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[isl.git] / isl_sample.c
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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>
23 #include <isl_vec_private.h>
25 static struct isl_vec *empty_sample(struct isl_basic_set *bset)
27 struct isl_vec *vec;
29 vec = isl_vec_alloc(bset->ctx, 0);
30 isl_basic_set_free(bset);
31 return vec;
34 /* Construct a zero sample of the same dimension as bset.
35 * As a special case, if bset is zero-dimensional, this
36 * function creates a zero-dimensional sample point.
38 static struct isl_vec *zero_sample(struct isl_basic_set *bset)
40 unsigned dim;
41 struct isl_vec *sample;
43 dim = isl_basic_set_total_dim(bset);
44 sample = isl_vec_alloc(bset->ctx, 1 + dim);
45 if (sample) {
46 isl_int_set_si(sample->el[0], 1);
47 isl_seq_clr(sample->el + 1, dim);
49 isl_basic_set_free(bset);
50 return sample;
53 static struct isl_vec *interval_sample(struct isl_basic_set *bset)
55 int i;
56 isl_int t;
57 struct isl_vec *sample;
59 bset = isl_basic_set_simplify(bset);
60 if (!bset)
61 return NULL;
62 if (isl_basic_set_plain_is_empty(bset))
63 return empty_sample(bset);
64 if (bset->n_eq == 0 && bset->n_ineq == 0)
65 return zero_sample(bset);
67 sample = isl_vec_alloc(bset->ctx, 2);
68 if (!sample)
69 goto error;
70 if (!bset)
71 return NULL;
72 isl_int_set_si(sample->block.data[0], 1);
74 if (bset->n_eq > 0) {
75 isl_assert(bset->ctx, bset->n_eq == 1, goto error);
76 isl_assert(bset->ctx, bset->n_ineq == 0, goto error);
77 if (isl_int_is_one(bset->eq[0][1]))
78 isl_int_neg(sample->el[1], bset->eq[0][0]);
79 else {
80 isl_assert(bset->ctx, isl_int_is_negone(bset->eq[0][1]),
81 goto error);
82 isl_int_set(sample->el[1], bset->eq[0][0]);
84 isl_basic_set_free(bset);
85 return sample;
88 isl_int_init(t);
89 if (isl_int_is_one(bset->ineq[0][1]))
90 isl_int_neg(sample->block.data[1], bset->ineq[0][0]);
91 else
92 isl_int_set(sample->block.data[1], bset->ineq[0][0]);
93 for (i = 1; i < bset->n_ineq; ++i) {
94 isl_seq_inner_product(sample->block.data,
95 bset->ineq[i], 2, &t);
96 if (isl_int_is_neg(t))
97 break;
99 isl_int_clear(t);
100 if (i < bset->n_ineq) {
101 isl_vec_free(sample);
102 return empty_sample(bset);
105 isl_basic_set_free(bset);
106 return sample;
107 error:
108 isl_basic_set_free(bset);
109 isl_vec_free(sample);
110 return NULL;
113 static struct isl_mat *independent_bounds(struct isl_basic_set *bset)
115 int i, j, n;
116 struct isl_mat *dirs = NULL;
117 struct isl_mat *bounds = NULL;
118 unsigned dim;
120 if (!bset)
121 return NULL;
123 dim = isl_basic_set_n_dim(bset);
124 bounds = isl_mat_alloc(bset->ctx, 1+dim, 1+dim);
125 if (!bounds)
126 return NULL;
128 isl_int_set_si(bounds->row[0][0], 1);
129 isl_seq_clr(bounds->row[0]+1, dim);
130 bounds->n_row = 1;
132 if (bset->n_ineq == 0)
133 return bounds;
135 dirs = isl_mat_alloc(bset->ctx, dim, dim);
136 if (!dirs) {
137 isl_mat_free(bounds);
138 return NULL;
140 isl_seq_cpy(dirs->row[0], bset->ineq[0]+1, dirs->n_col);
141 isl_seq_cpy(bounds->row[1], bset->ineq[0], bounds->n_col);
142 for (j = 1, n = 1; n < dim && j < bset->n_ineq; ++j) {
143 int pos;
145 isl_seq_cpy(dirs->row[n], bset->ineq[j]+1, dirs->n_col);
147 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
148 if (pos < 0)
149 continue;
150 for (i = 0; i < n; ++i) {
151 int pos_i;
152 pos_i = isl_seq_first_non_zero(dirs->row[i], dirs->n_col);
153 if (pos_i < pos)
154 continue;
155 if (pos_i > pos)
156 break;
157 isl_seq_elim(dirs->row[n], dirs->row[i], pos,
158 dirs->n_col, NULL);
159 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
160 if (pos < 0)
161 break;
163 if (pos < 0)
164 continue;
165 if (i < n) {
166 int k;
167 isl_int *t = dirs->row[n];
168 for (k = n; k > i; --k)
169 dirs->row[k] = dirs->row[k-1];
170 dirs->row[i] = t;
172 ++n;
173 isl_seq_cpy(bounds->row[n], bset->ineq[j], bounds->n_col);
175 isl_mat_free(dirs);
176 bounds->n_row = 1+n;
177 return bounds;
180 static void swap_inequality(struct isl_basic_set *bset, int a, int b)
182 isl_int *t = bset->ineq[a];
183 bset->ineq[a] = bset->ineq[b];
184 bset->ineq[b] = t;
187 /* Skew into positive orthant and project out lineality space.
189 * We perform a unimodular transformation that turns a selected
190 * maximal set of linearly independent bounds into constraints
191 * on the first dimensions that impose that these first dimensions
192 * are non-negative. In particular, the constraint matrix is lower
193 * triangular with positive entries on the diagonal and negative
194 * entries below.
195 * If "bset" has a lineality space then these constraints (and therefore
196 * all constraints in bset) only involve the first dimensions.
197 * The remaining dimensions then do not appear in any constraints and
198 * we can select any value for them, say zero. We therefore project
199 * out this final dimensions and plug in the value zero later. This
200 * is accomplished by simply dropping the final columns of
201 * the unimodular transformation.
203 static struct isl_basic_set *isl_basic_set_skew_to_positive_orthant(
204 struct isl_basic_set *bset, struct isl_mat **T)
206 struct isl_mat *U = NULL;
207 struct isl_mat *bounds = NULL;
208 int i, j;
209 unsigned old_dim, new_dim;
211 *T = NULL;
212 if (!bset)
213 return NULL;
215 isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
216 isl_assert(bset->ctx, bset->n_div == 0, goto error);
217 isl_assert(bset->ctx, bset->n_eq == 0, goto error);
219 old_dim = isl_basic_set_n_dim(bset);
220 /* Try to move (multiples of) unit rows up. */
221 for (i = 0, j = 0; i < bset->n_ineq; ++i) {
222 int pos = isl_seq_first_non_zero(bset->ineq[i]+1, old_dim);
223 if (pos < 0)
224 continue;
225 if (isl_seq_first_non_zero(bset->ineq[i]+1+pos+1,
226 old_dim-pos-1) >= 0)
227 continue;
228 if (i != j)
229 swap_inequality(bset, i, j);
230 ++j;
232 bounds = independent_bounds(bset);
233 if (!bounds)
234 goto error;
235 new_dim = bounds->n_row - 1;
236 bounds = isl_mat_left_hermite(bounds, 1, &U, NULL);
237 if (!bounds)
238 goto error;
239 U = isl_mat_drop_cols(U, 1 + new_dim, old_dim - new_dim);
240 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
241 if (!bset)
242 goto error;
243 *T = U;
244 isl_mat_free(bounds);
245 return bset;
246 error:
247 isl_mat_free(bounds);
248 isl_mat_free(U);
249 isl_basic_set_free(bset);
250 return NULL;
253 /* Find a sample integer point, if any, in bset, which is known
254 * to have equalities. If bset contains no integer points, then
255 * return a zero-length vector.
256 * We simply remove the known equalities, compute a sample
257 * in the resulting bset, using the specified recurse function,
258 * and then transform the sample back to the original space.
260 static struct isl_vec *sample_eq(struct isl_basic_set *bset,
261 struct isl_vec *(*recurse)(struct isl_basic_set *))
263 struct isl_mat *T;
264 struct isl_vec *sample;
266 if (!bset)
267 return NULL;
269 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
270 sample = recurse(bset);
271 if (!sample || sample->size == 0)
272 isl_mat_free(T);
273 else
274 sample = isl_mat_vec_product(T, sample);
275 return sample;
278 /* Return a matrix containing the equalities of the tableau
279 * in constraint form. The tableau is assumed to have
280 * an associated bset that has been kept up-to-date.
282 static struct isl_mat *tab_equalities(struct isl_tab *tab)
284 int i, j;
285 int n_eq;
286 struct isl_mat *eq;
287 struct isl_basic_set *bset;
289 if (!tab)
290 return NULL;
292 bset = isl_tab_peek_bset(tab);
293 isl_assert(tab->mat->ctx, bset, return NULL);
295 n_eq = tab->n_var - tab->n_col + tab->n_dead;
296 if (tab->empty || n_eq == 0)
297 return isl_mat_alloc(tab->mat->ctx, 0, tab->n_var);
298 if (n_eq == tab->n_var)
299 return isl_mat_identity(tab->mat->ctx, tab->n_var);
301 eq = isl_mat_alloc(tab->mat->ctx, n_eq, tab->n_var);
302 if (!eq)
303 return NULL;
304 for (i = 0, j = 0; i < tab->n_con; ++i) {
305 if (tab->con[i].is_row)
306 continue;
307 if (tab->con[i].index >= 0 && tab->con[i].index >= tab->n_dead)
308 continue;
309 if (i < bset->n_eq)
310 isl_seq_cpy(eq->row[j], bset->eq[i] + 1, tab->n_var);
311 else
312 isl_seq_cpy(eq->row[j],
313 bset->ineq[i - bset->n_eq] + 1, tab->n_var);
314 ++j;
316 isl_assert(bset->ctx, j == n_eq, goto error);
317 return eq;
318 error:
319 isl_mat_free(eq);
320 return NULL;
323 /* Compute and return an initial basis for the bounded tableau "tab".
325 * If the tableau is either full-dimensional or zero-dimensional,
326 * the we simply return an identity matrix.
327 * Otherwise, we construct a basis whose first directions correspond
328 * to equalities.
330 static struct isl_mat *initial_basis(struct isl_tab *tab)
332 int n_eq;
333 struct isl_mat *eq;
334 struct isl_mat *Q;
336 tab->n_unbounded = 0;
337 tab->n_zero = n_eq = tab->n_var - tab->n_col + tab->n_dead;
338 if (tab->empty || n_eq == 0 || n_eq == tab->n_var)
339 return isl_mat_identity(tab->mat->ctx, 1 + tab->n_var);
341 eq = tab_equalities(tab);
342 eq = isl_mat_left_hermite(eq, 0, NULL, &Q);
343 if (!eq)
344 return NULL;
345 isl_mat_free(eq);
347 Q = isl_mat_lin_to_aff(Q);
348 return Q;
351 /* Compute the minimum of the current ("level") basis row over "tab"
352 * and store the result in position "level" of "min".
