search for: matrixation

Ubuntu 8.04 Wine 1.1.10 The sonic mega collection contains almost every genesis sonic game, along with some game gear sonics. The game installed flawlessly, and the no-cd patch worked also. However, upon loading, it shows a faint shadow of the famous SEGA startup screen and then locks up and must be force killed. Changing it to various compat modes did nothing. Normal Output: Code: name at

Hi list, How to save a list content into a text file? Please consider example below, I have two numeric matrices that I bundle into a list & give each list element a name Example: > matrixA <- matrix(0,5,4) > matrixB <- matrix(1,7,13) > matrixList <- list(matrixA,matrixB) > names <- c("Matrix A","Matrix B") > names <-

Dear list, After running for a while, it crashes and gives the following error message: can anybody suggest how to deal with this? Error in if (ratio0[i] < log(runif(1))) { : missing value where TRUE/FALSE needed ################### original program ######## p2 <- function (Nsim=1000){ x<- c(0.301,0,-0.301,-0.602,-0.903,-1.208, -1.309,-1.807,-2.108,-2.71) # logdose

Transpose vector extracted from a matrix Hello, I am doing a recursive analysis that uses every line (vector) of a matrix in a loop. In the model, I need to transpose those vectors that are extracted from a matrix. Using simple vectors (no matrix involved) the transpose function works fine: simplevector <-matrix(1:3,3,1) tsimplevector <-t(simplevector) #transposed dim(simplevector)

Consider this: > y <- matrix(1:8, ncol=2) > is.matrix(y[-c(1,2),]) [1] TRUE > is.matrix(y[-c(1,2,3),]) [1] FALSE > is.matrix(y[-c(1,2,3,4),]) [1] TRUE It seems like an inconsistent behaviour: - with 2 or more rows we have a matrix - with 1 row we do not have a matrix and - with 0 rows we have a matrix again I just stumbled on this behaviour, because I had a problem with my

Hi list! I have prepared a custom function (below) in order to calculate separability indices (Divergence, Bhattacharyya, Jeffries-Matusita, Transformed divergene) between two samples of (spectral land cover) classes. I need help to cross-compare results to verify that it works as expected (since I don't know of any other foss-tool that will give me quickly some results). Does anybody

Hi all, I keep running into a small problem in my programming, and I'm sure there's an elegant way around it... I often want to use apply() on a matrix with a variable number of columns. It works just fine unless the number of columns is one, in which case the matrix becomes a vector, and apply() complains. Example below: ----------------------------- a.matrix <- matrix(rnorm(6),

I'm puzzled by as.matrix. It appears to work differently for Surv objects. Here is a session from my computer: tmt% R --vanilla > library(survival) Loading required package: splines > ytest <- Surv(1:3, c(1,0,1)) > is.matrix(ytest) >[1] TRUE > attr(ytest, 'type') [1] "right" > attr(as.matrix(ytest), 'type') [1] "right" >

Hi all, I'd like to write a piece of code which will remove columns from a matrix, if the column contains only one value, say every value in the column is a "3": Matrix <- matrix(NA, nrow=5, ncol=4) Matrix[,1] <- c(1,2,3,4,5) Matrix[,2] <- c(3,3,3,3,3) Matrix[,3] <- c(5,4,3,2,1) Matrix[,4] <- c(5,1,4,3,2) [,1] [,2] [,3] [,4] [1,] 1 3 5 5 [2,] 2

Under help(matrix) it is written: 'is.matrix' tests if its argument is a (strict) matrix. It is generic: you can write methods to handle specific classes of objects, see InternalMethods. Further down, under "Details", the meaning of "strict" is explained more explicitly: 'is.matrix' returns 'TRUE' if 'x' is a matrix

ng, I have a matrix (x) with binary content. Each row of the matrix holds exactly one 1, and the rest of the row is zeros. The thing is that I need to 'collapse' the matrix to one column where each row holds the original column index of the 1's (y). Sometimes, the matrix is quite large, so I have a perfomance problem. x <- matrix(c(1,0,0, 0,0,1, 0,1,0, 0,0,1, 0,1,0,

Hello, I have 2 functions (a and b) a = function(n) { matrix (runif(n*2,0.0,1), n) } > > > b = function (m, matrix) { > n=nrow (matrix) > p=ceiling (n/m) > lapply (1:p, function (l,n,m) { > inf = ((l-1)*m)+1 > if (l<p) sup=((l-1)*m)+m > else sup=n >

Dear all, how can I convert an m x n incidence matrix into an m x m adjacency matrix or an n x n adjacency matrix? The current matrix contains binary data, hence the new matrix would contain counts of common occurrences. Thank you for your help. Phil

Dear all, I am pretty sure that this has been discussed before. Unfortunately, I can not find anything in the archives -- probably because I am "RSiteSearching" for the wrong terms. If I remember correctly, I think I even asked this question a few years ago. But I cannot even find this. The basic problem is that a result depends on a previous result. This is easy with a loop--but

Dear R list members, I am seeking for an elegant way for matching NA elements of a matrix. Everthing I tried, the result was a vector. Here ist an example with vectors that works: a and b are vectors of same lenght representing pairs of data (a[i] b[i]) with some NA elements: ## R Code a <- (1:5) a[2] <- NA b <- (6:10) b[3] <- NA a 1 NA 3 4 5 b 6 7 NA 9 10 ## /R

Hello, All: What's the simplest way to convert a data.frame into a model.matrix? One way is given by the following example, modified from the examples in help(model.matrix): dd <- data.frame(a = gl(3,4), b = gl(4,1,12)) ab <- model.matrix(~ a + b, dd) ab0 <- model.matrix(~., dd) all.equal(ab, ab0) What do you think about replacing "model.matrix(~ a +

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))

Dear expeRts, I have two matrices A and B. They have the same number of columns but possibly different number of rows. I would like to compare each row of A with each row of B and check whether all entries in a row of A are less than or equal to all entries in a row of B. Here is a minimal working example: A <- rbind(matrix(1:4, ncol=2, byrow=TRUE), c(6, 2)) # (3, 2) matrix B <-

Dear List: I'm working to construct a very large sparse matrix and have found relief using the SparseM package. I have encountered an issue that is confusing to me and wonder if anyone may be able to suggest a smarter solution. The matrix I'm creating is a covariance matrix for a larger research problem that is subsequently used in a simulation. Below is the latex form of the matrix if

Hi, I just tried to upgrade Nixpkgs to R 3.5.0, but unfortunately the new version fails its regression test suite. We configure the build using the flags "--without-recommended-packages", in case that's relevant. You can see a complete build log with all relevant information at [1]. Anyway, the test failures look like this: | make[3]: Entering directory