matrix

问题 I have a Power BI Matrix below. It has 2 measures - Main Measure (a simple sum) and a Variance Measure. It has a column group called Category, which has 2 values - Category A and Category B. The Variance Measure is the subtraction of the Main Measure values between Category A and Category B, for corresponding time periods. For example, Main Measure value of 2020 Q1 for Category B is subtracted from the Main Measure value of 2020 Q1 for Category A . The result is the Variance Measure for 2020

问题 Please, consider the following code: x <- c('dog', 'cow', 'horse', 'rabbit', 'bear', 'seal', 'lion', 'ostrich','cat', 'hamster') y <- c('beaver', 'crow', 'donkey', 'lion', 'bear', 'fox', 'moose', 'mole') mtx <- matrix( data = apply( X = expand.grid( 'x' = x, 'y' = y ), MARGIN = 1, FUN = function(df) { identical(df[['x']], df[['y']]) } ), nrow = length(x) ) Result [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [2,] FALSE FALSE FALSE FALSE FALSE

问题 Lately I've been trying to get into programming for GPUs in Python using the Numba library. I have been reading up on it on their website using the tutorial there and currently I'm stuck on their example, which can be found here: https://numba.pydata.org/numba-doc/latest/cuda/examples.html. I'm attempting to generalize the example for the fast matrix multiplication a bit (which is of the form A*B=C). When testing I noticed that matrices with dimensions that are not perfectly divisible by the

问题 I am realizing an algorithm using C++ and CUDA. But I got into trouble when I tried to find an inverse of a special matrix. This matrix has following features: it is a square matrix (suppose: (m+3)x(m+3),m>0); its transpose matrix is its self; its main diagonal must be zeros; it must have a 3x3 zero matrix on the bottom right corner; you can consider this matrix in this form:H = [A ,B ;B' ,0]; I have tried some methods but all failed: pseudo-inverse matrix: I used matlab at first and got

问题 I am realizing an algorithm using C++ and CUDA. But I got into trouble when I tried to find an inverse of a special matrix. This matrix has following features: it is a square matrix (suppose: (m+3)x(m+3),m>0); its transpose matrix is its self; its main diagonal must be zeros; it must have a 3x3 zero matrix on the bottom right corner; you can consider this matrix in this form:H = [A ,B ;B' ,0]; I have tried some methods but all failed: pseudo-inverse matrix: I used matlab at first and got

问题 I want to do block matrix-matrix multiplication with the following C code.In this approach, blocks of size BLOCK_SIZE is loaded into the fastest cache in order to reduce memory traffic during calculation. void bMMikj(double **A , double **B , double ** C , int m, int n , int p , int BLOCK_SIZE){ int i, j , jj, k , kk ; register double jjTempMin = 0.0 , kkTempMin = 0.0; for (jj=0; jj<n; jj+= BLOCK_SIZE) { jjTempMin = min(jj+ BLOCK_SIZE,n); for (kk=0; kk<n; kk+= BLOCK_SIZE) { kkTempMin = min(kk

问题 I want to do block matrix-matrix multiplication with the following C code.In this approach, blocks of size BLOCK_SIZE is loaded into the fastest cache in order to reduce memory traffic during calculation. void bMMikj(double **A , double **B , double ** C , int m, int n , int p , int BLOCK_SIZE){ int i, j , jj, k , kk ; register double jjTempMin = 0.0 , kkTempMin = 0.0; for (jj=0; jj<n; jj+= BLOCK_SIZE) { jjTempMin = min(jj+ BLOCK_SIZE,n); for (kk=0; kk<n; kk+= BLOCK_SIZE) { kkTempMin = min(kk

问题 Given an array: array1 = [1 2 3]; I have to reverse it like so: array1MirrorImage = [3 2 1]; So far I obtained this ugly solution: array1MirrorImage = padarray(array1, [0 length(array1)], 'symmetric', 'pre'); array1MirrorImage = array1MirrorImage(1:length(array1)); Is there a prettier solution to this? 回答1: UPDATE: In newer versions of MATLAB (R2013b and after) it is preferred to use the function flip instead of flipdim, which has the same calling syntax: a = flip(a, 1); % Reverses elements

问题 I have run into an issue I do not understand, and I have not been able to find an answer to this issue on this website (I keep running into answers about how to convert dates to numeric or vice versa, but that is exactly what I do not want to know). The issue is that R converts values that are formatted as a date (for instance "20-09-1992") to numeric values when you assign them to a matrix or data frame. For example, we have "20-09-1992" with a date format, we have checked this using class()

问题 I am using mkl cblas_dgemm and currently have it with CblasRowMajor , CblasNoTrans , CblasNotrans , for my matrices. I know that c is a row major language, whereas dgemm is a column major algorithm. I am interested to know if switching the ordering of the matrices will have any affect on the cblas_dgemm algorithm if I am linking against mkl . Is mkl smart enough to do things behind the scenes that I would try to do to optimized the matrix multiplcations? If not, what is the best way to