354 static enum isl_lp_result compute_min(isl_ctx *ctx, struct isl_tab *tab,
355 __isl_keep isl_vec *min, int level)
357 return isl_tab_min(tab, tab->basis->row[1 + level],
358 ctx->one, &min->el[level], NULL, 0);
361 /* Compute the maximum of the current ("level") basis row over "tab"
362 * and store the result in position "level" of "max".
364 static enum isl_lp_result compute_max(isl_ctx *ctx, struct isl_tab *tab,
365 __isl_keep isl_vec *max, int level)
367 enum isl_lp_result res;
368 unsigned dim = tab->n_var;
370 isl_seq_neg(tab->basis->row[1 + level] + 1,
371 tab->basis->row[1 + level] + 1, dim);
372 res = isl_tab_min(tab, tab->basis->row[1 + level],
373 ctx->one, &max->el[level], NULL, 0);
374 isl_seq_neg(tab->basis->row[1 + level] + 1,
375 tab->basis->row[1 + level] + 1, dim);
376 isl_int_neg(max->el[level], max->el[level]);
378 return res;
381 /* Perform a greedy search for an integer point in the set represented
382 * by "tab", given that the minimal rational value (rounded up to the
383 * nearest integer) at "level" is smaller than the maximal rational
384 * value (rounded down to the nearest integer).
386 * Return 1 if we have found an integer point (if tab->n_unbounded > 0
387 * then we may have only found integer values for the bounded dimensions
388 * and it is the responsibility of the caller to extend this solution
389 * to the unbounded dimensions).
390 * Return 0 if greedy search did not result in a solution.
391 * Return -1 if some error occurred.
393 * We assign a value half-way between the minimum and the maximum
394 * to the current dimension and check if the minimal value of the
395 * next dimension is still smaller than (or equal) to the maximal value.
396 * We continue this process until either
397 * - the minimal value (rounded up) is greater than the maximal value
398 * (rounded down). In this case, greedy search has failed.
399 * - we have exhausted all bounded dimensions, meaning that we have
400 * found a solution.
401 * - the sample value of the tableau is integral.
402 * - some error has occurred.
404 static int greedy_search(isl_ctx *ctx, struct isl_tab *tab,
405 __isl_keep isl_vec *min, __isl_keep isl_vec *max, int level)
407 struct isl_tab_undo *snap;
408 enum isl_lp_result res;
410 snap = isl_tab_snap(tab);
412 do {
413 isl_int_add(tab->basis->row[1 + level][0],
414 min->el[level], max->el[level]);
415 isl_int_fdiv_q_ui(tab->basis->row[1 + level][0],
416 tab->basis->row[1 + level][0], 2);
417 isl_int_neg(tab->basis->row[1 + level][0],
418 tab->basis->row[1 + level][0]);
419 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
420 return -1;
421 isl_int_set_si(tab->basis->row[1 + level][0], 0);
423 if (++level >= tab->n_var - tab->n_unbounded)
424 return 1;
425 if (isl_tab_sample_is_integer(tab))
426 return 1;
428 res = compute_min(ctx, tab, min, level);
429 if (res == isl_lp_error)
430 return -1;
431 if (res != isl_lp_ok)
432 isl_die(ctx, isl_error_internal,
433 "expecting bounded rational solution",
434 return -1);
435 res = compute_max(ctx, tab, max, level);
436 if (res == isl_lp_error)
437 return -1;
438 if (res != isl_lp_ok)
439 isl_die(ctx, isl_error_internal,
440 "expecting bounded rational solution",
441 return -1);
442 } while (isl_int_le(min->el[level], max->el[level]));
444 if (isl_tab_rollback(tab, snap) < 0)
445 return -1;
447 return 0;
450 /* Given a tableau representing a set, find and return
451 * an integer point in the set, if there is any.
453 * We perform a depth first search
454 * for an integer point, by scanning all possible values in the range
455 * attained by a basis vector, where an initial basis may have been set
456 * by the calling function. Otherwise an initial basis that exploits
457 * the equalities in the tableau is created.
458 * tab->n_zero is currently ignored and is clobbered by this function.
460 * The tableau is allowed to have unbounded direction, but then
461 * the calling function needs to set an initial basis, with the
462 * unbounded directions last and with tab->n_unbounded set
463 * to the number of unbounded directions.
464 * Furthermore, the calling functions needs to add shifted copies
465 * of all constraints involving unbounded directions to ensure
466 * that any feasible rational value in these directions can be rounded
467 * up to yield a feasible integer value.
468 * In particular, let B define the given basis x' = B x
469 * and let T be the inverse of B, i.e., X = T x'.
470 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
471 * or a T x' + c >= 0 in terms of the given basis. Assume that
472 * the bounded directions have an integer value, then we can safely
473 * round up the values for the unbounded directions if we make sure
474 * that x' not only satisfies the original constraint, but also
475 * the constraint "a T x' + c + s >= 0" with s the sum of all
476 * negative values in the last n_unbounded entries of "a T".
477 * The calling function therefore needs to add the constraint
478 * a x + c + s >= 0. The current function then scans the first
479 * directions for an integer value and once those have been found,
480 * it can compute "T ceil(B x)" to yield an integer point in the set.
481 * Note that during the search, the first rows of B may be changed
482 * by a basis reduction, but the last n_unbounded rows of B remain
483 * unaltered and are also not mixed into the first rows.
485 * The search is implemented iteratively. "level" identifies the current
486 * basis vector. "init" is true if we want the first value at the current
487 * level and false if we want the next value.
489 * At the start of each level, we first check if we can find a solution
490 * using greedy search. If not, we continue with the exhaustive search.
492 * The initial basis is the identity matrix. If the range in some direction
493 * contains more than one integer value, we perform basis reduction based
494 * on the value of ctx->opt->gbr
495 * - ISL_GBR_NEVER: never perform basis reduction
496 * - ISL_GBR_ONCE: only perform basis reduction the first
497 * time such a range is encountered
498 * - ISL_GBR_ALWAYS: always perform basis reduction when
499 * such a range is encountered
501 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
502 * reduction computation to return early. That is, as soon as it
503 * finds a reasonable first direction.
