GeneralTests.cpp

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// kate: replace-tabs off; indent-width 4; indent-mode normal
// vim: ts=4:sw=4:noexpandtab
/*

Copyright (c) 2010--2012,
François Pomerleau and Stephane Magnenat, ASL, ETHZ, Switzerland
You can contact the authors at <f dot pomerleau at gmail dot com> and
<stephane at magnenat dot net>

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#include "../../utest.h"

using namespace std;
using namespace PointMatcherSupport;

//---------------------------
// Test ICP with all existing filters.

// Algorithm:
// 1. Iterate over all yaml files in
//    libpointmatcher/examples/data/icp_data, each file tests ICP
//    with one or more filters.
// 2. Run ICP with the given yaml file. The filters in the yaml
//    file are applied along the way.
// 3. Write the obtained ICP transform to disk, to the same directory,
//    with file extension .cur_trans (for easy future comparisons).
// 4. Load the reference (known as correct) ICP transform from disk,
//    from the same directory, with file extension .ref_trans.
// 5. See if the current and reference transforms are equal.

// To update an existing test or add a new test, simply add/modify
// the desired yaml file, run the tests (they may fail this time), then
// copy the (just written) desired current transform file on top of the
// corresponding reference transform file. Run the tests again. This
// time they will succeed.
//---------------------------

// Find the median coefficient of a matrix
double median_coeff(Eigen::MatrixXf& A){
  Eigen::Map<Eigen::VectorXf> v(A.data(),A.size());
  std::sort(v.data(), v.data() + v.size());
  return v[v.size()/2];
}

TEST(icpTest, icpTest)
{
        DP ref  = DP::load(dataPath + "cloud.00000.vtk");
        DP data = DP::load(dataPath + "cloud.00001.vtk");

        namespace fs = boost::filesystem;
        fs::path config_dir(dataPath + "icp_data");
        EXPECT_TRUE( fs::exists(config_dir) && fs::is_directory(config_dir) );

        fs::directory_iterator end_iter;
        for( fs::directory_iterator d(config_dir); d != end_iter; ++d)
        {
                if (!fs::is_regular_file(d->status()) ) continue;

                std::cout << "Testing file " << d->path().string() << std::endl;
                // Load config file, and form ICP object
                PM::ICP icp;
                std::string config_file = d->path().string();
                if (fs::extension(config_file) != ".yaml") continue;
                std::ifstream ifs(config_file.c_str());
                EXPECT_NO_THROW(icp.loadFromYaml(ifs)) << "This error was caused by the test file:" << endl << "   " << config_file;

                // Compute current ICP transform
                PM::TransformationParameters curT = icp(data, ref);

                // Write current transform to disk (to easily compare it
                // with reference transform offline)
                fs::path cur_file = d->path();
                cur_file.replace_extension(".cur_trans");
                //std::cout << "Writing: " << cur_file << std::endl;
                std::ofstream otfs(cur_file.c_str());
                otfs.precision(16);
                otfs << curT;
                otfs.close();
                
                // Load reference transform
                fs::path ref_file = d->path();
                ref_file.replace_extension(".ref_trans");
                PM::TransformationParameters refT = 0*curT;
                //std::cout << "Reading: " << ref_file << std::endl;
                std::ifstream itfs(ref_file.c_str());
                EXPECT_TRUE(itfs.good()) << "Could not find " << ref_file
                                         << ". If this is the first time this test is run, "
                                         << "create it as a copy of " << cur_file; 
                
                for (int row = 0; row < refT.cols(); row++)
                {
                        for (int col = 0; col < refT.cols(); col++)
                        {
                                itfs >>refT(row, col);
                        }
                }

                // Dump the reference transform and current one
                //std::cout.precision(17);
                //std::cout << "refT:\n" << refT << std::endl;
                //std::cout << "curT:\n" << curT << std::endl;

                // We need to compare the stored icp transform vs the computed one.
                // Since the icp solution is not unique, they may differ a lot.
                // Yet, the point of icp is
                // curT*data = ref, and refT*data = ref
                // so no matter what, the difference curT*data - refT*data
                // must be small, which is what we will test for.

                // Find the median absolute difference between curT*data and refT*data
                Eigen::MatrixXf AbsDiff = (curT*data.features - refT*data.features).array().abs();
                double median_diff = median_coeff(AbsDiff);

                // Find the median absolute value of curT*data
                Eigen::MatrixXf Data = (curT*data.features).array().abs();
                double median_data = median_coeff(Data);

                // Find the relative error
                double rel_err = median_diff/median_data;

                // A relative error of 3% is probably acceptable. 
                // FIXME(ynava) Original value of 3% was replaced by 5% due to randomly failing unit test.
                EXPECT_LT(rel_err, 0.05) << "This error was caused by the test file:" << endl << "   " << config_file;
        }
}

TEST(icpTest, icpSingular)
{
        // Here we test point-to-plane ICP where the point clouds underdetermine transformation
        // This situation requires special treatment in the algorithm.

