"Dataset 'Unity' has no native grid - please set 'unity_grid'."
)
# print an announcement
if len(WRF_experiments) > 0:
print('\n Regridding WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Regridding CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n And Observational Datasets:')
print(datasets)
print('\n To Grid and Resolution:')
for grid, reses in grids.iteritems():
print(' {0:s} {1:s}'.format(grid, printList(reses) if reses else ''))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode == 'climatology':
periodlist = periods if isinstance(periods,
(tuple, list)) else (periods, )
elif mode == 'time-series':
periodlist = (None, ) # ignore periods
else:
raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# expand datasets and resolutions
if datasets is None: datasets = gridded_datasets
# print an announcement
if len(WRF_experiments) > 0:
print('\n Extracting from WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Extracting from CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n Extracting from Observational Datasets:')
print(datasets)
print('\n According to Station Datasets:')
for stntype,datatypes in stations.iteritems():
print(' {0:s} {1:s}'.format(stntype,printList(datatypes)))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages (commands)
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode == 'climatology': periodlist = periods
elif mode == 'time-series': periodlist = (None,)
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# loop over station dataset types ...
for stntype,datatypes in stations.iteritems():
# ... and their filetypes
"Dataset 'Unity' has no native grid - please set 'unity_grid'."
)
# print an announcement
if len(WRF_experiments) > 0:
print('\n Extracting from WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Extracting from CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n Extracting from Observational Datasets:')
print(datasets)
print('\n According to Station Datasets:')
for stntype, datatypes in stations.iteritems():
print(' {0:s} {1:s}'.format(stntype, printList(datatypes)))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages (commands)
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode == 'climatology':
periodlist = [] if periods is None else periods
elif mode == 'time-series':
periodlist = (None, )
else:
raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# loop over station dataset types ...
if 'basins' in shapes:
for shp in shapes['basins']: shape_dict[shp] = basins[shp]
# print an announcement
if len(WRF_experiments) > 0:
print('\n Averaging from WRF Datasets ({:s}):'.format(WRF_project))
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Averaging from CESM Datasets ({:s}):'.format(CESM_project))
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n Averaging from Observational Datasets:')
print(datasets)
print('\n Using Shapefiles:')
for shptype,shplst in shapes.iteritems():
print(' {0:s} {1:s}'.format(shptype,printList(shplst)))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages (commands)
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode == 'climatology': periodlist = periods
elif mode == 'time-series': periodlist = (None,)
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# observational datasets (grid depends on dataset!)
for dataset in datasets:
mod = import_module('datasets.{0:s}'.format(dataset))
# expand datasets and resolutions
if datasets is None: datasets = gridded_datasets
# print an announcement
if len(WRF_experiments) > 0:
print('\n Regridding WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Regridding CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n And Observational Datasets:')
print(datasets)
print('\n To Grid and Resolution:')
for grid,reses in grids.iteritems():
print(' {0:s} {1:s}'.format(grid,printList(reses) if reses else ''))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode == 'climatology':
periodlist = periods if isinstance(periods, (tuple,list)) else (periods,)
elif mode == 'time-series':
periodlist = (None,) # ignore periods
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# loop over target grids ...
if datasets is None: datasets = gridded_datasets
if unity_grid is None and 'Unity' in datasets:
if WRF_project: unity_grid = import_module('projects.{:s}'.format(WRF_project)).unity_grid
else: raise DatasetError("Dataset 'Unity' has no native grid - please set 'unity_grid'.")
# print an announcement
if len(WRF_experiments) > 0:
print('\n Exporting WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Exporting CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n And Observational Datasets:')
print(datasets)
print('\n From Grid/Resolution:\n {:s}'.format(printList(grids)))
print('To File Format {:s}'.format(export_arguments['format']))
print('\n Project Designation: {:s}'.format(export_arguments['project']))
if bc_method:
print('\n And Observational Datasets:')
print(datasets)
print('Export Variable List: {:s}'.format(printList(export_arguments['exp_list'])))
if export_arguments['lm3']: '\n Converting kg/m^2/s (mm/s) into m^3/m^2/s (m/s)'
# check formats (will be iterated over in export function, hence not part of task list)
if export_arguments['format'] == 'ASCII_raster':
print('Export Folder: {:s}'.format(export_arguments['folder']))
print('File Prefix: {:s}'.format(export_arguments['prefix']))
elif export_arguments['format'].lower() in ('netcdf','netcdf4'):
pass
else:
raise ArgumentError, "Unsupported file format: '{:s}'".format(export_arguments['format'])
CESM_experiments = getExperimentList(CESM_experiments, CESM_project,
'CESM')
# expand datasets and resolutions
if datasets is None: datasets = gridded_datasets
# print an announcement
if len(WRF_experiments) > 0:
print('\n Exporting WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Exporting CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n And Observational Datasets:')
print(datasets)
print('\n From Grid/Resolution:\n {:s}'.format(printList(grids)))
print('\n To File Formats:')
for fileformat, params in formats.iteritems():
print(' {0:s} ({1:s})'.format(fileformat,
printList(params) if params else ''))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
# check formats (will be iterated over in export function, hence not part of task list)
for fileformat in formats.iterkeys():
if fileformat.lower() not in ('ascii_raster', 'netcdf'):
raise ArgumentError, "Unsupported file format: '{:s}'".format(
