Merge timing.

plot_single_transmission_paper.py

@@ -123,48 +123,44 @@ if __name__ == "__main__":
         serial_df.index = pd.to_datetime(serial_df.index)
         serial_df.sort_index()
 
-        transmission_df = pd.merge_asof(
-            transmission_df,
-            serial_df,
-            tolerance=pd.Timedelta("1milliseconds"),
-            right_index=True,
-            left_index=True,
-        )
+        # Select DataFrame rows between two dates
+        mask = (serial_df.index >= transmission_df.index[0]) & (serial_df.index <= transmission_df.index[-1])
+        serial_df = serial_df.loc[mask]
 
         transmission_df.index = transmission_df["arrival_time"]
 
         # filter active state
         for i in range(1, 5):
-            transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
+            serial_df["LTE_SCC{}_effective_bw".format(i)] = serial_df[
                 "LTE_SCC{}_bw".format(i)
             ]
 
-            mask = transmission_df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"])
-            transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
+            mask = serial_df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"])
+            serial_df["LTE_SCC{}_effective_bw".format(i)] = serial_df[
                 "LTE_SCC{}_effective_bw".format(i)
             ].where(mask, other=0)
 
         # filter if sc is usesd for uplink
         for i in range(1, 5):
-            mask = transmission_df["LTE_SCC{}_UL_Configured".format(i)].isin([False])
-            transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
+            mask = serial_df["LTE_SCC{}_UL_Configured".format(i)].isin([False])
+            serial_df["LTE_SCC{}_effective_bw".format(i)] = serial_df[
                 "LTE_SCC{}_effective_bw".format(i)
             ].where(mask, other=0)
 
         # sum all effective bandwidth for 5G and 4G
-        transmission_df["SCC1_NR5G_effective_bw"] = transmission_df[
+        serial_df["SCC1_NR5G_effective_bw"] = serial_df[
             "SCC1_NR5G_bw"
         ].fillna(0)
 
-        transmission_df["lte_effective_bw_sum"] = (
-                transmission_df["LTE_SCC1_effective_bw"].fillna(0)
-                + transmission_df["LTE_SCC2_effective_bw"].fillna(0)
-                + transmission_df["LTE_SCC3_effective_bw"].fillna(0)
-                + transmission_df["LTE_SCC4_effective_bw"].fillna(0)
-                + transmission_df["LTE_bw"].fillna(0))
-        transmission_df["nr_effective_bw_sum"] = transmission_df["SCC1_NR5G_effective_bw"]
+        serial_df["lte_effective_bw_sum"] = (
+                serial_df["LTE_SCC1_effective_bw"].fillna(0)
+                + serial_df["LTE_SCC2_effective_bw"].fillna(0)
+                + serial_df["LTE_SCC3_effective_bw"].fillna(0)
+                + serial_df["LTE_SCC4_effective_bw"].fillna(0)
+                + serial_df["LTE_bw"].fillna(0))
+        serial_df["nr_effective_bw_sum"] = serial_df["SCC1_NR5G_effective_bw"]
 
-        transmission_df["effective_bw_sum"] = transmission_df["nr_effective_bw_sum"] + transmission_df[
+        serial_df["effective_bw_sum"] = serial_df["nr_effective_bw_sum"] + serial_df[
             "lte_effective_bw_sum"]
 
         # transmission timeline
@@ -182,8 +178,6 @@ if __name__ == "__main__":
 
         ax00 = ax[1]
 
-
-
         snd_plot = ax0.plot(
             transmission_df["snd_cwnd"].dropna(),
             color="lime",
@@ -204,14 +198,14 @@ if __name__ == "__main__":
         )
 
         # sum all effective bandwidth for 5G and 4G
-        transmission_df["SCC1_NR5G_effective_bw"] = transmission_df["SCC1_NR5G_bw"].fillna(0)
-        transmission_df["effective_bw_sum"] = (
-                transmission_df["SCC1_NR5G_effective_bw"]
-                + transmission_df["LTE_SCC1_effective_bw"]
-                + transmission_df["LTE_SCC2_effective_bw"]
-                + transmission_df["LTE_SCC3_effective_bw"]
-                + transmission_df["LTE_SCC4_effective_bw"]
-                + transmission_df["LTE_bw"]
+        serial_df["SCC1_NR5G_effective_bw"] = serial_df["SCC1_NR5G_bw"].fillna(0)
+        serial_df["effective_bw_sum"] = (
+                serial_df["SCC1_NR5G_effective_bw"]
+                + serial_df["LTE_SCC1_effective_bw"]
+                + serial_df["LTE_SCC2_effective_bw"]
+                + serial_df["LTE_SCC3_effective_bw"]
+                + serial_df["LTE_SCC4_effective_bw"]
+                + serial_df["LTE_bw"]
         )
         bw_cols = [
             "SCC1_NR5G_effective_bw",
@@ -222,11 +216,10 @@ if __name__ == "__main__":
             "LTE_SCC4_effective_bw",
         ]
 
+        serial_df["time_rel"] = serial_df["time"] - serial_df["time"].iloc[0]
+        serial_df.index = serial_df["time_rel"] / 60
 
-        transmission_df.to_csv("{}{}_plot.csv".format(args.save, csv.replace(".csv", "")))
-        exit()
-
-        ax_stacked = transmission_df[bw_cols].plot.area(stacked=True, linewidth=0, ax=ax00)
+        ax_stacked = serial_df[bw_cols].plot.area(stacked=True, linewidth=0, ax=ax00)
         ax00.set_ylabel("bandwidth [MHz]")
         #ax.set_xlabel("time [minutes]")
         #ax00.set_xlim([0, transmission_df.index[-1]])