Make pass-by-reference explicit by using pointers
[isl.git] / isl_sample.c
blob71dec424df009de829253e22bd99810a3837e18e
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 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 /* Find a sample integer point, if any, in bset, which is known
113 * to have equalities. If bset contains no integer points, then
114 * return a zero-length vector.
115 * We simply remove the known equalities, compute a sample
116 * in the resulting bset, using the specified recurse function,
117 * and then transform the sample back to the original space.
119 static struct isl_vec *sample_eq(struct isl_basic_set *bset,
120 struct isl_vec *(*recurse)(struct isl_basic_set *))
122 struct isl_mat *T;
123 struct isl_vec *sample;
125 if (!bset)
126 return NULL;
128 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
129 sample = recurse(bset);
130 if (!sample || sample->size == 0)
131 isl_mat_free(T);
132 else
133 sample = isl_mat_vec_product(T, sample);
134 return sample;
137 /* Return a matrix containing the equalities of the tableau
138 * in constraint form. The tableau is assumed to have
139 * an associated bset that has been kept up-to-date.
141 static struct isl_mat *tab_equalities(struct isl_tab *tab)
143 int i, j;
144 int n_eq;
145 struct isl_mat *eq;
146 struct isl_basic_set *bset;
148 if (!tab)
149 return NULL;
151 bset = isl_tab_peek_bset(tab);
152 isl_assert(tab->mat->ctx, bset, return NULL);
154 n_eq = tab->n_var - tab->n_col + tab->n_dead;
155 if (tab->empty || n_eq == 0)
156 return isl_mat_alloc(tab->mat->ctx, 0, tab->n_var);
157 if (n_eq == tab->n_var)
158 return isl_mat_identity(tab->mat->ctx, tab->n_var);
160 eq = isl_mat_alloc(tab->mat->ctx, n_eq, tab->n_var);
161 if (!eq)
162 return NULL;
163 for (i = 0, j = 0; i < tab->n_con; ++i) {
164 if (tab->con[i].is_row)
165 continue;
166 if (tab->con[i].index >= 0 && tab->con[i].index >= tab->n_dead)
167 continue;
168 if (i < bset->n_eq)
169 isl_seq_cpy(eq->row[j], bset->eq[i] + 1, tab->n_var);
170 else
171 isl_seq_cpy(eq->row[j],
172 bset->ineq[i - bset->n_eq] + 1, tab->n_var);
173 ++j;
175 isl_assert(bset->ctx, j == n_eq, goto error);
176 return eq;
177 error:
178 isl_mat_free(eq);
179 return NULL;
182 /* Compute and return an initial basis for the bounded tableau "tab".
184 * If the tableau is either full-dimensional or zero-dimensional,
185 * the we simply return an identity matrix.
186 * Otherwise, we construct a basis whose first directions correspond
187 * to equalities.
189 static struct isl_mat *initial_basis(struct isl_tab *tab)
191 int n_eq;
192 struct isl_mat *eq;
193 struct isl_mat *Q;
195 tab->n_unbounded = 0;
196 tab->n_zero = n_eq = tab->n_var - tab->n_col + tab->n_dead;
197 if (tab->empty || n_eq == 0 || n_eq == tab->n_var)
198 return isl_mat_identity(tab->mat->ctx, 1 + tab->n_var);
200 eq = tab_equalities(tab);
201 eq = isl_mat_left_hermite(eq, 0, NULL, &Q);
202 if (!eq)
203 return NULL;
204 isl_mat_free(eq);
206 Q = isl_mat_lin_to_aff(Q);
207 return Q;
210 /* Compute the minimum of the current ("level") basis row over "tab"
211 * and store the result in position "level" of "min".
213 static enum isl_lp_result compute_min(isl_ctx *ctx, struct isl_tab *tab,
214 __isl_keep isl_vec *min, int level)
216 return isl_tab_min(tab, tab->basis->row[1 + level],
217 ctx->one, &min->el[level], NULL, 0);
220 /* Compute the maximum of the current ("level") basis row over "tab"
221 * and store the result in position "level" of "max".
223 static enum isl_lp_result compute_max(isl_ctx *ctx, struct isl_tab *tab,
224 __isl_keep isl_vec *max, int level)
226 enum isl_lp_result res;
227 unsigned dim = tab->n_var;
229 isl_seq_neg(tab->basis->row[1 + level] + 1,
230 tab->basis->row[1 + level] + 1, dim);
231 res = isl_tab_min(tab, tab->basis->row[1 + level],
232 ctx->one, &max->el[level], NULL, 0);
233 isl_seq_neg(tab->basis->row[1 + level] + 1,
234 tab->basis->row[1 + level] + 1, dim);
235 isl_int_neg(max->el[level], max->el[level]);
237 return res;
240 /* Perform a greedy search for an integer point in the set represented
241 * by "tab", given that the minimal rational value (rounded up to the
242 * nearest integer) at "level" is smaller than the maximal rational
243 * value (rounded down to the nearest integer).
