Black reformating

polca · Sep 26, 2023 · f2de32d · f2de32d
1 parent 0fe87b8
commit f2de32d
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Showing 7 changed files with 357 additions and 90 deletions.
diff --git a/premise/data_collection.py b/premise/data_collection.py
@@ -146,7 +146,11 @@ def get_gains_EU_data() -> xr.DataArray:
     )
     gains_emi_EU["sector"] = gains_emi_EU["Sector"] + gains_emi_EU["Activity"]
     gains_emi_EU.drop(
-        ["Sector", "Activity",], axis=1,
+        [
+            "Sector",
+            "Activity",
+        ],
+        axis=1,
     )
 
     gains_emi_EU = gains_emi_EU[~gains_emi_EU["value"].isna()]
@@ -225,15 +229,19 @@ def fix_efficiencies(data: xr.DataArray, min_year: int) -> xr.DataArray:
     # we correct it to 1, as we do not accept
     # that efficiency degrades over time
     data.loc[dict(year=[y for y in data.year.values if y > 2020])] = np.clip(
-        data.loc[dict(year=[y for y in data.year.values if y > 2020])], 1, None,
+        data.loc[dict(year=[y for y in data.year.values if y > 2020])],
+        1,
+        None,
     )
 
     # Inversely, if we are looking at a year prior to 2020
     # and the ratio in efficiency change is superior to 1
     # we correct it to 1, as we do not accept
     # that efficiency in the past was higher than now
     data.loc[dict(year=[y for y in data.year.values if y < 2020])] = np.clip(
-        data.loc[dict(year=[y for y in data.year.values if y < 2020])], None, 1,
+        data.loc[dict(year=[y for y in data.year.values if y < 2020])],
+        None,
+        1,
     )
 
     # ensure that efficiency can not decrease over time
@@ -390,7 +398,9 @@ def __init__(
         new_vars = flatten(new_vars)
 
         data = self.__get_iam_data(
-            key=key, filedir=filepath_iam_files, variables=new_vars,
+            key=key,
+            filedir=filepath_iam_files,
+            variables=new_vars,
         )
 
         self.regions = data.region.values.tolist()
@@ -402,7 +412,9 @@ def __init__(
         )
 
         self.electricity_markets = self.__fetch_market_data(
-            data=data, input_vars=electricity_prod_vars, system_model=self.system_model,
+            data=data,
+            input_vars=electricity_prod_vars,
+            system_model=self.system_model,
         )
 
         self.petrol_markets = self.__fetch_market_data(
@@ -427,7 +439,12 @@ def __init__(
             input_vars={
                 k: v
                 for k, v in fuel_prod_vars.items()
-                if any(x in k for x in ["diesel",])
+                if any(
+                    x in k
+                    for x in [
+                        "diesel",
+                    ]
+                )
             },
             system_model=self.system_model,
         )
@@ -454,7 +471,12 @@ def __init__(
             input_vars={
                 k: v
                 for k, v in fuel_prod_vars.items()
-                if any(x in k for x in ["hydrogen",])
+                if any(
+                    x in k
+                    for x in [
+                        "hydrogen",
+                    ]
+                )
             },
             system_model=self.system_model,
         )
@@ -511,7 +533,12 @@ def __init__(
             efficiency_labels={
                 k: v
                 for k, v in fuel_eff_vars.items()
-                if any(x in k for x in ["diesel",])
+                if any(
+                    x in k
+                    for x in [
+                        "diesel",
+                    ]
+                )
             },
         )
         self.gas_efficiencies = self.get_iam_efficiencies(
@@ -527,7 +554,12 @@ def __init__(
             efficiency_labels={
                 k: v
                 for k, v in fuel_eff_vars.items()
-                if any(x in k for x in ["hydrogen",])
+                if any(
+                    x in k
+                    for x in [
+                        "hydrogen",
+                    ]
+                )
             },
         )
 
@@ -1230,7 +1262,11 @@ def fetch_external_data_coal_power_plants(self):
         df = df.drop(columns=["fuel input"])
         array = (
             df.melt(
-                id_vars=["country", "CHP", "fuel",],
+                id_vars=[
+                    "country",
+                    "CHP",
+                    "fuel",
+                ],
                 var_name="variable",
                 value_name="value",
             )

