Hi,

Is it possible to use different types of plot.phylo (e.g., "cladogram", "fan", "unrooted", "radial") using dendextend?

Example:
plot(as.phylo(hclust(dist(mtcars))),type="fan")

Hi Tal,

Right now, tanglegram supports assigning any desired colors to the connectors of two dendrograms by simply making a sufficient-length vector. This allows for some super interesting graphics to highlight differences in the tree like this

I wonder if it's possible to do the same with the connector edge weights as well, to even further highlight interesting connections (lwd parameter)?

After poking around in the tanglegram.dendrogram function, it seems like for colors, you check to see if the argument supplied is a single color, in which case you repeat it as many times as needed, or you treat the list of colors as a vector and index through it as you draw your arrows.

https://github.com/talgalili/dendextend/blob/master/R/tanglegram.R#L897
https://github.com/talgalili/dendextend/blob/master/R/tanglegram.R#L906

I'm sure something similar could be done with lwd, right?

Perhaps if I have some time I can look through and try to implement this.

HI Tal, First of all greetings for 2016!

Now a quick question, which I think may imply a bug in the docs or in the cutree function. Something I often want to do is return the cluster ids for all individuals. I often need to return:

• the individuals in their original (data) order (like stats::cutree)
• but the cluster ids in dendrogram order

hc <- hclust(dist(USArrests), "ave")
cutree(hc, k=4)
plot(hc)

What I want can be achieved like this:

cutree(hc, k=4, order_clusters_as_data = F)[hc$labels]

But I can't seem to achieve it with any permutation of cutree arguments

# individuals in data order, cluster ids like stats::cutree
cutree(hc, k=4, order_clusters_as_data = T, sort_cluster_numbers = T)

# individuals in data order, cluster ids still identical to stats::cutree
cutree(hc, k=4, order_clusters_as_data = T, sort_cluster_numbers = F)

# individuals in dendrogram order, cluster ids in dendrogram order
cutree(hc, k=4, order_clusters_as_data = F, sort_cluster_numbers = T)

# individuals in dendrogram order, cluster ids like stats::cutree
cutree(hc, k=4, sort_cluster_numbers = F)

1. Does this seem like a sensible thing to want to do?
2. Can it be achieved directly?
3. Looking at the help for sort_cluster_numbers:

sort_cluster_numbers logical (TRUE). Should the resulting cluster id numbers be sorted? (default is TRUE in order to make the function compatible with cutree ) from stats, but it allows for sensible color order when using color_branches.

But I don't really understand that since

1. sort_cluster_numbers has no effect when order_clusters_as_data = T
2. one must set sort_cluster_numbers = F when order_clusters_as_data = F to give the same cluster ids as stats::cutree (the opposite of what I would expect from the help).

Thanks for any insight! Greg Jefferis.

Hi Tal,

I am looking at the vignette and think the last part of the following example code set("nodes_col", c("orange", "black", "plum", "NA")) should better be set("nodes_col", c("orange", "black", "plum", NA)),
or else you will have a color with value "NA" instead of NA.

Zuguang

dend <- iris[1:30,-5] %>% dist %>% hclust %>% as.dendrogram %>%
   set("branches_k_color", k=3) %>% set("branches_lwd", c(1.5,1,1.5)) %>%
   set("branches_lty", c(1,1,3,1,1,2)) %>%
   set("labels_colors") %>% set("labels_cex", c(.9,1.2)) %>% 
   set("nodes_pch", 19) %>% set("nodes_col", c("orange", "black", "plum", "NA"))


> attr(dend[[1]][[1]][[1]], "nodePar")
$lab.col
[1] "#CC476B"

$pch
[1] 19

$lab.cex
[1] 0.9

$col
[1] "NA"

Hello,

Thanks for that package, and for the very useful as.ggdend function!
I think there is a little bug in it, tough:

ggd1  <- 1:50 %>%
  dist() %>% 
  hclust %>%
  as.dendrogram %>% 
  as.ggdend

returns Error in FUN(X[[i]], ...) : subscript out of bounds.

It works fine when adding set("branches_lty", 1), as in the vignette.

ggd1  <- 1:50 %>%
  dist() %>% 
  hclust %>%
  as.dendrogram %>% 
  set("branches_lty", 1) %>% 
  as.ggdend

ggplot(ggd1)

As the other features of your vignette (branches_k_color, branches_lwd, labels_colors, labels_cex) seem to be optional, I wonder why this is not the case for branches_lty ?

I have attached the image of the dendrogram I have created. Is there a code in ddextend that can be used to mirror this image? So, I would have the questions on the left, and the tree extending to the left, as an inverse of what is seen here.

I've been looking through the ddextend manual for code to this effect, but have struggled to find any.

