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# scipy.linalg.eig

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

  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 Hermitian conjugation.

  Parameters : | a : (M, M) array_like A complex or real matrix whose eigenvalues and eigenvectors will be computed. b : (M, M) array_like, optional Right-hand side matrix in a generalized eigenvalue problem. Default is None, identity matrix is assumed. left : bool, optional Whether to calculate and return left eigenvectors. Default is False. right : bool, optional Whether to calculate and return right eigenvectors. Default is True. overwrite_a : bool, optional Whether to overwrite a; may improve performance. Default is False. overwrite_b : bool, optional Whether to overwrite b; may improve performance. Default is False. check_finite : boolean, optional Whether to check the input matrixes contain only finite numbers. Disabling may give a performance gain, but may result to problems (crashes, non-termination) if the inputs do contain infinities or NaNs.
  Returns : | w : (M,) double or complex ndarray The eigenvalues, each repeated according to its multiplicity. vl : (M, M) double or complex ndarray The normalized left eigenvector corresponding to the eigenvalue `w[i]` is the column v[:,i]. Only returned if `left=True`. vr : (M, M) double or complex ndarray The normalized right eigenvector corresponding to the eigenvalue `w[i]` is the column `vr[:,i]`. Only returned if `right=True`.
  Raises : | LinAlgError : If eigenvalue computation does not converge.

  See also

  `eigh`
    Eigenvalues and right eigenvectors for symmetric/Hermitian arrays.

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