[pre-commit.ci] auto fixes from pre-commit.com hooks

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pypsa-meets-earth · Aug 5, 2024 · fb263f7 · fb263f7
1 parent 7045e6b
commit fb263f7
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Showing 5 changed files with 34 additions and 30 deletions.
diff --git a/Snakefile b/Snakefile
@@ -96,7 +96,7 @@ rule prepare_sector_networks:
             RDIR
             + "/prenetworks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{sopts}_{planning_horizons}_{discountrate}_{demand}.nc",
             **config["scenario"],
-            **config["costs"]
+            **config["costs"],
         ),
 
 
@@ -107,7 +107,7 @@ rule override_res_all_nets:
             + "/prenetworks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{sopts}_{planning_horizons}_{discountrate}_{demand}_presec.nc",
             **config["scenario"],
             **config["costs"],
-            **config["export"]
+            **config["export"],
         ),
 
 
@@ -118,7 +118,7 @@ rule solve_all_networks:
             + "/postnetworks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{sopts}_{planning_horizons}_{discountrate}_{demand}_{h2export}export.nc",
             **config["scenario"],
             **config["costs"],
-            **config["export"]
+            **config["export"],
         ),
 
 
@@ -212,9 +212,11 @@ rule prepare_sector_network:
             + RDIR_PE
             + "bus_regions/regions_onshore_elec_s{simpl}_{clusters}.geojson"
         ),
-        pipelines="data_custom/pipelines.csv"
-        if config["custom_data"]["gas_network"]
-        else "resources/gas_networks/gas_network_elec_s{simpl}_{clusters}.csv",
+        pipelines=(
+            "data_custom/pipelines.csv"
+            if config["custom_data"]["gas_network"]
+            else "resources/gas_networks/gas_network_elec_s{simpl}_{clusters}.csv"
+        ),
     output:
         RDIR
         + "/prenetworks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{sopts}_{planning_horizons}_{discountrate}_{demand}.nc",
@@ -596,15 +598,15 @@ rule make_summary:
             + "/postnetworks/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{sopts}_{planning_horizons}_{discountrate}_{demand}_{h2export}export.nc",
             **config["scenario"],
             **config["costs"],
-            **config["export"]
+            **config["export"],
         ),
         costs=CDIR + "costs_{planning_horizons}.csv",
         plots=expand(
             RDIR
             + "/maps/elec_s{simpl}_{clusters}_ec_l{ll}_{opts}_{sopts}-costs-all_{planning_horizons}_{discountrate}_{demand}_{h2export}export.pdf",
             **config["scenario"],
             **config["costs"],
-            **config["export"]
+            **config["export"],
         ),
     output:
         nodal_costs=SDIR + "/csvs/nodal_costs.csv",

diff --git a/scripts/build_base_energy_totals.py b/scripts/build_base_energy_totals.py
@@ -95,9 +95,9 @@ def calc_sector(sector):
                 energy_totals_base.at[country, "total domestic aviation"] = np.NaN
 
             elif sector == "navigation":
-                energy_totals_base.at[
-                    country, "total international navigation"
-                ] = np.NaN
+                energy_totals_base.at[country, "total international navigation"] = (
+                    np.NaN
+                )
                 energy_totals_base.at[country, "total domestic navigation"] = np.NaN
 
             _logger.warning("No data for " + country + " in the sector " + sector + ".")
@@ -274,13 +274,13 @@ def calc_sector(sector):
                 )
 
             elif sector == "navigation":
-                energy_totals_base.at[
-                    country, "total international navigation"
-                ] = round(
-                    df_sector[
-                        df_sector.Transaction == "International marine bunkers"
-                    ].Quantity_TWh.sum(),
-                    4,
+                energy_totals_base.at[country, "total international navigation"] = (
+                    round(
+                        df_sector[
+                            df_sector.Transaction == "International marine bunkers"
+                        ].Quantity_TWh.sum(),
+                        4,
+                    )
                 )
                 energy_totals_base.at[country, "total domestic navigation"] = round(
                     df_sector[

diff --git a/scripts/build_industrial_database.py b/scripts/build_industrial_database.py
@@ -277,9 +277,9 @@ def create_cement_db():
     )
     avg_c_cap = df_cement.groupby(df_cement.country)["capacity"].mean()
     df_cement["capacity"] = df_cement.apply(
-        lambda x: avg_c_cap[x["country"]]
-        if math.isnan(x["capacity"])
-        else x["capacity"],
+        lambda x: (
+            avg_c_cap[x["country"]] if math.isnan(x["capacity"]) else x["capacity"]
+        ),
         axis=1,
     )
 
@@ -455,9 +455,9 @@ def create_paper_df():
     na_index
 
     df_paper["capacity"] = df_paper.apply(
-        lambda x: avg_c_cap[x["country"]]
-        if math.isnan(x["capacity"])
-        else x["capacity"],
+        lambda x: (
+            avg_c_cap[x["country"]] if math.isnan(x["capacity"]) else x["capacity"]
+        ),
         axis=1,
     )
 

diff --git a/scripts/plot_summary.py b/scripts/plot_summary.py
@@ -269,9 +269,11 @@ def plot_balances():
 
         # remove trailing link ports
         df.index = [
-            i[:-1]
-            if ((i != "co2") and (i != "H2") and (i[-1:] in ["0", "1", "2", "3"]))
-            else i
+            (
+                i[:-1]
+                if ((i != "co2") and (i != "H2") and (i[-1:] in ["0", "1", "2", "3"]))
+                else i
+            )
             for i in df.index
         ]
 

diff --git a/scripts/prepare_airports.py b/scripts/prepare_airports.py
@@ -94,9 +94,9 @@ def download_airports():
 
     df.insert(2, "airport_size_nr", 1)
     df.loc[df["type"].isin(["medium_airport"]), "airport_size_nr"] = 1
-    df.loc[
-        df["type"].isin(["large_airport"]), "airport_size_nr"
-    ] = snakemake.params.airport_sizing_factor
+    df.loc[df["type"].isin(["large_airport"]), "airport_size_nr"] = (
+        snakemake.params.airport_sizing_factor
+    )
 
     # Calculate the number of total airports size
     df1 = df.copy()