With the plotweb() function in the bipartite package in R, I've created a network, but some of the labels are too long for the plot area. As a result, they are being cut off at the top and bottom (I've included a picture).
I'm trying to make it fit in the plot, or if not possible, to be able to export it as an image without the edges being cut off.
I've tried par(mar=c(), but that doesn't seem to do anything. ybig() can allow the top half to fit in, but it doesn't change the bottom section.
See photo: labels being cut off from the web
It seems that the argument y.lim could be adjusted in such cases. From help(plotweb), about y.lim:
[...] Useful if labels are plotted outside the plotting region and for multitrophic plots [...]
Here is an example:
library(bipartite)
data(Safariland)
# Forge some long names/labels
cn <- colnames(Safariland)
rn <- rownames(Safariland)
colnames(Safariland) <- paste(cn, cn)
rownames(Safariland) <- paste(rn, rn)
# plotweb with trying to fit the labels - tweak y.lim until you get it right
plotweb(Safariland, text.rot = 90, y.lim = c(-1.5, 4))
Related
I have a simple issue in interactive heatmap in R. I couldn't figure out how to increase margins (distance between x and y labels with main plot) in heatmaply?
I want to add a little bit of space in ylab (province) from heatmap. Could anybody help me?
enter image description here
You can change the margins with heatmaply by using margins
Since you did not provide any code in your question, I will use an example plot using mtcars and changing the y-axis margins
heatmaply(mtcars, margins = c(0, 200, 0, 0))
If you want to move the y-axis labels away from the graph, then that will be trickier. Currently, there doesn't appear to be a way to do this, however, here is a workaround. There is currently now way to move the y-axis labels in heatmaply. Overall, this is a poor workaround but it appears to be the best solution as of right now.
df <- mtcars
#extract the labels on the y axis. In this example mtcars y-axis labels are the row names
df2 <- as.data.frame(rownames(mtcars))
#you then have to add spaces to the end of the labels and then apply this to the dataframe you are using.
rownames(df) <- paste0(df2$`rownames(mtcars)`, " ")
#you can now run heatmaply on the new labels with added spaces
heatmaply(df)
Overall, plotly has some great features however it lacks in tuneability. heatmaply has even fewer features than plotly so it makes it even harder to tune your graph the way you want to.
I am trying to arrange 3 plots together. All 3 plots have the same y axis scale, but the third plot has a longer x axis than the other two. I would like to arrange the first two plots side by side in the first row and then place the third plot on the second row aligned to the right. Ideally I would like the third plot's x values to align with plot 2 for the full extent of plot 2 and then continue on below plot one. I have seen some other postings about using the layout function to reach this general configuration (Arrange plots in a layout which cannot be achieved by 'par(mfrow ='), but I haven't found anything on fine tuning the plots so that the scales match. Below is a crappy picture that should be able to get the general idea across.
I thought you could do this by using par("plt"), which returns the coordinates of the plot region as a fraction of the total figure region, to programmatically calculate how much horizontal space to allocate to the bottom plot. But even when using this method, manual adjustments are necessary. Here's what I've got for now.
First, set the plot margins to be a bit thinner than the default. Also, las=1 rotates the y-axis labels to be horizontal, and xaxs="i" (default is "r") sets automatic x-axis padding to zero. Instead, we'll set the amount of padding we want when we create the plots.
par(mar=c(3,3,0.5,0.5), las=1, xaxs="i")
Some fake data:
dat1=data.frame(x=seq(-5000,-2500,length=100), y=seq(-0.2,0.6,length=100))
dat2=data.frame(x=seq(-6000,-2500,length=100), y=seq(-0.2,0.6,length=100))
Create a layout matrix:
# Coordinates of plot region as a fraction of the total figure region
# Order c(x1, x2, y1, y2)
pdim = par("plt")
# Constant padding value for left and right ends of x-axis
pad = 0.04*diff(range(dat1$x))
# If total width of the two top plots is 2 units, then the width of the
# bottom right plot is:
p3w = diff(pdim[1:2]) * (diff(range(dat2$x)) + 2*pad)/(diff(range(dat1$x)) + 2*pad) +
2*(1-pdim[2]) + pdim[1]
# Create a layout matrix with 200 "slots"
n=200
# Adjustable parameter for fine tuning to get top and bottom plot lined up
nudge=2
# Number of slots needed for the bottom right plot
l = round(p3w/2 * n) - nudge
# Create layout matrix
layout(matrix(c(rep(1:2, each=0.5*n), rep(4:3,c(n - l, l))), nrow=2, byrow=TRUE))
Now create the graphs: The two calls to abline are just to show us whether the graphs' x-axes line up. If not, we'll change the nudge parameter and run the code again. Once we've got the layout we want, we can run all the code one final time without the calls to abline.
