rev |
line source |
alpar@9
|
1 /* glpspm.c */
|
alpar@9
|
2
|
alpar@9
|
3 /***********************************************************************
|
alpar@9
|
4 * This code is part of GLPK (GNU Linear Programming Kit).
|
alpar@9
|
5 *
|
alpar@9
|
6 * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008,
|
alpar@9
|
7 * 2009, 2010, 2011 Andrew Makhorin, Department for Applied Informatics,
|
alpar@9
|
8 * Moscow Aviation Institute, Moscow, Russia. All rights reserved.
|
alpar@9
|
9 * E-mail: <mao@gnu.org>.
|
alpar@9
|
10 *
|
alpar@9
|
11 * GLPK is free software: you can redistribute it and/or modify it
|
alpar@9
|
12 * under the terms of the GNU General Public License as published by
|
alpar@9
|
13 * the Free Software Foundation, either version 3 of the License, or
|
alpar@9
|
14 * (at your option) any later version.
|
alpar@9
|
15 *
|
alpar@9
|
16 * GLPK is distributed in the hope that it will be useful, but WITHOUT
|
alpar@9
|
17 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
|
alpar@9
|
18 * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
|
alpar@9
|
19 * License for more details.
|
alpar@9
|
20 *
|
alpar@9
|
21 * You should have received a copy of the GNU General Public License
|
alpar@9
|
22 * along with GLPK. If not, see <http://www.gnu.org/licenses/>.
|
alpar@9
|
23 ***********************************************************************/
|
alpar@9
|
24
|
alpar@9
|
25 #include "glphbm.h"
|
alpar@9
|
26 #include "glprgr.h"
|
alpar@9
|
27 #include "glpspm.h"
|
alpar@9
|
28
|
alpar@9
|
29 /***********************************************************************
|
alpar@9
|
30 * NAME
|
alpar@9
|
31 *
|
alpar@9
|
32 * spm_create_mat - create general sparse matrix
|
alpar@9
|
33 *
|
alpar@9
|
34 * SYNOPSIS
|
alpar@9
|
35 *
|
alpar@9
|
36 * #include "glpspm.h"
|
alpar@9
|
37 * SPM *spm_create_mat(int m, int n);
|
alpar@9
|
38 *
|
alpar@9
|
39 * DESCRIPTION
|
alpar@9
|
40 *
|
alpar@9
|
41 * The routine spm_create_mat creates a general sparse matrix having
|
alpar@9
|
42 * m rows and n columns. Being created the matrix is zero (empty), i.e.
|
alpar@9
|
43 * has no elements.
|
alpar@9
|
44 *
|
alpar@9
|
45 * RETURNS
|
alpar@9
|
46 *
|
alpar@9
|
47 * The routine returns a pointer to the matrix created. */
|
alpar@9
|
48
|
alpar@9
|
49 SPM *spm_create_mat(int m, int n)
|
alpar@9
|
50 { SPM *A;
|
alpar@9
|
51 xassert(0 <= m && m < INT_MAX);
|
alpar@9
|
52 xassert(0 <= n && n < INT_MAX);
|
alpar@9
|
53 A = xmalloc(sizeof(SPM));
|
alpar@9
|
54 A->m = m;
|
alpar@9
|
55 A->n = n;
|
alpar@9
|
56 if (m == 0 || n == 0)
|
alpar@9
|
57 { A->pool = NULL;
|
alpar@9
|
58 A->row = NULL;
|
alpar@9
|
59 A->col = NULL;
|
alpar@9
|
60 }
|
alpar@9
|
61 else
|
alpar@9
|
62 { int i, j;
|
alpar@9
|
63 A->pool = dmp_create_pool();
|
alpar@9
|
64 A->row = xcalloc(1+m, sizeof(SPME *));
|
alpar@9
|
65 for (i = 1; i <= m; i++) A->row[i] = NULL;
|
alpar@9
|
66 A->col = xcalloc(1+n, sizeof(SPME *));
|
alpar@9
|
67 for (j = 1; j <= n; j++) A->col[j] = NULL;
|
alpar@9
|
68 }
|
alpar@9
|
69 return A;
|
alpar@9
|
70 }
|
alpar@9
|
71
|
alpar@9
|
72 /***********************************************************************
|
alpar@9
|
73 * NAME
|
alpar@9
|
74 *
|
alpar@9
|
75 * spm_new_elem - add new element to sparse matrix
|
alpar@9
|
76 *
|
alpar@9
|
77 * SYNOPSIS
|
alpar@9
|
78 *
|
alpar@9
|
79 * #include "glpspm.h"
|
alpar@9
|
80 * SPME *spm_new_elem(SPM *A, int i, int j, double val);
|
alpar@9
|
81 *
|
alpar@9
|
82 * DESCRIPTION
|
alpar@9
|
83 *
|
alpar@9
|
84 * The routine spm_new_elem adds a new element to the specified sparse
|
alpar@9
|
85 * matrix. Parameters i, j, and val specify the row number, the column
|
alpar@9
|
86 * number, and a numerical value of the element, respectively.
