def defineDataset(self,
dataset=None,
mode=None,
bc_method=None,
dataargs=None,
lwrite=True,
ldebug=False):
''' a method to set external parameters about the Dataset, so that the export destination
can be determined (and returned) '''
# get filename for target dataset and do some checks
if self.folder_pattern is None:
avgfolder = dataargs.avgfolder # regular source dataset location
else:
self.folder_pattern.format(
dataset,
self.project,
dataargs.dataset_name,
) # this could be expanded with dataargs
if not os.path.exists(avgfolder):
raise IOError, "Dataset folder '{:s}' does not exist!".format(
avgfolder)
filename = getTargetFile(dataset=dataset,
mode=mode,
dataargs=dataargs,
lwrite=lwrite,
filetype=self.filetype)
if ldebug: filename = 'test_{:s}'.format(filename)
self.filepath = '{:s}/{:s}'.format(avgfolder, filename)
return self.filepath
def defineDataset(self, dataset=None, mode=None, bc_method=None, dataargs=None, lwrite=True, ldebug=False):
''' a method to set external parameters about the Dataset, so that the export destination
can be determined (and returned) '''
# get filename for target dataset and do some checks
if self.folder_pattern is None: avgfolder = dataargs.avgfolder # regular source dataset location
else: self.folder_pattern.format(dataset, self.project, dataargs.dataset_name,) # this could be expanded with dataargs
if not os.path.exists(avgfolder): raise IOError, "Dataset folder '{:s}' does not exist!".format(avgfolder)
filename = getTargetFile(dataset=dataset, mode=mode, dataargs=dataargs, lwrite=lwrite, filetype=self.filetype)
if ldebug: filename = 'test_{:s}'.format(filename)
self.filepath = '{:s}/{:s}'.format(avgfolder,filename)
return self.filepath
def performExtraction(dataset, mode, stnfct, dataargs, loverwrite=False, varlist=None, lwrite=True, lreturn=False,
ldebug=False, lparallel=False, pidstr='', logger=None):
''' worker function to extract point data from gridded dataset '''
# input checking
if not isinstance(dataset,basestring): raise TypeError
if not isinstance(dataargs,dict): raise TypeError # all dataset arguments are kwargs
if not callable(stnfct): raise TypeError # function to load station dataset
if lparallel:
if not lwrite: raise IOError, 'In parallel mode we can only write to disk (i.e. lwrite = True).'
if lreturn: raise IOError, 'Can not return datasets in parallel mode (i.e. lreturn = False).'
# logging
if logger is None: # make new logger
logger = logging.getLogger() # new logger
logger.addHandler(logging.StreamHandler())
else:
if isinstance(logger,basestring):
logger = logging.getLogger(name=logger) # connect to existing one
elif not isinstance(logger,logging.Logger):
raise TypeError, 'Expected logger ID/handle in logger KW; got {}'.format(str(logger))
lclim = False; lts = False
if mode == 'climatology': lclim = True
elif mode == 'time-series': lts = True
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
## extract meta data from arguments
module, dataargs, loadfct, filepath, datamsgstr = getMetaData(dataset, mode, dataargs)
dataset_name = dataargs.dataset_name; periodstr = dataargs.periodstr; avgfolder = dataargs.avgfolder
# load template dataset
stndata = stnfct() # load station dataset from function
if not isinstance(stndata, Dataset): raise TypeError
# N.B.: the loading function is necessary, because DataseNetCDF instances do not pickle well
# determine age of source file
if not loverwrite: sourceage = datetime.fromtimestamp(os.path.getmtime(filepath))
# get filename for target dataset and do some checks
filename = getTargetFile(stndata.name, dataset, mode, module, dataargs, lwrite)
if ldebug: filename = 'test_' + filename
if not os.path.exists(avgfolder): raise IOError, "Dataset folder '{:s}' does not exist!".format(avgfolder)
lskip = False # else just go ahead
if lwrite:
if lreturn:
tmpfilename = filename # no temporary file if dataset is passed on (can't rename the file while it is open!)
