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ncepgrib2.py
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__version__ = '2.0.3'
import g2clib
import struct
import string
import math
import functools
import warnings
import operator
from datetime import datetime
try:
from StringIO import StringIO
except ImportError:
from io import BytesIO as StringIO
import numpy as np
from numpy import ma
try:
import pyproj
except ImportError:
try:
from mpl_toolkits.basemap import pyproj
except:
raise ImportError("either pyproj or basemap required")
# Code Table 3.2: Shape of the Earth.
_earthparams={0:6367470.0,
1:'Spherical - radius specified in m by data producer',
2:(6378160.0,6356775.0),
3:'OblateSpheroid - major and minor axes specified in km by data producer',
4:(6378137.0,6356752.314),
5:'WGS84',
6:6371229.0,
7:'OblateSpheroid - major and minor axes specified in m by data producer',
8:6371200.0,
255:'Missing'}
for _n in range(192):
if not _n in _earthparams: _earthparams[_n]='Reserved'
for _n in range(192,255):
_earthparams[_n] = 'Reserved for local use'
_table0={1:('Melbourne (WMC)','ammc'),
2:('Melbourne - BMRC (WMC)',None),
3:('Melbourne (WMC)',None),
4:('Moscow (WMC)',None),
5:('Moscow (WMC)',None),
6:('Moscow (WMC)',None),
7:('US National Weather Service - NCEP (WMC)','kwbc'),
8:('US National Weather Service - NWSTG (WMC)',None),
9:('US National Weather Service - Other (WMC)',None),
10:('Cairo (RSMC/RAFC)',None),
11:('Cairo (RSMC/RAFC)',None),
12:('Dakar (RSMC/RAFC)',None),
13:('Dakar (RSMC/RAFC)',None),
14:('Nairobi (RSMC/RAFC)',None),
15:('Nairobi (RSMC/RAFC)',None),
16:('Casablanca',None),
17:('Tunis (RSMC)',None),
18:('Tunis-Casablanca (RSMC)',None),
19:('Tunis-Casablanca (RSMC)',None),
20:('Las Palmas (RAFC)',None),
21:('Algiers (RSMC)',None),
22:('ACMAD',None),
23:('Mozambique (NMC)',None),
24:('Pretoria (RSMC)',None),
25:('La Reunion (RSMC)',None),
26:('Khabarovsk (RSMC)',None),
27:('Khabarovsk (RSMC)',None),
28:('New Delhi (RSMC/RAFC)',None),
29:('New Delhi (RSMC/RAFC)',None),
30:('Novosibirsk (RSMC)',None),
31:('Novosibirsk (RSMC)',None),
32:('Tashkent (RSMC)',None),
33:('Jeddah (RSMC)',None),
34:('Japanese Meteorological Agency - Tokyo (RSMC)','rjtd'),
35:('Japanese Meteorological Agency - Tokyo (RSMC)',None),
36:('Bankok',None),
37:('Ulan Bator',None),
38:('Beijing (RSMC)','babj'),
39:('Beijing (RSMC)',None),
40:('Korean Meteorological Administration - Seoul','rksl'),
41:('Buenos Aires (RSMC/RAFC)',None),
42:('Buenos Aires (RSMC/RAFC)',None),
43:('Brasilia (RSMC/RAFC)',None),
44:('Brasilia (RSMC/RAFC)',None),
45:('Santiago',None),
46:('Brazilian Space Agency - INPE','sbsj'),
47:('Columbia (NMC)',None),
48:('Ecuador (NMC)',None),
49:('Peru (NMC)',None),
50:('Venezuela (NMC)',None),
51:('Miami (RSMC/RAFC)',None),
52:('Tropical Prediction Center (NHC), Miami (RSMC)',None),
53:('Canadian Meteorological Service - Montreal (RSMC)',None),
54:('Canadian Meteorological Service - Montreal (RSMC)','cwao'),
55:('San Francisco',None),
56:('ARINC Center',None),
57:('U.S. Air Force - Global Weather Center',None),
58:('US Navy - Fleet Numerical Oceanography Center','fnmo'),
59:('NOAA Forecast Systems Lab, Boulder CO',None),
60:('National Center for Atmospheric Research (NCAR), Boulder, CO',None),
61:('Service ARGOS - Landover, MD, USA',None),
62:('US Naval Oceanographic Office',None),
63:('Reserved',None),
64:('Honolulu',None),
65:('Darwin (RSMC)',None),
66:('Darwin (RSMC)',None),
67:('Melbourne (RSMC)',None),
68:('Reserved',None),
69:('Wellington (RSMC/RAFC)',None),
70:('Wellington (RSMC/RAFC)',None),
71:('Nadi (RSMC)',None),
72:('Singapore',None),
73:('Malaysia (NMC)',None),
74:('U.K. Met Office - Exeter (RSMC)','egrr'),
75:('U.K. Met Office - Exeter (RSMC)',None),
76:('Moscow (RSMC/RAFC)',None),
77:('Reserved',None),
78:('Offenbach (RSMC)','edzw'),
79:('Offenbach (RSMC)',None),
80:('Rome (RSMC)','cnmc'),
81:('Rome (RSMC)',None),
82:('Norrkoping',None),
83:('Norrkoping',None),
84:('French Weather Service - Toulouse','lfpw'),
85:('French Weather Service - Toulouse','lfpw'),
86:('Helsinki',None),
87:('Belgrade',None),
88:('Oslo',None),
89:('Prague',None),
90:('Episkopi',None),
91:('Ankara',None),
92:('Frankfurt/Main (RAFC)',None),
93:('London (WAFC)',None),
94:('Copenhagen',None),
95:('Rota',None),
96:('Athens',None),
97:('European Space Agency (ESA)',None),
98:('European Center for Medium-Range Weather Forecasts (RSMC)','ecmf'),
99:('De BiltNone), Netherlands',None),
100:('Brazzaville',None),
101:('Abidjan',None),
102:('Libyan Arab Jamahiriya (NMC)',None),
