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enum | {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime),
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime, MaxColsAtCompileTime),
MatrixOptions = MatrixType::Options
} |
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typedef _MatrixType | MatrixType |
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typedef MatrixType::Scalar | Scalar |
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typedef NumTraits< typename MatrixType::Scalar >::Real | RealScalar |
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typedef Base::MatrixUType | MatrixUType |
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typedef Base::MatrixVType | MatrixVType |
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typedef Base::SingularValuesType | SingularValuesType |
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typedef Matrix< Scalar, Dynamic, Dynamic, ColMajor > | MatrixX |
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typedef Matrix< RealScalar, Dynamic, Dynamic, ColMajor > | MatrixXr |
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typedef Matrix< RealScalar, Dynamic, 1 > | VectorType |
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typedef Array< RealScalar, Dynamic, 1 > | ArrayXr |
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typedef Array< Index, 1, Dynamic > | ArrayXi |
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typedef Ref< ArrayXr > | ArrayRef |
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typedef Ref< ArrayXi > | IndicesRef |
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enum | |
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typedef internal::traits< BDCSVD< _MatrixType > >::MatrixType | MatrixType |
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typedef MatrixType::Scalar | Scalar |
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typedef NumTraits< typename MatrixType::Scalar >::Real | RealScalar |
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typedef MatrixType::StorageIndex | StorageIndex |
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typedef Eigen::Index | Index |
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typedef Matrix< Scalar, RowsAtCompileTime, RowsAtCompileTime, MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTime > | MatrixUType |
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typedef Matrix< Scalar, ColsAtCompileTime, ColsAtCompileTime, MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTime > | MatrixVType |
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typedef internal::plain_diag_type< MatrixType, RealScalar >::type | SingularValuesType |
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| BDCSVD () |
| Default Constructor. More...
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| BDCSVD (Index rows, Index cols, unsigned int computationOptions=0) |
| Default Constructor with memory preallocation. More...
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| BDCSVD (const MatrixType &matrix, unsigned int computationOptions=0) |
| Constructor performing the decomposition of given matrix. More...
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BDCSVD & | compute (const MatrixType &matrix, unsigned int computationOptions) |
| Method performing the decomposition of given matrix using custom options. More...
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BDCSVD & | compute (const MatrixType &matrix) |
| Method performing the decomposition of given matrix using current options. More...
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void | setSwitchSize (int s) |
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BDCSVD< _MatrixType > & | derived () |
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const BDCSVD< _MatrixType > & | derived () const |
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const MatrixUType & | matrixU () const |
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const MatrixVType & | matrixV () const |
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const SingularValuesType & | singularValues () const |
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Index | nonzeroSingularValues () const |
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Index | rank () const |
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BDCSVD< _MatrixType > & | setThreshold (const RealScalar &threshold) |
| Allows to prescribe a threshold to be used by certain methods, such as rank() and solve(), which need to determine when singular values are to be considered nonzero. More...
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BDCSVD< _MatrixType > & | setThreshold (Default_t) |
| Allows to come back to the default behavior, letting Eigen use its default formula for determining the threshold. More...
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RealScalar | threshold () const |
| Returns the threshold that will be used by certain methods such as rank(). More...
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bool | computeU () const |
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bool | computeV () const |
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Index | rows () const |
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Index | cols () const |
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const Solve< BDCSVD< _MatrixType >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
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EIGEN_DEVICE_FUNC void | _solve_impl (const RhsType &rhs, DstType &dst) const |
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void | _solve_impl (const RhsType &rhs, DstType &dst) const |
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template<typename _MatrixType>
class Eigen::BDCSVD< _MatrixType >
class Bidiagonal Divide and Conquer SVD
- Template Parameters
-
_MatrixType | the type of the matrix of which we are computing the SVD decomposition |
This class first reduces the input matrix to bi-diagonal form using class UpperBidiagonalization, and then performs a divide-and-conquer diagonalization. Small blocks are diagonalized using class JacobiSVD. You can control the switching size with the setSwitchSize() method, default is 16. For small matrice (<16), it is thus preferable to directly use JacobiSVD. For larger ones, BDCSVD is highly recommended and can several order of magnitude faster.
- Warning
- this algorithm is unlikely to provide accurate result when compiled with unsafe math optimizations. For instance, this concerns Intel's compiler (ICC), which perfroms such optimization by default unless you compile with the
-fp-model
precise
option. Likewise, the -ffast-math
option of GCC or clang will significantly degrade the accuracy.
- See also
- class JacobiSVD