def _insert_record(vname_map, nc_var, record, scalars_handled, count,
linked_index):
""" Inserts data into a netcdf variable
Parameters:
vname_map : dict
A dict extracted from the database containing metadata on this
particular variable.
nc_var : NetCDFVariable
The NetCDF variable object.
record : BUFRRecordEntry
The BUFR data from the bufr reader.
scalars_handled : bool
Defines whether variables that should be considdered as
constants / scalars are handled
count : int
Defines in which entry in the NetCDF running variable this
data should be inserted. This should be a continously
increasing variable.
"""
try:
# pack data if possible
packable_1dim = int(vname_map[linked_index]['packable_1dim'])
packable_2dim = int(vname_map[linked_index]['packable_2dim'])
var_type = vname_map[linked_index]['var_type']
if var_type not in ['int', 'float', 'str', 'double', 'long']:
logger.error("No valid type defined")
return
# Handle 32/64 numpy conversion
if 'int' in var_type and not packable_2dim:
var_type = 'int32'
try:
#
# Handle cases where the data can be packed into a single value or
# a single row or single column
# Data packs to a single value
if packable_2dim and packable_1dim:
if not scalars_handled:
data = bufr.pack_record(record)
try:
nc_var[0] = eval(var_type)(data)
except OverflowError, overflow_error:
logger.exception("Unable to convert "+\
"value for %s in %s" %\
( data, vname_map[linked_index]['netcdf_name']))
nc_var[ 0 ] = vname_map[linked_index]\
['netcdf__FillValue']
return
# Data packs to a single row
elif packable_1dim:
if not scalars_handled:
size = vname_map[ linked_index ]\
[ 'netcdf_dimension_length' ]
data = record.data
if data.shape[0] < size:
fillvalue = vname_map[ linked_index ]\
[ 'netcdf__FillValue' ]
data = bufr.pad_record(data, size, fillvalue)
elif data.shape[0] > size:
raise BUFR2NetCDFError("Size mismatch netcdf "+\
"variable expected size is"+\
" %d, data size is %d" % (size,
data.shape[0]) )
nc_var[:] = data
return
# Data packes to a single column
elif packable_2dim:
data = bufr.pack_record(record)
try:
nc_var[count] = eval(var_type)(data)
except OverflowError, overflow_error:
logger.exception("Unable to convert value for %s in %s" %\
( data, vname_map[linked_index]['netcdf_name']))
nc_var[ count ] = vname_map[linked_index]\
['netcdf__FillValue']
def _insert_record(vname_map, nc_var, record, scalars_handled, count, linked_index):
""" Inserts data into a netcdf variable
Parameters:
vname_map : dict
A dict extracted from the database containing metadata on this
particular variable.
nc_var : NetCDFVariable
The NetCDF variable object.
record : BUFRRecordEntry
The BUFR data from the bufr reader.
scalars_handled : bool
Defines whether variables that should be considdered as
constants / scalars are handled
count : int
Defines in which entry in the NetCDF running variable this
data should be inserted. This should be a continously
increasing variable.
"""
try:
# pack data if possible
packable_1dim = int(vname_map[linked_index]['packable_1dim'])
packable_2dim = int(vname_map[linked_index]['packable_2dim'])
var_type = vname_map[linked_index]['var_type']
if var_type not in ['int', 'float', 'str',
'double', 'long']:
logger.error("No valid type defined")
return
# Handle 32/64 numpy conversion
if 'int' in var_type and not packable_2dim:
var_type = 'int32'
try:
#
# Handle cases where the data can be packed into a single value or
# a single row or single column
# Data packs to a single value
if packable_2dim and packable_1dim:
if not scalars_handled:
data = bufr.pack_record(record)
try:
nc_var[ 0 ] = eval(var_type)(data)
except OverflowError, overflow_error:
logger.exception("Unable to convert "+\
"value for %s in %s" %\
( data, vname_map[linked_index]['netcdf_name']))
nc_var[ 0 ] = vname_map[linked_index]\
['netcdf__FillValue']
return
# Data packs to a single row
elif packable_1dim:
if not scalars_handled:
size = vname_map[ linked_index ]\
[ 'netcdf_dimension_length' ]
data = record.data
if data.shape[ 0 ] < size:
fillvalue = vname_map[ linked_index ]\
[ 'netcdf__FillValue' ]
data = bufr.pad_record(data, size, fillvalue)
elif data.shape[0] > size:
raise BUFR2NetCDFError("Size mismatch netcdf "+\
"variable expected size is"+\
" %d, data size is %d" % (size,
data.shape[0]) )
nc_var[:] = data
return
# Data packes to a single column
elif packable_2dim:
data = bufr.pack_record(record)
try:
nc_var[ count ] = eval(var_type)(data)
except OverflowError, overflow_error:
logger.exception("Unable to convert value for %s in %s" %\
( data, vname_map[linked_index]['netcdf_name']))
nc_var[ count ] = vname_map[linked_index]\
['netcdf__FillValue']
def _insert_record(vname_map, nc_var, record, scalars_handled, count):
""" Insert record in netcdf variables
"""
try:
# pack data if possible
packable_1dim = int(vname_map[record.index]['packable_1dim'])
packable_2dim = int(vname_map[record.index]['packable_2dim'])
var_type = vname_map[record.index]['var_type']
if var_type not in ['int', 'float', 'str',
'double', 'long']:
print "no valid type defined"
return
# Handle 32/64 numpy conversion
if 'int' in var_type and not packable_2dim:
var_type = 'int32'
try:
if packable_2dim and packable_1dim:
if not scalars_handled:
data = bufr.pack_record(record)
try:
nc_var[ 0 ] = eval(var_type)(data)
except OverflowError, overflow_error:
traceback.print_exc(file=sys.stdout)
print data
print nc_var
nc_var[ 0 ] = vname_map[record.index]\
['netcdf__FillValue']
return
elif packable_1dim:
if not scalars_handled:
size = vname_map[ record.index ]\
[ 'netcdf_dimension_length' ]
data = record.data
if data.shape[ 0 ] < size:
fillvalue = vname_map[ record.index ]\
[ 'netcdf__FillValue' ]
data = bufr.pad_record(data, size, fillvalue)
elif data.shape[0] > size:
raise BUFR2NetCDFError("Size mismatch netcdf variable"+\
" expected size is %d, data size is %d" %\
(size, data.shape[0]) )
nc_var[:] = data
return
elif packable_2dim:
data = bufr.pack_record(record)
try:
nc_var[ count ] = eval(var_type)(data)
except OverflowError, overflow_error:
traceback.print_exc(file=sys.stdout)
print data
print nc_var
nc_var[ count ] = vname_map[record.index]\
['netcdf__FillValue']