- EigenSymmetricDC
- EigenSymmetricQR
- EigenSymmetricRobust
- EigenSymmetricBisect
- EigenSymmetricDC2s
- EigenSymmetricQR2s
- EigenSymmetricRobust2s
- EigenSymmetricBisect2s
- EigenSymmetric2DC
- EigenSymmetric2QR
- EigenSymmetric2Bisect
EigenSymmetricDC
Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugated) matrix using the divide-and-conquer algorithm (lapack functions SYEVD, HEEVD).
Computing for type matrix<double>
bool matrix::EigenSymmetricDC(
|
Computing for type matrix<float>
bool matrixf::EigenSymmetricDC(
|
Computing for type matrix<complex>
bool matrixc::EigenSymmetricDC(
|
Computing for type matrix<complexf>
bool matrixcf::EigenSymmetricDC(
|
Parameters
jobv
[in] ENUM_EIG_VALUES enumeration value which determines the method for computing eigenvectors.
eigen_values
[out] Vector of eigenvalues.
eigen_vectors
[out] Matrix of eigenvectors.
Return Value
Return true if successful, otherwise false in case of an error.
Note
Computation depends on the value of the jobv parameter.
When jobv = EIGVALUES_V, eigenvectors and eigenvalues are calculated.
If EIGVALUES_N is set, eigenvectors are not calculated. Only eigenvalues are computed.
The input can be a symmetric (Hermitian), upper triangular or lower triangular matrix. Triangular matrices are assumed to be symmetric (Hermitian conjugated).
An enumeration that specifies whether to calculate eigenvectors.
ID |
Description |
---|---|
EIGVALUES_V |
Eigenvectors and eigenvalues are calculated. |
EIGVALUES_N |
Only eigenvalues are calculated, without vectors. |