def create_netcdf(self, storage_indices, data_descriptor):
'''
Function to create netCDF-CF file for specified storage indices
'''
temp_storage_path = self.get_temp_storage_path(storage_indices)
storage_path = self.get_storage_path(self.storage_type, storage_indices)
make_dir(os.path.dirname(storage_path))
if self.dryrun:
return storage_path
if os.path.isfile(storage_path) and not self.force:
logger.warning('Skipping existing storage unit %s' % storage_path)
return
# return storage_path #TODO: Remove this temporary debugging hack
t_indices = np.array([dt2secs(record_dict['end_datetime']) for record_dict in data_descriptor])
gdfnetcdf = GDFNetCDF(storage_config=self.storage_config[self.storage_type])
logger.debug('Creating temporary storage unit %s with %d timeslices', temp_storage_path, len(data_descriptor))
gdfnetcdf.create(netcdf_filename=temp_storage_path,
index_tuple=storage_indices,
dimension_index_dict={'T': t_indices}, netcdf_format=None)
del t_indices
# Set georeferencing from first or second tile for fault tolerance
try:
gdfnetcdf.georeference_from_file(data_descriptor[0]['tile_pathname'])
except:
gdfnetcdf.georeference_from_file(data_descriptor[1]['tile_pathname'])
variable_dict = self.storage_config[self.storage_type]['measurement_types']
variable_names = variable_dict.keys()
array_shape = tuple([len(variable_dict)] +
[dim['dimension_elements']
for dim in self.storage_config[self.storage_type]['dimensions'].values()
if dim['indexing_type'] == 'regular']
)
# All data types and no-data values should be the same - just use first one
array_dtype = variable_dict[variable_dict.keys()[0]]['numpy_datatype_name']
nodata_value = variable_dict[variable_dict.keys()[0]]['nodata_value']
if nodata_value is None:
nodata_value = np.nan
slice_index = 0
for record_dict in data_descriptor:
try:
tile_dataset = gdal.Open(record_dict['tile_pathname'])
assert tile_dataset, 'Failed to open tile file %s' % record_dict['tile_pathname']
logger.debug('Reading array data from tile file %s (%d/%d)', record_dict['tile_pathname'], slice_index + 1, len(data_descriptor))
data_array = tile_dataset.ReadAsArray()
assert data_array.shape == array_shape, 'Tile array shape is not %s' % array_shape
except Exception, e:
# Can't read data_array from GeoTIFF - create empty data_array instead
logger.warning('WARNING: Unable to read array from tile - empty array created: %s', e.message)
data_array = np.ones(array_shape, array_dtype) * nodata_value
logger.debug('data_array.shape = %s', data_array.shape)
#TODO: Set up proper mapping between AGDC & GDF bands so this works with non-contiguous ranges
for variable_index in range(len(variable_dict)):
variable_name = variable_names[variable_index]
logger.debug('Writing array to variable %s', variable_name)
if len(data_array.shape) == 3:
gdfnetcdf.write_slice(variable_name, data_array[variable_index], {'T': slice_index})
elif len(data_array.shape) == 2:
gdfnetcdf.write_slice(variable_name, data_array, {'T': slice_index})
gdfnetcdf.sync() # Write cached data to disk
slice_index += 1
def create_netcdf(self, storage_indices, data_descriptor):
'''
Function to create netCDF-CF file for specified storage indices
'''
temp_storage_path = self.get_temp_storage_path(storage_indices)
storage_path = self.get_storage_path(self.storage_type,
storage_indices)
make_dir(os.path.dirname(storage_path))
if self.dryrun:
return storage_path
if os.path.isfile(storage_path) and not self.force:
logger.warning('Skipping existing storage unit %s' % storage_path)
return
# return storage_path #TODO: Remove this temporary debugging hack
t_indices = np.array([
dt2secs(record_dict['end_datetime'])
for record_dict in data_descriptor