Thank you in advance for your help,
Elizabeth

I noticed some layout glitches when trying to plot the iris example with the 'hanged' option in ggplot. Here the reproducible example:

dend <- iris[1:30,-5] %>% dist %>% hclust %>% as.dendrogram %>% hang.dendrogram(hang = 0.1) %>%
  set("branches_k_color", k=3) %>% set("branches_lwd", c(1.5,1,1.5)) %>%
  set("branches_lty", c(1,1,3,1,1,2)) %>%
  set("labels_colors") %>% set("labels_cex", c(.9,1.2)) %>% 
  set("nodes_pch", 19) %>% set("nodes_col", c("orange", "black", "plum", NA))
# plot the dend in usual "base" plotting engine:
plot(dend, horiz=TRUE)

# Now let's do it in ggplot2 :)
ggd1 <- as.ggdend(dend)
library(ggplot2)
# the nodes are not implemented yet.
ggplot(ggd1) # reproducing the above plot in ggplot2 :)

and here's the output...it doesn't look very good :)

tnx for this wonderful package and have a nice day!
gabriele

Hello Tal and All,

I am looking to produce a tanglegram of two phylogenies of the same taxa with different datasets. I have already converted the phylogenies to dendrograms using DECIPHER.

I create an ordered character vector of colours based on tip label order on the left side phylogeny (I also reverse this as color_lines works from bottom to top). My problem is that the colours are not mapping accurately. I do think this is either due to the topology of one phylogeny/dendrogram or using the original phylogeny to generate the ordered vector (although I suspect not).

(note I have also tried ape cophyloplot and experience the same issue)

command : tanglegram(dendA, dendC, color_lines = x1)

Alternatively is there a method to colour associations lines similar to common_subtrees_color_lines, but involves specifying the subtrees/ clade in the left phylogeny (via the scale bar)??

Hope this makes sense.

Hi,

I have only recently started using the various dendextend features, and haven't yet come across something that I think would be useful for some users' applications:

When adjusting col, lwd or lty in branches_attr_by_labels; could you possibly add more flexibility as to how close to the root these features shall reach? I.e., allowing for the 'type' options in branches_attr_by_labels between 'all' and 'any' to also take an integer input that indicates the number of nodes away from the root until which the branch adjustment shall act?

This may enable highlighting of distances between leaves/clusters in a given dendrogram that don't connect through the root.

Best regards,
Max

The identify method doesn't appear to be working when horiz=T. This is my first bug report, sorry if this isn't the right venue! Below is an example taken from the dendextend tutorial. When clicking on the graphics device, identify(*,horiz=T) does not behave as expected, and it does not return a correct result.

require(dendextend)
require(colorspace)
data(iris)
d_iris <- dist(iris[,-5]) 
hc_iris <- hclust(d_iris)
dend_iris <- as.dendrogram(hc_iris)
iris_species <- rev(levels(iris[,5]))
dend_iris <- color_branches(dend_iris,k=3, groupLabels=iris_species)
labels_colors(dend_iris) <-rainbow_hcl(3)[sort_levels_values(as.numeric(iris[,5])[order.dendrogram(dend_iris)])]
labels(dend_iris) <- paste(as.character(iris[,5])[order.dendrogram(dend_iris)],"(",labels(dend_iris),")",sep = "")
dend_iris <- hang.dendrogram(dend_iris,hang_height=0.1)
dend_iris <- assign_values_to_leaves_nodePar(dend_iris, 0.5, "lab.cex")
par(mar = c(3,3,3,7))
plot(dend_iris,
main = "Clustered Iris dataset
(the labels give the true flower species)",
horiz = TRUE, nodePar = list(cex = .007))
legend("topleft", legend = iris_species, fill = rainbow_hcl(3))

identify(dend_iris,horiz=T)

Hi,

I am not sure if it is the intended behavior. When you call cor_cophenetic on objects of type hclust, it does not take into account the labels of the two objects. This causes a different result in the two cases below.

Thanks,
Erez

#example
h15 <- c(1:5) %>% dist %>% hclust(method = "average")

h15_1 <- h15
h15_2 <- h15

h15_1$labels <- c(2, 5,3, 4, 1)
h15_2$labels <- c(4, 3, 5, 1, 2)
cor_cophenetic(h15_1,h15_2)
#always 1
cor_cophenetic(as.phylo(h15_1), as.phylo(h15_2))
#0.3125
cor_cophenetic(as.dendrogram(h15_1), as.dendrogram(h15_2))
#0.3125
tanglegram(h15_1 ,h15_2 )

When using rect.dendrogram to highlight a branch, the upper boundary lies overtop of the horizontal arm of the branch. This looks a bit awkward. It would be nice to be able to push the boundary up a little bit, so you could clearly see the horizontal branches inside the coloured box.

You already provide lower_rect to allow us to tidy up the bottom of the box. Could you add upper_rect for the other end?

Thanks for a great package!

When trying to both add color to the subtrees as well as change branch width the tanglegram function gives an error. Find below both a function that reproduces the error as well as the error message. When using one or the other option separately the function works fine.

tanglegram(Phylo1,Phylo2, common_subtrees_color_branches=T, edge.lwd=4)

Error in value[is.na(values)] <- "black" : object 'value' not found
In addition: Warning message:
In branches_attr_by_clusters(dend2, dend2_clusters, values = dend1_leaves_colors[ss], :
There are NA's in the colors used by branches_attr_by_clusters. This probably means a bug somewhere. The color was replaced by 'black', but make sure your code does what you wanted it to...

