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# ----------------------------------------------------------
# Authors: Matthias Templ, Bernd Prantner and Andreas Alfons
# Vienna University of Technology
# ----------------------------------------------------------
#' Bivariate jitter plot
#'
#' Create a bivariate jitter plot.
#'
#' The amount of observed and missing/imputed values is visualized by jittered
#' points. Thereby the plot region is divided into up to four regions
#' according to the existence of missing/imputed values in one or both
#' variables. In addition, the amount of observed and missing/imputed values
#' can be represented by a number.
#'
#' @param x a `data.frame` or `matrix` with two columns.
#' @param delimiter a character-vector to distinguish between variables and
#' imputation-indices for imputed variables (therefore, `x` needs to have
#' [colnames()]). If given, it is used to determine the corresponding
#' imputation-index for any imputed variable (a logical-vector indicating which
#' values of the variable have been imputed). If such imputation-indices are
#' found, they are used for highlighting and the colors are adjusted according
#' to the given colors for imputed variables (see `col`).
#' @param col a vector of length five giving the colors to be used in the plot.
#' The first color will be used for complete observations, the second/fourth
#' color for missing/imputed values in only one variable, and the third/fifth
#' color for missing/imputed values in both variables. If only one color is
#' supplied, it is used for all. Else if two colors are supplied, the second
#' one is recycled.
#' @param alpha a numeric value between 0 and 1 giving the level of
#' transparency of the colors, or `NULL`. This can be used to prevent
#' overplotting.
#' @param cex the character expansion factor for the plot characters.
#' @param col.line the color for the lines dividing the plot region.
#' @param lty the line type for the lines dividing the plot region (see
#' [graphics::par()]).
#' @param lwd the line width for the lines dividing the plot region.
#' @param numbers a logical indicating whether the frequencies of observed and
#' missing/imputed values should be displayed (see \sQuote{Details}).
#' @param cex.numbers the character expansion factor to be used for the
#' frequencies of the observed and missing/imputed values.
#' @param main,sub main and sub title.
#' @param xlab,ylab axis labels.
#' @param axes a logical indicating whether both axes should be drawn on the
#' plot. Use graphical parameter `"xaxt"` or `"yaxt"` to suppress
#' just one of the axes.
#' @param frame.plot a logical indicating whether a box should be drawn around
#' the plot.
#' @param labels a vector of length three giving the axis labels for the
#' regions for observed, missing and imputed values (see \sQuote{Details}).
#' @param \dots further graphical parameters to be passed down (see
#' [graphics::par()]).
#' @note Some of the argument names and positions have changed with version 1.3
#' due to extended functionality and for more consistency with other plot
#' functions in `VIM`. For back compatibility, the argument
#' `cex.text` can still be supplied to \code{\dots{}} and is handled
#' correctly. Nevertheless, it is deprecated and no longer documented. Use
#' `cex.numbers` instead.
#' @author Matthias Templ, modifications by Andreas Alfons and Bernd Prantner
#' @references M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete
#' data using visualization tools. *Journal of Advances in Data Analysis
#' and Classification*, Online first. DOI: 10.1007/s11634-011-0102-y.
#' @keywords hplot
#' @family plotting functions
#' @examples
#'
#' data(tao, package = "VIM")
#' ## for missing values
#' scattJitt(tao[, c("Air.Temp", "Humidity")])
#'
#' ## for imputed values
#' scattJitt(kNN(tao[, c("Air.Temp", "Humidity")]), delimiter = "_imp")
#'
#' @export scattJitt
scattJitt <- function(x, delimiter = NULL, col = c("skyblue","red","red4","orange","orange4"),
alpha = NULL, cex = par("cex"), col.line = "lightgrey",
lty = "dashed", lwd = par("lwd"),
numbers = TRUE, cex.numbers = par("cex"),
main = NULL, sub = NULL, xlab = NULL,
ylab = NULL, axes = TRUE, frame.plot = axes,
labels = c("observed","missing","imputed"), ...) {
# back compatibility
dots <- list(...)
