def create_variable(self,output,var,years,months):
#Recover time axis for all files:
self.obtain_table()
queryable_file_types_available=list(set(self.table['file_type']).intersection(queryable_file_types))
if len(self.table['paths'])>0:
if len(queryable_file_types_available)>0:
#Open the first file and use its metadata to populate container file:
first_id=list(self.table['file_type']).index(queryable_file_types_available[0])
remote_data=remote_netcdf.remote_netCDF(self.table['paths'][first_id],self.table['file_type'][first_id],self.semaphores)
#try:
remote_data.open_with_error()
netcdf_utils.replicate_netcdf_file(output,remote_data.Dataset)
else:
remote_data=remote_netcdf.remote_netCDF(self.table['paths'][0],self.table['file_type'][0],self.semaphores)
#Convert time axis to numbers and find the unique time axis:
self.unique_time_axis(remote_data.Dataset,years,months)
self.reduce_paths_ordering()
#Create time axis in ouptut:
netcdf_utils.create_time_axis_date(output,remote_data.Dataset,self.time_axis_unique_date)
self.create(output)
#if len(queryable_file_types_available)>0:
self.record_indices(output,remote_data.Dataset,var)
#except dodsError as e:
# e_mod=" This is an uncommon error. It is likely to be FATAL."
# print e.value+e_mod
remote_data.close()
output.sync()
return
def replicate(self, output, hdf5=None, check_empty=False):
#replicate attributes
netcdf_utils.replicate_netcdf_file(output, self.data_root)
#replicate and copy variables:
for var_name in self.data_root.variables.keys():
netcdf_utils.replicate_and_copy_variable(output,
self.data_root,
var_name,
hdf5=hdf5,
check_empty=check_empty)
if 'soft_links' in self.data_root.groups.keys():
output_grp = netcdf_utils.replicate_group(output, self.data_root,
'soft_links')
netcdf_utils.replicate_netcdf_file(
output_grp, self.data_root.groups['soft_links'])
for var_name in self.data_root.groups['soft_links'].variables.keys(
):
if hdf5 != None:
netcdf_utils.replicate_and_copy_variable(
output_grp,
self.data_root.groups['soft_links'],
var_name,
hdf5=hdf5['soft_links'],
check_empty=check_empty)
else:
netcdf_utils.replicate_and_copy_variable(
output_grp,
self.data_root.groups['soft_links'],
var_name,
check_empty=check_empty)
return
def record_to_file(output_root,output,output_hdf5):
netcdf_utils.replicate_netcdf_file(output_root,output)
#netcdf_utils.replicate_full_netcdf_recursive(output_root,output,check_empty=True)
netcdf_utils.replicate_full_netcdf_recursive(output_root,output,check_empty=False,hdf5=output_hdf5)
#netcdf_utils.replicate_full_netcdf_recursive(output_root,output,check_empty=True,hdf5=output_hdf5)
return
