similar to: How can I divide an image and randomly plot the segements

Dear R-users, Say that I have a sequence of zeroes and ones: x <- c(1,1,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,0,0) The sequences of ones represent segments and I want to report the starting and endpoints of these segments. For example, in 'x', the first segment starts at location 1 and ends at 3, and the second segment starts at location 8 and ends at location 10. Is there an efficient

Hi all, I'm working with a large data set (on the order of 300X300) and trying to apply a function which compares the elements of all possible 2x2 submatrices. There are rc(r-1)(c-1) such submatrices, so obviously the naive method of looping through the rows and columns is computationally unfeasible for my data set: for(i in 1:(nrow(data)-1)) { for(j in (i+1):nrow(data)) { for (m

I need to multiply to very large, nonsparse matrices, and so get the error "allocMatrix: too many elements specified". Is there a way to set the limit for allocMatrix? In my case, the two matrices, A and B, are nxm and mxp where m is small, so I could subdivide each into blocks of submatrices A=rbind(A1,A2,...) and B=cbind(B1,B2,...) then multiply each pair of submatrices, but I was

Hi everybody, I'm looking for an optimal way to split a big matrix (e.g. ncol = 8, nrow=8) into small square submatrices (e.g. ncol=2, nrow=2) For example If I have > h [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1 9 17 25 33 41 49 57 [2,] 2 10 18 26 34 42 50 58 [3,] 3 11 19 27 35 43 51 59 [4,] 4 12 20 28 36

Dear all, I am currently working with the spatstat package, using windows and pixel images. First: My aim is to transform a shapefile (see attached) into a pixel image. My idea is to start transforming the shapefile into a Spatial Polygon file: x <- readShapeSpatial("200001441.shp") y <- as(x, "SpatialPolygons") z <- as.owin(y) Given z, I want to identify each

Hi, I have a matrix of say 1024x1024 and I want to look at it in chunks. That is I'd like to divide into a series of submatrices of order 2x2. | 1 2 3 4 5 6 7 8 ... | | 1 2 3 4 5 6 7 8 ... | | 1 2 3 4 5 6 7 8 ... | | 1 2 3 4 5 6 7 8 ... | ... So the first submatrix would be | 1 2 | | 1 2 | the second one would be | 3 4 | | 3 4 | and so on. That is I want the matrix to be evenly divided

Estimado Javier, Gracias por tu mensaje. No, lo unico que requiero es la lista de números (i1, 2, 3, 1, 2, 3, 4, 5, 1, 2). Saludos cordiales, Jorge.- 2015-10-28 14:35 GMT-05:00 Javier Rubén Marcuzzi < javier.ruben.marcuzzi en gmail.com>: > Estimado Jorge I Velez > > > > No comprendo un punto, dices que deseas construir sub matrices y extraer > elementos de sub

El código que me olvide pegar input m <- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 5, 5, 5), .Dim = c(10L, 5L)) m ## output output <- c(1:3, 1:5, 1:2) output nfilas <- nrow(m) while(nfilas > 0) { diagonal <- diag(m)

On 02/06/17 01:17, Lluis.Hurtado at uv.es wrote: > Dear all, > > I am currently working with the spatstat package, using windows and pixel images. > > First: > > My aim is to transform a shapefile (see attached) into a pixel image. > > My idea is to start transforming the shapefile into a Spatial Polygon file: > > x <-

Dear R users, I have a Hadamard matrix 16x15 and i want to put 16x5 submatrices in an array put i have an error. > A1<-matrix(c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, + 1,0,1,0,1,0,1,0,1,0,1,0,1,0,1, + 0,1,1,0,0,1,1,0,0,1,1,0,0,1,1, + 1,1,0,0,1,1,0,0,1,1,0,0,1,1,0, + 0,0,0,1,1,1,1,0,0,0,0,1,1,1,1, + 1,0,1,1,0,1,0,0,1,0,1,1,0,1,0, + 0,1,1,1,1,0,0,0,0,1,1,1,1,0,0, + 1,1,0,1,0,0,1,0,1,1,0,1,0,0,1, +

Buenos dias a todos, Quisiera extraer algunas entradas de una matrix "m" teniendo en cuenta algunas restricciones. El siguiente ejemplo ilustra la situacion: ## input m <- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 5, 5, 5), .Dim = c(10L, 5L)) m ## output output <-

Dear R community, I have trouble implementing a nested variance-covariance matrix in the lme function. The model has two fixed effects called End and logpgc, the response variable is the logarithm to base 2 of Intensity ( log2(Intensity) ) and the random effects are called Probe and ProbeNo. The model has the following nesting structure: A Pixel is nested within the ProbeNo,the ProbeNo is

I tried to use gpuCor function in the gputools package of R to calcuate the pairwise correlations of a matrix of 40,000 columns. Becuase there would be memory issues if I use the whole matrix at a time, I splitted the matrix into submatrix of 10,000 columns and then calculate the pairwise correlation of different submatrices. There are altogether 4 submatrices, so I need to calculate the pearson

Hello list, I try to optimize some R code and it turns out that the function as.matrix takes a lot of time in my code. There is only one reason why I need as.matrix: My code should work for matrices with ncol=p and p should be allowed to be 1 or larger. Now I have a matrix x with dim(x)=(n,p), and I need to work with the submatrix y <-x[gv,], (gv a vector of n logicals) and to calculate

Dear Rxperts Below is a small vector of values of zeros and non-zeros... was wondering if there is an efficient way to get the block sizes of submatrices of a big matrix similar to the one shown below? diagonal elements can be zero too. Rows with only a diagonal element may be considered as a unit block size. c(1,0,0,0,0,0,0,0,0,0,0, 1,1,0,0,0,0,0,0,0,0,0, 0,0,1,0,0,0,0,0,0,0,0,

Dear all, I have a large matrix with about 2500 variables, and 100 rows. I would like to calculate the means of the every 10 variables starting from 1:2500 and saving the results as a vector or matrix. How can I do that? Alternatively, How can I create 250 subset matrices in the order of variables 1:2500 in groups of 10 from the single matrix which had initially 2500 variables ? I guess I have

Hi all Suppose I have a dim=c(2,2,3) matrix A, say: A[,,1]= a b c d A[,,2]= e f g h A[,,3]= i j k l Suppose that I want to create a 2x2 matrix X, which picks elements from the above-mentioned submatrices according to an index matrix J referring to the "depth" dimension: J= 1 3 2 3 In other words, I want X to be X= a j g l since the matrix J says that the (1,1)-element should be

Hi, I have a test_table where the dim is 62220 by 73 (row by col) I would like to partition the rows into 170 equal parts (170 tables where each is of dim 366 by 73), and rearrange them horizontally. The source codes I have: for (i in 1:170) { c = cbind(c,test_table[(367*i+1):(367*(i+1)),2:73]); } Unfortunately, using for loop and cbind for a table of this size

Does anyone have something like tapply that is extremely fast for matrices when there is a very large number of levels of the grouping variable? I'm referring to, for example, tapply(x, grouping.variable, function.operating.on.submatrix) where x is a matrix and the submatrix is a subset of the rows of x. The grouping variable's length equals the number of rows of x. -- Frank E

Hi I am running analysis with Kcross from the package spatstat and I am getting a message that R can not allocate enough memory for a vector of 900MB. R seems to be running towards the 2GB limit per process. The dataset is not to big (ca 3000 points) but the mask for the points is extremely irregular (a buffer around roads which have been sampled) and I can do trhe analysis if I use a