|
1
|
|
|
# -*- coding: utf-8 -*- |
|
2
|
|
|
# vim:fileencoding=utf-8 |
|
3
|
|
|
# |
|
4
|
|
|
# Copyright (c) 2014-2017 Stefan Bender |
|
5
|
|
|
# |
|
6
|
|
|
# This file is part of sciapy. |
|
7
|
|
|
# sciapy is free software: you can redistribute it or modify it |
|
8
|
|
|
# under the terms of the GNU General Public License as published by |
|
9
|
|
|
# the Free Software Foundation, version 2. |
|
10
|
|
|
# See accompanying LICENSE file or http://www.gnu.org/licenses/gpl-2.0.html. |
|
11
|
1 |
|
"""SCIAMACHY level 1c limb spectra netcdf interface |
|
12
|
|
|
""" |
|
13
|
|
|
|
|
14
|
1 |
|
from __future__ import absolute_import, division, print_function |
|
15
|
|
|
|
|
16
|
1 |
|
import numpy as np |
|
17
|
1 |
|
try: |
|
18
|
1 |
|
from netCDF4 import Dataset as netcdf_file |
|
19
|
1 |
|
_fmtargs = {"format": "NETCDF4"} |
|
20
|
|
|
except ImportError: |
|
21
|
|
|
try: |
|
22
|
|
|
from scipy.io.netcdf import netcdf_file |
|
23
|
|
|
_fmtargs = {"version": 1} |
|
24
|
|
|
except ImportError: |
|
25
|
|
|
from pupynere import netcdf_file |
|
26
|
|
|
_fmtargs = {"version": 1} |
|
27
|
|
|
|
|
28
|
1 |
|
from ._types import _limb_data_dtype, _try_decode |
|
29
|
|
|
|
|
30
|
1 |
|
def read_from_netcdf(self, filename): |
|
31
|
|
|
"""SCIAMACHY level 1c limb scan netcdf import |
|
32
|
|
|
|
|
33
|
|
|
Parameters |
|
34
|
|
|
---------- |
|
35
|
|
|
filename : str |
|
36
|
|
|
The netcdf filename to read the data from. |
|
37
|
|
|
|
|
38
|
|
|
Returns |
|
39
|
|
|
------- |
|
40
|
|
|
nothing |
|
41
|
|
|
""" |
|
42
|
1 |
|
import numpy.lib.recfunctions as rfn |
|
43
|
|
|
|
|
44
|
1 |
|
ncf = netcdf_file(filename, 'r') |
|
45
|
|
|
|
|
46
|
1 |
|
self.textheader_length = ncf.textheader_length |
|
47
|
1 |
|
self.textheader = _try_decode(ncf.textheader) |
|
48
|
|
|
|
|
49
|
1 |
|
self.orbit_state = ncf.orbit_state |
|
50
|
1 |
|
(self.orbit, self.state_in_orbit, self.state_id, |
|
51
|
|
|
self.profiles_per_state, self.profile_in_state) = self.orbit_state |
|
52
|
1 |
|
self.date = ncf.date |
|
53
|
1 |
|
self.cent_lat_lon = ncf.cent_lat_lon |
|
54
|
1 |
|
self.orbit_phase = ncf.orbit_phase |
|
55
|
|
|
|
|
56
|
1 |
|
try: |
|
57
|
1 |
|
self.nalt = ncf.dimensions['limb'].size |
|
58
|
1 |
|
self.npix = ncf.dimensions['wavelength'].size |
|
59
|
|
|
except: |
|
60
|
|
|
self.nalt = ncf.dimensions['limb'] |
|
61
|
|
|
self.npix = ncf.dimensions['wavelength'] |
|
62
|
|
|
|
|
63
|
1 |
|
self.wls = ncf.variables['wavelength'][:].copy() |
|
64
|
|
|
|
|
65
|
|
|
# pre-set the limb_data |
|
66
|
1 |
|
if self._limb_data_dtype is None: |
|
67
|
1 |
|
self._limb_data_dtype = _limb_data_dtype[:] |
|
68
|
1 |