else:
if lparallel: tmppfx = 'tmp_exstns_{:s}_'.format(pidstr[1:-1])
else: tmppfx = 'tmp_exstns_'.format(pidstr[1:-1])
tmpfilename = tmppfx + filename
filepath = avgfolder + filename
tmpfilepath = avgfolder + tmpfilename
if os.path.exists(filepath):
if not loverwrite:
age = datetime.fromtimestamp(os.path.getmtime(filepath))
# if source file is newer than sink file or if sink file is a stub, recompute, otherwise skip
if age > sourceage and os.path.getsize(filepath) > 1e5: lskip = True
# N.B.: NetCDF files smaller than 100kB are usually incomplete header fragments from a previous crashed
if not lskip: os.remove(filepath) # recompute
# depending on last modification time of file or overwrite setting, start computation, or skip
if lskip:
# print message
skipmsg = "\n{:s} >>> Skipping: file '{:s}' in dataset '{:s}' already exists and is newer than source file.".format(pidstr,filename,dataset_name)
skipmsg += "\n{:s} >>> ('{:s}')\n".format(pidstr,filepath)
logger.info(skipmsg)
else:
## actually load datasets
source = loadfct() # load source
# check period
if 'period' in source.atts and dataargs.periodstr != source.atts.period: # a NetCDF attribute
raise DateError, "Specifed period is inconsistent with netcdf records: '{:s}' != '{:s}'".format(periodstr,source.atts.period)
# print message
if lclim: opmsgstr = "Extracting '{:s}'-type Point Data from Climatology ({:s})".format(stndata.name, periodstr)
elif lts: opmsgstr = "Extracting '{:s}'-type Point Data from Time-series".format(stndata.name)
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# print feedback to logger
logger.info('\n{0:s} *** {1:^65s} *** \n{0:s} *** {2:^65s} *** \n'.format(pidstr,datamsgstr,opmsgstr))
if not lparallel and ldebug: logger.info('\n'+str(source)+'\n')
## create new sink/target file
# set attributes
atts=source.atts.copy()
atts['period'] = dataargs.periodstr if dataargs.periodstr else 'time-series'
atts['name'] = dataset_name; atts['station'] = stndata.name
atts['title'] = '{:s} (Stations) from {:s} {:s}'.format(stndata.title,dataset_name,mode.title())
# make new dataset
if lwrite: # write to NetCDF file
if os.path.exists(tmpfilepath): os.remove(tmpfilepath) # remove old temp files
sink = DatasetNetCDF(folder=avgfolder, filelist=[tmpfilename], atts=atts, mode='w')
else: sink = Dataset(atts=atts) # ony create dataset in memory
# initialize processing
CPU = CentralProcessingUnit(source, sink, varlist=varlist, tmp=False, feedback=ldebug)
# extract data at station locations
CPU.Extract(template=stndata, flush=True)
# get results
CPU.sync(flush=True)
# print dataset
if not lparallel and ldebug:
logger.info('\n'+str(sink)+'\n')
# write results to file
if lwrite:
sink.sync()
writemsg = "\n{:s} >>> Writing to file '{:s}' in dataset {:s}".format(pidstr,filename,dataset_name)
writemsg += "\n{:s} >>> ('{:s}')\n".format(pidstr,filepath)
logger.info(writemsg)
# rename file to proper name
if not lreturn:
sink.unload(); sink.close(); del sink # destroy all references
if os.path.exists(filepath): os.remove(filepath) # remove old file
os.rename(tmpfilepath,filepath)
# N.B.: there is no temporary file if the dataset is returned, because an open file can't be renamed
# clean up and return
source.unload(); del source#, CPU
if lreturn:
return sink # return dataset for further use (netcdf file still open!)
else:
return 0 # "exit code"
def performRegridding(dataset,
mode,
griddef,
dataargs,
loverwrite=False,
varlist=None,
lwrite=True,
lreturn=False,
ldebug=False,
lparallel=False,
pidstr='',
logger=None):
''' worker function to perform regridding for a given dataset and target grid '''
# input checking
if not isinstance(dataset, basestring): raise TypeError
if not isinstance(dataargs, dict):
raise TypeError # all dataset arguments are kwargs
if not isinstance(griddef, GridDefinition): raise TypeError
if lparallel:
if not lwrite:
raise IOError, 'Can only write to disk in parallel mode (i.e. lwrite = True).'
if lreturn:
raise IOError, 'Can not return datasets in parallel mode (i.e. lreturn = False).'