After running dend_diff my par is set for mfrow=c(2,1) when I run other plots afterwards. Is there a way to restrict the scope of this that it either:

1. Reverts to the original options for par
   or
2. Defaults to par(mfrow=c(1,1)) once it has completed

I suspect this may make it difficult to use in a script. The documentation is ambiguous as to what "side by side" means. Perhaps it would be beneficial to clarify that these are separate plots, plotted horizontally.

Hi,

I recently came across the need to plot a dendrogram representing distance between certain strings and needed to plot the strings near each node.

I found the get_nodes_xy useful but it made me plot the characters one above the other and not as an intuitive string.

By any chance could you add an implemantation of get_nodes_xy to a horizontal dendrogram?

Thanks,
Barak

Hi,

I do not know if what is the probelm but after installing using the suggested script:
require2(devtools)
install_github('dendextend', 'talgalili')
require2(Rcpp)
install_github('dendextendRcpp', 'talgalili')

I can not run 3.7. Coloring branches example, the errors I get are:
Error: could not find function "color_branches"
Error: could not find function "rainbow_hcl"
Error: could not find function "hang.dendrogram"
Error: could not find function "assign_values_to_leaves_nodePar"
Error: unexpected symbol in "value recycled"
Error in legend("topleft", legend = iris_species, fill = rainbow_hcl(3)) :
could not find function "rainbow_hcl"

Any idea how to solve it?

Thanks.

So that cutree.hclust would be in R core, and I could use cutree.dendrogram.

Hi,

I tried to use the function as.ggdend(), but an error is generated when type = "triangle".

Please, find below a reproducible R code:

library(dendextend)
USArrests %>% scale %>% dist %>%
 hclust %>% as.dendrogram %>%
as.ggdend(type = "triangle")

I have got the following error:

Error in $<-.data.frame(*tmp*, "pch", value = c(NA, NA, NA, NA, NA, :
replacement has 99 rows, data has 50

Session info ----------------------------------------------------------------------------------------------------------------
 setting  value                       
 version  R version 3.2.4 (2016-03-10)
 system   x86_64, darwin13.4.0        
 ui       RStudio (0.99.491)          
 language (EN)                        
 collate  fr_FR.UTF-8                 
 tz       Europe/Paris                
 date     2016-11-08                  

Packages --------------------------------------------------------------------------------------------------------------------
 package      * version    date       source                         
 assertthat     0.1        2013-12-06 CRAN (R 3.2.0)                 
 class          7.3-14     2015-08-30 CRAN (R 3.2.4)                 
 cluster        2.0.3      2015-07-21 CRAN (R 3.2.4)                 
 colorspace     1.2-7      2016-10-11 CRAN (R 3.2.5)                 
 dendextend   * 1.3.0      2016-08-27 CRAN (R 3.2.5)                 
 DEoptimR       1.0-6      2016-07-06 CRAN (R 3.2.5)                 
 dichromat      2.0-0      2013-01-24 CRAN (R 3.2.0)                 
 digest         0.6.10     2016-08-02 CRAN (R 3.2.5)                 
 diptest        0.75-7     2015-06-08 CRAN (R 3.2.0)                 
 flexmix        2.3-13     2015-01-17 CRAN (R 3.2.0)                 
 fpc            2.1-10     2015-08-14 CRAN (R 3.2.0)                 
 ggplot2      * 2.1.0.9001 2016-10-18 Github (hadley/ggplot2@1709196)
 gtable         0.2.0      2016-02-26 CRAN (R 3.2.3)                 
 kernlab        0.9-25     2016-10-03 CRAN (R 3.2.5)                 
 labeling       0.3        2014-08-23 CRAN (R 3.2.0)                 
 lattice        0.20-33    2015-07-14 CRAN (R 3.2.4)                 
 lazyeval       0.2.0      2016-06-12 CRAN (R 3.2.5)                 
 magrittr       1.5        2014-11-22 CRAN (R 3.2.0)                 
 MASS           7.3-45     2015-11-10 CRAN (R 3.2.4)                 
 mclust         5.2        2016-03-31 CRAN (R 3.2.4)                 
 modeltools     0.2-21     2013-09-02 CRAN (R 3.2.0)                 
 munsell        0.4.3      2016-02-13 CRAN (R 3.2.3)                 
 mvtnorm        1.0-5      2016-02-02 CRAN (R 3.2.3)                 
 nnet           7.3-12     2016-02-02 CRAN (R 3.2.4)                 
 plyr           1.8.4      2016-06-08 CRAN (R 3.2.5)                 
 prabclus       2.2-6      2015-01-14 CRAN (R 3.2.0)                 
 RColorBrewer   1.1-2      2014-12-07 CRAN (R 3.2.0)                 
 Rcpp           0.12.7     2016-09-05 CRAN (R 3.2.5)                 
 reshape2       1.4.2      2016-10-22 CRAN (R 3.2.5)                 
 robustbase     0.92-6     2016-05-31 CRAN (R 3.2.5)                 
 scales         0.4.0.9003 2016-10-18 Github (hadley/scales@d58d83a) 
 stringi        1.1.2      2016-10-01 CRAN (R 3.2.5)                 
 stringr        1.1.0      2016-08-19 CRAN (R 3.2.5)                 
 tibble         1.2        2016-08-26 CRAN (R 3.2.5)                 
 trimcluster    0.1-2      2012-10-29 CRAN (R 3.2.0)                 
 whisker        0.3-2      2013-04-28 CRAN (R 3.2.0)        

Best regards,
A.

