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SciRuby: Science and Matrix Libraries For Ruby
Aciel writes "Ruby has long been popular in the web/business community, while Python dominates the scientific community. One new project seeks to bring balance to the force: SciRuby. We've already introduced a linear algebra library called NMatrix (currently alpha status). There's at least one fellowship available for students interested in working on the project this summer."
*cough* bullshit *cough*
*cough* bullshit *cough*
You first have to realize that there are exactly two programming languages in all existence: ruby and python.
The rest makes more sense if you start from there.
William of Ockham had no beard. The most likely explanation is that it was chewed off by squirrels every morning.
That Python is for C programmers who want to take a break from semicolons. And ruby is the same but for Java programmers.
If you mod me down the terrorists will have won
Given that Python and Ruby are 8th and 11th respectively on the Tiobe index with a combined rating of 5%, it's more like the Special Olympics. (yes, mod me troll)
"First they came for the slanderers and i said nothing."
It's not that. There are at least a couple of major issues here:
(1) The languages at the top of the Tiobe Index (even given that we can assume it has some claim to validity... I'm not so sure) are all compiled languages, or at least compilable to bytecode. Except PHP, which dominated the Web world for a long time but is sliding, and for good reasons.
(2) The languages at the top of the Tiobe index will always have distorted figures because they represent the majority of code that is already installed and being maintained, rather than new programs.
When compiled Ruby has become more mature (there are things like JRuby which is coming along nicely, and Ruby 3.0 will supposedly be compilable to bytecode) you will see an increase in its use, because then it will be more commercially viable and appropriate for desktop applications.
In the meantime, languages that have been mostly used for scripting like Ruby and Python are not used so much for business because all your code is exposed to any would-be customers. That says absolutely nothing about the features of the language itself, except that it is more difficult to compile dynamic languages.
Funny you should mention Fortran. Actually, this Ruby thing might actually work, but only if numerical analysts, scientists, engineers, etc. (non-CS types) like it better than Python. Many such domain experts seem to prefer Fortran or C/C++, perhaps because they learned it in school and/or because everyone in their field before them used it to build the existing code bases. Python does have a hell of a head start, though.
Precisely. If any language can be said to dominate the scientific community these days, it's probably Excel, with Matlab and R close behind.
sub f{($f)=@_;print"$f(q{$f});";}f(q{sub f{($f)=@_;print"$f(q{$f});";}f});
This seems like a terrible idea. What could scientific computing with Ruby possibly offer that SciPy doesn't already? Way to split the potential work force guys. If you want to develop a scientific computing library for a rich dynamic language, then contribute to SciPy. What a wasted effort.
This is why I'm developing "FORTRUBY".
/X/ SUM=SUM+X END))
FORTRUBY is an all new implemenation of Fortran on top of Ruby.
With FORTRUBY, scientists and engineers can jump right in and start programming in what they're most comfortable with, Fortran, but the Fortran code isn't actually compiled,it's interpreted by a Fortran interpreter written in Ruby.
This allows scientists and engineers to transition gracefully to a modern language like Ruby. At first, they can just write in Fortran and insert calls to the Ruby library. When they're ready to move on, they can actually insert Ruby code into their Fortran programs that gracefully accomodates Fortran data types and arrays by using the special 'RUBY' statement like this:
DIMENSION M(10)
RUBY(FORMAT (5HSUM=0))
RUBY(FORMAT (27HM.EACH DO
Finally, they can transition to full fledged Ruby by just writing the whole program inside RUBY statements. Finally scientists and engineers can move into the 21st century without leaving all their current hard-earned skills behind.
The fellowship is a summer long with only a $1,500 stipend. The most recent commit is from December 1st, 2011. The wiki and issue tracker appear to be similarly inactive. Even if the project does something, it probably won't do much; contrast it with numpy commits which are recent and numerous.
This story should never have been accepted. There are a million minor projects like this that similarly aren't newsworthy enough to discuss.
Excel isn't a language.
