| @@ -153,16 +153,14 @@ if __name__ == "__main__": | |||
| mask = transmission_df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"]) | |||
| transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[ | |||
| "LTE_SCC{}_effective_bw".format(i) | |||
| ].where(mask, other=np.NaN) | |||
| transmission_df["LTE_SCC{}_effective_bw".format(i)].dropna() | |||
| ].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[ | |||
| "LTE_SCC{}_effective_bw".format(i) | |||
| ].where(mask, other=np.nan) | |||
| transmission_df["LTE_SCC{}_effective_bw".format(i)].dropna() | |||
| ].where(mask, other=0) | |||
| # sum all effective bandwidth for 5G and 4G | |||
| transmission_df["SCC1_NR5G_effective_bw"] = transmission_df[ | |||
| @@ -235,6 +233,10 @@ if __name__ == "__main__": | |||
| "LTE_SCC4_effective_bw", | |||
| ] | |||
| 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) | |||
| ax00.set_ylabel("bandwidth [MHz]") | |||
| #ax.set_xlabel("time [minutes]") | |||