def _insert_slice(self, current):
"""
Inserts one slice
:param Slice current: the slice to be imported
"""
current_exception = None
current_str = ""
for attempt in range(0, ConfigManager.retries):
try:
current_str = str(current)
file = self._generate_gml_slice(current)
subsets = self._get_update_subsets_for_slice(current)
request = WCSTUpdateRequest(self.coverage.coverage_id,
file.get_url(), subsets,
ConfigManager.insitu)
executor = ConfigManager.executor
executor.execute(request, mock=ConfigManager.mock)
file.release()
self.resumer.add_imported_data(current.data_provider)
except Exception as e:
log.warn(
"\nException thrown when trying to insert slice: \n" +
current_str +
"Retrying, you can safely ignore the warning for now. Tried "
+ str(attempt + 1) + " times.\n")
current_exception = e
sleep(ConfigManager.retry_sleep)
pass
else:
break
else:
log.warn("\nFailed to insert slice. Attempted " +
str(ConfigManager.retries) + " times.")
raise current_exception
def __load_imported_data_from_resume_file(self, coverage_id):
"""
Try to load a resume file coverage_id.resume.json from input data folder.
:param str coverage_id: coverage id of current importer to find the resume file.
"""
if coverage_id not in Resumer.__IMPORTED_DATA_DICT:
resume_file_path = ConfigManager.resumer_dir_path + coverage_id + Resumer.__RESUMER_FILE_SUFFIX
Resumer.__RESUMER_FILE_NAME_DICT[coverage_id] = resume_file_path
try:
if os.path.isfile(resume_file_path) \
and os.access(resume_file_path, os.R_OK):
log.info(
"We found a resumer file in the ingredients folder. The slices listed in '"
+ resume_file_path + "' will not be imported.")
file = open(Resumer.__RESUMER_FILE_NAME_DICT[coverage_id])
data = json.loads(file.read())
Resumer.__IMPORTED_DATA_DICT[coverage_id] = data
file.close()
except IOError as e:
raise RuntimeException(
"Could not read the resume file, full error message: " +
str(e))
except ValueError as e:
log.warn(
"The resumer JSON file could not be parsed. A new one will be created."
)
def _insert_slice(self, current):
"""
Inserts one slice
:param Slice current: the slice to be imported
"""
current_exception = None
current_str = ""
for attempt in range(0, ConfigManager.retries):
try:
current_str = str(current)
file = self._generate_gml_slice(current)
subsets = self._get_update_subsets_for_slice(current)
request = WCSTUpdateRequest(self.coverage.coverage_id, file.get_url(), subsets, ConfigManager.insitu)
executor = ConfigManager.executor
executor.execute(request)
file.release()
self.resumer.add_imported_data(current.data_provider)
except Exception as e:
log.warn(
"\nException thrown when trying to insert slice: \n" + current_str + "Retrying, you can safely ignore the warning for now. Tried " + str(
attempt + 1) + " times.\n")
current_exception = e
sleep(ConfigManager.retry_sleep)
pass
else:
break
else:
log.warn("\nFailed to insert slice. Attempted " + str(ConfigManager.retries) + " times.")
raise current_exception
def __init__(self, coverage_id):
"""
The resumer keeps track of data providers that have been imported so that a record is kept if several
runs are performed
:param str coverage_id: the id of the coverage that is imported
"""
if ConfigManager.track_files:
self.__RESUMER_FILE_NAME__ = ConfigManager.resumer_dir_path + coverage_id + self.__RESUMER_FILE_SUFFIX__
self.imported_data = []
try:
if os.path.isfile(self.__RESUMER_FILE_NAME__) and os.access(
self.__RESUMER_FILE_NAME__, os.R_OK):
log.info(
"We found a resumer file in the ingredients folder. The slices listed in "
+ str(self.__RESUMER_FILE_NAME__) +
" will not be imported.")
self.resume_fp = open(self.__RESUMER_FILE_NAME__)
self.imported_data = json.loads(self.resume_fp.read())
self.resume_fp.close()
except IOError as e:
raise RuntimeException(
"Could not read the resume file, full error message: " +
str(e))
except ValueError as e:
log.warn(
"The resumer JSON file could not be parsed. A new one will be created."
)
def __parse_netcdf_bands_metadata(self, user_bands):
"""
Parse the netCDF file to extract the bands' metadata for the coverage
:return: dict:
"""
netcdf_files = self.session.get_files()
file_path = netcdf_files[0].filepath
# NOTE: all files should have same bands's metadata for each file
netCDF4 = import_netcdf4()
dataset = netCDF4.Dataset(file_path, 'r')
bands_metadata = {}
for user_band in user_bands:
band_id = user_band.identifier
attrs_list = dataset.variables[band_id].ncattrs()
bands_metadata[band_id] = {}
for attr in attrs_list:
try:
bands_metadata[band_id][attr] = str(getattr(dataset.variables[band_id], attr))
except:
log.warn("Attribute '" + attr + "' of band '" + band_id + "' cannot be parsed as string, ignored.")
return bands_metadata
def parse_netcdf_bands_metadata(file_path, user_bands):
"""
Parse the netCDF file to extract the bands' metadata for the coverage's global metadata
str file_path: path to the first input netCDF file
list[UserBand] user_bands: list of configured bands in ingredient file
:return: dict:
"""
# NOTE: all files should have same bands's metadata for each file
netCDF4 = import_netcdf4()
dataset = netCDF4.Dataset(file_path, 'r')
bands_metadata = {}
for user_band in user_bands:
band_id = user_band.identifier
attrs_list = dataset.variables[band_id].ncattrs()
bands_metadata[band_id] = {}
for attr in attrs_list:
try:
bands_metadata[band_id][attr] = str(getattr(dataset.variables[band_id], attr))
except:
log.warn("Attribute '" + attr + "' of band '" + band_id + "' cannot be parsed as string, ignored.")
return bands_metadata
def _get_level(self, file_path):
if '_MSIL1C_' in file_path:
return self.LVL_L1C
elif '_MSIL2A_' in file_path:
return self.LVL_L2A
else:
log.warn("Cannot determine level from collected file: " + file_path + "; assuming L1C.")
return self.LVL_L1C
def diff_files(out, exp):
"""
Print diff of out and exp on stderr.
"""
outstr = read_lines(out)
expstr = read_lines(exp)
for line in difflib.unified_diff(outstr, expstr, fromfile=exp, tofile=out):
log.warn(line.strip())
def get_progress(self):
"""
Returns the progress of the import
:rtype: tuple
"""
if self.total == 0:
log.warn("No slices to import.")
return -1, -1
return self.processed, self.total
def get_progress(self):
"""
Returns the progress of the import
:rtype: tuple
"""
if self.total == 0:
log.warn("No slices to import.")
return -1, -1
return self.processed, self.total
def validate_input_file_paths(file_paths):
"""
If all input file paths are not available to analyze. Exit wcst_import process and log an warning.
:param list[str] file_paths: list of input file paths
"""
if len(file_paths) == 0:
log.warn(
"No files provided. Check that the paths you provided are correct. Done."
)
exit(0)
def validate(self):
"""
Check that the test case is valid, e.g. it must have an id. Return
True if valid, False otherwise.
"""
ret = True
if not self.testid:
log.warn("Testcase missing an id.")
ret = False
return ret
def log_crs_replacement_epsg_version_0_by_version_85():
"""
Just log a warning when it needs to replace version 0 to version 8.5 for EPSG
"""
log.warn(
"EPSG/0/NNNN points to the latest EPSG dictionary version, "
"so CRS definitions may change with new releases of the EPSG dataset. \n"
"In particular, coverage was created when latest EPSG "
"version was 8.5, which for longitude axis is now incompatible with the current "
"EPSG version ('Long' axis label changed to 'Lon').\n Therefore wcst_import will change "
"longitude axis label to 'Long' for EPSG/0/NNNN.")
def add_config_line(self, line):
if line.strip() == "" or line.startswith("#"):
return False
if not ':' in line:
log.warn(
"Invalid test case, expected line of "
"format 'key: value', but no ':' is found in:\n%s", line)
return False
kv = line.split(":", 1)
self.add_config(kv[0].strip(), kv[1].strip())
return True
def uncompress_directory(d):
"""
If directory d is not found, check for d.tar.gz and uncompress it if it exists.
"""
if os.path.exists(d):
return True
dtargz = remove_slash(d) + ".tar.gz"
if not os.path.exists(dtargz):
log.warn("Directory '%s' or corresponding archive '%s' not found.", d,
dtargz)
return False
with tarfile.open(dtargz, "r:gz") as tar:
tar.extractall()
def _insert_slices(self):
"""
Insert the slices of the coverage
"""
for i in range(self.processed, self.total):
try:
self._insert_slice(self.coverage.slices[i])
except Exception as e:
if ConfigManager.skip:
log.warn("Skipped slice " + str(self.coverage.slices[i]))
else:
raise e
self.processed += 1
def kill_pids(pids, sig):
"""
Kill the list of pids with the given signal.
