def _get_result(self, primary_arg):
ds = primary_arg
score = 0
messages = []
vocabs = ESSVocabs(*self.vocabulary_ref.split(":")[:2])
fname = os.path.basename(ds.filepath())
fn_score, msg = vocabs.check_file_name(fname, keys=self.kwargs["order"],
delimiter=self.kwargs["delimiter"],
extension=self.kwargs["extension"])
score += fn_score
if fn_score < (self.out_of / 3.):
# a third of the marks are for the file name check
messages.extend(msg)
# Check global attributes one-by-one
items = os.path.splitext(fname)[0].split(self.kwargs["delimiter"])
for i, attr in enumerate(self.kwargs["order"]):
if attr.startswith('regex:') or attr in self.kwargs["ignore_attr_checks"]:
# Case 1: we do not have the attribute name - so cannot check
# Case 2: instructed to not perform this check
continue
res, msg = vocabs.check_global_attribute_value(ds, attr, items[i],
property="raw_name")
score += res
if res < 2:
messages.extend(msg)
return Result(self.level, (score, self.out_of),
self.get_short_name(), messages)
def _get_result(self, primary_arg):
ds = primary_arg
score = 0
self.out_of = 1
messages = []
vocabs = ESSVocabs(*self.vocabulary_ref.split(":")[:2])
var_id = self.kwargs["var_id"]
if var_id in ds.variables:
array = ds[var_id][:]
result = vocabs.check_array_matches_terms(
array, self.kwargs["pyessv_namespace"])
if result:
score += 1
else:
messages.append(self.get_messages()[score])
else:
messages.append(
"Variable '{}' not found in the file so cannot perform other checks."
.format(var_id))
return Result(self.level, (score, self.out_of), self.get_short_name(),
messages)
def _get_result(self, primary_arg):
ds = primary_arg
var_id = self.kwargs["var_id"]
messages = []
score = 0
# Check the variable exists first
if var_id not in ds.variables:
messages = [self.get_messages()[score]]
return Result(self.level, (score, self.out_of),
self.get_short_name(), messages)
score += 1
vocabs = ESSVocabs(*self.vocabulary_ref.split(":")[:2])
expected_values = vocabs.get_value("coordinate:{}".format(var_id),
"data")["value"]
actual_values = ds.variables[var_id][:]
# Cast to a list if not iterable
if not hasattr(actual_values, "__len__"):
actual_values = [actual_values]
if list(expected_values) == list(actual_values):
score += 1
else:
messages = [self.get_messages()[score]]
return Result(self.level, (score, self.out_of), self.get_short_name(),
messages)
def _get_result(self, primary_arg):
ds = primary_arg
var_id = self.kwargs["var_id"]
messages = []
score = 0
# Check the variable exists first
if var_id not in ds.variables:
messages = [self.get_messages()[score]]
return Result(self.level, (score, self.out_of),
self.get_short_name(), messages)
score += 1
vocabs = ESSVocabs(*self.vocabulary_ref.split(":")[:2])
expected_length = vocabs.get_value("coordinate:{}".format(var_id),
"data")["length"]
actual_length = len(ds.variables[var_id][:])
if expected_length == actual_length:
score += 1
else:
messages = [self.get_messages()[score]]
return Result(self.level, (score, self.out_of), self.get_short_name(),
messages)
def _get_result(self, primary_arg):
ds = primary_arg
score = 0
var_id = self._get_var_id(ds)
# Check the variable first (will match if `var_id` is None from previous call)
if var_id not in ds.variables:
messages = self.get_messages()[:1]
return Result(self.level, (score, self.out_of),
self.get_short_name(), messages)
# Work out the overall 'out of' value based on number of attributes
vocabs = ESSVocabs(*self.vocabulary_ref.split(":")[:2])
lookup = ":".join([self.kwargs["pyessv_namespace"], var_id])
expected_attr_dict = vocabs.get_value(lookup, "data")
self.out_of = 1 + len(expected_attr_dict) * 2
score += 1
variable = ds.variables[var_id]
messages = []
# Check the variable attributes one-by-one
for attr, expected_value in expected_attr_dict.items():
