Getting matrixL and matrixU from Eigen::SuperLU?
I need to get matrices L and U from Eigen::SuperLU. The method matrixU() returns a UMatrixType. When I call this method, I get the following error
:cannot convert from
'Eigen::SparseMatrix<std::complex<double>,0,int>'to'const Eigen::TriangularView<Eigen::SparseMatrix<std::complex<double>,0,int>,2> &'.
If I replace UMatrixType by LUMAtrixType in SuperLUSupport.h, everything compiles but the following code does not give the expected result.
using SpMatc = Eigen::SparseMatrix<std::complex<double>>;
Eigen::MatrixXcd matDense = Eigen::MatrixXd::Identity(n, n);
matDense(13, 15) = std::complex<double>(5., 3.);
matDense(8, 11) = std::complex<double>(3., 9.);
SpMatc mat = matDense.sparseView();
Eigen::VectorXcd b = Eigen::VectorXcd::Random(n);
mat.makeCompressed();
Eigen::SuperLU<SpMatc> slu;
slu.compute(mat);
Eigen::VectorXcd y = slu.solve(b);
const auto& matL = slu.matrixL();
const auto& matU = slu.matrixU();
auto permutationMatrixP = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationP());
auto permutationMatrixQ = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationQ());
Eigen::VectorXcd res = permutationMatrixP*b;
matL.triangularView<Eigen::Lower | Eigen::UnitDiag>().solveInPlace(res);
matU.triangularView<Eigen::Upper>().solveInPlace(res);
Eigen::VectorXcd finalRes = permutationMatrixQ.inverse() * res;
Eigen::VectorXcd diff = finalRes - y;
Assert::IsTrue(!finalRes.isApprox(y));
If I replace Eigen::SuperLU by Eigen::SparseLU, the result is ok.
c++ eigen
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
asked Nov 28 '18 at 16:12
kajezzkajezz
11
add a comment |
I need to get matrices L and U from Eigen::SuperLU. The method matrixU() returns a UMatrixType. When I call this method, I get the following error
:cannot convert from
'Eigen::SparseMatrix<std::complex<double>,0,int>'to'const Eigen::TriangularView<Eigen::SparseMatrix<std::complex<double>,0,int>,2> &'.
If I replace UMatrixType by LUMAtrixType in SuperLUSupport.h, everything compiles but the following code does not give the expected result.
using SpMatc = Eigen::SparseMatrix<std::complex<double>>;
Eigen::MatrixXcd matDense = Eigen::MatrixXd::Identity(n, n);
matDense(13, 15) = std::complex<double>(5., 3.);
matDense(8, 11) = std::complex<double>(3., 9.);
SpMatc mat = matDense.sparseView();
Eigen::VectorXcd b = Eigen::VectorXcd::Random(n);
mat.makeCompressed();
Eigen::SuperLU<SpMatc> slu;
slu.compute(mat);
Eigen::VectorXcd y = slu.solve(b);
const auto& matL = slu.matrixL();
const auto& matU = slu.matrixU();
auto permutationMatrixP = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationP());
auto permutationMatrixQ = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationQ());
Eigen::VectorXcd res = permutationMatrixP*b;
matL.triangularView<Eigen::Lower | Eigen::UnitDiag>().solveInPlace(res);
matU.triangularView<Eigen::Upper>().solveInPlace(res);
Eigen::VectorXcd finalRes = permutationMatrixQ.inverse() * res;
Eigen::VectorXcd diff = finalRes - y;
Assert::IsTrue(!finalRes.isApprox(y));
If I replace Eigen::SuperLU by Eigen::SparseLU, the result is ok.
c++ eigen
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
asked Nov 28 '18 at 16:12
kajezzkajezz
11
This is expected. SuperLU uses dense matrices, SparseLU uses Sparse matrices, and you are using Sparse matrices. The two types you have are not compatible and cannot be converted from one to the other.
– Matthieu Brucher
Nov 28 '18 at 16:15
SparseLUis a built-in rewrite of the external SuperLU solver, so better forget about SuperLU and stick with SparseLU.
– ggael
Nov 28 '18 at 21:33
add a comment |
I need to get matrices L and U from Eigen::SuperLU. The method matrixU() returns a UMatrixType. When I call this method, I get the following error
:cannot convert from
'Eigen::SparseMatrix<std::complex<double>,0,int>'to'const Eigen::TriangularView<Eigen::SparseMatrix<std::complex<double>,0,int>,2> &'.
