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remove plotting from workflow
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@doneachh
doneachh committed Jul 2, 2024
1 parent b734732 commit c3f103a
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Showing 2 changed files with 138 additions and 146 deletions.
5 changes: 3 additions & 2 deletions Snakefile
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Original file line number Diff line number Diff line change
Expand Up @@ -170,8 +170,9 @@ if not config["custom_data"]["gas_network"]:
),
output:
clustered_gas_network="resources/gas_networks/gas_network_elec_s{simpl}_{clusters}.csv",
gas_network_fig_1="resources/gas_networks/existing_gas_pipelines_{simpl}_{clusters}.png",
gas_network_fig_2="resources/gas_networks/clustered_gas_pipelines_{simpl}_{clusters}.png",
# TODO: Should be a own snakemake rule
# gas_network_fig_1="resources/gas_networks/existing_gas_pipelines_{simpl}_{clusters}.png",
# gas_network_fig_2="resources/gas_networks/clustered_gas_pipelines_{simpl}_{clusters}.png",
script:
"scripts/prepare_gas_network.py"

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279 changes: 135 additions & 144 deletions scripts/prepare_gas_network.py
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Original file line number Diff line number Diff line change
Expand Up @@ -739,148 +739,141 @@ def check_existence(row):
return merged_df


def plot_gas_network(pipelines, country_borders, bus_regions_onshore):
df = pipelines.copy()
df = gpd.overlay(df, country_borders, how="intersection")

if snakemake.params.gas_config["network_data"] == "IGGIELGN":
df = df.rename({"p_nom": "capacity [MW]"}, axis=1)

fig, ax = plt.subplots(1, 1)
fig.set_size_inches(12, 7)
bus_regions_onshore.to_crs(epsg=3857).plot(
ax=ax, color="white", edgecolor="darkgrey", linewidth=0.5
)
df.loc[(df.amount_states_passed > 1)].to_crs(epsg=3857).plot(
ax=ax,
column="capacity [MW]",
linewidth=2.5,
# linewidth=df['capacity [MW]'],
# alpha=0.8,
categorical=False,
cmap="viridis_r",
# legend=True,
# legend_kwds={'label':'Pipeline capacity [MW]'},
)

df.loc[(df.amount_states_passed <= 1)].to_crs(epsg=3857).plot(
ax=ax,
column="capacity [MW]",
linewidth=2.5,
# linewidth=df['capacity [MW]'],
alpha=0.5,
categorical=False,
# color='darkgrey',
ls="dotted",
)

# # Create custom legend handles for line types
# line_types = [ 'solid', 'dashed', 'dotted'] # solid
# legend_handles = [Line2D([0], [0], color='black', linestyle=line_type) for line_type in line_types]

# Define line types and labels
line_types = ["solid", "dotted"]
line_labels = ["Operating", "Not considered \n(within-state)"]

# Create custom legend handles for line types
legend_handles = [
Line2D([0], [0], color="black", linestyle=line_type, label=line_label)
for line_type, line_label in zip(line_types, line_labels)
]

# Add the line type legend
ax.legend(
handles=legend_handles,
title="Status",
borderpad=1,
title_fontproperties={"weight": "bold"},
fontsize=11,
loc=1,
)

# # create the colorbar
norm = colors.Normalize(
vmin=df["capacity [MW]"].min(), vmax=df["capacity [MW]"].max()
)
cbar = plt.cm.ScalarMappable(norm=norm, cmap="viridis_r")
# fig.colorbar(cbar, ax=ax).set_label('Capacity [MW]')

