measurement-scripts/plot_gps_csv.py

#!/usr/bin/env python3

from argparse import ArgumentParser

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

import seaborn as sns

sns.set()
#sns.set(font_scale=1.5)


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)
    gdf["is_retranmission"] = gdf["is_retranmission"].replace(True, np.NaN).dropna().astype(float)

    print("Start plotting...")

    df_wm = gdf.to_crs(epsg=3857)
    ax2 = df_wm.plot()
    ax2 = df_wm.plot(column=args.column, cmap="hot", legend=args.no_legend, ax=ax2, legend_kwds={"label": args.label},)
    # 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()
    if not args.no_legend:
        ax2.set_title(args.label if args.label else args.column)
    else:
        fig = ax2.figure
        cb_ax = fig.axes[0]
        cb_ax.set_label(args.label)
        cb_ax.tick_params(labelsize=30)

    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.eps".format(args.save), bbox_inches="tight")
    else:
        plt.show()