isl_basic_map_fix_pos: micro-optimization
[isl.git] / isl_sample.c
blob8ec6c0b132b8e355d458ce5082bd1de358e849c9
1 #include "isl_sample.h"
2 #include "isl_sample_piplib.h"
3 #include "isl_vec.h"
4 #include "isl_mat.h"
5 #include "isl_seq.h"
6 #include "isl_map_private.h"
7 #include "isl_equalities.h"
8 #include "isl_tab.h"
9 #include "isl_basis_reduction.h"
11 static struct isl_vec *empty_sample(struct isl_basic_set *bset)
13 struct isl_vec *vec;
15 vec = isl_vec_alloc(bset->ctx, 0);
16 isl_basic_set_free(bset);
17 return vec;
20 /* Construct a zero sample of the same dimension as bset.
21 * As a special case, if bset is zero-dimensional, this
22 * function creates a zero-dimensional sample point.
24 static struct isl_vec *zero_sample(struct isl_basic_set *bset)
26 unsigned dim;
27 struct isl_vec *sample;
29 dim = isl_basic_set_total_dim(bset);
30 sample = isl_vec_alloc(bset->ctx, 1 + dim);
31 if (sample) {
32 isl_int_set_si(sample->el[0], 1);
33 isl_seq_clr(sample->el + 1, dim);
35 isl_basic_set_free(bset);
36 return sample;
39 static struct isl_vec *interval_sample(struct isl_basic_set *bset)
41 int i;
42 isl_int t;
43 struct isl_vec *sample;
45 bset = isl_basic_set_simplify(bset);
46 if (!bset)
47 return NULL;
48 if (isl_basic_set_fast_is_empty(bset))
49 return empty_sample(bset);
50 if (bset->n_eq == 0 && bset->n_ineq == 0)
51 return zero_sample(bset);
53 sample = isl_vec_alloc(bset->ctx, 2);
54 isl_int_set_si(sample->block.data[0], 1);
56 if (bset->n_eq > 0) {
57 isl_assert(bset->ctx, bset->n_eq == 1, goto error);
58 isl_assert(bset->ctx, bset->n_ineq == 0, goto error);
59 if (isl_int_is_one(bset->eq[0][1]))
60 isl_int_neg(sample->el[1], bset->eq[0][0]);
61 else {
62 isl_assert(bset->ctx, isl_int_is_negone(bset->eq[0][1]),
63 goto error);
64 isl_int_set(sample->el[1], bset->eq[0][0]);
66 isl_basic_set_free(bset);
67 return sample;
70 isl_int_init(t);
71 if (isl_int_is_one(bset->ineq[0][1]))
72 isl_int_neg(sample->block.data[1], bset->ineq[0][0]);
73 else
74 isl_int_set(sample->block.data[1], bset->ineq[0][0]);
75 for (i = 1; i < bset->n_ineq; ++i) {
76 isl_seq_inner_product(sample->block.data,
77 bset->ineq[i], 2, &t);
78 if (isl_int_is_neg(t))
79 break;
81 isl_int_clear(t);
82 if (i < bset->n_ineq) {
83 isl_vec_free(sample);
84 return empty_sample(bset);
87 isl_basic_set_free(bset);
88 return sample;
89 error:
90 isl_basic_set_free(bset);
91 isl_vec_free(sample);
92 return NULL;
95 static struct isl_mat *independent_bounds(struct isl_ctx *ctx,
96 struct isl_basic_set *bset)
98 int i, j, n;
99 struct isl_mat *dirs = NULL;
100 struct isl_mat *bounds = NULL;
101 unsigned dim;
103 if (!bset)
104 return NULL;
106 dim = isl_basic_set_n_dim(bset);
107 bounds = isl_mat_alloc(ctx, 1+dim, 1+dim);
108 if (!bounds)
109 return NULL;
111 isl_int_set_si(bounds->row[0][0], 1);
112 isl_seq_clr(bounds->row[0]+1, dim);
113 bounds->n_row = 1;
115 if (bset->n_ineq == 0)
116 return bounds;
118 dirs = isl_mat_alloc(ctx, dim, dim);
119 if (!dirs) {
120 isl_mat_free(ctx, bounds);
121 return NULL;
123 isl_seq_cpy(dirs->row[0], bset->ineq[0]+1, dirs->n_col);
124 isl_seq_cpy(bounds->row[1], bset->ineq[0], bounds->n_col);
125 for (j = 1, n = 1; n < dim && j < bset->n_ineq; ++j) {
126 int pos;
128 isl_seq_cpy(dirs->row[n], bset->ineq[j]+1, dirs->n_col);
130 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
131 if (pos < 0)
132 continue;
133 for (i = 0; i < n; ++i) {
134 int pos_i;
135 pos_i = isl_seq_first_non_zero(dirs->row[i], dirs->n_col);
136 if (pos_i < pos)
137 continue;
138 if (pos_i > pos)
139 break;
140 isl_seq_elim(dirs->row[n], dirs->row[i], pos,
141 dirs->n_col, NULL);
142 pos = isl_seq_first_non_zero(dirs->row[n], dirs->n_col);
143 if (pos < 0)
144 break;
146 if (pos < 0)
147 continue;
148 if (i < n) {
149 int k;
150 isl_int *t = dirs->row[n];
151 for (k = n; k > i; --k)
152 dirs->row[k] = dirs->row[k-1];
153 dirs->row[i] = t;
155 ++n;
156 isl_seq_cpy(bounds->row[n], bset->ineq[j], bounds->n_col);
158 isl_mat_free(ctx, dirs);
159 bounds->n_row = 1+n;
160 return bounds;
163 static void swap_inequality(struct isl_basic_set *bset, int a, int b)
165 isl_int *t = bset->ineq[a];
166 bset->ineq[a] = bset->ineq[b];
167 bset->ineq[b] = t;
170 /* Skew into positive orthant and project out lineality space */
