I have generated a few network graphs in igraph. I like to use tkplot, however, after resizing the window manually and changing the layout, my machine freezes up when I try to export or even take a screenshot of the graph.
Any ideas? My machine is Windows XP Pro and has 2GB memory.
Many thanks in advance.
I can't reproduce your error on Windows 7. What you can try is
to set the canvas size yourself in
the tkplot command
to use the
function tkplot.export.postscript to
call for the export dialog.
This can be done by:
g <- graph.ring(10)
x <- tkplot(g,canvas.width=800, canvas.height=800)
tkplot.export.postscript(x)
Worst case scenario you could extract the coordinates using tkplot.getcoords(x) and use the base plot functions to reconstruct the graph. This is a whole lot trickier off course, as you have to keep track of which vertices are connected and which not.
Related
I am trying to use the default plot() function in R to try and plot a shapefile that is about 100MB, using RStudio. When I try and plot the shapefile, the command doesn't finish executing for around 5 minutes, and when it finally does, the plotting window remains blank. When I execute the same process exactly in VS Code, the plot appears almost instantly, as expected.
I have tried uninstalling and reinstalling RStudio with no success.
I can't speak for what VStudio does, but I can guarantee that plotting 100MB worth of data points is useless (unless the final plot is going to be maybe 6 by 10 meters in size).
First thing: can you load the source file into R at all? One would hope so since that's not a grossly huge data blob. Then use your choice of reduction algorithms to get a reasonable number of points to plot, e.g. 800 by 1600, which is all a monitor can display anyway.
Next try plotting a small subset to verify the data are in a valid form, etc.
Then consider reducing the data by collapsing maybe each 10x10 region to a single average value, or by using ggplot2:geom_hex .
I am trying to manually identify/correct trees using LiDAR data (1.7 GB object) and a tree tops object via the locate_trees function. Part of the problem is:
Rgl is rendering very slow even though the 4 GB Nvidia 3050 should be able to handle it.
The tree tops (red 3D dots) are not even showing in the rgl window. When I close the rgl window, the tree tops start popping up (red dots appear and disappear resulting in a blank white window) in a new rgl window. And if I close that window, a new tree top window opens up so I stop the process to prevent this from happening.
Does rgl automatically use the GPU or does it default to the integrated graphics on the motherboard? Is there a way to fasten up the rendering?
My other system specs are Corei9 (14 threads) and 64 GB RAM. Moreover, I am using R 4.2.1.
Code:
library(lidR)
# Import LiDAR data
LiDAR_File = readLAS("path/file_name.las")
# Find tree tops
TTops = find_trees(LiDAR_File , lmf(ws = 15, hmin = 5))
# Manually correct tree identification
TTops_Manual = locate_trees(LiDAR_File , manual(TTops)) # This is where rgl rendering becomes too slow if there are too many points involved.
There were two problems here. First, the lidR::manual() function which is used to select trees has a loop where one sphere is drawn for each tree. By default rgl will redraw the whole scene after each change; this should be suppressed. The patch in https://github.com/r-lidar/lidR/pull/611 fixes this. You can install a version with this fix as
remotes::install_github("r-lidar/lidR")
Second, rgl was somewhat inefficient in drawing the initial point cloud of data, duplicating the data unnecessarily. When you have tens of millions of points, this can exhaust all R memory, and things slow to a crawl. The development version of rgl fixes this. It's available via
remotes::install_github("dmurdoch/rgl")
The LiDAR images are very big, so you might find you still have problems even with these changes. Getting more regular RAM will help R: you may need this if the time to the first display is too long. After the first display, almost all the work is done in the graphics system; if things are still too slow, you may need a faster graphics card (or more memory for it).
rgl has trouble displaying too many points. The plot function in lidR is convenient and allows to produce ready to publish illustrations but cannot replace a real point cloud viewer for big point clouds. I don't have GPU on my computer and I don't know if and how rgl can take advantage of GPU.
In the doc of the lidR function your are talking about you can see:
This is only suitable for small-sized plots
do you guys know how to display an R plot in a terminal/console instead of showing it on plot viewers?
