VXDTFFilterTest Namespace Reference

helper struct for testing purposes providing the necessary coordinate accessors NOTE: this is only temporaryly stored in a separate header! More...

Classes
class	DecorrelationMatrixTest
	Test Class. More...
struct	TestSpacePoint
	Helper struct for SpacePoint Tests. More...

Typedefs
using	TestMatrix = Eigen::Matrix< double, 3, 3, Eigen::RowMajor >
	typedef for less typing effort

Functions
	TEST_F (DecorrelationMatrixTest, TestSetUp)
	basic test of correct SetUp
	TEST_F (DecorrelationMatrixTest, TestConstructor)
	test if the default constructor initializes the internal matrix to the identity matrix
	TEST_F (DecorrelationMatrixTest, TestCalculateDecorrMatrix)
	test if the decorrelation matrix is correctly calculated from a given covariance matrix
	TEST_F (DecorrelationMatrixTest, TestCaluclateCovMatrix)
	test if the calculation of the covariance matrix is correct
	TEST_F (DecorrelationMatrixTest, TestDecorrelationMatrixIO)
	test if the IO methods work as advertised.

Variables
const std::vector< double >	v1
	MATLAB generated random vector.
const std::vector< double >	v2
	MATLAB generated random vector.
const std::vector< double >	v3
	MATLAB generated random vector.

Detailed Description

helper struct for testing purposes providing the necessary coordinate accessors NOTE: this is only temporaryly stored in a separate header!

Typedef Documentation

TestMatrix

using TestMatrix = Eigen::Matrix<double, 3, 3, Eigen::RowMajor>

typedef for less typing effort

Definition at line 25 of file decorrelationMatrix.cc.

Function Documentation

TEST_F() [1/5]

TEST_F	(	DecorrelationMatrixTest	,
		TestCalculateDecorrMatrix
	)

test if the decorrelation matrix is correctly calculated from a given covariance matrix

Definition at line 124 of file decorrelationMatrix.cc.

  {
    DecorrelationMatrix<3> matrix{};
    matrix.calculateDecorrMatrix(m_testData);
 
    // test that the size of the input and the output vector does not change
    std::vector<double> testVec = { m_testData[0][0], m_testData[1][0], m_testData[2][0] };
    auto outputVec = matrix.decorrelate(testVec);
    EXPECT_EQ(testVec.size(), outputVec.size());
 
    // test that the covariance matrix of the decorrelated test data is indeed the identity (at least numerically)
    auto outputData = matrix.decorrelate(m_testData);
    auto covMat = calculateCovMatrix(outputData);
    for (auto i = 0; i < covMat.outerSize(); ++i) {
      for (auto j = 0; j < covMat.innerSize(); ++j) {
        if (i == j) {
          EXPECT_FLOAT_EQ(m_identity(i, j), covMat(i, j)); // the diagonal should be ones, even with considering numerics
        } else {
          EXPECT_NEAR(m_identity(i, j), covMat(i, j), 1e-15); // EXPECT_FLOAT_EQ is to stringent for the numerical calculations
        }
      }
    }
 
    // COULDDO: test non-normalized version as well
  }

TEST_F() [2/5]

TEST_F	(	DecorrelationMatrixTest	,
		TestCaluclateCovMatrix
	)

test if the calculation of the covariance matrix is correct

Definition at line 151 of file decorrelationMatrix.cc.

