from_csv = False
try:
pickle_file = open(pickle_file_path, 'rb')
except FileNotFoundError:
from_csv = True
else:
print(" from pickle.")
data_set.append(pickle.load(pickle_file))
pickle_file.close()
if from_csv:
print(" from csv")
vpp_data = analyze_vpp.read_vpp_file(base_dir + '/' + data_dir +
'/' + data_file)
#analyze_vpp.hack_moving_min_into_vpp_data(vpp_data, 'all_ts')
x, y = analyze_vpp.make_ecdf_data(vpp_data, 'all_ts', 'vec', True,
True)
#x_smooth, y_smooth = analyze_vpp.make_ecdf_data(vpp_data, 'all_ts_smooth', 'vec', True, True)
data_entry = (data_dir, data_file, vpp_data, x, y)
data_set.append(data_entry)
pickle_file = open(pickle_file_path, 'wb')
pickle.dump(data_entry, pickle_file)
pickle_file.close()
print("I have {} data_entires.".format(len(data_set)))
print("moving on to plotting")
do_values_vec = list()
wired_values_vec = list()
wifi_values_vec = list()
runs_to_plot = (
(r_cc_delay_5, "Dynamic window (CC)"),
(r_w50_delay_5, "50 packet window"),
(r_1r5_delay_0, "1.5 MBps pacer"),
)
f, ax = plt.subplots(1)
#ax.axhline(0.5, **GRIDLINEPROPS)
ax.axvline(0, **GRIDLINEPROPS)
#ax.axvline(1, **GRIDLINEPROPS)
for i in range(len(runs_to_plot)):
run, label = runs_to_plot[i]
x_values, y_values = analyze_vpp.make_ecdf_data(run, 'basic', ps_plot_interval)
ax.plot(x_values, y_values,
label=label,
color = COLORS[i],
marker = MARKERS[i][0],
markersize = MARKERS[i][1],
markeredgecolor = COLORS[i],
markerfacecolor = (0,0,0,0),
markevery = (0.1*i, 0.2))
ax.legend(title="Packet scheduler")
ax.set_xlim((-15, 15))
ax.set_xlabel("Error [ms]")
ax.set_ylabel("Cumulative fraction of data")
ax.set_yticks((0, 0.25, 0.5, 0.75, 1))
#ax.grid(True)
r_cc = analyze_vpp.analyze_run(
"/home/piet/eth/msc/vpp-data/std_congestion_controller_10ms_80s/1520177626-mQzsO_delay-10ms"
)
#r_delay_1ms = analyze_vpp.analyze_run("/home/piet/eth/msc/vpp-data/one_direction_10ms_80s/1520172327-7y4Rk_delay-1ms")
## ECDF
# Just plot the result of the basic analyzer ECDF
f, ax = plt.subplots(1)
set_fig_size(f, 10, 7.5)
#f.set_size_inches(10, 7)
x_limits = (-20, 20)
x, y = analyze_vpp.make_ecdf_data(r_cc, 'basic')
ax.plot(x, y)
ax.set_xlim(x_limits)
#ax.set_xlabel("Spin bit RTT - client reported RTT")
#ax.set_ylabel("Relative cumulative frequency")
save_figure(f, "basic_ecdf")
## TIME SERIE
f, ax = plt.subplots(1)
set_fig_size(f, 20, 6)
ax.plot(r_cc['server_times'], r_cc['server_rtts'], label="Server", color=RED)
ax.plot(r_cc['client_times'],
r_cc['client_rtts'],
label="Client",
(r_w60_reorder_30, 30),
(r_w60_reorder_40, 40),
)
##
## ECDF for a single loss reordering rate
##
run_for_ecdf = r_w60_reorder_10
f, ax = plt.subplots(1)
#ax.axhline(0.5, **GRIDLINEPROPS)
ax.axvline(0, **GRIDLINEPROPS)
for analyzer, label, i in analyzers_to_plot:
x_values, y_values = analyze_vpp.make_ecdf_data(run_for_ecdf, analyzer,
INTERVAL_OF_INTEREST)
ax.plot(
x_values,
y_values,
label=label,
#linestyle = LINESTYLES[i],
color=COLORS[i],
marker=MARKERS[i][0],
markersize=MARKERS[i][1],
markeredgecolor=COLORS[i],
markerfacecolor=(0, 0, 0, 0),
markevery=(0.0 * i, 0.2))
ax.legend()
ax.set_xlim((-55, 15))
ax.set_xlabel("Observer estimate – client estimate [ms]")