Adds pdf export.

plot_transmission_timeline.py

         lambda x: ((x * 8) / args.interval) / 10**6
     )
 
-    # load dataframe an put it into geopandas
-    df = pd.read_csv(args.gps_file)
-    df["kmh"] = df["speed (knots)"].apply(lambda x: x * 1.852)
-    df = df.set_index("datetime")
-    df.index = pd.to_datetime(df.index)
-
-    gdf = gpd.GeoDataFrame(
-        df,
-        geometry=gpd.points_from_xy(df["longitude"], df["latitude"]),
-        crs="EPSG:4326",
-    )
-    gdf = pd.merge_asof(
-        gdf,
-        transmission_df,
-        tolerance=pd.Timedelta("10s"),
-        right_index=True,
-        left_index=True,
-    )
 
     # read serial csv
     serial_df = pd.read_csv(args.serial_file)
     serial_df = serial_df.set_index("datetime")
     serial_df.index = pd.to_datetime(serial_df.index)
 
-    gdf = pd.merge_asof(
-        gdf,
+    transmission_df = pd.merge_asof(
+        transmission_df,
         serial_df,
         tolerance=pd.Timedelta("1s"),
         right_index=True,
         left_index=True,
     )
 
-    # format to needed format and add basemap as background
-    df_wm = gdf.to_crs(epsg=3857)
-
     scaley = 1.5
     scalex = 1.0
     plt.figure(figsize=[6.4 * scaley, 4.8 * scalex])
     par12.axis["right"].toggle(all=True)
     # par13.axis["right"].toggle(all=True)
 
-    host.plot(gdf["goodput"], "-", color="blue", label="goodput" )
+    host.plot(transmission_df["goodput"], "-", color="blue", label="goodput" )
     host.set_xlabel("datetime")
     host.set_ylabel("goodput [Mbps]")
     #host.set_ylim([0, 13])
     #host.set_yscale("log")
     #host.set_yscale("log")
 
-    par11.plot(gdf["downlink_cqi"], "--", color="green", label="CQI")
+    par11.plot(transmission_df["downlink_cqi"], "--", color="green", label="CQI")
     par11.set_ylabel("CQI")
     par11.set_ylim([0, 15])