isl_local_space_divs_known: extract out isl_local_divs_known
[isl.git] / isl_sample.c
blob058d689cef5f475b6ca7282f5ca72cb24ac2b023
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/vec.h>
14 #include <isl/mat.h>
15 #include <isl_seq.h>
16 #include "isl_equalities.h"
17 #include "isl_tab.h"
18 #include "isl_basis_reduction.h"
19 #include <isl_factorization.h>
20 #include <isl_point_private.h>
21 #include <isl_options_private.h>
22 #include <isl_vec_private.h>
24 #include <bset_from_bmap.c>
25 #include <set_to_map.c>
27 static __isl_give isl_vec *empty_sample(__isl_take isl_basic_set *bset)
29 struct isl_vec *vec;
31 vec = isl_vec_alloc(bset->ctx, 0);
32 isl_basic_set_free(bset);
33 return vec;
36 /* Construct a zero sample of the same dimension as bset.
37 * As a special case, if bset is zero-dimensional, this
38 * function creates a zero-dimensional sample point.
40 static __isl_give isl_vec *zero_sample(__isl_take isl_basic_set *bset)
42 unsigned dim;
43 struct isl_vec *sample;
45 dim = isl_basic_set_total_dim(bset);
46 sample = isl_vec_alloc(bset->ctx, 1 + dim);
47 if (sample) {
48 isl_int_set_si(sample->el[0], 1);
49 isl_seq_clr(sample->el + 1, dim);
51 isl_basic_set_free(bset);
52 return sample;
55 static __isl_give isl_vec *interval_sample(__isl_take isl_basic_set *bset)
57 int i;
58 isl_int t;
59 struct isl_vec *sample;
61 bset = isl_basic_set_simplify(bset);
62 if (!bset)
63 return NULL;
64 if (isl_basic_set_plain_is_empty(bset))
65 return empty_sample(bset);
66 if (bset->n_eq == 0 && bset->n_ineq == 0)
67 return zero_sample(bset);
69 sample = isl_vec_alloc(bset->ctx, 2);
70 if (!sample)
71 goto error;
72 if (!bset)
73 return NULL;
74 isl_int_set_si(sample->block.data[0], 1);
76 if (bset->n_eq > 0) {
77 isl_assert(bset->ctx, bset->n_eq == 1, goto error);
78 isl_assert(bset->ctx, bset->n_ineq == 0, goto error);
79 if (isl_int_is_one(bset->eq[0][1]))
80 isl_int_neg(sample->el[1], bset->eq[0][0]);
81 else {
82 isl_assert(bset->ctx, isl_int_is_negone(bset->eq[0][1]),
83 goto error);
84 isl_int_set(sample->el[1], bset->eq[0][0]);
86 isl_basic_set_free(bset);
87 return sample;
90 isl_int_init(t);
91 if (isl_int_is_one(bset->ineq[0][1]))
92 isl_int_neg(sample->block.data[1], bset->ineq[0][0]);
93 else
94 isl_int_set(sample->block.data[1], bset->ineq[0][0]);
95 for (i = 1; i < bset->n_ineq; ++i) {
96 isl_seq_inner_product(sample->block.data,
97 bset->ineq[i], 2, &t);
98 if (isl_int_is_neg(t))
99 break;
101 isl_int_clear(t);
102 if (i < bset->n_ineq) {
103 isl_vec_free(sample);
104 return empty_sample(bset);
107 isl_basic_set_free(bset);
108 return sample;
109 error:
110 isl_basic_set_free(bset);
111 isl_vec_free(sample);
112 return NULL;
115 /* Find a sample integer point, if any, in bset, which is known
116 * to have equalities. If bset contains no integer points, then
117 * return a zero-length vector.
118 * We simply remove the known equalities, compute a sample
119 * in the resulting bset, using the specified recurse function,
120 * and then transform the sample back to the original space.
122 static __isl_give isl_vec *sample_eq(__isl_take isl_basic_set *bset,
123 __isl_give isl_vec *(*recurse)(__isl_take isl_basic_set *))
125 struct isl_mat *T;
126 struct isl_vec *sample;
128 if (!bset)
129 return NULL;
131 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
132 sample = recurse(bset);
133 if (!sample || sample->size == 0)
134 isl_mat_free(T);
135 else
136 sample = isl_mat_vec_product(T, sample);
137 return sample;
140 /* Return a matrix containing the equalities of the tableau
141 * in constraint form. The tableau is assumed to have
142 * an associated bset that has been kept up-to-date.
