def main(args):
ap = argparse.ArgumentParser(prog=os.path.basename(__file__),
formatter_class=argparse.RawDescriptionHelpFormatter,
description='',
epilog=__doc__)
ap.add_argument('-c', '--config-file',
required=False,
help='the configuration file, default to "$HOME/.sdm.cfg"')
ap.add_argument('-V', '--verbose',
action='store_true',
default=False,
help='be more chatty')
ap.add_argument('-v', '--version',
action='version',
version='%s: v%s' % (ap.prog, __version__))
subparsers = ap.add_subparsers(dest='sub_command',
title='List of sub-commands',
metavar='sub-command',
help='"%s sub-command -h" for more help' % ap.prog)
cod_getpath_parser = subparsers.add_parser('cod-getpath',
help='get the full path to a CoD file')
cod_getpath_parser.add_argument('-m', '--model',
required=True,
help='model name')
cod_getpath_parser.add_argument('-c', '--scenario',
required=False,
help='scenario name, e.g. historical, rcp45, rcp85')
cod_getpath_parser.add_argument('-r', '--region-type',
required=True,
help='pre-defined region type name, e.g. sea, sec, tas ...')
cod_getpath_parser.add_argument('-s', '--season',
required=True,
help='season number, e.g. 1 (DJF), 2 (MAM), 3 (JJA), or 4 (SON)')
cod_getpath_parser.add_argument('-p', '--predictand',
required=True,
help='predictand name, e.g. rain, tmax, tmin')
dxt_gridded_parser = subparsers.add_parser('dxt-gridded',
help='extract gridded data using the given cod file')
dxt_gridded_parser.add_argument('cod_file_path',
help='full path to the CoD file')
dxt_gridded_parser.add_argument('output_file',
help='output netCDF file name')
dxt_gridded_parser.add_argument('-R', '--region',
required=False,
help='the region where the data are to be extracted')
dxt_gridded2_parser = subparsers.add_parser('dxt-gridded2',
help='extract gridded data with the given parameters')
dxt_gridded2_parser.add_argument('output_file',
help='output netCDF file name')
dxt_gridded2_parser.add_argument('-m', '--model',
required=True,
help='model name')
dxt_gridded2_parser.add_argument('-c', '--scenario',
required=False,
help='scenario name, e.g. historical, rcp45, rcp85')
dxt_gridded2_parser.add_argument('-r', '--region-type',
required=True,
help='pre-defined region type name, e.g. sea, sec, tas ...')
dxt_gridded2_parser.add_argument('-s', '--season',
required=True,
help='season number, e.g. 1 (DJF), 2 (MAM), 3 (JJA), or 4 (SON)')
dxt_gridded2_parser.add_argument('-p', '--predictand',
required=True,
help='predictand name, e.g. rain, tmax, tmin')
dxt_gridded2_parser.add_argument('-R', '--region',
required=False,
help='the region where the data are to be extracted (default to region-type)')
ns = ap.parse_args(args)
config = read_config(ns.config_file)
if ns.sub_command == 'cod-getpath':
print CoD(config.get('dxt', 'cod_base_dir'), verbose=ns.verbose).get_cod_file_path(
ns.model, ns.scenario, ns.region_type, ns.season, ns.predictand)
elif ns.sub_command in ('dxt-gridded', 'dxt-gridded2'):
gridded_extractor = GriddedExtractor(cod_base_dir=config.get('dxt', 'cod_base_dir'),
mask_base_dir=config.get('dxt', 'mask_base_dir'),
gridded_base_dir=config.get('dxt', 'gridded_base_dir'),
verbose=ns.verbose)
if ns.sub_command == 'dxt-gridded':
model, scenario, region_type, season, predictand = CoD.get_components_from_path(ns.cod_file_path)
else:
model, scenario, region_type, season, predictand = \
ns.model, ns.scenario, ns.region_type, ns.season, ns.predictand
data, dates, lat, lon = gridded_extractor.extract(model, scenario, region_type, season, predictand,
ns.region)
GriddedExtractor.save_netcdf(ns.output_file, data, dates, lat, lon,
model, scenario, region_type, season, predictand)
import numpy as np
from sdm.cod import CoD
from sdm.extractor import GriddedExtractor
data_extractor = GriddedExtractor(cod_base_dir=r'C:\Users\ywang\tmp\CMIP5_v2',
mask_base_dir=r'C:\Users\ywang\tmp\Masks',
gridded_base_dir=r'C:\Users\ywang\tmp\AWAP',
verbose=True)
data, dates, lat, lon = data_extractor.extract('ACCESS1.0', 'historical',
'tas', '2', 'tmin')
GriddedExtractor.save_netcdf('tmp.nc', data, dates, lat, lon, 'ACCESS1.0',
'historical', 'tas', '2', 'tmin')
data2, dates, lat, lon = data_extractor.extract(*CoD.get_components_from_path(
r'C:\Users\ywang\tmp\CMIP5_v2\ACCESS1.0_historical\tas\tmin\season_2\rawfield_analog_2'
))
np.testing.assert_equal(data, data2)
import numpy as np
from sdm.cod import CoD
from sdm.extractor import GriddedExtractor
data_extractor = GriddedExtractor(cod_base_dir=r'C:\Users\ywang\tmp\CMIP5_v2',
mask_base_dir=r'C:\Users\ywang\tmp\Masks',
gridded_base_dir=r'C:\Users\ywang\tmp\AWAP',
verbose=True)
data, dates, lat, lon = data_extractor.extract('ACCESS1.0', 'historical', 'tas', '2', 'tmin')
