Merge branch 'maint'
[isl.git] / isl_sample.c
blobec63745e5faf5bf0b3439aaa2b56059e811cec84
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_ctx_private.h>
11 #include <isl_map_private.h>
12 #include "isl_sample.h"
13 #include "isl_sample_piplib.h"
14 #include <isl/vec.h>
15 #include <isl/mat.h>
16 #include <isl/seq.h>
17 #include "isl_equalities.h"
18 #include "isl_tab.h"
19 #include "isl_basis_reduction.h"
20 #include <isl_factorization.h>
21 #include <isl_point_private.h>
22 #include <isl_options_private.h>
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 static struct isl_mat *independent_bounds(struct isl_basic_set *bset)
114 int i, j, n;
115 struct isl_mat *dirs = NULL;
116 struct isl_mat *bounds = NULL;
117 unsigned dim;
119 if (!bset)
120 return NULL;
122 dim = isl_basic_set_n_dim(bset);
123 bounds = isl_mat_alloc(bset->ctx, 1+dim, 1+dim);
124 if (!bounds)
125 return NULL;
127 isl_int_set_si(bounds->row[0][0], 1);
128 isl_seq_clr(bounds->row[0]+1, dim);
129 bounds->n_row = 1;
131 if (bset->n_ineq == 0)
132 return bounds;
134 dirs = isl_mat_alloc(bset->ctx, dim, dim);
135 if (!dirs) {
136 isl_mat_free(bounds);
137 return NULL;
139 isl_seq_cpy(dirs->row[0], bset->ineq[0]+1, dirs->n_col);
140 isl_seq_cpy(bounds->row[1], bset->ineq[0], bounds->n_col);
141 for (j = 1, n = 1; n < dim && j < bset->n_ineq; ++j) {
142 int pos;
144 isl_seq_cpy(dirs->row[n], bset->ineq[j]+1, dirs->n_col);
146 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
147 if (pos < 0)
148 continue;
149 for (i = 0; i < n; ++i) {
150 int pos_i;
151 pos_i = isl_seq_first_non_zero(dirs->row[i], dirs->n_col);
152 if (pos_i < pos)
153 continue;
154 if (pos_i > pos)
155 break;
156 isl_seq_elim(dirs->row[n], dirs->row[i], pos,
157 dirs->n_col, NULL);
158 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
159 if (pos < 0)
160 break;
162 if (pos < 0)
163 continue;
164 if (i < n) {
165 int k;
166 isl_int *t = dirs->row[n];
167 for (k = n; k > i; --k)
168 dirs->row[k] = dirs->row[k-1];
169 dirs->row[i] = t;
171 ++n;
172 isl_seq_cpy(bounds->row[n], bset->ineq[j], bounds->n_col);
174 isl_mat_free(dirs);
175 bounds->n_row = 1+n;
176 return bounds;
179 static void swap_inequality(struct isl_basic_set *bset, int a, int b)
181 isl_int *t = bset->ineq[a];
182 bset->ineq[a] = bset->ineq[b];
183 bset->ineq[b] = t;
186 /* Skew into positive orthant and project out lineality space.
188 * We perform a unimodular transformation that turns a selected
189 * maximal set of linearly independent bounds into constraints
190 * on the first dimensions that impose that these first dimensions
191 * are non-negative. In particular, the constraint matrix is lower
192 * triangular with positive entries on the diagonal and negative
193 * entries below.
194 * If "bset" has a lineality space then these constraints (and therefore
195 * all constraints in bset) only involve the first dimensions.
196 * The remaining dimensions then do not appear in any constraints and
197 * we can select any value for them, say zero. We therefore project
198 * out this final dimensions and plug in the value zero later. This
199 * is accomplished by simply dropping the final columns of
200 * the unimodular transformation.
202 static struct isl_basic_set *isl_basic_set_skew_to_positive_orthant(
203 struct isl_basic_set *bset, struct isl_mat **T)
205 struct isl_mat *U = NULL;
206 struct isl_mat *bounds = NULL;
207 int i, j;
208 unsigned old_dim, new_dim;
210 *T = NULL;
211 if (!bset)
212 return NULL;
214 isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
215 isl_assert(bset->ctx, bset->n_div == 0, goto error);
216 isl_assert(bset->ctx, bset->n_eq == 0, goto error);
218 old_dim = isl_basic_set_n_dim(bset);
219 /* Try to move (multiples of) unit rows up. */
220 for (i = 0, j = 0; i < bset->n_ineq; ++i) {
221 int pos = isl_seq_first_non_zero(bset->ineq[i]+1, old_dim);
222 if (pos < 0)
223 continue;
224 if (isl_seq_first_non_zero(bset->ineq[i]+1+pos+1,
225 old_dim-pos-1) >= 0)
226 continue;
227 if (i != j)
228 swap_inequality(bset, i, j);
229 ++j;
231 bounds = independent_bounds(bset);
232 if (!bounds)
233 goto error;
234 new_dim = bounds->n_row - 1;
235 bounds = isl_mat_left_hermite(bounds, 1, &U, NULL);
236 if (!bounds)
237 goto error;
238 U = isl_mat_drop_cols(U, 1 + new_dim, old_dim - new_dim);
239 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
240 if (!bset)
241 goto error;
242 *T = U;
243 isl_mat_free(bounds);
244 return bset;
245 error:
246 isl_mat_free(bounds);
247 isl_mat_free(U);
248 isl_basic_set_free(bset);
249 return NULL;
252 /* Find a sample integer point, if any, in bset, which is known
253 * to have equalities. If bset contains no integer points, then
254 * return a zero-length vector.