103:('Madagascar (NMC)',None),
104:('Mauritius (NMC)',None),
105:('Niger (NMC)',None),
106:('Seychelles (NMC)',None),
107:('Uganda (NMC)',None),
108:('Tanzania (NMC)',None),
109:('Zimbabwe (NMC)',None),
110:('Hong-Kong',None),
111:('Afghanistan (NMC)',None),
112:('Bahrain (NMC)',None),
113:('Bangladesh (NMC)',None),
114:('Bhutan (NMC)',None),
115:('Cambodia (NMC)',None),
116:("Democratic People's Republic of Korea (NMC)",None),
117:('Islamic Republic of Iran (NMC)',None),
118:('Iraq (NMC)',None),
119:('Kazakhstan (NMC)',None),
120:('Kuwait (NMC)',None),
121:('Kyrgyz Republic (NMC)',None),
122:("Lao People's Democratic Republic (NMC)",None),
123:('MacaoNone), China',None),
124:('Maldives (NMC)',None),
125:('Myanmar (NMC)',None),
126:('Nepal (NMC)',None),
127:('Oman (NMC)',None),
128:('Pakistan (NMC)',None),
129:('Qatar (NMC)',None),
130:('Republic of Yemen (NMC)',None),
131:('Sri Lanka (NMC)',None),
132:('Tajikistan (NMC)',None),
133:('Turkmenistan (NMC)',None),
134:('United Arab Emirates (NMC)',None),
135:('Uzbekistan (NMC)',None),
136:('Socialist Republic of Viet Nam (NMC)',None),
137:('Reserved',None),
138:('Reserved',None),
139:('Reserved',None),
140:('Bolivia (NMC)',None),
141:('Guyana (NMC)',None),
142:('Paraguay (NMC)',None),
143:('Suriname (NMC)',None),
144:('Uruguay (NMC)',None),
145:('French Guyana',None),
146:('Brazilian Navy Hydrographic Center',None),
147:('Reserved',None),
148:('Reserved',None),
149:('Reserved',None),
150:('Antigua and Barbuda (NMC)',None),
151:('Bahamas (NMC)',None),
152:('Barbados (NMC)',None),
153:('Belize (NMC)',None),
154:('British Caribbean Territories Center',None),
155:('San Jose',None),
156:('Cuba (NMC)',None),
157:('Dominica (NMC)',None),
158:('Dominican Republic (NMC)',None),
159:('El Salvador (NMC)',None),
160:('US NOAA/NESDIS',None),
161:('US NOAA Office of Oceanic and Atmospheric Research',None),
162:('Guatemala (NMC)',None),
163:('Haiti (NMC)',None),
164:('Honduras (NMC)',None),
165:('Jamaica (NMC)',None),
166:('Mexico',None),
167:('Netherlands Antilles and Aruba (NMC)',None),
168:('Nicaragua (NMC)',None),
169:('Panama (NMC)',None),
170:('Saint Lucia (NMC)',None),
171:('Trinidad and Tobago (NMC)',None),
172:('French Departments',None),
173:('Reserved',None),
174:('Reserved',None),
175:('Reserved',None),
176:('Reserved',None),
177:('Reserved',None),
178:('Reserved',None),
179:('Reserved',None),
180:('Reserved',None),
181:('Reserved',None),
182:('Reserved',None),
183:('Reserved',None),
184:('Reserved',None),
185:('Reserved',None),
186:('Reserved',None),
187:('Reserved',None),
188:('Reserved',None),
189:('Reserved',None),
190:('Cook Islands (NMC)',None),
191:('French Polynesia (NMC)',None),
192:('Tonga (NMC)',None),
193:('Vanuatu (NMC)',None),
194:('Brunei (NMC)',None),
195:('Indonesia (NMC)',None),
196:('Kiribati (NMC)',None),
197:('Federated States of Micronesia (NMC)',None),
198:('New Caledonia (NMC)',None),
199:('Niue',None),
200:('Papua New Guinea (NMC)',None),
201:('Philippines (NMC)',None),
202:('Samoa (NMC)',None),
203:('Solomon Islands (NMC)',None),
204:('Reserved',None),
205:('Reserved',None),
206:('Reserved',None),
207:('Reserved',None),
208:('Reserved',None),
209:('Reserved',None),
210:('Frascati',None),
211:('Lanion',None),
212:('Lisboa',None),
213:('Reykjavik',None),
214:('Madrid','lemm'),
215:('Zurich',None),
216:('Service ARGOS - ToulouseNone), FR',None),
217:('Bratislava',None),
218:('Budapest',None),
219:('Ljubljana',None),
220:('Warsaw',None),
221:('Zagreb',None),
222:('Albania (NMC)',None),
223:('Armenia (NMC)',None),
224:('Austria (NMC)',None),
225:('Azerbaijan (NMC)',None),
226:('Belarus (NMC)',None),
227:('Belgium (NMC)',None),
228:('Bosnia and Herzegovina (NMC)',None),
229:('Bulgaria (NMC)',None),
230:('Cyprus (NMC)',None),
231:('Estonia (NMC)',None),
232:('Georgia (NMC)',None),
233:('Dublin',None),
234:('Israel (NMC)',None),
235:('Jordan (NMC)',None),
236:('Latvia (NMC)',None),
237:('Lebanon (NMC)',None),
238:('Lithuania (NMC)',None),
239:('Luxembourg',None),
240:('Malta (NMC)',None),
241:('Monaco',None),
242:('Romania (NMC)',None),
243:('Syrian Arab Republic (NMC)',None),
244:('The former Yugoslav Republic of Macedonia (NMC)',None),
245:('Ukraine (NMC)',None),
246:('Republic of Moldova',None),
247:('Reserved',None),
248:('Reserved',None),
249:('Reserved',None),
250:('Reserved',None),
251:('Reserved',None),
252:('Reserved',None),
253:('Reserved',None),
254:('EUMETSAT Operations Center',None),
255:('Missing Value',None)}
def _dec2bin(val, maxbits = 8):
"""
A decimal to binary converter. Returns bits in a list.
