adjust summary and plot functions
This commit is contained in:
lisazeyen
parent
c963d356f7
commit
97f041e82c
@ -150,7 +150,7 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
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to_drop = costs.index.levels[0].symmetric_difference(n.buses.index)
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if len(to_drop) != 0:
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print("dropping non-buses", to_drop)
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costs.drop(to_drop, level=0, inplace=True, axis=0)
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costs.drop(to_drop, level=0, inplace=True, axis=0, errors="ignore")
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# make sure they are removed from index
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costs.index = pd.MultiIndex.from_tuples(costs.index.values)
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@ -251,19 +251,19 @@ def plot_h2_map(network):
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# Drop non-electric buses so they don't clutter the plot
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n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
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elec = n.links.index[n.links.carrier == "H2 Electrolysis"]
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elec = n.links[n.links.carrier.isin(["H2 Electrolysis", "H2 Fuel Cell"])].index
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bus_sizes = n.links.loc[elec,"p_nom_opt"].groupby(n.links.loc[elec,"bus0"]).sum() / bus_size_factor
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bus_sizes = n.links.loc[elec,"p_nom_opt"].groupby([n.links["bus0"], n.links.carrier]).sum() / bus_size_factor
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# make a fake MultiIndex so that area is correct for legend
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bus_sizes.index = pd.MultiIndex.from_product(
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[bus_sizes.index, ["electrolysis"]])
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bus_sizes.rename(index=lambda x: x.replace(" H2", ""), level=0, inplace=True)
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n.links.drop(n.links.index[n.links.carrier != "H2 pipeline"], inplace=True)
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n.links.drop(n.links.index[~n.links.carrier.str.contains("H2 pipeline")], inplace=True)
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link_widths = n.links.p_nom_opt / linewidth_factor
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link_widths[n.links.p_nom_opt < line_lower_threshold] = 0.
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n.links.bus0 = n.links.bus0.str.replace(" H2", "")
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n.links.bus1 = n.links.bus1.str.replace(" H2", "")
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@ -276,7 +276,8 @@ def plot_h2_map(network):
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fig.set_size_inches(7, 6)
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n.plot(bus_sizes=bus_sizes,
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bus_colors={"electrolysis": bus_color},
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bus_colors={"H2 Electrolysis": bus_color,
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"H2 Fuel Cell": "slateblue"},
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link_colors=link_color,
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link_widths=link_widths,
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branch_components=["Link"],
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@ -311,6 +312,266 @@ def plot_h2_map(network):
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bbox_inches="tight")
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def plot_ch4_map(network):
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n = network.copy()
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supply_energy = get_nodal_balance().droplevel([0,1]).sort_index()
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if "Gas pipeline" not in n.links.carrier.unique():
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return
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assign_location(n)
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bus_size_factor = 1e7
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linewidth_factor = 1e4
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# MW below which not drawn
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line_lower_threshold = 5e3
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bus_color = "maroon"
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link_color = "lightcoral"
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# Drop non-electric buses so they don't clutter the plot
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n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
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elec = n.generators[n.generators.carrier=="gas"].index
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methanation_i = n.links[n.links.carrier.isin(["helmeth", "Sabatier"])].index
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bus_sizes = n.generators_t.p.loc[:,elec].mul(n.snapshot_weightings, axis=0).sum().groupby(n.generators.loc[elec,"bus"]).sum() / bus_size_factor
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bus_sizes.rename(index=lambda x: x.replace(" gas", ""), inplace=True)
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bus_sizes = bus_sizes.reindex(n.buses.index).fillna(0)
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bus_sizes.index = pd.MultiIndex.from_product(
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[bus_sizes.index, ["fossil gas"]])
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methanation = abs(n.links_t.p1.loc[:,methanation_i].mul(n.snapshot_weightings, axis=0)).sum().groupby(n.links.loc[methanation_i,"bus1"]).sum() / bus_size_factor
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methanation = methanation.groupby(methanation.index).sum().rename(index=lambda x: x.replace(" gas", ""))
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# make a fake MultiIndex so that area is correct for legend
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methanation.index = pd.MultiIndex.from_product(
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[methanation.index, ["methanation"]])
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biogas_i = n.stores[n.stores.carrier=="biogas"].index
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biogas = n.stores_t.p.loc[:,biogas_i].mul(n.snapshot_weightings, axis=0).sum().groupby(n.stores.loc[biogas_i,"bus"]).sum() / bus_size_factor
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biogas = biogas.groupby(biogas.index).sum().rename(index=lambda x: x.replace(" biogas", ""))
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# make a fake MultiIndex so that area is correct for legend
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biogas.index = pd.MultiIndex.from_product(
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[biogas.index, ["biogas"]])
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bus_sizes = pd.concat([bus_sizes, methanation, biogas])
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bus_sizes.sort_index(inplace=True)
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n.links.drop(n.links.index[n.links.carrier != "Gas pipeline"], inplace=True)
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link_widths = n.links.p_nom_opt / linewidth_factor
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link_widths[n.links.p_nom_opt < line_lower_threshold] = 0.
