def check_timeseries_id(self, dataset):
'''
Checks that if a variable exists for the time series id it has the appropriate attributes
:param netCDF4.Dataset dataset: An open netCDF dataset
'''
results = []
required_ctx = TestCtx(BaseCheck.HIGH, 'Required variable for time series identifier')
recommended_ctx = TestCtx(BaseCheck.MEDIUM, 'Recommended attributes for the timeSeries variable')
# A variable with cf_role="timeseries_id" MUST exist for this to be a valid timeseries incomplete
timeseries_ids = dataset.get_variables_by_attributes(cf_role='timeseries_id')
required_ctx.assert_true(timeseries_ids, 'a unique variable must define attribute cf_role="timeseries_id"')
results.append(required_ctx.to_result())
if not timeseries_ids:
return results
timevar = util.get_time_variable(dataset)
nc_timevar = dataset.variables[timevar]
time_dimensions = nc_timevar.dimensions
timeseries_variable = timeseries_ids[0]
dims = timeseries_variable.dimensions
required_ctx.assert_true(
time_dimensions and time_dimensions[0] == dims[0],
'{} must have a dimension and that dimension must be shared by the time variable'.format(timeseries_variable.name)
)
recommended_ctx.assert_true(
getattr(timeseries_variable, 'long_name', '') != "",
"long_name attribute should exist and not be empty"
)
results.append(recommended_ctx.to_result())
return results
def check_dimensions(self, dataset):
"""
Checks that the feature types of this dataset are consitent with a point dataset
"""
required_ctx = TestCtx(BaseCheck.HIGH, "All geophysical variables are point feature types")
t = util.get_time_variable(dataset)
# Exit prematurely
if not t:
required_ctx.assert_true(False, "A dimension representing time is required for point feature types")
return required_ctx.to_result()
t_dims = dataset.variables[t].dimensions
o = None or (t_dims and t_dims[0])
message = "{} must be a valid timeseries feature type. It must have dimensions of ({}), and all coordinates must have dimensions of ({})"
for variable in util.get_geophysical_variables(dataset):
is_valid = util.is_point(dataset, variable)
required_ctx.assert_true(is_valid, message.format(variable, o, o))
return required_ctx.to_result()
def check_timeseries_id(self, dataset):
'''
Checks that if a variable exists for the time series id it has the appropriate attributes
:param netCDF4.Dataset dataset: An open netCDF dataset
'''
results = []
required_ctx = TestCtx(BaseCheck.HIGH,
'Required variable for time series identifier')
recommended_ctx = TestCtx(
BaseCheck.MEDIUM,
'Recommended attributes for the timeSeries variable')
# A variable with cf_role="timeseries_id" MUST exist for this to be a valid timeseries incomplete
timeseries_ids = dataset.get_variables_by_attributes(
cf_role='timeseries_id')
required_ctx.assert_true(
timeseries_ids,
'a unique variable must define attribute cf_role="timeseries_id"')
results.append(required_ctx.to_result())
if not timeseries_ids:
return results
timevar = util.get_time_variable(dataset)
nc_timevar = dataset.variables[timevar]
time_dimensions = nc_timevar.dimensions
timeseries_variable = timeseries_ids[0]
dims = timeseries_variable.dimensions
required_ctx.assert_true(
time_dimensions and time_dimensions[0] == dims[0],
'{} must have a dimension and that dimension must be shared by the time variable'
.format(timeseries_variable.name))
recommended_ctx.assert_true(
getattr(timeseries_variable, 'long_name', '') != "",
"long_name attribute should exist and not be empty")
results.append(recommended_ctx.to_result())
return results
def check_dimensions(self, dataset):
'''
Checks that the feature types of this dataset are consitent with a point dataset
'''
required_ctx = TestCtx(
BaseCheck.HIGH,
'All geophysical variables are point feature types')
t = util.get_time_variable(dataset)
# Exit prematurely
if not t:
required_ctx.assert_true(
False,
'A dimension representing time is required for point feature types'
)
return required_ctx.to_result()
t_dims = dataset.variables[t].dimensions
o = None or (t_dims and t_dims[0])
message = '{} must be a valid timeseries feature type. It must have dimensions of ({}), and all coordinates must have dimensions of ({})'
for variable in util.get_geophysical_variables(dataset):
is_valid = util.is_point(dataset, variable)
required_ctx.assert_true(is_valid, message.format(variable, o, o))
return required_ctx.to_result()
