// Ceres Solver - A fast non-linear least squares minimizer
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// Author: sameeragarwal@google.com (Sameer Agarwal)

#include "ceres/autodiff_cost_function.h"

#include <memory>

#include "ceres/array_utils.h"
#include "ceres/cost_function.h"
#include "gtest/gtest.h"

namespace ceres::internal {

class BinaryScalarCost {
 public:
  explicit BinaryScalarCost(double a) : a_(a) {}
  template <typename T>
  bool operator()(const T* const x, const T* const y, T* cost) const {
    cost[0] = x[0] * y[0] + x[1] * y[1] - T(a_);
    return true;
  }

 private:
  double a_;
};

TEST(AutodiffCostFunction, BilinearDifferentiationTest) {
  CostFunction* cost_function =
      new AutoDiffCostFunction<BinaryScalarCost, 1, 2, 2>(
          new BinaryScalarCost(1.0));

  auto** parameters = new double*[2];
  parameters[0] = new double[2];
  parameters[1] = new double[2];

  parameters[0][0] = 1;
  parameters[0][1] = 2;

  parameters[1][0] = 3;
  parameters[1][1] = 4;

  auto** jacobians = new double*[2];
  jacobians[0] = new double[2];
  jacobians[1] = new double[2];

  double residuals = 0.0;

  cost_function->Evaluate(parameters, &residuals, nullptr);
  EXPECT_EQ(10.0, residuals);

  cost_function->Evaluate(parameters, &residuals, jacobians);
  EXPECT_EQ(10.0, residuals);

  EXPECT_EQ(3, jacobians[0][0]);
  EXPECT_EQ(4, jacobians[0][1]);
  EXPECT_EQ(1, jacobians[1][0]);
  EXPECT_EQ(2, jacobians[1][1]);

  delete[] jacobians[0];
  delete[] jacobians[1];
  delete[] parameters[0];
  delete[] parameters[1];
  delete[] jacobians;
  delete[] parameters;
  delete cost_function;
}

struct TenParameterCost {
  template <typename T>
  bool operator()(const T* const x0,
                  const T* const x1,
                  const T* const x2,
                  const T* const x3,
                  const T* const x4,
                  const T* const x5,
                  const T* const x6,
                  const T* const x7,
                  const T* const x8,
                  const T* const x9,
                  T* cost) const {
    cost[0] = *x0 + *x1 + *x2 + *x3 + *x4 + *x5 + *x6 + *x7 + *x8 + *x9;
    return true;
  }
};

TEST(AutodiffCostFunction, ManyParameterAutodiffInstantiates) {
  CostFunction* cost_function =
      new AutoDiffCostFunction<TenParameterCost,
                               1,
                               1,
                               1,
                               1,
                               1,
                               1,
                               1,
                               1,
                               1,
                               1,
                               1>(new TenParameterCost);

  auto** parameters = new double*[10];
  auto** jacobians = new double*[10];
  for (int i = 0; i < 10; ++i) {
    parameters[i] = new double[1];
    parameters[i][0] = i;
    jacobians[i] = new double[1];
  }

  double residuals = 0.0;

  cost_function->Evaluate(parameters, &residuals, nullptr);
  EXPECT_EQ(45.0, residuals);

  cost_function->Evaluate(parameters, &residuals, jacobians);
  EXPECT_EQ(residuals, 45.0);
  for (int i = 0; i < 10; ++i) {
    EXPECT_EQ(1.0, jacobians[i][0]);
  }

  for (int i = 0; i < 10; ++i) {
    delete[] jacobians[i];
    delete[] parameters[i];
  }
  delete[] jacobians;
  delete[] parameters;
  delete cost_function;
}

struct OnlyFillsOneOutputFunctor {
  template <typename T>
  bool operator()(const T* x, T* output) const {
    output[0] = x[0];
    return true;
  }
};

TEST(AutoDiffCostFunction, PartiallyFilledResidualShouldFailEvaluation) {
  double parameter = 1.0;
  double jacobian[2];
  double residuals[2];
  double* parameters[] = {&parameter};
  double* jacobians[] = {jacobian};

  std::unique_ptr<CostFunction> cost_function(
      new AutoDiffCostFunction<OnlyFillsOneOutputFunctor, 2, 1>(
          new OnlyFillsOneOutputFunctor));
  InvalidateArray(2, jacobian);
  InvalidateArray(2, residuals);
  EXPECT_TRUE(cost_function->Evaluate(parameters, residuals, jacobians));
  EXPECT_FALSE(IsArrayValid(2, jacobian));
  EXPECT_FALSE(IsArrayValid(2, residuals));
}

}  // namespace ceres::internal
