2fc1ea0255
* some refactoring and code cleaning
* execute pre-commit
* pre-commit: limit large files
* add license to .pre-commit
* add pre-commit to env
* solve: tidy memory logger
* travis: add conda list for easier debugging
* undo config test/tutorial without plotting, rm matplotlibrc, .licenses
* remove {networks} wildcard
* unadd pre-commit config
* add release notes
* restore REUSE compliance
* fix docs environment python version
* env: remove gurobi from dependencies
* fix unclean merge block
* fix elif to if
* lighter rtd style
* lighter rtd style II
284 lines
10 KiB
Python
Executable File
284 lines
10 KiB
Python
Executable File
# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors
|
|
#
|
|
# SPDX-License-Identifier: GPL-3.0-or-later
|
|
|
|
"""
|
|
Plots map with pie charts and cost box bar charts.
|
|
|
|
Relevant Settings
|
|
-----------------
|
|
|
|
Inputs
|
|
------
|
|
|
|
Outputs
|
|
-------
|
|
|
|
Description
|
|
-----------
|
|
|
|
"""
|
|
|
|
import logging
|
|
from _helpers import (load_network_for_plots, aggregate_p, aggregate_costs,
|
|
configure_logging)
|
|
|
|
import pandas as pd
|
|
import numpy as np
|
|
from six.moves import zip
|
|
|
|
import cartopy.crs as ccrs
|
|
import matplotlib.pyplot as plt
|
|
import matplotlib as mpl
|
|
from matplotlib.patches import Circle, Ellipse
|
|
from matplotlib.legend_handler import HandlerPatch
|
|
to_rgba = mpl.colors.colorConverter.to_rgba
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
def make_handler_map_to_scale_circles_as_in(ax, dont_resize_actively=False):
|
|
fig = ax.get_figure()
|
|
def axes2pt():
|
|
return np.diff(ax.transData.transform([(0,0), (1,1)]), axis=0)[0] * (72./fig.dpi)
|
|
|
|
ellipses = []
|
|
if not dont_resize_actively:
|
|
def update_width_height(event):
|
|
dist = axes2pt()
|
|
for e, radius in ellipses: e.width, e.height = 2. * radius * dist
|
|
fig.canvas.mpl_connect('resize_event', update_width_height)
|
|
ax.callbacks.connect('xlim_changed', update_width_height)
|
|
ax.callbacks.connect('ylim_changed', update_width_height)
|
|
|
|
def legend_circle_handler(legend, orig_handle, xdescent, ydescent,
|
|
width, height, fontsize):
|
|
w, h = 2. * orig_handle.get_radius() * axes2pt()
|
|
e = Ellipse(xy=(0.5*width-0.5*xdescent, 0.5*height-0.5*ydescent), width=w, height=w)
|
|
ellipses.append((e, orig_handle.get_radius()))
|
|
return e
|
|
return {Circle: HandlerPatch(patch_func=legend_circle_handler)}
|
|
|
|
|
|
def make_legend_circles_for(sizes, scale=1.0, **kw):
|
|
return [Circle((0,0), radius=(s/scale)**0.5, **kw) for s in sizes]
|
|
|
|
|
|
def set_plot_style():
|
|
plt.style.use(['classic', 'seaborn-white',
|
|
{'axes.grid': False, 'grid.linestyle': '--', 'grid.color': u'0.6',
|
|
'hatch.color': 'white',
|
|
'patch.linewidth': 0.5,
|
|
'font.size': 12,
|
|
'legend.fontsize': 'medium',
|
|
'lines.linewidth': 1.5,
|
|
'pdf.fonttype': 42,
|
|
}])
|
|
|
|
|
|
def plot_map(n, ax=None, attribute='p_nom', opts={}):
|
|
if ax is None:
|
|
ax = plt.gca()
|
|
|
|
## DATA
|
|
line_colors = {'cur': "purple",
|
|
'exp': mpl.colors.rgb2hex(to_rgba("red", 0.7), True)}
|
|
tech_colors = opts['tech_colors']
|
|
|
|
if attribute == 'p_nom':
|
|
# bus_sizes = n.generators_t.p.sum().loc[n.generators.carrier == "load"].groupby(n.generators.bus).sum()
|
|
bus_sizes = pd.concat((n.generators.query('carrier != "load"').groupby(['bus', 'carrier']).p_nom_opt.sum(),
|
|
n.storage_units.groupby(['bus', 'carrier']).p_nom_opt.sum()))
|
|
line_widths_exp = dict(Line=n.lines.s_nom_opt, Link=n.links.p_nom_opt)
|
|
line_widths_cur = dict(Line=n.lines.s_nom_min, Link=n.links.p_nom_min)
|
|
else:
|
|
raise 'plotting of {} has not been implemented yet'.format(attribute)
|
|
|
|
|
|
line_colors_with_alpha = \
|
|
dict(Line=(line_widths_cur['Line'] / n.lines.s_nom > 1e-3)
|
|
.map({True: line_colors['cur'], False: to_rgba(line_colors['cur'], 0.)}),
|
|
Link=(line_widths_cur['Link'] / n.links.p_nom > 1e-3)
|
|
.map({True: line_colors['cur'], False: to_rgba(line_colors['cur'], 0.)}))
