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140 lines
4.0 KiB
C++
140 lines
4.0 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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#include <Eigen/CXX11/Tensor>
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using Eigen::RowMajor;
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using Eigen::Tensor;
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using Scalar = float;
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using TypedLTOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LT, true>;
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using TypedLEOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_LE, true>;
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using TypedGTOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GT, true>;
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using TypedGEOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_GE, true>;
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using TypedEQOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_EQ, true>;
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using TypedNEOp = internal::scalar_cmp_op<Scalar, Scalar, internal::cmp_NEQ, true>;
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static void test_orderings() {
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Tensor<Scalar, 3> mat1(2, 3, 7);
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Tensor<Scalar, 3> mat2(2, 3, 7);
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mat1.setRandom();
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mat2.setRandom();
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Tensor<bool, 3> lt(2, 3, 7);
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Tensor<bool, 3> le(2, 3, 7);
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Tensor<bool, 3> gt(2, 3, 7);
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Tensor<bool, 3> ge(2, 3, 7);
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Tensor<Scalar, 3> typed_lt(2, 3, 7);
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Tensor<Scalar, 3> typed_le(2, 3, 7);
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Tensor<Scalar, 3> typed_gt(2, 3, 7);
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Tensor<Scalar, 3> typed_ge(2, 3, 7);
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lt = mat1 < mat2;
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le = mat1 <= mat2;
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gt = mat1 > mat2;
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ge = mat1 >= mat2;
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typed_lt = mat1.binaryExpr(mat2, TypedLTOp());
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typed_le = mat1.binaryExpr(mat2, TypedLEOp());
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typed_gt = mat1.binaryExpr(mat2, TypedGTOp());
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typed_ge = mat1.binaryExpr(mat2, TypedGEOp());
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for (int i = 0; i < 2; ++i) {
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for (int j = 0; j < 3; ++j) {
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for (int k = 0; k < 7; ++k) {
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VERIFY_IS_EQUAL(lt(i, j, k), mat1(i, j, k) < mat2(i, j, k));
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VERIFY_IS_EQUAL(le(i, j, k), mat1(i, j, k) <= mat2(i, j, k));
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VERIFY_IS_EQUAL(gt(i, j, k), mat1(i, j, k) > mat2(i, j, k));
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VERIFY_IS_EQUAL(ge(i, j, k), mat1(i, j, k) >= mat2(i, j, k));
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VERIFY_IS_EQUAL(lt(i, j, k), (bool)typed_lt(i, j, k));
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VERIFY_IS_EQUAL(le(i, j, k), (bool)typed_le(i, j, k));
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VERIFY_IS_EQUAL(gt(i, j, k), (bool)typed_gt(i, j, k));
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VERIFY_IS_EQUAL(ge(i, j, k), (bool)typed_ge(i, j, k));
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}
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}
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}
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}
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static void test_equality() {
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Tensor<Scalar, 3> mat1(2, 3, 7);
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Tensor<Scalar, 3> mat2(2, 3, 7);
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mat1.setRandom();
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mat2.setRandom();
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for (int i = 0; i < 2; ++i) {
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for (int j = 0; j < 3; ++j) {
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for (int k = 0; k < 7; ++k) {
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if (internal::random<bool>()) {
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mat2(i, j, k) = mat1(i, j, k);
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}
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}
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}
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}
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Tensor<bool, 3> eq(2, 3, 7);
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Tensor<bool, 3> ne(2, 3, 7);
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Tensor<Scalar, 3> typed_eq(2, 3, 7);
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Tensor<Scalar, 3> typed_ne(2, 3, 7);
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eq = (mat1 == mat2);
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ne = (mat1 != mat2);
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typed_eq = mat1.binaryExpr(mat2, TypedEQOp());
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typed_ne = mat1.binaryExpr(mat2, TypedNEOp());
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for (int i = 0; i < 2; ++i) {
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for (int j = 0; j < 3; ++j) {
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for (int k = 0; k < 7; ++k) {
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VERIFY_IS_EQUAL(eq(i, j, k), mat1(i, j, k) == mat2(i, j, k));
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VERIFY_IS_EQUAL(ne(i, j, k), mat1(i, j, k) != mat2(i, j, k));
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VERIFY_IS_EQUAL(eq(i, j, k), (bool)typed_eq(i, j, k));
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VERIFY_IS_EQUAL(ne(i, j, k), (bool)typed_ne(i, j, k));
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}
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}
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}
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}
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static void test_isnan() {
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Tensor<Scalar, 3> mat(2, 3, 7);
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mat.setRandom();
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for (int i = 0; i < 2; ++i) {
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for (int j = 0; j < 3; ++j) {
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for (int k = 0; k < 7; ++k) {
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if (internal::random<bool>()) {
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mat(i, j, k) = std::numeric_limits<Scalar>::quiet_NaN();
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}
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}
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}
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}
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Tensor<bool, 3> nan(2, 3, 7);
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nan = (mat.isnan)();
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for (int i = 0; i < 2; ++i) {
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for (int j = 0; j < 3; ++j) {
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for (int k = 0; k < 7; ++k) {
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VERIFY_IS_EQUAL(nan(i, j, k), (std::isnan)(mat(i, j, k)));
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}
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}
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}
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}
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EIGEN_DECLARE_TEST(cxx11_tensor_comparisons) {
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CALL_SUBTEST(test_orderings());
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CALL_SUBTEST(test_equality());
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CALL_SUBTEST(test_isnan());
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}
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