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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2010, 2011, 2012.
# SMHI,
# Folkborgsvägen 1,
# Norrköping,
# Sweden
# Author(s):
# Martin Raspaud <martin.raspaud@smhi.se>
# Adam Dybbroe <adam.dybbroe@smhi.se>
# This file is part of mpop.
# mpop is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
# mpop is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE. See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with
# mpop. If not, see <http://www.gnu.org/licenses/>.
"""Very simple netcdf reader for mpop.
"""
# TODO
# - complete projection list and attribute list
# - handle other units than "m" for coordinates
# - handle units for data
# - pluginize
import warnings
from ConfigParser import NoSectionError
import numpy as np
from netCDF4 import Dataset, num2date
from mpop.instruments.visir import VisirCompositer
from mpop.satellites import GenericFactory
from mpop.satout.cfscene import TIME_UNITS
from mpop.utils import get_logger
LOG = get_logger("netcdf4/cf reader")
# To be complete, get from appendix F of cf conventions
MAPPING_ATTRIBUTES = {'grid_mapping_name': "proj",
'standard_parallel': ["lat_1", "lat_2"],
'latitude_of_projection_origin': "lat_0",
'longitude_of_projection_origin': "lon_0",
'longitude_of_central_meridian': "lon_0",
'perspective_point_height': "h",
'false_easting': "x_0",
'false_northing': "y_0",
'semi_major_axis': "a",
'semi_minor_axis': "b",
'inverse_flattening': "rf",
'ellipsoid': "ellps", # not in CF conventions...
}
# To be completed, get from appendix F of cf conventions
PROJNAME = {"vertical_perspective": "nsper",
"geostationary": "geos",
"albers_conical_equal_area": "aea",
"azimuthal_equidistant": "aeqd",
}
def _load02(filename):
"""Load data from a netcdf4 file, cf-satellite v0.2 (2012-02-03).
"""
rootgrp = Dataset(filename, 'r')
# processed variables
processed = set()
satellite_name, satellite_number = rootgrp.platform.rsplit("-", 1)
time_slot = rootgrp.variables["time"].getValue()[0]
time_slot = num2date(time_slot, TIME_UNITS)
processed |= set(["time"])
try:
service = str(rootgrp.service)
except AttributeError:
service = ""
instrument_name = str(rootgrp.instrument)
try:
orbit = str(rootgrp.orbit)
except AttributeError:
orbit = None
try:
scene = GenericFactory.create_scene(satellite_name,
satellite_number,
instrument_name,
time_slot,
orbit,
None,
service)
except NoSectionError:
scene = VisirCompositer(time_slot=time_slot)
scene.satname = satellite_name
scene.number = satellite_number
scene.service = service
dim_chart = {}
for var_name, var in rootgrp.variables.items():
varname = None
try:
varname = var.standard_name
except AttributeError:
try:
varname = var.long_name
except AttributeError:
pass
if varname in ["band_data", "Band data"]:
LOG.debug("Found some data: " + var_name)
dims = var.dimensions
for dim in dims:
dim_chart[dim] = var_name
for cnt, dim in enumerate(dims):
if dim.startswith("band"):
break
data = var
data.set_auto_maskandscale(False)
area = None
try:
area_var_name = getattr(var,"grid_mapping")
area_var = rootgrp.variables[area_var_name]
proj4_dict = {}
for attr, projattr in MAPPING_ATTRIBUTES.items():
try:
the_attr = getattr(area_var, attr)
if projattr == "proj":
proj4_dict[projattr] = PROJNAME[the_attr]
elif(isinstance(projattr, (list, tuple))):
try:
for i, subattr in enumerate(the_attr):
proj4_dict[projattr[i]] = subattr
except TypeError:
proj4_dict[projattr[0]] = the_attr
else:
proj4_dict[projattr] = the_attr
except AttributeError:
pass
y_name, x_name = dims[:cnt] + dims[cnt + 1:]
x__ = rootgrp.variables[x_name][:]
y__ = rootgrp.variables[y_name][:]
if proj4_dict["proj"] == "geos":
x__ *= proj4_dict["h"]
y__ *= proj4_dict["h"]
x_pixel_size = abs((np.diff(x__)).mean())
y_pixel_size = abs((np.diff(y__)).mean())
llx = x__[0] - x_pixel_size / 2.0
lly = y__[-1] - y_pixel_size / 2.0
urx = x__[-1] + x_pixel_size / 2.0
ury = y__[0] + y_pixel_size / 2.0
area_extent = (llx, lly, urx, ury)
try:
# create the pyresample areadef
from pyresample.geometry import AreaDefinition
area = AreaDefinition("myareaid", "myareaname",
"myprojid", proj4_dict,
len(x__), len(y__),
area_extent)
except ImportError:
LOG.warning("Pyresample not found, "
"cannot load area descrition")
processed |= set([area_var_name, x_name, y_name])
LOG.debug("Grid mapping found and used.")
