similar to: reducing a too-large matrix obtained with allocMatrix()

I need to multiply to very large, nonsparse matrices, and so get the error "allocMatrix: too many elements specified". Is there a way to set the limit for allocMatrix? In my case, the two matrices, A and B, are nxm and mxp where m is small, so I could subdivide each into blocks of submatrices A=rbind(A1,A2,...) and B=cbind(B1,B2,...) then multiply each pair of submatrices, but I was

On Sat, Feb 14, 2009 at 00:17, <ashrafi@ucdavis.edu> wrote: Hi, I was trying to read ~400 chips in an affybatch and I got the same message. Could you find a remedy for that. My server has 128 GB of RAM. However, R halted ever before it uses the memory. I have been able to load upto 250 CEL files but this time I wanted to test what would happen if I want to normalize 400 chips. Thanks

Dear R family, I faced a technical problem in r coding. #s=t(dev)%*%dev/(nr-1) # dev (100,000 by 2) stands for deviation from the mean #sinv=solve(s) #t2=diag(dev%*%sinv%*%t(dev)) I got an error message at t2 statement: Error in diag(dev %*% si %*% t(dev)) : allocMatrix: too many elements specified Please let me know if there is a way to overcome this problem. best moohwan

Yes, this did the trick, thanks very much! I?m cc?ing r-devel just for the record. Roger Koenker r.koenker at ucl.ac.uk<mailto:r.koenker at ucl.ac.uk> Department of Economics, UCL London WC1H 0AX. On Aug 7, 2019, at 4:55 PM, Steven Dirkse <sdirkse at gams.com<mailto:sdirkse at gams.com>> wrote: Roger, Updating Xcode has the unfortunate side effect of wiping out the std

Dear all: I¡¯m trying to get unbiased feature importance of my data via package ¡°party¡±, which contains 1-5 integer value, and a few numeric values attributes. The class label is 1-5 integer value as well. In total I have 20 features with 1100 observations. I checked the type my data in R using class(my_data_cell), no factor has been observed. I received a commond error like others did

Hi I'm having slight confusion. I plan to grow/realloc a matrix depending on the data available in a C program. Here is what I'm tried to do: Data=allocMatrix(REALSXP,3,4); SEXP Data; REAL(Data)[8]=0.001123; REAL(Data)[200000]=0.001125; printf("%f %f\n\n\n\n",REAL(Data)[8],REAL(Data)[200000]); Here is my confusion: Do I always require to allocate the exact number of data

Hi, I am writing an R package with two functions in C++. So far everything works. Now, i would like to write a third function which would use a pointer (it is a pointer to a class object) created by first function. I tried placing this pointer outside of the function definitions (i.e to make it global) but when called in the 3rd function i get > *** caught bus error *** address 0x0,

Hi, I am writing an R package with two functions in C++. So far everything works. Now, i would like to write a third function which would use a pointer (it is a pointer to a class object) created by first function. I tried placing this pointer outside of the function definitions (i.e to make it global) but when called in the 3rd function i get > *** caught bus error *** address 0x0,

Hi, Is there a way to resize a matrix defined as follows: SEXP a = PROTECT(allocMatrix(INTSXP, 10, 2)); int *pa = INTEGER(a) To row = 5 and col = 1 or do I have to allocate a second matrix "b" with pointer *pb and do a "for" loop to transfer the value of a to b? Thank you Best regards Morgan [[alternative HTML version deleted]]

I have ported some R code to C to make it faster. I can perform .Call("foobar",....) once and it works fine. Absolutely correct answer. If I put a loop inside foobar and run the main code routine more than 100 times, it crashes R. Or if I call .Call("foobar"....) seperately more than two tims it crashes R. For the most part I am doing matirx multiplies using EXP

