isl_tab_pip.c: fix typos in comments
[isl.git] / isl_sample.c
blob5098ce60bdabdce7a4bdba1bf7f75dd57fe21dc5
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 * This function assumes that at least one more row and at least
214 * one more element in the constraint array are available in the tableau.
216 static enum isl_lp_result compute_min(isl_ctx *ctx, struct isl_tab *tab,
217 __isl_keep isl_vec *min, int level)
219 return isl_tab_min(tab, tab->basis->row[1 + level],
220 ctx->one, &min->el[level], NULL, 0);
223 /* Compute the maximum of the current ("level") basis row over "tab"
224 * and store the result in position "level" of "max".
226 * This function assumes that at least one more row and at least
227 * one more element in the constraint array are available in the tableau.
229 static enum isl_lp_result compute_max(isl_ctx *ctx, struct isl_tab *tab,
230 __isl_keep isl_vec *max, int level)
232 enum isl_lp_result res;
233 unsigned dim = tab->n_var;
235 isl_seq_neg(tab->basis->row[1 + level] + 1,
236 tab->basis->row[1 + level] + 1, dim);
237 res = isl_tab_min(tab, tab->basis->row[1 + level],
238 ctx->one, &max->el[level], NULL, 0);
239 isl_seq_neg(tab->basis->row[1 + level] + 1,
240 tab->basis->row[1 + level] + 1, dim);
241 isl_int_neg(max->el[level], max->el[level]);
243 return res;
246 /* Perform a greedy search for an integer point in the set represented
247 * by "tab", given that the minimal rational value (rounded up to the
248 * nearest integer) at "level" is smaller than the maximal rational
249 * value (rounded down to the nearest integer).
251 * Return 1 if we have found an integer point (if tab->n_unbounded > 0
252 * then we may have only found integer values for the bounded dimensions
253 * and it is the responsibility of the caller to extend this solution
254 * to the unbounded dimensions).
255 * Return 0 if greedy search did not result in a solution.
256 * Return -1 if some error occurred.
258 * We assign a value half-way between the minimum and the maximum
259 * to the current dimension and check if the minimal value of the
260 * next dimension is still smaller than (or equal) to the maximal value.
261 * We continue this process until either
262 * - the minimal value (rounded up) is greater than the maximal value
263 * (rounded down). In this case, greedy search has failed.
264 * - we have exhausted all bounded dimensions, meaning that we have
265 * found a solution.
266 * - the sample value of the tableau is integral.
267 * - some error has occurred.
269 static int greedy_search(isl_ctx *ctx, struct isl_tab *tab,
270 __isl_keep isl_vec *min, __isl_keep isl_vec *max, int level)
272 struct isl_tab_undo *snap;
273 enum isl_lp_result res;
275 snap = isl_tab_snap(tab);
277 do {
278 isl_int_add(tab->basis->row[1 + level][0],
279 min->el[level], max->el[level]);
280 isl_int_fdiv_q_ui(tab->basis->row[1 + level][0],
281 tab->basis->row[1 + level][0], 2);
282 isl_int_neg(tab->basis->row[1 + level][0],
283 tab->basis->row[1 + level][0]);
284 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
285 return -1;
286 isl_int_set_si(tab->basis->row[1 + level][0], 0);
288 if (++level >= tab->n_var - tab->n_unbounded)
289 return 1;
290 if (isl_tab_sample_is_integer(tab))
291 return 1;
293 res = compute_min(ctx, tab, min, level);
294 if (res == isl_lp_error)
295 return -1;
296 if (res != isl_lp_ok)
297 isl_die(ctx, isl_error_internal,
298 "expecting bounded rational solution",
299 return -1);
300 res = compute_max(ctx, tab, max, level);
301 if (res == isl_lp_error)
302 return -1;
303 if (res != isl_lp_ok)
304 isl_die(ctx, isl_error_internal,
305 "expecting bounded rational solution",
306 return -1);
307 } while (isl_int_le(min->el[level], max->el[level]));
309 if (isl_tab_rollback(tab, snap) < 0)
310 return -1;
312 return 0;
315 /* Given a tableau representing a set, find and return
316 * an integer point in the set, if there is any.