144 static struct isl_mat *tab_equalities(struct isl_tab *tab)
146 int i, j;
147 int n_eq;
148 struct isl_mat *eq;
149 struct isl_basic_set *bset;
151 if (!tab)
152 return NULL;
154 bset = isl_tab_peek_bset(tab);
155 isl_assert(tab->mat->ctx, bset, return NULL);
157 n_eq = tab->n_var - tab->n_col + tab->n_dead;
158 if (tab->empty || n_eq == 0)
159 return isl_mat_alloc(tab->mat->ctx, 0, tab->n_var);
160 if (n_eq == tab->n_var)
161 return isl_mat_identity(tab->mat->ctx, tab->n_var);
163 eq = isl_mat_alloc(tab->mat->ctx, n_eq, tab->n_var);
164 if (!eq)
165 return NULL;
166 for (i = 0, j = 0; i < tab->n_con; ++i) {
167 if (tab->con[i].is_row)
168 continue;
169 if (tab->con[i].index >= 0 && tab->con[i].index >= tab->n_dead)
170 continue;
171 if (i < bset->n_eq)
172 isl_seq_cpy(eq->row[j], bset->eq[i] + 1, tab->n_var);
173 else
174 isl_seq_cpy(eq->row[j],
175 bset->ineq[i - bset->n_eq] + 1, tab->n_var);
176 ++j;
178 isl_assert(bset->ctx, j == n_eq, goto error);
179 return eq;
180 error:
181 isl_mat_free(eq);
182 return NULL;
185 /* Compute and return an initial basis for the bounded tableau "tab".
187 * If the tableau is either full-dimensional or zero-dimensional,
188 * the we simply return an identity matrix.
189 * Otherwise, we construct a basis whose first directions correspond
190 * to equalities.
192 static struct isl_mat *initial_basis(struct isl_tab *tab)
194 int n_eq;
195 struct isl_mat *eq;
196 struct isl_mat *Q;
198 tab->n_unbounded = 0;
199 tab->n_zero = n_eq = tab->n_var - tab->n_col + tab->n_dead;
200 if (tab->empty || n_eq == 0 || n_eq == tab->n_var)
201 return isl_mat_identity(tab->mat->ctx, 1 + tab->n_var);
203 eq = tab_equalities(tab);
204 eq = isl_mat_left_hermite(eq, 0, NULL, &Q);
205 if (!eq)
206 return NULL;
207 isl_mat_free(eq);
209 Q = isl_mat_lin_to_aff(Q);
210 return Q;
213 /* Compute the minimum of the current ("level") basis row over "tab"
214 * and store the result in position "level" of "min".
216 * This function assumes that at least one more row and at least
217 * one more element in the constraint array are available in the tableau.
219 static enum isl_lp_result compute_min(isl_ctx *ctx, struct isl_tab *tab,
220 __isl_keep isl_vec *min, int level)
222 return isl_tab_min(tab, tab->basis->row[1 + level],
223 ctx->one, &min->el[level], NULL, 0);
226 /* Compute the maximum of the current ("level") basis row over "tab"
227 * and store the result in position "level" of "max".
229 * This function assumes that at least one more row and at least
230 * one more element in the constraint array are available in the tableau.
232 static enum isl_lp_result compute_max(isl_ctx *ctx, struct isl_tab *tab,
233 __isl_keep isl_vec *max, int level)
235 enum isl_lp_result res;
236 unsigned dim = tab->n_var;
238 isl_seq_neg(tab->basis->row[1 + level] + 1,
239 tab->basis->row[1 + level] + 1, dim);
240 res = isl_tab_min(tab, tab->basis->row[1 + level],
241 ctx->one, &max->el[level], NULL, 0);
242 isl_seq_neg(tab->basis->row[1 + level] + 1,
243 tab->basis->row[1 + level] + 1, dim);
244 isl_int_neg(max->el[level], max->el[level]);
246 return res;
249 /* Perform a greedy search for an integer point in the set represented
250 * by "tab", given that the minimal rational value (rounded up to the
251 * nearest integer) at "level" is smaller than the maximal rational
252 * value (rounded down to the nearest integer).
254 * Return 1 if we have found an integer point (if tab->n_unbounded > 0
255 * then we may have only found integer values for the bounded dimensions
256 * and it is the responsibility of the caller to extend this solution
257 * to the unbounded dimensions).
258 * Return 0 if greedy search did not result in a solution.
259 * Return -1 if some error occurred.
261 * We assign a value half-way between the minimum and the maximum
262 * to the current dimension and check if the minimal value of the
263 * next dimension is still smaller than (or equal) to the maximal value.
264 * We continue this process until either
265 * - the minimal value (rounded up) is greater than the maximal value
266 * (rounded down). In this case, greedy search has failed.
267 * - we have exhausted all bounded dimensions, meaning that we have
268 * found a solution.
269 * - the sample value of the tableau is integral.
270 * - some error has occurred.
272 static int greedy_search(isl_ctx *ctx, struct isl_tab *tab,
273 __isl_keep isl_vec *min, __isl_keep isl_vec *max, int level)
275 struct isl_tab_undo *snap;
276 enum isl_lp_result res;
278 snap = isl_tab_snap(tab);
280 do {
281 isl_int_add(tab->basis->row[1 + level][0],
282 min->el[level], max->el[level]);
283 isl_int_fdiv_q_ui(tab->basis->row[1 + level][0],
284 tab->basis->row[1 + level][0], 2);
285 isl_int_neg(tab->basis->row[1 + level][0],
286 tab->basis->row[1 + level][0]);
287 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
288 return -1;
289 isl_int_set_si(tab->basis->row[1 + level][0], 0);
291 if (++level >= tab->n_var - tab->n_unbounded)
292 return 1;
293 if (isl_tab_sample_is_integer(tab))
294 return 1;
296 res = compute_min(ctx, tab, min, level);
297 if (res == isl_lp_error)
298 return -1;
299 if (res != isl_lp_ok)
300 isl_die(ctx, isl_error_internal,
301 "expecting bounded rational solution",
302 return -1);
303 res = compute_max(ctx, tab, max, level);
304 if (res == isl_lp_error)
305 return -1;
306 if (res != isl_lp_ok)
307 isl_die(ctx, isl_error_internal,
308 "expecting bounded rational solution",
309 return -1);
310 } while (isl_int_le(min->el[level], max->el[level]));
312 if (isl_tab_rollback(tab, snap) < 0)
313 return -1;
315 return 0;
318 /* Given a tableau representing a set, find and return
319 * an integer point in the set, if there is any.
