isl_map_subtract.c: tab_add_constraints: avoid NULL pointer dereference
[isl.git] / isl_sample.c
blob8a99d7e1fc769e46e246726d3b471cffc40dc971
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_sample.h"
11 #include "isl_sample_piplib.h"
12 #include "isl_vec.h"
13 #include "isl_mat.h"
14 #include "isl_seq.h"
15 #include "isl_map_private.h"
16 #include "isl_equalities.h"
17 #include "isl_tab.h"
18 #include "isl_basis_reduction.h"
19 #include <isl_point_private.h>
21 static struct isl_vec *empty_sample(struct isl_basic_set *bset)
23 struct isl_vec *vec;
25 vec = isl_vec_alloc(bset->ctx, 0);
26 isl_basic_set_free(bset);
27 return vec;
30 /* Construct a zero sample of the same dimension as bset.
31 * As a special case, if bset is zero-dimensional, this
32 * function creates a zero-dimensional sample point.
34 static struct isl_vec *zero_sample(struct isl_basic_set *bset)
36 unsigned dim;
37 struct isl_vec *sample;
39 dim = isl_basic_set_total_dim(bset);
40 sample = isl_vec_alloc(bset->ctx, 1 + dim);
41 if (sample) {
42 isl_int_set_si(sample->el[0], 1);
43 isl_seq_clr(sample->el + 1, dim);
45 isl_basic_set_free(bset);
46 return sample;
49 static struct isl_vec *interval_sample(struct isl_basic_set *bset)
51 int i;
52 isl_int t;
53 struct isl_vec *sample;
55 bset = isl_basic_set_simplify(bset);
56 if (!bset)
57 return NULL;
58 if (isl_basic_set_fast_is_empty(bset))
59 return empty_sample(bset);
60 if (bset->n_eq == 0 && bset->n_ineq == 0)
61 return zero_sample(bset);
63 sample = isl_vec_alloc(bset->ctx, 2);
64 if (!sample)
65 goto error;
66 if (!bset)
67 return NULL;
68 isl_int_set_si(sample->block.data[0], 1);
70 if (bset->n_eq > 0) {
71 isl_assert(bset->ctx, bset->n_eq == 1, goto error);
72 isl_assert(bset->ctx, bset->n_ineq == 0, goto error);
73 if (isl_int_is_one(bset->eq[0][1]))
74 isl_int_neg(sample->el[1], bset->eq[0][0]);
75 else {
76 isl_assert(bset->ctx, isl_int_is_negone(bset->eq[0][1]),
77 goto error);
78 isl_int_set(sample->el[1], bset->eq[0][0]);
80 isl_basic_set_free(bset);
81 return sample;
84 isl_int_init(t);
85 if (isl_int_is_one(bset->ineq[0][1]))
86 isl_int_neg(sample->block.data[1], bset->ineq[0][0]);
87 else
88 isl_int_set(sample->block.data[1], bset->ineq[0][0]);
89 for (i = 1; i < bset->n_ineq; ++i) {
90 isl_seq_inner_product(sample->block.data,
91 bset->ineq[i], 2, &t);
92 if (isl_int_is_neg(t))
93 break;
95 isl_int_clear(t);
96 if (i < bset->n_ineq) {
97 isl_vec_free(sample);
98 return empty_sample(bset);
101 isl_basic_set_free(bset);
102 return sample;
103 error:
104 isl_basic_set_free(bset);
105 isl_vec_free(sample);
106 return NULL;
109 static struct isl_mat *independent_bounds(struct isl_basic_set *bset)
111 int i, j, n;
112 struct isl_mat *dirs = NULL;
113 struct isl_mat *bounds = NULL;
114 unsigned dim;
116 if (!bset)
117 return NULL;
119 dim = isl_basic_set_n_dim(bset);
120 bounds = isl_mat_alloc(bset->ctx, 1+dim, 1+dim);
121 if (!bounds)
122 return NULL;
124 isl_int_set_si(bounds->row[0][0], 1);
125 isl_seq_clr(bounds->row[0]+1, dim);
126 bounds->n_row = 1;
128 if (bset->n_ineq == 0)
129 return bounds;
131 dirs = isl_mat_alloc(bset->ctx, dim, dim);
132 if (!dirs) {
133 isl_mat_free(bounds);
134 return NULL;
136 isl_seq_cpy(dirs->row[0], bset->ineq[0]+1, dirs->n_col);
137 isl_seq_cpy(bounds->row[1], bset->ineq[0], bounds->n_col);
138 for (j = 1, n = 1; n < dim && j < bset->n_ineq; ++j) {
139 int pos;
141 isl_seq_cpy(dirs->row[n], bset->ineq[j]+1, dirs->n_col);
143 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
144 if (pos < 0)
145 continue;
146 for (i = 0; i < n; ++i) {
147 int pos_i;
148 pos_i = isl_seq_first_non_zero(dirs->row[i], dirs->n_col);
149 if (pos_i < pos)
150 continue;
151 if (pos_i > pos)
152 break;
153 isl_seq_elim(dirs->row[n], dirs->row[i], pos,
154 dirs->n_col, NULL);
155 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
156 if (pos < 0)
157 break;
159 if (pos < 0)
160 continue;
161 if (i < n) {
162 int k;
163 isl_int *t = dirs->row[n];
164 for (k = n; k > i; --k)
165 dirs->row[k] = dirs->row[k-1];
166 dirs->row[i] = t;
168 ++n;
169 isl_seq_cpy(bounds->row[n], bset->ineq[j], bounds->n_col);
171 isl_mat_free(dirs);
172 bounds->n_row = 1+n;
173 return bounds;
176 static void swap_inequality(struct isl_basic_set *bset, int a, int b)
178 isl_int *t = bset->ineq[a];
179 bset->ineq[a] = bset->ineq[b];
180 bset->ineq[b] = t;
183 /* Skew into positive orthant and project out lineality space.