"""
pids = pgrep("rasserver")
failed_pids = []
for pid in pids:
try:
os.kill(int(pid), sig)
except OSError as err:
log.warn("Failed killing rasserver process with pid %d: %s.", pid,
err.strerr)
failed_pids.append(pid)
return failed_pids
def parse_netcdf_axes_metadata(file_path, crs_axes_configured_dict):
"""
Parse the netCDF file to extract the axes metadata for the coverage's global metadata
str file_path: path to the first input netCDF file
dict crs_axes_configured_dict: dictionary of crs axis labels and themselves configuration in ingredient file
under "slicer"/"axes" section.
:return: dict:
"""
netCDF4 = import_netcdf4()
# NOTE: all files should have same axes's metadata for each file
dataset = netCDF4.Dataset(file_path, 'r')
axes_metadata = {}
# Iterate all slicer/axes configured in ingredient file
for crs_axis_label, axis_configured_dict in crs_axes_configured_dict.items(
):
min = axis_configured_dict["min"]
# Get the axis variable name in netCDF file from the min configuration
# e.g: "Long": { "min": "${netcdf:variable:lon:min}" } -> axis variable name is "lon"
variable_axis_label = None
# Find the variable axis label from netCDF expression for this axis
for key, value in axis_configured_dict.items():
tmp = re.search("variable:(.*):.*}", str(value))
if tmp is not None:
variable_axis_label = tmp.group(1)
break
if variable_axis_label is not None:
if variable_axis_label in dataset.variables:
axes_metadata[crs_axis_label] = {}
attrs_list = dataset.variables[
variable_axis_label].ncattrs()
for attr in attrs_list:
try:
# crs axis (e.g: Long) -> variable axis (e.g: lon)
axes_metadata[crs_axis_label][attr] = str(
getattr(dataset.variables[variable_axis_label],
attr))
except:
log.warn("Attribute '" + attr + "' of axis '" +
variable_axis_label +
"' cannot be parsed as string, ignored.")
return axes_metadata
def validate(self):
super(Recipe, self).validate()
valid_files = []
# Local validate for input files
for file in self.session.get_files():
file_name = os.path.basename(file.get_filepath())
if not bool(re.match(self.GRD_FILE_PATTERN, file_name)):
log.warn(
"File '" + file.get_filepath() +
"' is not valid GRD TIFF file, ignored for further processing."
)
else:
valid_files.append(file)
self.session.files = valid_files
def __run_shell_command(self, command, abort_on_error=False):
"""
Run a shell command and exit wcst_import if needed
:param str command: shell command to run
"""
try:
log.info("Executing shell command '{}'...".format(command))
output = subprocess.check_output(command, stderr=subprocess.STDOUT, shell=True)
output = decode_res(output)
if output != "":
log.info("Output result '{}'".format(output))
except subprocess.CalledProcessError as exc:
log.warn("Failed, status code '{}', error message '{}'.".format(exc.returncode, str(exc.output).strip()))
if abort_on_error:
log.error("wcst_import terminated on running hook command.")
exit(1)
def parse_netcdf_global_metadata(file_path):
"""
Parse the first file of importing netCDF files to extract the global metadata for the coverage
str file_path: path to first netCDF input file
:return: dict: global_metadata
"""
# NOTE: all files should have same global metadata for each file
netCDF4 = import_netcdf4()
dataset = netCDF4.Dataset(file_path, 'r')
global_metadata = {}
for attr in dataset.ncattrs():
try:
global_metadata[attr] = str(getattr(dataset, attr))
except:
log.warn("Attribute '" + attr + "' of global metadata cannot be parsed as string, ignored.")
return global_metadata
def cmp_files(out, exp, show_diff=False):
"""
Compare output file (out) to expected file (exp).
"""
if not os.path.isfile(exp):
log.warn(
"Expected file '%s' not found, will be copied from output '%s'.",
exp, out)
shutil.copyfile(out, exp)
return False
ret = filecmp.cmp(out, exp)
if not ret:
log.error("Output file '%s' does not match expected file '%s'.%s", out,
exp, " Diff:" if show_diff else "")
if show_diff:
diff_files(out, exp)
return ret
def main():
args = parse_cmdline()
global RMANHOME, RMANHOME_BIN
RMANHOME = args.rmanhome
if not RMANHOME:
log.warn(
"RMANHOME has not been set; consider specifying it with the --rmanhome option."
)
else:
RMANHOME = append_slash(RMANHOME)
RMANHOME_BIN = RMANHOME + "bin/"
RASQL[0] = RMANHOME_BIN + RASQL[0]
log.info("rasql: %s", RASQL)
log.title("Running rasql systemtest.")
# queries and oracles directory are quite big, so they are distributed
# as compressed archives, which potentially need to be uncompressed (for a first run)
for d in [QUERIES_DIR, ORACLES_DIR]:
uncompress_directory(d)
all_tests = None
if args.testsfile:
all_tests = [SETUP_TESTS, args.testsfile]
elif args.drop:
all_tests = []
else:
all_tests = [SETUP_TESTS] + sorted([QUERIES_DIR + f
for f in os.listdir(QUERIES_DIR) \
if not f in SPECIAL_FILES and
not f.endswith('.bak')])
all_tests = all_tests + [TEARDOWN_TESTS]
log.info("Tests files to execute: %s", all_tests)
# run tests
ret = True
start_time = timer()
for tests_file in all_tests:
ret = evaluate_existing_tests(tests_file) and ret
end_time = timer()
print_stats(end_time - start_time)
return ret
def parse_input(self, paths):
"""
Parses the list of paths and returns an ordered list of complete file paths
:param list[str] paths: the list of paths
:rtype list[File]
"""
file_paths = self.__get_file_paths(paths)
if len(file_paths) < len(paths):
log.warn(
"WARNING: The materialized paths contain less files than the initial paths. This can be normal if "
"a directory provided in the paths is empty or if a path regex returns no results. If this is not "
"the case, make sure the paths are correct and readable by the importer."
)
file_paths.sort()
file_obs = [File(f) for f in file_paths]
return file_obs
def get_valid_files(self):
"""
Valid file path could be opened by GDAL
files is list of files need to valid
"""
# Validate input files by GDAL. If GDAL could not decode file then will have an warning.
# GDAL needs file name encode in 'utf8' or file name with spaces could not open.
file_paths = []
for file in self.files:
fileName = str(file).encode('utf8')
check = gdal.Open(fileName)
if check is not None:
file_paths = file_paths + [file]
else:
log.warn("WARNING: File " + fileName + " is not is not a valid GDAL decodable file. The import process will ignore this file.\n")
return file_paths
def ignore_coverage_slice_from_file_if_possible(file_path, exception):
"""
In case, wcst_import cannot process 1 file due to some problem on it and "skip" is set to True,
wcst_import should not throw exception but log an warning to user.
:param str file_path: path to the problem file.
:param Exception exception: exception was thrown from previous statements.
"""
if ConfigManager.skip:
log.warn(
"WARNING: input file '" + file_path +
"' cannot be processed,\n"
"wcst_import will ignore this file as \"skip\" is set to true in the ingredient file. Reason: "
+ str(exception))
else:
# Throws the original source of exception(!)
type, val, tb = sys.exc_info()
raise type, val, tb
def restart_rasdaman_if_rasmgr_down():
"""
if rasmgr is down: kill all rasservers, and run start_rasdaman.sh again
"""
if len(pgrep("rasmgr")) == 0:
log.warn(
"rasmgr is down. Killing all rasservers, and starting rasdaman again."
)
pids = pgrep("rasserver")
not_killed = kill_pids(pids, signal.SIGTERM)
not_killed = kill_pids(not_killed, signal.SIGKILL)
if len(not_killed) == 0:
out, err, rc = execute(["start_rasdaman.sh"])
log.info(
"Started rasdaman\nexit code: %d\nstdout: %s\nstderr: %s\n",
rc, out, err)
return True
else:
log.error("Failed killing rasservers, cannot start rasdaman.")
return False
def parse_input(self, paths):
"""
Parses the list of paths and returns an ordered list of complete file paths
:param list[str] paths: the list of paths
:rtype list[File]
"""
file_paths = []
for path in paths:
path = path.strip()
if not path.startswith("/"):
path = self.ingredients_dir_path + path
file_paths = file_paths + glob.glob(path)
if len(file_paths) < len(paths):
log.warn("WARNING: The materialized paths contain less files than the initial paths. This can be normal if "
"a directory provided in the paths is empty or if a path regex returns no results. If this is not "
"the case, make sure the paths are correct and readable by the importer.")