321 * We perform a depth first search
322 * for an integer point, by scanning all possible values in the range
323 * attained by a basis vector, where an initial basis may have been set
324 * by the calling function. Otherwise an initial basis that exploits
325 * the equalities in the tableau is created.
326 * tab->n_zero is currently ignored and is clobbered by this function.
328 * The tableau is allowed to have unbounded direction, but then
329 * the calling function needs to set an initial basis, with the
330 * unbounded directions last and with tab->n_unbounded set
331 * to the number of unbounded directions.
332 * Furthermore, the calling functions needs to add shifted copies
333 * of all constraints involving unbounded directions to ensure
334 * that any feasible rational value in these directions can be rounded
335 * up to yield a feasible integer value.
336 * In particular, let B define the given basis x' = B x
337 * and let T be the inverse of B, i.e., X = T x'.
338 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
339 * or a T x' + c >= 0 in terms of the given basis. Assume that
340 * the bounded directions have an integer value, then we can safely
341 * round up the values for the unbounded directions if we make sure
342 * that x' not only satisfies the original constraint, but also
343 * the constraint "a T x' + c + s >= 0" with s the sum of all
344 * negative values in the last n_unbounded entries of "a T".
345 * The calling function therefore needs to add the constraint
346 * a x + c + s >= 0. The current function then scans the first
347 * directions for an integer value and once those have been found,
348 * it can compute "T ceil(B x)" to yield an integer point in the set.
349 * Note that during the search, the first rows of B may be changed
350 * by a basis reduction, but the last n_unbounded rows of B remain
351 * unaltered and are also not mixed into the first rows.
353 * The search is implemented iteratively. "level" identifies the current
354 * basis vector. "init" is true if we want the first value at the current
355 * level and false if we want the next value.
357 * At the start of each level, we first check if we can find a solution
358 * using greedy search. If not, we continue with the exhaustive search.
360 * The initial basis is the identity matrix. If the range in some direction
361 * contains more than one integer value, we perform basis reduction based
362 * on the value of ctx->opt->gbr
363 * - ISL_GBR_NEVER: never perform basis reduction
364 * - ISL_GBR_ONCE: only perform basis reduction the first
365 * time such a range is encountered
366 * - ISL_GBR_ALWAYS: always perform basis reduction when
367 * such a range is encountered
369 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
370 * reduction computation to return early. That is, as soon as it
371 * finds a reasonable first direction.
373 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
375 unsigned dim;
376 unsigned gbr;
377 struct isl_ctx *ctx;
378 struct isl_vec *sample;
379 struct isl_vec *min;
380 struct isl_vec *max;
381 enum isl_lp_result res;
382 int level;
383 int init;
384 int reduced;
385 struct isl_tab_undo **snap;
387 if (!tab)
388 return NULL;
389 if (tab->empty)
390 return isl_vec_alloc(tab->mat->ctx, 0);
392 if (!tab->basis)
393 tab->basis = initial_basis(tab);
394 if (!tab->basis)
395 return NULL;
396 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
397 return NULL);
398 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
399 return NULL);
401 ctx = tab->mat->ctx;
402 dim = tab->n_var;
403 gbr = ctx->opt->gbr;
405 if (tab->n_unbounded == tab->n_var) {
406 sample = isl_tab_get_sample_value(tab);
407 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
408 sample = isl_vec_ceil(sample);
409 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
410 sample);
411 return sample;
414 if (isl_tab_extend_cons(tab, dim + 1) < 0)
415 return NULL;
417 min = isl_vec_alloc(ctx, dim);
418 max = isl_vec_alloc(ctx, dim);
419 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
421 if (!min || !max || !snap)
422 goto error;
424 level = 0;
425 init = 1;
426 reduced = 0;
428 while (level >= 0) {
429 if (init) {
430 int choice;
432 res = compute_min(ctx, tab, min, level);
433 if (res == isl_lp_error)
434 goto error;
435 if (res != isl_lp_ok)
436 isl_die(ctx, isl_error_internal,
437 "expecting bounded rational solution",