245 * Return 1 if we have found an integer point (if tab->n_unbounded > 0
246 * then we may have only found integer values for the bounded dimensions
247 * and it is the responsibility of the caller to extend this solution
248 * to the unbounded dimensions).
249 * Return 0 if greedy search did not result in a solution.
250 * Return -1 if some error occurred.
252 * We assign a value half-way between the minimum and the maximum
253 * to the current dimension and check if the minimal value of the
254 * next dimension is still smaller than (or equal) to the maximal value.
255 * We continue this process until either
256 * - the minimal value (rounded up) is greater than the maximal value
257 * (rounded down). In this case, greedy search has failed.
258 * - we have exhausted all bounded dimensions, meaning that we have
259 * found a solution.
260 * - the sample value of the tableau is integral.
261 * - some error has occurred.
263 static int greedy_search(isl_ctx *ctx, struct isl_tab *tab,
264 __isl_keep isl_vec *min, __isl_keep isl_vec *max, int level)
266 struct isl_tab_undo *snap;
267 enum isl_lp_result res;
269 snap = isl_tab_snap(tab);
271 do {
272 isl_int_add(tab->basis->row[1 + level][0],
273 min->el[level], max->el[level]);
274 isl_int_fdiv_q_ui(tab->basis->row[1 + level][0],
275 tab->basis->row[1 + level][0], 2);
276 isl_int_neg(tab->basis->row[1 + level][0],
277 tab->basis->row[1 + level][0]);
278 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
279 return -1;
280 isl_int_set_si(tab->basis->row[1 + level][0], 0);
282 if (++level >= tab->n_var - tab->n_unbounded)
283 return 1;
284 if (isl_tab_sample_is_integer(tab))
285 return 1;
287 res = compute_min(ctx, tab, min, level);
288 if (res == isl_lp_error)
289 return -1;
290 if (res != isl_lp_ok)
291 isl_die(ctx, isl_error_internal,
292 "expecting bounded rational solution",
293 return -1);
294 res = compute_max(ctx, tab, max, level);
295 if (res == isl_lp_error)
296 return -1;
297 if (res != isl_lp_ok)
298 isl_die(ctx, isl_error_internal,
299 "expecting bounded rational solution",
300 return -1);
301 } while (isl_int_le(min->el[level], max->el[level]));
303 if (isl_tab_rollback(tab, snap) < 0)
304 return -1;
306 return 0;
309 /* Given a tableau representing a set, find and return
310 * an integer point in the set, if there is any.
312 * We perform a depth first search
313 * for an integer point, by scanning all possible values in the range
314 * attained by a basis vector, where an initial basis may have been set
315 * by the calling function. Otherwise an initial basis that exploits
316 * the equalities in the tableau is created.
317 * tab->n_zero is currently ignored and is clobbered by this function.
319 * The tableau is allowed to have unbounded direction, but then
320 * the calling function needs to set an initial basis, with the
321 * unbounded directions last and with tab->n_unbounded set
322 * to the number of unbounded directions.
323 * Furthermore, the calling functions needs to add shifted copies
324 * of all constraints involving unbounded directions to ensure
325 * that any feasible rational value in these directions can be rounded
326 * up to yield a feasible integer value.
327 * In particular, let B define the given basis x' = B x
328 * and let T be the inverse of B, i.e., X = T x'.
329 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
330 * or a T x' + c >= 0 in terms of the given basis. Assume that
331 * the bounded directions have an integer value, then we can safely
332 * round up the values for the unbounded directions if we make sure
333 * that x' not only satisfies the original constraint, but also
334 * the constraint "a T x' + c + s >= 0" with s the sum of all
335 * negative values in the last n_unbounded entries of "a T".
336 * The calling function therefore needs to add the constraint
337 * a x + c + s >= 0. The current function then scans the first
338 * directions for an integer value and once those have been found,
339 * it can compute "T ceil(B x)" to yield an integer point in the set.
340 * Note that during the search, the first rows of B may be changed
341 * by a basis reduction, but the last n_unbounded rows of B remain
342 * unaltered and are also not mixed into the first rows.
344 * The search is implemented iteratively. "level" identifies the current
345 * basis vector. "init" is true if we want the first value at the current
346 * level and false if we want the next value.