"""
retval = []
for i in range(maxbits - 1, -1, -1):
bit = int(val / (2 ** i))
val = (val % (2 ** i))
retval.append(bit)
return retval
def _putieeeint(r):
"""convert a float to a IEEE format 32 bit integer"""
ra = np.array([r],'f')
ia = np.empty(1,'i')
g2clib.rtoi_ieee(ra,ia)
return ia[0]
def _getieeeint(i):
"""convert an IEEE format 32 bit integer to a float"""
ia = np.array([i],'i')
ra = np.empty(1,'f')
g2clib.itor_ieee(ia,ra)
return ra[0]
def _isString(string):
"""Test if string is a string like object if not return 0 """
try: string + ''
except: return 0
else: return 1
class Grib2Message:
"""
Class for accessing data in a GRIB Edition 2 message.
The L{Grib2Decode} function returns a list of these class instances,
one for each grib message in the file.
When a class instance is created, metadata in the GRIB2 file
is decoded and used to set various instance variables.
@ivar bitmap_indicator_flag: flag to indicate whether a bit-map is used (0 for yes, 255 for no).
@ivar data_representation_template: data representation template from section 5.
@ivar data_representation_template_number: data representation template number
from section 5
(U{Table 5.0
<http://www.nco.ncep.noaa.gov/pmb/docs/grib2/grib2_table5-0.shtml>})
@ivar has_local_use_section: True if grib message contains a local use
section. If True the actual local use section is contained in the
C{_local_use_section} instance variable, as a raw byte string.
@ivar discipline_code: product discipline code for grib message
(U{Table 0.0
<http://www.nco.ncep.noaa.gov/pmb/docs/grib2/grib2_table0-0.shtml>}).
@ivar earthRmajor: major (equatorial) earth radius.
@ivar earthRminor: minor (polar) earth radius.
@ivar grid_definition_info: grid definition section information from section 3.
See L{Grib2Encode.addgrid} for details.
@ivar grid_definition_template: grid definition template from section 3.
@ivar grid_definition_template_number: grid definition template number from section 3
(U{Table 3.1
<http://www.nco.ncep.noaa.gov/pmb/docs/grib2/grib2_table3-1.shtml>}).
@ivar gridlength_in_x_direction: x (or longitudinal) direction grid length.
@ivar gridlength_in_y_direction: y (or latitudinal) direction grid length.
@ivar identification_section: data from identification section (section 1).
See L{Grib2Encode.__init__} for details.
@ivar latitude_first_gridpoint: latitude of first grid point on grid.
@ivar latitude_last_gridpoint: latitude of last grid point on grid.
@ivar longitude_first_gridpoint: longitude of first grid point on grid.
@ivar longitude_last_gridpoint: longitude of last grid point on grid.
@ivar originating_center: name of national/international originating center.
@ivar center_wmo_code: 4 character wmo code for originating center.
@ivar scanmodeflags: scanning mode flags from Table 3.4
(U{Table 3.4
<http://www.nco.ncep.noaa.gov/pmb/docs/grib2/grib2_table3-4.shtml>}).
- bit 1:
0 - Points in the first row or column scan in the +i (+x) direction
1 - Points in the first row or column scan in the -i (-x) direction
- bit 2:
0 - Points in the first row or column scan in the -j (-y) direction
1 - Points in the first row or column scan in the +j (+y) direction
- bit 3:
0 - Adjacent points in the i (x) direction are consecutive (row-major order).
1 - Adjacent points in the j (y) direction are consecutive (column-major order).
- bit 4:
0 - All rows scan in the same direction
1 - Adjacent rows scan in the opposite direction
@ivar number_of_data_points_to_unpack: total number of data points in grib message.
@ivar points_in_x_direction: number of points in the x (longitudinal) direction.
@ivar points_in_y_direction: number of points in the y (latitudinal) direction.
@ivar product_definition_template: product definition template from section 4.
@ivar product_definition_template_number: product definition template number from section 4
(U{Table 4.0
<http://www.nco.ncep.noaa.gov/pmb/docs/grib2/grib2_table4-0.shtml>}).
@ivar shape_of_earth: string describing the shape of the earth (e.g. 'Oblate Spheroid', 'Spheroid').
@ivar spectral_truncation_parameters: pentagonal truncation parameters that describe the
spherical harmonic truncation (only relevant for grid_definition_template_numbers 50-52).
For triangular truncation, all three of these numbers are the same.
@ivar latitude_of_southern_pole: the geographic latitude in degrees of the southern
pole of the coordinate system (for rotated lat/lon or gaussian grids).
