33 lines
839 B
Python
33 lines
839 B
Python
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import geopandas as gpd
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import xarray as xr
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import pandas as pd
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import atlite
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cutout = atlite.Cutout(snakemake.config['renewable']['onwind']['cutout'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'])
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clustered_busregions_as_geopd = gpd.read_file(snakemake.input.regions_onshore).set_index('name', drop=True)
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clustered_busregions = pd.Series(clustered_busregions_as_geopd.geometry, index=clustered_busregions_as_geopd.index)
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I = cutout.indicatormatrix(clustered_busregions)
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items = ["total","urban","rural"]
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pop = pd.DataFrame(columns=items,
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index=clustered_busregions.index)
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for item in items:
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pop_layout = xr.open_dataarray(snakemake.input['pop_layout_'+item])
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pop[item] = I.dot(pop_layout.stack(spatial=('y', 'x')))
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pop.to_csv(snakemake.output.clustered_pop_layout)
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