8e4abc3fce
- country_shapes - offshore_shapes - nuts3_shapes (nuts3 shapes already include population and gdp data)
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import os
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from operator import attrgetter
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import pandas as pd
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import geopandas as gpd
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from vresutils.graph import voronoi_partition_pts
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import pypsa
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countries = snakemake.config['countries']
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n = pypsa.Network(snakemake.input.base_network)
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country_shapes = gpd.read_file(snakemake.input.country_shapes).set_index('id')['geometry']
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offshore_shapes = gpd.read_file(snakemake.input.offshore_shapes).set_index('id')['geometry']
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onshore_regions = []
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offshore_regions = []
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for country in countries:
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c_b = n.buses.country == country
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onshore_shape = country_shapes[country]
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onshore_locs = n.buses.loc[c_b & n.buses.substation_lv, ["x", "y"]]
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onshore_regions.append(gpd.GeoDataFrame({
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'geometry': voronoi_partition_pts(onshore_locs.values, onshore_shape),
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'country': country
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}, index=onshore_locs.index))
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if country not in offshore_shapes.index: continue
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offshore_shape = offshore_shapes[country]
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offshore_locs = n.buses.loc[c_b & n.buses.substation_off, ["x", "y"]]
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offshore_regions_c = gpd.GeoDataFrame({
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'geometry': voronoi_partition_pts(offshore_locs.values, offshore_shape),
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'country': country
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}, index=offshore_locs.index)
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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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def save_to_geojson(s, fn):
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if os.path.exists(fn):
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os.unlink(fn)
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s.reset_index().to_file(fn, driver='GeoJSON')
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save_to_geojson(pd.concat(onshore_regions), snakemake.output.regions_onshore)
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save_to_geojson(pd.concat(offshore_regions), snakemake.output.regions_offshore)
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