255 * We simply remove the known equalities, compute a sample
256 * in the resulting bset, using the specified recurse function,
257 * and then transform the sample back to the original space.
259 static struct isl_vec *sample_eq(struct isl_basic_set *bset,
260 struct isl_vec *(*recurse)(struct isl_basic_set *))
262 struct isl_mat *T;
263 struct isl_vec *sample;
265 if (!bset)
266 return NULL;
268 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
269 sample = recurse(bset);
270 if (!sample || sample->size == 0)
271 isl_mat_free(T);
272 else
273 sample = isl_mat_vec_product(T, sample);
274 return sample;
277 /* Return a matrix containing the equalities of the tableau
278 * in constraint form. The tableau is assumed to have
279 * an associated bset that has been kept up-to-date.
281 static struct isl_mat *tab_equalities(struct isl_tab *tab)
283 int i, j;
284 int n_eq;
285 struct isl_mat *eq;
286 struct isl_basic_set *bset;
288 if (!tab)
289 return NULL;
291 bset = isl_tab_peek_bset(tab);
292 isl_assert(tab->mat->ctx, bset, return NULL);
294 n_eq = tab->n_var - tab->n_col + tab->n_dead;
295 if (tab->empty || n_eq == 0)
296 return isl_mat_alloc(tab->mat->ctx, 0, tab->n_var);
297 if (n_eq == tab->n_var)
298 return isl_mat_identity(tab->mat->ctx, tab->n_var);
300 eq = isl_mat_alloc(tab->mat->ctx, n_eq, tab->n_var);
301 if (!eq)
302 return NULL;
303 for (i = 0, j = 0; i < tab->n_con; ++i) {
304 if (tab->con[i].is_row)
305 continue;
306 if (tab->con[i].index >= 0 && tab->con[i].index >= tab->n_dead)
307 continue;
308 if (i < bset->n_eq)
309 isl_seq_cpy(eq->row[j], bset->eq[i] + 1, tab->n_var);
310 else
311 isl_seq_cpy(eq->row[j],
312 bset->ineq[i - bset->n_eq] + 1, tab->n_var);
313 ++j;
315 isl_assert(bset->ctx, j == n_eq, goto error);
316 return eq;
317 error:
318 isl_mat_free(eq);
319 return NULL;
322 /* Compute and return an initial basis for the bounded tableau "tab".
324 * If the tableau is either full-dimensional or zero-dimensional,
325 * the we simply return an identity matrix.
326 * Otherwise, we construct a basis whose first directions correspond
327 * to equalities.
329 static struct isl_mat *initial_basis(struct isl_tab *tab)
331 int n_eq;
332 struct isl_mat *eq;
333 struct isl_mat *Q;
335 tab->n_unbounded = 0;
336 tab->n_zero = n_eq = tab->n_var - tab->n_col + tab->n_dead;
337 if (tab->empty || n_eq == 0 || n_eq == tab->n_var)
338 return isl_mat_identity(tab->mat->ctx, 1 + tab->n_var);
340 eq = tab_equalities(tab);
341 eq = isl_mat_left_hermite(eq, 0, NULL, &Q);
342 if (!eq)
343 return NULL;
344 isl_mat_free(eq);
346 Q = isl_mat_lin_to_aff(Q);
347 return Q;
350 /* Given a tableau representing a set, find and return
351 * an integer point in the set, if there is any.
353 * We perform a depth first search
354 * for an integer point, by scanning all possible values in the range
355 * attained by a basis vector, where an initial basis may have been set
356 * by the calling function. Otherwise an initial basis that exploits
357 * the equalities in the tableau is created.
358 * tab->n_zero is currently ignored and is clobbered by this function.
360 * The tableau is allowed to have unbounded direction, but then
361 * the calling function needs to set an initial basis, with the
362 * unbounded directions last and with tab->n_unbounded set
363 * to the number of unbounded directions.
364 * Furthermore, the calling functions needs to add shifted copies
365 * of all constraints involving unbounded directions to ensure
366 * that any feasible rational value in these directions can be rounded
367 * up to yield a feasible integer value.
368 * In particular, let B define the given basis x' = B x
369 * and let T be the inverse of B, i.e., X = T x'.
370 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
371 * or a T x' + c >= 0 in terms of the given basis. Assume that
372 * the bounded directions have an integer value, then we can safely
373 * round up the values for the unbounded directions if we make sure
374 * that x' not only satisfies the original constraint, but also
375 * the constraint "a T x' + c + s >= 0" with s the sum of all
376 * negative values in the last n_unbounded entries of "a T".