  {
    // test if the correct covariance matrix gets calculated
    const TestMatrix covMat = calculateCovMatrix(m_testData);
    EXPECT_EQ(covMat.outerSize(), 3);
    EXPECT_EQ(covMat.innerSize(), 3);
    for (auto i = 0; i < covMat.outerSize(); ++i) {
      for (auto j = 0; j < covMat.innerSize(); ++j) {
        EXPECT_DOUBLE_EQ(m_covMatrix(i, j), covMat(i, j));
      }
    }
 
    // check if an identity matrix is returned if the input is incorrect
    auto badTestData = m_testData;
    badTestData[0].erase(badTestData[0].begin()); // remove first element from the first vector in the array
    const TestMatrix badMat = calculateCovMatrix(badTestData);
    EXPECT_EQ(3, badMat.outerSize());
    EXPECT_EQ(3, badMat.innerSize());
    EXPECT_TRUE(badMat == m_identity);
  }

TEST_F() [3/5]

TEST_F	(	DecorrelationMatrixTest	,
		TestConstructor
	)

test if the default constructor initializes the internal matrix to the identity matrix

Definition at line 111 of file decorrelationMatrix.cc.

  {
    DecorrelationMatrix<3> matrix{};
    const auto& internalMatrix = matrix.getMatrix();
 
    for (auto i = 0; i < internalMatrix.outerSize(); ++i) {
      for (auto j = 0; j < internalMatrix.innerSize(); ++j) {
        EXPECT_DOUBLE_EQ(m_identity(i, j), internalMatrix(i, j));
      }
    }
  }

TEST_F() [4/5]

TEST_F	(	DecorrelationMatrixTest	,
		TestDecorrelationMatrixIO
	)

test if the IO methods work as advertised.

First write to and then read in again from a temporary file and then compare the written out and read in matrix

Definition at line 175 of file decorrelationMatrix.cc.

  {
    const char* filename = "tmp_matrix_testoutput.dat";
 
    ofstream ofs(filename);
    DecorrelationMatrix<3> covMatrix(m_covMatrix);
    ofs << covMatrix.print() << std::endl;
    ofs.close();
 
    ifstream ifs(filename);
    DecorrelationMatrix<3> inMatrix{};
    EXPECT_TRUE(inMatrix.readFromStream(ifs));
    ifs.close();
 
    const TestMatrix& inMat = inMatrix.getMatrix();
    for (auto i = 0; i < m_covMatrix.outerSize(); ++i) {
      for (auto j = 0; j < m_covMatrix.innerSize(); ++j) {
        EXPECT_DOUBLE_EQ(m_covMatrix(i, j), inMat(i, j));
      }
    }
 
    ASSERT_EQ(0, remove(filename)); // assert that the temporarily created file gets deleted again
  }

TEST_F() [5/5]

TEST_F	(	DecorrelationMatrixTest	,
		TestSetUp
	)

basic test of correct SetUp

Definition at line 104 of file decorrelationMatrix.cc.

  {
    EXPECT_EQ(3, m_testData.size());
    for (const auto& vec : m_testData) { EXPECT_EQ(10, vec.size()); }
  }

Variable Documentation

v1

const std::vector<double> v1

Initial value:

= {
    0.537667139546100,
    1.833885014595086,
    -2.258846861003648,
    0.862173320368121,
    0.318765239858981,
    -1.307688296305273,
    -0.433592022305684,
    0.342624466538650,
    3.578396939725760,
    2.769437029884877
  }

MATLAB generated random vector.

Definition at line 28 of file decorrelationMatrix.cc.

v2

const std::vector<double> v2

Initial value:

= {
    -1.349886940156521,
      3.034923466331855,
      0.725404224946106,
      -0.063054873189656,
      0.714742903826096,
      -0.204966058299775,
      -0.124144348216312,
      1.489697607785465,
      1.409034489800479,
      1.417192413429614
    }

MATLAB generated random vector.

Definition at line 42 of file decorrelationMatrix.cc.

v3

const std::vector<double> v3

Initial value:

= {
    0.671497133608080,
    -1.207486922685038,
    0.717238651328838,
    1.630235289164729,
    0.488893770311789,
    1.034693009917860,
    0.726885133383238,
    -0.303440924786016,
    0.293871467096658,
    -0.787282803758638
  }

MATLAB generated random vector.

Definition at line 56 of file decorrelationMatrix.cc.