isl_tab_pip.c: fix typo in comment
[isl.git] / isl_sample.c
blob812bb10b6b7feaeb46589e8f1663e0fe54654d96
1 /*
2 * Copyright 2008-2009 Katholieke Universiteit Leuven
4 * Use of this software is governed by the GNU LGPLv2.1 license
6 * Written by Sven Verdoolaege, K.U.Leuven, Departement
7 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
8 */
10 #include <isl_map_private.h>
11 #include "isl_sample.h"
12 #include "isl_sample_piplib.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>
22 static struct isl_vec *empty_sample(struct isl_basic_set *bset)
24 struct isl_vec *vec;
26 vec = isl_vec_alloc(bset->ctx, 0);
27 isl_basic_set_free(bset);
28 return vec;
31 /* Construct a zero sample of the same dimension as bset.
32 * As a special case, if bset is zero-dimensional, this
33 * function creates a zero-dimensional sample point.
35 static struct isl_vec *zero_sample(struct isl_basic_set *bset)
37 unsigned dim;
38 struct isl_vec *sample;
40 dim = isl_basic_set_total_dim(bset);
41 sample = isl_vec_alloc(bset->ctx, 1 + dim);
42 if (sample) {
43 isl_int_set_si(sample->el[0], 1);
44 isl_seq_clr(sample->el + 1, dim);
46 isl_basic_set_free(bset);
47 return sample;
50 static struct isl_vec *interval_sample(struct isl_basic_set *bset)
52 int i;
53 isl_int t;
54 struct isl_vec *sample;
56 bset = isl_basic_set_simplify(bset);
57 if (!bset)
58 return NULL;
59 if (isl_basic_set_fast_is_empty(bset))
60 return empty_sample(bset);
61 if (bset->n_eq == 0 && bset->n_ineq == 0)
62 return zero_sample(bset);
64 sample = isl_vec_alloc(bset->ctx, 2);
65 if (!sample)
66 goto error;
67 if (!bset)
68 return NULL;
69 isl_int_set_si(sample->block.data[0], 1);
71 if (bset->n_eq > 0) {
72 isl_assert(bset->ctx, bset->n_eq == 1, goto error);
73 isl_assert(bset->ctx, bset->n_ineq == 0, goto error);
74 if (isl_int_is_one(bset->eq[0][1]))
75 isl_int_neg(sample->el[1], bset->eq[0][0]);
76 else {
77 isl_assert(bset->ctx, isl_int_is_negone(bset->eq[0][1]),
78 goto error);
79 isl_int_set(sample->el[1], bset->eq[0][0]);
81 isl_basic_set_free(bset);
82 return sample;
85 isl_int_init(t);
86 if (isl_int_is_one(bset->ineq[0][1]))
87 isl_int_neg(sample->block.data[1], bset->ineq[0][0]);
88 else
89 isl_int_set(sample->block.data[1], bset->ineq[0][0]);
90 for (i = 1; i < bset->n_ineq; ++i) {
91 isl_seq_inner_product(sample->block.data,
92 bset->ineq[i], 2, &t);
93 if (isl_int_is_neg(t))
94 break;
96 isl_int_clear(t);
97 if (i < bset->n_ineq) {
98 isl_vec_free(sample);
99 return empty_sample(bset);
102 isl_basic_set_free(bset);
103 return sample;
104 error:
105 isl_basic_set_free(bset);
106 isl_vec_free(sample);
107 return NULL;
110 static struct isl_mat *independent_bounds(struct isl_basic_set *bset)
112 int i, j, n;
113 struct isl_mat *dirs = NULL;
114 struct isl_mat *bounds = NULL;
115 unsigned dim;
117 if (!bset)
118 return NULL;
120 dim = isl_basic_set_n_dim(bset);
121 bounds = isl_mat_alloc(bset->ctx, 1+dim, 1+dim);
122 if (!bounds)
123 return NULL;
125 isl_int_set_si(bounds->row[0][0], 1);
126 isl_seq_clr(bounds->row[0]+1, dim);
127 bounds->n_row = 1;
129 if (bset->n_ineq == 0)
130 return bounds;
132 dirs = isl_mat_alloc(bset->ctx, dim, dim);
133 if (!dirs) {
134 isl_mat_free(bounds);
135 return NULL;
137 isl_seq_cpy(dirs->row[0], bset->ineq[0]+1, dirs->n_col);
138 isl_seq_cpy(bounds->row[1], bset->ineq[0], bounds->n_col);
139 for (j = 1, n = 1; n < dim && j < bset->n_ineq; ++j) {
140 int pos;
142 isl_seq_cpy(dirs->row[n], bset->ineq[j]+1, dirs->n_col);
144 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
145 if (pos < 0)
146 continue;
147 for (i = 0; i < n; ++i) {
148 int pos_i;
149 pos_i = isl_seq_first_non_zero(dirs->row[i], dirs->n_col);
150 if (pos_i < pos)
151 continue;
152 if (pos_i > pos)
153 break;
154 isl_seq_elim(dirs->row[n], dirs->row[i], pos,
155 dirs->n_col, NULL);
156 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
157 if (pos < 0)
158 break;
160 if (pos < 0)
161 continue;
162 if (i < n) {
163 int k;
164 isl_int *t = dirs->row[n];
165 for (k = n; k > i; --k)
166 dirs->row[k] = dirs->row[k-1];
167 dirs->row[i] = t;
169 ++n;
170 isl_seq_cpy(bounds->row[n], bset->ineq[j], bounds->n_col);
172 isl_mat_free(dirs);
173 bounds->n_row = 1+n;
174 return bounds;
177 static void swap_inequality(struct isl_basic_set *bset, int a, int b)
179 isl_int *t = bset->ineq[a];
180 bset->ineq[a] = bset->ineq[b];
181 bset->ineq[b] = t;
184 /* Skew into positive orthant and project out lineality space.
