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bug #792: SparseLU::factorize failed for structurally rank deficient matrices

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This commit is contained in:
Christoph Hertzberg 2015-07-26 20:30:30 +02:00
parent 4b3052c54d
commit a44d022caf
3 changed files with 27 additions and 8 deletions
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11
Eigen/src/SparseLU/SparseLU_pivotL.h
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@ -71,7 +71,7 @@ Index SparseLUImpl<Scalar,StorageIndex>::pivotL(const Index jcol, const RealScal
// Determine the largest abs numerical value for partial pivoting
Index diagind = iperm_c(jcol); // diagonal index
RealScalar pivmax = 0.0;
RealScalar pivmax(-1.0);
Index pivptr = nsupc;
Index diag = emptyIdxLU;
RealScalar rtemp;
@ -87,8 +87,9 @@ Index SparseLUImpl<Scalar,StorageIndex>::pivotL(const Index jcol, const RealScal
}
// Test for singularity
if ( pivmax == 0.0 ) {
pivrow = lsub_ptr[pivptr];
if ( pivmax <= RealScalar(0.0) ) {
// if pivmax == -1, the column is structurally empty, otherwise it is only numerically zero
pivrow = pivmax < RealScalar(0.0) ? diagind : lsub_ptr[pivptr];
perm_r(pivrow) = StorageIndex(jcol);
return (jcol+1);
}
@ -104,13 +105,13 @@ Index SparseLUImpl<Scalar,StorageIndex>::pivotL(const Index jcol, const RealScal
// Diagonal element exists
using std::abs;
rtemp = abs(lu_col_ptr[diag]);
if (rtemp != 0.0 && rtemp >= thresh) pivptr = diag;
if (rtemp != RealScalar(0.0) && rtemp >= thresh) pivptr = diag;
}
pivrow = lsub_ptr[pivptr];
}
// Record pivot row
perm_r(pivrow) = StorageIndex(jcol);
perm_r(pivrow) = StorageIndex(jcol);
// Interchange row subscripts
if (pivptr != nsupc )
{

20
test/sparse_solver.h
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@ -332,7 +332,18 @@ Index generate_sparse_square_problem(Solver&, typename Solver::MatrixType& A, De
return size;
}
template<typename Solver> void check_sparse_square_solving(Solver& solver, int maxSize = 300, int maxRealWorldSize = 100000)
struct prune_column {
Index m_col;
prune_column(Index col) : m_col(col) {}
template<class Scalar>
bool operator()(Index, Index col, const Scalar&) const {
return col != m_col;
}
};
template<typename Solver> void check_sparse_square_solving(Solver& solver, int maxSize = 300, int maxRealWorldSize = 100000, bool checkDeficient = false)
{
typedef typename Solver::MatrixType Mat;
typedef typename Mat::Scalar Scalar;
@ -364,6 +375,13 @@ template<typename Solver> void check_sparse_square_solving(Solver& solver, int m
b = DenseVector::Zero(size);
check_sparse_solving(solver, A, b, dA, b);
}
// regression test for Bug 792 (structurally rank deficient matrices):
if(checkDeficient && size>1) {
Index col = internal::random<int>(0,size-1);
A.prune(prune_column(col));
solver.compute(A);
VERIFY_IS_EQUAL(solver.info(), NumericalIssue);
}
}
// First, get the folder

4
test/sparselu.cpp
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@ -42,8 +42,8 @@ template<typename T> void test_sparselu_T()
SparseLU<SparseMatrix<T, ColMajor, long int>, NaturalOrdering<long int> > sparselu_natural;
check_sparse_square_solving(sparselu_colamd);
check_sparse_square_solving(sparselu_amd, 300, 2000);
check_sparse_square_solving(sparselu_natural, 300, 2000);
check_sparse_square_solving(sparselu_amd, 300, 2000, !true); // FIXME AMD ordering fails for structurally deficient matrices!
check_sparse_square_solving(sparselu_natural, 300, 2000, true);
check_sparse_square_abs_determinant(sparselu_colamd);
check_sparse_square_abs_determinant(sparselu_amd);