# Plot first two graphs
with(dat1, plot(x,y, xlim=range(dat1$x) + c(-pad,pad)))
with(dat1, plot(x,y, xlim=range(dat1$x) + c(-pad,pad)))
abline(v=-5000, xpd=TRUE, col="red")
# Lower right plot
plot(dat2, xaxt="n", xlim=range(dat2$x) + c(-pad,pad))
abline(v=-5000, xpd=TRUE, col="blue")
axis(1, at=seq(-6000,-2500,500))
Here's what we get with nudge=2. Note the plots are lined up, but this is also affected by the pixel size of the saved plot (for png files), and I adjusted the size to get the upper and lower plots exactly lined up.
I would have thought that casting all the quantities in ratios that are relative to the plot area (by using par("plt")) would have both ensured that the upper and lower plots lined up and that they would stay lined up regardless of the number of pixels in the final image. But I must be missing something about how base graphics work or perhaps I've messed up a calculation (or both). In any case, I hope this helps you get the plot layout you wanted.
I'm trying to plot half circles using R. My final aim is to draw a circle, divided in the middle by color. The only way I have found yet is to draw two half-circles with different colors.
So I have created my own functions:
upper.half.circle <- function(x,y,r,nsteps=100,...){
rs <- seq(0,pi,len=nsteps)
xc <- x+r*cos(rs)
yc <- y+r*sin(rs)
polygon(xc,yc,...)
}
lower.half.circle <- function(x,y,r,nsteps=100,...){
rs <- seq(0,pi,len=nsteps)
xc <- x-r*cos(rs)
yc <- y-r*sin(rs)
polygon(xc,yc,...)
}
However, for some reason my half-circles end up more like half-ellipses. For example, try running:
plot(1, type="n",axes=F,xlab="", ylab="",xlim=c(0,200),ylim=c(0,200))
upper.half.circle(15,170,10,nsteps=1000,col='red')
Does anyone know why I'm having this trouble, or alternatively, knows of a better way to do what I want?
Thanks!
The problem is the default aspect ratio is not 1:1.
To fix this, set asp=1 in plot:
Inspired by this Q & A. You could have sniffed out this was the case by turning on the axes and x/y labels.
If using the grid package would be also an opportunity for you, there is a much simpler solution:
library(grid)
vp <- viewport(width=0.5, height=0.5, clip = "on")
grid.circle(0.5,0,r=0.5, gp = gpar(fill = 'red'), vp = vp)
This creates a viewport with clipping, i.e., an appropriate positioning of the filled circle creates a half circle.
If you want to add your half circles to an existing plot (and therefore cannot control the aspect ratio directly) then one option for this specific case is to use the floating.pie function from the plotrix package.
A more general tool for creating custom symbols and adding them to plots (with the symbols having a different aspect ratio from the overall plot) is to use the my.symbols function from the TeachingDemos package.
I'm trying to figure out a way to calculate the height of a legend for a plot prior to setting the margins of the plot. I intend to place the legend below the plot below the x-axis labels and title.
As it is part of a function which plots a range of things the legend can grow and shrink in size to cater for 2 items, up to 15 or more, so I need to figure out how I can do this dynamically rather that hard-coding. So, in the end I need to dynamically set the margin and some other bits and pieces.
The key challenge is to figure out the height of the legend to feed into par(mar) prior to drawing the plot, but after dissecting the base codes for legend however, it seems impossible to get a solid estimate of the height value unless the plot is actually drawn (chicken and egg anyone?)
Here's what I've tried already:
get a height using the legend$rect$h output from the base legend function (which seems to give a height value which is incorrect unless the plot is actually drawn)
calculate the number of rows in the legend (easy) and multiply this by the line height (in order to do this, seems you'd need to translate into inches (the base legend code uses yinch and I've also tried grconvertY but neither of those work unless a plot has been drawn).
