activatr
can parse additional information beyond the
basic lat/lon data from GPX/TCX files, as well as sample the files for
quicker manipulation.
All of the advanced functionality is included in the
parse_gpx
or parse_tcx
function with optional
arguments. As a reminder, this is what the default parsing would look
like and return:
library(activatr)
# Get the running_example.gpx file included with this package.
filename <- system.file(
"extdata",
"running_example.gpx.gz",
package = "activatr"
)
df <- parse_gpx(filename)
lat | lon | ele | time |
---|---|---|---|
37.80405 | -122.4267 | 17.0 | 2018-11-03 14:24:45 |
37.80406 | -122.4267 | 16.8 | 2018-11-03 14:24:46 |
37.80408 | -122.4266 | 17.0 | 2018-11-03 14:24:48 |
37.80409 | -122.4266 | 17.0 | 2018-11-03 14:24:49 |
37.80409 | -122.4265 | 17.2 | 2018-11-03 14:24:50 |
If your GPX file contains additional extension information,
activatr
can parse that as well. In this case,
running_example.gpx
contains heart rate, cadence, and
temperature information. We can parse that by setting
detail = "advanced"
in parse_gpx
:
lat | lon | ele | time | hr | cad |
---|---|---|---|---|---|
37.80405 | -122.4267 | 17.0 | 2018-11-03 14:24:45 | 102 | 68 |
37.80406 | -122.4267 | 16.8 | 2018-11-03 14:24:46 | 104 | 73 |
37.80408 | -122.4266 | 17.0 | 2018-11-03 14:24:48 | 107 | 89 |
37.80409 | -122.4266 | 17.0 | 2018-11-03 14:24:49 | 110 | 89 |
37.80409 | -122.4265 | 17.2 | 2018-11-03 14:24:50 | 112 | 89 |
Now we can do plots like heart rate over time, or a distribution of cadences:
If you’re parsing many GPX files or GPX files sampled every second,
you often don’t need a “full resolution” view of the activity. The
every
argument to parse_gpx
allows you to only
sample some points from the GPX, speeding up the parsing:
# Parsing as normal gets all of the rows, but takes longer
full_time <- system.time({
df_full <- parse_gpx(filename)
})
nrow(df_full)
#> [1] 4433
full_time
#> user system elapsed
#> 0.134 0.003 0.138
# Grabbing every hundredth data point runs much faster
sample_time <- system.time({
df_sample <- parse_gpx(filename, every = 100)
})
nrow(df_sample)
#> [1] 44
sample_time
#> user system elapsed
#> 0.021 0.001 0.022