similar to: hasNA() / anyNA()?

Inside of the anyNA() function, it will use the legacy any(is.na()) code if x is an OBJECT(). If x is a vector of POSIXct, it will be an OBJECT(), but it is also TYPEOF(x) == REALSXP. Therefore, it will skip the faster ITERATE_BY_REGION, which is typically 5x faster in my testing. Is the OBJECT() condition really necessary, or could it be moved after the switch() for the individual TYPEOF(x)

Hi, I'm just following your messages the overhead that the code for dealing with possible NA/NaN values brings. When I was setting up part of the matrixStats package, I've also though about this. I was thinking of having an additional logical argument 'hasNA'/'has.na' where you as a user can specify whether there is NA/NaN:s or not, allowing the code to avoid it or not.

Hello, When building R from source, during the part where the 'tools' package is built, I get: make[6]: Entering directory `/home/btyner/R-3.1.1/src/library/tools/src' make[6]: Leaving directory `/home/btyner/R-3.1.1/src/library/tools/src' make[5]: Leaving directory `/home/btyner/R-3.1.1/src/library/tools/src' make[4]: Leaving directory

>>>>> Harvey Smith >>>>> on Wed, 1 May 2019 03:20:55 -0400 writes: > Inside of the anyNA() function, it will use the legacy any(is.na()) code if > x is an OBJECT(). If x is a vector of POSIXct, it will be an OBJECT(), but > it is also TYPEOF(x) == REALSXP. Therefore, it will skip the faster > ITERATE_BY_REGION, which is typically 5x

Hi, I've spotted a possible memory leakage/violation in the latest R v2.1.1 patched and R v2.2.0dev on Windows XP Pro SP2 Eng. I first caught it deep down in a nested svd algorithm when subtracting a double 'c' from a integer vector 'a' where both had finite values but when assigning 'a <- a - c' would report NaNs whereas (a-c) alone would not. Different runs

Dear all, It was a pleasure to meet you at Iowa State University. Two days ago I submitted two experimental packages to CRAN (hope it will be there soon): rindex: quick indexing of large objects (currently only character, see ?index) regtest: some first support for automated regression testing (heavily used in \dontshow{} section of ?index) With rindex you can for example i <-

Hi, I am not sure if this is a bug or a non-implement feature of text-drawing functions with TeX-style expression, but hat() and some of its equals does not get the right "bounding boxes" if they are put in sub- or superscripts. For instance, for the expression 'b[hat(a)]' the hat() seems to shift 'hat(a)' too much to the right of 'b'. Try the below example and

Hi, I am puzzled with serialize(). It comes down generating identical hash codes for (apparently) identical objects using digest::digest(), which in turn relies on serialize(). Here is an example illustration the issue: ser <- function(object, ...) { list( names = names(object), namesRaw = charToRaw(names(object)), ser = serialize(names(object), connection=NULL, ascii=FALSE)

Hi, I've got two suggestions how to speed up median() about 50%. For all iterative methods calling median() in the loops this has a major impact. The second suggestion will apply to other methods too. This is what the functions look like today: > median function (x, na.rm = FALSE) { if (is.factor(x) || mode(x) != "numeric") stop("need numeric data")

I have a data set like this in one .txt file (cols separated by !): APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! APE!KKU!684! APE!VAL!! APE!UASU!! APE!PLA!1! APE!E!10! APE!TPVA!17122009! APE!STAP!1! GG!KK!KK! it contains over 14 000 000 records. Now

Below is a version of [.data.frame that is faster for subscripting rows of large data frames; it avoids calling duplicated(rows) if there is no need to check for duplicate row names, when: i is logical attr(x, "dup.row.names") is not NULL (S+ compatibility) i is numeric and negative i is strictly increasing "[.data.frame" <- function (x, i, j,

Dear all, I am stuck at applying loop function for creating separated plots. I have coding like below: dataset.table <- table(data.frame(var1=c(1,2,3,1,2,3,1),colour=c("a","b","c","c","a","b","b") )) kk = function(f) { ls=as.character(f) pie(dataset.table[ls,],main=ls)

This came up on r-help but indicates a bug. dnbinom(x,n,p) calls dbinom_raw(n-1,...) which returns 0 for n<1. -thomas ---------- Forwarded message ---------- Date: Thu, 08 Feb 2001 17:10:23 +0000 From: Yudi Pawitan <yudi@stat.ucc.ie> To: Mark Myatt <mark@myatt.demon.co.uk> Cc: R-Help <r-help@stat.math.ethz.ch> Subject: Re: [R] Goodness of fit to Poisson / NegBinomial

Hello, how to merge a data.frame and a matrix by one column in the data.frame and rownames of the matrix? df <- data.frame(col1=c("kk","yy","kk"),col2=c(6,4,3)) > df   col1 col2 1   kk    6 2   yy    4 3   kk    3 m<-matrix(c(3,8,56,9), nrow=2, dimnames = list(c("aa","kk"),c("col1","col2"))) > m    col1 col2 aa   

Dear all, I am dealing with the following (apparently simple problem): For some reasons I am interested in passing variables from a dataframe to a specific environment, and in fitting a standard glm: dati<-data.frame(y=rnorm(10),x1=runif(10),x2=runif(10)) KK<-new.env() for(i in 1:ncol(dati)) assign(names(dati[i]),dati[[i]],envir=KK) #Now the following two lines work correctly:

Dear folks? Is there a function to correctly find (and count) the NAs in a factor when exclude=NULL, regardless of whether their origin is in the original data or by subsequent assignment? In example number 1 below, where NAs are assigned by is.na()<-, testing the factor with is.na() finds the correct number of NAs. In example number 2, where the NAs are from the data, neither is.na(), ==NA,

I've redirected this reply from r-help to the bugs list. On 11/3/2006 8:25 AM, vito muggeo wrote: > Dear all, > I am dealing with the following (apparently simple problem): > For some reasons I am interested in passing variables from a dataframe > to a specific environment, and in fitting a standard glm: > > dati<-data.frame(y=rnorm(10),x1=runif(10),x2=runif(10)) >

Hi there, I am trying to understand how AliasAnalysis works out in LLVM. I used the following simple test-case (test4.c): -- void test() { int *jj, *kk; int aa = 100; jj = &aa; *jj = 300; } int main() { test(); return 0; } -- Then I did "llvm-gcc -emit-llvm -c -o test4.bc test4.c" to get bc. I tried the following 2 ways to get what I expect to get as

Hello all: I don't know what I'm doing bad, but --link-dest does not work for me: I have three directories, the original one, the first copy and the second copy I want to populate: $ ls -li total 12 1761433 drwxr-xr-x 2 envite envite 4096 dic 10 14:04 copy1 1761434 drwxr-xr-x 2 envite envite 4096 dic 11 01:18 copy2 1761432 drwxr-xr-x 2 envite envite 4096 dic 10 14:04 origin $ ls -li *

Hi, When validating users on my Linux system against an ActiveDirectory, the Windows event log are filled with messages like these (Windows Event ID 675): Pre-authentication failed: User Name: linux$ User ID: KK\linux$ Service Name: krbtgt/KK.LOCAL Pre-Authentication Type: 0x0 Failure Code: 0x19 Client