[R] efficient conversion of matrix column rows to list elements

[Chris Carleton]

Thanks for the suggestion. The solution below is much better than my
round-about way.

combn(outcomes, 2, list )

I can't do much about the speed of combn() so I wanted to trim the fat
wherever else I could.

C

On 17 November 2010 15:10, Charles C. Berry <cberry at tajo.ucsd.edu> wrote:
>
> On Wed, 17 Nov 2010, Chris Carleton wrote:
>
>> Hi List,
>>
>> I'm hoping to get opinions for enhancing the efficiency of the following
>> code designed to take a vector of probabilities (outcomes) and calculate a
>> union of the probability space. As part of the union calculation, combn()
>> must be used, which returns a matrix, and the parallelized version of
>> lapply() provided in the multicore package requires a list. I've found that
>> parallelization is very necessary for vectors of outcomes greater in length
>> than about 10 or 15 elements, which is why I need to make use of multicore
>> (and, therefore, convert the combn() matrix to a list). It would speed the
>> process up if there was a more direct way to convert the columns of combn()
>> to elements of a single list.
>
>
> I think you are mistaken.
>
> Is this what Rprof() tells you?
>
> On my system, combn() is the culprit
>
>> Rprof()
>> outcomes <- 1:25
>> nada <- replicate(200, {apply(combn(outcomes,2),2,column2list);NULL})
>> Rprof(NULL)
>> summaryRprof()
>
> $by.self
>          self.time self.pct total.time total.pct
> "combn"        0.64    61.54       0.70     67.31
> "apply"        0.20    19.23       1.04    100.00
> "FUN"          0.10     9.62       1.04    100.00
> "!="           0.04     3.85       0.04      3.85
> "<"            0.02     1.92       0.02      1.92
> "-"            0.02     1.92       0.02      1.92
> "is.null"      0.02     1.92       0.02      1.92
>
>
> And it hardly takes any time at that!
>
>
> HTH,
>
> Chuck
>
> p.s. Isn't
>
>        as.data.frame( combn( outcomes, 2 ) )
> or
>        combn(outcomes, 2, list )
>
> good enough?
>
>
> Any constructive suggestions will be greatly
>>
>> appreciated. Thanks for your consideration,
>>
>> C
>>
>> code:
>> ------------
>> unionIndependant <- function(outcomes) {
>>   intsctn <- c()
>>   column2list <- function(x){list(x)}
>>   pb <-
>> ProgressBar(max=length(outcomes),stepLength=1,newlineWhenDone=TRUE)
>>   for (i in 2:length(outcomes)){
>>       increase(pb)
>>       outcomes_ <- apply(combn(outcomes,i),2,column2list)
>>       for (j in 1:length(outcomes_)){outcomes_[[j]] <-
>> outcomes_[[j]][[1]]}
>>       outcomes_container <- mclapply(outcomes_,prod,mc.cores=3)
>>       intsctn[i] <- sum(unlist(outcomes_container))
>>   }
>>   intsctn <- intsctn[-1]
>>   return(sum(outcomes) - sum(intsctn[which(which((intsctn %in% intsctn))
>> %% 2 == 1)]) + sum(intsctn[which(which((intsctn %in% intsctn)) %% 2 == 0)])
>> + ((-1)^length(intsctn) * prod(outcomes)))
>> }
>> ------------
>> PS This code has been tested on vectors of up to length(outcomes) == 25 and
>> it should be noted that ProgressBar() requires the R.utils package.
>>
>>        [[alternative HTML version deleted]]
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> Charles C. Berry                            Dept of Family/Preventive Medicine
> cberry at tajo.ucsd.edu                        UC San Diego
> http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901
>
>
>