348 * At the start of each level, we first check if we can find a solution
349 * using greedy search. If not, we continue with the exhaustive search.
351 * The initial basis is the identity matrix. If the range in some direction
352 * contains more than one integer value, we perform basis reduction based
353 * on the value of ctx->opt->gbr
354 * - ISL_GBR_NEVER: never perform basis reduction
355 * - ISL_GBR_ONCE: only perform basis reduction the first
356 * time such a range is encountered
357 * - ISL_GBR_ALWAYS: always perform basis reduction when
358 * such a range is encountered
360 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
361 * reduction computation to return early. That is, as soon as it
362 * finds a reasonable first direction.
364 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
366 unsigned dim;
367 unsigned gbr;
368 struct isl_ctx *ctx;
369 struct isl_vec *sample;
370 struct isl_vec *min;
371 struct isl_vec *max;
372 enum isl_lp_result res;
373 int level;
374 int init;
375 int reduced;
376 struct isl_tab_undo **snap;
378 if (!tab)
379 return NULL;
380 if (tab->empty)
381 return isl_vec_alloc(tab->mat->ctx, 0);
383 if (!tab->basis)
384 tab->basis = initial_basis(tab);
385 if (!tab->basis)
386 return NULL;
387 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
388 return NULL);
389 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
390 return NULL);
392 ctx = tab->mat->ctx;
393 dim = tab->n_var;
394 gbr = ctx->opt->gbr;
396 if (tab->n_unbounded == tab->n_var) {
397 sample = isl_tab_get_sample_value(tab);
398 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
399 sample = isl_vec_ceil(sample);
400 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
401 sample);
402 return sample;
405 if (isl_tab_extend_cons(tab, dim + 1) < 0)
406 return NULL;
408 min = isl_vec_alloc(ctx, dim);
409 max = isl_vec_alloc(ctx, dim);
410 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
412 if (!min || !max || !snap)
413 goto error;
415 level = 0;
416 init = 1;
417 reduced = 0;
419 while (level >= 0) {
420 if (init) {
421 int choice;
423 res = compute_min(ctx, tab, min, level);
424 if (res == isl_lp_error)
425 goto error;
426 if (res != isl_lp_ok)
427 isl_die(ctx, isl_error_internal,
428 "expecting bounded rational solution",
429 goto error);
430 if (isl_tab_sample_is_integer(tab))
431 break;
432 res = compute_max(ctx, tab, max, 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 choice = isl_int_lt(min->el[level], max->el[level]);
442 if (choice) {
443 int g;
444 g = greedy_search(ctx, tab, min, max, level);
445 if (g < 0)
446 goto error;
447 if (g)
448 break;
450 if (!reduced && choice &&
451 ctx->opt->gbr != ISL_GBR_NEVER) {
452 unsigned gbr_only_first;
453 if (ctx->opt->gbr == ISL_GBR_ONCE)
454 ctx->opt->gbr = ISL_GBR_NEVER;
455 tab->n_zero = level;
456 gbr_only_first = ctx->opt->gbr_only_first;
457 ctx->opt->gbr_only_first =
458 ctx->opt->gbr == ISL_GBR_ALWAYS;
459 tab = isl_tab_compute_reduced_basis(tab);
460 ctx->opt->gbr_only_first = gbr_only_first;
461 if (!tab || !tab->basis)
462 goto error;
463 reduced = 1;
464 continue;
466 reduced = 0;
467 snap[level] = isl_tab_snap(tab);
468 } else
469 isl_int_add_ui(min->el[level], min->el[level], 1);
471 if (isl_int_gt(min->el[level], max->el[level])) {
472 level--;
473 init = 0;
474 if (level >= 0)
475 if (isl_tab_rollback(tab, snap[level]) < 0)
476 goto error;
477 continue;
479 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
480 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
481 goto error;
482 isl_int_set_si(tab->basis->row[1 + level][0], 0);
483 if (level + tab->n_unbounded < dim - 1) {
484 ++level;
485 init = 1;
486 continue;
488 break;
491 if (level >= 0) {
492 sample = isl_tab_get_sample_value(tab);
493 if (!sample)
494 goto error;
495 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
496 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
497 sample);
498 sample = isl_vec_ceil(sample);
499 sample = isl_mat_vec_inverse_product(
500 isl_mat_copy(tab->basis), sample);
502 } else
503 sample = isl_vec_alloc(ctx, 0);
505 ctx->opt->gbr = gbr;
506 isl_vec_free(min);
507 isl_vec_free(max);
508 free(snap);
509 return sample;
510 error:
511 ctx->opt->gbr = gbr;
512 isl_vec_free(min);
513 isl_vec_free(max);
514 free(snap);
515 return NULL;
518 static struct isl_vec *sample_bounded(struct isl_basic_set *bset);
520 /* Compute a sample point of the given basic set, based on the given,
521 * non-trivial factorization.