|
alpar@9
|
87 *
|
alpar@9
|
88 * RETURNS
|
alpar@9
|
89 *
|
alpar@9
|
90 * The routine returns a pointer to the new element added. */
|
alpar@9
|
91
|
alpar@9
|
92 SPME *spm_new_elem(SPM *A, int i, int j, double val)
|
alpar@9
|
93 { SPME *e;
|
alpar@9
|
94 xassert(1 <= i && i <= A->m);
|
alpar@9
|
95 xassert(1 <= j && j <= A->n);
|
alpar@9
|
96 e = dmp_get_atom(A->pool, sizeof(SPME));
|
alpar@9
|
97 e->i = i;
|
alpar@9
|
98 e->j = j;
|
alpar@9
|
99 e->val = val;
|
alpar@9
|
100 e->r_prev = NULL;
|
alpar@9
|
101 e->r_next = A->row[i];
|
alpar@9
|
102 if (e->r_next != NULL) e->r_next->r_prev = e;
|
alpar@9
|
103 e->c_prev = NULL;
|
alpar@9
|
104 e->c_next = A->col[j];
|
alpar@9
|
105 if (e->c_next != NULL) e->c_next->c_prev = e;
|
alpar@9
|
106 A->row[i] = A->col[j] = e;
|
alpar@9
|
107 return e;
|
alpar@9
|
108 }
|
alpar@9
|
109
|
alpar@9
|
110 /***********************************************************************
|
alpar@9
|
111 * NAME
|
alpar@9
|
112 *
|
alpar@9
|
113 * spm_delete_mat - delete general sparse matrix
|
alpar@9
|
114 *
|
alpar@9
|
115 * SYNOPSIS
|
alpar@9
|
116 *
|
alpar@9
|
117 * #include "glpspm.h"
|
alpar@9
|
118 * void spm_delete_mat(SPM *A);
|
alpar@9
|
119 *
|
alpar@9
|
120 * DESCRIPTION
|
alpar@9
|
121 *
|
alpar@9
|
122 * The routine deletes the specified general sparse matrix freeing all
|
alpar@9
|
123 * the memory allocated to this object. */
|
alpar@9
|
124
|
alpar@9
|
125 void spm_delete_mat(SPM *A)
|
alpar@9
|
126 { /* delete sparse matrix */
|
alpar@9
|
127 if (A->pool != NULL) dmp_delete_pool(A->pool);
|
alpar@9
|
128 if (A->row != NULL) xfree(A->row);
|
alpar@9
|
129 if (A->col != NULL) xfree(A->col);
|
alpar@9
|
130 xfree(A);
|
alpar@9
|
131 return;
|
alpar@9
|
132 }
|
alpar@9
|
133
|
alpar@9
|
134 /***********************************************************************
|
alpar@9
|
135 * NAME
|
alpar@9
|
136 *
|
alpar@9
|
137 * spm_test_mat_e - create test sparse matrix of E(n,c) class
|
alpar@9
|
138 *
|
alpar@9
|
139 * SYNOPSIS
|
alpar@9
|
140 *
|
alpar@9
|
141 * #include "glpspm.h"
|
alpar@9
|
142 * SPM *spm_test_mat_e(int n, int c);
|
alpar@9
|
143 *
|
alpar@9
|
144 * DESCRIPTION
|
alpar@9
|
145 *
|
alpar@9
|
146 * The routine spm_test_mat_e creates a test sparse matrix of E(n,c)
|
alpar@9
|
147 * class as described in the book: Ole 0sterby, Zahari Zlatev. Direct
|
alpar@9
|
148 * Methods for Sparse Matrices. Springer-Verlag, 1983.
|
alpar@9
|
149 *
|
alpar@9
|
150 * Matrix of E(n,c) class is a symmetric positive definite matrix of
|
alpar@9
|
151 * the order n. It has the number 4 on its main diagonal and the number
|
alpar@9
|
152 * -1 on its four co-diagonals, two of which are neighbour to the main
|
alpar@9
|
153 * diagonal and two others are shifted from the main diagonal on the
|
alpar@9
|
154 * distance c.
|
alpar@9
|
155 *
|
alpar@9
|
156 * It is necessary that n >= 3 and 2 <= c <= n-1.
|
alpar@9
|
157 *
|
alpar@9
|
158 * RETURNS
|
alpar@9
|
159 *
|
alpar@9
|
160 * The routine returns a pointer to the matrix created. */
|
alpar@9
|
161
|
alpar@9
|
162 SPM *spm_test_mat_e(int n, int c)
|
alpar@9
|
163 { SPM *A;
|
alpar@9
|
164 int i;
|
alpar@9
|
165 xassert(n >= 3 && 2 <= c && c <= n-1);
|
alpar@9
|
166 A = spm_create_mat(n, n);
|
alpar@9
|
167 for (i = 1; i <= n; i++)
|
alpar@9
|
168 spm_new_elem(A, i, i, 4.0);
|
alpar@9
|
169 for (i = 1; i <= n-1; i++)
|
alpar@9
|
170 { spm_new_elem(A, i, i+1, -1.0);
|
alpar@9
|
171 spm_new_elem(A, i+1, i, -1.0);
|
alpar@9
|
172 }
|
alpar@9
|
173 for (i = 1; i <= n-c; i++)
|
alpar@9
|
174 { spm_new_elem(A, i, i+c, -1.0);
|
alpar@9
|
175 spm_new_elem(A, i+c, i, -1.0);
|
alpar@9
|
176 }
|
alpar@9
|
177 return A;
|
alpar@9
|
178 }
|
alpar@9
|
179
|
alpar@9
|
180 /***********************************************************************
|
alpar@9
|
181 * NAME
|
alpar@9
|
182 *
|
alpar@9
|
183 * spm_test_mat_d - create test sparse matrix of D(n,c) class
|
alpar@9
|
184 *
|
alpar@9
|
185 * SYNOPSIS
|
alpar@9
|
186 *
|
alpar@9
|
187 * #include "glpspm.h"
|
alpar@9
|
188 * SPM *spm_test_mat_d(int n, int c);
|
alpar@9
|
189 *
|
alpar@9
|
190 * DESCRIPTION
|
alpar@9
|
191 *
|
alpar@9
|
192 * The routine spm_test_mat_d creates a test sparse matrix of D(n,c)
|
alpar@9
|
193 * class as described in the book: Ole 0sterby, Zahari Zlatev. Direct
|
alpar@9
|
194 * Methods for Sparse Matrices. Springer-Verlag, 1983.
|
alpar@9
|
195 *
|
alpar@9
|
196 * Matrix of D(n,c) class is a non-singular matrix of the order n. It
|
alpar@9
|
197 * has unity main diagonal, three co-diagonals above the main diagonal
|
alpar@9
|
198 * on the distance c, which are cyclically continued below the main
|
alpar@9
|
199 * diagonal, and a triangle block of the size 10x10 in the upper right
|
alpar@9
|
200 * corner.
|
alpar@9
|
201 *
|
alpar@9
|
202 * It is necessary that n >= 14 and 1 <= c <= n-13.
