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[pre-commit.ci] auto fixes from pre-commit.com hooks

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pre-commit-ci[bot] 2023-09-11 21:03:58 +00:00
parent 823df52309
commit 3eed341044
5 changed files with 88 additions and 56 deletions
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4
scripts/_helpers.py
View File

@ -6,8 +6,8 @@
import contextlib import contextlib
import logging import logging
import os import os
import urllib
import re import re
import urllib
from pathlib import Path from pathlib import Path
import pandas as pd import pandas as pd
@ -25,6 +25,7 @@ REGION_COLS = ["geometry", "name", "x", "y", "country"]
def get_opt(opts, expr, flags=None): def get_opt(opts, expr, flags=None):
""" """
Return the first option matching the regular expression. Return the first option matching the regular expression.
The regular expression is case-insensitive by default. The regular expression is case-insensitive by default.
""" """
if flags is None: if flags is None:
@ -35,6 +36,7 @@ def get_opt(opts, expr, flags=None):
return match.group(0) return match.group(0)
return None return None
# Define a context manager to temporarily mute print statements # Define a context manager to temporarily mute print statements
@contextlib.contextmanager @contextlib.contextmanager
def mute_print(): def mute_print():

26
scripts/prepare_network.py
View File

@ -71,6 +71,7 @@ idx = pd.IndexSlice
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
def find_opt(opts, expr): def find_opt(opts, expr):
""" """
Return if available the float after the expression. Return if available the float after the expression.
@ -84,6 +85,7 @@ def find_opt(opts, expr):
return True, None return True, None
return False, None return False, None
def add_co2limit(n, co2limit, Nyears=1.0): def add_co2limit(n, co2limit, Nyears=1.0):
n.add( n.add(
"GlobalConstraint", "GlobalConstraint",
@ -314,7 +316,9 @@ if __name__ == "__main__":
nhours_enable_config = nhours_opts_config.get("enable", None) nhours_enable_config = nhours_opts_config.get("enable", None)
nhours_config = str(nhours_opts_config.get("hour", None)) + "h" nhours_config = str(nhours_opts_config.get("hour", None)) + "h"
nhours_wildcard = get_opt(opts, r"^\d+h$") nhours_wildcard = get_opt(opts, r"^\d+h$")
if nhours_wildcard is not None or (nhours_enable_config and nhours_config is not None): if nhours_wildcard is not None or (
nhours_enable_config and nhours_config is not None
):
nhours = nhours_wildcard or nhours_config nhours = nhours_wildcard or nhours_config
n = average_every_nhours(n, nhours) n = average_every_nhours(n, nhours)
@ -323,15 +327,21 @@ if __name__ == "__main__":
time_seg_enable_config = nhours_opts_config.get("enable", None) time_seg_enable_config = nhours_opts_config.get("enable", None)
