remove spelling mistakes
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@ -1,19 +1,7 @@
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# -*- coding: utf-8 -*-
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# -*- coding: utf-8 -*-
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# SPDX-FileCopyrightText: : 2020-2023 The PyPSA-Eur Authors
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## Copyright 2015-2017 Frankfurt Institute for Advanced Studies
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#
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# SPDX-License-Identifier: MIT
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## This program is free software; you can redistribute it and/or
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## modify it under the terms of the GNU General Public License as
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## published by the Free Software Foundation; either version 3 of the
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## License, or (at your option) any later version.
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## This program is distributed in the hope that it will be useful,
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## but WITHOUT ANY WARRANTY; without even the implied warranty of
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## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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## GNU General Public License for more details.
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## You should have received a copy of the GNU General Public License
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## along with this program. If not, see <http://www.gnu.org/licenses/>.
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"""
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"""
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"""
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"""
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@ -553,7 +553,7 @@ def plot_carbon_budget_distribution(input_eurostat):
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markersize=12,
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markersize=12,
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markerfacecolor="black",
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markerfacecolor="black",
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markeredgecolor="black",
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markeredgecolor="black",
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label="EU commited target",
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label="EU committed target",
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)
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)
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for col in co2_cap.columns:
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for col in co2_cap.columns:
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@ -200,7 +200,7 @@ def concat_networks(years):
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else:
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else:
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# this is to avoid adding multiple times assets with
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# this is to avoid adding multiple times assets with
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# infinit lifetime as ror
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# infinite lifetime as ror
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cols = pnl_year.columns.difference(pnl[k].columns)
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cols = pnl_year.columns.difference(pnl[k].columns)
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pnl[k] = pd.concat([pnl[k], pnl_year[cols]], axis=1)
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pnl[k] = pd.concat([pnl[k], pnl_year[cols]], axis=1)
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@ -233,7 +233,7 @@ def adjust_stores(n):
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Make sure that stores still behave cyclic over one year and not whole
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Make sure that stores still behave cyclic over one year and not whole
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modelling horizon.
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modelling horizon.
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"""
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"""
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# cylclic constraint
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# cyclic constraint
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cyclic_i = n.stores[n.stores.e_cyclic].index
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cyclic_i = n.stores[n.stores.e_cyclic].index
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n.stores.loc[cyclic_i, "e_cyclic_per_period"] = True
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n.stores.loc[cyclic_i, "e_cyclic_per_period"] = True
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n.stores.loc[cyclic_i, "e_cyclic"] = False
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n.stores.loc[cyclic_i, "e_cyclic"] = False
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