public void SparseSample_ComplexFloat_Identity()
{
NumericsConfiguration.NativeProviderPath = @"C:\Program Files (x86)\Extreme Optimization\Numerical Libraries for .NET\bin\Net40";
NumericsConfiguration.Providers.RegisterSinglePrecisionProvider();
NumericsConfiguration.AutoLoadNativeProviders = true;
CoreImplementations <float> .UseNative();
Console.WriteLine(CoreImplementations <Complex <float> > .LinearAlgebra.Name);
SparseCompressedColumnMatrix <Complex <float> > matrixA = Matrix.CreateSparse <Complex <float> >(3, 3);
matrixA.SetValue(new Complex <float>(1, 0), 0, 0);
matrixA.SetValue(new Complex <float>(1, 0), 1, 1);
matrixA.SetValue(new Complex <float>(1, 0), 2, 2);
Vector <Complex <float> > vectorB = Vector.Create(new Complex <float>(1.0f, 0), new Complex <float>(2.0f, 0), new Complex <float>(3.0f, 0));
IterativeSparseSolver <Complex <float> > solver = new BiConjugateGradientSolver <Complex <float> >(matrixA);
DenseVector <Complex <float> > resultVector = solver.Solve(vectorB);
Console.WriteLine("Result: {0}", resultVector);
Console.WriteLine("Solved in {0} iterations.", solver.IterationsNeeded);
Console.WriteLine("Estimated error: {0}", solver.SolutionReport.Error);
// With incomplete LU preconditioner
solver.Preconditioner = new IncompleteLUPreconditioner <Complex <float> >(matrixA);
resultVector = solver.Solve(vectorB);
Console.WriteLine("Result: {0}", resultVector);
Console.WriteLine("Solved in {0} iterations.", solver.IterationsNeeded);
Console.WriteLine("Estimated error: {0}", solver.EstimatedError);
}
public void SimpleSample_Double_Identity()
{
Console.WriteLine(CoreImplementations <Complex <float> > .LinearAlgebra.Name);
// We load a sparse matrix and right-hand side from a data file:
SparseCompressedColumnMatrix <double> matrixA = SparseCompressedColumnMatrix <double> .CreateIdentity(3);
Vector <double> vectorB = Vector.Create(1.0, 2.0, 3.0);
IterativeSparseSolver <double> solver = new BiConjugateGradientSolver <double>(matrixA);
var resultVector = solver.Solve(vectorB);
Console.WriteLine("Result: {0}", resultVector);
Console.WriteLine("Solved in {0} iterations.", solver.IterationsNeeded);
Console.WriteLine("Estimated error: {0}", solver.SolutionReport.Error);
// With incomplete LU preconditioner
solver.Preconditioner = new IncompleteLUPreconditioner <double>(matrixA);
resultVector = solver.Solve(vectorB);
Console.WriteLine("Result: {0}", resultVector);
Console.WriteLine("Solved in {0} iterations.", solver.IterationsNeeded);
Console.WriteLine("Estimated error: {0}", solver.EstimatedError);
}
public void ClusterNmf(int numClusters, string path)
{
var data = _dataset.AllSamples.Select(ir => new
{
Row = _userMapping.ToInternalID(ir.User.Id),
Col = _itemMapping.ToInternalID(ir.Item.Id),
Value = Convert.ToDouble(ir.Rating)
}).ToList();
File.WriteAllLines(path + ".data", data.Select(d => string.Format("{0},{1},{2}", d.Row, d.Col, d.Value)).ToList());
var rows = data.Select(d => d.Row).ToArray();
var colums = data.Select(d => d.Col).ToArray();
var values = data.Select(d => d.Value).ToArray();
int numRows = rows.Max();
int numCols = colums.Max();
Console.WriteLine("Creating sparse matrix...\nNum users: {0} Num items: {1} Num ratings: {2}",
numRows, numCols, values.Count());
SparseCompressedColumnMatrix sparseMatrix = Matrix.CreateSparse(numRows + 1, numCols + 1, rows, colums, values);
var nmf = new NonNegativeMatrixFactorization(sparseMatrix, numClusters);
Console.WriteLine("Decomposing...");
nmf.Decompose();
Console.WriteLine("Writing decompose matrixes...");
var lf = nmf.LeftFactor.ToArray(MatrixElementOrder.RowMajor);
var rf = nmf.RightFactor.ToArray(MatrixElementOrder.RowMajor);
var lfWriter = new StreamWriter(path + ".lf");
var rfWriter = new StreamWriter(path + ".rf");
for (int i = 0; i < lf.Length; i++)
{
if (i != 0 && i % numClusters == 0)
{
lfWriter.WriteLine();
}
lfWriter.Write(lf[i] + " ");
}
lfWriter.Close();
for (int i = 0; i < rf.Length; i++)
{
if (i != 0 && i % numClusters == 0)
{
rfWriter.WriteLine();
}
rfWriter.Write(rf[i] + " ");
}
rfWriter.Close();
Console.WriteLine("Finished writing.");
}