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n.links.bus0 = n.links.bus0.str.replace(" gas", "")
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n.links.bus1 = n.links.bus1.str.replace(" gas", "")
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print(link_widths.sort_values())
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print(n.links[["bus0", "bus1"]])
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fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
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fig.set_size_inches(7, 6)
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n.plot(bus_sizes=bus_sizes,
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bus_colors={"fossil gas": bus_color,
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"methanation": "steelblue",
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"biogas": "seagreen"},
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link_colors=link_color,
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link_widths=link_widths,
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branch_components=["Link"],
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ax=ax, boundaries=(-10, 30, 34, 70))
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handles = make_legend_circles_for(
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[200, 1000], scale=bus_size_factor, facecolor=bus_color)
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labels = ["{} MW".format(s) for s in (200, 1000)]
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l2 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.01, 1.01),
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labelspacing=1.0,
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framealpha=1.,
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title='Biomass potential',
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handler_map=make_handler_map_to_scale_circles_as_in(ax))
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ax.add_artist(l2)
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handles = []
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labels = []
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for s in (50, 10):
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handles.append(plt.Line2D([0], [0], color=link_color,
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linewidth=s * 1e3 / linewidth_factor))
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labels.append("{} GW".format(s))
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l1_1 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.30, 1.01),
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framealpha=1,
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labelspacing=0.8, handletextpad=1.5,
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title='CH4 pipeline capacity')
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ax.add_artist(l1_1)
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fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_network"), transparent=True,
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bbox_inches="tight")
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##################################################
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supply_energy.drop("Gas pipeline", level=1, inplace=True)
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supply_energy = supply_energy[abs(supply_energy)>5]
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supply_energy.rename(index=lambda x: x.replace(" gas",""), level=0, inplace=True)
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demand = supply_energy[supply_energy<0].groupby(level=[0,1]).sum()
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supply = supply_energy[supply_energy>0].groupby(level=[0,1]).sum()
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#### DEMAND #######################################
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bus_size_factor = 2e7
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bus_sizes = abs(demand) / bus_size_factor
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fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
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fig.set_size_inches(7, 6)
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n.plot(bus_sizes=bus_sizes,
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bus_colors={"CHP": "r",
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"OCGT": "wheat",
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"SMR": "darkkhaki",
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"SMR CC": "tan",
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"gas boiler": "orange",
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"gas for industry": "grey",
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'gas for industry CC': "lightgrey"},
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link_colors=link_color,
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link_widths=link_widths,
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branch_components=["Link"],
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ax=ax, boundaries=(-10, 30, 34, 70))
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handles = make_legend_circles_for(
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[10e6, 20e6], scale=bus_size_factor, facecolor=bus_color)
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labels = ["{} TWh".format(s) for s in (10, 20)]
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l2 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.01, 1.01),
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labelspacing=1.0,
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framealpha=1.,
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title='CH4 demand',
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handler_map=make_handler_map_to_scale_circles_as_in(ax))
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ax.add_artist(l2)
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handles = []
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labels = []
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for s in (50, 10):
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handles.append(plt.Line2D([0], [0], color=link_color,
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linewidth=s * 1e3 / linewidth_factor))
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labels.append("{} GW".format(s))
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l1_1 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.30, 1.01),
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framealpha=1,
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labelspacing=0.8, handletextpad=1.5,
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title='CH4 pipeline capacity')
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ax.add_artist(l1_1)
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fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_demand"), transparent=True,
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bbox_inches="tight")
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#### SUPPLY #######################################
