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java.lang.Objectorg.ujmp.core.doublematrix.calculation.general.decomposition.SVD.SVDMatrix
public static final class SVD.SVDMatrix
Constructor Summary | |
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SVD.SVDMatrix(Matrix Arg)
Construct the singular value decomposition |
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SVD.SVDMatrix(Matrix Arg,
boolean thin,
boolean wantu,
boolean wantv)
Construct the singular value decomposition |
Method Summary | |
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double |
cond()
Two norm condition number |
Matrix |
getreciprocalS()
Return the diagonal matrix of the reciprocals of the singular values |
Matrix |
getS()
Return the diagonal matrix of singular values |
double[] |
getSingularValues()
Return the one-dimensional array of singular values |
Matrix |
getU()
Return the left singular vectors |
Matrix |
getV()
Return the right singular vectors |
Matrix |
inverse(boolean omit)
Return the Moore-Penrose (generalized) inverse Slightly modified version of Kim van der Linde's code |
double |
norm2()
Two norm |
int |
rank()
Effective numerical matrix rank |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public SVD.SVDMatrix(Matrix Arg)
Arg
- Rectangular matrixpublic SVD.SVDMatrix(Matrix Arg, boolean thin, boolean wantu, boolean wantv)
Arg
- Rectangular matrixthin
- If true U is economy sizedwantu
- If true generate the U matrixwantv
- If true generate the V matrixMethod Detail |
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public final Matrix getU()
public final Matrix getV()
public final double[] getSingularValues()
public final Matrix getS()
public final Matrix getreciprocalS()
public final Matrix inverse(boolean omit)
omit
- if true tolerance based omitting of negligible singular
values
public final double norm2()
public final double cond()
public final int rank()
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