R/plot.vfpca.R

In fdasrvf: Elastic Functional Data Analysis

#' @export
plot.vfpca <- function(x, ...){
  dims <- dim(x$q_pca)
  num.plot <- ceiling(dims[3]/3)
  time <- x$time
  cnt <- 1
  for (ii in 1:num.plot){
    graphics::layout(matrix(c(1,2,3,4,5,6), 2, 3, byrow = TRUE))

    graphics::matplot(time,x$q_pca[1:(dims[1]-1),,cnt],type="l")
    graphics::title(main=sprintf("q domain: PD %d", cnt))
    if (dims[3] >= cnt + 1){
      graphics::matplot(time,x$q_pca[1:(dims[1]-1),,cnt+1],type="l")
      graphics::title(main=sprintf("q domain: PD %d", cnt+1))
    } else {
      graphics::plot.new()
    }
    if (dims[3] >= cnt + 2){
      graphics::matplot(time,x$q_pca[1:(dims[1]-1),,cnt+2],type="l")
      graphics::title(main=sprintf("q domain: PD %d", cnt+2))
    }else {
      graphics::plot.new()
    }

    graphics::matplot(time,x$f_pca[1:(dims[1]-1),,cnt],type="l")
    graphics::title(main=sprintf("f domain: PD %d", cnt))
    if (dims[3] >= cnt + 1){
      graphics::matplot(time,x$f_pca[1:(dims[1]-1),,cnt+1],type="l")
      graphics::title(main=sprintf("f domain: PD %d", cnt+1))
    }else {
      graphics::plot.new()
    }
    if (dims[3] >= cnt + 2){
      graphics::matplot(time,x$f_pca[1:(dims[1]-1),,cnt+2],type="l")
      graphics::title(main=sprintf("f domain: PD %d", cnt+2))
    }

    cnt <- cnt + 3
  }

  graphics::layout(1)
  cumm_coef = 100*cumsum(x$latent)/sum(x$latent)
  plot(cumm_coef,type="l",col="blue",main="Coefficient Cumulative Percentage", ylab = "Percentage")

}