# Check items to ignore
ignores = self.kwargs["ignores"]
if ignores and attr in ignores:
self.out_of -= 2
continue
KNOWN_IGNORE_VALUES = ("<derived from file>",)
if expected_value in KNOWN_IGNORE_VALUES:
self.out_of -= 2
continue
if attr not in variable.ncattrs():
messages.append("Required variable attribute '{}' is not present for "
"variable: '{}'.".format(attr, var_id))
else:
score += 1
# Check the value of attribute
check = nc_util.check_nc_attribute(variable, attr, expected_value)
if check:
score += 1
else:
messages.append(u"Required variable attribute '{}' has incorrect value ('{}') "
u"for variable: '{}'. Value should be: '{}'.".format(attr,
getattr(variable, attr), var_id,
expected_value))
return Result(self.level, (score, self.out_of),
self.get_short_name(), messages)
def _get_result(self, primary_arg):
ds = primary_arg
vocabs = ESSVocabs(*self.vocabulary_ref.split(":")[:2])
score = vocabs.check_global_attribute(ds, self.kwargs["attribute"], vocab_lookup=self.kwargs["vocab_lookup"])
messages = []
if score < self.out_of:
messages.append(self.get_messages()[score])
return Result(self.level, (score, self.out_of),
self.get_short_name(), messages)
def _get_result(self, primary_arg):
ds = primary_arg
dim_id = self.kwargs["dim_id"]
ignore_coord_var_check = util._parse_boolean(self.kwargs["ignore_coord_var_check"])
score = 0
messages = []
if dim_id in ds.dimensions:
score += 1
self.out_of = 1
else:
messages = [self.get_messages()[score],
"Cannot look up coordinate variable because dimension does not exist.",
"Cannot assess coordinate variable properties because dimension does not exist."]
self.out_of = len(messages)
# Now return because all other checks are irrelevant
return Result(self.level, (score, self.out_of), self.get_short_name(), messages)
# Now test coordinate variable using look-up in vocabularies
# First, work out the overall 'out of' value based on number of attributes
vocabs = ESSVocabs(*self.vocabulary_ref.split(":")[:2])
lookup = ":".join([self.kwargs["pyessv_namespace"], dim_id])
expected_attr_dict = vocabs.get_value(lookup, "data")
# Check length if needed
if "length" in expected_attr_dict:
req_length = expected_attr_dict["length"]
# If expected length is <i> or <n> etc then dimension length does
# not matter, so give +1 without checking
skip_check = req_length.startswith("<") and req_length.endswith(">")
if skip_check or int(req_length) == ds.dimensions[dim_id].size:
score += 1
else:
messages.append("Dimension '{}' does not have required length: {}.".format(dim_id, req_length))
self.out_of += 1
# Ignore coordinate variable check if instructed to
if ignore_coord_var_check:
pass
# Check coordinate variable exists for dimension
elif dim_id in ds.variables:
score += 1
self.out_of += 1
variable = ds.variables[dim_id]
# Check the coordinate variable attributes one-by-one
for attr, expected_value in expected_attr_dict.items():
# Length has already been checked - so ignore here
if attr == "length": continue
self.out_of += 1
if attr not in variable.ncattrs():
messages.append("Required variable attribute '{}' is not present for "
"coorinate variable: '{}'.".format(attr, dim_id))
else:
score += 1
self.out_of += 1
# Check the value of attribute
check = nc_util.check_nc_attribute(variable, attr, expected_value)
if check:
score += 1
else:
messages.append("Required variable attribute '{}' has incorrect value ('{}') "
"for variable: '{}'. Value should be: '{}'.".format(attr,
getattr(variable, attr), dim_id, expected_value))
# If coordinate variable not found
else:
messages.append("Coordinate variable for dimension not found: {}.".format(dim_id))
self.out_of += 1
return Result(self.level, (score, self.out_of), self.get_short_name(), messages)