except AttributeError:
LOG.debug("No grid mapping found.")
try:
area_var = getattr(var,"coordinates")
coordinates_vars = area_var.split(" ")
lons = None
lats = None
for coord_var_name in coordinates_vars:
coord_var = rootgrp.variables[coord_var_name]
units = getattr(coord_var, "units")
if(coord_var_name.lower().startswith("lon") or
units.lower().endswith("east") or
units.lower().endswith("west")):
lons = coord_var[:]
elif(coord_var_name.lower().startswith("lat") or
units.lower().endswith("north") or
units.lower().endswith("south")):
lats = coord_var[:]
if lons and lats:
try:
from pyresample.geometry import SwathDefinition
area = SwathDefinition(lons=lons, lats=lats)
except ImportError:
LOG.warning("Pyresample not found, "
"cannot load area descrition")
processed |= set(coordinates_vars)
LOG.debug("Lon/lat found and used.")
except AttributeError:
LOG.debug("No lon/lat found.")
names = rootgrp.variables[dim][:]
scales = data.scale_factor
offsets = data.add_offset
if len(names) == 1:
scales = np.array([scales])
offsets = np.array([offsets])
print scales, offsets
for nbr, name in enumerate(names):
try:
if cnt == 0:
chn_data = data[nbr, :, :].squeeze()
if cnt == 1:
chn_data = data[:, nbr, :].squeeze()
if cnt == 2:
chn_data = data[:, :, nbr].squeeze()
scene[name] = (np.ma.masked_equal(chn_data, data._FillValue)
* scales[nbr] + offsets[nbr])
scene[name].info["units"] = var.units
except KeyError:
from mpop.channel import Channel
scene.channels.append(Channel(name))
if area is not None:
scene[name].area = area
processed |= set([var_name, dim])
non_processed = set(rootgrp.variables.keys()) - processed
for var_name in non_processed:
var = rootgrp.variables[var_name]
if not (hasattr(var, "standard_name") or
hasattr(var, "long_name")):
LOG.info("Delayed processing of " + var_name)
continue
dims = var.dimensions
if len(dims) != 1:
LOG.info("Don't know what to do with " + var_name)
continue
dim = dims[0]
if var.standard_name == "radiation_wavelength":
names = rootgrp.variables[dim][:]
for nbr, name in enumerate(names):
scene[name].wavelength_range[1] = var[nbr]
try:
bnds = rootgrp.variables[var.bounds][:]
for nbr, name in enumerate(names):
scene[name].wavelength_range[0] = bnds[nbr, 0]
scene[name].wavelength_range[2] = bnds[nbr, 1]
processed |= set([var.bounds])
except AttributeError:
pass
processed |= set([var_name])
non_processed = set(rootgrp.variables.keys()) - processed
if len(non_processed) > 0:
LOG.warning("Remaining non-processed variables: " + str(non_processed))
return scene
def load_from_nc4(filename):
"""Load data from a netcdf4 file, cf-satellite v0.1
"""
rootgrp = Dataset(filename, 'r')
try:
rootgrp.satellite_number
warnings.warn("You are loading old style netcdf files...", DeprecationWarning)
except AttributeError:
return _load02(filename)
if not isinstance(rootgrp.satellite_number, str):
satellite_number = "%02d" % rootgrp.satellite_number
else:
satellite_number = str(rootgrp.satellite_number)
time_slot = rootgrp.variables["time"].getValue()[0]
time_slot = num2date(time_slot, TIME_UNITS)
service = str(rootgrp.service)
satellite_name = str(rootgrp.satellite_name)
instrument_name = str(rootgrp.instrument_name)
try:
orbit = str(rootgrp.orbit)
except AttributeError:
orbit = None
try:
scene = GenericFactory.create_scene(satellite_name,
satellite_number,
instrument_name,
time_slot,
orbit,
None,
service)
except NoSectionError:
scene = VisirCompositer(time_slot=time_slot)
