arguments in function calls instead of kwarg-style
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@ -549,11 +549,11 @@ if __name__ == "__main__":
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n = pypsa.Network(paths.base_network)
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Nyears = n.snapshot_weightings.objective.sum() / 8760.
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costs = load_costs(paths.tech_costs, config['costs'], config['electricity'], Nyears=Nyears)
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costs = load_costs(paths.tech_costs, config['costs'], config['electricity'], Nyears)
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ppl = load_powerplants(paths.powerplants)
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attach_load(n, paths.regions, paths.load, paths.nuts3_shapes, config['countries'],
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scaling=config['load']['scaling_factor'])
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config['load']['scaling_factor'])
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update_transmission_costs(n, costs, config['lines']['length_factor'])
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@ -199,7 +199,7 @@ if __name__ == "__main__":
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elec_config = config['electricity']
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Nyears = n.snapshot_weightings.objective.sum() / 8760.
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costs = load_costs(paths.tech_costs, config['costs'], elec_config, Nyears=Nyears)
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costs = load_costs(paths.tech_costs, config['costs'], elec_config, Nyears)
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attach_storageunits(n, costs, elec_config)
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attach_stores(n, costs, elec_config)
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@ -374,12 +374,10 @@ if __name__ == "__main__":
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custom_busmap = pd.read_csv(paths.custom_busmap, index_col=0, squeeze=True)
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custom_busmap.index = custom_busmap.index.astype(str)
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logger.info(f"Imported custom busmap from {paths.custom_busmap}")
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clustering = clustering_for_n_clusters(n, n_clusters, custom_busmap, aggregate_carriers,
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line_length_factor=line_length_factor,
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potential_mode=potential_mode,
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solver_name=config['solving']['solver']['name'],
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extended_link_costs=hvac_overhead_cost,
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focus_weights=focus_weights)
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line_length_factor, potential_mode, config['solving']['solver']['name'],
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"kmeans", hvac_overhead_cost, focus_weights)
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update_p_nom_max(n)
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@ -140,7 +140,7 @@ def average_every_nhours(n, offset):
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return m
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def apply_time_segmentation(n, segments, solver_name="cplex"):
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def apply_time_segmentation(n, segments, solver_name="cbc"):
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logger.info(f"Aggregating time series to {segments} segments.")
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try:
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import tsam.timeseriesaggregation as tsam
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@ -212,11 +212,9 @@ if __name__ == "__main__":
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n = pypsa.Network(paths[0])
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Nyears = n.snapshot_weightings.objective.sum() / 8760.
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costs = load_costs(tech_costs = paths.tech_costs,
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config = config['costs'],
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elec_config = config['electricity'], Nyears = Nyears)
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costs = load_costs(paths.tech_costs, config['costs'], config['electricity'], Nyears)
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set_line_s_max_pu(n, s_max_pu=config['lines']['s_max_pu'])
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set_line_s_max_pu(n, config['lines']['s_max_pu'])
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for o in opts:
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m = re.match(r'^\d+h$', o, re.IGNORECASE)
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@ -228,7 +226,7 @@ if __name__ == "__main__":
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m = re.match(r'^\d+seg$', o, re.IGNORECASE)
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if m is not None:
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solver_name = config["solving"]["solver"]["name"]
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n = apply_time_segmentation(n, m.group(0)[:-3], solver_name=solver_name)
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n = apply_time_segmentation(n, m.group(0)[:-3], solver_name)
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break
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for o in opts:
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@ -285,8 +285,7 @@ if __name__ == "__main__":
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with memory_logger(filename=fn, interval=30.) as mem:
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n = pypsa.Network(paths[0])
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n = prepare_network(n, solve_opts)
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n = solve_network(n, config=config, opts=opts,
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solver_dir=tmpdir,
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n = solve_network(n, config, opts, solver_dir=tmpdir,
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solver_logfile=logs.solver)
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n.export_to_netcdf(out[0])
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@ -116,9 +116,8 @@ if __name__ == "__main__":
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fn = getattr(logs, 'memory', None)
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with memory_logger(filename=fn, interval=30.) as mem:
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n = prepare_network(n, solve_opts=config['solving']['options'])
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n = solve_network(n, config=config, opts=opts,
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solver_dir=tmpdir,
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n = prepare_network(n, config['solving']['options'])
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n = solve_network(n, config, opts, solver_dir=tmpdir,
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solver_logfile=logs.solver)
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n.export_to_netcdf(out[0])
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