// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2014 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> using Eigen::RowMajor; using Eigen::Tensor; using Scalar = float; using TypedLTOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT, true>; using TypedLEOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE, true>; using TypedGTOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT, true>; using TypedGEOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE, true>; using TypedEQOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ, true>; using TypedNEOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ, true>; static void test_orderings() { Tensor<Scalar, 3> mat1(2, 3, 7); Tensor<Scalar, 3> mat2(2, 3, 7); mat1.setRandom(); mat2.setRandom(); Tensor<bool, 3> lt(2, 3, 7); Tensor<bool, 3> le(2, 3, 7); Tensor<bool, 3> gt(2, 3, 7); Tensor<bool, 3> ge(2, 3, 7); Tensor<Scalar, 3> typed_lt(2, 3, 7); Tensor<Scalar, 3> typed_le(2, 3, 7); Tensor<Scalar, 3> typed_gt(2, 3, 7); Tensor<Scalar, 3> typed_ge(2, 3, 7); lt = mat1 < mat2; le = mat1 <= mat2; gt = mat1 > mat2; ge = mat1 >= mat2; typed_lt = mat1.binaryExpr(mat2, TypedLTOp()); typed_le = mat1.binaryExpr(mat2, TypedLEOp()); typed_gt = mat1.binaryExpr(mat2, TypedGTOp()); typed_ge = mat1.binaryExpr(mat2, TypedGEOp()); for (int i = 0; i < 2; ++i) { for (int j = 0; j < 3; ++j) { for (int k = 0; k < 7; ++k) { VERIFY_IS_EQUAL(lt(i, j, k), mat1(i, j, k) < mat2(i, j, k)); VERIFY_IS_EQUAL(le(i, j, k), mat1(i, j, k) <= mat2(i, j, k)); VERIFY_IS_EQUAL(gt(i, j, k), mat1(i, j, k) > mat2(i, j, k)); VERIFY_IS_EQUAL(ge(i, j, k), mat1(i, j, k) >= mat2(i, j, k)); VERIFY_IS_EQUAL(lt(i, j, k), (bool)typed_lt(i, j, k)); VERIFY_IS_EQUAL(le(i, j, k), (bool)typed_le(i, j, k)); VERIFY_IS_EQUAL(gt(i, j, k), (bool)typed_gt(i, j, k)); VERIFY_IS_EQUAL(ge(i, j, k), (bool)typed_ge(i, j, k)); } } } } static void test_equality() { Tensor<Scalar, 3> mat1(2, 3, 7); Tensor<Scalar, 3> mat2(2, 3, 7); mat1.setRandom(); mat2.setRandom(); for (int i = 0; i < 2; ++i) { for (int j = 0; j < 3; ++j) { for (int k = 0; k < 7; ++k) { if (internal::random<bool>()) { mat2(i, j, k) = mat1(i, j, k); } } } } Tensor<bool, 3> eq(2, 3, 7); Tensor<bool, 3> ne(2, 3, 7); Tensor<Scalar, 3> typed_eq(2, 3, 7); Tensor<Scalar, 3> typed_ne(2, 3, 7); eq = (mat1 == mat2); ne = (mat1 != mat2); typed_eq = mat1.binaryExpr(mat2, TypedEQOp()); typed_ne = mat1.binaryExpr(mat2, TypedNEOp()); for (int i = 0; i < 2; ++i) { for (int j = 0; j < 3; ++j) { for (int k = 0; k < 7; ++k) { VERIFY_IS_EQUAL(eq(i, j, k), mat1(i, j, k) == mat2(i, j, k)); VERIFY_IS_EQUAL(ne(i, j, k), mat1(i, j, k) != mat2(i, j, k)); VERIFY_IS_EQUAL(eq(i, j, k), (bool)typed_eq(i, j, k)); VERIFY_IS_EQUAL(ne(i, j, k), (bool)typed_ne(i, j, k)); } } } } static void test_isnan() { Tensor<Scalar, 3> mat(2, 3, 7); mat.setRandom(); for (int i = 0; i < 2; ++i) { for (int j = 0; j < 3; ++j) { for (int k = 0; k < 7; ++k) { if (internal::random<bool>()) { mat(i, j, k) = std::numeric_limits<Scalar>::quiet_NaN(); } } } } Tensor<bool, 3> nan(2, 3, 7); nan = (mat.isnan)(); for (int i = 0; i < 2; ++i) { for (int j = 0; j < 3; ++j) { for (int k = 0; k < 7; ++k) { VERIFY_IS_EQUAL(nan(i, j, k), (std::isnan)(mat(i, j, k))); } } } } EIGEN_DECLARE_TEST(cxx11_tensor_comparisons) { CALL_SUBTEST(test_orderings()); CALL_SUBTEST(test_equality()); CALL_SUBTEST(test_isnan()); }