time_seg_config = str(nhours_opts_config.get("hour", None)) + "seg" time_seg_config = str(nhours_opts_config.get("hour", None)) + "seg"
time_seg_wildcard = get_opt(opts, r"^\d+seg$") time_seg_wildcard = get_opt(opts, r"^\d+seg$")
if time_seg_wildcard is not None or (time_seg_enable_config and time_seg_config is not None): if time_seg_wildcard is not None or (
time_seg_enable_config and time_seg_config is not None
):
time_seg = time_seg_wildcard or time_seg_config time_seg = time_seg_wildcard or time_seg_config
solver_name = snakemake.config["solving"]["solver"]["name"] solver_name = snakemake.config["solving"]["solver"]["name"]
n = apply_time_segmentation(n, time_seg, solver_name) n = apply_time_segmentation(n, time_seg, solver_name)
Co2L_config = snakemake.params.co2limit_enable and isinstance(snakemake.params.co2limit,float) Co2L_config = snakemake.params.co2limit_enable and isinstance(
snakemake.params.co2limit, float
)
Co2L_wildcard, co2limit_wildcard = find_opt(opts, "Co2L") Co2L_wildcard, co2limit_wildcard = find_opt(opts, "Co2L")
if Co2L_wildcard or Co2L_config: if Co2L_wildcard or Co2L_config:
if co2limit_wildcard is not None: # TODO: what if you wat to determine the factor through the wildcard? if (
co2limit_wildcard is not None
): # TODO: what if you wat to determine the factor through the wildcard?
co2limit = co2limit_wildcard * snakemake.params.co2base co2limit = co2limit_wildcard * snakemake.params.co2base
add_co2limit(n, co2limit, Nyears) add_co2limit(n, co2limit, Nyears)
logger.info("Setting CO2 limit according to wildcard value.") logger.info("Setting CO2 limit according to wildcard value.")
@ -339,10 +349,14 @@ if __name__ == "__main__":
add_co2limit(n, snakemake.params.co2limit, Nyears) add_co2limit(n, snakemake.params.co2limit, Nyears)
logger.info("Setting CO2 limit according to config value.") logger.info("Setting CO2 limit according to config value.")
CH4L_config = snakemake.params.gaslimit_enable and isinstance(snakemake.params.gaslimit,float) CH4L_config = snakemake.params.gaslimit_enable and isinstance(
snakemake.params.gaslimit, float
)
CH4L_wildcard, gaslimit_wildcard = find_opt(opts, "CH4L") CH4L_wildcard, gaslimit_wildcard = find_opt(opts, "CH4L")
if CH4L_wildcard or CH4L_config: if CH4L_wildcard or CH4L_config:
if gaslimit_wildcard is not None: # TODO: what if you wat to determine the factor through the wildcard? if (
gaslimit_wildcard is not None
): # TODO: what if you wat to determine the factor through the wildcard?
gaslimit = gaslimit_wildcard * 1e6 gaslimit = gaslimit_wildcard * 1e6
add_gaslimit(n, gaslimit, Nyears) add_gaslimit(n, gaslimit, Nyears)
logger.info("Setting gas usage limit according to wildcard value.") logger.info("Setting gas usage limit according to wildcard value.")

