Adds correlation plots.

plot_single_transmission_timeline.py

@@ -162,6 +162,30 @@ if __name__ == "__main__":
 
         if args.save:
             plt.savefig("{}{}_plot.pdf".format(args.save, csv.replace(".csv", "")))
+
+
+        # plot correlations
+        corr_pairs = [
+            ["goodput_rolling", "RSRQ"],
+            ["goodput_rolling", "RSRP"],
+            ["goodput_rolling", "RSSI"],
+            ["goodput_rolling", "SINR"],
+            ["goodput_rolling", "downlink_cqi"],
+        ]
+
+        for pair in corr_pairs:
+            # spearman and pearson
+            sp = transmission_df[pair[0]].corr(transmission_df[pair[1]], method="spearman")
+            pe = transmission_df[pair[0]].corr(transmission_df[pair[1]], method="pearson")
+            title = "{}/{} spearman: {} pearson: {}".format(pair[0], pair[1], round(sp, 4), round(pe, 4))
+            transmission_df.plot.scatter(x=pair[0], y=pair[1], c="DarkBlue", title=title)
+
+            if args.save:
+                plt.savefig("{}{}_corr_{}_and_{}.pdf".format(args.save, csv.replace(".csv", ""), pair[0], pair[1]))
+
+            plt.clf()
+
+
         counter += 1
 
         plt.clf()