|
self.limb_data = np.zeros((self.nalt), dtype=self._limb_data_dtype) |
|
69
|
|
|
|
|
70
|
1 |
|
self.limb_data["sub_sat_lat"] = ncf.variables['sub_sat_lat'][:].copy() |
|
71
|
1 |
|
self.limb_data["sub_sat_lon"] = ncf.variables['sub_sat_lon'][:].copy() |
|
72
|
1 |
|
self.limb_data["tp_lat"] = ncf.variables['TP latitude'][:].copy() |
|
73
|
1 |
|
self.limb_data["tp_lon"] = ncf.variables['TP longitude'][:].copy() |
|
74
|
1 |
|
self.limb_data["tp_alt"] = ncf.variables['TP altitude'][:].copy() |
|
75
|
1 |
|
self.limb_data["tp_sza"] = ncf.variables['TP SZA'][:].copy() |
|
76
|
1 |
|
self.limb_data["tp_saa"] = ncf.variables['TP SAA'][:].copy() |
|
77
|
1 |
|
self.limb_data["tp_los"] = ncf.variables['TP LOS Zenith'][:].copy() |
|
78
|
1 |
|
self.limb_data["toa_sza"] = ncf.variables['TOA SZA'][:].copy() |
|
79
|
1 |
|
self.limb_data["toa_saa"] = ncf.variables['TOA SAA'][:].copy() |
|
80
|
1 |
|
self.limb_data["toa_los"] = ncf.variables['TOA LOS Zenith'][:].copy() |
|
81
|
1 |
|
self.limb_data["sat_sza"] = ncf.variables['SAT SZA'][:].copy() |
|
82
|
1 |
|
self.limb_data["sat_saa"] = ncf.variables['SAT SAA'][:].copy() |
|
83
|
1 |
|
self.limb_data["sat_los"] = ncf.variables['SAT LOS Zenith'][:].copy() |
|
84
|
1 |
|
self.limb_data["sat_alt"] = ncf.variables['SAT altitude'][:].copy() |
|
85
|
1 |
|
self.limb_data["earth_rad"] = ncf.variables['earthradius'][:].copy() |
|
86
|
|
|
|
|
87
|
1 |
|
tmp_rad_arr = list(ncf.variables['radiance'][:].copy()) |
|
88
|
1 |
|
tmp_err_arr = list(ncf.variables['radiance errors'][:].copy()) |
|
89
|
|
|
|
|
90
|
|
|
# save to limb_data recarray |
|
91
|
1 |
|
rads = np.rec.fromarrays([tmp_rad_arr], |
|
92
|
|
|
dtype=np.dtype([("rad", 'f4', (self.npix,))])) |
|
93
|
1 |
|
errs = np.rec.fromarrays([tmp_err_arr], |
|
94
|
|
|
dtype=np.dtype([("err", 'f4', (self.npix,))])) |
|
95
|
1 |
|
self.limb_data = rfn.merge_arrays([self.limb_data, rads, errs], |
|
96
|
|
|
usemask=False, asrecarray=True, flatten=True) |
|
97
|
1 |
|
self._limb_data_dtype = self.limb_data.dtype |
|
98
|
|
|
|
|
99
|
1 |
|
if hasattr(ncf, "_attributes"): |
|
100
|
|
|
# scipy.io.netcdf / pupynere |
|
101
|
|
|
ncattrs = ncf._attributes.keys() |
|
102
|
|
|
else: |
|
103
|
|
|
# netcdf4 |
|
104
|
1 |
|
ncattrs = ncf.ncattrs() |
|
105
|
1 |
|
for _k in ncattrs: |
|
106
|
1 |
|
if _k.startswith("metadata"): |
|
107
|
1 |
|
_meta_key = _k.split("::")[1] |
|
108
|
1 |
|
_att = getattr(ncf, _k) |
|
109
|
1 |
|
self.metadata[_meta_key] = _try_decode(_att) |
|
110
|
1 |
|
ncf.close() |
|
111
|
|
|
|
|
112
|
1 |
|
def write_to_netcdf(self, filename): |
|
113
|
|
|
"""SCIAMACHY level 1c limb scan netcdf export |
|
114
|
|
|
