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

// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
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// 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