| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2015 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 |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| // 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: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include <map> |
| |
| #include "ceres/line_search_preprocessor.h" |
| #include "ceres/problem_impl.h" |
| #include "ceres/sized_cost_function.h" |
| #include "ceres/solver.h" |
| #include "gtest/gtest.h" |
| |
| namespace ceres { |
| namespace 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 { |
| return false; |
| } |
| }; |
| |
| TEST(LineSearchPreprocessor, RemoveParameterBlocksFailed) { |
| ProblemImpl problem; |
| double x = 3.0; |
| problem.AddResidualBlock(new FailingCostFunction, NULL, &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 { |
| 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>, NULL, &x, &y); |
| problem.AddResidualBlock(new DummyCostFunction<1, 1, 1>, NULL, &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() != NULL); |
| } |
| |
| } // namespace internal |
| } // namespace ceres |