318 * We perform a depth first search
319 * for an integer point, by scanning all possible values in the range
320 * attained by a basis vector, where an initial basis may have been set
321 * by the calling function. Otherwise an initial basis that exploits
322 * the equalities in the tableau is created.
323 * tab->n_zero is currently ignored and is clobbered by this function.
325 * The tableau is allowed to have unbounded direction, but then
326 * the calling function needs to set an initial basis, with the
327 * unbounded directions last and with tab->n_unbounded set
328 * to the number of unbounded directions.
329 * Furthermore, the calling functions needs to add shifted copies
330 * of all constraints involving unbounded directions to ensure
331 * that any feasible rational value in these directions can be rounded
332 * up to yield a feasible integer value.
333 * In particular, let B define the given basis x' = B x
334 * and let T be the inverse of B, i.e., X = T x'.
335 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
336 * or a T x' + c >= 0 in terms of the given basis. Assume that
337 * the bounded directions have an integer value, then we can safely
338 * round up the values for the unbounded directions if we make sure
339 * that x' not only satisfies the original constraint, but also
340 * the constraint "a T x' + c + s >= 0" with s the sum of all
341 * negative values in the last n_unbounded entries of "a T".
342 * The calling function therefore needs to add the constraint
343 * a x + c + s >= 0. The current function then scans the first
344 * directions for an integer value and once those have been found,
345 * it can compute "T ceil(B x)" to yield an integer point in the set.
346 * Note that during the search, the first rows of B may be changed
347 * by a basis reduction, but the last n_unbounded rows of B remain
348 * unaltered and are also not mixed into the first rows.
350 * The search is implemented iteratively. "level" identifies the current
351 * basis vector. "init" is true if we want the first value at the current
352 * level and false if we want the next value.
354 * At the start of each level, we first check if we can find a solution
355 * using greedy search. If not, we continue with the exhaustive search.
357 * The initial basis is the identity matrix. If the range in some direction
358 * contains more than one integer value, we perform basis reduction based
359 * on the value of ctx->opt->gbr
360 * - ISL_GBR_NEVER: never perform basis reduction
361 * - ISL_GBR_ONCE: only perform basis reduction the first
362 * time such a range is encountered
363 * - ISL_GBR_ALWAYS: always perform basis reduction when
364 * such a range is encountered
366 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
367 * reduction computation to return early. That is, as soon as it
368 * finds a reasonable first direction.
370 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
372 unsigned dim;
373 unsigned gbr;
374 struct isl_ctx *ctx;
375 struct isl_vec *sample;
376 struct isl_vec *min;
377 struct isl_vec *max;
378 enum isl_lp_result res;
379 int level;
380 int init;
381 int reduced;
382 struct isl_tab_undo **snap;
384 if (!tab)
385 return NULL;
386 if (tab->empty)
387 return isl_vec_alloc(tab->mat->ctx, 0);
389 if (!tab->basis)
390 tab->basis = initial_basis(tab);
391 if (!tab->basis)
392 return NULL;
393 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
394 return NULL);
395 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
396 return NULL);
398 ctx = tab->mat->ctx;
399 dim = tab->n_var;
400 gbr = ctx->opt->gbr;
402 if (tab->n_unbounded == tab->n_var) {
403 sample = isl_tab_get_sample_value(tab);
404 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
405 sample = isl_vec_ceil(sample);
406 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
407 sample);
408 return sample;
411 if (isl_tab_extend_cons(tab, dim + 1) < 0)
412 return NULL;
414 min = isl_vec_alloc(ctx, dim);
415 max = isl_vec_alloc(ctx, dim);
416 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
418 if (!min || !max || !snap)
419 goto error;
421 level = 0;
422 init = 1;
423 reduced = 0;
425 while (level >= 0) {
426 if (init) {
427 int choice;
429 res = compute_min(ctx, tab, min, level);
430 if (res == isl_lp_error)
431 goto error;
