Infrastructure for Running, Cycling and Swimming Data from
GPS-Enabled Tracking Devices
Provides infrastructure for handling running, cycling and swimming data from GPS-enabled tracking devices within R. The package provides methods to extract, clean and organise workout and competition data into session-based and unit-aware data objects of class 'trackeRdata' (S3 class). The information can then be visualised, summarised, and analysed through flexible and extensible methods. Frick and Kosmidis (2017) , which is updated and maintained as one of the vignettes, provides detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality.
threshold.trackeRdata reports on the progress of the operation if
trace = TRUE in its arguments
- Added new logo
- Updated documentation
- Fixed a bug that caused
threshold to not threshold if applied without specifying any of variable, lower, upper and sport.
plot_route now returns plots using stamen maps (see
?ggmap::get_map for the reasons we are moving away from other maps).
Updated vignettes to avoid errors during CRAN checks
- Multi-sport support (cycling, running, swimming)
- Comprehensive support for temperature recordings from devices
readGPX for reading Strava GPX files
readX functions now return objects with a
sport attribute with values (
trackeRdata objects now have a print method with basic summaries
ridges method for
conProfile objects for ridgeline plots of concentration profiles
session_times methods for
auto_breaks argument when plotting zones, distribution and concentration profiles
unique methods for
- Numerous under-the-hood performance and design improvements
- Refactored code for
readTCX; reading Garmin TCX is now notably faster (circa 15x faster) and more robust
- Refactored code for
summary method for
trackeRdata objects, making it faster (circa 10x faster)
- Code improvements in
c improvements for
readDirectory can be perfromed in parallel usign foreach
- sane multi-platform parallelization across methods using
foreach. The parallel backend and its details needs to be set by the user
- Wprime has been adapted for a multisport environment
- Enhancements to the definition of the
trackeRdata object and the associated methods; the object now carries file and sport information
- Various bug fixes in
- Fixed bug in
scaled method that would cause an error for single sessions
aggregate method is now doing what is supposed to
- Maintainer changed from Hannah Frick to Ioannis Kosmidis
- Robin Hornak joined developer team as author
- Added citation for JSS paper.
- The color palette for plots of trackeRdataZones objects is now also based on black/blue.
- The vignette Tour de trackeR and the examples for
plotRoute() now use maps from Stamen rather than OpenStreetMap.
- The sanity checks performed when creating a trackeRdata object now throw warnings. This can be switched off with the argument
silent = TRUE.
- The color palette for plots of trackeRdataSummary and trackeRdataZones objects changed slightly.
plotRoute() can now include more than one session in one plot. The
leafletRoute() uses the leaflet package to produce an
- Added a method for distribution and concentration profiles to fit a functional principal components analysis and a plot function to accompany it.
- Added a second, shorter vignette "Tour de trackeR" to illustrate basic features and new functionality.
- Added a new timeline plot for trackeRdata object to visualise the date time of the sessions.
- Added a new nsessions method to access the number of sessions in various trackeR objects.
- Updated "runs" data object by splitting former session 20 into 2 sessions as the two parts of the session took place in two different place with a break of over 1.5 hours between them.
- The scale options has been removed from the distribution profile and is now set-up as a separate operation. In this implementation first smoothing and then scaling (the right order for those operations) is possible.
- Some improvements for trackeRdata(): session containing no information beyond the timestamps are removed; conversions between distance and speed now recognise the respective units.
- Distribution profile: if all values of the variable for which the profile is to be calculated are missing, the profile (and its smoothed version) will also consist of only NA (rather than throwing an error).
- Experimental support for reading Golden Cheetah's JSON files.
- First CRAN release of new "trackeR" package which provides
infrastructure for handling running and cycling data from
GPS-enabled tracking devices. See vignette("trackeR", package =
"trackeR") for details.