Plotting tanglegrams subplots in R using dendextend - r

I am plotting Tanglegrams in R using dendextend. I am wondering if it is possible to plot multiple subplots using par(mfrow = c(2,2))?
I can't seem to figure it out.
Thanks
library(dendextend)
dend15 <- c(1:5) %>% dist %>% hclust(method = "average") %>% as.dendrogram
dend15 <- dend15 %>% set("labels_to_char")
dend51 <- dend15 %>% set("labels", as.character(5:1)) %>% match_order_by_labels(dend15)
dends_15_51 <- dendlist(dend15, dend51)
par(mfrow = c(2,2))
tanglegram(dends_15_51)
tanglegram(dends_15_51)
tanglegram(dends_15_51)
tanglegram(dends_15_51)

tl;dr: It is not possible to use par(mfrow=...) with the function tanglegram, but it is possible using layout.
Explanation: If you look closer at function tanglegram, you'll see (methods(tanglegram)) that, underneath, there are several methods, among which, dendextend:::tanglegram.dendrogram which is called to draw the tanglegram (as can be seen inside dendextend:::tanglegram.dendlist function).
Inside this function, there is a call to layout:
layout(matrix(1:3, nrow = 1), widths = columns_width)
This "erases" your previous setting of par(mfrow=c(2, 2)) and changes it to c(1, 3) (just for the "time" of the function though because at the end of the function, the value is reset...).
Indeed, in the help page of layout, it says:
These functions are totally incompatible with the other mechanisms for arranging plots on a device: par(mfrow), par(mfcol) and split.screen.
Conclusion: If you want to plot several tanglegrams in the same "window" you'll need to use the layout call (with 12 subparts: 2 rows and 6 columns) ahead of the calls to tanglegram and suppress the layout call inside tanglegram using the argument just_one=FALSE.
Example of drawing several tanglegrams:
Using the code below, you can then obtain the desired plot (I put the function's default widths for the layout):
layout(matrix(1:12, nrow=2, byrow=TRUE), widths=rep(c(5, 3, 5), 2))
tanglegram.dendlist_mod(dends_15_51, just_one=FALSE)
tanglegram.dendlist_mod(dends_15_51, just_one=FALSE)
tanglegram.dendlist_mod(dends_15_51, just_one=FALSE)
tanglegram.dendlist_mod(dends_15_51, just_one=FALSE)
This was done by updating the dendextend package in which: I modified the 2 functions tanglegram.dendrogram and tanglegram.dendlist to add a just_one parameter, which defaults to TRUE and changed the line of the layout in tanglegram.dendrogram to:
if (just_one) layout(matrix(1:3, nrow = 1), widths = columns_width)
I also suppressed the reset of par parameters and of course changed the call in tanglegram.dendlist (now called tanglegram.dendlist_mod) so it calls the new modified function, incorporates the just_one parameter and passes it to the modified tanglegram.dendrogram function.

Rather than creating a combined plot in a single graphical device, you could create multiple plots and arrange them when you put them in a document. The knitr package makes it easy to do this, by using fig.show = "hold" to hold on to multiple plots produced in a single R chunk and specifying a relevant out.width, e.g. 50% to have two plots in a row, for when the plots are placed in the document.
For example, in an R markdown (.Rmd) file you might have
```{r, fig.show = "hold", out.width = "50%", echo = FALSE}
suppressPackageStartupMessages(library(dendextend))
dend15 <- c(1:5) %>% dist %>% hclust(method = "average") %>% as.dendrogram
dend15 <- dend15 %>% set("labels_to_char")
dend51 <- dend15 %>% set("labels", as.character(5:1)) %>% match_order_by_labels(dend15)
dends_15_51 <- dendlist(dend15, dend51)
tanglegram(dends_15_51, margin_outer = 1)
plot.new()
tanglegram(dends_15_51, margin_outer = 1)
plot.new()
tanglegram(dends_15_51, margin_outer = 1)
plot.new()
tanglegram(dends_15_51, margin_outer = 1)
```
which when knitted to HTML, would look like the following:
There a few modifications I made to the code:
Suppressed package startup messages from dendextend.
Increased default margin_outer to avoid overlapping x axis labels from neighbouring plots.
Added plot.new() in between calls to tanglegram, otherwise the next plot would be drawn on top of the previous one (this is a result of tanglegram using layout and is not needed in general when producing multiple plots).
The same approach can be used in .Rnw files. If you are compiling to PDF (via LaTeX) you can add a figure caption and subcaptions, see knitr demo #067 - Graphics Options for more detail.