432 if (res != isl_lp_ok)
433 isl_die(ctx, isl_error_internal,
434 "expecting bounded rational solution",
435 goto error);
436 if (isl_tab_sample_is_integer(tab))
437 break;
438 res = compute_max(ctx, tab, max, level);
439 if (res == isl_lp_error)
440 goto error;
441 if (res != isl_lp_ok)
442 isl_die(ctx, isl_error_internal,
443 "expecting bounded rational solution",
444 goto error);
445 if (isl_tab_sample_is_integer(tab))
446 break;
447 choice = isl_int_lt(min->el[level], max->el[level]);
448 if (choice) {
449 int g;
450 g = greedy_search(ctx, tab, min, max, level);
451 if (g < 0)
452 goto error;
453 if (g)
454 break;
456 if (!reduced && choice &&
457 ctx->opt->gbr != ISL_GBR_NEVER) {
458 unsigned gbr_only_first;
459 if (ctx->opt->gbr == ISL_GBR_ONCE)
460 ctx->opt->gbr = ISL_GBR_NEVER;
461 tab->n_zero = level;
462 gbr_only_first = ctx->opt->gbr_only_first;
463 ctx->opt->gbr_only_first =
464 ctx->opt->gbr == ISL_GBR_ALWAYS;
465 tab = isl_tab_compute_reduced_basis(tab);
466 ctx->opt->gbr_only_first = gbr_only_first;
467 if (!tab || !tab->basis)
468 goto error;
469 reduced = 1;
470 continue;
472 reduced = 0;
473 snap[level] = isl_tab_snap(tab);
474 } else
475 isl_int_add_ui(min->el[level], min->el[level], 1);
477 if (isl_int_gt(min->el[level], max->el[level])) {
478 level--;
479 init = 0;
480 if (level >= 0)
481 if (isl_tab_rollback(tab, snap[level]) < 0)
482 goto error;
483 continue;
485 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
486 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
487 goto error;
488 isl_int_set_si(tab->basis->row[1 + level][0], 0);
489 if (level + tab->n_unbounded < dim - 1) {
490 ++level;
491 init = 1;
492 continue;
494 break;
497 if (level >= 0) {
498 sample = isl_tab_get_sample_value(tab);
499 if (!sample)
500 goto error;
501 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
502 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
503 sample);
504 sample = isl_vec_ceil(sample);
505 sample = isl_mat_vec_inverse_product(
506 isl_mat_copy(tab->basis), sample);
508 } else
509 sample = isl_vec_alloc(ctx, 0);
511 ctx->opt->gbr = gbr;
512 isl_vec_free(min);
513 isl_vec_free(max);
514 free(snap);
515 return sample;
516 error:
517 ctx->opt->gbr = gbr;
518 isl_vec_free(min);
519 isl_vec_free(max);
520 free(snap);
521 return NULL;
524 static struct isl_vec *sample_bounded(struct isl_basic_set *bset);
526 /* Compute a sample point of the given basic set, based on the given,
527 * non-trivial factorization.
529 static __isl_give isl_vec *factored_sample(__isl_take isl_basic_set *bset,
530 __isl_take isl_factorizer *f)
532 int i, n;
533 isl_vec *sample = NULL;
534 isl_ctx *ctx;
535 unsigned nparam;
536 unsigned nvar;
538 ctx = isl_basic_set_get_ctx(bset);
539 if (!ctx)
540 goto error;
542 nparam = isl_basic_set_dim(bset, isl_dim_param);
543 nvar = isl_basic_set_dim(bset, isl_dim_set);
545 sample = isl_vec_alloc(ctx, 1 + isl_basic_set_total_dim(bset));
546 if (!sample)
547 goto error;
548 isl_int_set_si(sample->el[0], 1);
550 bset = isl_morph_basic_set(isl_morph_copy(f->morph), bset);
552 for (i = 0, n = 0; i < f->n_group; ++i) {
553 isl_basic_set *bset_i;
554 isl_vec *sample_i;
556 bset_i = isl_basic_set_copy(bset);
557 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
558 nparam + n + f->len[i], nvar - n - f->len[i]);
559 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
560 nparam, n);
561 bset_i = isl_basic_set_drop(bset_i, isl_dim_set,
562 n + f->len[i], nvar - n - f->len[i]);
563 bset_i = isl_basic_set_drop(bset_i, isl_dim_set, 0, n);
565 sample_i = sample_bounded(bset_i);
566 if (!sample_i)
567 goto error;
568 if (sample_i->size == 0) {
569 isl_basic_set_free(bset);
570 isl_factorizer_free(f);
571 isl_vec_free(sample);
572 return sample_i;
574 isl_seq_cpy(sample->el + 1 + nparam + n,
575 sample_i->el + 1, f->len[i]);
576 isl_vec_free(sample_i);
578 n += f->len[i];
581 f->morph = isl_morph_inverse(f->morph);
582 sample = isl_morph_vec(isl_morph_copy(f->morph), sample);
584 isl_basic_set_free(bset);
585 isl_factorizer_free(f);
586 return sample;
587 error:
588 isl_basic_set_free(bset);
589 isl_factorizer_free(f);
590 isl_vec_free(sample);
591 return NULL;
594 /* Given a basic set that is known to be bounded, find and return
595 * an integer point in the basic set, if there is any.
