diff --git a/Snakefile b/Snakefile index 2f338813..7ce29b4f 100644 --- a/Snakefile +++ b/Snakefile @@ -162,16 +162,13 @@ else: rule build_heat_demands: input: - pop_layout_total="resources/pop_layout_total.nc", - pop_layout_urban="resources/pop_layout_urban.nc", - pop_layout_rural="resources/pop_layout_rural.nc", + pop_layout="resources/pop_layout_{scope}.nc", regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson") output: - heat_demand_urban="resources/heat_demand_urban_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" + heat_demand="resources/heat_demand_{scope}_elec_s{simpl}_{clusters}.nc" 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" diff --git a/scripts/build_heat_demand.py b/scripts/build_heat_demand.py index ed8a10b9..1c49f80d 100644 --- a/scripts/build_heat_demand.py +++ b/scripts/build_heat_demand.py @@ -5,6 +5,7 @@ import atlite import pandas as pd import xarray as xr import numpy as np +from dask.distributed import Client, LocalCluster if __name__ == '__main__': if 'snakemake' not in globals(): @@ -15,14 +16,9 @@ if __name__ == '__main__': clusters=48, ) - if 'snakemake' not in globals(): - from vresutils import Dict - import yaml - snakemake = Dict() - with open('config.yaml') as f: - snakemake.config = yaml.safe_load(f) - snakemake.input = Dict() - snakemake.output = Dict() + nprocesses = int(snakemake.threads) + cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1) + client = Client(cluster, asynchronous=True) time = pd.date_range(freq='h', **snakemake.config['snapshots']) cutout_config = snakemake.config['atlite']['cutout'] @@ -33,14 +29,14 @@ if __name__ == '__main__': 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')) + M = I.T.dot(np.diag(I.dot(stacked_pop))) - stacked_pop = pop_layout.stack(spatial=('y', 'x')) - M = I.T.dot(np.diag(I.dot(stacked_pop))) + heat_demand = cutout.heat_demand( + matrix=M.T, index=clustered_regions.index, + dask_kwargs=dict(scheduler=client), + show_progress=False) - heat_demand = cutout.heat_demand( - matrix=M.T, index=clustered_regions.index) - - heat_demand.to_netcdf(snakemake.output[f"heat_demand_{area}"]) + heat_demand.to_netcdf(snakemake.output.heat_demand)