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enable some tests that have been commented out
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@ -57,10 +57,27 @@ template<typename Scalar> void sparse_ldlt(int rows, int cols)
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else
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std::cerr << "warning LDLT failed\n";
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// VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
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VERIFY_IS_APPROX(refMat3.template selfadjointView<Upper>() * x, b);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
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#ifdef EIGEN_CHOLMOD_SUPPORT
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{
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x = b;
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SparseLDLT<SparseSelfAdjointMatrix, Cholmod> ldlt2(m3);
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if (ldlt2.succeeded())
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{
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ldlt2.solveInPlace(x);
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VERIFY_IS_APPROX(refMat3.template selfadjointView<Upper>() * x, b);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solveInPlace");
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x = ldlt2.solve(b);
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VERIFY_IS_APPROX(refMat3.template selfadjointView<Upper>() * x, b);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solve");
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}
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else
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std::cerr << "warning LDLT failed\n";
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}
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#endif
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// new Simplicial LLT
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@ -144,28 +161,7 @@ template<typename Scalar> void sparse_ldlt(int rows, int cols)
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// VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
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// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
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#ifdef EIGEN_CHOLMOD_SUPPORT
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// x = b;
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// SparseLDLT<SparseSelfAdjointMatrix, Cholmod> ldlt2(m2);
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// if (ldlt2.succeeded())
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// ldlt2.solveInPlace(x);
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// else
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// std::cerr << "warning LDLT failed\n";
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//
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// VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
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// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solveInPlace");
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//
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//
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// SparseLDLT<SparseSelfAdjointMatrix, Cholmod> ldlt3(m2);
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// if (ldlt3.succeeded())
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// x = ldlt3.solve(b);
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// else
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// std::cerr << "warning LDLT failed\n";
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//
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// VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
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// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solve");
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#endif
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}
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void test_sparse_ldlt()
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@ -44,7 +44,6 @@ template<typename Scalar> void sparse_lu(int rows, int cols)
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std::vector<Vector2i> zeroCoords;
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std::vector<Vector2i> nonzeroCoords;
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static int count = 0;
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SparseMatrix<Scalar> m2(rows, cols);
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DenseMatrix refMat2(rows, cols);
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@ -61,6 +60,21 @@ template<typename Scalar> void sparse_lu(int rows, int cols)
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x.setZero();
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// // SparseLU<SparseMatrix<Scalar> > (m2).solve(b,&x);
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// // VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: default");
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#ifdef EIGEN_UMFPACK_SUPPORT
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{
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// check solve
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x.setZero();
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SparseLU<SparseMatrix<Scalar>,UmfPack> lu(m2);
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VERIFY(lu.succeeded() && "umfpack LU decomposition failed");
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VERIFY(lu.solve(b,&x) && "umfpack LU solving failed");
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack");
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VERIFY_IS_APPROX(refDet,lu.determinant());
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// TODO check the extracted data
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//std::cerr << slu.matrixL() << "\n";
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}
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#endif
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#ifdef EIGEN_SUPERLU_SUPPORT
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{
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x.setZero();
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@ -85,24 +99,7 @@ template<typename Scalar> void sparse_lu(int rows, int cols)
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}
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}
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#endif
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#ifdef EIGEN_UMFPACK_SUPPORT
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// {
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// // check solve
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// x.setZero();
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// SparseLU<SparseMatrix<Scalar>,UmfPack> slu(m2);
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// if (slu.succeeded()) {
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// if (slu.solve(b,&x)) {
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// if (count==0) {
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// VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack"); // FIXME solve is not very stable for complex
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// }
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// }
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// VERIFY_IS_APPROX(refDet,slu.determinant());
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// // TODO check the extracted data
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// //std::cerr << slu.matrixL() << "\n";
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// }
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// }
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#endif
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count++;
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}
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void test_sparse_lu()
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