|
alpar@9
|
203 *
|
alpar@9
|
204 * RETURNS
|
alpar@9
|
205 *
|
alpar@9
|
206 * The routine returns a pointer to the matrix created. */
|
alpar@9
|
207
|
alpar@9
|
208 SPM *spm_test_mat_d(int n, int c)
|
alpar@9
|
209 { SPM *A;
|
alpar@9
|
210 int i, j;
|
alpar@9
|
211 xassert(n >= 14 && 1 <= c && c <= n-13);
|
alpar@9
|
212 A = spm_create_mat(n, n);
|
alpar@9
|
213 for (i = 1; i <= n; i++)
|
alpar@9
|
214 spm_new_elem(A, i, i, 1.0);
|
alpar@9
|
215 for (i = 1; i <= n-c; i++)
|
alpar@9
|
216 spm_new_elem(A, i, i+c, (double)(i+1));
|
alpar@9
|
217 for (i = n-c+1; i <= n; i++)
|
alpar@9
|
218 spm_new_elem(A, i, i-n+c, (double)(i+1));
|
alpar@9
|
219 for (i = 1; i <= n-c-1; i++)
|
alpar@9
|
220 spm_new_elem(A, i, i+c+1, (double)(-i));
|
alpar@9
|
221 for (i = n-c; i <= n; i++)
|
alpar@9
|
222 spm_new_elem(A, i, i-n+c+1, (double)(-i));
|
alpar@9
|
223 for (i = 1; i <= n-c-2; i++)
|
alpar@9
|
224 spm_new_elem(A, i, i+c+2, 16.0);
|
alpar@9
|
225 for (i = n-c-1; i <= n; i++)
|
alpar@9
|
226 spm_new_elem(A, i, i-n+c+2, 16.0);
|
alpar@9
|
227 for (j = 1; j <= 10; j++)
|
alpar@9
|
228 for (i = 1; i <= 11-j; i++)
|
alpar@9
|
229 spm_new_elem(A, i, n-11+i+j, 100.0 * (double)j);
|
alpar@9
|
230 return A;
|
alpar@9
|
231 }
|
alpar@9
|
232
|
alpar@9
|
233 /***********************************************************************
|
alpar@9
|
234 * NAME
|
alpar@9
|
235 *
|
alpar@9
|
236 * spm_show_mat - write sparse matrix pattern in BMP file format
|
alpar@9
|
237 *
|
alpar@9
|
238 * SYNOPSIS
|
alpar@9
|
239 *
|
alpar@9
|
240 * #include "glpspm.h"
|
alpar@9
|
241 * int spm_show_mat(const SPM *A, const char *fname);
|
alpar@9
|
242 *
|
alpar@9
|
243 * DESCRIPTION
|
alpar@9
|
244 *
|
alpar@9
|
245 * The routine spm_show_mat writes pattern of the specified sparse
|
alpar@9
|
246 * matrix in uncompressed BMP file format (Windows bitmap) to a binary
|
alpar@9
|
247 * file whose name is specified by the character string fname.
|
alpar@9
|
248 *
|
alpar@9
|
249 * Each pixel corresponds to one matrix element. The pixel colors have
|
alpar@9
|
250 * the following meaning:
|
alpar@9
|
251 *
|
alpar@9
|
252 * Black structurally zero element
|
alpar@9
|
253 * White positive element
|
alpar@9
|
254 * Cyan negative element
|
alpar@9
|
255 * Green zero element
|
alpar@9
|
256 * Red duplicate element
|
alpar@9
|
257 *
|
alpar@9
|
258 * RETURNS
|
alpar@9
|
259 *
|
alpar@9
|
260 * If no error occured, the routine returns zero. Otherwise, it prints
|
alpar@9
|
261 * an appropriate error message and returns non-zero. */
|
alpar@9
|
262
|
alpar@9
|
263 int spm_show_mat(const SPM *A, const char *fname)
|
alpar@9
|
264 { int m = A->m;
|
alpar@9
|
265 int n = A->n;
|
alpar@9
|
266 int i, j, k, ret;
|
alpar@9
|
267 char *map;
|
alpar@9
|
268 xprintf("spm_show_mat: writing matrix pattern to `%s'...\n",
|
alpar@9
|
269 fname);
|
alpar@9
|
270 xassert(1 <= m && m <= 32767);
|
alpar@9
|
271 xassert(1 <= n && n <= 32767);
|
alpar@9
|
272 map = xmalloc(m * n);
|
alpar@9
|
273 memset(map, 0x08, m * n);
|
alpar@9
|
274 for (i = 1; i <= m; i++)
|
alpar@9
|
275 { SPME *e;
|
alpar@9
|
276 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
277 { j = e->j;
|
alpar@9
|
278 xassert(1 <= j && j <= n);
|
alpar@9
|
279 k = n * (i - 1) + (j - 1);
|
alpar@9
|
280 if (map[k] != 0x08)
|
alpar@9
|
281 map[k] = 0x0C;
|
alpar@9
|
282 else if (e->val > 0.0)
|
alpar@9
|
283 map[k] = 0x0F;
|
alpar@9
|
284 else if (e->val < 0.0)
|
alpar@9
|
285 map[k] = 0x0B;
|
alpar@9
|
286 else
|
alpar@9
|
287 map[k] = 0x0A;
|
alpar@9
|
288 }
|
alpar@9
|
289 }
|
alpar@9
|
290 ret = rgr_write_bmp16(fname, m, n, map);
|
alpar@9
|
291 xfree(map);
|
alpar@9
|
292 return ret;
|
alpar@9
|
293 }
|
alpar@9
|
294
|
alpar@9
|
295 /***********************************************************************
|
alpar@9
|
296 * NAME
|
alpar@9
|
297 *
|
alpar@9
|
298 * spm_read_hbm - read sparse matrix in Harwell-Boeing format
|
alpar@9
|
299 *
|
alpar@9
|
300 * SYNOPSIS
|
alpar@9
|
301 *
|
alpar@9
|
302 * #include "glpspm.h"
|
alpar@9
|
303 * SPM *spm_read_hbm(const char *fname);
|
alpar@9
|
304 *
|
alpar@9
|
305 * DESCRIPTION
|
alpar@9
|
306 *
|
alpar@9
|
307 * The routine spm_read_hbm reads a sparse matrix in the Harwell-Boeing
|
alpar@9
|
308 * format from a text file whose name is the character string fname.
|
alpar@9
|
309 *
|
alpar@9
|
310 * Detailed description of the Harwell-Boeing format recognised by this
|
alpar@9
|
311 * routine can be found in the following report:
|
alpar@9
|
312 *
|
alpar@9
|
313 * I.S.Duff, R.G.Grimes, J.G.Lewis. User's Guide for the Harwell-Boeing
|
alpar@9
|
314 * Sparse Matrix Collection (Release I), TR/PA/92/86, October 1992.
