Bugfixes

cdf_compare.py

     return iter(lambda: tuple(islice(it, size)), ())
 
 
-def plot_cdf(dataframe, column_name):
+def plot_cdf(dataframe, column_name, axis=None):
     stats_df = dataframe \
         .groupby(column_name) \
         [column_name] \
     stats_df["CDF"] = stats_df["PDF"].cumsum()
     stats_df = stats_df.reset_index()
 
-    stats_df.plot(x=column_name, y=["CDF"], grid=True)
+    if axis:
+        stats_df.plot(x=column_name, y=["CDF"], grid=True, ax=axis)
+    else:
+        stats_df.plot(x=column_name, y=["CDF"], grid=True)
+    return axis
 
 
 if __name__ == "__main__":
         ))
 
     # Plot sRTT CDF
-    plot_cdf(transmission_df_list[0]["df"], "srtt")
-    plot_cdf(transmission_df_list[1]["df"], "srtt")
+    ax = plot_cdf(transmission_df_list[0]["df"], "srtt")
+    plot_cdf(transmission_df_list[1]["df"], "srtt", axis=ax)
     plt.xscale("log")
     plt.xlabel("sRTT [s]")
     plt.ylabel("CDF")
     plt.clf()
 
     # Plot goodput CDF
-    plot_cdf(transmission_df_list[0]["df"], "goodput")
-    plot_cdf(transmission_df_list[1]["df"], "goodput")
+    ax = plot_cdf(transmission_df_list[0]["df"], "goodput")
+    plot_cdf(transmission_df_list[1]["df"], "goodput", axis=ax)
     plt.xlabel("goodput [mbps]")
     plt.ylabel("CDF")
     plt.legend([transmission_df_list[0]["cc_algo"], transmission_df_list[1]["cc_algo"]])