R/TKRparcoordMiss.R
In alexkowa/VIMGUI: Visualization and Imputation of Missing Values - Graphical User Interface
# ---------------------------------------
# Author: Andreas Alfons and Daniel Schopfhauser
# Vienna University of Technology
# ---------------------------------------
#' Parallel coordinate plot with information about missing/imputed values
#'
#' Parallel coordinate plot with adjustments for missing/imputed values.
#' Missing values in the plotted variables may be represented by a point above
#' the corresponding coordinate axis to prevent disconnected lines. In
#' addition, observations with missing/imputed values in selected variables may
#' be highlighted.
#'
#' In parallel coordinate plots, the variables are represented by parallel
#' axes. Each observation of the scaled data is shown as a line. Observations
#' with missing/imputed values in selected variables may thereby be
#' highlighted. However, plotting variables with missing values results in
#' disconnected lines, making it impossible to trace the respective
#' observations across the graph. As a remedy, missing values may be
#' represented by a point above the corresponding coordinate axis, which is
#' separated from the main plot by a small gap and a horizontal line, as
#' determined by \code{plotNA}. Connected lines can then be drawn for all
#' observations. Nevertheless, a caveat of this display is that it may draw
#' attention away from the main relationships between the variables.
#'
#' If \code{interactive} is \code{TRUE}, it is possible switch between this
#' display and the standard display without the separate level for missing
#' values by clicking in the top margin of the plot. In addition, the variables
#' to be used for highlighting can be selected interactively. Observations
#' with missing/imputed values in any or in all of the selected variables are
#' highlighted (as determined by \code{selection}). A variable can be added to
#' the selection by clicking on a coordinate axis. If a variable is already
#' selected, clicking on its coordinate axis removes it from the selection.
#' Clicking anywhere outside the plot region (except the top margin, if
#' missing/imputed values exist) quits the interactive session.
#'
#' \code{TKRparcoordMiss} behaves like \code{parcoordMiss}, but uses
#' \code{\link[tkrplot]{tkrplot}} to embed the plot in a \emph{Tcl/Tk} window.
#' This is useful if the number of variables is large, because scrollbars allow
#' to move from one part of the plot to another.
#'
#' @param x a matrix or \code{data.frame}.
#' @param delimiter a character-vector to distinguish between variables and
#' imputation-indices for imputed variables (therefore, \code{x} needs to have
#' \code{\link{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 \code{col}).
#' @param highlight a vector giving the variables to be used for highlighting.
#' If \code{NULL} (the default), all variables are used for highlighting.
#' @param selection the selection method for highlighting missing/imputed
#' values in multiple highlight variables. Possible values are \code{"any"}
#' (highlighting of missing/imputed values in \emph{any} of the highlight
#' variables) and \code{"all"} (highlighting of missing/imputed values in
#' \emph{all} of the highlight variables).
#' @param plotvars a vector giving the variables to be plotted. If \code{NULL}
#' (the default), all variables are plotted.
#' @param col if \code{plotNA} is \code{TRUE}, a vector of length six giving
#' the colors to be used for observations with different combinations of
#' observed and missing/imputed values in the plot variables and highlight
#' variables (vectors of length one or two are recycled). Otherwise, a vector
#' of length two giving the colors for non-highlighted and highlighted
#' observations (if a single color is supplied, it is used for both).
#' @param plotNA a logical indicating whether missing values in the plot
#' variables should be represented by a point above the corresponding
#' coordinate axis to prevent disconnected lines.
#' @param alpha a numeric value between 0 and 1 giving the level of
#' transparency of the colors, or \code{NULL}. This can be used to prevent
#' overplotting.
#' @param \dots for \code{parcoordMiss}, further graphical parameters to be
#' passed down (see \code{\link[graphics]{par}}). For \code{TKRparcoordMiss},
#' further arguments to be passed to \code{parcoordMiss}.
