// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2009 Benoit Jacob // // 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/. // SPDX-License-Identifier: MPL-2.0 // discard stack allocation as that too bypasses malloc #define EIGEN_STACK_ALLOCATION_LIMIT 0 // heap allocation will raise an assert if enabled at runtime #define EIGEN_RUNTIME_NO_MALLOC #include "main.h" using namespace std; template void diagonalmatrices(const MatrixType& m) { typedef typename MatrixType::Scalar Scalar; enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime }; typedef Matrix VectorType; typedef Matrix RowVectorType; typedef Matrix SquareMatrixType; typedef Matrix DynMatrixType; typedef DiagonalMatrix LeftDiagonalMatrix; typedef DiagonalMatrix RightDiagonalMatrix; typedef Matrix BigMatrix; Index rows = m.rows(); Index cols = m.cols(); MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols); VectorType v1 = VectorType::Random(rows), v2 = VectorType::Random(rows); RowVectorType rv1 = RowVectorType::Random(cols), rv2 = RowVectorType::Random(cols); LeftDiagonalMatrix ldm1(v1), ldm2(v2); RightDiagonalMatrix rdm1(rv1), rdm2(rv2); Scalar s1 = internal::random(); SquareMatrixType sq_m1(v1.asDiagonal()); VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix()); sq_m1 = v1.asDiagonal(); VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix()); SquareMatrixType sq_m2 = v1.asDiagonal(); VERIFY_IS_APPROX(sq_m1, sq_m2); ldm1 = v1.asDiagonal(); LeftDiagonalMatrix ldm3(v1); VERIFY_IS_APPROX(ldm1.diagonal(), ldm3.diagonal()); LeftDiagonalMatrix ldm4 = v1.asDiagonal(); VERIFY_IS_APPROX(ldm1.diagonal(), ldm4.diagonal()); sq_m1.block(0, 0, rows, rows) = ldm1; VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix()); sq_m1.transpose() = ldm1; VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix()); Index i = internal::random(0, rows - 1); Index j = internal::random(0, cols - 1); internal::set_is_malloc_allowed(false); VERIFY_IS_APPROX(((ldm1 * m1)(i, j)), ldm1.diagonal()(i) * m1(i, j)); VERIFY_IS_APPROX(((ldm1 * (m1 + m2))(i, j)), ldm1.diagonal()(i) * (m1 + m2)(i, j)); VERIFY_IS_APPROX(((m1 * rdm1)(i, j)), rdm1.diagonal()(j) * m1(i, j)); VERIFY_IS_APPROX(((v1.asDiagonal() * m1)(i, j)), v1(i) * m1(i, j)); VERIFY_IS_APPROX(((m1 * rv1.asDiagonal())(i, j)), rv1(j) * m1(i, j)); VERIFY_IS_APPROX((((v1 + v2).asDiagonal() * m1)(i, j)), (v1 + v2)(i)*m1(i, j)); VERIFY_IS_APPROX((((v1 + v2).asDiagonal() * (m1 + m2))(i, j)), (v1 + v2)(i) * (m1 + m2)(i, j)); VERIFY_IS_APPROX(((m1 * (rv1 + rv2).asDiagonal())(i, j)), (rv1 + rv2)(j)*m1(i, j)); VERIFY_IS_APPROX((((m1 + m2) * (rv1 + rv2).asDiagonal())(i, j)), (rv1 + rv2)(j) * (m1 + m2)(i, j)); VERIFY_IS_APPROX((ldm1 * ldm1).diagonal()(i), ldm1.diagonal()(i) * ldm1.diagonal()(i)); VERIFY_IS_APPROX((ldm1 * ldm1 * m1)(i, j), ldm1.diagonal()(i) * ldm1.diagonal()(i) * m1(i, j)); VERIFY_IS_APPROX(((v1.asDiagonal() * v1.asDiagonal()).diagonal()(i)), v1(i) * v1(i)); internal::set_is_malloc_allowed(true); if (rows > 1) { DynMatrixType tmp = m1.topRows(rows / 2), res; VERIFY_IS_APPROX((res = m1.topRows(rows / 2) * rv1.asDiagonal()), tmp * rv1.asDiagonal()); VERIFY_IS_APPROX((res = v1.head(rows / 2).asDiagonal() * m1.topRows(rows / 2)), v1.head(rows / 2).asDiagonal() * tmp); } BigMatrix big; big.setZero(2 * rows, 2 * cols); big.block(i, j, rows, cols) = m1; big.block(i, j, rows, cols) = v1.asDiagonal() * big.block(i, j, rows, cols); VERIFY_IS_APPROX((big.block(i, j, rows, cols)), v1.asDiagonal() * m1); big.block(i, j, rows, cols) = m1; big.block(i, j, rows, cols) = big.block(i, j, rows, cols) * rv1.asDiagonal(); VERIFY_IS_APPROX((big.block(i, j, rows, cols)), m1 * rv1.asDiagonal()); // products do not allocate memory MatrixType res(rows, cols); internal::set_is_malloc_allowed(false); res.noalias() = ldm1 * m1; res.noalias() = m1 * rdm1; res.noalias() = ldm1 * m1 * rdm1; res.noalias() = LeftDiagonalMatrix::Identity(rows) * m1 * RightDiagonalMatrix::Zero(cols); internal::set_is_malloc_allowed(true); // scalar multiple VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1 * s1).diagonal(), ldm1.diagonal() * s1); VERIFY_IS_APPROX(LeftDiagonalMatrix(s1 * ldm1).diagonal(), s1 * ldm1.diagonal()); VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1); VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1); // Diagonal to dense sq_m1.setRandom(); sq_m2 = sq_m1; VERIFY_IS_APPROX((sq_m1 += (s1 * v1).asDiagonal()), sq_m2 += (s1 * v1).asDiagonal().toDenseMatrix()); VERIFY_IS_APPROX((sq_m1 -= (s1 * v1).asDiagonal()), sq_m2 -= (s1 * v1).asDiagonal().toDenseMatrix()); VERIFY_IS_APPROX((sq_m1 = (s1 * v1).asDiagonal()), (s1 * v1).asDiagonal().toDenseMatrix()); sq_m1.setRandom(); sq_m2 = v1.asDiagonal(); sq_m2 = sq_m1 * sq_m2; VERIFY_IS_APPROX((sq_m1 * v1.asDiagonal()).col(i), sq_m2.col(i)); VERIFY_IS_APPROX((sq_m1 * v1.asDiagonal()).row(i), sq_m2.row(i)); sq_m1 = v1.asDiagonal(); sq_m2 = v2.asDiagonal(); SquareMatrixType sq_m3 = v1.asDiagonal(); VERIFY_IS_APPROX(sq_m3 = v1.asDiagonal() + v2.asDiagonal(), sq_m1 + sq_m2); VERIFY_IS_APPROX(sq_m3 = v1.asDiagonal() - v2.asDiagonal(), sq_m1 - sq_m2); VERIFY_IS_APPROX(sq_m3 = v1.asDiagonal() - 2 * v2.asDiagonal() + v1.asDiagonal(), sq_m1 - 2 * sq_m2 + sq_m1); // Zero and Identity LeftDiagonalMatrix zero = LeftDiagonalMatrix::Zero(rows); LeftDiagonalMatrix identity = LeftDiagonalMatrix::Identity(rows); VERIFY_IS_APPROX(identity.diagonal().sum(), Scalar(rows)); VERIFY_IS_APPROX(zero.diagonal().sum(), Scalar(0)); VERIFY_IS_APPROX((zero + 2 * LeftDiagonalMatrix::Identity(rows)).diagonal().sum(), Scalar(2 * rows)); } template void as_scalar_product(const MatrixType& m) { typedef typename MatrixType::Scalar Scalar; typedef Matrix VectorType; typedef Matrix DynMatrixType; typedef Matrix DynVectorType; typedef Matrix DynRowVectorType; Index rows = m.rows(); Index depth = internal::random(1, EIGEN_TEST_MAX_SIZE); VectorType v1 = VectorType::Random(rows); DynVectorType dv1 = DynVectorType::Random(depth); DynRowVectorType drv1 = DynRowVectorType::Random(depth); DynMatrixType dm1 = dv1; DynMatrixType drm1 = drv1; Scalar s = v1(0); VERIFY_IS_APPROX(v1.asDiagonal() * drv1, s * drv1); VERIFY_IS_APPROX(dv1 * v1.asDiagonal(), dv1 * s); VERIFY_IS_APPROX(v1.asDiagonal() * drm1, s * drm1); VERIFY_IS_APPROX(dm1 * v1.asDiagonal(), dm1 * s); } template void bug987() { Matrix3Xd points = Matrix3Xd::Random(3, 3); Vector2d diag = Vector2d::Random(); Matrix2Xd tmp1 = points.topRows<2>(), res1, res2; VERIFY_IS_APPROX(res1 = diag.asDiagonal() * points.topRows<2>(), res2 = diag.asDiagonal() * tmp1); Matrix2d tmp2 = points.topLeftCorner<2, 2>(); VERIFY_IS_APPROX((res1 = points.topLeftCorner<2, 2>() * diag.asDiagonal()), res2 = tmp2 * diag.asDiagonal()); } template void bug2013() { Matrix3d m = Matrix3d::Random(); Vector3d d = Vector3d::Random(); Matrix3d ref_unit_lower = m.template triangularView(); Matrix3d ref_unit_upper = m.template triangularView(); Matrix3d ref_lower = m.template triangularView(); Matrix3d ref_upper = m.template triangularView(); VERIFY_IS_APPROX((m.template triangularView() * d.asDiagonal()).eval(), ref_unit_lower * d.asDiagonal()); VERIFY_IS_APPROX((d.asDiagonal() * m.template triangularView()).eval(), d.asDiagonal() * ref_unit_lower); VERIFY_IS_APPROX((m.template