diff --git a/premise/ecoinvent_modification.py b/premise/ecoinvent_modification.py
@@ -732,12 +732,18 @@ def __import_inventories(self, keep_uncertainty_data: bool = False) -> List[dict
             (FILEPATH_SYNGAS_FROM_COAL_INVENTORIES, "3.7"),
             (FILEPATH_BIOFUEL_INVENTORIES, "3.7"),
             (FILEPATH_SYNFUEL_INVENTORIES, "3.7"),
-            (FILEPATH_SYNFUEL_FROM_FT_FROM_WOOD_GASIFICATION_INVENTORIES, "3.7",),
+            (
+                FILEPATH_SYNFUEL_FROM_FT_FROM_WOOD_GASIFICATION_INVENTORIES,
+                "3.7",
+            ),
             (
                 FILEPATH_SYNFUEL_FROM_FT_FROM_WOOD_GASIFICATION_WITH_CCS_INVENTORIES,
                 "3.7",
             ),
-            (FILEPATH_SYNFUEL_FROM_FT_FROM_COAL_GASIFICATION_INVENTORIES, "3.7",),
+            (
+                FILEPATH_SYNFUEL_FROM_FT_FROM_COAL_GASIFICATION_INVENTORIES,
+                "3.7",
+            ),
             (
                 FILEPATH_SYNFUEL_FROM_FT_FROM_COAL_GASIFICATION_WITH_CCS_INVENTORIES,
                 "3.7",
@@ -856,7 +862,12 @@ def update_dac(self) -> None:
         # use multiprocessing to speed up the process
         with ProcessPool(processes=multiprocessing.cpu_count()) as pool:
             args = [
-                (scenario, self.version, self.system_model, self.modified_datasets,)
+                (
+                    scenario,
+                    self.version,
+                    self.system_model,
+                    self.modified_datasets,
+                )
                 for scenario in self.scenarios
             ]
             results = pool.starmap(_update_dac, args)
@@ -877,7 +888,12 @@ def update_fuels(self) -> None:
         # use multiprocessing to speed up the process
         with ProcessPool(processes=multiprocessing.cpu_count()) as pool:
             args = [
-                (scenario, self.version, self.system_model, self.modified_datasets,)
+                (
+                    scenario,
+                    self.version,
+                    self.system_model,
+                    self.modified_datasets,
+                )
                 for scenario in self.scenarios
             ]
             results = pool.starmap(_update_fuels, args)
@@ -898,7 +914,12 @@ def update_cement(self) -> None:
         # use multiprocessing to speed up the process
         with ProcessPool(processes=multiprocessing.cpu_count()) as pool:
             args = [
-                (scenario, self.version, self.system_model, self.modified_datasets,)
+                (
+                    scenario,
+                    self.version,
+                    self.system_model,
+                    self.modified_datasets,
+                )
                 for scenario in self.scenarios
             ]
             results = pool.starmap(_update_cement, args)
@@ -919,7 +940,12 @@ def update_steel(self) -> None:
         # use multiprocessing to speed up the process
         with ProcessPool(processes=multiprocessing.cpu_count()) as pool:
             args = [
-                (scenario, self.version, self.system_model, self.modified_datasets,)
+                (
+                    scenario,
+                    self.version,
+                    self.system_model,
+                    self.modified_datasets,
+                )
                 for scenario in self.scenarios
             ]
             results = pool.starmap(_update_steel, args)
@@ -1200,7 +1226,9 @@ def write_superstructure_db_to_brightway(
         )
 
         write_brightway2_database(
-            data=self.database, name=name, reset_codes=True,
+            data=self.database,
+            name=name,
+            reset_codes=True,
         )
 
         # generate scenario report
@@ -1268,7 +1296,8 @@ def write_db_to_brightway(self, name: [str, List[str]] = None):
 
         for scen, scenario in enumerate(self.scenarios):
             write_brightway2_database(
-                scenario["database"], name[scen],
+                scenario["database"],
+                name[scen],
             )
         # generate scenario report
         self.generate_scenario_report()

diff --git a/premise/export.py b/premise/export.py
@@ -310,7 +310,12 @@ def create_codes_and_names_of_tech_matrix(database: List[dict]):
     :rtype: dict
     """
     return {
-        (i["name"], i["reference product"], i["unit"], i["location"],): i["code"]
+        (
+            i["name"],
+            i["reference product"],
+            i["unit"],
+            i["location"],
+        ): i["code"]
         for i in database
     }
 
@@ -332,7 +337,10 @@ def biosphere_flows_dictionary(version):
     csv_dict = {}
 
     with open(fp, encoding="utf-8") as file:
-        input_dict = csv.reader(file, delimiter=get_delimiter(filepath=fp),)
+        input_dict = csv.reader(
+            file,
+            delimiter=get_delimiter(filepath=fp),
+        )
         for row in input_dict:
             csv_dict[(row[0], row[1], row[2], row[3])] = row[-1]
 