Another challenge is to work out the correct y value for placement of the legend - I figure that once I've solved the first challenge, the second will be easy.
EDIT:
After a day of sweating over how this is (not) working. I have a couple of insights and a couple of questions. For the sake of clarity, this is what my function essentially does:
step 1) set the margins
step 2) create the barplot on the left axis
step 3) re-set the usr coordinates - this is necessary to ensure alignment of the right axis otherwise it plots against the x-axis scale. Not good when they are markedly different.
step 4) create the right axis
step 5) create a series of line charts on the right axis
step 6) do some labelling of the two axes and the x-axis
step 7) add in the legend
Here are the questions
Q1) What units are things reported in? I'm interested in margin lines and coordinates (user-coordinates), inches is self explanatory. - I can do some conversions using grconvertY() but I'm not sure what I'm looking at and what I should be converting to - the documentation isn't so great.
Q2) I need to set the margin in step 1 so that there is enough room at the bottom of the chart for the legend. I think I'm getting that right, however I need to set the legend after the right axis and line charts are set, which means that the user coordinates (and the pixel value of an inch, has changed. Because of Q1 above I'm not sure how to translate one system to the other. Any ideas in this regard would be appreciated.
After another day of sweating over this here's what solved it mostly for me.
I pulled apart the code for the core legend function and compiled this:
#calculate legend buffer
cin <- par("cin")
Cex <- par("cex")
yc <- Cex * cin[2L] #cin(inches) * maginfication
yextra <- 0
ymax <- yc * max(1, strheight("Example", units = "inches", cex = Cex)/yc)
ychar <- yextra + ymax #coordinates
legendHeight <- (legendLines * ychar) + yc # in
Which is essentially mimicking the way the core function calculates legend height but returns the height in inches rather than in user coordinates. legendLines is the number of lines in the legend.
After that, it's a doddle to work out how to place the legend, and to set the lower margin correctly. I'm using:
#calculate inches per margin line
inchesPerMarLine<-par("mai")[1]/par("mar")[1]
To calculate the number of inches per margin line, and the following to set the buffers (for the axis labels and title, and the bottom of the chart), and the margin of the plot.
#set buffers
bottomBuffer = 1
buffer=2
#calculate legend buffer
legBuffer <- legendHeight/inchesPerMarLine
#start the new plot
plot.new()
# set margin
bottomMargin <- buffer + legBuffer + bottomBuffer
par(mar=c(bottomMargin,8,3,5))
The plot is made
barplot(data, width=1, col=barCol, names.arg=names, ylab="", las=1 ,axes=F, ylim=c(0,maxL), axis.lty=1)
And then the legend is placed. I've used a different method to extract the legend width which does have some challenges when there is a legend with 1 point, however, it works ok for now. Putting the legend into a variable allows you to access the width of the box like l$rect$w. trace=TRUE and plot=FALSE stop the legend being written to the plot just yet.
ycoord <- -1*(yinch(inchesPerMarLine*buffer)*1.8)
l<-legend(x=par("usr")[1], y=ycoord, inset=c(0,-0.25), legendText, fill=legendColour, horiz=FALSE, bty = "n", ncol=3, trace=TRUE,plot=FALSE)
lx <- mean(par("usr")[1:2]-(l$rect$w/2))
legend(x=lx, y=ycoord, legendText, fill=legendColour, horiz=FALSE, bty = "n", ncol=3)
For completeness, this is how I calculate the number of lines in the legend. Note - the number of columns in the legend is 3. labelSeries is the list of legend labels.
legendLines <- ceiling(nrow(labelSeries)/3)
The R package wordcloud has a very useful function which is called wordlayout. It takes initial positions of words and their respective sizes an rearranges them in a way that they do not overlap. I would like to use the results of this functions to do a geom_text plot in ggplot.