|
|
|
|
## FORMAT
|
|
linewidth_factor = opts['map'][attribute]['linewidth_factor']
|
|
bus_size_factor = opts['map'][attribute]['bus_size_factor']
|
|
|
|
## PLOT
|
|
n.plot(line_widths=pd.concat(line_widths_exp)/linewidth_factor,
|
|
line_colors=dict(Line=line_colors['exp'], Link=line_colors['exp']),
|
|
bus_sizes=bus_sizes/bus_size_factor,
|
|
bus_colors=tech_colors,
|
|
boundaries=map_boundaries,
|
|
geomap=True,
|
|
ax=ax)
|
|
n.plot(line_widths=pd.concat(line_widths_cur)/linewidth_factor,
|
|
line_colors=pd.concat(line_colors_with_alpha),
|
|
bus_sizes=0,
|
|
bus_colors=tech_colors,
|
|
boundaries=map_boundaries,
|
|
geomap=False,
|
|
ax=ax)
|
|
ax.set_aspect('equal')
|
|
ax.axis('off')
|
|
|
|
# Rasterize basemap
|
|
# TODO : Check if this also works with cartopy
|
|
for c in ax.collections[:2]: c.set_rasterized(True)
|
|
|
|
# LEGEND
|
|
handles = []
|
|
labels = []
|
|
|
|
for s in (10, 1):
|
|
handles.append(plt.Line2D([0],[0],color=line_colors['exp'],
|
|
linewidth=s*1e3/linewidth_factor))
|
|
labels.append("{} GW".format(s))
|
|
l1_1 = ax.legend(handles, labels,
|
|
loc="upper left", bbox_to_anchor=(0.24, 1.01),
|
|
frameon=False,
|
|
labelspacing=0.8, handletextpad=1.5,
|
|
title='Transmission Exist./Exp. ')
|
|
ax.add_artist(l1_1)
|
|
|
|
handles = []
|
|
labels = []
|
|
for s in (10, 5):
|
|
handles.append(plt.Line2D([0],[0],color=line_colors['cur'],
|
|
linewidth=s*1e3/linewidth_factor))
|
|
labels.append("/")
|
|
l1_2 = ax.legend(handles, labels,
|
|
loc="upper left", bbox_to_anchor=(0.26, 1.01),
|
|
frameon=False,
|
|
labelspacing=0.8, handletextpad=0.5,
|
|
title=' ')
|
|
ax.add_artist(l1_2)
|
|
|
|
handles = make_legend_circles_for([10e3, 5e3, 1e3], scale=bus_size_factor, facecolor="w")
|
|
labels = ["{} GW".format(s) for s in (10, 5, 3)]
|
|
l2 = ax.legend(handles, labels,
|
|
loc="upper left", bbox_to_anchor=(0.01, 1.01),
|
|
frameon=False, labelspacing=1.0,
|
|
title='Generation',
|
|
handler_map=make_handler_map_to_scale_circles_as_in(ax))
|
|
ax.add_artist(l2)
|
|
|
|
techs = (bus_sizes.index.levels[1]) & pd.Index(opts['vre_techs'] + opts['conv_techs'] + opts['storage_techs'])
|
|
handles = []
|
|
labels = []
|
|
for t in techs:
|
|
handles.append(plt.Line2D([0], [0], color=tech_colors[t], marker='o', markersize=8, linewidth=0))
|
|
labels.append(opts['nice_names'].get(t, t))
|
|
l3 = ax.legend(handles, labels, loc="upper center", bbox_to_anchor=(0.5, -0.), # bbox_to_anchor=(0.72, -0.05),
|
|
handletextpad=0., columnspacing=0.5, ncol=4, title='Technology')
|
|
|
|
return fig
|
|
|
|
|
|
def plot_total_energy_pie(n, ax=None):
|
|
if ax is None: ax = plt.gca()
|
|
|
|
ax.set_title('Energy per technology', fontdict=dict(fontsize="medium"))
|
|
|
|
e_primary = aggregate_p(n).drop('load', errors='ignore').loc[lambda s: s>0]
|
|
|
|
patches, texts, autotexts = ax.pie(e_primary,
|
|
startangle=90,
|
|
labels = e_primary.rename(opts['nice_names']).index,
|
|
autopct='%.0f%%',
|
|
shadow=False,
|
|
colors = [opts['tech_colors'][tech] for tech in e_primary.index])
|
|
for t1, t2, i in zip(texts, autotexts, e_primary.index):
|
|
if e_primary.at[i] < 0.04 * e_primary.sum():
|
|
t1.remove()
|
|
t2.remove()
|
|
|
|
def plot_total_cost_bar(n, ax=None):
|
|
if ax is None: ax = plt.gca()
|
|
|
|
total_load = (n.snapshot_weightings * n.loads_t.p.sum(axis=1)).sum()
|
|
tech_colors = opts['tech_colors']
|
|
|
|
def split_costs(n):
|
|
costs = aggregate_costs(n).reset_index(level=0, drop=True)
|
|
costs_ex = aggregate_costs(n, existing_only=True).reset_index(level=0, drop=True)
|
|
return (costs['capital'].add(costs['marginal'], fill_value=0.),
|
|
costs_ex['capital'], costs['capital'] - costs_ex['capital'], costs['marginal'])
|
|
|
|
costs, costs_cap_ex, costs_cap_new, costs_marg = split_costs(n)
|
|
|
|
costs_graph = pd.DataFrame(dict(a=costs.drop('load', errors='ignore')),
|
|
index=['AC-AC', 'AC line', 'onwind', 'offwind-ac',
|
|
'offwind-dc', 'solar', 'OCGT','CCGT', 'battery', 'H2']).dropna()
|
|
bottom = np.array([0., 0.])
