Merge pull request #1013 from PyPSA/store-network-shapes
Store network shapes
This commit is contained in:
commit
0a19d90b60
@ -184,6 +184,8 @@ Upcoming Release
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* Fix custom busmap read in `cluster_network`.
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* Added shapes to .nc file for different stages of the network object in `base_network`, `build_bus_regions`, and `cluster_network`.
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* Fix p_nom_min of renewables generators for myopic approach and add check of existing capacities in `add_land_use_constraint_m`.
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* Add documentation section for how to contribute documentation
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@ -698,6 +698,22 @@ def _adjust_capacities_of_under_construction_branches(n, config):
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return n
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def _set_shapes(n, country_shapes, offshore_shapes):
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# Write the geodataframes country_shapes and offshore_shapes to the network.shapes component
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country_shapes = gpd.read_file(country_shapes).rename(columns={"name": "idx"})
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country_shapes["type"] = "country"
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offshore_shapes = gpd.read_file(offshore_shapes).rename(columns={"name": "idx"})
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offshore_shapes["type"] = "offshore"
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all_shapes = pd.concat([country_shapes, offshore_shapes], ignore_index=True)
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n.madd(
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"Shape",
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all_shapes.index,
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geometry=all_shapes.geometry,
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idx=all_shapes.idx,
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type=all_shapes["type"],
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)
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def base_network(
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eg_buses,
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eg_converters,
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@ -758,11 +774,14 @@ def base_network(
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n = _adjust_capacities_of_under_construction_branches(n, config)
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_set_shapes(n, country_shapes, offshore_shapes)
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return n
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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("base_network")
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@ -109,6 +109,34 @@ def voronoi_partition_pts(points, outline):
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return polygons
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def append_bus_shapes(n, shapes, type):
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"""
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Append shapes to the network. If shapes with the same component and type
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already exist, they will be removed.
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Parameters:
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n (pypsa.Network): The network to which the shapes will be appended.
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shapes (geopandas.GeoDataFrame): The shapes to be appended.
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**kwargs: Additional keyword arguments used in `n.madd`.
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Returns:
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None
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"""
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remove = n.shapes.query("component == 'Bus' and type == @type").index
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n.mremove("Shape", remove)
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offset = n.shapes.index.astype(int).max() + 1 if not n.shapes.empty else 0
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shapes = shapes.rename(lambda x: int(x) + offset)
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n.madd(
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"Shape",
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shapes.index,
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geometry=shapes.geometry,
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idx=shapes.name,
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component="Bus",
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type=type,
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)
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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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@ -119,7 +147,8 @@ if __name__ == "__main__":
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countries = snakemake.params.countries
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n = pypsa.Network(snakemake.input.base_network)
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base_network = snakemake.input.base_network
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n = pypsa.Network(base_network)
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country_shapes = gpd.read_file(snakemake.input.country_shapes).set_index("name")[
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"geometry"
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@ -173,12 +202,17 @@ if __name__ == "__main__":
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offshore_regions_c = offshore_regions_c.loc[offshore_regions_c.area > 1e-2]
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offshore_regions.append(offshore_regions_c)
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pd.concat(onshore_regions, ignore_index=True).to_file(
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snakemake.output.regions_onshore
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)
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shapes = pd.concat(onshore_regions, ignore_index=True)
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shapes.to_file(snakemake.output.regions_onshore)
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append_bus_shapes(n, shapes, "onshore")
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if offshore_regions:
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pd.concat(offshore_regions, ignore_index=True).to_file(
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snakemake.output.regions_offshore
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)
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shapes = pd.concat(offshore_regions, ignore_index=True)
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shapes.to_file(snakemake.output.regions_offshore)
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append_bus_shapes(n, shapes, "offshore")
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else:
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offshore_shapes.to_frame().to_file(snakemake.output.regions_offshore)
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# save network with shapes
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n.export_to_netcdf(base_network)
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@ -135,6 +135,7 @@ import pypsa
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import seaborn as sns
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from _helpers import configure_logging, set_scenario_config, update_p_nom_max
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from add_electricity import load_costs
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from build_bus_regions import append_bus_shapes
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from packaging.version import Version, parse
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from pypsa.clustering.spatial import (
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busmap_by_greedy_modularity,
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@ -428,20 +429,27 @@ def clustering_for_n_clusters(
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return clustering
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def cluster_regions(busmaps, input=None, output=None):
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def cluster_regions(busmaps, regions):
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"""
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Cluster regions based on busmaps and save the results to a file and to the
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network.