# logging
if logger is None: # make new logger
logger = logging.getLogger() # new logger
logger.addHandler(logging.StreamHandler())
else:
if isinstance(logger, basestring):
logger = logging.getLogger(name=logger) # connect to existing one
elif not isinstance(logger, logging.Logger):
raise TypeError, 'Expected logger ID/handle in logger KW; got {}'.format(
str(logger))
## extract meta data from arguments
dataargs, loadfct, srcage, datamsgstr = getMetaData(
dataset, mode, dataargs)
dataset_name = dataargs.dataset_name
periodstr = dataargs.periodstr
avgfolder = dataargs.avgfolder
# get filename for target dataset and do some checks
filename = getTargetFile(
dataset=dataset,
mode=mode,
dataargs=dataargs,
lwrite=lwrite,
grid=griddef.name.lower(),
)
# prepare target dataset
if ldebug: filename = 'test_' + filename
if not os.path.exists(avgfolder):
raise IOError, "Dataset folder '{:s}' does not exist!".format(
avgfolder)
lskip = False # else just go ahead
if lwrite:
if lreturn:
tmpfilename = filename # no temporary file if dataset is passed on (can't rename the file while it is open!)
else:
if lparallel: tmppfx = 'tmp_regrid_{:s}_'.format(pidstr[1:-1])
else: tmppfx = 'tmp_regrid_'.format(pidstr[1:-1])
tmpfilename = tmppfx + filename
filepath = avgfolder + filename
tmpfilepath = avgfolder + tmpfilename
if os.path.exists(filepath):
if not loverwrite:
age = datetime.fromtimestamp(os.path.getmtime(filepath))
# if source file is newer than sink file or if sink file is a stub, recompute, otherwise skip
if age > srcage and os.path.getsize(filepath) > 1e6:
lskip = True
if hasattr(griddef,
'filepath') and griddef.filepath is not None:
gridage = datetime.fromtimestamp(
os.path.getmtime(griddef.filepath))
if age < gridage: lskip = False
# N.B.: NetCDF files smaller than 1MB are usually incomplete header fragments from a previous crashed
# depending on last modification time of file or overwrite setting, start computation, or skip
if lskip:
# print message
skipmsg = "\n{:s} >>> Skipping: file '{:s}' in dataset '{:s}' already exists and is newer than source file.".format(
pidstr, filename, dataset_name)
skipmsg += "\n{:s} >>> ('{:s}')\n".format(pidstr, filepath)
logger.info(skipmsg)
else:
## actually load datasets
source = loadfct() # load source
# check period
if 'period' in source.atts and dataargs.periodstr != source.atts.period: # a NetCDF attribute
raise DateError, "Specifed period is inconsistent with netcdf records: '{:s}' != '{:s}'".format(
periodstr, source.atts.period)
# print message
if mode == 'climatology':
opmsgstr = 'Regridding Climatology ({:s}) to {:s} Grid'.format(
periodstr, griddef.name)
elif mode == 'time-series':
opmsgstr = 'Regridding Time-series to {:s} Grid'.format(
griddef.name)
else:
raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# print feedback to logger
logger.info(
'\n{0:s} *** {1:^65s} *** \n{0:s} *** {2:^65s} *** \n'
.format(pidstr, datamsgstr, opmsgstr))
if not lparallel and ldebug: logger.info('\n' + str(source) + '\n')
## create new sink/target file
# set attributes
atts = source.atts.copy()
atts['period'] = periodstr
atts['name'] = dataset_name
atts['grid'] = griddef.name
if mode == 'climatology':
atts['title'] = '{:s} Climatology on {:s} Grid'.format(
dataset_name, griddef.name)
elif mode == 'time-series':
atts['title'] = '{:s} Time-series on {:s} Grid'.format(
dataset_name, griddef.name)
# make new dataset
if lwrite: # write to NetCDF file
if os.path.exists(tmpfilepath):
os.remove(tmpfilepath) # remove old temp files
sink = DatasetNetCDF(folder=avgfolder,
filelist=[tmpfilename],
atts=atts,
mode='w')
else:
sink = Dataset(atts=atts) # ony create dataset in memory
# initialize processing
CPU = CentralProcessingUnit(source,
sink,
varlist=varlist,
tmp=False,
feedback=ldebug)
# perform regridding (if target grid is different from native grid!)
if griddef.name != dataset:
# reproject and resample (regrid) dataset
CPU.Regrid(griddef=griddef, flush=True)
# get results
CPU.sync(flush=True)
# add geolocators
sink = addGeoLocator(sink,
griddef=griddef,
lgdal=True,
lreplace=True,
lcheck=True)
# N.B.: WRF datasets come with their own geolocator arrays - we need to replace those!
# add length and names of month
if mode == 'climatology' and not sink.hasVariable(
'length_of_month') and sink.hasVariable('time'):
addLengthAndNamesOfMonth(
sink,
noleap=True if dataset.upper() in ('WRF', 'CESM') else False)
# print dataset
if not lparallel and ldebug:
logger.info('\n' + str(sink) + '\n')
# write results to file
if lwrite:
sink.sync()
writemsg = "\n{:s} >>> Writing to file '{:s}' in dataset {:s}".format(
pidstr, filename, dataset_name)
writemsg += "\n{:s} >>> ('{:s}')\n".format(pidstr, filepath)
logger.info(writemsg)
# rename file to proper name
if not lreturn:
sink.unload()
sink.close()
del sink # destroy all references
if os.path.exists(filepath):
os.remove(filepath) # remove old file
os.rename(
tmpfilepath,
filepath) # this would also overwrite the old file...