@@ -534,7 +542,9 @@ def build_datapackage(df, inventories, list_scenarios, ei_version, name):
             "version": ei_version,
             "type": "source",
         },
-        {"name": "biosphere3",},
+        {
+            "name": "biosphere3",
+        },
     ]
     package.descriptor["scenarios"] = [
         {
@@ -1022,7 +1032,10 @@ class Export:
     """
 
     def __init__(
-        self, scenario: dict = None, filepath: Path = None, version: str = None,
+        self,
+        scenario: dict = None,
+        filepath: Path = None,
+        version: str = None,
     ):
         self.db = scenario["database"]
         self.model = scenario["model"]
@@ -1131,15 +1144,23 @@ def export_db_to_matrices(self):
 
         # Export A matrix
         with open(self.filepath / "A_matrix.csv", "w", encoding="utf-8") as file:
-            writer = csv.writer(file, delimiter=";", lineterminator="\n",)
+            writer = csv.writer(
+                file,
+                delimiter=";",
+                lineterminator="\n",
+            )
             writer.writerow(["index of activity", "index of product", "value"])
             rows = self.create_A_matrix_coordinates()
             for row in rows:
                 writer.writerow(row)
 
         # Export A index
         with open(self.filepath / "A_matrix_index.csv", "w", encoding="utf-8") as file:
-            writer = csv.writer(file, delimiter=";", lineterminator="\n",)
+            writer = csv.writer(
+                file,
+                delimiter=";",
+                lineterminator="\n",
+            )
             index_A = create_index_of_A_matrix(self.db)
             for d in index_A:
                 data = list(d) + [index_A[d]]
@@ -1149,15 +1170,23 @@ def export_db_to_matrices(self):
 
         # Export B matrix
         with open(self.filepath / "B_matrix.csv", "w", encoding="utf-8") as file:
-            writer = csv.writer(file, delimiter=";", lineterminator="\n",)
+            writer = csv.writer(
+                file,
+                delimiter=";",
+                lineterminator="\n",
+            )
             writer.writerow(["index of activity", "index of biosphere flow", "value"])
             rows = self.create_B_matrix_coordinates()
             for row in rows:
                 writer.writerow(row)
 
         # Export B index
         with open(self.filepath / "B_matrix_index.csv", "w", encoding="utf-8") as file:
-            writer = csv.writer(file, delimiter=";", lineterminator="\n",)
+            writer = csv.writer(
+                file,
+                delimiter=";",
+                lineterminator="\n",
+            )
             for d in index_B:
                 data = list(d) + [index_B[d]]
                 writer.writerow(data)

diff --git a/premise/inventory_imports.py b/premise/inventory_imports.py
@@ -60,7 +60,10 @@ def get_biosphere_code(version) -> dict:
     csv_dict = {}
 
     with open(fp, encoding="utf-8") as file:
-        input_dict = csv.reader(file, delimiter=get_delimiter(filepath=fp),)
+        input_dict = csv.reader(
+            file,
+            delimiter=get_delimiter(filepath=fp),
+        )
         for row in input_dict:
             csv_dict[(row[0], row[1], row[2], row[3])] = row[4]
 
@@ -87,7 +90,8 @@ def generate_migration_maps(origin: str, destination: str) -> Dict[str, list]:
 
     with open(FILEPATH_MIGRATION_MAP, "r", encoding="utf-8") as read_obj:
         csv_reader = csv.reader(
-            read_obj, delimiter=get_delimiter(filepath=FILEPATH_MIGRATION_MAP),
+            read_obj,
+            delimiter=get_delimiter(filepath=FILEPATH_MIGRATION_MAP),
         )
         next(csv_reader)
         for row in csv_reader:
@@ -507,7 +511,15 @@ def correct_product_field(self, exc: tuple) -> [str, None]:
             return candidate["reference product"]
 
         self.list_unlinked.append(
-            (exc[0], exc[-1], exc[1], None, exc[2], "technosphere", self.path.name,)
+            (
+                exc[0],
+                exc[-1],
+                exc[1],
+                None,
+                exc[2],
+                "technosphere",
+                self.path.name,
+            )
         )
 
         return None
@@ -680,8 +692,10 @@ def prepare_inventory(self) -> None:
             )
 
         if self.system_model == "consequential":
-            self.import_db.data = check_for_datasets_compliance_with_consequential_database(
-                self.import_db.data, self.consequential_blacklist
+            self.import_db.data = (
+                check_for_datasets_compliance_with_consequential_database(
+                    self.import_db.data, self.consequential_blacklist
+                )
             )
 
         self.import_db.data = remove_categories(self.import_db.data)
@@ -831,8 +845,10 @@ def prepare_inventory(self):
             )
 
         if self.system_model == "consequential":
-            self.import_db.data = check_for_datasets_compliance_with_consequential_database(
-                self.import_db.data, self.consequential_blacklist
+            self.import_db.data = (
+                check_for_datasets_compliance_with_consequential_database(
+                    self.import_db.data, self.consequential_blacklist
+                )
             )
 
         self.import_db.data = remove_categories(self.import_db.data)