public void TestAntiSymmetricity()
{
var matrix = new SkewSymmetricSparseMatrix(5);
matrix[1, 3] = 1.0f;
Assert.AreEqual(-1.0f, matrix[3, 1]);
}
[Test()] public void TestCreateMatrix()
{
var matrix1 = new SkewSymmetricSparseMatrix(5);
var matrix2 = matrix1.CreateMatrix(4, 4);
Assert.IsInstanceOf(matrix1.GetType(), matrix2);
}
[Test()] public void TestAntiSymmetricity()
{
var matrix = new SkewSymmetricSparseMatrix(5);
matrix[1, 3] = 1.0f;
Assert.AreEqual(-1.0f, matrix[3, 1]);
}
public void TestNonEmptyEntryIDs()
{
var matrix = new SkewSymmetricSparseMatrix(5);
Assert.AreEqual(0, matrix.NonEmptyEntryIDs.Count);
matrix[3, 1] = 1.0f;
Assert.AreEqual(2, matrix.NonEmptyEntryIDs.Count);
}
///
void InitModel()
{
// create data structure
diff_matrix_like = new SkewSymmetricSparseMatrix(MaxItemID + 1);
freq_matrix_like = new SymmetricSparseMatrix <int>(MaxItemID + 1);
diff_matrix_dislike = new SkewSymmetricSparseMatrix(MaxItemID + 1);
freq_matrix_dislike = new SymmetricSparseMatrix <int>(MaxItemID + 1);
user_average = new double[MaxUserID + 1];
}
[Test()] public void TestNonEmptyEntryIDs()
{
var matrix = new SkewSymmetricSparseMatrix(5);
Assert.AreEqual(0, matrix.NonEmptyEntryIDs.Count);
matrix[3, 1] = 1.0f;
Assert.AreEqual(2, matrix.NonEmptyEntryIDs.Count);
}
public void TestIsSymmetric()
{
var matrix = new SkewSymmetricSparseMatrix(5);
Assert.IsTrue(matrix.IsSymmetric);
matrix[1, 3] = 1.0f;
Assert.IsFalse(matrix.IsSymmetric);
matrix[1, 3] = 0f;
Assert.IsTrue(matrix.IsSymmetric);
}
public void TestGetSet()
{
var matrix = new SkewSymmetricSparseMatrix(5);
matrix[1, 3] = 1.0f;
Assert.AreEqual( 1.0f, matrix[1, 3]);
Assert.AreEqual(-1.0f, matrix[3, 1]);
matrix[4, 1] = -2.0f;
Assert.AreEqual(-2.0f, matrix[4, 1]);
Assert.AreEqual( 2.0f, matrix[1, 4]);
}
[Test()] public void TestIsSymmetric()
{
var matrix = new SkewSymmetricSparseMatrix(5);
Assert.IsTrue(matrix.IsSymmetric);
matrix[1, 3] = 1.0f;
Assert.IsFalse(matrix.IsSymmetric);
matrix[1, 3] = 0f;
Assert.IsTrue(matrix.IsSymmetric);
}
[Test()] public void TestGetSet()
{
var matrix = new SkewSymmetricSparseMatrix(5);
matrix[1, 3] = 1.0f;
Assert.AreEqual(1.0f, matrix[1, 3]);
Assert.AreEqual(-1.0f, matrix[3, 1]);
matrix[4, 1] = -2.0f;
Assert.AreEqual(-2.0f, matrix[4, 1]);
Assert.AreEqual(2.0f, matrix[1, 4]);
}
[Test()] public void TestNumberOfNonEmptyEntries()
{
var matrix = new SkewSymmetricSparseMatrix(5);
Assert.AreEqual(0, matrix.NumberOfNonEmptyEntries);
matrix[3, 1] = 1.0f;
Assert.AreEqual(2, matrix.NumberOfNonEmptyEntries);
matrix[3, 1] = 2.0f;
Assert.AreEqual(2, matrix.NumberOfNonEmptyEntries);
matrix[3, 3] = 1.0f;
Assert.AreEqual(3, matrix.NumberOfNonEmptyEntries);
}
///
public override void LoadModel(string file)
{
InitModel();
using ( StreamReader reader = Recommender.GetReader(file, this.GetType()) )
{
var global_average = double.Parse(reader.ReadLine(), CultureInfo.InvariantCulture);
var diff_matrix = (SkewSymmetricSparseMatrix) IMatrixUtils.ReadMatrix(reader, this.diff_matrix); // TODO take symmetric matrix into account for smaller model files
var freq_matrix = (SymmetricSparseMatrix<int>) IMatrixUtils.ReadMatrix(reader, this.freq_matrix); // TODO take anti-symmetric matrix into account for smaller model files
// assign new model
this.global_average = global_average;
this.diff_matrix = diff_matrix;
this.freq_matrix = freq_matrix;
}
}
///
public override void LoadModel(string file)
{
InitModel();
using (StreamReader reader = Recommender.GetReader(file, this.GetType()))
{
var global_average = double.Parse(reader.ReadLine(), CultureInfo.InvariantCulture);
var diff_matrix = (SkewSymmetricSparseMatrix)IMatrixUtils.ReadMatrix(reader, this.diff_matrix); // TODO take symmetric matrix into account for smaller model files
var freq_matrix = (SymmetricSparseMatrix <int>)IMatrixUtils.ReadMatrix(reader, this.freq_matrix); // TODO take anti-symmetric matrix into account for smaller model files
// assign new model
this.global_average = global_average;
this.diff_matrix = diff_matrix;
this.freq_matrix = freq_matrix;
}
}
///
public override void LoadModel(string file)
{
InitModel();
using ( StreamReader reader = Model.GetReader(file, this.GetType()) )
{
var global_average = float.Parse(reader.ReadLine(), CultureInfo.InvariantCulture);