|
|
texts = []
|
|
|
|
for i,ind in enumerate(costs_graph.index):
|
|
data = np.asarray(costs_graph.loc[ind])/total_load
|
|
ax.bar([0.5], data, bottom=bottom, color=tech_colors[ind],
|
|
width=0.7, zorder=-1)
|
|
bottom_sub = bottom
|
|
bottom = bottom+data
|
|
|
|
if ind in opts['conv_techs'] + ['AC line']:
|
|
for c in [costs_cap_ex, costs_marg]:
|
|
if ind in c:
|
|
data_sub = np.asarray([c.loc[ind]])/total_load
|
|
ax.bar([0.5], data_sub, linewidth=0,
|
|
bottom=bottom_sub, color=tech_colors[ind],
|
|
width=0.7, zorder=-1, alpha=0.8)
|
|
bottom_sub += data_sub
|
|
|
|
if abs(data[-1]) < 5:
|
|
continue
|
|
|
|
text = ax.text(1.1,(bottom-0.5*data)[-1]-3,opts['nice_names'].get(ind,ind))
|
|
texts.append(text)
|
|
|
|
ax.set_ylabel("Average system cost [Eur/MWh]")
|
|
ax.set_ylim([0, opts.get('costs_max', 80)])
|
|
ax.set_xlim([0, 1])
|
|
ax.set_xticklabels([])
|
|
ax.grid(True, axis="y", color='k', linestyle='dotted')
|
|
|
|
|
|
if __name__ == "__main__":
|
|
if 'snakemake' not in globals():
|
|
from _helpers import mock_snakemake
|
|
snakemake = mock_snakemake('plot_network', network='elec', simpl='',
|
|
clusters='5', ll='copt', opts='Co2L-24H',
|
|
attr='p_nom', ext="pdf")
|
|
configure_logging(snakemake)
|
|
|
|
set_plot_style()
|
|
|
|
opts = snakemake.config['plotting']
|
|
map_figsize = opts['map']['figsize']
|
|
map_boundaries = opts['map']['boundaries']
|
|
|
|
n = load_network_for_plots(snakemake.input.network, snakemake.input.tech_costs, snakemake.config)
|
|
|
|
scenario_opts = snakemake.wildcards.opts.split('-')
|
|
|
|
fig, ax = plt.subplots(figsize=map_figsize, subplot_kw={"projection": ccrs.PlateCarree()})
|
|
plot_map(n, ax, snakemake.wildcards.attr, opts)
|
|
|
|
fig.savefig(snakemake.output.only_map, dpi=150, bbox_inches='tight')
|
|
|
|
ax1 = fig.add_axes([-0.115, 0.625, 0.2, 0.2])
|
|
plot_total_energy_pie(n, ax1)
|
|
|
|
ax2 = fig.add_axes([-0.075, 0.1, 0.1, 0.45])
|
|
plot_total_cost_bar(n, ax2)
|
|
|
|
ll = snakemake.wildcards.ll
|
|
ll_type = ll[0]
|
|
ll_factor = ll[1:]
|
|
lbl = dict(c='line cost', v='line volume')[ll_type]
|
|
amnt = '{ll} x today\'s'.format(ll=ll_factor) if ll_factor != 'opt' else 'optimal'
|
|
fig.suptitle('Expansion to {amount} {label} at {clusters} clusters'
|
|
.format(amount=amnt, label=lbl, clusters=snakemake.wildcards.clusters))
|
|
|
|
fig.savefig(snakemake.output.ext, transparent=True, bbox_inches='tight')
|