Hello, I would like to provide a helpful bug report to the maintainer of Rmixmod, but I'm not skilled in memory profiling. The following example illustrates the problem : library(Rmixmod) genes <- matrix(rnorm(5000*50, 9, 2), nrow = 5000, ncol = 50) selected <- sample(5000, 25) columns <- split(1:50, rep(1:10, each = 5)) lapply(1:100, function(index) # 100 resamples with replacement { lapply(1:5, function(fold) # 5-fold cross validation { apply(genes[selected, columns[[fold]]], 1, function(aGene) mixmodCluster(aGene, nbCluster = 1:3)) return(NULL) }) }) Even though no data was assigned to any variables, even if I do gc() after the loop, 5 GB of RAM is used. This makes the software unusable in a loop, because the server freezes when it runs out of RAM. May someone who is an expert help me ? -------------------------------------- Dario Strbenac PhD Student University of Sydney Camperdown NSW 2050 Australia
Read ?maintainer and the Posting Guide mentioned below. --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --------------------------------------------------------------------------- Sent from my phone. Please excuse my brevity. On July 31, 2014 6:00:21 PM PDT, Dario Strbenac <dstr7320 at uni.sydney.edu.au> wrote:>Hello, > >I would like to provide a helpful bug report to the maintainer of >Rmixmod, but I'm not skilled in memory profiling. > >The following example illustrates the problem : > >library(Rmixmod) >genes <- matrix(rnorm(5000*50, 9, 2), nrow = 5000, ncol = 50) >selected <- sample(5000, 25) >columns <- split(1:50, rep(1:10, each = 5)) >lapply(1:100, function(index) # 100 resamples with replacement >{ > lapply(1:5, function(fold) # 5-fold cross validation > { >apply(genes[selected, columns[[fold]]], 1, function(aGene) >mixmodCluster(aGene, nbCluster = 1:3)) > return(NULL) > }) >}) > >Even though no data was assigned to any variables, even if I do gc() >after the loop, 5 GB of RAM is used. This makes the software unusable >in a loop, because the server freezes when it runs out of RAM. > >May someone who is an expert help me ? > >-------------------------------------- >Dario Strbenac >PhD Student >University of Sydney >Camperdown NSW 2050 >Australia > >______________________________________________ >R-help at 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.
Hi Dario, The maintainer of that package is: Benjamin Auder and I have copied him on this message. Usually it is best to include the maintainer in this sort of situation. Jim On Fri, 1 Aug 2014 01:00:21 AM Dario Strbenac wrote:> Hello, > > I would like to provide a helpful bug report to the maintainer ofRmixmod,> but I'm not skilled in memory profiling. > > The following example illustrates the problem : > > library(Rmixmod) > genes <- matrix(rnorm(5000*50, 9, 2), nrow = 5000, ncol = 50) > selected <- sample(5000, 25) > columns <- split(1:50, rep(1:10, each = 5)) > lapply(1:100, function(index) # 100 resamples with replacement > { > lapply(1:5, function(fold) # 5-fold cross validation > { > apply(genes[selected, columns[[fold]]], 1, function(aGene) > mixmodCluster(aGene, nbCluster = 1:3)) return(NULL) > }) > }) > > Even though no data was assigned to any variables, even if I do gc()after> the loop, 5 GB of RAM is used. This makes the software unusable ina loop,> because the server freezes when it runs out of RAM. > > May someone who is an expert help me ? > > -------------------------------------- > Dario Strbenac > PhD Student > University of Sydney > Camperdown NSW 2050 > Australia > > ______________________________________________ > R-help at 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, reproduciblecode.