Selaa lähdekoodia

Refactor GPS scripts.

master
Lukas Prause 2 vuotta sitten
vanhempi
commit
180f4dcc8a
2 muutettua tiedostoa jossa 76 lisäystä ja 50 poistoa
  1. +3
    -50
      calc_gps_map_csv.py
  2. +73
    -0
      plot_gps_csv.py

plot_gps.py → calc_gps_map_csv.py Näytä tiedosto

@@ -50,18 +50,8 @@ if __name__ == "__main__":
parser.add_argument("-f", "--gps_file", required=True, help="GPS csv file.")
parser.add_argument("-s", "--serial_file", required=True, help="Serial csv file.")
parser.add_argument("-p", "--pcap_csv_folder", required=True, help="PCAP csv folder.")
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("--time_offset", default=None, type=int, help="Minutes added to GPS datetime.")
parser.add_argument("--no_plot", default=False, action="store_true", help="Only calculations without plotting.")

parser.add_argument(
"--show_providerinfo",
default=False,
help="Show providerinfo for map tiles an zoom levels.",
)
parser.add_argument(
"-c",
"--cores",
@@ -180,43 +170,6 @@ if __name__ == "__main__":
df_wm = gdf.to_crs(epsg=3857)
#df_wm.to_csv("debug-data.csv")
# ax2 = df_wm.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
if args.no_plot:
df_wm.to_csv("{}gps_plot.csv".format(args.save))
print("Saved calculations to: {}gps_plot.csv".format(args.save))
exit(0)

print("Start plotting...")

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=15)

# 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()

df_wm.to_csv("{}gps_plot.csv".format(args.save))
print("Saved calculations to: {}gps_plot.csv".format(args.save))

+ 73
- 0
plot_gps_csv.py Näytä tiedosto

@@ -0,0 +1,73 @@
#!/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

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(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()

Loading…
Peruuta
Tallenna