isl_ast_build_from_context: allow unnamed set dimensions
[isl.git] / isl_sample.c
blobc6a0f314425b0bc2d4683589997a3034b652abe0
1 /*
2 * Copyright 2008-2009 Katholieke Universiteit Leuven
4 * Use of this software is governed by the MIT license
6 * Written by Sven Verdoolaege, K.U.Leuven, Departement
7 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
8 */
10 #include <isl_ctx_private.h>
11 #include <isl_map_private.h>
12 #include "isl_sample.h"
13 #include "isl_sample_piplib.h"
14 #include <isl/vec.h>
15 #include <isl/mat.h>
16 #include <isl/seq.h>
17 #include "isl_equalities.h"
18 #include "isl_tab.h"
19 #include "isl_basis_reduction.h"
20 #include <isl_factorization.h>
21 #include <isl_point_private.h>
22 #include <isl_options_private.h>
24 static struct isl_vec *empty_sample(struct isl_basic_set *bset)
26 struct isl_vec *vec;
28 vec = isl_vec_alloc(bset->ctx, 0);
29 isl_basic_set_free(bset);
30 return vec;
33 /* Construct a zero sample of the same dimension as bset.
34 * As a special case, if bset is zero-dimensional, this
35 * function creates a zero-dimensional sample point.
37 static struct isl_vec *zero_sample(struct isl_basic_set *bset)
39 unsigned dim;
40 struct isl_vec *sample;
42 dim = isl_basic_set_total_dim(bset);
43 sample = isl_vec_alloc(bset->ctx, 1 + dim);
44 if (sample) {
45 isl_int_set_si(sample->el[0], 1);
46 isl_seq_clr(sample->el + 1, dim);
48 isl_basic_set_free(bset);
49 return sample;
52 static struct isl_vec *interval_sample(struct isl_basic_set *bset)
54 int i;
55 isl_int t;
56 struct isl_vec *sample;
58 bset = isl_basic_set_simplify(bset);
59 if (!bset)
60 return NULL;
61 if (isl_basic_set_plain_is_empty(bset))
62 return empty_sample(bset);
63 if (bset->n_eq == 0 && bset->n_ineq == 0)
64 return zero_sample(bset);
66 sample = isl_vec_alloc(bset->ctx, 2);
67 if (!sample)
68 goto error;
69 if (!bset)
70 return NULL;
71 isl_int_set_si(sample->block.data[0], 1);
73 if (bset->n_eq > 0) {
74 isl_assert(bset->ctx, bset->n_eq == 1, goto error);
75 isl_assert(bset->ctx, bset->n_ineq == 0, goto error);
76 if (isl_int_is_one(bset->eq[0][1]))
77 isl_int_neg(sample->el[1], bset->eq[0][0]);
78 else {
79 isl_assert(bset->ctx, isl_int_is_negone(bset->eq[0][1]),
80 goto error);
81 isl_int_set(sample->el[1], bset->eq[0][0]);
83 isl_basic_set_free(bset);
84 return sample;
87 isl_int_init(t);
88 if (isl_int_is_one(bset->ineq[0][1]))
89 isl_int_neg(sample->block.data[1], bset->ineq[0][0]);
90 else
91 isl_int_set(sample->block.data[1], bset->ineq[0][0]);
92 for (i = 1; i < bset->n_ineq; ++i) {
93 isl_seq_inner_product(sample->block.data,
94 bset->ineq[i], 2, &t);
95 if (isl_int_is_neg(t))
96 break;
98 isl_int_clear(t);
99 if (i < bset->n_ineq) {
100 isl_vec_free(sample);
101 return empty_sample(bset);
104 isl_basic_set_free(bset);
105 return sample;
106 error:
107 isl_basic_set_free(bset);
108 isl_vec_free(sample);
109 return NULL;
112 static struct isl_mat *independent_bounds(struct isl_basic_set *bset)
114 int i, j, n;
115 struct isl_mat *dirs = NULL;
116 struct isl_mat *bounds = NULL;
117 unsigned dim;
119 if (!bset)
120 return NULL;
122 dim = isl_basic_set_n_dim(bset);
123 bounds = isl_mat_alloc(bset->ctx, 1+dim, 1+dim);
124 if (!bounds)
125 return NULL;
127 isl_int_set_si(bounds->row[0][0], 1);
128 isl_seq_clr(bounds->row[0]+1, dim);
129 bounds->n_row = 1;
131 if (bset->n_ineq == 0)
132 return bounds;
134 dirs = isl_mat_alloc(bset->ctx, dim, dim);
135 if (!dirs) {
136 isl_mat_free(bounds);
137 return NULL;
139 isl_seq_cpy(dirs->row[0], bset->ineq[0]+1, dirs->n_col);
140 isl_seq_cpy(bounds->row[1], bset->ineq[0], bounds->n_col);
141 for (j = 1, n = 1; n < dim && j < bset->n_ineq; ++j) {
142 int pos;
144 isl_seq_cpy(dirs->row[n], bset->ineq[j]+1, dirs->n_col);
146 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
147 if (pos < 0)
148 continue;
149 for (i = 0; i < n; ++i) {
150 int pos_i;
151 pos_i = isl_seq_first_non_zero(dirs->row[i], dirs->n_col);
152 if (pos_i < pos)
153 continue;
154 if (pos_i > pos)
155 break;
156 isl_seq_elim(dirs->row[n], dirs->row[i], pos,
157 dirs->n_col, NULL);
158 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
159 if (pos < 0)
160 break;
162 if (pos < 0)
163 continue;
164 if (i < n) {
165 int k;
166 isl_int *t = dirs->row[n];
167 for (k = n; k > i; --k)
168 dirs->row[k] = dirs->row[k-1];
169 dirs->row[i] = t;
171 ++n;
172 isl_seq_cpy(bounds->row[n], bset->ineq[j], bounds->n_col);
174 isl_mat_free(dirs);
175 bounds->n_row = 1+n;
176 return bounds;
179 static void swap_inequality(struct isl_basic_set *bset, int a, int b)
181 isl_int *t = bset->ineq[a];
182 bset->ineq[a] = bset->ineq[b];
183 bset->ineq[b] = t;
186 /* Skew into positive orthant and project out lineality space.
