// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2024 Tobias Wood tobias@spinicist.org.uk // // 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/. #include "main.h" #include using Eigen::array; using Eigen::Tensor; template static void test_simple_roll() { Tensor tensor(2, 3, 5, 7); tensor.setRandom(); array dim_roll; dim_roll[0] = 0; dim_roll[1] = 1; dim_roll[2] = 4; dim_roll[3] = 8; Tensor rolled_tensor; rolled_tensor = tensor.roll(dim_roll); VERIFY_IS_EQUAL(rolled_tensor.dimension(0), 2); VERIFY_IS_EQUAL(rolled_tensor.dimension(1), 3); VERIFY_IS_EQUAL(rolled_tensor.dimension(2), 5); VERIFY_IS_EQUAL(rolled_tensor.dimension(3), 7); for (int i = 0; i < 2; ++i) { for (int j = 0; j < 3; ++j) { for (int k = 0; k < 5; ++k) { for (int l = 0; l < 7; ++l) { VERIFY_IS_EQUAL(tensor(i, (j + 1) % 3, (k + 4) % 5, (l + 8) % 7), rolled_tensor(i, j, k, l)); } } } } dim_roll[0] = -3; dim_roll[1] = -2; dim_roll[2] = -1; dim_roll[3] = 0; rolled_tensor = tensor.roll(dim_roll); VERIFY_IS_EQUAL(rolled_tensor.dimension(0), 2); VERIFY_IS_EQUAL(rolled_tensor.dimension(1), 3); VERIFY_IS_EQUAL(rolled_tensor.dimension(2), 5); VERIFY_IS_EQUAL(rolled_tensor.dimension(3), 7); for (int i = 0; i < 2; ++i) { for (int j = 0; j < 3; ++j) { for (int k = 0; k < 5; ++k) { for (int l = 0; l < 7; ++l) { VERIFY_IS_EQUAL(tensor((i + 1) % 2, (j + 1) % 3, (k + 4) % 5, l), rolled_tensor(i, j, k, l)); } } } } } template static void test_expr_roll(bool LValue) { Tensor tensor(2, 3, 5, 7); tensor.setRandom(); array dim_roll; dim_roll[0] = 2; dim_roll[1] = 1; dim_roll[2] = 0; dim_roll[3] = 3; Tensor expected(tensor.dimensions()); if (LValue) { expected.roll(dim_roll) = tensor; } else { expected = tensor.roll(dim_roll); } Tensor result(tensor.dimensions()); array src_slice_dim; src_slice_dim[0] = tensor.dimension(0); src_slice_dim[1] = tensor.dimension(1); src_slice_dim[2] = 1; src_slice_dim[3] = tensor.dimension(3); array src_slice_start; src_slice_start[0] = 0; src_slice_start[1] = 0; src_slice_start[2] = 0; src_slice_start[3] = 0; array dst_slice_dim = src_slice_dim; array dst_slice_start = src_slice_start; for (int i = 0; i < tensor.dimension(2); ++i) { if (LValue) { result.slice(dst_slice_start, dst_slice_dim).roll(dim_roll) = tensor.slice(src_slice_start, src_slice_dim); } else { result.slice(dst_slice_start, dst_slice_dim) = tensor.slice(src_slice_start, src_slice_dim).roll(dim_roll); } src_slice_start[2] += 1; dst_slice_start[2] += 1; } VERIFY_IS_EQUAL(result.dimension(0), tensor.dimension(0)); VERIFY_IS_EQUAL(result.dimension(1), tensor.dimension(1)); VERIFY_IS_EQUAL(result.dimension(2), tensor.dimension(2)); VERIFY_IS_EQUAL(result.dimension(3), tensor.dimension(3)); for (int i = 0; i < expected.dimension(0); ++i) { for (int j = 0; j < expected.dimension(1); ++j) { for (int k = 0; k < expected.dimension(2); ++k) { for (int l = 0; l < expected.dimension(3); ++l) { VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l)); } } } } dst_slice_start[2] = 0; result.setRandom(); for (int i = 0; i < tensor.dimension(2); ++i) { if (LValue) { result.slice(dst_slice_start, dst_slice_dim).roll(dim_roll) = tensor.slice(dst_slice_start, dst_slice_dim); } else { result.slice(dst_slice_start, dst_slice_dim) = tensor.roll(dim_roll).slice(dst_slice_start, dst_slice_dim); } dst_slice_start[2] += 1; } for (int i = 0; i < expected.dimension(0); ++i) { for (int j = 0; j < expected.dimension(1); ++j) { for (int k = 0; k < expected.dimension(2); ++k) { for (int l = 0; l < expected.dimension(3); ++l) { VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l)); } } } } } EIGEN_DECLARE_TEST(cxx11_tensor_roll) { CALL_SUBTEST(test_simple_roll()); CALL_SUBTEST(test_simple_roll()); CALL_SUBTEST(test_expr_roll(true)); CALL_SUBTEST(test_expr_roll(true)); CALL_SUBTEST(test_expr_roll(false)); CALL_SUBTEST(test_expr_roll(false)); }