185 * We perform a unimodular transformation that turns a selected
186 * maximal set of linearly independent bounds into constraints
187 * on the first dimensions that impose that these first dimensions
188 * are non-negative. In particular, the constraint matrix is lower
189 * triangular with positive entries on the diagonal and negative
190 * entries below.
191 * If "bset" has a lineality space then these constraints (and therefore
192 * all constraints in bset) only involve the first dimensions.
193 * The remaining dimensions then do not appear in any constraints and
194 * we can select any value for them, say zero. We therefore project
195 * out this final dimensions and plug in the value zero later. This
196 * is accomplished by simply dropping the final columns of
197 * the unimodular transformation.
199 static struct isl_basic_set *isl_basic_set_skew_to_positive_orthant(
200 struct isl_basic_set *bset, struct isl_mat **T)
202 struct isl_mat *U = NULL;
203 struct isl_mat *bounds = NULL;
204 int i, j;
205 unsigned old_dim, new_dim;
207 *T = NULL;
208 if (!bset)
209 return NULL;
211 isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
212 isl_assert(bset->ctx, bset->n_div == 0, goto error);
213 isl_assert(bset->ctx, bset->n_eq == 0, goto error);
215 old_dim = isl_basic_set_n_dim(bset);
216 /* Try to move (multiples of) unit rows up. */
217 for (i = 0, j = 0; i < bset->n_ineq; ++i) {
218 int pos = isl_seq_first_non_zero(bset->ineq[i]+1, old_dim);
219 if (pos < 0)
220 continue;
221 if (isl_seq_first_non_zero(bset->ineq[i]+1+pos+1,
222 old_dim-pos-1) >= 0)
223 continue;
224 if (i != j)
225 swap_inequality(bset, i, j);
226 ++j;
228 bounds = independent_bounds(bset);
229 if (!bounds)
230 goto error;
231 new_dim = bounds->n_row - 1;
232 bounds = isl_mat_left_hermite(bounds, 1, &U, NULL);
233 if (!bounds)
234 goto error;
235 U = isl_mat_drop_cols(U, 1 + new_dim, old_dim - new_dim);
236 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
237 if (!bset)
238 goto error;
239 *T = U;
240 isl_mat_free(bounds);
241 return bset;
242 error:
243 isl_mat_free(bounds);
244 isl_mat_free(U);
245 isl_basic_set_free(bset);
246 return NULL;
249 /* Find a sample integer point, if any, in bset, which is known
250 * to have equalities. If bset contains no integer points, then
251 * return a zero-length vector.
252 * We simply remove the known equalities, compute a sample
253 * in the resulting bset, using the specified recurse function,
254 * and then transform the sample back to the original space.
256 static struct isl_vec *sample_eq(struct isl_basic_set *bset,
257 struct isl_vec *(*recurse)(struct isl_basic_set *))
259 struct isl_mat *T;
260 struct isl_vec *sample;
262 if (!bset)
263 return NULL;
265 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
266 sample = recurse(bset);
267 if (!sample || sample->size == 0)
268 isl_mat_free(T);
269 else
270 sample = isl_mat_vec_product(T, sample);
271 return sample;
274 /* Return a matrix containing the equalities of the tableau
275 * in constraint form. The tableau is assumed to have
276 * an associated bset that has been kept up-to-date.
278 static struct isl_mat *tab_equalities(struct isl_tab *tab)
280 int i, j;
281 int n_eq;
282 struct isl_mat *eq;
283 struct isl_basic_set *bset;
285 if (!tab)
286 return NULL;
288 bset = isl_tab_peek_bset(tab);
289 isl_assert(tab->mat->ctx, bset, return NULL);
291 n_eq = tab->n_var - tab->n_col + tab->n_dead;
292 if (tab->empty || n_eq == 0)
293 return isl_mat_alloc(tab->mat->ctx, 0, tab->n_var);
294 if (n_eq == tab->n_var)
295 return isl_mat_identity(tab->mat->ctx, tab->n_var);
297 eq = isl_mat_alloc(tab->mat->ctx, n_eq, tab->n_var);
298 if (!eq)
299 return NULL;
300 for (i = 0, j = 0; i < tab->n_con; ++i) {
301 if (tab->con[i].is_row)
302 continue;
303 if (tab->con[i].index >= 0 && tab->con[i].index >= tab->n_dead)
304 continue;
305 if (i < bset->n_eq)
306 isl_seq_cpy(eq->row[j], bset->eq[i] + 1, tab->n_var);
307 else
308 isl_seq_cpy(eq->row[j],
309 bset->ineq[i - bset->n_eq] + 1, tab->n_var);
310 ++j;
312 isl_assert(bset->ctx, j == n_eq, goto error);
313 return eq;
314 error:
315 isl_mat_free(eq);
316 return NULL;
319 /* Compute and return an initial basis for the bounded tableau "tab".
321 * If the tableau is either full-dimensional or zero-dimensional,
322 * the we simply return an identity matrix.
323 * Otherwise, we construct a basis whose first directions correspond
324 * to equalities.