377 * The calling function therefore needs to add the constraint
378 * a x + c + s >= 0. The current function then scans the first
379 * directions for an integer value and once those have been found,
380 * it can compute "T ceil(B x)" to yield an integer point in the set.
381 * Note that during the search, the first rows of B may be changed
382 * by a basis reduction, but the last n_unbounded rows of B remain
383 * unaltered and are also not mixed into the first rows.
385 * The search is implemented iteratively. "level" identifies the current
386 * basis vector. "init" is true if we want the first value at the current
387 * level and false if we want the next value.
389 * The initial basis is the identity matrix. If the range in some direction
390 * contains more than one integer value, we perform basis reduction based
391 * on the value of ctx->opt->gbr
392 * - ISL_GBR_NEVER: never perform basis reduction
393 * - ISL_GBR_ONCE: only perform basis reduction the first
394 * time such a range is encountered
395 * - ISL_GBR_ALWAYS: always perform basis reduction when
396 * such a range is encountered
398 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
399 * reduction computation to return early. That is, as soon as it
400 * finds a reasonable first direction.
402 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
404 unsigned dim;
405 unsigned gbr;
406 struct isl_ctx *ctx;
407 struct isl_vec *sample;
408 struct isl_vec *min;
409 struct isl_vec *max;
410 enum isl_lp_result res;
411 int level;
412 int init;
413 int reduced;
414 struct isl_tab_undo **snap;
416 if (!tab)
417 return NULL;
418 if (tab->empty)
419 return isl_vec_alloc(tab->mat->ctx, 0);
421 if (!tab->basis)
422 tab->basis = initial_basis(tab);
423 if (!tab->basis)
424 return NULL;
425 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
426 return NULL);
427 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
428 return NULL);
430 ctx = tab->mat->ctx;
431 dim = tab->n_var;
432 gbr = ctx->opt->gbr;
434 if (tab->n_unbounded == tab->n_var) {
435 sample = isl_tab_get_sample_value(tab);
436 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
437 sample = isl_vec_ceil(sample);
438 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
439 sample);
440 return sample;
443 if (isl_tab_extend_cons(tab, dim + 1) < 0)
444 return NULL;
446 min = isl_vec_alloc(ctx, dim);
447 max = isl_vec_alloc(ctx, dim);
448 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
450 if (!min || !max || !snap)
451 goto error;
453 level = 0;
454 init = 1;
455 reduced = 0;
457 while (level >= 0) {
458 int empty = 0;
459 if (init) {
460 res = isl_tab_min(tab, tab->basis->row[1 + level],
461 ctx->one, &min->el[level], NULL, 0);
462 if (res == isl_lp_empty)
463 empty = 1;
464 isl_assert(ctx, res != isl_lp_unbounded, goto error);
465 if (res == isl_lp_error)
466 goto error;
467 if (!empty && isl_tab_sample_is_integer(tab))
468 break;
469 isl_seq_neg(tab->basis->row[1 + level] + 1,
470 tab->basis->row[1 + level] + 1, dim);
471 res = isl_tab_min(tab, tab->basis->row[1 + level],
472 ctx->one, &max->el[level], NULL, 0);
473 isl_seq_neg(tab->basis->row[1 + level] + 1,
474 tab->basis->row[1 + level] + 1, dim);
475 isl_int_neg(max->el[level], max->el[level]);
476 if (res == isl_lp_empty)
477 empty = 1;
478 isl_assert(ctx, res != isl_lp_unbounded, goto error);
479 if (res == isl_lp_error)
480 goto error;
481 if (!empty && isl_tab_sample_is_integer(tab))
482 break;
483 if (!empty && !reduced &&
484 ctx->opt->gbr != ISL_GBR_NEVER &&
485 isl_int_lt(min->el[level], max->el[level])) {
486 unsigned gbr_only_first;
487 if (ctx->opt->gbr == ISL_GBR_ONCE)
488 ctx->opt->gbr = ISL_GBR_NEVER;
489 tab->n_zero = level;
490 gbr_only_first = ctx->opt->gbr_only_first;
491 ctx->opt->gbr_only_first =
492 ctx->opt->gbr == ISL_GBR_ALWAYS;
493 tab = isl_tab_compute_reduced_basis(tab);
494 ctx->opt->gbr_only_first = gbr_only_first;
495 if (!tab || !tab->basis)
496 goto error;
497 reduced = 1;
498 continue;
500 reduced = 0;
501 snap[level] = isl_tab_snap(tab);
502 } else
503 isl_int_add_ui(min->el[level], min->el[level], 1);
505 if (empty || isl_int_gt(min->el[level], max->el[level])) {
506 level--;
507 init = 0;
508 if (level >= 0)
509 if (isl_tab_rollback(tab, snap[level]) < 0)
510 goto error;
511 continue;
513 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
514 if (isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]) < 0)
515 goto error;
516 isl_int_set_si(tab->basis->row[1 + level][0], 0);
517 if (level + tab->n_unbounded < dim - 1) {
518 ++level;
519 init = 1;
520 continue;
522 break;
525 if (level >= 0) {
526 sample = isl_tab_get_sample_value(tab);
527 if (!sample)
528 goto error;
529 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
530 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
531 sample);
532 sample = isl_vec_ceil(sample);
533 sample = isl_mat_vec_inverse_product(
534 isl_mat_copy(tab->basis), sample);
536 } else
537 sample = isl_vec_alloc(ctx, 0);
539 ctx->opt->gbr = gbr;
540 isl_vec_free(min);
541 isl_vec_free(max);
542 free(snap);
543 return sample;
544 error:
545 ctx->opt->gbr = gbr;
546 isl_vec_free(min);
547 isl_vec_free(max);
548 free(snap);
549 return NULL;
552 static struct isl_vec *sample_bounded(struct isl_basic_set *bset);
554 /* Compute a sample point of the given basic set, based on the given,
555 * non-trivial factorization.