186 * We perform a unimodular transformation that turns a selected
187 * maximal set of linearly independent bounds into constraints
188 * on the first dimensions that impose that these first dimensions
189 * are non-negative. In particular, the constraint matrix is lower
190 * triangular with positive entries on the diagonal and negative
191 * entries below.
192 * If "bset" has a lineality space then these constraints (and therefore
193 * all constraints in bset) only involve the first dimensions.
194 * The remaining dimensions then do not appear in any constraints and
195 * we can select any value for them, say zero. We therefore project
196 * out this final dimensions and plug in the value zero later. This
197 * is accomplished by simply dropping the final columns of
198 * the unimodular transformation.
200 static struct isl_basic_set *isl_basic_set_skew_to_positive_orthant(
201 struct isl_basic_set *bset, struct isl_mat **T)
203 struct isl_mat *U = NULL;
204 struct isl_mat *bounds = NULL;
205 int i, j;
206 unsigned old_dim, new_dim;
208 *T = NULL;
209 if (!bset)
210 return NULL;
212 isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
213 isl_assert(bset->ctx, bset->n_div == 0, goto error);
214 isl_assert(bset->ctx, bset->n_eq == 0, goto error);
216 old_dim = isl_basic_set_n_dim(bset);
217 /* Try to move (multiples of) unit rows up. */
218 for (i = 0, j = 0; i < bset->n_ineq; ++i) {
219 int pos = isl_seq_first_non_zero(bset->ineq[i]+1, old_dim);
220 if (pos < 0)
221 continue;
222 if (isl_seq_first_non_zero(bset->ineq[i]+1+pos+1,
223 old_dim-pos-1) >= 0)
224 continue;
225 if (i != j)
226 swap_inequality(bset, i, j);
227 ++j;
229 bounds = independent_bounds(bset);
230 if (!bounds)
231 goto error;
232 new_dim = bounds->n_row - 1;
233 bounds = isl_mat_left_hermite(bounds, 1, &U, NULL);
234 if (!bounds)
235 goto error;
236 U = isl_mat_drop_cols(U, 1 + new_dim, old_dim - new_dim);
237 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
238 if (!bset)
239 goto error;
240 *T = U;
241 isl_mat_free(bounds);
242 return bset;
243 error:
244 isl_mat_free(bounds);
245 isl_mat_free(U);
246 isl_basic_set_free(bset);
247 return NULL;
250 /* Find a sample integer point, if any, in bset, which is known
251 * to have equalities. If bset contains no integer points, then
252 * return a zero-length vector.
253 * We simply remove the known equalities, compute a sample
254 * in the resulting bset, using the specified recurse function,
255 * and then transform the sample back to the original space.
257 static struct isl_vec *sample_eq(struct isl_basic_set *bset,
258 struct isl_vec *(*recurse)(struct isl_basic_set *))
260 struct isl_mat *T;
261 struct isl_vec *sample;
263 if (!bset)
264 return NULL;
266 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
267 sample = recurse(bset);
268 if (!sample || sample->size == 0)
269 isl_mat_free(T);
270 else
271 sample = isl_mat_vec_product(T, sample);
272 return sample;
275 /* Return a matrix containing the equalities of the tableau
276 * in constraint form. The tableau is assumed to have
277 * an associated bset that has been kept up-to-date.
279 static struct isl_mat *tab_equalities(struct isl_tab *tab)
281 int i, j;
282 int n_eq;
283 struct isl_mat *eq;
284 struct isl_basic_set *bset;
286 if (!tab)
287 return NULL;
289 bset = isl_tab_peek_bset(tab);
290 isl_assert(tab->mat->ctx, bset, return NULL);
292 n_eq = tab->n_var - tab->n_col + tab->n_dead;
293 if (tab->empty || n_eq == 0)
294 return isl_mat_alloc(tab->mat->ctx, 0, tab->n_var);
295 if (n_eq == tab->n_var)
296 return isl_mat_identity(tab->mat->ctx, tab->n_var);
298 eq = isl_mat_alloc(tab->mat->ctx, n_eq, tab->n_var);
299 if (!eq)
300 return NULL;
301 for (i = 0, j = 0; i < tab->n_con; ++i) {
302 if (tab->con[i].is_row)
303 continue;
304 if (tab->con[i].index >= 0 && tab->con[i].index >= tab->n_dead)
305 continue;
306 if (i < bset->n_eq)
307 isl_seq_cpy(eq->row[j], bset->eq[i] + 1, tab->n_var);
308 else
309 isl_seq_cpy(eq->row[j],
310 bset->ineq[i - bset->n_eq] + 1, tab->n_var);
311 ++j;
313 isl_assert(bset->ctx, j == n_eq, goto error);
314 return eq;
315 error:
316 isl_mat_free(eq);
317 return NULL;
320 /* Compute and return an initial basis for the bounded tableau "tab".
322 * If the tableau is either full-dimensional or zero-dimensional,
323 * the we simply return an identity matrix.
324 * Otherwise, we construct a basis whose first directions correspond
325 * to equalities.
327 static struct isl_mat *initial_basis(struct isl_tab *tab)
329 int n_eq;
330 struct isl_mat *eq;
331 struct isl_mat *Q;
333 tab->n_unbounded = 0;
334 tab->n_zero = n_eq = tab->n_var - tab->n_col + tab->n_dead;
335 if (tab->empty || n_eq == 0 || n_eq == tab->n_var)
336 return isl_mat_identity(tab->mat->ctx, 1 + tab->n_var);
338 eq = tab_equalities(tab);
339 eq = isl_mat_left_hermite(eq, 0, NULL, &Q);
340 if (!eq)
341 return NULL;
342 isl_mat_free(eq);
344 Q = isl_mat_lin_to_aff(Q);
345 return Q;
348 /* Given a tableau representing a set, find and return
349 * an integer point in the set, if there is any.
351 * We perform a depth first search
352 * for an integer point, by scanning all possible values in the range
353 * attained by a basis vector, where an initial basis may have been set
354 * by the calling function. Otherwise an initial basis that exploits
355 * the equalities in the tableau is created.
356 * tab->n_zero is currently ignored and is clobbered by this function.
358 * The tableau is allowed to have unbounded direction, but then
359 * the calling function needs to set an initial basis, with the
360 * unbounded directions last and with tab->n_unbounded set
361 * to the number of unbounded directions.
362 * Furthermore, the calling functions needs to add shifted copies
363 * of all constraints involving unbounded directions to ensure
364 * that any feasible rational value in these directions can be rounded
365 * up to yield a feasible integer value.
366 * In particular, let B define the given basis x' = B x
367 * and let T be the inverse of B, i.e., X = T x'.
368 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
369 * or a T x' + c >= 0 in terms of the given basis. Assume that
370 * the bounded directions have an integer value, then we can safely
371 * round up the values for the unbounded directions if we make sure
372 * that x' not only satisfies the original constraint, but also
373 * the constraint "a T x' + c + s >= 0" with s the sum of all
374 * negative values in the last n_unbounded entries of "a T".
375 * The calling function therefore needs to add the constraint
376 * a x + c + s >= 0. The current function then scans the first
377 * directions for an integer value and once those have been found,
378 * it can compute "T ceil(B x)" to yield an integer point in the set.
379 * Note that during the search, the first rows of B may be changed
380 * by a basis reduction, but the last n_unbounded rows of B remain
381 * unaltered and are also not mixed into the first rows.
383 * The search is implemented iteratively. "level" identifies the current
384 * basis vector. "init" is true if we want the first value at the current
385 * level and false if we want the next value.
387 * The initial basis is the identity matrix. If the range in some direction
388 * contains more than one integer value, we perform basis reduction based
389 * on the value of ctx->opt->gbr
390 * - ISL_GBR_NEVER: never perform basis reduction
391 * - ISL_GBR_ONCE: only perform basis reduction the first
392 * time such a range is encountered
393 * - ISL_GBR_ALWAYS: always perform basis reduction when
394 * such a range is encountered
396 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
397 * reduction computation to return early. That is, as soon as it
398 * finds a reasonable first direction.
400 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
402 unsigned dim;
403 unsigned gbr;
404 struct isl_ctx *ctx;
405 struct isl_vec *sample;
406 struct isl_vec *min;
407 struct isl_vec *max;
408 enum isl_lp_result res;
409 int level;
410 int init;
411 int reduced;
412 struct isl_tab_undo **snap;
414 if (!tab)
415 return NULL;
416 if (tab->empty)
417 return isl_vec_alloc(tab->mat->ctx, 0);
419 if (!tab->basis)
420 tab->basis = initial_basis(tab);
421 if (!tab->basis)
422 return NULL;
423 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
424 return NULL);
425 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
426 return NULL);
428 ctx = tab->mat->ctx;
429 dim = tab->n_var;
430 gbr = ctx->opt->gbr;
432 if (tab->n_unbounded == tab->n_var) {
433 sample = isl_tab_get_sample_value(tab);
434 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
435 sample = isl_vec_ceil(sample);
436 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
437 sample);
438 return sample;
441 if (isl_tab_extend_cons(tab, dim + 1) < 0)
442 return NULL;
444 min = isl_vec_alloc(ctx, dim);
445 max = isl_vec_alloc(ctx, dim);
446 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
448 if (!min || !max || !snap)
449 goto error;
451 level = 0;
452 init = 1;