326 static struct isl_mat *initial_basis(struct isl_tab *tab)
328 int n_eq;
329 struct isl_mat *eq;
330 struct isl_mat *Q;
332 tab->n_unbounded = 0;
333 tab->n_zero = n_eq = tab->n_var - tab->n_col + tab->n_dead;
334 if (tab->empty || n_eq == 0 || n_eq == tab->n_var)
335 return isl_mat_identity(tab->mat->ctx, 1 + tab->n_var);
337 eq = tab_equalities(tab);
338 eq = isl_mat_left_hermite(eq, 0, NULL, &Q);
339 if (!eq)
340 return NULL;
341 isl_mat_free(eq);
343 Q = isl_mat_lin_to_aff(Q);
344 return Q;
347 /* Given a tableau representing a set, find and return
348 * an integer point in the set, if there is any.
350 * We perform a depth first search
351 * for an integer point, by scanning all possible values in the range
352 * attained by a basis vector, where an initial basis may have been set
353 * by the calling function. Otherwise an initial basis that exploits
354 * the equalities in the tableau is created.
355 * tab->n_zero is currently ignored and is clobbered by this function.
357 * The tableau is allowed to have unbounded direction, but then
358 * the calling function needs to set an initial basis, with the
359 * unbounded directions last and with tab->n_unbounded set
360 * to the number of unbounded directions.
361 * Furthermore, the calling functions needs to add shifted copies
362 * of all constraints involving unbounded directions to ensure
363 * that any feasible rational value in these directions can be rounded
364 * up to yield a feasible integer value.
365 * In particular, let B define the given basis x' = B x
366 * and let T be the inverse of B, i.e., X = T x'.
367 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
368 * or a T x' + c >= 0 in terms of the given basis. Assume that
369 * the bounded directions have an integer value, then we can safely
370 * round up the values for the unbounded directions if we make sure
371 * that x' not only satisfies the original constraint, but also
372 * the constraint "a T x' + c + s >= 0" with s the sum of all
373 * negative values in the last n_unbounded entries of "a T".
374 * The calling function therefore needs to add the constraint
375 * a x + c + s >= 0. The current function then scans the first
376 * directions for an integer value and once those have been found,
377 * it can compute "T ceil(B x)" to yield an integer point in the set.
378 * Note that during the search, the first rows of B may be changed
379 * by a basis reduction, but the last n_unbounded rows of B remain
380 * unaltered and are also not mixed into the first rows.
382 * The search is implemented iteratively. "level" identifies the current
383 * basis vector. "init" is true if we want the first value at the current
384 * level and false if we want the next value.
386 * The initial basis is the identity matrix. If the range in some direction
387 * contains more than one integer value, we perform basis reduction based
388 * on the value of ctx->opt->gbr
389 * - ISL_GBR_NEVER: never perform basis reduction
390 * - ISL_GBR_ONCE: only perform basis reduction the first
391 * time such a range is encountered
392 * - ISL_GBR_ALWAYS: always perform basis reduction when
393 * such a range is encountered
395 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
396 * reduction computation to return early. That is, as soon as it
397 * finds a reasonable first direction.
399 struct isl_vec *isl_tab_sample(struct isl_tab *tab)
401 unsigned dim;
402 unsigned gbr;
403 struct isl_ctx *ctx;
404 struct isl_vec *sample;
405 struct isl_vec *min;
406 struct isl_vec *max;
407 enum isl_lp_result res;
408 int level;
409 int init;
410 int reduced;
411 struct isl_tab_undo **snap;
413 if (!tab)
414 return NULL;
415 if (tab->empty)
416 return isl_vec_alloc(tab->mat->ctx, 0);
418 if (!tab->basis)
419 tab->basis = initial_basis(tab);
420 if (!tab->basis)
421 return NULL;
422 isl_assert(tab->mat->ctx, tab->basis->n_row == tab->n_var + 1,
423 return NULL);
424 isl_assert(tab->mat->ctx, tab->basis->n_col == tab->n_var + 1,
425 return NULL);
427 ctx = tab->mat->ctx;
428 dim = tab->n_var;
429 gbr = ctx->opt->gbr;
431 if (tab->n_unbounded == tab->n_var) {
432 sample = isl_tab_get_sample_value(tab);
433 sample = isl_mat_vec_product(isl_mat_copy(tab->basis), sample);
434 sample = isl_vec_ceil(sample);
435 sample = isl_mat_vec_inverse_product(isl_mat_copy(tab->basis),
436 sample);
437 return sample;
440 if (isl_tab_extend_cons(tab, dim + 1) < 0)
441 return NULL;
443 min = isl_vec_alloc(ctx, dim);
444 max = isl_vec_alloc(ctx, dim);
445 snap = isl_alloc_array(ctx, struct isl_tab_undo *, dim);
447 if (!min || !max || !snap)
448 goto error;
