I have Scilab code related my Ph.D Work, Now i want to create a toolbox so that it could be work in Scilab platform. My code contain the one .sce file(Main program) and several .sci files(Sub routines called in main program). Is it Possible to create toolbox which can be used later in other programs (like Command Syntax).
Just like Ex: print,disp,etc..
See the instructions in the Scilab Wiki : https://wiki.scilab.org/howto/Create%20a%20toolbox
Related
Similar to Rstudio, Atom allowed you to run code segments on interactively rather than the entire script all at once. Is there a suitable Julia language IDE that is comparable to rstudio or Atom (juno) and allows for on-the-fly execution of code blocks because Atom is being phased out?
note: Thanks for answers in vs code to obtain interactive feature hold ctrl + return will run code.
Did you try the Microsoft Visual Studio Code ? You can check how to download and setup for Julia notebook in link below.
https://github.com/julia-vscode/julia-vscode#installing-juliavs-codevs-code-julia-extension
The Best, Wr
In Microsoft VS Code you can define code cells using magic comments (## or # %% or #- can play this role - the choice is yours):
##
(your code goes here)
##
A code cell is executed by pressing Alt + Enter while the cursor is inside the cell.
At the code below I pressed Alt + Enter while being in line 10.
The keyboard shortcut can be configured by selecting in the main menu View->Command Palette or pressing Ctrl + Shift + P:
VSCode. The Julia team was working on a Julia IDE called Juno but the website now says "Juno will receive no more feature updates. Development focus has shifted to the Julia extension for VSCode", and VSCode seems to be the recommended way to develop in julia.
The Julia extension for VSCode let's you run code block by just pressing shift+enter and it uses Revise.jl to make interactive sessions better. You can see plots and other outputs right in the editor, and recenty they have even added performance monitoring/benchmarking tools.
However, if you prefer notebook-style workflows, you can use Jupyter with Julia (and the IJulia kernel) but even better imo is Pluto, which is specifically made for Julia and has some nice features such as no hidden state.
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.
Is it possible to run something similar to a Linux R console (which uses GNU Readline) from within a C++ program using RInside? The best option would be, if such a console would have all the nice features like the autocomplete.
The background:
I have a big solver, which has a RInside-based plugin for running small chunks of R code during a simulation. It would be nice if the user would be able to switch it to "interactive" mode and check things out as they go.
Notice:
1. I cannot just run R as a separate program, as I need it to see my objects and pointers from the main code. 2. I know about callbacks in RInside, but they do not provide any console-like capabilities.
Code: I doubt it will help, but here is my code now: https://github.com/llaniewski/TCLB/blob/RInside/src/Handlers/cbRunR.cpp.Rt
can someone tell me, where i can find the source-codes contained in the IDL-Directory.
In IDL one can run "demo". Under "Math and Statistics" -> "Math and Statistics Demo", there is as an example a polynomial fit. Where is the source-code for this polynomial fit contained within the idl directory?
best regards
So your answer has several parts. You can find the "demo" source code in your IDL installation, inside examples/demo/demosrc. If you want the source code to the actual polynomial fit routines, those will either be in source code inside the "lib" directory, or they might be written in C code for speed. The documentation will tell you if it is written in pro code.
For pro code routines, once you've compiled the routine, you can always use the "routine_filepath" command to find the source code location. Hope this helps!
Is is possible to change the "Control + R" shortcut for sending scripts from the R text editor in the Windows GUI to the R console? I'd like to change it to "Control + Enter" to be more like the shortcut on my Mac. I do all my normal work on a Mac but have to use R on a PC to interface with some PC-only computational software.
Additional tidbits:
I'd rather not run an IDE on the PC if I don't have to, though perhaps this is the solution.
I use Rstudio on my Mac, but Rstudio does not get along with the PC software I'm running
The short answer is:
"No, there are no [built-in] ways to alter the menu shortcuts in the R Console"
I'm however gathering here -community wiki style- some of suggestions posted as remarks to this questions.
One approach may be to download the R source, hack it (see circa line 625 of src/gnuwin32/editor.c: ), and build the R binary anew (see the R for Windows FAQ for the tools you need to build from source). This seems to be a rather radical approach for the mere convenience of using an alternate keystroke sequence...
A similar approach may be to create an automatic patcher program which would patch the R executable, by locating the byte patterns surrounding the compiled logic of editor.c mentioned above and replacing it with a byte sequence for the desired keystroke. This solution may be sensitive to changes in the binaries, but also avoids the build process altogether...
An easier way to achieve this is probably by using an external text editor. Most modern editors have macros or configs that can be used, for example, to execute a source command in R for the selected text.
Customizing keyboard shortcuts is made available in Rstudio 0.99.644.
See https://support.rstudio.com/hc/en-us/articles/206382178-Customizing-Keyboard-Shortcuts for more information.