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-rw-r--r--Eigen/src/IterativeLinearSolvers/IncompleteLUT.h9
1 files changed, 0 insertions, 9 deletions
diff --git a/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h b/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
index 43bd8e8f6..09436cb67 100644
--- a/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
+++ b/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
@@ -225,7 +225,6 @@ void IncompleteLUT<Scalar,StorageIndex>::analyzePattern(const _MatrixType& amat)
// Compute the Fill-reducing permutation
// Since ILUT does not perform any numerical pivoting,
// it is highly preferable to keep the diagonal through symmetric permutations.
-#ifndef EIGEN_MPL2_ONLY
// To this end, let's symmetrize the pattern and perform AMD on it.
SparseMatrix<Scalar,ColMajor, StorageIndex> mat1 = amat;
SparseMatrix<Scalar,ColMajor, StorageIndex> mat2 = amat.transpose();
@@ -235,14 +234,6 @@ void IncompleteLUT<Scalar,StorageIndex>::analyzePattern(const _MatrixType& amat)
AMDOrdering<StorageIndex> ordering;
ordering(AtA,m_P);
m_Pinv = m_P.inverse(); // cache the inverse permutation
-#else
- // If AMD is not available, (MPL2-only), then let's use the slower COLAMD routine.
- SparseMatrix<Scalar,ColMajor, StorageIndex> mat1 = amat;
- COLAMDOrdering<StorageIndex> ordering;
- ordering(mat1,m_Pinv);
- m_P = m_Pinv.inverse();
-#endif
-
m_analysisIsOk = true;
m_factorizationIsOk = false;
m_isInitialized = true;