file_paths.sort()
file_obs = map(lambda f: File(f), file_paths)
return file_obs
def __init__(self, coverage_id):
"""
The resumer keeps track of data providers that have been imported so that a record is kept if several
runs are performed
:param str coverage_id: the id of the coverage that is imported
"""
if ConfigManager.track_files:
self.__RESUMER_FILE_NAME__ = ConfigManager.resumer_dir_path + coverage_id + self.__RESUMER_FILE_SUFFIX__
self.imported_data = []
try:
if os.path.isfile(self.__RESUMER_FILE_NAME__) and os.access(self.__RESUMER_FILE_NAME__, os.R_OK):
log.info(
"We found a resumer file in the ingredients folder. The slices listed in " + str(
self.__RESUMER_FILE_NAME__) + " will not be imported.")
self.resume_fp = open(self.__RESUMER_FILE_NAME__)
self.imported_data = json.loads(self.resume_fp.read())
self.resume_fp.close()
except IOError as e:
raise RuntimeException("Could not read the resume file, full error message: " + str(e))
except ValueError as e:
log.warn("The resumer JSON file could not be parsed. A new one will be created.")
def interpret_result(ret, test, separator):
"""
Collect statistics, and log failed / known fails tests.
"""
global TOTAL_TESTS_COUNT, TOTAL_TESTS_IGNORED, TOTAL_QUERIES_COUNT, FAILED_TESTS
TOTAL_TESTS_COUNT += 1
TOTAL_QUERIES_COUNT += len(test.queries)
if test.skip:
log.warn("Test evaluation skipped, reason: %s", test.skip)
IGNORED_TESTS.append("{} (evaluation skipped, reason: {})".format(
test.testid, test.skip))
ret = True
elif not ret and test.knownfail:
log.warn("Test result ignored, reason: %s", test.knownfail)
IGNORED_TESTS.append("{} (result ignored, reason: {})".format(
test.testid, test.knownfail))
ret = True
elif ret and test.knownfail:
log.warn("Test marked as known fail has been fixed (%s)",
test.knownfail)
elif not ret:
FAILED_TESTS.append(test.testid)
log.info(separator)
return ret
def validate_file_path(file_path):
"""
Check if file exists, if not just log it and continue
:param file_path: path to an input file
:return: boolean
"""
# For gdal virtual file path, example:
# SENTINEL2_L1C:/vsizip//*_20181204T111726.zip/*_20181204T111726.SAFE/MTD_MSIL1C.xml:TCI:EPSG_32632
pattern = re.compile(".*/vsi[a-z]+/.*")
if pattern.match(file_path) or ":" in file_path:
# It is gdal virtual file system or subdataset (e.g: NETCDF:file_path:variable), just ignore
return True
elif not os.access(file_path, os.R_OK):
log.warn(
"File '" + file_path +
"' is not accessible, will be skipped from further processing."
)
return False
return True
def get_valid_files(self):
"""
Valid file path could be opened by GDAL
files is list of files need to valid
"""
# Validate input files by GDAL. If GDAL could not decode file then will have an warning.
# GDAL needs file name encode in 'utf8' or file name with spaces could not open.
file_paths = []
for file in self.files:
fileName = str(file).encode('utf8')
check = gdal.Open(fileName)
if check is not None:
file_paths = file_paths + [file]
else:
log.warn(
"WARNING: File " + fileName +
" is not is not a valid GDAL decodable file. The import process will ignore this file.\n"
)
return file_paths
def parse_input(self, paths):
"""
Parses the list of paths and returns an ordered list of complete file paths
:param list[str] paths: the list of paths
:rtype list[File]
"""
file_paths = []
for path in paths:
path = path.strip()
if not path.startswith("/"):
path = self.ingredients_dir_path + path
file_paths = file_paths + glob.glob(path)
if len(file_paths) < len(paths):
log.warn(
"WARNING: The materialized paths contain less files than the initial paths. This can be normal if "
"a directory provided in the paths is empty or if a path regex returns no results. If this is not "
"the case, make sure the paths are correct and readable by the importer."