557 static __isl_give isl_vec *factored_sample(__isl_take isl_basic_set *bset,
558 __isl_take isl_factorizer *f)
560 int i, n;
561 isl_vec *sample = NULL;
562 isl_ctx *ctx;
563 unsigned nparam;
564 unsigned nvar;
566 ctx = isl_basic_set_get_ctx(bset);
567 if (!ctx)
568 goto error;
570 nparam = isl_basic_set_dim(bset, isl_dim_param);
571 nvar = isl_basic_set_dim(bset, isl_dim_set);
573 sample = isl_vec_alloc(ctx, 1 + isl_basic_set_total_dim(bset));
574 if (!sample)
575 goto error;
576 isl_int_set_si(sample->el[0], 1);
578 bset = isl_morph_basic_set(isl_morph_copy(f->morph), bset);
580 for (i = 0, n = 0; i < f->n_group; ++i) {
581 isl_basic_set *bset_i;
582 isl_vec *sample_i;
584 bset_i = isl_basic_set_copy(bset);
585 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
586 nparam + n + f->len[i], nvar - n - f->len[i]);
587 bset_i = isl_basic_set_drop_constraints_involving(bset_i,
588 nparam, n);
589 bset_i = isl_basic_set_drop(bset_i, isl_dim_set,
590 n + f->len[i], nvar - n - f->len[i]);
591 bset_i = isl_basic_set_drop(bset_i, isl_dim_set, 0, n);
593 sample_i = sample_bounded(bset_i);
594 if (!sample_i)
595 goto error;
596 if (sample_i->size == 0) {
597 isl_basic_set_free(bset);
598 isl_factorizer_free(f);
599 isl_vec_free(sample);
600 return sample_i;
602 isl_seq_cpy(sample->el + 1 + nparam + n,
603 sample_i->el + 1, f->len[i]);
604 isl_vec_free(sample_i);
606 n += f->len[i];
609 f->morph = isl_morph_inverse(f->morph);
610 sample = isl_morph_vec(isl_morph_copy(f->morph), sample);
612 isl_basic_set_free(bset);
613 isl_factorizer_free(f);
614 return sample;
615 error:
616 isl_basic_set_free(bset);
617 isl_factorizer_free(f);
618 isl_vec_free(sample);
619 return NULL;
622 /* Given a basic set that is known to be bounded, find and return
623 * an integer point in the basic set, if there is any.
625 * After handling some trivial cases, we construct a tableau
626 * and then use isl_tab_sample to find a sample, passing it
627 * the identity matrix as initial basis.
629 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
631 unsigned dim;
632 struct isl_ctx *ctx;
633 struct isl_vec *sample;
634 struct isl_tab *tab = NULL;
635 isl_factorizer *f;
637 if (!bset)
638 return NULL;
640 if (isl_basic_set_plain_is_empty(bset))
641 return empty_sample(bset);
643 dim = isl_basic_set_total_dim(bset);
644 if (dim == 0)
645 return zero_sample(bset);
646 if (dim == 1)
647 return interval_sample(bset);
648 if (bset->n_eq > 0)
649 return sample_eq(bset, sample_bounded);
651 f = isl_basic_set_factorizer(bset);
652 if (!f)
653 goto error;
654 if (f->n_group != 0)
655 return factored_sample(bset, f);
656 isl_factorizer_free(f);
658 ctx = bset->ctx;
660 tab = isl_tab_from_basic_set(bset);
661 if (tab && tab->empty) {
662 isl_tab_free(tab);
663 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
664 sample = isl_vec_alloc(bset->ctx, 0);
665 isl_basic_set_free(bset);
666 return sample;
669 if (isl_tab_track_bset(tab, isl_basic_set_copy(bset)) < 0)
670 goto error;
671 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
672 if (isl_tab_detect_implicit_equalities(tab) < 0)
673 goto error;
675 sample = isl_tab_sample(tab);
676 if (!sample)
677 goto error;
679 if (sample->size > 0) {
680 isl_vec_free(bset->sample);
681 bset->sample = isl_vec_copy(sample);
684 isl_basic_set_free(bset);
685 isl_tab_free(tab);
686 return sample;
687 error:
688 isl_basic_set_free(bset);
689 isl_tab_free(tab);
690 return NULL;
693 /* Given a basic set "bset" and a value "sample" for the first coordinates
694 * of bset, plug in these values and drop the corresponding coordinates.
