def test_create_epsg4326_netcdf(tmpnetcdf_filename):
nco = create_netcdf(tmpnetcdf_filename)
create_coordinate(nco, 'latitude', numpy.array([1., 2., 3.]), 'm')
create_coordinate(nco, 'longitude', numpy.array([1., 2., 3.]), 'm')
create_grid_mapping_variable(nco, GEO_PROJ)
nco.close()
with netCDF4.Dataset(tmpnetcdf_filename) as nco:
assert crs_var in nco.variables
assert nco[crs_var].grid_mapping_name == 'latitude_longitude'
_ensure_spheroid(nco[crs_var])
_ensure_geospatial(nco)
def test_create_sinus_netcdf(tmpnetcdf_filename):
nco = create_netcdf(tmpnetcdf_filename)
create_coordinate(nco, 'x', numpy.array([1., 2., 3.]), 'm')
create_coordinate(nco, 'y', numpy.array([1., 2., 3.]), 'm')
create_grid_mapping_variable(nco, SINIS_PROJ)
nco.close()
with netCDF4.Dataset(tmpnetcdf_filename) as nco:
assert crs_var in nco.variables
assert nco[crs_var].grid_mapping_name == 'sinusoidal'
assert 'longitude_of_central_meridian' in nco[crs_var].ncattrs()
_ensure_spheroid(nco[crs_var])
_ensure_geospatial(nco)
def test_create_albers_projection_netcdf(tmpnetcdf_filename):
nco = create_netcdf(tmpnetcdf_filename)
create_coordinate(nco, 'x', numpy.array([1., 2., 3.]), 'm')
create_coordinate(nco, 'y', numpy.array([1., 2., 3.]), 'm')
create_grid_mapping_variable(nco, ALBERS_PROJ)
nco.close()
with netCDF4.Dataset(tmpnetcdf_filename) as nco:
assert crs_var in nco.variables
assert nco[crs_var].grid_mapping_name == 'albers_conical_equal_area'
assert 'standard_parallel' in nco[crs_var].ncattrs()
assert 'longitude_of_central_meridian' in nco[crs_var].ncattrs()
assert 'latitude_of_projection_origin' in nco[crs_var].ncattrs()
_ensure_spheroid(nco[crs_var])
_ensure_gdal(nco[crs_var])
_ensure_geospatial(nco)
def test_create_lambert_conformal_conic_2sp_projection_netcdf(tmpnetcdf_filename):
nco = create_netcdf(tmpnetcdf_filename)
create_coordinate(nco, 'x', numpy.array([1., 2., 3.]), 'm')
create_coordinate(nco, 'y', numpy.array([1., 2., 3.]), 'm')
create_grid_mapping_variable(nco, LCC2_PROJ)
nco.close()
with netCDF4.Dataset(tmpnetcdf_filename) as nco:
assert 'crs' in nco.variables
assert nco['crs'].grid_mapping_name == 'lambert_conformal_conic'
assert 'standard_parallel' in nco['crs'].ncattrs()
assert 'longitude_of_central_meridian' in nco['crs'].ncattrs()
assert 'latitude_of_projection_origin' in nco['crs'].ncattrs()
assert 'false_easting' in nco['crs'].ncattrs()
assert 'false_northing' in nco['crs'].ncattrs()
_ensure_spheroid(nco['crs'])
_ensure_gdal(nco['crs'])
_ensure_geospatial(nco)
def saveNC(output, filename, history):
logging.info('saveNC: dataset {} - {}'.format(type(output), output))
start = time.time()
nco = netcdf_writer.create_netcdf(filename)
nco.history = (history.encode('ascii', 'replace'))
coords = output.coords
cnames = ()
# This 3 lines were created by Aurelio
# if an error occurs in this function please
# check this 3 lines first.
# we reorder the coordinates system to match
coord_names = list(output.coords.keys())
print('coord_names_antes', coord_names)
sample_coords = []
if 'time' in coord_names:
sample_coords.append('time')
coord_names.remove('time')
if 'latitude' in coord_names:
sample_coords.append('latitude')
coord_names.remove('latitude')
else:
raise Exception("No hay 'latitude' como coordenada en el dataset")
if 'longitude' in coord_names:
sample_coords.append('longitude')
coord_names.remove('longitude')
else:
raise Exception("No hay 'longitude' como coordenada en el dataset")
sample_coords = sample_coords + coord_names
coord_names = sample_coords
print('coord_names_despues', coord_names)
#for x in coords:
for x in coord_names:
if not 'units' in coords[x].attrs:
if x == "time":
coords[x].attrs["units"] = u"seconds since 1970-01-01 00:00:00"
netcdf_writer.create_coordinate(nco, x, coords[x].values,
coords[x].units)
cnames = cnames + (x, )
_crs = output.crs
if isinstance(_crs, xr.DataArray):
_crs = CRS(str(_crs.spatial_ref))
netcdf_writer.create_grid_mapping_variable(nco, _crs)
for band in output.data_vars:
#Para evitar problemas con xarray <0.11
if band in coords.keys() or band == 'crs':
continue
output.data_vars[band].values[np.isnan(
output.data_vars[band].values)] = nodata
var = netcdf_writer.create_variable(nco,
band,
netcdf_writer.Variable(
output.data_vars[band].dtype,
nodata, cnames, None),
set_crs=True)
var[:] = netcdf_writer.netcdfy_data(output.data_vars[band].values)
nco.close()
end = time.time()
logging.info('TIEMPO SALIDA NC:' + str((end - start)))