188 * We perform a unimodular transformation that turns a selected
189 * maximal set of linearly independent bounds into constraints
190 * on the first dimensions that impose that these first dimensions
191 * are non-negative. In particular, the constraint matrix is lower
192 * triangular with positive entries on the diagonal and negative
193 * entries below.
194 * If "bset" has a lineality space then these constraints (and therefore
195 * all constraints in bset) only involve the first dimensions.
196 * The remaining dimensions then do not appear in any constraints and
197 * we can select any value for them, say zero. We therefore project
198 * out this final dimensions and plug in the value zero later. This
199 * is accomplished by simply dropping the final columns of
200 * the unimodular transformation.
202 static struct isl_basic_set *isl_basic_set_skew_to_positive_orthant(
203 struct isl_basic_set *bset, struct isl_mat **T)
205 struct isl_mat *U = NULL;
206 struct isl_mat *bounds = NULL;
207 int i, j;
208 unsigned old_dim, new_dim;
210 *T = NULL;
211 if (!bset)
212 return NULL;
214 isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
215 isl_assert(bset->ctx, bset->n_div == 0, goto error);
216 isl_assert(bset->ctx, bset->n_eq == 0, goto error);
218 old_dim = isl_basic_set_n_dim(bset);
219 /* Try to move (multiples of) unit rows up. */
220 for (i = 0, j = 0; i < bset->n_ineq; ++i) {
221 int pos = isl_seq_first_non_zero(bset->ineq[i]+1, old_dim);
222 if (pos < 0)
223 continue;
224 if (isl_seq_first_non_zero(bset->ineq[i]+1+pos+1,
225 old_dim-pos-1) >= 0)
226 continue;
227 if (i != j)
228 swap_inequality(bset, i, j);
229 ++j;
231 bounds = independent_bounds(bset);
232 if (!bounds)
233 goto error;
234 new_dim = bounds->n_row - 1;
235 bounds = isl_mat_left_hermite(bounds, 1, &U, NULL);
236 if (!bounds)
237 goto error;
238 U = isl_mat_drop_cols(U, 1 + new_dim, old_dim - new_dim);
239 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
240 if (!bset)
241 goto error;
242 *T = U;
243 isl_mat_free(bounds);
244 return bset;
245 error:
246 isl_mat_free(bounds);
247 isl_mat_free(U);
248 isl_basic_set_free(bset);
249 return NULL;
252 /* Find a sample integer point, if any, in bset, which is known
253 * to have equalities. If bset contains no integer points, then
254 * return a zero-length vector.
255 * We simply remove the known equalities, compute a sample
256 * in the resulting bset, using the specified recurse function,
257 * and then transform the sample back to the original space.
259 static struct isl_vec *sample_eq(struct isl_basic_set *bset,
260 struct isl_vec *(*recurse)(struct isl_basic_set *))
262 struct isl_mat *T;
263 struct isl_vec *sample;
265 if (!bset)
266 return NULL;
268 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
269 sample = recurse(bset);
270 if (!sample || sample->size == 0)
271 isl_mat_free(T);
272 else
273 sample = isl_mat_vec_product(T, sample);
274 return sample;
277 /* Return a matrix containing the equalities of the tableau
278 * in constraint form. The tableau is assumed to have
279 * an associated bset that has been kept up-to-date.
281 static struct isl_mat *tab_equalities(struct isl_tab *tab)
283 int i, j;
284 int n_eq;
285 struct isl_mat *eq;
286 struct isl_basic_set *bset;
288 if (!tab)
289 return NULL;
291 bset = isl_tab_peek_bset(tab);
292 isl_assert(tab->mat->ctx, bset, return NULL);
294 n_eq = tab->n_var - tab->n_col + tab->n_dead;
295 if (tab->empty || n_eq == 0)
296 return isl_mat_alloc(tab->mat->ctx, 0, tab->n_var);
297 if (n_eq == tab->n_var)
298 return isl_mat_identity(tab->mat->ctx, tab->n_var);
300 eq = isl_mat_alloc(tab->mat->ctx, n_eq, tab->n_var);
301 if (!eq)
302 return NULL;
303 for (i = 0, j = 0; i < tab->n_con; ++i) {
304 if (tab->con[i].is_row)
305 continue;
306 if (tab->con[i].index >= 0 && tab->con[i].index >= tab->n_dead)
307 continue;
308 if (i < bset->n_eq)
309 isl_seq_cpy(eq->row[j], bset->eq[i] + 1, tab->n_var);
310 else
311 isl_seq_cpy(eq->row[j],
312 bset->ineq[i - bset->n_eq] + 1, tab->n_var);
313 ++j;
315 isl_assert(bset->ctx, j == n_eq, goto error);
316 return eq;
317 error:
318 isl_mat_free(eq);
319 return NULL;
322 /* Compute and return an initial basis for the bounded tableau "tab".
324 * If the tableau is either full-dimensional or zero-dimensional,
325 * the we simply return an identity matrix.
326 * Otherwise, we construct a basis whose first directions correspond
327 * to equalities.
329 static struct isl_mat *initial_basis(struct isl_tab *tab)
331 int n_eq;
332 struct isl_mat *eq;
333 struct isl_mat *Q;
335 tab->n_unbounded = 0;
336 tab->n_zero = n_eq = tab->n_var - tab->n_col + tab->n_dead;
337 if (tab->empty || n_eq == 0 || n_eq == tab->n_var)
338 return isl_mat_identity(tab->mat->ctx, 1 + tab->n_var);
340 eq = tab_equalities(tab);
341 eq = isl_mat_left_hermite(eq, 0, NULL, &Q);
342 if (!eq)
343 return NULL;
344 isl_mat_free(eq);
346 Q = isl_mat_lin_to_aff(Q);
347 return Q;
350 /* Compute the minimum of the current ("level") basis row over "tab"
351 * and store the result in position "level" of "min".