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bus_size_factor = 2e7
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bus_sizes = supply / bus_size_factor
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fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
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fig.set_size_inches(7, 6)
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n.plot(bus_sizes=bus_sizes,
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bus_colors={"gas": "maroon",
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"methanation": "steelblue",
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"helmeth": "slateblue",
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"biogas": "seagreen"},
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link_colors=link_color,
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link_widths=link_widths,
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branch_components=["Link"],
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ax=ax, boundaries=(-10, 30, 34, 70))
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handles = make_legend_circles_for(
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[10e6, 20e6], scale=bus_size_factor, facecolor="black")
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labels = ["{} TWh".format(s) for s in (10, 20)]
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l2 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.01, 1.01),
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labelspacing=1.0,
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framealpha=1.,
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title='CH4 supply',
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handler_map=make_handler_map_to_scale_circles_as_in(ax))
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ax.add_artist(l2)
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handles = []
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labels = []
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for s in (50, 10):
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handles.append(plt.Line2D([0], [0], color=link_color,
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linewidth=s * 1e3 / linewidth_factor))
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labels.append("{} GW".format(s))
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l1_1 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.30, 1.01),
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framealpha=1,
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labelspacing=0.8, handletextpad=1.5,
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title='CH4 pipeline capacity')
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ax.add_artist(l1_1)
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fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_supply"), transparent=True,
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bbox_inches="tight")
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###########################################################################
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net = pd.concat([demand.groupby(level=0).sum().rename("demand"),
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supply.groupby(level=0).sum().rename("supply")], axis=1).sum(axis=1)
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mask = net>0
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net_importer = net.mask(mask).rename("net_importer")
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net_exporter = net.mask(~mask).rename("net_exporter")
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bus_size_factor = 2e7
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linewidth_factor = 1e-1
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bus_sizes = pd.concat([abs(net_importer), net_exporter], axis=1).fillna(0).stack() / bus_size_factor
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link_widths = abs(n.links_t.p0).max().loc[n.links.index] / n.links.p_nom_opt
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link_widths /= linewidth_factor
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fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
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fig.set_size_inches(7, 6)
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n.plot(bus_sizes=bus_sizes,
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bus_colors={"net_importer": "r",
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"net_exporter": "darkgreen",
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},
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link_colors="lightgrey",
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link_widths=link_widths,
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branch_components=["Link"],
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ax=ax, boundaries=(-10, 30, 34, 70))
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handles = make_legend_circles_for(
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[10e6, 20e6], scale=bus_size_factor, facecolor="black")
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labels = ["{} TWh".format(s) for s in (10, 20)]
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l2 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.01, 1.01),
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labelspacing=1.0,
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framealpha=1.,
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title='Net Import/Export',
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handler_map=make_handler_map_to_scale_circles_as_in(ax))
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ax.add_artist(l2)
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handles = []
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labels = []
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for s in (0.5, 1):
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handles.append(plt.Line2D([0], [0], color="lightgrey",
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linewidth=s / linewidth_factor))
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labels.append("{} per unit".format(s))
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l1_1 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.30, 1.01),
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framealpha=1,
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labelspacing=0.8, handletextpad=1.5,
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title='maximum used CH4 pipeline capacity')
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ax.add_artist(l1_1)
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fig.savefig(snakemake.output.map.replace("-costs-all","-ch4_net_balance"), transparent=True,
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bbox_inches="tight")
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def plot_map_without(network):
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n = network.copy()
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@ -331,7 +592,8 @@ def plot_map_without(network):
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dc_color = "m"
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# hack because impossible to drop buses...