523 static __isl_give isl_vec *factored_sample(__isl_take isl_basic_set *bset,
524 __isl_take isl_factorizer *f)
526 int i, n;
527 isl_vec *sample = NULL;
528 isl_ctx *ctx;
529 unsigned nparam;
530 unsigned nvar;
532 ctx = isl_basic_set_get_ctx(bset);
533 if (!ctx)
534 goto error;
536 nparam = isl_basic_set_dim(bset, isl_dim_param);
537 nvar = isl_basic_set_dim(bset, isl_dim_set);
539 sample = isl_vec_alloc(ctx, 1 + isl_basic_set_total_dim(bset));
540 if (!sample)
541 goto error;
542 isl_int_set_si(sample->el[0], 1);
544 bset = isl_morph_basic_set(isl_morph_copy(f->morph), bset);
546 for (i = 0, n = 0; i < f->n_group; ++i) {
547 isl_basic_set *bset_i;
548 isl_vec *sample_i;
550 bset_i = isl_basic_set_copy(bset);
551 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
552 nparam + n + f->len[i], nvar - n - f->len[i]);
553 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
554 nparam, n);
555 bset_i = isl_basic_set_drop(bset_i, isl_dim_set,
556 n + f->len[i], nvar - n - f->len[i]);
557 bset_i = isl_basic_set_drop(bset_i, isl_dim_set, 0, n);
559 sample_i = sample_bounded(bset_i);
560 if (!sample_i)
561 goto error;
562 if (sample_i->size == 0) {
563 isl_basic_set_free(bset);
564 isl_factorizer_free(f);
565 isl_vec_free(sample);
566 return sample_i;
568 isl_seq_cpy(sample->el + 1 + nparam + n,
569 sample_i->el + 1, f->len[i]);
570 isl_vec_free(sample_i);
572 n += f->len[i];
575 f->morph = isl_morph_inverse(f->morph);
576 sample = isl_morph_vec(isl_morph_copy(f->morph), sample);
578 isl_basic_set_free(bset);
579 isl_factorizer_free(f);
580 return sample;
581 error:
582 isl_basic_set_free(bset);
583 isl_factorizer_free(f);
584 isl_vec_free(sample);
585 return NULL;
588 /* Given a basic set that is known to be bounded, find and return
589 * an integer point in the basic set, if there is any.
591 * After handling some trivial cases, we construct a tableau
592 * and then use isl_tab_sample to find a sample, passing it
593 * the identity matrix as initial basis.
595 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
597 unsigned dim;
598 struct isl_vec *sample;
599 struct isl_tab *tab = NULL;
600 isl_factorizer *f;
602 if (!bset)
603 return NULL;
605 if (isl_basic_set_plain_is_empty(bset))
606 return empty_sample(bset);
608 dim = isl_basic_set_total_dim(bset);
609 if (dim == 0)
610 return zero_sample(bset);
611 if (dim == 1)
612 return interval_sample(bset);
613 if (bset->n_eq > 0)
614 return sample_eq(bset, sample_bounded);
616 f = isl_basic_set_factorizer(bset);
617 if (!f)
618 goto error;
619 if (f->n_group != 0)
620 return factored_sample(bset, f);
621 isl_factorizer_free(f);
623 tab = isl_tab_from_basic_set(bset, 1);
624 if (tab && tab->empty) {
625 isl_tab_free(tab);
626 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
627 sample = isl_vec_alloc(isl_basic_set_get_ctx(bset), 0);
628 isl_basic_set_free(bset);
629 return sample;
632 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
633 if (isl_tab_detect_implicit_equalities(tab) < 0)
634 goto error;
636 sample = isl_tab_sample(tab);
637 if (!sample)
638 goto error;
640 if (sample->size > 0) {
641 isl_vec_free(bset->sample);
642 bset->sample = isl_vec_copy(sample);
645 isl_basic_set_free(bset);
646 isl_tab_free(tab);
647 return sample;
648 error:
649 isl_basic_set_free(bset);
650 isl_tab_free(tab);
651 return NULL;
654 /* Given a basic set "bset" and a value "sample" for the first coordinates
655 * of bset, plug in these values and drop the corresponding coordinates.
657 * We do this by computing the preimage of the transformation
659 * [ 1 0 ]
660 * x = [ s 0 ] x'
661 * [ 0 I ]
663 * where [1 s] is the sample value and I is the identity matrix of the
664 * appropriate dimension.
666 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
667 struct isl_vec *sample)
669 int i;
670 unsigned total;
671 struct isl_mat *T;
673 if (!bset || !sample)
674 goto error;
676 total = isl_basic_set_total_dim(bset);
677 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
678 if (!T)
679 goto error;
681 for (i = 0; i < sample->size; ++i) {
682 isl_int_set(T->row[i][0], sample->el[i]);
683 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
685 for (i = 0; i < T->n_col - 1; ++i) {
686 isl_seq_clr(T->row[sample->size + i], T->n_col);
687 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
689 isl_vec_free(sample);
691 bset = isl_basic_set_preimage(bset, T);
692 return bset;
693 error:
694 isl_basic_set_free(bset);
695 isl_vec_free(sample);
696 return NULL;
699 /* Given a basic set "bset", return any (possibly non-integer) point
700 * in the basic set.
702 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
704 struct isl_tab *tab;
705 struct isl_vec *sample;
707 if (!bset)
708 return NULL;
710 tab = isl_tab_from_basic_set(bset, 0);
711 sample = isl_tab_get_sample_value(tab);
712 isl_tab_free(tab);
714 isl_basic_set_free(bset);
716 return sample;
719 /* Given a linear cone "cone" and a rational point "vec",
720 * construct a polyhedron with shifted copies of the constraints in "cone",
721 * i.e., a polyhedron with "cone" as its recession cone, such that each
722 * point x in this polyhedron is such that the unit box positioned at x
723 * lies entirely inside the affine cone 'vec + cone'.
724 * Any rational point in this polyhedron may therefore be rounded up
725 * to yield an integer point that lies inside said affine cone.
727 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
728 * point "vec" by v/d.
729 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
730 * by <a_i, x> - b/d >= 0.
731 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
732 * We prefer this polyhedron over the actual affine cone because it doesn't
733 * require a scaling of the constraints.
734 * If each of the vertices of the unit cube positioned at x lies inside
735 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
736 * We therefore impose that x' = x + \sum e_i, for any selection of unit
737 * vectors lies inside the polyhedron, i.e.,
739 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
741 * The most stringent of these constraints is the one that selects
742 * all negative a_i, so the polyhedron we are looking for has constraints
744 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
746 * Note that if cone were known to have only non-negative rays
747 * (which can be accomplished by a unimodular transformation),
748 * then we would only have to check the points x' = x + e_i
749 * and we only have to add the smallest negative a_i (if any)
750 * instead of the sum of all negative a_i.
752 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
753 struct isl_vec *vec)
755 int i, j, k;
756 unsigned total;
758 struct isl_basic_set *shift = NULL;
760 if (!cone || !vec)
761 goto error;
763 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
765 total = isl_basic_set_total_dim(cone);
767 shift = isl_basic_set_alloc_space(isl_basic_set_get_space(cone),
768 0, 0, cone->n_ineq);
770 for (i = 0; i < cone->n_ineq; ++i) {
771 k = isl_basic_set_alloc_inequality(shift);
772 if (k < 0)
773 goto error;
774 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
775 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
776 &shift->ineq[k][0]);
777 isl_int_cdiv_q(shift->ineq[k][0],
778 shift->ineq[k][0], vec->el[0]);
779 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
780 for (j = 0; j < total; ++j) {
781 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
782 continue;
783 isl_int_add(shift->ineq[k][0],
784 shift->ineq[k][0], shift->ineq[k][1 + j]);
788 isl_basic_set_free(cone);
789 isl_vec_free(vec);
791 return isl_basic_set_finalize(shift);
792 error:
793 isl_basic_set_free(shift);
794 isl_basic_set_free(cone);
795 isl_vec_free(vec);
796 return NULL;
799 /* Given a rational point vec in a (transformed) basic set,
800 * such that cone is the recession cone of the original basic set,
801 * "round up" the rational point to an integer point.
803 * We first check if the rational point just happens to be integer.
804 * If not, we transform the cone in the same way as the basic set,
805 * pick a point x in this cone shifted to the rational point such that
806 * the whole unit cube at x is also inside this affine cone.
807 * Then we simply round up the coordinates of x and return the
808 * resulting integer point.