438 goto error);
439 if (isl_tab_sample_is_integer(tab))
440 break;
441 res = compute_max(ctx, tab, max, level);
442 if (res == isl_lp_error)
443 goto error;
444 if (res != isl_lp_ok)
445 isl_die(ctx, isl_error_internal,
446 "expecting bounded rational solution",
447 goto error);
448 if (isl_tab_sample_is_integer(tab))
449 break;
450 choice = isl_int_lt(min->el[level], max->el[level]);
451 if (choice) {
452 int g;
453 g = greedy_search(ctx, tab, min, max, level);
454 if (g < 0)
455 goto error;
456 if (g)
457 break;
459 if (!reduced && choice &&
460 ctx->opt->gbr != ISL_GBR_NEVER) {
461 unsigned gbr_only_first;
462 if (ctx->opt->gbr == ISL_GBR_ONCE)
463 ctx->opt->gbr = ISL_GBR_NEVER;
464 tab->n_zero = level;
465 gbr_only_first = ctx->opt->gbr_only_first;
466 ctx->opt->gbr_only_first =
467 ctx->opt->gbr == ISL_GBR_ALWAYS;
468 tab = isl_tab_compute_reduced_basis(tab);
469 ctx->opt->gbr_only_first = gbr_only_first;
470 if (!tab || !tab->basis)
471 goto error;
472 reduced = 1;
473 continue;
475 reduced = 0;
476 snap[level] = isl_tab_snap(tab);
477 } else
478 isl_int_add_ui(min->el[level], min->el[level], 1);
480 if (isl_int_gt(min->el[level], max->el[level])) {
481 level--;
482 init = 0;
483 if (level >= 0)
484 if (isl_tab_rollback(tab, snap[level]) < 0)
485 goto error;
486 continue;
488 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
489 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
490 goto error;
491 isl_int_set_si(tab->basis->row[1 + level][0], 0);
492 if (level + tab->n_unbounded < dim - 1) {
493 ++level;
494 init = 1;
495 continue;
497 break;
500 if (level >= 0) {
501 sample = isl_tab_get_sample_value(tab);
502 if (!sample)
503 goto error;
504 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
505 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
506 sample);
507 sample = isl_vec_ceil(sample);
508 sample = isl_mat_vec_inverse_product(
509 isl_mat_copy(tab->basis), sample);
511 } else
512 sample = isl_vec_alloc(ctx, 0);
514 ctx->opt->gbr = gbr;
515 isl_vec_free(min);
516 isl_vec_free(max);
517 free(snap);
518 return sample;
519 error:
520 ctx->opt->gbr = gbr;
521 isl_vec_free(min);
522 isl_vec_free(max);
523 free(snap);
524 return NULL;
527 static __isl_give isl_vec *sample_bounded(__isl_take isl_basic_set *bset);
529 /* Compute a sample point of the given basic set, based on the given,
530 * non-trivial factorization.
532 static __isl_give isl_vec *factored_sample(__isl_take isl_basic_set *bset,
533 __isl_take isl_factorizer *f)
535 int i, n;
536 isl_vec *sample = NULL;
537 isl_ctx *ctx;
538 unsigned nparam;
539 unsigned nvar;
541 ctx = isl_basic_set_get_ctx(bset);
542 if (!ctx)
543 goto error;
545 nparam = isl_basic_set_dim(bset, isl_dim_param);
546 nvar = isl_basic_set_dim(bset, isl_dim_set);
548 sample = isl_vec_alloc(ctx, 1 + isl_basic_set_total_dim(bset));
549 if (!sample)
550 goto error;
551 isl_int_set_si(sample->el[0], 1);
553 bset = isl_morph_basic_set(isl_morph_copy(f->morph), bset);
555 for (i = 0, n = 0; i < f->n_group; ++i) {
556 isl_basic_set *bset_i;
557 isl_vec *sample_i;
559 bset_i = isl_basic_set_copy(bset);
560 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
561 nparam + n + f->len[i], nvar - n - f->len[i]);
562 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
563 nparam, n);
564 bset_i = isl_basic_set_drop(bset_i, isl_dim_set,
565 n + f->len[i], nvar - n - f->len[i]);
566 bset_i = isl_basic_set_drop(bset_i, isl_dim_set, 0, n);
568 sample_i = sample_bounded(bset_i);
569 if (!sample_i)
570 goto error;
571 if (sample_i->size == 0) {
572 isl_basic_set_free(bset);
573 isl_factorizer_free(f);
574 isl_vec_free(sample);
575 return sample_i;
577 isl_seq_cpy(sample->el + 1 + nparam + n,
578 sample_i->el + 1, f->len[i]);
579 isl_vec_free(sample_i);
581 n += f->len[i];
584 f->morph = isl_morph_inverse(f->morph);
585 sample = isl_morph_vec(isl_morph_copy(f->morph), sample);
587 isl_basic_set_free(bset);
588 isl_factorizer_free(f);
589 return sample;
590 error:
591 isl_basic_set_free(bset);
592 isl_factorizer_free(f);
593 isl_vec_free(sample);
594 return NULL;
597 /* Given a basic set that is known to be bounded, find and return
598 * an integer point in the basic set, if there is any.
600 * After handling some trivial cases, we construct a tableau
601 * and then use isl_tab_sample to find a sample, passing it
602 * the identity matrix as initial basis.
