regularise_time: regularise_time
In frycast/studentlife: Tidy Handling and Navigation of the Student-Life Dataset

Transform an SL_tibble (as produced by load_SL_tibble) in such a way that the observations are aggregated in equal length intervals called 'blocks' (for more information on blocks see add_block_labels).

regularise_time(
  tab,
  ...,
  blocks = c("epoch", "day"),
  add_NAs = TRUE,
  unsafe = F,
  study_duration = getOption("SL_duration"),
  start_date = getOption("SL_start"),
  epoch_levels = getOption("SL_epoch_levels"),
  epoch_ubs = getOption("SL_epoch_ubs"),
  uid_range = getOption("SL_uids"),
  date_range = seq(from = start_date, by = 1, length.out = study_duration)
)

`tab`	An `SL_tibble` as returned by the function `load_SL_tibble`. The `SL_tibble` must have some date-time information.
`...`	Arguments passed to `summarise`, used to aggregate values when multiple observations are encountered in a block. Any columns not specified here or under `blocks` will be dropped.
`blocks`	A character vector naming one or more of the block options "hour_in_day", "epoch", "day", "week", "weekday", "month" or "date". If not present as column names in `tab`, an attempt will be made to infer the blocks from existing time information with `add_block_labels`. The returned `data.frame` will have one observation (possibly `NA`) for each block.
`add_NAs`	A logical. If TRUE then NAs will be introduced to fill missing blocks.
`unsafe`	A logical. Default is `FALSE`. If this is set to `TRUE` then less checks will be performed.
`study_duration`	Integer. The duration of the StudentLife study in days. This parameter does nothing if `limit_date_range` it `TRUE`.
`start_date`	Date. The date that the StudentLife study started.
`epoch_levels`	A character vector of epoch labels.
`epoch_ubs`	An integer vector that defines the hour that is the upper boundary of each epoch.
`uid_range`	An integer vector. The range of uids in the StudentLife study.
`date_range`	A vector of dates to be used if `limit_date_range` is `FALSE`.

d <- tempdir()
download_studentlife(location = d, url = "testdata")

tab <- load_SL_tibble(
  loc = d, schema = "sensing", table = "activity", csv_nrows = 10)

r_tab <- regularise_time(
  tab, blocks = c("day","weekday"),
  act_inf = max(activity_inference), add_NAs = FALSE)

r_tab