This function takes a data frame of image data and calculates snow, temperature, effort, count, and RAI metrics aggregated over a specified time window. These can optionally be calculated using a moving window ("rolling") calculation.
Usage
rai_by_time(
image_data,
by = c("date", "week", "month", "year"),
roll = FALSE,
k = 7,
by_species = TRUE,
species = NULL,
by_deployment = FALSE,
deployment_label = NULL,
sample_start_date = NULL,
sample_end_date = NULL,
snow_agg = "max"
)Arguments
- image_data
data.frame of class
image_data, as read in byread_image_data().- by
time to aggregate by: One of
"date"(default),"week","month", or"year".- roll
should it use a rolling window? Default
FALSE- k
the size of the rolling window. Default
7.- by_species
Should an RAI be calculated for each species (
TRUE, default), or one RAI for all species (FALSE)- species
Optionally, or more species as a character vector. Default
NULLto calculate RAI for each species detected.- by_deployment
Should it be calculated by
deployment. DefaultFALSE- deployment_label
Optionally, one or more deployment labels to select. Default
NULLto use all deployments.- sample_start_date
a custom start date. Note that this will apply the same start date to all deployments/sessions in the data.
- sample_end_date
a custom end date. Note that this will apply the same start date to all deployments/sessions in the data.
- snow_agg
if
by_deployment = FALSE, how to aggregate snow measurements across sites. Takes the name of an aggregation function (e.g.,"mean"). Default"max"