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.
Related
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.
I have been using RDCOMClient for a while now to interact with vendor software. For the most part it has worked fine. Recently, however, I have the need to loop through many operations (several hundred). I am running into problems with the RDCOM.err file growing to a very large size (easily GBs). This file is put in C: with no apparent option to change that. Is there some way that I can suppress this output or specify another location for the file to go? I don't need any of the output in the file so suppressing it would be best.
EDIT: I tried to add to my script a file.remove but R has the file locked. The only way I can get the lock released is to restart R.
Thanks.
Setting the permissions to read only was going to be my suggested hack.
A slightly more elegant approach is to edit one line of the C code in the package in src/RUtils.h from
\#define errorLog(a,...) fprintf(getErrorFILE(), a, ##__VA_ARGS__); fflush(getErrorFILE());
to
\#define errorLog(a, ...) {}
However, I've pushed some simple updates to the package on github that add a writeErrors() function that one can use to toggle whether errors are written or not. So this allows this to be turned on and off dynamically.
So
library(RDCOMClient)
writeErrors(FALSE)
will turn off the error logging to the file.
I found a work around for this. I created the files C:\RDCOM.err and C:\RDCOM_server.err and marked them both as read-only. I am not sure if there is a better way to accomplish this, but for now I am running without logging.
I just spent an infuriating day trying to make a gif out of a series of jpg files in R. I installed ImageMagick to run the following code:
system("convert -delay 40 *.png example_4.gif")
but I get the following error message:
Warning message:
running command 'convert -delay 40 *.png example_4.gif' had status 4
which looks like a path error. Now I've looked for convert in the Imagemagick download and can't see it anywhere. Does anyone know where it is?
Alternately, is there another easier method of making a gif from a series of jpegs in R that isn't ridiculously long?
Thanks
Three options:
Consider using the magick R package instead of using system().
Change your script from convert ... to magick convert ....
Re-install imagemagick, and enable the "Install legacy utilities (e.g. convert)" option.
This change has been around since 7.0.1 (now up to 7.0.7), and is discussed in their porting guide, specifically in the section entitled "Command Changes".
Philosophically, I prefer to not install the legacy utilities, mostly because it can cause some confusion with command names. For instance, the non-ImageMagick convert.exe in windows tries to convert a filesystem ... probably not what you want to accidentally trigger (there is a very low chance that you could get the arguments right to actually make a change, but it's still not 0). The order of directories in your PATH will dictate which you are calling.
EDITs:
From comments, it seems like the difference between "static" and "dll" installers might disable the option to install legacy utilities such as convert.exe. So you can either switch to the "dll" to get the legacy option, or you are restricted to options 1 (magick R package) and 2 ("magick convert ...").
From further comments (thanks to fmw42 and MarkSetchell), it is clear that the old convert.exe and the current legacy mode of magick.exe convert are not the same as the currently recommended magick.exe (without "convert"); the first two are legacy and compatibility modes, but they do not accept all arguments currently supported by magick-alone. So the use of "convert" anywhere in the command should indicate use of v6, not the current v7. This answer is then merely a patch for continued use of the v6 mechanisms; one could argue a better solution would be to use magick.exe's v7 interface, completely removing the "convert" legacy mode.
This is an issue I am encountering for different pieces of codes I am writing in R.
Basically, I would like to generate a window that displays a picture (a .png file). Following for instance guidances from this or this, I come up with this kind of code:
library(tcltk)
tmpFile <- tempfile(fileext = ".png")
download.file("https://www.r-project.org/logo/Rlogo.png", tmpFile)
tcl("image","create","photo", "imageLogo", file=tmpFile)
win1 <- tktoplevel()
tkpack(ttklabel(win1, image="imageLogo", compound="image"))
This works fine under Mac OS, but not on Linux nor on Windows, where I am displayed such an error message:
[tcl] couldn't recognize data in image file
I can find some workarounds when I want to display graphs, using for instance packages tkrplot or igraph. Nonetheless, I would be really eager to understand why I got such errors when running my scripts on Linux or Windows, whereas it works just fine on Mac OS.
Apologies in case this issue is obvious, but I haven't found anything about potential differences with the tcltk package depending on the OS.
Tk's native support for PNG was added in 8.6. Prior to that, you need to have the tkimg extension loaded into Tk to add the image format handler required. If your installation of Tcl/Tk that R is using is set up right, you can probably make it work with:
tclRequire("Img")
once you've initialised things sufficiently. Yes, the name used internally is “Img” for historical reasons, but that's just impossible to search for! (This is the key thing in this mailing list message from way back.)
However, upgrading the versions of Tcl and Tk to 8.6 is likely to be a better move.
Finally and a bit lately, I would like to close this issue and sum up the different suggestions that were kindly made in response of my question:
R comes along with Tcl 8.5, even with the latest version 3.3.2, which means that there is no way for embedding a PNG file with the usual command into a window created thanks to Tcl/Tk. For some reasons it is working on Mac OS, but do not expect this to work easily on other OSs.
In order to display pictures, graphs, etc. in a window generated by Tcl/Tk in R, better look for either using the GIF support (when possible) or trying alternative solutions (see the question for possible alternative options).
In case one really wants to display PNG files, the solution consists of installing Tcl 8.5 (for instance ActiveTcl) along with the extension Img. In order to use the Tcl/Tk package that you've just installed on your computer, you can refer to the R FAQ for Windows for instance (as stated in the FAQ, you need to install Tcl 8.5 - I tried with Tcl 8.6, thereby hoping to solve my issue, but it didn't work). Basically, you need to set up an environment variable (MY_TCLTK) and put the path where the package Tcl/Tk is installed. Needless to be said, Tcl/Tk is commonly used in R in order to implement GUIs; if you have to go through very complex procedures to set up the system, the package definitely loses its advantages.
Finally, since Tcl 8.6 should be available soon or later with R (already implemented in the devel version), this issue will be de facto outdated.
R noobie here.
I'm am trying to use a package that I download off of github using source_gist, but it appears that I need to re-download it every time I quit R (I'm using RStudio).
To clarify, the function that I'm using is part of plotrix package and is called barp. Someone made a modified version of it (called barp2) and put it up on github. That's what I want to use.
So my question is this: is there anyway to have this modified code saved inside the plotrix package, so I wouldn't have to download it every time?
I hope I'm explaining this correctly.
So, let's get some quick terminology straight: the function you're getting off of github isn't a package, it's just a single function. If it was a package, you could use devtools::install_github once and then load it with require() or library() like any other package.
A good solution isn't too different. Just go to the gist, copy the code, paste it into your R editor, and save it somewhere as a .R script file. Something like C:/path/to/barp2.R (adjusting, of course, based on where you actually want to keep it and based on your OS). Then you can read it locally using source("C:/path/to/barp2.R") instead of devtools::source_gist().
If you always want to load it, you could load plotrix and then source this file every time R starts with a couple lines in your R profile, see ?Startup as #BondedDust suggests for details on this.
Reading it off of github every time does have the advantage that, if the author fixes bugs or otherwise improves it, you'll always be using the up-to-date version. It has several disadvantages too: requiring an internet connection, losing access if the gist is deleted, or being unable to access old versions if the author changes it in a way you don't like. Keeping a copy of a version you like is a smart move.