Fixes typo and and too large dataset.
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@@ -153,16 +153,14 @@ if __name__ == "__main__":
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mask = transmission_df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"])
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mask = transmission_df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"])
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transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
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transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
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"LTE_SCC{}_effective_bw".format(i)
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"LTE_SCC{}_effective_bw".format(i)
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].where(mask, other=np.NaN)
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].where(mask, other=0)
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transmission_df["LTE_SCC{}_effective_bw".format(i)].dropna()
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# filter if sc is usesd for uplink
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# filter if sc is usesd for uplink
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for i in range(1, 5):
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for i in range(1, 5):
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mask = transmission_df["LTE_SCC{}_UL_Configured".format(i)].isin([False])
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mask = transmission_df["LTE_SCC{}_UL_Configured".format(i)].isin([False])
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transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
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transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
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"LTE_SCC{}_effective_bw".format(i)
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"LTE_SCC{}_effective_bw".format(i)
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].where(mask, other=np.nan)
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].where(mask, other=0)
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transmission_df["LTE_SCC{}_effective_bw".format(i)].dropna()
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# sum all effective bandwidth for 5G and 4G
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# sum all effective bandwidth for 5G and 4G
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transmission_df["SCC1_NR5G_effective_bw"] = transmission_df[
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transmission_df["SCC1_NR5G_effective_bw"] = transmission_df[
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@@ -235,6 +233,10 @@ if __name__ == "__main__":
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"LTE_SCC4_effective_bw",
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"LTE_SCC4_effective_bw",
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]
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]
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transmission_df.to_csv("{}{}_plot.csv".format(args.save, csv.replace(".csv", "")))
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exit()
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ax_stacked = transmission_df[bw_cols].plot.area(stacked=True, linewidth=0, ax=ax00)
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ax_stacked = transmission_df[bw_cols].plot.area(stacked=True, linewidth=0, ax=ax00)
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ax00.set_ylabel("bandwidth [MHz]")
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ax00.set_ylabel("bandwidth [MHz]")
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#ax.set_xlabel("time [minutes]")
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#ax.set_xlabel("time [minutes]")
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