MYNT-EYE-S-SDK/3rdparty/ceres-solver-1.11.0/internal/ceres/gradient_problem_test.cc
2019-01-03 16:25:18 +08:00

112 lines
3.8 KiB
C++

// 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: strandmark@google.com (Petter Strandmark)
#include "ceres/gradient_problem.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
class QuadraticTestFunction : public ceres::FirstOrderFunction {
public:
explicit QuadraticTestFunction(bool* flag_to_set_on_destruction = NULL)
: flag_to_set_on_destruction_(flag_to_set_on_destruction) {}
virtual ~QuadraticTestFunction() {
if (flag_to_set_on_destruction_) {
*flag_to_set_on_destruction_ = true;
}
}
virtual bool Evaluate(const double* parameters,
double* cost,
double* gradient) const {
const double x = parameters[0];
cost[0] = x * x;
if (gradient != NULL) {
gradient[0] = 2.0 * x;
}
return true;
}
virtual int NumParameters() const { return 1; }
private:
bool* flag_to_set_on_destruction_;
};
TEST(GradientProblem, TakesOwnershipOfFirstOrderFunction) {
bool is_destructed = false;
{
ceres::GradientProblem problem(new QuadraticTestFunction(&is_destructed));
}
EXPECT_TRUE(is_destructed);
}
TEST(GradientProblem, EvaluationWithoutParameterizationOrGradient) {
ceres::GradientProblem problem(new QuadraticTestFunction());
double x = 7.0;
double cost = 0;
problem.Evaluate(&x, &cost, NULL);
EXPECT_EQ(x * x, cost);
}
TEST(GradientProblem, EvalutaionWithParameterizationAndNoGradient) {
ceres::GradientProblem problem(new QuadraticTestFunction(),
new IdentityParameterization(1));
double x = 7.0;
double cost = 0;
problem.Evaluate(&x, &cost, NULL);
EXPECT_EQ(x * x, cost);
}
TEST(GradientProblem, EvaluationWithoutParameterizationAndWithGradient) {
ceres::GradientProblem problem(new QuadraticTestFunction());
double x = 7.0;
double cost = 0;
double gradient = 0;
problem.Evaluate(&x, &cost, &gradient);
EXPECT_EQ(2.0 * x, gradient);
}
TEST(GradientProblem, EvaluationWithParameterizationAndWithGradient) {
ceres::GradientProblem problem(new QuadraticTestFunction(),
new IdentityParameterization(1));
double x = 7.0;
double cost = 0;
double gradient = 0;
problem.Evaluate(&x, &cost, &gradient);
EXPECT_EQ(2.0 * x, gradient);
}
} // namespace internal
} // namespace ceres