Package com.actelion.research.calc
Class SingularValueDecomposition
- java.lang.Object
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- com.actelion.research.calc.SingularValueDecomposition
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- All Implemented Interfaces:
java.io.Serializable
public class SingularValueDecomposition extends java.lang.Object implements java.io.Serializable
Singular Value Decomposition.For an m-by-n matrix A with m >= n, the singular value decomposition is an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and an n-by-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 decompostion 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
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Constructor Summary
Constructors Constructor Description SingularValueDecomposition(double[][] A, ProgressListener progressListener, ThreadMaster threadMaster)
Construct the singular value decomposition
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description double
cond()
Two norm condition numberdouble[]
getSingularValues()
Return the one-dimensional array of singular valuesdouble[][]
getU()
Return the left singular vectorsdouble[][]
getV()
Return the right singular vectorsstatic double
hypot(double a, double b)
double
norm2()
Two normint
rank()
Effective numerical matrix rank
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Constructor Detail
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SingularValueDecomposition
public SingularValueDecomposition(double[][] A, ProgressListener progressListener, ThreadMaster threadMaster)
Construct the singular value decomposition- Parameters:
A
- Rectangular matrix
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Method Detail
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getU
public double[][] getU()
Return the left singular vectors- Returns:
- U
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getV
public double[][] getV()
Return the right singular vectors- Returns:
- V
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getSingularValues
public double[] getSingularValues()
Return the one-dimensional array of singular values- Returns:
- diagonal of S.
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norm2
public double norm2()
Two norm- Returns:
- max(S)
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cond
public double cond()
Two norm condition number- Returns:
- max(S)/min(S)
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rank
public int rank()
Effective numerical matrix rank- Returns:
- Number of nonnegligible singular values.
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hypot
public static double hypot(double a, double b)
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