453 reduced = 0;
455 while (level >= 0) {
456 int empty = 0;
457 if (init) {
458 res = isl_tab_min(tab, tab->basis->row[1 + level],
459 ctx->one, &min->el[level], NULL, 0);
460 if (res == isl_lp_empty)
461 empty = 1;
462 isl_assert(ctx, res != isl_lp_unbounded, goto error);
463 if (res == isl_lp_error)
464 goto error;
465 if (!empty && isl_tab_sample_is_integer(tab))
466 break;
467 isl_seq_neg(tab->basis->row[1 + level] + 1,
468 tab->basis->row[1 + level] + 1, dim);
469 res = isl_tab_min(tab, tab->basis->row[1 + level],
470 ctx->one, &max->el[level], NULL, 0);
471 isl_seq_neg(tab->basis->row[1 + level] + 1,
472 tab->basis->row[1 + level] + 1, dim);
473 isl_int_neg(max->el[level], max->el[level]);
474 if (res == isl_lp_empty)
475 empty = 1;
476 isl_assert(ctx, res != isl_lp_unbounded, goto error);
477 if (res == isl_lp_error)
478 goto error;
479 if (!empty && isl_tab_sample_is_integer(tab))
480 break;
481 if (!empty && !reduced &&
482 ctx->opt->gbr != ISL_GBR_NEVER &&
483 isl_int_lt(min->el[level], max->el[level])) {
484 unsigned gbr_only_first;
485 if (ctx->opt->gbr == ISL_GBR_ONCE)
486 ctx->opt->gbr = ISL_GBR_NEVER;
487 tab->n_zero = level;
488 gbr_only_first = ctx->opt->gbr_only_first;
489 ctx->opt->gbr_only_first =
490 ctx->opt->gbr == ISL_GBR_ALWAYS;
491 tab = isl_tab_compute_reduced_basis(tab);
492 ctx->opt->gbr_only_first = gbr_only_first;
493 if (!tab || !tab->basis)
494 goto error;
495 reduced = 1;
496 continue;
498 reduced = 0;
499 snap[level] = isl_tab_snap(tab);
500 } else
501 isl_int_add_ui(min->el[level], min->el[level], 1);
503 if (empty || isl_int_gt(min->el[level], max->el[level])) {
504 level--;
505 init = 0;
506 if (level >= 0)
507 if (isl_tab_rollback(tab, snap[level]) < 0)
508 goto error;
509 continue;
511 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
512 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
513 goto error;
514 isl_int_set_si(tab->basis->row[1 + level][0], 0);
515 if (level + tab->n_unbounded < dim - 1) {
516 ++level;
517 init = 1;
518 continue;
520 break;
523 if (level >= 0) {
524 sample = isl_tab_get_sample_value(tab);
525 if (!sample)
526 goto error;
527 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
528 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
529 sample);
530 sample = isl_vec_ceil(sample);
531 sample = isl_mat_vec_inverse_product(
532 isl_mat_copy(tab->basis), sample);
534 } else
535 sample = isl_vec_alloc(ctx, 0);
537 ctx->opt->gbr = gbr;
538 isl_vec_free(min);
539 isl_vec_free(max);
540 free(snap);
541 return sample;
542 error:
543 ctx->opt->gbr = gbr;
544 isl_vec_free(min);
545 isl_vec_free(max);
546 free(snap);
547 return NULL;
550 static struct isl_vec *sample_bounded(struct isl_basic_set *bset);
552 /* Compute a sample point of the given basic set, based on the given,
553 * non-trivial factorization.
555 static __isl_give isl_vec *factored_sample(__isl_take isl_basic_set *bset,
556 __isl_take isl_factorizer *f)
558 int i, n;
559 isl_vec *sample = NULL;
560 isl_ctx *ctx;
561 unsigned nparam;
562 unsigned nvar;
564 ctx = isl_basic_set_get_ctx(bset);
565 if (!ctx)
566 goto error;
568 nparam = isl_basic_set_dim(bset, isl_dim_param);
569 nvar = isl_basic_set_dim(bset, isl_dim_set);
571 sample = isl_vec_alloc(ctx, 1 + isl_basic_set_total_dim(bset));
572 if (!sample)
573 goto error;
574 isl_int_set_si(sample->el[0], 1);
576 bset = isl_morph_basic_set(isl_morph_copy(f->morph), bset);
578 for (i = 0, n = 0; i < f->n_group; ++i) {
579 isl_basic_set *bset_i;
580 isl_vec *sample_i;
582 bset_i = isl_basic_set_copy(bset);
583 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
584 nparam + n + f->len[i], nvar - n - f->len[i]);
585 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
586 nparam, n);
587 bset_i = isl_basic_set_drop(bset_i, isl_dim_set,
588 n + f->len[i], nvar - n - f->len[i]);
589 bset_i = isl_basic_set_drop(bset_i, isl_dim_set, 0, n);
591 sample_i = sample_bounded(bset_i);
592 if (!sample_i)
593 goto error;
594 if (sample_i->size == 0) {
595 isl_basic_set_free(bset);
596 isl_factorizer_free(f);
597 isl_vec_free(sample);
598 return sample_i;
600 isl_seq_cpy(sample->el + 1 + nparam + n,
601 sample_i->el + 1, f->len[i]);
602 isl_vec_free(sample_i);
604 n += f->len[i];
607 f->morph = isl_morph_inverse(f->morph);
608 sample = isl_morph_vec(isl_morph_copy(f->morph), sample);
610 isl_basic_set_free(bset);
611 isl_factorizer_free(f);
612 return sample;
613 error:
614 isl_basic_set_free(bset);
615 isl_factorizer_free(f);
616 isl_vec_free(sample);
617 return NULL;
620 /* Given a basic set that is known to be bounded, find and return
621 * an integer point in the basic set, if there is any.
623 * After handling some trivial cases, we construct a tableau
624 * and then use isl_tab_sample to find a sample, passing it
625 * the identity matrix as initial basis.