450 level = 0;
451 init = 1;
452 reduced = 0;
454 while (level >= 0) {
455 int empty = 0;
456 if (init) {
457 res = isl_tab_min(tab, tab->basis->row[1 + level],
458 ctx->one, &min->el[level], NULL, 0);
459 if (res == isl_lp_empty)
460 empty = 1;
461 isl_assert(ctx, res != isl_lp_unbounded, goto error);
462 if (res == isl_lp_error)
463 goto error;
464 if (!empty && isl_tab_sample_is_integer(tab))
465 break;
466 isl_seq_neg(tab->basis->row[1 + level] + 1,
467 tab->basis->row[1 + level] + 1, dim);
468 res = isl_tab_min(tab, tab->basis->row[1 + level],
469 ctx->one, &max->el[level], NULL, 0);
470 isl_seq_neg(tab->basis->row[1 + level] + 1,
471 tab->basis->row[1 + level] + 1, dim);
472 isl_int_neg(max->el[level], max->el[level]);
473 if (res == isl_lp_empty)
474 empty = 1;
475 isl_assert(ctx, res != isl_lp_unbounded, goto error);
476 if (res == isl_lp_error)
477 goto error;
478 if (!empty && isl_tab_sample_is_integer(tab))
479 break;
480 if (!empty && !reduced &&
481 ctx->opt->gbr != ISL_GBR_NEVER &&
482 isl_int_lt(min->el[level], max->el[level])) {
483 unsigned gbr_only_first;
484 if (ctx->opt->gbr == ISL_GBR_ONCE)
485 ctx->opt->gbr = ISL_GBR_NEVER;
486 tab->n_zero = level;
487 gbr_only_first = ctx->opt->gbr_only_first;
488 ctx->opt->gbr_only_first =
489 ctx->opt->gbr == ISL_GBR_ALWAYS;
490 tab = isl_tab_compute_reduced_basis(tab);
491 ctx->opt->gbr_only_first = gbr_only_first;
492 if (!tab || !tab->basis)
493 goto error;
494 reduced = 1;
495 continue;
497 reduced = 0;
498 snap[level] = isl_tab_snap(tab);
499 } else
500 isl_int_add_ui(min->el[level], min->el[level], 1);
502 if (empty || isl_int_gt(min->el[level], max->el[level])) {
503 level--;
504 init = 0;
505 if (level >= 0)
506 if (isl_tab_rollback(tab, snap[level]) < 0)
507 goto error;
508 continue;
510 isl_int_neg(tab->basis->row[1 + level][0], min->el[level]);
511 tab = isl_tab_add_valid_eq(tab, tab->basis->row[1 + level]);
512 isl_int_set_si(tab->basis->row[1 + level][0], 0);
513 if (level + tab->n_unbounded < dim - 1) {
514 ++level;
515 init = 1;
516 continue;
518 break;
521 if (level >= 0) {
522 sample = isl_tab_get_sample_value(tab);
523 if (!sample)
524 goto error;
525 if (tab->n_unbounded && !isl_int_is_one(sample->el[0])) {
526 sample = isl_mat_vec_product(isl_mat_copy(tab->basis),
527 sample);
528 sample = isl_vec_ceil(sample);
529 sample = isl_mat_vec_inverse_product(
530 isl_mat_copy(tab->basis), sample);
532 } else
533 sample = isl_vec_alloc(ctx, 0);
535 ctx->opt->gbr = gbr;
536 isl_vec_free(min);
537 isl_vec_free(max);
538 free(snap);
539 return sample;
540 error:
541 ctx->opt->gbr = gbr;
542 isl_vec_free(min);
543 isl_vec_free(max);
544 free(snap);
545 return NULL;
548 /* Given a basic set that is known to be bounded, find and return
549 * an integer point in the basic set, if there is any.
551 * After handling some trivial cases, we construct a tableau
552 * and then use isl_tab_sample to find a sample, passing it
553 * the identity matrix as initial basis.
555 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
557 unsigned dim;
558 struct isl_ctx *ctx;
559 struct isl_vec *sample;
560 struct isl_tab *tab = NULL;
562 if (!bset)
563 return NULL;
565 if (isl_basic_set_fast_is_empty(bset))
566 return empty_sample(bset);
568 dim = isl_basic_set_total_dim(bset);
569 if (dim == 0)
570 return zero_sample(bset);
571 if (dim == 1)
572 return interval_sample(bset);
573 if (bset->n_eq > 0)
574 return sample_eq(bset, sample_bounded);
576 ctx = bset->ctx;
578 tab = isl_tab_from_basic_set(bset);
579 if (tab && tab->empty) {
580 isl_tab_free(tab);
581 ISL_F_SET(bset, ISL_BASIC_SET_EMPTY);
582 sample = isl_vec_alloc(bset->ctx, 0);
583 isl_basic_set_free(bset);
584 return sample;
587 if (isl_tab_track_bset(tab, isl_basic_set_copy(bset)) < 0)
588 goto error;
589 if (!ISL_F_ISSET(bset, ISL_BASIC_SET_NO_IMPLICIT))
590 if (isl_tab_detect_implicit_equalities(tab) < 0)
591 goto error;
593 sample = isl_tab_sample(tab);
594 if (!sample)
595 goto error;
597 if (sample->size > 0) {
598 isl_vec_free(bset->sample);
599 bset->sample = isl_vec_copy(sample);
602 isl_basic_set_free(bset);
603 isl_tab_free(tab);
604 return sample;
605 error:
606 isl_basic_set_free(bset);
607 isl_tab_free(tab);
608 return NULL;
611 /* Given a basic set "bset" and a value "sample" for the first coordinates
612 * of bset, plug in these values and drop the corresponding coordinates.
614 * We do this by computing the preimage of the transformation
616 * [ 1 0 ]
617 * x = [ s 0 ] x'
618 * [ 0 I ]
620 * where [1 s] is the sample value and I is the identity matrix of the
621 * appropriate dimension.