505 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
507 unsigned dim;
508 unsigned gbr;
509 struct isl_ctx *ctx;
510 struct isl_vec *sample;
511 struct isl_vec *min;
512 struct isl_vec *max;
513 enum isl_lp_result res;
514 int level;
515 int init;
516 int reduced;
517 struct isl_tab_undo **snap;
519 if (!tab)
520 return NULL;
521 if (tab->empty)
522 return isl_vec_alloc(tab->mat->ctx, 0);
524 if (!tab->basis)
525 tab->basis = initial_basis(tab);
526 if (!tab->basis)
527 return NULL;
528 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
529 return NULL);
530 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
531 return NULL);
533 ctx = tab->mat->ctx;
534 dim = tab->n_var;
535 gbr = ctx->opt->gbr;
537 if (tab->n_unbounded == tab->n_var) {
538 sample = isl_tab_get_sample_value(tab);
539 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
540 sample = isl_vec_ceil(sample);
541 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
542 sample);
543 return sample;
546 if (isl_tab_extend_cons(tab, dim + 1) < 0)
547 return NULL;
549 min = isl_vec_alloc(ctx, dim);
550 max = isl_vec_alloc(ctx, dim);
551 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
553 if (!min || !max || !snap)
554 goto error;
556 level = 0;
557 init = 1;
558 reduced = 0;
560 while (level >= 0) {
561 if (init) {
562 int choice;
564 res = compute_min(ctx, tab, min, level);
565 if (res == isl_lp_error)
566 goto error;
567 if (res != isl_lp_ok)
568 isl_die(ctx, isl_error_internal,
569 "expecting bounded rational solution",
570 goto error);
571 if (isl_tab_sample_is_integer(tab))
572 break;
573 res = compute_max(ctx, tab, max, level);
574 if (res == isl_lp_error)
575 goto error;
576 if (res != isl_lp_ok)
577 isl_die(ctx, isl_error_internal,
578 "expecting bounded rational solution",
579 goto error);
580 if (isl_tab_sample_is_integer(tab))
581 break;
582 choice = isl_int_lt(min->el[level], max->el[level]);
583 if (choice) {
584 int g;
585 g = greedy_search(ctx, tab, min, max, level);
586 if (g < 0)
587 goto error;
588 if (g)
589 break;
591 if (!reduced && choice &&
592 ctx->opt->gbr != ISL_GBR_NEVER) {
593 unsigned gbr_only_first;
594 if (ctx->opt->gbr == ISL_GBR_ONCE)
595 ctx->opt->gbr = ISL_GBR_NEVER;
596 tab->n_zero = level;
597 gbr_only_first = ctx->opt->gbr_only_first;
598 ctx->opt->gbr_only_first =
599 ctx->opt->gbr == ISL_GBR_ALWAYS;
600 tab = isl_tab_compute_reduced_basis(tab);
601 ctx->opt->gbr_only_first = gbr_only_first;
602 if (!tab || !tab->basis)
603 goto error;
604 reduced = 1;
605 continue;
607 reduced = 0;
608 snap[level] = isl_tab_snap(tab);
609 } else
610 isl_int_add_ui(min->el[level], min->el[level], 1);
612 if (isl_int_gt(min->el[level], max->el[level])) {
613 level--;
614 init = 0;
615 if (level >= 0)
616 if (isl_tab_rollback(tab, snap[level]) < 0)
617 goto error;
618 continue;
620 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
621 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
622 goto error;
623 isl_int_set_si(tab->basis->row[1 + level][0], 0);
624 if (level + tab->n_unbounded < dim - 1) {
625 ++level;
626 init = 1;
627 continue;
629 break;
632 if (level >= 0) {
633 sample = isl_tab_get_sample_value(tab);
634 if (!sample)
635 goto error;
636 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
637 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
638 sample);
639 sample = isl_vec_ceil(sample);
640 sample = isl_mat_vec_inverse_product(
641 isl_mat_copy(tab->basis), sample);
643 } else
644 sample = isl_vec_alloc(ctx, 0);
646 ctx->opt->gbr = gbr;
647 isl_vec_free(min);
648 isl_vec_free(max);
649 free(snap);
650 return sample;
651 error:
652 ctx->opt->gbr = gbr;
653 isl_vec_free(min);
654 isl_vec_free(max);
655 free(snap);
656 return NULL;
659 static struct isl_vec *sample_bounded(struct isl_basic_set *bset);
661 /* Compute a sample point of the given basic set, based on the given,
662 * non-trivial factorization.