Hi all, im triyng to implement a bayesian model with R and c++. I have a strange problem. I can't reproduce the error with a small script and then i post the original one. The problem is after the line for(MCMC_iter2=0;MCMC_iter2<thin;MCMC_iter2++) For the first 34 iterations all work fine, after, all the simulations of mu_acc_P return an "nan". If i delete the line

Dear R contributors, I'm running into trouble when trying to allocate some large (but in theory viable) vector in the context of C code bound to R through .Call(). Here is some sample code summarizing the problem: SEXP test() { int size = 10000000; double largevec[size]; memset(largevec, 0, size*sizeof(double)); return(R_NilValue); } If size if small enough (up to 10^6), everything is

Hi My code is as following: #include <R.h> #include <Rinternals.h> //* the Projector part *// void Projector(double *L, int *dimL, double *G, int *dimG, double *W, int *dimW, int *xymod, int *dimxy, double *modif, int *dimif, double *Lsum) { ...} //* the interface part *// #define getDim(A) INTEGER(coerceVector(getAttrib(A,R_DimSymbol), INTSXP)) SEXP Projector5(SEXP L, SEXP G,

Can someone explain the use of SETLENGTH() and SETTRUELENGTH()? I would like to allocate a vector and reserve some space at the end, so that it appears shorter than the allocated size. So that I can more efficiently append to the vector, without requiring a new copy every time. So I'd like to use SETLENGTH() with a shorter apparent length, and bump this up as needed until I've used the

Hi, I have a R program that call a C function. I define a vector of pointer as int nLC=3; int pownLC = nLC*nLC double *MatCovExtra[nT+1]; for(k=0;k<K+1;k++) { MatCovExtra[k] = (double*)R_alloc(pownLC, sizeof(double)); } where nT>K. Then i put some values on the vector associated with the pointer: for(k=0;k<K+1;k++) { for(i=0;i<nLC;i++)

Hello. I'm trying to read a delimited file. I'm a little new to the R api. In the program, I do something like this... /*****************************/ SEXP retval; PROTECT(retval = allocMatrix(STRSXP,1,names.dim)); int r_eltctr = 0; while(!myfile.eof()) { SET_LENGTH(retval,r_eltctr+num_of_fields); for(int i = 0;numofcolumns; ++i) { INTEGER(retval)[r_eltctr++] = 1;/*some

Hola, tengo una serie de datos datExpr, al usar cor() : cor(datExpr ,method = "pearson", use ="pairwise.complete.obs") me da el siguiente error allocMatrix: too many elements specified Trate con "complete.obs", "na.or.complete", y el resto de las opciones para "use", pero siempre me da algun error.  ¿Alguna idea de como puedo hacer que cor() lea

I'm looking to analyze a large data set: a within-Ss 2*2*1500 design with 20 Ss. However, aov() gives me an error, reproducible as follows: id = factor(1:20) a = factor(1:2) b = factor(1:2) d = factor(1:1500) temp = expand.grid(id=id, a=a, b=b, d=d) temp$y = rnorm(length(temp[, 1])) #generate some random DV data this_aov = aov( y~a*b*d+Error(id/(a*b*d)) , data=temp ) While yields the

I believe there is a memory leak in isoreg in the current version of R, as I believe the following shows > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 120405 3.3 350000 9.4 350000 9.4 Vcells 78639 0.6 786432 6.0 392463 3.0 > for(k in 1:100) { + + y <- runif(10000) + isoreg(x,y) + } > rm(x) > rm(y) > gc() used (Mb) gc

Hi I've written the following program: #include <R.h> #include <Rdefines.h> #include "Projector.h" SEXP Projector2(SEXP L, SEXP G, SEXP W, SEXP xymod, SEXP modif){ int nprot=0; PROTECT(L=AS_NUMERIC(L));nprot++; PROTECT(G=AS_NUMERIC(G));nprot++; PROTECT(W=AS_NUMERIC(W));nprot++; PROTECT(xymod=AS_INTEGER(xymod));nprot++; PROTECT(modif=AS_NUMERIC(modif));nprot++;