This function adds to tag
the parameters defining the 3D grid of the map. The spatial
parameters (extent
and scale
) define the geographical dimensions of the map, and the
temporal dimension is defined based on the stationary periods built using the labels.
include_stap_id
and include_min_duration
can be used to limit which stationary periods are
computed and modelled in the analysis. By default, all stationary periods are included.
In addition, tag
offers the possibility to define known
locations (e.g., equipment or
retrieval site). These can only be defined at the level of a stationary period (i.e., assuming
constant position during the whole stationary period) but you can define as many known stationary
periods as you wish. Because the index of the last stationary period is generally unknown, you
can use negative indexing in known
, i.e., known$stap_id = -1
will be converted to
nrow(tag$stap)
.
By default, no likelihood map will be computed for these stationary periods and the trajectory
model will be more constrained, saving significant computational time. You can change this
using the compute_known
parameter in geopressure_map()
.
Usage
tag_set_map(
tag,
extent,
scale = 10,
known = data.frame(stap_id = integer(), known_lat = double(), known_lon = double()),
include_stap_id = NULL,
include_min_duration = 0
)
Arguments
- tag
a GeoPressureR
tag
object.- extent
geographical extent of the map on which the likelihood and graph model will be computed. Vector of length 4
c(xmin, xmax, ymin, ymax)
orc(W, E, S, N)
.- scale
number of pixels per 1° latitude-longitude. For instance,
scale = 10
for a resolution of 0.1° (~10km) andscale=4
for a resolution of 0.25° (~30km). To avoid interpolating the ERA5 data, the scale should be equal to or smaller than 10. Read more about scale on the Google earth Engine documentation .- known
data.frame containing the known positions of the bird (e.g., equipment or retrieval site) with columns
stap_id
,known_lat
andknown_lon
. You can set position of the last stationary period usingstap_id = -1
. Also accept list which are converted as data.frame.- include_stap_id
vector of
stap_id
defining which stationary period to model, that is, to compute in the likelihood map and use in the graph.- include_min_duration
minimum duration threshold of stationary periods to include (in hours).
Value
A GeoPressureR tag
object with:
stap
: Data.frame of all stationary periods with three new columns:known_lat
andknown_lon
define the known position during these stationary periods, andinclude
defines whether the likelihood map of this stationary period should be computed and later used in the graph.extent
same as input parameterextent
scale
same as input parameterscale
See also
Other tag:
print.tag()
,
tag_create()
,
tag_update()
Examples
withr::with_dir(system.file("extdata", package = "GeoPressureR"), {
tag <- tag_create("18LX", quiet = TRUE) |> tag_label(quiet = TRUE)
})
# Default tag
tag_default <- tag_set_map(tag, c(-16, 23, 0, 50))
print(tag_default)
#>
#> ── GeoPressureR `tag` object for 18LX ──────────────────────────────────────────
#> Note: All green texts are fields of `tag` (i.e., `tag$field`).
#>
#> ── Parameter param
#> Run `tag$param` to display full table
#>
#> ── Sensors data
#> Manufacturer: soi
#> Date range: 2017-07-27 to 2017-08-09 23:30:00
#> • pressure: 672 datapoints
#> • acceleration: 4,032 datapoints
#> • light: 4,032 datapoints
#> • temperature_external: 2,448 datapoints
#>
#> ── Stationary periods stap
#> 5 stationary periods
#> stap_id start end known_lat known_lon include
#> 1 1 2017-07-26 23:57:30 2017-08-04 19:47:30 NA NA TRUE
#> 2 2 2017-08-04 23:17:30 2017-08-05 19:27:30 NA NA TRUE
#> 3 3 2017-08-06 02:52:30 2017-08-06 19:12:30 NA NA TRUE
#> ...
#> Run `tag$stap` to see full stap table
#>
#> ── Map
#> • Extent (W, E, S, N): -16°, 23°, 0°, 50°
#> • Dimensions (lat x lon): 500 x 390 (res. 0.1°)
#> ✖ No pressure likelihood computed yet. Use `geopressure_map()`.
# Customized tag, with coarse grid scale, known position for the first stationary
# period and considering only the stationary periods lasting more than 20hours.
tag_custom <- tag_set_map(tag,
extent = c(-16, 23, 0, 50),
scale = 1,
include_min_duration = 20,
known = data.frame(
stap_id = 1,
known_lon = 17.05,
known_lat = 48.9
)
)
print(tag_custom)
#>
#> ── GeoPressureR `tag` object for 18LX ──────────────────────────────────────────
#> Note: All green texts are fields of `tag` (i.e., `tag$field`).
#>
#> ── Parameter param
#> Run `tag$param` to display full table
#>
#> ── Sensors data
#> Manufacturer: soi
#> Date range: 2017-07-27 to 2017-08-09 23:30:00
#> • pressure: 672 datapoints
#> • acceleration: 4,032 datapoints
#> • light: 4,032 datapoints
#> • temperature_external: 2,448 datapoints
#>
#> ── Stationary periods stap
#> 5 stationary periods
#> stap_id start end known_lat known_lon include
#> 1 1 2017-07-26 23:57:30 2017-08-04 19:47:30 48.9 17.05 TRUE
#> 2 2 2017-08-04 23:17:30 2017-08-05 19:27:30 NA NA TRUE
#> 3 3 2017-08-06 02:52:30 2017-08-06 19:12:30 NA NA FALSE
#> ...
#> Run `tag$stap` to see full stap table
#>
#> ── Map
#> • Extent (W, E, S, N): -16°, 23°, 0°, 50°
#> • Dimensions (lat x lon): 50 x 39 (res. 1°)
#> ✖ No pressure likelihood computed yet. Use `geopressure_map()`.