...

xlap/analyse/e2e.py

@@ -41,9 +41,10 @@ def _plot_regions(dataset):
     correlations = list(map(lambda x: x['Slowdown'], relevant))
     ticks = list(map(lambda x: "<%s,%s>" % (x['Start'][:-2], x['End'][:-2]), relevant))
     fig, ax = plt.subplots()
-    rects = ax.barh(x, correlations, align="center", tick_label="")
+    rects = ax.barh(x, correlations, align="center", tick_label="", color='#3babaf')
     autolabel(rects, ax, ticks)
 
+    plt.xlabel('Normalized slowdown')
     plt.tight_layout()
     plt.savefig("normalized-slowdown.pdf")
     plt.close()

xlap/command_line.py

@@ -48,7 +48,7 @@ def main():
         elif command == "e2e":
             khz1 = 2000000
             khz2 = 3000000
-            path="../publications/nsdi-18/eval/20180419_energy/"
+            path="../publications/rtn-18/eval/20180419_energy/"
             df_data1 = evaluate(path+"sender-"+str(khz1)+".csv", path+"receiver-"+str(khz1)+".csv", config=config, kind=0)
             df_data2 = evaluate(path+"sender-"+str(khz2)+".csv", path+"receiver-"+str(khz2)+".csv", config=config, kind=0)
             e2e.analyse(df_data1, df_data2, config)
@@ -57,7 +57,7 @@ def main():
             a = latency.analyse(df_data, config)
             print(a.corr.sort_values(ascending=False))
         elif command == "difference":
-            path="../publications/nsdi-18/eval/20180420_"
+            path="../publications/rtn-18/eval/20180420_"
             khz = 3000000
             df_data1 = evaluate(path+"base1/sender-"+str(khz)+".csv", path+"base1/receiver-"+str(khz)+".csv", config=config, kind=0)
             # sanity check: