﻿cvEigenVV Method
http://www.emgu.com
Computes eigenvalues and eigenvectors of a symmetric matrix

Namespace: Emgu.CV
Assembly: Emgu.CV (in Emgu.CV.dll) Version: 2.4.2.1777 (2.4.2.1777)

# Syntax

C#
```public static void cvEigenVV(
IntPtr mat,
IntPtr evects,
IntPtr evals,
double eps,
int lowindex,
int highindex
)```
Visual Basic
```Public Shared Sub cvEigenVV ( _
mat As IntPtr, _
evects As IntPtr, _
evals As IntPtr, _
eps As Double, _
lowindex As Integer, _
highindex As Integer _
)```
Visual C++
```public:
static void cvEigenVV(
IntPtr mat,
IntPtr evects,
IntPtr evals,
double eps,
int lowindex,
int highindex
)```

#### Parameters

mat
Type: System..::..IntPtr
The input symmetric square matrix, modified during the processing
evects
Type: System..::..IntPtr
The output matrix of eigenvectors, stored as subsequent rows
evals
Type: System..::..IntPtr
The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is syncronized, of course)
eps
Type: System..::..Double
Accuracy of diagonalization. Typically, DBL EPSILON (about 10^(-15)) works well. THIS PARAMETER IS CURRENTLY IGNORED.
lowindex
Type: System..::..Int32
Optional index of largest eigenvalue/-vector to calculate. If either low- or highindex is supplied the other is required, too. Indexing is 1-based. Use 0 for default.
highindex
Type: System..::..Int32
Optional index of smallest eigenvalue/-vector to calculate. If either low- or highindex is supplied the other is required, too. Indexing is 1-based. Use 0 for default.

# Remarks

Currently the function is slower than cvSVD yet less accurate, so if A is known to be positivelydefined (for example, it is a covariance matrix)it is recommended to use cvSVD to find eigenvalues and eigenvectors of A, especially if eigenvectors are not required.

# Examples

To calculate the largest eigenvector/-value set lowindex = highindex = 1. For legacy reasons this function always returns a square matrix the same size as the source matrix with eigenvectors and a vector the length of the source matrix with eigenvalues. The selected eigenvectors/-values are always in the first highindex - lowindex + 1 rows.