# add colorbar
ax_cbar = fig.colorbar(cbar, ax=ax, location="left", shrink=0.8, pad=0.01)
# add label for the colorbar
ax_cbar.set_label("Natural gas pipeline capacity [MW]", fontsize=15)

ax.set_axis_off()
fig.savefig(snakemake.output.gas_network_fig_1, dpi=300, bbox_inches="tight")


def plot_clustered_gas_network(pipelines, bus_regions_onshore):
# Create a new GeoDataFrame with centroids
centroids = bus_regions_onshore.copy()
centroids["geometry"] = centroids["geometry"].centroid
centroids["gadm_id"] = centroids["gadm_id"].apply(
lambda id: three_2_two_digits_country(id[:3]) + id[3:]
)
gdf1 = pd.merge(
pipelines, centroids, left_on=["bus0"], right_on=["gadm_id"], how="left"
)
gdf1.rename(columns={"geometry": "geometry_bus0"}, inplace=True)
pipe_links = pd.merge(
gdf1, centroids, left_on=["bus1"], right_on=["gadm_id"], how="left"
)
pipe_links.rename(columns={"geometry": "geometry_bus1"}, inplace=True)

# Create LineString geometries from the points
pipe_links["geometry"] = pipe_links.apply(
lambda row: LineString([row["geometry_bus0"], row["geometry_bus1"]]), axis=1
)

clustered = gpd.GeoDataFrame(pipe_links, geometry=pipe_links["geometry"])

# Optional: Set the coordinate reference system (CRS) if needed
clustered.crs = "EPSG:3857" # For example, WGS84

# plot pipelines
fig, ax = plt.subplots(1, 1)
fig.set_size_inches(12, 7)
bus_regions_onshore.to_crs(epsg=3857).plot(
ax=ax, color="white", edgecolor="darkgrey", linewidth=0.5
)
clustered.to_crs(epsg=3857).plot(
ax=ax,
column="capacity",
linewidth=1.5,
categorical=False,
cmap="plasma",
)

centroids.to_crs(epsg=3857).plot(
ax=ax,
color="red",
markersize=35,
alpha=0.5,
)

norm = colors.Normalize(
vmin=pipelines["capacity"].min(), vmax=pipelines["capacity"].max()
)
cbar = plt.cm.ScalarMappable(norm=norm, cmap="plasma")

# add colorbar
ax_cbar = fig.colorbar(cbar, ax=ax, location="left", shrink=0.8, pad=0.01)
# add label for the colorbar
ax_cbar.set_label("Natural gas pipeline capacity [MW]", fontsize=15)

ax.set_axis_off()
fig.savefig(snakemake.output.gas_network_fig_2, dpi=300, bbox_inches="tight")


# TODO: remove as soon as plotting is an extra rule
def plot_empty_dataframe():
fig, ax = plt.subplots(1, 1)
fig.set_size_inches(12, 7)
fig.savefig(snakemake.output.gas_network_fig_1, dpi=300, bbox_inches="tight")
fig.savefig(snakemake.output.gas_network_fig_2, dpi=300, bbox_inches="tight")
# TODO: Move it to a separate plotting rule!
# def plot_gas_network(pipelines, country_borders, bus_regions_onshore):
# df = pipelines.copy()
# df = gpd.overlay(df, country_borders, how="intersection")

# if snakemake.params.gas_config["network_data"] == "IGGIELGN":
# df = df.rename({"p_nom": "capacity [MW]"}, axis=1)

# fig, ax = plt.subplots(1, 1)
# fig.set_size_inches(12, 7)
# bus_regions_onshore.to_crs(epsg=3857).plot(
# ax=ax, color="white", edgecolor="darkgrey", linewidth=0.5
# )
# df.loc[(df.amount_states_passed > 1)].to_crs(epsg=3857).plot(
# ax=ax,
# column="capacity [MW]",
# linewidth=2.5,
# # linewidth=df['capacity [MW]'],
# # alpha=0.8,
# categorical=False,
# cmap="viridis_r",
# # legend=True,
# # legend_kwds={'label':'Pipeline capacity [MW]'},
# )

# df.loc[(df.amount_states_passed <= 1)].to_crs(epsg=3857).plot(
# ax=ax,
# column="capacity [MW]",
# linewidth=2.5,
# # linewidth=df['capacity [MW]'],
# alpha=0.5,
# categorical=False,
# # color='darkgrey',
# ls="dotted",
# )

# # # Create custom legend handles for line types
# # line_types = [ 'solid', 'dashed', 'dotted'] # solid
# # legend_handles = [Line2D([0], [0], color='black', linestyle=line_type) for line_type in line_types]

