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java.lang.Object cern.colt.matrix.linalg.EigenvalueDecomposition
Eigenvalues and eigenvectors of a real matrix A.
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.mult(D.mult(transpose(V))) and V.mult(transpose(V)) 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.mult(V) equals V.mult(D). The matrix V may be badly conditioned, or even singular, so the validity of the equation A = V*D*inverse(V) depends upon Algebra.cond(V).
Constructor Summary | |
EigenvalueDecomposition(DoubleMatrix2D A)
Constructs and returns a new eigenvalue decomposition object; The decomposed matrices can be retrieved via instance methods of the returned decomposition object. |
Method Summary | |
DoubleMatrix2D |
getD()
Returns the block diagonal eigenvalue matrix, D. |
DoubleMatrix1D |
getImagEigenvalues()
Returns the imaginary parts of the eigenvalues. |
DoubleMatrix1D |
getRealEigenvalues()
Returns the real parts of the eigenvalues. |
DoubleMatrix2D |
getV()
Returns the eigenvector matrix, V |
String |
toString()
Returns a String with (propertyName, propertyValue) pairs. |
Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
public EigenvalueDecomposition(DoubleMatrix2D A)
A
- A square matrix.
IllegalArgumentException
- if A is not square.Method Detail |
public DoubleMatrix2D getD()
public DoubleMatrix1D getImagEigenvalues()
public DoubleMatrix1D getRealEigenvalues()
public DoubleMatrix2D getV()
public String toString()
rank : 3 trace : 0
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