for i, scheduler in enumerate(no_error):
no_error_data[i].append(np.array(res[scheduler]).mean())
for i, scheduler in enumerate(with_error):
with_error_data[i].append(np.array(res[scheduler]).mean())
figures = [("No error", float(0), no_error, no_error_data),
(r"$\sigma={}$".format(args.sigma),
args.sigma, with_error, with_error_data)]
for title, sigma, schedulers, data in figures:
fig = plt.figure(title)
ax = fig.add_subplot(111)
plt.xlabel("$d/n$")
plt.ylabel("mean sojourn time (s)")
for scheduler, mst, style in zip(schedulers, data,
plot_helpers.cycle_styles('x')):
ax.semilogy(dns, mst, style, label=scheduler)
ax.grid()
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc=2, bbox_to_anchor=(1, 1))
ax.grid('on')
if args.for_paper:
fmt = 'sojourn-vs-dn_{}_{}_{}.pdf'
fname = fmt.format(args.dataset, sigma, args.load)
plt.savefig(fname,bbox_extra_artists=(lgd,), bbox_inches='tight')
if not args.for_paper:
plt.show()
for i, scheduler in enumerate(no_error):
no_error_data[i].append(np.array(res[scheduler]).mean())
for i, scheduler in enumerate(with_error):
with_error_data[i].append(np.array(res[scheduler]).mean())
figures = [("No error", float(0), no_error, no_error_data),
(r"$\sigma={}$".format(args.sigma), args.sigma, with_error,
with_error_data)]
for title, sigma, schedulers, data in figures:
fig = plt.figure(title)
ax = fig.add_subplot(111)
plt.xlabel("$d/n$")
plt.ylabel("mean sojourn time (s)")
for scheduler, mst, style in zip(schedulers, data,
plot_helpers.cycle_styles('x')):
ax.semilogy(dns, mst, style, label=scheduler)
ax.grid()
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc=2, bbox_to_anchor=(1, 1))
ax.grid('on')
if args.for_paper:
fmt = 'sojourn-vs-dn_{}_{}_{}.pdf'
fname = fmt.format(args.dataset, sigma, args.load)
plt.savefig(fname, bbox_extra_artists=(lgd, ), bbox_inches='tight')
if not args.for_paper:
plt.show()
res = shelve.open(fname, 'r')
for i, scheduler in enumerate(no_error):
no_error_data[i].append(np.array(res[scheduler]).mean())
for i, scheduler in enumerate(with_error):
with_error_data[i].append([r.mean() for r in res[scheduler]])
for scheduler, err_data in zip(with_error, with_error_data):
fig = plt.figure(scheduler)
ax = fig.add_subplot(111)
plt.xlabel("$\sigma$")
plt.ylabel("mean sojourn time (s)")
xs = list(range(1, len(sigmas) + 1))
xs[0] -= 1
xs[-1] += 1
for noerr_sched, noerr_data, style in zip(no_error, no_error_data,
plot_helpers.cycle_styles()):
ax.semilogy(xs, noerr_data, style, label=noerr_sched)
ax.boxplot(err_data)
plt.xticks(range(1, len(sigmas) + 1), sigmas)
plt.ylim(min([min(d) for d in no_error_data]) * 0.85,
max([max(d) for d in no_error_data]) / 0.85)
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc=2, bbox_to_anchor=(1, 1))
if args.for_paper:
fmt = 'sojourn-vs-error_{}_{}_{}_{}.pdf'
fname = fmt.format(scheduler, args.dataset, args.d_over_n, args.load)
plt.savefig(fname,bbox_extra_artists=(lgd,), bbox_inches='tight')
if not args.for_paper:
plt.show()
res = shelve.open(fname, 'r')
for scheduler in no_error:
no_error_data.append(samples(res[scheduler]))
for scheduler in with_error:
with_error_data.append(samples(res[scheduler]))
figures = [("No error", float(0), no_error, no_error_data),
(r"$\sigma={}$".format(args.sigma), args.sigma, with_error,
with_error_data)]
for title, sigma, schedulers, data in figures:
plt.figure(title)
plt.xlabel("Slowdown")
plt.ylabel("ECDF")
ys = np.linspace(1 / NPOINTS, 1, NPOINTS)
for scheduler, xs, style in zip(schedulers, data,
plot_helpers.cycle_styles()):
# plot the CDF of results
plt.semilogx(xs, ys, label=scheduler)
plt.grid()
plt.legend(loc=0)
if args.for_paper:
fmt = 'slowdown_{}_{}_{}_{}.pdf'
fname = fmt.format(args.dataset, sigma, args.d_over_n, args.l)
plt.savefig(fname)
if not args.for_paper:
plt.show()