R/bezier.R

In mousetrap: Process and Analyze Mouse-Tracking Data

#' Create Bezier-curves using the Bernstein approximation.
#' 
#' \code{bezier} creates 3-point Bezier-curves using the 
#'   Bernstein approximation to simulate continuous competition 
#'   in mouse- and hand-trajectories.   
#'   
#' @param x a numeric vector giving the x-coordinates of exactly three
#'   Bezier-points. Defaults to c(0,1,-1) matching the 'mt' format in
#'   \link{mt_align}.
#' @param y a numeric vector giving the x-coordinates of exactly three
#'   Bezier-points. Defaults to c(0,1.5,1.5) matching the 'mt' format in
#'   \link{mt_align}.
#' @param w a numeric value or vector specifying one or several Bezier curves, 
#'   with \code{w} governing the pull towards the middle point. Each entry in
#'   \code{w} creates one Bezier-curve.
#' @param resol a numeric value specifying the spatial resolution of the bezier
#'   curves. For example, \code{resol = 100} creates bezier curves comprised of
#'   100 points each.
#' 
#' @return A trajectory array containing the bezier curves.
#'   
#' @examples
#' # Generate range of Bezier-curves
#' bezier_curves <- bezier(w=seq(0,10,.1))
#' 
#' # Plot curves
#' mt_plot(bezier_curves)
#'    
#' @author
#' Dirk U. Wulff
#' 
#' @export    
bezier <- function(x = c(0,1,-1), y = c(0,1.5,1.5), w = 1, resol = 100){
  
  # Setup array
  b = array(
    dim=c(length(w), resol, 2),
    dimnames=list(
      paste0('bezier_',1:length(w)),
      NULL,
      c('xpos','ypos')
      )
    )
  
  for(i in 1:length(w)){
    t = seq(0,1,length = resol)           #Resolution
    B = cbind( (1-t)^2, 2*t*(1-t),t^2 )   #Bernstein
    bx = ( B[,1] * x[1] + w[i] * B[,2] * x[2] + B[,3] * x[3] ) / 
         ( B[,1]        + w[i] * B[,2]        + B[,3]) 
    by = ( B[,1] * y[1] + w[i] * B[,2] * y[2] + B[,3] * y[3] ) / 
         ( B[,1]        + w[i] * B[,2]        + B[,3]) 
    b_mat = cbind(bx,by)
    b[i,,] = b_mat 
    }
  
  return(b)
  }