My Rstudio crushes whenever i call tanglegram as follows

tanglegram(F,G)
where F and G are my phylo trees of 50 tips each.
Note: I made the trees ultrametric using chronos before this command, otherwise it complained that they weren't ultrametric.

I decided to use the native R in Mac and while loading the dendextend library, I get the error below:

library(dendextend)

*** caught segfault ***
address 0x18, cause 'memory not mapped'

Traceback:
1: dyn.load(file, DLLpath = DLLpath, ...)
2: library.dynam(lib, package, package.lib)
3: loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
4: asNamespace(ns)
5: namespaceImportFrom(ns, loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]), i[[2L]], from = package)
6: loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]])
7: namespaceImport(ns, loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]), from = package)
8: loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]])
9: namespaceImport(ns, loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]), from = package)
10: loadNamespace(package, lib.loc)
11: doTryCatch(return(expr), name, parentenv, handler)
12: tryCatchOne(expr, names, parentenv, handlers[[1L]])
13: tryCatchList(expr, classes, parentenv, handlers)
14: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L msg <- conditionMessage(e) sm <- strsplit(msg, "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && identical(getOption("show.error.messages"), TRUE)) { cat(msg, file = stderr()) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})
15: try({ attr(package, "LibPath") <- which.lib.loc ns <- loadNamespace(package, lib.loc) env <- attachNamespace(ns, pos = pos, deps)})
16: library(dendextend)

Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspac

Any help?

Hello,
at first I have to thank you for this great package! I have one suggestion about 'by_labels_branches_col' can you add option to look up branches using regexp? Some of my branches have category name in their labels and this would really help me.
Thank you again, great work!

Is is possible to have no tip labels when plotting a tanglegram?

Hello,
I am trying to install this package in an R server (red hat) that doesn't have internet connection.
R version 3.2.1
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server release 6.6
I receive the following message:

Installing dendextend
'/usr/lib64/R/bin/R' --no-site-file --no-environ --no-save --no-restore
--quiet CMD INSTALL
'/tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master'
--library='/usr/lib64/R/library' --install-tests

