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- #!/usr/bin/env python3
-
- from argparse import ArgumentParser
-
-
- import pandas as pd
- import matplotlib.pyplot as plt
-
- if __name__ == "__main__":
- parser = ArgumentParser()
- parser.add_argument("-f", "--file", required=True, help="Serial CSV")
- parser.add_argument("--save", default=None, help="Location to save pdf file.")
-
- args = parser.parse_args()
-
- df = pd.read_csv(args.file)
- df["time_rel"] = df["time"] - df["time"].iloc[0]
- df.index = df["time_rel"] / 60
-
- for i in range(1, 5):
- df["LTE_SCC{}_effective_bw".format(i)] = df["LTE_SCC{}_bw".format(i)]
-
- mask = df["LTE_SCC{}_state".format(i)].isin(["ACTIVE"])
- df["LTE_SCC{}_effective_bw".format(i)] = df[
- "LTE_SCC{}_effective_bw".format(i)
- ].where(mask, other=0)
-
- df["SCC1_NR5G_effective_bw"] = df["SCC1_NR5G_bw"].fillna(0)
- df["effective_bw_sum"] = (
- df["SCC1_NR5G_effective_bw"]
- + df["LTE_SCC1_effective_bw"]
- + df["LTE_SCC2_effective_bw"]
- + df["LTE_SCC3_effective_bw"]
- + df["LTE_SCC4_effective_bw"]
- + df["LTE_bw"]
- )
- bw_cols = [
- "SCC1_NR5G_effective_bw",
- "LTE_bw",
- "LTE_SCC1_effective_bw",
- "LTE_SCC2_effective_bw",
- "LTE_SCC3_effective_bw",
- "LTE_SCC4_effective_bw",
- ]
-
- ax = df[bw_cols].plot.area(stacked=True)
- ax.set_ylabel("bandwidth [MHz]")
- ax.set_xlabel("time [minutes]")
-
- L = plt.legend()
- L.get_texts()[0].set_text("5G main")
- L.get_texts()[1].set_text("4G main")
- L.get_texts()[2].set_text("4G SCC 1")
- L.get_texts()[3].set_text("4G SCC 2")
- L.get_texts()[4].set_text("4G SCC 3")
- L.get_texts()[5].set_text("4G SCC 4")
-
- if args.save:
- plt.savefig("{}-used_bandwidth.pdf".format(args.save))
- else:
- plt.show()
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