Version 2.2.1 Released
It has been a while since any kind of significant update has been released for the ggetern library, and the other day a minor update was submitted to CRAN, which is now available. There were a few minor bug fixes, and the inclusion of a few new geometries which some of you may find of value.
Newly Approved Geometry: geom_encircle
One of our users commented on the ggtern blog, that the geom_encircle geometry provided by the ggalt package might be handy, and after some investigation, this didn’t need any kind of modification, so it has been added to the list of approved protos, and can be used as follows:
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library(ggtern) library(ggalt) #<<< Install this if it isn't installed! data("Fragments") base = ggtern(Fragments,aes(Qm,Qp,Rf+M,fill=GrainSize,shape=GrainSize)) + theme_bw() + theme_legend_position('tr') + geom_encircle(alpha=0.5,size=1) + geom_point() + labs(title = "Example Plot", subtitle = "using geom_encircle") print(base) |
Pretty simple huh, well this produces the following output:
As you can see (and as expected), points have been circled in an ‘approximate’ manner, sort of like someone grabbing a pen and circling on a piece of paper, perfect for highlighting features without any sort of statistical significance. Of course you will need to install the ggalt package, if it is not already installed.
New Text/Label Geometries:
Some other feedback was generously offered, in that it might be convenient if users could apply text or label elements to the plot region, by defining a fractional position in x or y, relative to the viewport, and so, this has been taken this on board and created two new geometries geom_text_viewport and and geom_label_viewport — these are basically the same as the geom_text and geom_label geometries, except, the user is only expected to provide an x and y positional mapping, which are values constrained between the limits [0,1], representing fractional coordinates of the plot viewport, used as follows:
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df.vp = data.frame(x = c(.5,1,0,0,1), y = c(.5,1,0,1,0), label = c('Middle','Top Right','Bottom Left','Top Left','Bottom Right')) base2 = base + theme(legend.position = 'right') + geom_mask() + geom_text_viewport(data=df.vp,aes(x=x,y=y,label=label,color=label),inherit.aes = FALSE) + labs(color = "Label", subtitle = "using geom_text_viewport") print(base2) |
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base3 = base + theme(legend.position = 'right') + geom_mask() + geom_label_viewport(data=df.vp,aes(x=x,y=y,label=label,color=label),inherit.aes = FALSE) + labs(color = "Label", subtitle = "using geom_label_viewport") print(base3) |
The above have the special added benefit with respect to ternary diagrams, insomuch as they reduce the mental overhead of having to think in ternary coordinates, if you want to manually place a label somewhere. Furthermore, both of these new geometries behave similarly on native ggplot2 objects, so, these represent an intuitive way to place labels in a relative manner to the plot region, without having to consider the axis limits.
Finally, many of you have been citing ggtern in the literature, which I am grateful for, please continue to do so, and let me know so that I might add your respective publications to the publications ledger.
I have been thinking alot of the best way to enable piper diagrams, and/or diagrams with cartesian-binary plots perpendicular to the ternary axes, I am hoping to get this functionality happening soon, which will considerably improve the depth of outputs that this package is able to produce.
Some of you have contacted me to produce custom geometries for your respective projects, and as a final plug, this is something I am more than happy to do…
Cheerio,
NH
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Version 2.2.2 Released
ggtern version 2.2.2 has just been submitted to CRAN, and it includes a number -
Version 2.1.1 Released
Hi Folks, ggtern v2.1.1 has just been submitted to CRAN. This includes a number
About Author
Nick Hamilton
Author of the ggtern package. PhD candidate at the University of New South Wales in the School of Materials Science and Engineering. My field is in the simulations of metallic glasses via several advanced simulation techniques such as QMD and RMC.
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I’m using ggtern to display ternary diagrams of “Archetypal Athletes” – see http://rpubs.com/znmeb/pdxdataviz20170209 for the guts of what I’m doing.
I need to find some kind of tweak for easily resolving multiple players close together; there are sometimes three or four centers or point guards that plot on top of each other. Any suggestions?
Hi Ed, Can you please email me an example (nick at ggtern.com), including code and data, for me to play around with?. In summary, there are a number of options that come to mind without the above. You can jitter the data (but this may not be acceptable), you can zoom in on a region, or, you can facet into different plots.
Another option, would be to plot the points very small, and then run some labels and arrows like the geom_repel (https://goo.gl/Su5gZe) geometry in the ggrepel package — this doesn’t yet work with ggtern, I will need to adapt it.
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