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n.buses.loc["EU gas", ["x", "y"]] = n.buses.loc["DE0 0", ["x", "y"]]
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if "EU gas" in n.buses.index:
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n.buses.loc["EU gas", ["x", "y"]] = n.buses.loc["DE0 0", ["x", "y"]]
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n.links.drop(n.links.index[(n.links.carrier != "DC") & (
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n.links.carrier != "B2B")], inplace=True)
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@ -502,35 +764,59 @@ def plot_series(network, carrier="AC", name="test"):
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transparent=True)
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def get_nodal_balance(carrier="gas"):
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bus_map = (n.buses.carrier == carrier)
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bus_map.at[""] = False
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supply_energy = pd.Series(dtype="float64")
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for c in n.iterate_components(n.one_port_components):
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items = c.df.index[c.df.bus.map(bus_map).fillna(False)]
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if len(items) == 0:
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continue
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s = round(c.pnl.p.multiply(n.snapshot_weightings,axis=0).sum().multiply(c.df['sign']).loc[items]
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.groupby([c.df.bus, c.df.carrier]).sum())
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s = pd.concat([s], keys=[c.list_name])
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s = pd.concat([s], keys=[carrier])
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supply_energy = supply_energy.reindex(s.index.union(supply_energy.index))
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supply_energy.loc[s.index] = s
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for c in n.iterate_components(n.branch_components):
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for end in [col[3:] for col in c.df.columns if col[:3] == "bus"]:
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items = c.df.index[c.df["bus" + str(end)].map(bus_map,na_action=False)]
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if len(items) == 0:
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continue
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s = ((-1)*c.pnl["p"+end][items].multiply(n.snapshot_weightings,axis=0).sum()
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.groupby([c.df.loc[items,'bus{}'.format(end)], c.df.loc[items,'carrier']]).sum())
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s.index = s.index
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s = pd.concat([s], keys=[c.list_name])
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s = pd.concat([s], keys=[carrier])
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supply_energy = supply_energy.reindex(s.index.union(supply_energy.index))
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supply_energy.loc[s.index] = s
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supply_energy = supply_energy.rename(index=lambda x: rename_techs(x), level=3)
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return supply_energy
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# %%
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if __name__ == "__main__":
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# Detect running outside of snakemake and mock snakemake for testing
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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.config['run'] = "retro_vs_noretro"
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snakemake.wildcards = {"lv": "1.0"} # lv1.0, lv1.25, lvopt
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name = "elec_s_48_lv{}__Co2L0-3H-T-H-B".format(snakemake.wildcards["lv"])
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suffix = "_retro_tes"
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name = name + suffix
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snakemake.input = Dict()
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snakemake.output = Dict(
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map=(snakemake.config['results_dir'] + snakemake.config['run']
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+ "/maps/{}".format(name)),
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today=(snakemake.config['results_dir'] + snakemake.config['run']