#' @param hscale horizontal scale factor for plot to be embedded in a
#' \emph{Tcl/Tk} window (see \sQuote{Details}). The default value depends on
#' the number of variables.
#' @param vscale vertical scale factor for the plot to be embedded in a
#' \emph{Tcl/Tk} window (see \sQuote{Details}).
#' @param TKRpar a list of graphical parameters to be set for the plot to be
#' embedded in a \emph{Tcl/Tk} window (see \sQuote{Details} and
#' \code{\link[graphics]{par}}).
#' @note Some of the argument names and positions have changed with versions
#' 1.3 and 1.4 due to extended functionality and for more consistency with
#' other plot functions in \code{VIM}. For back compatibility, the arguments
#' \code{colcomb} and \code{xaxlabels} can still be supplied to \code{\dots{}}
#' and are handled correctly. Nevertheless, they are deprecated and no longer
#' documented. Use \code{highlight} and \code{labels} instead.
#' @author Andreas Alfons, Matthias Templ, modifications by Bernd Prantner
#' @seealso \code{\link{pbox}}
#' @references Wegman, E. J. (1990) Hyperdimensional data analysis using
#' parallel coordinates. \emph{Journal of the American Statistical Association}
#' \bold{85 (411)}, 664--675.
#'
#' M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete data using
#' visualization tools. \emph{Journal of Advances in Data Analysis and
#' Classification}, Online first. DOI: 10.1007/s11634-011-0102-y.
#'
#' @references A. Kowarik, M. Templ (2016) Imputation with
#' R package VIM. \emph{Journal of
#' Statistical Software}, 74(7), 1-16
#' @keywords hplot
#' @examples
#'
#' data(chorizonDL, package = "VIM")
#' ## for missing values
#' parcoordMiss(chorizonDL[,c(15,101:110)],
#' plotvars=2:11, interactive = FALSE)
#' legend("top", col = c("skyblue", "red"), lwd = c(1,1),
#' legend = c("observed in Bi", "missing in Bi"))
#'
#' ## for imputed values
#' parcoordMiss(kNN(chorizonDL[,c(15,101:110)]), delimiter = "_imp" ,
#' plotvars=2:11, interactive = FALSE)
#' legend("top", col = c("skyblue", "orange"), lwd = c(1,1),
#' legend = c("observed in Bi", "imputed in Bi"))
#'
#' @export TKRparcoordMiss
#' @S3method TKRparcoordMiss data.frame
#' @S3method TKRparcoordMiss survey.design
#' @S3method TKRparcoordMiss default
TKRparcoordMiss <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
UseMethod("TKRparcoordMiss", x)
}
TKRparcoordMiss.data.frame <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
TKRparcoordMiss_work(x, delimiter, highlight, selection, plotvars, plotNA,
col, alpha, hscale, vscale, TKRpar, ...)
}
TKRparcoordMiss.survey.design <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
TKRparcoordMiss_work(x$variables, delimiter, highlight, selection, plotvars, plotNA,
col, alpha, hscale, vscale, TKRpar, ...)
}
TKRparcoordMiss.default <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
TKRparcoordMiss_work(as.data.frame(x), delimiter, highlight, selection, plotvars, plotNA,
col, alpha, hscale, vscale, TKRpar, ...)
}
TKRparcoordMiss_work <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
# initializations and error messages
if(!(inherits(x, c("data.frame","matrix")))) {
stop("'x' must be a data.frame or matrix")
}
imp_var <- NULL
## 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]
}
}
px <- ncol(x)
cn <- colnames(x)
if(is.null(cn)) colnames(x) <- defaultNames(px)
if(length(highlight) > ncol(x)) stop("'highlight' is too long")
if(length(plotvars) > ncol(x)) stop("'plotvars' is too long")
z <- if(is.null(plotvars)) x else x[, plotvars, drop=FALSE]
pz <- ncol(z)
if(pz < 2) stop("the data to be plotted must be at least 2-dimensional")
selection <- match.arg(selection)
plotNA <- isTRUE(plotNA)
# prepare data
if(is.data.frame(z)) z <- data.matrix(z)
else if(mode(x) != "numeric") mode(x) <- "numeric"
if(is.null(imp_var)) haveNA <- any(isNA(z, selection="any"))
else haveNA <- any(isImp(z, pos = NULL, delimiter = delimiter, imp_var = imp_var, selection = selection)[["missh"]])
# prepare tkrplot
if(is.null(highlight)) highlight <- cn
else if(!is.character(highlight)) highlight <- cn[highlight]
plotvars <- colnames(z)
if(!is.null(imp_var)) x <- cbind(x,imp_var)
dots <- list(x=x, delimiter = delimiter, selection=selection, plotvars=plotvars, ...)