810 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
811 struct isl_basic_set *cone, struct isl_mat *U)
813 unsigned total;
815 if (!vec || !cone || !U)
816 goto error;
818 isl_assert(vec->ctx, vec->size != 0, goto error);
819 if (isl_int_is_one(vec->el[0])) {
820 isl_mat_free(U);
821 isl_basic_set_free(cone);
822 return vec;
825 total = isl_basic_set_total_dim(cone);
826 cone = isl_basic_set_preimage(cone, U);
827 cone = isl_basic_set_remove_dims(cone, isl_dim_set,
828 0, total - (vec->size - 1));
830 cone = shift_cone(cone, vec);
832 vec = rational_sample(cone);
833 vec = isl_vec_ceil(vec);
834 return vec;
835 error:
836 isl_mat_free(U);
837 isl_vec_free(vec);
838 isl_basic_set_free(cone);
839 return NULL;
842 /* Concatenate two integer vectors, i.e., two vectors with denominator
843 * (stored in element 0) equal to 1.
845 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
847 struct isl_vec *vec;
849 if (!vec1 || !vec2)
850 goto error;
851 isl_assert(vec1->ctx, vec1->size > 0, goto error);
852 isl_assert(vec2->ctx, vec2->size > 0, goto error);
853 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
854 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
856 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
857 if (!vec)
858 goto error;
860 isl_seq_cpy(vec->el, vec1->el, vec1->size);
861 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
863 isl_vec_free(vec1);
864 isl_vec_free(vec2);
866 return vec;
867 error:
868 isl_vec_free(vec1);
869 isl_vec_free(vec2);
870 return NULL;
873 /* Give a basic set "bset" with recession cone "cone", compute and
874 * return an integer point in bset, if any.
876 * If the recession cone is full-dimensional, then we know that
877 * bset contains an infinite number of integer points and it is
878 * fairly easy to pick one of them.
879 * If the recession cone is not full-dimensional, then we first
880 * transform bset such that the bounded directions appear as
881 * the first dimensions of the transformed basic set.
882 * We do this by using a unimodular transformation that transforms
883 * the equalities in the recession cone to equalities on the first
884 * dimensions.
886 * The transformed set is then projected onto its bounded dimensions.
887 * Note that to compute this projection, we can simply drop all constraints
888 * involving any of the unbounded dimensions since these constraints
889 * cannot be combined to produce a constraint on the bounded dimensions.
890 * To see this, assume that there is such a combination of constraints
891 * that produces a constraint on the bounded dimensions. This means
892 * that some combination of the unbounded dimensions has both an upper
893 * bound and a lower bound in terms of the bounded dimensions, but then
894 * this combination would be a bounded direction too and would have been
895 * transformed into a bounded dimensions.
897 * We then compute a sample value in the bounded dimensions.
898 * If no such value can be found, then the original set did not contain
899 * any integer points and we are done.
900 * Otherwise, we plug in the value we found in the bounded dimensions,
901 * project out these bounded dimensions and end up with a set with
902 * a full-dimensional recession cone.
903 * A sample point in this set is computed by "rounding up" any
904 * rational point in the set.
906 * The sample points in the bounded and unbounded dimensions are
907 * then combined into a single sample point and transformed back
908 * to the original space.
910 __isl_give isl_vec *isl_basic_set_sample_with_cone(
911 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
913 unsigned total;
914 unsigned cone_dim;
915 struct isl_mat *M, *U;
916 struct isl_vec *sample;
917 struct isl_vec *cone_sample;
918 struct isl_ctx *ctx;
919 struct isl_basic_set *bounded;
921 if (!bset || !cone)
922 goto error;
924 ctx = isl_basic_set_get_ctx(bset);
925 total = isl_basic_set_total_dim(cone);
926 cone_dim = total - cone->n_eq;
928 M = isl_mat_sub_alloc6(ctx, cone->eq, 0, cone->n_eq, 1, total);
929 M = isl_mat_left_hermite(M, 0, &U, NULL);
930 if (!M)
931 goto error;
932 isl_mat_free(M);
934 U = isl_mat_lin_to_aff(U);
935 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
937 bounded = isl_basic_set_copy(bset);
938 bounded = isl_basic_set_drop_constraints_involving(bounded,
939 total - cone_dim, cone_dim);
940 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
941 sample = sample_bounded(bounded);
942 if (!sample || sample->size == 0) {
943 isl_basic_set_free(bset);
944 isl_basic_set_free(cone);
945 isl_mat_free(U);
946 return sample;
948 bset = plug_in(bset, isl_vec_copy(sample));
949 cone_sample = rational_sample(bset);
950 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
951 sample = vec_concat(sample, cone_sample);
952 sample = isl_mat_vec_product(U, sample);
953 return sample;
954 error:
955 isl_basic_set_free(cone);
956 isl_basic_set_free(bset);
957 return NULL;
960 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
962 int i;
964 isl_int_set_si(*s, 0);
966 for (i = 0; i < v->size; ++i)
967 if (isl_int_is_neg(v->el[i]))
968 isl_int_add(*s, *s, v->el[i]);
971 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
972 * to the recession cone and the inverse of a new basis U = inv(B),
973 * with the unbounded directions in B last,
974 * add constraints to "tab" that ensure any rational value
975 * in the unbounded directions can be rounded up to an integer value.
