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

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pre-commit-ci[bot] 2023-07-22 11:26:39 +00:00
parent d36bdaf6bb
commit 615684d124
3 changed files with 57 additions and 1043 deletions
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1070
notebooks/cross_border_data.ipynb
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File diff suppressed because one or more lines are too long

2
rules/validate.smk
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@ -7,7 +7,7 @@ PRODUCTION_PLOTS = [
"production_deviation_bar", "production_deviation_bar",
"seasonal_operation_area", "seasonal_operation_area",
] ]
CROSS_BORDER_PLOTS = ["trade_time_series","cross_border_bar"] CROSS_BORDER_PLOTS = ["trade_time_series", "cross_border_bar"]
PRICES_PLOTS = ["price_bar", "price_line"] PRICES_PLOTS = ["price_bar", "price_line"]

28
scripts/plot_validation_cross_border_flows.py
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@ -4,10 +4,10 @@
# #
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
import country_converter as coco
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import pandas as pd import pandas as pd
import pypsa import pypsa
import country_converter as coco
import seaborn as sns import seaborn as sns
from _helpers import configure_logging from _helpers import configure_logging
@ -51,6 +51,7 @@ color_country = {
"SK": "#d3e75a", "SK": "#d3e75a",
} }
def sort_one_country(country, df): def sort_one_country(country, df):
indices = [link for link in df.columns if country in link] indices = [link for link in df.columns if country in link]
df_country = df[indices].copy() df_country = df[indices].copy()
@ -64,10 +65,9 @@ def sort_one_country(country, df):
def cross_border_time_series(countries, data): def cross_border_time_series(countries, data):
fig, ax = plt.subplots(2 * len(countries), 1, figsize=(15, 10 * len(countries)))
fig, ax = plt.subplots(2*len(countries), 1, figsize=(15, 10*len(countries)))
axis = 0 axis = 0
for country in countries: for country in countries:
ymin = 0 ymin = 0
ymax = 0 ymax = 0
@ -88,7 +88,7 @@ def cross_border_time_series(countries, data):
title = "Historic" title = "Historic"
else: else:
title = "Optimized" title = "Optimized"
ax[axis].set_title( ax[axis].set_title(
title + " Import / Export for " + cc.convert(country, to="name_short") title + " Import / Export for " + cc.convert(country, to="name_short")
) )
@ -119,8 +119,8 @@ def cross_border_time_series(countries, data):
ymax = pos_max ymax = pos_max
axis = axis + 1 axis = axis + 1
for x in range(axis-2,axis): for x in range(axis - 2, axis):
ax[x].set_ylim([neg_min, pos_max]) ax[x].set_ylim([neg_min, pos_max])
fig.savefig(snakemake.output.trade_time_series, bbox_inches="tight") fig.savefig(snakemake.output.trade_time_series, bbox_inches="tight")
@ -154,12 +154,12 @@ def cross_border_bar(countries, data):
df_negative = pd.concat([df_negative_new, df_negative]) df_negative = pd.concat([df_negative_new, df_negative])
order = order + 1 order = order + 1
fig, ax = plt.subplots(figsize=(15, 60)) fig, ax = plt.subplots(figsize=(15, 60))
df_positive.plot.barh(ax=ax, stacked=True, color=color, zorder=2) df_positive.plot.barh(ax=ax, stacked=True, color=color, zorder=2)
df_negative.plot.barh(ax=ax, stacked=True, color=color, zorder=2) df_negative.plot.barh(ax=ax, stacked=True, color=color, zorder=2)
plt.grid(axis="x", zorder=0) plt.grid(axis="x", zorder=0)
plt.grid(axis="y", zorder=0) plt.grid(axis="y", zorder=0)
@ -212,7 +212,7 @@ if __name__ == "__main__":
# Preparing network data to be shaped similar to ENTSOE datastructure # Preparing network data to be shaped similar to ENTSOE datastructure
optimized_links = n.links_t.p0.rename( optimized_links = n.links_t.p0.rename(
columns=dict(n.links.bus0.str[:2] + " - " + n.links.bus1.str[:2]) columns=dict(n.links.bus0.str[:2] + " - " + n.links.bus1.str[:2])
) )
optimized_lines = n.lines_t.p0.rename( optimized_lines = n.lines_t.p0.rename(
columns=dict(n.lines.bus0.str[:2] + " - " + n.lines.bus1.str[:2]) columns=dict(n.lines.bus0.str[:2] + " - " + n.lines.bus1.str[:2])
@ -220,7 +220,9 @@ if __name__ == "__main__":
optimized = pd.concat([optimized_links, optimized_lines], axis=1) optimized = pd.concat([optimized_links, optimized_lines], axis=1)
# Drop internal country connection # Drop internal country connection
optimized.drop([c for c in optimized.columns if c[:2] == c[5:]], axis=1, inplace=True) optimized.drop(
[c for c in optimized.columns if c[:2] == c[5:]], axis=1, inplace=True
)
# align columns name # align columns name
for c1 in optimized.columns: for c1 in optimized.columns:
@ -230,7 +232,7 @@ if __name__ == "__main__":
optimized = optimized.groupby(lambda x: x, axis=1).sum() optimized = optimized.groupby(lambda x: x, axis=1).sum()
cross_border_bar(countries,[historic, optimized]) cross_border_bar(countries, [historic, optimized])
cross_border_time_series(countries, [historic, optimized]) cross_border_time_series(countries, [historic, optimized])