Actual source code: dsm.c
1: /* dsm.f -- translated by f2c (version of 25 March 1992 12:58:56). */
3: #include <../src/mat/graphops/color/impls/minpack/color.h>
5: static PetscInt c_n1 = -1;
7: PetscErrorCode MINPACKdsm(PetscInt *m, PetscInt *n, PetscInt *npairs, PetscInt *indrow, PetscInt *indcol, PetscInt *ngrp, PetscInt *maxgrp, PetscInt *mingrp, PetscInt *info, PetscInt *ipntr, PetscInt *jpntr, PetscInt *iwa, PetscInt *liwa)
8: {
9: /* System generated locals */
10: PetscInt i__1, i__2, i__3;
12: /* Local variables */
13: PetscInt i, j, maxclq, numgrp;
15: /* Given the sparsity pattern of an m by n matrix A, this */
16: /* subroutine determines a partition of the columns of A */
17: /* consistent with the direct determination of A. */
18: /* The sparsity pattern of the matrix A is specified by */
19: /* the arrays indrow and indcol. On input the indices */
20: /* for the non-zero elements of A are */
21: /* indrow(k),indcol(k), k = 1,2,...,npairs. */
22: /* The (indrow,indcol) pairs may be specified in any order. */
23: /* Duplicate input pairs are permitted, but the subroutine */
24: /* eliminates them. */
25: /* The subroutine partitions the columns of A into groups */
26: /* such that columns in the same group do not have a */
27: /* non-zero in the same row position. A partition of the */
28: /* columns of A with this property is consistent with the */
29: /* direct determination of A. */
30: /* The subroutine statement is */
31: /* subroutine dsm(m,n,npairs,indrow,indcol,ngrp,maxgrp,mingrp, */
32: /* info,ipntr,jpntr,iwa,liwa) */
33: /* where */
34: /* m is a positive integer input variable set to the number */
35: /* of rows of A. */
36: /* n is a positive integer input variable set to the number */
37: /* of columns of A. */
38: /* npairs is a positive integer input variable set to the */
39: /* number of (indrow,indcol) pairs used to describe the */
40: /* sparsity pattern of A. */
41: /* indrow is an integer array of length npairs. On input indrow */
42: /* must contain the row indices of the non-zero elements of A. */
43: /* On output indrow is permuted so that the corresponding */
44: /* column indices are in non-decreasing order. The column */
45: /* indices can be recovered from the array jpntr. */
46: /* indcol is an integer array of length npairs. On input indcol */
47: /* must contain the column indices of the non-zero elements of */
48: /* A. On output indcol is permuted so that the corresponding */
49: /* row indices are in non-decreasing order. The row indices */
50: /* can be recovered from the array ipntr. */
51: /* ngrp is an integer output array of length n which specifies */
52: /* the partition of the columns of A. Column jcol belongs */
53: /* to group ngrp(jcol). */
54: /* maxgrp is an integer output variable which specifies the */
55: /* number of groups in the partition of the columns of A. */
56: /* mingrp is an integer output variable which specifies a lower */
57: /* bound for the number of groups in any consistent partition */
58: /* of the columns of A. */
59: /* info is an integer output variable set as follows. For */
60: /* normal termination info = 1. If m, n, or npairs is not */
61: /* positive or liwa is less than max(m,6*n), then info = 0. */
62: /* If the k-th element of indrow is not an integer between */
63: /* 1 and m or the k-th element of indcol is not an integer */
64: /* between 1 and n, then info = -k. */
65: /* ipntr is an integer output array of length m + 1 which */
66: /* specifies the locations of the column indices in indcol. */
67: /* The column indices for row i are */
68: /* indcol(k), k = ipntr(i),...,ipntr(i+1)-1. */
69: /* Note that ipntr(m+1)-1 is then the number of non-zero */
70: /* elements of the matrix A. */
71: /* jpntr is an integer output array of length n + 1 which */
72: /* specifies the locations of the row indices in indrow. */
73: /* The row indices for column j are */
74: /* indrow(k), k = jpntr(j),...,jpntr(j+1)-1. */
75: /* Note that jpntr(n+1)-1 is then the number of non-zero */
76: /* elements of the matrix A. */
77: /* iwa is an integer work array of length liwa. */
78: /* liwa is a positive integer input variable not less than */
79: /* max(m,6*n). */
80: /* Subprograms called */
81: /* MINPACK-supplied ... degr,ido,numsrt,seq,setr,slo,srtdat */
82: /* FORTRAN-supplied ... max */
83: /* Argonne National Laboratory. MINPACK Project. December 1984. */
84: /* Thomas F. Coleman, Burton S. Garbow, Jorge J. More' */
86: PetscFunctionBegin;
87: /* Parameter adjustments */
88: --iwa;
89: --jpntr;
90: --ipntr;
91: --ngrp;
92: --indcol;
93: --indrow;
95: *info = 0;
97: /* Determine a lower bound for the number of groups. */
99: *mingrp = 0;
100: i__1 = *m;
101: for (i = 1; i <= i__1; ++i) {
102: /* Computing MAX */
103: i__2 = *mingrp;
104: i__3 = ipntr[i + 1] - ipntr[i];
105: *mingrp = PetscMax(i__2, i__3);
106: }
108: /* Determine the degree sequence for the intersection */
109: /* graph of the columns of A. */
111: PetscCall(MINPACKdegr(n, &indrow[1], &jpntr[1], &indcol[1], &ipntr[1], &iwa[*n * 5 + 1], &iwa[*n + 1]));
113: /* Color the intersection graph of the columns of A */
114: /* with the smallest-last (SL) ordering. */
116: PetscCall(MINPACKslo(n, &indrow[1], &jpntr[1], &indcol[1], &ipntr[1], &iwa[*n * 5 + 1], &iwa[(*n << 2) + 1], &maxclq, &iwa[1], &iwa[*n + 1], &iwa[(*n << 1) + 1], &iwa[*n * 3 + 1]));
117: PetscCall(MINPACKseq(n, &indrow[1], &jpntr[1], &indcol[1], &ipntr[1], &iwa[(*n << 2) + 1], &ngrp[1], maxgrp, &iwa[*n + 1]));
118: *mingrp = PetscMax(*mingrp, maxclq);
120: /* Exit if the smallest-last ordering is optimal. */
122: if (*maxgrp == *mingrp) PetscFunctionReturn(PETSC_SUCCESS);
124: /* Color the intersection graph of the columns of A */
125: /* with the incidence-degree (ID) ordering. */
127: PetscCall(MINPACKido(m, n, &indrow[1], &jpntr[1], &indcol[1], &ipntr[1], &iwa[*n * 5 + 1], &iwa[(*n << 2) + 1], &maxclq, &iwa[1], &iwa[*n + 1], &iwa[(*n << 1) + 1], &iwa[*n * 3 + 1]));
128: PetscCall(MINPACKseq(n, &indrow[1], &jpntr[1], &indcol[1], &ipntr[1], &iwa[(*n << 2) + 1], &iwa[1], &numgrp, &iwa[*n + 1]));
129: *mingrp = PetscMax(*mingrp, maxclq);
131: /* Retain the better of the two orderings so far. */
133: if (numgrp < *maxgrp) {
134: *maxgrp = numgrp;
135: i__1 = *n;
136: for (j = 1; j <= i__1; ++j) ngrp[j] = iwa[j];
138: /* Exit if the incidence-degree ordering is optimal. */
140: if (*maxgrp == *mingrp) PetscFunctionReturn(PETSC_SUCCESS);
141: }
143: /* Color the intersection graph of the columns of A */
144: /* with the largest-first (LF) ordering. */
146: i__1 = *n - 1;
147: PetscCall(MINPACKnumsrt(n, &i__1, &iwa[*n * 5 + 1], &c_n1, &iwa[(*n << 2) + 1], &iwa[(*n << 1) + 1], &iwa[*n + 1]));
148: PetscCall(MINPACKseq(n, &indrow[1], &jpntr[1], &indcol[1], &ipntr[1], &iwa[(*n << 2) + 1], &iwa[1], &numgrp, &iwa[*n + 1]));
150: /* Retain the best of the three orderings and exit. */
152: if (numgrp < *maxgrp) {
153: *maxgrp = numgrp;
154: i__1 = *n;
155: for (j = 1; j <= i__1; ++j) ngrp[j] = iwa[j];
156: }
157: PetscFunctionReturn(PETSC_SUCCESS);
158: }