def graph_individual_intersections(labels, colours, fp, metrics, save_dir):
#rows are metrics
#columns are intersections
tsc = os.listdir(fp)
tsc.remove('sotl')
intersections = os.listdir(fp + tsc[0] + '/' + metrics[0] + '/')
ncols = len(intersections)
nrows = len(metrics)
f, ax = plt.subplots(nrows=nrows, ncols=ncols)
if ax.ndim == 1:
ax = ax[..., np.newaxis]
for m, r in zip(metrics, range(nrows)):
#get metric data for each intersection
data = {}
for t in tsc:
data[t] = {}
for i in intersections:
alias_p = 60
data[t][i] = alias(
stack_folder_files(fp + '/' + t + '/' + m + '/' + i + '/'),
alias_p)
xtitle = 'Time ' + r" $(min)$" if r == nrows - 1 else ''
#graph same metric for each intersection
for I, c in zip(intersections, range(ncols)):
title = I if r == 0 else ''
if m == 'queue':
ytitle = m.capitalize() + r" $(veh)$" if c == 0 else ''
else:
ytitle = m.capitalize() + r" $(s)$" if c == 0 else ''
legend = (0.59, 0.6)
data_order = sorted(data.keys())
alias_p = 60
order_data = [data[d][I] for d in data_order]
order_labels = [labels[d] for d in data_order]
order_colors = [colours[d] for d in data_order]
label_c = {labels[d]: colours[d] for d in data_order}
graph(ax[r, c],
order_data,
multi_line_with_CI(ax[r, c], order_data, order_colors,
order_labels),
xtitle=xtitle,
ytitle_pad=(ytitle, 60),
title=title,
legend=legend,
colours=label_c,
grid=True)
ax[r, c].set_xlim(left=0)
ax[r, c].set_ylim(bottom=0)
f.suptitle('Intersection Measures of Effectiveness')
save_graph(f, save_dir + 'intersection_moe.pdf', 600, 14, 24.9)
plt.show()
def graph_conf_interval(labels, colours, fp, metric):
#read metric data for all tsc types
data = get_data(fp, metric, get_metric_data)
#prepare data for graph
data_order = sorted(data.keys())
data = [ data[d] for d in data_order]
labels = [ labels[d] for d in data_order]
#graph data
f, ax = plt.subplots(1,1)
metric_title = metric.capitalize()
graph( ax, data, multi_line_with_CI( ax, data, colours, labels),
xtitle='Time (s)',
ytitle_pad = (metric_title, 60),
title=metric_title+' by\nTraffic Signal Controller',
legend=(0.72, 0.72),
grid=True)
#f.suptitle(metric_title)
#display graph
plt.show()