        // create a x-y- planar grid point cloud in points
        const size_t nX = 10, nY = nX;
        Eigen::MatrixXf points(4, nX * nY);
        const float d = 0.1;
        const float oX = -(nX * d / 2), oY = -(nY * d / 2);

        for(size_t x = 0; x < nX; x++){
                for(size_t y = 0; y < nY; y++){
                        points.col( x * nY + y) << d * x + oX, d * y + oY, 0, 1;
                }
        }

        DP pts0;
        pts0.features = points;
        DP pts1;
        points.row(2).setOnes();
        pts1.features = points; // pts1 is pts0 shifted by one in z-direction

        PM::ICP icp;
        std::string config_file = dataPath + "default-identity.yaml";
        EXPECT_TRUE(boost::filesystem::exists(config_file));

        std::ifstream ifs(config_file.c_str());
        EXPECT_NO_THROW(icp.loadFromYaml(ifs)) << "This error was caused by the test file:" << endl << "   " << config_file;

        // Compute ICP transform
        PM::TransformationParameters curT = icp(pts0, pts1);

        PM::Matrix expectedT = PM::Matrix::Identity(4,4);
        expectedT(2,3) = 1;
        EXPECT_TRUE(expectedT.isApprox(curT)) << "Expecting pure translation in z-direction of unit distance." << endl;
}

TEST(icpTest, icpIdentity)
{
        // Here we test point-to-plane ICP where we expect the output transform to be 
        // the identity. This situation requires special treatment in the algorithm.
        const float epsilon = 0.0001;
        
        DP pts0 = DP::load(dataPath + "cloud.00000.vtk");
        DP pts1 = DP::load(dataPath + "cloud.00000.vtk");

        PM::ICP icp;
        std::string config_file = dataPath + "default-identity.yaml";
        EXPECT_TRUE(boost::filesystem::exists(config_file));

        std::ifstream ifs(config_file.c_str());
        EXPECT_NO_THROW(icp.loadFromYaml(ifs)) << "This error was caused by the test file:" << endl << "   " << config_file;

        // Compute current ICP transform
        PM::TransformationParameters curT = icp(pts0, pts1);

        EXPECT_TRUE(curT.isApprox(PM::Matrix::Identity(4, 4), epsilon)) << "Expecting identity transform." << endl;
}

TEST(icpTest, similarityTransform)
{
        // Here we test similarity point-to-point ICP.
        
        DP pts0 = DP::load(dataPath + "car_cloud400.csv");
        DP pts1 = DP::load(dataPath + "car_cloud400_scaled.csv");

        PM::ICP icp;
        std::string config_file = dataPath + "icp_data/defaultSimilarityPointToPointMinDistDataPointsFilter.yaml";
        EXPECT_TRUE(boost::filesystem::exists(config_file));

        std::ifstream ifs(config_file.c_str());
        EXPECT_NO_THROW(icp.loadFromYaml(ifs)) << "This error was caused by the test file:" << endl << "   " << config_file;

        // Compute current ICP transform
        PM::TransformationParameters curT = icp(pts0, pts1);

        // We know the scale we're looking for is 1.04.
        double scale = pow(curT.determinant(), 1.0/3.0);
        EXPECT_LT( std::abs(scale - 1.04), 0.001)
          << "Expecting the similarity transform scale to be 1.04.";
}

TEST(icpTest, icpSequenceTest)
{
        DP pts0 = DP::load(dataPath + "cloud.00000.vtk");
        DP pts1 = DP::load(dataPath + "cloud.00001.vtk");
        DP pts2 = DP::load(dataPath + "cloud.00002.vtk");
        
        PM::TransformationParameters Ticp = PM::Matrix::Identity(4,4);

        PM::ICPSequence icpSequence;

        std::ifstream ifs((dataPath + "default.yaml").c_str());
        icpSequence.loadFromYaml(ifs);

        EXPECT_FALSE(icpSequence.hasMap());

        DP map = icpSequence.getPrefilteredInternalMap();
        EXPECT_EQ(map.getNbPoints(), 0u);
        EXPECT_EQ(map.getHomogeneousDim(), 0u);
        
        map = icpSequence.getPrefilteredMap();
        EXPECT_EQ(map.getNbPoints(), 0u);
        EXPECT_EQ(map.getHomogeneousDim(), 0u);

        icpSequence.setMap(pts0);
        map = icpSequence.getPrefilteredInternalMap();
        EXPECT_LE(map.getNbPoints(), pts0.getNbPoints());
        EXPECT_GT(map.getNbPoints(), 0u);
        EXPECT_EQ(map.getHomogeneousDim(), pts0.getHomogeneousDim());

        Ticp = icpSequence(pts1);
        map = icpSequence.getPrefilteredMap();
        EXPECT_LE(map.getNbPoints(), pts0.getNbPoints());
        EXPECT_GT(map.getNbPoints(), 0u);
        EXPECT_EQ(map.getHomogeneousDim(), pts0.getHomogeneousDim());
        
        Ticp = icpSequence(pts2);
        map = icpSequence.getPrefilteredMap();
        EXPECT_LE(map.getNbPoints(), pts0.getNbPoints());
        EXPECT_GT(map.getNbPoints(), 0u);
        EXPECT_EQ(map.getHomogeneousDim(), pts0.getHomogeneousDim());

        icpSequence.clearMap();
        map = icpSequence.getPrefilteredInternalMap();
        EXPECT_EQ(map.getNbPoints(), 0u);
        EXPECT_EQ(map.getHomogeneousDim(), 0u);
}

// Utility classes
class GenericTest: public IcpHelper
{

public:

        // Will be called for every tests
        virtual void SetUp()
        {
                icp.setDefault();
                // Uncomment for consol outputs
                //setLogger(PM::get().LoggerRegistrar.create("FileLogger"));
        }

        // Will be called for every tests
        virtual void TearDown()
        {       
        }
};

//---------------------------
// Generic tests
//---------------------------

TEST_F(GenericTest, ICP_default)
{
        validate2dTransformation();
        validate3dTransformation();
}