• installing source package ‘dendextend’ ...
  ** R
  ** data
  *** moving datasets to lazyload DB
  ** demo
  ** inst
  ** tests
  ** preparing package for lazy loading
  Warning: replacing previous import by ‘magrittr::%>%’ when loading ‘dendextend’
  ** help
  *** installing help indices
  converting help for package ‘dendextend’
  finding HTML links ... done
  Bk html
  Bk_permutations html
  Bk_plot html
  DendSer.dendrogram html
  FM_index html
  FM_index_R html
  FM_index_permutation html
  FM_index_profdpm html
  all.equal.dendrogram html
  all_couple_rotations_at_k html
  all_unique html
  as.dendlist html
  as.phylo.dendrogram html
  as_hclust_fixed html
  assign_dendextend_options html
  assign_values_to_branches_edgePar html
  assign_values_to_leaves_edgePar html
  assign_values_to_leaves_nodePar html
  assign_values_to_nodes_nodePar html
  bakers_gamma_for_2_k_matrix html
  branches_attr_by_clusters html
  branches_attr_by_labels html
  circlize_dendrogram html
  click_rotate html
  collapse_branch html
  color_branches html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_branches.Rd:58: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_branches.Rd:26: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_branches.Rd:28: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_branches.Rd:13: missing file link ‘cutree.dendrogram’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_branches.Rd:193: missing file link ‘cutree’
  color_labels html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_labels.Rd:44: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_labels.Rd:18: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_labels.Rd:20: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/color_labels.Rd:74: missing file link ‘cutree’
  color_unique_labels html
  colored_bars html
  common_subtrees_clusters html
  cor.dendlist html
  cor_FM_index html
  cor_bakers_gamma html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/cor_bakers_gamma.Rd:21: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/cor_bakers_gamma.Rd:35: missing file link ‘cutree’
  cor_common_nodes html
  cor_cophenetic html
  count_terminal_nodes html
  cut_lower_fun html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/cut_lower_fun.Rd:31: missing file link ‘cutree.dendrogram’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/cut_lower_fun.Rd:63: missing file link ‘cutree.dendrogram’
  cutree-methods html
  cutree_1h.dendrogram html
  cutree_1k.dendrogram html
  d3dendro_options html
  d3dendrogram html
  dend_diff html
  dendextend-package html
  dendextend_labels.dendrogram html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/dendextend_labels.dendrogram.Rd:18: missing file link ‘labels.dendrogram’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/dendextend_labels.dendrogram.Rd:28: missing file link ‘labels.dendrogram’
  dendextend_options html
  dendlist html
  dist.dendlist html
  dist_long html
  distinct_edges html
  duplicate_leaf html
  entanglement html
  fac2num html
  find_k html
  fix_members_attr.dendrogram html
  flatten.dendrogram html
  flip_leaves html
  get_branches_heights html
  get_childrens_heights html
  get_leaves_attr html
  get_leaves_branches_attr html
  get_leaves_branches_col html
  get_leaves_edgePar html
  get_leaves_nodePar html
  get_nodes_attr html
  get_nodes_xy html
  get_root_branches_attr html
  ggdend html
  hang.dendrogram html
  heights_per_k.dendrogram html
  highlight_distinct_edges html
  identify.dendrogram html
  intersect_trees html
  is.dendlist html
  is.dendrogram html
  is.dist html
  is.hclust html
  is.natural.number html
  is.phylo html
  is_null_list html
  khan html
  labels-assign html
  labels_cex html
  labels_colors html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/labels_colors.Rd:67: missing file link ‘cutree’
  ladderize html
  leaf_Colors html
  lowest_common_branch html
  match_order_by_labels html
  match_order_dendrogram_by_old_order html
  na_locf html
  nleaves html
  nnodes html
  noded_with_condition html
  order.dendrogram-assign html
  order.hclust html
  partition_leaves html
  plot_horiz.dendrogram html
  prune html
  prune_common_subtrees.dendlist html
  prune_leaf html
  pvclust_show_signif html
  pvclust_show_signif_gradient html
  raise.dendrogram html
  rank_branches html
  rank_order.dendrogram html
  rank_values_with_clusters html
  rect.dendrogram html
  reexports html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/reexports.Rd:13: missing file link ‘%>%’
  remove_branches_edgePar html
  remove_leaves_nodePar html
  remove_nodes_nodePar html
  rllply html
  rotate html
  rotate_DendSer html
  sample.dendrogram html
  seriate_dendrogram html
  set html
  set_labels html
  shuffle html
  sort_2_clusters_vectors html
  sort_dist_mat html
  sort_levels_values html
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/sort_levels_values.Rd:39: missing file link ‘cutree’
  Rd warning: /tmp/Rtmpp7T5VK/devtools222533ea0528/dendextend-master/man/sort_levels_values.Rd:68: missing file link ‘cutree’
  tanglegram html
  theme_dendro html
  unbranch html
  unclass_dend html
  untangle html
  untangle_DendSer html
  untangle_random_search html
  untangle_step_rotate_1side html
  untangle_step_rotate_2side html
  which_leaf html
  which_node html
  ** building package indices
  ** installing vignettes
  ‘Cluster_Analysis.Rmd’
  ‘FAQ.Rmd’
  ‘Quick_Introduction.Rmd’
  ‘introduction.Rmd’
  ** testing if installed package can be loaded
  Warning: replacing previous import by ‘magrittr::%>%’ when loading ‘dendextend’
• DONE (dendextend)
  Making 'packages.html' ... done

I am worried about the messages:

• missing file link ‘cutree’
• Warning: replacing previous import by ‘magrittr::%>%’ when loading ‘dendextend’
• missing file link ‘labels.dendrogram’

I am having a problem using the library d3heatmap which needs this one and I dont know whether these errors are causing a bad installation of the d3heatmap or not.

If you have any advice please let me know
Thanks

This can be implemented using the sample.dendrogram function...

Good example:

library(cluster)
set.seed(999)
iris2 <- iris[sample(x = 1:150,size = 50,replace = F),]
clust <- diana(iris2)
dend <- as.dendrogram(clust)

temp_col <- c("red", "blue", "green")[as.numeric(iris2$Species)]
temp_col <- temp_col[order.dendrogram(dend)]
temp_col <- factor(temp_col, unique(temp_col))

library(dendextend)
dend %>% color_branches(clusters = as.numeric(temp_col), col = levels(temp_col)) %>% 
   set("labels_colors", as.character(temp_col)) %>% 
   plot

I would like to:

• add , order_value = TRUE argument (to order clusters)
• allow clusters to act differently for factors, integers, character.

Hello, Tal,

I'm trying to colour labels in the two dendrograms that contain terminal branches with zero height.
One of the dendrograms is coloured successfully, the other one fails with an error message from cutree_1k.dendrogram.

Does it happen because the first dendrogram contains the branches with zero height only with 2 leaves, while the other one has up to 4 leaves in such branches?

Could you suggest any solution?

