search for: bigtabulate

...64bit machine? It seems like it (given <https://stat.ethz.ch/R-manual/R-devel/library/base/html/Memory-limits.html> and <http://www.win-vector.com/blog/2015/06/r-in-a-64-bit-world/>, but I just want to make sure I understood that right); - I thought I could handle this with the package bigtabulate, but whenever I run xy.tab <- bigtable(data.frame(x, y), ccols=1:2) R crashes as follows: terminate called after throwing an instance of 'std::bad_alloc' what(): std::bad_alloc Aborted Any idea on what I am doing wrong with bigtabulate? Thanks for your consideration

...eems like it > (given <https://stat.ethz.ch/R-manual/R-devel/library/base/html/Memory-limits.html> > and <http://www.win-vector.com/blog/2015/06/r-in-a-64-bit-world/>, but > I just want to make sure I understood that right); > - I thought I could handle this with the package bigtabulate, but whenever I run > > xy.tab <- bigtable(data.frame(x, y), ccols=1:2) > > R crashes as follows: > > terminate called after throwing an instance of 'std::bad_alloc' > what(): std::bad_alloc > Aborted > > Any idea on what I am doing wrong with bigtabulate...

I have a large file backed big. matrix, with millions of rows and 20 columns. The columns contain data that I simply need to tabulate. There are a few dozen unique values. and I just want a frequency count Test code with a small "big" matrix. library(bigmemory) library(bigtabulate) test <- big.matrix(nrow = 100, ncol = 10) test[,1:3]<- sample(150) test[,4:6]<- sample(100) test[,7:10]<- sample(100) ## so we have sample big memory matrix. Its not file backed but will do for testing. ## the result we want is one that you would get if you could run t...

...w above) will show up multiple times in a given file. I want to sum column 4 across each pair of individuals. If I could bring the matrix into R, I could use tapply() to accomplish this by indexing on paste(X[,1],X[,2]), but the matrix doesn't fit into R. I have been trying to use bigmemory and bigtabulate packages in R, but when I try to use the bigsplit function, R never completes the operation (after a day, I killed the process). In particular, I did this: X <- read.big.matrix("file.loc.X",sep=" ",type="double") hap.indices <- bigsplit(X,1:2) #this runs for too...

The long-promised revision to bigmemory has arrived, with package 4.2.3 now on CRAN. The mutexes (locks) have been extracted and will be available through package synchronicity (on R-Forge, soon to appear on CRAN). Initial versions of packages biganalytics and bigtabulate are on CRAN, and new versions which resolve the warnings and have streamlined CRAN-friendly configurations will appear shortly. Package bigalgebra will remain on R-Forge for the time being as the user-interface is developed and the configuration possibilities expand. For more information, please...

The long-promised revision to bigmemory has arrived, with package 4.2.3 now on CRAN. The mutexes (locks) have been extracted and will be available through package synchronicity (on R-Forge, soon to appear on CRAN). Initial versions of packages biganalytics and bigtabulate are on CRAN, and new versions which resolve the warnings and have streamlined CRAN-friendly configurations will appear shortly. Package bigalgebra will remain on R-Forge for the time being as the user-interface is developed and the configuration possibilities expand. For more information, please...

Dear helpers, Does anyone have information on the status of bigmemory and R3.0? Will it just take time for the devs to re-code for the new environment? Or is there an alternative for this new version? Thanks Ben Caldwell [[alternative HTML version deleted]]

I work with problems that have rather large data requirements -- typically a bunch of multigig arrays. Given how generous R is with using memory, the only way for me to work with R has been to use bigmatrices from bigmemory package. One thing that is missing a bit is interoperability of bigmatrices with C++ and possibly java. What i mean by that is API that would allow read and write filebacked

I'm in the process of converting some S3 methods to S4 methods. I have this function : setGeneric("enrichmentCalc", function(rs, organism, seqLen, ...){standardGeneric("enrichmentCalc")}) setMethod("enrichmentCalc", c("GenomeDataList", "BSgenome"), function(rs, organism, seqLen, ...) { ... ... ... })

...the candidate algorithms' order. * biganalytics (1.0.14) Jay and Mike http://crantastic.org/packages/biganalytics This package extends the bigmemory package with various analytics. Functions bigkmeans and binit may also be used with native R objects. For tapply-like functions, the bigtabulate package may also be helpful. For linear algebra support, see bigalgebra. For mutex (locking) support for advanced shared-memory usage, see synchronicity. * bigtabulate (1.0.11) Jay and Mike http://crantastic.org/packages/bigtabulate This package extends the bigmemory package with tab...