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

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2024-02-14 17:31:48 +00:00 · 2024-02-14 17:31:48 +00:00 · b45df1724b
commit b45df1724b
parent e14bae345b
5 changed files with 78 additions and 39 deletions
--- a/rules/build_sector.smk
+++ b/rules/build_sector.smk
@ -443,7 +443,8 @@ rule build_industry_sector_ratios_intermediate:
        industrial_production_per_country=RESOURCES
        + "industrial_production_per_country.csv",
    output:
-        industry_sector_ratios=RESOURCES + "industry_sector_ratios_{planning_horizons}.csv",
+        industry_sector_ratios=RESOURCES
+        + "industry_sector_ratios_{planning_horizons}.csv",
    threads: 1
    resources:
        mem_mb=1000,
@ -559,7 +560,8 @@ rule build_industrial_production_per_node:

 rule build_industrial_energy_demand_per_node:
    input:
-        industry_sector_ratios=RESOURCES + "industry_sector_ratios_{planning_horizons}.csv",
+        industry_sector_ratios=RESOURCES
+        + "industry_sector_ratios_{planning_horizons}.csv",
        industrial_production_per_node=RESOURCES
        + "industrial_production_elec_s{simpl}_{clusters}_{planning_horizons}.csv",
        industrial_energy_demand_per_node_today=RESOURCES
--- a/scripts/build_industrial_energy_demand_per_country_today.py
+++ b/scripts/build_industrial_energy_demand_per_country_today.py
@ -96,19 +96,35 @@ def industrial_energy_demand_per_country(country, year, jrc_dir):

 def separate_basic_chemicals(demand, production):

-    ammonia = pd.DataFrame({"hydrogen": production["Ammonia"] * params["MWh_H2_per_tNH3_electrolysis"],
-                            "electricity" : production["Ammonia"] * params["MWh_elec_per_tNH3_electrolysis"]}).T
-    chlorine = pd.DataFrame({"hydrogen": production["Chlorine"] * params["MWh_H2_per_tCl"],
-                             "electricity" : production["Chlorine"] * params["MWh_elec_per_tCl"]}).T
-    methanol = pd.DataFrame({"gas": production["Methanol"] * params["MWh_CH4_per_tMeOH"],
-                             "electricity" : production["Methanol"] * params["MWh_elec_per_tMeOH"]}).T
+    ammonia = pd.DataFrame(
+        {
+            "hydrogen": production["Ammonia"] * params["MWh_H2_per_tNH3_electrolysis"],
+            "electricity": production["Ammonia"]
+            * params["MWh_elec_per_tNH3_electrolysis"],
+        }
+    ).T
+    chlorine = pd.DataFrame(
+        {
+            "hydrogen": production["Chlorine"] * params["MWh_H2_per_tCl"],
+            "electricity": production["Chlorine"] * params["MWh_elec_per_tCl"],
+        }
+    ).T
+    methanol = pd.DataFrame(
+        {
+            "gas": production["Methanol"] * params["MWh_CH4_per_tMeOH"],
+            "electricity": production["Methanol"] * params["MWh_elec_per_tMeOH"],
+        }
+    ).T

    demand["Ammonia"] = ammonia.unstack().reindex(index=demand.index, fill_value=0.0)
    demand["Chlorine"] = chlorine.unstack().reindex(index=demand.index, fill_value=0.0)
    demand["Methanol"] = methanol.unstack().reindex(index=demand.index, fill_value=0.0)

    demand["HVC"] = (
-        demand["Basic chemicals"] - demand["Ammonia"] - demand["Methanol"] - demand["Chlorine"]
+        demand["Basic chemicals"]
+        - demand["Ammonia"]
+        - demand["Methanol"]
+        - demand["Chlorine"]
    )

    demand.drop(columns="Basic chemicals", inplace=True)
@ -166,8 +182,10 @@ if __name__ == "__main__":
    demand = industrial_energy_demand(countries.intersection(eu28), year)

    # output in MtMaterial/a
-    production = pd.read_csv(snakemake.input.industrial_production_per_country,
-                             index_col=0) / 1e3
+    production = (
+        pd.read_csv(snakemake.input.industrial_production_per_country, index_col=0)
+        / 1e3
+    )

    demand = separate_basic_chemicals(demand, production)

--- a/scripts/build_industrial_energy_demand_per_node.py
+++ b/scripts/build_industrial_energy_demand_per_node.py
@ -21,9 +21,7 @@ if __name__ == "__main__":

    # import ratios
    fn = snakemake.input.industry_sector_ratios
-    sector_ratios = pd.read_csv(fn,
-                                header=[0,1],
-                                index_col=0)
+    sector_ratios = pd.read_csv(fn, header=[0, 1], index_col=0)

    # material demand per node and industry (Mton/a)
    fn = snakemake.input.industrial_production_per_node
@ -33,14 +31,19 @@ if __name__ == "__main__":
    fn = snakemake.input.industrial_energy_demand_per_node_today
    nodal_today = pd.read_csv(fn, index_col=0)

-    nodal_sector_ratios = pd.concat({node: sector_ratios[node[:2]] for node in nodal_production.index},
-                                    axis=1)
+    nodal_sector_ratios = pd.concat(
+        {node: sector_ratios[node[:2]] for node in nodal_production.index}, axis=1
+    )

    nodal_production_stacked = nodal_production.stack()
    nodal_production_stacked.index.names = [None, None]

