/// <summary>
        /// find strongly connected components of A
        /// </summary>
        /// <param name="A"></param>
        /// <param name="n"></param>
        /// <returns></returns>
        internal static StronglyConnectedComponents Generate(SymbolicColumnStorage A, int n)
        {
            // matrix A temporarily modified, then restored

            int i, k, b, nb = 0, top;

            int[] xi, p, r, Ap, ATp;

            var AT = A.Transpose(); // AT = A'

            Ap  = A.ColumnPointers;
            ATp = AT.ColumnPointers;

            xi = new int[2 * n + 1];                       // get workspace

            var D = new StronglyConnectedComponents(n, 0); // allocate result

            p = D.p;
            r = D.r;

            top = n;
            for (i = 0; i < n; i++) // first dfs(A) to find finish times (xi)
            {
                if (!(Ap[i] < 0))
                {
                    top = GraphHelper.DepthFirstSearch(i, A.ColumnPointers, A.RowIndices, top, xi, xi, n, null);
                }
            }
            for (i = 0; i < n; i++)
            {
                //CS_MARK(Ap, i);
                Ap[i] = -(Ap[i]) - 2; // restore A; unmark all nodes
            }
            top = n;
            nb  = n;
            for (k = 0; k < n; k++) // dfs(A') to find strongly connnected comp
            {
                i = xi[k];          // get i in reverse order of finish times
                if (ATp[i] < 0)
                {
                    continue;  // skip node i if already ordered
                }
                r[nb--] = top; // node i is the start of a component in p
                top     = GraphHelper.DepthFirstSearch(i, AT.ColumnPointers, AT.RowIndices, top, p, xi, n, null);
            }
            r[nb] = 0; // first block starts at zero; shift r up
            for (k = nb; k <= n; k++)
            {
                r[k - nb] = r[k];
            }
            D.nb = nb = n - nb;      // nb = # of strongly connected components
            for (b = 0; b < nb; b++) // sort each block in natural order
            {
                for (k = r[b]; k < r[b + 1]; k++)
                {
                    xi[p[k]] = b;
                }
            }
            for (b = 0; b <= nb; b++)
            {
                xi[n + b] = r[b];
            }
            for (i = 0; i < n; i++)
            {
                p[xi[n + xi[i]]++] = i;
            }

            Array.Resize(ref D.r, nb + 1);

            return(D);
        }
Esempio n. 2
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        /// <summary>
        /// Compute coarse and then fine Dulmage-Mendelsohn decomposition. seed
        /// optionally selects a randomized algorithm.
        /// </summary>
        /// <param name="matrix">column-compressed matrix</param>
        /// <param name="seed">0: natural, -1: reverse, random order otherwise</param>
        /// <returns>Dulmage-Mendelsohn analysis</returns>
        public static DulmageMendelsohn Generate <T>(CompressedColumnStorage <T> matrix, int seed = 0)
            where T : struct, IEquatable <T>, IFormattable
        {
            int i, j, k, cnz, nc, nb1, nb2;

            int[] Cp, ps, rs;
            bool  ok;

            // We are not interested in the actual matrix values.
            var A = SymbolicColumnStorage.Create(matrix);

            // Maximum matching
            int m = A.RowCount;
            int n = A.ColumnCount;

            var result = new DulmageMendelsohn(m, n); // allocate result

            int[] p  = result.p;
            int[] q  = result.q;
            int[] r  = result.r;
            int[] s  = result.s;
            int[] cc = result.cc;
            int[] rr = result.rr;

            int[] jimatch = MaximumMatching.Generate(A, seed); // max transversal

            if (jimatch == null)
            {
                return(null);
            }

            // Coarse decomposition
            for (j = 0; j < n; j++)
            {
                s[j] = -1;                     // unmark all cols for bfs
            }
            for (i = 0; i < m; i++)
            {
                r[i] = -1;                                                   // unmark all rows for bfs
            }
            result.BreadthFirstSearch(A, n, r, s, q, jimatch, m, 0, 1);      // find C1, R1 from C0*/
            ok = result.BreadthFirstSearch(A, m, s, r, p, jimatch, 0, m, 3); // find R3, C3 from R0*/

            if (!ok)
            {
                return(null);
            }

            result.Unmatched(n, s, q, cc, 0);                      // unmatched set C0
            result.Matched(n, s, jimatch, m, p, q, cc, rr, 1, 1);  // set R1 and C1
            result.Matched(n, s, jimatch, m, p, q, cc, rr, 2, -1); // set R2 and C2
            result.Matched(n, s, jimatch, m, p, q, cc, rr, 3, 3);  // set R3 and C3
            result.Unmatched(m, r, p, rr, 3);                      // unmatched set R0

            // Fine decomposition
            int[] pinv = Permutation.Invert(p); // pinv=p'

            var C = SymbolicColumnStorage.Create(matrix);

            A.Permute(pinv, q, C); // C=A(p,q) (it will hold A(R2,C2))

            Cp = C.ColumnPointers;
            nc = cc[3] - cc[2]; // delete cols C0, C1, and C3 from C
            if (cc[2] > 0)
            {
                for (j = cc[2]; j <= cc[3]; j++)
                {
                    Cp[j - cc[2]] = Cp[j];
                }
            }
            C.Reshape(-1, nc);
            if (rr[2] - rr[1] < m) // delete rows R0, R1, and R3 from C
            {
                RowPrune(C, nc, rr);
                cnz = Cp[nc];
                int[] Ci = C.RowIndices;
                if (rr[1] > 0)
                {
                    for (k = 0; k < cnz; k++)
                    {
                        Ci[k] -= rr[1];
                    }
                }
            }
            C.Reshape(nc, -1);
            var scc = StronglyConnectedComponents.Generate(C, nc); // find strongly connected components of C*/

            // Combine coarse and fine decompositions
            ps  = scc.p;  // C(ps,ps) is the permuted matrix
            rs  = scc.r;  // kth block is rs[k]..rs[k+1]-1
            nb1 = scc.nb; // # of blocks of A(R2,C2)
            for (k = 0; k < nc; k++)
            {
                s[k] = q[ps[k] + cc[2]];
            }
            for (k = 0; k < nc; k++)
            {
                q[k + cc[2]] = s[k];
            }
            for (k = 0; k < nc; k++)
            {
                r[k] = p[ps[k] + rr[1]];
            }
            for (k = 0; k < nc; k++)
            {
                p[k + rr[1]] = r[k];
            }
            nb2  = 0; // create the fine block partitions
            r[0] = s[0] = 0;
            if (cc[2] > 0)
            {
                nb2++;                  // leading coarse block A (R1, [C0 C1])
            }
            for (k = 0; k < nb1; k++)   // coarse block A (R2,C2)
            {
                r[nb2] = rs[k] + rr[1]; // A (R2,C2) splits into nb1 fine blocks
                s[nb2] = rs[k] + cc[2];
                nb2++;
            }
            if (rr[2] < m)
            {
                r[nb2] = rr[2]; // trailing coarse block A ([R3 R0], C3)
                s[nb2] = cc[3];
                nb2++;
            }
            r[nb2]    = m;
            s[nb2]    = n;
            result.nb = nb2;

            // Remove unused space
            Array.Resize(ref result.r, nb2 + 1);
            Array.Resize(ref result.s, nb2 + 1);

            return(result);
        }