@ivar longitude_of_southern_pole: the geographic longitude in degrees of the southern
pole of the coordinate system (for rotated lat/lon or gaussian grids).
@ivar angle_of_pole_rotation: The angle of rotation in degrees about the new
polar axis (measured clockwise when looking from the southern to the northern pole)
of the coordinate system. For rotated lat/lon or gaussian grids.
@ivar missing_value: primary missing value (for data_representation_template_numbers
2 and 3).
@ivar missing_value2: secondary missing value (for data_representation_template_numbers
2 and 3).
@ivar proj4_: instance variables with this prefix are used to set the map projection
parameters for U{PROJ.4<http://proj.maptools.org>}.
"""
def __init__(self,**kwargs):
"""
create a Grib2Decode class instance given a GRIB Edition 2 filename.
(used by L{Grib2Decode} function - not directly called by user)
"""
for k,v in kwargs.items():
setattr(self,k,v)
# grid information
gdsinfo = self.grid_definition_info
gdtnum = self.grid_definition_template_number
gdtmpl = self.grid_definition_template
reggrid = gdsinfo[2] == 0 # gdsinfo[2]=0 means regular 2-d grid
# shape of the earth.
if gdtnum not in [50,51,52,1200]:
earthR = _earthparams[gdtmpl[0]]
if earthR == 'Reserved': earthR = None
else:
earthR = None
if _isString(earthR) and (earthR.startswith('Reserved') or earthR=='Missing'):
self.shape_of_earth = earthR
self.earthRminor = None
self.earthRmajor = None
elif _isString(earthR) and earthR.startswith('Spherical'):
self.shape_of_earth = earthR
scaledearthR = gdtmpl[2]
earthRscale = gdtmpl[1]
self.earthRmajor = math.pow(10,-earthRscale)*scaledearthR
self.earthRminor = self.earthRmajor
elif _isString(earthR) and earthR.startswith('OblateSpheroid'):
self.shape_of_earth = earthR
scaledearthRmajor = gdtmpl[4]
earthRmajorscale = gdtmpl[3]
self.earthRmajor = math.pow(10,-earthRmajorscale)*scaledearthRmajor
self.earthRmajor = self.earthRmajor*1000. # convert to m from km
scaledearthRminor = gdtmpl[6]
earthRminorscale = gdtmpl[5]
self.earthRminor = math.pow(10,-earthRminorscale)*scaledearthRminor
self.earthRminor = self.earthRminor*1000. # convert to m from km
elif _isString(earthR) and earthR.startswith('WGS84'):
self.shape_of_earth = earthR
self.earthRmajor = 6378137.0
self.earthRminor = 6356752.3142
elif isinstance(earthR,tuple):
self.shape_of_earth = 'OblateSpheroid'
self.earthRmajor = earthR[0]
self.earthRminor = earthR[1]
else:
if earthR is not None:
self.shape_of_earth = 'Spherical'
self.earthRmajor = earthR
self.earthRminor = self.earthRmajor
if reggrid and gdtnum not in [50,51,52,53,100,120,1000,1200]:
self.points_in_x_direction = gdtmpl[7]
self.points_in_y_direction = gdtmpl[8]
if not reggrid and gdtnum == 40: # 'reduced' gaussian grid.
self.points_in_y_direction = gdtmpl[8]
if gdtnum in [0,1,203,205,32768,32769]: # regular or rotated lat/lon grid
scalefact = float(gdtmpl[9])
divisor = float(gdtmpl[10])
if scalefact == 0: scalefact = 1.
if divisor <= 0: divisor = 1.e6
self.latitude_first_gridpoint = scalefact*gdtmpl[11]/divisor
self.longitude_first_gridpoint = scalefact*gdtmpl[12]/divisor
self.latitude_last_gridpoint = scalefact*gdtmpl[14]/divisor
self.longitude_last_gridpoint = scalefact*gdtmpl[15]/divisor
self.gridlength_in_x_direction = scalefact*gdtmpl[16]/divisor
self.gridlength_in_y_direction = scalefact*gdtmpl[17]/divisor
if self.latitude_first_gridpoint > self.latitude_last_gridpoint:
self.gridlength_in_y_direction = -self.gridlength_in_y_direction
if self.longitude_first_gridpoint > self.longitude_last_gridpoint:
self.gridlength_in_x_direction = -self.gridlength_in_x_direction
self.scanmodeflags = _dec2bin(gdtmpl[18])[0:4]
if gdtnum == 1:
self.latitude_of_southern_pole = scalefact*gdtmpl[19]/divisor
self.longitude_of_southern_pole = scalefact*gdtmpl[20]/divisor
self.angle_of_pole_rotation = gdtmpl[21]
elif gdtnum == 10: # mercator
self.latitude_first_gridpoint = gdtmpl[9]/1.e6
self.longitude_first_gridpoint = gdtmpl[10]/1.e6
self.latitude_last_gridpoint = gdtmpl[13]/1.e6
self.longitude_last_gridpoint = gdtmpl[14]/1.e6
self.gridlength_in_x_direction = gdtmpl[17]/1.e3
self.gridlength_in_y_direction= gdtmpl[18]/1.e3
self.proj4_lat_ts = gdtmpl[12]/1.e6
self.proj4_lon_0 = 0.5*(self.longitude_first_gridpoint+self.longitude_last_gridpoint)
self.proj4_proj = 'merc'
self.scanmodeflags = _dec2bin(gdtmpl[15])[0:4]
elif gdtnum == 20: # stereographic
projflag = _dec2bin(gdtmpl[16])[0]
self.latitude_first_gridpoint = gdtmpl[9]/1.e6
self.longitude_first_gridpoint = gdtmpl[10]/1.e6
self.proj4_lat_ts = gdtmpl[12]/1.e6
if projflag == 0:
self.proj4_lat_0 = 90
elif projflag == 1:
self.proj4_lat_0 = -90
else:
raise ValueError('Invalid projection center flag = %s'%projflag)
self.proj4_lon_0 = gdtmpl[13]/1.e6
self.gridlength_in_x_direction = gdtmpl[14]/1000.