Related

drake readd function not working for plots

I'm trying to trouble shoot why Drake plots are not showing up with readd() - the rest of the pipeline seem's to have worked though.
Not sure if this is caused by minfi::densityPlot or some other reason; my thoughts are the later as it's also not working for the barplot function which is base R.
In the RMarkdown report I have readd(dplot1) etc. in the chunks but the output is NULL
This is the code I have in my R/setup.R file:
library(drake)
library(tidyverse)
library(magrittr)
library(minfi)
library(DNAmArray)
library(methylumi)
library(RColorBrewer)
library(minfiData)
pkgconfig::set_config("drake::strings_in_dots" = "literals") # New file API
# Your custom code is a bunch of functions.
make_beta <- function(rgSet){
rgSet_betas = minfi::getBeta(rgSet)
}
make_filter <- function(rgSet){
rgSet_filtered = DNAmArray::probeFiltering(rgSet)
}
This is my R/plan.R file:
# The workflow plan data frame outlines what you are going to do
plan <- drake_plan(
baseDir = system.file("extdata", package = "minfiData"),
targets = read.metharray.sheet(baseDir),
rgSet = read.metharray.exp(targets = targets),
mSetSq = preprocessQuantile(rgSet),
detP = detectionP(rgSet),
dplot1 = densityPlot(rgSet, sampGroups=targets$Sample_Group,main="Raw", legend=FALSE),
dplot2 = densityPlot (getBeta (mSetSq), sampGroups=targets$Sample_Group, main="Normalized", legend=FALSE),
pal = RColorBrewer::brewer.pal (8,"Dark2"),
dplot3 = barplot (colMeans (detP[,1:6]), col=pal[ factor (targets$Sample_Group[1:6])], las=2, cex.names=0.8, ylab="Mean detection p-values"),
report = rmarkdown::render(
knitr_in("report.Rmd"),
output_file = file_out("report.html"),
quiet = TRUE
)
)
After using make(plan) it looks like everything ran smoothly:
config <- drake_config(plan)
vis_drake_graph(config)
I am able to use loadd() to load the objects needed for one of these plots and then make the plots, like this:
loadd(rgSet)
loadd(targets)
densityPlot(rgSet, sampGroups=targets$Sample_Group,main="Raw", legend=FALSE)
But the readd() command doesn't work?
The output in the .html for dplot3 looks weird...
Fortunately, this is expected behavior. drake targets are return values of commands, and so the value of dplot3 is supposed to be the return value of barplot(). The return value of barplot() is actually not a plot. The "Value" section of the help file (?barplot) explains the return value.
A numeric vector (or matrix, when beside = TRUE), say mp, giving the coordinates of all the bar midpoints drawn, useful for adding to the graph.
If beside is true, use colMeans(mp) for the midpoints of each group of bars, see example.
So what is going on? As with most base graphics functions, the plot from barplot() is actually a side effect. barplot() sends the plot to a graphics device and then returns something else to the user.
Have you considered ggplot2? The return value of ggplot() is actually a plot object, which is more intuitive. If you want to stick with base graphics, maybe you could save the plot to an output file.
plan <- drake_plan(
...,
dplot3 = {
pdf(file_out("dplot3.pdf"))
barplot(...)
dev.off()
}
)

Replay recorded plot with new layout in R

I am trying to create and record plots in a 1x1 device:
par(mfrow = c(1, 1) )
plot(rnorm(10) )
p1 <- recordPlot()
plot(rnorm(20) )
p2 <- recordPlot()
and then to put them in a new layout (e.g., a 1x2 device):
par(mfrow = c(1, 2) )
p1
p2
However, this produce the same effect (i.e., plotting each plot in a 1x1 device). It seems replaying plots uses the original layout (graphical parameters) that was in effect when they were recorded.
Is there some method that allows a saved plot to be replayed in a new layout ?
NB: I am aware this would be easier via ggplot2, but my question is about base plots.
I did some digging, and I don't think this is possible. I used the following to look at what attributes are available inside the object. None of them seemed to indicate the layout could be adjusted.
summary(p1)
p1[[1]]
p1[[2]]
If you need the same plot across two different layouts could you use set.seed() to recreated the same plot? See the example below.
par(mfrow = c(1, 1))
set.seed(1234)
plot(rnorm(10))
par(mfrow = c(1, 2))
set.seed(1234)
plot(rnorm(10))
I'd be interested to see if anyone else has a better answer!