triangularView() * d.asDiagonal()).eval(), ref_unit_upper * d.asDiagonal()); VERIFY_IS_APPROX((d.asDiagonal() * m.template triangularView()).eval(), d.asDiagonal() * ref_unit_upper); Matrix3d actual = Matrix3d::Random(); Matrix3d expected = actual; actual = m; expected = m; actual.template triangularView() = actual.template triangularView() * d.asDiagonal(); expected.template triangularView() = Matrix3d(ref_upper * d.asDiagonal()); VERIFY_IS_APPROX(actual, expected); actual = m; expected = m; actual.template triangularView() = d.asDiagonal() * actual.template triangularView(); expected.template triangularView() = Matrix3d(d.asDiagonal() * ref_lower); VERIFY_IS_APPROX(actual, expected); actual.setRandom(); expected = actual; actual.noalias() += m.template triangularView() * d.asDiagonal(); expected.noalias() += ref_unit_lower * d.asDiagonal(); VERIFY_IS_APPROX(actual, expected); actual.setRandom(); expected = actual; actual.noalias() -= d.asDiagonal() * m.template triangularView(); expected.noalias() -= d.asDiagonal() * ref_unit_upper; VERIFY_IS_APPROX(actual, expected); MatrixXd dynamic_m = MatrixXd::Random(4, 4); VectorXd dynamic_d = VectorXd::Random(4); MatrixXd dynamic_expected(4, 4); MatrixXd no_malloc_result(4, 4); dynamic_expected = MatrixXd(dynamic_m.template triangularView()) * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(false); no_malloc_result.noalias() = dynamic_m.template triangularView() * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); dynamic_expected = dynamic_d.asDiagonal() * MatrixXd(dynamic_m.template triangularView()); internal::set_is_malloc_allowed(false); no_malloc_result.noalias() = dynamic_d.asDiagonal() * dynamic_m.template triangularView(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); // Triangular destination assignment from a structured*diagonal product must go through the // lazy product_evaluator and avoid materializing a full PlainObject temporary. no_malloc_result = dynamic_m; dynamic_expected = dynamic_m; dynamic_expected.template triangularView() = MatrixXd(dynamic_m.template triangularView()) * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(false); no_malloc_result.template triangularView() = dynamic_m.template triangularView() * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); no_malloc_result = dynamic_m; dynamic_expected = dynamic_m; dynamic_expected.template triangularView() = dynamic_d.asDiagonal() * MatrixXd(dynamic_m.template triangularView()); internal::set_is_malloc_allowed(false); no_malloc_result.template triangularView() = dynamic_d.asDiagonal() * dynamic_m.template triangularView(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); } template void selfadjoint_diagonal_products() { Matrix3cd m = Matrix3cd::Random(); m.diagonal() = m.diagonal().real(); Vector3cd d = Vector3cd::Random(); Matrix3cd ref_lower = m.template selfadjointView(); Matrix3cd ref_upper = m.template selfadjointView(); VERIFY_IS_APPROX((m.template selfadjointView() * d.asDiagonal()).eval(), ref_lower * d.asDiagonal()); VERIFY_IS_APPROX((d.asDiagonal() * m.template selfadjointView()).eval(), d.asDiagonal() * ref_lower); VERIFY_IS_APPROX((m.template selfadjointView() * d.asDiagonal()).eval(), ref_upper * d.asDiagonal()); VERIFY_IS_APPROX((d.asDiagonal() * m.template selfadjointView()).eval(), d.asDiagonal() * ref_upper); Matrix3cd actual = Matrix3cd::Random(); Matrix3cd expected = actual; actual = m; expected = m; actual.template selfadjointView() = actual.template selfadjointView() * d.asDiagonal(); expected.template triangularView() = Matrix3cd(ref_upper * d.asDiagonal()); VERIFY_IS_APPROX(actual, expected); actual = m; expected = m; actual.template selfadjointView() = d.asDiagonal() * actual.template selfadjointView(); expected.template triangularView() = Matrix3cd(d.asDiagonal() * ref_lower); VERIFY_IS_APPROX(actual, expected); actual.setRandom(); expected = actual; actual.noalias() += m.template selfadjointView() * d.asDiagonal(); expected.noalias() += ref_lower * d.asDiagonal(); VERIFY_IS_APPROX(actual, expected); actual.setRandom(); expected = actual; actual.noalias() -= d.asDiagonal() * m.template selfadjointView(); expected.noalias() -= d.asDiagonal() * ref_upper; VERIFY_IS_APPROX(actual, expected); MatrixXcd dynamic_m = MatrixXcd::Random(4, 4); dynamic_m.diagonal() = dynamic_m.diagonal().real(); VectorXcd dynamic_d = VectorXcd::Random(4); MatrixXcd dynamic_expected(4, 4); MatrixXcd no_malloc_result(4, 4); dynamic_expected = MatrixXcd(dynamic_m.template selfadjointView()) * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(false); no_malloc_result.noalias() = dynamic_m.template selfadjointView() * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); dynamic_expected = dynamic_d.asDiagonal() * MatrixXcd(dynamic_m.template selfadjointView()); internal::set_is_malloc_allowed(false); no_malloc_result.noalias() = dynamic_d.asDiagonal() * dynamic_m.template selfadjointView(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); // Triangular destination assignment from selfadjoint*diagonal must use the lazy // product_evaluator (with conjugate-mirror coeffs) and not materialize a temporary. no_malloc_result = dynamic_m; dynamic_expected = dynamic_m; dynamic_expected.template triangularView() = MatrixXcd(dynamic_m.template selfadjointView()) * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(false); no_malloc_result.template triangularView() = dynamic_m.template selfadjointView() * dynamic_d.asDiagonal(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); no_malloc_result = dynamic_m; dynamic_expected = dynamic_m; dynamic_expected.template triangularView() = dynamic_d.asDiagonal() * MatrixXcd(dynamic_m.template selfadjointView()); internal::set_is_malloc_allowed(false); no_malloc_result.template triangularView() = dynamic_d.asDiagonal() * dynamic_m.template selfadjointView(); internal::set_is_malloc_allowed(true); VERIFY_IS_APPROX(no_malloc_result, dynamic_expected); } // Exercise the block-tile path of the dense selfadjoint x diagonal kernel // (BlockSize = 32 in ProductEvaluators.h). Picks a few sizes that hit // full blocks (size = 64), partial blocks (size = 33, 65), and a tiny size // that bypasses the block loop entirely (size = 8). Also verifies the // overwrite path leaves no stale data when dst is pre-filled. template void selfadjoint_diagonal_products_at(Index n) { typedef Matrix MatType; typedef Matrix VecType; MatType m = MatType::Random(n, n); m.diagonal() = m.diagonal().real().template cast(); // Hermitian diagonal VecType d = VecType::Random(n); MatType ref_lower = m.template selfadjointView(); MatType ref_upper = m.template selfadjointView(); // Plain assignment goes through evalTo (overwrite kernel). // Pre-fill dst with garbage to verify no stale entries remain. MatType dst = MatType::Constant(n, n, Scalar(42)); dst.noalias() = m.template selfadjointView() * d.asDiagonal(); VERIFY_IS_APPROX(dst, ref_upper * d.asDiagonal()); dst = MatType::Constant(n, n, Scalar(-7)); dst.noalias() = m.template selfadjointView() * d.asDiagonal(); VERIFY_IS_APPROX(dst, ref_lower * d.asDiagonal()); dst = MatType::Constant(n, n, Scalar(13)); dst.noalias() = d.asDiagonal() * m.template