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build_heat_demand: parallelize

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Fabian Neumann 2022-12-28 12:21:00 +01:00
parent 097d054f06
commit 494d3010eb
2 changed files with 16 additions and 23 deletions
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11
Snakefile
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@ -162,16 +162,13 @@ else:
rule build_heat_demands: rule build_heat_demands:
input: input:
pop_layout_total="resources/pop_layout_total.nc", pop_layout="resources/pop_layout_{scope}.nc",
pop_layout_urban="resources/pop_layout_urban.nc",
pop_layout_rural="resources/pop_layout_rural.nc",
regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson") regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson")
output: output:
heat_demand_urban="resources/heat_demand_urban_elec_s{simpl}_{clusters}.nc", heat_demand="resources/heat_demand_{scope}_elec_s{simpl}_{clusters}.nc"
heat_demand_rural="resources/heat_demand_rural_elec_s{simpl}_{clusters}.nc",
heat_demand_total="resources/heat_demand_total_elec_s{simpl}_{clusters}.nc"
resources: mem_mb=20000 resources: mem_mb=20000
benchmark: "benchmarks/build_heat_demands/s{simpl}_{clusters}" threads: 8
benchmark: "benchmarks/build_heat_demands/{scope}_s{simpl}_{clusters}"
script: "scripts/build_heat_demand.py" script: "scripts/build_heat_demand.py"

22
scripts/build_heat_demand.py
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@ -5,6 +5,7 @@ import atlite
import pandas as pd import pandas as pd
import xarray as xr import xarray as xr
import numpy as np import numpy as np
from dask.distributed import Client, LocalCluster
if __name__ == '__main__': if __name__ == '__main__':
if 'snakemake' not in globals(): if 'snakemake' not in globals():
@ -15,14 +16,9 @@ if __name__ == '__main__':
clusters=48, clusters=48,
) )
if 'snakemake' not in globals(): nprocesses = int(snakemake.threads)
from vresutils import Dict cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1)
import yaml client = Client(cluster, asynchronous=True)
snakemake = Dict()
with open('config.yaml') as f:
snakemake.config = yaml.safe_load(f)
snakemake.input = Dict()
snakemake.output = Dict()
time = pd.date_range(freq='h', **snakemake.config['snapshots']) time = pd.date_range(freq='h', **snakemake.config['snapshots'])
cutout_config = snakemake.config['atlite']['cutout'] cutout_config = snakemake.config['atlite']['cutout']
@ -33,14 +29,14 @@ if __name__ == '__main__':
I = cutout.indicatormatrix(clustered_regions) I = cutout.indicatormatrix(clustered_regions)
for area in ["rural", "urban", "total"]: pop_layout = xr.open_dataarray(snakemake.input.pop_layout)
pop_layout = xr.open_dataarray(snakemake.input[f'pop_layout_{area}'])
stacked_pop = pop_layout.stack(spatial=('y', 'x')) stacked_pop = pop_layout.stack(spatial=('y', 'x'))
M = I.T.dot(np.diag(I.dot(stacked_pop))) M = I.T.dot(np.diag(I.dot(stacked_pop)))
heat_demand = cutout.heat_demand( heat_demand = cutout.heat_demand(
matrix=M.T, index=clustered_regions.index) matrix=M.T, index=clustered_regions.index,
dask_kwargs=dict(scheduler=client),
show_progress=False)
heat_demand.to_netcdf(snakemake.output[f"heat_demand_{area}"]) heat_demand.to_netcdf(snakemake.output.heat_demand)