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124       m_sigma[k] = matA.col(k).end(m-k).norm();
129 matA.col(k).end(m-k) /= m_sigma[k];
140 Scalar t = matA.col(k).end(m-k).eigen2_dot(matA.col(j).end(m-k)); // FIXME dot product or cwise prod + .sum() ??
142 matA.col(j).end(m-k) += t * matA.col(k).end(m-k);
152 m_matU.col(k).end(m-k) = matA.col(k).end(m-k);
172 matA.col(j).end(m-k-1) += (-e[j]/e[k+1]) * work.end(m-k-1);
177 m_matV.col(k).end(n-k-1) = e.end(n-k-1);
197 m_matU.col(j).setZero();
206 Scalar t = m_matU.col(k).end(m-k).eigen2_dot(m_matU.col(j).end(m-k)); // FIXME is it really a dot product we want ?
208 m_matU.col(j).end(m-k) += t * m_matU.col(k).end(m-k);
210 m_matU.col(k).end(m-k) = - m_matU.col(k).end(m-k);
213 m_matU.col(k).start(k-1).setZero();
217 m_matU.col(k).setZero();
232 Scalar t = m_matV.col(k).end(n-k-1).eigen2_dot(m_matV.col(j).end(n-k-1)); // FIXME is it really a dot product we want ?
234 m_matV.col(j).end(n-k-1) += t * m_matV.col(k).end(n-k-1);
237 m_matV.col(k).setZero();
444 m_matV.col(k).start(pp+1) = -m_matV.col(k).start(pp+1);
456 m_matV.col(k).swap(m_matV.col(k+1));
458 m_matU.col(k).swap(m_matU.col(k+1));
521 Matrix<Scalar,MatrixUType::RowsAtCompileTime,1> aux = m_matU.transpose() * b.col(j);
532 result->col(j) = m_matV * aux;
594 m.col(0) /= x;
620 m.col(0) /= x;