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java.lang.ObjectJama.EigenvalueDecomposition
public class EigenvalueDecomposition
Eigenvalues and eigenvectors of a real matrix.
If A is symmetric, then A = V*D*V' where the eigenvalue matrix D is diagonal and the eigenvector matrix V is orthogonal. I.e. A = V.times(D.times(V.transpose())) and V.times(V.transpose()) equals the identity matrix.
If A is not symmetric, then the eigenvalue matrix D is block diagonal with the real eigenvalues in 1-by-1 blocks and any complex eigenvalues, lambda + i*mu, in 2-by-2 blocks, [lambda, mu; -mu, lambda]. The columns of V represent the eigenvectors in the sense that A*V = V*D, i.e. A.times(V) equals V.times(D). The matrix V may be badly conditioned, or even singular, so the validity of the equation A = V*D*inverse(V) depends upon V.cond().
| Constructor Summary | |
|---|---|
| EigenvalueDecomposition(Matrix Arg)Check for symmetry, then construct the eigenvalue decomposition | |
| Method Summary | |
|---|---|
|  Matrix | getD()Return the block diagonal eigenvalue matrix | 
|  double[] | getImagEigenvalues()Return the imaginary parts of the eigenvalues | 
|  double[] | getRealEigenvalues()Return the real parts of the eigenvalues | 
|  Matrix | getV()Return the eigenvector matrix | 
| Methods inherited from class java.lang.Object | 
|---|
| equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait | 
| Constructor Detail | 
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public EigenvalueDecomposition(Matrix Arg)
Arg - Square matrix| Method Detail | 
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public Matrix getV()
public double[] getRealEigenvalues()
public double[] getImagEigenvalues()
public Matrix getD()
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