|
alpar@9
|
315 *
|
alpar@9
|
316 * NOTE
|
alpar@9
|
317 *
|
alpar@9
|
318 * The routine spm_read_hbm reads the matrix "as is", due to which zero
|
alpar@9
|
319 * and/or duplicate elements can appear in the matrix.
|
alpar@9
|
320 *
|
alpar@9
|
321 * RETURNS
|
alpar@9
|
322 *
|
alpar@9
|
323 * If no error occured, the routine returns a pointer to the matrix
|
alpar@9
|
324 * created. Otherwise, the routine prints an appropriate error message
|
alpar@9
|
325 * and returns NULL. */
|
alpar@9
|
326
|
alpar@9
|
327 SPM *spm_read_hbm(const char *fname)
|
alpar@9
|
328 { SPM *A = NULL;
|
alpar@9
|
329 HBM *hbm;
|
alpar@9
|
330 int nrow, ncol, nnzero, i, j, beg, end, ptr, *colptr, *rowind;
|
alpar@9
|
331 double val, *values;
|
alpar@9
|
332 char *mxtype;
|
alpar@9
|
333 hbm = hbm_read_mat(fname);
|
alpar@9
|
334 if (hbm == NULL)
|
alpar@9
|
335 { xprintf("spm_read_hbm: unable to read matrix\n");
|
alpar@9
|
336 goto fini;
|
alpar@9
|
337 }
|
alpar@9
|
338 mxtype = hbm->mxtype;
|
alpar@9
|
339 nrow = hbm->nrow;
|
alpar@9
|
340 ncol = hbm->ncol;
|
alpar@9
|
341 nnzero = hbm->nnzero;
|
alpar@9
|
342 colptr = hbm->colptr;
|
alpar@9
|
343 rowind = hbm->rowind;
|
alpar@9
|
344 values = hbm->values;
|
alpar@9
|
345 if (!(strcmp(mxtype, "RSA") == 0 || strcmp(mxtype, "PSA") == 0 ||
|
alpar@9
|
346 strcmp(mxtype, "RUA") == 0 || strcmp(mxtype, "PUA") == 0 ||
|
alpar@9
|
347 strcmp(mxtype, "RRA") == 0 || strcmp(mxtype, "PRA") == 0))
|
alpar@9
|
348 { xprintf("spm_read_hbm: matrix type `%s' not supported\n",
|
alpar@9
|
349 mxtype);
|
alpar@9
|
350 goto fini;
|
alpar@9
|
351 }
|
alpar@9
|
352 A = spm_create_mat(nrow, ncol);
|
alpar@9
|
353 if (mxtype[1] == 'S' || mxtype[1] == 'U')
|
alpar@9
|
354 xassert(nrow == ncol);
|
alpar@9
|
355 for (j = 1; j <= ncol; j++)
|
alpar@9
|
356 { beg = colptr[j];
|
alpar@9
|
357 end = colptr[j+1];
|
alpar@9
|
358 xassert(1 <= beg && beg <= end && end <= nnzero + 1);
|
alpar@9
|
359 for (ptr = beg; ptr < end; ptr++)
|
alpar@9
|
360 { i = rowind[ptr];
|
alpar@9
|
361 xassert(1 <= i && i <= nrow);
|
alpar@9
|
362 if (mxtype[0] == 'R')
|
alpar@9
|
363 val = values[ptr];
|
alpar@9
|
364 else
|
alpar@9
|
365 val = 1.0;
|
alpar@9
|
366 spm_new_elem(A, i, j, val);
|
alpar@9
|
367 if (mxtype[1] == 'S' && i != j)
|
alpar@9
|
368 spm_new_elem(A, j, i, val);
|
alpar@9
|
369 }
|
alpar@9
|
370 }
|
alpar@9
|
371 fini: if (hbm != NULL) hbm_free_mat(hbm);
|
alpar@9
|
372 return A;
|
alpar@9
|
373 }
|
alpar@9
|
374
|
alpar@9
|
375 /***********************************************************************
|
alpar@9
|
376 * NAME
|
alpar@9
|
377 *
|
alpar@9
|
378 * spm_count_nnz - determine number of non-zeros in sparse matrix
|
alpar@9
|
379 *
|
alpar@9
|
380 * SYNOPSIS
|
alpar@9
|
381 *
|
alpar@9
|
382 * #include "glpspm.h"
|
alpar@9
|
383 * int spm_count_nnz(const SPM *A);
|
alpar@9
|
384 *
|
alpar@9
|
385 * RETURNS
|
alpar@9
|
386 *
|
alpar@9
|
387 * The routine spm_count_nnz returns the number of structural non-zero
|
alpar@9
|
388 * elements in the specified sparse matrix. */
|
alpar@9
|
389
|
alpar@9
|
390 int spm_count_nnz(const SPM *A)
|
alpar@9
|
391 { SPME *e;
|
alpar@9
|
392 int i, nnz = 0;
|
alpar@9
|
393 for (i = 1; i <= A->m; i++)
|
alpar@9
|
394 for (e = A->row[i]; e != NULL; e = e->r_next) nnz++;
|
alpar@9
|
395 return nnz;
|
alpar@9
|
396 }
|
alpar@9
|
397
|
alpar@9
|
398 /***********************************************************************
|
alpar@9
|
399 * NAME
|
alpar@9
|
400 *
|
alpar@9
|
401 * spm_drop_zeros - remove zero elements from sparse matrix
|
alpar@9
|
402 *
|
alpar@9
|
403 * SYNOPSIS
|
alpar@9
|
404 *
|
alpar@9
|
405 * #include "glpspm.h"
|
alpar@9
|
406 * int spm_drop_zeros(SPM *A, double eps);
|
alpar@9
|
407 *
|
alpar@9
|
408 * DESCRIPTION
|
alpar@9
|
409 *
|
alpar@9
|
410 * The routine spm_drop_zeros removes all elements from the specified
|
alpar@9
|
411 * sparse matrix, whose absolute value is less than eps.
|
alpar@9
|
412 *
|
alpar@9
|
413 * If the parameter eps is 0, only zero elements are removed from the
|
alpar@9
|
414 * matrix.
|
alpar@9
|
415 *
|
alpar@9
|
416 * RETURNS
|
alpar@9
|
417 *
|
alpar@9
|
418 * The routine returns the number of elements removed. */
|
alpar@9
|
419
|
alpar@9
|
420 int spm_drop_zeros(SPM *A, double eps)
|
alpar@9
|
421 { SPME *e, *next;
|
alpar@9
|
422 int i, count = 0;
|
alpar@9
|
423 for (i = 1; i <= A->m; i++)
|
alpar@9
|
424 { for (e = A->row[i]; e != NULL; e = next)
|
alpar@9
|
425 { next = e->r_next;
|
alpar@9
|
426 if (e->val == 0.0 || fabs(e->val) < eps)
|
alpar@9
|
427 { /* remove element from the row list */
|
alpar@9
|
428 if (e->r_prev == NULL)
|
alpar@9
|
429 A->row[e->i] = e->r_next;
|
alpar@9
|
430 else
|
alpar@9
|
431 e->r_prev->r_next = e->r_next;
|
alpar@9
|
432 if (e->r_next == NULL)
|
alpar@9
|
433 ;
|
alpar@9
|
434 else
|
alpar@9
|
435 e->r_next->r_prev = e->r_prev;
|
alpar@9
|
436 /* remove element from the column list */
|
alpar@9
|
437 if (e->c_prev == NULL)
|
alpar@9
|
438 A->col[e->j] = e->c_next;
|
alpar@9
|
439 else
|
alpar@9
|
440 e->c_prev->c_next = e->c_next;
|
alpar@9
|
441 if (e->c_next == NULL)
|
alpar@9
|
442 ;
|
alpar@9
|
443 else
|
alpar@9
|
444 e->c_next->c_prev = e->c_prev;
|
alpar@9
|
445 /* return element to the memory pool */
|
alpar@9
|
446 dmp_free_atom(A->pool, e, sizeof(SPME));
|
alpar@9
|
447 count++;
|
alpar@9
|
448 }
|
alpar@9
|
449 }
|
alpar@9
|
450 }
|
alpar@9
|
451 return count;
|
alpar@9
|
452 }
|
alpar@9
|
453
|
alpar@9
|
454 /***********************************************************************
|
alpar@9
|
455 * NAME
|
alpar@9
|
456 *
|
alpar@9
|
457 * spm_read_mat - read sparse matrix from text file
|
alpar@9
|
458 *
|
alpar@9
|
459 * SYNOPSIS
|
alpar@9
|
460 *
|
alpar@9
|
461 * #include "glpspm.h"
|
alpar@9
|
462 * SPM *spm_read_mat(const char *fname);
|
alpar@9
|
463 *
|
alpar@9
|
464 * DESCRIPTION
|
alpar@9
|
465 *
|
alpar@9
|
466 * The routine reads a sparse matrix from a text file whose name is
|
alpar@9
|
467 * specified by the parameter fname.
|
alpar@9
|
468 *
|
alpar@9
|
469 * For the file format see description of the routine spm_write_mat.
|
alpar@9
|
470 *
|
alpar@9
|
471 * RETURNS
|
alpar@9
|
472 *
|
alpar@9
|
473 * On success the routine returns a pointer to the matrix created,
|
alpar@9
|
474 * otherwise NULL. */
|
alpar@9
|
475
|
alpar@9
|
476 #if 1
|
alpar@9
|
477 SPM *spm_read_mat(const char *fname)
|
alpar@9
|
478 { xassert(fname != fname);
|
alpar@9
|
479 return NULL;
|
alpar@9
|
480 }
|
alpar@9
|
481 #else
|
alpar@9
|
482 SPM *spm_read_mat(const char *fname)
|
alpar@9
|
483 { SPM *A = NULL;
|
alpar@9
|
484 PDS *pds;
|
alpar@9
|
485 jmp_buf jump;
|
alpar@9
|
486 int i, j, k, m, n, nnz, fail = 0;
|
alpar@9
|
487 double val;
|
alpar@9
|
488 xprintf("spm_read_mat: reading matrix from `%s'...\n", fname);
|
alpar@9
|
489 pds = pds_open_file(fname);
|
alpar@9
|
490 if (pds == NULL)
|
alpar@9
|
491 { xprintf("spm_read_mat: unable to open `%s' - %s\n", fname,
|
alpar@9
|
492 strerror(errno));
|
alpar@9
|
493 fail = 1;
|
alpar@9
|
494 goto done;
|
alpar@9
|
495 }
|
alpar@9
|
496 if (setjmp(jump))
|
alpar@9
|
497 { fail = 1;
|
alpar@9
|
498 goto done;
|
alpar@9
|
499 }
|
alpar@9
|
500 pds_set_jump(pds, jump);
|
alpar@9
|
501 /* number of rows, number of columns, number of non-zeros */
|
alpar@9
|
502 m = pds_scan_int(pds);
|
alpar@9
|
503 if (m < 0)
|
alpar@9
|
504 pds_error(pds, "invalid number of rows\n");
|
alpar@9
|
505 n = pds_scan_int(pds);
|
alpar@9
|
506 if (n < 0)
|
alpar@9
|
507 pds_error(pds, "invalid number of columns\n");
|
alpar@9
|
508 nnz = pds_scan_int(pds);
|
alpar@9
|
509 if (nnz < 0)
|
alpar@9
|
510 pds_error(pds, "invalid number of non-zeros\n");
|
alpar@9
|
511 /* create matrix */
|
alpar@9
|
512 xprintf("spm_read_mat: %d rows, %d columns, %d non-zeros\n",
|
alpar@9
|
513 m, n, nnz);
|
alpar@9
|
514 A = spm_create_mat(m, n);
|
alpar@9
|
515 /* read matrix elements */
|
alpar@9
|
516 for (k = 1; k <= nnz; k++)
|
alpar@9
|
517 { /* row index, column index, element value */
|
alpar@9
|
518 i = pds_scan_int(pds);
|
alpar@9
|
519 if (!(1 <= i && i <= m))
|
alpar@9
|
520 pds_error(pds, "row index out of range\n");
|
alpar@9
|
521 j = pds_scan_int(pds);
|
alpar@9
|
522 if (!(1 <= j && j <= n))
|
alpar@9
|
523 pds_error(pds, "column index out of range\n");
|
alpar@9
|
524 val = pds_scan_num(pds);
|
alpar@9
|
525 /* add new element to the matrix */
|
alpar@9
|
526 spm_new_elem(A, i, j, val);
|
alpar@9
|
527 }
|
alpar@9
|
528 xprintf("spm_read_mat: %d lines were read\n", pds->count);
|
alpar@9
|
529 done: if (pds != NULL) pds_close_file(pds);
|
alpar@9
|
530 if (fail && A != NULL) spm_delete_mat(A), A = NULL;
|
alpar@9
|
531 return A;
|
alpar@9
|
532 }
|
alpar@9
|
533 #endif
|
alpar@9
|
534
|
alpar@9
|
535 /***********************************************************************
|
alpar@9
|
536 * NAME
|
alpar@9
|
537 *
|
alpar@9
|
538 * spm_write_mat - write sparse matrix to text file
|
alpar@9
|
539 *
|
alpar@9
|
540 * SYNOPSIS
|
alpar@9
|
541 *
|
alpar@9
|
542 * #include "glpspm.h"
|
alpar@9
|
543 * int spm_write_mat(const SPM *A, const char *fname);
|
alpar@9
|
544 *
|
alpar@9
|
545 * DESCRIPTION
|
alpar@9
|
546 *
|
alpar@9
|
547 * The routine spm_write_mat writes the specified sparse matrix to a
|
alpar@9
|
548 * text file whose name is specified by the parameter fname. This file
|
alpar@9
|
549 * can be read back with the routine spm_read_mat.
