public static SparseMatrix SparseMatrix(int rows, int columns, double density, bool symmetric)
{
if (symmetric)
{
return(CreateSparse.RandomSymmetric(rows, density));
}
return(CreateSparse.Random(rows, columns, density));
}
public static IStorageAdapter CreateRandom(int rowCount, int columnCount,
double density, bool symmetric)
{
var A = symmetric ? CreateSparse.RandomSymmetric(rowCount, density) :
CreateSparse.Random(rowCount, columnCount, density);
var norms = ToComplexArray((2 * A.RowNorms(1)).ToArray());
A.FastAddDiagonalMatrix(norms, A);
return(new SparseStorageAdapter(A));
}
public void TestAddDiagonalMatrixNew()
{
var diag = DenseVector.Create(10, 1.0);
var A = CreateSparse.Random(10, 10, 0.8);
A.FastLowerTriangle();
A.SetDiagonal(diag);
var empty = CreateSparse.Zeros(A.RowCount, A.ColumnCount, A.NonZerosCount);
// Add diagonal and save to new matrix.
A.FastAddDiagonalMatrix(diag.Negate().ToArray(), empty);
var d = empty.FastDiagonal();
for (int i = 0; i < 10; i++)
{
Assert.AreEqual(d[i], 0.0);
}
}
/// <summary>
/// Setup test matrices.
/// </summary>
private static void SetupMatrices()
{
var A55 = CreateSparse.Random(5, 5, 0.5);
var A57 = CreateSparse.Random(5, 7, 0.5);
var A75 = CreateSparse.Random(7, 5, 0.5);
var B55 = CreateSparse.Random(5, 5, 0.5);
var B57 = CreateSparse.Random(5, 7, 0.5);
var B75 = CreateSparse.Random(7, 5, 0.5);
// Set all diagonal entries to 1.0.
for (int i = 0; i < 5; i++)
{
A55[i, i] = 1.0;
A57[i, i] = 1.0;
A75[i, i] = 1.0;
B55[i, i] = 1.0;
B57[i, i] = 1.0;
B75[i, i] = 1.0;
}
// Ensure there are no zero rows/columns in A.
A57[4, 5] = 0.1;
A57[4, 6] = 0.2;
A75[5, 4] = 0.1;
A75[6, 4] = 0.2;
TestMatricesA = new Dictionary <int, SparseMatrix>();
TestMatricesB = new Dictionary <int, SparseMatrix>();
TestMatricesA.Add(55, A55);
TestMatricesA.Add(57, A57);
TestMatricesA.Add(75, A75);
TestMatricesB.Add(55, B55);
TestMatricesB.Add(57, B57);
TestMatricesB.Add(75, B75);
}