dots$interactive <- FALSE
putVm(".highlight", highlight) # we don't need 'highlight' in 'dots'
putVm(".plotNA", plotNA) # we don't need 'plotNA' in 'dots'
dev <- TKRdevice()
if(length(hscale) == 0) {
pmax <- 25
hscale <- 1 + max(pz-pmax, 0)/pmax # horizontal scale factor
}
img <- tkrplot(dev$frame,
fun=function() {
if(length(TKRpar)) par(TKRpar)
dots$highlight <- getVm(".highlight")
if(!is.null(alpha)) {
bg <- par("bg")
if(Sys.info()["sysname"] == "Windows" && bg == "transparent") bg <- grDevices::windows.options()$canvas
else if (bg == "transparent") bg <- X11.options()$canvas
col <- alphablend(col, alpha, bg)
}
dots$col <- col
dots$plotNA <- getVm(".plotNA")
do.call(parcoordMiss, dots)
putVm(".plt", par("plt"))
putVm(".usr", par("usr"))
},
hscale=hscale, vscale=vscale)
# interactive features
OnLeftClick <- function(x, y) {
plt <- getVm(".plt")
usr <- getVm(".usr")
width <- as.numeric(tclvalue(tkwinfo("reqwidth", img)))
height <- as.numeric(tclvalue(tkwinfo("reqheight", img)))
xMin <- plt[1]*width
xMax <- plt[2]*width
yMin <- plt[3]*height
yMax <- plt[4]*height
rangeX <- diff(usr[1:2])
rangeY <- diff(usr[3:4])
x <- as.numeric(x)
y <- height-as.numeric(y)
pt <- list(x=usr[1]+(x-xMin)*rangeX/(xMax-xMin),
y=usr[3]+(y-yMin)*rangeY/(yMax-yMin))
if(max(1, usr[1]) <= pt$x && pt$x < min(px, usr[2]) &&
max(0, usr[3]) <= pt$y &&
if(haveNA) TRUE else pt$y <= min(1, usr[4])) {
if(pt$y <= min(1, usr[4])) {
# variable selected or deselected
i <- round(pt$x)
highlight <- getVm(".highlight")
highlight <-
if(plotvars[i] %in% highlight)
setdiff(highlight, plotvars[i])
else c(highlight, plotvars[i])
putVm(".highlight", highlight)
tkrreplot(img)
highlightInfo(highlight, selection) # print out current selection
} else {
# toggle separate NA level for missings in plot variables
plotNA <- !getVm(".plotNA")
putVm(".plotNA", plotNA)
tkrreplot(img)
}
}
}
tkbind(img, "<ButtonRelease-1>", OnLeftClick)
# finish TKRdevice
lab <- paste("Click on a coordinate axis to add to",
"or remove from the highlight selection.")
if(haveNA) {
if(is.null(imp_var)) label <- "missing"
else label <- "imputed missing"
lab <- paste(lab, "\n",
"Click in the top margin to toggle visualizing ",
label, " values in the plot variables.", sep="")
}
finish(dev, img, label=lab)
highlightInfo(highlight, selection) # print out current selection
invisible()
}
alexkowa/VIMGUI documentation built on May 10, 2019, 8:54 a.m.