scene.satname = satellite_name
scene.number = satellite_number
scene.service = service
for var_name, var in rootgrp.variables.items():
area = None
if var_name.startswith("band_data"):
resolution = var.resolution
str_res = str(int(resolution)) + "m"
names = rootgrp.variables["bandname"+str_res][:]
data = var[:, :, :].astype(var.dtype)
data = np.ma.masked_outside(data,
var.valid_range[0],
var.valid_range[1])
try:
area_var = getattr(var,"grid_mapping")
area_var = rootgrp.variables[area_var]
proj4_dict = {}
for attr, projattr in MAPPING_ATTRIBUTES.items():
try:
the_attr = getattr(area_var, attr)
if projattr == "proj":
proj4_dict[projattr] = PROJNAME[the_attr]
elif(isinstance(projattr, (list, tuple))):
try:
for i, subattr in enumerate(the_attr):
proj4_dict[projattr[i]] = subattr
except TypeError:
proj4_dict[projattr[0]] = the_attr
else:
proj4_dict[projattr] = the_attr
except AttributeError:
pass
x__ = rootgrp.variables["x"+str_res][:]
y__ = rootgrp.variables["y"+str_res][:]
x_pixel_size = abs((x__[1] - x__[0]))
y_pixel_size = abs((y__[1] - y__[0]))
llx = x__[0] - x_pixel_size / 2.0
lly = y__[-1] - y_pixel_size / 2.0
urx = x__[-1] + x_pixel_size / 2.0
ury = y__[0] + y_pixel_size / 2.0
area_extent = (llx, lly, urx, ury)
try:
# create the pyresample areadef
from pyresample.geometry import AreaDefinition
area = AreaDefinition("myareaid", "myareaname",
"myprojid", proj4_dict,
data.shape[1], data.shape[0],
area_extent)
except ImportError:
LOG.warning("Pyresample not found, "
"cannot load area descrition")
except AttributeError:
LOG.debug("No grid mapping found.")
try:
area_var = getattr(var,"coordinates")
coordinates_vars = area_var.split(" ")
lons = None
lats = None
for coord_var_name in coordinates_vars:
coord_var = rootgrp.variables[coord_var_name]
units = getattr(coord_var, "units")
if(coord_var_name.lower().startswith("lon") or
units.lower().endswith("east") or
units.lower().endswith("west")):
lons = coord_var[:]
elif(coord_var_name.lower().startswith("lat") or
units.lower().endswith("north") or
units.lower().endswith("south")):
lats = coord_var[:]
if lons and lats:
try:
from pyresample.geometry import SwathDefinition
area = SwathDefinition(lons=lons, lats=lats)
except ImportError:
LOG.warning("Pyresample not found, "
"cannot load area descrition")
except AttributeError:
LOG.debug("No lon/lat found.")
for i, name in enumerate(names):
if var.dimensions[0].startswith("band"):
chn_data = data[i, :, :]
elif var.dimensions[1].startswith("band"):
chn_data = data[:, i, :]
elif var.dimensions[2].startswith("band"):
chn_data = data[:, :, i]
else:
raise ValueError("Invalid dimension names for band data")
try:
scene[name] = (chn_data *
rootgrp.variables["scale"+str_res][i] +
rootgrp.variables["offset"+str_res][i])
#FIXME complete this
#scene[name].info
except KeyError:
# build the channel on the fly
from mpop.channel import Channel
wv_var = rootgrp.variables["nominal_wavelength"+str_res]
wb_var = rootgrp.variables[getattr(wv_var, "bounds")]
minmax = wb_var[i]
scene.channels.append(Channel(name,
resolution,
(minmax[0],
wv_var[i][0],
minmax[1])))
scene[name] = (chn_data *
rootgrp.variables["scale"+str_res][i] +
rootgrp.variables["offset"+str_res][i])
if area is not None:
scene[name].area = area
area = None
for attr in rootgrp.ncattrs():
scene.info[attr] = getattr(rootgrp, attr)
scene.add_to_history("Loaded from netcdf4/cf by mpop")
return scene
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