627 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
629 unsigned dim;
630 struct isl_ctx *ctx;
631 struct isl_vec *sample;
632 struct isl_tab *tab = NULL;
633 isl_factorizer *f;
635 if (!bset)
636 return NULL;
638 if (isl_basic_set_fast_is_empty(bset))
639 return empty_sample(bset);
641 dim = isl_basic_set_total_dim(bset);
642 if (dim == 0)
643 return zero_sample(bset);
644 if (dim == 1)
645 return interval_sample(bset);
646 if (bset->n_eq > 0)
647 return sample_eq(bset, sample_bounded);
649 f = isl_basic_set_factorizer(bset);
650 if (!f)
651 goto error;
652 if (f->n_group != 0)
653 return factored_sample(bset, f);
654 isl_factorizer_free(f);
656 ctx = bset->ctx;
658 tab = isl_tab_from_basic_set(bset);
659 if (tab && tab->empty) {
660 isl_tab_free(tab);
661 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
662 sample = isl_vec_alloc(bset->ctx, 0);
663 isl_basic_set_free(bset);
664 return sample;
667 if (isl_tab_track_bset(tab, isl_basic_set_copy(bset)) < 0)
668 goto error;
669 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
670 if (isl_tab_detect_implicit_equalities(tab) < 0)
671 goto error;
673 sample = isl_tab_sample(tab);
674 if (!sample)
675 goto error;
677 if (sample->size > 0) {
678 isl_vec_free(bset->sample);
679 bset->sample = isl_vec_copy(sample);
682 isl_basic_set_free(bset);
683 isl_tab_free(tab);
684 return sample;
685 error:
686 isl_basic_set_free(bset);
687 isl_tab_free(tab);
688 return NULL;
691 /* Given a basic set "bset" and a value "sample" for the first coordinates
692 * of bset, plug in these values and drop the corresponding coordinates.
694 * We do this by computing the preimage of the transformation
696 * [ 1 0 ]
697 * x = [ s 0 ] x'
698 * [ 0 I ]
700 * where [1 s] is the sample value and I is the identity matrix of the
701 * appropriate dimension.
703 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
704 struct isl_vec *sample)
706 int i;
707 unsigned total;
708 struct isl_mat *T;
710 if (!bset || !sample)
711 goto error;
713 total = isl_basic_set_total_dim(bset);
714 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
715 if (!T)
716 goto error;
718 for (i = 0; i < sample->size; ++i) {
719 isl_int_set(T->row[i][0], sample->el[i]);
720 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
722 for (i = 0; i < T->n_col - 1; ++i) {
723 isl_seq_clr(T->row[sample->size + i], T->n_col);
724 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
726 isl_vec_free(sample);
728 bset = isl_basic_set_preimage(bset, T);
729 return bset;
730 error:
731 isl_basic_set_free(bset);
732 isl_vec_free(sample);
733 return NULL;
736 /* Given a basic set "bset", return any (possibly non-integer) point
737 * in the basic set.
739 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
741 struct isl_tab *tab;
742 struct isl_vec *sample;
744 if (!bset)
745 return NULL;
747 tab = isl_tab_from_basic_set(bset);
748 sample = isl_tab_get_sample_value(tab);
749 isl_tab_free(tab);
751 isl_basic_set_free(bset);
753 return sample;
756 /* Given a linear cone "cone" and a rational point "vec",
757 * construct a polyhedron with shifted copies of the constraints in "cone",
758 * i.e., a polyhedron with "cone" as its recession cone, such that each
759 * point x in this polyhedron is such that the unit box positioned at x
760 * lies entirely inside the affine cone 'vec + cone'.
761 * Any rational point in this polyhedron may therefore be rounded up
762 * to yield an integer point that lies inside said affine cone.
764 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
765 * point "vec" by v/d.
766 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
767 * by <a_i, x> - b/d >= 0.
768 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
769 * We prefer this polyhedron over the actual affine cone because it doesn't
770 * require a scaling of the constraints.
771 * If each of the vertices of the unit cube positioned at x lies inside
772 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
773 * We therefore impose that x' = x + \sum e_i, for any selection of unit
774 * vectors lies inside the polyhedron, i.e.,
776 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
778 * The most stringent of these constraints is the one that selects
779 * all negative a_i, so the polyhedron we are looking for has constraints
781 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
783 * Note that if cone were known to have only non-negative rays
784 * (which can be accomplished by a unimodular transformation),
785 * then we would only have to check the points x' = x + e_i
786 * and we only have to add the smallest negative a_i (if any)
787 * instead of the sum of all negative a_i.
789 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
790 struct isl_vec *vec)
792 int i, j, k;
793 unsigned total;
795 struct isl_basic_set *shift = NULL;
797 if (!cone || !vec)
798 goto error;
800 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
802 total = isl_basic_set_total_dim(cone);
804 shift = isl_basic_set_alloc_dim(isl_basic_set_get_dim(cone),
805 0, 0, cone->n_ineq);
807 for (i = 0; i < cone->n_ineq; ++i) {
808 k = isl_basic_set_alloc_inequality(shift);
809 if (k < 0)
810 goto error;
811 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
812 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
813 &shift->ineq[k][0]);
814 isl_int_cdiv_q(shift->ineq[k][0],
815 shift->ineq[k][0], vec->el[0]);
816 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
817 for (j = 0; j < total; ++j) {
818 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
819 continue;
820 isl_int_add(shift->ineq[k][0],
821 shift->ineq[k][0], shift->ineq[k][1 + j]);
825 isl_basic_set_free(cone);
826 isl_vec_free(vec);
828 return isl_basic_set_finalize(shift);
829 error:
830 isl_basic_set_free(shift);
831 isl_basic_set_free(cone);
832 isl_vec_free(vec);
833 return NULL;
836 /* Given a rational point vec in a (transformed) basic set,
837 * such that cone is the recession cone of the original basic set,
838 * "round up" the rational point to an integer point.
