# scipy.linalg.eig¶

scipy.linalg.eig(a, b=None, left=False, right=True, overwrite_a=False, overwrite_b=False)

Solve an ordinary or generalized eigenvalue problem of a square matrix.

Find eigenvalues w and right or left eigenvectors of a general matrix:

```a   vr[:,i] = w[i]        b   vr[:,i]
a.H vl[:,i] = w[i].conj() b.H vl[:,i]```

where .H is the Hermitean conjugation.

Parameters : a : array, shape (M, M) A complex or real matrix whose eigenvalues and eigenvectors will be computed. b : array, shape (M, M) Right-hand side matrix in a generalized eigenvalue problem. If omitted, identity matrix is assumed. left : boolean Whether to calculate and return left eigenvectors right : boolean Whether to calculate and return right eigenvectors overwrite_a : boolean Whether to overwrite data in a (may improve performance) overwrite_b : boolean Whether to overwrite data in b (may improve performance) w : double or complex array, shape (M,) The eigenvalues, each repeated according to its multiplicity. (if left == True) : vl : double or complex array, shape (M, M) The normalized left eigenvector corresponding to the eigenvalue w[i] is the column v[:,i]. (if right == True) : vr : double or complex array, shape (M, M) The normalized right eigenvector corresponding to the eigenvalue w[i] is the column vr[:,i]. Raises LinAlgError if eigenvalue computation does not converge :