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FloatEigDecomp Class

Class FloatEigDecomp computes the eigenvalues and left and right eigenvectors of a general matrix, with preliminary balancing.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreFloatEigDecomp

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.4
Syntax
[SerializableAttribute]
public class FloatEigDecomp : ICloneable

The FloatEigDecomp type exposes the following members.

Constructors
  NameDescription
Public methodFloatEigDecomp
Default constructor. Constructs an empty eigenvalue decomposition.
Public methodFloatEigDecomp(FloatMatrix)
Construct a FloatEigDecomp instance for the given matrix.
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Properties
  NameDescription
Public propertyCols
Gets the number of columns in the decomposed matrix.
Public propertyEigenValues
Gets the computed eigenvalues.
Public propertyIsGood
Returns true if the all the eigenvalues and eigenvectors were successfully computed; otherwise, false.
Public propertyLeftEigenVectors
Gets the matrix of left eigenvectors.
Public propertyNumberOfEigenValues
Gets the number of eigenvalues computed.
Public propertyNumberOfLeftEigenVectors
Gets the number of left eigenvectors.
Public propertyNumberOfRightEigenVectors
Gets the number of right eigenvectors.
Public propertyRightEigenVectors
Gets the matrix of right eigenvectors.
Public propertyRows
Gets the number of rows in the decomposed matrix.
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Methods
  NameDescription
Public methodClone
Creates a deep copy of this eigenvalue decompostiion.
Public methodEigenValue
Returns the ith eigenvalue.
Public methodFactor
Computes all the eigenvalues and eigenvectors for the given square matrix.
Public methodFactorNoPreconditioning
Computes all eigenvalues and eigenvectors for the given square matrix.
Public methodLeftEigenVector
Returns the ith left eigenvector.
Public methodRightEigenVector
Returns the ith right eigenvector.
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Remarks
Balancing a matrix means permuting the rows and columns to make it more nearly upper triangular, and applying a diagonal similarity transformation to make its rows and columns closer in norm and the condition numbers of its eigenvalues and eigenvectors smaller.
See Also