similar to: Indexing matrices from the Matrix package with [i, j] seems to be very slow. Are there "faster alternatives"?

Hi Berend, I see you are one of the contributors to the rbecnhmark package. I am sorry that I am bothering you again. I have tried to run your code (slightly tweaked) involving the benchmark function, and I am getting the following error message. What am I doing wrong? Error in benchmark(d1 <- s1(df), d2 <- s2(df), d3 <- s3(df), d4 <- s4(df), : could not find function

If x is a (long) vector and n << length(x), what is a fast way of finding the top-n values of x? Some suggestions (calculating the ratio of the two top values): library("rbenchmark") set.seed(1); x <- runif(1e6, max=1e7); x[1] <- NA; benchmark( replications=20, columns=c("test","elapsed"), order="elapsed" , sort = {a<-sort(x,

[I originally posted this on the R-help mailing list, and it was suggested that R-devel would be a better place to dicuss it.] Running ?table? on a factor with levels containing non-ASCII characters seems to result in extremely bad performance on Windows. Here?s a simple example with benchmark results (I?ve reduced the number of replications to make the function finish within reasonable time):

Mark, that's actually a fair statement, although your extra operator doesn't cause construction at parse time. You still call paste0(), but just add an extra layer on top of it. I also doubt that even in gigantic loops the benefit is going to be significant. Take following example: atestfun <- function(x){ y <- paste0("a very long", "string for

I would like to know whether there is a faster way to do the below operation (updating vec1). My objective is to update the elements of a vector (vec1), where a particular element i is dependent on the previous one. I need to do this on vectors that are 1 million or longer and need to repeat that process several hundred times. The for loop works but is slow. If there is a faster way, please let

Hmm. Chuck: I don't see how this example represents incomplete/incommensurate recycling. Doesn't TRUE replicate from length-1 to length-3 in this case (mat[c(TRUE,FALSE),2] would be an example of incomplete recycling)? William: clever, but maybe too clever unless you really need the speed? (The clever way is 8 times faster in the following case ...) x <- rep(1,1e6)

Does anyone have something like tapply that is extremely fast for matrices when there is a very large number of levels of the grouping variable? I'm referring to, for example, tapply(x, grouping.variable, function.operating.on.submatrix) where x is a matrix and the submatrix is a subset of the rows of x. The grouping variable's length equals the number of rows of x. -- Frank E

Hi, I have a vector "v" and would like to find the number of occurrence of element "x" in the same. Is there a way other than, sum(as.integer(v==x)) or length(which(x==v)) to do the this. I have a huge file to process and do this. Both the above described methods are pretty slow while dealing with a large vector. Please have your comments. Praveen

Hi, all, How to get a time as a number? While script is running, I want to print the elapsed time something like TIME_AS_SECOND() in the following script inittime <- TIME_AS_SECOND() for (i in 1:100){ do_something(i) curtime <- TIME_AS_SECOND() elapsedtime <- curtime-inittime print(paste(i, elapsedtime)) } Thanks in advance, Hyunchul [[alternative HTML version

I've had a lot of requests for additions to the reproducible research task view that fall into a grey area (to me at least). For example, roxygen2 is a tool that broadly enable reproducibility but I see it more as a tool for better programming. I'm about to check in a new version of the task view that includes packrat and checkpoint, as they seem closer to reproducible research, but also

Is there a good reason not to allow matrix extents to be zero? I have been writing a function which fits glms under certain linear constraints. I fit the model with a reduced set of variables and then transform back to the original set. This involves operating on submatrices of the covariance matrix and subsets of the coefficients. Sometimes these subsets are empty. A zero-length subset of the

Hi, everybody: I asked about this in r-help last week and promised a summary of answers. Special thanks to the folks that helped me understand do.call and pointed me toward plyr. We face this problem all the time. A procedure generates a list of data frames. How to stack them together? The short answer is that the plyr package's rbind.fill method is probably the fastest method that is not

Dear R users, i have a matrix with 31 rows and 444 columns and i want to extract every 37th column of that matrix starting from 1. more precisely i want to select columns 1, 38,75, 112 and so on. then doing the same by starting from column number 2(2,39,76,113.......). i know that there is a manual way of doing it but i wanted to make it more quickly as i have fairly large data to dealth with.

Hi, (sorry for the wall of text; the issue here appears to be rather complicated) I'm seeing a somewhat strange case where checking whether an S4 object inherits from a parent class defined from another package with 'inherits' fails if that object is materialized through a call to 'load'. That's a mouthful, so I've put together a relatively small reproducible example

Hi, I need to extract the second largest element from each row of a matrix. Below is my solution, but I think there should be a more efficient way to accomplish the same, or not? set.seed(1) a <- matrix(rnorm(9), 3 ,3) sec.large <- as.vector(apply(a, 1, order, decreasing=T)[2,]) ans <- sapply(1:length(sec.large), function(i) a[i, sec.large[i]]) ans Thanks in advance for your

Dear all, I'm a relative new user of R and I have a problem with merging a collection of matrices. All matrices in this collection have the same dimension (532 rows and 532 columns), but can differ in the row and columns names. I'd like to merge these matrices in such a way that the resulting matrix only contains unique row- and column-names and that in case of a match between the row or

Why does R need the concept of "Vector"? In my opinion, it is a useless and confusing concept. A vector is simply a special case of a matrix whose row or column number is equal to 1. When I take submatrix from one matrix and if row or column number is 1, R will automatically convert it into a vector. It is very straightforward that a submatrix of a matrix should be a matrix. In

I run Fedora 22 R package. It is build with --with-lapack \ --with-blas \ --enable-R-shlib \. As the machine will act as a server with lots of R data computing, I try to optimize my R package. At first, I installed parallel_studio_xe_2016 with a free one year licence. Then, I build a package for R with Intel MKL and compiler. This took me lots of time as it was my first .rmp build. I finally

Dear R-help, I have been trying really hard to generate the following vector given the data (x) and parameter (alpha) efficiently. Let y be the output list, the aim is to produce the the following vector(y) with at least half the time used by the loop example below. y[1] = alpha * x[1] y[2] = alpha^2 * x[1] + alpha * x[2] y[3] = alpha^3 * x[1] + alpha^2 * x[2] + alpha * x[3] ..... below are

Hi, is there any way to keep a sub matrix dimension? exemple : i1<-1; i2<-1 j1<-2; j2<-3; ret <-matrix(1,4,4)[i1:i2,j1:j2] ; dim(ret) is NULL because the submatrix single col or single row is coerce to a vector automaticaly. How can i bypass this cast : submatrix->vector ??????? Thank you. --------------------------------- [[alternative HTML version