Re-represent each trajectory spatially using a constant number of points so that adjacent points on the trajectory become equidistant to each other.
mt_length_normalize(
data,
use = "trajectories",
dimensions = c("xpos", "ypos"),
save_as = "ln_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 (by default called ln_trajectories) containing the length
normalized trajectories. If a trajectory array was provided directly as
data, only the length normalized trajectories will be returned.
mt_length_normalize 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_length_normalize
re-distributes these points so that the spatial distribution is uniform
across the entire trajectory. mt_length_normalize is mainly used to
improve the results of clustering (in particular mt_cluster) and
visualization.
KH2017 <- mt_length_normalize(data=KH2017,
dimensions = c('xpos','ypos'),
n_points = 20)