Thierry: (Apologies for beating a dead horse ...)
Just wanted to point out that sometimes it does not pay to try to be clever: Try the **obvious, simple** solution using a for loop (where z is your list of matrices): > z1 <- 0 > for(i in seq_len(1e6))z1<- z1+z[[i]] > z1<- z1/length(z)}) This was just about as fast as the more elegant Reduce() solution when I tried it on my previous example of a million 10x10 matrices. (Note that your OS and memory may affect this). -- Bert On Tue, Nov 6, 2012 at 5:45 AM, ONKELINX, Thierry <thierry.onkel...@inbo.be> wrote: > Dear all, > > Thanks a lot for your suggestions. > > Arun's suggestion of using simplify2array is only marginally faster than my > attempt. > The solutions of Dimitris and Bert however were 78 and 30 times faster than > my attempt (using n = 51, s = 25, r = 1000 what will be about their size in > my application). > > As there shouldn't be any missing data in the array, I'll stick to the > solution based on Reduce() because I find it as well fast as elegant. > > Best regards, > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature and > Forest > team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance > Kliniekstraat 25 > 1070 Anderlecht > Belgium > + 32 2 525 02 51 > + 32 54 43 61 85 > thierry.onkel...@inbo.be > www.inbo.be > > To call in the statistician after the experiment is done may be no more than > asking him to perform a post-mortem examination: he may be able to say what > the experiment died of. > ~ Sir Ronald Aylmer Fisher > > The plural of anecdote is not data. > ~ Roger Brinner > > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of data. > ~ John Tukey > > -----Oorspronkelijk bericht----- > Van: Bert Gunter [mailto:gunter.ber...@gene.com] > Verzonden: maandag 5 november 2012 16:13 > Aan: D. Rizopoulos > CC: ONKELINX, Thierry; r-help@r-project.org > Onderwerp: Re: [R] averaging a list of matrices element wise > > Gents: > > Although it is difficult to say what may be faster, as it typically depends > on the data, and it is even more difficult to say what is fast enough, I > suspect that > > ?rowMeans ## specifically written for speed > > would be considerably faster than Reduce (or an apply() )approach on the > array), but I have **not** checked. I am of course prepared to eat my words > in the face of data to the contrary. > > The call would be: > > result <- rowMeans( array(unlist(raw), dim = c(r,s,length(raw)), dims=2) > > Note that rowMeans() has an na.rm arguments to handle NA's. See the help file > for deatils. > Note also the tradeoff to memory, as copies of raw probably are made during > evaluation. > Finally note that dimnames are lost in the final result, so the above would > have to be followed by > > dimnames(result) <- dimnames(raw[[1]]) > > to get them back. > > -- Bert > > > On Mon, Nov 5, 2012 at 2:43 AM, D. Rizopoulos <d.rizopou...@erasmusmc.nl> > wrote: >> If you don't have any NAs, then one way is: >> >> n <- 3 >> r <- 5 >> s <- 6 >> raw <- lapply(seq_len(n), function(i){ >> matrix(rnorm(r * s), ncol = r) >> }) >> >> Reduce("+", raw) / length(raw) >> >> >> I hope it helps. >> >> Best, >> Dimitris >> >> >> On 11/5/2012 11:32 AM, ONKELINX, Thierry wrote: >>> Dear all, >>> >>> I have a list of n matrices which all have the same dimension (r x >>> s). What would be a fast/elegant way to calculate the element wise >>> average? So result[1, 1] <- mean(c(raw[[1]][1, 1] , raw[[2]][1, 1], >>> raw[[...]][1, 1], raw[[n]][1, 1])) >>> >>> Here is my attempt. >>> >>> #create a dummy dataset >>> n <- 3 >>> r <- 5 >>> s <- 6 >>> raw <- lapply(seq_len(n), function(i){ >>> matrix(rnorm(r * s), ncol = r) >>> }) >>> >>> #do the calculation >>> result <- array(dim = c(dim(raw[[1]]), length(raw))) for(i in >>> seq_along(raw)){ >>> result[,,i] <- raw[[i]] >>> } >>> result <- apply(result, 1:2, mean) >>> >>> >>> Best regards, >>> >>> Thierry >>> >>> ir. Thierry Onkelinx >>> Instituut voor natuur- en bosonderzoek / Research Institute for >>> Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & >>> Quality Assurance Kliniekstraat 25 >>> 1070 Anderlecht >>> Belgium >>> + 32 2 525 02 51 >>> + 32 54 43 61 85 >>> thierry.onkel...@inbo.be >>> www.inbo.be >>> >>> To call in the statistician after the experiment is done may be no more >>> than asking him to perform a post-mortem examination: he may be able to say >>> what the experiment died of. >>> ~ Sir Ronald Aylmer Fisher >>> >>> The plural of anecdote is not data. >>> ~ Roger Brinner >>> >>> The combination of some data and an aching desire for an answer does not >>> ensure that a reasonable answer can be extracted from a given body of data. >>> ~ John Tukey >>> >>> * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * >>> * Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver >>> weer en binden het INBO onder geen enkel beding, zolang dit bericht niet >>> bevestigd is door een geldig ondertekend document. >>> The views expressed in this message and any annex are purely those of the >>> writer and may not be regarded as stating an official position of INBO, as >>> long as the message is not confirmed by a duly signed document. >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> >> -- >> Dimitris Rizopoulos >> Assistant Professor >> Department of Biostatistics >> Erasmus University Medical Center >> >> Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands >> Tel: +31/(0)10/7043478 >> Fax: +31/(0)10/7043014 >> Web: http://www.erasmusmc.nl/biostatistiek/ >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > > > -- > > Bert Gunter > Genentech Nonclinical Biostatistics > > Internal Contact Info: > Phone: 467-7374 > Website: > http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm > * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * * > Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer > en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd > is door een geldig ondertekend document. > The views expressed in this message and any annex are purely those of the > writer and may not be regarded as stating an official position of INBO, as > long as the message is not confirmed by a duly signed document. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
