Re-represent each trajectory spatially using a constant number of points so that adjacent points on the trajectory become equidistant to each other. Please note that this function is deprecated and that mt_length_normalize should be used instead.
mt_spatialize(
data,
use = "trajectories",
dimensions = c("xpos", "ypos"),
save_as = "sp_trajectories",
n_points = 20
)
a mousetrap data object created using one of the mt_import
functions (see mt_example for details). Alternatively, a trajectory
array can be provided directly (in this case use
will be ignored).
a character string specifying which trajectory data should be used.
a character string specifying which trajectory variables should be used. Can be of length 2 or 3 for two-dimensional or three-dimensional data.
a character string specifying where the resulting trajectory data should be stored.
an integer or vector of integers specifying the number of points used to represent the spatially rescaled trajectories. If a single integer is provided, the number of points will be constant across trajectories. Alternatively, a vector of integers can provided that specify the number of points for each trajectory individually.
A mousetrap data object (see mt_example) with an additional
array containing the spatialized trajectories. If a trajectory array was
provided directly as data
, only the spatialized trajectories will be
returned.
mt_spatialize
is used to emphasize the trajectories' shape. Usually,
the vast majority of points of a raw or a time-normalized trajectory lie
close to the start and end point. mt_spatialize
re-distributes these
points so that the spatial distribution is uniform across the entire
trajectory. mt_spatialize
is mainly used to improve the results of
clustering (in particular mt_cluster) and visualization.
if (FALSE) {
KH2017 <- mt_spatialize(data=KH2017,
dimensions = c('xpos','ypos'),
n_points = 20)
}