plotting data in R from matlab - r

I was wondering if it is possible to work between matlab and R to plot some data. I have a script in matlab which generates a text file. From this I was wondering if it was possible to open R from within matlab and plot the data from this text file and then return to matlab.
For example, if I save a text file called test.txt, in the path 'E:\', and then define the path of R which in my case will be:
pathR = 'C:\Program Files\R\R-2.14.1\bin\R';
Is it possible to run a script already written in R saved under test1.R (saved in the same directory as test.txt) in R from matlab?

If you're working with Windows (from the path it looks like you are), you can use the MATLAB R-link from the File Exchange to pass data from Matlab to R, execute commands there, and retrieve output.

I don't use R so this is not something I have done but I see no reason why you shouldn't be able to use the system function to call R from a Matlab session. Look in the product documentation under the section Run External Commands, Scripts, and Programs for this and related approaches.
There are some platform-specific peculiarities to be aware of and you may have to wrestle a little with what is returned (though since you are planning to have R create a plot which is likely to be a side-effect rather than what is returned you may not). As ever this is covered quite well in the product's documentation

After using R(D)COM and Matlab R-link for a while, I do not recommend it. The COM interface has trouble parsing many commands and it is difficult to debug the code. I recommend using a system command from Matlab as described in the R Wiki. This also avoids having to install RAndFriends.

Related

Very simple question on Console vs Script in R

I have just started to learn to code on R, so I apologize for the very simple question. I understand it is best to type your code in as a Script so you can edit and save it. However, when I try to make an object in the script section, it does not work. If I make an object in the console, R saves the object and it appears in my environment. I am typing in a very simple code to try a quick exercise on rolling dice:
die <- 1:6
But it only works in the console and not when typed as a script. Any help/explanation appreciated!
Essentially, you interact with R environment differently when running an .R script via RScript.exe or via console with R.exe, Rterm, etc. and in GUI IDEs like RGui or RStudio. (This applies to any programming language with interactive compilers not just R).
The script does save thedie object in R environment but only during the run or lifetime of that script (i.e., from beginning to end of code lines). Your code line is simply an assignment of object. You do nothing with it. Apply some function, output results, and other actions in that script to see.
On the console, the R environment persists interactively until you quit it with q(). So assigned objects remains for lifetime of your console session. After assigning, you can afterwards apply function, output results, or other actions in line by line calls.
Ultimately, scripts gathers all line by line code in advance of run for automated execution without relying on user to supply lines. Imagine running 1,000 lines of code with nested if/then or for/while loops, apply functions on console! Therefore, have all your R coding needs summarily handled in scripts.
It is always better to have the script, as you say, you can save edit correct, without having to rewrite the code to change a variable or number.
I recommend using Rstudio, it is very practical and will help you to program more efficiently and allows you to see, among other things, the different objects that you have created.

Are there any good resources/best-practices to "industrialize" code in R for a data science project?

I need to "industrialize" an R code for a data science project, because the project will be rerun several times in the future with fresh data. The new code should be really easy to follow even for people who have not worked on the project before and they should be able to redo the whole workflow quite quickly. Therefore I am looking for tips, suggestions, resources and best-practices on how to achieve this objective.
Thank you for your help in advance!
You can make an R package out of your project, because it has everything you need for a standalone project that you want to share with others :
Easy to share, download and install
R has a very efficient documentation system for your functions and objects when you work within R Studio. Combined with roxygen2, it enables you to document precisely every function, and makes the code clearer since you can avoid commenting with inline comments (but please do so anyway if needed)
You can specify quite easily which dependancies your package will need, so that every one knows what to install for your project to work. You can also use packrat if you want to mimic python's virtualenv
R also provide a long format documentation system, which are called vignettes and are similar to a printed notebook : you can display code, text, code results, etc. This is were you will write guidelines and methods on how to use the functions, provide detailed instructions for a certain method, etc. Once the package is installed they are automatically included and available for all users.
The only downside is the following : since R is a functional programming language, a package consists of mainly functions, and some other relevant objects (data, for instance), but not really scripts.
More details about the last point if your project consists in a script that calls a set of functions to do something, it cannot directly appear within the package. Two options here : a) you make a dispatcher function that runs a set of functions to do the job, so that users just have to call one function to run the whole method (not really good for maintenance) ; b) you make the whole script appear in a vignette (see above). With this method, people just have to write a single R file (which can be copy-pasted from the vignette), which may look like this :
library(mydatascienceproject)
library(...)
...
dothis()
dothat()
finishwork()
That enables you to execute the whole work from a terminal or a distant machine with Rscript, with the following (using argparse to add arguments)
Rscript myautomatedtask.R --arg1 anargument --arg2 anotherargument
And finally if you write a bash file calling Rscript, you can automate everything !
Feel free to read Hadley Wickham's book about R packages, it is super clear, full of best practices and of great help in writing your packages.
One can get lost in the multiple files in the project's folder, so it should be structured properly: link
Naming conventions that I use: first, second.
Set up the random seed, so the outputs should be reproducible.
Documentation is important: you can use the Roxygen skeleton in rstudio (default ctrl+alt+shift+r).
I usually separate the code into smaller, logically cohesive scripts, and use a main.R script, that uses the others.
If you use a special set of libraries, you can consider using packrat. Once you set it up, you can manage the installed project-specific libraries.

