// 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