def draw_component_loss_barchart_v2(scenario,
ctype_loss_vals_tot,
ctype_loss_by_type,
sc_haz_val_str,
fig_name):
""" Plots bar charts of direct economic losses for components types """
bar_width = 0.3
bar_offset = 0.03
bar_clr_1 = spl.COLR_SET1[0]
bar_clr_2 = spl.COLR_SET1[1]
cpt = [spl.split_long_label(x,delims=[' ', '_'], max_chars_per_line=22)
for x in ctype_resp_sorted.index.tolist()]
pos = np.arange(0, len(cpt))
fig = plt.figure(figsize=(4.5, len(pos)*0.6), facecolor='white')
axes = fig.add_subplot(111, axisbg='white')
# Economic loss:
# - Contribution to % loss of total system, by components type
# - Percentage econ loss for all components of a specific type
axes.barh(
pos-bar_width-bar_offset, ctype_loss_vals_tot, bar_width,
color=bar_clr_1, alpha=0.85, edgecolor='bisque',
label="Percentage loss of total system value (by component type)"
)
axes.barh(
pos+bar_offset*2, ctype_loss_by_type, bar_width,
color=bar_clr_2, alpha=0.85, edgecolor='bisque',
label="Percentage loss for component type"
)
axes.tick_params(top='off', bottom='off', left='on', right='off')
axes.set_xlim(0, max(ctype_loss_by_type))
axes.set_xticklabels([''])
axes.set_ylim([pos.max()+bar_width+0.4, pos.min()-bar_width-0.4])
axes.set_yticks(pos)
axes.set_yticklabels(cpt, size=11, color='k')
axes.tick_params(top='off', bottom='off', left='on', right='off')
for p, c, cv in zip(pos, cpt, ctype_loss_vals_tot):
axes.annotate(('%0.1f' % np.float(cv))+'%',
xy=(cv+0.5, p-bar_offset-bar_width/2.0),
xycoords=('data', 'data'),
ha='left', va='center', size=11, color=bar_clr_1,
annotation_clip=False)
for p, c, cv in zip(pos, cpt, ctype_loss_by_type):
axes.annotate(('%0.1f' % np.float(cv))+'%',
xy=(cv+0.5, p+bar_offset*2+bar_width/2.0),
xycoords=('data', 'data'),
ha='left', va='center', size=11, color=bar_clr_2,
annotation_clip=False)
axes.xaxis.set_ticks_position('none')
spines_to_remove = ['left', 'top', 'right']
for spine in spines_to_remove:
axes.spines[spine].set_visible(False)
axes.yaxis.grid(False)
axes.xaxis.grid(False)
axes.annotate(
'Percentage Economic Loss by Component Type',
xy=(0.0, -1.6), xycoords=('axes fraction', 'data'),
ha='left', va='top',
fontname='Open Sans', size=12, color='k', weight='bold',
annotation_clip=False);
axes.annotate(
'Hazard Event: Earthquake ' + sc_haz_val_str + ' ' +
scenario.intensity_measure_param,
xy=(0.0, -1.1), xycoords=('axes fraction', 'data'),
ha='left', va='top',
fontname='Open Sans', size=12, color='grey', weight='bold',
annotation_clip=False);
axes.legend(loc=9, ncol=1, bbox_to_anchor=(0.46, -0.01),
frameon=0, prop={'size':10})
fig.savefig(
os.path.join(scenario.output_path, fig_name),
format='png', bbox_inches='tight', dpi=300
)
plt.close(fig)
def draw_component_failure_barchart(uncosted_comptypes,
ctype_failure_mean,
sc_haz_val_str,
output_path,
figname):
comp_type_fail_sorted = \
ctype_failure_mean.sort_values(by=[sc_haz_val_str], ascending=[0])
for x in uncosted_comptypes:
if x in comp_type_fail_sorted.index.tolist():
comp_type_fail_sorted = comp_type_fail_sorted.drop(x, axis=0)
cptypes = comp_type_fail_sorted.index.tolist()
cpt = [spl.split_long_label(x,delims=[' ', '_'],max_chars_per_line=22)
for x in cptypes]
pos = np.arange(len(cptypes))
cpt_failure_vals = comp_type_fail_sorted[sc_haz_val_str].values * 100
fig = plt.figure(figsize=(10, len(pos)*0.6), facecolor='white')
ax = fig.add_subplot(111, axisbg='white')
bar_width = 0.6
bar_clr = spl.COLR_SET3[4] # dodgerblue
ax.barh(pos, cpt_failure_vals, bar_width,
color=bar_clr, edgecolor="bisque")
# add the numbers to the side of each bar
for p, c, cv in zip(pos, cptypes, cpt_failure_vals):
plt.annotate(('%0.1f' % cv)+'%', xy=(cv+0.3, p+bar_width/2.0),
va='center', size=11, color='k')
spines_to_remove = ['left', 'top', 'right', 'bottom']
for spine in spines_to_remove:
ax.spines[spine].set_visible(False)
#cutomize ticks
plt.gca().yaxis.tick_left()
plt.yticks(pos + bar_width/2.0, cpt, size=11, color='k')
