|  | // 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 | 
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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 | 
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|  | // | 
|  | // Author: sameeragarwal@google.com (Sameer Agarwal) | 
|  |  | 
|  | #include "ceres/line_search_preprocessor.h" | 
|  |  | 
|  | #include <limits> | 
|  |  | 
|  | #include "ceres/preprocessor.h" | 
|  | #include "ceres/problem_impl.h" | 
|  | #include "ceres/sized_cost_function.h" | 
|  | #include "ceres/solver.h" | 
|  | #include "ceres/types.h" | 
|  | #include "gtest/gtest.h" | 
|  |  | 
|  | namespace ceres::internal { | 
|  |  | 
|  | TEST(LineSearchPreprocessor, ZeroProblem) { | 
|  | ProblemImpl problem; | 
|  | Solver::Options options; | 
|  | options.minimizer_type = LINE_SEARCH; | 
|  | LineSearchPreprocessor preprocessor; | 
|  | PreprocessedProblem pp; | 
|  | EXPECT_TRUE(preprocessor.Preprocess(options, &problem, &pp)); | 
|  | } | 
|  |  | 
|  | TEST(LineSearchPreprocessor, ProblemWithInvalidParameterBlock) { | 
|  | ProblemImpl problem; | 
|  | double x = std::numeric_limits<double>::quiet_NaN(); | 
|  | problem.AddParameterBlock(&x, 1); | 
|  | Solver::Options options; | 
|  | options.minimizer_type = LINE_SEARCH; | 
|  | LineSearchPreprocessor preprocessor; | 
|  | PreprocessedProblem pp; | 
|  | EXPECT_FALSE(preprocessor.Preprocess(options, &problem, &pp)); | 
|  | } | 
|  |  | 
|  | TEST(LineSearchPreprocessor, ParameterBlockHasBounds) { | 
|  | ProblemImpl problem; | 
|  | double x = 1.0; | 
|  | problem.AddParameterBlock(&x, 1); | 
|  | problem.SetParameterUpperBound(&x, 0, 1.0); | 
|  | problem.SetParameterLowerBound(&x, 0, 2.0); | 
|  | Solver::Options options; | 
|  | options.minimizer_type = LINE_SEARCH; | 
|  | LineSearchPreprocessor preprocessor; | 
|  | PreprocessedProblem pp; | 
|  | EXPECT_FALSE(preprocessor.Preprocess(options, &problem, &pp)); | 
|  | } | 
|  |  | 
|  | class FailingCostFunction : public SizedCostFunction<1, 1> { | 
|  | public: | 
|  | bool Evaluate(double const* const* parameters, | 
|  | double* residuals, | 
|  | double** jacobians) const override { | 
|  | return false; | 
|  | } | 
|  | }; | 
|  |  | 
|  | TEST(LineSearchPreprocessor, RemoveParameterBlocksFailed) { | 
|  | ProblemImpl problem; | 
|  | double x = 3.0; | 
|  | problem.AddResidualBlock(new FailingCostFunction, nullptr, &x); | 
|  | problem.SetParameterBlockConstant(&x); | 
|  | Solver::Options options; | 
|  | options.minimizer_type = LINE_SEARCH; | 
|  | LineSearchPreprocessor preprocessor; | 
|  | PreprocessedProblem pp; | 
|  | EXPECT_FALSE(preprocessor.Preprocess(options, &problem, &pp)); | 
|  | } | 
|  |  | 
|  | TEST(LineSearchPreprocessor, RemoveParameterBlocksSucceeds) { | 
|  | ProblemImpl problem; | 
|  | double x = 3.0; | 
|  | problem.AddParameterBlock(&x, 1); | 
|  | Solver::Options options; | 
|  | options.minimizer_type = LINE_SEARCH; | 
|  |  | 
|  | LineSearchPreprocessor preprocessor; | 
|  | PreprocessedProblem pp; | 
|  | EXPECT_TRUE(preprocessor.Preprocess(options, &problem, &pp)); | 
|  | } | 
|  |  | 
|  | template <int kNumResiduals, int... Ns> | 
|  | class DummyCostFunction : public SizedCostFunction<kNumResiduals, Ns...> { | 
|  | public: | 
|  | bool Evaluate(double const* const* parameters, | 
|  | double* residuals, | 
|  | double** jacobians) const override { | 
|  | return true; | 
|  | } | 
|  | }; | 
|  |  | 
|  | TEST(LineSearchPreprocessor, NormalOperation) { | 
|  | ProblemImpl problem; | 
|  | double x = 1.0; | 
|  | double y = 1.0; | 
|  | double z = 1.0; | 
|  | problem.AddResidualBlock(new DummyCostFunction<1, 1, 1>, nullptr, &x, &y); | 
|  | problem.AddResidualBlock(new DummyCostFunction<1, 1, 1>, nullptr, &y, &z); | 
|  |  | 
|  | Solver::Options options; | 
|  | options.minimizer_type = LINE_SEARCH; | 
|  |  | 
|  | LineSearchPreprocessor preprocessor; | 
|  | PreprocessedProblem pp; | 
|  | EXPECT_TRUE(preprocessor.Preprocess(options, &problem, &pp)); | 
|  | EXPECT_EQ(pp.evaluator_options.linear_solver_type, CGNR); | 
|  | EXPECT_TRUE(pp.evaluator.get() != nullptr); | 
|  | } | 
|  |  | 
|  | }  // namespace ceres::internal |