selfadjointView(); VERIFY_IS_APPROX(dst, d.asDiagonal() * ref_upper); dst = MatType::Constant(n, n, Scalar(99)); dst.noalias() = d.asDiagonal() * m.template selfadjointView(); VERIFY_IS_APPROX(dst, d.asDiagonal() * ref_lower); // Accumulating paths (scaleAndAddTo). MatType base = MatType::Random(n, n); dst = base; dst.noalias() += m.template selfadjointView() * d.asDiagonal(); VERIFY_IS_APPROX(dst, base + ref_upper * d.asDiagonal()); dst = base; dst.noalias() -= d.asDiagonal() * m.template selfadjointView(); VERIFY_IS_APPROX(dst, base - d.asDiagonal() * ref_lower); // Scalar-scaled products: the "Dense ?= scalar * Product" rewriting rule // folds alpha into the SelfAdjointView. For a complex alpha that fold is // not Hermitian, so the dispatch must restore alpha rather than apply it // straight to the kernel — verify all four orientation x triangle combos. Scalar alpha = internal::random(); dst = base; dst.noalias() += alpha * (m.template selfadjointView() * d.asDiagonal()); VERIFY_IS_APPROX(dst, base + alpha * (ref_lower * d.asDiagonal())); dst = base; dst.noalias() -= alpha * (m.template selfadjointView() * d.asDiagonal()); VERIFY_IS_APPROX(dst, base - alpha * (ref_upper * d.asDiagonal())); dst = base; dst.noalias() += alpha * (d.asDiagonal() * m.template selfadjointView()); VERIFY_IS_APPROX(dst, base + alpha * (d.asDiagonal() * ref_upper)); dst = base; dst.noalias() -= alpha * (d.asDiagonal() * m.template selfadjointView()); VERIFY_IS_APPROX(dst, base - alpha * (d.asDiagonal() * ref_lower)); // Overwrite-with-scalar path: hits evalTo's HasScalarFactor branch. dst = MatType::Constant(n, n, Scalar(17)); dst.noalias() = alpha * (m.template selfadjointView() * d.asDiagonal()); VERIFY_IS_APPROX(dst, alpha * (ref_lower * d.asDiagonal())); dst = MatType::Constant(n, n, Scalar(-3)); dst.noalias() = alpha * (d.asDiagonal() * m.template selfadjointView()); VERIFY_IS_APPROX(dst, alpha * (d.asDiagonal() * ref_upper)); // Conjugated nested expressions go through the same blas_traits extraction // path. The extracted matrix must keep NeedToConjugate, otherwise the kernel // computes with m instead of m.conjugate(). MatType conj_ref_lower = m.conjugate().template selfadjointView(); MatType conj_ref_upper = m.conjugate().template selfadjointView(); dst = MatType::Constant(n, n, Scalar(23)); dst.noalias() = m.conjugate().template selfadjointView() * d.asDiagonal(); VERIFY_IS_APPROX(dst, conj_ref_upper * d.asDiagonal()); dst = MatType::Constant(n, n, Scalar(-29)); dst.noalias() = d.asDiagonal() * m.conjugate().template selfadjointView(); VERIFY_IS_APPROX(dst, d.asDiagonal() * conj_ref_lower); dst = base; dst.noalias() += alpha * (m.conjugate().template selfadjointView() * d.asDiagonal()); VERIFY_IS_APPROX(dst, base + alpha * (conj_ref_lower * d.asDiagonal())); dst = base; dst.noalias() -= alpha * (d.asDiagonal() * m.conjugate().template selfadjointView()); VERIFY_IS_APPROX(dst, base - alpha * (d.asDiagonal() * conj_ref_upper)); } template void selfadjoint_diagonal_products_block_path() { selfadjoint_diagonal_products_at(8); selfadjoint_diagonal_products_at(33); // partial off-diagonal block selfadjoint_diagonal_products_at(64); // exact multiple of BlockSize selfadjoint_diagonal_products_at(65); // off-by-one selfadjoint_diagonal_products_at>(33); selfadjoint_diagonal_products_at>(65); } // In-place patterns where the diagonal operand shares storage with the destination view. // The fast path in triangular_product_assignment_dispatcher detects the run-time overlap // and materializes a temporary, so the result must match a reference computed