var diff_matrix = (SkewSymmetricSparseMatrix) reader.ReadMatrix(this.diff_matrix);
var freq_matrix = (SymmetricSparseMatrix<int>) reader.ReadMatrix(this.freq_matrix);
// assign new model
this.global_average = global_average;
this.diff_matrix = diff_matrix;
this.freq_matrix = freq_matrix;
}
}
///
public override void LoadModel(string file)
{
InitModel();
using (StreamReader reader = Model.GetReader(file, this.GetType()))
{
var global_average = float.Parse(reader.ReadLine(), CultureInfo.InvariantCulture);
var diff_matrix = (SkewSymmetricSparseMatrix)reader.ReadMatrix(this.diff_matrix);
var freq_matrix = (SymmetricSparseMatrix <int>)reader.ReadMatrix(this.freq_matrix);
// assign new model
this.global_average = global_average;
this.diff_matrix = diff_matrix;
this.freq_matrix = freq_matrix;
}
}
///
public override void LoadModel(string file)
{
InitModel();
using (StreamReader reader = Recommender.GetReader(file, this.GetType()))
{
var global_average = double.Parse(reader.ReadLine(), CultureInfo.InvariantCulture);
var diff_matrix_like = (SkewSymmetricSparseMatrix)IMatrixUtils.ReadMatrix(reader, this.diff_matrix_like);
var freq_matrix_like = (SymmetricSparseMatrix <int>)IMatrixUtils.ReadMatrix(reader, this.freq_matrix_like);
var diff_matrix_dislike = (SkewSymmetricSparseMatrix)IMatrixUtils.ReadMatrix(reader, this.diff_matrix_dislike);
var freq_matrix_dislike = (SymmetricSparseMatrix <int>)IMatrixUtils.ReadMatrix(reader, this.freq_matrix_dislike);
var user_average = VectorUtils.ReadVector(reader);
// assign new model
this.global_average = global_average;
this.diff_matrix_like = diff_matrix_like;
this.freq_matrix_like = freq_matrix_like;
this.diff_matrix_dislike = diff_matrix_dislike;
this.freq_matrix_dislike = freq_matrix_dislike;
this.user_average = user_average;
}
}
public void TestNumberOfNonEmptyEntries()
{
var matrix = new SkewSymmetricSparseMatrix(5);
Assert.AreEqual(0, matrix.NumberOfNonEmptyEntries);
matrix[3, 1] = 1.0f;
Assert.AreEqual(2, matrix.NumberOfNonEmptyEntries);
matrix[3, 1] = 2.0f;
Assert.AreEqual(2, matrix.NumberOfNonEmptyEntries);
matrix[3, 3] = 0f;
Assert.AreEqual(2, matrix.NumberOfNonEmptyEntries);
}
void InitModel()
{
diff_matrix = new SkewSymmetricSparseMatrix(MaxItemID + 1);
freq_matrix = new SymmetricSparseMatrix<int>(MaxItemID + 1);
}
void InitModel()
{
diff_matrix = new SkewSymmetricSparseMatrix(MaxItemID + 1);
freq_matrix = new SymmetricSparseMatrix <int>(MaxItemID + 1);
}
[Test()] public void TestNumberOfColumns()
{
var matrix = new SkewSymmetricSparseMatrix(3);
Assert.AreEqual(3, matrix.NumberOfColumns);
}
///
void InitModel()
{
// create data structure
diff_matrix_like = new SkewSymmetricSparseMatrix(MaxItemID + 1);
freq_matrix_like = new SymmetricSparseMatrix<int>(MaxItemID + 1);
diff_matrix_dislike = new SkewSymmetricSparseMatrix(MaxItemID + 1);
freq_matrix_dislike = new SymmetricSparseMatrix<int>(MaxItemID + 1);
user_average = new double[MaxUserID + 1];
}
public void TestCreateMatrix()
{
var matrix1 = new SkewSymmetricSparseMatrix(5);
var matrix2 = matrix1.CreateMatrix(4, 4);
Assert.IsInstanceOfType(matrix1.GetType(), matrix2);
}
///
public override void LoadModel(string file)
{
InitModel();
using ( StreamReader reader = Recommender.GetReader(file, this.GetType()) )
{
var global_average = double.Parse(reader.ReadLine(), CultureInfo.InvariantCulture);
var diff_matrix_like = (SkewSymmetricSparseMatrix) IMatrixUtils.ReadMatrix(reader, this.diff_matrix_like);
var freq_matrix_like = (SymmetricSparseMatrix<int>) IMatrixUtils.ReadMatrix(reader, this.freq_matrix_like);
var diff_matrix_dislike = (SkewSymmetricSparseMatrix) IMatrixUtils.ReadMatrix(reader, this.diff_matrix_dislike);
var freq_matrix_dislike = (SymmetricSparseMatrix<int>) IMatrixUtils.ReadMatrix(reader, this.freq_matrix_dislike);
var user_average = VectorUtils.ReadVector(reader);
// assign new model
this.global_average = global_average;
this.diff_matrix_like = diff_matrix_like;
this.freq_matrix_like = freq_matrix_like;
this.diff_matrix_dislike = diff_matrix_dislike;
this.freq_matrix_dislike = freq_matrix_dislike;
this.user_average = user_average;
}
}
public void TestNumberOfRows()
{
var matrix = new SkewSymmetricSparseMatrix(3);
Assert.AreEqual(3, matrix.NumberOfRows);
}