matrix-inverse

I'm trying to understand how BLAS and LAPACK in Fortran work and so on, so I made a code that generates a matrix and inverts it. Here's the code program test Implicit none external ZGETRF external ZGETRI integer ::M complex*16,allocatable,dimension(:,:)::A complex*16,allocatable,dimension(:)::WORK integer,allocatable,dimension(:)::IPIV integer i,j,info,error Print*, 'Enter size of the matrix' Read*, M Print*, 'Enter file of the matrix' READ(*,*), A OPEN(UNIT=10,FILE = '(/A/)' ,STATUS='OLD',ACTION='READ') allocate(A(M,M),WORK(M),IPIV(M),stat=error) if (error.ne.0)then print *,"error:not enough

I have this problem which requires solving for X in AX=B . A is of the order 15000 x 15000 and is sparse and symmetric. B is 15000 X 7500 and is NOT sparse. What is the fastest way to solve for X? I can think of 2 ways. Simplest possible way, X = A\B Using for loop, invA = A\speye(size(A)) for i = 1:size(B,2) X(:,i) = invA*B(:,i); end Is there a better way than the above two? If not, which one is best between the two I mentioned? angainor First things first - never, ever compute inverse of A. That is never sparse except when A is a diagonal matrix. Try it for a simple tridiagonal matrix. That

I would like to be able to compute the inverse of a general NxN matrix in C/C++ using lapack. My understanding is that the way to do an inversion in lapack is by using the dgetri function, however, I can't figure out what all of its arguments are supposed to be. Here is the code I have: void dgetri_(int* N, double* A, int* lda, int* IPIV, double* WORK, int* lwork, int* INFO); int main(){ double M [9] = { 1,2,3, 4,5,6, 7,8,9 }; return 0; } How would you complete it to obtain the inverse of the 3x3 matrix M using dgetri_? First, M has to be a two-dimensional array, like double M[3][3] . Your

This is probably a very basic problem, but I haven't found a solution yet and it's been bugging me. I'd like to show arrows indicating the world coordinate directions (x, y, z) in the bottom right hand corner of the camera like is done in Maya, so that when rotating the camera around an object, or moving through a scene, you can still identify the directions of the world coordinates. I've tried to accomplish this using two different approaches and neither has worked so far. I have an object with three arrows as children using the THREE.ArrowHelper class, we'll call it XYZ for the moment. The

How do I get the inverse of a matrix in python? I've implemented it myself, but it's pure python, and I suspect there are faster modules out there to do it. You should have a look at numpy if you do matrix manipulation. This is a module mainly written in C, which will be much faster than programming in pure python. Here is an example of how to invert a matrix, and do other matrix manipulation. from numpy import matrix from numpy import linalg A = matrix( [[1,2,3],[11,12,13],[21,22,23]]) # Creates a matrix. x = matrix( [[1],[2],[3]] ) # Creates a matrix (like a column vector). y = matrix( [[1,2

I'm trying to calculate the inverse matrix in Java. I'm following the adjoint method (first calculation of the adjoint matrix, then transpose this matrix and finally, multiply it for the inverse of the value of the determinant). It works when the matrix is not too big. I've checked that for matrixes up to a size of 12x12 the result is quickly provided. However, when the matrix is bigger than 12x12 the time it needs to complete the calculation increases exponentially. The matrix I need to invert is 19x19, and it takes too much time. The method that more time consumes is the method used for the

Since CUDA 5.5, the CUBLAS library contains routines for batched matrix factorization and inversion ( cublas<t>getrfBatched and cublas<t>getriBatched respectively). Getting guide from the documentation, I wrote a test code for inversion of an N x N matrix using these routines. The code gives correct output only if the matrix has all non zero pivots. Setting any pivot to zero results in incorrect results. I have verified the results using MATLAB. I realize that I am providing row major matrices as input while CUBLAS expects column major matrices, but it shouldn't matter as it would only