| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2023 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are met: | |
| // | |
| // * Redistributions of source code must retain the above copyright notice, | |
| // this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above copyright notice, | |
| // this list of conditions and the following disclaimer in the documentation | |
| // and/or other materials provided with the distribution. | |
| // * Neither the name of Google Inc. nor the names of its contributors may be | |
| // used to endorse or promote products derived from this software without | |
| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE | |
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| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS | |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN | |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) | |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | |
| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: strandmark@google.com (Petter Strandmark) | |
| #include "ceres/gradient_problem.h" | |
| #include <memory> | |
| #include "ceres/manifold.h" | |
| #include "gtest/gtest.h" | |
| namespace ceres::internal { | |
| class QuadraticTestFunction : public ceres::FirstOrderFunction { | |
| public: | |
| explicit QuadraticTestFunction(bool* flag_to_set_on_destruction = nullptr) | |
| : flag_to_set_on_destruction_(flag_to_set_on_destruction) {} | |
| ~QuadraticTestFunction() override { | |
| if (flag_to_set_on_destruction_) { | |
| *flag_to_set_on_destruction_ = true; | |
| } | |
| } | |
| bool Evaluate(const double* parameters, | |
| double* cost, | |
| double* gradient) const final { | |
| const double x = parameters[0]; | |
| cost[0] = x * x; | |
| if (gradient != nullptr) { | |
| gradient[0] = 2.0 * x; | |
| } | |
| return true; | |
| } | |
| int NumParameters() const final { return 1; } | |
| private: | |
| bool* flag_to_set_on_destruction_; | |
| }; | |
| TEST(GradientProblem, TakesOwnershipOfFirstOrderFunction) { | |
| bool is_destructed = false; | |
| { | |
| ceres::GradientProblem problem( | |
| std::make_unique<QuadraticTestFunction>(&is_destructed)); | |
| } | |
| EXPECT_TRUE(is_destructed); | |
| } | |
| TEST(GradientProblem, EvaluationWithManifoldAndNoGradient) { | |
| ceres::GradientProblem problem(std::make_unique<QuadraticTestFunction>(), | |
| std::make_unique<EuclideanManifold<1>>()); | |
| double x = 7.0; | |
| double cost = 0; | |
| problem.Evaluate(&x, &cost, nullptr); | |
| EXPECT_EQ(x * x, cost); | |
| } | |
| TEST(GradientProblem, EvaluationWithoutManifoldAndWithGradient) { | |
| ceres::GradientProblem problem(std::make_unique<QuadraticTestFunction>()); | |
| double x = 7.0; | |
| double cost = 0; | |
| double gradient = 0; | |
| problem.Evaluate(&x, &cost, &gradient); | |
| EXPECT_EQ(2.0 * x, gradient); | |
| } | |
| TEST(GradientProblem, EvaluationWithManifoldAndWithGradient) { | |
| ceres::GradientProblem problem(std::make_unique<QuadraticTestFunction>(), | |
| std::make_unique<EuclideanManifold<1>>()); | |
| double x = 7.0; | |
| double cost = 0; | |
| double gradient = 0; | |
| problem.Evaluate(&x, &cost, &gradient); | |
| EXPECT_EQ(2.0 * x, gradient); | |
| } | |
| } // namespace ceres::internal |