604 static __isl_give isl_vec *sample_bounded(__isl_take isl_basic_set *bset)
606 unsigned dim;
607 struct isl_vec *sample;
608 struct isl_tab *tab = NULL;
609 isl_factorizer *f;
611 if (!bset)
612 return NULL;
614 if (isl_basic_set_plain_is_empty(bset))
615 return empty_sample(bset);
617 dim = isl_basic_set_total_dim(bset);
618 if (dim == 0)
619 return zero_sample(bset);
620 if (dim == 1)
621 return interval_sample(bset);
622 if (bset->n_eq > 0)
623 return sample_eq(bset, sample_bounded);
625 f = isl_basic_set_factorizer(bset);
626 if (!f)
627 goto error;
628 if (f->n_group != 0)
629 return factored_sample(bset, f);
630 isl_factorizer_free(f);
632 tab = isl_tab_from_basic_set(bset, 1);
633 if (tab && tab->empty) {
634 isl_tab_free(tab);
635 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
636 sample = isl_vec_alloc(isl_basic_set_get_ctx(bset), 0);
637 isl_basic_set_free(bset);
638 return sample;
641 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
642 if (isl_tab_detect_implicit_equalities(tab) < 0)
643 goto error;
645 sample = isl_tab_sample(tab);
646 if (!sample)
647 goto error;
649 if (sample->size > 0) {
650 isl_vec_free(bset->sample);
651 bset->sample = isl_vec_copy(sample);
654 isl_basic_set_free(bset);
655 isl_tab_free(tab);
656 return sample;
657 error:
658 isl_basic_set_free(bset);
659 isl_tab_free(tab);
660 return NULL;
663 /* Given a basic set "bset" and a value "sample" for the first coordinates
664 * of bset, plug in these values and drop the corresponding coordinates.
666 * We do this by computing the preimage of the transformation
668 * [ 1 0 ]
669 * x = [ s 0 ] x'
670 * [ 0 I ]
672 * where [1 s] is the sample value and I is the identity matrix of the
673 * appropriate dimension.
675 static __isl_give isl_basic_set *plug_in(__isl_take isl_basic_set *bset,
676 __isl_take isl_vec *sample)
678 int i;
679 unsigned total;
680 struct isl_mat *T;
682 if (!bset || !sample)
683 goto error;
685 total = isl_basic_set_total_dim(bset);
686 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
687 if (!T)
688 goto error;
690 for (i = 0; i < sample->size; ++i) {
691 isl_int_set(T->row[i][0], sample->el[i]);
692 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
694 for (i = 0; i < T->n_col - 1; ++i) {
695 isl_seq_clr(T->row[sample->size + i], T->n_col);
696 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
698 isl_vec_free(sample);
700 bset = isl_basic_set_preimage(bset, T);
701 return bset;
702 error:
703 isl_basic_set_free(bset);
704 isl_vec_free(sample);
705 return NULL;
708 /* Given a basic set "bset", return any (possibly non-integer) point
709 * in the basic set.
711 static __isl_give isl_vec *rational_sample(__isl_take isl_basic_set *bset)
713 struct isl_tab *tab;
714 struct isl_vec *sample;
716 if (!bset)
717 return NULL;
719 tab = isl_tab_from_basic_set(bset, 0);
720 sample = isl_tab_get_sample_value(tab);
721 isl_tab_free(tab);
723 isl_basic_set_free(bset);
725 return sample;
728 /* Given a linear cone "cone" and a rational point "vec",
729 * construct a polyhedron with shifted copies of the constraints in "cone",
730 * i.e., a polyhedron with "cone" as its recession cone, such that each
731 * point x in this polyhedron is such that the unit box positioned at x
732 * lies entirely inside the affine cone 'vec + cone'.
733 * Any rational point in this polyhedron may therefore be rounded up
734 * to yield an integer point that lies inside said affine cone.
736 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
737 * point "vec" by v/d.
738 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
739 * by <a_i, x> - b/d >= 0.
740 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
741 * We prefer this polyhedron over the actual affine cone because it doesn't
742 * require a scaling of the constraints.
743 * If each of the vertices of the unit cube positioned at x lies inside
744 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
745 * We therefore impose that x' = x + \sum e_i, for any selection of unit
746 * vectors lies inside the polyhedron, i.e.,
748 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
750 * The most stringent of these constraints is the one that selects
751 * all negative a_i, so the polyhedron we are looking for has constraints
753 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
755 * Note that if cone were known to have only non-negative rays
756 * (which can be accomplished by a unimodular transformation),
757 * then we would only have to check the points x' = x + e_i
758 * and we only have to add the smallest negative a_i (if any)
759 * instead of the sum of all negative a_i.
761 static __isl_give isl_basic_set *shift_cone(__isl_take isl_basic_set *cone,
762 __isl_take isl_vec *vec)
764 int i, j, k;
765 unsigned total;
767 struct isl_basic_set *shift = NULL;
769 if (!cone || !vec)
770 goto error;
772 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
774 total = isl_basic_set_total_dim(cone);
776 shift = isl_basic_set_alloc_space(isl_basic_set_get_space(cone),
777 0, 0, cone->n_ineq);
779 for (i = 0; i < cone->n_ineq; ++i) {
780 k = isl_basic_set_alloc_inequality(shift);
781 if (k < 0)
782 goto error;
783 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
784 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
785 &shift->ineq[k][0]);
786 isl_int_cdiv_q(shift->ineq[k][0],
787 shift->ineq[k][0], vec->el[0]);
788 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
789 for (j = 0; j < total; ++j) {
790 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
791 continue;
792 isl_int_add(shift->ineq[k][0],
793 shift->ineq[k][0], shift->ineq[k][1 + j]);
797 isl_basic_set_free(cone);
798 isl_vec_free(vec);
800 return isl_basic_set_finalize(shift);
801 error:
802 isl_basic_set_free(shift);
803 isl_basic_set_free(cone);
804 isl_vec_free(vec);
805 return NULL;
808 /* Given a rational point vec in a (transformed) basic set,
809 * such that cone is the recession cone of the original basic set,
810 * "round up" the rational point to an integer point.