696 * We do this by computing the preimage of the transformation
698 * [ 1 0 ]
699 * x = [ s 0 ] x'
700 * [ 0 I ]
702 * where [1 s] is the sample value and I is the identity matrix of the
703 * appropriate dimension.
705 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
706 struct isl_vec *sample)
708 int i;
709 unsigned total;
710 struct isl_mat *T;
712 if (!bset || !sample)
713 goto error;
715 total = isl_basic_set_total_dim(bset);
716 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
717 if (!T)
718 goto error;
720 for (i = 0; i < sample->size; ++i) {
721 isl_int_set(T->row[i][0], sample->el[i]);
722 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
724 for (i = 0; i < T->n_col - 1; ++i) {
725 isl_seq_clr(T->row[sample->size + i], T->n_col);
726 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
728 isl_vec_free(sample);
730 bset = isl_basic_set_preimage(bset, T);
731 return bset;
732 error:
733 isl_basic_set_free(bset);
734 isl_vec_free(sample);
735 return NULL;
738 /* Given a basic set "bset", return any (possibly non-integer) point
739 * in the basic set.
741 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
743 struct isl_tab *tab;
744 struct isl_vec *sample;
746 if (!bset)
747 return NULL;
749 tab = isl_tab_from_basic_set(bset);
750 sample = isl_tab_get_sample_value(tab);
751 isl_tab_free(tab);
753 isl_basic_set_free(bset);
755 return sample;
758 /* Given a linear cone "cone" and a rational point "vec",
759 * construct a polyhedron with shifted copies of the constraints in "cone",
760 * i.e., a polyhedron with "cone" as its recession cone, such that each
761 * point x in this polyhedron is such that the unit box positioned at x
762 * lies entirely inside the affine cone 'vec + cone'.
763 * Any rational point in this polyhedron may therefore be rounded up
764 * to yield an integer point that lies inside said affine cone.
766 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
767 * point "vec" by v/d.
768 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
769 * by <a_i, x> - b/d >= 0.
770 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
771 * We prefer this polyhedron over the actual affine cone because it doesn't
772 * require a scaling of the constraints.
773 * If each of the vertices of the unit cube positioned at x lies inside
774 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
775 * We therefore impose that x' = x + \sum e_i, for any selection of unit
776 * vectors lies inside the polyhedron, i.e.,
778 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
780 * The most stringent of these constraints is the one that selects
781 * all negative a_i, so the polyhedron we are looking for has constraints
783 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
785 * Note that if cone were known to have only non-negative rays
786 * (which can be accomplished by a unimodular transformation),
787 * then we would only have to check the points x' = x + e_i
788 * and we only have to add the smallest negative a_i (if any)
789 * instead of the sum of all negative a_i.
791 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
792 struct isl_vec *vec)
794 int i, j, k;
795 unsigned total;
797 struct isl_basic_set *shift = NULL;
799 if (!cone || !vec)
800 goto error;
802 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
804 total = isl_basic_set_total_dim(cone);
806 shift = isl_basic_set_alloc_space(isl_basic_set_get_space(cone),
807 0, 0, cone->n_ineq);
809 for (i = 0; i < cone->n_ineq; ++i) {
810 k = isl_basic_set_alloc_inequality(shift);
811 if (k < 0)
812 goto error;
813 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
814 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
815 &shift->ineq[k][0]);
816 isl_int_cdiv_q(shift->ineq[k][0],
817 shift->ineq[k][0], vec->el[0]);
818 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
819 for (j = 0; j < total; ++j) {
820 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
821 continue;
822 isl_int_add(shift->ineq[k][0],
823 shift->ineq[k][0], shift->ineq[k][1 + j]);
827 isl_basic_set_free(cone);
828 isl_vec_free(vec);
830 return isl_basic_set_finalize(shift);
831 error:
832 isl_basic_set_free(shift);
833 isl_basic_set_free(cone);
834 isl_vec_free(vec);
835 return NULL;
838 /* Given a rational point vec in a (transformed) basic set,
839 * such that cone is the recession cone of the original basic set,
840 * "round up" the rational point to an integer point.
842 * We first check if the rational point just happens to be integer.
843 * If not, we transform the cone in the same way as the basic set,
844 * pick a point x in this cone shifted to the rational point such that
845 * the whole unit cube at x is also inside this affine cone.
846 * Then we simply round up the coordinates of x and return the
847 * resulting integer point.