353 static enum isl_lp_result compute_min(isl_ctx *ctx, struct isl_tab *tab,
354 __isl_keep isl_vec *min, int level)
356 return isl_tab_min(tab, tab->basis->row[1 + level],
357 ctx->one, &min->el[level], NULL, 0);
360 /* Compute the maximum of the current ("level") basis row over "tab"
361 * and store the result in position "level" of "max".
363 static enum isl_lp_result compute_max(isl_ctx *ctx, struct isl_tab *tab,
364 __isl_keep isl_vec *max, int level)
366 enum isl_lp_result res;
367 unsigned dim = tab->n_var;
369 isl_seq_neg(tab->basis->row[1 + level] + 1,
370 tab->basis->row[1 + level] + 1, dim);
371 res = isl_tab_min(tab, tab->basis->row[1 + level],
372 ctx->one, &max->el[level], NULL, 0);
373 isl_seq_neg(tab->basis->row[1 + level] + 1,
374 tab->basis->row[1 + level] + 1, dim);
375 isl_int_neg(max->el[level], max->el[level]);
377 return res;
380 /* Perform a greedy search for an integer point in the set represented
381 * by "tab", given that the minimal rational value (rounded up to the
382 * nearest integer) at "level" is smaller than the maximal rational
383 * value (rounded down to the nearest integer).
385 * Return 1 if we have found an integer point (if tab->n_unbounded > 0
386 * then we may have only found integer values for the bounded dimensions
387 * and it is the responsibility of the caller to extend this solution
388 * to the unbounded dimensions).
389 * Return 0 if greedy search did not result in a solution.
390 * Return -1 if some error occurred.
392 * We assign a value half-way between the minimum and the maximum
393 * to the current dimension and check if the minimal value of the
394 * next dimension is still smaller than (or equal) to the maximal value.
395 * We continue this process until either
396 * - the minimal value (rounded up) is greater than the maximal value
397 * (rounded down). In this case, greedy search has failed.
398 * - we have exhausted all bounded dimensions, meaning that we have
399 * found a solution.
400 * - the sample value of the tableau is integral.
401 * - some error has occurred.
403 static int greedy_search(isl_ctx *ctx, struct isl_tab *tab,
404 __isl_keep isl_vec *min, __isl_keep isl_vec *max, int level)
406 struct isl_tab_undo *snap;
407 enum isl_lp_result res;
409 snap = isl_tab_snap(tab);
411 do {
412 isl_int_add(tab->basis->row[1 + level][0],
413 min->el[level], max->el[level]);
414 isl_int_fdiv_q_ui(tab->basis->row[1 + level][0],
415 tab->basis->row[1 + level][0], 2);
416 isl_int_neg(tab->basis->row[1 + level][0],
417 tab->basis->row[1 + level][0]);
418 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
419 return -1;
420 isl_int_set_si(tab->basis->row[1 + level][0], 0);
422 if (++level >= tab->n_var - tab->n_unbounded)
423 return 1;
424 if (isl_tab_sample_is_integer(tab))
425 return 1;
427 res = compute_min(ctx, tab, min, level);
428 if (res == isl_lp_error)
429 return -1;
430 if (res != isl_lp_ok)
431 isl_die(ctx, isl_error_internal,
432 "expecting bounded rational solution",
433 return -1);
434 res = compute_max(ctx, tab, max, level);
435 if (res == isl_lp_error)
436 return -1;
437 if (res != isl_lp_ok)
438 isl_die(ctx, isl_error_internal,
439 "expecting bounded rational solution",
440 return -1);
441 } while (isl_int_le(min->el[level], max->el[level]));
443 if (isl_tab_rollback(tab, snap) < 0)
444 return -1;
446 return 0;
449 /* Given a tableau representing a set, find and return
450 * an integer point in the set, if there is any.
452 * We perform a depth first search
453 * for an integer point, by scanning all possible values in the range
454 * attained by a basis vector, where an initial basis may have been set
455 * by the calling function. Otherwise an initial basis that exploits
456 * the equalities in the tableau is created.
457 * tab->n_zero is currently ignored and is clobbered by this function.
459 * The tableau is allowed to have unbounded direction, but then
460 * the calling function needs to set an initial basis, with the
461 * unbounded directions last and with tab->n_unbounded set
462 * to the number of unbounded directions.
463 * Furthermore, the calling functions needs to add shifted copies
464 * of all constraints involving unbounded directions to ensure
465 * that any feasible rational value in these directions can be rounded
466 * up to yield a feasible integer value.
467 * In particular, let B define the given basis x' = B x
468 * and let T be the inverse of B, i.e., X = T x'.
469 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
470 * or a T x' + c >= 0 in terms of the given basis. Assume that
471 * the bounded directions have an integer value, then we can safely
472 * round up the values for the unbounded directions if we make sure
473 * that x' not only satisfies the original constraint, but also
474 * the constraint "a T x' + c + s >= 0" with s the sum of all
475 * negative values in the last n_unbounded entries of "a T".
476 * The calling function therefore needs to add the constraint
477 * a x + c + s >= 0. The current function then scans the first
478 * directions for an integer value and once those have been found,
479 * it can compute "T ceil(B x)" to yield an integer point in the set.
480 * Note that during the search, the first rows of B may be changed
481 * by a basis reduction, but the last n_unbounded rows of B remain
482 * unaltered and are also not mixed into the first rows.
