Get custom effort

Gets the custom effort (deployment duration) for a custom time window and a specific time interval such as day, week, month or year. The custom effort is also calculated over all deployments, although filtering predicates can be applied as well. This function calls get_cam_op() internally.

Usage

get_custom_effort(
  package = NULL,
  ...,
  start = NULL,
  end = NULL,
  group_by = NULL,
  unit = "hour",
  datapkg = lifecycle::deprecated()
)

Arguments

package

Camera trap data package object, as returned by read_camtrap_dp().

...

filter predicates

start

Start date. Default: NULL. If NULL the earliest start date among all deployments is used. If group_by unit is not NULL, 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. If group_by unit is NULL the start must be later than or equal to the start date among all deployments.

end

End date. Default: NULL. If NULL the latest end date among all deployments is used. If group_by unit is not NULL, 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. If group_by unit is NULL 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 in group_by. Default: NULL: no grouping, i.e. the entire interval from start to end is taken into account as a whole. Calendar values are used, i.e. grouping by year will calculate the effort from Jan 1st up to Dec 31st for each year.

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 
#> # ℹ 548 more rows

# Effort at weekly interval
get_custom_effort(
  mica,
  group_by = "week"
)
#> # A tibble: 81 × 3
#>    begin      effort unit 
#>    <date>      <dbl> <chr>
#>  1 2019-10-06   84.7 hour 
#>  2 2019-10-13  168   hour 
#>  3 2019-10-20   82.0 hour 
#>  4 2019-10-27    0   hour 
#>  5 2019-11-03    0   hour 
#>  6 2019-11-10    0   hour 
#>  7 2019-11-17    0   hour 
#>  8 2019-11-24    0   hour 
#>  9 2019-12-01    0   hour 
#> 10 2019-12-08    0   hour 
#> # ℹ 71 more rows

# Effort at monthly interval
get_custom_effort(
  mica,
  group_by = "month"
)
#> # A tibble: 19 × 3
#>    begin      effort unit 
#>    <date>      <dbl> <chr>
#>  1 2019-10-01  335.  hour 
#>  2 2019-11-01    0   hour 
#>  3 2019-12-01    0   hour 
#>  4 2020-01-01    0   hour 
#>  5 2020-02-01    0   hour 
#>  6 2020-03-01    0   hour 
#>  7 2020-04-01    0   hour 
#>  8 2020-05-01    0   hour 
#>  9 2020-06-01  219.  hour 
#> 10 2020-07-01   66.5 hour 
#> 11 2020-08-01  172.  hour 
#> 12 2020-09-01    0   hour 
#> 13 2020-10-01    0   hour 
#> 14 2020-11-01    0   hour 
#> 15 2020-12-01    0   hour 
#> 16 2021-01-01    0   hour 
#> 17 2021-02-01    0   hour 
#> 18 2021-03-01   99.4 hour 
#> 19 2021-04-01  429.  hour 

# Effort at yearly interval
get_custom_effort(
  mica,
  group_by = "year"
)
#> # A tibble: 3 × 3
#>   begin      effort unit 
#>   <date>      <dbl> <chr>
#> 1 2019-01-01   335. hour 
#> 2 2020-01-01   457. hour 
#> 3 2021-01-01   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