849 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
850 struct isl_basic_set *cone, struct isl_mat *U)
852 unsigned total;
854 if (!vec || !cone || !U)
855 goto error;
857 isl_assert(vec->ctx, vec->size != 0, goto error);
858 if (isl_int_is_one(vec->el[0])) {
859 isl_mat_free(U);
860 isl_basic_set_free(cone);
861 return vec;
864 total = isl_basic_set_total_dim(cone);
865 cone = isl_basic_set_preimage(cone, U);
866 cone = isl_basic_set_remove_dims(cone, isl_dim_set,
867 0, total - (vec->size - 1));
869 cone = shift_cone(cone, vec);
871 vec = rational_sample(cone);
872 vec = isl_vec_ceil(vec);
873 return vec;
874 error:
875 isl_mat_free(U);
876 isl_vec_free(vec);
877 isl_basic_set_free(cone);
878 return NULL;
881 /* Concatenate two integer vectors, i.e., two vectors with denominator
882 * (stored in element 0) equal to 1.
884 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
886 struct isl_vec *vec;
888 if (!vec1 || !vec2)
889 goto error;
890 isl_assert(vec1->ctx, vec1->size > 0, goto error);
891 isl_assert(vec2->ctx, vec2->size > 0, goto error);
892 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
893 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
895 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
896 if (!vec)
897 goto error;
899 isl_seq_cpy(vec->el, vec1->el, vec1->size);
900 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
902 isl_vec_free(vec1);
903 isl_vec_free(vec2);
905 return vec;
906 error:
907 isl_vec_free(vec1);
908 isl_vec_free(vec2);
909 return NULL;
912 /* Give a basic set "bset" with recession cone "cone", compute and
913 * return an integer point in bset, if any.
915 * If the recession cone is full-dimensional, then we know that
916 * bset contains an infinite number of integer points and it is
917 * fairly easy to pick one of them.
918 * If the recession cone is not full-dimensional, then we first
919 * transform bset such that the bounded directions appear as
920 * the first dimensions of the transformed basic set.
921 * We do this by using a unimodular transformation that transforms
922 * the equalities in the recession cone to equalities on the first
923 * dimensions.
925 * The transformed set is then projected onto its bounded dimensions.
926 * Note that to compute this projection, we can simply drop all constraints
927 * involving any of the unbounded dimensions since these constraints
928 * cannot be combined to produce a constraint on the bounded dimensions.
929 * To see this, assume that there is such a combination of constraints
930 * that produces a constraint on the bounded dimensions. This means
931 * that some combination of the unbounded dimensions has both an upper
932 * bound and a lower bound in terms of the bounded dimensions, but then
933 * this combination would be a bounded direction too and would have been
934 * transformed into a bounded dimensions.
936 * We then compute a sample value in the bounded dimensions.
937 * If no such value can be found, then the original set did not contain
938 * any integer points and we are done.
939 * Otherwise, we plug in the value we found in the bounded dimensions,
940 * project out these bounded dimensions and end up with a set with
941 * a full-dimensional recession cone.
942 * A sample point in this set is computed by "rounding up" any
943 * rational point in the set.
945 * The sample points in the bounded and unbounded dimensions are
946 * then combined into a single sample point and transformed back
947 * to the original space.
949 __isl_give isl_vec *isl_basic_set_sample_with_cone(
950 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
952 unsigned total;
953 unsigned cone_dim;
954 struct isl_mat *M, *U;
955 struct isl_vec *sample;
956 struct isl_vec *cone_sample;
957 struct isl_ctx *ctx;
958 struct isl_basic_set *bounded;
960 if (!bset || !cone)
961 goto error;
963 ctx = bset->ctx;
964 total = isl_basic_set_total_dim(cone);
965 cone_dim = total - cone->n_eq;
967 M = isl_mat_sub_alloc6(bset->ctx, cone->eq, 0, cone->n_eq, 1, total);
968 M = isl_mat_left_hermite(M, 0, &U, NULL);
969 if (!M)
970 goto error;
971 isl_mat_free(M);
973 U = isl_mat_lin_to_aff(U);
974 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
976 bounded = isl_basic_set_copy(bset);
977 bounded = isl_basic_set_drop_constraints_involving(bounded,
978 total - cone_dim, cone_dim);
979 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
980 sample = sample_bounded(bounded);
981 if (!sample || sample->size == 0) {
982 isl_basic_set_free(bset);
983 isl_basic_set_free(cone);
984 isl_mat_free(U);
985 return sample;
987 bset = plug_in(bset, isl_vec_copy(sample));
988 cone_sample = rational_sample(bset);
989 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
990 sample = vec_concat(sample, cone_sample);
991 sample = isl_mat_vec_product(U, sample);
992 return sample;
993 error:
994 isl_basic_set_free(cone);
995 isl_basic_set_free(bset);
996 return NULL;
999 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
1001 int i;
1003 isl_int_set_si(*s, 0);
1005 for (i = 0; i < v->size; ++i)
1006 if (isl_int_is_neg(v->el[i]))
1007 isl_int_add(*s, *s, v->el[i]);
1010 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
1011 * to the recession cone and the inverse of a new basis U = inv(B),
1012 * with the unbounded directions in B last,
1013 * add constraints to "tab" that ensure any rational value
1014 * in the unbounded directions can be rounded up to an integer value.
