consider using cf_xarray

[dcherian]

I saw your tweet and this looks like a cool project.

cf_xarray should help you remove the CF parsing code, it's intended to allow indexing by standard_name etc. I'd be happy to consider changes that would make its use in this project easier.

[juseg]

Thank you for passing by here and bringing this up! It seems like something I should be using indeed.

[juseg]

Closing this as done (for one year actually). Hyoga will use cf_xarray from the next release v0.1.2. However, the code still relies on internal method getvar for some heuristics, e.g. computing a vector magnitude from its components, or glacier surface altitude as bedrock altitude plus ice thickness.

hyoga/hyoga/hyoga.py

Lines 231 to 304 in 7e735f9

	def getvar(self, standard_name, infer=True, directions=None):
	"""Get a variable by conventional standard name.
	Parameters
	----------
	standard_name : str
	The variable's "standard_name" attribute, which in principle
	should be set according to netCDF Climate and Forecast (CF)
	conventions (http://cfconventions.org/standard-names.html).
	infer : bool
	Try to infer missing variables from others present in the dataset.
	If one of the topographic variables ("bedrock_altitude",
	"land_ice_thickness", and "surface_altitude") is requested and
	missing from the data, try to compute it from the other two.
	If a variable name starting with "magnitude_of" is requested and
	missing, try to compute it as the norm of its components.
	directions : iterable
	Allowed direction keywords for computing vector magnitudes.
	Defaults to ("upward", "downward", "x", "y"). Computing magnitudes
	on a sphere is not supported and thus longitude and latitude
	directions ("northward", "southward", "eastward", "westward")
	are not included by default.
	Returns
	-------
	array : DataArray
	The data array corresponding to that variable if a unique variable
	with that standard name has been found.
	"""
	# if variable is present, return it
	if standard_name in self._ds.cf:
	return self._ds.cf[standard_name]
	# no variable found, try to compute it from other variables
	if infer is True:
	# try to get ice mask from ice thickness
	# FIXME make threshold configurable
	if standard_name == 'land_ice_area_fraction':
	return (self.getvar('land_ice_thickness') > 0).astype(
	float).assign_attrs(standard_name=standard_name)
	# try to compute altitude and thickness variables
	# (infer=False is needed to avoid infinite recursion)
	if standard_name == 'bedrock_altitude':
	return self._safe_sub(
	'surface_altitude', 'land_ice_thickness', infer=False
	).assign_attrs(standard_name=standard_name)
	if standard_name == 'land_ice_thickness':
	return self._safe_sub(
	'surface_altitude', 'bedrock_altitude', infer=False
	).assign_attrs(standard_name=standard_name)
	if standard_name == 'surface_altitude':
	return self._safe_sum(
	'bedrock_altitude', 'land_ice_thickness', infer=False
	).assign_attrs(standard_name=standard_name)
	# try to get the magnitude of a vector from its components
	if standard_name.startswith('magnitude_of_'):
	vector = standard_name.replace('magnitude_of_', '', 1)
	directions = directions or ('upward', 'downward', 'x', 'y')
	components = [
	var.attrs['standard_name'] for var in self._ds.values() if
	vector in [
	var.attrs.get('standard_name', '').replace('_'+d, '')
	for d in directions]]
	if len(components) > 0:
	return self._safe_mag(*components).assign_attrs(
	standard_name=standard_name)
	# really nothing worked, give up
	raise ValueError(
	f"No variable found with standard name {standard_name}.")

[dcherian]

Good to hear!