similar to: loop question

Would anyone object to an attempt to improve cast<> error messages by outputting the expected type and the type received? The interface I'm thinking of is to use ADL to do visitor-style lookup, so we don't need to change every client. In particular, for clients in clang, we can just create these functions implicitly from our TableGen-generated files. I'm not sure about

Gracias, Jorge. Y cual fue la solucion a la que llegaron? --JIV Sent from my phone. Please excuse my brevity and misspelling. On Aug 25, 2013, at 8:36 AM, Jorge Ayuso Rejas <jayusor@gmail.com> wrote: Esto lo hice yo en una práctica en la universidad, Definíamos un problema de optimización entera minimizando el error de redondeo y restringiendo a la suma de filas y columnas. El 23 de

Hi, I have a dataset with a response variable and multiple factors with more than two levels, which I have been fitting using lm() or glm(). In these fits, I am generally more interested in deviations from the global mean than I am in comparing to a "control" group, so I use contr.sum() as the factor contrasts. I think I'm happy to interpret the coefficients in the model summary

I bumped into the following situation: Browse[1]> coef deg0NA deg4NA deg8NA deg0NP deg4NP deg8NP (Intercept) 462 510 528 492 660 762 Browse[1]> coef[,1] [1] 462 Browse[1]> coef[,1,drop=F] deg0NA (Intercept) 462 where I really wanted neither, but (Intercept) 462 Anyone happen to know a neat way out of the conundrum? I can think of

Dear all, Even though one of R users answered my question, I cannot understand, so I re-ask this question. I am trying to use "do.call", but I don't think I totally understand this function. Here is an simple example. -------------------------------------------- > B <- matrix(c(.5,.1,.2,.3),2,2) > B [,1] [,2] [1,] 0.5 0.2 [2,] 0.1 0.3 > x <- c(.1,.2) >

Say I have the following data: testDat <- data.frame(A = c(1,NA,3), B = c(NA, NA, 3)) > testDat A B 1 1 NA 2 NA NA 3 3 3 rowsums() with na.rm=TRUE generates the following, which is not desired: > rowSums(testDat[, c('A', 'B')], na.rm=T) [1] 1 0 6 rowsums() with na.rm=F generates the following, which is also not desired: > rowSums(testDat[, c('A',

Dear all, I am trying to extract rows from a data.frame based on the rowSums != 0. I want to preserve rownames in the first column in the subset. Does anyone know how to extract all species that don't have rowSums equal to zero? Here it is: # dataset x <- data.frame( species=c("sp.1","sp.2","sp.3","sp.4"), site1=c(2,3,0,0), site2=c(0,0,0,0),

Hi Berend, I see you are one of the contributors to the rbecnhmark package. I am sorry that I am bothering you again. I have tried to run your code (slightly tweaked) involving the benchmark function, and I am getting the following error message. What am I doing wrong? Error in benchmark(d1 <- s1(df), d2 <- s2(df), d3 <- s3(df), d4 <- s4(df), : could not find function

Working with an NxMxO sized matrix, currently I can do this in my code: if (max(colSums(array)) >= number) But to get an equivalent result using rowSums, I have to do: for (i in 1:10) { if (max(rowSums(array[,,i])) >= number) } I'm running both in a much larger loop that loops millions of times, so speed and such is quite a big factor for me. Currently, the colSums line uses about

Dear All, in some functions of my package, I use the Matrix S4 class, as defined in the Matrix package. I don't want to depend on Matrix, however, because my package is perfectly fine without Matrix, most of the functionality does not need Matrix. Matrix is so included in the 'Suggests' line. I load Matrix via require(), from the functions that really need it. This mostly works

Hi, I'm using colSums and rowSums to sum the first dimensions of arrays. It works ok but the resulting object is different. See > a3d <- array(rnorm(120, mean=2), dim=c(20,6,1)) > dim(colSums(a3d)) [1] 6 1 > dim(rowSums(a3d)) NULL > class(colSums(a3d)) [1] "matrix" > class(rowSums(a3d)) [1] "numeric" I was expecting rowSums to preserve the array