664 static __isl_give isl_vec *factored_sample(__isl_take isl_basic_set *bset,
665 __isl_take isl_factorizer *f)
667 int i, n;
668 isl_vec *sample = NULL;
669 isl_ctx *ctx;
670 unsigned nparam;
671 unsigned nvar;
673 ctx = isl_basic_set_get_ctx(bset);
674 if (!ctx)
675 goto error;
677 nparam = isl_basic_set_dim(bset, isl_dim_param);
678 nvar = isl_basic_set_dim(bset, isl_dim_set);
680 sample = isl_vec_alloc(ctx, 1 + isl_basic_set_total_dim(bset));
681 if (!sample)
682 goto error;
683 isl_int_set_si(sample->el[0], 1);
685 bset = isl_morph_basic_set(isl_morph_copy(f->morph), bset);
687 for (i = 0, n = 0; i < f->n_group; ++i) {
688 isl_basic_set *bset_i;
689 isl_vec *sample_i;
691 bset_i = isl_basic_set_copy(bset);
692 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
693 nparam + n + f->len[i], nvar - n - f->len[i]);
694 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
695 nparam, n);
696 bset_i = isl_basic_set_drop(bset_i, isl_dim_set,
697 n + f->len[i], nvar - n - f->len[i]);
698 bset_i = isl_basic_set_drop(bset_i, isl_dim_set, 0, n);
700 sample_i = sample_bounded(bset_i);
701 if (!sample_i)
702 goto error;
703 if (sample_i->size == 0) {
704 isl_basic_set_free(bset);
705 isl_factorizer_free(f);
706 isl_vec_free(sample);
707 return sample_i;
709 isl_seq_cpy(sample->el + 1 + nparam + n,
710 sample_i->el + 1, f->len[i]);
711 isl_vec_free(sample_i);
713 n += f->len[i];
716 f->morph = isl_morph_inverse(f->morph);
717 sample = isl_morph_vec(isl_morph_copy(f->morph), sample);
719 isl_basic_set_free(bset);
720 isl_factorizer_free(f);
721 return sample;
722 error:
723 isl_basic_set_free(bset);
724 isl_factorizer_free(f);
725 isl_vec_free(sample);
726 return NULL;
729 /* Given a basic set that is known to be bounded, find and return
730 * an integer point in the basic set, if there is any.
732 * After handling some trivial cases, we construct a tableau
733 * and then use isl_tab_sample to find a sample, passing it
734 * the identity matrix as initial basis.
736 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
738 unsigned dim;
739 struct isl_ctx *ctx;
740 struct isl_vec *sample;
741 struct isl_tab *tab = NULL;
742 isl_factorizer *f;
744 if (!bset)
745 return NULL;
747 if (isl_basic_set_plain_is_empty(bset))
748 return empty_sample(bset);
750 dim = isl_basic_set_total_dim(bset);
751 if (dim == 0)
752 return zero_sample(bset);
753 if (dim == 1)
754 return interval_sample(bset);
755 if (bset->n_eq > 0)
756 return sample_eq(bset, sample_bounded);
758 f = isl_basic_set_factorizer(bset);
759 if (!f)
760 goto error;
761 if (f->n_group != 0)
762 return factored_sample(bset, f);
763 isl_factorizer_free(f);
765 ctx = bset->ctx;
767 tab = isl_tab_from_basic_set(bset, 1);
768 if (tab && tab->empty) {
769 isl_tab_free(tab);
770 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
771 sample = isl_vec_alloc(bset->ctx, 0);
772 isl_basic_set_free(bset);
773 return sample;
776 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
777 if (isl_tab_detect_implicit_equalities(tab) < 0)
778 goto error;
780 sample = isl_tab_sample(tab);
781 if (!sample)
782 goto error;
784 if (sample->size > 0) {
785 isl_vec_free(bset->sample);
786 bset->sample = isl_vec_copy(sample);
789 isl_basic_set_free(bset);
790 isl_tab_free(tab);
791 return sample;
792 error:
793 isl_basic_set_free(bset);
794 isl_tab_free(tab);
795 return NULL;
798 /* Given a basic set "bset" and a value "sample" for the first coordinates
799 * of bset, plug in these values and drop the corresponding coordinates.
801 * We do this by computing the preimage of the transformation
803 * [ 1 0 ]
804 * x = [ s 0 ] x'
805 * [ 0 I ]
807 * where [1 s] is the sample value and I is the identity matrix of the
808 * appropriate dimension.
810 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
811 struct isl_vec *sample)
813 int i;
814 unsigned total;
815 struct isl_mat *T;
817 if (!bset || !sample)
818 goto error;
820 total = isl_basic_set_total_dim(bset);
821 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
822 if (!T)
823 goto error;
825 for (i = 0; i < sample->size; ++i) {
826 isl_int_set(T->row[i][0], sample->el[i]);
827 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
829 for (i = 0; i < T->n_col - 1; ++i) {
830 isl_seq_clr(T->row[sample->size + i], T->n_col);
831 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
833 isl_vec_free(sample);
835 bset = isl_basic_set_preimage(bset, T);
836 return bset;
837 error:
838 isl_basic_set_free(bset);
839 isl_vec_free(sample);
840 return NULL;
843 /* Given a basic set "bset", return any (possibly non-integer) point
844 * in the basic set.
846 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
848 struct isl_tab *tab;
849 struct isl_vec *sample;
851 if (!bset)
852 return NULL;
854 tab = isl_tab_from_basic_set(bset, 0);
855 sample = isl_tab_get_sample_value(tab);
856 isl_tab_free(tab);
858 isl_basic_set_free(bset);
860 return sample;
863 /* Given a linear cone "cone" and a rational point "vec",
864 * construct a polyhedron with shifted copies of the constraints in "cone",
865 * i.e., a polyhedron with "cone" as its recession cone, such that each
866 * point x in this polyhedron is such that the unit box positioned at x
867 * lies entirely inside the affine cone 'vec + cone'.
868 * Any rational point in this polyhedron may therefore be rounded up
869 * to yield an integer point that lies inside said affine cone.
871 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
872 * point "vec" by v/d.
873 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
874 * by <a_i, x> - b/d >= 0.
875 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
876 * We prefer this polyhedron over the actual affine cone because it doesn't
877 * require a scaling of the constraints.
878 * If each of the vertices of the unit cube positioned at x lies inside
879 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
880 * We therefore impose that x' = x + \sum e_i, for any selection of unit
881 * vectors lies inside the polyhedron, i.e.,
883 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
885 * The most stringent of these constraints is the one that selects
886 * all negative a_i, so the polyhedron we are looking for has constraints
888 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
890 * Note that if cone were known to have only non-negative rays
891 * (which can be accomplished by a unimodular transformation),
892 * then we would only have to check the points x' = x + e_i
893 * and we only have to add the smallest negative a_i (if any)
894 * instead of the sum of all negative a_i.
