private static void TestReordering()
{
Skip.IfNot(TestSettings.TestSuiteSparse, TestSettings.MessageWhenSkippingSuiteSparse);
int order = SparseSymm5by5.Order;
int[] rowIndices = SparseSymm5by5.CscRowIndices;
int[] colOffsets = SparseSymm5by5.CscColOffsets;
int[] permutation = new int[order];
IntPtr common = SuiteSparsePInvokes.CreateCommon(0, 0);
int status = SuiteSparsePInvokes.ReorderAMDUpper(order, rowIndices.Length, rowIndices, colOffsets, permutation,
out int factorNNZ, common);
Assert.True(status == 1, "SuiteSparse reordering failed. A possible reason is the lack of enough available memory");
comparer.AssertEqual(SparseSymm5by5.MatlabPermutationAMD, permutation);
SuiteSparsePInvokes.DestroyCommon(ref common);
}
/// <summary>
/// Find a fill reducing permutation for the sparsity pattern of a symmetric matrix defined by the parameters.
/// The returned permutation is new-to-old, namely reordered[i] = original[permutation[i]].
/// </summary>
/// <param name="order">The number of rows/columns of the symmetric matrix.</param>
/// <param name="nonZerosUpper">The number of (structural) non-zero entries in the upper triangle of the symmetric
/// matrix.</param>
/// <param name="cscRowIndices">Row indices of the upper triangle entries of the symmetric matrix, in Compressed Sparse
/// Columns format. All row indices of the same column must be sorted.</param>
/// <param name="cscColOffsets">Column offsets of the upper triangle entries of the symmetric matrix, in Compressed
/// Sparse Columns format. All column offsets must be sorted.</param>
/// <returns>permutation: An array containing the new-to-old fill reducing permutation.
/// stats: Measuments taken by SuiteSparse during the execution of AMD.</returns>
/// <exception cref="SuiteSparseException">Thrown if SuiteSparse dlls cannot be loaded or if AMD fails.</exception>
public (int[] permutation, ReorderingStatistics stats) FindPermutation(int order, int nonZerosUpper, int[] cscRowIndices,
int[] cscColOffsets)
{
var permutation = new int[order];
IntPtr common = SuiteSparsePInvokes.CreateCommon(0, 0);
if (common == IntPtr.Zero)
{
throw new SuiteSparseException("Failed to initialize SuiteSparse.");
}
int status = SuiteSparsePInvokes.ReorderAMDUpper(order, nonZerosUpper, cscRowIndices, cscColOffsets, permutation,
out int nnzFactor, common);
if (status == 0)
{
throw new SuiteSparseException("AMD failed. This could be caused by the matrix being so large it"
+ " cannot be processed with the available memory.");
}
SuiteSparsePInvokes.DestroyCommon(ref common);
return(permutation, new ReorderingStatistics(nnzFactor, -1));
}
private static void TestCholeskySolver()
{
Skip.IfNot(TestSettings.TestSuiteSparse, TestSettings.MessageWhenSkippingSuiteSparse);
// Define linear system
const int n = 4;
const int nnz = 7;
int[] colOffsets = new int[n + 1] {
0, 1, 2, 5, nnz
};
int[] rowIndices = new int[nnz] {
0, 1, 0, 1, 2, 1, 3
};
double[] values = new double[nnz] {
4.0, 10.0, 2.0, 1.0, 8.0, 3.0, 9.0
};
double[] rhs = new double[n] {
6.0, 14.0, 11.0, 12.0
};
double[] solutionExpected = { 1.0, 1.0, 1.0, 1.0 };
double[] solution = new double[n];
// Solve it using SuiteSparse
IntPtr handle = SuiteSparsePInvokes.CreateCommon(0, 0);
int status = SuiteSparsePInvokes.FactorizeCSCUpper(n, nnz, values, rowIndices, colOffsets, out IntPtr factor, handle);
Assert.True(status == -1);
int nnzFactor = SuiteSparsePInvokes.GetFactorNonZeros(factor);
Console.WriteLine($"Before factorization: nnz = {nnz}");
Console.WriteLine($"After factorization: nnz = {nnzFactor}");
SuiteSparsePInvokes.Solve(0, n, 1, factor, rhs, solution, handle);
comparer.AssertEqual(solutionExpected, solution);
SuiteSparsePInvokes.DestroyFactor(ref factor, handle);
SuiteSparsePInvokes.DestroyCommon(ref handle);
}