812 * We first check if the rational point just happens to be integer.
813 * If not, we transform the cone in the same way as the basic set,
814 * pick a point x in this cone shifted to the rational point such that
815 * the whole unit cube at x is also inside this affine cone.
816 * Then we simply round up the coordinates of x and return the
817 * resulting integer point.
819 static __isl_give isl_vec *round_up_in_cone(__isl_take isl_vec *vec,
820 __isl_take isl_basic_set *cone, __isl_take isl_mat *U)
822 unsigned total;
824 if (!vec || !cone || !U)
825 goto error;
827 isl_assert(vec->ctx, vec->size != 0, goto error);
828 if (isl_int_is_one(vec->el[0])) {
829 isl_mat_free(U);
830 isl_basic_set_free(cone);
831 return vec;
834 total = isl_basic_set_total_dim(cone);
835 cone = isl_basic_set_preimage(cone, U);
836 cone = isl_basic_set_remove_dims(cone, isl_dim_set,
837 0, total - (vec->size - 1));
839 cone = shift_cone(cone, vec);
841 vec = rational_sample(cone);
842 vec = isl_vec_ceil(vec);
843 return vec;
844 error:
845 isl_mat_free(U);
846 isl_vec_free(vec);
847 isl_basic_set_free(cone);
848 return NULL;
851 /* Concatenate two integer vectors, i.e., two vectors with denominator
852 * (stored in element 0) equal to 1.
854 static __isl_give isl_vec *vec_concat(__isl_take isl_vec *vec1,
855 __isl_take isl_vec *vec2)
857 struct isl_vec *vec;
859 if (!vec1 || !vec2)
860 goto error;
861 isl_assert(vec1->ctx, vec1->size > 0, goto error);
862 isl_assert(vec2->ctx, vec2->size > 0, goto error);
863 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
864 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
866 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
867 if (!vec)
868 goto error;
870 isl_seq_cpy(vec->el, vec1->el, vec1->size);
871 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
873 isl_vec_free(vec1);
874 isl_vec_free(vec2);
876 return vec;
877 error:
878 isl_vec_free(vec1);
879 isl_vec_free(vec2);
880 return NULL;
883 /* Give a basic set "bset" with recession cone "cone", compute and
884 * return an integer point in bset, if any.
886 * If the recession cone is full-dimensional, then we know that
887 * bset contains an infinite number of integer points and it is
888 * fairly easy to pick one of them.
889 * If the recession cone is not full-dimensional, then we first
890 * transform bset such that the bounded directions appear as
891 * the first dimensions of the transformed basic set.
892 * We do this by using a unimodular transformation that transforms
893 * the equalities in the recession cone to equalities on the first
894 * dimensions.
896 * The transformed set is then projected onto its bounded dimensions.
897 * Note that to compute this projection, we can simply drop all constraints
898 * involving any of the unbounded dimensions since these constraints
899 * cannot be combined to produce a constraint on the bounded dimensions.
900 * To see this, assume that there is such a combination of constraints
901 * that produces a constraint on the bounded dimensions. This means
902 * that some combination of the unbounded dimensions has both an upper
903 * bound and a lower bound in terms of the bounded dimensions, but then
904 * this combination would be a bounded direction too and would have been
905 * transformed into a bounded dimensions.
907 * We then compute a sample value in the bounded dimensions.
908 * If no such value can be found, then the original set did not contain
909 * any integer points and we are done.
910 * Otherwise, we plug in the value we found in the bounded dimensions,
911 * project out these bounded dimensions and end up with a set with
912 * a full-dimensional recession cone.
913 * A sample point in this set is computed by "rounding up" any
914 * rational point in the set.
916 * The sample points in the bounded and unbounded dimensions are
917 * then combined into a single sample point and transformed back
918 * to the original space.
