similar to: Rprof and setMethod conflict?

Hello, (This is follow up from this thread: http://www.nabble.com/execution-time-of-.packages-td22304833.html but with a different focus) I am often confused by the result of the profiler, when a loop is involved. Consider these two scripts: script1: Rprof( ) x <- numeric( ) for( i in 1:10000){ x <- c( x, rnorm(10) ) } Rprof( NULL ) print( summaryRprof( ) ) script2:

Hi Consider the following example: f <- function(expr) g(expr) g <- function(expr) { ? h(expr) } h <- function(expr) { ? expr # evaluation happens here ? i(expr) } i <- function(expr) { ? expr # already evaluated, no costs here ? invisible() } rprof <- tempfile() Rprof(rprof) f(replicate(1e2, sample.int(1e4))) Rprof(NULL) cat(readLines(rprof), sep = "\n") #>

I'm having difficulty with Rprof. I have a documentation example test.qss that runs fine without profiling, but under Rprof, > Rprof() > source("test.qss") Error in standardGeneric("model.matrix") : UseMethod used in an inappropriate fashion Luke wrote about a similar circumstance last summer: # From: Luke Tierney (luke@stat.umn.edu) # Date: Fri Jul

Full_Name: Jelle Goeman Version: 1.9.0 OS: mingw32, windows 2000 Submission from: (NULL) (145.88.209.33) Hi Everyone, I get very strange results using the function hasArg with the ... function argument. In my own function: > gt <- globaltest(X,Y) > sampling(gt) works fine, but > sampling(globaltest(X,Y)) results in: Error in eval(expr, envir, enclos) : "missing"

Full_Name: Kevin C. Bartz Version: 1.5.1 OS: Solaris 2.6 Submission from: (NULL) (192.223.226.5) A while ago, I noticed this oddity about R profiling and setMethod. First, I "test out" Rprof. > require(methods) Loading required package: methods [1] TRUE > > Rprof("test.out") > data.frame("a") X.a. 1 a > Rprof(NULL) So far, so good. Next, I

I'm picking up this 5-year old thread. 1. About the four memory allocations without a stacktrace I think the four memory allocations without a stacktrace reported by Rprofmem(): > Rprofmem(); x <- raw(2000); Rprofmem("") > cat(readLines("Rprofmem.out", n=5, warn=FALSE), sep="\n") 192 :360 :360 :1064 :2040 :"raw" are due to some

I noticed this oddity about [ and setMethod. First, I define testFunc, which sorts a data frame by the first column and returns the entries that aren't NAs, and testIt, which runs testFunc repeatedly on a random large data frame, each time saving the return into a dummy placeholder (for demonstration's sake). > require(methods) Loading required package: methods [1] TRUE > testFunc

I noticed this oddity about [ and setMethod. First, I define testFunc, which sorts a data frame by the first column and returns the entries that aren't NAs, and testIt, which runs testFunc repeatedly on a random large data frame, each time saving the return into a dummy placeholder (for demonstration's sake). > require(methods) Loading required package: methods [1] TRUE > testFunc

I am having some difficulties using dynamically loaded C functions on a Sparc 10 with R compiled using cc (both R-0.49 and R-0.50). I get sporadic errors with the error message: Error: character variables must be duplicated in .C/.Fortran, with C functions which pass character variables. my C functions look like: anyfunc(char **filename, other variables ) This error message appears about 25%

I am having some difficulties using dynamically loaded C functions on a Sparc 10 with R compiled using cc (both R-0.49 and R-0.50). I get sporadic errors with the error message: Error: character variables must be duplicated in .C/.Fortran, with C functions which pass character variables. my C functions look like: anyfunc(char **filename, other variables ) This error message appears about 25%

John Chambers suggested that I forward this thread (first posted to r-help) along to r-devel... Thanks, Kevin -----Original Message----- From: John Chambers [mailto:jmc@research.bell-labs.com] Sent: Tuesday, August 06, 2002 6:31 PM To: Bartz, Kevin Cc: r-help@stat.math.ethz.ch Subject: Re: [R] [ and setMethod conflict? Definitely something funny going on, but perhaps a little less sweeping

I'm a day-old R newbie (but a war-weary S veteran), with couple of first-day questions: In R 0.61, this code fails. Ops.test <- function(e1,e2) { e1 <- NextMethod(.Generic) e1 } x <- 4 class(x) <- "test" y <- x < 3 The error message is "Error in NextMethod(.Generic) : negative length vectors are not allowed.". I assume it is a bug.

Hi R-helper! I have problem with setMethods for "[". Here is example : setClass("myClass", representation(ID.r = "numeric", ID.c = "character", DAT = "matrix")) to.myClass <- function(ID.r, ID.c, DAT) {     out <- new("myClass", ID.r = ID.r, ID.c = ID.c, DAT = DAT)     return(out)       }       setMethod("[",

Hi R-Help, Please consider the following simple case: I have a class like setClass("myClass", representation(x="matrix", y="character")) and I would like to use the method *"["* for a *myClass* objects (but changing the default *drop* argument from TRUE to FALSE): setMethod("[","myClass", function(x,i,j,...,drop=FALSE)

Hello, I have defined a new class > setClass("myclass", representation(min = "numeric", max = "numeric")) and want to write accessor functions, so that for > foo = new("myclass", min = 0, max = 1) > min(foo) # prints 0 > max(foo) # prints 1 At first i created a generic function for "min" > setGeneric("min",

I'm using R 1.8.1 (Win32, Linux) and have some difficulties using validation functions for S4 classes. The problem is if I specify a validation function with setValidity("myclass", validate.myclass) object validation is only performed when I create an instance using new("myclass"), or when I explicitly call validObject(x) where x is of class "myclass", of

The Rprofmem facility is currently enabled only if the configuration option --enable-memory-profiling is used. However, the overhead of having it enabled is negligible when profiling is not actually being done, and can easily be made even smaller. So I think it ought to be enabled all the time. I've attached a patch doing this, which also makes a number of other improvements to Rprofmem,

Hello R-help: I was hoping someone could help me understand a particular function i came across in a package: "$.myClass" <- function( x, name ) { sym = paste( "foo", name, sep = "_" ) if( is.loaded(sym) ) .Call(sym,x) } I understand the paste, and .Call part, but I'm not sure how this function would get called? What exactly is

Hello: I have written some an elementary S4 classes around a matrix to strengthen control of some key attributes. When I run a fairly elementary function ("f") on the matrix outside the class it runs instantaneously (elapsed system.time = 0) but when I setMethod "f" on myClass -- returning an instance of myClass -- it runs perceptibly slower (elapsed system.time = .06). I

I do lots of analyses on large microarray data sets so memory use and speed and both important issues for me. I have been trying to estimate the overheads associated with using formal S4 data objects instead of ordinary lists for large data objects. In some simple experiments (using R 1.7.1 in Windows 2000) with large but simple objects it seems that giving a data object a formal class