896 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
897 struct isl_vec *vec)
899 int i, j, k;
900 unsigned total;
902 struct isl_basic_set *shift = NULL;
904 if (!cone || !vec)
905 goto error;
907 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
909 total = isl_basic_set_total_dim(cone);
911 shift = isl_basic_set_alloc_space(isl_basic_set_get_space(cone),
912 0, 0, cone->n_ineq);
914 for (i = 0; i < cone->n_ineq; ++i) {
915 k = isl_basic_set_alloc_inequality(shift);
916 if (k < 0)
917 goto error;
918 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
919 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
920 &shift->ineq[k][0]);
921 isl_int_cdiv_q(shift->ineq[k][0],
922 shift->ineq[k][0], vec->el[0]);
923 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
924 for (j = 0; j < total; ++j) {
925 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
926 continue;
927 isl_int_add(shift->ineq[k][0],
928 shift->ineq[k][0], shift->ineq[k][1 + j]);
932 isl_basic_set_free(cone);
933 isl_vec_free(vec);
935 return isl_basic_set_finalize(shift);
936 error:
937 isl_basic_set_free(shift);
938 isl_basic_set_free(cone);
939 isl_vec_free(vec);
940 return NULL;
943 /* Given a rational point vec in a (transformed) basic set,
944 * such that cone is the recession cone of the original basic set,
945 * "round up" the rational point to an integer point.
947 * We first check if the rational point just happens to be integer.
948 * If not, we transform the cone in the same way as the basic set,
949 * pick a point x in this cone shifted to the rational point such that
950 * the whole unit cube at x is also inside this affine cone.
951 * Then we simply round up the coordinates of x and return the
952 * resulting integer point.
954 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
955 struct isl_basic_set *cone, struct isl_mat *U)
957 unsigned total;
959 if (!vec || !cone || !U)
960 goto error;
962 isl_assert(vec->ctx, vec->size != 0, goto error);
963 if (isl_int_is_one(vec->el[0])) {
964 isl_mat_free(U);
965 isl_basic_set_free(cone);
966 return vec;
969 total = isl_basic_set_total_dim(cone);
970 cone = isl_basic_set_preimage(cone, U);
971 cone = isl_basic_set_remove_dims(cone, isl_dim_set,
972 0, total - (vec->size - 1));
974 cone = shift_cone(cone, vec);
976 vec = rational_sample(cone);
977 vec = isl_vec_ceil(vec);
978 return vec;
979 error:
980 isl_mat_free(U);
981 isl_vec_free(vec);
982 isl_basic_set_free(cone);
983 return NULL;
986 /* Concatenate two integer vectors, i.e., two vectors with denominator
987 * (stored in element 0) equal to 1.
989 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
991 struct isl_vec *vec;
993 if (!vec1 || !vec2)
994 goto error;
995 isl_assert(vec1->ctx, vec1->size > 0, goto error);
996 isl_assert(vec2->ctx, vec2->size > 0, goto error);
997 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
998 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
1000 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
1001 if (!vec)
1002 goto error;
1004 isl_seq_cpy(vec->el, vec1->el, vec1->size);
1005 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
1007 isl_vec_free(vec1);
1008 isl_vec_free(vec2);
1010 return vec;
1011 error:
1012 isl_vec_free(vec1);
1013 isl_vec_free(vec2);
1014 return NULL;
1017 /* Give a basic set "bset" with recession cone "cone", compute and
1018 * return an integer point in bset, if any.
1020 * If the recession cone is full-dimensional, then we know that
1021 * bset contains an infinite number of integer points and it is
1022 * fairly easy to pick one of them.
1023 * If the recession cone is not full-dimensional, then we first
1024 * transform bset such that the bounded directions appear as
1025 * the first dimensions of the transformed basic set.
1026 * We do this by using a unimodular transformation that transforms
1027 * the equalities in the recession cone to equalities on the first
1028 * dimensions.
1030 * The transformed set is then projected onto its bounded dimensions.
1031 * Note that to compute this projection, we can simply drop all constraints
1032 * involving any of the unbounded dimensions since these constraints
1033 * cannot be combined to produce a constraint on the bounded dimensions.
1034 * To see this, assume that there is such a combination of constraints
1035 * that produces a constraint on the bounded dimensions. This means
1036 * that some combination of the unbounded dimensions has both an upper
1037 * bound and a lower bound in terms of the bounded dimensions, but then
1038 * this combination would be a bounded direction too and would have been
1039 * transformed into a bounded dimensions.
1041 * We then compute a sample value in the bounded dimensions.
1042 * If no such value can be found, then the original set did not contain
1043 * any integer points and we are done.
1044 * Otherwise, we plug in the value we found in the bounded dimensions,
1045 * project out these bounded dimensions and end up with a set with
1046 * a full-dimensional recession cone.
1047 * A sample point in this set is computed by "rounding up" any
1048 * rational point in the set.
1050 * The sample points in the bounded and unbounded dimensions are
1051 * then combined into a single sample point and transformed back
1052 * to the original space.
