measurement-scripts/plot_gps_new.py

#!/usr/bin/env python3

from argparse import ArgumentParser

import pandas as pd
import geopandas as gpd
import contextily as cx
import matplotlib.pyplot as plt

if __name__ == "__main__":
    parser = ArgumentParser()
    parser.add_argument("-f", "--file", required=True, help="Messfahrt csv")
    parser.add_argument("-a", "--column", required=True, help="Column to plot")
    parser.add_argument("-l", "--label", help="Label above the plot.")
    parser.add_argument("--no_legend", action="store_false", default=True, help="Do not show legend.")
    parser.add_argument("--save", default=None, help="Location to save pdf file.")

    parser.add_argument(
        "--show_providerinfo",
        default=False,
        help="Show providerinfo for map tiles an zoom levels.",
    )

    args = parser.parse_args()

    df = pd.read_csv(args.file)

    gdf = gpd.GeoDataFrame(
        df,
        geometry=gpd.points_from_xy(df["longitude"], df["latitude"]),
        crs="EPSG:4326",
    )

    gdf["srtt"] = gdf["srtt"].apply(lambda x: x / 10 ** 6)

    print("Start plotting...")

    df_wm = gdf.to_crs(epsg=3857)
    ax2 = df_wm.plot()
    ax2 = df_wm.plot(args.column, cmap="hot", legend=args.no_legend, ax=ax2)
    # ax2 = df_wm.plot.scatter(x="longitude", y="latitude", c="kmh", cmap="hot")
    # zoom 17 is pretty
    cx.add_basemap(ax2, source=cx.providers.OpenStreetMap.Mapnik, zoom=17)

    #    gdf.plot()
    ax2.set_axis_off()
    ax2.set_title(args.label if args.label else args.column)

    if args.show_providerinfo:
        #####################################
        # Identifying how many tiles
        latlon_outline = gdf.to_crs("epsg:4326").total_bounds
        def_zoom = cx.tile._calculate_zoom(*latlon_outline)
        print(f"Default Zoom level {def_zoom}")

        cx.howmany(*latlon_outline, def_zoom, ll=True)
        cx.howmany(*latlon_outline, def_zoom + 1, ll=True)
        cx.howmany(*latlon_outline, def_zoom + 2, ll=True)

        # Checking out some of the other providers and tiles
        print(cx.providers.CartoDB.Voyager)
        print(cx.providers.Stamen.TonerLite)
        print(cx.providers.Stamen.keys())
        #####################################

    # df.plot(x="longitude", y="latitude", kind="scatter", colormap="YlOrRd")

    if args.save:
        plt.savefig("{}gps_plot.pdf".format(args.save))
    else:
        plt.show()