|
|
115
|
|
|
Parameters |
|
116
|
|
|
---------- |
|
117
|
|
|
filename : str |
|
118
|
|
|
The netcdf filename to write the data to. |
|
119
|
|
|
|
|
120
|
|
|
Returns |
|
121
|
|
|
------- |
|
122
|
|
|
nothing |
|
123
|
|
|
""" |
|
124
|
1 |
|
ncf = netcdf_file(filename, 'w', **_fmtargs) |
|
125
|
|
|
|
|
126
|
1 |
|
ncf.textheader_length = self.textheader_length |
|
127
|
1 |
|
ncf.textheader = self.textheader |
|
128
|
|
|
|
|
129
|
1 |
|
ncf.orbit_state = self.orbit_state |
|
130
|
1 |
|
ncf.date = self.date |
|
131
|
1 |
|
ncf.cent_lat_lon = self.cent_lat_lon |
|
132
|
1 |
|
ncf.orbit_phase = self.orbit_phase |
|
133
|
|
|
|
|
134
|
1 |
|
ncf.createDimension('limb', self.nalt) |
|
135
|
1 |
|
ncf.createDimension('wavelength', self.npix) |
|
136
|
|
|
|
|
137
|
1 |
|
wavs = ncf.createVariable('wavelength', np.dtype('float32').char, ('wavelength',)) |
|
138
|
1 |
|
wavs.units = 'nm' |
|
139
|
1 |
|
wavs[:] = np.asarray(self.wls) |
|
140
|
|
|
|
|
141
|
1 |
|
sslat = ncf.createVariable('sub_sat_lat', np.dtype('float32').char, ('limb',)) |
|
142
|
1 |
|
sslat.units = 'deg' |
|
143
|
1 |
|
sslat[:] = np.asarray(self.limb_data["sub_sat_lat"]) |
|
144
|
1 |
|
sslon = ncf.createVariable('sub_sat_lon', np.dtype('float32').char, ('limb',)) |
|
145
|
1 |
|
sslon.units = 'deg' |
|
146
|
1 |
|
sslon[:] = np.asarray(self.limb_data["sub_sat_lon"]) |
|
147
|
1 |
|
tp_lats = ncf.createVariable('TP latitude', np.dtype('float32').char, ('limb',)) |
|
148
|
1 |
|
tp_lats.units = 'deg' |
|
149
|
1 |
|
tp_lats[:] = np.asarray(self.limb_data["tp_lat"]) |
|
150
|
1 |
|
tp_lons = ncf.createVariable('TP longitude', np.dtype('float32').char, ('limb',)) |
|
151
|
1 |
|
tp_lons.units = 'deg' |
|
152
|
1 |
|
tp_lons[:] = np.asarray(self.limb_data["tp_lon"]) |
|
153
|
1 |
|
tp_alts = ncf.createVariable('TP altitude', np.dtype('float32').char, ('limb',)) |
|
154
|
1 |
|
tp_alts.units = 'km' |
|
155
|
1 |
|
tp_alts[:] = np.asarray(self.limb_data["tp_alt"]) |
|
156
|
1 |
|
tp_szas = ncf.createVariable('TP SZA', np.dtype('float32').char, ('limb',)) |
|
157
|
1 |
|
tp_szas.units = 'deg' |
|
158
|
1 |
|
tp_szas[:] = np.asarray(self.limb_data["tp_sza"]) |
|
159
|
1 |
|
tp_saas = ncf.createVariable('TP SAA', np.dtype('float32').char, ('limb',)) |
|
160
|
1 |
|
tp_saas.units = 'deg' |
|
161
|
1 |
|
tp_saas[:] = np.asarray(self.limb_data["tp_saa"]) |
|
162
|
1 |
|
tp_los_zeniths = ncf.createVariable('TP LOS Zenith', np.dtype('float32').char, ('limb',)) |
|
163
|
1 |
|
tp_los_zeniths.units = 'deg' |
|
164
|
1 |
|
tp_los_zeniths[:] = np.asarray(self.limb_data["tp_los"]) |
|
165
|
1 |
|
toa_szas = ncf.createVariable('TOA SZA', np.dtype('float32').char, ('limb',)) |
