Learn R Programming

dendextend (version 1.3.0)

set: Set (/update) features to a dendrogram

Description

a master function for updating various attributes and features of dendrogram objects.

Usage

set(dend, ...)
"set"(dend, what = c("labels", "labels_colors", "labels_cex", "labels_to_character", "leaves_pch", "leaves_cex", "leaves_col", "nodes_pch", "nodes_cex", "nodes_col", "hang_leaves", "rank_branches", "branches_k_color", "branches_k_lty", "branches_col", "branches_lwd", "branches_lty", "by_labels_branches_col", "by_labels_branches_lwd", "by_labels_branches_lty", "clear_branches", "clear_leaves" ), value, ...) "set"(dend, ..., which)
"set"(...)

Arguments

dend
a tree (dendrogram, or dendlist)
...
passed to the specific function for more options.
what
a character indicating what is the property of the tree that should be set/updated. (see the usage and the example section for the different options)
value
an object with the value to set in the dendrogram tree. (the type of the value depends on the "what")
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 dends in the dendlist.

Value

An updated dendrogram (or dendlist), with some change to the parameters of it

Details

This is a wrapper function for many of the main tasks we might wish to perform on a dendrogram before plotting.

The options of by_labels_branches_col, by_labels_branches_lwd, by_labels_branches_lty have extra parameters: type, attr, TF_value. You can read more about them here: branches_attr_by_labels

The "what" parameter" can accept the following options:

See Also

labels<-.dendrogram, labels_colors<-, hang.dendrogram, color_branches, assign_values_to_leaves_nodePar, assign_values_to_branches_edgePar, remove_branches_edgePar, remove_leaves_nodePar, noded_with_condition, branches_attr_by_labels, dendrogram

Examples

Run this code

## Not run: 
# 
# set.seed(23235)
# ss <- sample(1:150, 10 )
# 
# # Getting the dend object
# dend <- iris[ss,-5] %>% dist %>% hclust %>% as.dendrogram
# dend %>% plot
# 
# dend %>% labels
# dend %>% set("labels", 1:10) %>% labels
# dend %>% set("labels", 1:10) %>% plot 
# dend %>% set("labels_color") %>% plot 
# dend %>% set("labels_col", c(1,2)) %>% plot # Works also with partial matching :)
# dend %>% set("labels_cex", c(1, 1.2)) %>% plot 
# dend %>% set("leaves_pch", NA) %>% plot 
# dend %>% set("leaves_pch", c(1:5)) %>% plot    
# dend %>% set("leaves_pch", c(19,19, NA)) %>% 
#    set("leaves_cex", c(1,2)) %>% plot 
# dend %>% set("leaves_pch", c(19,19, NA)) %>% 
#    set("leaves_cex", c(1,2)) %>%
#    set("leaves_col", c(1,1,2,2)) %>% 
#    plot 
# dend %>% set("hang") %>% plot 
# 
# dend %>% set("branches_k_col") %>% plot 
# dend %>% set("branches_k_col", c(1,2)) %>% plot 
# dend %>% set("branches_k_col", c(1,2,3), k=3) %>% plot
# dend %>% set("branches_k_col", k=3) %>% plot 
# 
# dend %>% set("branches_k_lty", k=3) %>% plot 
# dend %>% set("branches_k_col", k=3) %>% set("branches_k_lty", k=3) %>% plot 
# 
# dend %>% set("branches_col", c(1,2, 1, 2, NA)) %>% plot
# dend %>% set("branches_lwd", c(2,1,2)) %>% plot
# dend %>% set("branches_lty", c(1,2,1)) %>% plot
# 
# #    clears all of the things added to the leaves
# dend %>% 
#    set("labels_color", c(19,19, NA)) %>% 
#    set("leaves_pch", c(19,19, NA))  %>%  # plot  
#    set("clear_leaves") %>% # remove all of what was done until this point
#    plot
# # Different order
# dend %>% 
#    set("leaves_pch", c(19,19, NA)) %>% 
#    set("labels_color", c(19,19, NA)) %>% 
#    set("clear_leaves") %>% plot
# 
# 
# # doing this without chaining (%>%) will NOT be fun:
# dend %>% 
#    set("labels", 1:10) %>%
#    set("labels_color") %>%
#    set("branches_col", c(1,2, 1, 2, NA)) %>%
#    set("branches_lwd", c(2,1,2)) %>%
#    set("branches_lty", c(1,2,1)) %>%
#    set("hang") %>%
#    plot 
# 
# #----------------------------
# # Examples for: by_labels_branches_col, by_labels_branches_lwd, by_labels_branches_lty
# 
# old_labels <- labels(dend)
# dend %>% 
#    set("labels", seq_len(nleaves(dend))) %>% 
#    set("by_labels_branches_col", c(1:4, 7)) %>% 
#    set("by_labels_branches_lwd", c(1:4, 7)) %>% 
#    set("by_labels_branches_lty", c(1:4, 7)) %>% 
#    set("labels", old_labels) %>% 
#    plot
# 
# dend %>% 
#    set("labels", seq_len(nleaves(dend))) %>% 
#    set("by_labels_branches_col", c(1:4, 7), type = "any", TF_values = c(4,2)) %>% 
#    set("by_labels_branches_lwd", c(1:4, 7), type = "all", TF_values = c(4,1)) %>% 
#    set("by_labels_branches_lty", c(1:4, 7), TF_values = c(4,1)) %>% 
#    plot
# 
# 
# 
# 
# 
# #----------------------------
# # A few dendlist examples:
# dendlist(dend,dend) %>% set("hang") %>% plot
# dendlist(dend,dend) %>% set("branches_k_col", k=3) %>% plot
# dendlist(dend,dend) %>% set("labels_col", c(1,2)) %>% plot
# 
# dendlist(dend,dend) %>% 
#    set("hang") %>%
#    set("labels_col", c(1,2), which = 1) %>% 
#    set("branches_k_col", k=3, which = 2) %>%
#    set("labels_cex", 1.2) %>%
#    plot
# 
# 
# #----------------------------
# # example of modifying the dendrogram in a heatmap:
# 
# library(gplots)
# data(mtcars)
# x  <- as.matrix(mtcars)
# rc <- rainbow(nrow(x), start=0, end=.3)
# cc <- rainbow(ncol(x), start=0, end=.3)
# 
# ##
# ##' demonstrate the effect of row and column dendrogram options
# ##
# Rowv_dend <- x %>% dist %>% hclust %>% 
#    as.dendrogram %>% 
#    set("branches_k", k = 3) %>% 
#    set("branches_lwd", 2) %>%  ladderize # rotate_DendSer
# Colv_dend <- t(x) %>% dist %>% hclust %>% 
#    as.dendrogram %>% 
#    set("branches_k", k = 3) %>% 
#    set("branches_lwd", 2) %>%  ladderize # rotate_DendSer
# heatmap.2(x, Rowv = Rowv_dend, Colv = Colv_dend)  
# 
# 
# 
# 
# 
# ## End(Not run)

Run the code above in your browser using DataLab