Removes correlation plot.
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@@ -163,29 +163,6 @@ if __name__ == "__main__":
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if args.save:
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if args.save:
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plt.savefig("{}{}_plot.pdf".format(args.save, csv.replace(".csv", "")))
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plt.savefig("{}{}_plot.pdf".format(args.save, csv.replace(".csv", "")))
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# plot correlations
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corr_pairs = [
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["goodput_rolling", "RSRQ"],
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["goodput_rolling", "RSRP"],
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["goodput_rolling", "RSSI"],
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["goodput_rolling", "SINR"],
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["goodput_rolling", "downlink_cqi"],
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]
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for pair in corr_pairs:
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# spearman and pearson
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sp = transmission_df[pair[0]].corr(transmission_df[pair[1]], method="spearman")
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pe = transmission_df[pair[0]].corr(transmission_df[pair[1]], method="pearson")
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title = "{}/{} spearman: {} pearson: {}".format(pair[0], pair[1], round(sp, 4), round(pe, 4))
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transmission_df.plot.scatter(x=pair[0], y=pair[1], c="DarkBlue", title=title)
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if args.save:
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plt.savefig("{}{}_corr_{}_and_{}.pdf".format(args.save, csv.replace(".csv", ""), pair[0], pair[1]))
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plt.clf()
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counter += 1
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counter += 1
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plt.clf()
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plt.clf()
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