With best regards,

Marina

Here is the link to the Rdata and the code

easy_mod <- color_labels(easy, col = easy_cols) # is coloured successfuly
par(mar = c(4, 2, 2, 10))
plot(easy_mod, horiz = T)

hard_mod <- color_labels(hard, col = hard_cols) # fails to be coloured

# Error in if (length(col) < k) { : missing value where TRUE/FALSE needed
# In addition: Warning messages:
#1: In cutree_1k.dendrogram(k = x, ...) :
#   Couldn't cut the tree - returning NA.
#2: In cutree_1k.dendrogram(k = x, ...) :
#   No cut exists for creating 92 clusters.  The possible range for clusters is: [0-76]

To be able to address also the inner nodes, it would help to get the numbers of all nodes (i.e. the numbers you show in the vignette where you visualize the depth-first search), if possible together with the members at each node. (Is there a way to get the members of nodes, other than with cutree?) By those numbers (and based on the members they represent) then the nodes could be chosen for coloring etc., something like nodes_attr_by_nodenumbers...
I hope it makes sense.

tanglegram(dend2, dend1)
Loading required namespace: colorspace
Failed with error: ‘there is no package called ‘colorspace’’

It seems that "colorspace" is not imported in the package namespace, but it is required to load for the function to complete.

I am trying to plot a simple two columned dataframe and receive the following error:

Error: all(vapply(s, is.integer, NA)) is not TRUE

The dataframe I'm working with has two columns each with class = integer so I'm not seeing where this would come from. I have attached a subset of the df that still creates the issue.

load("example_df.Rda")
heatmaply(example_df)

Any help would be greatly appreciated. Below is version and session info.

example_df.Rda.zip

R version:

platform       x86_64-redhat-linux-gnu
arch           x86_64
os             linux-gnu
system         x86_64, linux-gnu
status
major          3
minor          2.3
year           2015
month          12
day            10
svn rev        69752
language       R
version.string R version 3.2.3 (2015-12-10)
nickname       Wooden Christmas-Tree

SessionInfo

R version 3.2.3 (2015-12-10)
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] stringi_1.1.2   heatmaply_0.6.0 viridis_0.3.4   plotly_4.5.6
[5] ggplot2_2.2.1

loaded via a namespace (and not attached):
 [1] gtools_3.5.0       modeltools_0.2-21  purrr_0.2.2        kernlab_0.9-25
 [5] reshape2_1.4.1     lattice_0.20-34    colorspace_1.2-7   htmltools_0.3.5
 [9] stats4_3.2.3       viridisLite_0.1.3  yaml_2.1.13        base64enc_0.1-3
[13] DBI_0.5-1          prabclus_2.2-6     RColorBrewer_1.1-2 registry_0.3
[17] fpc_2.1-10         foreach_1.4.3      plyr_1.8.4         robustbase_0.92-6
[21] stringr_1.1.0      munsell_0.4.3      gtable_0.2.0       htmlwidgets_0.7
[25] caTools_1.17.1     mvtnorm_1.0-5      codetools_0.2-15   labeling_0.3
[29] seriation_1.2-1    flexmix_2.3-13     class_7.3-14       DEoptimR_1.0-6
[33] trimcluster_0.1-2  Rcpp_0.12.7        KernSmooth_2.23-15 scales_0.4.1
[37] diptest_0.75-7     gdata_2.17.0       jsonlite_1.1       gplots_3.0.1
[41] gridExtra_2.2.1    digest_0.6.10      gclus_1.3.1        dplyr_0.5.0
[45] grid_3.2.3         tools_3.2.3        bitops_1.0-6       magrittr_1.5
[49] lazyeval_0.2.0     tibble_1.2         cluster_2.0.5      whisker_0.3-2
[53] tidyr_0.6.0        dendextend_1.3.0   MASS_7.3-45        assertthat_0.1
[57] httr_1.2.1         iterators_1.0.8    R6_2.2.0           TSP_1.1-4
[61] mclust_5.2         nnet_7.3-12

library(dendextend)
hc <- hclust(dist(USArrests[1:5,]),"ave")

This gives out an error:

Error in as.hclust.dendrogram(x, ...) : 
  dendrogram entries must be 1,2,..,3 (in any order), to be coercible to "hclust"

While of course pruning leaves as dendrogram obviously work, coercing the resulting dendrogram to hclust don't work, either:

dendro <- as.dendrogram(hc)
dendro.pruned<-prune(dendro, c("Alaska","California"))
as.hclust(dendro.pruned)
Error in as.hclust.dendrogram(dendro.pruned) : 
  dendrogram entries must be 1,2,..,3 (in any order), to be coercible to "hclust"

Looking at the code for stats::as.hclust, it seems the issue is the leaves' ID were not updated after pruning, like this:

> str(unclass(dendro.pruned))
List of 2
 $ : atomic [1:1] 4
  ..- attr(*, "members")= int 1
  ..- attr(*, "height")= num 0
  ..- attr(*, "label")= chr "Arkansas"
  ..- attr(*, "leaf")= logi TRUE
 $ :List of 2
  ..$ : atomic [1:1] 3
  .. ..- attr(*, "label")= chr "Arizona"
  .. ..- attr(*, "members")= int 1
  .. ..- attr(*, "height")= num 0
  .. ..- attr(*, "leaf")= logi TRUE
  ..$ : atomic [1:1] 1
  .. ..- attr(*, "label")= chr "Alabama"
  .. ..- attr(*, "members")= int 1
  .. ..- attr(*, "height")= num 0
  .. ..- attr(*, "leaf")= logi TRUE
  ..- attr(*, "members")= num 2
  ..- attr(*, "midpoint")= num 0.5
  ..- attr(*, "height")= num 52.6
 - attr(*, "members")= num 3
 - attr(*, "midpoint")= num 0.75
 - attr(*, "height")= num 82.6

