hilly 0.1.3

Tools for summarizing and viewing sporty GPX traces

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.