Save high-quality {DiagrammeR} node graph - r

I've made a node graph with {DiagrammeR} and need to save it in high-quality for publication, but none of the usual high-quality saving methods work (e.g. ggsave() -naturally-, svg(), png(), etc.)
No need to upload the whole code, but the two final lines (should suffy) are the following:
graph <- create_graph(nodes_df = nodes, edges_df =
render_graph(graph)
Does anybody know how can I do it? I've tried simply exporting it as .png in the viewer panel and vectorize it online, but couldn't get the quality I want (though if anybody knows of a very good free only vectorizer, grateful to hear it).
Thanks!

I found a way in export_graph: export_graph(graph, file_name = "filename.svg") from the same DiagrammeR package. You can also choose .png and other formats.

Related

Is it possible to download graph of scalars in TensorBoard?

I'm using Tensorboard to visualize the training of a neural network in R. Tensorboard gives really nice graphs of the accuracy, the loss, validation accuracy etcetera. I would like to download these graphs (including smoothing and legend) just like one can download the graph of the nodes. Is this possible? I know that you can download the data one by one, but then you would have to make the graph manually including the smoothing and legend. This would be a lot of work, while you already have such a nice looking graph. I have tried using SVG Crowbar, but I don't know which one to download (if this even works...). I do not know what to do. The best solution thus far seems to be using printscreen and paint.
Thanks in advance for helping me!

Rasterize plot when using PDF output device

Hello everybody out there using R,
When putting multiple plots with thousands of data points into a single PDF file, this file can get huge and take a long time to open.
The following post describes exactly the same problem in Matplotlib, as well as a nice fix for it:
Matplotlib: multipage PDF with rasterized plots
Particularly nice about it is, that it only rasterizes the points without rasterizing the labels.
http://www.astrobetter.com/blog/2014/01/17/slim-down-your-bloated-graphics/ contains a nice example of it.
I am now looking for a similar solution in R.

SVGAnnotation to create tool tips for each value in R heatmaps

I'd like to create a heat map in R that I want to use on a website. I stumbled upon the SVGAnnotation package which seems to be very nice to process SVG graphics in R to make them more interactive. First, I was planning to add tool tips for each cell in the heatmap - if the user hovers over the cell, the value of this cell should pop up. However, I am fighting with SVGAnnotation for more than 3 hours now, reading and trying things, and I can't get it to work.
I would appreciate any help on the SVGAnnotation tool tip function. But I would also very much appreciate alternatives to SVGAnnotation to add some activity to my R SVG heatmap.
So, what I have got so far looks like this:
library(SVGAnnotation)
data(mtcars)
cars <- as.matrix(mtcars)
map <- svgPlot(heatmap(cars))
addToolTips(map, ...) # problem
saveXML(map, "cars.svg")
My problem is the addToolTips function itself, I guess. Intuitively, I would simply insert the data matrix, i.e., cars, but this does not work and R gets stuck (it's calculating, but doesn't return anything, I waited 50 minutes)
EDIT:
After some more online research, I found a good example of what I want to achieve: http://online.wsj.com/article/SB125993225142676615.html#articleTabs=interactive
This heat map looks really great, and the interactive features (tool tips) work very well. I am wondering how they did that. To me, it looks like the graphic was done in R using the ggplot package.
I wrote a command line tool that can do exactly that if you are still interested to add tool tips to your heat map. It runs in Windows/Linux/MacOS terminals. All you need as input is the heat map as svg file and the data table/matrix that you used as input to create your heat map as csv or other text file.

Reduce pdf file size of plot in R

i am plotting some data in R using the following commands:
jj = ts(read.table("overlap.txt"))
pdf(file = "plot.pdf")
plot(jj, ylab="", main="")
dev.off()
The result looks like this:
The problem I have is that the pdf file that I get is quite big (25Mb). Is the a way to reduce the file size? JPEG is not an option because I need a vector graphic.
Take a look at tools::compactPDF - you need to have either qpdf or ghostscript installed, but it can make a huge difference to pdf file size.
If reading a PDF file from disk, there are 3 options for GostScript quality (gs_quality), as indicated in the R help file:
printer (300dpi)
ebook (150dpi)
screen (72dpi)
The default is none. For example to convert all PDFs in folder mypdfs/ to ebook quality, use the command
tools::compactPDF('mypdfs/', gs_quality='ebook')
You're drawing a LOT of lines or points. Vector image formats such as pdf, ps, eps, svg, etc. maintain logical information about all of those points, lines, or other items that increase complexity, which translates to size and drawing time, as the number of points increases. Generally vector images are the best in a number of ways, most compact, scale best, and highest quality reproduction. But, if the number of graphical elements becomes very large then it's often best to go to a raster image format such as png. When you switch to raster it's best to have a good idea what size image you want, both in pixels and also in things like print measurements, in order to produce the best image.
For information from the other direction, too large a raster image, see this answer.
One way of reducing the file size is to reduce the number of values that you have. Assuming you have a dataframe called df:
# take sample of data from dataframe
sampleNo = 10000
sampleData <- df[sample(nrow(df), sampleNo), ]
I think the only other alternative within R is to produce a non-vector. Outside of R you could use Acrobat Professional (which is not free) to optimize the pdf. This can reduce the file size enormously.
Which version of R are you using? In R 2.14.0, pdf() has an argument compress to support compression. I'm not sure how much it can help you, but there are also other tools to compress PDF files such as Pdftk and qpdf. I have two wrappers for them in the animation package, but you may want to use command line directly.
Hard to tell without seeing what the plot looks like - post a screenshot?
I suspect its a lot of very detailed lines and most of the information probably isn't visible - lots of things overlapping or very very small detail. Try thinning your data in one dimension or another. I doubt you'll lose visible information.

Changing resolution of bitmaps

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.

Resources