Parallel Colt 0.7.2

cern.colt.matrix.tfloat.algo.decomposition
Class FloatSingularValueDecomposition

java.lang.Object
  extended by cern.colt.matrix.tfloat.algo.decomposition.FloatSingularValueDecomposition
All Implemented Interfaces:
Serializable

public class FloatSingularValueDecomposition
extends Object
implements Serializable

For an m x n matrix A with m >= n, the singular value decomposition is an m x n orthogonal matrix U, an n x n diagonal matrix S, and an n x n orthogonal matrix V so that A = U*S*V'.

The singular values, sigma[k] = S[k][k], are ordered so that sigma[0] >= sigma[1] >= ... >= sigma[n-1].

The singular value decomposition always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.

See Also:
Serialized Form

Constructor Summary
FloatSingularValueDecomposition(FloatMatrix2D Arg)
          Constructs and returns a new singular value decomposition object; The decomposed matrices can be retrieved via instance methods of the returned decomposition object.
 
Method Summary
 float cond()
          Returns the two norm condition number, which is max(S) / min(S).
 FloatMatrix2D getS()
          Returns the diagonal matrix of singular values.
 float[] getSingularValues()
          Returns the diagonal of S, which is a one-dimensional array of singular values
 FloatMatrix2D getU()
          Returns the left singular vectors U.
 FloatMatrix2D getV()
          Returns the right singular vectors V.
 float norm2()
          Returns the two norm, which is max(S).
 int rank()
          Returns the effective numerical matrix rank, which is the number of nonnegligible singular values.
 String toString()
          Returns a String with (propertyName, propertyValue) pairs.
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

FloatSingularValueDecomposition

public FloatSingularValueDecomposition(FloatMatrix2D Arg)
Constructs and returns a new singular value decomposition object; The decomposed matrices can be retrieved via instance methods of the returned decomposition object.

Parameters:
Arg - A rectangular matrix.
Throws:
IllegalArgumentException - if A.rows() < A.columns().
Method Detail

cond

public float cond()
Returns the two norm condition number, which is max(S) / min(S).


getS

public FloatMatrix2D getS()
Returns the diagonal matrix of singular values.

Returns:
S

getSingularValues

public float[] getSingularValues()
Returns the diagonal of S, which is a one-dimensional array of singular values

Returns:
diagonal of S.

getU

public FloatMatrix2D getU()
Returns the left singular vectors U.

Returns:
U

getV

public FloatMatrix2D getV()
Returns the right singular vectors V.

Returns:
V

norm2

public float norm2()
Returns the two norm, which is max(S).


rank

public int rank()
Returns the effective numerical matrix rank, which is the number of nonnegligible singular values.


toString

public String toString()
Returns a String with (propertyName, propertyValue) pairs. Useful for debugging or to quickly get the rough picture. For example,
         rank          : 3
         trace         : 0
 
 

Overrides:
toString in class Object

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