diff options
| author |  Gael Guennebaud <g.gael@free.fr> | 2013-09-12 22:16:35 +0200 |
|---|---|---|
| committer | Gael Guennebaud <g.gael@free.fr> | 2013-09-12 22:16:35 +0200 |
| commit | 1b4623e7132c0959925386801e9e342ba5565f19 (patch) | |
| tree | da5c44fba65ad414ff667b8604b66dbab6c2a5d1 /Eigen/src/SparseQR | |
| parent | 4612a1cd870b4a72b3849608fcdce9a18dc80a65 (diff) | |
Fix elimination tree and SparseQR with rows<cols
Diffstat (limited to 'Eigen/src/SparseQR')
| -rw-r--r-- | Eigen/src/SparseQR/SparseQR.h | 9 |
1 files changed, 5 insertions, 4 deletions
diff --git a/Eigen/src/SparseQR/SparseQR.h b/Eigen/src/SparseQR/SparseQR.h index c42dfc556..50c4c1145 100644 --- a/Eigen/src/SparseQR/SparseQR.h +++ b/Eigen/src/SparseQR/SparseQR.h @@ -161,8 +161,9 @@ class SparseQR b = y; // Solve with the triangular matrix R + y.resize((std::max)(cols(),Index(y.rows())),y.cols()); y.topRows(rank) = this->matrixR().topLeftCorner(rank, rank).template triangularView<Upper>().solve(b.topRows(rank)); - y.bottomRows(y.size()-rank).setZero(); + y.bottomRows(y.rows()-rank).setZero(); // Apply the column permutation if (m_perm_c.size()) dest.topRows(cols()) = colsPermutation() * y.topRows(cols()); @@ -246,7 +247,7 @@ class SparseQR Index m_nonzeropivots; // Number of non zero pivots found IndexVector m_etree; // Column elimination tree IndexVector m_firstRowElt; // First element in each row - bool m_isQSorted; // whether Q is sorted or not + bool m_isQSorted; // whether Q is sorted or not template <typename, typename > friend struct SparseQR_QProduct; template <typename > friend struct SparseQRMatrixQReturnType; @@ -338,7 +339,7 @@ void SparseQR<MatrixType,OrderingType>::factorize(const MatrixType& mat) Index nonzeroCol = 0; // Record the number of valid pivots // Left looking rank-revealing QR factorization: compute a column of R and Q at a time - for (Index col = 0; col < n; ++col) + for (Index col = 0; col < (std::min)(n,m); ++col) { mark.setConstant(-1); m_R.startVec(col); @@ -346,7 +347,7 @@ void SparseQR<MatrixType,OrderingType>::factorize(const MatrixType& mat) mark(nonzeroCol) = col; Qidx(0) = nonzeroCol; nzcolR = 0; nzcolQ = 1; - found_diag = false; + found_diag = col>=m; tval.setZero(); // Symbolic factorization: find the nonzero locations of the column k of the factors R and Q, i.e., |