From 1b4623e7132c0959925386801e9e342ba5565f19 Mon Sep 17 00:00:00 2001
From: Gael Guennebaud <g.gael@free.fr>
Date: Thu, 12 Sep 2013 22:16:35 +0200
Subject: Fix elimination tree and SparseQR with rows<cols

---
 Eigen/src/SparseQR/SparseQR.h | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

(limited to 'Eigen/src/SparseQR')

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.,
-- 
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