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authorGravatar Christoph Hertzberg <chtz@informatik.uni-bremen.de>2018-05-17 19:17:01 +0200
committerGravatar Christoph Hertzberg <chtz@informatik.uni-bremen.de>2018-05-17 19:17:01 +0200
commitd6559009530b87f80fc5aaa864c012ae5109e848 (patch)
tree95a651e4a2c5529b799fcce4615e42670ea7f88f /Eigen/src/SparseQR
parent0371380d5b6e7686d12e544b9477142219f67ea5 (diff)
bug #1544: Generate correct Q matrix in complex case. Original patch was by Jeff Trull in PR-386.
Diffstat (limited to 'Eigen/src/SparseQR')
-rw-r--r--Eigen/src/SparseQR/SparseQR.h15
1 files changed, 9 insertions, 6 deletions
diff --git a/Eigen/src/SparseQR/SparseQR.h b/Eigen/src/SparseQR/SparseQR.h
index f7111fe2e..278d775aa 100644
--- a/Eigen/src/SparseQR/SparseQR.h
+++ b/Eigen/src/SparseQR/SparseQR.h
@@ -52,7 +52,7 @@ namespace internal {
* rank-revealing permutations. Use colsPermutation() to get it.
*
* Q is the orthogonal matrix represented as products of Householder reflectors.
- * Use matrixQ() to get an expression and matrixQ().transpose() to get the transpose.
+ * Use matrixQ() to get an expression and matrixQ().adjoint() to get the adjoint.
* You can then apply it to a vector.
*
* R is the sparse triangular or trapezoidal matrix. The later occurs when A is rank-deficient.
@@ -65,6 +65,7 @@ namespace internal {
* \implsparsesolverconcept
*
* \warning The input sparse matrix A must be in compressed mode (see SparseMatrix::makeCompressed()).
+ * \warning For complex matrices matrixQ().transpose() will actually return the adjoint matrix.
*
*/
template<typename _MatrixType, typename _OrderingType>
@@ -196,9 +197,9 @@ class SparseQR : public SparseSolverBase<SparseQR<_MatrixType,_OrderingType> >
Index rank = this->rank();
- // Compute Q^T * b;
+ // Compute Q^* * b;
typename Dest::PlainObject y, b;
- y = this->matrixQ().transpose() * B;
+ y = this->matrixQ().adjoint() * B;
b = y;
// Solve with the triangular matrix R
@@ -641,7 +642,7 @@ struct SparseQR_QProduct : ReturnByValue<SparseQR_QProduct<SparseQRType, Derived
Scalar tau = Scalar(0);
tau = m_qr.m_Q.col(k).dot(res.col(j));
if(tau==Scalar(0)) continue;
- tau = tau * m_qr.m_hcoeffs(k);
+ tau = tau * numext::conj(m_qr.m_hcoeffs(k));
res.col(j) -= tau * m_qr.m_Q.col(k);
}
}
@@ -650,7 +651,7 @@ struct SparseQR_QProduct : ReturnByValue<SparseQR_QProduct<SparseQRType, Derived
const SparseQRType& m_qr;
const Derived& m_other;
- bool m_transpose;
+ bool m_transpose; // TODO this actually means adjoint
};
template<typename SparseQRType>
@@ -668,13 +669,14 @@ struct SparseQRMatrixQReturnType : public EigenBase<SparseQRMatrixQReturnType<Sp
{
return SparseQR_QProduct<SparseQRType,Derived>(m_qr,other.derived(),false);
}
+ // To use for operations with the adjoint of Q
SparseQRMatrixQTransposeReturnType<SparseQRType> adjoint() const
{
return SparseQRMatrixQTransposeReturnType<SparseQRType>(m_qr);
}
inline Index rows() const { return m_qr.rows(); }
inline Index cols() const { return (std::min)(m_qr.rows(),m_qr.cols()); }
- // To use for operations with the transpose of Q
+ // To use for operations with the transpose of Q FIXME this is the same as adjoint at the moment
SparseQRMatrixQTransposeReturnType<SparseQRType> transpose() const
{
return SparseQRMatrixQTransposeReturnType<SparseQRType>(m_qr);
@@ -682,6 +684,7 @@ struct SparseQRMatrixQReturnType : public EigenBase<SparseQRMatrixQReturnType<Sp
const SparseQRType& m_qr;
};
+// TODO this actually represents the adjoint of Q
template<typename SparseQRType>
struct SparseQRMatrixQTransposeReturnType
{