self.gridlength_in_y_direction = gdtmpl[15]/1000.
self.proj4_proj = 'stere'
self.scanmodeflags = _dec2bin(gdtmpl[17])[0:4]
elif gdtnum == 30: # lambert conformal
self.latitude_first_gridpoint = gdtmpl[9]/1.e6
self.longitude_first_gridpoint = gdtmpl[10]/1.e6
self.gridlength_in_x_direction = gdtmpl[14]/1000.
self.gridlength_in_y_direction = gdtmpl[15]/1000.
self.proj4_lat_1 = gdtmpl[18]/1.e6
self.proj4_lat_2 = gdtmpl[19]/1.e6
self.proj4_lat_0 = gdtmpl[12]/1.e6
self.proj4_lon_0 = gdtmpl[13]/1.e6
self.proj4_proj = 'lcc'
self.scanmodeflags = _dec2bin(gdtmpl[17])[0:4]
elif gdtnum == 31: # albers equal area.
self.latitude_first_gridpoint = gdtmpl[9]/1.e6
self.longitude_first_gridpoint = gdtmpl[10]/1.e6
self.gridlength_in_x_direction = gdtmpl[14]/1000.
self.gridlength_in_y_direction = gdtmpl[15]/1000.
self.proj4_lat_1 = gdtmpl[18]/1.e6
self.proj4_lat_2 = gdtmpl[19]/1.e6
self.proj4_lat_0 = gdtmpl[12]/1.e6
self.proj4_lon_0 = gdtmpl[13]/1.e6
self.proj4_proj = 'aea'
self.scanmodeflags = _dec2bin(gdtmpl[17])[0:4]
elif gdtnum == 40 or gdtnum == 41: # gaussian grid.
scalefact = float(gdtmpl[9])
divisor = float(gdtmpl[10])
if scalefact == 0: scalefact = 1.
if divisor <= 0: divisor = 1.e6
self.points_between_pole_and_equator = gdtmpl[17]
self.latitude_first_gridpoint = scalefact*gdtmpl[11]/divisor
self.longitude_first_gridpoint = scalefact*gdtmpl[12]/divisor
self.latitude_last_gridpoint = scalefact*gdtmpl[14]/divisor
self.longitude_last_gridpoint = scalefact*gdtmpl[15]/divisor
if reggrid:
self.gridlength_in_x_direction = scalefact*gdtmpl[16]/divisor
if self.longitude_first_gridpoint > self.longitude_last_gridpoint:
self.gridlength_in_x_direction = -self.gridlength_in_x_direction
self.scanmodeflags = _dec2bin(gdtmpl[18])[0:4]
if gdtnum == 41:
self.latitude_of_southern_pole = scalefact*gdtmpl[19]/divisor
self.longitude_of_southern_pole = scalefact*gdtmpl[20]/divisor
self.angle_of_pole_rotation = gdtmpl[21]
elif gdtnum == 50: # spectral coefficients.
self.spectral_truncation_parameters = (gdtmpl[0],gdtmpl[1],gdtmpl[2])
self.scanmodeflags = [None,None,None,None] # doesn't apply
elif gdtnum == 90: # near-sided vertical perspective satellite projection
self.proj4_lat_0 = gdtmpl[9]/1.e6
self.proj4_lon_0 = gdtmpl[10]/1.e6
self.proj4_h = self.earthRmajor * (gdtmpl[18]/1.e6)
dx = gdtmpl[12]
dy = gdtmpl[13]
# if lat_0 is equator, it's a geostationary view.
if self.proj4_lat_0 == 0.: # if lat_0 is equator, it's a
self.proj4_proj = 'geos'
# general case of 'near-side perspective projection' (untested)
else:
self.proj4_proj = 'nsper'
msg = """
only geostationary perspective is supported.
lat/lon values returned by grid method may be incorrect."""
warnings.warn(msg)
# latitude of horizon on central meridian
lonmax = 90.-(180./np.pi)*np.arcsin(self.earthRmajor/self.proj4_h)
# longitude of horizon on equator
latmax = 90.-(180./np.pi)*np.arcsin(self.earthRminor/self.proj4_h)
# truncate to nearest thousandth of a degree (to make sure
# they aren't slightly over the horizon)
latmax = int(1000*latmax)/1000.
lonmax = int(1000*lonmax)/1000.
