Calculate metrics for values inside and/or outside a specified time range.

This function applies a given function to a subset of data filtered by time of day.

Usage

calculate_sleep_wake(
  data,
  FUN,
  sleep_start = 0,
  sleep_end = 6,
  calculate = c("sleep", "wake", "both"),
  ...
)

Arguments

data

DataFrame object with column names "id", "time", and "gl".

FUN

Function to be applied to the filtered data.

sleep_start

Numeric between 0-24 signifying the hour at which the time range should start.

sleep_end

Numeric between 0-24 signifying the hour at which the time range should end.

calculate

String determining whether FUN should be applied to values inside or outside the time range. Both separately is an option

...

Optional arguments which will be passed to FUN

Value

An object of the same return type as FUN, with columns corresponding to the values returned by FUN. Separated for values inside or outside the time range, if calculate = both.

Details

An object of the same return type as FUN, with the same column names as FUN will be returned. If calculate = "both", there will be columns for FUN applied to both inside and outside values, with either "in range" or "out of range" append to signify whether the statistic was calculated on values which were inside the time range or outside the range.

FUN is found by a call to match.fun and typically is either a function or a character string specifying a function to be searched for from the environment of the call to apply. Arguments in ... cannot have the same name as any of the other arguments, and care may be needed to avoid partial matching to FUN. FUN is applied to the data after the data is filtered based on whether its hour falls within the given range. If sleep_start is an integer, all times within that hour will be included in the range, but if sleep_end is an integer only times up to that hour will be included in the range. If sleep_start is after sleep_end, the data will be filtered to include all hours after sleep_start and all times before sleep_end.

Examples

data(example_data_1_subject)
calculate_sleep_wake(example_data_1_subject, sd_glu, calculate = "sleep")
#> # A tibble: 1 × 2
#>   id           SD
#>   <fct>     <dbl>
#> 1 Subject 1  25.4

data(example_data_5_subject)
calculate_sleep_wake(example_data_5_subject, cogi, targets = c(80, 150),
weights = c(.3,.2,.5), calculate = "wake")
#> # A tibble: 5 × 2
#>   id         COGI
#>   <fct>     <dbl>
#> 1 Subject 1  82.4
#> 2 Subject 2  52.5
#> 3 Subject 3  69.6
#> 4 Subject 4  82.9
#> 5 Subject 5  56.0
calculate_sleep_wake(example_data_5_subject, sd_measures, sleep_start = 2,
sleep_end = 8, calculate = "both")
#> # A tibble: 5 × 13
#>   id        `SDw sleep` `SDhhmm sleep` `SDwsh sleep` `SDdm sleep` `SDb sleep`
#>   <fct>           <dbl>          <dbl>         <dbl>        <dbl>       <dbl>
#> 1 Subject 1        10.2           3.04          3.15         21.3        23.9
#> 2 Subject 2        18.9          12.8           6.22         41.9        43.6
#> 3 Subject 3        17.6           9.99          4.86         20.1        32.7
#> 4 Subject 4        10.8           3.98          3.43         12.2        17.3
#> 5 Subject 5        28.1          13.3           5.88         29.4        38.4
#> # ℹ 7 more variables: `SDbdm sleep` <dbl>, `SDw wake` <dbl>,
#> #   `SDhhmm wake` <dbl>, `SDwsh wake` <dbl>, `SDdm wake` <dbl>,
#> #   `SDb wake` <dbl>, `SDbdm wake` <dbl>