knitr adds an empty figure with ssplot from seqHMM package

I have the following chunk in RStudio:
<<sumfig,dependson='data',fig.cap="Summary of sequences">>=
ssplot(smult)
#
ssplot is a function in seqHMM package which creates a frequency graph and smult is my sequence data.
When I run my code, I get two figures in my pdf: The first one is an empty white figure with label {fig:sumfig1} and the second one is the real figure with label {fig:sumfig1}. I have similar experience with other plots from this package. I also have some other graphs in my file from other packages which work just fine.
Is it something wrong with the package or I am doing something wrong?
The root of this issue seems to be seqHMM:ssplot, not knitr: Even in an interactive sesion, ssplot generates two plots, an empty one and the actual plot.
If there is only one plot generated in the chunk with ssplot, the chunk option fig.keep = "last" can be used to disregard the first plot and show only the second (last) one.
\documentclass{article}
\begin{document}
<<echo = FALSE, message = FALSE, fig.keep = "last">>=
library(seqHMM)
# from ?ssplot
data("biofam3c")
# Creating sequence objects
child_seq <- seqdef(biofam3c$children, start = 15)
marr_seq <- seqdef(biofam3c$married, start = 15)
left_seq <- seqdef(biofam3c$left, start = 15)
## Choosing colors
attr(child_seq, "cpal") <- c("#66C2A5", "#FC8D62")
attr(marr_seq, "cpal") <- c("#AB82FF", "#E6AB02", "#E7298A")
attr(left_seq, "cpal") <- c("#A6CEE3", "#E31A1C")
# Plotting state distribution plots of observations
ssplot(list("Children" = child_seq, "Marriage" = marr_seq,
"Residence" = left_seq))
#
\end{document}
As of knitr 1.14 (the current development version, available on GitHub), you can also use fig.keep to specify which plots exactly you want to keep: fig.keep = c(1,3) will keep the first and the third plot.