# h is measured from surface of earth at equator.
self.proj4_h = self.proj4_h - self.earthRmajor
# width and height of visible projection
P = pyproj.Proj(proj=self.proj4_proj,\
a=self.earthRmajor,b=self.earthRminor,\
lat_0=0,lon_0=0,h=self.proj4_h)
x1,y1 = P(0.,latmax); x2,y2 = P(lonmax,0.)
width = 2*x2; height = 2*y1
self.gridlength_in_x_direction = width/dx
self.gridlength_in_y_direction = height/dy
self.scanmodeflags = _dec2bin(gdtmpl[16])[0:4]
elif gdtnum == 110: # azimuthal equidistant.
self.proj4_lat_0 = gdtmpl[9]/1.e6
self.proj4_lon_0 = gdtmpl[10]/1.e6
self.gridlength_in_x_direction = gdtmpl[12]/1000.
self.gridlength_in_y_direction = gdtmpl[13]/1000.
self.proj4_proj = 'aeqd'
self.scanmodeflags = _dec2bin(gdtmpl[15])[0:4]
elif gdtnum == 204: # curvilinear orthogonal
self.scanmodeflags = _dec2bin(gdtmpl[18])[0:4]
# missing value.
drtnum = self.data_representation_template_number
drtmpl = self.data_representation_template
if (drtnum == 2 or drtnum == 3) and drtmpl[6] != 0:
self.missing_value = _getieeeint(drtmpl[7])
if drtmpl[6] == 2:
self.missing_value2 = _getieeeint(drtmpl[8])
def __repr__(self):
strings = []
# python 3 keys() is an iterator that can't be sorted
keys = list(self.__dict__.keys())
keys.sort()
for k in keys:
if not k.startswith('_'):
strings.append('%s = %s\n'%(k,self.__dict__[k]))
return ''.join(strings)
def data(self,fill_value=9.9692099683868690e+36,masked_array=True,expand=True,order=None):
"""
returns an unpacked data grid. Can also be accomplished with L{values}
property.
@keyword fill_value: missing or masked data is filled with this value
(default 9.9692099683868690e+36).
@keyword masked_array: if True, return masked array if there is bitmap
for missing or masked data (default True).
@keyword expand: if True (default), ECMWF 'reduced' gaussian grids are
expanded to regular gaussian grids.
@keyword order: if 1, linear interpolation is used for expanding reduced
gaussian grids. if 0, nearest neighbor interpolation is used. Default
is 0 if grid has missing or bitmapped values, 1 otherwise.
@return: C{B{data}}, a float32 numpy regular or masked array
with shape (nlats,lons) containing the requested grid.
"""
# make sure scan mode is supported.
# if there is no 'scanmodeflags', then grid is not supported.
from redtoreg import _redtoreg
if not hasattr(self,'scanmodeflags'):
raise ValueError('unsupported grid definition template number %s'%self.grid_definition_template_number)
else:
if self.scanmodeflags[2]:
storageorder='F'
else:
storageorder='C'
bitmapflag = self.bitmap_indicator_flag
drtnum = self.data_representation_template_number
drtmpl = self.data_representation_template
# default order=0 is missing values or bitmap exists.
if order is None:
if ((drtnum == 3 or drtnum == 2) and drtmpl[6] != 0) or bitmapflag == 0:
order = 0
else:
order = 1
try:
f = open(self._grib_filename,'rb')
# self._grib_filename can be a grib message binary string
# if it is, ValueError is returned in python 3.5 (issue #24)
except (ValueError,TypeError,IOError):
f = StringIO(self._grib_filename)
f.seek(self._grib_message_byteoffset)
gribmsg = f.read(self._grib_message_length)
f.close()
gdtnum = self.grid_definition_template_number
gdtmpl = self.grid_definition_template
ndpts = self.number_of_data_points_to_unpack
gdsinfo = self.grid_definition_info
ngrdpts = gdsinfo[1]
ipos = self._section7_byte_offset
fld1=g2clib.unpack7(gribmsg,gdtnum,gdtmpl,drtnum,drtmpl,ndpts,ipos,np.empty,storageorder=storageorder)
# apply bitmap.
if bitmapflag == 0:
bitmap=self._bitmap
fld = fill_value*np.ones(ngrdpts,'f')
np.put(fld,np.nonzero(bitmap),fld1)
if masked_array:
fld = ma.masked_values(fld,fill_value)
# missing values instead of bitmap
elif masked_array and hasattr(self,'missing_value'):
if hasattr(self, 'missing_value2'):
mask = np.logical_or(fld1 == self.missing_value, fld1 == self.missing_value2)
else:
mask = fld1 == self.missing_value
fld = ma.array(fld1,mask=mask)
else:
fld = fld1
nx = None; ny = None
if hasattr(self,'points_in_x_direction'):
nx = self.points_in_x_direction
if hasattr(self,'points_in_y_direction'):
ny = self.points_in_y_direction
if nx is not None and ny is not None: # rectangular grid.
if ma.isMA(fld):
fld = ma.reshape(fld,(ny,nx))
else:
fld = np.reshape(fld,(ny,nx))
else:
if gdsinfo[2] and gdtnum == 40: # ECMWF 'reduced' global gaussian grid.
if expand:
nx = 2*ny
lonsperlat = self.grid_definition_list
if ma.isMA(fld):
fld = ma.filled(fld)
fld = _redtoreg(nx, lonsperlat.astype(np.long),\
fld.astype(np.double), fill_value)
fld = ma.masked_values(fld,fill_value)
else:
fld = _redtoreg(nx, lonsperlat.astype(np.long),\
fld.astype(np.double), fill_value)
# check scan modes for rect grids.
if nx is not None and ny is not None:
# rows scan in the -x direction (so flip)
#if self.scanmodeflags[0]:
# fldsave = fld.astype('f') # casting makes a copy
# fld[:,:] = fldsave[:,::-1]
# columns scan in the -y direction (so flip)
#if not self.scanmodeflags[1]:
# fldsave = fld.astype('f') # casting makes a copy
# fld[:,:] = fldsave[::-1,:]
# adjacent rows scan in opposite direction.
# (flip every other row)
if self.scanmodeflags[3]:
fldsave = fld.astype('f') # casting makes a copy
fld[1::2,:] = fldsave[1::2,::-1]
return fld
values = property(data)
def latlons(self):
"""alias for L{grid}"""
return self.grid()
def grid(self):
"""
return lats,lons (in degrees) of grid.
currently can handle reg. lat/lon, global gaussian, mercator, stereographic,
lambert conformal, albers equal-area, space-view and azimuthal
equidistant grids. L{latlons} method does the same thing.