840 * We first check if the rational point just happens to be integer.
841 * If not, we transform the cone in the same way as the basic set,
842 * pick a point x in this cone shifted to the rational point such that
843 * the whole unit cube at x is also inside this affine cone.
844 * Then we simply round up the coordinates of x and return the
845 * resulting integer point.
847 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
848 struct isl_basic_set *cone, struct isl_mat *U)
850 unsigned total;
852 if (!vec || !cone || !U)
853 goto error;
855 isl_assert(vec->ctx, vec->size != 0, goto error);
856 if (isl_int_is_one(vec->el[0])) {
857 isl_mat_free(U);
858 isl_basic_set_free(cone);
859 return vec;
862 total = isl_basic_set_total_dim(cone);
863 cone = isl_basic_set_preimage(cone, U);
864 cone = isl_basic_set_remove_dims(cone, isl_dim_set,
865 0, total - (vec->size - 1));
867 cone = shift_cone(cone, vec);
869 vec = rational_sample(cone);
870 vec = isl_vec_ceil(vec);
871 return vec;
872 error:
873 isl_mat_free(U);
874 isl_vec_free(vec);
875 isl_basic_set_free(cone);
876 return NULL;
879 /* Concatenate two integer vectors, i.e., two vectors with denominator
880 * (stored in element 0) equal to 1.
882 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
884 struct isl_vec *vec;
886 if (!vec1 || !vec2)
887 goto error;
888 isl_assert(vec1->ctx, vec1->size > 0, goto error);
889 isl_assert(vec2->ctx, vec2->size > 0, goto error);
890 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
891 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
893 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
894 if (!vec)
895 goto error;
897 isl_seq_cpy(vec->el, vec1->el, vec1->size);
898 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
900 isl_vec_free(vec1);
901 isl_vec_free(vec2);
903 return vec;
904 error:
905 isl_vec_free(vec1);
906 isl_vec_free(vec2);
907 return NULL;
910 /* Give a basic set "bset" with recession cone "cone", compute and
911 * return an integer point in bset, if any.
913 * If the recession cone is full-dimensional, then we know that
914 * bset contains an infinite number of integer points and it is
915 * fairly easy to pick one of them.
916 * If the recession cone is not full-dimensional, then we first
917 * transform bset such that the bounded directions appear as
918 * the first dimensions of the transformed basic set.
919 * We do this by using a unimodular transformation that transforms
920 * the equalities in the recession cone to equalities on the first
921 * dimensions.
923 * The transformed set is then projected onto its bounded dimensions.
924 * Note that to compute this projection, we can simply drop all constraints
925 * involving any of the unbounded dimensions since these constraints
926 * cannot be combined to produce a constraint on the bounded dimensions.
927 * To see this, assume that there is such a combination of constraints
928 * that produces a constraint on the bounded dimensions. This means
929 * that some combination of the unbounded dimensions has both an upper
930 * bound and a lower bound in terms of the bounded dimensions, but then
931 * this combination would be a bounded direction too and would have been
932 * transformed into a bounded dimensions.
934 * We then compute a sample value in the bounded dimensions.
935 * If no such value can be found, then the original set did not contain
936 * any integer points and we are done.
937 * Otherwise, we plug in the value we found in the bounded dimensions,
938 * project out these bounded dimensions and end up with a set with
939 * a full-dimensional recession cone.
940 * A sample point in this set is computed by "rounding up" any
941 * rational point in the set.
943 * The sample points in the bounded and unbounded dimensions are
944 * then combined into a single sample point and transformed back
945 * to the original space.
947 __isl_give isl_vec *isl_basic_set_sample_with_cone(
948 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
950 unsigned total;
951 unsigned cone_dim;
952 struct isl_mat *M, *U;
953 struct isl_vec *sample;
954 struct isl_vec *cone_sample;
955 struct isl_ctx *ctx;
956 struct isl_basic_set *bounded;
958 if (!bset || !cone)
959 goto error;
961 ctx = bset->ctx;
962 total = isl_basic_set_total_dim(cone);
963 cone_dim = total - cone->n_eq;
965 M = isl_mat_sub_alloc(bset->ctx, cone->eq, 0, cone->n_eq, 1, total);
966 M = isl_mat_left_hermite(M, 0, &U, NULL);
967 if (!M)
968 goto error;
969 isl_mat_free(M);
971 U = isl_mat_lin_to_aff(U);
972 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
974 bounded = isl_basic_set_copy(bset);
975 bounded = isl_basic_set_drop_constraints_involving(bounded,
976 total - cone_dim, cone_dim);
977 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
978 sample = sample_bounded(bounded);
979 if (!sample || sample->size == 0) {
980 isl_basic_set_free(bset);
981 isl_basic_set_free(cone);
982 isl_mat_free(U);
983 return sample;
985 bset = plug_in(bset, isl_vec_copy(sample));
986 cone_sample = rational_sample(bset);
987 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
988 sample = vec_concat(sample, cone_sample);
989 sample = isl_mat_vec_product(U, sample);
990 return sample;
991 error:
992 isl_basic_set_free(cone);
993 isl_basic_set_free(bset);
994 return NULL;
997 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
999 int i;
1001 isl_int_set_si(*s, 0);
1003 for (i = 0; i < v->size; ++i)
1004 if (isl_int_is_neg(v->el[i]))
1005 isl_int_add(*s, *s, v->el[i]);
1008 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
1009 * to the recession cone and the inverse of a new basis U = inv(B),
1010 * with the unbounded directions in B last,
1011 * add constraints to "tab" that ensure any rational value
1012 * in the unbounded directions can be rounded up to an integer value.
1014 * The new basis is given by x' = B x, i.e., x = U x'.
1015 * For any rational value of the last tab->n_unbounded coordinates
1016 * in the update tableau, the value that is obtained by rounding
1017 * up this value should be contained in the original tableau.
1018 * For any constraint "a x + c >= 0", we therefore need to add
1019 * a constraint "a x + c + s >= 0", with s the sum of all negative
1020 * entries in the last elements of "a U".
1022 * Since we are not interested in the first entries of any of the "a U",
1023 * we first drop the columns of U that correpond to bounded directions.
1025 static int tab_shift_cone(struct isl_tab *tab,
1026 struct isl_tab *tab_cone, struct isl_mat *U)
1028 int i;
1029 isl_int v;
1030 struct isl_basic_set *bset = NULL;
1032 if (tab && tab->n_unbounded == 0) {
1033 isl_mat_free(U);
1034 return 0;
1036 isl_int_init(v);
1037 if (!tab || !tab_cone || !U)
1038 goto error;
1039 bset = isl_tab_peek_bset(tab_cone);
1040 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
1041 for (i = 0; i < bset->n_ineq; ++i) {
1042 int ok;
1043 struct isl_vec *row = NULL;
1044 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
1045 continue;
1046 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
1047 if (!row)
1048 goto error;
1049 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
1050 row = isl_vec_mat_product(row, isl_mat_copy(U));
1051 if (!row)
1052 goto error;
1053 vec_sum_of_neg(row, &v);
1054 isl_vec_free(row);
1055 if (isl_int_is_zero(v))
1056 continue;
1057 tab = isl_tab_extend(tab, 1);
1058 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
1059 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1060 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1061 if (!ok)
1062 goto error;
1065 isl_mat_free(U);
1066 isl_int_clear(v);
1067 return 0;
1068 error:
1069 isl_mat_free(U);
1070 isl_int_clear(v);
1071 return -1;
1074 /* Compute and return an initial basis for the possibly
1075 * unbounded tableau "tab". "tab_cone" is a tableau
1076 * for the corresponding recession cone.
1077 * Additionally, add constraints to "tab" that ensure
1078 * that any rational value for the unbounded directions
1079 * can be rounded up to an integer value.
1081 * If the tableau is bounded, i.e., if the recession cone
1082 * is zero-dimensional, then we just use inital_basis.
1083 * Otherwise, we construct a basis whose first directions
1084 * correspond to equalities, followed by bounded directions,
1085 * i.e., equalities in the recession cone.
1086 * The remaining directions are then unbounded.
1088 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1089 struct isl_tab *tab_cone)
1091 struct isl_mat *eq;
1092 struct isl_mat *cone_eq;
1093 struct isl_mat *U, *Q;
1095 if (!tab || !tab_cone)
1096 return -1;
1098 if (tab_cone->n_col == tab_cone->n_dead) {
1099 tab->basis = initial_basis(tab);
1100 return tab->basis ? 0 : -1;
1103 eq = tab_equalities(tab);
1104 if (!eq)
1105 return -1;
1106 tab->n_zero = eq->n_row;
1107 cone_eq = tab_equalities(tab_cone);
1108 eq = isl_mat_concat(eq, cone_eq);
1109 if (!eq)
1110 return -1;
1111 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1112 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1113 if (!eq)
1114 return -1;
1115 isl_mat_free(eq);
1116 tab->basis = isl_mat_lin_to_aff(Q);
1117 if (tab_shift_cone(tab, tab_cone, U) < 0)
1118 return -1;
1119 if (!tab->basis)
1120 return -1;
1121 return 0;
1124 /* Compute and return a sample point in bset using generalized basis
1125 * reduction. We first check if the input set has a non-trivial
1126 * recession cone. If so, we perform some extra preprocessing in
1127 * sample_with_cone. Otherwise, we directly perform generalized basis
1128 * reduction.
