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java.lang.Object org.apache.commons.math3.linear.EigenDecomposition
public class EigenDecomposition
Calculates the eigen decomposition of a real matrix.
The eigen decomposition of matrix A is a set of two matrices: V and D such that A = V × D × VT. A, V and D are all m × m matrices.
This class is similar in spirit to the EigenvalueDecomposition
class from the JAMA
library, with the following changes:
getVt
method has been added,getRealEigenvalue
and getImagEigenvalue
methods to pick up a single eigenvalue have been added,getEigenvector
method to pick up a single
eigenvector has been added,getDeterminant
method has been added.getSolver
method has been added.As of 3.1, this class supports general real matrices (both symmetric and non-symmetric):
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.multiply(D.multiply(V.transpose())) and V.multiply(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.multiply(V) equals V.multiply(D). The matrix V may be badly conditioned, or even singular, so the validity of the equation A = V*D*inverse(V) depends upon the condition of V.
This implementation is based on the paper by A. Drubrulle, R.S. Martin and J.H. Wilkinson "The Implicit QL Algorithm" in Wilksinson and Reinsch (1971) Handbook for automatic computation, vol. 2, Linear algebra, Springer-Verlag, New-York
Constructor Summary | |
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EigenDecomposition(double[] main,
double[] secondary)
Calculates the eigen decomposition of the symmetric tridiagonal matrix. |
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EigenDecomposition(double[] main,
double[] secondary,
double splitTolerance)
Deprecated. in 3.1 (to be removed in 4.0) due to unused parameter |
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EigenDecomposition(RealMatrix matrix)
Calculates the eigen decomposition of the given real matrix. |
|
EigenDecomposition(RealMatrix matrix,
double splitTolerance)
Deprecated. in 3.1 (to be removed in 4.0) due to unused parameter |
Method Summary | |
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RealMatrix |
getD()
Gets the block diagonal matrix D of the decomposition. |
double |
getDeterminant()
Computes the determinant of the matrix. |
RealVector |
getEigenvector(int i)
Gets a copy of the ith eigenvector of the original matrix. |
double |
getImagEigenvalue(int i)
Gets the imaginary part of the ith eigenvalue of the original matrix. |
double[] |
getImagEigenvalues()
Gets a copy of the imaginary parts of the eigenvalues of the original matrix. |
double |
getRealEigenvalue(int i)
Returns the real part of the ith eigenvalue of the original matrix. |
double[] |
getRealEigenvalues()
Gets a copy of the real parts of the eigenvalues of the original matrix. |
DecompositionSolver |
getSolver()
Gets a solver for finding the A × X = B solution in exact linear sense. |
RealMatrix |
getSquareRoot()
Computes the square-root of the matrix. |
RealMatrix |
getV()
Gets the matrix V of the decomposition. |
RealMatrix |
getVT()
Gets the transpose of the matrix V of the decomposition. |
boolean |
hasComplexEigenvalues()
Returns whether the calculated eigen values are complex or real. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public EigenDecomposition(RealMatrix matrix) throws MathArithmeticException
Supports decomposition of a general matrix since 3.1.
matrix
- Matrix to decompose.
MaxCountExceededException
- if the algorithm fails to converge.
MathArithmeticException
- if the decomposition of a general matrix
results in a matrix with zero norm@Deprecated public EigenDecomposition(RealMatrix matrix, double splitTolerance) throws MathArithmeticException
matrix
- Matrix to decompose.splitTolerance
- Dummy parameter (present for backward
compatibility only).
MathArithmeticException
- if the decomposition of a general matrix
results in a matrix with zero norm
MaxCountExceededException
- if the algorithm fails to converge.public EigenDecomposition(double[] main, double[] secondary)
main
- Main diagonal of the symmetric tridiagonal form.secondary
- Secondary of the tridiagonal form.
MaxCountExceededException
- if the algorithm fails to converge.@Deprecated public EigenDecomposition(double[] main, double[] secondary, double splitTolerance)
main
- Main diagonal of the symmetric tridiagonal form.secondary
- Secondary of the tridiagonal form.splitTolerance
- Dummy parameter (present for backward
compatibility only).
MaxCountExceededException
- if the algorithm fails to converge.Method Detail |
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public RealMatrix getV()
public RealMatrix getD()
getRealEigenvalues()
,
getImagEigenvalues()
public RealMatrix getVT()
public boolean hasComplexEigenvalues()
The method performs a zero check for each element of the
getImagEigenvalues()
array and returns true
if any
element is not equal to zero.
true
if the eigen values are complex, false
otherwisepublic double[] getRealEigenvalues()
getD()
,
getRealEigenvalue(int)
,
getImagEigenvalues()
public double getRealEigenvalue(int i)
i
- index of the eigenvalue (counting from 0)
getD()
,
getRealEigenvalues()
,
getImagEigenvalue(int)
public double[] getImagEigenvalues()
getD()
,
getImagEigenvalue(int)
,
getRealEigenvalues()
public double getImagEigenvalue(int i)
i
- Index of the eigenvalue (counting from 0).
getD()
,
getImagEigenvalues()
,
getRealEigenvalue(int)
public RealVector getEigenvector(int i)
i
- Index of the eigenvector (counting from 0).
getD()
public double getDeterminant()
public RealMatrix getSquareRoot()
MathUnsupportedOperationException
- if the matrix is not
symmetric or not positive definite.public DecompositionSolver getSolver()
Since 3.1, eigen decomposition of a general matrix is supported,
but the DecompositionSolver
only supports real eigenvalues.
MathUnsupportedOperationException
- if the decomposition resulted in
complex eigenvalues
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