# N.B.: there is no temporary file if the dataset is returned, because an open file can't be renamed
# clean up and return
source.unload()
del source, CPU
if lreturn:
return sink # return dataset for further use (netcdf file still open!)
else:
return 0 # "exit code"
def performExtraction(dataset,
mode,
stnfct,
dataargs,
loverwrite=False,
varlist=None,
lwrite=True,
lreturn=False,
ldebug=False,
lparallel=False,
pidstr='',
logger=None):
''' worker function to extract point data from gridded dataset '''
# input checking
if not isinstance(dataset, basestring): raise TypeError
if not isinstance(dataargs, dict):
raise TypeError # all dataset arguments are kwargs
if not callable(stnfct):
raise TypeError # function to load station dataset
if lparallel:
if not lwrite:
raise IOError, 'In parallel mode we can only write to disk (i.e. lwrite = True).'
if lreturn:
raise IOError, 'Can not return datasets in parallel mode (i.e. lreturn = False).'
# logging
if logger is None: # make new logger
logger = logging.getLogger() # new logger
logger.addHandler(logging.StreamHandler())
else:
if isinstance(logger, basestring):
logger = logging.getLogger(name=logger) # connect to existing one
elif not isinstance(logger, logging.Logger):
raise TypeError, 'Expected logger ID/handle in logger KW; got {}'.format(
str(logger))
lclim = False
lts = False
if mode == 'climatology': lclim = True
elif mode == 'time-series': lts = True
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
## extract meta data from arguments
dataargs, loadfct, srcage, datamsgstr = getMetaData(
dataset, mode, dataargs)
dataset_name = dataargs.dataset_name
periodstr = dataargs.periodstr
avgfolder = dataargs.avgfolder
# load template dataset
stndata = stnfct() # load station dataset from function
if not isinstance(stndata, Dataset): raise TypeError
# N.B.: the loading function is necessary, because DataseNetCDF instances do not pickle well
# get filename for target dataset and do some checks
filename = getTargetFile(dataset=dataset,
mode=mode,
dataargs=dataargs,
lwrite=lwrite,
station=stndata.name)
if ldebug: filename = 'test_' + filename
if not os.path.exists(avgfolder):
raise IOError, "Dataset folder '{:s}' does not exist!".format(
avgfolder)
lskip = False # else just go ahead
if lwrite:
if lreturn:
tmpfilename = filename # no temporary file if dataset is passed on (can't rename the file while it is open!)
else:
if lparallel: tmppfx = 'tmp_exstns_{:s}_'.format(pidstr[1:-1])
else: tmppfx = 'tmp_exstns_'.format(pidstr[1:-1])
tmpfilename = tmppfx + filename
filepath = avgfolder + filename
tmpfilepath = avgfolder + tmpfilename
if os.path.exists(filepath):
if not loverwrite:
age = datetime.fromtimestamp(os.path.getmtime(filepath))
# if source file is newer than sink file or if sink file is a stub, recompute, otherwise skip
if age > srcage and os.path.getsize(filepath) > 1e5:
lskip = True
# N.B.: NetCDF files smaller than 100kB are usually incomplete header fragments from a previous crashed
# depending on last modification time of file or overwrite setting, start computation, or skip
if lskip:
# print message
skipmsg = "\n{:s} >>> Skipping: file '{:s}' in dataset '{:s}' already exists and is newer than source file.".format(
pidstr, filename, dataset_name)
skipmsg += "\n{:s} >>> ('{:s}')\n".format(pidstr, filepath)
logger.info(skipmsg)
else:
## actually load datasets
source = loadfct() # load source
# check period
if 'period' in source.atts and dataargs.periodstr != source.atts.period: # a NetCDF attribute
raise DateError, "Specifed period is inconsistent with netcdf records: '{:s}' != '{:s}'".format(
periodstr, source.atts.period)
# print message
if lclim:
opmsgstr = "Extracting '{:s}'-type Point Data from Climatology ({:s})".format(
stndata.name, periodstr)
