scipy.linalg.eigvals_banded(a_band, lower=0, overwrite_a_band=0, select='a', select_range=None)

Solve real symmetric or complex hermitian band matrix eigenvalue problem.

Find eigenvalues w of a:

a v[:,i] = w[i] v[:,i]
v.H v    = identity

The matrix a is stored in ab either in lower diagonal or upper diagonal ordered form:

ab[u + i - j, j] == a[i,j] (if upper form; i <= j) ab[ i - j, j] == a[i,j] (if lower form; i >= j)

Example of ab (shape of a is (6,6), u=2):

upper form:
*   *   a02 a13 a24 a35
*   a01 a12 a23 a34 a45
a00 a11 a22 a33 a44 a55

lower form:
a00 a11 a22 a33 a44 a55
a10 a21 a32 a43 a54 *
a20 a31 a42 a53 *   *

Cells marked with * are not used.


a_band : array, shape (M, u+1)

Banded matrix whose eigenvalues to calculate

lower : boolean

Is the matrix in the lower form. (Default is upper form)

overwrite_a_band: :

Discard data in a_band (may enhance performance)

select: {‘a’, ‘v’, ‘i’} :

Which eigenvalues to calculate




All eigenvalues


Eigenvalues in the interval (min, max]


Eigenvalues with indices min <= i <= max

select_range : (min, max)

Range of selected eigenvalues


w : array, shape (M,)

The eigenvalues, in ascending order, each repeated according to its multiplicity.

Raises LinAlgError if eigenvalue computation does not converge :

See also

eigenvalues and right eigenvectors for symmetric/Hermitian band matrices
eigenvalues of general arrays
eigenvalues and right eigenvectors for symmetric/Hermitian arrays
eigenvalues and right eigenvectors for non-symmetric arrays

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