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Parameters:
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- busmaps (list): A list of busmaps used for clustering.
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- which (str): The type of regions to cluster.
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Returns:
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None
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"""
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busmap = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
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for which in ("regions_onshore", "regions_offshore"):
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regions = gpd.read_file(getattr(input, which))
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regions = regions.reindex(columns=["name", "geometry"]).set_index("name")
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regions_c = regions.dissolve(busmap)
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regions_c.index.name = "name"
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regions_c = regions_c.reset_index()
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regions_c.to_file(getattr(output, which))
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regions = regions.reindex(columns=["name", "geometry"]).set_index("name")
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regions_c = regions.dissolve(busmap)
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regions_c.index.name = "name"
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return regions_c.reset_index()
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def plot_busmap_for_n_clusters(n, n_clusters, fn=None):
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busmap = busmap_for_n_clusters(n, n_clusters)
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def plot_busmap_for_n_clusters(n, n_clusters, solver_name="scip", fn=None):
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busmap = busmap_for_n_clusters(n, n_clusters, solver_name)
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cs = busmap.unique()
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cr = sns.color_palette("hls", len(cs))
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n.plot(bus_colors=busmap.map(dict(zip(cs, cr))))
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@ -538,21 +546,25 @@ if __name__ == "__main__":
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params.focus_weights,
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)
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update_p_nom_max(clustering.network)
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nc = clustering.network
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update_p_nom_max(nc)
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if params.cluster_network.get("consider_efficiency_classes"):
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labels = [f" {label} efficiency" for label in ["low", "medium", "high"]]
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nc = clustering.network
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nc.generators["carrier"] = nc.generators.carrier.replace(labels, "", regex=True)
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clustering.network.meta = dict(
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snakemake.config, **dict(wildcards=dict(snakemake.wildcards))
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)
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clustering.network.export_to_netcdf(snakemake.output.network)
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for attr in (
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"busmap",
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"linemap",
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): # also available: linemap_positive, linemap_negative
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getattr(clustering, attr).to_csv(snakemake.output[attr])
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cluster_regions((clustering.busmap,), snakemake.input, snakemake.output)
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nc.shapes = n.shapes.copy()
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for which in ["regions_onshore", "regions_offshore"]:
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regions = gpd.read_file(snakemake.input[which])
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clustered_regions = cluster_regions((clustering.busmap,), regions)
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clustered_regions.to_file(snakemake.output[which])
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append_bus_shapes(nc, clustered_regions, type=which.split("_")[1])
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nc.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
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nc.export_to_netcdf(snakemake.output.network)
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@ -88,12 +88,14 @@ The rule :mod:`simplify_network` does up to four things:
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import logging
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from functools import reduce
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import geopandas as gpd
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import numpy as np
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import pandas as pd
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import pypsa
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import scipy as sp
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from _helpers import configure_logging, set_scenario_config, update_p_nom_max
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from add_electricity import load_costs
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from build_bus_regions import append_bus_shapes
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from cluster_network import cluster_regions, clustering_for_n_clusters
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from pypsa.clustering.spatial import (
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aggregateoneport,
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@ -610,6 +612,7 @@ if __name__ == "__main__":
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n.lines.drop(remove, axis=1, errors="ignore", inplace=True)
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if snakemake.wildcards.simpl:
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shapes = n.shapes
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n, cluster_map = cluster(
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n,
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int(snakemake.wildcards.simpl),
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@ -619,14 +622,19 @@ if __name__ == "__main__":
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params.simplify_network["feature"],
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params.aggregation_strategies,
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)
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n.shapes = shapes
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busmaps.append(cluster_map)
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update_p_nom_max(n)
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n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
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n.export_to_netcdf(snakemake.output.network)
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busmap_s = reduce(lambda x, y: x.map(y), busmaps[1:], busmaps[0])
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busmap_s.to_csv(snakemake.output.busmap)
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cluster_regions(busmaps, snakemake.input, snakemake.output)
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for which in ["regions_onshore", "regions_offshore"]:
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regions = gpd.read_file(snakemake.input[which])
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clustered_regions = cluster_regions(busmaps, regions)
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clustered_regions.to_file(snakemake.output[which])
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append_bus_shapes(n, clustered_regions, type=which.split("_")[1])
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n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
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n.export_to_netcdf(snakemake.output.network)
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