49 lines
1.9 KiB
Python
49 lines
1.9 KiB
Python
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"""Build regional demand for international navigation based on outflow volume of ports."""
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import pandas as pd
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import geopandas as gpd
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import json
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if __name__ == '__main__':
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if 'snakemake' not in globals():
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from helper import mock_snakemake
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snakemake = mock_snakemake(
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'build_shipping_demand_per_node',
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simpl='',
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clusters=48,
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)
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scope = gpd.read_file(snakemake.input.scope).geometry[0]
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regions = gpd.read_file(snakemake.input.regions).set_index('name')
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demand = pd.read_csv(snakemake.input.demand, index_col=0)["total international navigation"]
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# read port data into GeoDataFrame
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with open(snakemake.input.ports, 'r', encoding='latin_1') as f:
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ports = json.load(f)
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ports = pd.json_normalize(ports, "features", sep="_")
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coordinates = ports.geometry_coordinates
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geometry = gpd.points_from_xy(coordinates.str[0], coordinates.str[1])
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ports = gpd.GeoDataFrame(ports, geometry=geometry, crs=4326)
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# filter global port data by European ports
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european_ports = ports[ports.within(scope)]
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# assign ports to nearest region
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p = european_ports.to_crs(3857)
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r = regions.to_crs(3857)
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outflows = p.sjoin_nearest(r).groupby("index_right").properties_outflows.sum().div(1e3)
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# calculate fraction of each country's port outflows
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countries = outflows.index.str[:2]
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outflows_per_country = outflows.groupby(countries).sum()
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fraction = outflows / countries.map(outflows_per_country)
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# distribute per-country demands to nodes based on these fractions
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nodal_demand = demand.loc[countries].fillna(0.)
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nodal_demand.index = fraction.index
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nodal_demand = nodal_demand.multiply(fraction, axis=0)
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nodal_demand = nodal_demand.reindex(regions.index, fill_value=0)
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# export nodal international navigation demands
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nodal_demand.to_csv(snakemake.output[0])
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