Add dummy function for getting lat,lon (preparation for mllam#33)

mllam_data_prep/derived_variables.py

@@ -38,19 +38,25 @@ def derive_variables(fp, derived_variables, chunking):
     ds_subset = xr.Dataset()
     ds_subset.attrs.update(ds.attrs)
     for _, derived_variable in derived_variables.items():
-        required_variables = derived_variable.kwargs
+        required_kwargs = derived_variable.kwargs
         function_name = derived_variable.function
         derived_variable_attributes = derived_variable.attributes or {}
-        ds_input = ds[required_variables.keys()]
+
+        # Separate the lat,lon from the required variables as these will be derived separately
+        latlon_coords_to_include = {}
+        for k, v in list(required_kwargs.items()):
+            if k in ["lat", "lon"]:
+                latlon_coords_to_include[k] = required_kwargs.pop(k)
+
+        # Subset the dataset
+        ds_input = ds[required_kwargs.keys()]
 
         # Any coordinates needed for the derivation, for which chunking should be performed,
-        # should be converted to variables since it is not possible for coordinates to be
-        # chunked dask arrays
+        # should be converted to variables since it is not possible for *indexed* coordinates
+        # to be chunked dask arrays
         chunks = {d: chunking.get(d, int(ds_input[d].count())) for d in ds_input.dims}
         required_coordinates = [
-            req_var
-            for req_var in required_variables.keys()
-            if req_var in ds_input.coords
+            req_var for req_var in required_kwargs.keys() if req_var in ds_input.coords
         ]
         ds_input = ds_input.drop_indexes(required_coordinates, errors="ignore")
         for req_coord in required_coordinates:
@@ -60,9 +66,15 @@ def derive_variables(fp, derived_variables, chunking):
         # Chunk the data variables
         ds_input = ds_input.chunk(chunks)
 
-        # Calculate the derived variable
-        kwargs = {v: ds_input[k] for k, v in required_variables.items()}
+        # Add function arguments to kwargs
+        kwargs = {}
+        if len(latlon_coords_to_include):
+            latlon = get_latlon_coords_for_input(ds)
+            for k, v in latlon_coords_to_include.items():
+                kwargs[v] = latlon[k]
+        kwargs.update({v: ds_input[k] for k, v in required_kwargs.items()})
         func = _get_derived_variable_function(function_name)
+        # Calculate the derived variable
         derived_field = func(**kwargs)
 
         # Check the derived field(s)
@@ -408,3 +420,8 @@ def cyclic_encoding(data_array, da_max):
     data_array_cos = np.cos((data_array / da_max) * 2 * np.pi)
 
     return data_array_cos, data_array_sin
+
+
+def get_latlon_coords_for_input(ds_input):
+    """Dummy function for getting lat and lon."""
+    return ds_input[["lat", "lon"]].chunk(-1, -1)