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+ "/maps/{}.pdf".format(name)))
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snakemake.input.scenario = "lv" + snakemake.wildcards["lv"]
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# snakemake.config["run"] = "bio_costs"
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path = snakemake.config['results_dir'] + snakemake.config['run']
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snakemake.input.network = (path +
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"/postnetworks/{}.nc"
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.format(name))
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snakemake.output.network = (path +
|
||||
"/maps/{}"
|
||||
.format(name))
|
||||
from helper import mock_snakemake
|
||||
snakemake = mock_snakemake('plot_network',
|
||||
network='elec', simpl='', clusters='128',
|
||||
lv='1.0', opts='', planning_horizons='2030',
|
||||
sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1')
|
||||
|
||||
n = pypsa.Network(snakemake.input.network,
|
||||
override_component_attrs=override_component_attrs)
|
||||
@ -539,6 +825,7 @@ if __name__ == "__main__":
|
||||
bus_size_factor=1.5e10, transmission=False)
|
||||
|
||||
plot_h2_map(n)
|
||||
plot_ch4_map(n)
|
||||
plot_map_without(n)
|
||||
|
||||
#plot_series(n, carrier="AC", name=suffix)
|
||||
|
||||
@ -22,7 +22,8 @@ def rename_techs(label):
|
||||
"retrofitting" : "building retrofitting",
|
||||
"H2" : "hydrogen storage",
|
||||
"battery" : "battery storage",
|
||||
"CC" : "CC"}
|
||||
#"CC" : "CC"
|
||||
}
|
||||
|
||||
rename = {"solar" : "solar PV",
|
||||
"Sabatier" : "methanation",
|
||||
@ -258,7 +259,7 @@ def historical_emissions(cts):
|
||||
e["domestic navigation"] = "1.A.3.d - Domestic Navigation"
|
||||
e['international navigation'] = '1.D.1.b - International Navigation'
|
||||
e["domestic aviation"] = '1.A.3.a - Domestic Aviation'
|
||||
e["international aviation"] = '1.D.1.a - International Aviation'
|
||||
e["international aviation"] = '1.D.1.a - International Aviation'
|
||||
e['total energy'] = '1 - Energy'
|
||||
e['industrial processes'] = '2 - Industrial Processes and Product Use'
|
||||
e['agriculture'] = '3 - Agriculture'
|
||||
@ -268,25 +269,25 @@ def historical_emissions(cts):
|
||||
e['indirect'] = 'ind_CO2 - Indirect CO2'
|
||||
e["total wL"] = "Total (with LULUCF)"
|
||||
e["total woL"] = "Total (without LULUCF)"
|
||||
|
||||
pol = ["CO2"] # ["All greenhouse gases - (CO2 equivalent)"]
|
||||
|
||||
pol = ["CO2"] # ["All greenhouse gases - (CO2 equivalent)"]
|
||||
cts
|
||||
if "GB" in cts:
|
||||
cts.remove("GB")
|
||||
cts.append("UK")
|
||||
|
||||
|
||||
year = np.arange(1990,2018).tolist()
|
||||
|
||||
idx = pd.IndexSlice
|
||||
co2_totals = df.loc[idx[year,e.values,cts,pol],"emissions"].unstack("Year").rename(index=pd.Series(e.index,e.values))
|
||||
|
||||
co2_totals = df.loc[idx[year,e.values,cts,pol],"emissions"].unstack("Year").rename(index=pd.Series(e.index,e.values))
|
||||
|
||||
co2_totals = (1/1e6)*co2_totals.groupby(level=0, axis=0).sum() #Gton CO2
|
||||
|
||||
co2_totals.loc['industrial non-elec'] = co2_totals.loc['total energy'] - co2_totals.loc[['electricity', 'services non-elec','residential non-elec', 'road non-elec',
|
||||
'rail non-elec', 'domestic aviation', 'international aviation', 'domestic navigation',
|
||||
'international navigation']].sum()
|
||||
|
||||
emissions = co2_totals.loc["electricity"]
|
||||
emissions = co2_totals.loc["electricity"]
|
||||
if "T" in opts:
|
||||
emissions += co2_totals.loc[[i+ " non-elec" for i in ["rail","road"]]].sum()
|
||||
if "H" in opts:
|
||||
@ -294,7 +295,7 @@ def historical_emissions(cts):
|
||||
if "I" in opts:
|
||||
emissions += co2_totals.loc[["industrial non-elec","industrial processes",
|
||||
"domestic aviation","international aviation",
|
||||
"domestic navigation","international navigation"]].sum()
|
||||
"domestic navigation","international navigation"]].sum()
|
||||
return emissions
|
||||
|
||||
|
||||
@ -302,8 +303,8 @@ def historical_emissions(cts):
|
||||
def plot_carbon_budget_distribution():
|
||||
"""
|
||||
Plot historical carbon emissions in the EU and decarbonization path
|
||||
"""
|
||||
|
||||
"""
|
||||
|
||||
import matplotlib.gridspec as gridspec
|
||||
import seaborn as sns; sns.set()
|
||||
sns.set_style('ticks')
|
||||
@ -311,7 +312,7 @@ def plot_carbon_budget_distribution():
|
||||
plt.rcParams['xtick.direction'] = 'in'
|
||||
plt.rcParams['ytick.direction'] = 'in'
|
||||
plt.rcParams['xtick.labelsize'] = 20
|
||||
plt.rcParams['ytick.labelsize'] = 20
|
||||
plt.rcParams['ytick.labelsize'] = 20
|
||||
|
||||
plt.figure(figsize=(10, 7))
|
||||
