Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

The future of R - pessimistic thoughts by R founder Ross Ihaka

r-bloggers.com

Post reply on HN
Print view View original

51–60 of 78 posts

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#51

Post by piggybox »

Quiark wrote: post #27
ewjordan wrote: post #10

Earlier quoted context omitted.

But I wonder why R actually needs to exist as its own language. It seems it could be recast in Ruby for example or one of the latest functional languages. Indeed - it would be a shame for them to start over from scratch and end up coming up with a brand new language, brand new syntax, brand new quirks, brand new performance problems, etc., while they could have simply searched around a bit for something that's alread…

For JVM, there is Incanter which is a statistics library written in Clojure. It is backed by Parallel Colt for the heavy number lifting. Note that I'm not trying to say that Clojure would be a scientist-friendly language :)

A lot of people blame Lisp for too many brackets, but I generally feel they are not the issue after reading Lisp for a while. What may make it scientist-unfriendly is to write math formulas in infix grammar.

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#52

Post by hadley »

nanairo wrote: post #37
haberman wrote: post #32

To me the problem with R isn't performance problems, which I've never run into myself, but rather the complicated and confusing semantics of its data types. R's aggregate data types are: vector, matrix, array, dataframe, and list. The semantics of these types and the relationships between them are extremely confusing. I wish I had gathered examples of this so I could be more specific, but I have basically come to the…

I may be wrong but I think that: list => are basically hash, or an array that can have mixed objects inside vector, matrix, array => are all the same thing. They are what in most computer languages are called arrays, and can have only one type. The difference between those three is just the number of dimensions (vector:1, matrix:2, array:3+). dataframe I will concede is a little more complex, and I still have some pr…

Vectors are not the same as 1d matrices/arrays because a vector does not have direction (i.e. it's not a row vector or a column vector, but will work as either depending on circumstance).

  > all.equal(1:10, matrix(1:10, ncol = 1))
  [1] "Attributes: "
  [2] "target is numeric, current is matrix"   
  > all.equal(matrix(1:10, ncol = 1), array(1:10, c(10, 1)))
  [1] TRUE

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#53

Post by hadley »

nanairo wrote: post #6

To be honest I've been using R a bit lately for my work and while I like it I don't find it at all innovative. That's not a criticism of R: the libraries it has are amazing, as well as the mindshare among people who care of statistics. But I wonder why R actually needs to exist as its own language. It seems it could be recast in Ruby for example or one of the latest functional languages. So I am kind of pleased my th…

I'd be interested to learn how to add missing value support into an existing language. It's pervasive in R, so important for statistics, and it seems like it would be hard to patch onto an existing language.

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#54

Post by forkandwait »

haberman wrote: post #32

To me the problem with R isn't performance problems, which I've never run into myself, but rather the complicated and confusing semantics of its data types. R's aggregate data types are: vector, matrix, array, dataframe, and list. The semantics of these types and the relationships between them are extremely confusing. I wish I had gathered examples of this so I could be more specific, but I have basically come to the…

I would suggest checking out Octave, a Matlab compatible language. It doesn't have the rich libraries of statistical procedures like R, but it far easier to use to build your own matrix based algorithms.

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#55

Post by knowtheory »

equark wrote: post #42
knowtheory wrote: post #30

Earlier quoted context omitted.

o? what is it that you're doing?

Building a next generation of statistical computing.

I was hoping you'd be at least the slightest bit more specific :) are you working in a proprietary startup? are you working in academia? presumably you're working on a codebase with the intent to distribute it to users at some point?

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#56

Post by lambda »

nanairo wrote: post #6

To be honest I've been using R a bit lately for my work and while I like it I don't find it at all innovative. That's not a criticism of R: the libraries it has are amazing, as well as the mindshare among people who care of statistics. But I wonder why R actually needs to exist as its own language. It seems it could be recast in Ruby for example or one of the latest functional languages. So I am kind of pleased my th…

If you want to do scientific computing in a modern general purpose language, NumPy/SciPy are pretty popular. Haven't used them much myself, but they look pretty decent.

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#57

Post by equark »

hadley wrote: post #53
nanairo wrote: post #6

To be honest I've been using R a bit lately for my work and while I like it I don't find it at all innovative. That's not a criticism of R: the libraries it has are amazing, as well as the mindshare among people who care of statistics. But I wonder why R actually needs to exist as its own language. It seems it could be recast in Ruby for example or one of the latest functional languages. So I am kind of pleased my th…

I'd be interested to learn how to add missing value support into an existing language. It's pervasive in R, so important for statistics, and it seems like it would be hard to patch onto an existing language.

How important is the distinction between NaN versus NA? I agree this is a subtle issue.

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#58

Post by equark »

messel wrote: post #44
_delirium wrote: post #19

Earlier quoted context omitted.

But I wonder why R actually needs to exist as its own language. It seems it could be recast in Ruby for example or one of the latest functional languages. I agree if we're talking about defining a new R (like the blog post discusses), but the existing R makes sense to me to exist as its own language. It wasn't really invented from scratch gratuitously, but began as an open-source reimplementation of the Bell Labs "S"…

"One in-between possibility could be to retain the standard syntax/semantics but target an existing VM with a bigger development community" I think that's a great move for a number of languages as they lose popularity over time. The Scheme on lisp machines was outpaced by version on compiled machines, and is the version we use today.

The problem is a huge number of R packages use compiled code that won't be portable to this new VM.

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#59

Post by zheaton »

earl wrote: post #46
studer wrote: post #36

Earlier quoted context omitted.

Given that numpy/scipy is basically a collection of C/C++/Fortran primitives, chances are that you managed to write a program that spent very little time actually computing things, and a lot of time doing something else. Not sure what that could be, though; even low-level algorithms usually run 10-100x slower than C speed if naively coded in plain Python, so a 30000x slowdown using a specialized library sounds rather…

Here's my code -- I would have contacted you directly, but I can't find your email. It's as simple as this: http://gist.github.com/578226#file_gistfile1.py (sorry, that's an editable link, so please be nice) Anyway -- the machine is not swapping -- python grabs ~20GB of ram, there is another ~100GB available. It pegs one of the cores. Nothing else was running during this test so there was no competition for the fsb.…

Is there any chance that SciPy was compiled without the ATLAS/BLAS/LAPACK libraries? (You can verify this using with the "numpy.show_config()" and "scipy.show_config()" functions in an interactive python session.) In that case, all the numerical math would be done in straight Python rather than optimized C/FORTRAN.

Re: The future of R - pessimistic thoughts by R founder Ross Ihaka

#60

Post by cdavid »

equark wrote: post #57
hadley wrote: post #53

Earlier quoted context omitted.

I'd be interested to learn how to add missing value support into an existing language. It's pervasive in R, so important for statistics, and it seems like it would be hard to patch onto an existing language.

How important is the distinction between NaN versus NA? I agree this is a subtle issue.

It is important - you cannot know whether NaN is coming from a computation or is really a missing value otherwise. In Numpy, we have the MaskedArray implementation to do this.
Post reply on HN