xt = list(plt.xticks()[0])
xt.append(max(xt)+10.0)
plt.xticks(xt, [' '] * len(xt))
ax.grid(False)
ax.tick_params(top='off', bottom='off', left='off', right='off')
#set plot limits
plt.xlim(0, max(cpt_failure_vals)+5.0)
plt.ylim(pos.max() + 1.0, pos.min() - 1.0)
ax.annotate('Percentage Loss: Number of Components by Type',
xy=(0.0, -1.3), xycoords=('axes fraction', 'data'),
ha='left', va='top', annotation_clip=False,
fontname='Open Sans', size=12, weight='bold', color='k');
ax.annotate('Hazard Event: Earthquake ' + sc_haz_val_str + ' ' +
scenario.intensity_measure_param,
xy=(0.0, -0.8), xycoords=('axes fraction', 'data'),
ha='left', va='top', annotation_clip=False,
fontname='Open Sans', size=12, weight='bold',
color='darkgrey');
fig.savefig(
os.path.join(output_path, figname),
format='png', bbox_inches='tight', dpi=300
)
plt.close(fig)
def draw_component_loss_barchart_v1(scenario,
ctype_loss_vals_tot,
ctype_loss_by_type,
ctype_lossbytype_rank,
sc_haz_val_str,
fig_name):
""" Plots bar charts of direct economic losses for components types """
# Set color maps:
clrmap1 = [plt.cm.autumn(1.2*x/float(len(ctype_loss_vals_tot)))
for x in range(len(ctype_loss_vals_tot))]
clrmap2 = [clrmap1[int(i)] for i in ctype_lossbytype_rank]
a = 1.0 # transparency
bar_width = 0.7
yadjust = bar_width/2.0
subplot_spacing = 0.6
cpt = [spl.split_long_label(x,delims=[' ', '_'], max_chars_per_line=22)
for x in ctype_resp_sorted.index.tolist()]
pos = np.arange(0,len(cpt))
fig, (ax1, ax2) = plt.subplots(ncols=2, sharey=True,
facecolor='white',
figsize=(12,len(pos)*0.6))
fig.subplots_adjust(wspace=subplot_spacing)
# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
# Economic loss contributed by all components of a specific type,
# as a percentage of the value of the system
ax1.barh(pos, ctype_loss_vals_tot, bar_width,
color=clrmap1, edgecolor='bisque', alpha=a)
ax1.set_xlim(0, max(ctype_loss_by_type))
ax1.set_ylim(pos.max()+bar_width, pos.min()-bar_width)
# ax1.grid(False)
ax1.tick_params(top='off', bottom='off', left='off', right='on')
ax1.set_title('Economic Loss \nPercent of System Value',
fontname='Open Sans', fontsize=12,
fontweight='bold', ha='right', x=1.00, y=0.99)
# add the numbers to the side of each bar
for p, c, cv in zip(pos, cpt, ctype_loss_vals_tot):
ax1.annotate(('%0.1f' % np.float(cv))+'%',
xy=(cv+0.5, p+yadjust),
xycoords=('data', 'data'),
ha='right', va='center', size=11,
annotation_clip=False)
ax1.xaxis.set_ticks_position('none')
ax1.set_axis_off()
# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
# Aggregated economic loss for all components of a specific type
ax2.barh(pos, ctype_loss_by_type, bar_width,
color=clrmap2, edgecolor='bisque', alpha=a)
ax2.set_xlim(0, max(ctype_loss_by_type))
ax2.set_ylim(pos.max()+bar_width, pos.min()-bar_width)
ax2.tick_params(top='off', bottom='off', left='on', right='off')
ax2.set_title('Economic Loss \nPercent of Component Type Value',
fontname='Open Sans', fontsize=12,
fontweight='bold', ha='left', x=0, y=0.99)
for p, c, cv in zip(pos, cpt, ctype_loss_by_type):
ax2.annotate(('%0.1f' % np.float(cv))+'%', xy=(cv+0.5, p+yadjust),
xycoords=('data', 'data'),
ha='left', va='center', size=11,
annotation_clip=False)
ax2.xaxis.set_ticks_position('none')
ax2.set_axis_off()
# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
ax1.invert_xaxis()
for yloc, ylab in zip(pos, cpt):
ax1.annotate(ylab,
xy=(1.0+subplot_spacing/2.0, yloc+yadjust),
xycoords=('axes fraction', 'data'),
ha='center', va='center', size=11, color='k',
annotation_clip=False)
ax1.annotate('HAZARD EVENT\n' +
'Earthquake\n' +
sc_haz_val_str + ' ' + scenario.intensity_measure_param,
xy=(1.0 + subplot_spacing/2.0, -1.25),
xycoords=('axes fraction', 'data'),
ha='center', va='center', size=12,
fontname='Open Sans', color='darkgrey', weight='bold',
annotation_clip=False)
fig.savefig(os.path.join(scenario.output_path, fig_name),
format='png', bbox_inches='tight', dpi=300)
plt.close(fig)