34
scripts/prepare_sector_network.py
View File

@ -17,7 +17,7 @@ import numpy as np
import pandas as pd import pandas as pd
import pypsa import pypsa
import xarray as xr import xarray as xr
from _helpers import generate_periodic_profiles, update_config_with_sector_opts, get_opt from _helpers import generate_periodic_profiles, get_opt, update_config_with_sector_opts
from add_electricity import calculate_annuity, sanitize_carriers from add_electricity import calculate_annuity, sanitize_carriers
from build_energy_totals import build_co2_totals, build_eea_co2, build_eurostat_co2 from build_energy_totals import build_co2_totals, build_eea_co2, build_eurostat_co2
from networkx.algorithms import complement from networkx.algorithms import complement
@ -175,9 +175,13 @@ def emission_sectors_from_opts(opts):
"international navigation", "international navigation",
] ]
heat_and_industry = opts_config.get("industry",False) and opts_config.get("heating",False) heat_and_industry = opts_config.get("industry", False) and opts_config.get(
"heating", False
)
if ("I" in opts and "H" in opts and"A" in opts) or (heat_and_industry and opts_config.get("agriculture_machinery",False)): if ("I" in opts and "H" in opts and "A" in opts) or (
heat_and_industry and opts_config.get("agriculture_machinery", False)
):
sectors += ["agriculture"] sectors += ["agriculture"]
return sectors return sectors
@ -3264,7 +3268,9 @@ def set_temporal_aggregation(n, opts, solver_name):
nhours_enable_config = nhours_opts_config.get("enable", None) nhours_enable_config = nhours_opts_config.get("enable", None)
nhours_config = str(nhours_opts_config.get("hour", None)) + "H" nhours_config = str(nhours_opts_config.get("hour", None)) + "H"
nhours_wildcard = get_opt(opts, r"^\d+h$") nhours_wildcard = get_opt(opts, r"^\d+h$")
if nhours_wildcard is not None or (nhours_enable_config and nhours_config is not None): if nhours_wildcard is not None or (
nhours_enable_config and nhours_config is not None
):
nhours = nhours_wildcard or nhours_config nhours = nhours_wildcard or nhours_config
n = average_every_nhours(n, nhours) n = average_every_nhours(n, nhours)
return n return n
@ -3274,7 +3280,9 @@ def set_temporal_aggregation(n, opts, solver_name):
snapshots_enable_config = snapshots_opts_config.get("enable", None) snapshots_enable_config = snapshots_opts_config.get("enable", None)
snapshots_config = snapshots_opts_config.get("hour", None) snapshots_config = snapshots_opts_config.get("hour", None)
snapshots_wildcard = get_opt(opts, r"(^\d+)sn$") snapshots_wildcard = get_opt(opts, r"(^\d+)sn$")
if snapshots_wildcard is not None or (snapshots_enable_config and snapshots_config is not None): if snapshots_wildcard is not None or (
snapshots_enable_config and snapshots_config is not None
):
sn = int(snapshots_wildcard[:-2]) or snapshots_config sn = int(snapshots_wildcard[:-2]) or snapshots_config
logger.info(f"Use every {sn} snapshot as representative") logger.info(f"Use every {sn} snapshot as representative")
n.set_snapshots(n.snapshots[::sn]) n.set_snapshots(n.snapshots[::sn])
@ -3286,7 +3294,9 @@ def set_temporal_aggregation(n, opts, solver_name):
time_seg_enable_config = nhours_opts_config.get("enable", None) time_seg_enable_config = nhours_opts_config.get("enable", None)
time_seg_config = nhours_opts_config.get("hour", None) time_seg_config = nhours_opts_config.get("hour", None)
time_seg_wildcard = get_opt(opts, r"^(\d+)seg$") time_seg_wildcard = get_opt(opts, r"^(\d+)seg$")
if time_seg_wildcard is not None or (time_seg_enable_config and time_seg_config is not None): if time_seg_wildcard is not None or (
time_seg_enable_config and time_seg_config is not None
):
segments = int(time_seg_wildcard[:-3]) or time_seg_config segments = int(time_seg_wildcard[:-3]) or time_seg_config
logger.info(f"Use temporal segmentation with {segments} segments") logger.info(f"Use temporal segmentation with {segments} segments")
n = apply_time_segmentation(n, segments, solver_name=solver_name) n = apply_time_segmentation(n, segments, solver_name=solver_name)
@ -3320,7 +3330,9 @@ if __name__ == "__main__":
opts_config = snakemake.params.enable_sector opts_config = snakemake.params.enable_sector
heat_and_industry = opts_config.get("industry",False) and opts_config.get("heating",False) heat_and_industry = opts_config.get("industry", False) and opts_config.get(
"heating", False
)
investment_year = int(snakemake.wildcards.planning_horizons[-4:]) investment_year = int(snakemake.wildcards.planning_horizons[-4:])
@ -3393,10 +3405,14 @@ if __name__ == "__main__":
if "I" in opts or opts_config.get("industry", False): if "I" in opts or opts_config.get("industry", False):
add_industry(n, costs) add_industry(n, costs)
if ("I" in opts and "H" in opts) or (heat_and_industry and opts_config.get("waste_heat",False)): if ("I" in opts and "H" in opts) or (
heat_and_industry and opts_config.get("waste_heat", False)
):
add_waste_heat(n) add_waste_heat(n)
if ("I" in opts and "H" in opts and"A" in opts) or (heat_and_industry and opts_config.get("agriculture_machinery",False)): # requires H and I if ("I" in opts and "H" in opts and "A" in opts) or (
heat_and_industry and opts_config.get("agriculture_machinery", False)
): # requires H and I
add_agriculture(n, costs) add_agriculture(n, costs)
if options["dac"]: if options["dac"]: