I've tried Araxis merge and it's good to use. However it is too costly.
I need only file and folder diff. I also need merge for two files.
Although this Wikipedia page lists all of the free tools but it is really difficult to conclude which tool will be best.
I'm curious which is the most recommeded free merge tool for Drupalians!
I'm not sure Drupalian have specific needs merging-wise compared to other web makers :D
Try Kdiff3 ( http://kdiff3.sourceforge.net/ )which is dead simple.
Sorry I talked about opendiff which I use on my mac but it doesn't seem to be available for windows. But if you are on mac it is part of the original install.
Command-line diff (together with colordiff), vimdiff, emacs has quite good implementation as well...
Related
I would like to learn programming for CNC lathes.
First, what open-source programs (similar BobCAD-CAM) would be best?
Second, what is the best way to proceed in learning to use the programs?
I look forward to learning the answers to my questions. Thank you!
There are a few good free CAD/CAM programs you can get off the net, just look on google. Personally, I recommend using Featurecam or Mastercam ( although neither are free, but they are good programs.)
As for learning to program, this website has a lot of useful information http://cnc-programming-by-gord.blogspot.com/2012_07_01_archive.html
I hope it helps you like it helped me.
Autodesk Fusion is free for hobby users. It allows you a full CAD/CAM package with loads of tutorials online and on Youtube. for simulation OpenSCAM will allow you to check on your code. Some of the fancier live tooling lathes have some machine specific stuff on them but in the end a solid knowledge of G-code will help decipher it.
#1, you need to know which lathe & which controller you want to program. Then get the manuals for it. Some G & M codes are similar across many machines, but not all of them. So, get the proper programming manual for the exact machine.
#2, research the CAM software you want to learn. Are there certain shops you want to work at? Well then, what do they use? Research the most popular packages in your area. Figure that out & then learn the specific software. Otherwise, you're wasting your time.
Depending on what you pick, there are videos out there to give you a good idea of how they work. Re-sellers offer classes. Some websites have tutorials & manuals. Again, don't waste your time learning something you might not even use. Even after you pick something, the different versions of it have proven to be very different. So be sure you're learning the right software & the right version.
This question is inspired by the remark of Duncan Murdoch on the r-devel mailing list in response to a bug report about Sweave :
This is fixed in R-patched. (It would
have been fixed in 2.12.0 if more
people tested the betas...).
Honestly, I've stayed away from beta -aka development- versions for a number of reasons, and these are reasons I hear from more people :
I am a bit horrified it would
somehow cause conflicts with my
current R distribution. As I need it
for work, having to repair it regularly would be a loss of
time I can't explain to my boss
I wouldn't have a clue how to test
efficiently. I reckon every test I
could come up with has already been
run by the development team.
I still find it difficult to figure
out when something is a bug, and
when (most often) it is my own
stupidity kicking in.
But as I understood, it would be a valuable contribution to the R community, and I'm willing to do my bit of the testing as well if I can fit it somehow into my own work. I was thinking of keeping the beta on the side and running my scripts through it as well as a checkup. Saving the constructed objects allows a quick and easy all.equal() to see if something is wrong.
Anybody some more/better ideas on how I could help testing with a minimum amount of effort and a maximum amount of efficiency?
I'd also like to promote this a bit more on our department as well. Apart from the "It's time to give back to the community", any other good reasons why testing betas is worth the effort? How can I counter the arguments given above?
Edit:
As Dirk Eddelbuettel pointed out in the comments, part of the deal is preventing the path variables in Windows. I have some ideas on that, but pointers on how to practically organize your computer for testing R-devel versions are greatly appreciated as well.
I fear you misunderstand. This may not be straightforward or obvious at first so maybe this helps:
"patched" is not "beta". Patched is what R 2.12.1 will be.
There is no conflict. It drops in for 2.12.0.
It is a separate download, and a nightly build available from here.
This is not r-devel but r-patched.
It is our duty as users to test pre-releases as well. So if anything, in an ideal word you would have R-patched installed --- as well as R-devel!
Testing can be as easy as installing another version, keeping it outside your path and then adjusting PATH and R_HOME dynamicaly from a script. Testing means running it on your code and data to prevent you from getting bitten by bugs once the new code is released.
I wouldn't have a clue how to test efficiently. I reckon every test I could come up with has already been run by the development team.
I still find it difficult to figure out when something is a bug, and when (most often) it is my own stupidity kicking in.
The problem is, software is not (or not only) going to be used by developers. It is going to be used by people that may not have programming knowledge at all (I'm speaking generally, this is valid for R as well as for any other software).
If the help or the interface or the general way the software is built do not give you enough informations on how to do something, well, that is maybe not a bug, but it is something that can be improved (and pointed out to the devs).
Also, remember that the developers wrote the software. They know how to use it and often they will be biased in testing it mainly by using it correctly and see if it gives the good result rather than by "trying to break it".
By using it in YOUR way (which may possibly be "uncorrect"), you are effectively running tests that maybe escaped the developers, just because they were not thinking of using it like you did.
Occasionally I see small ways I could improve either R (recently the IQR command) and R documentation (just this week perhaps elaborating differences among and better interconnecting aggregate, tapply, and by). But I don't see a way to really make that contribution back. I looked into the developer site and it seems that my options are either to attempt to become a full fledged developer or create packages, neither of which fit what I wish to accomplish.
I did propose IQR changes on the R mailing list but got no response so I figure that's going nowhere.
And to clarify, I'm talking about base-R. Additional packages are another matter.
Any tips?
Send (or CC) to r-devel. Traffic is quite high on r-help, and things can be overlooked there.
File a bug under the wishlist category detailing the improvement you would like to see.
Having filed the bug, try to provide a patch against the R code and or documentation as appropriate. I've done this before where there was a problem or infelicity in R, supplied a patch and a fix to the help files/manual and had the changes accepted (after suitable modification) by R Core.
If it is an addition to the R code base, you are going to have to show that there is a real pressing need for the addition. Basically you are asking R Core to maintain your code in perpetuity, and they are unlikely to do that unless you can demonstrate a need.
If it is an addition, look for a popular R package that does similar/related things and suggest to the package maintainer that they include your function. That way you don't need to start a whole package for something simple but contribute your code. There are several, popular, *misc packages on CRAN for example.
If you want to contribute fixes to the R documentation and/or manuals, provide patches to the sources. You can find the sources at svn.r-project.org/R
Hopefully that gives you some ideas. Patches and code always help!
How about patches to existing packages?
How about open bug reports on packages? R-Forge projects don't seem to use the issue trackers much, but some folks on the RPostgreSQL team I'm on enabled it (where it is hosted on Google Code), and it has been helpful -- see here. And we had a really useful inflow of fresh blood with a rocking new developer from Japan, probably in part because of the visibility of the project there.
In essence, try to find a project / group / team to become acquainted with and join. In that sense, this is just like any other Open Source project. The r-devel list (gmane view) is a good place for R development in general.
The R Core team, on the other hand, is a little more closed and per invitation only and unlikely to change. So be it, for better or worse. It has worked so far, and hence I am not among those who bemoan this loudly.
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What good IDEs are there for R in Linux?
I've tried Rcmdr and Eclipse, but neither seems to have the same usability as Tinn-R in Windows. Are there any other options?
A newcomer to the scene, which IMO looks very promising - and downright baller - relative to other existing IDEs like Rattle and JGR, is RStudio. It's free software, is cross-platform, looks very polished, and even has features like automatic refactoring.
Update 2012-04-12: I've been running it for a bit on our DB server, and I love that it's a web app that saves your sessions, resume-able from anywhere else. Plotting requires not only no X tunneling or png-writing but is easier to use than out-of-the-box R. Extremely easy to get up and running, and it comes with packages for Debian/Ubuntu (which I use).
The company/development is moving pretty fast, aiming to be the de facto standard IDE for all R users. If I'm gushing, it's probably because I was pleasantly surprised by the quality of the IDE after a long time of using sub-par IDEs, not just for R but for plenty of other languages. So this was a bit out of the blue. I still need more time to really dig into it but I like what I'm seeing so far.
JGR isn't bad:
http://rforge.net/JGR/
Most people I know rave about Emacs + ESS:
http://ess.r-project.org/
But it's not quite the same thing as Tinn-R.
Along different lines ...
If you're looking at a high level functions for data mining, then Rattle is an option:
http://rattle.togaware.com/
and another high level app for interactive plotting:
http://code.google.com/p/playwith/
I have found that the Emacs-ESS combination is well worth the learning curve. I enjoy being able to:
have code and R console side by side
send the current line, paragraph, file, or function to the R console without touching the mouse
easily interact with R sessions on remote computers
enjoy all the editing abilities of Emacs
Here's the website for the project:
http://ess.r-project.org/
Here's a helpful document about ESS in particular:
http://www.demog.berkeley.edu/Refs/ess.pdf
Brand new IDE out there (as of Feb 2011) is http://www.rstudio.org/. Seems very promising from what I've seen so far.
Although Eclipse was mentioned by the OP, I do not know if he ment it with the StatET plugin.
Eclipse with StatET is a really great IDE besides e.g. EmacsSpeaksStatistics (ESS), but as in other environments the user have to learn it's the basic usage first. The only handicap of this IDE could be the relatively high resources requirements as based on Java, but this makes the program OS independent of course.
Why I really would suggest to take the time to learn use StatET efficiently (cauction: very subjective list!):
be able to run your code really fast and easily with comfigurable shortcuts (by Ctrl+r by default),
thanks to the script editor and running environment is heavily integrated, debuging and reviewing your code cannot be easier,
configurabled environments by default (e.g.: R scripts),
you may define templates for frequent commands and those's environment (e.g.: loop, if conditions etc),
highly customizable syntax highlight,
TeXlipse integrated to view and edit tex code with ease (LaTeX support for Eclipse),
Roxygen support for literate programming (very handy at package development to automatically generate Rd files (manuals) from inline comments),
easily extendable with othet Eclipse plugins (e.g.: spell checking, (SQL) database management, image viewer, running external programs like Sweave).
A nice guide to read is A Guide to Eclipse and the R plug-in StatET by Longhow Lam.
Gedit + RGedit plugin + Snippets plugin
You've suggested eclipse; there is a plugin called StatEt which work quite well (even Sweave is supported!).
There is a KDE 4 based IDE called RKward. It's nice because of:
Workspace Browser
Integrating the R console
data.frames editor
Syntax colored editor
GUI frontend for installing CRAN packages
For my case, I would recommend RKward for linux, it is a KDE. I've been using RStudio in Windows, but when I switched to Ubuntu, I find RKward easy to use, and has a good interface.
You can create a data frame without coding it with data.frame() function.
If you are used to Eclipse, StatET (mentioned by mbq) is probably the right choice for you.
That being said I have a more exotic choice to offer that you might want to consider, if you like auto suggestion and pure syntax highlighting is not enough for you. At least for me auto completion of R-Code did not work with StatET.
Now I use Komodo Edit with Sciviews-K and R64. Sending Code from editor to R works really well and the editor offers auto-completion for R-Code which is really nice – in particular if you are new to R. I work on a Mac, but it should be easy to setup for Linux too.
I think it has lost some popularity because it wasn't to stable in the past, but at I feel it's much better now and it hardly crashes in my setup. So you might wanna give it a chance too.
EDIT: If you work on Mac Textmate with the corresponding R bundle might be interesting, too. Recently I am about to switch to Textmate. If you don't care about the $45 for textmate, it's probably the most stable choice I tested so far. But it's only available on a Mac. But hey I am really amazed by this editor (and as you can see I like testing setups ;).
