Reference#
track_viz#
Visualize Tracking Data.
- class track_viz.TrackingColumn#
Names of columns in a tracking dataframe.
- track_viz.gpx_to_dataframe(gpx)#
Process GPX file.
- Parameters
gpx (Path) –
- Return type
DataFrame
- track_viz.heatmap(track)#
Create heatmap.
- Parameters
track (Path) –
- Return type
Figure
- track_viz.heatmap_from_dataframe(track)#
Create heatmap.
- Parameters
track (DataFrame) –
- Return type
Figure
- track_viz.plot_acceleration(track)#
Create the speed plot.
- Parameters
track (Path) –
- Return type
Figure
- track_viz.plot_movement_field(movements, mvt_field)#
Standard plot for 1 field of the movements dataframe.
- Parameters
movements (DataFrame) –
mvt_field (str) –
- Return type
Figure
- track_viz.plot_speed(track)#
Create the speed plot.
- Parameters
track (Path) –
- Return type
Figure
- track_viz.plot_speed_moving_avg(track)#
Create the speed plot.
- Parameters
track (Path) –
- Return type
Figure
- track_viz.run_webserver(host, port)#
Run webserver.
- Parameters
host (str) –
port (int) –
- Return type
None
- track_viz.tcx_to_dataframe(tcx)#
Process a TCX file.
- Parameters
tcx (Path) –
- Return type
DataFrame
- track_viz.track_2_movements(df)#
Transform tracking information to time series of speed and other metrics.
List of fields in the movements dataframe: * delta_time: time difference between one sample and the previous one * prev_lon, prev_lat: longitude / latitude of previous tracking point * delta_alt_m: altitude difference in meters between current sample and previous sample * elapsed_time: timestamp of a tracking point, considering the run started on Jan 1 2021 at 00:00 * ground_distance_m: distance over earth surface covered between previous point and current point, in meters * distance_m: distance in meters between previous point and current point, taking altitude difference into account * speed_ms: speed at the current point in meters per second * speed_kmh: speed in kilometers per hour * speed_moving_avg_1min: moving average of the speed over the last minute, in kilometers per hour * delta_speed_ms: change in speed in meters per second * delta_moving_avg_1min: change in moving average in kilometers per hour * acceleration_ms2: acceleration in meters per square meters * use_point: bool indicates whether the point is “usable”
The sampling frequency is identified as the most frequent time difference between 2 samples. Any time this time difference is more than 2 times this sampling frequency, we mark the first point AFTER the gap with FALSE in field “use_point”.
- Parameters
df (DataFrame) –
- Return type
DataFrame
- track_viz.web_plot_speed_climb_kde(track)#
Create plot for website for KDE with speed and elevation.
- Parameters
track (DataFrame) –
- Return type
Figure
- track_viz.web_plot_speed_elevation(track)#
Create plot for website with both speed and elevation.
- Parameters
track (DataFrame) –
- Return type
Figure