scipy.linalg.eigvals¶
- scipy.linalg.eigvals(a, b=None, overwrite_a=False, check_finite=True, homogeneous_eigvals=False)[source]¶
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