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// 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());
}