    # final energy consumption per node and industry (TWh/a)
-    nodal_df = (nodal_sector_ratios.multiply(nodal_production_stacked)).T.groupby(level=0).sum()
+    nodal_df = (
+        (nodal_sector_ratios.multiply(nodal_production_stacked))
+        .T.groupby(level=0)
+        .sum()
+    )

    rename_sectors = {
        "elec": "electricity",
--- a/scripts/build_industrial_production_per_country.py
+++ b/scripts/build_industrial_production_per_country.py
@ -261,7 +261,11 @@ def separate_basic_chemicals(demand, year):
    demand["Basic chemicals"].clip(lower=0.0, inplace=True)

    # assume HVC, methanol, chlorine production proportional to non-ammonia basic chemicals
-    distribution_key = demand["Basic chemicals"] / params["basic_chemicals_without_NH3_production_today"] / 1e3
+    distribution_key = (
+        demand["Basic chemicals"]
+        / params["basic_chemicals_without_NH3_production_today"]
+        / 1e3
+    )
    demand["HVC"] = params["HVC_production_today"] * 1e3 * distribution_key
    demand["Chlorine"] = params["chlorine_production_today"] * 1e3 * distribution_key
    demand["Methanol"] = params["methanol_production_today"] * 1e3 * distribution_key
--- a/scripts/build_industry_sector_ratios_intermediate.py
+++ b/scripts/build_industry_sector_ratios_intermediate.py
@ -4,39 +4,45 @@
 # SPDX-License-Identifier: MIT
 """
 Build specific energy consumption by carrier and industries and by country,
-that interpolates between the current average energy consumption (from 2015-2020)
-and the ideal future best-in-class consumption.
+that interpolates between the current average energy consumption (from
+2015-2020) and the ideal future best-in-class consumption.
 """

 import pandas as pd
-
 from prepare_sector_network import get

+
 def build_industry_sector_ratios_intermediate():

    # in TWh/a
-    demand = pd.read_csv(snakemake.input.industrial_energy_demand_per_country_today,
+    demand = pd.read_csv(
+        snakemake.input.industrial_energy_demand_per_country_today,
        header=[0, 1],
-                         index_col=0)
+        index_col=0,
+    )

    # in Mt/a
-    production = pd.read_csv(snakemake.input.industrial_production_per_country,
-                             index_col=0) / 1e3
+    production = (
+        pd.read_csv(snakemake.input.industrial_production_per_country, index_col=0)
+        / 1e3
+    )
    production = production.unstack().swaplevel()

    # in MWh/t
-    future_sector_ratios = pd.read_csv(snakemake.input.industry_sector_ratios,
-                                       index_col=0)
+    future_sector_ratios = pd.read_csv(
+        snakemake.input.industry_sector_ratios, index_col=0
+    )

    production.index.names = [None, None]

    today_sector_ratios = demand.div(production, axis=1)

-    today_sector_ratios.drop(columns=today_sector_ratios.columns[today_sector_ratios.isna().all()],
-                             inplace=True)
+    today_sector_ratios.drop(
+        columns=today_sector_ratios.columns[today_sector_ratios.isna().all()],
+        inplace=True,
+    )

-    rename = pd.Series(today_sector_ratios.index,
-                       today_sector_ratios.index)
+    rename = pd.Series(today_sector_ratios.index, today_sector_ratios.index)
    rename["waste"] = "biomass"
    rename["electricity"] = "elec"
    rename["solid"] = "coke"
@ -44,9 +50,7 @@ def build_industry_sector_ratios_intermediate():
    rename["other"] = "biomass"
    rename["liquid"] = "naphtha"

-    today_sector_ratios.rename(rename,
-                               inplace=True)
-
+    today_sector_ratios.rename(rename, inplace=True)

    fraction_future = get(params["sector_ratios_fraction_future"], year)

@ -56,14 +60,22 @@ def build_industry_sector_ratios_intermediate():

        intermediate_sector_ratio = future_sector_ratios.copy()

-        intermediate_sector_ratio.loc[today_sector_ratios[ct].index,today_sector_ratios[ct].columns] = (fraction_future*intermediate_sector_ratio.loc[today_sector_ratios[ct].index,today_sector_ratios[ct].columns]
-                                                                                                        + (1 - fraction_future)*today_sector_ratios[ct])
+        intermediate_sector_ratio.loc[
+            today_sector_ratios[ct].index, today_sector_ratios[ct].columns
+        ] = (
+            fraction_future
+            * intermediate_sector_ratio.loc[
+                today_sector_ratios[ct].index, today_sector_ratios[ct].columns
+            ]
+            + (1 - fraction_future) * today_sector_ratios[ct]
+        )
        intermediate_sector_ratios[ct] = intermediate_sector_ratio

    intermediate_sector_ratios = pd.concat(intermediate_sector_ratios, axis=1)

    intermediate_sector_ratios.to_csv(snakemake.output.industry_sector_ratios)

+
 if __name__ == "__main__":
    if "snakemake" not in globals():
        from _helpers import mock_snakemake