])
gdfnetcdf = GDFNetCDF(
storage_config=self.storage_config[self.storage_type])
logger.debug('Creating temporary storage unit %s with %d timeslices',
temp_storage_path, len(data_descriptor))
gdfnetcdf.create(netcdf_filename=temp_storage_path,
index_tuple=storage_indices,
dimension_index_dict={'T': t_indices},
netcdf_format=None)
del t_indices
# Set georeferencing from first or second tile for fault tolerance
try:
gdfnetcdf.georeference_from_file(
data_descriptor[0]['tile_pathname'])
except:
gdfnetcdf.georeference_from_file(
data_descriptor[1]['tile_pathname'])
variable_dict = self.storage_config[
self.storage_type]['measurement_types']
variable_names = variable_dict.keys()
array_shape = tuple([len(variable_dict)] + [
dim['dimension_elements']
for dim in self.storage_config[self.storage_type]
['dimensions'].values() if dim['indexing_type'] == 'regular'
])
# All data types and no-data values should be the same - just use first one
array_dtype = variable_dict[variable_dict.keys()
[0]]['numpy_datatype_name']
nodata_value = variable_dict[variable_dict.keys()[0]]['nodata_value']
if nodata_value is None:
nodata_value = np.nan
slice_index = 0
for record_dict in data_descriptor:
try:
tile_dataset = gdal.Open(record_dict['tile_pathname'])
assert tile_dataset, 'Failed to open tile file %s' % record_dict[
'tile_pathname']
logger.debug('Reading array data from tile file %s (%d/%d)',
record_dict['tile_pathname'], slice_index + 1,
len(data_descriptor))
data_array = tile_dataset.ReadAsArray()
assert data_array.shape == array_shape, 'Tile array shape is not %s' % array_shape
except Exception, e:
# Can't read data_array from GeoTIFF - create empty data_array instead
logger.warning(
'WARNING: Unable to read array from tile - empty array created: %s',
e.message)
data_array = np.ones(array_shape, array_dtype) * nodata_value
logger.debug('data_array.shape = %s', data_array.shape)
#TODO: Set up proper mapping between AGDC & GDF bands so this works with non-contiguous ranges
for variable_index in range(len(variable_dict)):
variable_name = variable_names[variable_index]
logger.debug('Writing array to variable %s', variable_name)
if len(data_array.shape) == 3:
gdfnetcdf.write_slice(variable_name,
data_array[variable_index],
{'T': slice_index})
elif len(data_array.shape) == 2:
gdfnetcdf.write_slice(variable_name, data_array,
{'T': slice_index})
gdfnetcdf.sync() # Write cached data to disk
slice_index += 1
def create_netcdf(self, storage_indices, data_descriptor):
'''
Function to create netCDF-CF file for specified storage indices
'''
temp_storage_path = self.get_temp_storage_path(storage_indices)
storage_path = self.get_storage_path(self.storage_type, storage_indices)
make_dir(os.path.dirname(storage_path))
if self.dryrun:
return storage_path
if os.path.isfile(storage_path) and not self.force:
logger.warning('Skipping existing storage unit %s' % storage_path)
return
# return storage_path #TODO: Remove this temporary debugging hack
t_indices = np.array([dt2secs(record_dict['end_datetime']) for record_dict in data_descriptor])
gdfnetcdf = GDFNetCDF(storage_config=self.storage_config[self.storage_type])
logger.debug('Creating temporary storage unit %s with %d timeslices', temp_storage_path, len(data_descriptor))
gdfnetcdf.create(netcdf_filename=temp_storage_path,
index_tuple=storage_indices,
dimension_index_dict={'T': t_indices}, netcdf_format=None)
del t_indices
# Set georeferencing from first tile
gdfnetcdf.georeference_from_file(data_descriptor[0]['tile_pathname'])
variable_dict = self.storage_config[self.storage_type]['measurement_types']
variable_names = variable_dict.keys()
slice_index = 0
for record_dict in data_descriptor:
tile_dataset = gdal.Open(record_dict['tile_pathname'])
assert tile_dataset, 'Failed to open tile file %s' % record_dict['tile_pathname']
logger.debug('Reading array data from tile file %s (%d/%d)', record_dict['tile_pathname'], slice_index + 1, len(data_descriptor))
data_array = tile_dataset.ReadAsArray()
logger.debug('data_array.shape = %s', data_array.shape)
#TODO: Set up proper mapping between AGDC & GDF bands so this works with non-contiguous ranges
for variable_index in range(len(variable_dict)):
variable_name = variable_names[variable_index]
logger.debug('Writing array to variable %s', variable_name)
if len(data_array.shape) == 3:
gdfnetcdf.write_slice(variable_name, data_array[variable_index], {'T': slice_index})
elif len(data_array.shape) == 2:
gdfnetcdf.write_slice(variable_name, data_array, {'T': slice_index})
gdfnetcdf.sync() # Write cached data to disk
slice_index += 1
del gdfnetcdf # Close the netCDF
logger.debug('Moving temporary storage unit %s to %s', temp_storage_path, storage_path)
if os.path.isfile(storage_path):
logger.debug('Removing existing storage unit %s' % storage_path)
os.remove(storage_path)
shutil.move(temp_storage_path, storage_path)
return storage_path
def create_netcdf(self, storage_indices, data_descriptor):
'''
Function to create netCDF-CF file for specified storage indices
'''
temp_storage_path = self.get_temp_storage_path(storage_indices)
storage_path = self.get_storage_path(self.storage_type,
storage_indices)
make_dir(os.path.dirname(storage_path))
if self.dryrun:
return storage_path
if os.path.isfile(storage_path) and not self.force:
logger.warning('Skipping existing storage unit %s' % storage_path)
return
# return storage_path #TODO: Remove this temporary debugging hack
t_indices = np.array([
dt2secs(record_dict['end_datetime'])
for record_dict in data_descriptor
])
gdfnetcdf = GDFNetCDF(
storage_config=self.storage_config[self.storage_type])
logger.debug('Creating temporary storage unit %s with %d timeslices',
temp_storage_path, len(data_descriptor))
gdfnetcdf.create(netcdf_filename=temp_storage_path,
index_tuple=storage_indices,
dimension_index_dict={'T': t_indices},
netcdf_format=None)
del t_indices
# Set georeferencing from first tile
gdfnetcdf.georeference_from_file(data_descriptor[0]['tile_pathname'])
variable_dict = self.storage_config[
self.storage_type]['measurement_types']
variable_names = variable_dict.keys()
slice_index = 0
for record_dict in data_descriptor:
tile_dataset = gdal.Open(record_dict['tile_pathname'])
assert tile_dataset, 'Failed to open tile file %s' % record_dict[
'tile_pathname']
logger.debug('Reading array data from tile file %s (%d/%d)',
record_dict['tile_pathname'], slice_index + 1,
len(data_descriptor))
data_array = tile_dataset.ReadAsArray()
logger.debug('data_array.shape = %s', data_array.shape)
#TODO: Set up proper mapping between AGDC & GDF bands so this works with non-contiguous ranges
for variable_index in range(len(variable_dict)):
variable_name = variable_names[variable_index]
logger.debug('Writing array to variable %s', variable_name)
if len(data_array.shape) == 3:
gdfnetcdf.write_slice(variable_name,
data_array[variable_index],
{'T': slice_index})
elif len(data_array.shape) == 2:
gdfnetcdf.write_slice(variable_name, data_array,
{'T': slice_index})
gdfnetcdf.sync() # Write cached data to disk
slice_index += 1
del gdfnetcdf # Close the netCDF
logger.debug('Moving temporary storage unit %s to %s',
temp_storage_path, storage_path)
if os.path.isfile(storage_path):
logger.debug('Removing existing storage unit %s' % storage_path)
os.remove(storage_path)
shutil.move(temp_storage_path, storage_path)
return storage_path