GriddedExtractor.save_netcdf('tmp.nc', data, dates, lat, lon,
'ACCESS1.0', 'historical', 'tas', '2', 'tmin')
data2, dates, lat, lon = data_extractor.extract(
*CoD.get_main_parameters_by_path(
r'C:\Users\ywang\tmp\CMIP5_v2\ACCESS1.0_historical\tas\tmin\season_2\rawfield_analog_2'))
np.testing.assert_equal(data, data2)
import numpy as np
from sdm.cod import CoD
from sdm.extractor import GriddedExtractor
data_extractor = GriddedExtractor(cod_base_dir=r'C:\Users\ywang\tmp\CMIP5_v2',
mask_base_dir=r'C:\Users\ywang\tmp\Masks',
gridded_base_dir=r'C:\Users\ywang\tmp\AWAP',
verbose=True)
data, dates, lat, lon = data_extractor.extract('ACCESS1.0', 'historical', 'tas', '2', 'tmin')
GriddedExtractor.save_netcdf('tmp.nc', data, dates, lat, lon,
'ACCESS1.0', 'historical', 'tas', '2', 'tmin')
data2, dates, lat, lon = data_extractor.extract(
*CoD.get_components_from_path(
r'C:\Users\ywang\tmp\CMIP5_v2\ACCESS1.0_historical\tas\tmin\season_2\rawfield_analog_2'))
np.testing.assert_equal(data, data2)
def main(args):
ap = argparse.ArgumentParser(
prog=os.path.basename(__file__),
formatter_class=argparse.RawDescriptionHelpFormatter,
description='',
epilog=__doc__)
ap.add_argument('-c',
'--config-file',
required=False,
help='the configuration file, default to "$HOME/.sdm.cfg"')
ap.add_argument('-V',
'--verbose',
action='store_true',
default=False,
help='be more chatty')
ap.add_argument('-v',
'--version',
action='version',
version='%s: v%s' % (ap.prog, __version__))
subparsers = ap.add_subparsers(dest='sub_command',
title='List of sub-commands',
metavar='sub-command',
help='"%s sub-command -h" for more help' %
ap.prog)
cod_getpath_parser = subparsers.add_parser(
'cod-getpath', help='get the full path to a CoD file')
cod_getpath_parser.add_argument('-m',
'--model',
required=True,
help='model name')
cod_getpath_parser.add_argument(
'-c',
'--scenario',
required=False,
help='scenario name, e.g. historical, rcp45, rcp85')
cod_getpath_parser.add_argument(
'-r',
'--region-type',
required=True,
help='pre-defined region type name, e.g. sea, sec, tas ...')
cod_getpath_parser.add_argument(
'-s',
'--season',
required=True,
help='season number, e.g. 1 (DJF), 2 (MAM), 3 (JJA), or 4 (SON)')
cod_getpath_parser.add_argument(
'-p',
'--predictand',
required=True,
help='predictand name, e.g. rain, tmax, tmin')
dxt_gridded_parser = subparsers.add_parser(
'dxt-gridded', help='extract gridded data using the given cod file')
dxt_gridded_parser.add_argument('cod_file_path',
help='full path to the CoD file')
dxt_gridded_parser.add_argument('output_file',
help='output netCDF file name')
dxt_gridded_parser.add_argument(
'-R',
'--region',
required=False,
help='the region where the data are to be extracted')
dxt_gridded2_parser = subparsers.add_parser(
'dxt-gridded2', help='extract gridded data with the given parameters')
dxt_gridded2_parser.add_argument('output_file',
help='output netCDF file name')
dxt_gridded2_parser.add_argument('-m',
'--model',
required=True,
help='model name')
dxt_gridded2_parser.add_argument(
'-c',
'--scenario',
required=False,
help='scenario name, e.g. historical, rcp45, rcp85')
dxt_gridded2_parser.add_argument(
'-r',
'--region-type',
required=True,
help='pre-defined region type name, e.g. sea, sec, tas ...')
dxt_gridded2_parser.add_argument(
'-s',
'--season',
required=True,
help='season number, e.g. 1 (DJF), 2 (MAM), 3 (JJA), or 4 (SON)')
dxt_gridded2_parser.add_argument(
'-p',
'--predictand',
required=True,
help='predictand name, e.g. rain, tmax, tmin')
dxt_gridded2_parser.add_argument(
'-R',
'--region',
required=False,
help=
'the region where the data are to be extracted (default to region-type)'
)
ns = ap.parse_args(args)
config = read_config(ns.config_file)
if ns.sub_command == 'cod-getpath':
print CoD(config.get('dxt', 'cod_base_dir'),
verbose=ns.verbose).get_cod_file_path(
ns.model, ns.scenario, ns.region_type, ns.season,
ns.predictand)
elif ns.sub_command in ('dxt-gridded', 'dxt-gridded2'):
gridded_extractor = GriddedExtractor(
cod_base_dir=config.get('dxt', 'cod_base_dir'),
mask_base_dir=config.get('dxt', 'mask_base_dir'),
gridded_base_dir=config.get('dxt', 'gridded_base_dir'),
verbose=ns.verbose)
if ns.sub_command == 'dxt-gridded':
model, scenario, region_type, season, predictand = CoD.get_components_from_path(
ns.cod_file_path)
else:
model, scenario, region_type, season, predictand = \
ns.model, ns.scenario, ns.region_type, ns.season, ns.predictand
data, dates, lat, lon = gridded_extractor.extract(
model, scenario, region_type, season, predictand, ns.region)
GriddedExtractor.save_netcdf(ns.output_file, data, dates, lat, lon,
model, scenario, region_type, season,
predictand)