R: colouring ggplot's plotmatrix by k-means clusters
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I am trying to create a pairs plot of 6 data variables using ggplot2 and colour the points according to the k-means cluster they belong to. I read the documentation of the highly impressive 'GGally' package as well as an informal fix by Adam Laiacano [http://adamlaiacano.tumblr.com/post/13501402316/colored-plotmatrix-in-ggplot2]. Unfortunately, I could not find any way to get the desired output in either. 

Here is a sample code:-

    #The Swiss fertility dataset has been used here
    
    data_ <- read.csv("/home/tejaskale/Ubuntu\ One/IUCAA/Datasets/swiss.csv", header=TRUE)
    data_ <- na.omit(data_)

    u <- c(2, 3, 4, 5, 6, 7)
    x <- data_[,u]
    k <- 3
    maxIterations <- 100
    noOfStarts <- 100
    filename <- 'swiss.csv'

    library(ggplot2)
    library(gridExtra)
    library(GGally)

    kmeansOutput <- kmeans(x, k, maxIterations, noOfStarts)

    xNew <- cbind(x[,1:6], as.factor(kmeansOutput$cluster))
    names(xNew)[7] <- 'cluster'
    kmeansPlot <- ggpairs(xNew[,1:6], color=xNew$cluster)

    OR

    kmeansPlot <- plotmatrix(xNew[,1:6], mapping=aes(colour=xNew$cluster))

Both plots are created but aren't coloured according to clusters. 

Hope I haven't missed an answer to this question on the forum and apologize if that is indeed the case. Any help would be highly appreciated.

Thanks!