I've recently working to integrate R with external tools, and somehow the only function works is to returns all the value shown up in the console result. Thus, I need some sort of workaround to be able to post a plot in the external tools.
Thanks in advance!
No. That is not possible. The reason is that the plot needs a graphic device.
The terminal (and R console) is a text-based device.
What you can do, is use the image-format files as graphic device. Here, you have a multitude of choices, such as PNG, BMP, JPEG. In R, look up ?png.
I am trying to build graphs using tree-like data, where nodes typically split into >2 edges. I have tried various layouts, and I see that the layout.reingold.tilford parameter will generate tree-like graphs with non-bifurcating data. However the outputs are not particularly attractive. I would rather use something like the layout.lgl or layout.kamada.kawai since these produce more radial structures. I cannot see how to change the parameters in R such that these trees have no overlapping edges though. Is this possible?
I imported a simple data file in Pajek format, with 355 nodes and 354 edges. I'm currently printing it using:
plot.igraph(g,vertex.size=3,vertex.label=NA,layout=layout.lgl)
This gives me an output like this, which is nice, but still has overlapping edges. I have read that you can manually fix this using tkplot, or another program like cytoscape, however I have quite a few of these to build, and the size of them makes manual correction a hassle.
Many thanks.
Just want to add a comment but my rep is too low. The method that #bdemarest posted does not work on igraph version > 0.7. The newer version does not support the area parameter, so I cannot get the same effect. And getting the old version to build took me a while, so I though I'd share some insights. You can manually install igraph 0.7 from source if you download it from igraph nightly builds. On my machine (Mac OS 10.10), I encountered some problems building it, due to gfortran, so I found this link that solved the problem. Hope that helps anyone who wants to create similar graphs in R.
You may want to try layout.fruchterman.reingold(). It seems to do a good job keeping the edges from crossing. I've tested it with a 355 node version of the barabasi graph suggested by #Tamás.
library(igraph)
g = barabasi.game(355, directed=FALSE)
png("plot1.png", height=6, width=12, units="in", res=200)
par(mfrow=c(1, 2))
plot.igraph(g,vertex.size=3,vertex.label=NA,
layout=layout.fruchterman.reingold(g, niter=10000))
mtext("layout.fruchterman.reingold, area = vcount^2", side=1)
plot.igraph(g,vertex.size=3,vertex.label=NA,
layout=layout.fruchterman.reingold(g, niter=10000, area=30*vcount(g)^2))
mtext("layout.fruchterman.reingold, area = 30 * vcount^2", side=1)
dev.off()
layout.reingold.tilford has a parameter called circular. Setting this to TRUE will convert the final layout into a radial one by treating the X coordinate as the angle (after appropriate rescaling) and the Y coordinate as the radius. Ironically enough, this does not guarantee that there will be no edge crossings in the end, but it works nicely if your subtrees are not exceedingly wide compared to the rest of the graph:
> g <- barabasi.game(100, directed=F)
> layout <- layout.reingold.tilford(g, circular=T)
> plot(g, layout=layout)
I am making some graphs with R and I am coping them to Word. I was coping them as metafiles but Word doesn't seem to be able to cope with them. The other option in R to copy graphs is a bitmap, but when I use this the quality of the graphs in word is terrible.
I saw some answers about changing the resolution in this website but only if I saved the graphs which I would like to avoid. Is there a way of changing the resolution for copied graphs?
Thanks,
sbg
When the graphs are onscreen, they are drawn for a screen resolution (i.e. 72dpi). For print, you need to use at least 300dpi, or switch to a vector format. Word can import graphs in Windows Metafile (.wmf) format; but your other option is to save the plot using, e.g.,
png("my plot.png", res = 300)
plot(1:5)
dev.off()
This saves to disk, which you said you wanted to avoid, but you can always delete it again later (programatically even, with file.remove).
I'd also like to make the case that when you copy and paste, your work isn't as easily reproducible as when you use code. There is no trace of what you have done, and when your data changes, you need to go through the rigmarole of clicking again, rather than just executing your updated script.