| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2011-2015 Gael Guennebaud <gael.guennebaud@inria.fr> | |
| // | |
| // This Source Code Form is subject to the terms of the Mozilla | |
| // Public License v. 2.0. If a copy of the MPL was not distributed | |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
| static long int nb_transposed_copies; | |
| #define EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN \ | |
| { nb_transposed_copies++; } | |
| #define VERIFY_TRANSPOSITION_COUNT(XPR, N) \ | |
| { \ | |
| nb_transposed_copies = 0; \ | |
| XPR; \ | |
| if (nb_transposed_copies != N) std::cerr << "nb_transposed_copies == " << nb_transposed_copies << "\n"; \ | |
| VERIFY((#XPR) && nb_transposed_copies == N); \ | |
| } | |
| static long int nb_temporaries; | |
| #define EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN \ | |
| { nb_temporaries++; } | |
| #define VERIFY_TEMPORARY_COUNT(XPR, N) \ | |
| { \ | |
| nb_temporaries = 0; \ | |
| XPR; \ | |
| if (nb_temporaries != N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \ | |
| VERIFY((#XPR) && nb_temporaries == N); \ | |
| } | |
| #include "sparse.h" | |
| template <typename T> | |
| bool is_sorted(const T& mat) { | |
| for (Index k = 0; k < mat.outerSize(); ++k) { | |
| Index prev = -1; | |
| for (typename T::InnerIterator it(mat, k); it; ++it) { | |
| if (prev >= it.index()) return false; | |
| prev = it.index(); | |
| } | |
| } | |
| return true; | |
| } | |
| template <typename T> | |
| typename internal::nested_eval<T, 1>::type eval(const T& xpr) { | |
| VERIFY(int(internal::nested_eval<T, 1>::type::Flags & RowMajorBit) == | |
| int(internal::evaluator<T>::Flags & RowMajorBit)); | |
| return xpr; | |
| } | |
| template <int OtherStorage, typename SparseMatrixType> | |
| void sparse_permutations(const SparseMatrixType& ref) { | |
| const Index rows = ref.rows(); | |
| const Index cols = ref.cols(); | |
| typedef typename SparseMatrixType::Scalar Scalar; | |
| typedef typename SparseMatrixType::StorageIndex StorageIndex; | |
| typedef SparseMatrix<Scalar, OtherStorage, StorageIndex> OtherSparseMatrixType; | |
| typedef Matrix<Scalar, Dynamic, Dynamic> DenseMatrix; | |
| typedef Matrix<StorageIndex, Dynamic, 1> VectorI; | |
| // bool IsRowMajor1 = SparseMatrixType::IsRowMajor; | |
| // bool IsRowMajor2 = OtherSparseMatrixType::IsRowMajor; | |
| double density = (std::max)(8. / static_cast<double>(rows * cols), 0.01); | |
| SparseMatrixType mat(rows, cols), up(rows, cols), lo(rows, cols); | |
| OtherSparseMatrixType res; | |
| DenseMatrix mat_d = DenseMatrix::Zero(rows, cols), up_sym_d, lo_sym_d, res_d; | |
| initSparse<Scalar>(density, mat_d, mat, 0); | |
| up = mat.template triangularView<Upper>(); | |
| lo = mat.template triangularView<Lower>(); | |
| up_sym_d = mat_d.template selfadjointView<Upper>(); | |
| lo_sym_d = mat_d.template selfadjointView<Lower>(); | |
| VERIFY_IS_APPROX(mat, mat_d); | |
| VERIFY_IS_APPROX(up, DenseMatrix(mat_d.template triangularView<Upper>())); | |
| VERIFY_IS_APPROX(lo, DenseMatrix(mat_d.template triangularView<Lower>())); | |
| PermutationMatrix<Dynamic> p, p_null; | |
| VectorI pi; | |
| randomPermutationVector(pi, cols); | |
| p.indices() = pi; | |
| VERIFY(is_sorted(::eval(mat * p))); | |
| VERIFY(is_sorted(res = mat * p)); | |
| VERIFY_TRANSPOSITION_COUNT(::eval(mat * p), 0); | |
| VERIFY_TEMPORARY_COUNT(::eval(mat * p), 1) | |
| res_d = mat_d * p; | |
| VERIFY(res.isApprox(res_d) && "mat*p"); | |
| VERIFY(is_sorted(::eval(p * mat))); | |
| VERIFY(is_sorted(res = p * mat)); | |
| VERIFY_TRANSPOSITION_COUNT(::eval(p * mat), 0); | |
