cluster_network: Allow configuring the line_length_factor
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@ -133,7 +133,7 @@ def plot_busmap_for_n_clusters(n, n_clusters=50):
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n.plot(bus_colors=busmap.map(dict(zip(cs, cr))))
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del cs, cr
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def clustering_for_n_clusters(n, n_clusters, aggregate_renewables=True):
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def clustering_for_n_clusters(n, n_clusters, aggregate_renewables=True, line_length_factor=1.25):
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aggregate_generators_carriers = (None if aggregate_renewables
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else (pd.Index(n.generators.carrier.unique())
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.difference(['onwind', 'offwind', 'solar'])))
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@ -142,7 +142,8 @@ def clustering_for_n_clusters(n, n_clusters, aggregate_renewables=True):
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bus_strategies=dict(country=_make_consense("Bus", "country")),
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aggregate_generators_weighted=True,
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aggregate_generators_carriers=aggregate_generators_carriers,
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aggregate_one_ports=["Load", "StorageUnit"]
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aggregate_one_ports=["Load", "StorageUnit"],
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line_length_factor=line_length_factor
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)
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return clustering
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@ -200,7 +201,8 @@ if __name__ == "__main__":
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linemap = n.lines.index.to_series()
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clustering = pypsa.networkclustering.Clustering(n, busmap, linemap, linemap, pd.Series(dtype='O'))
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else:
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clustering = clustering_for_n_clusters(n, n_clusters, aggregate_renewables)
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line_length_factor = snakemake.config['lines']['length_factor']
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clustering = clustering_for_n_clusters(n, n_clusters, aggregate_renewables, line_length_factor=line_length_factor)
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clustering.network.export_to_netcdf(snakemake.output.network)
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with pd.HDFStore(snakemake.output.clustermaps, model='w') as store:
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