def adjust_spatial_attrs(ds: xr.Dataset, allow_point: bool = False) -> xr.Dataset:
"""
Adjust the global spatial attributes of the dataset by doing some
introspection of the dataset and adjusting the appropriate attributes
accordingly.
In case the determined attributes do not exist in the dataset, these will
be added.
For more information on suggested global attributes see
`Attribute Convention for Data Discovery <http://wiki.esipfed.org/index.php/Attribute_Convention_for_Data_Discovery>`_
:param ds: Dataset to adjust
:param allow_point: Whether a dataset containing a single point is allowed
:return: Adjusted dataset
"""
return adjust_spatial_attrs_impl(ds, allow_point=allow_point)
def adjust_spatial_attrs(ds: xr.Dataset, allow_point: bool = False) -> xr.Dataset:
"""
Adjust the global spatial attributes of the dataset by doing some
introspection of the dataset and adjusting the appropriate attributes
accordingly.
In case the determined attributes do not exist in the dataset, these will
be added.
For more information on suggested global attributes see
`Attribute Convention for Data Discovery <http://wiki.esipfed.org/index.php/Attribute_Convention_for_Data_Discovery>`_
:param ds: Dataset to adjust
:param allow_point: Whether a dataset containing a single point is allowed
:return: Adjusted dataset
"""
return adjust_spatial_attrs_impl(ds, allow_point=allow_point)
def _make_local(self,
local_ds: 'LocalDataSource',
time_range: TimeRangeLike.TYPE = None,
region: PolygonLike.TYPE = None,
var_names: VarNamesLike.TYPE = None,
monitor: Monitor = Monitor.NONE):
local_id = local_ds.id
time_range = TimeRangeLike.convert(time_range) if time_range else None
var_names = VarNamesLike.convert(
var_names) if var_names else None # type: Sequence
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL',
NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
encoding_update = dict()
if compression_enabled:
encoding_update.update({
'zlib': True,
'complevel': compression_level
})
local_path = os.path.join(local_ds.data_store.data_store_path,
local_id)
data_store_path = local_ds.data_store.data_store_path
if not os.path.exists(local_path):
os.makedirs(local_path)
monitor.start("Sync " + self.id, total_work=len(self._files.items()))
for remote_relative_filepath, coverage in self._files.items():
child_monitor = monitor.child(work=1)
file_name = os.path.basename(remote_relative_filepath)
local_relative_filepath = os.path.join(local_id, file_name)
local_absolute_filepath = os.path.join(data_store_path,
local_relative_filepath)
remote_absolute_filepath = os.path.join(
self._data_store.data_store_path, remote_relative_filepath)
if isinstance(coverage, Tuple):
time_coverage_start = coverage[0]
time_coverage_end = coverage[1]
if not time_range or time_coverage_start >= time_range[
0] and time_coverage_end <= time_range[1]:
if region or var_names:
do_update_of_variables_meta_info_once = True
do_update_of_region_meta_info_once = True
try:
remote_dataset = xr.open_dataset(
remote_absolute_filepath)
if var_names:
remote_dataset = remote_dataset.drop([
var_name for var_name in
remote_dataset.data_vars.keys()
if var_name not in var_names
])
if region:
remote_dataset = normalize_impl(remote_dataset)
remote_dataset = adjust_spatial_attrs_impl(
subset_spatial_impl(
remote_dataset, region),
allow_point=False)
if do_update_of_region_meta_info_once:
# subset_spatial_impl
local_ds.meta_info[
'bbox_maxx'] = remote_dataset.attrs[
'geospatial_lon_max']
local_ds.meta_info[
'bbox_minx'] = remote_dataset.attrs[
'geospatial_lon_min']
local_ds.meta_info[
'bbox_maxy'] = remote_dataset.attrs[
'geospatial_lat_max']
local_ds.meta_info[
'bbox_miny'] = remote_dataset.attrs[
'geospatial_lat_min']
do_update_of_region_meta_info_once = False
if compression_enabled:
for sel_var_name in remote_dataset.variables.keys(
):
remote_dataset.variables.get(
sel_var_name).encoding.update(
encoding_update)
remote_dataset.to_netcdf(local_absolute_filepath)
child_monitor.progress(
work=1, msg=str(time_coverage_start))
finally:
if do_update_of_variables_meta_info_once:
variables_info = local_ds.meta_info.get(
'variables', [])
local_ds.meta_info['variables'] = [
var_info for var_info in variables_info
if var_info.get('name') in remote_dataset.
variables.keys() and var_info.get('name')
not in remote_dataset.dims.keys()
]
do_update_of_variables_meta_info_once = False
local_ds.add_dataset(
os.path.join(local_id, file_name),
(time_coverage_start, time_coverage_end))
child_monitor.done()
else:
shutil.copy(remote_absolute_filepath,
local_absolute_filepath)
local_ds.add_dataset(
local_relative_filepath,
(time_coverage_start, time_coverage_end))
child_monitor.done()
monitor.done()
return local_id
def _make_local(self,
local_ds: LocalDataSource,
time_range: TimeRangeLike.TYPE = None,
region: PolygonLike.TYPE = None,
var_names: VarNamesLike.TYPE = None,
monitor: Monitor = Monitor.NONE):
local_id = local_ds.id
time_range = TimeRangeLike.convert(time_range)
var_names = VarNamesLike.convert(var_names)
excluded_variables = get_exclude_variables_fix_known_issues(self.id)
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL', NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
do_update_of_verified_time_coverage_start_once = True
verified_time_coverage_start = None
verified_time_coverage_end = None
encoding_update = dict()
if compression_enabled:
encoding_update.update({'zlib': True, 'complevel': compression_level})
if region or var_names:
protocol = _ODP_PROTOCOL_OPENDAP
else:
protocol = _ODP_PROTOCOL_HTTP
local_path = os.path.join(local_ds.data_store.data_store_path, local_id)
if not os.path.exists(local_path):
os.makedirs(local_path)
selected_file_list = self._find_files(time_range)
if not selected_file_list:
msg = 'CCI Open Data Portal data source "{}"\ndoes not seem to have any datasets'.format(self.id)
if time_range is not None:
msg += ' in given time range {}'.format(TimeRangeLike.format(time_range))
raise DataAccessError(msg)
try:
if protocol == _ODP_PROTOCOL_OPENDAP:
do_update_of_variables_meta_info_once = True
do_update_of_region_meta_info_once = True
files = self._get_urls_list(selected_file_list, protocol)
monitor.start('Sync ' + self.id, total_work=len(files))
for idx, dataset_uri in enumerate(files):
child_monitor = monitor.child(work=1)
file_name = os.path.basename(dataset_uri)
local_filepath = os.path.join(local_path, file_name)
time_coverage_start = selected_file_list[idx][1]
time_coverage_end = selected_file_list[idx][2]
child_monitor.start(label=file_name, total_work=1)
remote_dataset = xr.open_dataset(dataset_uri, drop_variables=[variable.get('name') for variable in
excluded_variables])
if var_names:
remote_dataset = remote_dataset.drop([var_name for var_name in remote_dataset.data_vars.keys()
if var_name not in var_names])
if region:
remote_dataset = normalize_impl(remote_dataset)
remote_dataset = adjust_spatial_attrs_impl(subset_spatial_impl(remote_dataset, region),
allow_point=False)
if do_update_of_region_meta_info_once:
local_ds.meta_info['bbox_minx'] = remote_dataset.attrs['geospatial_lon_min']
local_ds.meta_info['bbox_maxx'] = remote_dataset.attrs['geospatial_lon_max']
local_ds.meta_info['bbox_maxy'] = remote_dataset.attrs['geospatial_lat_max']
local_ds.meta_info['bbox_miny'] = remote_dataset.attrs['geospatial_lat_min']
do_update_of_region_meta_info_once = False
if compression_enabled:
for sel_var_name in remote_dataset.variables.keys():
remote_dataset.variables.get(sel_var_name).encoding.update(encoding_update)
remote_dataset.to_netcdf(local_filepath)
child_monitor.progress(work=1, msg=str(time_coverage_start))
if do_update_of_variables_meta_info_once:
variables_info = local_ds.meta_info.get('variables', [])
local_ds.meta_info['variables'] = [var_info for var_info in variables_info
if var_info.get('name')
in remote_dataset.variables.keys() and
var_info.get('name')
not in remote_dataset.dims.keys()]
do_update_of_variables_meta_info_once = False
local_ds.add_dataset(os.path.join(local_id, file_name),
(time_coverage_start, time_coverage_end))
if do_update_of_verified_time_coverage_start_once:
verified_time_coverage_start = time_coverage_start
do_update_of_verified_time_coverage_start_once = False
verified_time_coverage_end = time_coverage_end
child_monitor.done()
else:
outdated_file_list = []
for file_rec in selected_file_list:
filename, _, _, file_size, url = file_rec
dataset_file = os.path.join(local_path, filename)