r - Missing object when ggsave output as .svg

I'm attempting to step through a dataset and create a histogram and summary table for each factor and save the output as a .svg . The histogram is created using ggplot2 and the summary table using summary().
I have successfully used the code below to save the output to a single .pdf with each page containing the relevant histogram/table. However, when I attempt to save each histogram/table combo into a set of .svg images using ggsave only the ggplot histogram is showing up in the .svg. The table is just white space.
I've tried using dev.copy Cairo and svg but all end up with the same result: Histogram renders, but table does not. If I save the image as a .png the table shows up.
I'm using the iris data as a reproducible dataset. I'm not using R-Studio which I saw was causing some "empty plot" grief for others.
#packages used
library(ggplot2)
library(gridExtra)
library(gtable)
library(Cairo)
#Create iris histogram plot
iris.hp<-ggplot(data=iris, aes(x=Sepal.Length)) +
geom_histogram(binwidth =.25,origin=-0.125,
right = TRUE,col="white", fill="steelblue4",alpha=1) +
labs(title = "Iris Sepal Length")+
labs(x="Sepal Length", y="Count")
iris.list<-by(data = iris, INDICES = iris$Species, simplify = TRUE,FUN = function(x)
{iris.hp %+% x + ggtitle(unique(x$Species))})
#Generate list of data to create summary statistics table
sum.str<-aggregate(Sepal.Length~Species,iris,summary)
spec<-sum.str[,1]
spec.stats<-sum.str[,2]
sum.data<-data.frame(spec,spec.stats)
sum.table<-tableGrob(sum.data)
colnames(sum.data) <-c("species","sep.len.min","sep.len.1stQ","sep.len.med",
"sep.len.mean","sep. len.3rdQ","sep.len.max")
table.list<-by(data = sum.data, INDICES = sum.data$"species", simplify = TRUE,
FUN = function(x) {tableGrob(x)})
#Combined histogram and summary table across multiple plots
multi.plots<-marrangeGrob(grobs=(c(rbind(iris.list,table.list))),
nrow=2, ncol=1, top = quote(paste(iris$labels$Species,'\nPage', g, 'of',pages)))
#bypass the class check per #baptiste
ggsave <- ggplot2::ggsave; body(ggsave) <- body(ggplot2::ggsave)[-2]
#
for(i in 1:3){
multi.plots<-marrangeGrob(grobs=(c(rbind(iris.list[i],table.list[i]))),
nrow=2, ncol=1,heights=c(1.65,.35),
top = quote(paste(iris$labels$Species,'\nPage', g, 'of',pages)))
prefix<-unique(iris$Species)
prefix<-prefix[i]
filename<-paste(prefix,".svg",sep="")
ggsave(filename,multi.plots)
#dev.off()
}
Edit removed theme tt3 that #rawr referenced. It was accidentally left in example code. It was not causing the problem, just in case anyone was curious.
Edit: Removing previous answer regarding it working under 32bit install and not x64 install because that was not the problem. Still unsure what was causing the issue, but it is working now. Leaving the info about grid.export as it may be a useful alternative for someone else.
Below is the loop for saving the .svg's using grid.export(), although I was having some text formatting issues with this (different dataset).
for(i in 1:3){
multi.plots<-marrangeGrob(grobs=(c(rbind(iris.list[i],table.list[i]))),
nrow=2, ncol=1,heights=c(1.65,.35), top =quote(paste(iris$labels$Species,'\nPage', g,
'of',pages)))
prefix<-unique(iris$Species)
prefix<-prefix[i]
filename<-paste(prefix,".svg",sep="")
grid.draw(multi.plots)
grid.export(filename)
grid.newpage()
}
EDIT: As for using arrangeGrob per #baptiste's comment. Below is the updated code. I was incorrectly using the single brackets [] for the returned by list, so I switched to the correct double brackets [[]] and used grid.draw to on the ggsave call.
for(i in 1:3){
prefix<-unique(iris$Species)
prefix<-prefix[i]
multi.plots<-grid.arrange(arrangeGrob(iris.list[[i]],table.list[[i]],
nrow=2,ncol=1,top = quote(paste(iris$labels$Species))))
filename<-paste(prefix,".svg",sep="")
ggsave(filename,grid.draw(multi.plots))
}

Combine two plots created with effects package in R

I have the following Problem. After running an ordered logit model, I want to R's effects package to visualize the results. This works fine and I did so for two independent variables, then I tried to combine the two plots. However, this does not seem to work. I provide a little replicable example here so you can see my problem for yourself:
library(car)
data(Chile)
mod <- polr(vote ~ age + log(income), data=Chile)
eff <- effect("log(income)", mod)
plot1 <- plot(eff, style="stacked",rug=F, key.args=list(space="right"))
eff2 <- effect("age", mod)
plot2 <- plot(eff2, style="stacked",rug=F, key.args=list(space="right"))
I can print these two plots now independently, but when I try to plot them together, the first plot is overwritten. I tried setting par(mfrow=c(2,1)), which didn't work. Next I tried the following:
print(plot1, position=c(0, .5, 1, 1), more=T)
print(plot2, position=c(0,0, 1, .5))
In this latter case, the positions of the two plots are just fine, but still the first plot vanishes once I add the second (or better, it is overwritten). Any suggestions how to prevent this behavior would be appreciated.
Reading down the long list of arguments to ?print.eff we see that there are some arguments for doing just this:
plot(eff, style="stacked",rug=F, key.args=list(space="right"),
row = 1,col = 1,nrow = 1,ncol = 2,more = TRUE)
plot(eff2, style="stacked",rug=F, key.args=list(space="right"),
row = 1,col = 2,nrow = 1,ncol = 2)
The reason par() didn't work is because this package is using lattice graphics, which are based on the grid system, which is incompatible with base graphics. Neither par() nor layout will have any effect on grid graphics.
This seems to work:
plot(eff,col=1,row=2,ncol=1,nrow=2,style="stacked",rug=F,
key.args=list(space="right"),more=T)
plot(eff2,col=1,row=1,ncol=1,nrow=2,style="stacked",rug=F,
key.args=list(space="right"))
edit: Too late...

Resources