/* triang.c (find maximal triangular part of rectangular matrix) */ /*********************************************************************** * This code is part of GLPK (GNU Linear Programming Kit). * Copyright (C) 2012-2013 Free Software Foundation, Inc. * Written by Andrew Makhorin . * * GLPK is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * GLPK is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public * License for more details. * * You should have received a copy of the GNU General Public License * along with GLPK. If not, see . ***********************************************************************/ #include "env.h" #include "triang.h" /*********************************************************************** * triang - find maximal triangular part of rectangular matrix * * Given a mxn sparse matrix A this routine finds permutation matrices * P and Q such that matrix A' = P * A * Q has the following structure: * * 1 s n * 1 * . . . . . x x x x x * * * . . . . x x x x x * * * * . . . x x x x x * * * * * . . x x x x x * * * * * * . x x x x x * s * * * * * * x x x x x * x x x x x x x x x x x * x x x x x x x x x x x * m x x x x x x x x x x x * * where '*' are elements of the triangular part, '.' are structural * zeros, 'x' are other elements. * * The formal routine mat specifies the original matrix A in both row- * and column-wise format. If the routine mat is called with k = +i, * 1 <= i <= m, it should store column indices and values of non-zero * elements of i-th row of A in locations ind[1], ..., ind[len] and * val[1], ..., val[len], resp., where len is the returned number of * non-zeros in the row, 0 <= len <= n. Similarly, if the routine mat * is called with k = -j, 1 <= j <= n, it should store row indices and * values of non-zero elements of j-th column of A and return len, the * number of non-zeros in the column, 0 <= len <= m. Should note that * duplicate indices are not allowed. * * The parameter info is a transit pointer passed to the routine mat. * * The parameter tol is a tolerance. The routine triang guarantees that * each diagonal element in the triangular part of matrix A' is not * less in magnitude than tol * max, where max is the maximal magnitude * of elements in corresponding column. * * On exit the routine triang stores information on the triangular part * found in the arrays rn and cn. Elements rn[1], ..., rn[s] specify * row numbers and elements cn[1], ..., cn[s] specify column numbers * of the original matrix A, which correspond to rows/columns 1, ..., s * of matrix A', where s is the size of the triangular part returned by * the routine, 0 <= s <= min(m, n). The order of rows and columns that * are not included in the triangular part remains unspecified. * * ALGORITHM * * The routine triang uses a simple greedy heuristic. * * At some step the matrix A' = P * A * Q has the following structure: * * 1 n * 1 * . . . . . . . x x x * * * . . . . . . x x x * * * * . . . . . x x x * * * * * . . . . x x x * x x x x # # # # x x x * x x x x # # # # x x x * x x x x # # # # x x x * x x x x # # # # x x x * m x x x x # # # # x x x * * where '#' are elements of active submatrix. Initially P = Q = I, so * the active submatrix is the original matrix A = A'. * * If some row has exactly one non-zero in the active submatrix (row * singleton), the routine includes this row and corresponding column * in the triangular part, and removes the column from the active * submatrix. Otherwise, the routine simply removes a column having * maximal number of non-zeros from the active submatrix in the hope * that new row singleton(s) will appear. * * COMPLEXITY * * The time complexity of the routine triang is O(nnz), where nnz is * number of non-zeros in the original matrix A. */ int triang(int m, int n, int (*mat)(void *info, int k, int ind[], double val[]), void *info, double tol, int rn[], int cn[]) { int head, i, j, jj, k, kk, ks, len, len2, next_j, ns, size; int *cind, *rind, *cnt, *ptr, *list, *prev, *next; double *cval, *rval, *big; char *flag; /* allocate working arrays */ cind = talloc(1+m, int); cval = talloc(1+m, double); rind = talloc(1+n, int); rval = talloc(1+n, double); cnt = ptr = talloc(1+m, int); list = talloc(1+n, int); prev = talloc(1+n, int); next = talloc(1+n, int); big = talloc(1+n, double); flag = talloc(1+n, char); /*--------------------------------------------------------------*/ /* build linked lists of columns having equal lengths */ /*--------------------------------------------------------------*/ /* ptr[len], 0 <= len <= m, is number of first column of length * len; * next[j], 1 <= j <= n, is number of next column having the same * length as column j; * big[j], 1 <= j <= n, is maximal magnitude of elements in j-th * column */ for (len = 0; len <= m; len++) ptr[len] = 