lakes=['GreatLakes',]+list(great_lakes.values()))
# N.B.: individual lakes have to be initialized seperately and added to the set post-hoc,
# because they don't share a folder
# add aliases
lake_list = OrderedDict()
for name,lake in list(great_lakes.items()): # do not iter, since dict is changes in for-loop
lake_list[name] = lake
lake_list[lake.name] = lake
lake_list[lake.long_name] = lake
## generate loadGageStation* versions with these basins
from datasets.WSC import loadGageStation, loadWSC_Shp, loadWSC_ShpTS, loadWSC_Stn, loadWSC_StnTS
addLoadFcts(locals(), locals(), basins=basins, basin_list=basin_list)
## some testing/verification
if __name__ == '__main__':
## print basins
for name,basin in basin_list.items():
s = ' {:3s} ({:s}): '.format(name,basin.shapetype)
if hasattr(basin, 'subbasins'):
for subbasin in basin.subbasins: s += ' {:9s}'.format('{:s},'.format(subbasin))
print(s)
# if basin.maingage: print(basin.maingage.monthly_file)
# ## print Great Lakes
# for name,lake in great_lakes.iteritems():
ensembles['all-ens'+suffix] = ensembles['phys-ens'+suffix] + ensembles['mex-ens'+suffix][1:]
# N.B.: omit max-ctrl the second time
# historical ensembles (no future periods)
ensembles['3km-ens'] = ('erai-3km', 'max-3km')
# replace names with experiment instances
for ensname,enslist in ensembles.items():
ensembles[ensname] = tuple(experiments[expname] for expname in enslist)
# make sorted copy
WRF_ens = OrderedDict()
name_list = list(ensembles.keys()); name_list.sort()
for key in name_list:
WRF_ens[key] = ensembles[key]
ensembles = enss = WRF_ens
## generate loadWRF* versions with these experiments
# import datasets.WRF as dataset
import inspect,functools
from datasets.WRF import loadWRF, loadWRF_Shp, loadWRF_Stn, loadWRF_TS, loadWRF_ShpTS, loadWRF_StnTS, loadWRF_Ensemble, loadWRF_ShpEns, loadWRF_StnEns
addLoadFcts(locals(), locals(), exps=WRF_exps, enses=WRF_ens)
# loadWRF = functools.partial(loadWRF, exps=WRF_exps)
if __name__ == '__main__':
## view/test ensembles
for name,members in WRF_ens.items():
s = ' {:s}: '.format(name)
for member in members: s += ' {:s},'.format(member.name)
print(s)
A package that contains settings for the WesternCanada region projects for use with the geodata package.
@author: Andre R. Erler, GPL v3
'''
# import figure settings
from figure_settings import getVariableSettings, getFigureSettings, figure_folder
# import map projection settings (basemap)
try:
from map_settings import getSetup, map_folder
except ImportError:
print("Error importing map settings - 'basemap' is likely no installed.")
