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# scipy.linalg.eigvals

`scipy.linalg.``eigvals`(a, b=None, overwrite_a=False, check_finite=True, homogeneous_eigvals=False)

  Compute eigenvalues from an ordinary or generalized eigenvalue problem.

  Find eigenvalues of a general matrix:

      a   vr[:,i] = w[i]        b   vr[:,i]

  > 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. If omitted, identity matrix is assumed. overwrite_a : bool, optional Whether to overwrite data in a (may improve performance) check_finite : bool, optional Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs. homogeneous_eigvals : bool, optional If True, return the eigenvalues in homogeneous coordinates. In this case `w` is a (2, M) array so that:
  >     w[1,i] a vr[:,i] = w[0,i] b vr[:,i]
  Default is False.
  Returns: | w : (M,) or (2, M) double or complex ndarray The eigenvalues, each repeated according to its multiplicity but not in any specific order. The shape is (M,) unless `homogeneous_eigvals=True`.
  Raises: | LinAlgError If eigenvalue computation does not converge

  See also

  `eigvalsh`
    eigenvalues of symmetric or Hermitian arrays,
  `eig`
    eigenvalues and right eigenvectors of general arrays.
  `eigh`
    eigenvalues and eigenvectors of symmetric/Hermitian arrays.