fileformat)
## construct argument list
args = [] # list of job packages
# loop over modes
## load observations/reference dataset
obs_dataset = loadDataset(name=obs_name, mode=obs_mode, **obs_args).load()
# print an announcement
if len(WRF_experiments) > 0:
print('\n Bias-correcting WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Bias-correcting CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n Bias-correcting Other Datasets:')
print(datasets)
print('\n On Grid/Resolution:\n {:s}'.format(grid))
print('\n Variable List: {:s}'.format(
'All' if varlist is None else printList(varlist)))
print('\n Bias-Correction Method: {:s}'.format(bc_method))
print('\n Observationa/Reference Dataset:\n {:s}'.format(
obs_dataset if ldebug else obs_dataset.name))
print('\n OVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode[-5:] == '-mean': periodlist = periods
elif mode == 'climatology': periodlist = periods
elif mode == 'time-series': periodlist = (None, )
else:
raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# check and expand CESM experiment list
CESM_experiments = getExperimentList(CESM_experiments, CESM_project, 'CESM')
# expand datasets and resolutions
if datasets is None: datasets = gridded_datasets
# print an announcement
if len(WRF_experiments) > 0:
print('\n Exporting WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Exporting CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n And Observational Datasets:')
print(datasets)
print('\n From Grid/Resolution:\n {:s}'.format(printList(grids)))
print('\n To File Formats:')
for fileformat,params in formats.iteritems():
print(' {0:s} ({1:s})'.format(fileformat,printList(params) if params else ''))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
# check formats (will be iterated over in export function, hence not part of task list)
for fileformat in formats.iterkeys():
if fileformat.lower() not in ('ascii_raster','netcdf'):
raise ArgumentError, "Unsupported file format: '{:s}'".format(fileformat)
## construct argument list
args = [] # list of job packages
# loop over modes
for mode in modes:
# only climatology mode has periods
## load observations/reference dataset
obs_dataset = loadDataset(name=obs_name, mode=obs_mode, **obs_args).load()
# print an announcement
if len(WRF_experiments) > 0:
print('\n Bias-correcting WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Bias-correcting CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n Bias-correcting Other Datasets:')
print(datasets)
print('\n On Grid/Resolution:\n {:s}'.format(grid))
print('\n Variable List: {:s}'.format('All' if varlist is None else printList(varlist)))
print('\n Bias-Correction Method: {:s}'.format(bc_method))
print('\n Observationa/Reference Dataset:\n {:s}'.format(obs_dataset if ldebug else obs_dataset.name))
print('\n OVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode[-5:] == '-mean': periodlist = periods
elif mode == 'climatology': periodlist = periods
elif mode == 'time-series': periodlist = (None,)
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# check and expand CESM experiment list
CESM_experiments = getExperimentList(CESM_experiments, CESM_project, 'CESM')
# expand datasets and resolutions
if datasets is None: datasets = gridded_datasets
# print an announcement
if len(WRF_experiments) > 0:
print('\n Exporting WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Exporting CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n And Observational Datasets:')
print(datasets)
print('\n From Grid/Resolution:\n {:s}'.format(printList(grids)))
print('To File Format {:s}'.format(export_arguments['format']))
print('\n Project Designation: {:s}'.format(export_arguments['project']))
print('Export Variable List: {:s}'.format(printList(export_arguments['varlist'])))
if export_arguments['lm3']: '\n Converting kg/m^2/s (mm/s) into m^3/m^2/s (m/s)'
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
# check formats (will be iterated over in export function, hence not part of task list)
if export_arguments['format'] == 'ASCII_raster':
print('Export Folder: {:s}'.format(export_arguments['folder']))
print('File Prefix: {:s}'.format(export_arguments['prefix']))
elif export_arguments['format'].lower() in ('netcdf','netcdf4'):
pass
else:
raise ArgumentError, "Unsupported file format: '{:s}'".format(export_arguments['format'])
## load observations/reference dataset
obs_dataset = loadDataset(name=obs_name, mode=obs_mode, **obs_args).load()
# print an announcement
if len(WRF_experiments) > 0:
print('\n Bias-correcting WRF Datasets:')
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Bias-correcting CESM Datasets:')
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n Bias-correcting Other Datasets:')
print(datasets)
print('\n On Grid/Resolution:\n {:s}'.format(grid))
print('\n Variable List: {:s}'.format('All' if varlist is None else printList(varlist)))
print('\n Bias-Correction Method: {:s}'.format(bc_method))
print('\n Observationa/Reference Dataset:\n {:s}'.format(obs_dataset if ldebug else obs_dataset.name))
print('\n OVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode[-5:] == '-mean': periodlist = periods
elif mode == 'climatology': periodlist = periods
elif mode == 'time-series': periodlist = (None,)
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
for shp in shapes['basins']:
shape_dict[shp] = basins[shp]
# print an announcement
if len(WRF_experiments) > 0:
print('\n Averaging from WRF Datasets ({:s}):'.format(WRF_project))
print([exp.name for exp in WRF_experiments])
if len(CESM_experiments) > 0:
print('\n Averaging from CESM Datasets ({:s}):'.format(CESM_project))
print([exp.name for exp in CESM_experiments])
if len(datasets) > 0:
print('\n Averaging from Observational Datasets:')
print(datasets)
print('\n Using Shapefiles:')
for shptype, shplst in shapes.iteritems():
print(' {0:s} {1:s}'.format(shptype, printList(shplst)))
print('\nOVERWRITE: {0:s}\n'.format(str(loverwrite)))
## construct argument list
args = [] # list of job packages (commands)
# loop over modes
for mode in modes:
# only climatology mode has periods
if mode == 'climatology': periodlist = periods
elif mode == 'time-series': periodlist = (None, )
else:
raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# observational datasets (grid depends on dataset!)
for dataset in datasets:
mod = import_module('datasets.{0:s}'.format(dataset))
