Building R’s RGL library for OSX Snow Leopard

RGL is needed for nice interactive 3d plots in R, but a pain to find out how to build on a modern OSX machine.

“The rgl package is a visualization device system for R, using OpenGL as the rendering backend. An rgl device at its core is a real-time 3D engine written in C++. It provides an interactive viewpoint navigation facility (mouse + wheel support) and an R programming interface.”

The following commands worked for me in OSX Snow Leopard:

  • svn checkout svn://
  • R CMD INSTALL ./rgl/pkg/rgl –configure-args=”–disable-carbon” rgl

Here’s a test that should give an interactive 3D display if all went well, using a built-in dataset:

library(rgl) <- as.matrix(sweep(mtcars[, -1], 2, colMeans(mtcars[, -1]))) # cargo cult'd
xx <- svd( %*% t(
xxd <- xx$v %*% sqrt(diag(xx$d))
x1 <- xxd[, 1]
y1 <- xxd[, 2]
z1 <- xxd[, 3]
plot3d(x1,y1,z1,col="green", size=4)
text3d(x1,y1,z1, row.names(mtcars))

Querying Linked GeoData with R SPARQL client

Assuming you already have the R statistics toolkit installed, this should be easy.
Install Willem van Hage‘s R SPARQL client. I followed the instructions and it worked, although I had to also install the XML library, which was compiled and installed when I typed install.packages(“XML“, repos = ““) ‘ within the R interpreter.
Yesterday I set up a simple SPARQL endpoint using Benjamin Nowack’s ARC2 and RDF data from the Ravensburg dataset. The data includes category information about many points of interest in a German town. We can type the following 5 lines into R and show R consuming SPARQL results from the Web:
  • library(SPARQL)
  • endpoint = “
  • q = “PREFIX vcard: <>\nPREFIX foaf:\n<>\nPREFIX rv:\n<>\nPREFIX gr:\n<>\n \nSELECT ?poi ?l ?lon ?lat ?k\nWHERE {\nGRAPH <> {\n?poi\nvcard:geo ?l .\n  ?l vcard:longitude ?lon .\n  ?l vcard:latitude ?lat\n.\n ?poi foaf:homepage ?hp .\n?poi rv:kategorie ?k .\n\n}\n}\n”
  • res<-SPARQL(endpoint,q)
  • pie(table(res$k))

This is the simplest thing that works to show the data flow. When combined with richer server-side support (eg. OWL tools, or spatial reasoning) and the capabilities of R plus its other extensions, there is a lot of potential here. A pie chart doesn’t capture all that, but it does show how to get started…

Note also that you can send any SPARQL query you like, so long as the server understands it and responds using W3C’s standard XML response. The R library doesn’t try to interpret the query, so you’re free to make use of any special features or experimental extensions understood by the server.