623 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
624 struct isl_vec *sample)
626 int i;
627 unsigned total;
628 struct isl_mat *T;
630 if (!bset || !sample)
631 goto error;
633 total = isl_basic_set_total_dim(bset);
634 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
635 if (!T)
636 goto error;
638 for (i = 0; i < sample->size; ++i) {
639 isl_int_set(T->row[i][0], sample->el[i]);
640 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
642 for (i = 0; i < T->n_col - 1; ++i) {
643 isl_seq_clr(T->row[sample->size + i], T->n_col);
644 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
646 isl_vec_free(sample);
648 bset = isl_basic_set_preimage(bset, T);
649 return bset;
650 error:
651 isl_basic_set_free(bset);
652 isl_vec_free(sample);
653 return NULL;
656 /* Given a basic set "bset", return any (possibly non-integer) point
657 * in the basic set.
659 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
661 struct isl_tab *tab;
662 struct isl_vec *sample;
664 if (!bset)
665 return NULL;
667 tab = isl_tab_from_basic_set(bset);
668 sample = isl_tab_get_sample_value(tab);
669 isl_tab_free(tab);
671 isl_basic_set_free(bset);
673 return sample;
676 /* Given a linear cone "cone" and a rational point "vec",
677 * construct a polyhedron with shifted copies of the constraints in "cone",
678 * i.e., a polyhedron with "cone" as its recession cone, such that each
679 * point x in this polyhedron is such that the unit box positioned at x
680 * lies entirely inside the affine cone 'vec + cone'.
681 * Any rational point in this polyhedron may therefore be rounded up
682 * to yield an integer point that lies inside said affine cone.
684 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
685 * point "vec" by v/d.
686 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
687 * by <a_i, x> - b/d >= 0.
688 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
689 * We prefer this polyhedron over the actual affine cone because it doesn't
690 * require a scaling of the constraints.
691 * If each of the vertices of the unit cube positioned at x lies inside
692 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
693 * We therefore impose that x' = x + \sum e_i, for any selection of unit
694 * vectors lies inside the polyhedron, i.e.,
696 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
698 * The most stringent of these constraints is the one that selects
699 * all negative a_i, so the polyhedron we are looking for has constraints
701 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
703 * Note that if cone were known to have only non-negative rays
704 * (which can be accomplished by a unimodular transformation),
705 * then we would only have to check the points x' = x + e_i
706 * and we only have to add the smallest negative a_i (if any)
707 * instead of the sum of all negative a_i.
709 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
710 struct isl_vec *vec)
712 int i, j, k;
713 unsigned total;
715 struct isl_basic_set *shift = NULL;
717 if (!cone || !vec)
718 goto error;
720 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
722 total = isl_basic_set_total_dim(cone);
724 shift = isl_basic_set_alloc_dim(isl_basic_set_get_dim(cone),
725 0, 0, cone->n_ineq);
727 for (i = 0; i < cone->n_ineq; ++i) {
728 k = isl_basic_set_alloc_inequality(shift);
729 if (k < 0)
730 goto error;
731 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
732 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
733 &shift->ineq[k][0]);
734 isl_int_cdiv_q(shift->ineq[k][0],
735 shift->ineq[k][0], vec->el[0]);
736 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
737 for (j = 0; j < total; ++j) {
738 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
739 continue;
740 isl_int_add(shift->ineq[k][0],
741 shift->ineq[k][0], shift->ineq[k][1 + j]);
745 isl_basic_set_free(cone);
746 isl_vec_free(vec);
748 return isl_basic_set_finalize(shift);
749 error:
750 isl_basic_set_free(shift);
751 isl_basic_set_free(cone);
752 isl_vec_free(vec);
753 return NULL;
756 /* Given a rational point vec in a (transformed) basic set,
757 * such that cone is the recession cone of the original basic set,
758 * "round up" the rational point to an integer point.
760 * We first check if the rational point just happens to be integer.
761 * If not, we transform the cone in the same way as the basic set,
762 * pick a point x in this cone shifted to the rational point such that
763 * the whole unit cube at x is also inside this affine cone.
764 * Then we simply round up the coordinates of x and return the
765 * resulting integer point.
767 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
768 struct isl_basic_set *cone, struct isl_mat *U)
770 unsigned total;
772 if (!vec || !cone || !U)
773 goto error;
775 isl_assert(vec->ctx, vec->size != 0, goto error);
776 if (isl_int_is_one(vec->el[0])) {
777 isl_mat_free(U);
778 isl_basic_set_free(cone);
779 return vec;
782 total = isl_basic_set_total_dim(cone);
783 cone = isl_basic_set_preimage(cone, U);
784 cone = isl_basic_set_remove_dims(cone, 0, total - (vec->size - 1));
786 cone = shift_cone(cone, vec);
788 vec = rational_sample(cone);
789 vec = isl_vec_ceil(vec);
790 return vec;
791 error:
792 isl_mat_free(U);
793 isl_vec_free(vec);
794 isl_basic_set_free(cone);
795 return NULL;
798 /* Concatenate two integer vectors, i.e., two vectors with denominator
799 * (stored in element 0) equal to 1.
801 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
803 struct isl_vec *vec;
805 if (!vec1 || !vec2)
806 goto error;
807 isl_assert(vec1->ctx, vec1->size > 0, goto error);
808 isl_assert(vec2->ctx, vec2->size > 0, goto error);
809 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
810 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
812 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
813 if (!vec)
814 goto error;
816 isl_seq_cpy(vec->el, vec1->el, vec1->size);
817 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
819 isl_vec_free(vec1);
820 isl_vec_free(vec2);
822 return vec;
823 error:
824 isl_vec_free(vec1);
825 isl_vec_free(vec2);
826 return NULL;
829 /* Drop all constraints in bset that involve any of the dimensions
830 * first to first+n-1.