## import load functions with GreatLakes experiments into local namespace
# import relevant WRF experiments
from WRF_experiments import WRF_exps, WRF_ens
# import WRF load functions
from WRF_experiments import loadWRF, loadWRF_Shp, loadWRF_Stn, loadWRF_TS, loadWRF_ShpTS, loadWRF_StnTS, loadWRF_Ensemble, loadWRF_ShpEns, loadWRF_StnEns
# also load CESM experiments and functions
from projects.CESM_experiments import CESM_exps, CESM_ens
# import CESM load functions
from projects.CESM_experiments import loadCESM, loadCESM_Shp, loadCESM_Stn, loadCESM_TS, loadCESM_ShpTS, loadCESM_StnTS, loadCESM_Ensemble, loadCESM_ShpEns, loadCESM_StnEns
# add relevant experiments to general load functions
from datasets.common import loadDataset, loadClim, loadShpTS, loadStnTS, loadEnsembleTS, addLoadFcts
# modify functions (wont affect modified WRF/CESM functions)
addLoadFcts(locals(), locals(), WRF_exps=WRF_exps, WRF_ens=WRF_ens, CESM_exps=CESM_exps, CESM_ens=CESM_ens)
ensembles['all-ens' +
suffix] = ensembles['phys-ens' + suffix] + ensembles['mex-ens' +
suffix][1:]
# N.B.: omit max-ctrl the second time
# replace names with experiment instances
for ensname, enslist in ensembles.iteritems():
ensembles[ensname] = tuple(experiments[expname] for expname in enslist)
# make sorted copy
WRF_ens = OrderedDict()
name_list = ensembles.keys()
name_list.sort()
for key in name_list:
WRF_ens[key] = ensembles[key]
ensembles = enss = WRF_ens
## generate loadWRF* versions with these experiments
# import datasets.WRF as dataset
import inspect, functools
from datasets.WRF import loadWRF, loadWRF_Shp, loadWRF_Stn, loadWRF_TS, loadWRF_ShpTS, loadWRF_StnTS, loadWRF_Ensemble, loadWRF_ShpEns, loadWRF_StnEns
addLoadFcts(locals(), locals(), exps=WRF_exps, enses=WRF_ens)
# loadWRF = functools.partial(loadWRF, exps=WRF_exps)
if __name__ == '__main__':
## view/test ensembles
for name, members in WRF_ens.iteritems():
s = ' {:s}: '.format(name)
for member in members:
s += ' {:s},'.format(member.name)
print(s)
from projects.CESM_experiments import CESM_exps, CESM_ens
# import CESM load functions
from projects.CESM_experiments import loadCESM, loadCESM_Shp, loadCESM_Stn, loadCESM_TS, loadCESM_ShpTS, loadCESM_StnTS, loadCESM_Ensemble, loadCESM_ShpEns, loadCESM_StnEns
except (ImportError,IOError):
CESM_exps = None; CESM_ens = None
warn("Error importing CESM experiments.")
# add relevant experiments to general load functions
from datasets.common import loadDataset, loadEnsembleTS, addLoadFcts
try:
from datasets.Unity import loadUnity, loadUnity_Shp, loadUnity_Stn, loadUnity_ShpTS, loadUnity_StnTS # loadUnity_TS doesn't exist
except (ImportError,IOError):
warn("Error importing Unified Observational Dataset 'Unity'.")
unity_grid = 'glb1_d02' # Unified Dataset default grid
# N.B.: it is recommended to import Unity load fcts. from here
# modify functions (wont affect modified WRF/CESM functions)
addLoadFcts(locals(), locals(), unity_grid=unity_grid , WRF_exps=WRF_exps, WRF_ens=WRF_ens,
CESM_exps=CESM_exps, CESM_ens=CESM_ens)
## import shape dictionaries
try:
from projects.WSC_basins import basins, provinces, great_lakes # import the dicts with unique entries
except (ImportError,IOError):
warn("Error importing shape files and/or WSC module.")
# import figure with hydro settings
from .analysis_settings import loadStationEnsemble, loadShapeEnsemble, loadShapeObservations # load datasets
from .analysis_settings import loadStationFit, loadShapeFit
from .analysis_settings import exps_rc, variables_rc, constraints_rc
from .analysis_settings import climFigAx, climPlot, evaFigAx, distPlot, quantPlot # plotting
# initial condition ensemble
ensembles['ens20trcn1x1'] = [tag+'20trcn1x1' for tag in 'tb', 'hab', 'hab', 'hab']
ensembles['ensrcp85cn1x1'] = [tag+'rcp85cn1x1' for tag in 'htb', 'hab', 'hab', 'hab']
ensembles['ensrcp85cn1x1d'] = [tag+'rcp85cn1x1d' for tag in 'htb', 'hab', 'hab', 'hab']
ensembles['mens20trcn1x1'] = [tag+'20trcn1x1' for tag in 'hab', 'hab', 'hab']
ensembles['mensrcp85cn1x1'] = [tag+'rcp85cn1x1' for tag in 'hab', 'hab', 'hab']
ensembles['mensrcp85cn1x1d'] = [tag+'rcp85cn1x1d' for tag in 'hab', 'hab', 'hab']
# add aliases
CESM_ens = enss = ensembles
# N.B.: static & meta data for the ensemble is copied from the first-listed member;
# this includes station attributes, such as the elevation error
# replace names with experiment instances
for ensname,enslist in ensembles.items(): # don't use iter, because we chagne the dict!