gs1 = gridspec.GridSpec(1, 1)
|
||||
@ -319,55 +320,55 @@ def plot_carbon_budget_distribution():
|
||||
ax1.set_ylabel('CO$_2$ emissions (Gt per year)',fontsize=22)
|
||||
ax1.set_ylim([0,5])
|
||||
ax1.set_xlim([1990,snakemake.config['scenario']['planning_horizons'][-1]+1])
|
||||
|
||||
|
||||
path_cb = snakemake.config['results_dir'] + snakemake.config['run'] + '/csvs/'
|
||||
countries=pd.read_csv(path_cb + 'countries.csv', index_col=1)
|
||||
countries=pd.read_csv(path_cb + 'countries.csv', index_col=1)
|
||||
cts=countries.index.to_list()
|
||||
e_1990 = co2_emissions_year(cts, opts, year=1990)
|
||||
CO2_CAP=pd.read_csv(path_cb + 'carbon_budget_distribution.csv',
|
||||
index_col=0)
|
||||
|
||||
|
||||
ax1.plot(e_1990*CO2_CAP[o],linewidth=3,
|
||||
e_1990 = co2_emissions_year(cts, opts, year=1990)
|
||||
CO2_CAP=pd.read_csv(path_cb + 'carbon_budget_distribution.csv',
|
||||
index_col=0)
|
||||
|
||||
|
||||
ax1.plot(e_1990*CO2_CAP[o],linewidth=3,
|
||||
color='dodgerblue', label=None)
|
||||
|
||||
|
||||
emissions = historical_emissions(cts)
|
||||
|
||||
ax1.plot(emissions, color='black', linewidth=3, label=None)
|
||||
|
||||
#plot commited and uder-discussion targets
|
||||
ax1.plot(emissions, color='black', linewidth=3, label=None)
|
||||
|
||||
#plot commited and uder-discussion targets
|
||||
#(notice that historical emissions include all countries in the
|
||||
# network, but targets refer to EU)
|
||||
ax1.plot([2020],[0.8*emissions[1990]],
|
||||
marker='*', markersize=12, markerfacecolor='black',
|
||||
markeredgecolor='black')
|
||||
|
||||
markeredgecolor='black')
|
||||
|
||||
ax1.plot([2030],[0.45*emissions[1990]],
|
||||
marker='*', markersize=12, markerfacecolor='white',
|
||||
markeredgecolor='black')
|
||||
|
||||
markeredgecolor='black')
|
||||
|
||||
ax1.plot([2030],[0.6*emissions[1990]],
|
||||
marker='*', markersize=12, markerfacecolor='black',
|
||||
markeredgecolor='black')
|
||||
|
||||
|
||||
ax1.plot([2050, 2050],[x*emissions[1990] for x in [0.2, 0.05]],
|
||||
color='gray', linewidth=2, marker='_', alpha=0.5)
|
||||
|
||||
color='gray', linewidth=2, marker='_', alpha=0.5)
|
||||
|
||||
ax1.plot([2050],[0.01*emissions[1990]],
|
||||
marker='*', markersize=12, markerfacecolor='white',
|
||||
linewidth=0, markeredgecolor='black',
|
||||
label='EU under-discussion target', zorder=10,
|
||||
clip_on=False)
|
||||
|
||||
marker='*', markersize=12, markerfacecolor='white',
|
||||
linewidth=0, markeredgecolor='black',
|
||||
label='EU under-discussion target', zorder=10,
|
||||
clip_on=False)
|
||||
|
||||
ax1.plot([2050],[0.125*emissions[1990]],'ro',
|
||||
marker='*', markersize=12, markerfacecolor='black',
|
||||
markeredgecolor='black', label='EU commited target')
|
||||
|
||||
ax1.legend(fancybox=True, fontsize=18, loc=(0.01,0.01),
|
||||
facecolor='white', frameon=True)
|
||||
|
||||
path_cb_plot = snakemake.config['results_dir'] + snakemake.config['run'] + '/graphs/'
|
||||
plt.savefig(path_cb_plot+'carbon_budget_plot.pdf', dpi=300)
|
||||
|
||||
ax1.legend(fancybox=True, fontsize=18, loc=(0.01,0.01),
|
||||
facecolor='white', frameon=True)
|
||||
|
||||
path_cb_plot = snakemake.config['results_dir'] + snakemake.config['run'] + '/graphs/'
|
||||
plt.savefig(path_cb_plot+'carbon_budget_plot.pdf', dpi=300)
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Detect running outside of snakemake and mock snakemake for testing
|
||||
@ -380,15 +381,15 @@ if __name__ == "__main__":
|
||||
snakemake.input = Dict()
|
||||
snakemake.output = Dict()
|
||||
snakemake.wildcards = Dict()
|
||||
#snakemake.wildcards['sector_opts']='3H-T-H-B-I-solar3-dist1-cb48be3'
|
||||
|
||||
#snakemake.wildcards['sector_opts']='3H-T-H-B-I-solar3-dist1-cb48be3'
|
||||
|
||||
for item in ["costs", "energy"]:
|
||||
snakemake.input[item] = snakemake.config['summary_dir'] + '/{name}/csvs/{item}.csv'.format(name=snakemake.config['run'],item=item)
|
||||
snakemake.output[item] = snakemake.config['summary_dir'] + '/{name}/graphs/{item}.pdf'.format(name=snakemake.config['run'],item=item)
|
||||
snakemake.input["balances"] = snakemake.config['summary_dir'] + '/{name}/csvs/supply_energy.csv'.format(name=snakemake.config['run'],item=item)
|
||||
snakemake.output["balances"] = snakemake.config['summary_dir'] + '/{name}/graphs/balances-energy.csv'.format(name=snakemake.config['run'],item=item)
|
||||
|
||||
|
||||
|
||||
|
||||
n_header = 4
|
||||
|
||||
plot_costs()
|
||||
@ -396,7 +397,7 @@ if __name__ == "__main__":
|
||||
plot_energy()
|
||||
|
||||
plot_balances()
|
||||
|
||||
|
||||
for sector_opts in snakemake.config['scenario']['sector_opts']:
|
||||
opts=sector_opts.split('-')
|
||||
for o in opts:
|
||||
|
||||
Loading…
Reference in New Issue
Block a user