| Title: | Estimate Sleep Status from Accelerometry Data |
| Version: | 0.5.0 |
| Description: | Wraps the classifier from the Sundararajan (2021) <doi:10.1038/s41598-020-79217-x> to estimate sleep using a random forest. Users must download the model files from Sundararajan (2020) <doi:10.5281/zenodo.3752645> in order to use this method. |
| License: | GPL (≥ 3) |
| Encoding: | UTF-8 |
| Depends: | R (≥ 4.1.0) |
| Imports: | assertthat, curl, dplyr, methods, reticulate, rlang |
| Suggests: | callr, readr, testthat (≥ 3.0.0) |
| Config/roxygen2/version: | 8.0.0 |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2026-09-08 16:50:58 UTC; johnmuschelli |
| Author: | John Muschelli 
[aut, cre] |
| Maintainer: | John Muschelli <muschellij2@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2026-09-17 09:10:02 UTC |
Run estimate_sleep with Python
Description
Run estimate_sleep with Python
Usage
py_estimate_sleep(
...,
pyenv_function = function() {
sleeper::py_require_sleeper()
},
show = FALSE
)
Arguments
... |
arguments to pass to estimate_sleep |
pyenv_function |
function that loads the forest Python package.
By default, it uses py_require_sleeper to import
the package. If this function has an |
show |
Logical, whether to show the standard output on the
screen while the child process is running, passed to |
Value
Output from estimate_sleep(),
a tibble of times and classification of sleep.
Command for py_require for the full sleeper workflow
Description
Command for py_require for the full sleeper workflow
Usage
py_require_sleeper(...)
Arguments
... |
arguments to pass to |
Value
A logical value indicating whether the package is available.
Compact Example Sleep Models
Description
Compact Example Sleep Models
Usage
sl_example_model(
model_dir = file.path(tempdir(), "sleeper-example-models"),
overwrite = FALSE
)
Arguments
model_dir |
Directory in which to save the example models. |
overwrite |
Logical; overwrite files that are already present. |
Value
The downloaded model paths, or NULL when a download fails.
Examples
models = sl_example_model()
Get Sleep Features
Description
Get Sleep Features
Usage
sl_features(data)
Arguments
data |
A |
Value
A tibble of times and classification of sleep.
Examples
file = system.file("extdata", "example_data.csv.gz", package = "sleeper")
if (requireNamespace("readr", quietly = TRUE)) {
data = readr::read_csv(file, n_max = 3600L)
feat = sl_features(data)
}
Check for Downloaded Sleep Models
Description
Check for Downloaded Sleep Models
Usage
sl_have_models(model_dir)
sl_download_models(
model_dir,
quiet = FALSE,
...,
overwrite = FALSE,
folds = 1:5
)
Arguments
model_dir |
path to the folder with models from doi:10.5281/zenodo.3752645 |
quiet |
argument passed to curl::curl_download |
... |
additional arguments to pass to curl::curl_download |
overwrite |
logical, if |
folds |
should all model folds be downloaded? If only some folds, specify that (used almost exclusively for testing). |
Value
A logical indicating all folds are downloaded.
Estimate Sleep from Wrist-Worn Accelerometry
Description
Estimate Sleep from Wrist-Worn Accelerometry
Usage
sl_python_modules_installed(component = c("models", "features"))
estimate_sleep(data, epoch = 30L, model_dir, cores = 1L)
Arguments
component |
Python dependency set to check. The default, |
data |
A |
epoch |
Time in seconds for the time interval estimate |
model_dir |
path to the folder with models from doi:10.5281/zenodo.3752645 |
cores |
Number of workers to use for model prediction. Any non-zero
integer accepted by Python |
Value
A tibble of times and classification of category.
Examples
if (sl_python_modules_installed("models")) {
models = sl_example_model()
if (!is.null(models) && requireNamespace("readr", quietly = TRUE)) {
file = system.file("extdata", "example_data.csv.gz", package = "sleeper")
data = readr::read_csv(file, n_max = 3600L)
# Two minutes is sufficient to demonstrate the workflow and avoids
# applying the forest to the full 12-hour example recording.
try({estimate_sleep(data, model_dir = dirname(models$binary[1]))})
}
}