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Austin Schuh70cc9552019-01-21 19:46:48 -08001// Ceres Solver - A fast non-linear least squares minimizer
Austin Schuh3de38b02024-06-25 18:25:10 -07002// Copyright 2023 Google Inc. All rights reserved.
Austin Schuh70cc9552019-01-21 19:46:48 -08003// http://ceres-solver.org/
4//
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6// modification, are permitted provided that the following conditions are met:
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29// Author: sameeragarwal@google.com (Sameer Agarwal)
30
31#include <cmath>
32#include <cstdlib>
33
34#include "ceres/ceres.h"
35#include "glog/logging.h"
36#include "gtest/gtest.h"
37
Austin Schuh3de38b02024-06-25 18:25:10 -070038namespace ceres::internal {
Austin Schuh70cc9552019-01-21 19:46:48 -080039
40class QuadraticFirstOrderFunction : public ceres::FirstOrderFunction {
41 public:
Austin Schuh1d1e6ea2020-12-23 21:56:30 -080042 bool Evaluate(const double* parameters,
43 double* cost,
44 double* gradient) const final {
Austin Schuh70cc9552019-01-21 19:46:48 -080045 cost[0] = parameters[0] * parameters[0];
Austin Schuh3de38b02024-06-25 18:25:10 -070046 if (gradient != nullptr) {
Austin Schuh70cc9552019-01-21 19:46:48 -080047 gradient[0] = 2.0 * parameters[0];
48 }
49 return true;
50 }
51
Austin Schuh1d1e6ea2020-12-23 21:56:30 -080052 int NumParameters() const final { return 1; }
Austin Schuh70cc9552019-01-21 19:46:48 -080053};
54
55TEST(LineSearchMinimizerTest, FinalCostIsZero) {
56 double parameters[1] = {2.0};
57 ceres::GradientProblem problem(new QuadraticFirstOrderFunction);
58 ceres::GradientProblemSolver::Options options;
59 ceres::GradientProblemSolver::Summary summary;
60 ceres::Solve(options, problem, parameters, &summary);
61 EXPECT_NEAR(summary.final_cost, 0.0, std::numeric_limits<double>::epsilon());
62}
63
Austin Schuh3de38b02024-06-25 18:25:10 -070064} // namespace ceres::internal