)
file_paths.sort()
file_obs = map(lambda f: File(f), file_paths)
return file_obs
def __filter_invalid_geo_bounds(self, slices_dict):
"""
Filter any coverage slices (scenes) which have invalid lat and long bounds
in EPSG:4326
"""
results = OrderedDict()
for key, slices in slices_dict.items():
results[key] = []
for slice in slices:
input_file = slice.data_provider.file.filepath
axis_subsets = slice.axis_subsets
is_valid = True
for axis_subset in axis_subsets:
axis = axis_subset.coverage_axis.axis
geo_lower_bound = axis.low
geo_upper_bound = axis.high
axis_label = axis.label
if axis.crs_axis.uri.endswith(self.EPSG_4326):
if CRSUtil.is_latitude_axis(axis_label):
is_valid = geo_lower_bound >= -90 and geo_upper_bound <= 90
elif CRSUtil.is_longitude_axis(axis_label):
is_valid = geo_lower_bound >= -180 and geo_upper_bound <= 180
if not is_valid:
log.warn(
"File '" + input_file +
"' has invalid lat or long axes geo bounds in EPSG:4326 CRS, ignored for further processing."
)
break
if is_valid:
results[key].append(slice)
return results
def get_progress(self):
if self.total == 0:
log.warn("No slices to import.")
return -1, -1
else:
return self.processed, self.total
def _apply_operation(self, nc_dataset, nc_obj_name, operation):
"""
Applies operation on a given variable which contains a list of values (e.g: lat = [0, 1, 2, 3,...]),
(e.g: find the min of time variable ${netcdf:variable:time:min})
:param netCDF4 nc_dataset: the netcdf dataset
:param str nc_obj_name: name of netCDF variable or netCDF dimension
:param str operation: the operation to apply:
:return: str value: The value from the applied operation with precession
"""
""" NOTE: min or max of list(variable) with values like [148654.08425925925,...]
will return 148654.084259 in float which will cause problem with calculate coefficient as the first coeffcient should be 0
but due to this change of min/max value, the coefficient is like 0.00000000001 (case: PML)
"min": "${netcdf:variable:ansi:min} * 24 * 3600 - 11644560000.0", -> return: 1199152879.98
"directPositions": "[float(x) * 24 * 3600 - 11644560000.0 for x in ${netcdf:variable:ansi}]", -> return 1199152880.0
So we must use the values in the list by string and split it to a list to get the same values
"""
MAX = "max"
MIN = "min"
LAST = "last"
FIRST = "first"
RESOLUTION = "resolution"
METADATA = "metadata"
# List of support operation on a netCDF variable
supported_operations = [MAX, MIN, LAST, FIRST, RESOLUTION, METADATA]
import_util.import_numpy()
import numpy as np
if nc_obj_name in nc_dataset.variables:
nc_obj = nc_dataset.variables[nc_obj_name]
if operation not in supported_operations:
# it must be an attribute of variable
return nc_obj.__getattribute__(operation)
# It must be an operation that could be applied on a netCDF variable
# convert list of string values to list of decimal values
values = nc_obj[:].flatten()
elif nc_obj_name in nc_dataset.dimensions:
nc_obj = nc_dataset.dimensions[nc_obj_name]
# Cannot determine list of values from variable but only dimension (e.g: station = 758)
values = np.arange(0, nc_obj.size)
else:
raise Exception("Cannot find '" + nc_obj_name + "' from list of netCDF variables and dimensions.")
if operation == MAX:
return to_decimal(np.amax(values))
elif operation == MIN:
return to_decimal(np.amin(values))
elif operation == LAST:
last_index = len(nc_obj) - 1
return to_decimal(values[last_index])
elif operation == FIRST:
return to_decimal(values[0])
elif operation == RESOLUTION:
# NOTE: only netCDF needs this expression to calculate resolution automatically
# for GDAL: it uses: ${gdal:resolutionX} and GRIB: ${grib:jDirectionIncrementInDegrees} respectively
return self.__calculate_netcdf_resolution(values)
elif operation == METADATA:
# return a dict of variable (axis) metadata with keys, values as string
tmp_dict = {}
for attr in nc_obj.ncattrs():
try:
tmp_dict[attr] = escape(getattr(nc_obj, attr))
except:
log.warn("Attribute '" + attr + "' of variable '" + nc_obj._getname() + "' cannot be parsed as string, ignored.")
return tmp_dict
# Not supported operation and not valid attribute of netCDF variable
raise RuntimeException(
"Invalid operation on netcdf variable: " + operation
+ ". Currently supported: " + ', '.join(supported_operations) + " or any metadata entry of the variable.")