597 * After handling some trivial cases, we construct a tableau
598 * and then use isl_tab_sample to find a sample, passing it
599 * the identity matrix as initial basis.
601 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
603 unsigned dim;
604 struct isl_vec *sample;
605 struct isl_tab *tab = NULL;
606 isl_factorizer *f;
608 if (!bset)
609 return NULL;
611 if (isl_basic_set_plain_is_empty(bset))
612 return empty_sample(bset);
614 dim = isl_basic_set_total_dim(bset);
615 if (dim == 0)
616 return zero_sample(bset);
617 if (dim == 1)
618 return interval_sample(bset);
619 if (bset->n_eq > 0)
620 return sample_eq(bset, sample_bounded);
622 f = isl_basic_set_factorizer(bset);
623 if (!f)
624 goto error;
625 if (f->n_group != 0)
626 return factored_sample(bset, f);
627 isl_factorizer_free(f);
629 tab = isl_tab_from_basic_set(bset, 1);
630 if (tab && tab->empty) {
631 isl_tab_free(tab);
632 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
633 sample = isl_vec_alloc(isl_basic_set_get_ctx(bset), 0);
634 isl_basic_set_free(bset);
635 return sample;
638 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
639 if (isl_tab_detect_implicit_equalities(tab) < 0)
640 goto error;
642 sample = isl_tab_sample(tab);
643 if (!sample)
644 goto error;
646 if (sample->size > 0) {
647 isl_vec_free(bset->sample);
648 bset->sample = isl_vec_copy(sample);
651 isl_basic_set_free(bset);
652 isl_tab_free(tab);
653 return sample;
654 error:
655 isl_basic_set_free(bset);
656 isl_tab_free(tab);
657 return NULL;
660 /* Given a basic set "bset" and a value "sample" for the first coordinates
661 * of bset, plug in these values and drop the corresponding coordinates.
663 * We do this by computing the preimage of the transformation
665 * [ 1 0 ]
666 * x = [ s 0 ] x'
667 * [ 0 I ]
669 * where [1 s] is the sample value and I is the identity matrix of the
670 * appropriate dimension.
672 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
673 struct isl_vec *sample)
675 int i;
676 unsigned total;
677 struct isl_mat *T;
679 if (!bset || !sample)
680 goto error;
682 total = isl_basic_set_total_dim(bset);
683 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
684 if (!T)
685 goto error;
687 for (i = 0; i < sample->size; ++i) {
688 isl_int_set(T->row[i][0], sample->el[i]);
689 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
691 for (i = 0; i < T->n_col - 1; ++i) {
692 isl_seq_clr(T->row[sample->size + i], T->n_col);
693 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
695 isl_vec_free(sample);
697 bset = isl_basic_set_preimage(bset, T);
698 return bset;
699 error:
700 isl_basic_set_free(bset);
701 isl_vec_free(sample);
702 return NULL;
705 /* Given a basic set "bset", return any (possibly non-integer) point
706 * in the basic set.
708 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
710 struct isl_tab *tab;
711 struct isl_vec *sample;
713 if (!bset)
714 return NULL;
716 tab = isl_tab_from_basic_set(bset, 0);
717 sample = isl_tab_get_sample_value(tab);
718 isl_tab_free(tab);
720 isl_basic_set_free(bset);
722 return sample;
725 /* Given a linear cone "cone" and a rational point "vec",
726 * construct a polyhedron with shifted copies of the constraints in "cone",
727 * i.e., a polyhedron with "cone" as its recession cone, such that each
728 * point x in this polyhedron is such that the unit box positioned at x
729 * lies entirely inside the affine cone 'vec + cone'.
