public void TestEmptyAdd(int rows, int columns)
{
var A = new SymbolicColumnStorage(rows, columns, 0, true);
var B = new SymbolicColumnStorage(rows, columns, 0, true);
var C = A.Add(B);
Assert.IsNotNull(C);
}
// Construct matrix C
private static SymbolicColumnStorage ConstructMatrix(SymbolicColumnStorage A, ColumnOrdering order)
{
SymbolicColumnStorage result = null;
// Compute A'
var AT = A.Transpose();
int m = A.RowCount;
int n = A.ColumnCount;
if (order == ColumnOrdering.MinimumDegreeAtPlusA)
{
if (n != m)
{
throw new ArgumentException(Resources.MatrixSquare, "A");
}
// Return A+A'
result = A.Add(AT);
}
else if (order == ColumnOrdering.MinimumDegreeStS)
{
// Drop dense columns from AT
int dense, p, p2 = 0;
// Find dense threshold
dense = Math.Max(16, 10 * (int)Math.Sqrt(n));
dense = Math.Min(n - 2, dense);
var colptr = AT.ColumnPointers;
var rowind = AT.RowIndices;
for (int j = 0; j < m; j++)
{
// Column j of AT starts here.
p = colptr[j];
// New column j starts here.
colptr[j] = p2;
if (colptr[j + 1] - p > dense)
{
// Skip dense column j
continue;
}
for (; p < colptr[j + 1]; p++)
{
rowind[p2++] = rowind[p];
}
}
colptr[m] = p2;
// Return A'*A with no dense rows
result = AT.Multiply(AT.Transpose());
}
else
{
// Return A'*A
result = AT.Multiply(A);
}
// Drop diagonal entries.
result.Keep(KeepOffDiag);
return(result);
}