832 static struct isl_basic_set *drop_constraints_involving
833 (struct isl_basic_set *bset, unsigned first, unsigned n)
835 int i;
837 bset = isl_basic_set_cow(bset);
839 if (!bset)
840 return NULL;
842 for (i = bset->n_ineq - 1; i >= 0; --i) {
843 if (isl_seq_first_non_zero(bset->ineq[i] + 1 + first, n) == -1)
844 continue;
845 isl_basic_set_drop_inequality(bset, i);
848 return bset;
851 /* Give a basic set "bset" with recession cone "cone", compute and
852 * return an integer point in bset, if any.
854 * If the recession cone is full-dimensional, then we know that
855 * bset contains an infinite number of integer points and it is
856 * fairly easy to pick one of them.
857 * If the recession cone is not full-dimensional, then we first
858 * transform bset such that the bounded directions appear as
859 * the first dimensions of the transformed basic set.
860 * We do this by using a unimodular transformation that transforms
861 * the equalities in the recession cone to equalities on the first
862 * dimensions.
864 * The transformed set is then projected onto its bounded dimensions.
865 * Note that to compute this projection, we can simply drop all constraints
866 * involving any of the unbounded dimensions since these constraints
867 * cannot be combined to produce a constraint on the bounded dimensions.
868 * To see this, assume that there is such a combination of constraints
869 * that produces a constraint on the bounded dimensions. This means
870 * that some combination of the unbounded dimensions has both an upper
871 * bound and a lower bound in terms of the bounded dimensions, but then
872 * this combination would be a bounded direction too and would have been
873 * transformed into a bounded dimensions.
875 * We then compute a sample value in the bounded dimensions.
876 * If no such value can be found, then the original set did not contain
877 * any integer points and we are done.
878 * Otherwise, we plug in the value we found in the bounded dimensions,
879 * project out these bounded dimensions and end up with a set with
880 * a full-dimensional recession cone.
881 * A sample point in this set is computed by "rounding up" any
882 * rational point in the set.
884 * The sample points in the bounded and unbounded dimensions are
885 * then combined into a single sample point and transformed back
886 * to the original space.
888 __isl_give isl_vec *isl_basic_set_sample_with_cone(
889 __isl_take isl_basic_set *bset, __isl_take isl_basic_set *cone)
891 unsigned total;
892 unsigned cone_dim;
893 struct isl_mat *M, *U;
894 struct isl_vec *sample;
895 struct isl_vec *cone_sample;
896 struct isl_ctx *ctx;
897 struct isl_basic_set *bounded;
899 if (!bset || !cone)
900 goto error;
902 ctx = bset->ctx;
903 total = isl_basic_set_total_dim(cone);
904 cone_dim = total - cone->n_eq;
906 M = isl_mat_sub_alloc(bset->ctx, cone->eq, 0, cone->n_eq, 1, total);
907 M = isl_mat_left_hermite(M, 0, &U, NULL);
908 if (!M)
909 goto error;
910 isl_mat_free(M);
912 U = isl_mat_lin_to_aff(U);
913 bset = isl_basic_set_preimage(bset, isl_mat_copy(U));
915 bounded = isl_basic_set_copy(bset);
916 bounded = drop_constraints_involving(bounded, total - cone_dim, cone_dim);
917 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
918 sample = sample_bounded(bounded);
919 if (!sample || sample->size == 0) {
920 isl_basic_set_free(bset);
921 isl_basic_set_free(cone);
922 isl_mat_free(U);
923 return sample;
925 bset = plug_in(bset, isl_vec_copy(sample));
926 cone_sample = rational_sample(bset);
927 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(U));
928 sample = vec_concat(sample, cone_sample);
929 sample = isl_mat_vec_product(U, sample);
930 return sample;
931 error:
932 isl_basic_set_free(cone);
933 isl_basic_set_free(bset);
934 return NULL;
937 static void vec_sum_of_neg(struct isl_vec *v, isl_int *s)
939 int i;
941 isl_int_set_si(*s, 0);
943 for (i = 0; i < v->size; ++i)
944 if (isl_int_is_neg(v->el[i]))
945 isl_int_add(*s, *s, v->el[i]);
948 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
949 * to the recession cone and the inverse of a new basis U = inv(B),
950 * with the unbounded directions in B last,
951 * add constraints to "tab" that ensure any rational value
952 * in the unbounded directions can be rounded up to an integer value.
954 * The new basis is given by x' = B x, i.e., x = U x'.
955 * For any rational value of the last tab->n_unbounded coordinates
956 * in the update tableau, the value that is obtained by rounding
957 * up this value should be contained in the original tableau.
958 * For any constraint "a x + c >= 0", we therefore need to add
959 * a constraint "a x + c + s >= 0", with s the sum of all negative
960 * entries in the last elements of "a U".
962 * Since we are not interested in the first entries of any of the "a U",
963 * we first drop the columns of U that correpond to bounded directions.
