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langspielplatte
2023-01-11 10:16:46 +01:00
parent cb59a663b8
commit 69dfc9a1d8
1 changed files with 11 additions and 9 deletions
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plot_transmission_timeline.py
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@@ -192,21 +192,23 @@ if __name__ == "__main__":
print("Calculate and polt CDF...") print("Calculate and polt CDF...")
# Get the frequency, PDF and CDF for each value in the series # Get the frequency, PDF and CDF for each value in the series
# copy column
transmission_df["gp_frequency"] = transmission_df.loc[:, "goodput"]
print(transmission_df)
# Frequency # Frequency
transmission_df = transmission_df.groupby("gp_frequency")["gp_frequency"].agg("count").pipe(pd.DataFrame) stats_df = transmission_df \
.groupby("goodput") \
["goodput"] \
.agg("count") \
.pipe(pd.DataFrame) \
.rename(columns={"goodput": "frequency"})
# PDF # PDF
transmission_df["pdf"] = transmission_df["gp_frequency"] / sum(transmission_df["gp_frequency"]) stats_df["pdf"] = stats_df["frequency"] / sum(stats_df["frequency"])
# CDF # CDF
transmission_df["cdf"] = transmission_df["pdf"].cumsum() stats_df["cdf"] = stats_df["pdf"].cumsum()
print(transmission_df) stats_df = stats_df.reset_index()
transmission_df = transmission_df.reset_index()
transmission_df.plot(x="goodput", y=["cdf"], grid=True) stats_df.plot(x="goodput", y=["cdf"], grid=True)
if args.save: if args.save:
plt.savefig("{}cdf_plot.pdf".format(args.save)) plt.savefig("{}cdf_plot.pdf".format(args.save))