| VERIFY_TEMPORARY_COUNT(::eval(p * mat), 1); | |
| res_d = p * mat_d; | |
| VERIFY(res.isApprox(res_d) && "p*mat"); | |
| VERIFY(is_sorted((mat * p).eval())); | |
| VERIFY(is_sorted(res = mat * p.inverse())); | |
| VERIFY_TRANSPOSITION_COUNT(::eval(mat * p.inverse()), 0); | |
| VERIFY_TEMPORARY_COUNT(::eval(mat * p.inverse()), 1); | |
| res_d = mat * p.inverse(); | |
| VERIFY(res.isApprox(res_d) && "mat*inv(p)"); | |
| VERIFY(is_sorted((p * mat + p * mat).eval())); | |
| VERIFY(is_sorted(res = p.inverse() * mat)); | |
| VERIFY_TRANSPOSITION_COUNT(::eval(p.inverse() * mat), 0); | |
| VERIFY_TEMPORARY_COUNT(::eval(p.inverse() * mat), 1); | |
| res_d = p.inverse() * mat_d; | |
| VERIFY(res.isApprox(res_d) && "inv(p)*mat"); | |
| // | |
| VERIFY(is_sorted((p * mat * p.inverse()).eval())); | |
| VERIFY(is_sorted(res = mat.twistedBy(p))); | |
| VERIFY_TRANSPOSITION_COUNT(::eval(p * mat * p.inverse()), 0); | |
| res_d = (p * mat_d) * p.inverse(); | |
| VERIFY(res.isApprox(res_d) && "p*mat*inv(p)"); | |
| VERIFY(is_sorted(res = mat.template selfadjointView<Upper>().twistedBy(p_null))); | |
| res_d = up_sym_d; | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full"); | |
| VERIFY(is_sorted(res = mat.template selfadjointView<Lower>().twistedBy(p_null))); | |
| res_d = lo_sym_d; | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full"); | |
| VERIFY(is_sorted(res = up.template selfadjointView<Upper>().twistedBy(p_null))); | |
| res_d = up_sym_d; | |
| VERIFY(res.isApprox(res_d) && "upper selfadjoint to full"); | |
| VERIFY(is_sorted(res = lo.template selfadjointView<Lower>().twistedBy(p_null))); | |
| res_d = lo_sym_d; | |
| VERIFY(res.isApprox(res_d) && "lower selfadjoint full"); | |
| VERIFY(is_sorted(res = mat.template selfadjointView<Upper>())); | |
| res_d = up_sym_d; | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full"); | |
| VERIFY(is_sorted(res = mat.template selfadjointView<Lower>())); | |
| res_d = lo_sym_d; | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full"); | |
| VERIFY(is_sorted(res = up.template selfadjointView<Upper>())); | |
| res_d = up_sym_d; | |
| VERIFY(res.isApprox(res_d) && "upper selfadjoint to full"); | |
| VERIFY(is_sorted(res = lo.template selfadjointView<Lower>())); | |
| res_d = lo_sym_d; | |
| VERIFY(res.isApprox(res_d) && "lower selfadjoint full"); | |
| res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>(); | |
| res_d = up_sym_d.template triangularView<Upper>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint upper to upper"); | |
| res.template selfadjointView<Lower>() = mat.template selfadjointView<Upper>(); | |
| res_d = up_sym_d.template triangularView<Lower>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint upper to lower"); | |
| res.template selfadjointView<Upper>() = mat.template selfadjointView<Lower>(); | |
| res_d = lo_sym_d.template triangularView<Upper>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint lower to upper"); | |
| res.template selfadjointView<Lower>() = mat.template selfadjointView<Lower>(); | |
| res_d = lo_sym_d.template triangularView<Lower>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint lower to lower"); | |
| res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>().twistedBy(p); | |
| res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Upper>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to upper"); | |
| res.template selfadjointView<Upper>() = mat.template selfadjointView<Lower>().twistedBy(p); | |
| res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Upper>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to upper"); | |
