MYNT-EYE-S-SDK/3rdparty/ceres-solver-1.11.0/internal/ceres/line_search_preprocessor_test.cc

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2019-01-03 10:25:18 +02:00
// 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/problem_impl.h"
#include "ceres/sized_cost_function.h"
#include "ceres/solver.h"
#include "ceres/line_search_preprocessor.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 N1 = 0, int N2 = 0, int N3 = 0>
class DummyCostFunction : public SizedCostFunction<kNumResiduals, N1, N2, N3> {
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