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# ---------------------------------------
# Author: Andreas Alfons and Daniel Schopfhauser
# Vienna University of Technology
# ---------------------------------------
#' Parallel coordinate plot with information about missing/imputed values
#'
#' Parallel coordinate plot with adjustments for missing/imputed values.
#' Missing values in the plotted variables may be represented by a point above
#' the corresponding coordinate axis to prevent disconnected lines. In
#' addition, observations with missing/imputed values in selected variables may
#' be highlighted.
#'
#' In parallel coordinate plots, the variables are represented by parallel
#' axes. Each observation of the scaled data is shown as a line. Observations
#' with missing/imputed values in selected variables may thereby be
#' highlighted. However, plotting variables with missing values results in
#' disconnected lines, making it impossible to trace the respective
#' observations across the graph. As a remedy, missing values may be
#' represented by a point above the corresponding coordinate axis, which is
#' separated from the main plot by a small gap and a horizontal line, as
#' determined by \code{plotNA}. Connected lines can then be drawn for all
#' observations. Nevertheless, a caveat of this display is that it may draw
#' attention away from the main relationships between the variables.
#'
#' If \code{interactive} is \code{TRUE}, it is possible switch between this
#' display and the standard display without the separate level for missing
#' values by clicking in the top margin of the plot. In addition, the variables
#' to be used for highlighting can be selected interactively. Observations
#' with missing/imputed values in any or in all of the selected variables are
#' highlighted (as determined by \code{selection}). A variable can be added to
#' the selection by clicking on a coordinate axis. If a variable is already
#' selected, clicking on its coordinate axis removes it from the selection.
#' Clicking anywhere outside the plot region (except the top margin, if
#' missing/imputed values exist) quits the interactive session.
#'
#' \code{TKRparcoordMiss} behaves like \code{parcoordMiss}, but uses
#' \code{\link[tkrplot]{tkrplot}} to embed the plot in a \emph{Tcl/Tk} window.
#' This is useful if the number of variables is large, because scrollbars allow
#' to move from one part of the plot to another.
#'
#' @param x a matrix or \code{data.frame}.
#' @param delimiter a character-vector to distinguish between variables and
#' imputation-indices for imputed variables (therefore, \code{x} needs to have
#' \code{\link{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 \code{col}).
#' @param highlight a vector giving the variables to be used for highlighting.
#' If \code{NULL} (the default), all variables are used for highlighting.
#' @param selection the selection method for highlighting missing/imputed
#' values in multiple highlight variables. Possible values are \code{"any"}
#' (highlighting of missing/imputed values in \emph{any} of the highlight
#' variables) and \code{"all"} (highlighting of missing/imputed values in
#' \emph{all} of the highlight variables).
#' @param plotvars a vector giving the variables to be plotted. If \code{NULL}
#' (the default), all variables are plotted.
#' @param col if \code{plotNA} is \code{TRUE}, a vector of length six giving
#' the colors to be used for observations with different combinations of
#' observed and missing/imputed values in the plot variables and highlight
#' variables (vectors of length one or two are recycled). Otherwise, a vector
#' of length two giving the colors for non-highlighted and highlighted
#' observations (if a single color is supplied, it is used for both).
#' @param plotNA a logical indicating whether missing values in the plot
#' variables should be represented by a point above the corresponding
#' coordinate axis to prevent disconnected lines.
#' @param alpha a numeric value between 0 and 1 giving the level of
#' transparency of the colors, or \code{NULL}. This can be used to prevent
#' overplotting.
#' @param \dots for \code{parcoordMiss}, further graphical parameters to be
#' passed down (see \code{\link[graphics]{par}}). For \code{TKRparcoordMiss},
#' further arguments to be passed to \code{parcoordMiss}.
#' @param hscale horizontal scale factor for plot to be embedded in a
#' \emph{Tcl/Tk} window (see \sQuote{Details}). The default value depends on
#' the number of variables.
#' @param vscale vertical scale factor for the plot to be embedded in a
#' \emph{Tcl/Tk} window (see \sQuote{Details}).
