RFF documentation

Author: Kit Schwarz

dscim/utils/rff.py

@@ -14,16 +14,28 @@ def clean_simulation(
     draw,
     root,
 ):
+    """
+    Clean the weights csvs generated by the RFF emulator.
+    This produces a file of the weights.
+
+    Parameters
+    ----------
+    draw : int, weight draw
+    root : str, root directory
+    """
+
     ds = pd.read_csv(
         f"{root}/emulate-fivebean-{draw}.csv",
         skiprows=9,
     )
 
+    # cleaning columns
     for i, name in enumerate(["model", "ssp"]):
         ds[name] = ds["name"].str.split("/", expand=True)[i]
     for i, name in enumerate(["year", "model"]):
         ds[name] = ds["model"].str.split(":", expand=True)[i]
 
+    # dropping error rows and keeping only weights rows
     ds = ds.loc[ds.param != "error"]
 
     ds["model"] = ds.model.replace({"low": "IIASA GDP", "high": "OECD Env-Growth"})
@@ -41,15 +53,26 @@ def clean_error(
     draw,
     root,
 ):
+    """
+    Clean the weights csvs generated by the RFF emulator.
+    This produces a file of the errors (for diagnostics).
+
+    Parameters
+    ----------
+    draw : int, weight draw
+    root : str, root directory
+    """
 
     ds = pd.read_csv(
         f"{root}/emulate-fivebean-{draw}.csv",
         skiprows=9,
     )
 
+    # cleaning columns
     for i, name in enumerate(["iso", "year"]):
         ds[name] = ds["name"].str.split(":", expand=True)[i]
 
+    # dropping weights rows and keeping only error rows
     ds = ds.loc[ds.param == "error"]
 
     ds["rff_sp"] = draw
@@ -76,6 +99,9 @@ def weight_df(
     pulse_year,
     fractional=False,
 ):
+    """Weight, fractionalize, and combine SSP damage functions,
+    then multiply by RFF GDP to return RFF damage functions.
+    """
 
     # get damage function as share of global GDP
     df = (
@@ -121,6 +147,7 @@ def rff_damage_functions(
     weights_path,
     pulse_year,
 ):
+    """Wrapper function for `weight_df()`."""
 
     # ssp GDP for fractionalizing damage functions
     ssp_gdp = xr.open_zarr(ssp_gdp, consolidated=True).sum("region").gdp
@@ -169,6 +196,7 @@ def prep_rff_socioeconomics(
     out_path,
     USA,
 ):
+    """Generate the global or domestic RFF socioeconomics file for use with the `dscim` MainRecipe."""
 
     # Load Fed GDP deflator
     fed_gdpdef = pd.read_csv(inflation_path).set_index("year")["gdpdef"].to_dict()
@@ -212,6 +240,9 @@ def aggregate_rff_weights(
     root,
     output,
 ):
+    """Wrapper function for `clean_simulation()` and `clean_error()`.
+    Generates an aggregated file of RFF emulator weights.
+    """
 
     # clean simulation files
     datasets = p_map(partial(clean_simulation, root=root), range(1, 10001, 1))