# todo (forman, 20160915): must perform better checks on dataset_file if it is...
# ... outdated or incomplete or corrupted.
# JSON also includes "checksum" and "checksum_type" fields.
if not os.path.isfile(dataset_file) or (file_size and os.path.getsize(dataset_file) != file_size):
outdated_file_list.append(file_rec)
if outdated_file_list:
with monitor.starting('Sync ' + self.id, len(outdated_file_list)):
bytes_to_download = sum([file_rec[3] for file_rec in outdated_file_list])
dl_stat = _DownloadStatistics(bytes_to_download)
file_number = 1
for filename, coverage_from, coverage_to, file_size, url in outdated_file_list:
dataset_file = os.path.join(local_path, filename)
sub_monitor = monitor.child(work=1.0)
# noinspection PyUnusedLocal
def reporthook(block_number, read_size, total_file_size):
dl_stat.handle_chunk(read_size)
sub_monitor.progress(work=read_size, msg=str(dl_stat))
sub_monitor_msg = "file %d of %d" % (file_number, len(outdated_file_list))
with sub_monitor.starting(sub_monitor_msg, file_size):
urllib.request.urlretrieve(url[protocol], filename=dataset_file, reporthook=reporthook)
file_number += 1
local_ds.add_dataset(os.path.join(local_id, filename), (coverage_from, coverage_to))
if do_update_of_verified_time_coverage_start_once:
verified_time_coverage_start = coverage_from
do_update_of_verified_time_coverage_start_once = False
verified_time_coverage_end = coverage_to
except (OSError, ValueError) as e:
raise DataAccessError("Copying remote data source failed: {}".format(e), source=self) from e
local_ds.meta_info['temporal_coverage_start'] = TimeLike.format(verified_time_coverage_start)
local_ds.meta_info['temporal_coverage_end'] = TimeLike.format(verified_time_coverage_end)
local_ds.meta_info['exclude_variables'] = excluded_variables
local_ds.save(True)
def _make_local(self,
local_ds: 'LocalDataSource',
time_range: TimeRangeLike.TYPE = None,
region: PolygonLike.TYPE = None,
var_names: VarNamesLike.TYPE = None,
monitor: Monitor = Monitor.NONE):
local_id = local_ds.id
time_range = TimeRangeLike.convert(time_range) if time_range else None
var_names = VarNamesLike.convert(var_names) if var_names else None # type: Sequence
compression_level = get_config_value('NETCDF_COMPRESSION_LEVEL', NETCDF_COMPRESSION_LEVEL)
compression_enabled = True if compression_level > 0 else False
encoding_update = dict()
if compression_enabled:
encoding_update.update({'zlib': True, 'complevel': compression_level})
local_path = os.path.join(local_ds.data_store.data_store_path, local_id)
data_store_path = local_ds.data_store.data_store_path
if not os.path.exists(local_path):
os.makedirs(local_path)
monitor.start("Sync " + self.id, total_work=len(self._files.items()))
for remote_relative_filepath, coverage in self._files.items():
child_monitor = monitor.child(work=1)
file_name = os.path.basename(remote_relative_filepath)
local_relative_filepath = os.path.join(local_id, file_name)
local_absolute_filepath = os.path.join(data_store_path, local_relative_filepath)
remote_absolute_filepath = os.path.join(self._data_store.data_store_path, remote_relative_filepath)
if isinstance(coverage, Tuple):
time_coverage_start = coverage[0]
time_coverage_end = coverage[1]
if not time_range or time_coverage_start >= time_range[0] and time_coverage_end <= time_range[1]:
if region or var_names:
do_update_of_variables_meta_info_once = True
do_update_of_region_meta_info_once = True
remote_dataset = None
try:
remote_dataset = xr.open_dataset(remote_absolute_filepath)
if var_names:
remote_dataset = remote_dataset.drop(
[var_name for var_name in remote_dataset.data_vars.keys()
if var_name not in var_names])
if region:
remote_dataset = normalize_impl(remote_dataset)
remote_dataset = adjust_spatial_attrs_impl(subset_spatial_impl(remote_dataset, region),
allow_point=False)
if do_update_of_region_meta_info_once:
# subset_spatial_impl
local_ds.meta_info['bbox_maxx'] = remote_dataset.attrs['geospatial_lon_max']
local_ds.meta_info['bbox_minx'] = remote_dataset.attrs['geospatial_lon_min']
local_ds.meta_info['bbox_maxy'] = remote_dataset.attrs['geospatial_lat_max']
local_ds.meta_info['bbox_miny'] = remote_dataset.attrs['geospatial_lat_min']
do_update_of_region_meta_info_once = False
if compression_enabled:
for sel_var_name in remote_dataset.variables.keys():
remote_dataset.variables.get(sel_var_name).encoding.update(encoding_update)
remote_dataset.to_netcdf(local_absolute_filepath)
child_monitor.progress(work=1, msg=str(time_coverage_start))
finally:
if do_update_of_variables_meta_info_once and remote_dataset is not None:
variables_info = local_ds.meta_info.get('variables', [])
local_ds.meta_info['variables'] = [var_info for var_info in variables_info
if var_info.get('name')
in remote_dataset.variables.keys()
and var_info.get('name')
not in remote_dataset.dims.keys()]
# noinspection PyUnusedLocal
do_update_of_variables_meta_info_once = False
local_ds.add_dataset(os.path.join(local_id, file_name),
(time_coverage_start, time_coverage_end))
child_monitor.done()
else:
shutil.copy(remote_absolute_filepath, local_absolute_filepath)
local_ds.add_dataset(local_relative_filepath, (time_coverage_start, time_coverage_end))
child_monitor.done()
monitor.done()
return local_id