EDIT: I realize this thread is still being read by someone, so I definitely need to mention RStudio. It came out of nowhere and quickly became the choice of a lot of people. And it's well deserved. It still has some bugs (like not being able to stop RSessions) but it has tremendous auto-complete with context help. But at least on my setup (Mac) it's more stable than StatET / Eclipse. Sweave and ROxygen is not really supported yet, but the developers are very active. Definitely worth trying.
EDIT II: Because it's fun to track this here's another edit. RStudio continues to win more and more users. The combination of RStudio, Roxygen2 and particularly knitr integration has likely been the largest contribution to this development. While Rstudio was rather used by applied users and in teaching and has improved to dramatically that there's isn't many situations in which another IDE / editor is a better choice. Being maried to ESS seems like to only valid reason left to not use it. Also the documentation of its ecosystem is just great. The latest: Package development by Hadley http://r-pkgs.had.co.nz/description.html and his advanced programming http://adv-r.had.co.nz/
I strongly recommend learning emacs+ess, but for a more modern-looking interface you can try RKward: http://sourceforge.net/apps/mediawiki/rkward/index.php?title=Main_Page.
I use Geany in combination with R. Geany provides a terminal in which one can start an R session and shortcuts an be defined in order to send highlighted text to the terminal.
www.geany.org
RGedit, great tool if you're keen on GNOME default text editor. Lacks autocompletion in script mode, though... but you can define snippets in a separate plugin (Snippets)... You can send code directly to R session running in the terminal window, tabbed multiple R sesions, there are several GUI templates for common data analysis (t-test, correlation), long story short, take a look at:
http://sourceforge.net/projects/rgedit/
Few months ago (when I gave my blogging skills a try), I wrote a review for RGedit, here's a link (and a little bit of self-advertising):
http://psy-stat.com/?p=12
EDIT:
Oh, and you can use Geany and set it up so you can send code chunks to R session... I've never done it, but I know it's manageable!
EDIT #2:
here's a helpful link: http://sgsong.blogspot.com/2010/08/integrating-r-with-geany.html
This might be what you're looking for. It integrated Komodo and the SciViews package. I found it a bit too fiddley (I prefer vi) but if you're looking for a full blown IDE/editor for R in Linux it's pretty close to Tinn-R for Windows and it's written by the same guys!
Link:
http://www.sciviews.org/SciViews-K/index.html
Rattle: http://rattle.togaware.com/
Emacs with ESS. Probably not as polished as Eclipse, but I do like it.
Personnaly, I use gedit and my console. It works great :)
Are there any real world applications written in the Clean programming language? Either open source or proprietary.
This is not a direct answer, but when I checked last time (and I find the language very interesting) I didn't find anything ready for real-world.
The idealist in myself always wants to try out new languagages, very hot on my list (apart from the aforementioned very cool Clean Language) is currently (random order) IO, Fan and Scala...
But in the meantime I then get my pragmatism out and check the Tiobe Index. I know you can discuss it, but still: It tells me what I will be able to use in a year from now and what I possibly won't be able to use...
No pun intended!
I am using Clean together with the iTasks library to build websites quite easy around workflows.
But I guess another problem with Clean is the lack of documentation and examples: "the Clean book" is from quite a few years back, and a lot of new features don't get documented except for the papers they publish.
http://clean.cs.ru.nl/Projects page doesn't look promising :) It looks like just another research project with no real-world use to date.
As one of my professors at college has been involved in the creation of Clean, it was no shock he'd created a real world application. The rostering-program of our university was created entirely in Clean.
The Clean IDE and the Clean compiler are written in Clean. (http://wiki.clean.cs.ru.nl/Download_Clean)
Cloogle, a search engine for Clean libraries, syntax, etc. (like Hoogle for Haskell) is written in Clean. Its source is on Radboud University's GitLab instance (web frontend; engine).