eigvals_banded — SciPy v1.15.2 Manual (original) (raw)

scipy.linalg.

scipy.linalg.eigvals_banded(a_band, lower=False, overwrite_a_band=False, select='a', select_range=None, check_finite=True)[source]#

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 a_band either in lower diagonal or upper diagonal ordered form:

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

where u is the number of bands above the diagonal.

Example of a_band (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.

Parameters:

a_band(u+1, M) array_like

The bands of the M by M matrix a.

lowerbool, optional

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

overwrite_a_bandbool, optional

Discard data in a_band (may enhance performance)

select{‘a’, ‘v’, ‘i’}, optional

Which eigenvalues to calculate

select	calculated
‘a’	All eigenvalues
‘v’	Eigenvalues in the interval (min, max]
‘i’	Eigenvalues with indices min <= i <= max

select_range(min, max), optional

Range of selected eigenvalues

check_finitebool, optional

Whether to check that the input matrix contains 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.

Returns:

w(M,) ndarray

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

Raises:

LinAlgError

If eigenvalue computation does not converge.