Merge branch 'master' into methanol
This commit is contained in:
Fabian Neumann
commit
38fd51fca9
37
Snakefile
37
Snakefile
@ -162,34 +162,26 @@ else:
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rule build_heat_demands:
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input:
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pop_layout_total="resources/pop_layout_total.nc",
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pop_layout_urban="resources/pop_layout_urban.nc",
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pop_layout_rural="resources/pop_layout_rural.nc",
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pop_layout="resources/pop_layout_{scope}.nc",
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regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson")
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output:
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heat_demand_urban="resources/heat_demand_urban_elec_s{simpl}_{clusters}.nc",
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heat_demand_rural="resources/heat_demand_rural_elec_s{simpl}_{clusters}.nc",
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heat_demand_total="resources/heat_demand_total_elec_s{simpl}_{clusters}.nc"
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heat_demand="resources/heat_demand_{scope}_elec_s{simpl}_{clusters}.nc"
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resources: mem_mb=20000
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benchmark: "benchmarks/build_heat_demands/s{simpl}_{clusters}"
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threads: 8
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benchmark: "benchmarks/build_heat_demands/{scope}_s{simpl}_{clusters}"
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script: "scripts/build_heat_demand.py"
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rule build_temperature_profiles:
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input:
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pop_layout_total="resources/pop_layout_total.nc",
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pop_layout_urban="resources/pop_layout_urban.nc",
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pop_layout_rural="resources/pop_layout_rural.nc",
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pop_layout="resources/pop_layout_{scope}.nc",
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regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson")
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output:
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temp_soil_total="resources/temp_soil_total_elec_s{simpl}_{clusters}.nc",
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temp_soil_rural="resources/temp_soil_rural_elec_s{simpl}_{clusters}.nc",
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temp_soil_urban="resources/temp_soil_urban_elec_s{simpl}_{clusters}.nc",
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temp_air_total="resources/temp_air_total_elec_s{simpl}_{clusters}.nc",
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temp_air_rural="resources/temp_air_rural_elec_s{simpl}_{clusters}.nc",
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temp_air_urban="resources/temp_air_urban_elec_s{simpl}_{clusters}.nc"
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temp_soil="resources/temp_soil_{scope}_elec_s{simpl}_{clusters}.nc",
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temp_air="resources/temp_air_{scope}_elec_s{simpl}_{clusters}.nc",
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resources: mem_mb=20000
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benchmark: "benchmarks/build_temperature_profiles/s{simpl}_{clusters}"
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threads: 8
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benchmark: "benchmarks/build_temperature_profiles/{scope}_s{simpl}_{clusters}"
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script: "scripts/build_temperature_profiles.py"
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@ -215,16 +207,13 @@ rule build_cop_profiles:
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rule build_solar_thermal_profiles:
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input:
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pop_layout_total="resources/pop_layout_total.nc",
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pop_layout_urban="resources/pop_layout_urban.nc",
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pop_layout_rural="resources/pop_layout_rural.nc",
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pop_layout="resources/pop_layout_{scope}.nc",
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regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson")
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output:
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solar_thermal_total="resources/solar_thermal_total_elec_s{simpl}_{clusters}.nc",
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solar_thermal_urban="resources/solar_thermal_urban_elec_s{simpl}_{clusters}.nc",
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solar_thermal_rural="resources/solar_thermal_rural_elec_s{simpl}_{clusters}.nc"
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solar_thermal="resources/solar_thermal_{scope}_elec_s{simpl}_{clusters}.nc",
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resources: mem_mb=20000
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benchmark: "benchmarks/build_solar_thermal_profiles/s{simpl}_{clusters}"
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threads: 16
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benchmark: "benchmarks/build_solar_thermal_profiles/{scope}_s{simpl}_{clusters}"
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script: "scripts/build_solar_thermal_profiles.py"
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@ -5,6 +5,7 @@ import atlite
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import pandas as pd
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import xarray as xr
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import numpy as np
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from dask.distributed import Client, LocalCluster
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if __name__ == '__main__':
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if 'snakemake' not in globals():
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@ -15,14 +16,9 @@ if __name__ == '__main__':
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clusters=48,
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)
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if 'snakemake' not in globals():
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from vresutils import Dict
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import yaml
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snakemake = Dict()
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with open('config.yaml') as f:
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snakemake.config = yaml.safe_load(f)
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snakemake.input = Dict()
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snakemake.output = Dict()
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nprocesses = int(snakemake.threads)
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cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1)
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client = Client(cluster, asynchronous=True)
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time = pd.date_range(freq='h', **snakemake.config['snapshots'])
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cutout_config = snakemake.config['atlite']['cutout']
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@ -33,14 +29,14 @@ if __name__ == '__main__':
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I = cutout.indicatormatrix(clustered_regions)
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for area in ["rural", "urban", "total"]:
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pop_layout = xr.open_dataarray(snakemake.input.pop_layout)
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pop_layout = xr.open_dataarray(snakemake.input[f'pop_layout_{area}'])
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stacked_pop = pop_layout.stack(spatial=('y', 'x'))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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stacked_pop = pop_layout.stack(spatial=('y', 'x'))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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heat_demand = cutout.heat_demand(
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matrix=M.T, index=clustered_regions.index,