730 * Any rational point in this polyhedron may therefore be rounded up
731 * to yield an integer point that lies inside said affine cone.
733 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
734 * point "vec" by v/d.
735 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
736 * by <a_i, x> - b/d >= 0.
737 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
738 * We prefer this polyhedron over the actual affine cone because it doesn't
739 * require a scaling of the constraints.
740 * If each of the vertices of the unit cube positioned at x lies inside
741 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
742 * We therefore impose that x' = x + \sum e_i, for any selection of unit
743 * vectors lies inside the polyhedron, i.e.,
745 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
747 * The most stringent of these constraints is the one that selects
748 * all negative a_i, so the polyhedron we are looking for has constraints
750 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
752 * Note that if cone were known to have only non-negative rays
753 * (which can be accomplished by a unimodular transformation),
754 * then we would only have to check the points x' = x + e_i
755 * and we only have to add the smallest negative a_i (if any)
756 * instead of the sum of all negative a_i.
758 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
759 struct isl_vec *vec)
761 int i, j, k;
762 unsigned total;
764 struct isl_basic_set *shift = NULL;
766 if (!cone || !vec)
767 goto error;
769 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
771 total = isl_basic_set_total_dim(cone);
773 shift = isl_basic_set_alloc_space(isl_basic_set_get_space(cone),
774 0, 0, cone->n_ineq);
776 for (i = 0; i < cone->n_ineq; ++i) {
777 k = isl_basic_set_alloc_inequality(shift);
778 if (k < 0)
779 goto error;
780 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
781 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
782 &shift->ineq[k][0]);
783 isl_int_cdiv_q(shift->ineq[k][0],
784 shift->ineq[k][0], vec->el[0]);
785 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
786 for (j = 0; j < total; ++j) {
787 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
788 continue;
789 isl_int_add(shift->ineq[k][0],
790 shift->ineq[k][0], shift->ineq[k][1 + j]);
794 isl_basic_set_free(cone);
795 isl_vec_free(vec);
797 return isl_basic_set_finalize(shift);
798 error:
799 isl_basic_set_free(shift);
800 isl_basic_set_free(cone);
801 isl_vec_free(vec);
802 return NULL;
805 /* Given a rational point vec in a (transformed) basic set,
806 * such that cone is the recession cone of the original basic set,
807 * "round up" the rational point to an integer point.
809 * We first check if the rational point just happens to be integer.
810 * If not, we transform the cone in the same way as the basic set,
811 * pick a point x in this cone shifted to the rational point such that
812 * the whole unit cube at x is also inside this affine cone.
813 * Then we simply round up the coordinates of x and return the
814 * resulting integer point.
816 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
817 struct isl_basic_set *cone, struct isl_mat *U)
819 unsigned total;
821 if (!vec || !cone || !U)
822 goto error;
824 isl_assert(vec->ctx, vec->size != 0, goto error);
825 if (isl_int_is_one(vec->el[0])) {
826 isl_mat_free(U);
827 isl_basic_set_free(cone);
828 return vec;
831 total = isl_basic_set_total_dim(cone);
832 cone = isl_basic_set_preimage(cone, U);
833 cone = isl_basic_set_remove_dims(cone, isl_dim_set,
834 0, total - (vec->size - 1));
836 cone = shift_cone(cone, vec);
838 vec = rational_sample(cone);
839 vec = isl_vec_ceil(vec);
840 return vec;
841 error:
842 isl_mat_free(U);
843 isl_vec_free(vec);
844 isl_basic_set_free(cone);
845 return NULL;
848 /* Concatenate two integer vectors, i.e., two vectors with denominator
849 * (stored in element 0) equal to 1.
851 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
853 struct isl_vec *vec;
855 if (!vec1 || !vec2)
856 goto error;
857 isl_assert(vec1->ctx, vec1->size > 0, goto error);
858 isl_assert(vec2->ctx, vec2->size > 0, goto error);
859 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
860 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
862 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
863 if (!vec)
864 goto error;
866 isl_seq_cpy(vec->el, vec1->el, vec1->size);
867 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
869 isl_vec_free(vec1);
870 isl_vec_free(vec2);
872 return vec;
873 error:
874 isl_vec_free(vec1);
875 isl_vec_free(vec2);
876 return NULL;
879 /* Give a basic set "bset" with recession cone "cone", compute and
880 * return an integer point in bset, if any.