# # Define line types and labels
# line_types = ["solid", "dotted"]
# line_labels = ["Operating", "Not considered \n(within-state)"]

# # Create custom legend handles for line types
# legend_handles = [
# Line2D([0], [0], color="black", linestyle=line_type, label=line_label)
# for line_type, line_label in zip(line_types, line_labels)
# ]

# # Add the line type legend
# ax.legend(
# handles=legend_handles,
# title="Status",
# borderpad=1,
# title_fontproperties={"weight": "bold"},
# fontsize=11,
# loc=1,
# )

# # # create the colorbar
# norm = colors.Normalize(
# vmin=df["capacity [MW]"].min(), vmax=df["capacity [MW]"].max()
# )
# cbar = plt.cm.ScalarMappable(norm=norm, cmap="viridis_r")
# # fig.colorbar(cbar, ax=ax).set_label('Capacity [MW]')

# # add colorbar
# ax_cbar = fig.colorbar(cbar, ax=ax, location="left", shrink=0.8, pad=0.01)
# # add label for the colorbar
# ax_cbar.set_label("Natural gas pipeline capacity [MW]", fontsize=15)

# ax.set_axis_off()
# fig.savefig(snakemake.output.gas_network_fig_1, dpi=300, bbox_inches="tight")

# TODO: Move it to a separate plotting rule!
# def plot_clustered_gas_network(pipelines, bus_regions_onshore):
# # Create a new GeoDataFrame with centroids
# centroids = bus_regions_onshore.copy()
# centroids["geometry"] = centroids["geometry"].centroid
# centroids["gadm_id"] = centroids["gadm_id"].apply(
# lambda id: three_2_two_digits_country(id[:3]) + id[3:]
# )
# gdf1 = pd.merge(
# pipelines, centroids, left_on=["bus0"], right_on=["gadm_id"], how="left"
# )
# gdf1.rename(columns={"geometry": "geometry_bus0"}, inplace=True)
# pipe_links = pd.merge(
# gdf1, centroids, left_on=["bus1"], right_on=["gadm_id"], how="left"
# )
# pipe_links.rename(columns={"geometry": "geometry_bus1"}, inplace=True)

# # Create LineString geometries from the points
# pipe_links["geometry"] = pipe_links.apply(
# lambda row: LineString([row["geometry_bus0"], row["geometry_bus1"]]), axis=1
# )

# clustered = gpd.GeoDataFrame(pipe_links, geometry=pipe_links["geometry"])

# # Optional: Set the coordinate reference system (CRS) if needed
# clustered.crs = "EPSG:3857" # For example, WGS84

# # plot pipelines
# fig, ax = plt.subplots(1, 1)
# fig.set_size_inches(12, 7)
# bus_regions_onshore.to_crs(epsg=3857).plot(
# ax=ax, color="white", edgecolor="darkgrey", linewidth=0.5
# )
# clustered.to_crs(epsg=3857).plot(
# ax=ax,
# column="capacity",
# linewidth=1.5,
# categorical=False,
# cmap="plasma",
# )

# centroids.to_crs(epsg=3857).plot(
# ax=ax,
# color="red",
# markersize=35,
# alpha=0.5,
# )

# norm = colors.Normalize(
# vmin=pipelines["capacity"].min(), vmax=pipelines["capacity"].max()
# )
# cbar = plt.cm.ScalarMappable(norm=norm, cmap="plasma")

# # add colorbar
# ax_cbar = fig.colorbar(cbar, ax=ax, location="left", shrink=0.8, pad=0.01)
# # add label for the colorbar
# ax_cbar.set_label("Natural gas pipeline capacity [MW]", fontsize=15)

# ax.set_axis_off()
# fig.savefig(snakemake.output.gas_network_fig_2, dpi=300, bbox_inches="tight")


if not snakemake.params.custom_gas_network:
Expand Down Expand Up @@ -938,5 +931,3 @@ def plot_empty_dataframe():

pipelines = pd.DataFrame(pipelines)
pipelines.to_csv(snakemake.output.clustered_gas_network, index=False)

plot_empty_dataframe()

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