Gets the custom effort (deployment duration) for a custom time window and a specific time interval such as day or month. The custom effort is also calculated over all deployments, although filtering predicates can be applied as well.
Usage
get_custom_effort(
package = NULL,
...,
start = NULL,
end = NULL,
group_by = NULL,
unit = "hour",
datapkg = NULL
)
Arguments
- package
Camera trap data package object, as returned by
read_camtrap_dp()
.- ...
filter predicates
- start
Start date. Default:
NULL
. IfNULL
the earliest start date among all deployments is used. Ifgroup_by
unit is notNULL
, the lowest start value allowed is one group by unit before the start date of the earliest deployment. If this condition doesn't hold true, a warning is returned and the earliest start date among all deployments is used. Ifgroup_by
unit isNULL
the start must be later than or equal to the start date among all deployments.- end
End date. Default:
NULL
. IfNULL
the latest end date among all deployments is used. Ifgroup_by
unit is notNULL
, the latest end value allowed is one group by unit after the end date of the latest deployment. If this condition doesn't hold true, a warning is returned and the latest end date among all deployments is used. Ifgroup_by
unit isNULL
the end must be earlier than or equal to the end date among all deployments.- group_by
Character, one of
"day"
,"week"
,"month"
,"year"
. The effort is calculated at the interval rate defined ingroup_by
. Default:NULL
: no grouping, i.e. the entire interval fromstart
toend
is taken into account as a whole. A week is defined as a period of 7 days, a month as a period of 30 days, a year as a period of 365 days.- unit
Character, the time unit to use while returning custom effort. One of:
hour
(default),day
.- datapkg
Deprecated. Use
package
instead.
Value
A tibble data frame with following columns:
begin
: Begin date of the interval the effort is calculated over.effort
: The effort as number.unit
: Character specifying the effort unit.
See also
Other exploration functions:
get_cam_op()
,
get_effort()
,
get_n_individuals()
,
get_n_obs()
,
get_n_species()
,
get_rai_individuals()
,
get_rai()
,
get_record_table()
,
get_scientific_name()
,
get_species()
Examples
# A global effort over the entire duration of the project (datapackage)
# measured in hours
get_custom_effort(mica)
#> # A tibble: 1 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2019-10-09 1321. hour
# Global effort expressed in days
get_custom_effort(mica, unit = "day")
#> # A tibble: 1 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2019-10-09 55.0 day
# Total effort from a specific start to a specific end
get_custom_effort(
mica,
start = as.Date("2019-12-15"), # or lubridate::as_date("2019-12-15")
end = as.Date("2021-01-10")
)
#> # A tibble: 1 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2019-12-15 457. hour
# Effort at daily interval
get_custom_effort(
mica,
group_by = "day"
)
#> # A tibble: 558 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2019-10-09 12.7 hour
#> 2 2019-10-10 24 hour
#> 3 2019-10-11 24 hour
#> 4 2019-10-12 24 hour
#> 5 2019-10-13 24 hour
#> 6 2019-10-14 24 hour
#> 7 2019-10-15 24 hour
#> 8 2019-10-16 24 hour
#> 9 2019-10-17 24 hour
#> 10 2019-10-18 24 hour
#> # … with 548 more rows
# Effort at weekly interval
get_custom_effort(
mica,
group_by = "week"
)
#> # A tibble: 80 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2019-10-09 157. hour
#> 2 2019-10-16 168 hour
#> 3 2019-10-23 10.0 hour
#> 4 2019-10-30 0 hour
#> 5 2019-11-06 0 hour
#> 6 2019-11-13 0 hour
#> 7 2019-11-20 0 hour
#> 8 2019-11-27 0 hour
#> 9 2019-12-04 0 hour
#> 10 2019-12-11 0 hour
#> # … with 70 more rows
# Effort at monthly interval
get_custom_effort(
mica,
group_by = "month"
)
#> # A tibble: 19 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2019-10-09 335. hour
#> 2 2019-11-08 0 hour
#> 3 2019-12-08 0 hour
#> 4 2020-01-07 0 hour
#> 5 2020-02-06 0 hour
#> 6 2020-03-07 0 hour
#> 7 2020-04-06 0 hour
#> 8 2020-05-06 0 hour
#> 9 2020-06-05 219. hour
#> 10 2020-07-05 139. hour
#> 11 2020-08-04 100. hour
#> 12 2020-09-03 0 hour
#> 13 2020-10-03 0 hour
#> 14 2020-11-02 0 hour
#> 15 2020-12-02 0 hour
#> 16 2021-01-01 0 hour
#> 17 2021-01-31 0 hour
#> 18 2021-03-02 99.4 hour
#> 19 2021-04-01 429. hour
# Effort at yearly interval
get_custom_effort(
mica,
group_by = "year"
)
#> # A tibble: 2 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2019-10-09 792. hour
#> 2 2020-10-08 529. hour
# Applying filter(s), e.g. deployments with latitude >= 51.18
get_custom_effort(mica, pred_gte("latitude", 51.18))
#> df %>% dplyr::filter((latitude >= 51.18))
#> # A tibble: 1 × 3
#> begin effort unit
#> <date> <dbl> <chr>
#> 1 2020-06-19 457. hour