R: Highlight distint edges in a tree (compared to another one)

highlight_distinct_edges {dendextend} | R Documentation

## Highlight distint edges in a tree (compared to another one)

### Description

Highlight distint edges in a tree (compared to another one) by changing the branches' color, line width, or line type.

This function enables this feature in dend_diff and tanglegram

### Usage

    highlight_distinct_edges(dend, ...)

    ## S3 method for class 'dendrogram'
    highlight_distinct_edges(dend, dend2, value = 2,
      edgePar = c("col", "lty", "lwd"), ...)

    ## S3 method for class 'dendlist'
    highlight_distinct_edges(dend, ..., which = c(1L, 2L))

### Arguments

`dend` | a dendrogram or dendlist to find unique edges in (to highlight)
`...` | Ignored.
`dend2` | a dendrogram to compare with
`value` | a new value scalar for the edgePar attribute.
`edgePar` | a character indicating the value inside edgePar to adjust. Can be either "col", "lty", or "lwd".
`which` | an integer vector indicating, in the case "dend" is a dendlist, on which of the trees should the modification be performed. If missing - the change will be performed on all of objects in the dendlist.

### Value

A dendrogram with modified edges - the distinct ones are changed (color, line width, or line type)

### See Also

distinct_edges, highlight_distinct_edges, dist.dendlist, tanglegram assign_values_to_branches_edgePar, distinct.edges,

### Examples

    x <- 1:5 %>% dist %>% hclust %>% as.dendrogram
    y <- set(x, "labels", 5:1)
    distinct_edges(x, y)
    distinct_edges(y, x)

    par(mfrow = c(1,2))
    plot(highlight_distinct_edges(x, y))
    plot(y)

    # tanglegram(highlight_distinct_edges(x, y),y)
    # dend_diff(x, y)

    ## Not run:

    # using  highlight_distinct_edges combined with dendlist and set
    # to clearly highlight "stable" branches.
    data(iris); ss <- c(1:5, 51:55, 101:105)
    iris1 <-iris[ss,-5] %>% dist %>% hclust(method = "single") %>% as.dendrogram
    iris2 <- iris[ss,-5] %>% dist %>% hclust(method = "complete") %>% as.dendrogram
    iris12 <- dendlist(iris1, iris2) %>% set("branches_k_color",k=3) %>%
       set("branches_lwd", 3) %>%  highlight_distinct_edges(value = 1, edgePar = "lwd")
    iris12 %>% untangle(method = "step2side")  %>%
    tanglegram(sub="Iris dataset", main_left = "'single' clustering",
    				main_right = "'complete' clustering")

    ## End(Not run)

[Package dendextend version 1.8.0 Index]