882 * If the recession cone is full-dimensional, then we know that
883 * bset contains an infinite number of integer points and it is
884 * fairly easy to pick one of them.
885 * If the recession cone is not full-dimensional, then we first
886 * transform bset such that the bounded directions appear as
887 * the first dimensions of the transformed basic set.
888 * We do this by using a unimodular transformation that transforms
889 * the equalities in the recession cone to equalities on the first
890 * dimensions.
892 * The transformed set is then projected onto its bounded dimensions.
893 * Note that to compute this projection, we can simply drop all constraints
894 * involving any of the unbounded dimensions since these constraints
895 * cannot be combined to produce a constraint on the bounded dimensions.
896 * To see this, assume that there is such a combination of constraints
897 * that produces a constraint on the bounded dimensions. This means
898 * that some combination of the unbounded dimensions has both an upper
899 * bound and a lower bound in terms of the bounded dimensions, but then
900 * this combination would be a bounded direction too and would have been
901 * transformed into a bounded dimensions.
903 * We then compute a sample value in the bounded dimensions.
904 * If no such value can be found, then the original set did not contain
905 * any integer points and we are done.
906 * Otherwise, we plug in the value we found in the bounded dimensions,
907 * project out these bounded dimensions and end up with a set with
908 * a full-dimensional recession cone.
909 * A sample point in this set is computed by "rounding up" any
910 * rational point in the set.
912 * The sample points in the bounded and unbounded dimensions are
913 * then combined into a single sample point and transformed back
914 * to the original space.
916 __isl_give isl_vec *isl_basic_set_sample_with_cone(
917 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
919 unsigned total;
920 unsigned cone_dim;
921 struct isl_mat *M, *U;
922 struct isl_vec *sample;
923 struct isl_vec *cone_sample;
924 struct isl_ctx *ctx;
925 struct isl_basic_set *bounded;
927 if (!bset || !cone)
928 goto error;
930 ctx = isl_basic_set_get_ctx(bset);
931 total = isl_basic_set_total_dim(cone);
932 cone_dim = total - cone->n_eq;
934 M = isl_mat_sub_alloc6(ctx, cone->eq, 0, cone->n_eq, 1, total);
935 M = isl_mat_left_hermite(M, 0, &U, NULL);
936 if (!M)
937 goto error;
938 isl_mat_free(M);
940 U = isl_mat_lin_to_aff(U);
941 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
943 bounded = isl_basic_set_copy(bset);
944 bounded = isl_basic_set_drop_constraints_involving(bounded,
945 total - cone_dim, cone_dim);
946 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
947 sample = sample_bounded(bounded);
948 if (!sample || sample->size == 0) {
949 isl_basic_set_free(bset);
950 isl_basic_set_free(cone);
951 isl_mat_free(U);
952 return sample;
954 bset = plug_in(bset, isl_vec_copy(sample));
955 cone_sample = rational_sample(bset);
956 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
957 sample = vec_concat(sample, cone_sample);
958 sample = isl_mat_vec_product(U, sample);
959 return sample;
960 error:
961 isl_basic_set_free(cone);
962 isl_basic_set_free(bset);
963 return NULL;
966 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
968 int i;
970 isl_int_set_si(*s, 0);
972 for (i = 0; i < v->size; ++i)
973 if (isl_int_is_neg(v->el[i]))
974 isl_int_add(*s, *s, v->el[i]);
977 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
978 * to the recession cone and the inverse of a new basis U = inv(B),
979 * with the unbounded directions in B last,
980 * add constraints to "tab" that ensure any rational value
981 * in the unbounded directions can be rounded up to an integer value.
983 * The new basis is given by x' = B x, i.e., x = U x'.
984 * For any rational value of the last tab->n_unbounded coordinates
985 * in the update tableau, the value that is obtained by rounding
986 * up this value should be contained in the original tableau.
987 * For any constraint "a x + c >= 0", we therefore need to add
988 * a constraint "a x + c + s >= 0", with s the sum of all negative
989 * entries in the last elements of "a U".
991 * Since we are not interested in the first entries of any of the "a U",
992 * we first drop the columns of U that correpond to bounded directions.
