[R] Is it possible to vectorize/accelerate this?

[R. Michael Weylandt]

Yes -- if & else is much faster than ifelse() because if is a
primitive while ifelse() is a whole function call (in fact, you can
see the code by typing ifelse into the prompt and see that it has two
if calls within it.

Michael

On Thu, Nov 3, 2011 at 4:38 PM, hihi <v.p.mail at freemail.hu> wrote:
> Hi,
> thank you for your very immediate response. :-) Is if than and else faster
> than ifelse? I'm wondering (or not knowing something)
> Best regards,
> Peter
> 2011/11/3 R. Michael Weylandt <michael.weylandt at gmail.com>
> <michael.weylandt at gmail.com>
>>
>> I don't immediately see a good trick for vectorization so this seems to me
>> to be a good candidate for work in a lower-level language. Staying within R,
>> I'd suggest you use if and else rather than ifelse() since your computation
>> isn't vectorized: this will eliminate a small amount over overhead. Since
>> you also always add a_vec, you could also define b_vec as a copy of a to
>> avoid all those calls to subset a, but I don't think the effects will be
>> large and the code might not be as clear.
>>
>> You indicated that you may be comfortable with writing C, but I'd suggest
>> you look into the Rcpp/Inline package pair which make the whole process much
>> easier than it would otherwise be.
>>
>>  I'm not at a computer write now or I'd write a fuller example, but the
>> documentation for those packages is uncommonly good an you should be able to
>> easily get it down into C++. If you aren't able to get it by tomorrow, let
>> me know and I can help troubleshoot. The only things I foresee that you'll
>> need to change are zero-basing, C's loop syntax, and (I think) the call to
>> abs(). (I always forget where abs() lives in c++ ....)
>>
>> The only possible hold up is that you need to be at a computer with a C
>> compiler
>>
>> Hope this helps,
>>
>> Michael
>>
>> On Nov 3, 2011, at 3:10 PM, hihi <v.p.mail at freemail.hu> wrote:
>>
>> > Dear Members,
>> >
>> > I work on a simulaton experiment but it has an bottleneck. It's quite
>> > fast because of R and vectorizing, but it has a very slow for loop. The
>> > adjacent element of a vector (in terms of index number) depends
>> > conditionally on the former value of itself. Like a simple cumulating
>> > function (eg. cumsum) but with condition. Let's show me an example:
>> > a_vec = rnorm(100)
>> > b_vec = rep(0, 100)
>> > b_vec[1]=a_vec[1]
>> > for (i in 2:100){b_vec[i]=ifelse(abs(b_vec[i-1]+a_vec[i])>1, a_vec[i],
>> > b_vec[i-1]+a_vec[i])}
>> > print(b_vec)
>> >
>> > (The behaviour is like cumsum's, but when the value would excess 1.0
>> > then it has another value from a_vec.)
>> > Is it possible to make this faster? I experienced that my way is even
>> > slower than in Excel! Programming in C would my last try...
>> > Any suggestions?
>> >
>> > Than you,
>> > Peter
>> >
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>
>