484 * The search is implemented iteratively. "level" identifies the current
485 * basis vector. "init" is true if we want the first value at the current
486 * level and false if we want the next value.
488 * At the start of each level, we first check if we can find a solution
489 * using greedy search. If not, we continue with the exhaustive search.
491 * The initial basis is the identity matrix. If the range in some direction
492 * contains more than one integer value, we perform basis reduction based
493 * on the value of ctx->opt->gbr
494 * - ISL_GBR_NEVER: never perform basis reduction
495 * - ISL_GBR_ONCE: only perform basis reduction the first
496 * time such a range is encountered
497 * - ISL_GBR_ALWAYS: always perform basis reduction when
498 * such a range is encountered
500 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
501 * reduction computation to return early. That is, as soon as it
502 * finds a reasonable first direction.
504 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
506 unsigned dim;
507 unsigned gbr;
508 struct isl_ctx *ctx;
509 struct isl_vec *sample;
510 struct isl_vec *min;
511 struct isl_vec *max;
512 enum isl_lp_result res;
513 int level;
514 int init;
515 int reduced;
516 struct isl_tab_undo **snap;
518 if (!tab)
519 return NULL;
520 if (tab->empty)
521 return isl_vec_alloc(tab->mat->ctx, 0);
523 if (!tab->basis)
524 tab->basis = initial_basis(tab);
525 if (!tab->basis)
526 return NULL;
527 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
528 return NULL);
529 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
530 return NULL);
532 ctx = tab->mat->ctx;
533 dim = tab->n_var;
534 gbr = ctx->opt->gbr;
536 if (tab->n_unbounded == tab->n_var) {
537 sample = isl_tab_get_sample_value(tab);
538 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
539 sample = isl_vec_ceil(sample);
540 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
541 sample);
542 return sample;
545 if (isl_tab_extend_cons(tab, dim + 1) < 0)
546 return NULL;
548 min = isl_vec_alloc(ctx, dim);
549 max = isl_vec_alloc(ctx, dim);
550 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
552 if (!min || !max || !snap)
553 goto error;
555 level = 0;
556 init = 1;
557 reduced = 0;
559 while (level >= 0) {
560 if (init) {
561 int choice;
563 res = compute_min(ctx, tab, min, level);
564 if (res == isl_lp_error)
565 goto error;
566 if (res != isl_lp_ok)
567 isl_die(ctx, isl_error_internal,
568 "expecting bounded rational solution",
569 goto error);
570 if (isl_tab_sample_is_integer(tab))
571 break;
572 res = compute_max(ctx, tab, max, level);
573 if (res == isl_lp_error)
574 goto error;
575 if (res != isl_lp_ok)
576 isl_die(ctx, isl_error_internal,
577 "expecting bounded rational solution",
578 goto error);
579 if (isl_tab_sample_is_integer(tab))
580 break;
581 choice = isl_int_lt(min->el[level], max->el[level]);
582 if (choice) {
583 int g;
584 g = greedy_search(ctx, tab, min, max, level);
585 if (g < 0)
586 goto error;
587 if (g)
588 break;
590 if (!reduced && choice &&
591 ctx->opt->gbr != ISL_GBR_NEVER) {
592 unsigned gbr_only_first;
593 if (ctx->opt->gbr == ISL_GBR_ONCE)
594 ctx->opt->gbr = ISL_GBR_NEVER;
595 tab->n_zero = level;
596 gbr_only_first = ctx->opt->gbr_only_first;
597 ctx->opt->gbr_only_first =
598 ctx->opt->gbr == ISL_GBR_ALWAYS;
599 tab = isl_tab_compute_reduced_basis(tab);
600 ctx->opt->gbr_only_first = gbr_only_first;
601 if (!tab || !tab->basis)
602 goto error;
603 reduced = 1;
604 continue;
606 reduced = 0;
607 snap[level] = isl_tab_snap(tab);
608 } else
609 isl_int_add_ui(min->el[level], min->el[level], 1);
611 if (isl_int_gt(min->el[level], max->el[level])) {
612 level--;
613 init = 0;
614 if (level >= 0)
615 if (isl_tab_rollback(tab, snap[level]) < 0)
616 goto error;
617 continue;
619 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
620 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
621 goto error;
622 isl_int_set_si(tab->basis->row[1 + level][0], 0);
623 if (level + tab->n_unbounded < dim - 1) {
624 ++level;
625 init = 1;
626 continue;
628 break;
631 if (level >= 0) {
632 sample = isl_tab_get_sample_value(tab);
633 if (!sample)
634 goto error;
635 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
636 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
637 sample);
638 sample = isl_vec_ceil(sample);
639 sample = isl_mat_vec_inverse_product(
640 isl_mat_copy(tab->basis), sample);
642 } else
643 sample = isl_vec_alloc(ctx, 0);
645 ctx->opt->gbr = gbr;
646 isl_vec_free(min);
647 isl_vec_free(max);
648 free(snap);
649 return sample;
650 error:
651 ctx->opt->gbr = gbr;
652 isl_vec_free(min);
653 isl_vec_free(max);
654 free(snap);
655 return NULL;
658 static struct isl_vec *sample_bounded(struct isl_basic_set *bset);
660 /* Compute a sample point of the given basic set, based on the given,
661 * non-trivial factorization.
