similar to: Documentation for is.atomic and is.recursive

What is the recommended class for time of day (independent of calendar date)? And what is the recommended way to get the time of day from a POSIXct object? (Not a string representation, but a computable representation.) I have looked in the man page for DateTimeClasses, in the Time Series Analysis Task View and in Spector's Data Manipulation book but haven't found these. Clearly I can

Tested in: R version 2.8.1 (2008-12-22) / Windows Recursive default argument references normally give nice clear errors. In the first set of examples, you get the error: Error in ... : promise already under evaluation: recursive default argument reference or earlier problems? (function(a = a) a ) () (function(a = a) c(a) ) () (function(a = a) a[1] ) () (function(a = a)

Since both comparison and negation are well-defined for time differences, I wonder why abs and division are not defined for class difftime. This behavior is clearly documented on the man page: "limited arithmetic is available on 'difftime' objects"; but why? Both are natural, semantically sound, and useful operations and I see no obvious reason that they should give an error:

Since both comparison and negation are well-defined for time differences, I wonder why abs and division are not defined for class difftime. This behavior is clearly documented on the man page: "limited arithmetic is available on 'difftime' objects"; but why? Both are natural, semantically sound, and useful operations and I see no obvious reason that they should give an error:

The semantics of [ and [[ don't seem to be fully specified in the Reference manual. In particular, I can't find where the following cases are covered: > cc <- c(1); ll <- list(1) > cc[3] [1] NA OK, RefMan says: If i is positive and exceeds length(x) then the corresponding selection is NA. > dput(ll[3]) list(NULL) ? i is positive and exceeds length(x); why isn't this

In another thread recursive snapshot creation was found atomic so that it is done quickly, and more important, all at once or nothing at all. Do you know if recursive destroying and renaming of snapshots are atomic too? Regards Henrik Heino

I'm new to R and very excited about its possibilities. But I'm struggling with some very simple things, probably because I haven't found the correct documentation. Here's a simple example which illustrates several of my problems. Suppose I want to have a regexp match against a string, and return all the matching substrings in a vector of strings. regexp <-

In 2.8.1/Windows: According to ? : Details: For numeric arguments 'from:to' is equivalent to 'seq(from, to)' ... Value: For numeric arguments, a numeric vector. This will be of type 'integer' if 'from' and 'to' are both integers and representable in the integer type, otherwise of type 'numeric'.... The first claim

I've read in many places that R semantics are based on Scheme semantics. As a long-time Lisp user and implementor, I've tried to make this more precise, and this is what I've found so far. I've excluded trivial things that aren't basic semantic issues: support for arbitrary-precision integers; subscripting; general style; etc. I would appreciate corrections or additions from

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)

I have two vectors, a and b. b is a text file. I want to find in b those elements of a which occur at the beginning of the line in b. I have the following code, but it only returns a value for the first value in a, but I want both. Any ideas please. a = c(2,3) b = NULL b[1] = "aaa 2 aaa" b[2] = "2 aaa" b[3] = "3 aaa" b[4] = "aaa 3 aaa"

Inspired by the exchange between Rolf Turner and Wacek Kusnierczyk, I thought I'd clear up for myself the exact relationship among the various sequence concepts in R, including not only generic vectors (lists) and atomic vectors, but also pairlists, factor sequences, date/time sequences, and difftime sequences. I tabulated type of sequence vs. property to see if I could make sense of all

Inspired by the exchange between Rolf Turner and Wacek Kusnierczyk, I thought I'd clear up for myself the exact relationship among the various sequence concepts in R, including not only generic vectors (lists) and atomic vectors, but also pairlists, factor sequences, date/time sequences, and difftime sequences. I tabulated type of sequence vs. property to see if I could make sense of all

In R 2.9.1 Windows: > nchar(factor(paste('sdf',1:10))) [1] 1 1 1 1 1 1 1 1 2 1 so it appears that nchar is counting the number of characters in the numeric representation, just like: > nchar(as.numeric(factor(paste('sdf',1:10)))) [1] 1 1 1 1 1 1 1 1 2 1 but ?nchar says explicitly: x: character vector, or a vector to be coerced to a character vector.

I recently traced a bug of mine to the fact that cumsum(s)[length(s)] is not always exactly equal to sum(s). For example, x<-1/(12:14) sum(x) - cumsum(x)[3] => 2.8e-17 Floating-point addition is of course not exact, and in particular is not associative, so there are various possible reasons for this. Perhaps sum uses clever summing tricks to get more accurate results? In some

To test two environments for object equality (Lisp EQ), I can use 'identity': > e1 <- environment(local(function()x)) > e2 <- environment(local(function()x)) > identical(e1,e2) # compares object identity [1] FALSE > identical(as.list(e1),as.list(e2)) # compares values as name->value mapping [1] TRUE # (is there a

On Tue, Feb 10, 2009 at 10:11 AM, Duncan Murdoch <murdoch at stats.uwo.ca> wrote: > Stavros Macrakis wrote: >> On Tue, Feb 10, 2009 at 8:31 AM, Duncan Murdoch <murdoch at stats.uwo.ca>wrote: >>> The evaluator recognizes the context of usage and will get the >>> function for a function call.... >> Can you point me to chapter and verse in the language

What is the 'idiomatic' way of writing a vectorized switch statement? That is, I would like to write, e.g., vswitch( c('a','x','b','a'), a= 1:4, b=11:14, 100 ) => c(1, 100, 13, 4 ) equivalent to ifelse( c('a','x','b','a') ==

I was surprised to find that df$a[1] is an order of magnitude faster than df[1,"a"]: > df <- data.frame(a=1:10) > system.time(replicate(100000, df$a[3])) user system elapsed 0.36 0.00 0.36 > system.time(replicate(100000, df[3,"a"])) user system elapsed 4.09 0.00 4.09 A priori, I'd have thought that combining the row and column

R factors are the natural way to represent factors -- and should be efficient since they use small integers. But in fact, for many (but not all) operations, R factors are considerably slower than integers, or even character strings. This appears to be because whenever a factor vector is subsetted, the entire levels vector is copied. For example: > i1 <- sample(1e4,1e6,replace=T) > c1