diff options
| -rw-r--r-- | Eigen/src/SparseLU/SparseLU.h | 3 | ||||
| -rw-r--r-- | Eigen/src/SparseLU/SparseLU_Matrix.h | 1 | ||||
| -rw-r--r-- | Eigen/src/SparseLU/SparseLU_column_bmod.h | 1 | ||||
| -rw-r--r-- | Eigen/src/SparseLU/SparseLU_pruneL.h | 2 | ||||
| -rw-r--r-- | bench/spbench/test_sparseLU.cpp | 1 |
5 files changed, 6 insertions, 2 deletions
diff --git a/Eigen/src/SparseLU/SparseLU.h b/Eigen/src/SparseLU/SparseLU.h index a07b5a9f3..e4a4c3a7b 100644 --- a/Eigen/src/SparseLU/SparseLU.h +++ b/Eigen/src/SparseLU/SparseLU.h @@ -186,7 +186,6 @@ class SparseLU // Triangular solve Map<const Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(Lval[luptr]), nsupc, nsupc, OuterStride<>(nsupr) ); Map< Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > U (&(X.data()[fsupc]), nsupc, nrhs, OuterStride<>(X.rows()) ); -// Block<MatrixBase<Dest> > U(X, fsupc, 0, nsupc, nrhs); //FIXME TODO Consider more RHS U = A.template triangularView<Lower>().solve(U); // Matrix-vector product @@ -536,6 +535,7 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix) // Eliminate the current column info = LU_pivotL(icol, m_diagpivotthresh, m_perm_r.indices(), iperm_c.indices(), pivrow, m_glu); + eigen_assert(info==0 && " SINGULAR MATRIX"); if ( info ) { m_info = NumericalIssue; @@ -609,6 +609,7 @@ void SparseLU<MatrixType, OrderingType>::factorize(const MatrixType& matrix) // Form the L-segment info = LU_pivotL(jj, m_diagpivotthresh, m_perm_r.indices(), iperm_c.indices(), pivrow, m_glu); + eigen_assert(info==0 && " SINGULAR MATRIX"); if ( info ) { std::cerr<< "THE MATRIX IS STRUCTURALLY SINGULAR ... ZERO COLUMN AT " << info <<std::endl; diff --git a/Eigen/src/SparseLU/SparseLU_Matrix.h b/Eigen/src/SparseLU/SparseLU_Matrix.h index 5b2c64154..90a0f2740 100644 --- a/Eigen/src/SparseLU/SparseLU_Matrix.h +++ b/Eigen/src/SparseLU/SparseLU_Matrix.h @@ -79,6 +79,7 @@ class SuperNodalMatrix m_nzval_colptr = nzval_colptr.data(); m_rowind = rowind.data(); m_rowind_colptr = rowind_colptr.data(); + m_nsuper = col_to_sup(n); m_col_to_sup = col_to_sup.data(); m_sup_to_col = sup_to_col.data(); diff --git a/Eigen/src/SparseLU/SparseLU_column_bmod.h b/Eigen/src/SparseLU/SparseLU_column_bmod.h index 8dadeaa93..02ea7c360 100644 --- a/Eigen/src/SparseLU/SparseLU_column_bmod.h +++ b/Eigen/src/SparseLU/SparseLU_column_bmod.h @@ -133,6 +133,7 @@ int LU_column_bmod(const int jcol, const int nseg, BlockScalarVector& dense, Sca // Dense triangular solve -- start effective triangle luptr += nsupr * no_zeros + no_zeros; // Form Eigen matrix and vector +// std::cout<< "jcol " << jcol << " rows " << segsize << std::endl; Map<Matrix<Scalar,Dynamic,Dynamic>, 0, OuterStride<> > A( &(lusup.data()[luptr]), segsize, segsize, OuterStride<>(nsupr) ); VectorBlock<ScalarVector> u(tempv, 0, segsize); diff --git a/Eigen/src/SparseLU/SparseLU_pruneL.h b/Eigen/src/SparseLU/SparseLU_pruneL.h index 42218ba4a..91c795fac 100644 --- a/Eigen/src/SparseLU/SparseLU_pruneL.h +++ b/Eigen/src/SparseLU/SparseLU_pruneL.h @@ -123,7 +123,7 @@ void LU_pruneL(const int jcol, const IndexVector& perm_r, const int pivrow, cons if (perm_r(lsub(kmax)) == IND_EMPTY) kmax--; else if ( perm_r(lsub(kmin)) != IND_EMPTY) - kmin--; + kmin++; else { // kmin below pivrow (not yet pivoted), and kmax diff --git a/bench/spbench/test_sparseLU.cpp b/bench/spbench/test_sparseLU.cpp index 0bbbb0627..4727cc12b 100644 --- a/bench/spbench/test_sparseLU.cpp +++ b/bench/spbench/test_sparseLU.cpp @@ -52,6 +52,7 @@ int main(int argc, char **args) } /* Compute the factorization */ + solver.isSymmetric(true); solver.compute(A); solver._solve(b, x); |