Software
The tag tool kit originated in matlab, so many of the file in/out and calibration tools will be translated from matlab to octave and R. Matlab is paid software (you need a license to install it). Getting started in Matlab:
- https://www.mathworks.com/support/learn-with-matlab-tutorials.html (requires a mathworks account)
- https://www.tutorialspoint.com/matlab
Octave is being developed as a free alternative to matlab. Its capabilities have really matured recently, and in it you can use nearly exactly the same code as in matlab to achieve the same results.
You can download the software at https://www.gnu.org/software/octave/.
Some online tutorials are available:
R is free statistical computing software. We will use it via the RStudio IDE.
First, install R from https://cran.r-project.org/. Then, install RStudio from https://www.rstudio.com/products/rstudio/download2/ -- the Desktop, open-source version.
There are some more detailed installation instructions available, too.
Some tutorials for getting started in R via RStudio:
- Tutorial: R basics from Calvin STAT courses
- Tutorial: R programming from RStudio Education
- Video: using RStudio
- Our tools are stored in the form of an R package. This video introduces writing packages in R.
- Many resources are linked at https://www.rstudio.com/online-learning/ -- R programming, R markdown, and Shiny may be useful to us in this project.
We will use GitHub for version control on the tag tools software. There are plenty of resources online about using Git. You can use it via the command line, but for starters I suggest you access it via RStudio. Here are some tips and resources for getting started:
- #1 Resource: Happy git with R
- Blog about RStudio and github integration
- An introduction to Git and how to use it with RStudio
- Learn Git Branching has a nice interactive tutorial that explains how git branches work. This is more than you need to know to get started with git (especially if you are working in RStudio), but it helps clarify what git is actually doing and is very helpful when you get into tricky situations or want to roll back to old versions, etc.
Our tagtools will be bundled together in an R "package". This requires a lot of specific documentation and formatting so that it meets the standards of CRAN, the organization that manages and distributes R packages to users. There is a great online reference that can help guide you through the process of creating (and adding to) an R package: