Hilly

Tools for summarizing and viewing sporty GPX traces

Install

pip install hilly

Dev Install

git clone
cd hilly
poetry install

Features

• Traces are loaded as GeoDataFrames (convenient exploring and editing)
• Rasterize traces to see popular routes/trails.
• Label/Filter Skiing Trace to label/exclude chair-lifts.
• Summary for Skiing day

Usage

Import a trace:

import hilly

df = hilly.io.load_trace("path/to/trace.gpx")

If it is a ski/snowboarding trace, apply filters to identify runs/lifts:

ski_df = hilly.ski.apply_filters(df)
ski_df.labels_str.unique().tolist()
# ['', 'lift-1', 'run-1', 'run-2', 'lift-2', 'run-3', 'lift-3', 'run-4']

The labels_str column labels points in the trace as belonging to a lift ride or run, otherwise it is empty. The number indicates a count of lift/runs.

From there you can get a summary for the trace (assuming it is over a single day):

summary = hilly.ski.summary(ski_df)
#🏂 Ski Stats ⛷
#    runs: 4
#    Total Dist(km): 4.815023209198009
#    Longest Run(km): 1.409849302232853
#    Total time: 0 days 00:17:32
#    Total lift time: 0 days 00:36:55.990000
#    Time Ratio: 0.4747313841668961

Or, you can view the trace:

# open leaflet map showing points, dropping datetime column for proper JSON
m = ski_df.drop(columns=["time"]).explore("labels", cmap="coolwarm_r")
m.show_in_browser()

or rasterize the trace to get a density map:

arr, bounds = hilly.utils.rasterize(ski_df, runs_only=True, res=1)
m = hilly.io.map_raster(arr, bounds)
m.show_in_browser()

Collecting Traces

There are many apps available for collecting traces. I use OpenTracks and follow the Export instructions from the settings menu.