79     FullPivLU(Index rows, Index cols);
313       return cols() - rank();  in dimensionOfKernel()
326       return rank() == cols();  in isInjective()
351       return isInjective() && (m_lu.rows() == m_lu.cols());  in isInvertible()
364 …  eigen_assert(m_lu.rows() == m_lu.cols() && "You can't take the inverse of a non-square matrix!");  in inverse()
366                (*this, MatrixType::Identity(m_lu.rows(), m_lu.cols()));  in inverse()
372     inline Index cols() const { return m_lu.cols(); }  in cols()  function
392 FullPivLU<MatrixType>::FullPivLU(Index rows, Index cols)  in FullPivLU()  argument
393   : m_lu(rows, cols),  in FullPivLU()
395     m_q(cols),  in FullPivLU()
397     m_colsTranspositions(cols),  in FullPivLU()
405   : m_lu(matrix.rows(), matrix.cols()),  in FullPivLU()
407     m_q(matrix.cols()),  in FullPivLU()
409     m_colsTranspositions(matrix.cols()),  in FullPivLU()
424   const Index cols = matrix.cols();  in compute()  local
429   m_colsTranspositions.resize(matrix.cols());  in compute()
442     biggest_in_corner = m_lu.bottomRightCorner(rows-k, cols-k)  in compute()
483 …m_lu.block(k+1,k+1,rows-k-1,cols-k-1).noalias() -= m_lu.col(k).tail(rows-k-1) * m_lu.row(k).tail(c…  in compute()
493   m_q.setIdentity(cols);  in compute()
505 …eigen_assert(m_lu.rows() == m_lu.cols() && "You can't take the determinant of a non-square matrix!…  in determinant()
516   const Index smalldim = (std::min)(m_lu.rows(), m_lu.cols());  in reconstructedMatrix()
518   MatrixType res(m_lu.rows(),m_lu.cols());  in reconstructedMatrix()
550     const Index cols = dec().matrixLU().cols(), dimker = cols - rank();
590       m(dec().matrixLU().block(0, 0, rank(), cols));
594       m.row(i).tail(cols-i) = dec().matrixLU().row(pivots.coeff(i)).tail(cols-i);
615     for(Index i = rank(); i < cols; ++i) dst.row(dec().permutationQ().indices().coeff(i)).setZero();
675     const Index rows = dec().rows(), cols = dec().cols(),
678     const Index smalldim = (std::min)(rows, cols);
686     typename Rhs::PlainObject c(rhs().rows(), rhs().cols());
696     if(rows>cols)
698       c.bottomRows(rows-cols)
699         -= dec().matrixLU().bottomRows(rows-cols)
700          * c.topRows(cols);
712     for(Index i = nonzero_pivots; i < dec().matrixLU().cols(); ++i)