plot_electricity_prices: fix header spec
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scripts/plot_validation_cross_border_flows.py
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57
scripts/plot_validation_cross_border_flows.py
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@ -0,0 +1,57 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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import matplotlib.pyplot as plt
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import pandas as pd
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import pypsa
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import seaborn as sns
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from _helpers import configure_logging
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from pypsa.statistics import get_bus_and_carrier
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sns.set_theme("paper", style="whitegrid")
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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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"plot_electricity_prices",
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simpl="",
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opts="Ept-12h",
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clusters="37",
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ll="v1.0",
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)
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configure_logging(snakemake)
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n = pypsa.Network(snakemake.input.network)
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n.loads.carrier = "load"
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historic = pd.read_csv(
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snakemake.input.cross_border_flows,
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index_col=0,
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header=0,
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parse_dates=True,
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)
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if len(historic.index) > len(n.snapshots):
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historic = historic.resample(n.snapshots.inferred_freq).mean().loc[n.snapshots]
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# optimized = n.buses_t.marginal_price.groupby(n.buses.country, axis=1).mean()
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# data = pd.concat([historic, optimized], keys=["Historic", "Optimized"], axis=1)
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# data.columns.names = ["Kind", "Country"]
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# # %% total production per carrier
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# fig, ax = plt.subplots(figsize=(6, 6))
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# df = data.mean().unstack().T
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# df.plot.barh(ax=ax, xlabel="Electricity Price [€/MWh]", ylabel="")
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# ax.grid(axis="y")
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# fig.savefig(snakemake.output.price_bar, bbox_inches="tight")
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# touch file
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with open(snakemake.output.plots_touch, "a"):
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pass
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@ -32,7 +32,7 @@ if __name__ == "__main__":
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historic = pd.read_csv(
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snakemake.input.electricity_prices,
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index_col=0,
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header=[0, 1],
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header=0,
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parse_dates=True,
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)
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