public class SingularValueDecomposition extends Object
The Singular Value Decomposition of matrix A is a set of three matrices: U, Σ and V such that A = U × Σ × VT. Let A be a m × n matrix, then U is a m × p orthogonal matrix, Σ is a p × p diagonal matrix with positive or null elements, V is a p × n orthogonal matrix (hence VT is also orthogonal) where p=min(m,n).
This class is similar to the class with similar name from the JAMA library, with the following changes:
norm2
method which has been renamed as getNorm
,cond
method which has been renamed as getConditionNumber
,rank
method which has been renamed as getRank
,getUT
method has been added,getVT
method has been added,getSolver
method has been added,getCovariance
method has been added.Constructor | Description |
---|---|
SingularValueDecomposition(RealMatrix matrix) |
Calculates the compact Singular Value Decomposition of the given matrix.
|
Modifier and Type | Method | Description |
---|---|---|
double |
getConditionNumber() |
Return the condition number of the matrix.
|
RealMatrix |
getCovariance(double minSingularValue) |
Returns the n × n covariance matrix.
|
double |
getInverseConditionNumber() |
Computes the inverse of the condition number.
|
double |
getNorm() |
Returns the L2 norm of the matrix.
|
int |
getRank() |
Return the effective numerical matrix rank.
|
RealMatrix |
getS() |
Returns the diagonal matrix Σ of the decomposition.
|
double[] |
getSingularValues() |
Returns the diagonal elements of the matrix Σ of the decomposition.
|
DecompositionSolver |
getSolver() |
Get a solver for finding the A × X = B solution in least square sense.
|
RealMatrix |
getU() |
Returns the matrix U of the decomposition.
|
RealMatrix |
getUT() |
Returns the transpose of the matrix U of the decomposition.
|
RealMatrix |
getV() |
Returns the matrix V of the decomposition.
|
RealMatrix |
getVT() |
Returns the transpose of the matrix V of the decomposition.
|
public SingularValueDecomposition(RealMatrix matrix)
matrix
- Matrix to decompose.public RealMatrix getU()
U is an orthogonal matrix, i.e. its transpose is also its inverse.
getUT()
public RealMatrix getUT()
U is an orthogonal matrix, i.e. its transpose is also its inverse.
getU()
public RealMatrix getS()
Σ is a diagonal matrix. The singular values are provided in non-increasing order, for compatibility with Jama.
public double[] getSingularValues()
The singular values are provided in non-increasing order, for compatibility with Jama.
public RealMatrix getV()
V is an orthogonal matrix, i.e. its transpose is also its inverse.
getVT()
public RealMatrix getVT()
V is an orthogonal matrix, i.e. its transpose is also its inverse.
getV()
public RealMatrix getCovariance(double minSingularValue)
The covariance matrix is V × J × VT where J is the diagonal matrix of the inverse of the squares of the singular values.
minSingularValue
- value below which singular values are ignored
(a 0 or negative value implies all singular value will be used)IllegalArgumentException
- if minSingularValue is larger than
the largest singular value, meaning all singular values are ignoredpublic double getNorm()
The L2 norm is max(|A × u|2 / |u|2), where |.|2 denotes the vectorial 2-norm (i.e. the traditional euclidian norm).
public double getConditionNumber()
public double getInverseConditionNumber()
condition
number
will become undefined.public int getRank()
The effective numerical rank is the number of non-negligible singular values. The threshold used to identify non-negligible terms is max(m,n) × ulp(s1) where ulp(s1) is the least significant bit of the largest singular value.
public DecompositionSolver getSolver()
Copyright © 2016–2018 Hipparchus.org. All rights reserved.