#' @param TKRpar a list of graphical parameters to be set for the plot to be
#' embedded in a \emph{Tcl/Tk} window (see \sQuote{Details} and
#' \code{\link[graphics]{par}}).
#' @note Some of the argument names and positions have changed with versions
#' 1.3 and 1.4 due to extended functionality and for more consistency with
#' other plot functions in \code{VIM}. For back compatibility, the arguments
#' \code{colcomb} and \code{xaxlabels} can still be supplied to \code{\dots{}}
#' and are handled correctly. Nevertheless, they are deprecated and no longer
#' documented. Use \code{highlight} and \code{labels} instead.
#' @author Andreas Alfons, Matthias Templ, modifications by Bernd Prantner
#' @seealso \code{\link{pbox}}
#' @references Wegman, E. J. (1990) Hyperdimensional data analysis using
#' parallel coordinates. \emph{Journal of the American Statistical Association}
#' \bold{85 (411)}, 664--675.
#'
#' M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete data using
#' visualization tools. \emph{Journal of Advances in Data Analysis and
#' Classification}, Online first. DOI: 10.1007/s11634-011-0102-y.
#'
#' @references A. Kowarik, M. Templ (2016) Imputation with
#' R package VIM. \emph{Journal of
#' Statistical Software}, 74(7), 1-16
#' @keywords hplot
#' @examples
#'
#' data(chorizonDL, package = "VIM")
#' ## for missing values
#' parcoordMiss(chorizonDL[,c(15,101:110)],
#' plotvars=2:11, interactive = FALSE)
#' legend("top", col = c("skyblue", "red"), lwd = c(1,1),
#' legend = c("observed in Bi", "missing in Bi"))
#'
#' ## for imputed values
#' parcoordMiss(kNN(chorizonDL[,c(15,101:110)]), delimiter = "_imp" ,
#' plotvars=2:11, interactive = FALSE)
#' legend("top", col = c("skyblue", "orange"), lwd = c(1,1),
#' legend = c("observed in Bi", "imputed in Bi"))
#'
#' @export TKRparcoordMiss
#' @S3method TKRparcoordMiss data.frame
#' @S3method TKRparcoordMiss survey.design
#' @S3method TKRparcoordMiss default
TKRparcoordMiss <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
UseMethod("TKRparcoordMiss", x)
}
TKRparcoordMiss.data.frame <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
TKRparcoordMiss_work(x, delimiter, highlight, selection, plotvars, plotNA,
col, alpha, hscale, vscale, TKRpar, ...)
}
TKRparcoordMiss.survey.design <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
TKRparcoordMiss_work(x$variables, delimiter, highlight, selection, plotvars, plotNA,
col, alpha, hscale, vscale, TKRpar, ...)
}
TKRparcoordMiss.default <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
TKRparcoordMiss_work(as.data.frame(x), delimiter, highlight, selection, plotvars, plotNA,
col, alpha, hscale, vscale, TKRpar, ...)
}
TKRparcoordMiss_work <- function(x, delimiter = NULL, highlight = NULL,
selection = c("any","all"), plotvars = NULL, plotNA = TRUE,
col = c("skyblue","red","skyblue4","red4","orange","orange4"),
alpha = NULL, hscale = NULL, vscale = 1,
TKRpar = list(), ...) {
# initializations and error messages
if(!(inherits(x, c("data.frame","matrix")))) {
stop("'x' must be a data.frame or matrix")
}
imp_var <- NULL
## 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]
}
}
px <- ncol(x)
cn <- colnames(x)
if(is.null(cn)) colnames(x) <- defaultNames(px)
if(length(highlight) > ncol(x)) stop("'highlight' is too long")
if(length(plotvars) > ncol(x)) stop("'plotvars' is too long")
z <- if(is.null(plotvars)) x else x[, plotvars, drop=FALSE]
pz <- ncol(z)
if(pz < 2) stop("the data to be plotted must be at least 2-dimensional")
selection <- match.arg(selection)
plotNA <- isTRUE(plotNA)
# prepare data
if(is.data.frame(z)) z <- data.matrix(z)
else if(mode(x) != "numeric") mode(x) <- "numeric"
if(is.null(imp_var)) haveNA <- any(isNA(z, selection="any"))
else haveNA <- any(isImp(z, pos = NULL, delimiter = delimiter, imp_var = imp_var, selection = selection)[["missh"]])
# prepare tkrplot
if(is.null(highlight)) highlight <- cn
else if(!is.character(highlight)) highlight <- cn[highlight]
plotvars <- colnames(z)
if(!is.null(imp_var)) x <- cbind(x,imp_var)
dots <- list(x=x, delimiter = delimiter, selection=selection, plotvars=plotvars, ...)