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dask_kwargs=dict(scheduler=client),
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show_progress=False)
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heat_demand = cutout.heat_demand(
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matrix=M.T, index=clustered_regions.index)
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heat_demand.to_netcdf(snakemake.output[f"heat_demand_{area}"])
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heat_demand.to_netcdf(snakemake.output.heat_demand)
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@ -5,6 +5,7 @@ import atlite
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import pandas as pd
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import xarray as xr
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import numpy as np
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from dask.distributed import Client, LocalCluster
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if __name__ == '__main__':
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if 'snakemake' not in globals():
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@ -15,14 +16,9 @@ if __name__ == '__main__':
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clusters=48,
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)
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if 'snakemake' not in globals():
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from vresutils import Dict
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import yaml
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snakemake = Dict()
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with open('config.yaml') as f:
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snakemake.config = yaml.safe_load(f)
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snakemake.input = Dict()
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snakemake.output = Dict()
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nprocesses = int(snakemake.threads)
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cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1)
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client = Client(cluster, asynchronous=True)
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config = snakemake.config['solar_thermal']
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@ -35,18 +31,18 @@ if __name__ == '__main__':
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I = cutout.indicatormatrix(clustered_regions)
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for area in ["total", "rural", "urban"]:
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pop_layout = xr.open_dataarray(snakemake.input.pop_layout)
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pop_layout = xr.open_dataarray(snakemake.input[f'pop_layout_{area}'])
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stacked_pop = pop_layout.stack(spatial=('y', 'x'))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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stacked_pop = pop_layout.stack(spatial=('y', 'x'))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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nonzero_sum = M.sum(axis=0, keepdims=True)
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nonzero_sum[nonzero_sum == 0.] = 1.
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M_tilde = M / nonzero_sum
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nonzero_sum = M.sum(axis=0, keepdims=True)
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nonzero_sum[nonzero_sum == 0.] = 1.
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M_tilde = M / nonzero_sum
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solar_thermal = cutout.solar_thermal(**config, matrix=M_tilde.T,
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index=clustered_regions.index,
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dask_kwargs=dict(scheduler=client),
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show_progress=False)
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solar_thermal = cutout.solar_thermal(**config, matrix=M_tilde.T,
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index=clustered_regions.index)
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solar_thermal.to_netcdf(snakemake.output[f"solar_thermal_{area}"])
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solar_thermal.to_netcdf(snakemake.output.solar_thermal)
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@ -5,6 +5,7 @@ import atlite
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import pandas as pd
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import xarray as xr
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import numpy as np
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from dask.distributed import Client, LocalCluster
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if __name__ == '__main__':
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if 'snakemake' not in globals():
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@ -15,6 +16,10 @@ if __name__ == '__main__':
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clusters=48,
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)
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nprocesses = int(snakemake.threads)
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cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1)
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client = Client(cluster, asynchronous=True)
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time = pd.date_range(freq='h', **snakemake.config['snapshots'])
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cutout_config = snakemake.config['atlite']['cutout']
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cutout = atlite.Cutout(cutout_config).sel(time=time)
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@ -24,23 +29,25 @@ if __name__ == '__main__':
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I = cutout.indicatormatrix(clustered_regions)
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for area in ["total", "rural", "urban"]:
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pop_layout = xr.open_dataarray(snakemake.input.pop_layout)
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pop_layout = xr.open_dataarray(snakemake.input[f'pop_layout_{area}'])
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stacked_pop = pop_layout.stack(spatial=('y', 'x'))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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stacked_pop = pop_layout.stack(spatial=('y', 'x'))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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nonzero_sum = M.sum(axis=0, keepdims=True)
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nonzero_sum[nonzero_sum == 0.] = 1.
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M_tilde = M / nonzero_sum
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nonzero_sum = M.sum(axis=0, keepdims=True)
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nonzero_sum[nonzero_sum == 0.] = 1.
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M_tilde = M / nonzero_sum
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temp_air = cutout.temperature(
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matrix=M_tilde.T, index=clustered_regions.index,
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dask_kwargs=dict(scheduler=client),
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show_progress=False)
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temp_air = cutout.temperature(
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matrix=M_tilde.T, index=clustered_regions.index)
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temp_air.to_netcdf(snakemake.output.temp_air)
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temp_air.to_netcdf(snakemake.output[f"temp_air_{area}"])
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temp_soil = cutout.soil_temperature(
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matrix=M_tilde.T, index=clustered_regions.index,
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dask_kwargs=dict(scheduler=client),
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show_progress=False)
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temp_soil = cutout.soil_temperature(
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matrix=M_tilde.T, index=clustered_regions.index)
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temp_soil.to_netcdf(snakemake.output[f"temp_soil_{area}"])
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temp_soil.to_netcdf(snakemake.output.temp_soil)
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