members = tuple([experiments[expname] for expname in enslist])
ensembles[ensname] = members
ensembles[experiments[ensname].shortname] = members
## generate loadCESM* versions with these experiments
from datasets.CESM import loadCESM, loadCESM_Shp, loadCESM_Stn, loadCESM_TS, loadCESM_ShpTS, loadCESM_StnTS, loadCESM_Ensemble, loadCESM_ShpEns, loadCESM_StnEns
addLoadFcts(locals(), locals(), exps=CESM_exps, enses=CESM_ens)
if __name__ == '__main__':
## view/test ensembles
for name,members in CESM_ens.iteritems():
s = ' {:s}: '.format(name)
for member in members: s += ' {:s},'.format(member.name)
print(s)
ensembles['mensrcp85cn1x1'] = [
tag + 'rcp85cn1x1' for tag in 'hab', 'hab', 'hab'
]
ensembles['mensrcp85cn1x1d'] = [
tag + 'rcp85cn1x1d' for tag in 'hab', 'hab', 'hab'
]
# N.B.: static & meta data for the ensemble is copied from the first-listed member;
# this includes station attributes, such as the elevation error
# replace names with experiment instances
for ensname, enslist in ensembles.items(
): # don't use iter, because we chagne the dict!
members = tuple([experiments[expname] for expname in enslist])
ensembles[ensname] = members
ensembles[experiments[ensname].shortname] = members
# add aliases
CESM_ens = enss = ensembles
## generate loadCESM* versions with these experiments
from datasets.CESM import loadCESM, loadCESM_Shp, loadCESM_Stn, loadCESM_TS, loadCESM_ShpTS, loadCESM_StnTS, loadCESM_Ensemble, loadCESM_ShpEns, loadCESM_StnEns
addLoadFcts(locals(), locals(), exps=CESM_exps, enses=CESM_ens)
if __name__ == '__main__':
## view/test ensembles
for name, members in CESM_ens.iteritems():
s = ' {:s}: '.format(name)
for member in members:
s += ' {:s},'.format(member.name)
print(s)
# import figure settings
from figure_settings import getVariableSettings, getFigureSettings, figure_folder
# import map projection settings (basemap)
try:
from map_settings import getSetup, map_folder
except ImportError:
print("Error importing map settings - 'basemap' is likely no installed.")
## import load functions with GreatLakes experiments into local namespace
# import relevant WRF experiments
from WRF_experiments import WRF_exps, WRF_ens
# import WRF load functions
from WRF_experiments import loadWRF, loadWRF_Shp, loadWRF_Stn, loadWRF_TS, loadWRF_ShpTS, loadWRF_StnTS, loadWRF_Ensemble, loadWRF_ShpEns, loadWRF_StnEns
# also load CESM experiments and functions
from projects.CESM_experiments import CESM_exps, CESM_ens
# import CESM load functions
from projects.CESM_experiments import loadCESM, loadCESM_Shp, loadCESM_Stn, loadCESM_TS, loadCESM_ShpTS, loadCESM_StnTS, loadCESM_Ensemble, loadCESM_ShpEns, loadCESM_StnEns
# add relevant experiments to general load functions
from datasets.common import loadDataset, loadClim, loadShpTS, loadStnTS, loadEnsembleTS, addLoadFcts
# modify functions (wont affect modified WRF/CESM functions)
addLoadFcts(locals(),
locals(),
WRF_exps=WRF_exps,
WRF_ens=WRF_ens,
CESM_exps=CESM_exps,
CESM_ens=CESM_ens)
