1 /* dsm.f -- translated by f2c (version of 25 March 1992 12:58:56). */
2
3 #include <../src/mat/graphops/color/impls/minpack/color.h>
4
5 static PetscInt c_n1 = -1;
6
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)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;
11
12 /* Local variables */
13 PetscInt i, j, maxclq, numgrp;
14
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' */
85
86 PetscFunctionBegin;
87 /* Parameter adjustments */
88 --iwa;
89 --jpntr;
90 --ipntr;
91 --ngrp;
92 --indcol;
93 --indrow;
94
95 *info = 0;
96
97 /* Determine a lower bound for the number of groups. */
98
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 }
107
108 /* Determine the degree sequence for the intersection */
109 /* graph of the columns of A. */
110
111 PetscCall(MINPACKdegr(n, &indrow[1], &jpntr[1], &indcol[1], &ipntr[1], &iwa[*n * 5 + 1], &iwa[*n + 1]));
112
113 /* Color the intersection graph of the columns of A */
114 /* with the smallest-last (SL) ordering. */
115
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);
119
120 /* Exit if the smallest-last ordering is optimal. */
121
122 if (*maxgrp == *mingrp) PetscFunctionReturn(PETSC_SUCCESS);
123
124 /* Color the intersection graph of the columns of A */
125 /* with the incidence-degree (ID) ordering. */
126
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);
130
131 /* Retain the better of the two orderings so far. */
132
133 if (numgrp < *maxgrp) {
134 *maxgrp = numgrp;
135 i__1 = *n;
136 for (j = 1; j <= i__1; ++j) ngrp[j] = iwa[j];
137
138 /* Exit if the incidence-degree ordering is optimal. */
139
140 if (*maxgrp == *mingrp) PetscFunctionReturn(PETSC_SUCCESS);
141 }
142
143 /* Color the intersection graph of the columns of A */
144 /* with the largest-first (LF) ordering. */
145
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]));
149
150 /* Retain the best of the three orderings and exit. */
151
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 }
159