Which makes some items in unlist(dendro.pruned) to be greater than nleaves(dendro.pruned), which in turn fails the first few lines of as.hclust.dendrogram:

as.hclust.dendrogram <- function(x, ...)
{
    stopifnot(is.list(x), length(x) == 2)
    n <- length(ord <- as.integer(unlist(x)))
    iOrd <- sort.list(ord)
    if(!identical(ord[iOrd], seq_len(n)))
	stop(gettextf(
	    "dendrogram entries must be 1,2,..,%d (in any order), to be coercible to \"hclust\"",
	    n), domain=NA)

To fix this, I think, would need to fix the leave indices such that they are within [1, nleaves(dendro.pruned)].

> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] dendextend_1.4.0

loaded via a namespace (and not attached):
 [1] flexmix_2.3-13    Rcpp_0.12.9       cluster_2.0.5     whisker_0.3-2     magrittr_1.5      fpc_2.1-10       
 [7] MASS_7.3-45       munsell_0.4.3     mclust_5.2.2      colorspace_1.3-2  lattice_0.20-34   plyr_1.8.4       
[13] prabclus_2.2-6    tools_3.3.2       nnet_7.3-12       grid_3.3.2        gtable_0.2.0      modeltools_0.2-21
[19] class_7.3-14      lazyeval_0.2.0    assertthat_0.1    tibble_1.2        gridExtra_2.2.1   kernlab_0.9-25   
[25] trimcluster_0.1-2 ggplot2_2.2.1     viridis_0.3.4     robustbase_0.92-7 DEoptimR_1.0-8    scales_0.4.1     
[31] diptest_0.75-7    stats4_3.3.2      mvtnorm_1.0-5   

I ran into problems with cutree, when I had a tree with zero distance leafs.
Here is a minimal example that reproduces the problem:

dend<-as.dendrogram(hclust(dist(c(1,1,1,2,2))))
cutree(dend,k=5)
[1] 0 0 0 0 0

I expected the result to be:

cutree(hclust(dist(c(1,1,1,2,2))),k=5)
[1] 1 2 3 4 5

I figured out that it has to do with the function heights_per_k.dendrogram.
It results in negative values for h:

heights_per_k.dendrogram(dend)
1 2 0
1.5 0.5 -0.5

Negative height reproduced the results, that I got before:

cutree(dend,h=-0.5)
[1] 0 0 0 0 0

There is a call to library(ape) in collapse_branch.Rd examples.
As the ape is suggested dependency, it should not be required to run examples according to R-exts. This can be conditionally escaped with requireNamespace.
It is possible there are other cases of that issue in other examples, this one was to first that fails due to not having ape pkg.

Hello,

Thanks for the quick fix of issue #12!
I have another issue related to as.ggdend: is there any way to use the rect.dendrogram() function within the ggplot paradigm? As rect.dendogram returns a list of k elements and not a dendrogram, it cannot be passed as parameter of as.ggdend.

Regards

Hi,

I'm using the function chclust from the package rioja to do constrained HC. The order of individuals is forced to a quantitative variable. When plotting, the option xvar sets the "x-coordinates for the leaves of the dendrogram". Here is an example:

library(tidyverse)
library(rioja)

data <- mtcars %>% arrange(mpg) %>% distinct(mpg, .keep_all = TRUE)
x_coord <- data$mpg
data <- data %>% select(-mpg)

clustering <- data %>% sqrt() %>% dist() %>% chclust()
plot(clustering, hang = -1, xvar = x_coord)

Is it possible to achieve similar scaling with dendextend? Thanks for your help!

From Kurt:

Unfortunately, the above is incompatible with the CRAN Policy which has

• A package must not tamper with the code already loaded into R: any
  attempt to change code in the standard and recommended packages which
  ship with R is prohibited.

The best I can think of is for dendextendRcpp to provide its own labels
generic, with default method calling base::labels, and its own method
for dendrogram. (Not sure if this will work, though.)

I want to color the leaves of the dendrogram by a vector with the same length of the data, e.g. clustering labels from hierarchical clustering via cutree():

library(MASS)
library(dendextend)
library(dplyr)
library(ggplot2)
data(Cars93)
cars_cont <- select(Cars93, Price, MPG.city, MPG.highway, EngineSize, 
                    Horsepower, RPM, Fuel.tank.capacity, Passengers,
                    Length, Wheelbase, Width, Turn.circle, Weight)

hc <- cars_cont %>% scale %>% dist %>% hclust 
dend <- hc %>% as.dendrogram
dend %>% set("labels_colors", cutree(hc, k = 4)) %>% ggplot

But the behavior here is not as expected. That is, the colors of the leaves under a given branch of the dendrogram should all be the same color (corresponding to the four-cluster solution), but they appear to be displayed randomly.

