dendextend: identify.dendrogram – R documentation

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identify.dendrogram

Identify Clusters in a Dendrogram (not hclust)

Description

Just like identify.hclust: reads the position of the graphics pointer when the (first) mouse button is pressed. It then cuts the tree at the vertical position of the pointer and highlights the cluster containing the horizontal position of the pointer. Optionally a function is applied to the index of data points contained in the cluster.

Usage

## S3 method for class 'dendrogram'
identify(
  x,
  FUN = NULL,
  N = 20,
  MAXCLUSTER,
  DEV.FUN = NULL,
  horiz = FALSE,
  stop_if_out = FALSE,
  ...
)

Arguments

`x`	a dendrogram object.
`FUN`	(optional) function to be applied to the index numbers of the data points in a cluster (see 'Details' below).
`N`	the maximum number of clusters to be identified.
`MAXCLUSTER`	the maximum number of clusters that can be produced by a cut (limits the effective vertical range of the pointer).
`DEV.FUN`	(optional) integer scalar. If specified, the corresponding graphics device is made active before FUN is applied.
`horiz`	logical (FALSE), indicating if the rectangles should be drawn horizontally or not (for when using plot(dend, horiz = TRUE) ) .
`stop_if_out`	logical (default is FALSE). This default makes the function NOT stop if k of the locator is outside the range (this default is different than the behavior of the identify.hclust function - but it is nicer for the user.).
`...`	further arguments to FUN.

Details

By default clusters can be identified using the mouse and an invisible list of indices of the respective data points is returned. If FUN is not NULL, then the index vector of data points is passed to this function as first argument, see the examples below. The active graphics device for FUN can be specified using DEV.FUN. The identification process is terminated by pressing any mouse button other than the first, see also identify.

Value

(Invisibly) returns a list where each element contains a vector of data points contained in the respective cluster.

Source

This function is based on identify.hclust, with slight modifications to have it work with a dendrogram, as well as adding "horiz"

Examples

## Not run: 
set.seed(23235)
ss <- sample(1:150, 10)
hc <- iris[ss, -5] %>%
  dist() %>%
  hclust()
dend <- hc %>% as.dendrogram()

plot(dend)
identify(dend)

plot(dend, horiz = TRUE)
identify(dend, horiz = TRUE)

## End(Not run)

dendextend

Extending 'dendrogram' Functionality in R

v1.15.1

GPL-2 | GPL-3

Authors

Tal Galili [aut, cre, cph] (https://www.r-statistics.com), Yoav Benjamini [ths], Gavin Simpson [ctb], Gregory Jefferis [aut, ctb] (imported code from his dendroextras package), Marco Gallotta [ctb] (a.k.a: marcog), Johan Renaudie [ctb] (https://github.com/plannapus), The R Core Team [ctb] (Thanks for the Infastructure, and code in the examples), Kurt Hornik [ctb], Uwe Ligges [ctb], Andrej-Nikolai Spiess [ctb], Steve Horvath [ctb], Peter Langfelder [ctb], skullkey [ctb], Mark Van Der Loo [ctb] (https://github.com/markvanderloo d3dendrogram), Andrie de Vries [ctb] (ggdendro author), Zuguang Gu [ctb] (circlize author), Cath [ctb] (https://github.com/CathG), John Ma [ctb] (https://github.com/JohnMCMa), Krzysiek G [ctb] (https://github.com/storaged), Manuela Hummel [ctb] (https://github.com/hummelma), Chase Clark [ctb] (https://github.com/chasemc), Lucas Graybuck [ctb] (https://github.com/hypercompetent), jdetribol [ctb] (https://github.com/jdetribol), Ben Ho [ctb] (https://github.com/SplitInf), Samuel Perreault [ctb] (https://github.com/samperochkin), Christian Hennig [ctb] (http://www.homepages.ucl.ac.uk/~ucakche/), David Bradley [ctb] (https://github.com/DBradley27), Houyun Huang [ctb] (https://github.com/houyunhuang)

Initial release

2021-05-08