Create a trackeRdata object from a data frame with observations being divided in separate training sessions. For breaks within a session observations are imputed.
trackeRdata(dat, units = NULL, sport = NULL, session_threshold = 2,
correct_distances = FALSE, smooth_elevation_gain = TRUE,
from_distances = TRUE, country = NULL, mask = TRUE, lgap = 30,
lskip = 5, m = 11, silent = FALSE)
A data.frame
object.
The output of generate_units
.
What sport does dat
contain data of? Either
'cycling'
, 'running'
, 'swimming'
or
NULL
(default), in which case the sport is directly
extracted from the dat
. See Details.
The threshold in hours for the time difference between consecutive timestamps above which they are considered to belong to different training sessions.
Logical. Should the distances be corrected
for elevation? Default is FALSE
.
Logical. Should the elevation gain be
smoothed before computing elevation gain? Default
is TRUE
.
Logical. Should the speeds be calculated from the distance recordings instead of taken from the speed recordings directly?
ISO3 country code for downloading altitude data. If
NULL
, country is derived from longitude and latitude
Logical. Passed on to
getData
. Should only the altitudes for
the specified country
be extracted (TRUE
) or also
those for the neighboring countries (FALSE
)?
Time in seconds corresponding to the minimal sampling rate.
Time in seconds between the last observation before a small break and the first imputed speed or the last imputed speed and the first observation after a small break.
Number of imputed observations in each small break.
Logical. Should warnings be generated if any of the sanity checks on the data are triggered?
During small breaks within a session, e.g., because the recording device was paused, observations are imputed the following way: 0 for speed, last known position for latitude, longitude and altitude, NA or 0 power for running or cycling session, respectively, and NA for all other variables. Distances are (re-)calculated based on speeds after imputation.
trackeRdata
assumes that all observations in dat
are
from the same sport
, even if dat
ends up having
observations from different sessions (also depending on the value
of session_threshold
.
if attr(dat, 'sport')
is NA
then the current
implementation of trackeRdata
returns an error.
More details about the resulting trackeRdata
object are
available in the package vignette, which is an up-to-date version
of Frick & Kosmidis (2017).
Frick, H., Kosmidis, I. (2017). trackeR: Infrastructure for Running and Cycling Data from GPS-Enabled Tracking Devices in R. Journal of Statistical Software, 82(7), 1--29. doi:10.18637/jss.v082.i07
readContainer
for reading .tcx and .db3
files directly into trackeRdata
objects, and
get_elevation_gain
for details on the computation
of the elevation gain.
## read raw data
filepath <- system.file('extdata/tcx/', '2013-06-08-090442.TCX.gz', package = 'trackeR')
run0 <- readTCX(file = filepath, timezone = 'GMT')
## turn into trackeRdata object
units0 <- generate_units()
run0 <- trackeRdata(run0, units = units0)
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