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minor chnages in Taucs and Cholmod backends
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@ -31,22 +31,22 @@ void ei_cholmod_configure_matrix(CholmodType& mat)
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if (ei_is_same_type<Scalar,float>::ret)
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{
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mat.xtype = CHOLMOD_REAL;
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mat.dtype = 1;
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mat.dtype = CHOLMOD_SINGLE;
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}
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else if (ei_is_same_type<Scalar,double>::ret)
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{
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mat.xtype = CHOLMOD_REAL;
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mat.dtype = 0;
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mat.dtype = CHOLMOD_DOUBLE;
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}
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else if (ei_is_same_type<Scalar,std::complex<float> >::ret)
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{
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mat.xtype = CHOLMOD_COMPLEX;
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mat.dtype = 1;
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mat.dtype = CHOLMOD_SINGLE;
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}
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else if (ei_is_same_type<Scalar,std::complex<double> >::ret)
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{
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mat.xtype = CHOLMOD_COMPLEX;
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mat.dtype = 0;
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mat.dtype = CHOLMOD_DOUBLE;
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}
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else
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{
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@ -74,6 +74,7 @@ cholmod_sparse SparseMatrixBase<Derived>::asCholmodMatrix()
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ei_cholmod_configure_matrix<Scalar>(res);
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if (Derived::Flags & SelfAdjoint)
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{
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if (Derived::Flags & Upper)
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@ -50,6 +50,7 @@ taucs_ccs_matrix SparseMatrixBase<Derived>::asTaucsMatrix()
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ei_assert(false && "Scalar type not supported by TAUCS");
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}
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// FIXME 1) shapes are not in the Flags and 2) it seems Taucs ignores these flags anyway and only accept lower symmetric matrices
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if (Flags & Upper)
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res.flags |= TAUCS_UPPER;
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if (Flags & Lower)
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@ -86,6 +87,7 @@ class SparseLLT<MatrixType,Taucs> : public SparseLLT<MatrixType>
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using Base::m_flags;
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using Base::m_matrix;
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using Base::m_status;
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using Base::m_succeeded;
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public:
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@ -126,10 +128,16 @@ void SparseLLT<MatrixType,Taucs>::compute(const MatrixType& a)
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m_taucsSupernodalFactor = 0;
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}
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taucs_ccs_matrix taucsMatA = const_cast<MatrixType&>(a).asTaucsMatrix();
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if (m_flags & IncompleteFactorization)
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{
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taucs_ccs_matrix taucsMatA = const_cast<MatrixType&>(a).asTaucsMatrix();
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taucs_ccs_matrix* taucsRes = taucs_ccs_factor_llt(&taucsMatA, Base::m_precision, 0);
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if(!taucsRes)
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{
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m_succeeded = false;
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return;
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}
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// the matrix returned by Taucs is not necessarily sorted,
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// so let's copy it in two steps
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DynamicSparseMatrix<Scalar,RowMajor> tmp = MappedSparseMatrix<Scalar>(*taucsRes);
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@ -141,7 +149,6 @@ void SparseLLT<MatrixType,Taucs>::compute(const MatrixType& a)
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}
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else
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{
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taucs_ccs_matrix taucsMatA = const_cast<MatrixType&>(a).asTaucsMatrix();
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if ( (m_flags & SupernodalLeftLooking)
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|| ((!(m_flags & SupernodalMultifrontal)) && (m_flags & MemoryEfficient)) )
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{
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@ -154,6 +161,7 @@ void SparseLLT<MatrixType,Taucs>::compute(const MatrixType& a)
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}
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m_status = (m_status & ~IncompleteFactorization) | CompleteFactorization | MatrixLIsDirty;
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}
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m_succeeded = true;
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}
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template<typename MatrixType>
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@ -131,16 +131,20 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
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#endif
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#ifdef EIGEN_TAUCS_SUPPORT
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x = b;
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SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
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// TODO fix TAUCS with complexes
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x = b;
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SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
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x = b;
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SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
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if (!NumTraits<Scalar>::IsComplex)
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{
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x = b;
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// SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
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// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
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x = b;
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SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
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x = b;
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SparseLLT<SparseMatrix<Scalar> ,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
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}
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#endif
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}
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@ -154,9 +158,9 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
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DenseVector b = DenseVector::Random(cols);
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DenseVector refX(cols), x(cols);
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//initSPD(density, refMat2, m2);
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// initSPD(density, refMat2, m2);
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initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
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refMat2 += refMat2.adjoint();
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refMat2 += (refMat2.adjoint()).eval();
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refMat2.diagonal() *= 0.5;
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refX = refMat2.llt().solve(b); // FIXME use LLT to compute the reference because LDLT seems to fail with large matrices
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@ -202,7 +206,7 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
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}
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if (slu.solve(b, &x, SvAdjoint)) {
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// VERIFY(b.isApprox(m2.adjoint() * x, test_precision<Scalar>()));
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VERIFY(b.isApprox(m2.adjoint() * x, test_precision<Scalar>()));
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}
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if (count==0) {
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@ -236,8 +240,8 @@ template<typename Scalar> void sparse_solvers(int rows, int cols)
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void test_sparse_solvers()
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{
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for(int i = 0; i < g_repeat; i++) {
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// CALL_SUBTEST(sparse_solvers<double>(8, 8) );
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CALL_SUBTEST(sparse_solvers<std::complex<double> >(16, 16) );
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// CALL_SUBTEST(sparse_solvers<double>(100, 100) );
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CALL_SUBTEST_1(sparse_solvers<double>(8, 8) );
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CALL_SUBTEST_2(sparse_solvers<std::complex<double> >(16, 16) );
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CALL_SUBTEST_1(sparse_solvers<double>(100, 100) );
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}
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}
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