elif lts:
opmsgstr = "Extracting '{:s}'-type Point Data from Time-series".format(
stndata.name)
else:
raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# print feedback to logger
logger.info(
'\n{0:s} *** {1:^65s} *** \n{0:s} *** {2:^65s} *** \n'
.format(pidstr, datamsgstr, opmsgstr))
if not lparallel and ldebug: logger.info('\n' + str(source) + '\n')
## create new sink/target file
# set attributes
atts = source.atts.copy()
atts[
'period'] = dataargs.periodstr if dataargs.periodstr else 'time-series'
atts['name'] = dataset_name
atts['station'] = stndata.name
atts['title'] = '{:s} (Stations) from {:s} {:s}'.format(
stndata.title, dataset_name, mode.title())
# make new dataset
if lwrite: # write to NetCDF file
if os.path.exists(tmpfilepath):
os.remove(tmpfilepath) # remove old temp files
sink = DatasetNetCDF(folder=avgfolder,
filelist=[tmpfilename],
atts=atts,
mode='w')
else:
sink = Dataset(atts=atts) # ony create dataset in memory
# initialize processing
CPU = CentralProcessingUnit(source,
sink,
varlist=varlist,
tmp=False,
feedback=ldebug)
# extract data at station locations
CPU.Extract(template=stndata, flush=True)
# get results
CPU.sync(flush=True)
# print dataset
if not lparallel and ldebug:
logger.info('\n' + str(sink) + '\n')
# write results to file
if lwrite:
sink.sync()
writemsg = "\n{:s} >>> Writing to file '{:s}' in dataset {:s}".format(
pidstr, filename, dataset_name)
writemsg += "\n{:s} >>> ('{:s}')\n".format(pidstr, filepath)
logger.info(writemsg)
# rename file to proper name
if not lreturn:
sink.unload()
sink.close()
del sink # destroy all references
if os.path.exists(filepath):
os.remove(filepath) # remove old file
os.rename(tmpfilepath, filepath)
# N.B.: there is no temporary file if the dataset is returned, because an open file can't be renamed
# clean up and return
source.unload()
del source #, CPU
if lreturn:
return sink # return dataset for further use (netcdf file still open!)
else:
return 0 # "exit code"
def performRegridding(dataset, mode, griddef, dataargs, loverwrite=False, varlist=None, lwrite=True,
lreturn=False, ldebug=False, lparallel=False, pidstr='', logger=None):
''' worker function to perform regridding for a given dataset and target grid '''
# input checking
if not isinstance(dataset,basestring): raise TypeError
if not isinstance(dataargs,dict): raise TypeError # all dataset arguments are kwargs
if not isinstance(griddef,GridDefinition): raise TypeError
if lparallel:
if not lwrite: raise IOError, 'Can only write to disk in parallel mode (i.e. lwrite = True).'
if lreturn: raise IOError, 'Can not return datasets in parallel mode (i.e. lreturn = False).'
# logging
if logger is None: # make new logger
logger = logging.getLogger() # new logger
logger.addHandler(logging.StreamHandler())
else:
if isinstance(logger,basestring):
logger = logging.getLogger(name=logger) # connect to existing one
elif not isinstance(logger,logging.Logger):
raise TypeError, 'Expected logger ID/handle in logger KW; got {}'.format(str(logger))
## extract meta data from arguments
dataargs, loadfct, srcage, datamsgstr = getMetaData(dataset, mode, dataargs)
dataset_name = dataargs.dataset_name; periodstr = dataargs.periodstr; avgfolder = dataargs.avgfolder
# get filename for target dataset and do some checks
filename = getTargetFile(dataset=dataset, mode=mode, dataargs=dataargs, lwrite=lwrite,
grid=griddef.name.lower(), period=None, filetype=None)
# prepare target dataset
if ldebug: filename = 'test_' + filename
if not os.path.exists(avgfolder): raise IOError, "Dataset folder '{:s}' does not exist!".format(avgfolder)
lskip = False # else just go ahead
if lwrite:
if lreturn: tmpfilename = filename # no temporary file if dataset is passed on (can't rename the file while it is open!)
