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eigs (Matlab function)

Subset of eigenvalues and eigenvectors

Matlab / Scilab equivalent

Matlab Scilab
d = eigs(A)
d = eigs(A, k)

d = eigs(A, k, sigma)
    % sigma:
    % 'largestabs' (default)
    % 'smallestabs'
    % 'largestreal'
    % 'smallestreal'
    % 'bothendsreal'
    % 'largestimag'
    % 'smallestimag'
    % 'bothendsimag'
    % scalar
    % (No equivalent)
    % (No equivalent)
    % (No equivalent)

d = eigs(A, k, sigma, Name, Value)

d = eigs(A, k, sigma, opts)
    % opts.issym  = 1
    % opts.tol
    % opts.maxit (= 300)
    % opts.p
    % opts.v0
    % opts.disp
    % opts.fail
    % opts.spdB
    % opts.cholB
    % opts.permB
    % (No equivalent)

d = eigs(A, B, ..)
d = eigs(Afun, n, ..)
[V, D] = eigs(..)
[V, D, flag] = eigs(..)
d = eigs(A)
d = eigs(A, [], k)

d = eigs(A, [], k, sigma)
    // sigma:
    // 'LM' : Largest Magnitudes (default)
    // 'SM' : Smallest Magnitudes
    // 'LR' : Largest Real parts
    // 'SM' : Smallest Real parts
    // (No equivalent)
    // 'LI' : Largest Imaginary parts (real non-symmetric or complex problems)
    // 'SI' : Smallest Imaginary parts (real non-symmetric or complex problems)
    // (No equivalent)
    // scalar
    // 'LA' : Largest Algebraic eigenvalues (real symmetric problems).
    // 'SA' : Smallest Algebraic eigenvalues (real symmetric problems).
    // 'BE' : half from each end of the spectrum (real symmetric problems).

// No equivalent. Sets and uses the opts structure instead

d = eigs(A, [], k, sigma, opts)
    // opts.issym   (= %t) : used with Afun
    // opts.tol
    // opts.maxiter (= 300)
    // opts.ncv       : Number of Lanczos basis vectors
    // opts.resid     : starting residual vector
    // (No equivalent)
    // (No equivalent)
    // (No equivalent)
    // opts.cholB
    // (No equivalent)
    // opts.isreal (= %t) : used with Afun

d = eigs(A, B, ..)
d = eigs(Afun, n, ..)
[D, V] = eigs(..)    // D still as first output
// No equivalent

See also

  • eig — Find eigenvalues and eigenvectors
  • spec — valeurs propres, et vecteurs propres d'une matrice ou d'un faisceau de matrices
  • bdiag — bloc-diagonalisation, vecteurs propres généralisés
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Last updated:
Thu Oct 24 11:16:04 CEST 2024