If I replace UMatrixType by LUMAtrixType in SuperLUSupport.h, everything compiles but the following code does not give the expected result.
using SpMatc = Eigen::SparseMatrix<std::complex<double>>;
Eigen::MatrixXcd matDense = Eigen::MatrixXd::Identity(n, n);
matDense(13, 15) = std::complex<double>(5., 3.);
matDense(8, 11) = std::complex<double>(3., 9.);
SpMatc mat = matDense.sparseView();
Eigen::VectorXcd b = Eigen::VectorXcd::Random(n);
mat.makeCompressed();
Eigen::SuperLU<SpMatc> slu;
slu.compute(mat);
Eigen::VectorXcd y = slu.solve(b);
const auto& matL = slu.matrixL();
const auto& matU = slu.matrixU();
auto permutationMatrixP = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationP());
auto permutationMatrixQ = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationQ());
Eigen::VectorXcd res = permutationMatrixP*b;
matL.triangularView<Eigen::Lower | Eigen::UnitDiag>().solveInPlace(res);
matU.triangularView<Eigen::Upper>().solveInPlace(res);
Eigen::VectorXcd finalRes = permutationMatrixQ.inverse() * res;
Eigen::VectorXcd diff = finalRes - y;
Assert::IsTrue(!finalRes.isApprox(y));
If I replace Eigen::SuperLU by Eigen::SparseLU, the result is ok.
c++ eigen
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
asked Nov 28 '18 at 16:12
kajezzkajezz
11
I need to get matrices L and U from Eigen::SuperLU. The method matrixU() returns a UMatrixType. When I call this method, I get the following error
:cannot convert from
'Eigen::SparseMatrix<std::complex<double>,0,int>'to'const Eigen::TriangularView<Eigen::SparseMatrix<std::complex<double>,0,int>,2> &'.
If I replace UMatrixType by LUMAtrixType in SuperLUSupport.h, everything compiles but the following code does not give the expected result.
using SpMatc = Eigen::SparseMatrix<std::complex<double>>;
Eigen::MatrixXcd matDense = Eigen::MatrixXd::Identity(n, n);
matDense(13, 15) = std::complex<double>(5., 3.);
matDense(8, 11) = std::complex<double>(3., 9.);
SpMatc mat = matDense.sparseView();
Eigen::VectorXcd b = Eigen::VectorXcd::Random(n);
mat.makeCompressed();
Eigen::SuperLU<SpMatc> slu;
slu.compute(mat);
Eigen::VectorXcd y = slu.solve(b);
const auto& matL = slu.matrixL();
const auto& matU = slu.matrixU();
auto permutationMatrixP = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationP());
auto permutationMatrixQ = Eigen::PermutationMatrix<Eigen::Dynamic>(slu.permutationQ());
Eigen::VectorXcd res = permutationMatrixP*b;
matL.triangularView<Eigen::Lower | Eigen::UnitDiag>().solveInPlace(res);
matU.triangularView<Eigen::Upper>().solveInPlace(res);
Eigen::VectorXcd finalRes = permutationMatrixQ.inverse() * res;
Eigen::VectorXcd diff = finalRes - y;
Assert::IsTrue(!finalRes.isApprox(y));
If I replace Eigen::SuperLU by Eigen::SparseLU, the result is ok.
c++ eigen
c++ eigen
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
asked Nov 28 '18 at 16:12
kajezzkajezz
11
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
asked Nov 28 '18 at 16:12
kajezzkajezz
11
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
edited Nov 28 '18 at 16:18
Öö Tiib
7,8442034
7,8442034
asked Nov 28 '18 at 16:12
kajezzkajezz
11
asked Nov 28 '18 at 16:12
kajezzkajezz
11
asked Nov 28 '18 at 16:12
kajezzkajezz
11
11
This is expected. SuperLU uses dense matrices, SparseLU uses Sparse matrices, and you are using Sparse matrices. The two types you have are not compatible and cannot be converted from one to the other.
– Matthieu Brucher
Nov 28 '18 at 16:15
SparseLUis a built-in rewrite of the external SuperLU solver, so better forget about SuperLU and stick with SparseLU.
– ggael
Nov 28 '18 at 21:33
add a comment |
This is expected. SuperLU uses dense matrices, SparseLU uses Sparse matrices, and you are using Sparse matrices. The two types you have are not compatible and cannot be converted from one to the other.
– Matthieu Brucher
Nov 28 '18 at 16:15
SparseLUis a built-in rewrite of the external SuperLU solver, so better forget about SuperLU and stick with SparseLU.
– ggael
Nov 28 '18 at 21:33
This is expected. SuperLU uses dense matrices, SparseLU uses Sparse matrices, and you are using Sparse matrices. The two types you have are not compatible and cannot be converted from one to the other.
– Matthieu Brucher
Nov 28 '18 at 16:15
This is expected. SuperLU uses dense matrices, SparseLU uses Sparse matrices, and you are using Sparse matrices. The two types you have are not compatible and cannot be converted from one to the other.
– Matthieu Brucher
Nov 28 '18 at 16:15
SparseLU is a built-in rewrite of the external SuperLU solver, so better forget about SuperLU and stick with SparseLU.– ggael
Nov 28 '18 at 21:33
SparseLU is a built-in rewrite of the external SuperLU solver, so better forget about SuperLU and stick with SparseLU.– ggael
Nov 28 '18 at 21:33
add a comment |
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This is expected. SuperLU uses dense matrices, SparseLU uses Sparse matrices, and you are using Sparse matrices. The two types you have are not compatible and cannot be converted from one to the other.
– Matthieu Brucher
Nov 28 '18 at 16:15
SparseLUis a built-in rewrite of the external SuperLU solver, so better forget about SuperLU and stick with SparseLU.– ggael
Nov 28 '18 at 21:33