920 __isl_give isl_vec *isl_basic_set_sample_with_cone(
921 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
923 unsigned total;
924 unsigned cone_dim;
925 struct isl_mat *M, *U;
926 struct isl_vec *sample;
927 struct isl_vec *cone_sample;
928 struct isl_ctx *ctx;
929 struct isl_basic_set *bounded;
931 if (!bset || !cone)
932 goto error;
934 ctx = isl_basic_set_get_ctx(bset);
935 total = isl_basic_set_total_dim(cone);
936 cone_dim = total - cone->n_eq;
938 M = isl_mat_sub_alloc6(ctx, cone->eq, 0, cone->n_eq, 1, total);
939 M = isl_mat_left_hermite(M, 0, &U, NULL);
940 if (!M)
941 goto error;
942 isl_mat_free(M);
944 U = isl_mat_lin_to_aff(U);
945 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
947 bounded = isl_basic_set_copy(bset);
948 bounded = isl_basic_set_drop_constraints_involving(bounded,
949 total - cone_dim, cone_dim);
950 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
951 sample = sample_bounded(bounded);
952 if (!sample || sample->size == 0) {
953 isl_basic_set_free(bset);
954 isl_basic_set_free(cone);
955 isl_mat_free(U);
956 return sample;
958 bset = plug_in(bset, isl_vec_copy(sample));
959 cone_sample = rational_sample(bset);
960 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
961 sample = vec_concat(sample, cone_sample);
962 sample = isl_mat_vec_product(U, sample);
963 return sample;
964 error:
965 isl_basic_set_free(cone);
966 isl_basic_set_free(bset);
967 return NULL;
970 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
972 int i;
974 isl_int_set_si(*s, 0);
976 for (i = 0; i < v->size; ++i)
977 if (isl_int_is_neg(v->el[i]))
978 isl_int_add(*s, *s, v->el[i]);
981 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
982 * to the recession cone and the inverse of a new basis U = inv(B),
983 * with the unbounded directions in B last,
984 * add constraints to "tab" that ensure any rational value
985 * in the unbounded directions can be rounded up to an integer value.
987 * The new basis is given by x' = B x, i.e., x = U x'.
988 * For any rational value of the last tab->n_unbounded coordinates
989 * in the update tableau, the value that is obtained by rounding
990 * up this value should be contained in the original tableau.
991 * For any constraint "a x + c >= 0", we therefore need to add
992 * a constraint "a x + c + s >= 0", with s the sum of all negative
993 * entries in the last elements of "a U".
995 * Since we are not interested in the first entries of any of the "a U",
996 * we first drop the columns of U that correpond to bounded directions.
998 static int tab_shift_cone(struct isl_tab *tab,
999 struct isl_tab *tab_cone, struct isl_mat *U)
1001 int i;
1002 isl_int v;
1003 struct isl_basic_set *bset = NULL;
1005 if (tab && tab->n_unbounded == 0) {
1006 isl_mat_free(U);
1007 return 0;
1009 isl_int_init(v);
1010 if (!tab || !tab_cone || !U)
1011 goto error;
1012 bset = isl_tab_peek_bset(tab_cone);
1013 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
1014 for (i = 0; i < bset->n_ineq; ++i) {
1015 int ok;
1016 struct isl_vec *row = NULL;
1017 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
1018 continue;
1019 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
1020 if (!row)
1021 goto error;
1022 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
1023 row = isl_vec_mat_product(row, isl_mat_copy(U));
1024 if (!row)
1025 goto error;
1026 vec_sum_of_neg(row, &v);
1027 isl_vec_free(row);
1028 if (isl_int_is_zero(v))
1029 continue;
1030 if (isl_tab_extend_cons(tab, 1) < 0)
1031 goto error;
1032 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
1033 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1034 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1035 if (!ok)
1036 goto error;
1039 isl_mat_free(U);
1040 isl_int_clear(v);
1041 return 0;
1042 error:
1043 isl_mat_free(U);
1044 isl_int_clear(v);
1045 return -1;
1048 /* Compute and return an initial basis for the possibly
1049 * unbounded tableau "tab". "tab_cone" is a tableau
1050 * for the corresponding recession cone.
1051 * Additionally, add constraints to "tab" that ensure
1052 * that any rational value for the unbounded directions
1053 * can be rounded up to an integer value.
1055 * If the tableau is bounded, i.e., if the recession cone
1056 * is zero-dimensional, then we just use inital_basis.
1057 * Otherwise, we construct a basis whose first directions
1058 * correspond to equalities, followed by bounded directions,
1059 * i.e., equalities in the recession cone.
1060 * The remaining directions are then unbounded.
1062 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1063 struct isl_tab *tab_cone)
1065 struct isl_mat *eq;
1066 struct isl_mat *cone_eq;
1067 struct isl_mat *U, *Q;
1069 if (!tab || !tab_cone)
1070 return -1;
1072 if (tab_cone->n_col == tab_cone->n_dead) {
1073 tab->basis = initial_basis(tab);
1074 return tab->basis ? 0 : -1;
1077 eq = tab_equalities(tab);
1078 if (!eq)
1079 return -1;
1080 tab->n_zero = eq->n_row;
1081 cone_eq = tab_equalities(tab_cone);
1082 eq = isl_mat_concat(eq, cone_eq);
1083 if (!eq)
1084 return -1;
1085 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1086 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1087 if (!eq)
1088 return -1;
1089 isl_mat_free(eq);
1090 tab->basis = isl_mat_lin_to_aff(Q);
1091 if (tab_shift_cone(tab, tab_cone, U) < 0)
1092 return -1;
1093 if (!tab->basis)
1094 return -1;
1095 return 0;
1098 /* Compute and return a sample point in bset using generalized basis
1099 * reduction. We first check if the input set has a non-trivial
1100 * recession cone. If so, we perform some extra preprocessing in
1101 * sample_with_cone. Otherwise, we directly perform generalized basis
1102 * reduction.
