| 42 | } |
| 43 | |
| 44 | template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(const SparseMatrixType& ref) |
| 45 | { |
| 46 | const Index rows = ref.rows(); |
| 47 | const Index cols = ref.cols(); |
| 48 | typedef typename SparseMatrixType::Scalar Scalar; |
| 49 | typedef typename SparseMatrixType::StorageIndex StorageIndex; |
| 50 | typedef SparseMatrix<Scalar, OtherStorage, StorageIndex> OtherSparseMatrixType; |
| 51 | typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; |
| 52 | typedef Matrix<StorageIndex,Dynamic,1> VectorI; |
| 53 | // bool IsRowMajor1 = SparseMatrixType::IsRowMajor; |
| 54 | // bool IsRowMajor2 = OtherSparseMatrixType::IsRowMajor; |
| 55 | |
| 56 | double density = (std::max)(8./(rows*cols), 0.01); |
| 57 | |
| 58 | SparseMatrixType mat(rows, cols), up(rows,cols), lo(rows,cols); |
| 59 | OtherSparseMatrixType res; |
| 60 | DenseMatrix mat_d = DenseMatrix::Zero(rows, cols), up_sym_d, lo_sym_d, res_d; |
| 61 | |
| 62 | initSparse<Scalar>(density, mat_d, mat, 0); |
| 63 | |
| 64 | up = mat.template triangularView<Upper>(); |
| 65 | lo = mat.template triangularView<Lower>(); |
| 66 | |
| 67 | up_sym_d = mat_d.template selfadjointView<Upper>(); |
| 68 | lo_sym_d = mat_d.template selfadjointView<Lower>(); |
| 69 | |
| 70 | VERIFY_IS_APPROX(mat, mat_d); |
| 71 | VERIFY_IS_APPROX(up, DenseMatrix(mat_d.template triangularView<Upper>())); |
| 72 | VERIFY_IS_APPROX(lo, DenseMatrix(mat_d.template triangularView<Lower>())); |
| 73 | |
| 74 | PermutationMatrix<Dynamic> p, p_null; |
| 75 | VectorI pi; |
| 76 | randomPermutationVector(pi, cols); |
| 77 | p.indices() = pi; |
| 78 | |
| 79 | VERIFY( is_sorted( ::eval(mat*p) )); |
| 80 | VERIFY( is_sorted( res = mat*p )); |
| 81 | VERIFY_TRANSPOSITION_COUNT( ::eval(mat*p), 0); |
| 82 | //VERIFY_TRANSPOSITION_COUNT( res = mat*p, IsRowMajor ? 1 : 0 ); |
| 83 | res_d = mat_d*p; |
| 84 | VERIFY(res.isApprox(res_d) && "mat*p"); |
| 85 | |
| 86 | VERIFY( is_sorted( ::eval(p*mat) )); |
| 87 | VERIFY( is_sorted( res = p*mat )); |
| 88 | VERIFY_TRANSPOSITION_COUNT( ::eval(p*mat), 0); |
| 89 | res_d = p*mat_d; |
| 90 | VERIFY(res.isApprox(res_d) && "p*mat"); |
| 91 | |
| 92 | VERIFY( is_sorted( (mat*p).eval() )); |
| 93 | VERIFY( is_sorted( res = mat*p.inverse() )); |
| 94 | VERIFY_TRANSPOSITION_COUNT( ::eval(mat*p.inverse()), 0); |
| 95 | res_d = mat*p.inverse(); |
| 96 | VERIFY(res.isApprox(res_d) && "mat*inv(p)"); |
| 97 | |
| 98 | VERIFY( is_sorted( (p*mat+p*mat).eval() )); |
| 99 | VERIFY( is_sorted( res = p.inverse()*mat )); |
| 100 | VERIFY_TRANSPOSITION_COUNT( ::eval(p.inverse()*mat), 0); |
| 101 | res_d = p.inverse()*mat_d; |