Merge branch 'master' of ssh://git.black-mesa.xyz:434/langspielplatte/measurement-scripts

This commit is contained in:
Lukas Prause
2023-02-10 14:29:53 +01:00
2 changed files with 29 additions and 7 deletions

View File

@@ -14,7 +14,6 @@ if __name__ == "__main__":
parser.add_argument("-l", "--label", help="Label above the plot.") parser.add_argument("-l", "--label", help="Label above the plot.")
parser.add_argument("--no_legend", action="store_false", default=True, help="Do not show legend.") parser.add_argument("--no_legend", action="store_false", default=True, help="Do not show legend.")
parser.add_argument("--save", default=None, help="Location to save pdf file.") parser.add_argument("--save", default=None, help="Location to save pdf file.")
parser.add_argument("--time_offset", default=None, type=int, help="Minutes added to GPS datetime.")
parser.add_argument( parser.add_argument(
"--show_providerinfo", "--show_providerinfo",

View File

@@ -53,9 +53,8 @@ if __name__ == "__main__":
transmission_df.index = pd.to_datetime(transmission_df.index) transmission_df.index = pd.to_datetime(transmission_df.index)
transmission_df = transmission_df.sort_index() transmission_df = transmission_df.sort_index()
#print("Calculate goodput...") # srtt to [s]
transmission_df["srtt"] = transmission_df["srtt"].apply(lambda x: x / 10**6)
#print(transmission_df)
# key for columns and level for index # key for columns and level for index
transmission_df["goodput"] = transmission_df["payload_size"].groupby(pd.Grouper(level="datetime", freq="{}s".format(args.interval))).transform("sum") transmission_df["goodput"] = transmission_df["payload_size"].groupby(pd.Grouper(level="datetime", freq="{}s".format(args.interval))).transform("sum")
@@ -131,8 +130,8 @@ if __name__ == "__main__":
ax.axvspan(bounds.min(), bounds.max(), alpha=0.3, color=color_list[c]) ax.axvspan(bounds.min(), bounds.max(), alpha=0.3, color=color_list[c])
p4, = twin3.plot(transmission_df["snd_cwnd"].dropna(), color="lime", linestyle="dashed", label="cwnd") p4, = twin3.plot(transmission_df["snd_cwnd"].dropna(), color="lime", linestyle="dashed", label="cwnd")
p3, = twin2.plot(transmission_df["ack_rtt"].dropna(), color="red", linestyle="dashdot", label="ACK RTT") p3, = twin2.plot(transmission_df["srtt"].dropna(), color="red", linestyle="dashdot", label="sRTT")
p1, = ax.plot(transmission_df["goodput_rolling"], color="blue", linestyle="solid", label="goodput") p1, = ax.plot(transmission_df["arrival_time"], transmission_df["goodput_rolling"], color="blue", linestyle="solid", label="goodput")
p2, = twin1.plot(transmission_df["downlink_cqi"].dropna(), color="magenta", linestyle="dotted", label="CQI") p2, = twin1.plot(transmission_df["downlink_cqi"].dropna(), color="magenta", linestyle="dotted", label="CQI")
ax.set_xlim(transmission_df["index"].min(), transmission_df["index"].max()) ax.set_xlim(transmission_df["index"].min(), transmission_df["index"].max())
@@ -144,7 +143,7 @@ if __name__ == "__main__":
ax.set_xlabel("arrival time") ax.set_xlabel("arrival time")
ax.set_ylabel("Goodput [mbps]") ax.set_ylabel("Goodput [mbps]")
twin1.set_ylabel("CQI") twin1.set_ylabel("CQI")
twin2.set_ylabel("ACK RTT [s]") twin2.set_ylabel("sRTT [s]")
twin3.set_ylabel("cwnd") twin3.set_ylabel("cwnd")
ax.yaxis.label.set_color(p1.get_color()) ax.yaxis.label.set_color(p1.get_color())
@@ -163,6 +162,30 @@ if __name__ == "__main__":
if args.save: if args.save:
plt.savefig("{}{}_plot.pdf".format(args.save, csv.replace(".csv", ""))) plt.savefig("{}{}_plot.pdf".format(args.save, csv.replace(".csv", "")))
# plot correlations
corr_pairs = [
["goodput_rolling", "RSRQ"],
["goodput_rolling", "RSRP"],
["goodput_rolling", "RSSI"],
["goodput_rolling", "SINR"],
["goodput_rolling", "downlink_cqi"],
]
for pair in corr_pairs:
# spearman and pearson
sp = transmission_df[pair[0]].corr(transmission_df[pair[1]], method="spearman")
pe = transmission_df[pair[0]].corr(transmission_df[pair[1]], method="pearson")
title = "{}/{} spearman: {} pearson: {}".format(pair[0], pair[1], round(sp, 4), round(pe, 4))
transmission_df.plot.scatter(x=pair[0], y=pair[1], c="DarkBlue", title=title)
if args.save:
plt.savefig("{}{}_corr_{}_and_{}.pdf".format(args.save, csv.replace(".csv", ""), pair[0], pair[1]))
plt.clf()
counter += 1 counter += 1
plt.clf() plt.clf()