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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// modification, are permitted provided that the following conditions are met:
//
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// 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
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/line_search_preprocessor.h"
#include <map>
#include "ceres/problem_impl.h"
#include "ceres/sized_cost_function.h"
#include "ceres/solver.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