| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2015 Benoit Steiner <benoit.steiner.goog@gmail.com> |
| // |
| // 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 <Eigen/CXX11/Tensor> |
| |
| struct Generator1D { |
| Generator1D() { } |
| |
| float operator()(const array<Eigen::DenseIndex, 1>& coordinates) const { |
| return coordinates[0]; |
| } |
| }; |
| |
| template <int DataLayout> |
| static void test_1D() |
| { |
| Tensor<float, 1> vec(6); |
| Tensor<float, 1> result = vec.generate(Generator1D()); |
| |
| for (int i = 0; i < 6; ++i) { |
| VERIFY_IS_EQUAL(result(i), i); |
| } |
| } |
| |
| |
| struct Generator2D { |
| Generator2D() { } |
| |
| float operator()(const array<Eigen::DenseIndex, 2>& coordinates) const { |
| return 3 * coordinates[0] + 11 * coordinates[1]; |
| } |
| }; |
| |
| template <int DataLayout> |
| static void test_2D() |
| { |
| Tensor<float, 2> matrix(512, 512); |
| Tensor<float, 2> result = matrix.generate(Generator2D()); |
| |
| for (int i = 0; i < 512; ++i) { |
| for (int j = 0; j < 512; ++j) { |
| VERIFY_IS_EQUAL(result(i, j), 3*i + 11*j); |
| } |
| } |
| } |
| |
| |
| template <int DataLayout> |
| static void test_gaussian() |
| { |
| int rows = 32; |
| int cols = 48; |
| array<float, 2> means; |
| means[0] = rows / 2.0f; |
| means[1] = cols / 2.0f; |
| array<float, 2> std_devs; |
| std_devs[0] = 3.14f; |
| std_devs[1] = 2.7f; |
| internal::GaussianGenerator<float, Eigen::DenseIndex, 2> gaussian_gen(means, std_devs); |
| |
| Tensor<float, 2> matrix(rows, cols); |
| Tensor<float, 2> result = matrix.generate(gaussian_gen); |
| |
| for (int i = 0; i < rows; ++i) { |
| for (int j = 0; j < cols; ++j) { |
| float g_rows = powf(rows/2.0f - i, 2) / (3.14f * 3.14f) * 0.5f; |
| float g_cols = powf(cols/2.0f - j, 2) / (2.7f * 2.7f) * 0.5f; |
| float gaussian = expf(-g_rows - g_cols); |
| VERIFY_IS_EQUAL(result(i, j), gaussian); |
| } |
| } |
| } |
| |
| |
| EIGEN_DECLARE_TEST(cxx11_tensor_generator) |
| { |
| CALL_SUBTEST(test_1D<ColMajor>()); |
| CALL_SUBTEST(test_1D<RowMajor>()); |
| CALL_SUBTEST(test_2D<ColMajor>()); |
| CALL_SUBTEST(test_2D<RowMajor>()); |
| CALL_SUBTEST(test_gaussian<ColMajor>()); |
| CALL_SUBTEST(test_gaussian<RowMajor>()); |
| } |