####**********************************************************************
####**********************************************************************
####
#### ----------------------------------------------------------------
#### Written by:
#### John Ehrlinger, Ph.D.
####
#### email: john.ehrlinger@gmail.com
#### URL: https://github.com/ehrlinger/ggRandomForests
#### ----------------------------------------------------------------
####
####**********************************************************************
####**********************************************************************
#' Construct a set of (x, y, z) matrices for surface plotting a
#' \code{gg_partial_coplot} object
#'
#' @param dta a gg_partial_coplot object containing at least 3 numeric columns
#' of data
#' @param xvar a vector of 3 column names from the data object, in (x, y, z)
#' order
#'
#' @details To create a surface plot, the \code{plot3D::surf3D} function expects
#' 3 matrices of n.x by n.y. Take the p+1 by n \code{gg_partial_coplot} object,
#' and extract and construct the x, y and z matrices from the provided
#' \code{xvar} column names.
#'
#' @examples
#' \dontrun{
#' ## From vignette(randomForestRegression, package="ggRandomForests")
#' data(Boston, package="MASS")
#' rfsrc_boston <- randomForestSRC::rfsrc(medv~., Boston)
#'
#' varsel_boston <- var.select(rfsrc_boston)
#'
#' rm_pts <- quantile_pts(rfsrc_boston$xvar$rm,
#' groups = 9,
#' intervals = TRUE)
#'
#' partial_boston_surf <- lapply(rm_pts, function(ct) {
#' rfsrc_boston$xvar$rm <- ct
#' randomForestSRC::plot.variable(
#' rfsrc_boston,
#' xvar.names = "lstat",
#' time = 1,
#' npts = 10,
#' show.plots = FALSE,
#' partial = TRUE
#' )
#' })
#'
#' # Instead of groups, we want the raw rm point values,
#' # To make the dimensions match, we need to repeat the values
#' # for each of the 50 points in the lstat direction
#' rm.tmp <- do.call(c,lapply(rm_pts,
#' function(grp) {rep(grp,
#' length(partial_boston_surf))}))
#'
#' # Convert the list of plot.variable output to
#' partial_surf <- do.call(rbind,lapply(partial_boston_surf, gg_partial))
#'
#' # attach the data to the gg_partial_coplot
#' partial_surf$rm <- rm.tmp
#'
#' # Transform the gg_partial_coplot object into a list of three named matrices
#' # for surface plotting with plot3D::surf3D
#' srf <- surface_matrix(partial_surf, c("lstat", "rm", "yhat"))
#' }
#'
#' \dontrun{
#' # surf3D is in the plot3D package.
#' library(plot3D)
#' # Generate the figure.
#' surf3D(x=srf$x, y=srf$y, z=srf$z, col=topo.colors(10),
#' colkey=FALSE, border = "black", bty="b2",
#' shade = 0.5, expand = 0.5,
#' lighting = TRUE, lphi = -50,
#' xlab="Lower Status", ylab="Average Rooms", zlab="Median Value"
#' )
#' }
#'
#' @aliases surface_matrix surface_matrix.gg_partial_coplot
#' @export
surface_matrix <- function(dta, xvar) {
# Test for class type
if (!inherits(dta, "gg_partial_coplot")) {
warning("data object is not a gg_partial_coplot object.")
print(class(dta))
}
# Get the columns of interest.
if (missing(xvar)) {
xvar <- colnames(dta)[which(colnames(dta) != "group")]
}
# Verify there are three
if (length(xvar) != 3) {
stop("We expect the xvar argument to contain three column names
for (x, y, z) specification.")
}
# Verify the columns are in the dta object
if (sum(xvar %in% colnames(dta)) != length(xvar)) {
stop("xvar argument does not reference columns in this data set.")
}
if (is.null(dta$group))
dta$group <- factor(dta[, xvar[1]])
x_tmp <- lapply(unique(dta$group),
function(grp) {
dta[which(dta$group == grp), xvar[1]]
})
y_tmp <- lapply(unique(dta$group),
function(grp) {
dta[which(dta$group == grp), xvar[2]]
})
z_tmp <- lapply(unique(dta$group),
function(grp) {
dta[which(dta$group == grp), xvar[3]]
})
x_tmp <- do.call(rbind, x_tmp)
y_tmp <- do.call(rbind, y_tmp)
z_tmp <- do.call(rbind, z_tmp)
invisible(list(x = x_tmp, y = y_tmp, z = z_tmp))
}
surface_matrix.gg_partial_coplot <- surface_matrix
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