bout_analysis {sleepr} | R Documentation |
Find "bouts" in categorical time series
Description
This function is used to find contiguous regions of unique value in a – potentially irregular/heterogeneous – univariate categorical time series.
Usage
bout_analysis(var, data)
Arguments
var |
name of the variable to use from |
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. |
Value
an object of the same type as data
(i.e. data.table::data.table or behavr::behavr).
Each row is a specific bout characterised by three columns.
-
t
– its onset -
duration
– its length -
<var>
– a column with the same name asvar
. The value ofvar
for this bout.
References
The relevant rethomic tutorial section – on sleep analysis
See Also
-
sleep_annotation – to generate a binary sleep variable
-
rle run length encoding function – on which this analysis is based
Examples
# Bout analysis on binary variable:
dt <- toy_dam_data()
dt[, moving := activity > 0]
bdt <- bout_analysis(moving,dt)
print(bdt)
# With multiple states
dt <- toy_ethoscope_data()
# we discretise x position in three states: left, middle and right (1/3 each)
dt[, location := as.character( cut(x,
breaks = c(0.0, .33, .67, 1.0),
labels = c("left", "middle", "right")))]
bdt <- bout_analysis(location, dt)