R/plotData.R

In SPOT: Sequential Parameter Optimization Toolbox

###################################################################################################
#' Interpolated plot
#'
#' A (filled) contour or perspective plot of a data set with
#' two independent and one dependent variable. The plot is generated by some 
#' interpolation or regression model. By default, the \code{loess} function is used.
#'
#' @param x independent variables, or input variables. this should be a matrix of at least two columns 
#' and several rows. If more than two columns are present, all will be used for fitting the model.
#' The parameter \code{which} will determine which of these will be plotted, and the parameter
#' \code{constant} will determine the values of all parameters that are not varied.
#' @param y dependent, or observed output variable to be interpolated/regressed and plotted.
#' @param which a vector with two elements, each an integer giving the two independent variables of the plot 
#' (the integers are indices of the respective data set, i.e., columns of x). All other parameters will be fixed to the best known 
#' solution, i.e., the one with minimal y-value.
#' @param constant a numeric vector that states for each variable a constant value that it will take on
#' if it is not varied in the plot. This affects the parameters not selected by the \code{which} parameter.
#' By default, this will be fixed to the best known solution, i.e., the one with minimal y-value, according
#' to \code{which.min(object$y)}. The length of this numeric vector should be the same as the number of columns in \code{object$x}
#' @param model the model building function to be used, by default \code{buildLOESS}.
#' @param modelControl control list of the chosen model building function.
#' @param xlab a vector of characters, giving the labels for each of the two independent variables
#' @param ylab character, the value of the dependent variable predicted by the corresponding model
#' @param type string describing the type of the plot:  \code{"filled.contour"} (default), \code{"contour"}, 
#' \code{"persp"} (perspective), or \code{"persp3d"} plot.
#' Note that "persp3d" is based on the plotly package and will work in RStudio, but not in the standard RGui.
#' @param ... additional parameters passed to the \code{contour} or \code{filled.contour} function
#'
#' @examples
#' ## generate random test data
#' testfun <- function (x) sum(x^2)
#' set.seed(1)
#' k <- 30
#' x <- cbind(runif(k)*15-5,runif(k)*15)
#' y <- as.matrix(apply(x,1,testfun))
#' plotData(x,y)
#' plotData(x,y,type="contour")
#' plotData(x,y,type="persp")
#'
#' @seealso \code{\link{plotFunction}}, \code{\link{plotModel}}
#'
#' @export
###################################################################################################
plotData <- function(x,y, 
										which=1:2, constant=x[which.min(y),],
										model = buildLOESS, modelControl = list(),
                    xlab= c("x1","x2"),ylab="y",
                    type="filled.contour",...){
  df <- data.frame(x[,1], x[,2], y)
  names(df) <- c("x", "y", "z")
  fit <- model(x,y,control=modelControl)
  plotModel(object=fit,
            which=which,
            constant=constant,
            xlab= xlab,
            ylab=ylab,
            type=type,
            ...)
}