994 static int tab_shift_cone(struct isl_tab *tab,
995 struct isl_tab *tab_cone, struct isl_mat *U)
997 int i;
998 isl_int v;
999 struct isl_basic_set *bset = NULL;
1001 if (tab && tab->n_unbounded == 0) {
1002 isl_mat_free(U);
1003 return 0;
1005 isl_int_init(v);
1006 if (!tab || !tab_cone || !U)
1007 goto error;
1008 bset = isl_tab_peek_bset(tab_cone);
1009 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
1010 for (i = 0; i < bset->n_ineq; ++i) {
1011 int ok;
1012 struct isl_vec *row = NULL;
1013 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
1014 continue;
1015 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
1016 if (!row)
1017 goto error;
1018 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
1019 row = isl_vec_mat_product(row, isl_mat_copy(U));
1020 if (!row)
1021 goto error;
1022 vec_sum_of_neg(row, &v);
1023 isl_vec_free(row);
1024 if (isl_int_is_zero(v))
1025 continue;
1026 if (isl_tab_extend_cons(tab, 1) < 0)
1027 goto error;
1028 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
1029 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1030 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1031 if (!ok)
1032 goto error;
1035 isl_mat_free(U);
1036 isl_int_clear(v);
1037 return 0;
1038 error:
1039 isl_mat_free(U);
1040 isl_int_clear(v);
1041 return -1;
1044 /* Compute and return an initial basis for the possibly
1045 * unbounded tableau "tab". "tab_cone" is a tableau
1046 * for the corresponding recession cone.
1047 * Additionally, add constraints to "tab" that ensure
1048 * that any rational value for the unbounded directions
1049 * can be rounded up to an integer value.
1051 * If the tableau is bounded, i.e., if the recession cone
1052 * is zero-dimensional, then we just use inital_basis.
1053 * Otherwise, we construct a basis whose first directions
1054 * correspond to equalities, followed by bounded directions,
1055 * i.e., equalities in the recession cone.
1056 * The remaining directions are then unbounded.
1058 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1059 struct isl_tab *tab_cone)
1061 struct isl_mat *eq;
1062 struct isl_mat *cone_eq;
1063 struct isl_mat *U, *Q;
1065 if (!tab || !tab_cone)
1066 return -1;
1068 if (tab_cone->n_col == tab_cone->n_dead) {
1069 tab->basis = initial_basis(tab);
1070 return tab->basis ? 0 : -1;
1073 eq = tab_equalities(tab);
1074 if (!eq)
1075 return -1;
1076 tab->n_zero = eq->n_row;
1077 cone_eq = tab_equalities(tab_cone);
1078 eq = isl_mat_concat(eq, cone_eq);
1079 if (!eq)
1080 return -1;
1081 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1082 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1083 if (!eq)
1084 return -1;
1085 isl_mat_free(eq);
1086 tab->basis = isl_mat_lin_to_aff(Q);
1087 if (tab_shift_cone(tab, tab_cone, U) < 0)
1088 return -1;
1089 if (!tab->basis)
1090 return -1;
1091 return 0;
1094 /* Compute and return a sample point in bset using generalized basis
1095 * reduction. We first check if the input set has a non-trivial
1096 * recession cone. If so, we perform some extra preprocessing in
1097 * sample_with_cone. Otherwise, we directly perform generalized basis
1098 * reduction.
1100 static struct isl_vec *gbr_sample(struct isl_basic_set *bset)
1102 unsigned dim;
1103 struct isl_basic_set *cone;
1105 dim = isl_basic_set_total_dim(bset);
1107 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1108 if (!cone)
1109 goto error;
1111 if (cone->n_eq < dim)
1112 return isl_basic_set_sample_with_cone(bset, cone);
1114 isl_basic_set_free(cone);
1115 return sample_bounded(bset);
1116 error:
1117 isl_basic_set_free(bset);
1118 return NULL;
1121 static struct isl_vec *basic_set_sample(struct isl_basic_set *bset, int bounded)
1123 struct isl_ctx *ctx;
1124 unsigned dim;
1125 if (!bset)
1126 return NULL;
1128 ctx = bset->ctx;
1129 if (isl_basic_set_plain_is_empty(bset))
1130 return empty_sample(bset);
1132 dim = isl_basic_set_n_dim(bset);
1133 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1134 isl_assert(ctx, bset->n_div == 0, goto error);
1136 if (bset->sample && bset->sample->size == 1 + dim) {
1137 int contains = isl_basic_set_contains(bset, bset->sample);
1138 if (contains < 0)
1139 goto error;
1140 if (contains) {
1141 struct isl_vec *sample = isl_vec_copy(bset->sample);
1142 isl_basic_set_free(bset);
1143 return sample;
1146 isl_vec_free(bset->sample);
1147 bset->sample = NULL;
1149 if (bset->n_eq > 0)
1150 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1151 : isl_basic_set_sample_vec);
1152 if (dim == 0)
1153 return zero_sample(bset);
1154 if (dim == 1)
1155 return interval_sample(bset);
1157 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1158 error:
1159 isl_basic_set_free(bset);
1160 return NULL;
1163 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1165 return basic_set_sample(bset, 0);
1168 /* Compute an integer sample in "bset", where the caller guarantees
1169 * that "bset" is bounded.
