similar to: Possible inconsistency between `as.complex(NA_real_)` and the docs

So, to summarize, the open questions are: (1) Should as.complex(NA_character_) give complex(r=NA_real_, i=0) instead of NA_complex_? (2) Should the first argument in c(NA, x) and c(NA_integer_, x), where typeof(x) == "complex", be promoted to complex(r=NA_real_, i=0) instead of NA_complex_? My opinions: (1) No. The imaginary part of the

>>>>> Mikael Jagan >>>>> on Wed, 8 Nov 2023 11:13:18 -0500 writes: > So, to summarize, the open questions are: > (1) Should as.complex(NA_character_) give complex(r=NA_real_, i=0) > instead of NA_complex_? > (2) Should the first argument in c(NA, x) and c(NA_integer_, x), > where typeof(x) == "complex", be promoted

Hmm, it is not actually at odds with help(c), it is just that the autocoercion works different that it used to, so that as.complex(NA) == as.complex(NA_real) == NA_real_+0i) which now differs from NA_complex although both print as NA. I haven't been quite alert when this change was discussed, but it does look a bit unfortunate that usage patterns like c(NA, 0+1i) does not give complex NA

In R 2.8.0 on Windows (tested both under ESS and under R Console in case there was an I/O issue) There is a bug in printing val <- matrix(list(NA_complex_,NA_complex_),1). > dput(val) structure(list(NA_complex_, NA_complex_), .Dim = 1:2) > print(val) [,1] [1,] [,2] [1,] Note that a large number of spaces are printed instead of NA. Compare the unproblematic real case:

This is another follow-up to the thread from September "Recent changes to as.complex(NA_real_)". A test in data.table was broken by the changes for NA coercion to complex; the breakage essentially comes from c(NA, 0+1i) # vs c(as.complex(NA), 0+1i) The former is the output we tested against; the latter is essentially (via coerceVector() in C) what's generated by our

>>>>> Michael Chirico >>>>> on Sun, 5 Nov 2023 09:41:42 -0800 writes: > This is another follow-up to the thread from September > "Recent changes to as.complex(NA_real_)". > A test in data.table was broken by the changes for NA > coercion to complex; the breakage essentially comes from > c(NA, 0+1i) > # vs

Thanks Martin. My hang-up was not on what the outcome of as.complex(NA) should be, but rather, how I should read code like c(x, y) generally. Till now, I have thought of it like 'c(x, y)' is c(as(x, typeof(y)), y)` when "type(y) > type(x)". Basically in my mind, "coercion" in R <-> as.<newtype>(.) (or coerceVector() in C). So I tracked down the source

Hi, I have discovered that sample() fails with an uninformative error message when the x argument is a single NA of type double or integer. I can reproduce the problem with the following code: base::sample(NA) # NA is of logical type above base::sample(NA_character_) base::sample(NA_complex_) base::sample(NA_real_) base::sample(NA_integer_) The last two lines throw the following error: Error

According to http://cran.r-project.org/doc/manuals/r-release/R-lang.html#Reserved-words if else repeat while function for in next break TRUE FALSE NULL Inf NaN NA NA_integer_ NA_real_ NA_complex_ NA_character_ ... ..1 ..2 etc. are all reserved keywords. However, in R 3.0.2 you can do things like: `if` <- function(cond, val1, val2) val2 after which if(TRUE) 1 else 2 returns 2.

I am trying to set up a data set for a survival analysis with time-varying covariates. The data is already in a long format, but does not have a variable to signify the stopping point for the interval. The variable DaysEnrolled is the variable I would like to use to form this interval. This is what I have now: ID Age DaysEnrolled HAZ WAZ WHZ Food onARV

Consider #as.numeric for emphasis sprintf('%d', as.numeric(1)) # [1] "1" vs. sprintf('%d', NA_real_) > Error in sprintf("%d", NA_real_) : invalid format '%d'; use format %f, %e, %g or %a for numeric object > I understand the error is correct, but if it works for other numeric input, why doesn't R just coerce NA_real_ to NA_integer_?

I don't see this specific case documented anywhere (I also tried to search the r-devel archives, as well as I could); the only close reference mentions NA & FALSE = FALSE, NA | TRUE = TRUE. And there's also this snippet from R-lang: In cases where the result of the operation would be the same for all > possible values the NA could take, the operation may return this value. >

I initially thought this is "documented behaviour". ?sprintf says: Numeric variables with __exactly integer__ values will be coerced to integer. (emphasis mine). Turns out this only works when the first value is numeric and not NA, as shown by the following example: > sprintf("%d", as.numeric(c(NA,1))) Error in sprintf("%d", as.numeric(c(NA, 1))) : invalid

https://github.com/Rdatatable/data.table/issues/2171 The fix was easy, it's just surprising to see the behavior change almost on a whim. Just wanted to point it out in case this is unknown behavior, but Evan seems to have found this as well. On Tue, May 23, 2017 at 12:00 PM, Michael Chirico <michaelchirico4 at gmail.com > wrote: > Astute observation. And of course we should be

On Linux when I compile R 2.10.0(devel) (src/main/arithmetic.c in particular) with gcc 3.4.5 using the flags -g -O2 I get noncommutative behavior when adding NA and NaN: > NA_real_ + NaN [1] NaN > NaN + NA_real_ [1] NA If I compile src/main/arithmetic.c without optimization (just -g) then both of those return NA. On Windows, using a precompiled R 2.8.1 from CRAN I get NA for

I'm observing that base::sum(x, na.rm=FALSE) for typeof(x) == "double" is much more time consuming when there are missing values versus when there are not. I'm observing this on both Window and Linux, but it's quite surprising to me. Currently, my main suspect is settings in on how R was built. The second suspect is my brain. I hope that someone can clarify the below

Hi, Tested with the latest r-devel snapshot build for Windows (2009-05-28 r48663): > png("test.png") Error in png("test.png") : invalid value of 'fillOddEven' The png() function is defined like this: > png function (filename = "Rplot%03d.png", width = 480, height = 480, units = "px", pointsize = 12, bg = "white", res = NA,

This is a great example how you cannot figure it out after spending two hours troubleshooting, but a few minutes after you post to R-devel, it's just jumps to you (is there a word for this other than "impatient"?); Let me answer my own question. The discrepancy between my sum2() code and the internal code for base::sum() is that the latter uses LDOUBLE = long double (on some system

#is there a way to get NA in the table of descriptive statistics instead of the function stopping Thank you in advance #data x.f <- structure(list(Site = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("BC", "HC", "RM119", "RM148", "RM179", "RM185",

Hello, I have the following loop for two data sets: diveData_2008 and diveData_2009. It uses two other data: diveCond_all and fishTable. The problem is at the point to identify the dive_id for the given index (index is timestamp). It keeps on saying for the1st loop Error in fishReport$dive_id[i] <- dive_id : replacement has length zero for the 2nd loop Error in fishReport$dive_id[i + j] <-