663 static __isl_give isl_vec *factored_sample(__isl_take isl_basic_set *bset,
664 __isl_take isl_factorizer *f)
666 int i, n;
667 isl_vec *sample = NULL;
668 isl_ctx *ctx;
669 unsigned nparam;
670 unsigned nvar;
672 ctx = isl_basic_set_get_ctx(bset);
673 if (!ctx)
674 goto error;
676 nparam = isl_basic_set_dim(bset, isl_dim_param);
677 nvar = isl_basic_set_dim(bset, isl_dim_set);
679 sample = isl_vec_alloc(ctx, 1 + isl_basic_set_total_dim(bset));
680 if (!sample)
681 goto error;
682 isl_int_set_si(sample->el[0], 1);
684 bset = isl_morph_basic_set(isl_morph_copy(f->morph), bset);
686 for (i = 0, n = 0; i < f->n_group; ++i) {
687 isl_basic_set *bset_i;
688 isl_vec *sample_i;
690 bset_i = isl_basic_set_copy(bset);
691 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
692 nparam + n + f->len[i], nvar - n - f->len[i]);
693 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
694 nparam, n);
695 bset_i = isl_basic_set_drop(bset_i, isl_dim_set,
696 n + f->len[i], nvar - n - f->len[i]);
697 bset_i = isl_basic_set_drop(bset_i, isl_dim_set, 0, n);
699 sample_i = sample_bounded(bset_i);
700 if (!sample_i)
701 goto error;
702 if (sample_i->size == 0) {
703 isl_basic_set_free(bset);
704 isl_factorizer_free(f);
705 isl_vec_free(sample);
706 return sample_i;
708 isl_seq_cpy(sample->el + 1 + nparam + n,
709 sample_i->el + 1, f->len[i]);
710 isl_vec_free(sample_i);
712 n += f->len[i];
715 f->morph = isl_morph_inverse(f->morph);
716 sample = isl_morph_vec(isl_morph_copy(f->morph), sample);
718 isl_basic_set_free(bset);
719 isl_factorizer_free(f);
720 return sample;
721 error:
722 isl_basic_set_free(bset);
723 isl_factorizer_free(f);
724 isl_vec_free(sample);
725 return NULL;
728 /* Given a basic set that is known to be bounded, find and return
729 * an integer point in the basic set, if there is any.
731 * After handling some trivial cases, we construct a tableau
732 * and then use isl_tab_sample to find a sample, passing it
733 * the identity matrix as initial basis.
735 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
737 unsigned dim;
738 struct isl_ctx *ctx;
739 struct isl_vec *sample;
740 struct isl_tab *tab = NULL;
741 isl_factorizer *f;
743 if (!bset)
744 return NULL;
746 if (isl_basic_set_plain_is_empty(bset))
747 return empty_sample(bset);
749 dim = isl_basic_set_total_dim(bset);
750 if (dim == 0)
751 return zero_sample(bset);
752 if (dim == 1)
753 return interval_sample(bset);
754 if (bset->n_eq > 0)
755 return sample_eq(bset, sample_bounded);
757 f = isl_basic_set_factorizer(bset);
758 if (!f)
759 goto error;
760 if (f->n_group != 0)
761 return factored_sample(bset, f);
762 isl_factorizer_free(f);
764 ctx = bset->ctx;
766 tab = isl_tab_from_basic_set(bset, 1);
767 if (tab && tab->empty) {
768 isl_tab_free(tab);
769 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
770 sample = isl_vec_alloc(bset->ctx, 0);
771 isl_basic_set_free(bset);
772 return sample;
775 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
776 if (isl_tab_detect_implicit_equalities(tab) < 0)
777 goto error;
779 sample = isl_tab_sample(tab);
780 if (!sample)
781 goto error;
783 if (sample->size > 0) {
784 isl_vec_free(bset->sample);
785 bset->sample = isl_vec_copy(sample);
788 isl_basic_set_free(bset);
789 isl_tab_free(tab);
790 return sample;
791 error:
792 isl_basic_set_free(bset);
793 isl_tab_free(tab);
794 return NULL;
797 /* Given a basic set "bset" and a value "sample" for the first coordinates
798 * of bset, plug in these values and drop the corresponding coordinates.
800 * We do this by computing the preimage of the transformation
802 * [ 1 0 ]
803 * x = [ s 0 ] x'
804 * [ 0 I ]
806 * where [1 s] is the sample value and I is the identity matrix of the
807 * appropriate dimension.
809 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
810 struct isl_vec *sample)
812 int i;
813 unsigned total;
814 struct isl_mat *T;
816 if (!bset || !sample)
817 goto error;
819 total = isl_basic_set_total_dim(bset);
820 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
821 if (!T)
822 goto error;
824 for (i = 0; i < sample->size; ++i) {
825 isl_int_set(T->row[i][0], sample->el[i]);
826 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
828 for (i = 0; i < T->n_col - 1; ++i) {
829 isl_seq_clr(T->row[sample->size + i], T->n_col);
830 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
832 isl_vec_free(sample);
834 bset = isl_basic_set_preimage(bset, T);
835 return bset;
836 error:
837 isl_basic_set_free(bset);
838 isl_vec_free(sample);
839 return NULL;
842 /* Given a basic set "bset", return any (possibly non-integer) point
843 * in the basic set.
845 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
847 struct isl_tab *tab;
848 struct isl_vec *sample;
850 if (!bset)
851 return NULL;
853 tab = isl_tab_from_basic_set(bset, 0);
854 sample = isl_tab_get_sample_value(tab);
855 isl_tab_free(tab);
857 isl_basic_set_free(bset);
859 return sample;
862 /* Given a linear cone "cone" and a rational point "vec",
863 * construct a polyhedron with shifted copies of the constraints in "cone",
864 * i.e., a polyhedron with "cone" as its recession cone, such that each
865 * point x in this polyhedron is such that the unit box positioned at x
866 * lies entirely inside the affine cone 'vec + cone'.
867 * Any rational point in this polyhedron may therefore be rounded up
868 * to yield an integer point that lies inside said affine cone.
870 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
871 * point "vec" by v/d.
872 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
873 * by <a_i, x> - b/d >= 0.
874 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
875 * We prefer this polyhedron over the actual affine cone because it doesn't
876 * require a scaling of the constraints.