Additionally, setting the leaf labels with a length-n vector does not appear to work properly either. For example, dend %>% ggplot shows that the first three default leaf labels, moving from left to right, are 31, 80, and 42 -- presumably corresponding to rows 31, 80, and 42 in the dataset.

The types of cars for these indices are:

> Cars93$Type[c(31, 80, 42)]
[1] Small Small Small

But when setting the labels with the Type vector, the appropriate labels do not appear in these positions in the dendrogram. For example, the labels in the corresponding positions after setting the labels according to the car Type are Small Midsize Compact using the following code:

dend %>% set("labels", Cars93$Type) %>% ggplot

Both of these issues appear to be because the set() function does not take into account the $order of the hclust object. When I use the following code, everything works:

dend %>% set("labels_colors", cutree(hc, k = 4)[hc$order]) %>% ggplot
dend %>% set("labels", Cars93$Type[hc$order]) %>% ggplot

Is it possible to make it so set() takes into account the $order of the hclust object, in order to prevent this counterintuitive labeling style?

Also, after reading through the documentation, it's not immediately obvious if the order.hclust() or order.dendrogram() functions attempt to fix these issues already. Is it possible that could you update the documentation here with some examples of the interplay of these functions and set()? (Or did I miss an example?)

Thanks!

-SV

Position of text labels by the text = argument in rect.dendrogram is on the horizontal axis rather than the vertical axis when horiz = TRUE.

dend15 <- c(1:5) %>% dist %>% hclust(method = "average") %>% as.dendrogram

par(mar=c(5, 5, 5, 5))

dend15 %>% plot(main="dend15")
dend15 %>% rect.dendrogram(k=3, 
                       border = 8, lty = 5, lwd = 2, text = as.roman(1:3))

dend15 %>% plot(main="dend15", horiz = TRUE)
dend15 %>% rect.dendrogram(k=3, horiz = TRUE,
                       border = 8, lty = 5, lwd = 2, text = as.roman(1:3))

I'm not sure if this bug is related to dendextend rather than arules itself. It looks like there is a masking glitch here or there...

Anyway, here's how to reproduce the defect:

require(arules)
a_matrix <- matrix(c(
  1,1,1,0,0,
  1,1,0,0,0,
  1,1,0,1,0,
  0,0,1,0,1,
  1,1,0,1,1
), ncol = 5)

## set dim names
dimnames(a_matrix) <- list(c("a","b","c","d","e"),
                           paste("Tr",c(1:5), sep = ""))

a_matrix

## this works
trans1 <- as(a_matrix, "transactions")

## this mess up the whole thing
require(dendextend)
trans2 <- as(a_matrix, "transactions")

hope this help!

regards,
gabriele

The problem:

Once a dendrogram has a branch with both a line type AND a color (which is a character color), the plot.dendrogram function will not plot and return an error.

This is because I should have edgePar hold a list.

This e-mail includes an example, and what I think a solution might be.

Reproducible example:

install.packages('dendextend')
library('dendextend')

dend <- 1:2 %>% dist %>% hclust %>% as.dendrogram
plot(dend) # works fine

dend %>% set("branches_lty", 1:2) %>% plot # works fine
dend %>% set("branches_col", 1:2) %>% plot # works fine
dend %>% set("branches_col", as.character(1:2)) %>% plot # works fine

Fails:

dend %>% set("branches_lty", 1:2) %>% set("branches_col", as.character(1:2)) %>% plot

Error:

Error in segments(x0, y0, x1, y1, col = col, lty = lty, lwd = lwd) :

invalid line type: must be length 2, 4, 6 or 8

This is because edgePar has to hold both "lty" and "col"

Since "col" is a character, it forces "lty" to become a character also.

dend %>% set("branches_lty", 1:2) %>% set("branches_col", as.character(1:2)) %>%
unclass %>% str

Similar title to the tanglegram issue, I was wondering if its possible to add support for variable length line widths for individual branches. An example of what I mean by this is shown on this page from this library in Python's scikit-learn module, in the "condensed tree" plot. The line widths steadily get smaller as they go down the branch, but the top horizontal 'split' lines remain the same line width.

https://www.researchgate.net/publication/282353458_Elemental_analysis_in_tree-rings_from_two_different_forests_in_southern_Ecuador

Implement this:
https://stackoverflow.com/questions/38034663/rotate-labels-for-ggplot-dendrogram/38038719
The code to change is here:
https://github.com/talgalili/dendextend/blob/master/R/ggdend.R

These could be based on NbClust:

library(NbClust)

dd <- dist(iris[,-5])
hc <- hclust(dd, "ave")
plot(hc)
dd <- cophenetic(hc)

indexes <- c("frey", "mcclain", "cindex", "silhouette", "dunn")
for(i in indexes) {
	print(i)
	a = 	print(
		NbClust(diss = dd , distance = NULL, method = "complete", index = i)
	)
}

a = NbClust(diss = dd , distance = NULL, method = "complete", index = "cindex")

plot(-a$All.index~ as.numeric(names(a$All.index)), type = "b")

The median of all methods could be taken as a decent estimator.