def exportDataset(self, dataset): ''' method to export a Dataset instance to NetCDF format and write to disk ''' # create NetCDF file filepath = self.filepath writeNetCDF(dataset=dataset, ncfile=filepath, **self.export_arguments) # check first and last if not os.path.exists(filepath): raise IOError, filepath
def exportDataset(self, dataset): ''' method to export a Dataset instance to NetCDF format and write to disk ''' # create NetCDF file filepath = self.filepath writeNetCDF(dataset=dataset, ncfile=filepath, **self.export_arguments) # check first and last if not os.path.exists(filepath): raise IOError, filepath
def writeNetCDF(self, filename=None, folder=None, ncformat='NETCDF4', zlib=True, writeData=True, close=False, flush=False):
''' Write current temporary storage to a NetCDF file. '''
if self.tmp:
if not isinstance(filename,basestring): raise TypeError
if folder is not None: filename = folder + filename
output = writeNetCDF(self.tmpput, filename, ncformat=ncformat, zlib=zlib, writeData=writeData, close=False)
if flush: self.tmpput.unload()
if self.feedback: print('\nOutput written to {0:s}\n'.format(filename))
else:
self.output.sync()
output = self.output.dataset # get (primary) NetCDF file
if self.feedback: print('\nSynchronized dataset {0:s} with temporary storage.\n'.format(output.name))
# flush?
if flush: self.output.unload()
# close file or return file handle
if close: output.close()
else: return output
dataset.atts.resolution = res
# load data into memory
dataset.load()
# add landmask
addLandMask(dataset) # create landmask from precip mask
dataset.mask(dataset.landmask) # mask all fields using the new landmask
# add length and names of month
addLengthAndNamesOfMonth(dataset, noleap=False)
# figure out a different filename
filename = getFileName(grid=res, period=None, name='GPCC', filepattern=avgfile)
print('\n'+filename+'\n')
if os.path.exists(avgfolder+filename): os.remove(avgfolder+filename)
# write data and some annotation
ncset = writeNetCDF(dataset, avgfolder+filename, close=False)
# add_var(ncset,'name_of_month', name_of_month, 'time', # add names of month
# atts=dict(name='name_of_month', units='', long_name='Name of the Month'))
# close...
ncset.close()
dataset.close()
# print dataset before
print(dataset)
print('')
elif mode == 'average_timeseries':
# load source
dataset.title = 'NARR Long-term Climatology'
# load data into memory
dataset.load()
# # add landmask
# addLandMask(dataset) # create landmask from precip mask
# dataset.mask(dataset.landmask) # mask all fields using the new landmask
# add length and names of month
addLengthAndNamesOfMonth(dataset, noleap=False)
# figure out a different filename
filename = getFileName(grid='NARR', period=None, name='NARR', filepattern=avgfile)
print('\n'+filename+'\n')
if os.path.exists(avgfolder+filename): os.remove(avgfolder+filename)
# write data and some annotation
ncset = writeNetCDF(dataset, avgfolder+filename, close=False)
add_strvar(ncset,'name_of_month', name_of_month, 'time', # add names of month
atts=dict(name='name_of_month', units='', long_name='Name of the Month'))
# close...
ncset.close()
dataset.close()
# print dataset before
print(dataset)
print('')
# generate averaged climatology
elif mode == 'average_timeseries':
# load source