877 * If each of the vertices of the unit cube positioned at x lies inside
878 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
879 * We therefore impose that x' = x + \sum e_i, for any selection of unit
880 * vectors lies inside the polyhedron, i.e.,
882 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
884 * The most stringent of these constraints is the one that selects
885 * all negative a_i, so the polyhedron we are looking for has constraints
887 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
889 * Note that if cone were known to have only non-negative rays
890 * (which can be accomplished by a unimodular transformation),
891 * then we would only have to check the points x' = x + e_i
892 * and we only have to add the smallest negative a_i (if any)
893 * instead of the sum of all negative a_i.
895 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
896 struct isl_vec *vec)
898 int i, j, k;
899 unsigned total;
901 struct isl_basic_set *shift = NULL;
903 if (!cone || !vec)
904 goto error;
906 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
908 total = isl_basic_set_total_dim(cone);
910 shift = isl_basic_set_alloc_space(isl_basic_set_get_space(cone),
911 0, 0, cone->n_ineq);
913 for (i = 0; i < cone->n_ineq; ++i) {
914 k = isl_basic_set_alloc_inequality(shift);
915 if (k < 0)
916 goto error;
917 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
918 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
919 &shift->ineq[k][0]);
920 isl_int_cdiv_q(shift->ineq[k][0],
921 shift->ineq[k][0], vec->el[0]);
922 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
923 for (j = 0; j < total; ++j) {
924 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
925 continue;
926 isl_int_add(shift->ineq[k][0],
927 shift->ineq[k][0], shift->ineq[k][1 + j]);
931 isl_basic_set_free(cone);
932 isl_vec_free(vec);
934 return isl_basic_set_finalize(shift);
935 error:
936 isl_basic_set_free(shift);
937 isl_basic_set_free(cone);
938 isl_vec_free(vec);
939 return NULL;
942 /* Given a rational point vec in a (transformed) basic set,
943 * such that cone is the recession cone of the original basic set,
944 * "round up" the rational point to an integer point.
946 * We first check if the rational point just happens to be integer.
947 * If not, we transform the cone in the same way as the basic set,
948 * pick a point x in this cone shifted to the rational point such that
949 * the whole unit cube at x is also inside this affine cone.
950 * Then we simply round up the coordinates of x and return the
951 * resulting integer point.
953 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
954 struct isl_basic_set *cone, struct isl_mat *U)
956 unsigned total;
958 if (!vec || !cone || !U)
959 goto error;
961 isl_assert(vec->ctx, vec->size != 0, goto error);
962 if (isl_int_is_one(vec->el[0])) {
963 isl_mat_free(U);
964 isl_basic_set_free(cone);
965 return vec;
968 total = isl_basic_set_total_dim(cone);
969 cone = isl_basic_set_preimage(cone, U);
970 cone = isl_basic_set_remove_dims(cone, isl_dim_set,
971 0, total - (vec->size - 1));
973 cone = shift_cone(cone, vec);
975 vec = rational_sample(cone);
976 vec = isl_vec_ceil(vec);
977 return vec;
978 error:
979 isl_mat_free(U);
980 isl_vec_free(vec);
981 isl_basic_set_free(cone);
982 return NULL;
985 /* Concatenate two integer vectors, i.e., two vectors with denominator
986 * (stored in element 0) equal to 1.
988 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
990 struct isl_vec *vec;
992 if (!vec1 || !vec2)
993 goto error;
994 isl_assert(vec1->ctx, vec1->size > 0, goto error);
995 isl_assert(vec2->ctx, vec2->size > 0, goto error);
996 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
997 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
999 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
1000 if (!vec)
1001 goto error;
1003 isl_seq_cpy(vec->el, vec1->el, vec1->size);
1004 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
1006 isl_vec_free(vec1);
1007 isl_vec_free(vec2);
1009 return vec;
1010 error:
1011 isl_vec_free(vec1);
1012 isl_vec_free(vec2);
1013 return NULL;
1016 /* Give a basic set "bset" with recession cone "cone", compute and
1017 * return an integer point in bset, if any.
1019 * If the recession cone is full-dimensional, then we know that
1020 * bset contains an infinite number of integer points and it is
1021 * fairly easy to pick one of them.
1022 * If the recession cone is not full-dimensional, then we first
1023 * transform bset such that the bounded directions appear as
1024 * the first dimensions of the transformed basic set.
1025 * We do this by using a unimodular transformation that transforms
1026 * the equalities in the recession cone to equalities on the first
1027 * dimensions.
1029 * The transformed set is then projected onto its bounded dimensions.
1030 * Note that to compute this projection, we can simply drop all constraints
1031 * involving any of the unbounded dimensions since these constraints
1032 * cannot be combined to produce a constraint on the bounded dimensions.
1033 * To see this, assume that there is such a combination of constraints
1034 * that produces a constraint on the bounded dimensions. This means
1035 * that some combination of the unbounded dimensions has both an upper
1036 * bound and a lower bound in terms of the bounded dimensions, but then
1037 * this combination would be a bounded direction too and would have been
1038 * transformed into a bounded dimensions.
1040 * We then compute a sample value in the bounded dimensions.
1041 * If no such value can be found, then the original set did not contain
1042 * any integer points and we are done.
1043 * Otherwise, we plug in the value we found in the bounded dimensions,
1044 * project out these bounded dimensions and end up with a set with
1045 * a full-dimensional recession cone.
1046 * A sample point in this set is computed by "rounding up" any
1047 * rational point in the set.
1049 * The sample points in the bounded and unbounded dimensions are
1050 * then combined into a single sample point and transformed back
1051 * to the original space.