965 static int tab_shift_cone(struct isl_tab *tab,
966 struct isl_tab *tab_cone, struct isl_mat *U)
968 int i;
969 isl_int v;
970 struct isl_basic_set *bset = NULL;
972 if (tab && tab->n_unbounded == 0) {
973 isl_mat_free(U);
974 return 0;
976 isl_int_init(v);
977 if (!tab || !tab_cone || !U)
978 goto error;
979 bset = isl_tab_peek_bset(tab_cone);
980 U = isl_mat_drop_cols(U, 0, tab->n_var - tab->n_unbounded);
981 for (i = 0; i < bset->n_ineq; ++i) {
982 int ok;
983 struct isl_vec *row = NULL;
984 if (isl_tab_is_equality(tab_cone, tab_cone->n_eq + i))
985 continue;
986 row = isl_vec_alloc(bset->ctx, tab_cone->n_var);
987 if (!row)
988 goto error;
989 isl_seq_cpy(row->el, bset->ineq[i] + 1, tab_cone->n_var);
990 row = isl_vec_mat_product(row, isl_mat_copy(U));
991 if (!row)
992 goto error;
993 vec_sum_of_neg(row, &v);
994 isl_vec_free(row);
995 if (isl_int_is_zero(v))
996 continue;
997 tab = isl_tab_extend(tab, 1);
998 isl_int_add(bset->ineq[i][0], bset->ineq[i][0], v);
999 ok = isl_tab_add_ineq(tab, bset->ineq[i]) >= 0;
1000 isl_int_sub(bset->ineq[i][0], bset->ineq[i][0], v);
1001 if (!ok)
1002 goto error;
1005 isl_mat_free(U);
1006 isl_int_clear(v);
1007 return 0;
1008 error:
1009 isl_mat_free(U);
1010 isl_int_clear(v);
1011 return -1;
1014 /* Compute and return an initial basis for the possibly
1015 * unbounded tableau "tab". "tab_cone" is a tableau
1016 * for the corresponding recession cone.
1017 * Additionally, add constraints to "tab" that ensure
1018 * that any rational value for the unbounded directions
1019 * can be rounded up to an integer value.
1021 * If the tableau is bounded, i.e., if the recession cone
1022 * is zero-dimensional, then we just use inital_basis.
1023 * Otherwise, we construct a basis whose first directions
1024 * correspond to equalities, followed by bounded directions,
1025 * i.e., equalities in the recession cone.
1026 * The remaining directions are then unbounded.
1028 int isl_tab_set_initial_basis_with_cone(struct isl_tab *tab,
1029 struct isl_tab *tab_cone)
1031 struct isl_mat *eq;
1032 struct isl_mat *cone_eq;
1033 struct isl_mat *U, *Q;
1035 if (!tab || !tab_cone)
1036 return -1;
1038 if (tab_cone->n_col == tab_cone->n_dead) {
1039 tab->basis = initial_basis(tab);
1040 return tab->basis ? 0 : -1;
1043 eq = tab_equalities(tab);
1044 if (!eq)
1045 return -1;
1046 tab->n_zero = eq->n_row;
1047 cone_eq = tab_equalities(tab_cone);
1048 eq = isl_mat_concat(eq, cone_eq);
1049 if (!eq)
1050 return -1;
1051 tab->n_unbounded = tab->n_var - (eq->n_row - tab->n_zero);
1052 eq = isl_mat_left_hermite(eq, 0, &U, &Q);
1053 if (!eq)
1054 return -1;
1055 isl_mat_free(eq);
1056 tab->basis = isl_mat_lin_to_aff(Q);
1057 if (tab_shift_cone(tab, tab_cone, U) < 0)
1058 return -1;
1059 if (!tab->basis)
1060 return -1;
1061 return 0;
1064 /* Compute and return a sample point in bset using generalized basis
1065 * reduction. We first check if the input set has a non-trivial
1066 * recession cone. If so, we perform some extra preprocessing in
1067 * sample_with_cone. Otherwise, we directly perform generalized basis
1068 * reduction.
1070 static struct isl_vec *gbr_sample(struct isl_basic_set *bset)
1072 unsigned dim;
1073 struct isl_basic_set *cone;
1075 dim = isl_basic_set_total_dim(bset);
1077 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
1078 if (!cone)
1079 goto error;
1081 if (cone->n_eq < dim)
1082 return isl_basic_set_sample_with_cone(bset, cone);
1084 isl_basic_set_free(cone);
1085 return sample_bounded(bset);
1086 error:
1087 isl_basic_set_free(bset);
1088 return NULL;
1091 static struct isl_vec *pip_sample(struct isl_basic_set *bset)
1093 struct isl_mat *T;
1094 struct isl_ctx *ctx;
1095 struct isl_vec *sample;
1097 bset = isl_basic_set_skew_to_positive_orthant(bset, &T);
1098 if (!bset)
1099 return NULL;
1101 ctx = bset->ctx;
1102 sample = isl_pip_basic_set_sample(bset);
1104 if (sample && sample->size != 0)
1105 sample = isl_mat_vec_product(T, sample);
1106 else
1107 isl_mat_free(T);
1109 return sample;
1112 static struct isl_vec *basic_set_sample(struct isl_basic_set *bset, int bounded)
1114 struct isl_ctx *ctx;
1115 unsigned dim;
1116 if (!bset)
1117 return NULL;
1119 ctx = bset->ctx;
1120 if (isl_basic_set_fast_is_empty(bset))
1121 return empty_sample(bset);
1123 dim = isl_basic_set_n_dim(bset);
1124 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
1125 isl_assert(ctx, bset->n_div == 0, goto error);
1127 if (bset->sample && bset->sample->size == 1 + dim) {
1128 int contains = isl_basic_set_contains(bset, bset->sample);
1129 if (contains < 0)
1130 goto error;
1131 if (contains) {
1132 struct isl_vec *sample = isl_vec_copy(bset->sample);
1133 isl_basic_set_free(bset);
1134 return sample;
1137 isl_vec_free(bset->sample);
1138 bset->sample = NULL;
1140 if (bset->n_eq > 0)
1141 return sample_eq(bset, bounded ? isl_basic_set_sample_bounded
1142 : isl_basic_set_sample_vec);
1143 if (dim == 0)
1144 return zero_sample(bset);
1145 if (dim == 1)
1146 return interval_sample(bset);
1148 switch (bset->ctx->opt->ilp_solver) {
1149 case ISL_ILP_PIP:
1150 return pip_sample(bset);
1151 case ISL_ILP_GBR:
1152 return bounded ? sample_bounded(bset) : gbr_sample(bset);
1154 isl_assert(bset->ctx, 0, );
1155 error:
1156 isl_basic_set_free(bset);
1157 return NULL;
1160 __isl_give isl_vec *isl_basic_set_sample_vec(__isl_take isl_basic_set *bset)
1162 return basic_set_sample(bset, 0);
1165 /* Compute an integer sample in "bset", where the caller guarantees
1166 * that "bset" is bounded.
