similar to: seq.int broken (seq as well) (PR#14169)

I have a script that goes wrong because I assumed that seq.int would return integers. Below please see it does not unless user is super cautious about inserting "L" with inputs. I think seq.int should do coercion for me before returning the sequence. > xx <- seq.int(1,10) > class(xx) [1] "integer" > is.integer(xx) [1] TRUE > xx <- seq.int(1,10, 2) >

Hi, Does anyone know where the following package is available: Holleczek B, Gondos A, Brenner H. PeriodR - an R package to calculate long term survival estimates using period analysis. Methods of Information in Medicine 2009; 48: 123-128. Thanks Jens Oehlschl?gel -- GRATIS f?r alle GMX-Mitglieder: Die maxdome Movie-FLAT!

Hi, Is there any official way to determine the colClasses of a data.frame? Why has POSIXct such a strange class structure? Why is colClasses "ordered" not allowed (and doesn't work)? Background ========== I am writing a chunked csv reader that provides the functionality of read.table for large files (in the next version of package ff). In chunked reading, one wants to learn the

Dear all, differing from the standard behaviour of 'format' the current (2.7.0) 'format.factor' destroys attributes like 'dim' and 'dimnames'. This unfortunately breaks some general code in the new package 'ff' for large file-based data which will support vectors and arrays of atomic and factors. It would be nice if you could include the following fix in

I am going to document a 10.000 lines of R code project. Before reinventing the wheel, has anyone written a function that analyzes dependencies between R functions? I am thinking of output like caller1 calee1 caller1 calee2 caller1 : caller2 calee7 : and I would like to restrict caller and callee to certain positions in the search path. My guess is, that a quick and dirty solution is

I am going to document a 10.000 lines of R code project. Before reinventing the wheel, has anyone written a function that analyzes dependencies between R functions? I am thinking of output like caller1 calee1 caller1 calee2 caller1 : caller2 calee7 : and I would like to restrict caller and callee to certain positions in the search path. My guess is, that a quick and dirty solution is

Is it intended that version$os no longer is 'Win32' for the Windows-Compile? What is the approbriate way to check for Windows? Best Jens Oehlschl?gel In 1.4.1 we had > version _ platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 4.1 year

Try to close the file on the first nfs client before reopening it on the second nfs client. NFS has something called "close-to-open cache consistency". This means that two clients which have the same nfs file open, cannot rely on seeing the updates from the respective other client. If one clients closes, and the other client opens thereafter, it should see the changes. If you want

Can please someone familiar with the R internals enlighten me on the following strange observation: # this is IDENTICAL as expected identical(substitute(substitute()), substitute(substitute())) # but NOT EQUAL !???? substitute(substitute()) == substitute(substitute()) # I originally found it on t2 <- function(e){ substitute(e) } t2(substitute(x==y, list(y=y)))[1] # I would expect all

Can please someone familiar with the R internals explain on the following: PR#1434 from r-bugs clarifies that assign("a[1]", x, SomeOtherFrame) or assign("a$a", x, SomeOtherFrame) will NOT assign to an object 'a' in the other frame BUT create a new object called 'a[1]' resp. 'a$a'. This leads to the following question: what is the most

Dear all, is there any function to calculate the center of a polygon mass in R? Actually I need to find the best location within polygons to place labels. Thanks for any hint Jens Oehlschl?gel -- COMPUTERBILD 15/03: Premium-e-mail-Dienste im Test\ --------...{{dropped}}

Dear all, Has someone implemented in R (or any other language) Knol DL, ten Berge JMF. Least-squares approximation of an improper correlation matrix by a proper one. Psychometrika, 1989, 54, 53-61. or any other similar algorithm? Best regards Jens Oehlschl?gel Background: I want to factanal() matrices of polychoric correlations which have negative eigenvalue. I coded Highham 2002

>>>>> Mick Jordan <mick.jordan at oracle.com> >>>>> on Tue, 3 Jan 2017 07:57:15 -0800 writes: > This is a message for someone familiar with the implementation. > Superficially the R code for seq.default and the C code for seq.int > appear to be semantically very similar. My question is whether, in fact, > it is intended that

I believe the performance of isUnsorted() in sort.c could be improved by calling REAL() once (outside of the for loop), rather than calling it twice inside the loop. As an aside, it is implemented in the faster way in doSort() (sort.c line 401). The example below shows the performance improvement for a vectors of double of moving REAL() outside the for loop. # example as implemented in

>>>>> Mick Jordan <mick.jordan at oracle.com> >>>>> on Wed, 4 Jan 2017 08:15:03 -0800 writes: > On 1/4/17 1:26 AM, Martin Maechler wrote: >>>>>>> Mick Jordan <mick.jordan at oracle.com> >>>>>>> on Tue, 3 Jan 2017 07:57:15 -0800 writes: >> > This is a message for someone familiar

I wonder what is the history of "seq" and "seq.int"? >From "help(seq)", one reads that "'seq.int' is an internal generic which can be much faster but has a few restrictions". And indeed, "seq.int(1,99,by=2)" is over 40 times faster than "seq(1,99,by=2)" in a quick test I just did. This is not surprising given that

... and also all objects that actually live in the .GenericArgsEnv environment. > all( sapply( ls( .GenericArgsEnv ), function(.) is.null(environment(.)) ) ) [1] TRUE This has the consequence preventing argsAnywhere to get the args of seq.int. > argsAnywhere( seq.int ) Error in exists(".packageName", envir = envir, inherits = FALSE) : use of NULL environment is defunct

This is a message for someone familiar with the implementation. Superficially the R code for seq.default and the C code for seq.int appear to be semantically very similar. My question is whether, in fact, it is intended that behave identically for all inputs. I have found two cases so far where they differ, first that seq.int will coerce a character string to a real (via Rf_asReal) whereas

> .Internal(inspect(1:10)) @300e4e8 13 INTSXP g0c0 [NAM(3)] 1 : 10 (compact) > .Internal(inspect(seq(1,10))) @3b6e1f8 13 INTSXP g0c4 [] (len=10, tl=0) 1,2,3,4,5,... > system.time(1:1e7) user system elapsed 0 0 0 > system.time(seq(1,1e7)) user system elapsed 0.05 0.00 0.04 It seems that result of function 'seq' doesn't use compact

names(unlist(...)) seems to be able to construct corrupt strings detected via: two identical strings behave different in paste observed in RW1.4.1 and RW1.5.0 pure replication code after output Best Jens Oehlschlägel > l <- names(unlist(list(aa = list(bb = 1)))) > l [1] "aa.bb" > # this is exactly "aa.bb" > identical(l, "aa.bb") [1] TRUE > >