fig, ax_list = plt.subplots(len(var_list),1,sharex=True, figsize=(13,13))
if len(var_list)==1:
ax_list = [ax_list]
for var, ax in zip(var_list, ax_list):
if (var not in df_l3.columns) :
print(var, 'not in L3 or tx data at', station)
if len(var_list) == 1:
plt.close(fig)
print(var)
ax.set_ylabel(var)
if var == 't_i_all':
var = ['t_i_%i'%i for i in range(1,12) if 't_i_%i'%i in df_l3.columns]
ax.plot(df_l3[var].index, df_l3[var].values,
marker='.',markeredgecolor='None',
linestyle='None', label=var,alpha=0.7)
else:
try:
ax.plot(df_l3[var].index, df_l3[var].values, marker='.',markeredgecolor='None', linestyle='None', label='l3',alpha=0.5)
except:
print(var,'not in L3 files')
ax.legend(loc='center right', bbox_to_anchor=(1.13, 0.5))
ax.grid()
# ax.plot(df_l3[var].index,Y_pred)
# ax.plot(df_l3[var].index,Y_pred*0, 'k', ls=':')
# print(station, Y_pred[-1] - Y[~np.isnan(X+Y)][0])
plt.suptitle('%s %i/%i'%(station, k+1, len(var_list_list)))
fig.savefig('figures/'+station+'_'+str( k+1)+'.png',dpi=300)