nmdots <- names(dots)
if(missing(cex.numbers) && "cex.text" %in% nmdots) {
cex.numbers <- dots$cex.text
}
# error messages
if(!(inherits(x,c("data.frame","matrix")))) {
stop("'x' must be a data.frame or matrix")
}
imputed <- FALSE # indicates if there are Variables with missing-index
## delimiter ##
if(!is.null(delimiter)) {
tmp <- grep(delimiter, colnames(x)) # Position of the missing-index
if(length(tmp) > 0) {
imp_var <- x[, tmp, drop=FALSE]
x <- x[, -tmp, drop=FALSE]
if(ncol(x) == 0) stop("Only the missing-index is given")
if(is.matrix(imp_var) && range(imp_var) == c(0,1)) imp_var <- apply(imp_var,2,as.logical)
if(is.null(dim(imp_var))) {
if(!is.logical(imp_var)) stop("The missing-index of imputed Variables must be of the type logical")
} else {
if(!any(as.logical(lapply(imp_var,is.logical)))) stop("The missing-index of imputed Variables must be of the type logical")
}
imputed <- TRUE
} else {
warning("'delimiter' is given, but no missing-index-Variable is found", call. = FALSE)
}
}
if(ncol(x) != 2) stop("'x' must be 2-dimensional")
if(length(col) == 0) col <- c("skyblue","red","red4","orange","orange4")
else if(length(col) == 1) col <- rep.int(col, 5)
else if(length(col) == 2 || length(col) == 4) col <- c(col, rep(col[2],3))
else if(length(col) != 5) col <- c(col[1],rep(col[2:3],2))
if(length(labels) == 0) {
if(!imputed) labels <- c("observed","missing")
else labels <- c("observed","imputed")
}
else if(length(labels) == 1) stop("'labels' must be a vector of length 2 or 3")
else if(length(labels) > 2) {
if(!imputed) labels <- labels[1:2]
else labels <- labels[c(1,3)]
}
# semitransparent colors
if(!is.null(alpha)) col <- alphablend(col, alpha)
# get number of complete observations and missings
nobs <- nrow(na.omit(x))
if(!imputed) {
nmissx <- countNA(x[,1])
nmissy <- countNA(x[,2])
nmissall <- length(which(isNA(x, "all")))
} else {
nmiss <- countImp(x, delimiter, imp_var)
nmissx <- nmiss[1]
nmissy <- nmiss[2]
nmissall <- length(which(isImp(x, pos = NULL, delimiter = delimiter, imp_var = imp_var, selection = "all")[["missh"]]))
}
z <- cbind(
x=jitter(rep(c(-1,1,-1,1), c(nobs,nmissx,nmissy,nmissall)), amount=0.7),
y=jitter(rep(c(-1,-1,1,1), c(nobs,nmissx,nmissy,nmissall)), amount=0.7))
if(is.null(colnames(x))) {
if(is.null(xlab)) xlab <- ""
if(is.null(ylab)) ylab <- ""
} else colnames(z) <- colnames(x)
plot.xaxis <- if(is.null(dots$xaxt)) axes else dots$xaxt != "n" && axes
plot.yaxis <- if(is.null(dots$yaxt)) axes else dots$yaxt != "n" && axes
if(nmissx && nmissy) { # missings in both variables
if(!imputed) col <- col[1:3]
else col <- col[c(1,4,5)]
col <- rep(col,c(nobs, nmissx+nmissy, nmissall))
localPlot <- function(..., cex.text, type,
xlim, ylim, log, axes, frame.plot,
panel.first, panel.last, asp) {
plot(..., xlim=c(-1.7,1.7), ylim=c(-1.7,1.7), axes=FALSE)
}
localPlot(z, col=col, cex=cex, main=main,
sub=sub, xlab=xlab, ylab=ylab, ...)
