matrix

问题 I have a matrix [1 2 3 6 7 1 2 1] and would like to remove mirror imaged pairs..i.e. output would be either: [1 2 3 6 7 1] or [3 6 7 1 2 1] Is there a simple way to do this? I can imagine a complicated for loop, something like (or a version which wouldn't delete the original pair..only the duplicates): for i=1:y var1=(i,1); var2=(i,2); for i=1:y if array(i,1)==var1 && array(i,2)==var2 | array(i,1)==var2 && array(i,2)==var1 array(i,1:2)=[]; end end end thanks 回答1: How's this for simplicity - A

问题 I simply want to traverse a matrix from start to finish touching upon every element. However, I see that there is no one iterator for boost matrix, rather there are two iterators, and I haven't been able to figure out how to make them work so that you can traverse the entire matrix typedef boost::numeric::ublas::matrix<float> matrix; matrix m1(3, 7); for (auto i = 0; i < m1.size1(); i++) { for (auto j = 0; j < m1.size2(); j++) { m1(i, j) = i + 1 + 0.1*j; } } for (auto itr1 = m1.begin1(); itr1

问题 I can not find any function or package to calculate the null space or (QR decomposition) of a bigmatrix (from library(bigmemory) ) in R. For example: library(bigmemory) a <- big.matrix(1000000, 1000, type='double', init=0) I tried the following but got the errors shown. How can I find the null space of a bigmemory object? a.qr <- Matrix::qr(a) # Error in as.vector(data) : # no method for coercing this S4 class to a vector q.null <- MASS::Null(a) # Error in as.vector(data) : # no method for

问题 I have a lot of rows and columns in a very large matrix (184 x 4000, type double), and I want to remove all 0's. The values in the matrix are usually greater than 0 but there are some rows of 0.0000 . I tried to remove the rows with zeros using this: x <- x[which(rowSums(x) > 0),] but what I am left with is a mere 3 rows out of 184. And I know for a fact that the deleted 181 rows were not all 0 rows. Does anyone have a clue why this is happening and how I can fix it? I used this same code on

问题 Could someone please explain to me the difference in column referencing between matrix , data.frame , and data.table ? I'm getting my head around which syntax to use for each class, but I don't understand how/why they're different. Take a 10x10 matrix foo <- matrix( nrow = 10, ncol = 10 ) I'll just fill the 2nd column to demonstrate: foo[,2] <- rnorm(10) head( foo, 3 ) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] NA -0.4688874 NA NA NA NA NA NA NA NA [2,] NA -1.0273370 NA NA NA NA

问题 It looks a very simple question. There are many lines available as their two endpoints. The question is how to discretize them into a matrix . Then the matrix can be used for image processing purposes. At the following figure example lines (yellow) and their corresponding pixelated demonstrations are shown. A piece of code in any language would be of great help and strongly recommended and of course is in advance appreciated. Note that performance and accuracy are very important factors. Also

问题 Given the matrix I = [1,2;3,4] , I would like to duplicate the elements to create a matrix I2 such that: I2 = [1 1 1 2 2 2 1 1 1 2 2 2 1 1 1 2 2 2 3 3 3 4 4 4 3 3 3 4 4 4 3 3 3 4 4 4] Other than using repmat , what other methods or functions are available? 回答1: Use kron: >> N = 3 %// Number of times to replicate a number in each dimension >> I = [1,2;3,4]; >> kron(I, ones(N)) ans = 1 1 1 2 2 2 1 1 1 2 2 2 1 1 1 2 2 2 3 3 3 4 4 4 3 3 3 4 4 4 3 3 3 4 4 4 This probably deserves some explanation

问题 This question already has answers here : Closed 7 years ago . Possible Duplicate: R: subset() logical-and operator for combining conditions should be & not && I have a simple question, but I don't know how to solve this... I want to select all rows where value_1 > 0 and value_2 > 0. Now I have this code: dataOnBoth<-data[data$value_1 > 0,][data$value_2 > 0,] When I head this data, ordering on log2_fold_change, I have This output: gene_id sample_1 sample_2 status value_1 value_2 log2_fold

问题 There is a large matrix that is used in Ax=b type problem. A is symmetric. Is there any algorithm to let us save only half of the matrix and do operation like x=A\b on it? 回答1: You'll only save half the memory, but you can do this by creating a flat version of the matrix, saving that, then unflattening it. The extra time required probably doesn't make the saving worthwhile, mind: % pretend this is symettric... A = rand(10, 10); % store it as a flat list flatA = []; for k = 1:size(A,1) flatA =

问题 I read these: https://stackoverflow.com/a/5159049/1175496 Matrices are for data of the same type. https://stackoverflow.com/q/29732279/1175496 Vectors (and so matrix) can accept only one type of data If matrix can only accept one data type, why can I do this: > m_list<-matrix(list('1',2,3,4),2,2) > m_list [,1] [,2] [1,] "1" 3 [2,] 2 4 The console output looks like I am combining character and integer data types. The console output looks similar to this matrix: > m_vector<-matrix(1:4,2,2) > m