Hi all I have a data frame with duplicate columns and i want to remove duplicates by adding rows in each group of duplicates, but have lots of NA's. Data: dfrm <- data.frame(a = 1:4, b= 1:4, cc= 1:4, dd=1:10, ee=1:4) names(dfrm) <- c("a", "a", "b", "b", "b") dfrm[3,2:3]<-NA dfrm a a b b b 1 1 1 1 1 1 2 2 2 2 2 2 3

Dear list users, let me ask you this trivial question. I worked on that for a long time, by now. Suppose to have a data frame with NAs and to sum some columns with rowSums: df <- data.frame(A = runif(10), B = runif(10), C = rnorm(10)) df[1, ] <- NA rowSums(df[ , which(names(df) %in% c("A","B"))], na.rm=T) If all the elements of the selected columns are NA, rowSums

Dear all, I am trying to use "do.call", but I don't think I totally understand this function. Here is an simple example. -------------------------------------------- > B <- matrix(c(.5,.1,.2,.3),2,2) > B [,1] [,2] [1,] 0.5 0.2 [2,] 0.1 0.3 > x <- c(.1,.2) > X <- cbind(1,x) > X x [1,] 1 0.1 [2,] 1 0.2 > > lt <-

Dear R users, I??ve got a simple question but somehow I can??t find the solution: I have a data frame with columns 1-5 containing one set of integer values, and columns 6-10 containing another set of integer values. Columns 6-10 contain NA??s at some places. I now want to calculate (1) the number of values in each row of columns 6-10 that were NA??s (2) the sum of all values on columns 1-5

Dear all, I have a big problem: - I got two matrices, A and B - A shows identifies the value of B, however the values of B must be summed - For instance, 1 1 2 2 2 2 1 1 gives matrix a 3 4 2 1 1 1 2 2 gives matrix b Now the result for the value 1 would be 7 4 which are the rowsums of the values of matrix B given that matrix A has the value 1. How can I do this automatically? I

Hi, I have a matrix, say m=matrix(c( 983,679,134, 383,416,84, 2892,2625,570 ),nrow=3 ) i can find its row/col sum by rowSums(m) colSums(m) How do I divide each row/column by its rowSum/colSums and still return in the matrix form? (i.e. the new rowSums/colSums =1) Thanks. Casper -- View this message in context:

Hi [R-2.6.0, macOSX 10.4.10]. The helppage says that rowSums() and colSums() are equivalent to 'apply' with 'FUN = sum'. But I came across this: > a <- matrix(1:30,5,6) > is.integer(apply(a,1,sum)) [1] TRUE > is.integer(rowSums(a)) [1] FALSE > so rowSums() returns a float. Why is this? -- Robin Hankin Uncertainty Analyst National Oceanography Centre,

Dear R-help community, If I have a data.frame df as follows: > df x1 x2 x3 x4 x5 x6 1 5 5 1 1 2 1 2 5 5 5 5 1 5 3 1 5 5 5 5 5 4 5 5 1 4 5 5 5 5 1 5 2 4 1 6 5 1 5 4 5 1 7 5 1 5 4 4 5 8 5 1 1 1 1 5 9 1 5 1 1 2 5 10 5 1 5 4 5 5 11 1 5 5 2 1 1 12 5 5 5 4 4 1 13 1 5 1 4 4 1 14 1 1 5 4 5 5 15 1 5 5 4

Hello, I'm having a litle issue with Xapian-1.0.6 with php bindings under php5 when trying to add a new document it throws: Fatal error: Uncaught exception 'Exception' with message 'DatabaseCorruptError: Failed to unlink /var/lib/xapian/trade.ar/termlist.baseA: No such file or directory' in /usr/share/php5/xapian.php:1140 Stack trace: #0 /usr/share/php5/xapian.php(1140):