1054 __isl_give isl_vec *isl_basic_set_sample_with_cone(
1055 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
1057 unsigned total;
1058 unsigned cone_dim;
1059 struct isl_mat *M, *U;
1060 struct isl_vec *sample;
1061 struct isl_vec *cone_sample;
1062 struct isl_ctx *ctx;
1063 struct isl_basic_set *bounded;
1065 if (!bset || !cone)
1066 goto error;
1068 ctx = bset->ctx;
1069 total = isl_basic_set_total_dim(cone);
1070 cone_dim = total - cone->n_eq;
1072 M = isl_mat_sub_alloc6(bset->ctx, cone->eq, 0, cone->n_eq, 1, total);
1073 M = isl_mat_left_hermite(M, 0, &U, NULL);
1074 if (!M)
1075 goto error;
1076 isl_mat_free(M);
1078 U = isl_mat_lin_to_aff(U);
1079 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
1081 bounded = isl_basic_set_copy(bset);
1082 bounded = isl_basic_set_drop_constraints_involving(bounded,
1083 total - cone_dim, cone_dim);
1084 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
1085 sample = sample_bounded(bounded);
1086 if (!sample || sample->size == 0) {
1087 isl_basic_set_free(bset);
1088 isl_basic_set_free(cone);
1089 isl_mat_free(U);
1090 return sample;
1092 bset = plug_in(bset, isl_vec_copy(sample));
1093 cone_sample = rational_sample(bset);
1094 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
1095 sample = vec_concat(sample, cone_sample);
1096 sample = isl_mat_vec_product(U, sample);
1097 return sample;
1098 error:
1099 isl_basic_set_free(cone);
1100 isl_basic_set_free(bset);
1101 return NULL;
1104 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
1106 int i;
1108 isl_int_set_si(*s, 0);
1110 for (i = 0; i < v->size; ++i)
1111 if (isl_int_is_neg(v->el[i]))
1112 isl_int_add(*s, *s, v->el[i]);
1115 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
1116 * to the recession cone and the inverse of a new basis U = inv(B),
1117 * with the unbounded directions in B last,
1118 * add constraints to "tab" that ensure any rational value
1119 * in the unbounded directions can be rounded up to an integer value.
1121 * The new basis is given by x' = B x, i.e., x = U x'.
1122 * For any rational value of the last tab->n_unbounded coordinates
1123 * in the update tableau, the value that is obtained by rounding
1124 * up this value should be contained in the original tableau.
1125 * For any constraint "a x + c >= 0", we therefore need to add
1126 * a constraint "a x + c + s >= 0", with s the sum of all negative
1127 * entries in the last elements of "a U".
1129 * Since we are not interested in the first entries of any of the "a U",
1130 * we first drop the columns of U that correpond to bounded directions.
1132 static int tab_shift_cone(struct isl_tab *tab,
1133 struct isl_tab *tab_cone, struct isl_mat *U)
1135 int i;
1136 isl_int v;
1137 struct isl_basic_set *bset = NULL;
1139 if (tab && tab->n_unbounded == 0) {
1140 isl_mat_free(U);
1141 return 0;
1143 isl_int_init(v);
1144 if (!tab || !tab_cone || !U)
1145 goto error;
1146 bset = isl_tab_peek_bset(tab_cone);
1147 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
1148 for (i = 0; i < bset->n_ineq; ++i) {
1149 int ok;
1150 struct isl_vec *row = NULL;
1151 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
1152 continue;
1153 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
1154 if (!row)
1155 goto error;
1156 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
1157 row = isl_vec_mat_product(row, isl_mat_copy(U));
1158 if (!row)
1159 goto error;
1160 vec_sum_of_neg(row, &v);
1161 isl_vec_free(row);
1162 if (isl_int_is_zero(v))
1163 continue;
1164 tab = isl_tab_extend(tab, 1);
1165 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
1166 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1167 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1168 if (!ok)
1169 goto error;
1172 isl_mat_free(U);
1173 isl_int_clear(v);
1174 return 0;
1175 error:
1176 isl_mat_free(U);
1177 isl_int_clear(v);
1178 return -1;
1181 /* Compute and return an initial basis for the possibly
1182 * unbounded tableau "tab". "tab_cone" is a tableau
1183 * for the corresponding recession cone.
1184 * Additionally, add constraints to "tab" that ensure
1185 * that any rational value for the unbounded directions
1186 * can be rounded up to an integer value.
1188 * If the tableau is bounded, i.e., if the recession cone
1189 * is zero-dimensional, then we just use inital_basis.
1190 * Otherwise, we construct a basis whose first directions
1191 * correspond to equalities, followed by bounded directions,
1192 * i.e., equalities in the recession cone.
1193 * The remaining directions are then unbounded.
1195 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1196 struct isl_tab *tab_cone)
1198 struct isl_mat *eq;
1199 struct isl_mat *cone_eq;
1200 struct isl_mat *U, *Q;
1202 if (!tab || !tab_cone)
1203 return -1;
1205 if (tab_cone->n_col == tab_cone->n_dead) {
1206 tab->basis = initial_basis(tab);
1207 return tab->basis ? 0 : -1;
1210 eq = tab_equalities(tab);
1211 if (!eq)
1212 return -1;
1213 tab->n_zero = eq->n_row;
1214 cone_eq = tab_equalities(tab_cone);
1215 eq = isl_mat_concat(eq, cone_eq);
1216 if (!eq)
1217 return -1;
1218 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1219 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1220 if (!eq)
1221 return -1;
1222 isl_mat_free(eq);
1223 tab->basis = isl_mat_lin_to_aff(Q);
1224 if (tab_shift_cone(tab, tab_cone, U) < 0)
1225 return -1;
1226 if (!tab->basis)
1227 return -1;
1228 return 0;
1231 /* Compute and return a sample point in bset using generalized basis
1232 * reduction. We first check if the input set has a non-trivial
1233 * recession cone. If so, we perform some extra preprocessing in
1234 * sample_with_cone. Otherwise, we directly perform generalized basis
1235 * reduction.