977 * The new basis is given by x' = B x, i.e., x = U x'.
978 * For any rational value of the last tab->n_unbounded coordinates
979 * in the update tableau, the value that is obtained by rounding
980 * up this value should be contained in the original tableau.
981 * For any constraint "a x + c >= 0", we therefore need to add
982 * a constraint "a x + c + s >= 0", with s the sum of all negative
983 * entries in the last elements of "a U".
985 * Since we are not interested in the first entries of any of the "a U",
986 * we first drop the columns of U that correpond to bounded directions.
988 static int tab_shift_cone(struct isl_tab *tab,
989 struct isl_tab *tab_cone, struct isl_mat *U)
991 int i;
992 isl_int v;
993 struct isl_basic_set *bset = NULL;
995 if (tab && tab->n_unbounded == 0) {
996 isl_mat_free(U);
997 return 0;
999 isl_int_init(v);
1000 if (!tab || !tab_cone || !U)
1001 goto error;
1002 bset = isl_tab_peek_bset(tab_cone);
1003 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
1004 for (i = 0; i < bset->n_ineq; ++i) {
1005 int ok;
1006 struct isl_vec *row = NULL;
1007 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
1008 continue;
1009 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
1010 if (!row)
1011 goto error;
1012 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
1013 row = isl_vec_mat_product(row, isl_mat_copy(U));
1014 if (!row)
1015 goto error;
1016 vec_sum_of_neg(row, &v);
1017 isl_vec_free(row);
1018 if (isl_int_is_zero(v))
1019 continue;
1020 if (isl_tab_extend_cons(tab, 1) < 0)
1021 goto error;
1022 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
1023 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1024 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1025 if (!ok)
1026 goto error;
1029 isl_mat_free(U);
1030 isl_int_clear(v);
1031 return 0;
1032 error:
1033 isl_mat_free(U);
1034 isl_int_clear(v);
1035 return -1;
1038 /* Compute and return an initial basis for the possibly
1039 * unbounded tableau "tab". "tab_cone" is a tableau
1040 * for the corresponding recession cone.
1041 * Additionally, add constraints to "tab" that ensure
1042 * that any rational value for the unbounded directions
1043 * can be rounded up to an integer value.
1045 * If the tableau is bounded, i.e., if the recession cone
1046 * is zero-dimensional, then we just use inital_basis.
1047 * Otherwise, we construct a basis whose first directions
1048 * correspond to equalities, followed by bounded directions,
1049 * i.e., equalities in the recession cone.
1050 * The remaining directions are then unbounded.
1052 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1053 struct isl_tab *tab_cone)
1055 struct isl_mat *eq;
1056 struct isl_mat *cone_eq;
1057 struct isl_mat *U, *Q;
1059 if (!tab || !tab_cone)
1060 return -1;
1062 if (tab_cone->n_col == tab_cone->n_dead) {
1063 tab->basis = initial_basis(tab);
1064 return tab->basis ? 0 : -1;
1067 eq = tab_equalities(tab);
1068 if (!eq)
1069 return -1;
1070 tab->n_zero = eq->n_row;
1071 cone_eq = tab_equalities(tab_cone);
1072 eq = isl_mat_concat(eq, cone_eq);
1073 if (!eq)
1074 return -1;
1075 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1076 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1077 if (!eq)
1078 return -1;
1079 isl_mat_free(eq);
1080 tab->basis = isl_mat_lin_to_aff(Q);
1081 if (tab_shift_cone(tab, tab_cone, U) < 0)
1082 return -1;
1083 if (!tab->basis)
1084 return -1;
1085 return 0;
1088 /* Compute and return a sample point in bset using generalized basis
1089 * reduction. We first check if the input set has a non-trivial
1090 * recession cone. If so, we perform some extra preprocessing in
1091 * sample_with_cone. Otherwise, we directly perform generalized basis
1092 * reduction.
