39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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"""
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Distribute country-level energy demands by population.
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"""
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import pandas as pd
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from _helpers import set_scenario_config
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if __name__ == "__main__":
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if "snakemake" not in globals():
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from _helpers import mock_snakemake
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snakemake = mock_snakemake(
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"build_population_weighted_energy_totals",
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weather_year="",
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simpl="",
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clusters=48,
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)
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set_scenario_config(snakemake)
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config = snakemake.config["energy"]
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data_year = int(config["energy_totals_year"])
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if snakemake.wildcards.weather_year and snakemake.wildcards.kind == "heat":
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data_year = int(snakemake.wildcards.weather_year)
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pop_layout = pd.read_csv(snakemake.input.clustered_pop_layout, index_col=0)
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totals = pd.read_csv(snakemake.input.energy_totals, index_col=[0, 1])
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totals = totals.xs(data_year, level="year")
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nodal_totals = totals.loc[pop_layout.ct].fillna(0.0)
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nodal_totals.index = pop_layout.index
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nodal_totals = nodal_totals.multiply(pop_layout.fraction, axis=0)
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nodal_totals.to_csv(snakemake.output[0])
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