1016 * The new basis is given by x' = B x, i.e., x = U x'.
1017 * For any rational value of the last tab->n_unbounded coordinates
1018 * in the update tableau, the value that is obtained by rounding
1019 * up this value should be contained in the original tableau.
1020 * For any constraint "a x + c >= 0", we therefore need to add
1021 * a constraint "a x + c + s >= 0", with s the sum of all negative
1022 * entries in the last elements of "a U".
1024 * Since we are not interested in the first entries of any of the "a U",
1025 * we first drop the columns of U that correpond to bounded directions.
1027 static int tab_shift_cone(struct isl_tab *tab,
1028 struct isl_tab *tab_cone, struct isl_mat *U)
1030 int i;
1031 isl_int v;
1032 struct isl_basic_set *bset = NULL;
1034 if (tab && tab->n_unbounded == 0) {
1035 isl_mat_free(U);
1036 return 0;
1038 isl_int_init(v);
1039 if (!tab || !tab_cone || !U)
1040 goto error;
1041 bset = isl_tab_peek_bset(tab_cone);
1042 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
1043 for (i = 0; i < bset->n_ineq; ++i) {
1044 int ok;
1045 struct isl_vec *row = NULL;
1046 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
1047 continue;
1048 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
1049 if (!row)
1050 goto error;
1051 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
1052 row = isl_vec_mat_product(row, isl_mat_copy(U));
1053 if (!row)
1054 goto error;
1055 vec_sum_of_neg(row, &v);
1056 isl_vec_free(row);
1057 if (isl_int_is_zero(v))
1058 continue;
1059 tab = isl_tab_extend(tab, 1);
1060 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
1061 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1062 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1063 if (!ok)
1064 goto error;
1067 isl_mat_free(U);
1068 isl_int_clear(v);
1069 return 0;
1070 error:
1071 isl_mat_free(U);
1072 isl_int_clear(v);
1073 return -1;
1076 /* Compute and return an initial basis for the possibly
1077 * unbounded tableau "tab". "tab_cone" is a tableau
1078 * for the corresponding recession cone.
1079 * Additionally, add constraints to "tab" that ensure
1080 * that any rational value for the unbounded directions
1081 * can be rounded up to an integer value.
1083 * If the tableau is bounded, i.e., if the recession cone
1084 * is zero-dimensional, then we just use inital_basis.
1085 * Otherwise, we construct a basis whose first directions
1086 * correspond to equalities, followed by bounded directions,
1087 * i.e., equalities in the recession cone.
1088 * The remaining directions are then unbounded.
1090 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1091 struct isl_tab *tab_cone)
1093 struct isl_mat *eq;
1094 struct isl_mat *cone_eq;
1095 struct isl_mat *U, *Q;
1097 if (!tab || !tab_cone)
1098 return -1;
1100 if (tab_cone->n_col == tab_cone->n_dead) {
1101 tab->basis = initial_basis(tab);
1102 return tab->basis ? 0 : -1;
1105 eq = tab_equalities(tab);
1106 if (!eq)
1107 return -1;
1108 tab->n_zero = eq->n_row;
1109 cone_eq = tab_equalities(tab_cone);
1110 eq = isl_mat_concat(eq, cone_eq);
1111 if (!eq)
1112 return -1;
1113 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1114 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1115 if (!eq)
1116 return -1;
1117 isl_mat_free(eq);
1118 tab->basis = isl_mat_lin_to_aff(Q);
1119 if (tab_shift_cone(tab, tab_cone, U) < 0)
1120 return -1;
1121 if (!tab->basis)
1122 return -1;
1123 return 0;
1126 /* Compute and return a sample point in bset using generalized basis
1127 * reduction. We first check if the input set has a non-trivial
1128 * recession cone. If so, we perform some extra preprocessing in
1129 * sample_with_cone. Otherwise, we directly perform generalized basis
1130 * reduction.