@return: C{B{lats},B{lons}}, float32 numpy arrays
containing latitudes and longitudes of grid (in degrees).
"""
gdsinfo = self.grid_definition_info
gdtnum = self.grid_definition_template_number
gdtmpl = self.grid_definition_template
reggrid = gdsinfo[2] == 0 # gdsinfo[2]=0 means regular 2-d grid
projparams = {}
projparams['a']=self.earthRmajor
projparams['b']=self.earthRminor
if gdtnum == 0: # regular lat/lon grid
lon1, lat1 = self.longitude_first_gridpoint, self.latitude_first_gridpoint
lon2, lat2 = self.longitude_last_gridpoint, self.latitude_last_gridpoint
delon = self.gridlength_in_x_direction
delat = self.gridlength_in_y_direction
lats = np.arange(lat1,lat2+delat,delat)
lons = np.arange(lon1,lon2+delon,delon)
# flip if scan mode says to.
#if self.scanmodeflags[0]:
# lons = lons[::-1]
#if not self.scanmodeflags[1]:
# lats = lats[::-1]
projparams['proj'] = 'cyl'
lons,lats = np.meshgrid(lons,lats) # make 2-d arrays.
elif gdtnum == 40: # gaussian grid (only works for global!)
try:
from pygrib import gaulats
except:
raise ImportError("pygrib required to compute Gaussian lats/lons")
lon1, lat1 = self.longitude_first_gridpoint, self.latitude_first_gridpoint
lon2, lat2 = self.longitude_last_gridpoint, self.latitude_last_gridpoint
nlats = self.points_in_y_direction
if not reggrid: # ECMWF 'reduced' gaussian grid.
nlons = 2*nlats
delon = 360./nlons
else:
nlons = self.points_in_x_direction
delon = self.gridlength_in_x_direction
lons = np.arange(lon1,lon2+delon,delon)
# compute gaussian lats (north to south)
lats = gaulats(nlats)
if lat1 < lat2: # reverse them if necessary
lats = lats[::-1]
# flip if scan mode says to.
#if self.scanmodeflags[0]:
# lons = lons[::-1]
#if not self.scanmodeflags[1]:
# lats = lats[::-1]
projparams['proj'] = 'cyl'
lons,lats = np.meshgrid(lons,lats) # make 2-d arrays
# mercator, lambert conformal, stereographic, albers equal area, azimuthal equidistant
elif gdtnum in [10,20,30,31,110]:
nx = self.points_in_x_direction
ny = self.points_in_y_direction
dx = self.gridlength_in_x_direction
dy = self.gridlength_in_y_direction
lon1, lat1 = self.longitude_first_gridpoint, self.latitude_first_gridpoint
if gdtnum == 10: # mercator.
projparams['lat_ts']=self.proj4_lat_ts
projparams['proj']=self.proj4_proj
projparams['lon_0']=self.proj4_lon_0
pj = pyproj.Proj(projparams)
llcrnrx, llcrnry = pj(lon1,lat1)
x = llcrnrx+dx*np.arange(nx)
y = llcrnry+dy*np.arange(ny)
x, y = np.meshgrid(x, y)
lons, lats = pj(x, y, inverse=True)
elif gdtnum == 20: # stereographic
projparams['lat_ts']=self.proj4_lat_ts
projparams['proj']=self.proj4_proj
projparams['lat_0']=self.proj4_lat_0
projparams['lon_0']=self.proj4_lon_0
pj = pyproj.Proj(projparams)
llcrnrx, llcrnry = pj(lon1,lat1)
x = llcrnrx+dx*np.arange(nx)
y = llcrnry+dy*np.arange(ny)
x, y = np.meshgrid(x, y)
lons, lats = pj(x, y, inverse=True)
elif gdtnum in [30,31]: # lambert, albers
projparams['lat_1']=self.proj4_lat_1
projparams['lat_2']=self.proj4_lat_2
projparams['proj']=self.proj4_proj
projparams['lon_0']=self.proj4_lon_0
pj = pyproj.Proj(projparams)
llcrnrx, llcrnry = pj(lon1,lat1)
x = llcrnrx+dx*np.arange(nx)
y = llcrnry+dy*np.arange(ny)
x, y = np.meshgrid(x, y)
lons, lats = pj(x, y, inverse=True)
elif gdtnum == 110: # azimuthal equidistant
projparams['proj']=self.proj4_proj
projparams['lat_0']=self.proj4_lat_0
projparams['lon_0']=self.proj4_lon_0
pj = pyproj.Proj(projparams)
llcrnrx, llcrnry = pj(lon1,lat1)
x = llcrnrx+dx*np.arange(nx)
y = llcrnry+dy*np.arange(ny)
x, y = np.meshgrid(x, y)
lons, lats = pj(x, y, inverse=True)
elif gdtnum == 90: # satellite projection.
nx = self.points_in_x_direction
ny = self.points_in_y_direction
dx = self.gridlength_in_x_direction
dy = self.gridlength_in_y_direction
projparams['proj']=self.proj4_proj
projparams['lon_0']=self.proj4_lon_0
projparams['lat_0']=self.proj4_lat_0
projparams['h']=self.proj4_h
pj = pyproj.Proj(projparams)
x = dx*np.indices((ny,nx),'f')[1,:,:]
x = x - 0.5*x.max()
y = dy*np.indices((ny,nx),'f')[0,:,:]
y = y - 0.5*y.max()
lons, lats = pj(x,y,inverse=True)
# set lons,lats to 1.e30 where undefined
abslons = np.fabs(lons); abslats = np.fabs(lats)
lons = np.where(abslons < 1.e20, lons, 1.e30)
lats = np.where(abslats < 1.e20, lats, 1.e30)
else:
raise ValueError('unsupported grid')
self.projparams = projparams
return lats.astype('f'), lons.astype('f')
def Grib2Decode(filename,gribmsg=False):
"""
Read the contents of a GRIB2 file.