1130 static struct isl_vec *gbr_sample(struct isl_basic_set *bset)
1132 unsigned dim;
1133 struct isl_basic_set *cone;
1135 dim = isl_basic_set_total_dim(bset);
1137 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1138 if (!cone)
1139 goto error;
1141 if (cone->n_eq < dim)
1142 return isl_basic_set_sample_with_cone(bset, cone);
1144 isl_basic_set_free(cone);
1145 return sample_bounded(bset);
1146 error:
1147 isl_basic_set_free(bset);
1148 return NULL;
1151 static struct isl_vec *pip_sample(struct isl_basic_set *bset)
1153 struct isl_mat *T;
1154 struct isl_ctx *ctx;
1155 struct isl_vec *sample;
1157 bset = isl_basic_set_skew_to_positive_orthant(bset, &T);
1158 if (!bset)
1159 return NULL;
1161 ctx = bset->ctx;
1162 sample = isl_pip_basic_set_sample(bset);
1164 if (sample && sample->size != 0)
1165 sample = isl_mat_vec_product(T, sample);
1166 else
1167 isl_mat_free(T);
1169 return sample;
1172 static struct isl_vec *basic_set_sample(struct isl_basic_set *bset, int bounded)
1174 struct isl_ctx *ctx;
1175 unsigned dim;
1176 if (!bset)
1177 return NULL;
1179 ctx = bset->ctx;
1180 if (isl_basic_set_fast_is_empty(bset))
1181 return empty_sample(bset);
1183 dim = isl_basic_set_n_dim(bset);
1184 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1185 isl_assert(ctx, bset->n_div == 0, goto error);
1187 if (bset->sample && bset->sample->size == 1 + dim) {
1188 int contains = isl_basic_set_contains(bset, bset->sample);
1189 if (contains < 0)
1190 goto error;
1191 if (contains) {
1192 struct isl_vec *sample = isl_vec_copy(bset->sample);
1193 isl_basic_set_free(bset);
1194 return sample;
1197 isl_vec_free(bset->sample);
1198 bset->sample = NULL;
1200 if (bset->n_eq > 0)
1201 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1202 : isl_basic_set_sample_vec);
1203 if (dim == 0)
1204 return zero_sample(bset);
1205 if (dim == 1)
1206 return interval_sample(bset);
1208 switch (bset->ctx->opt->ilp_solver) {
1209 case ISL_ILP_PIP:
1210 return pip_sample(bset);
1211 case ISL_ILP_GBR:
1212 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1214 isl_assert(bset->ctx, 0, );
1215 error:
1216 isl_basic_set_free(bset);
1217 return NULL;
1220 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1222 return basic_set_sample(bset, 0);
1225 /* Compute an integer sample in "bset", where the caller guarantees
1226 * that "bset" is bounded.
1228 struct isl_vec *isl_basic_set_sample_bounded(struct isl_basic_set *bset)
1230 return basic_set_sample(bset, 1);
1233 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1235 int i;
1236 int k;
1237 struct isl_basic_set *bset = NULL;
1238 struct isl_ctx *ctx;
1239 unsigned dim;
1241 if (!vec)
1242 return NULL;
1243 ctx = vec->ctx;
1244 isl_assert(ctx, vec->size != 0, goto error);
1246 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1247 if (!bset)
1248 goto error;
1249 dim = isl_basic_set_n_dim(bset);
1250 for (i = dim - 1; i >= 0; --i) {
1251 k = isl_basic_set_alloc_equality(bset);
1252 if (k < 0)
1253 goto error;
1254 isl_seq_clr(bset->eq[k], 1 + dim);
1255 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1256 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1258 bset->sample = vec;
1260 return bset;
1261 error:
1262 isl_basic_set_free(bset);
1263 isl_vec_free(vec);
1264 return NULL;
1267 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1269 struct isl_basic_set *bset;
1270 struct isl_vec *sample_vec;
1272 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1273 sample_vec = isl_basic_set_sample_vec(bset);
1274 if (!sample_vec)
1275 goto error;
1276 if (sample_vec->size == 0) {
1277 struct isl_basic_map *sample;
1278 sample = isl_basic_map_empty_like(bmap);
1279 isl_vec_free(sample_vec);
1280 isl_basic_map_free(bmap);
1281 return sample;
1283 bset = isl_basic_set_from_vec(sample_vec);
1284 return isl_basic_map_overlying_set(bset, bmap);
1285 error:
1286 isl_basic_map_free(bmap);
1287 return NULL;
1290 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1292 int i;
1293 isl_basic_map *sample = NULL;
1295 if (!map)
1296 goto error;
1298 for (i = 0; i < map->n; ++i) {
1299 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1300 if (!sample)
1301 goto error;
1302 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1303 break;
1304 isl_basic_map_free(sample);
1306 if (i == map->n)
1307 sample = isl_basic_map_empty_like_map(map);
1308 isl_map_free(map);
1309 return sample;
1310 error:
1311 isl_map_free(map);
1312 return NULL;
1315 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1317 return (isl_basic_set *) isl_map_sample((isl_map *)set);
1320 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1322 isl_vec *vec;
1323 isl_dim *dim;
1325 dim = isl_basic_set_get_dim(bset);
1326 bset = isl_basic_set_underlying_set(bset);
1327 vec = isl_basic_set_sample_vec(bset);
1329 return isl_point_alloc(dim, vec);
1332 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1334 int i;
1335 isl_point *pnt;
1337 if (!set)
1338 return NULL;
1340 for (i = 0; i < set->n; ++i) {
1341 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1342 if (!pnt)
1343 goto error;
1344 if (!isl_point_is_void(pnt))
1345 break;
1346 isl_point_free(pnt);
1348 if (i == set->n)
1349 pnt = isl_point_void(isl_set_get_dim(set));
1351 isl_set_free(set);
1352 return pnt;
1353 error:
1354 isl_set_free(set);
1355 return NULL;