|
alpar@9
|
550 *
|
alpar@9
|
551 * RETURNS
|
alpar@9
|
552 *
|
alpar@9
|
553 * On success the routine returns zero, otherwise non-zero.
|
alpar@9
|
554 *
|
alpar@9
|
555 * FILE FORMAT
|
alpar@9
|
556 *
|
alpar@9
|
557 * The file created by the routine spm_write_mat is a plain text file,
|
alpar@9
|
558 * which contains the following information:
|
alpar@9
|
559 *
|
alpar@9
|
560 * m n nnz
|
alpar@9
|
561 * row[1] col[1] val[1]
|
alpar@9
|
562 * row[2] col[2] val[2]
|
alpar@9
|
563 * . . .
|
alpar@9
|
564 * row[nnz] col[nnz] val[nnz]
|
alpar@9
|
565 *
|
alpar@9
|
566 * where:
|
alpar@9
|
567 * m is the number of rows;
|
alpar@9
|
568 * n is the number of columns;
|
alpar@9
|
569 * nnz is the number of non-zeros;
|
alpar@9
|
570 * row[k], k = 1,...,nnz, are row indices;
|
alpar@9
|
571 * col[k], k = 1,...,nnz, are column indices;
|
alpar@9
|
572 * val[k], k = 1,...,nnz, are element values. */
|
alpar@9
|
573
|
alpar@9
|
574 #if 1
|
alpar@9
|
575 int spm_write_mat(const SPM *A, const char *fname)
|
alpar@9
|
576 { xassert(A != A);
|
alpar@9
|
577 xassert(fname != fname);
|
alpar@9
|
578 return 0;
|
alpar@9
|
579 }
|
alpar@9
|
580 #else
|
alpar@9
|
581 int spm_write_mat(const SPM *A, const char *fname)
|
alpar@9
|
582 { FILE *fp;
|
alpar@9
|
583 int i, nnz, ret = 0;
|
alpar@9
|
584 xprintf("spm_write_mat: writing matrix to `%s'...\n", fname);
|
alpar@9
|
585 fp = fopen(fname, "w");
|
alpar@9
|
586 if (fp == NULL)
|
alpar@9
|
587 { xprintf("spm_write_mat: unable to create `%s' - %s\n", fname,
|
alpar@9
|
588 strerror(errno));
|
alpar@9
|
589 ret = 1;
|
alpar@9
|
590 goto done;
|
alpar@9
|
591 }
|
alpar@9
|
592 /* number of rows, number of columns, number of non-zeros */
|
alpar@9
|
593 nnz = spm_count_nnz(A);
|
alpar@9
|
594 fprintf(fp, "%d %d %d\n", A->m, A->n, nnz);
|
alpar@9
|
595 /* walk through rows of the matrix */
|
alpar@9
|
596 for (i = 1; i <= A->m; i++)
|
alpar@9
|
597 { SPME *e;
|
alpar@9
|
598 /* walk through elements of i-th row */
|
alpar@9
|
599 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
600 { /* row index, column index, element value */
|
alpar@9
|
601 fprintf(fp, "%d %d %.*g\n", e->i, e->j, DBL_DIG, e->val);
|
alpar@9
|
602 }
|
alpar@9
|
603 }
|
alpar@9
|
604 fflush(fp);
|
alpar@9
|
605 if (ferror(fp))
|
alpar@9
|
606 { xprintf("spm_write_mat: writing error on `%s' - %s\n", fname,
|
alpar@9
|
607 strerror(errno));
|
alpar@9
|
608 ret = 1;
|
alpar@9
|
609 goto done;
|
alpar@9
|
610 }
|
alpar@9
|
611 xprintf("spm_write_mat: %d lines were written\n", 1 + nnz);
|
alpar@9
|
612 done: if (fp != NULL) fclose(fp);
|
alpar@9
|
613 return ret;
|
alpar@9
|
614 }
|
alpar@9
|
615 #endif
|
alpar@9
|
616
|
alpar@9
|
617 /***********************************************************************
|
alpar@9
|
618 * NAME
|
alpar@9
|
619 *
|
alpar@9
|
620 * spm_transpose - transpose sparse matrix
|
alpar@9
|
621 *
|
alpar@9
|
622 * SYNOPSIS
|
alpar@9
|
623 *
|
alpar@9
|
624 * #include "glpspm.h"
|
alpar@9
|
625 * SPM *spm_transpose(const SPM *A);
|
alpar@9
|
626 *
|
alpar@9
|
627 * RETURNS
|
alpar@9
|
628 *
|
alpar@9
|
629 * The routine computes and returns sparse matrix B, which is a matrix
|
alpar@9
|
630 * transposed to sparse matrix A. */
|
alpar@9
|
631
|
alpar@9
|
632 SPM *spm_transpose(const SPM *A)
|
alpar@9
|
633 { SPM *B;
|
alpar@9
|
634 int i;
|
alpar@9
|
635 B = spm_create_mat(A->n, A->m);
|
alpar@9
|
636 for (i = 1; i <= A->m; i++)
|
alpar@9
|
637 { SPME *e;
|
alpar@9
|
638 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
639 spm_new_elem(B, e->j, i, e->val);
|
alpar@9
|
640 }
|
alpar@9
|
641 return B;
|
alpar@9
|
642 }
|
alpar@9
|
643
|
alpar@9
|
644 SPM *spm_add_sym(const SPM *A, const SPM *B)
|
alpar@9
|
645 { /* add two sparse matrices (symbolic phase) */
|
alpar@9
|
646 SPM *C;
|
alpar@9
|
647 int i, j, *flag;
|
alpar@9
|
648 xassert(A->m == B->m);
|
alpar@9
|
649 xassert(A->n == B->n);
|
alpar@9
|
650 /* create resultant matrix */
|
alpar@9
|
