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#include <pcl/test/gtest.h>

#include <pcl/pcl_tests.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>

#include <pcl/sample_consensus/msac.h>
#include <pcl/sample_consensus/lmeds.h>
#include <pcl/sample_consensus/rmsac.h>
#include <pcl/sample_consensus/mlesac.h>
#include <pcl/sample_consensus/ransac.h>
#include <pcl/sample_consensus/rransac.h>
#include <pcl/sample_consensus/sac_model_plane.h>
#include <pcl/sample_consensus/sac_model_normal_plane.h>
#include <pcl/sample_consensus/sac_model_normal_parallel_plane.h>

using namespace pcl;
using namespace pcl::io;

using SampleConsensusModelPlanePtr = SampleConsensusModelPlane<PointXYZ>::Ptr;
using SampleConsensusModelNormalPlanePtr = SampleConsensusModelNormalPlane<PointXYZ, Normal>::Ptr;
using SampleConsensusModelNormalParallelPlanePtr = SampleConsensusModelNormalParallelPlane<PointXYZ, Normal>::Ptr;

PointCloud<PointXYZ>::Ptr cloud_ (new PointCloud<PointXYZ> ());
PointCloud<Normal>::Ptr normals_ (new PointCloud<Normal> ());
std::vector<int> indices_;
float plane_coeffs_[] = {-0.8964f, -0.5868f, -1.208f};

template <typename ModelType, typename SacType>
void verifyPlaneSac (ModelType& model,
                     SacType& sac,
                     unsigned int inlier_number = 2000,
                     float tol = 1e-1f,
                     float refined_tol = 1e-1f,
                     float proj_tol = 1e-3f)
{
  // Algorithm tests
  bool result = sac.computeModel ();
  ASSERT_TRUE (result);

  std::vector<int> sample;
  sac.getModel (sample);
  EXPECT_EQ (3, sample.size ());

  std::vector<int> inliers;
  sac.getInliers (inliers);
  EXPECT_LT (inlier_number, inliers.size ());

  Eigen::VectorXf coeff;
  sac.getModelCoefficients (coeff);
  EXPECT_EQ (4, coeff.size ());
  EXPECT_NEAR (plane_coeffs_[0], coeff[0] / coeff[3], tol);
  EXPECT_NEAR (plane_coeffs_[1], coeff[1] / coeff[3], tol);
  EXPECT_NEAR (plane_coeffs_[2], coeff[2] / coeff[3], tol);

  Eigen::VectorXf coeff_refined;
  model->optimizeModelCoefficients (inliers, coeff, coeff_refined);
  EXPECT_EQ (4, coeff_refined.size ());
  EXPECT_NEAR (plane_coeffs_[0], coeff_refined[0] / coeff_refined[3], refined_tol);
  EXPECT_NEAR (plane_coeffs_[1], coeff_refined[1] / coeff_refined[3], refined_tol);

  // This test fails in Windows (VS 2010) -- not sure why yet -- relaxing the constraint from 1e-2 to 1e-1
  // This test fails in MacOS too -- not sure why yet -- disabling
  //EXPECT_NEAR (coeff_refined[2] / coeff_refined[3], plane_coeffs_[2], refined_tol);

  // Projection tests
  PointCloud<PointXYZ> proj_points;
  model->projectPoints (inliers, coeff_refined, proj_points);
  EXPECT_XYZ_NEAR (PointXYZ (1.1266,  0.0152, -0.0156), proj_points.points[20], proj_tol);
  EXPECT_XYZ_NEAR (PointXYZ (1.1843, -0.0635, -0.0201), proj_points.points[30], proj_tol);
  EXPECT_XYZ_NEAR (PointXYZ (1.0749, -0.0586,  0.0587), proj_points.points[50], proj_tol);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelPlane, Base)
{
  // Create a shared plane model pointer directly
  SampleConsensusModelPlanePtr model (new SampleConsensusModelPlane<PointXYZ> (cloud_));

  // Basic tests
  PointCloud<PointXYZ>::ConstPtr cloud = model->getInputCloud ();
  ASSERT_EQ (cloud_->points.size (), cloud->points.size ());

  model->setInputCloud (cloud);
  cloud = model->getInputCloud ();
  ASSERT_EQ (cloud_->points.size (), cloud->points.size ());

  auto indices = model->getIndices ();
  ASSERT_EQ (indices_.size (), indices->size ());
  model->setIndices (indices_);
  indices = model->getIndices ();
  ASSERT_EQ (indices_.size (), indices->size ());
  model->setIndices (indices);
  indices = model->getIndices ();
  ASSERT_EQ (indices_.size (), indices->size ());
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelPlane, RANSAC)
{
  srand (0);

  // Create a shared plane model pointer directly
  SampleConsensusModelPlanePtr model (new SampleConsensusModelPlane<PointXYZ> (cloud_));

  // Create the RANSAC object
  RandomSampleConsensus<PointXYZ> sac (model, 0.03);

  verifyPlaneSac (model, sac);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelPlane, LMedS)
{
  srand (0);

  // Create a shared plane model pointer directly
  SampleConsensusModelPlanePtr model (new SampleConsensusModelPlane<PointXYZ> (cloud_));

  // Create the LMedS object
  LeastMedianSquares<PointXYZ> sac (model, 0.03);

  verifyPlaneSac (model, sac);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelPlane, MSAC)
{
  srand (0);

