impactr 0.4.1
- Fixed an issue with saving the non-wear plot with
remove_nonwear()
(#2).
- Change the name of the “valid_observation” to “valid_file” in the
non-wear summary to better express its meaning.
- Limited the number of characters of the non-wear plot title to 50
characters, preventing the plot title to exceed the plot window limits.
In case of large (n. char. > 50) titles,
remove_nonwear()
automatically crops it.
- Return
NA
in the summary variables from
summarise_loading()
whenever the number of detected peaks
is 0.
- Change the coefficients of the prediction models for walking/running
to match the final version of the published paper.
impactr 0.4.0
- Added the function
remove_nonwear()
to detect and
remove accelerometer non-wear time.
- Added the function
summarise_loading()
.
- Include an interface to access example datasets from the {accdata} package. Run
?import_dataset
for help.
- Changed how resultant vector is computed to improve speed.
read_acc()
no longer displays a progress bar.
impactr 0.3.0
pracma::findpeaks()
is now used to get the index of the
curve start.
- Fixed a bug in which
predict_loading()
did not return
the expected columns if outcome
is set to “all”.
- Added a new supported model: “jumping”.
impactr 0.2.0
define_region()
now works with multi-day data. See the
updated documentation.
specify_parameters()
and filter_acc()
throw errors when called more than once on the same data. This prevents
attributes being accidentally added on top of existing ones.
predict()
throws an error when required attributes are
missing.
- Fixed a test failure with {tibble} release 3.1.4 (#1).