Fixes typo and and too large dataset.

This commit is contained in:
Lukas Prause
2023-07-12 14:17:33 +02:00
parent 97f0946ad0
commit 951bac5f1e

View File

@@ -144,12 +144,6 @@ if __name__ == "__main__":
transmission_df.index = transmission_df["arrival_time"] transmission_df.index = transmission_df["arrival_time"]
# replace 0 in RSRQ with Nan
transmission_df["NR5G_RSRQ_(dB)"] = transmission_df["NR5G_RSRQ_(dB)"].replace(
0, np.NaN
)
transmission_df["RSRQ_(dB)"] = transmission_df["RSRQ_(dB)"].replace(0, np.NaN)
# filter active state # filter active state
for i in range(1, 5): for i in range(1, 5):
transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[ transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
@@ -159,14 +153,16 @@ if __name__ == "__main__":
mask = transmission_df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"]) mask = transmission_df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"])
transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[ transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
"LTE_SCC{}_effective_bw".format(i) "LTE_SCC{}_effective_bw".format(i)
].where(mask, other=0) ].where(mask, other=np.NaN)
transmission_df["LTE_SCC{}_effective_bw".format(i)].dropna()
# filter if sc is usesd for uplink # filter if sc is usesd for uplink
for i in range(1, 5): for i in range(1, 5):
mask = transmission_df["LTE_SCC{}_UL_Configured".format(i)].isin([False]) mask = transmission_df["LTE_SCC{}_UL_Configured".format(i)].isin([False])
transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[ transmission_df["LTE_SCC{}_effective_bw".format(i)] = transmission_df[
"LTE_SCC{}_effective_bw".format(i) "LTE_SCC{}_effective_bw".format(i)
].where(mask, other=0) ].where(mask, other=np.nan)
transmission_df["LTE_SCC{}_effective_bw".format(i)].dropna()
# sum all effective bandwidth for 5G and 4G # sum all effective bandwidth for 5G and 4G
transmission_df["SCC1_NR5G_effective_bw"] = transmission_df[ transmission_df["SCC1_NR5G_effective_bw"] = transmission_df[