Don't use rescaler in ggpcp (Fixes #279).

Also clean up examples code

NEWS

@@ -47,6 +47,8 @@ MINOR CHANGES
   specific to a given data structure. Default implementation throws
   an error. It is designed to have implementations provided by other
   packages.
+
+* `ggpcp` loses the `scale` argument because it relied on reshape(1) code
 
 DEVELOPMENT
 

R/templates.r

@@ -9,37 +9,28 @@
 #' geom functions.  In particular this makes it very easy to create parallel
 #' boxplots, as shown in the example.
 #' 
-#' Three different scaling function are available:
-#'
-#' \itemize{
-#'   \item "range": scale coordinates to have common range $[0, 1]
-#'   \item "var": scale coordinates to have mean 0 and variance 1
-#'   \item "I": don't scale the coordinates at all 
-#' }
-#'
 #' @param data data frame
 #' @param vars variables to include in parallel coordinates plot
-#' @param scale scaling function, one of "range", "var" or "I"
 #' @param ... other arguments passed on plot creation
 #' @export
 #' @examples
 #' ggpcp(mtcars) + geom_line()
-#' ggpcp(mtcars, scale="var") + geom_line()
-#' ggpcp(mtcars, vars=names(mtcars)[3:6], formula= . ~cyl, scale="I") + geom_line()
-#' ggpcp(mtcars, scale="I") + geom_boxplot(aes(group=variable))
 #' ggpcp(mtcars, vars=names(mtcars[2:6])) + geom_line()
+#' ggpcp(mtcars) + geom_boxplot(aes(group=variable))
+#'
 #' p <- ggpcp(mtcars, vars=names(mtcars[2:6]))
 #' p + geom_line()
 #' p + geom_line(aes(colour=mpg)) 
-ggpcp <- function(data, vars=names(data), scale="range", ...) {
-  force(vars)  
-  scaled <- rescaler(data[, vars], type=scale)
+ggpcp <- function(data, vars=names(data), ...) {
+
+  scaled <- as.data.frame(lapply(data[, vars], rescale01))
   data <- cunion(scaled, data)
 
   data$ROWID <- 1:nrow(data)
   molten <- melt(data, m=vars)
 
-  ggplot(molten, aes_string(x = "variable", y = "value", group = "ROWID"), ...)
+  ggplot(molten, aes_string(x = "variable", y = "value", group = "ROWID"),
+    ...)
 }
 
 #' Create a fluctuation plot.

R/utilities.r

@@ -168,3 +168,9 @@ should_stop <- function(expr) {
 # Waive decision
 waiver <- function() structure(NULL, class="waiver")
 is.waive <- function(x) inherits(x, "waiver")
+
+
+rescale01 <- function(x) {
+  rng <- range(x, na.rm = TRUE)
+  (x - rng[1]) / (rng[2] - rng[1])
+}

man/ggpcp.Rd

@@ -2,17 +2,14 @@
 \alias{ggpcp}
 \title{Make a parallel coordinates plot.}
 \usage{
-  ggpcp(data, vars = names(data), scale = "range", ...)
+  ggpcp(data, vars = names(data), ...)
 }
 \arguments{
   \item{data}{data frame}
 
   \item{vars}{variables to include in parallel coordinates
   plot}
 
-  \item{scale}{scaling function, one of "range", "var" or
-  "I"}
-
   \item{...}{other arguments passed on plot creation}
 }
 \description{
@@ -27,20 +24,12 @@
   use any of the existing geom functions.  In particular
   this makes it very easy to create parallel boxplots, as
   shown in the example.
-
-  Three different scaling function are available:
-
-  \itemize{ \item "range": scale coordinates to have common
-  range $[0, 1] \item "var": scale coordinates to have mean
-  0 and variance 1 \item "I": don't scale the coordinates
-  at all }
 }
 \examples{
 ggpcp(mtcars) + geom_line()
-ggpcp(mtcars, scale="var") + geom_line()
-ggpcp(mtcars, vars=names(mtcars)[3:6], formula= . ~cyl, scale="I") + geom_line()
-ggpcp(mtcars, scale="I") + geom_boxplot(aes(group=variable))
 ggpcp(mtcars, vars=names(mtcars[2:6])) + geom_line()
+ggpcp(mtcars) + geom_boxplot(aes(group=variable))
+
 p <- ggpcp(mtcars, vars=names(mtcars[2:6]))
 p + geom_line()
 p + geom_line(aes(colour=mpg))