/external/eigen/Eigen/src/QR/ |
H A D | HouseholderQR_LAPACKE.h | 47 static void run(MatrixQR& mat, HCoeffs& hCoeffs, Index = 32, \ 54 LAPACKE_##LAPACKE_PREFIX##geqrf( matrix_order, m, n, (LAPACKE_TYPE*)mat.data(), lda, (LAPACKE_TYPE*)hCoeffs.data()); \ 55 hCoeffs.adjointInPlace(); \
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H A D | HouseholderQR.h | 212 const HCoeffsType& hCoeffs() const { return m_hCoeffs; } function in class:Eigen::HouseholderQR 256 void householder_qr_inplace_unblocked(MatrixQR& mat, HCoeffs& hCoeffs, typename MatrixQR::Scalar* tempData = 0) argument 264 eigen_assert(hCoeffs.size() == size); 280 mat.col(k).tail(remainingRows).makeHouseholderInPlace(hCoeffs.coeffRef(k), beta); 285 .applyHouseholderOnTheLeft(mat.col(k).tail(remainingRows-1), hCoeffs.coeffRef(k), tempData+k+1); 296 static void run(MatrixQR& mat, HCoeffs& hCoeffs, Index maxBlockSize=32, argument 332 Block<HCoeffs,Dynamic,1> hCoeffsSegment = hCoeffs.segment(k,bs);
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H A D | CompleteOrthogonalDecomposition.h | 289 inline const HCoeffsType& hCoeffs() const { return m_cpqr.hCoeffs(); } function in class:Eigen::CompleteOrthogonalDecomposition 507 householderSequence(matrixQTZ(), hCoeffs()).setLength(rank).transpose());
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H A D | FullPivHouseholderQR.h | 325 const HCoeffsType& hCoeffs() const { return m_hCoeffs; } function in class:Eigen::FullPivHouseholderQR 605 const HCoeffsType& hCoeffs, 608 m_hCoeffs(hCoeffs), 604 FullPivHouseholderQRMatrixQReturnType(const MatrixType& qr, const HCoeffsType& hCoeffs, const IntDiagSizeVectorType& rowsTranspositions) argument
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H A D | ColPivHouseholderQR.h | 334 const HCoeffsType& hCoeffs() const { return m_hCoeffs; } function in class:Eigen::ColPivHouseholderQR
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/external/eigen/Eigen/src/Householder/ |
H A D | BlockHouseholder.h | 22 // void make_block_householder_triangular_factor(TriangularFactorType& triFactor, const VectorsType& vectors, const CoeffsType& hCoeffs) 31 // // Warning, note that hCoeffs may alias with vectors. 33 // typename CoeffsType::Scalar h = hCoeffs(i); 44 // triFactor(i,i) = hCoeffs(i); 51 void make_block_householder_triangular_factor(TriangularFactorType& triFactor, const VectorsType& vectors, const CoeffsType& hCoeffs) argument 63 triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint() 70 triFactor(i,i) = hCoeffs(i); 79 void apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vectors, const CoeffsType& hCoeffs, bool forward) argument 85 if(forward) make_block_householder_triangular_factor(T, vectors, hCoeffs); 86 else make_block_householder_triangular_factor(T, vectors, hCoeffs [all...] |
/external/eigen/Eigen/src/Eigenvalues/ |
H A D | Tridiagonalization.h | 28 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs); 329 * \param[out] hCoeffs returned Householder coefficients (see below) 338 * where \f$ h_i = hCoeffs[i]\f$ is the \f$ i \f$th Householder coefficient and 347 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs) argument 354 eigen_assert(n==hCoeffs.size()+1 || n==1); 367 hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>() 370 hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); 373 .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); 376 hCoeffs [all...] |
H A D | HessenbergDecomposition.h | 272 static void _compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp); 285 * \param hCoeffs returned Householder coefficients 294 void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp) argument 307 hCoeffs.coeffRef(i) = h;
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/external/eigen/test/ |
H A D | householder.cpp | 87 HCoeffsVectorType hc = qr.hCoeffs().conjugate();
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/external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
H A D | LevenbergMarquardt.h | 474 fjac.diagonal() = qrfac.hCoeffs();
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