abline(h=0, col=col.line, lty=lty, lwd=lwd)
abline(v=0, col=col.line, lty=lty, lwd=lwd)
if(numbers) { # display numbers
text(x=rep(-0.1,2), y=c(-0.15,0.15), labels=c(nobs,nmissy),
adj=c(1,0.5), cex=cex.numbers)
text(x=rep(0.1,2), y=c(-0.15,0.15), labels=c(nmissx,nmissall),
adj=c(0,0.5), cex=cex.numbers)
}
# arguments for axis
x.at <- c(-0.9,0.9)
x.labels <- labels
y.at <- c(-0.9,0.9)
y.labels=labels
} else if(nmissx && !nmissy) { # missings only in x-variable
if(!imputed) col <- col[1:2]
else col <- col[c(1,4)]
col <- rep(col,c(nobs, nmissx))
localPlot <- function(..., cex.text, type,
xlim, ylim, log, axes, frame.plot,
panel.first, panel.last, asp) {
plot(..., xlim=c(-1.7,1.7), ylim=c(-1.7,-0.3), axes=FALSE)
}
localPlot(z, col=col, cex=cex, main=main,
sub=sub, xlab=xlab, ylab=ylab, ...)
abline(v=0, col=col.line, lty=lty, lwd=lwd)
if(numbers) { # display numbers
text(x=-0.1, y=-1, labels=nobs, adj=c(1,0.5), cex=cex.numbers)
text(x=0.1, y=-1, labels=nmissx, adj=c(0,0.5), cex=cex.numbers)
}
# arguments for axis
x.at <- c(-0.9,0.9)
x.labels <- labels
y.at <- -1
y.labels=labels[1]
} else if(!nmissx && nmissy) { # missings only in y-variable
if(!imputed) col <- col[1:2]
else col <- col[c(1,4)]
col <- rep(col,c(nobs, nmissy))
localPlot <- function(..., cex.text, type,
xlim, ylim, log, axes, frame.plot,
panel.first, panel.last, asp) {
plot(..., xlim=c(-1.7,-0.3), ylim=c(-1.7,1.7), axes=FALSE)
}
localPlot(z, col=col, cex=cex, main=main,
sub=sub, xlab=xlab, ylab=ylab, ...)
abline(h=0, col=col.line, lty=lty, lwd=lwd)
if(numbers) { # display numbers
text(x=-1, y=-0.15, labels=nobs, adj=c(0.5,0.5), cex=cex.numbers)
text(x=-1, y=0.15, labels=nmissy, adj=c(0.5,0.5), cex=cex.numbers)
}
# arguments for axis
x.at <- -1
x.labels <- labels[1]
y.at <- c(-0.9,0.9)
y.labels=labels
} else { # no missings
col <- col[1]
localPlot <- function(..., cex.text, type,
xlim, ylim, log, axes, frame.plot,
panel.first, panel.last, asp) {
plot(..., xlim=c(-1.7,-0.3), ylim=c(-1.7,-0.3), axes=FALSE)
}
localPlot(z, col=col, cex=cex, main=main,
sub=sub, xlab=xlab, ylab=ylab, ...)
# arguments for axis
x.at <- -1
x.labels <- labels[1]
y.at <- -1
y.labels=labels[1]
}
localAxis <- function(..., cex.text, type, xlim,
ylim, log, ann, panel.first, panel.last,
asp, col, bg, pch, cex, lty, lwd) {
axis(..., lty=0)
}
if(plot.xaxis) localAxis(side=1, at=x.at, labels=x.labels, ...)
if(plot.yaxis) localAxis(side=2, at=y.at, labels=y.labels, ...)
if(frame.plot) {
localBox <- function(..., cex.text, type, xlim,
ylim, log, ann, panel.first, panel.last,
asp, col, bg, pch, cex, lty, lwd) {
box(...)
}
localBox()
}
invisible()
}
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