  // Create a shared plane model pointer directly
  SampleConsensusModelPlanePtr model (new SampleConsensusModelPlane<PointXYZ> (cloud_));

  // Create the MSAC object
  MEstimatorSampleConsensus<PointXYZ> sac (model, 0.03);

  verifyPlaneSac (model, sac);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelPlane, RRANSAC)
{
  srand (0);

  // Create a shared plane model pointer directly
  SampleConsensusModelPlanePtr model (new SampleConsensusModelPlane<PointXYZ> (cloud_));

  // Create the RRANSAC object
  RandomizedRandomSampleConsensus<PointXYZ> sac (model, 0.03);

  sac.setFractionNrPretest (0.1);
  ASSERT_EQ (0.1, sac.getFractionNrPretest ());

  verifyPlaneSac (model, sac, 600, 1.0f, 1.0f, 0.01f);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelPlane, MLESAC)
{
  srand (0);

  // Create a shared plane model pointer directly
  SampleConsensusModelPlanePtr model (new SampleConsensusModelPlane<PointXYZ> (cloud_));

  // Create the MSAC object
  MaximumLikelihoodSampleConsensus<PointXYZ> sac (model, 0.03);

  verifyPlaneSac (model, sac, 1000, 0.3f, 0.2f, 0.01f);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelPlane, RMSAC)
{
  srand (0);

  // Create a shared plane model pointer directly
  SampleConsensusModelPlanePtr model (new SampleConsensusModelPlane<PointXYZ> (cloud_));

  // Create the RMSAC object
  RandomizedMEstimatorSampleConsensus<PointXYZ> sac (model, 0.03);

  sac.setFractionNrPretest (10.0);
  ASSERT_EQ (10.0, sac.getFractionNrPretest ());

  verifyPlaneSac (model, sac, 600, 1.0f, 1.0f, 0.01f);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelNormalPlane, RANSAC)
{
  srand (0);

  // Create a shared plane model pointer directly
  SampleConsensusModelNormalPlanePtr model (new SampleConsensusModelNormalPlane<PointXYZ, Normal> (cloud_));
  model->setInputNormals (normals_);
  model->setNormalDistanceWeight (0.01);

  // Create the RANSAC object
  RandomSampleConsensus<PointXYZ> sac (model, 0.03);

  verifyPlaneSac (model, sac);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
TEST (SampleConsensusModelNormalParallelPlane, RANSAC)
{
  srand (0);

  // Use a custom point cloud for these tests until we need something better
  PointCloud<PointXYZ> cloud;
  PointCloud<Normal> normals;
  cloud.points.resize (10);
  normals.resize (10);

  for (std::size_t idx = 0; idx < cloud.size (); ++idx)
  {
    cloud.points[idx].x = static_cast<float> ((rand () % 200) - 100);
    cloud.points[idx].y = static_cast<float> ((rand () % 200) - 100);
    cloud.points[idx].z = 0.0f;

    normals.points[idx].normal_x = 0.0f;
    normals.points[idx].normal_y = 0.0f;
    normals.points[idx].normal_z = 1.0f;
  }

  // Create a shared plane model pointer directly
  SampleConsensusModelNormalParallelPlanePtr model (new SampleConsensusModelNormalParallelPlane<PointXYZ, Normal> (cloud.makeShared ()));
  model->setInputNormals (normals.makeShared ());

  const float max_angle_rad = 0.01f;
  const float angle_eps = 0.001f;
  model->setEpsAngle (max_angle_rad);

  // Test true axis
  {
    model->setAxis (Eigen::Vector3f (0, 0, 1));

    RandomSampleConsensus<PointXYZ> sac (model, 0.03);
    sac.computeModel();

    std::vector<int> inliers;
    sac.getInliers (inliers);
    ASSERT_EQ (cloud.size (), inliers.size ());
  }

  // test axis slightly in valid range
  {
    model->setAxis (Eigen::Vector3f (0, sin (max_angle_rad * (1 - angle_eps)), std::cos (max_angle_rad * (1 - angle_eps))));
    RandomSampleConsensus<PointXYZ> sac (model, 0.03);
    sac.computeModel ();

    std::vector<int> inliers;
    sac.getInliers (inliers);
    ASSERT_EQ (cloud.size (), inliers.size ());
  }

  // test axis slightly out of valid range
  {
    model->setAxis (Eigen::Vector3f (0, sin (max_angle_rad * (1 + angle_eps)), std::cos (max_angle_rad * (1 + angle_eps))));
    RandomSampleConsensus<PointXYZ> sac (model, 0.03);
    sac.computeModel ();

    std::vector<int> inliers;
    sac.getInliers (inliers);
    ASSERT_EQ (0, inliers.size ());
  }
}


int
main (int argc, char** argv)
{
  if (argc < 2)
  {
    std::cerr << "No test file given. Please download `sac_plane_test.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }

  // Load a standard PCD file from disk
  pcl::PCLPointCloud2 cloud_blob;
  if (loadPCDFile (argv[1], cloud_blob) < 0)
  {
    std::cerr << "Failed to read test file. Please download `sac_plane_test.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }

  fromPCLPointCloud2 (cloud_blob, *cloud_);
  fromPCLPointCloud2 (cloud_blob, *normals_);

  indices_.resize (cloud_->points.size ());
  for (std::size_t i = 0; i < indices_.size (); ++i) { indices_[i] = int (i); }

  testing::InitGoogleTest (&argc, argv);
  return (RUN_ALL_TESTS ());
}

