Visualising your completed Komoot tours
Project description
About gpx_vis
gpx_vis
enables simple and convenient visualisation of your cycling or hiking tours.
Important note: Currently, it exclusively supports .GPX files generated from completed paths in Komoot. Please be aware that this tool is still in development.
Install
pip install gpx_vis
Update to the latest version:
pip install gpx_vis --upgrade
Instantiate
from gpx_vis import Track
track = Track(pathname)
pathname
serves as a reference to either a single .gpx
file or a directory.
If a directory path is provided, all .gpx files contained within that directory
will be merged, but retain their original metadata (e.g., different tracks remain separated).
This allows users to overlay multiple tracks onto a single map,
providing a comprehensive summary of the data being analyzed.
Map creation
track.create_map(filename)
This generates an HTML file saved under filename
, which contains an interactive map.
Users can hover over routes or click on final waypoints (flags) for additional information.
In cases where the map contains a large dataset and loading time is a concern (if one
has been very hardworking), users have the option to include lite = True
. By default, this option limits the
number of data points displayed on each route to 50
. However, users can adjust this
limit using the nlite
argument, for instance,
track.create_map(filename, lite=True, nlite=100)
City overview
track.city_list
Interested in the cities you passed through on your journey? This command generates a list
of cities - sorted by country and name - that were detected along the tour route. The
frequency
parameter indicates how many times each city was encountered,
providing a rough estimate of the time spent in each city.
Additional information
If you wish to plot or inspect different values, these parameters are also accessible via:
track.t
: time (UTC)
track.x
: longitude (deg)
track.y
: latitude (deg)
track.z
: elevation (m)
For a more comprehensive and unprocessed dataset, you can use:
track.data
: Returns a pandas.DataFrame
with headers ['trackName', 'latitude', 'longitude', 'elevation', 'time']
Dependencies
(numpy) https://numpy.org/
(pandas) https://pandas.pydata.org/
(altair) https://altair-viz.github.io/
(branca) https://pypi.org/project/branca/
(gpxpy) https://github.com/tkrajina/gpxpy
(vincenty) https://pypi.org/project/vincenty/
(folium) https://github.com/python-visualization/folium
(humanfriendly) https://pypi.org/project/humanfriendly/
(reverse-geocode) https://pypi.org/project/reverse-geocode/
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