I came up with the following example but soon realized that there seems to be a big difference betweetn cex (wordlayout) and size (geom_plot) since words in graphics package appear way larger.
here is my sample code. Plot 1 is the original wordcloud plot which has no overlaps:
library(wordcloud)
library(tm)
library(ggplot2)
samplesize=100
textdf <- data.frame(label=sample(stopwords("en"),samplesize,replace=TRUE),x=sample(c(1:1000),samplesize,replace=TRUE),y=sample(c(1:1000),samplesize,replace=TRUE),size=sample(c(1:5),samplesize,replace=TRUE))
#plot1
plot.new()
pdf(file="plot1.pdf")
textplot(textdf$x,textdf$y,textdf$label,textdf$size)
dev.off()
#plot2
ggplot(textdf,aes(x,y))+geom_text(aes(label = label, size = size))
ggsave("plot2.pdf")
#plot3
new_pos <- wordlayout(x=textdf$x,y=textdf$y,words=textdf$label,cex=textdf$size)
textdf$x <- new_pos[,1]
textdf$y <- new_pos[,2]
ggplot(textdf,aes(x,y))+geom_text(aes(label = label, size = size))
ggsave("plot3.pdf")
#plot4
textdf$x <- new_pos[,1]+0.5*new_pos[,3]#this is the way the wordcloud package rearranges the positions. I took this out of the textplot function
textdf$y <- new_pos[,2]+0.5*new_pos[,4]
ggplot(textdf,aes(x,y))+geom_text(aes(label = label, size = size))
ggsave("plot4.pdf")
is there a way to overcome this cex/size difference and reuse wordlayout for ggplots?
cex stands for character expansion and is the factor by which text is magnified relative the default, specified by cin - set on my installation to 0.15 in by 0.2 in: see ?par for more details.
#hadley explains that ggplot2 sizes are measured in mm. Therefore cex=1 would correspond to size=3.81 or size=5.08 depending on if it is being scaled by the width or height. Of course, font selection may cause differences.
In addition, to use absolute sizes, you need to have the size specification outside the aes otherwise it considers it a variable to map to and choose the scale itself, eg:
ggplot(textdf,aes(x,y))+geom_text(aes(label = label),size = textdf$size*3.81)
Sadly I think you're going to find the short answer is no! I think the package handles the text vector mapping differently from ggplot2, so you can tinker with size and font face/family, etc. but will struggle to replicate exactly what the package is doing.
I tried a few things:
1) Try to plot the grobs from textdata using annotation_custom
require(plyr)
require(grid)
# FIRST TRY PLOT INDIVIDUAL TEXT GROBS
qplot(0:1000,0:1000,geom="blank") +
alply(textdf,1,function(x){
annotation_custom(textGrob(label=x$label,0,0,c("center","center"),gp=gpar(cex=x$size)),x$x,x$x,x$y,x$y)
})
2) Run the wordlayout() function which should readjust the text, but difficult to see for what font (similarly doesn't work)
# THEN USE wordcloud() TO GET CO-ORDS
plot.new()
wordlayout(textdf$x,textdf$y,words=textdf$label,cex=textdf$size,xlim=c(min(textdf$x),max(textdf$x)),ylim=c(min(textdf$y),max(textdf$y)))
plotdata<-cbind(data.frame(rownames(w)),w)
colnames(plotdata)=c("word","x","y","w","h")
# PLOT WORDCLOUD DATA
qplot(0:1000,0:1000,geom="blank") +
alply(plotdata,1,function(x){
annotation_custom(textGrob(label=x$word,0,0,c("center","center"),gp=gpar(cex=x$h*40)),x$x,x$x,x$y,x$y)
})
Here's a cheat if you just want to overplot other ggplot functions on top of it (although the co-ords don't seem to match up exactly between the data and the plot). It basically images the wordcloud, removes the margins, and under-plots it at the same scale:
# make a png file of just the panel
plot.new()
png(filename="bgplot.png")
par(mar=c(0.01,0.01,0.01,0.01))
textplot(textdf$x,textdf$y,textdf$label,textdf$size,xaxt="n",yaxt="n",xlab="",ylab="",asp=1)
dev.off()
# library to get PNG file
require(png)
# then plot it behind the panel
qplot(0:1000,0:1000,geom="blank") +
annotation_custom(rasterGrob(readPNG("bgplot.png"),0,0,1,1,just=c("left","bottom")),0,1000,0,1000) +
coord_fixed(1,c(0,1000),c(0,1000))