1094 static struct isl_vec *gbr_sample(struct isl_basic_set *bset)
1096 unsigned dim;
1097 struct isl_basic_set *cone;
1099 dim = isl_basic_set_total_dim(bset);
1101 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1102 if (!cone)
1103 goto error;
1105 if (cone->n_eq < dim)
1106 return isl_basic_set_sample_with_cone(bset, cone);
1108 isl_basic_set_free(cone);
1109 return sample_bounded(bset);
1110 error:
1111 isl_basic_set_free(bset);
1112 return NULL;
1115 static struct isl_vec *basic_set_sample(struct isl_basic_set *bset, int bounded)
1117 struct isl_ctx *ctx;
1118 unsigned dim;
1119 if (!bset)
1120 return NULL;
1122 ctx = bset->ctx;
1123 if (isl_basic_set_plain_is_empty(bset))
1124 return empty_sample(bset);
1126 dim = isl_basic_set_n_dim(bset);
1127 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1128 isl_assert(ctx, bset->n_div == 0, goto error);
1130 if (bset->sample && bset->sample->size == 1 + dim) {
1131 int contains = isl_basic_set_contains(bset, bset->sample);
1132 if (contains < 0)
1133 goto error;
1134 if (contains) {
1135 struct isl_vec *sample = isl_vec_copy(bset->sample);
1136 isl_basic_set_free(bset);
1137 return sample;
1140 isl_vec_free(bset->sample);
1141 bset->sample = NULL;
1143 if (bset->n_eq > 0)
1144 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1145 : isl_basic_set_sample_vec);
1146 if (dim == 0)
1147 return zero_sample(bset);
1148 if (dim == 1)
1149 return interval_sample(bset);
1151 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1152 error:
1153 isl_basic_set_free(bset);
1154 return NULL;
1157 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1159 return basic_set_sample(bset, 0);
1162 /* Compute an integer sample in "bset", where the caller guarantees
1163 * that "bset" is bounded.
1165 struct isl_vec *isl_basic_set_sample_bounded(struct isl_basic_set *bset)
1167 return basic_set_sample(bset, 1);
1170 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1172 int i;
1173 int k;
1174 struct isl_basic_set *bset = NULL;
1175 struct isl_ctx *ctx;
1176 unsigned dim;
1178 if (!vec)
1179 return NULL;
1180 ctx = vec->ctx;
1181 isl_assert(ctx, vec->size != 0, goto error);
1183 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1184 if (!bset)
1185 goto error;
1186 dim = isl_basic_set_n_dim(bset);
1187 for (i = dim - 1; i >= 0; --i) {
1188 k = isl_basic_set_alloc_equality(bset);
1189 if (k < 0)
1190 goto error;
1191 isl_seq_clr(bset->eq[k], 1 + dim);
1192 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1193 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1195 bset->sample = vec;
1197 return bset;
1198 error:
1199 isl_basic_set_free(bset);
1200 isl_vec_free(vec);
1201 return NULL;
1204 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1206 struct isl_basic_set *bset;
1207 struct isl_vec *sample_vec;
1209 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1210 sample_vec = isl_basic_set_sample_vec(bset);
1211 if (!sample_vec)
1212 goto error;
1213 if (sample_vec->size == 0) {
1214 isl_vec_free(sample_vec);
1215 return isl_basic_map_set_to_empty(bmap);
1217 bset = isl_basic_set_from_vec(sample_vec);
1218 return isl_basic_map_overlying_set(bset, bmap);
1219 error:
1220 isl_basic_map_free(bmap);
1221 return NULL;
1224 __isl_give isl_basic_set *isl_basic_set_sample(__isl_take isl_basic_set *bset)
1226 return isl_basic_map_sample(bset);
1229 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1231 int i;
1232 isl_basic_map *sample = NULL;
1234 if (!map)
1235 goto error;
1237 for (i = 0; i < map->n; ++i) {
1238 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1239 if (!sample)
1240 goto error;
1241 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1242 break;
1243 isl_basic_map_free(sample);
1245 if (i == map->n)
1246 sample = isl_basic_map_empty(isl_map_get_space(map));
1247 isl_map_free(map);
1248 return sample;
1249 error:
1250 isl_map_free(map);
1251 return NULL;
1254 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1256 return (isl_basic_set *) isl_map_sample((isl_map *)set);
1259 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1261 isl_vec *vec;
1262 isl_space *dim;
1264 dim = isl_basic_set_get_space(bset);
1265 bset = isl_basic_set_underlying_set(bset);
1266 vec = isl_basic_set_sample_vec(bset);
1268 return isl_point_alloc(dim, vec);
1271 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1273 int i;
1274 isl_point *pnt;
1276 if (!set)
1277 return NULL;
1279 for (i = 0; i < set->n; ++i) {
1280 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1281 if (!pnt)
1282 goto error;
1283 if (!isl_point_is_void(pnt))
1284 break;
1285 isl_point_free(pnt);
1287 if (i == set->n)
1288 pnt = isl_point_void(isl_set_get_space(set));
1290 isl_set_free(set);
1291 return pnt;
1292 error:
1293 isl_set_free(set);
1294 return NULL;