651 C = spm_create_mat(A->m, A->n);
|
alpar@9
|
652 /* allocate and clear the flag array */
|
alpar@9
|
653 flag = xcalloc(1+C->n, sizeof(int));
|
alpar@9
|
654 for (j = 1; j <= C->n; j++)
|
alpar@9
|
655 flag[j] = 0;
|
alpar@9
|
656 /* compute pattern of C = A + B */
|
alpar@9
|
657 for (i = 1; i <= C->m; i++)
|
alpar@9
|
658 { SPME *e;
|
alpar@9
|
659 /* at the beginning i-th row of C is empty */
|
alpar@9
|
660 /* (i-th row of C) := (i-th row of C) union (i-th row of A) */
|
alpar@9
|
661 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
662 { /* (note that i-th row of A may have duplicate elements) */
|
alpar@9
|
663 j = e->j;
|
alpar@9
|
664 if (!flag[j])
|
alpar@9
|
665 { spm_new_elem(C, i, j, 0.0);
|
alpar@9
|
666 flag[j] = 1;
|
alpar@9
|
667 }
|
alpar@9
|
668 }
|
alpar@9
|
669 /* (i-th row of C) := (i-th row of C) union (i-th row of B) */
|
alpar@9
|
670 for (e = B->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
671 { /* (note that i-th row of B may have duplicate elements) */
|
alpar@9
|
672 j = e->j;
|
alpar@9
|
673 if (!flag[j])
|
alpar@9
|
674 { spm_new_elem(C, i, j, 0.0);
|
alpar@9
|
675 flag[j] = 1;
|
alpar@9
|
676 }
|
alpar@9
|
677 }
|
alpar@9
|
678 /* reset the flag array */
|
alpar@9
|
679 for (e = C->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
680 flag[e->j] = 0;
|
alpar@9
|
681 }
|
alpar@9
|
682 /* check and deallocate the flag array */
|
alpar@9
|
683 for (j = 1; j <= C->n; j++)
|
alpar@9
|
684 xassert(!flag[j]);
|
alpar@9
|
685 xfree(flag);
|
alpar@9
|
686 return C;
|
alpar@9
|
687 }
|
alpar@9
|
688
|
alpar@9
|
689 void spm_add_num(SPM *C, double alfa, const SPM *A, double beta,
|
alpar@9
|
690 const SPM *B)
|
alpar@9
|
691 { /* add two sparse matrices (numeric phase) */
|
alpar@9
|
692 int i, j;
|
alpar@9
|
693 double *work;
|
alpar@9
|
694 /* allocate and clear the working array */
|
alpar@9
|
695 work = xcalloc(1+C->n, sizeof(double));
|
alpar@9
|
696 for (j = 1; j <= C->n; j++)
|
alpar@9
|
697 work[j] = 0.0;
|
alpar@9
|
698 /* compute matrix C = alfa * A + beta * B */
|
alpar@9
|
699 for (i = 1; i <= C->n; i++)
|
alpar@9
|
700 { SPME *e;
|
alpar@9
|
701 /* work := alfa * (i-th row of A) + beta * (i-th row of B) */
|
alpar@9
|
702 /* (note that A and/or B may have duplicate elements) */
|
alpar@9
|
703 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
704 work[e->j] += alfa * e->val;
|
alpar@9
|
705 for (e = B->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
706 work[e->j] += beta * e->val;
|
alpar@9
|
707 /* (i-th row of C) := work, work := 0 */
|
alpar@9
|
708 for (e = C->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
709 { j = e->j;
|
alpar@9
|
710 e->val = work[j];
|
alpar@9
|
711 work[j] = 0.0;
|
alpar@9
|
712 }
|
alpar@9
|
713 }
|
alpar@9
|
714 /* check and deallocate the working array */
|
alpar@9
|
715 for (j = 1; j <= C->n; j++)
|
alpar@9
|
716 xassert(work[j] == 0.0);
|
alpar@9
|
717 xfree(work);
|
alpar@9
|
718 return;
|
alpar@9
|
719 }
|
alpar@9
|
720
|
alpar@9
|
721 SPM *spm_add_mat(double alfa, const SPM *A, double beta, const SPM *B)
|
alpar@9
|
722 { /* add two sparse matrices (driver routine) */
|
alpar@9
|
723 SPM *C;
|
alpar@9
|
724 C = spm_add_sym(A, B);
|
alpar@9
|
725 spm_add_num(C, alfa, A, beta, B);
|
alpar@9
|
726 return C;
|
alpar@9
|
727 }
|
alpar@9
|
728
|
alpar@9
|
729 SPM *spm_mul_sym(const SPM *A, const SPM *B)
|
alpar@9
|
730 { /* multiply two sparse matrices (symbolic phase) */
|
alpar@9
|
731 int i, j, k, *flag;
|
alpar@9
|
732 SPM *C;
|
alpar@9
|
733 xassert(A->n == B->m);
|
alpar@9
|
734 /* create resultant matrix */
|
alpar@9
|
735 C = spm_create_mat(A->m, B->n);
|
alpar@9
|
736 /* allocate and clear the flag array */
|
alpar@9
|
737 flag = xcalloc(1+C->n, sizeof(int));
|
alpar@9
|
738 for (j = 1; j <= C->n; j++)
|
alpar@9
|
739 flag[j] = 0;
|
alpar@9
|
740 /* compute pattern of C = A * B */
|
alpar@9
|
741 for (i = 1; i <= C->m; i++)
|
alpar@9
|
742 { SPME *e, *ee;
|
alpar@9
