Transform data to a trace — to

This function does the opposite of unpack_trace. It takes in a data.frame and return a trace according to predpeds requirements. The data.frame should at least have the column names "x", "y", "time", and "id", containing the coordinates, times at which the data were gathered (in seconds), and the id-number of the person whose data it is. Additionally, data.frame needs information on the goals that agents were trying to achieve at each timepoint, of which their positions should be saved under "goal_x" and "goal_y", and their id to "goal_id".

Usage

to_trace(
  data,
  background,
  b_turning = NULL,
  a_turning = NULL,
  velocities = c(1.5, 1, 0.5),
  orientations = c(72.5, 50, 32.5, 20, 10, 0, -10, -20, -32.5, -50, -72.5),
  time_step = 0.5,
  threshold = qnorm(0.975, 2 * 0.035, 4 * 0.035^4)/time_step,
  stay_stopped = TRUE,
  cpp = TRUE,
  ...
)

Arguments

data: Instance of a data.frame containing the data you want to transform.
background: Instance of the background-class containing the setting in which the data were gathered.
b_turning, a_turning: Numeric denoting the values of the parameters \(b\) and \(a\) for the relationship between orientation and velocity. For more information, see the documentation of compute_centers. Defaults to NULL, meaning that this relationship takes on the default values of predped.
velocities: Numeric vector denoting the changes in speeds as assumed by the M4MA. Defaults to 1.5 (acceleration), 1, and 0.5 (deceleration).
orientations: Numeric vector denoting the changes in orientation as assumed by the M4MA. Defaults to 72.5, 50, 32.5, 20, 10, 0, 350, 340, 327.5, 310, 287.5 (note that the larger angles are actually the negative symmetric versions of the smaller angles).
time_step: Numeric denoting the time between each iteration. Defaults to 0.5 (the same as in simulate).
threshold: Numeric denoting under which observed value for speed the cell to which an agent has moved should be put to `0`. Defaults to a value based on the observed measurement error in our system.
stay_stopped: Logical denoting whether agents will predict others that are currently not moving to remain immobile in the next iteration. Is needed to compute the utility variables accurately. Defaults to TRUE.
cpp: Logical denoting whether to use the Rcpp (TRUE) or R (FALSE) version of this function. Defaults to TRUE.
...: Arguments passed to find_path.

Examples

# This is my example