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## org.apache.commons.math.linear
Interface SingularValueDecomposition

All Known Implementing Classes:
  SingularValueDecompositionImpl

    public interface SingularValueDecomposition

An interface to classes that implement an algorithm to calculate the Singular Value Decomposition of a real matrix.

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 interface is similar to the class with similar name from the JAMA library, with the following changes:

- the `norm2` method which has been renamed as `getNorm`,
- the `cond` method which has been renamed as `getConditionNumber`,
- the `rank` method which has been renamed as `getRank`,
- a `getUT` method has been added,
- a `getVT` method has been added,
- a `getSolver` method has been added,
- a `getCovariance` method has been added.

Since:
  2.0
Version:
  $Revision: 928081 $ $Date: 2010-03-26 23:36:38 +0100 (ven. 26 mars 2010) $
See Also:
  MathWorld, Wikipedia

Method Summary
`double` | `getConditionNumber()` Return the condition number of the matrix.
`RealMatrix` | `getCovariance(double minSingularValue)` Returns the n × n covariance matrix.
`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.

Method Detail

### getU

    RealMatrix getU()

  Returns the matrix U of the decomposition.

  U is an orthogonal matrix, i.e. its transpose is also its inverse.

  Returns:
    the U matrix
  See Also:
    `getUT()`

### getUT

    RealMatrix getUT()

  Returns the transpose of the matrix U of the decomposition.

  U is an orthogonal matrix, i.e. its transpose is also its inverse.

  Returns:
    the U matrix (or null if decomposed matrix is singular)
  See Also:
    `getU()`

### getS

    RealMatrix getS()

  Returns the diagonal matrix Σ of the decomposition.

  Σ is a diagonal matrix. The singular values are provided in non-increasing order, for compatibility with Jama.

  Returns:
    the Σ matrix

### getSingularValues

    double[] getSingularValues()

  Returns the diagonal elements of the matrix Σ of the decomposition.

  The singular values are provided in non-increasing order, for compatibility with Jama.

  Returns:
    the diagonal elements of the Σ matrix

### getV

    RealMatrix getV()

  Returns the matrix V of the decomposition.

  V is an orthogonal matrix, i.e. its transpose is also its inverse.

  Returns:
    the V matrix (or null if decomposed matrix is singular)
  See Also:
    `getVT()`

### getVT

    RealMatrix getVT()

  Returns the transpose of the matrix V of the decomposition.

  V is an orthogonal matrix, i.e. its transpose is also its inverse.

  Returns:
    the V matrix (or null if decomposed matrix is singular)
  See Also:
    `getV()`

### getCovariance

    RealMatrix getCovariance(double minSingularValue)
                             throws IllegalArgumentException

  Returns the n × n covariance matrix.

  The covariance matrix is V × J × VT where J is the diagonal matrix of the inverse of the squares of the singular values.

  Parameters:
    `minSingularValue` - value below which singular values are ignored (a 0 or negative value implies all singular value will be used)
  Returns:
    covariance matrix
  Throws:
    `IllegalArgumentException` - if minSingularValue is larger than the largest singular value, meaning all singular values are ignored

### getNorm

    double getNorm()

  Returns the L2 norm of the matrix.

  The L2 norm is max(|A × u|2 / |u|2), where |.|2 denotes the vectorial 2-norm (i.e. the traditional euclidian norm).

  Returns:
    norm

### getConditionNumber

    double getConditionNumber()

  Return the condition number of the matrix.

  Returns:
    condition number of the matrix

### getRank

    int getRank()

  Return the effective numerical matrix rank.

  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.

  Returns:
    effective numerical matrix rank

### getSolver

    DecompositionSolver getSolver()

  Get a solver for finding the A × X = B solution in least square sense.

  Returns:
    a solver

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