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#RStudio

2 posts2 participants0 posts today

I have been exploring writing #Python in the somewhat new #PositronIDE from the #RStudio developers, and it seems like it could overtake my beloved #SpyderIDE as a daily driver.

It has an integrated IPython console working out of the box, which has been a massive pain to get working properly on other #VSCode derivatives. Furthermore, RStudio and Spyder have a similar layout, so I do find this Positron layout with its plots and variables panels quite familiar and intuitive.

If you ever need it: Installing R and Rstudio on a Linux Debian machine: Hard to find a good installation guide. Here is one: r-bloggers.com/2022/08/take-th

R-bloggers · Take the RStudio IDE experimental support for arm64 architectures out for a spin | R-bloggersBasic Set Up and Dependencies Installing the RStudio IDE Final Comments Apple’s bet on the arm architecture with their M1 and M2 processors has had an interesting side effect, developers of mainstream software are now forced to support the arm64 architecture and, since they are already supporting macOS for Apple Silicon processors anyways, supporting Linux arm64 distributions is no longer that much of a burden for them. The RStudio IDE development team is not strange to this circumstance and they have been working on general arm64 support. Currently, they have made available experimental builds for the arm64 architecture (also known as aarch64) compiled for Ubuntu 22.04 (possibly compatible with Debian 12 as well) and since Ubuntu 22.04.1 LTS has official support for Raspberry Pi SBCs, I have decided to give it a try. If you are interested, join me in the installation process. Basic Set Up and Dependencies The first thing you need is a Raspberry Pi SBC (2/3/4) with Ubuntu 22.04.1 LTS installed and updated, make sure to update your system libraries before you start. sudo apt update sudo apt dist-upgrade Then, the most important dependency for RStudio is, unsurprisingly, the R language. You have some options for installing R in Ubuntu 22.04 (arm64), each one with its own pros and cons. You can install the R version that comes with Ubuntu standard repositories, which is 4.1.2, this is the easiest option but this version is a little old: sudo apt install r-base Another option is to compile the latest R version yourself (4.2.1 at the moment of writing), this is time-consuming but it gives you the most flexibility since you can choose options like compiling with BLAS and LAPACK: sudo apt install -y g++ gcc gfortran libreadline-dev libx11-dev libxt-dev \ libpng-dev libjpeg-dev libcairo2-dev xvfb \ libbz2-dev libzstd-dev liblzma-dev libtiff5 \ libssh-dev libgit2-dev libcurl4-openssl-dev \ libblas-dev liblapack-dev libopenblas-base \ zlib1g-dev openjdk-11-jdk \ texinfo texlive texlive-fonts-extra \ screen wget libpcre2-dev make cd /usr/local/src sudo wget https://cran.rstudio.com/src/base/R-4/R-4.2.1.tar.gz sudo su tar zxvf R-4.2.1.tar.gz cd R-4.2.1 ./configure --enable-R-shlib --with-blas --with-lapack #optional make make install cd .. rm -rf R-4.2.1* exit cd Just to rule this option out, for the time being, using a precompiled binary from the R4Pi project is not a viable option for this particular application, there is no arm64 R binary publicly available from them yet but the people from the R4Pi project have been kind enough to make a link available with an experimental arm64 binary for me to try out, sadly, it has been compiled for Raspberry Pi OS 64-bit which, at the time of writing, is based on Debian 11, and Ubuntu 22.04 is Debian 12 based so it is not compatible. I’ll update this section if things change in the future since it would be a very nice option. Sadly, no luck for me, since you compile for Bullseye, and the RStudio experimental builds are compiled for Ubuntu 22.04 (Debian 12) there is a problem with a library version mismatch (https://t.co/OXm5tpcAxa.67). I'll wait for a Debian 11 compatible build, fingers crossed!— Andrés Castro (@Andresrcs) August 22, 2022 The experimental RStudio IDE builds do not come with Pandoc nor Quarto bundled since they do not offer official support for arm64. Pandoc you can easily install from the Ubuntu repositories and the IDE will recognize the system version automatically: sudo apt install pandoc pandoc-citeproc Quarto is a different story, the problem with it is that one of its dependencies, Deno (and its Deno DOM plug-in) is not available for arm64 because of the lack of arm64 GitHub Actions runners which makes CI/CD workflows unpractical. I have tried using an alternative source for the Deno binary but I can’t find an alternative source for the Deno DOM plug-in so I guess we will have to live without Quarto capabilities on arm64 for the time being (or if you are more clever than me you can find out a way around this and share with the rest of us). Lastly, for installing the RStudio IDE deb file, as you would do on an x86_64 system, you might want to install gdebi: sudo apt install gdebi Installing the RStudio IDE Now we get to the point, there is no stable release of the RStudio IDE for arm64 but there are experimental daily builds available here, both for the server and desktop versions, I’m going to try out the server version because I prefer to work with the IDE on my regular computer instead of directly on the Raspberry Pi but you can install the desktop version the same way if you prefer, just change the link accordingly. wget https://s3.amazonaws.com/rstudio-ide-build/server/jammy/arm64/rstudio-server-2022.11.0-daily-123-arm64.deb sudo gdebi rstudio-server-2022.11.0-daily-123-arm64.deb Once the installation process is completed, you get a working RStudio IDE installation running on your Raspberry Pi, if you have chosen to install the server version as I did, you can open an RStudio session by opening a browser on any device in your network and typing the proper address i.e. http:\your_pi_ip_addres:8787 Final Comments Have in mind that these are experimental builds of the development version of the RStudio IDE and they are likely to be unstable and buggy so do not trust this for any sort of critical job. Currently, the experimental builds are for Ubuntu 22.04 only and they are believed to be compatible with Debian 12 out of the box (not confirmed yet) but they are looking into building for older Ubuntu LTS releases (Based on Debian 11) which might make them compatible with the latest Raspberry Pi OS x64 version. You can follow along with the progress on this GitHub issue. Performance on the Raspberry Pi is acceptable, within reason for under-powered systems like these SBCs, but it is pretty far from the performance you would get on more powerful systems like Apple Silicon or full-size arm64 computers, if you have access to one of those. I hope you found this article useful, I will be updating the content as things develop, especially if installation on Raspberry Pi OS 64-bit becomes a viable option.

Digitizing Water Quality Data Collection with Posit and Esri Integration

Webinar - This Friday! June 27, 1pm ET

The VA Dept of Environmental Quality (DEQ) will cover their integration of Posit and Esri to modernize data collection methods for water quality monitoring.

Sign up now!

r-consortium.org/webinars/from

Continued thread

Well, fuck me. The new method to order contours fails in other simpler cases. Going back to the old well-tested one. Hopefully because the ordering now happens before projection, this will also fix the previos bug.

Are you doing #GeoSpatial #Statistics in #RStats :rstats: ?

A common operation is to get the adjacency matrix, or neighbour list of the regions using {spdep} and {sf}.

But: often there are islands or unconnected regions. This is a problem for the statistical models! And it's really annoying to fix when you have many regions.

Presenting {sfneighbourconnector}: an #rstudio add-in to manually add connections to the neighbour list through a point-and-click interface. github.com/vankesteren/sfneigh