vr_gpu (pycuda.gpuarray.GPUArray) – The normalized (Euclidean norm equal to 1) right eigenvectors, such that the column vr[:,i] is the eigenvector corresponding to the eigenvalue w[i].
However, I am only getting sensible results if I extract the eigenvectors if I assume them to be vr[i,:].
It may be a simply that the help assumes column-major order, but in practise, user should get the vectors by doing vr[i,:] , which can be confusing.
Environment
OS platform (including distro if you are on Linux) : Windows10
Python version: 3.0.0
CUDA version + how you installed it : NVidia installer
PyCUDA version (including GitHub revision if you have installed it from there) : 2021.1
scikit-cuda version (including GitHub revision if you have installed it from
there) : 0.5.4 , installed from github, clone, then run pyton setup.py install
Problem
I am trying to solve the 2D schrodinger equation using the eigenvector and eigenvalue solver skcuda.linalg.eig
In the instructions here
it says that
vr_gpu (pycuda.gpuarray.GPUArray) – The normalized (Euclidean norm equal to 1) right eigenvectors, such that the column vr[:,i] is the eigenvector corresponding to the eigenvalue w[i].However, I am only getting sensible results if I extract the eigenvectors if I assume them to be
vr[i,:].It may be a simply that the help assumes column-major order, but in practise, user should get the vectors by doing
vr[i,:], which can be confusing.Environment