The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
{strength} is a collection of computations commonly needed in
exercise science to plan and quantify strength training. Currently this
covers mapping between rating of perceived exertion (rpe),
repetitions performed in a set (reps) and percentage of one
rep max (pct_1rm). There is also a convenience function
hard_sets().
You can install the CRAN version of strength with:
install.packages("strength")You can install the development version of strength from GitHub with:
# install.packages('remotes')
remotes::install_github("alexpaynter/strength")The following example calculates the estimated percentage of one rep max associated with 4 sets where reps and RPE were recorded:
library(strength)
library(tidyr)
dat <- tidyr::expand_grid(
reps = c(3,10),
rpe = c(8.5, 7)
) |>
dplyr::mutate(pct_1rm = pct1rm_rts(reps = reps, rpe = rpe))
dat
#> # A tibble: 4 × 3
#> reps rpe pct_1rm
#> <dbl> <dbl> <dbl>
#> 1 3 8.5 87.8
#> 2 3 7 83.7
#> 3 10 8.5 71.6
#> 4 10 7 69.1Computing the number of hard sets using a cutoff of 8 for RPE is an easy addon:
library(strength)
library(tidyr)
dat %>%
dplyr::summarize(hard_sets(rpe = rpe, cutoff = 8))
#> # A tibble: 1 × 1
#> `hard_sets(rpe = rpe, cutoff = 8)`
#> <int>
#> 1 2These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.