curate_dead_animals: Remove - irrelevant - data after individual have died
In sleepr: Analyse Activity and Sleep Behaviour

Description Usage Arguments Details Value See Also Examples

This function detects when individuals have died based on their first (very) long bout of immobility. Following data (which may include spurious artefact of movement) are removed.

1 2	curate_dead_animals(data, moving_var = moving, time_window = hours(24), prop_immobile = 0.01, resolution = 24)

`data`	data.table containing behavioural variable from or one multiple animals. When it has a key, unique values, are assumed to represent unique individuals (e.g. in a behavr table). Otherwise, it analysis the data as coming from a single animal. `data` must have a column `t` representing time.
`moving_var`	logical variable in `data` used to define the moving (alive) state (default is `moving`)
`time_window`	window during which to define death (default is one day)
`prop_immobile`	proportion of immobility that counts as "dead" during time_window (see details)
`resolution`	how much scanning windows overlap. Expressed as a factor (see details).

This function scans the time series looking for "death" in the right (future) data, within time_window. Death is defined as mean(moving_var) < prop_immobile within a time window. Moving window start every time_window/resolution. resolution = 1 is fast but means no overlap. The default would score an animal as dead it does not move more than one percent of the time for at least one day. All data following a "death" event are removed.

an object of the same type as data (i.e. data.table::data.table or behavr::behavr).

sleep_annotation – to score movement and slepe

dt1 <- toy_activity_data()
#all movement after day 3 is set at 0
dt1[t > days(3), moving := FALSE]
# one artefact of movement is detected at day 3.5
dt1[t == days(3.5), moving := TRUE]

dt2 <- curate_dead_animals(dt1)
dt3 <- curate_dead_animals(dt1,prop_immobile = 0)
## Not run: 
library(ggplot2)
ggplot(data=dt1[,test:=1],aes(t, as.numeric(moving))) +
  geom_line(data=dt1[,test:=1]) +
  geom_line(data=dt2[, test:=2])+
  geom_line(data=dt3[, test:=3])+
  facet_grid(test ~ .)+
  scale_x_time()

## End(Not run)