1104 static __isl_give isl_vec *gbr_sample(__isl_take isl_basic_set *bset)
1106 unsigned dim;
1107 struct isl_basic_set *cone;
1109 dim = isl_basic_set_total_dim(bset);
1111 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1112 if (!cone)
1113 goto error;
1115 if (cone->n_eq < dim)
1116 return isl_basic_set_sample_with_cone(bset, cone);
1118 isl_basic_set_free(cone);
1119 return sample_bounded(bset);
1120 error:
1121 isl_basic_set_free(bset);
1122 return NULL;
1125 static __isl_give isl_vec *basic_set_sample(__isl_take isl_basic_set *bset,
1126 int bounded)
1128 struct isl_ctx *ctx;
1129 unsigned dim;
1130 if (!bset)
1131 return NULL;
1133 ctx = bset->ctx;
1134 if (isl_basic_set_plain_is_empty(bset))
1135 return empty_sample(bset);
1137 dim = isl_basic_set_n_dim(bset);
1138 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1139 isl_assert(ctx, bset->n_div == 0, goto error);
1141 if (bset->sample && bset->sample->size == 1 + dim) {
1142 int contains = isl_basic_set_contains(bset, bset->sample);
1143 if (contains < 0)
1144 goto error;
1145 if (contains) {
1146 struct isl_vec *sample = isl_vec_copy(bset->sample);
1147 isl_basic_set_free(bset);
1148 return sample;
1151 isl_vec_free(bset->sample);
1152 bset->sample = NULL;
1154 if (bset->n_eq > 0)
1155 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1156 : isl_basic_set_sample_vec);
1157 if (dim == 0)
1158 return zero_sample(bset);
1159 if (dim == 1)
1160 return interval_sample(bset);
1162 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1163 error:
1164 isl_basic_set_free(bset);
1165 return NULL;
1168 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1170 return basic_set_sample(bset, 0);
1173 /* Compute an integer sample in "bset", where the caller guarantees
1174 * that "bset" is bounded.
1176 __isl_give isl_vec *isl_basic_set_sample_bounded(__isl_take isl_basic_set *bset)
1178 return basic_set_sample(bset, 1);
1181 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1183 int i;
1184 int k;
1185 struct isl_basic_set *bset = NULL;
1186 struct isl_ctx *ctx;
1187 unsigned dim;
1189 if (!vec)
1190 return NULL;
1191 ctx = vec->ctx;
1192 isl_assert(ctx, vec->size != 0, goto error);
1194 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1195 if (!bset)
1196 goto error;
1197 dim = isl_basic_set_n_dim(bset);
1198 for (i = dim - 1; i >= 0; --i) {
1199 k = isl_basic_set_alloc_equality(bset);
1200 if (k < 0)
1201 goto error;
1202 isl_seq_clr(bset->eq[k], 1 + dim);
1203 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1204 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1206 bset->sample = vec;
1208 return bset;
1209 error:
1210 isl_basic_set_free(bset);
1211 isl_vec_free(vec);
1212 return NULL;
1215 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1217 struct isl_basic_set *bset;
1218 struct isl_vec *sample_vec;
1220 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1221 sample_vec = isl_basic_set_sample_vec(bset);
1222 if (!sample_vec)
1223 goto error;
1224 if (sample_vec->size == 0) {
1225 isl_vec_free(sample_vec);
1226 return isl_basic_map_set_to_empty(bmap);
1228 isl_vec_free(bmap->sample);
1229 bmap->sample = isl_vec_copy(sample_vec);
1230 bset = isl_basic_set_from_vec(sample_vec);
1231 return isl_basic_map_overlying_set(bset, bmap);
1232 error:
1233 isl_basic_map_free(bmap);
1234 return NULL;
1237 __isl_give isl_basic_set *isl_basic_set_sample(__isl_take isl_basic_set *bset)
1239 return isl_basic_map_sample(bset);
1242 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1244 int i;
1245 isl_basic_map *sample = NULL;
1247 if (!map)
1248 goto error;
1250 for (i = 0; i < map->n; ++i) {
1251 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1252 if (!sample)
1253 goto error;
1254 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1255 break;
1256 isl_basic_map_free(sample);
1258 if (i == map->n)
1259 sample = isl_basic_map_empty(isl_map_get_space(map));
1260 isl_map_free(map);
1261 return sample;
1262 error:
1263 isl_map_free(map);
1264 return NULL;
1267 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1269 return bset_from_bmap(isl_map_sample(set_to_map(set)));
1272 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1274 isl_vec *vec;
1275 isl_space *dim;
1277 dim = isl_basic_set_get_space(bset);
1278 bset = isl_basic_set_underlying_set(bset);
1279 vec = isl_basic_set_sample_vec(bset);
1281 return isl_point_alloc(dim, vec);
1284 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1286 int i;
1287 isl_point *pnt;
1289 if (!set)
1290 return NULL;
1292 for (i = 0; i < set->n; ++i) {
1293 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1294 if (!pnt)
1295 goto error;
1296 if (!isl_point_is_void(pnt))
1297 break;
1298 isl_point_free(pnt);
1300 if (i == set->n)
1301 pnt = isl_point_void(isl_set_get_space(set));
1303 isl_set_free(set);
1304 return pnt;
1305 error:
1306 isl_set_free(set);
1307 return NULL;