similar to: logical masking of a matrix converts it to a vector

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

Full_Name: Doug Grove Version: 1.7.0 OS: Linux Submission from: (NULL) (209.31.211.56) Hi, Minor mistake in the documentation on the colSums page. In the ARGUMENTS section it states for 'dims' that: For `col*', the sum or mean is over dimensions `dims+1, ...'; for `row*' it is over dimensions `1:dims'. These two are reversed. Thanks, Doug Grove

> On Oct 21, 2017, at 7:50 AM, Martin Maechler <maechler at stat.math.ethz.ch> wrote: > >>>>>> C W <tmrsg11 at gmail.com> >>>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > >> Thank you for your responses. I guess I don't feel >> alone. I don't find the documentation go into any detail. > >> I also find

Dear list, I just made a very simple mistake, but it was hard to spot. And I think that I should warn other people, because it is probably so simple to make... === R code === # Let us create a matrix: (a <- cbind(c(0,1,1), rep(1,3))) # [,1] [,2] # [1,] 0 1 # [2,] 1 1 # [3,] 1 1 # That is a MISTAKE: a/colSums(a) # [,1] [,2] # [1,] 0.0000000 0.3333333

Dear R users, I need to normalize a bunch of row vectors. At a certain point I need to divide a matrix by a vector of norms. I find that the behavior of Matrix objects differs from normal matrix objects. Example the following code examples differ only in xnormed changing from normal to Matrix object: x = matrix(1:12,3,4) x = as(x, "CsparseMatrix") xnorms = sqrt(colSums(x^2))

Hi, I am looking for some generalization of colSums and rowSums for general vector valued functions, and for arrays of more than 2 dimensions. So as a concrete example, suppose I have a 3 dimensional array, given by x = array(1:100,c(3,4,5)). and I want to sum the 3rd index of x to obain a 3 by 4 matrix. Using rowSums would return a vector of length 3 because it treats the last two indices as

Buenos días quiero definir situación_2 <-tapply(ICE_3$FACTOR_CORR, list(X.1.1Eneltrimestrequeestáacabando=ICE_3$X.1.1Eneltrimestrequeestáacabando, CNAE_1=ICE_3$CNAE_1), f) donde f sea el porcentaje por filas (y/o el porcentaje por columnas) y las funciones rowPercent y colPercent me dan el siguiente error Error en tapply(ICE_3$FACTOR_CORR, list(X.1.1Eneltrimestrequeestáacabando =

Dear Contributors, I am asking help on the way how to solve a problem related to loops for that I always get confused with. I would like to perform the following procedure in a compact way. Consider that p is a matrix composed of 100 rows and three columns. I need to calculate the sum over some rows of each column separately, as follows: fa1<-(colSums(p[1:25,])) fa2<-(colSums(p[26:50,]))

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:

Dear All It is very kind of you to guide me. When I want to run this line, I see this error stat.obs <- apply(GS, 2, function(z) Hott2(t(DATA[which(z==1),]), cl)) Error in colSums(w * x) : 'x' must be an array of at least two dimensions cl <- as.factor(y) GS: a matrix with 0 or 1 GS: gene sets -> a data matrix with rows=genes, columns= gene sets, GS[i,j]=1 if gene i in

>>>>> C W <tmrsg11 at gmail.com> >>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > Thank you for your responses. I guess I don't feel > alone. I don't find the documentation go into any detail. > I also find it surprising that, >> object.size(train$data) > 1730904 bytes >>

Hello, I am using tapply to pull out data by the day of week and then perform functions (e.g. mean). I would like to have the number of values used for the calcuation for the functions, sorted by each day of week. A number of entries in any given column are NAs. I have tried the following code and simple variants with no luck. for (i in 1:length(a[1,])){ x<-tapply(a[,i],a[,1],mean,

Hi, all! My project today is to write a speedy colSums(), which is a function available in S-Plus to add the columns of a matrix. Here are 4 ways to do it, with the time it took (elapsed, best of 3 trials) in both R and S-Plus: m <- matrix(1, 400, 40000) x1 <- apply(m, 2, sum) ## R=16.55 S=52.39 x2 <- as.vector(rep(1,nrow(m)) %*% m) ## R= 2.39 S= 8.52 x3 <-

Dear all, How can I obtain the union of a list of logical values? Consider the following: x <- head(iris) x[,c(2,4)] <- NA x[c(2,4),] <- NA # > x # Sepal.Length Sepal.Width Petal.Length Petal.Width Species # 1 5.1 NA 1.4 NA setosa # 2 NA NA NA NA <NA> # 3 4.7 NA 1.3

Hi, I'd like to simply add column-wise using Matrix objects (Csparse). It looks like one can apply mosty any base function to these objects (i.e., apply, colSums), but there is a nasty conversion to traditional matrix objects if one does that. Is there any workaround? I can see colSum listed in the help for Class 'CsparseMatrix' , but I wonder whether I'm using the default

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

Buenas tardes a tod@s, Me gustaria redondear las entradas de una matriz m manteniendo la suma de filas y columnas constantes (son valores fijos conocidos). En la aplicacion que estoy trabajando (en la que por supuesto m tiene una dimension mayor que en el ejemplo), no son permitidos numeros decimales y por ello debe efectuarse el redondeo. La forma de m es: m <- matrix(c(3.546, 4.5345,

Hi, it's my first time to write a loop with R for my homework. This loop is part of the function. I wanna assign values for hll according to panel [ii,1]=pp. I didn't get any error message in this part. but then when I further calculate another stuff with hll, the function can't return. I think it must be some problem in my loop. Probably something stupid or easy. But I tried to look

Hi, I feel dumb even asking, but isn't there an R function somewhere that I can use to reduce the resolution of a vector (or matrix) by summing terms in uniform blocks? That is, for a vector X, reduce it to some X.short as X.short[1]<- sum(X[1:10]); X.short[2] <- sum(X[11:20]), and so on. I did the following: X.short<-colSums(matrix(X,16,2048/16)) # X is of length 2048 but

Dear all, ## I have 4 tables like this: satu <- array(c(5,15,20,68,29,54,84,119), dim=c(2,4), dimnames=list(c("Negative", "Positive"), c("Black", "Brown", "Red", "Blond"))) dua <- array(c(50,105,30,8,29,25,84,9), dim=c(2,4), dimnames=list(c("Negative", "Positive"),