Debugging code in R Markdown

I've been playing a little bit with R Markdown and I really like it, because after each of my analyses I need to write a (Word) report detailing the results. With R Markdown, the code and report are the same document, so it's easy to remember that I chose to perform analysis B at a certain point in the code, because of the results of analysis A before.
However, I'm not able to set breakpoints in R Markdown inside R Studio, and this limits severely the possibility of performing efficient debugging. This implies that in the end I can only use Markdown for very trivial analyses, where the R code is so simple that either I don't have to debug it, or I can debug it manually. It this to be expected, i.e., is it well-known that R Markdown can only be used for simple analyses? Or is there a solution?
You can use browser() in your code to set breakpoints. See https://support.rstudio.com/hc/en-us/articles/205612627-Debugging-with-RStudio#debugging-in-r-markdown-documents
I've find it more useful to write custom functions in a .R and source() it in Markdown. Then, you get the best of both worlds.
You can generate Word and other reports from normal R scripts using knitr::spin in combination with special roxygen2-style comments. Then you can run your script and use breakpoints as normal.
https://rmarkdown.rstudio.com/articles_report_from_r_script.html
There's also a toolbar button in RStudio to do this.

How to keep various-topic R script at hand?

I have written and collected R code on various topics that solve particular problems at hand. I stored the R script/code in .txt files. I have now 100s of them.
How do you keep your R code at hand efficiently?
#Manetheran has the right idea: write a package. It's easy to do (especially with RStudio). Read "Writing R Extensions" and then on top of that learn about roxygen2 (which allows you to document each function in-line and avoid writing .Rd files).
Then you can use devtools to load your package locally, or once it's stable if you think other people can use the functions you can submit your package to CRAN.
I prefer to keep it simple. I use Total Commander and when I need an example which uses some R function, I just do Alt-F7 and search for *.R files which contain the desired string.
I use RStudio and have created two or three basic scripts. I save my much-used functions in the basic script that is most appropriate. Then, at the start of an RStudio script for a project, I source one or more of the basic scripts as is appropriate.

R2PPT crashes R; are there alternatives to R2PPT?

I am attempting to automate the insertion of JPEG images into Powerpoint. I have a macro done for that already, except using R would be infinitely better for my purposes.
The package R2PPT should do this, I understand. However, I cannot use it. For example, when I try to use PPT.Open, I understand I can do it two different ways by calling method = "rcom" or method = "RDCOMClient". Using the latter, R will always crash, sending an error report to windows. Using the former, it tells me I need to install statconnDCOM , before giving the error:
Error in PPT.Open(x) : attempt to apply non-function.
I cannot install statconnDCOM freely, as I wouldn't call this work non-commercial. So if there isn't a way to get around this issue, are there at least some free alternatives to R2PPT so that I can save several hours of manual work with a simple R code? If there is a way for me to use R2PPT, that would be ideal.
Thanks!
Edit:
I'm using R version 2.15 and downloaded the most recent version of R2PPT. Powerpoint is 2007.
Do you have administrative privileges on this machine?
There is an issue with package RDCOMClient. It needs permissions to write file rdcom.err in the root of drive C:. If you don't have privileges to write to c:, there is a rather cumbersome workaround:
Close R
Create "c:\temp" folder if it doesn't exist.
Locate on your hard drive file rdcomclient.dll. It usually placed in \R\library\RDCOMClient\libs\i386\ and in \R\library\RDCOMClient\libs\x64\ (you need to patch file which corresponds your Windows version - 32 bit or 64 bit). It's recommended to make backup copy of this files before patching.
Open rdcomclient.dll in text editor (Notepad++, for example -http://notepad-plus-plus.org/)
Find in file string c:\rdcom.err - it occurs only once.
Go into overwrite mode (usually by pressing "Ins" key). It is very important that new path will have the same number of characters as original one. Type C:\temp\e.rr instead of c:\rdcom.err
Save the file.
Now all should work fine.
Arguably not an answer, but have you looked at using Sweave/knitr to render your presentations in LaTeX using something like Beamer? (As discussed on slide 17 here.)
Wouldn't help any with getting JPGs into a PowerPoint, but would certainly make putting R-output (numerical or graphical) into a presentation much easier!
Edit: if you want to use knitr (which I recommend), here's another reference.

Resources