Summary of localization data — atl_summary • tools4watlas

This function generates a summary of localization data by calculating the total number of positions, first and last data, days of data and time gaps between localizations, as well as data coverage. It returns a summary for each unique ID specified in id_columns.

Usage

atl_summary(data, id_columns = c("tag"))

Arguments

data: A data.table containing localization data with columns for ID, x, y coordinates, time, and datetime.
id_columns: A character vector specifying the column(s) to group by. Defaults to "tag".

Value

A data.table with summary statistics for each ID group, including the total number of positions, first and last data, days of data and time gaps between localizations, as well as data coverage.

Author

Johannes Krietsch

Examples

# packages
library(tools4watlas)

# path to csv with filtered data
data_path <- system.file(
  "extdata", "watlas_data_filtered.csv",
  package = "tools4watlas"
)

# load data
data <- fread(data_path, yaml = TRUE)

# summarize data
summary <- atl_summary(data, id_columns = c("tag"))
summary
#>       tag n_positions          first_data           last_data days_data min_gap
#>    <char>       <int>              <POSc>              <POSc>     <num>   <num>
#> 1:   3027       15833 2023-09-23 03:13:22 2023-09-23 22:24:26       0.8       3
#> 2:   3038       15935 2023-09-23 00:00:01 2023-09-23 23:59:57       1.0       3
#> 3:   3063       12294 2023-09-23 03:27:49 2023-09-23 22:24:55       0.8       3
#> 4:   3100        8411 2023-09-23 04:21:46 2023-09-23 21:41:16       0.7       3
#> 5:   3158       12401 2023-09-23 00:00:01 2023-09-23 23:59:57       1.0       3
#> 6:   3188       10050 2023-09-23 00:00:45 2023-09-23 23:41:50       1.0       3
#> 7:   3212        3846 2023-09-23 00:00:00 2023-09-23 23:59:56       1.0       8
#> 8:   3288        8130 2023-09-23 00:00:03 2023-09-23 23:59:54       1.0       6
#>    max_gap max_gap_f coverage
#>      <num>    <char>    <num>
#> 1:    2523    42 min     0.69
#> 2:    2850  47.5 min     0.55
#> 3:    2541  42.4 min     0.54
#> 4:   16145 4.5 hours     0.40
#> 5:    3252  54.2 min     0.43
#> 6:    9021 2.5 hours     0.35
#> 7:    7664 2.1 hours     0.36
#> 8:    2622  43.7 min     0.56