View source: R/graph_most_likely.R
graph_most_likely | R Documentation |
Compute the trajectory which maximizes the joint probability using the Viterbi algorithm on the graph structure. For more details, see section 2.3.1 of Nussbaumer et al. (2023b) and the GeoPressureManual.
graph_most_likely(graph, quiet = FALSE)
graph |
a graph object. |
quiet |
logical to hide messages about the progress. |
Path data.frame containing the columns
-stap_id
stationary period
j
unique ID for each path, here always 1 as there is a single path.
ind
indices of the coordinate in the 2D grid. Useful to retrieve map or graph information
lat
latitude,
lon
longitude
start
datetime of the start of the stationary period (same as in stap
)
end
datetime of the end of the stationary period (same as in stap
)
include
logical if stationary period was modelled (same as in stap
)
Nussbaumer, Raphaël, Mathieu Gravey, Martins Briedis, Felix Liechti, and Daniel Sheldon. 2023. Reconstructing bird trajectories from pressure and wind data using a highly optimized hidden Markov model. Methods in Ecology and Evolution, 14, 1118–1129 https://doi.org/10.1111/2041-210X.14082.
Other graph:
graph_create()
,
graph_marginal()
,
graph_set_movement()
,
graph_simulation()
,
print.graph()
withr::with_dir(system.file("extdata", package = "GeoPressureR"), {
tag <- tag_create("18LX", quiet = TRUE) |>
tag_label(quiet = TRUE) |>
twilight_create() |>
twilight_label_read() |>
tag_set_map(
extent = c(-16, 23, 0, 50),
known = data.frame(stap_id = 1, known_lon = 17.05, known_lat = 48.9)
) |>
geopressure_map(quiet = TRUE) |>
geolight_map(quiet = TRUE)
})
# Create graph
graph <- graph_create(tag, quiet = TRUE)
# Define movement model
graph <- graph_set_movement(graph)
# Compute most likely path
path_most_likely <- graph_most_likely(graph, quiet = TRUE)
plot_path(path_most_likely)
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