@param filename: name of GRIB2 file (default, gribmsg=False) or binary string
representing a grib message (if gribmsg=True).
@return: a list of L{Grib2Message} instances representing all of the
grib messages in the file. Messages with multiple fields are split
into separate messages (so that each L{Grib2Message} instance contains
just one data field). The metadata in each GRIB2 message can be
accessed via L{Grib2Message} instance variables, the actual data
can be read using L{Grib2Message.data}, and the lat/lon values of the grid
can be accesses using L{Grib2Message.grid}. If there is only one grib
message, just the L{Grib2Message} instance is returned, instead of a list
with one element.
"""
if gribmsg:
f = StringIO(filename)
else:
f = open(filename,'rb')
nmsg = 0
# loop over grib messages, read section 0, get entire grib message.
disciplines = []
startingpos = []
msglen = []
while 1:
# find next occurence of string 'GRIB' (or EOF).
nbyte = f.tell()
while 1:
f.seek(nbyte)
start = f.read(4).decode('ascii','ignore')
if start == '' or start == 'GRIB': break
nbyte = nbyte + 1
if start == '': break # at EOF
# otherwise, start (='GRIB') contains indicator message (section 0)
startpos = f.tell()-4
f.seek(2,1) # next two octets are reserved
# get discipline info.
disciplines.append(struct.unpack('>B',f.read(1))[0])
# check to see it's a grib edition 2 file.
vers = struct.unpack('>B',f.read(1))[0]
if vers != 2:
raise IOError('not a GRIB2 file (version number %d)' % vers)
lengrib = struct.unpack('>q',f.read(8))[0]
msglen.append(lengrib)
startingpos.append(startpos)
# read in entire grib message.
f.seek(startpos)
gribmsg = f.read(lengrib)
# make sure the message ends with '7777'
end = gribmsg[-4:lengrib].decode('ascii','ignore')
if end != '7777':
raise IOError('partial GRIB message (no "7777" at end)')
# do next message.
nmsg=nmsg+1
# if no grib messages found, nmsg is still 0 and it's not GRIB.
if nmsg==0:
raise IOError('not a GRIB file')
# now for each grib message, find number of fields.
numfields = []
f.seek(0) # rewind file.
for n in range(nmsg):
f.seek(startingpos[n])
gribmsg = f.read(msglen[n])
pos = 0
numflds = 0
while 1:
if gribmsg[pos:pos+4].decode('ascii','ignore') == 'GRIB':
sectnum = 0
lensect = 16
elif gribmsg[pos:pos+4].decode('ascii','ignore') == '7777':
break
else:
lensect = struct.unpack('>i',gribmsg[pos:pos+4])[0]
sectnum = struct.unpack('>B',gribmsg[pos+4:pos+5])[0]
if sectnum == 4: numflds=numflds+1
#if sectnum == 2: numlocal=numlocal+1
pos = pos + lensect
#print sectnum,lensect,pos
#print n+1,len(gribmsg),numfields,numlocal
numfields.append(numflds)
# decode each section in grib message (sections 1 and above).
gdtnum = [] # grid defn template number from sxn 3
gdtmpl = [] # grid defn template from sxn 3
gdeflist = [] # optional grid definition list from sxn 3
gdsinfo = [] # grid definition section info from sxn3
pdtmpl = [] # product defn template from sxn 4
pdtnum = [] # product defn template number from sxn 4
coordlist = [] # vertical coordinate info from sxn 4
drtmpl = [] # data representation template from sxn 5
drtnum = [] # data representation template number from sxn 5
ndpts = [] # number of data points to be unpacked (from sxn 5)
bitmapflag = [] # bit-map indicator flag from sxn 6
bitmap = [] # bitmap from sxn 6.
pos7 = [] # byte offset for section 7.
localsxn = [] # local use sections.
msgstart = [] # byte offset in file for message start.
msglength = [] # length of the message in bytes.
message = [] # the actual grib message.
identsect = [] # identification section (section 1).
discipline = [] # discipline code.
for n in range(nmsg):
spos = startingpos[n]
lengrib = msglen[n]
#gribmsg = gribmsgs[n]
f.seek(spos)
gribmsg = f.read(lengrib)
discipl = disciplines[n]
lensect0 = 16
# get length of section 1 and section number.
#lensect1 = struct.unpack('>i',gribmsg[lensect0:lensect0+4])[0]
#sectnum1 = struct.unpack('>B',gribmsg[lensect0+4])[0]
#print 'sectnum1, lensect1 = ',sectnum1,lensect1
# unpack section 1, octets 1-21 (13 parameters). This section
# can occur only once per grib message.
#idsect,pos = _unpack1(gribmsg,lensect0) # python version
idsect,pos = g2clib.unpack1(gribmsg,lensect0,np.empty) # c version
# loop over rest of sections in message.
gdtnums = []
gdtmpls = []
gdeflists = []