0; for (j = 1; j <= n; j++) { /* get j-th column */ len = mat(info, -j, cind, cval); xassert(0 <= len && len <= m); /* add this column to beginning of list ptr[len] */ next[j] = ptr[len]; ptr[len] = j; /* determine maximal magnitude of elements in this column */ big[j] = 0.0; for (k = 1; k <= len; k++) { if (big[j] < fabs(cval[k])) big[j] = fabs(cval[k]); } } /*--------------------------------------------------------------*/ /* build doubly linked list of columns ordered by decreasing */ /* column lengths */ /*--------------------------------------------------------------*/ /* head is number of first column in the list; * prev[j], 1 <= j <= n, is number of column that precedes j-th * column in the list; * next[j], 1 <= j <= n, is number of column that follows j-th * column in the list */ head = 0; for (len = 0; len <= m; len++) { /* walk thru list of columns of length len */ for (j = ptr[len]; j != 0; j = next_j) { next_j = next[j]; /* add j-th column to beginning of the column list */ prev[j] = 0; next[j] = head; if (head != 0) prev[head] = j; head = j; } } /*--------------------------------------------------------------*/ /* build initial singleton list */ /*--------------------------------------------------------------*/ /* there are used two list of columns: * 1) doubly linked list of active columns, in which all columns * are ordered by decreasing column lengths; * 2) singleton list; an active column is included in this list * if it has at least one row singleton in active submatrix */ /* flag[j], 1 <= j <= n, is a flag of j-th column: * 0 j-th column is inactive; * 1 j-th column is active; * 2 j-th column is active and has row singleton(s) */ /* initially all columns are active */ for (j = 1; j <= n; j++) flag[j] = 1; /* initialize row counts and build initial singleton list */ /* cnt[i], 1 <= i <= m, is number of non-zeros, which i-th row * has in active submatrix; * ns is size of singleton list; * list[1], ..., list[ns] are numbers of active columns included * in the singleton list */ ns = 0; for (i = 1; i <= m; i++) { /* get i-th row */ len = cnt[i] = mat(info, +i, rind, rval); xassert(0 <= len && len <= n); if (len == 1) { /* a[i,j] is row singleton */ j = rind[1]; xassert(1 <= j && j <= n); if (flag[j] != 2) { /* include j-th column in singleton list */ flag[j] = 2; list[++ns] = j; } } } /*--------------------------------------------------------------*/ /* main loop */ /*--------------------------------------------------------------*/ size = 0; /* size of triangular part */ /* loop until active column list is non-empty, i.e. until the * active submatrix has at least one column */ while (head != 0) { if (ns == 0) { /* singleton list is empty */ /* remove from the active submatrix a column of maximal * length in the hope that some row singletons appear */ j = head; len = mat(info, -j, cind, cval); xassert(0 <= len && len <= m); goto drop; } /* take column j from the singleton list */ j = list[ns--]; xassert(flag[j] == 2); /* j-th column has at least one row singleton in the active * submatrix; choose one having maximal magnitude */ len = mat(info, -j, cind, cval); xassert(0 <= len && len <= m); kk = 0; for (k = 1; k <= len; k++) { i = cind[k]; xassert(1 <= i && i <= m); if (cnt[i] == 1) { /* a[i,j] is row singleton */ if (kk == 0 || fabs(cval[kk]) < fabs(cval[k])) kk = k; } } xassert(kk > 0); /* check magnitude of the row singleton chosen */ if (fabs(cval[kk]) < tol * big[j]) { /* all row singletons are too small in magnitude; drop j-th * column */ goto drop; } /* row singleton a[i,j] is ok; add i-th row and j-th column to * the triangular part */ size++; rn[size] = cind[kk]; cn[size] = j; drop: /* remove j-th column from the active submatrix */ xassert(flag[j]); flag[j] = 0; if (prev[j] == 0) head = next[j]; else next[prev[j]] = next[j]; if (next[j] == 0) ; else prev[next[j]] = prev[j]; /* decrease row counts */ for (k = 1; k <= len; k++) { i = cind[k]; xassert(1 <= i && i <= m); xassert(cnt[i] > 0); cnt[i]--; if (cnt[i] == 1) { /* new singleton appeared in i-th row; determine number * of corresponding column (it is the only active column * in this row) */ len2 = mat(info, +i, rind, rval); xassert(0 <= len2 && len2 <= n); ks = 0; for (kk = 1; kk <= len2; kk++) { jj = rind[kk]; xassert(1 <= jj && jj <= n); if (flag[jj]) { xassert(ks == 0); ks = kk; } } xassert(ks > 0); /* a[i,jj] is new row singleton */ jj = rind[ks]; if (flag[jj] != 2) { /* include jj-th column in the singleton list */ flag[jj] = 2; list[++ns] = jj; } } } } /* now all row counts should be zero */ for (i = 1; i <= m; i++) xassert(cnt[i] == 0); /* deallocate working arrays */ tfree(cind); tfree(cval); tfree(rind); tfree(rval); tfree(ptr); tfree(list); tfree(prev); tfree(next); tfree(big); tfree(flag); return size; } /* eof */