1168 struct isl_vec *isl_basic_set_sample_bounded(struct isl_basic_set *bset)
1170 return basic_set_sample(bset, 1);
1173 __isl_give isl_basic_set *isl_basic_set_from_vec(__isl_take isl_vec *vec)
1175 int i;
1176 int k;
1177 struct isl_basic_set *bset = NULL;
1178 struct isl_ctx *ctx;
1179 unsigned dim;
1181 if (!vec)
1182 return NULL;
1183 ctx = vec->ctx;
1184 isl_assert(ctx, vec->size != 0, goto error);
1186 bset = isl_basic_set_alloc(ctx, 0, vec->size - 1, 0, vec->size - 1, 0);
1187 if (!bset)
1188 goto error;
1189 dim = isl_basic_set_n_dim(bset);
1190 for (i = dim - 1; i >= 0; --i) {
1191 k = isl_basic_set_alloc_equality(bset);
1192 if (k < 0)
1193 goto error;
1194 isl_seq_clr(bset->eq[k], 1 + dim);
1195 isl_int_neg(bset->eq[k][0], vec->el[1 + i]);
1196 isl_int_set(bset->eq[k][1 + i], vec->el[0]);
1198 bset->sample = vec;
1200 return bset;
1201 error:
1202 isl_basic_set_free(bset);
1203 isl_vec_free(vec);
1204 return NULL;
1207 __isl_give isl_basic_map *isl_basic_map_sample(__isl_take isl_basic_map *bmap)
1209 struct isl_basic_set *bset;
1210 struct isl_vec *sample_vec;
1212 bset = isl_basic_map_underlying_set(isl_basic_map_copy(bmap));
1213 sample_vec = isl_basic_set_sample_vec(bset);
1214 if (!sample_vec)
1215 goto error;
1216 if (sample_vec->size == 0) {
1217 struct isl_basic_map *sample;
1218 sample = isl_basic_map_empty_like(bmap);
1219 isl_vec_free(sample_vec);
1220 isl_basic_map_free(bmap);
1221 return sample;
1223 bset = isl_basic_set_from_vec(sample_vec);
1224 return isl_basic_map_overlying_set(bset, bmap);
1225 error:
1226 isl_basic_map_free(bmap);
1227 return NULL;
1230 __isl_give isl_basic_map *isl_map_sample(__isl_take isl_map *map)
1232 int i;
1233 isl_basic_map *sample = NULL;
1235 if (!map)
1236 goto error;
1238 for (i = 0; i < map->n; ++i) {
1239 sample = isl_basic_map_sample(isl_basic_map_copy(map->p[i]));
1240 if (!sample)
1241 goto error;
1242 if (!ISL_F_ISSET(sample, ISL_BASIC_MAP_EMPTY))
1243 break;
1244 isl_basic_map_free(sample);
1246 if (i == map->n)
1247 sample = isl_basic_map_empty_like_map(map);
1248 isl_map_free(map);
1249 return sample;
1250 error:
1251 isl_map_free(map);
1252 return NULL;
1255 __isl_give isl_basic_set *isl_set_sample(__isl_take isl_set *set)
1257 return (isl_basic_set *) isl_map_sample((isl_map *)set);
1260 __isl_give isl_point *isl_basic_set_sample_point(__isl_take isl_basic_set *bset)
1262 isl_vec *vec;
1263 isl_dim *dim;
1265 dim = isl_basic_set_get_dim(bset);
1266 bset = isl_basic_set_underlying_set(bset);
1267 vec = isl_basic_set_sample_vec(bset);
1269 return isl_point_alloc(dim, vec);
1272 __isl_give isl_point *isl_set_sample_point(__isl_take isl_set *set)
1274 int i;
1275 isl_point *pnt;
1277 if (!set)
1278 return NULL;
1280 for (i = 0; i < set->n; ++i) {
1281 pnt = isl_basic_set_sample_point(isl_basic_set_copy(set->p[i]));
1282 if (!pnt)
1283 goto error;
1284 if (!isl_point_is_void(pnt))
1285 break;
1286 isl_point_free(pnt);
1288 if (i == set->n)
1289 pnt = isl_point_void(isl_set_get_dim(set));
1291 isl_set_free(set);
1292 return pnt;
1293 error:
1294 isl_set_free(set);
1295 return NULL;