|
743 /* compute pattern of i-th row of C */
|
alpar@9
|
744 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
745 { k = e->j;
|
alpar@9
|
746 for (ee = B->row[k]; ee != NULL; ee = ee->r_next)
|
alpar@9
|
747 { j = ee->j;
|
alpar@9
|
748 /* if a[i,k] != 0 and b[k,j] != 0 then c[i,j] != 0 */
|
alpar@9
|
749 if (!flag[j])
|
alpar@9
|
750 { /* c[i,j] does not exist, so create it */
|
alpar@9
|
751 spm_new_elem(C, i, j, 0.0);
|
alpar@9
|
752 flag[j] = 1;
|
alpar@9
|
753 }
|
alpar@9
|
754 }
|
alpar@9
|
755 }
|
alpar@9
|
756 /* reset the flag array */
|
alpar@9
|
757 for (e = C->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
758 flag[e->j] = 0;
|
alpar@9
|
759 }
|
alpar@9
|
760 /* check and deallocate the flag array */
|
alpar@9
|
761 for (j = 1; j <= C->n; j++)
|
alpar@9
|
762 xassert(!flag[j]);
|
alpar@9
|
763 xfree(flag);
|
alpar@9
|
764 return C;
|
alpar@9
|
765 }
|
alpar@9
|
766
|
alpar@9
|
767 void spm_mul_num(SPM *C, const SPM *A, const SPM *B)
|
alpar@9
|
768 { /* multiply two sparse matrices (numeric phase) */
|
alpar@9
|
769 int i, j;
|
alpar@9
|
770 double *work;
|
alpar@9
|
771 /* allocate and clear the working array */
|
alpar@9
|
772 work = xcalloc(1+A->n, sizeof(double));
|
alpar@9
|
773 for (j = 1; j <= A->n; j++)
|
alpar@9
|
774 work[j] = 0.0;
|
alpar@9
|
775 /* compute matrix C = A * B */
|
alpar@9
|
776 for (i = 1; i <= C->m; i++)
|
alpar@9
|
777 { SPME *e, *ee;
|
alpar@9
|
778 double temp;
|
alpar@9
|
779 /* work := (i-th row of A) */
|
alpar@9
|
780 /* (note that A may have duplicate elements) */
|
alpar@9
|
781 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
782 work[e->j] += e->val;
|
alpar@9
|
783 /* compute i-th row of C */
|
alpar@9
|
784 for (e = C->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
785 { j = e->j;
|
alpar@9
|
786 /* c[i,j] := work * (j-th column of B) */
|
alpar@9
|
787 temp = 0.0;
|
alpar@9
|
788 for (ee = B->col[j]; ee != NULL; ee = ee->c_next)
|
alpar@9
|
789 temp += work[ee->i] * ee->val;
|
alpar@9
|
790 e->val = temp;
|
alpar@9
|
791 }
|
alpar@9
|
792 /* reset the working array */
|
alpar@9
|
793 for (e = A->row[i]; e != NULL; e = e->r_next)
|
alpar@9
|
794 work[e->j] = 0.0;
|
alpar@9
|
795 }
|
alpar@9
|
796 /* check and deallocate the working array */
|
alpar@9
|
797 for (j = 1; j <= A->n; j++)
|
alpar@9
|
798 xassert(work[j] == 0.0);
|
alpar@9
|
799 xfree(work);
|
alpar@9
|
800 return;
|
alpar@9
|
801 }
|
alpar@9
|
802
|
alpar@9
|
803 SPM *spm_mul_mat(const SPM *A, const SPM *B)
|
alpar@9
|
804 { /* multiply two sparse matrices (driver routine) */
|
alpar@9
|
805 SPM *C;
|
alpar@9
|
806 C = spm_mul_sym(A, B);
|
alpar@9
|
807 spm_mul_num(C, A, B);
|
alpar@9
|
808 return C;
|
alpar@9
|
809 }
|
alpar@9
|
810
|
alpar@9
|
811 PER *spm_create_per(int n)
|
alpar@9
|
812 { /* create permutation matrix */
|
alpar@9
|
813 PER *P;
|
alpar@9
|
814 int k;
|
alpar@9
|
815 xassert(n >= 0);
|
alpar@9
|
816 P = xmalloc(sizeof(PER));
|
alpar@9
|
817 P->n = n;
|
alpar@9
|
818 P->row = xcalloc(1+n, sizeof(int));
|
alpar@9
|
819 P->col = xcalloc(1+n, sizeof(int));
|
alpar@9
|
820 /* initially it is identity matrix */
|
alpar@9
|
821 for (k = 1; k <= n; k++)
|
alpar@9
|
822 P->row[k] = P->col[k] = k;
|
alpar@9
|
823 return P;
|
alpar@9
|
824 }
|
alpar@9
|
825
|
alpar@9
|
826 void spm_check_per(PER *P)
|
alpar@9
|
827 { /* check permutation matrix for correctness */
|
alpar@9
|
828 int i, j;
|
alpar@9
|
829 xassert(P->n >= 0);
|
alpar@9
|
830 for (i = 1; i <= P->n; i++)
|
alpar@9
|
831 { j = P->row[i];
|
alpar@9
|
832 xassert(1 <= j && j <= P->n);
|
alpar@9
|
833 xassert(P->col[j] == i);
|
alpar@9
|
834 }
|
alpar@9
|
835 return;
|
alpar@9
|
836 }
|
alpar@9
|
837
|
alpar@9
|
838 void spm_delete_per(PER *P)
|
alpar@9
|
839 { /* delete permutation matrix */
|
alpar@9
|
840 xfree(P->row);
|
alpar@9
|
841 xfree(P->col);
|
alpar@9
|
842 xfree(P);
|
alpar@9
|
843 return;
|
alpar@9
|
844 }
|
alpar@9
|
845
|
alpar@9
|
846 /* eof */
|