1053 __isl_give isl_vec *isl_basic_set_sample_with_cone(
1054 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
1056 unsigned total;
1057 unsigned cone_dim;
1058 struct isl_mat *M, *U;
1059 struct isl_vec *sample;
1060 struct isl_vec *cone_sample;
1061 struct isl_ctx *ctx;
1062 struct isl_basic_set *bounded;
1064 if (!bset || !cone)
1065 goto error;
1067 ctx = bset->ctx;
1068 total = isl_basic_set_total_dim(cone);
1069 cone_dim = total - cone->n_eq;
1071 M = isl_mat_sub_alloc6(bset->ctx, cone->eq, 0, cone->n_eq, 1, total);
1072 M = isl_mat_left_hermite(M, 0, &U, NULL);
1073 if (!M)
1074 goto error;
1075 isl_mat_free(M);
1077 U = isl_mat_lin_to_aff(U);
1078 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
1080 bounded = isl_basic_set_copy(bset);
1081 bounded = isl_basic_set_drop_constraints_involving(bounded,
1082 total - cone_dim, cone_dim);
1083 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
1084 sample = sample_bounded(bounded);
1085 if (!sample || sample->size == 0) {
1086 isl_basic_set_free(bset);
1087 isl_basic_set_free(cone);
1088 isl_mat_free(U);
1089 return sample;
1091 bset = plug_in(bset, isl_vec_copy(sample));
1092 cone_sample = rational_sample(bset);
1093 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
1094 sample = vec_concat(sample, cone_sample);
1095 sample = isl_mat_vec_product(U, sample);
1096 return sample;
1097 error:
1098 isl_basic_set_free(cone);
1099 isl_basic_set_free(bset);
1100 return NULL;
1103 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
1105 int i;
1107 isl_int_set_si(*s, 0);
1109 for (i = 0; i < v->size; ++i)
1110 if (isl_int_is_neg(v->el[i]))
1111 isl_int_add(*s, *s, v->el[i]);
1114 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
1115 * to the recession cone and the inverse of a new basis U = inv(B),
1116 * with the unbounded directions in B last,
1117 * add constraints to "tab" that ensure any rational value
1118 * in the unbounded directions can be rounded up to an integer value.
1120 * The new basis is given by x' = B x, i.e., x = U x'.
1121 * For any rational value of the last tab->n_unbounded coordinates
1122 * in the update tableau, the value that is obtained by rounding
1123 * up this value should be contained in the original tableau.
1124 * For any constraint "a x + c >= 0", we therefore need to add
1125 * a constraint "a x + c + s >= 0", with s the sum of all negative
1126 * entries in the last elements of "a U".
1128 * Since we are not interested in the first entries of any of the "a U",
1129 * we first drop the columns of U that correpond to bounded directions.
1131 static int tab_shift_cone(struct isl_tab *tab,
1132 struct isl_tab *tab_cone, struct isl_mat *U)
1134 int i;
1135 isl_int v;
1136 struct isl_basic_set *bset = NULL;
1138 if (tab && tab->n_unbounded == 0) {
1139 isl_mat_free(U);
1140 return 0;
1142 isl_int_init(v);
1143 if (!tab || !tab_cone || !U)
1144 goto error;
1145 bset = isl_tab_peek_bset(tab_cone);
1146 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
1147 for (i = 0; i < bset->n_ineq; ++i) {
1148 int ok;
1149 struct isl_vec *row = NULL;
1150 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
1151 continue;
1152 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
1153 if (!row)
1154 goto error;
1155 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
1156 row = isl_vec_mat_product(row, isl_mat_copy(U));
1157 if (!row)
1158 goto error;
1159 vec_sum_of_neg(row, &v);
1160 isl_vec_free(row);
1161 if (isl_int_is_zero(v))
1162 continue;
1163 tab = isl_tab_extend(tab, 1);
1164 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
1165 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1166 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1167 if (!ok)
1168 goto error;
1171 isl_mat_free(U);
1172 isl_int_clear(v);
1173 return 0;
1174 error:
1175 isl_mat_free(U);
1176 isl_int_clear(v);
1177 return -1;
1180 /* Compute and return an initial basis for the possibly
1181 * unbounded tableau "tab". "tab_cone" is a tableau
1182 * for the corresponding recession cone.
1183 * Additionally, add constraints to "tab" that ensure
1184 * that any rational value for the unbounded directions
1185 * can be rounded up to an integer value.
1187 * If the tableau is bounded, i.e., if the recession cone
1188 * is zero-dimensional, then we just use inital_basis.
1189 * Otherwise, we construct a basis whose first directions
1190 * correspond to equalities, followed by bounded directions,
1191 * i.e., equalities in the recession cone.
1192 * The remaining directions are then unbounded.
1194 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1195 struct isl_tab *tab_cone)
1197 struct isl_mat *eq;
1198 struct isl_mat *cone_eq;
1199 struct isl_mat *U, *Q;
1201 if (!tab || !tab_cone)
1202 return -1;
1204 if (tab_cone->n_col == tab_cone->n_dead) {
1205 tab->basis = initial_basis(tab);
1206 return tab->basis ? 0 : -1;
1209 eq = tab_equalities(tab);
1210 if (!eq)
1211 return -1;
1212 tab->n_zero = eq->n_row;
1213 cone_eq = tab_equalities(tab_cone);
1214 eq = isl_mat_concat(eq, cone_eq);
1215 if (!eq)
1216 return -1;
1217 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1218 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1219 if (!eq)
1220 return -1;
1221 isl_mat_free(eq);
1222 tab->basis = isl_mat_lin_to_aff(Q);
1223 if (tab_shift_cone(tab, tab_cone, U) < 0)
1224 return -1;
1225 if (!tab->basis)
1226 return -1;
1227 return 0;
1230 /* Compute and return a sample point in bset using generalized basis
1231 * reduction. We first check if the input set has a non-trivial
1232 * recession cone. If so, we perform some extra preprocessing in
1233 * sample_with_cone. Otherwise, we directly perform generalized basis
1234 * reduction.
