| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137 | // 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
 |