R/plotLong.R

In karchjd/gppmr: Gaussian Process Panel Modeling

#' Plot a Long Data Frame
#'
#' This function is used to plot data from class 'LongData' as it is returned by \code{\link{datas}} \code{\link{simulate.GPPM}}.
#'
#' @param x longitudinal data frame of class 'LongData'.
#'
#' @param plotIds vector of IDs for which the data should be printed. Can be left empty. Then 5 IDs are picked randomly.
#'
#' @param by label of the variable on the x-axis. Can be left empty.
#'
#' @param ID label of the ID column. Can be left empty.
#'
#' @param DV label of the variable on the y-axis. Can be left empty.
#'
#' @param ... additional parameters (currently not used).
#'
#' @return a fitted Gaussian process panel model, which is an object of class 'GPPM'
#' @examples
#' data("demoLGCM")
#' plot(demoLGCM,plotIds=c(1,2,3))
#' plot(demoLGCM) #five random ids
#' @method plot LongData
#' @export
plot.LongData <- function(x,plotIds,by,ID,DV,...){
  if (!is.null(attr(x,'preds')) && missing(by)){
    by <- attr(x,'preds')
  }
  x <- as_LongData(x,ID,DV)
  idCol <- attr(x,'ID')
  dvCol <- attr(x,'DV')
  if(missing(plotIds)){
    Ids <- unique(x[,idCol])
    nIds <- length(Ids)
    plotIds <- sample(Ids,min(5,nIds))
  }
  plotData <- x[x[,idCol] %in% plotIds,]
  plotData[,idCol] <- as.factor(plotData[,idCol])
  toPlot <- ggplot2::ggplot(plotData,aes_string(x=by,y=dvCol,colour=idCol)) + geom_line() + ggthemes::theme_tufte()
  return(toPlot)
}