else:
if lparallel: tmppfx = 'tmp_regrid_{:s}_'.format(pidstr[1:-1])
else: tmppfx = 'tmp_regrid_'.format(pidstr[1:-1])
tmpfilename = tmppfx + filename
filepath = avgfolder + filename
tmpfilepath = avgfolder + tmpfilename
if os.path.exists(filepath):
if not loverwrite:
age = datetime.fromtimestamp(os.path.getmtime(filepath))
# if source file is newer than sink file or if sink file is a stub, recompute, otherwise skip
if age > srcage and os.path.getsize(filepath) > 1e6:
lskip = True
if hasattr(griddef, 'filepath') and griddef.filepath is not None:
gridage = datetime.fromtimestamp(os.path.getmtime(griddef.filepath))
if age < gridage: lskip = False
# N.B.: NetCDF files smaller than 1MB are usually incomplete header fragments from a previous crashed
if not lskip: os.remove(filepath) # recompute
# depending on last modification time of file or overwrite setting, start computation, or skip
if lskip:
# print message
skipmsg = "\n{:s} >>> Skipping: file '{:s}' in dataset '{:s}' already exists and is newer than source file.".format(pidstr,filename,dataset_name)
skipmsg += "\n{:s} >>> ('{:s}')\n".format(pidstr,filepath)
logger.info(skipmsg)
else:
## actually load datasets
source = loadfct() # load source
# check period
if 'period' in source.atts and dataargs.periodstr != source.atts.period: # a NetCDF attribute
raise DateError, "Specifed period is inconsistent with netcdf records: '{:s}' != '{:s}'".format(periodstr,source.atts.period)
# print message
if mode == 'climatology': opmsgstr = 'Regridding Climatology ({:s}) to {:s} Grid'.format(periodstr, griddef.name)
elif mode == 'time-series': opmsgstr = 'Regridding Time-series to {:s} Grid'.format(griddef.name)
else: raise NotImplementedError, "Unrecognized Mode: '{:s}'".format(mode)
# print feedback to logger
logger.info('\n{0:s} *** {1:^65s} *** \n{0:s} *** {2:^65s} *** \n'.format(pidstr,datamsgstr,opmsgstr))
if not lparallel and ldebug: logger.info('\n'+str(source)+'\n')
## create new sink/target file
# set attributes
atts=source.atts.copy()
atts['period'] = periodstr; atts['name'] = dataset_name; atts['grid'] = griddef.name
if mode == 'climatology': atts['title'] = '{:s} Climatology on {:s} Grid'.format(dataset_name, griddef.name)
elif mode == 'time-series': atts['title'] = '{:s} Time-series on {:s} Grid'.format(dataset_name, griddef.name)
# make new dataset
if lwrite: # write to NetCDF file
if os.path.exists(tmpfilepath): os.remove(tmpfilepath) # remove old temp files
sink = DatasetNetCDF(folder=avgfolder, filelist=[tmpfilename], atts=atts, mode='w')
else: sink = Dataset(atts=atts) # ony create dataset in memory
# initialize processing
CPU = CentralProcessingUnit(source, sink, varlist=varlist, tmp=False, feedback=ldebug)
# perform regridding (if target grid is different from native grid!)
if griddef.name != dataset:
# reproject and resample (regrid) dataset
CPU.Regrid(griddef=griddef, flush=True)
# get results
CPU.sync(flush=True)
# add geolocators
sink = addGeoLocator(sink, griddef=griddef, lgdal=True, lreplace=True, lcheck=True)
# N.B.: WRF datasets come with their own geolocator arrays - we need to replace those!
# add length and names of month
if mode == 'climatology' and not sink.hasVariable('length_of_month') and sink.hasVariable('time'):
addLengthAndNamesOfMonth(sink, noleap=True if dataset.upper() in ('WRF','CESM') else False)
# print dataset
if not lparallel and ldebug:
logger.info('\n'+str(sink)+'\n')
# write results to file
if lwrite:
sink.sync()
writemsg = "\n{:s} >>> Writing to file '{:s}' in dataset {:s}".format(pidstr,filename,dataset_name)
writemsg += "\n{:s} >>> ('{:s}')\n".format(pidstr,filepath)
logger.info(writemsg)
# rename file to proper name
if not lreturn:
sink.unload(); sink.close(); del sink # destroy all references
if os.path.exists(filepath): os.remove(filepath) # remove old file
os.rename(tmpfilepath,filepath) # this would also overwrite the old file...
# N.B.: there is no temporary file if the dataset is returned, because an open file can't be renamed
# clean up and return
source.unload(); del source, CPU
if lreturn:
return sink # return dataset for further use (netcdf file still open!)
else:
return 0 # "exit code"