You know that and I know that. But I've worked for physicists, chemists and biologists, and believe me, that little detail doesn't stop them one little bit. A little birdie tells me that it's even worse in the social sciences.
MatLab might beat Python, but it's been losing ground.
Very slowly, and in the fields I've worked in, invariably to R.
R? I love R, but it's not a general purpose language and very few scientists know how to use it.
Those two little details don't stop scientists either.
In my experience, scientists will do just about anything to convince themselves that they're not actually programming, if only to avoid pesky annoyances like source code control. The less it looks like a programming language, the better.
sub f{($f)=@_;print"$f(q{$f});";}f(q{sub f{($f)=@_;print"$f(q{$f});";}f});
In my experience, scientists will do just about anything to convince themselves that they're not actually programming, if only to avoid pesky annoyances like source code control. The less it looks like a programming language, the better.
Oh god. That would explain why none of their code looks like it's written in a programming language.*
* I work with biologists. By 'they,' I mean biologists. I know you physicists and quantum chemists have it lucky. Stop bragging. You're making me feel bad.
Bio questions? Ask me to start a Q&A journal. Computer analogies available for most topics!
During one of the interviews, the guy hit the nail on the head:
A lot of people don't write Ruby when they're coding in Ruby.
In reality, Ruby practices make a lot of sense under the context of the language and when you get comfortable with them then you've reached a position when you can take advantage of what Ruby has to offer -- mainly brevity (without sacrificing clarity) and flexibility (crazy introspection and meta-programming capabilities).
There are a lot of things in the Ruby universe that suck (the interpreter can be quirky, gem management can bit flaky, documentation could be better), the language proper is not one of them.
However, (surprise, surprise) like with anything else in life, you've got to weigh the pros and cons and find something that suits you and/or your needs.
Ruby suits a lot of people's needs, that's why it exists, obviously -- so no, we're not where we were 20 years ago, not by a looong shot.
I've been using Octave (an open source version of Matlab) in Stanford's online PGM course. My first reaction was "great matrix manipulation library, extremely bad language". It's like time travelling to the 70's and discarding every progress CS made in the last forty years. Actually Matlab has object oriented classes now but somebody commented in the PGM forums that it's not so good. (Octave uses an older Matlab OO syntax I'll be merciful not to comment about.) I don't have any direct experience with R but on the PGM forum I read that its status is not so different.
My suggestion to the scientific community is to work on replacing those old languages with something modern, even Python which I cordially hate because of that white space thing. Obviously you need a fast (written in C) scientific library and an interactive prompt is extremely handy. Python and Ruby are sensible choices IMHO. Matlab and R won't disappear, Cobol didn't go away, but there is no reason why a 20 years old student shouldn't start coding with a modern language, if it's on par with the old ones (a big if, I know).
It cuts both ways. I'm a geneticist, and it's painful having to work with tech guys who don't know the first thing about even basic biology, never mind genetics.
It's the same here on Slashdot. I always cringe every time I load up the comments on a story about genetics or evolution, because I know there'll be a slew of ignorant comments modded up to +5 insightful. At least most scientists know their limitations at programming, but the same cannot be said with regard to non-engineering subjects for many engineers, who feel themselves qualified to comment on just about any topic under the sun, regardless of their lack of knowledge.
Physicists are perhaps more famous for the same folly; one example I recently stumbled upon was David Boehm, who, in conjunction with a psychologist, developed a completely nonsensical theory of higher brain function and the emergence of independent thought based on nothing more than the appeal of physics concepts to a biological problem.
If it consoles you any, rectifying such misconceptions is one of the reasons I make a habit of posting here. Experience more suggests, however, that not reading the article is more commonly a source of error—but perhaps that's an artefact of the same presumptiveness.
Bio questions? Ask me to start a Q&A journal. Computer analogies available for most topics!
Let's not forget Mathematica (my personal favorite) and Lab View (used for programming National Instruments cards, but soms people start using it as a general programming language because that's what they know -- visual interface, more like circuit design, quite interesting actually).