关于 r:Change Dendrogram 叶子


Change Dendrogram leaves

我想修改从 hclust 对象的绘图生成的树状图中叶子的属性。最低限度，我想更改颜色，但您可以提供的任何帮助将不胜感激。

我确实尝试用谷歌搜索答案，但我看到的每一个解决方案似乎都比我想象的要困难得多。

不久前，Joris Meys 好心地向我提供了这段改变树叶颜色的代码片段。修改它以反映您的属性。

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clusDendro <- as.dendrogram(Clustering)
labelColors <- c("red","blue","darkgreen","darkgrey","purple")

## function to get colorlabels
colLab <- function(n) {
   if(is.leaf(n)) {
       a <- attributes(n)
       # clusMember - a vector designating leaf grouping
       # labelColors - a vector of colors for the above grouping
       labCol <- labelColors[clusMember[which(names(clusMember) == a$label)]]
       attr(n,"nodePar") <- c(a$nodePar, lab.col = labCol)
   }
   n
}

## Graph
clusDendro <- dendrapply(clusDendro, colLab)
op <- par(mar = par("mar") + c(0,0,0,2))
plot(clusDendro,
     main ="Major title",
     horiz = T, type ="triangle", center = T)

par(op)
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这里有一个解决这个问题的方法，它使用了一个名为 "dendextend" 的新包，专为这类事情而构建。

您可以在以下 URL 的"使用"部分的演示文稿和小插图中看到许多示例：https://github.com/talgalili/dendextend

这是这个问题的解决方案：

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# define dendrogram object to play with:
dend <- as.dendrogram(hclust(dist(USArrests[1:3,]),"ave"))
# loading the package
install.packages('dendextend') # it is now on CRAN
library(dendextend)# let's add some color:
labels_colors(dend) <- 2:4
labels_colors(dend)
plot(dend)

enter

不清楚你想用它做什么，但我经常需要在树状图中识别一个分支。我已经破解了 rect.hclust 方法来添加密度和标签输入。

你可以这样称呼它：

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k <- 3 # number of branches to identify
labels.to.identify <- c('1','2','3')
required.density <- 10 # the density of shading lines, in lines per inch
rect.hclust.nice(tree, k, labels=labels.to.identify, density=density.required)

这里是函数

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rect.hclust.nice = function (tree, k = NULL, which = NULL, x = NULL, h = NULL, border = 2,
    cluster = NULL,  density = NULL,labels = NULL, ...)
{
    if (length(h) > 1 | length(k) > 1)
        stop("'k' and 'h' must be a scalar")
    if (!is.null(h)) {
        if (!is.null(k))
            stop("specify exactly one of 'k' and 'h'")
        k <- min(which(rev(tree$height) < h))
        k <- max(k, 2)
    }
    else if (is.null(k))
        stop("specify exactly one of 'k' and 'h'")
    if (k < 2 | k > length(tree$height))
        stop(gettextf("k must be between 2 and %d", length(tree$height)),
            domain = NA)
    if (is.null(cluster))
        cluster <- cutree(tree, k = k)
    clustab <- table(cluster)[unique(cluster[tree$order])]
    m <- c(0, cumsum(clustab))
    if (!is.null(x)) {
        if (!is.null(which))
            stop("specify exactly one of 'which' and 'x'")
        which <- x
        for (n in 1L:length(x)) which[n] <- max(which(m < x[n]))
    }
    else if (is.null(which))
        which <- 1L:k
    if (any(which > k))
        stop(gettextf("all elements of 'which' must be between 1 and %d",
            k), domain = NA)
    border <- rep(border, length.out = length(which))
    labels <- rep(labels, length.out = length(which))
    retval <- list()
    for (n in 1L:length(which)) {
        rect(m[which[n]] + 0.66, par("usr")[3L], m[which[n] +
            1] + 0.33, mean(rev(tree$height)[(k - 1):k]), border = border[n], col = border[n], density = density, ...)
        text((m[which[n]] + m[which[n] + 1]+1)/2, grconvertY(grconvertY(par("usr")[3L],"user","ndc")+0.02,"ndc","user"),labels[n])
        retval[[n]] <- which(cluster == as.integer(names(clustab)[which[n]]))
    }
    invisible(retval)
}
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