matrix

问题 Suppose I have a numpy array np.array([ [3, 0, 5, 3, 0, 1], [0, 1, 2, 1, 5, 2], [4, 3, 5, 3, 1, 4], [2, 5, 2, 5, 3, 1], [0, 1, 2, 1, 5, 2], ]) Now, I want to randomly replace some elements with 0. So that I have an output like this np.array([ [3, 0, 0, 3, 0, 1], [0, 1, 2, 0, 5, 2], [0, 3, 0, 3, 1, 0], [2, 0, 2, 5, 0, 1], [0, 0, 2, 0, 5, 0], ]) 回答1: We can use np.random.choice(..., replace=False) to randomly select a number of unique non-zero flattened indices and then simply index and reset

问题 After several hours of searching, I am turning to your expertise. Beginner in R, I try to speed up my code. My goal is to replace the values in a matrix A . However, I want to replace values based on two vectors of another matrix B . B[, 1] is the name of row i of the matrix A . The second column, B[, 2] corresponds to the name of column of the matrix A . The first version of my code was to use the match function in a loop. for(k in 1:L){ i <- B[k,1] j <- B[k,2] d <- match(i,rownames(A)) e <-

问题 I have an n-by-m matrix that I want to convert to a mn-by-m matrix, with each m-by-m block of the result containing the diagonal of each row. For example, if the input is: [1 2; 3 4; 5 6] the output should be: [1 0; 0 2; 3 0; 0 4; 5 0; 0 6] Of course, I don't want to assemble the matrix step by step myself with a for loop. Is there a vectorized and simple way to achieve this? 回答1: For a vectorized way to do this, create the linear indices of the diagonal elements into the resulting matrix,

问题 I'm implementing a simple camera system in OpenGL. I set up gluPerspective under the projection matrix and then use gluLookAt on the ModelView matrix. After this I have my main render loop which checks for keyboard events and, if any of the arrow keys are pressed, modifies angular and forward speeds (I only rotate through the y axis and move through the z (forwards)). Then I move the view using the following code (deltaTime is the amount of time since the last frame was rendered in seconds,

问题 I have: B <- matrix(c(1, 0, 0, 1, 1, 1), nrow=3, ncol=2) and I want: B [,1] [,2] [1,] TRUE TRUE [2,] FALSE TRUE [3,] FALSE TRUE as.logical(B) gives a 1D vector. Is there an idiomatic way to do the matrix type conversion? I'm currently doing the wordy: boolVector <- as.logical(B) m <- nrow(B) n <- ncol(B) m <- matrix(boolVector, m , n) m 回答1: mode(B) <- "logical" or "mode<-"(B, "logical") . We can also use storage.mode function. This workaround is good for two reasons: the code is much

问题 Let's make a replicable example: This is my initial matrix d<- matrix(1:80,,5) d [,1] [,2] [,3] [,4] [,5] [1,] 1 17 33 49 65 [2,] 2 18 34 50 66 [3,] 3 19 35 51 67 [4,] 4 20 36 52 68 [5,] 5 21 37 53 69 [6,] 6 22 38 54 70 [7,] 7 23 39 55 71 [8,] 8 24 40 56 72 [9,] 9 25 41 57 73 [10,] 10 26 42 58 74 [11,] 11 27 43 59 75 [12,] 12 28 44 60 76 [13,] 13 29 45 61 77 [14,] 14 30 46 62 78 [15,] 15 31 47 63 79 [16,] 16 32 48 64 80 I would like to reshape my matrix cutting every colomn by 4 and taking

问题 I have a large number of images which I've broken down into segments such that their matrices look like: img = [ 1 1 1 1 1 2 2 2 3 3 3 3 1 1 1 1 2 2 2 2 2 3 3 3 1 1 1 4 4 4 2 2 2 3 3 3 5 5 5 5 5 5 5 2 2 3 3 3 ]; where each number represents a different region and each region is arbitrarily shaped. So in this case, region 1 has neighbours 2, 4 and 5, region 2 has neighbours 1, 3 and 4 and so on. I've extracted all of the regions into separate cells and obtained statistics (mean, variance, etc)

问题 Here is my problem: I have a nxn matrix in matlab. I want to delete all the zeros of this matrix and put the rows of it in vectors. For n=4 , let say I have the following matrix: A = [ 1 1 0 0 1 2 0 0 1 0 0 0 1 2 1 0 ]; How to get the following: v1 = [ 1 1 ]; v2 = [ 1 2 ]; v3 = [ 1 ]; v4 = [ 1 2 1 ]; I did the following: for i = 1:size(A, 1) tmp = A(i, :); tmp(A(i, :)==0)=[]; v{i} = tmp; end 回答1: Slightly faster than Divakar's answer: nzv = arrayfun(@(n) nonzeros(A(n,:)), 1:size(A,1),

问题 I have a matrix that i want to duplicate n times in a list. Obviously the rep() function does not work on matrices, so does anyone have a good suggestion how to make this better than my code below? Thanks! # Create sample matrix jwprox <- matrix(ncol=15,nrow=15) # Create list of n-times matrices jwprox <- list(jwprox,jwprox,jwprox) 回答1: You can use either lapply() n <- 3 x <- lapply(seq_len(n), function(X) jwprox) str(x) # List of 3 # $ : logi [1:15, 1:15] NA NA NA NA NA NA ... # $ : logi [1

问题 I have 2x N amount of 1D Signals in files where Column 1 is Signal 1 and Column 2 Signal 2. Code 1 is simplified example about 1x N amount of 1D signals, while Code 2 is the actual target with two pieces of pseudocode about: to create two dimensional vector ( files[[i]] = i,i+1 ) - just two integer data units in each row separated by comma, and and then accessing the data there later ( tcrossprod( files[[]][, 2], files[[]][, 2] ) ) where I cannot refer to all columns 2 of all signals