Update to LINEAR emission limit calculations

Previously historical emission data from EMBER was only pulled if the historical year was within the model horizon. However, this meant that in certain instances no LINEAR interpolation could be applied. Changes have been made to pull the latest historical data year, perform the interpolation, and drop historical years that are out of the model horizon.

workflow/scripts/osemosys_global/emissions/emission_limit.py

@@ -52,7 +52,7 @@ def add_emission_limits(emissions, emission_limit, ember,
 
                 # Filter template df for given country and emission
                 data = template.copy().loc[template["EMISSION"].isin(
-                    [emission + country])]
+                    [emission + country])].reset_index(drop = True)
 
                 # Loop through limits per country
                 for idx, row in limits.iterrows():
@@ -68,12 +68,25 @@ def add_emission_limits(emissions, emission_limit, ember,
                         if data_type == 'LINEAR':
                             ember_data = ember.copy().loc[
                                 (ember["EMISSION"].isin([emission + country]))]
+
                             # Check if year for country specific EMBER data exists in horizon.
                             for year in ember_data["YEAR"].unique():
                                 if year in data["YEAR"].values:
                                     # Set baseline year data for LINEAR
                                     data.loc[(data["YEAR"] == year),"VALUE"] = ember_data.loc[
                                         (ember_data["YEAR"] == year)]['VALUE'].iloc[0]
+
+                            # If none of EMBER data years exist in horizon, pull latest EMBER year
+                            # to be able to set linear interpolation values.
+                            if ember_data["YEAR"].unique()[-1] < data["YEAR"].values[0]:
+                                data.loc[len(data)] = [data['EMISSION'].iloc[-1], 
+                                                       ember_data["YEAR"].unique()[-1]]
+
+                                data = data.sort_values(by = ['YEAR']).reset_index(drop = True)
+
+                                data.loc[(data["YEAR"] == ember_data["YEAR"].unique()[-1]),"VALUE"
+                                         ] = ember_data.loc[
+                                             (ember_data["YEAR"] == year)]['VALUE'].iloc[0]
 
                         # Set baseline year data for POINT
                         data.loc[(data["YEAR"] == data_year),"VALUE"] = data_value     
@@ -104,6 +117,7 @@ def add_emission_limits(emissions, emission_limit, ember,
                 # Format df
                 data.dropna(axis=0, inplace=True)
                 data["REGION"] = region_name
+                data = data.loc[data["YEAR"].between(start_year, end_year)]
                 data = data[["REGION", "EMISSION", "YEAR", "VALUE"]]
 
                 if annual_emission_limit.empty: