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Added support for custom-scalars
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@ -205,7 +205,7 @@ class SparseQR
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/** \brief Reports whether previous computation was successful.
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/** \brief Reports whether previous computation was successful.
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*
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*
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* \returns \c Success if computation was succesful,
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* \returns \c Success if computation was successful,
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* \c NumericalIssue if the QR factorization reports a numerical problem
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* \c NumericalIssue if the QR factorization reports a numerical problem
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* \c InvalidInput if the input matrix is invalid
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* \c InvalidInput if the input matrix is invalid
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*
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*
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@ -256,7 +256,7 @@ class SparseQR
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/** \brief Preprocessing step of a QR factorization
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/** \brief Preprocessing step of a QR factorization
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*
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*
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* In this step, the fill-reducing permutation is computed and applied to the columns of A
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* In this step, the fill-reducing permutation is computed and applied to the columns of A
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* and the column elimination tree is computed as well. Only the sparcity pattern of \a mat is exploited.
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* and the column elimination tree is computed as well. Only the sparsity pattern of \a mat is exploited.
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*
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*
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* \note In this step it is assumed that there is no empty row in the matrix \a mat.
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* \note In this step it is assumed that there is no empty row in the matrix \a mat.
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*/
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*/
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@ -292,7 +292,7 @@ void SparseQR<MatrixType,OrderingType>::analyzePattern(const MatrixType& mat)
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/** \brief Performs the numerical QR factorization of the input matrix
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/** \brief Performs the numerical QR factorization of the input matrix
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*
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*
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* The function SparseQR::analyzePattern(const MatrixType&) must have been called beforehand with
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* The function SparseQR::analyzePattern(const MatrixType&) must have been called beforehand with
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* a matrix having the same sparcity pattern than \a mat.
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* a matrix having the same sparsity pattern than \a mat.
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*
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*
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* \param mat The sparse column-major matrix
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* \param mat The sparse column-major matrix
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*/
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*/
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@ -445,7 +445,8 @@ void SparseQR<MatrixType,OrderingType>::factorize(const MatrixType& mat)
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}
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}
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else
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else
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{
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{
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beta = std::sqrt(numext::abs2(c0) + sqrNorm);
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using std::sqrt;
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beta = sqrt(numext::abs2(c0) + sqrNorm);
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if(numext::real(c0) >= RealScalar(0))
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if(numext::real(c0) >= RealScalar(0))
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beta = -beta;
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beta = -beta;
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tval(Qidx(0)) = 1;
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tval(Qidx(0)) = 1;
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