![]() ![]() ) to navigate to where you’ve got the R.***.tar.gz and record its location, or -if you already know it - just copy the path to it to the clipboard. I’m fairly comfortable with the command line, so was happy to use that option, but did make a few silly mistakes with the paths, so am documenting what worked below, in the hope that it helps others: forget .įor details about why this works see here.Īfter that completes successfully (note: you’ll need to enter your password to use sudo) you can run the GUI installer. To do this you need to open a Terminal and type the following command: sudo pkgutil -forget .el-capitan.fw.pkg \ The workaround to prevent this from happening is to make your system, and hence the R installer, “forget” it has R installed. So the reason I think the GUI is “riskier” is because usually when you run the GUI for a new version of R, it cleanly removes the old version of R from your machine. In my case, I downloaded the latest stable branch (72 Mb): tar.gz copy of the R framework from the developer page. Option 2: Pre-built copy (the approach I took)ĭownload a pre-built. This is NOT the approach I took, because if done wrong this approach can remove your existing R installation, but I will describe how in theory I think it’s meant to be used below. ![]() Option 1: GUI (IMHO riskier)ĭownload the graphical installer R-4.0.0.pkg, which is the top link when on CRAN you click on “Download R for (Mac) OS X”. There is more than one way to get a new version of R onto your machine. (Eventually) End up with a nice switch icon in your menubar. Go through all of the hoops of getting it approved by MacOS and able to be run by accepting the risks of running software from an unidentified developer. Updating R versions mid-analysis can have … unintended consequences. Make sure you have closed R and RStudio prior to embarking on the below. Also, I had some funky hiccups with getting the right filepath and not using sudo at the outset, so I’m hoping this helps someone avoid some extra rm -r. I’ve played with it for all of two days, and it seems to work - so I’ve written this post in the hopes of helping others. Below I document, in what is probably excruciating detail, the steps of how I got this to work. But with this major new release I was sorely tempted, so have gone down the rabbit-hole of installing RSwitch and R4.0 on my Mac (Catalina 10.15.4). ![]() In the past, I’ve always been too “chicken” to try running multiple versions of R on my work laptop, as I’ve usually got a few key analysis projects going that need to be delivered on time and within full feature scope - which means I don’t have time to fix basic version incompatibility bugs. I'm worried that the macOS R is inexplicably slow.You’d have to be living under a rock in the R community to not be aware of the fact that R 4.0 has been released, with some major changes, the biggest of which is probably the new default for read.table(): stringsAsFactors = FALSE, as well as the fact that matrix() now converts character columns to factors and factors to integers. On Ubuntu or Fedora, using OpenBlas on theThinkpad, the results are similar to Windows. Windows uses Microsoft R Open and that may explain the difference. The computations are much quicker: > system.time(crossprod(X)) stats graphics grDevices utils datasets methods Running under: Windows 10 圆4 (build 19042) Under Windows using my Thinkpad E 580 it is a whole different story: R version 4.0.2 () It seems to me that R uses Apple Acclerate framework's BLAS libraries, but the benchmarks are similar: > system.time(crossprod(X)) Interestingly, the sessionInfo has different output in R Console: > sessionInfo()īLAS: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRblas.dylib The results from the benchmark are: > N M X system.time(crossprod(X)) Loaded via a namespace (and not attached): stats graphics grDevices utils datasets methods base LAPACK: /Library/Frameworks/R.framework/Versions/4.1-arm64/Resources/lib/libRlapack.dylib Platform: aarch64-apple-darwin20 (64-bit) Let's start with the Mac: > sessionInfo() The results on my MacBook Pro with the M1 chip look disturbing to me. and native Apple silicon support to dome some benchmarks against other platforms. ![]()
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