1236 static struct isl_vec *gbr_sample(struct isl_basic_set *bset)
1238 unsigned dim;
1239 struct isl_basic_set *cone;
1241 dim = isl_basic_set_total_dim(bset);
1243 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1244 if (!cone)
1245 goto error;
1247 if (cone->n_eq < dim)
1248 return isl_basic_set_sample_with_cone(bset, cone);
1250 isl_basic_set_free(cone);
1251 return sample_bounded(bset);
1252 error:
1253 isl_basic_set_free(bset);
1254 return NULL;
1257 static struct isl_vec *pip_sample(struct isl_basic_set *bset)
1259 struct isl_mat *T;
1260 struct isl_ctx *ctx;
1261 struct isl_vec *sample;
1263 bset = isl_basic_set_skew_to_positive_orthant(bset, &T);
1264 if (!bset)
1265 return NULL;
1267 ctx = bset->ctx;
1268 sample = isl_pip_basic_set_sample(bset);
1270 if (sample && sample->size != 0)
1271 sample = isl_mat_vec_product(T, sample);
1272 else
1273 isl_mat_free(T);
1275 return sample;
1278 static struct isl_vec *basic_set_sample(struct isl_basic_set *bset, int bounded)
1280 struct isl_ctx *ctx;
1281 unsigned dim;
1282 if (!bset)
1283 return NULL;
1285 ctx = bset->ctx;
1286 if (isl_basic_set_plain_is_empty(bset))
1287 return empty_sample(bset);
1289 dim = isl_basic_set_n_dim(bset);
1290 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1291 isl_assert(ctx, bset->n_div == 0, goto error);
1293 if (bset->sample && bset->sample->size == 1 + dim) {
1294 int contains = isl_basic_set_contains(bset, bset->sample);
1295 if (contains < 0)
1296 goto error;
1297 if (contains) {
1298 struct isl_vec *sample = isl_vec_copy(bset->sample);
1299 isl_basic_set_free(bset);
1300 return sample;
1303 isl_vec_free(bset->sample);
1304 bset->sample = NULL;
1306 if (bset->n_eq > 0)
1307 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1308 : isl_basic_set_sample_vec);
1309 if (dim == 0)
1310 return zero_sample(bset);
1311 if (dim == 1)
1312 return interval_sample(bset);
1314 switch (bset->ctx->opt->ilp_solver) {
1315 case ISL_ILP_PIP:
1316 return pip_sample(bset);
1317 case ISL_ILP_GBR:
1318 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1320 isl_assert(bset->ctx, 0, );
1321 error:
1322 isl_basic_set_free(bset);
1323 return NULL;
1326 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1328 return basic_set_sample(bset, 0);
1331 /* Compute an integer sample in "bset", where the caller guarantees
1332 * that "bset" is bounded.
1334 struct isl_vec *isl_basic_set_sample_bounded(struct isl_basic_set *bset)
1336 return basic_set_sample(bset, 1);
1339 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1341 int i;
1342 int k;
1343 struct isl_basic_set *bset = NULL;
1344 struct isl_ctx *ctx;
1345 unsigned dim;
1347 if (!vec)
1348 return NULL;
1349 ctx = vec->ctx;
1350 isl_assert(ctx, vec->size != 0, goto error);
1352 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1353 if (!bset)
1354 goto error;
1355 dim = isl_basic_set_n_dim(bset);
1356 for (i = dim - 1; i >= 0; --i) {
1357 k = isl_basic_set_alloc_equality(bset);
1358 if (k < 0)
1359 goto error;
1360 isl_seq_clr(bset->eq[k], 1 + dim);
1361 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1362 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1364 bset->sample = vec;
1366 return bset;
1367 error:
1368 isl_basic_set_free(bset);
1369 isl_vec_free(vec);
1370 return NULL;
1373 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1375 struct isl_basic_set *bset;
1376 struct isl_vec *sample_vec;
1378 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1379 sample_vec = isl_basic_set_sample_vec(bset);
1380 if (!sample_vec)
1381 goto error;
1382 if (sample_vec->size == 0) {
1383 struct isl_basic_map *sample;
1384 sample = isl_basic_map_empty_like(bmap);
1385 isl_vec_free(sample_vec);
1386 isl_basic_map_free(bmap);
1387 return sample;
1389 bset = isl_basic_set_from_vec(sample_vec);
1390 return isl_basic_map_overlying_set(bset, bmap);
1391 error:
1392 isl_basic_map_free(bmap);
1393 return NULL;
1396 __isl_give isl_basic_set *isl_basic_set_sample(__isl_take isl_basic_set *bset)
1398 return isl_basic_map_sample(bset);
1401 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1403 int i;
1404 isl_basic_map *sample = NULL;
1406 if (!map)
1407 goto error;
1409 for (i = 0; i < map->n; ++i) {
1410 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1411 if (!sample)
1412 goto error;
1413 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1414 break;
1415 isl_basic_map_free(sample);
1417 if (i == map->n)
1418 sample = isl_basic_map_empty_like_map(map);
1419 isl_map_free(map);
1420 return sample;
1421 error:
1422 isl_map_free(map);
1423 return NULL;
1426 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1428 return (isl_basic_set *) isl_map_sample((isl_map *)set);
1431 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1433 isl_vec *vec;
1434 isl_space *dim;
1436 dim = isl_basic_set_get_space(bset);
1437 bset = isl_basic_set_underlying_set(bset);
1438 vec = isl_basic_set_sample_vec(bset);
1440 return isl_point_alloc(dim, vec);
1443 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1445 int i;
1446 isl_point *pnt;
1448 if (!set)
1449 return NULL;
1451 for (i = 0; i < set->n; ++i) {
1452 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1453 if (!pnt)
1454 goto error;
1455 if (!isl_point_is_void(pnt))
1456 break;
1457 isl_point_free(pnt);
1459 if (i == set->n)
1460 pnt = isl_point_void(isl_set_get_space(set));
1462 isl_set_free(set);
1463 return pnt;
1464 error:
1465 isl_set_free(set);
1466 return NULL;