| Brown_cut | R Documentation | 
This is a convenience wrapper arount cut() and dplyr::mutate(). It
creates a state column dividing a light column into recommended levels by
Brown et al. (2022). Cuts can be adjusted or extended with vector_cuts and
vector_labels
Brown_cut(
  dataset,
  MEDI.colname = MEDI,
  New.state.colname = state,
  vector_cuts = c(-Inf, 1, 10, 250, Inf),
  vector_labels = "default",
  overwrite = TRUE
)
| dataset | A light exposure dataframe | 
| MEDI.colname | The colname containing melanopic EDI values (or,
alternatively, Illuminance). Defaults to  | 
| New.state.colname | Name of the new column that will contain the cut data. Expects a symbol. | 
| vector_cuts | Numeric vector of breaks for the cuts. | 
| vector_labels | Vector of labels for the cuts. Must be one entry shorter
than  | 
| overwrite | Logical. Should the  | 
The input dataset with an additional (or overwritten) column containing a cut light vector
https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001571
Other Brown: 
Brown2reference(),
Brown_check(),
Brown_rec(),
sleep_int2Brown()
sample.data.environment |>
Brown_cut(vector_labels = c("0-1lx", "1-10lx", "10-250lx", "250lx-Inf")) |>
dplyr::count(state)
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