1171 struct isl_vec *isl_basic_set_sample_bounded(struct isl_basic_set *bset)
1173 return basic_set_sample(bset, 1);
1176 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1178 int i;
1179 int k;
1180 struct isl_basic_set *bset = NULL;
1181 struct isl_ctx *ctx;
1182 unsigned dim;
1184 if (!vec)
1185 return NULL;
1186 ctx = vec->ctx;
1187 isl_assert(ctx, vec->size != 0, goto error);
1189 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1190 if (!bset)
1191 goto error;
1192 dim = isl_basic_set_n_dim(bset);
1193 for (i = dim - 1; i >= 0; --i) {
1194 k = isl_basic_set_alloc_equality(bset);
1195 if (k < 0)
1196 goto error;
1197 isl_seq_clr(bset->eq[k], 1 + dim);
1198 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1199 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1201 bset->sample = vec;
1203 return bset;
1204 error:
1205 isl_basic_set_free(bset);
1206 isl_vec_free(vec);
1207 return NULL;
1210 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1212 struct isl_basic_set *bset;
1213 struct isl_vec *sample_vec;
1215 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1216 sample_vec = isl_basic_set_sample_vec(bset);
1217 if (!sample_vec)
1218 goto error;
1219 if (sample_vec->size == 0) {
1220 isl_vec_free(sample_vec);
1221 return isl_basic_map_set_to_empty(bmap);
1223 isl_vec_free(bmap->sample);
1224 bmap->sample = isl_vec_copy(sample_vec);
1225 bset = isl_basic_set_from_vec(sample_vec);
1226 return isl_basic_map_overlying_set(bset, bmap);
1227 error:
1228 isl_basic_map_free(bmap);
1229 return NULL;
1232 __isl_give isl_basic_set *isl_basic_set_sample(__isl_take isl_basic_set *bset)
1234 return isl_basic_map_sample(bset);
1237 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1239 int i;
1240 isl_basic_map *sample = NULL;
1242 if (!map)
1243 goto error;
1245 for (i = 0; i < map->n; ++i) {
1246 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1247 if (!sample)
1248 goto error;
1249 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1250 break;
1251 isl_basic_map_free(sample);
1253 if (i == map->n)
1254 sample = isl_basic_map_empty(isl_map_get_space(map));
1255 isl_map_free(map);
1256 return sample;
1257 error:
1258 isl_map_free(map);
1259 return NULL;
1262 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1264 return (isl_basic_set *) isl_map_sample((isl_map *)set);
1267 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1269 isl_vec *vec;
1270 isl_space *dim;
1272 dim = isl_basic_set_get_space(bset);
1273 bset = isl_basic_set_underlying_set(bset);
1274 vec = isl_basic_set_sample_vec(bset);
1276 return isl_point_alloc(dim, vec);
1279 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1281 int i;
1282 isl_point *pnt;
1284 if (!set)
1285 return NULL;
1287 for (i = 0; i < set->n; ++i) {
1288 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1289 if (!pnt)
1290 goto error;
1291 if (!isl_point_is_void(pnt))
1292 break;
1293 isl_point_free(pnt);
1295 if (i == set->n)
1296 pnt = isl_point_void(isl_set_get_space(set));
1298 isl_set_free(set);
1299 return pnt;
1300 error:
1301 isl_set_free(set);
1302 return NULL;