1237 static struct isl_vec *gbr_sample(struct isl_basic_set *bset)
1239 unsigned dim;
1240 struct isl_basic_set *cone;
1242 dim = isl_basic_set_total_dim(bset);
1244 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1245 if (!cone)
1246 goto error;
1248 if (cone->n_eq < dim)
1249 return isl_basic_set_sample_with_cone(bset, cone);
1251 isl_basic_set_free(cone);
1252 return sample_bounded(bset);
1253 error:
1254 isl_basic_set_free(bset);
1255 return NULL;
1258 static struct isl_vec *pip_sample(struct isl_basic_set *bset)
1260 struct isl_mat *T;
1261 struct isl_ctx *ctx;
1262 struct isl_vec *sample;
1264 bset = isl_basic_set_skew_to_positive_orthant(bset, &T);
1265 if (!bset)
1266 return NULL;
1268 ctx = bset->ctx;
1269 sample = isl_pip_basic_set_sample(bset);
1271 if (sample && sample->size != 0)
1272 sample = isl_mat_vec_product(T, sample);
1273 else
1274 isl_mat_free(T);
1276 return sample;
1279 static struct isl_vec *basic_set_sample(struct isl_basic_set *bset, int bounded)
1281 struct isl_ctx *ctx;
1282 unsigned dim;
1283 if (!bset)
1284 return NULL;
1286 ctx = bset->ctx;
1287 if (isl_basic_set_plain_is_empty(bset))
1288 return empty_sample(bset);
1290 dim = isl_basic_set_n_dim(bset);
1291 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1292 isl_assert(ctx, bset->n_div == 0, goto error);
1294 if (bset->sample && bset->sample->size == 1 + dim) {
1295 int contains = isl_basic_set_contains(bset, bset->sample);
1296 if (contains < 0)
1297 goto error;
1298 if (contains) {
1299 struct isl_vec *sample = isl_vec_copy(bset->sample);
1300 isl_basic_set_free(bset);
1301 return sample;
1304 isl_vec_free(bset->sample);
1305 bset->sample = NULL;
1307 if (bset->n_eq > 0)
1308 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1309 : isl_basic_set_sample_vec);
1310 if (dim == 0)
1311 return zero_sample(bset);
1312 if (dim == 1)
1313 return interval_sample(bset);
1315 switch (bset->ctx->opt->ilp_solver) {
1316 case ISL_ILP_PIP:
1317 return pip_sample(bset);
1318 case ISL_ILP_GBR:
1319 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1321 isl_assert(bset->ctx, 0, );
1322 error:
1323 isl_basic_set_free(bset);
1324 return NULL;
1327 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1329 return basic_set_sample(bset, 0);
1332 /* Compute an integer sample in "bset", where the caller guarantees
1333 * that "bset" is bounded.
1335 struct isl_vec *isl_basic_set_sample_bounded(struct isl_basic_set *bset)
1337 return basic_set_sample(bset, 1);
1340 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1342 int i;
1343 int k;
1344 struct isl_basic_set *bset = NULL;
1345 struct isl_ctx *ctx;
1346 unsigned dim;
1348 if (!vec)
1349 return NULL;
1350 ctx = vec->ctx;
1351 isl_assert(ctx, vec->size != 0, goto error);
1353 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1354 if (!bset)
1355 goto error;
1356 dim = isl_basic_set_n_dim(bset);
1357 for (i = dim - 1; i >= 0; --i) {
1358 k = isl_basic_set_alloc_equality(bset);
1359 if (k < 0)
1360 goto error;
1361 isl_seq_clr(bset->eq[k], 1 + dim);
1362 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1363 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1365 bset->sample = vec;
1367 return bset;
1368 error:
1369 isl_basic_set_free(bset);
1370 isl_vec_free(vec);
1371 return NULL;
1374 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1376 struct isl_basic_set *bset;
1377 struct isl_vec *sample_vec;
1379 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1380 sample_vec = isl_basic_set_sample_vec(bset);
1381 if (!sample_vec)
1382 goto error;
1383 if (sample_vec->size == 0) {
1384 struct isl_basic_map *sample;
1385 sample = isl_basic_map_empty_like(bmap);
1386 isl_vec_free(sample_vec);
1387 isl_basic_map_free(bmap);
1388 return sample;
1390 bset = isl_basic_set_from_vec(sample_vec);
1391 return isl_basic_map_overlying_set(bset, bmap);
1392 error:
1393 isl_basic_map_free(bmap);
1394 return NULL;
1397 __isl_give isl_basic_set *isl_basic_set_sample(__isl_take isl_basic_set *bset)
1399 return isl_basic_map_sample(bset);
1402 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1404 int i;
1405 isl_basic_map *sample = NULL;
1407 if (!map)
1408 goto error;
1410 for (i = 0; i < map->n; ++i) {
1411 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1412 if (!sample)
1413 goto error;
1414 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1415 break;
1416 isl_basic_map_free(sample);
1418 if (i == map->n)
1419 sample = isl_basic_map_empty_like_map(map);
1420 isl_map_free(map);
1421 return sample;
1422 error:
1423 isl_map_free(map);
1424 return NULL;
1427 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1429 return (isl_basic_set *) isl_map_sample((isl_map *)set);
1432 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1434 isl_vec *vec;
1435 isl_space *dim;
1437 dim = isl_basic_set_get_space(bset);
1438 bset = isl_basic_set_underlying_set(bset);
1439 vec = isl_basic_set_sample_vec(bset);
1441 return isl_point_alloc(dim, vec);
1444 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1446 int i;
1447 isl_point *pnt;
1449 if (!set)
1450 return NULL;
1452 for (i = 0; i < set->n; ++i) {
1453 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1454 if (!pnt)
1455 goto error;
1456 if (!isl_point_is_void(pnt))
1457 break;
1458 isl_point_free(pnt);
1460 if (i == set->n)
1461 pnt = isl_point_void(isl_set_get_space(set));
1463 isl_set_free(set);
1464 return pnt;
1465 error:
1466 isl_set_free(set);
1467 return NULL;