1132 static struct isl_vec *gbr_sample(struct isl_basic_set *bset)
1134 unsigned dim;
1135 struct isl_basic_set *cone;
1137 dim = isl_basic_set_total_dim(bset);
1139 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1140 if (!cone)
1141 goto error;
1143 if (cone->n_eq < dim)
1144 return isl_basic_set_sample_with_cone(bset, cone);
1146 isl_basic_set_free(cone);
1147 return sample_bounded(bset);
1148 error:
1149 isl_basic_set_free(bset);
1150 return NULL;
1153 static struct isl_vec *pip_sample(struct isl_basic_set *bset)
1155 struct isl_mat *T;
1156 struct isl_ctx *ctx;
1157 struct isl_vec *sample;
1159 bset = isl_basic_set_skew_to_positive_orthant(bset, &T);
1160 if (!bset)
1161 return NULL;
1163 ctx = bset->ctx;
1164 sample = isl_pip_basic_set_sample(bset);
1166 if (sample && sample->size != 0)
1167 sample = isl_mat_vec_product(T, sample);
1168 else
1169 isl_mat_free(T);
1171 return sample;
1174 static struct isl_vec *basic_set_sample(struct isl_basic_set *bset, int bounded)
1176 struct isl_ctx *ctx;
1177 unsigned dim;
1178 if (!bset)
1179 return NULL;
1181 ctx = bset->ctx;
1182 if (isl_basic_set_plain_is_empty(bset))
1183 return empty_sample(bset);
1185 dim = isl_basic_set_n_dim(bset);
1186 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1187 isl_assert(ctx, bset->n_div == 0, goto error);
1189 if (bset->sample && bset->sample->size == 1 + dim) {
1190 int contains = isl_basic_set_contains(bset, bset->sample);
1191 if (contains < 0)
1192 goto error;
1193 if (contains) {
1194 struct isl_vec *sample = isl_vec_copy(bset->sample);
1195 isl_basic_set_free(bset);
1196 return sample;
1199 isl_vec_free(bset->sample);
1200 bset->sample = NULL;
1202 if (bset->n_eq > 0)
1203 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1204 : isl_basic_set_sample_vec);
1205 if (dim == 0)
1206 return zero_sample(bset);
1207 if (dim == 1)
1208 return interval_sample(bset);
1210 switch (bset->ctx->opt->ilp_solver) {
1211 case ISL_ILP_PIP:
1212 return pip_sample(bset);
1213 case ISL_ILP_GBR:
1214 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1216 isl_assert(bset->ctx, 0, );
1217 error:
1218 isl_basic_set_free(bset);
1219 return NULL;
1222 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1224 return basic_set_sample(bset, 0);
1227 /* Compute an integer sample in "bset", where the caller guarantees
1228 * that "bset" is bounded.
1230 struct isl_vec *isl_basic_set_sample_bounded(struct isl_basic_set *bset)
1232 return basic_set_sample(bset, 1);
1235 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1237 int i;
1238 int k;
1239 struct isl_basic_set *bset = NULL;
1240 struct isl_ctx *ctx;
1241 unsigned dim;
1243 if (!vec)
1244 return NULL;
1245 ctx = vec->ctx;
1246 isl_assert(ctx, vec->size != 0, goto error);
1248 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1249 if (!bset)
1250 goto error;
1251 dim = isl_basic_set_n_dim(bset);
1252 for (i = dim - 1; i >= 0; --i) {
1253 k = isl_basic_set_alloc_equality(bset);
1254 if (k < 0)
1255 goto error;
1256 isl_seq_clr(bset->eq[k], 1 + dim);
1257 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1258 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1260 bset->sample = vec;
1262 return bset;
1263 error:
1264 isl_basic_set_free(bset);
1265 isl_vec_free(vec);
1266 return NULL;
1269 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1271 struct isl_basic_set *bset;
1272 struct isl_vec *sample_vec;
1274 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1275 sample_vec = isl_basic_set_sample_vec(bset);
1276 if (!sample_vec)
1277 goto error;
1278 if (sample_vec->size == 0) {
1279 struct isl_basic_map *sample;
1280 sample = isl_basic_map_empty_like(bmap);
1281 isl_vec_free(sample_vec);
1282 isl_basic_map_free(bmap);
1283 return sample;
1285 bset = isl_basic_set_from_vec(sample_vec);
1286 return isl_basic_map_overlying_set(bset, bmap);
1287 error:
1288 isl_basic_map_free(bmap);
1289 return NULL;
1292 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1294 int i;
1295 isl_basic_map *sample = NULL;
1297 if (!map)
1298 goto error;
1300 for (i = 0; i < map->n; ++i) {
1301 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1302 if (!sample)
1303 goto error;
1304 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1305 break;
1306 isl_basic_map_free(sample);
1308 if (i == map->n)
1309 sample = isl_basic_map_empty_like_map(map);
1310 isl_map_free(map);
1311 return sample;
1312 error:
1313 isl_map_free(map);
1314 return NULL;
1317 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1319 return (isl_basic_set *) isl_map_sample((isl_map *)set);
1322 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1324 isl_vec *vec;
1325 isl_space *dim;
1327 dim = isl_basic_set_get_space(bset);
1328 bset = isl_basic_set_underlying_set(bset);
1329 vec = isl_basic_set_sample_vec(bset);
1331 return isl_point_alloc(dim, vec);
1334 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1336 int i;
1337 isl_point *pnt;
1339 if (!set)
1340 return NULL;
1342 for (i = 0; i < set->n; ++i) {
1343 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1344 if (!pnt)
1345 goto error;
1346 if (!isl_point_is_void(pnt))
1347 break;
1348 isl_point_free(pnt);
1350 if (i == set->n)
1351 pnt = isl_point_void(isl_set_get_space(set));
1353 isl_set_free(set);
1354 return pnt;
1355 error:
1356 isl_set_free(set);
1357 return NULL;