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Add states to a dataset based on groups and start/end times

Source: R/extract_states.R
add_states.Rd

add_states() brings states to a time series dataset. It uses the States.dataset to add states to the dataset. The States.dataset must at least contain the same variables as the dataset grouping, as well as a start and end time. Beware if both datasets operate on different time zones and consider to set force.tz = TRUE.

Usage

add_states(
  dataset,
  States.dataset,
  Datetime.colname = Datetime,
  start.colname = start,
  end.colname = end,
  force.tz = FALSE,
  leave.out = c("duration", "epoch")
)

Arguments

dataset

A light logger dataset. Needs to be a dataframe.

States.dataset

A light logger dataset. Needs to be a dataframe. This dataset must contain the same variables as the dataset grouping, as well as a start and end time. Any other column, that is not in leave.out will be added to the dataset.

Datetime.colname

The column that contains the datetime. Needs to be a POSIXct and part of the dataset.

start.colname, end.colname

The columns that contain the start and end time. Need to be POSIXct and part of the States.dataset.

force.tz

If TRUE, the start and end times of the States.dataset will be forced to the same time zone as the dataset using lubridate::force_tz(). If FALSE (default), the start and end times of the States.dataset will be used as is.

leave.out

A character vector of columns that should not be carried over to the dataset

Value

a modified dataset with the states added. The states are added as new columns to the dataset. The columns are named after the columns in the States.dataset, except for the start and end times, which are removed.

Details

Beware if columns in the dataset and States.dataset have the same name (other then grouping variables). The underlying function, dplyr::left_join() will mark the columns in the dataset with a suffix .x, and in the States.dataset with a suffix .y.

Examples

states <-
sample.data.environment |>
  filter_Date(length = "1 day") |> 
  extract_states(Daylight, MEDI > 1000)

states |> head(2)
#> # A tibble: 2 × 7
#> # Groups:   Id, Daylight [1]
#>   Id          Daylight state.count epoch start               end                
#>   <fct>       <lgl>    <chr>       <dbl> <dttm>              <dttm>             
#> 1 Environment FALSE    FALSE 1        30 2023-08-28 23:59:53 2023-08-29 06:57:53
#> 2 Environment FALSE    FALSE 2        30 2023-08-29 19:45:23 2023-08-29 23:59:53
#> # ℹ 1 more variable: duration <Duration>

#add states to a dataset and plot them - as we only looked for states on the
# first day (see above), only the first day will show up in the plot
sample.data.environment |> 
 filter_Date(length = "2 day") |> 
 add_states(states) |> 
 gg_days() |> 
 gg_state(Daylight)