$n
$n : int
Row and column dimension (square matrix).
Class to obtain eigenvalues and eigenvectors of a real matrix.
If A is symmetric, then A = VDV' where the eigenvalue matrix D is diagonal and the eigenvector matrix V is orthogonal (i.e. A = V.times(D.times(V.transpose())) and V.times(V.transpose()) equals the identity matrix).
If A is not symmetric, then the eigenvalue matrix D is block diagonal with the real eigenvalues in 1-by-1 blocks and any complex eigenvalues, lambda + imu, in 2-by-2 blocks, [lambda, mu; -mu, lambda]. The columns of V represent the eigenvectors in the sense that AV = VD, i.e. A.times(V) equals V.times(D). The matrix V may be badly conditioned, or even singular, so the validity of the equation A = VD*inverse(V) depends upon V.cond().
$n : int
Row and column dimension (square matrix).
$d : array
Arrays for internal storage of eigenvalues.
$V : array
Array for internal storage of eigenvectors.
$H : array
Array for internal storage of nonsymmetric Hessenberg form.
$ort : array
Working storage for nonsymmetric algorithm.
$cdivr : float
Used for complex scalar division.