search for: applied

Please CC me on answer, as I'm not subscribed on the list Here is the description of the problem. The system description follows. Everytime I read my email using KMail 3.5.6, dovecot hangs up near the end. I get the following in mail.err: IMAP(doudou): file ostream-crlf.c: line 339 (_send_istream): assertion failed: ((size_t)ret <= iov.iov_len) IMAP(doudou): Raw backtrace: imap

...) ## create function .apply.myClass for myClass objects .apply.myClass <- function(obj, ## object of class myClass margin, ## a numeric which should be 1 or 2 fun, ## a function groups = NULL, ## should fun be applied in a group ## specific manner? ... ## additional arguments passed to fun ) { ## attach the data frame contained in obj attach(obj at Data) ## make sure to detach it at the end...

Hi, have recently bought MI5 (Tales of Monkey Island), and I am currently trying to run it under wine in Ubuntu 9.04 and I am running the latest development version 1.1.25. I am running this over the latest stable version due to less graphical errors when trying to run the game. To get the game running I followed this guide posted on the telltale's ( the creators of the game) forum >

...Platform: i386 OS/Version: All Status: NEW Severity: normal Priority: P2 Component: unknown AssignedTo: laforge@netfilter.org ReportedBy: georg.wild@gmx.de CC: netfilter-buglog@lists.netfilter.org Hello, I applied netfilter to my openmosix-2.4.20-kernel and now I got a kernel panic. I wonder whether the error is netfilter-based or not. I think it is because the kernel panic comes directly after the netfilter message on startup. Do you know anything about this? I'll attach the ksymoops and the applied pa...

libswfdec/swfdec_as_function.c | 35 ++++++++++++++++++---------------- libswfdec/swfdec_as_object.c | 2 - test/trace/Makefile.am | 9 ++++++++ test/trace/function-apply-crash-5.swf |binary test/trace/function-apply-crash-6.swf |binary test/trace/function-apply-crash-7.swf |binary test/trace/function-apply-crash-8.swf |binary

Dear R Developers, the new simplify argument in apply causes that my package (hsdar) does not pass the checks in R-devel. The workaround, Kurt Hornik send me, is working for the R-code: if("simplify" %in% names(formals(base::apply))) do something else do something else Unfortunately, I cannot conditionalize the man pages of the functions. I get the message that

Hello, everyone I have a piece of code that looks like this: mrets <- merge(mrets, BMM.SR=apply(mrets, 1, MyFunc, ret="BMM.AV120", stdev="BMM.SD120")) mrets <- merge(mrets, GM1.SR=apply(mrets, 1, MyFunc, ret="GM1.AV120", stdev="GM1.SD120")) mrets <- merge(mrets, IYC.SR=apply(mrets, 1, MyFunc, ret="IYC.AV120",

Interesting problem. I'm very rusty on S4 but would one solution be to, already now, add 'simplify = TRUE' to the S4 method and document it; setMethod("apply", signature(X = "Speclib"), function(X, FUN, bySI = NULL, ..., simplify = TRUE) { ? Henrik On Fri, May 22, 2020 at 6:26

There are a few version of apply() (e.g., lapply(), sapply()). I'm wondering if there is one that does not return anything but just silently apply a function to the list argument. For example, the plot function is applied to each element in 'alist'. It is redundant to return anything from apply. apply(alist,function(x){ plot each element of alist})

Hi Martin, Fair enough for R functions in general. But the behaviour of apply violates the expectation that apply(m, 1, fun) calls fun n times when m has n rows. That seems pretty basic. Also, I understand from your argument why it makes sense to call apply and return a special result (presumably NULL) for an empty argument; but why should apply call fun? Cheers David On Mon, 30 Jul 2018 at

Hi, I had a weird results from using apply(). Here is an simple example: > y<-data.frame(list(a=c(1,NA),b=c('2k','0'))) > y ??? a???? b 1? 1?? 2k 2 NA?? 0 > apply(y,1,function(x){x<-unlist(x); if (!is.na(x[2]) & x[2]=='2k' & !is.na(x[1]) & x[1]=='1') 1 else 0} ) This should print "1 0" as output, as demonstrated by: >

I would like to reference array dimensions by name in an apply and a summary function. For example: apply(x, "workers", sum) Is there a better way to do this than creating a new attribute for the array and then creating new methods for apply and summary? I don't want to name the individual elements of each dimension (such as with dimnames) but rather name the dimensions. Thanks

Hi, I have a function foo(x,y) and a dataframe, DF, comprised of two vectors, x & w, as follows : x w 1 1 1 2 2 1 3 3 1 4 4 1 etc I would like to apply the function foo to each 'pair' within DF e.g foo(1,1), foo(2,1), foo(3,1) etc I have tried >apply(DF,foo) >apply(DF[,],foo) >apply(DF[DF$x,DF$w],foo) However, none of the above worked. Can anyone help ?

...enario: > m <- matrix(1:4, ncol=2) > m [,1] [,2] [1,] 1 3 [2,] 2 4 > apply(m, 2, sum) [1] 3 7 > apply(m, 1, sum) [1] 4 6 So I can apply to rows *or* columns. According to the documentation (?apply) MARGIN a vector giving the subscripts which the function will be applied over. E.g., for a matrix 1 indicates rows, 2 indicates columns, c(1, 2) indicates rows and columns. Where X has named dimnames, it can be a character vector selecting dimension names. But I get the following results: > apply(m, c(1,2), sum) [,1] [,2] [1,] 1 3 [2,] 2 4 Ho...

Dear R'ers, When I used S-plus i wrote a small program for a Mantel-Haenszel test for trend (I think it worked). Unfortunately I can't get it working in R. It appears as if my use of 'el' is the problem but I can't sort it out. Error in apply(array, c(, 2, 3), function(el) el * 1:s) : argument is missing, with no default Further down in the program I use 'el'

Dear all, I would like to use the apply or a similar function belonging to this family, but applying for each column (or row) but let say for each q columns. For example I would like to apply a function FUN for the first q columns of matrix X then for q+1:2*q and so on. If I do apply (X, 2, FUN) it applies for each column and not for every q columns. Is that possible with any similar function?

I thought the "apply" functions are faster than for loops, but my most recent test shows that apply actually takes a significantly longer than a for loop. Am I missing something? It doesn't matter much if I do column wise calculations rather than row wise ## Example of how apply is SLOWER than for loop: #rm(list=ls()) ## DEFINE VARIABLES mu=0.05 ; sigma=0.20 ; dt=.25 ; T=50 ;

Dear subscribers, I have made a simulation using loops rather than apply, simply because the loop function seems more natural to me. However, the current simulation takes forever and I have decided - finally - to learn how to use apply, but - as many other people before me - I am having a hard time changing habits. My current problem is: My current code for the loop is: distances <-

When porting patches from dash git to klibc git, where dash has a different directory structure those switches are handy: Exported with format-patch on dash side and used am as import for klibc side. Signed-off-by: maximilian attems <max at stro.at> --- Documentation/git-am.txt | 5 ++++- git-am.sh | 4 +++- 2 files changed, 7 insertions(+), 2 deletions(-) diff --git

Dear all, 'Apply' is a great thing for running functions on rows or columns of a matrix: X <- rnorm(20, mean = 0, sd = 1) dim(X) <- c(5,4) apply(X,2,sum) Is there a way to use apply for excluding rows or columns from a matrix to run functions on the remaining rows or columns? I know, I could do this with a 'for' loop, but 'apply' would be much easier and