| res.template selfadjointView<Lower>() = mat.template selfadjointView<Lower>().twistedBy(p); | |
| res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Lower>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to lower"); | |
| res.template selfadjointView<Lower>() = mat.template selfadjointView<Upper>().twistedBy(p); | |
| res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Lower>(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to lower"); | |
| res.template selfadjointView<Upper>() = up.template selfadjointView<Upper>().twistedBy(p); | |
| res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Upper>(); | |
| VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to upper"); | |
| res.template selfadjointView<Upper>() = lo.template selfadjointView<Lower>().twistedBy(p); | |
| res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Upper>(); | |
| VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to upper"); | |
| res.template selfadjointView<Lower>() = lo.template selfadjointView<Lower>().twistedBy(p); | |
| res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Lower>(); | |
| VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to lower"); | |
| res.template selfadjointView<Lower>() = up.template selfadjointView<Upper>().twistedBy(p); | |
| res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Lower>(); | |
| VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to lower"); | |
| VERIFY(is_sorted(res = mat.template selfadjointView<Upper>().twistedBy(p))); | |
| res_d = (p * up_sym_d) * p.inverse(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to full"); | |
| VERIFY(is_sorted(res = mat.template selfadjointView<Lower>().twistedBy(p))); | |
| res_d = (p * lo_sym_d) * p.inverse(); | |
| VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to full"); | |
| VERIFY(is_sorted(res = up.template selfadjointView<Upper>().twistedBy(p))); | |
| res_d = (p * up_sym_d) * p.inverse(); | |
| VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to full"); | |
| VERIFY(is_sorted(res = lo.template selfadjointView<Lower>().twistedBy(p))); | |
| res_d = (p * lo_sym_d) * p.inverse(); | |
| VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to full"); | |
| } | |
| template <typename Scalar> | |
| void sparse_permutations_all(int size) { | |
| CALL_SUBTEST((sparse_permutations<ColMajor>(SparseMatrix<Scalar, ColMajor>(size, size)))); | |
| CALL_SUBTEST((sparse_permutations<ColMajor>(SparseMatrix<Scalar, RowMajor>(size, size)))); | |
| CALL_SUBTEST((sparse_permutations<RowMajor>(SparseMatrix<Scalar, ColMajor>(size, size)))); | |
| CALL_SUBTEST((sparse_permutations<RowMajor>(SparseMatrix<Scalar, RowMajor>(size, size)))); | |
| } | |
| EIGEN_DECLARE_TEST(sparse_permutations) { | |
| for (int i = 0; i < g_repeat; i++) { | |
| int s = Eigen::internal::random<int>(1, 50); | |
| CALL_SUBTEST_1((sparse_permutations_all<double>(s))); | |
| CALL_SUBTEST_2((sparse_permutations_all<std::complex<double> >(s))); | |
| } | |
| VERIFY((internal::is_same< | |
| internal::permutation_matrix_product<SparseMatrix<double>, OnTheRight, false, SparseShape>::ReturnType, | |
| internal::nested_eval<Product<SparseMatrix<double>, PermutationMatrix<Dynamic, Dynamic>, AliasFreeProduct>, | |
| 1>::type>::value)); | |
| VERIFY((internal::is_same< | |
| internal::permutation_matrix_product<SparseMatrix<double>, OnTheLeft, false, SparseShape>::ReturnType, | |
| internal::nested_eval<Product<PermutationMatrix<Dynamic, Dynamic>, SparseMatrix<double>, AliasFreeProduct>, | |
| 1>::type>::value)); | |
| } |