against a // materialized source. The structured (triangular/selfadjoint) operand can safely share // storage with dst because the kernel reads each cell before writing it. template void verify_triangular_in_place_with_aliased_diagonal(const Mat& m) { // diagonal * tri_view { Mat actual = m, expected = m; Mat ref_diag = actual.diagonal().asDiagonal(); Mat ref_tri = actual.template triangularView(); expected.template triangularView() = (ref_diag * ref_tri).eval(); actual.template triangularView() = actual.diagonal().asDiagonal() * actual.template triangularView(); VERIFY_IS_APPROX(actual, expected); } // tri_view * diagonal { Mat actual = m, expected = m; Mat ref_diag = actual.diagonal().asDiagonal(); Mat ref_tri = actual.template triangularView(); expected.template triangularView() = (ref_tri * ref_diag).eval(); actual.template triangularView() = actual.template triangularView() * actual.diagonal().asDiagonal(); VERIFY_IS_APPROX(actual, expected); } } template void verify_selfadjoint_in_place_with_aliased_diagonal(const Mat& m) { // diagonal * sa_view { Mat actual = m, expected = m; Mat ref_diag = actual.diagonal().asDiagonal(); Mat ref_sa = actual.template selfadjointView(); expected.template triangularView() = (ref_diag * ref_sa).eval(); actual.template selfadjointView() = actual.diagonal().asDiagonal() * actual.template selfadjointView(); VERIFY_IS_APPROX(actual.template triangularView().toDenseMatrix(), expected.template triangularView().toDenseMatrix()); } // sa_view * diagonal { Mat actual = m, expected = m; Mat ref_diag = actual.diagonal().asDiagonal(); Mat ref_sa = actual.template selfadjointView(); expected.template triangularView() = (ref_sa * ref_diag).eval(); actual.template selfadjointView() = actual.template selfadjointView() * actual.diagonal().asDiagonal(); VERIFY_IS_APPROX(actual.template triangularView().toDenseMatrix(), expected.template triangularView().toDenseMatrix()); } } template void structured_diagonal_aliasing() { for (int n : {3, 5, 8, 17, 32, 33, 64, 65}) { MatrixXcd m = MatrixXcd::Random(n, n); m.diagonal() = m.diagonal().real(); // Hermitian-friendly diagonal verify_triangular_in_place_with_aliased_diagonal(m); verify_triangular_in_place_with_aliased_diagonal(m); verify_selfadjoint_in_place_with_aliased_diagonal(m); verify_selfadjoint_in_place_with_aliased_diagonal(m); } } EIGEN_DECLARE_TEST(diagonalmatrices) { for (int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1(diagonalmatrices(Matrix())); CALL_SUBTEST_1(as_scalar_product(Matrix())); CALL_SUBTEST_2(diagonalmatrices(Matrix3f())); CALL_SUBTEST_3(diagonalmatrices(Matrix())); CALL_SUBTEST_4(diagonalmatrices(Matrix4d())); CALL_SUBTEST_5(diagonalmatrices(Matrix())); CALL_SUBTEST_6(diagonalmatrices( MatrixXcf(internal::random(1, EIGEN_TEST_MAX_SIZE), internal::random(1, EIGEN_TEST_MAX_SIZE)))); CALL_SUBTEST_6(as_scalar_product(MatrixXcf(1, 1))); CALL_SUBTEST_7(diagonalmatrices( MatrixXi(internal::random(1, EIGEN_TEST_MAX_SIZE), internal::random(1, EIGEN_TEST_MAX_SIZE)))); CALL_SUBTEST_8(diagonalmatrices(Matrix( internal::random(1, EIGEN_TEST_MAX_SIZE), internal::random(1, EIGEN_TEST_MAX_SIZE)))); CALL_SUBTEST_9(diagonalmatrices( MatrixXf(internal::random(1, EIGEN_TEST_MAX_SIZE), internal::random(1, EIGEN_TEST_MAX_SIZE)))); CALL_SUBTEST_9(diagonalmatrices(MatrixXf(1, 1))); CALL_SUBTEST_9(as_scalar_product(MatrixXf(1, 1))); } CALL_SUBTEST_10(bug987<0>()); CALL_SUBTEST_10(bug2013<0>()); CALL_SUBTEST_10(selfadjoint_diagonal_products<0>()); CALL_SUBTEST_10(selfadjoint_diagonal_products_block_path<0>()); CALL_SUBTEST_10(structured_diagonal_aliasing<0>()); }