dots$interactive <- FALSE
putVm(".highlight", highlight) # we don't need 'highlight' in 'dots'
putVm(".plotNA", plotNA) # we don't need 'plotNA' in 'dots'
dev <- TKRdevice()
if(length(hscale) == 0) {
pmax <- 25
hscale <- 1 + max(pz-pmax, 0)/pmax # horizontal scale factor
}
img <- tkrplot(dev$frame,
fun=function() {
if(length(TKRpar)) par(TKRpar)
dots$highlight <- getVm(".highlight")
if(!is.null(alpha)) {
bg <- par("bg")
if(Sys.info()["sysname"] == "Windows" && bg == "transparent") bg <- grDevices::windows.options()$canvas
else if (bg == "transparent") bg <- X11.options()$canvas
col <- alphablend(col, alpha, bg)
}
dots$col <- col
dots$plotNA <- getVm(".plotNA")
do.call(parcoordMiss, dots)
putVm(".plt", par("plt"))
putVm(".usr", par("usr"))
},
hscale=hscale, vscale=vscale)
# interactive features
OnLeftClick <- function(x, y) {
plt <- getVm(".plt")
usr <- getVm(".usr")
width <- as.numeric(tclvalue(tkwinfo("reqwidth", img)))
height <- as.numeric(tclvalue(tkwinfo("reqheight", img)))
xMin <- plt[1]*width
xMax <- plt[2]*width
yMin <- plt[3]*height
yMax <- plt[4]*height
rangeX <- diff(usr[1:2])
rangeY <- diff(usr[3:4])
x <- as.numeric(x)
y <- height-as.numeric(y)
pt <- list(x=usr[1]+(x-xMin)*rangeX/(xMax-xMin),
y=usr[3]+(y-yMin)*rangeY/(yMax-yMin))
if(max(1, usr[1]) <= pt$x && pt$x < min(px, usr[2]) &&
max(0, usr[3]) <= pt$y &&
if(haveNA) TRUE else pt$y <= min(1, usr[4])) {
if(pt$y <= min(1, usr[4])) {
# variable selected or deselected
i <- round(pt$x)
highlight <- getVm(".highlight")
highlight <-
if(plotvars[i] %in% highlight)
setdiff(highlight, plotvars[i])
else c(highlight, plotvars[i])
putVm(".highlight", highlight)
tkrreplot(img)
highlightInfo(highlight, selection) # print out current selection
} else {
# toggle separate NA level for missings in plot variables
plotNA <- !getVm(".plotNA")
putVm(".plotNA", plotNA)
tkrreplot(img)
}
}
}
tkbind(img, "<ButtonRelease-1>", OnLeftClick)
# finish TKRdevice
lab <- paste("Click on a coordinate axis to add to",
"or remove from the highlight selection.")
if(haveNA) {
if(is.null(imp_var)) label <- "missing"
else label <- "imputed missing"
lab <- paste(lab, "\n",
"Click in the top margin to toggle visualizing ",
label, " values in the plot variables.", sep="")
}
finish(dev, img, label=lab)
highlightInfo(highlight, selection) # print out current selection
invisible()
}
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