|
166
|
1 |
|
toa_szas.units = 'deg' |
|
167
|
1 |
|
toa_szas[:] = np.asarray(self.limb_data["toa_sza"]) |
|
168
|
1 |
|
toa_saas = ncf.createVariable('TOA SAA', np.dtype('float32').char, ('limb',)) |
|
169
|
1 |
|
toa_saas.units = 'deg' |
|
170
|
1 |
|
toa_saas[:] = np.asarray(self.limb_data["toa_saa"]) |
|
171
|
1 |
|
toa_los_zeniths = ncf.createVariable('TOA LOS Zenith', np.dtype('float32').char, ('limb',)) |
|
172
|
1 |
|
toa_los_zeniths.units = 'deg' |
|
173
|
1 |
|
toa_los_zeniths[:] = np.asarray(self.limb_data["toa_los"]) |
|
174
|
1 |
|
sat_szas = ncf.createVariable('SAT SZA', np.dtype('float32').char, ('limb',)) |
|
175
|
1 |
|
sat_szas.units = 'deg' |
|
176
|
1 |
|
sat_szas[:] = np.asarray(self.limb_data["sat_sza"]) |
|
177
|
1 |
|
sat_saas = ncf.createVariable('SAT SAA', np.dtype('float32').char, ('limb',)) |
|
178
|
1 |
|
sat_saas.units = 'deg' |
|
179
|
1 |
|
sat_saas[:] = np.asarray(self.limb_data["sat_saa"]) |
|
180
|
1 |
|
sat_los_zeniths = ncf.createVariable('SAT LOS Zenith', np.dtype('float32').char, ('limb',)) |
|
181
|
1 |
|
sat_los_zeniths.units = 'deg' |
|
182
|
1 |
|
sat_los_zeniths[:] = np.asarray(self.limb_data["sat_los"]) |
|
183
|
1 |
|
sat_alts = ncf.createVariable('SAT altitude', np.dtype('float32').char, ('limb',)) |
|
184
|
1 |
|
sat_alts.units = 'km' |
|
185
|
1 |
|
sat_alts[:] = np.asarray(self.limb_data["sat_alt"]) |
|
186
|
1 |
|
eradii_alts = ncf.createVariable('earthradius', np.dtype('float32').char, ('limb',)) |
|
187
|
1 |
|
eradii_alts.units = 'km' |
|
188
|
1 |
|
eradii_alts[:] = np.asarray(self.limb_data["earth_rad"]) |
|
189
|
|
|
|
|
190
|
1 |
|
try: |
|
191
|
1 |
|
rads = ncf.createVariable('radiance', np.dtype('float32').char, |
|
192
|
|
|
('limb', 'wavelength'), zlib=True, complevel=1) |
|
193
|
1 |
|
errs = ncf.createVariable('radiance errors', np.dtype('float32').char, |
|
194
|
|
|
('limb', 'wavelength'), zlib=True, complevel=1) |
|
195
|
|
|
except TypeError: |
|
196
|
|
|
rads = ncf.createVariable('radiance', np.dtype('float32').char, |
|
197
|
|
|
('limb', 'wavelength')) |
|
198
|
|
|
errs = ncf.createVariable('radiance errors', np.dtype('float32').char, |
|
199
|
|
|
('limb', 'wavelength')) |
|
200
|
1 |
|
rads.units = 'ph / s / cm^2 / nm' |
|
201
|
1 |
|
errs.units = 'ph / s / cm^2 / nm' |
|
202
|
1 |
|
rads[:] = np.asarray(self.limb_data["rad"]).reshape(self.nalt, self.npix) |
|
203
|
1 |
|
errs[:] = np.asarray(self.limb_data["err"]).reshape(self.nalt, self.npix) |
|
204
|
|
|
|
|
205
|
1 |
|
for _k, _v in self.metadata.items(): |
|
206
|
1 |
|
setattr(ncf, "metadata::" + _k, _v) |
|
207
|
|
|
ncf.close() |
|
208
|
|
|
|
st-bender /
sciapy