171 static struct isl_basic_set *isl_basic_set_skew_to_positive_orthant(
172 struct isl_basic_set *bset, struct isl_mat **T)
174 struct isl_mat *U = NULL;
175 struct isl_mat *bounds = NULL;
176 int i, j;
177 unsigned old_dim, new_dim;
178 struct isl_ctx *ctx;
180 *T = NULL;
181 if (!bset)
182 return NULL;
184 ctx = bset->ctx;
185 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
186 isl_assert(ctx, bset->n_div == 0, goto error);
187 isl_assert(ctx, bset->n_eq == 0, goto error);
189 old_dim = isl_basic_set_n_dim(bset);
190 /* Try to move (multiples of) unit rows up. */
191 for (i = 0, j = 0; i < bset->n_ineq; ++i) {
192 int pos = isl_seq_first_non_zero(bset->ineq[i]+1, old_dim);
193 if (pos < 0)
194 continue;
195 if (isl_seq_first_non_zero(bset->ineq[i]+1+pos+1,
196 old_dim-pos-1) >= 0)
197 continue;
198 if (i != j)
199 swap_inequality(bset, i, j);
200 ++j;
202 bounds = independent_bounds(ctx, bset);
203 if (!bounds)
204 goto error;
205 new_dim = bounds->n_row - 1;
206 bounds = isl_mat_left_hermite(ctx, bounds, 1, &U, NULL);
207 if (!bounds)
208 goto error;
209 U = isl_mat_drop_cols(ctx, U, 1 + new_dim, old_dim - new_dim);
210 bset = isl_basic_set_preimage(bset, isl_mat_copy(ctx, U));
211 if (!bset)
212 goto error;
213 *T = U;
214 isl_mat_free(ctx, bounds);
215 return bset;
216 error:
217 isl_mat_free(ctx, bounds);
218 isl_mat_free(ctx, U);
219 isl_basic_set_free(bset);
220 return NULL;
223 /* Find a sample integer point, if any, in bset, which is known
224 * to have equalities. If bset contains no integer points, then
225 * return a zero-length vector.
226 * We simply remove the known equalities, compute a sample
227 * in the resulting bset, using the specified recurse function,
228 * and then transform the sample back to the original space.
230 static struct isl_vec *sample_eq(struct isl_basic_set *bset,
231 struct isl_vec *(*recurse)(struct isl_basic_set *))
233 struct isl_mat *T;
234 struct isl_vec *sample;
235 struct isl_ctx *ctx;
237 if (!bset)
238 return NULL;
240 ctx = bset->ctx;
241 bset = isl_basic_set_remove_equalities(bset, &T, NULL);
242 sample = recurse(bset);
243 if (!sample || sample->size == 0)
244 isl_mat_free(ctx, T);
245 else
246 sample = isl_mat_vec_product(ctx, T, sample);
247 return sample;
250 /* Given a basic set "bset" and an affine function "f"/"denom",
251 * check if bset is bounded and non-empty and if so, return the minimal
252 * and maximal value attained by the affine function in "min" and "max".
253 * The minimal value is rounded up to the nearest integer, while the
254 * maximal value is rounded down.
255 * The return value indicates whether the set was empty or unbounded.
257 * If we happen to find an integer point while looking for the minimal
258 * or maximal value, then we record that value in "bset" and return early.
260 static enum isl_lp_result basic_set_range(struct isl_basic_set *bset,
261 isl_int *f, isl_int denom, isl_int *min, isl_int *max)
263 unsigned dim;
264 struct isl_tab *tab;
265 enum isl_lp_result res;
267 if (!bset)
268 return isl_lp_error;
269 if (isl_basic_set_fast_is_empty(bset))
270 return isl_lp_empty;
272 tab = isl_tab_from_basic_set(bset);
273 res = isl_tab_min(bset->ctx, tab, f, denom, min, NULL, 0);
274 if (res != isl_lp_ok)
275 goto done;
277 if (isl_tab_sample_is_integer(bset->ctx, tab)) {
278 isl_vec_free(bset->sample);
279 bset->sample = isl_tab_get_sample_value(bset->ctx, tab);
280 if (!bset->sample)
281 goto error;
282 isl_int_set(*max, *min);
283 goto done;
286 dim = isl_basic_set_total_dim(bset);
287 isl_seq_neg(f, f, 1 + dim);
288 res = isl_tab_min(bset->ctx, tab, f, denom, max, NULL, 0);
289 isl_seq_neg(f, f, 1 + dim);
290 isl_int_neg(*max, *max);
292 if (isl_tab_sample_is_integer(bset->ctx, tab)) {
293 isl_vec_free(bset->sample);
294 bset->sample = isl_tab_get_sample_value(bset->ctx, tab);
295 if (!bset->sample)
296 goto error;
299 done:
300 isl_tab_free(bset->ctx, tab);
301 return res;
302 error:
303 isl_tab_free(bset->ctx, tab);
304 return isl_lp_error;
307 /* Perform a basis reduction on "bset" and return the inverse of
308 * the new basis, i.e., an affine mapping from the new coordinates to the old,
309 * in *T.
311 static struct isl_basic_set *basic_set_reduced(struct isl_basic_set *bset,
312 struct isl_mat **T)
314 struct isl_ctx *ctx;
315 unsigned gbr_only_first;
317 *T = NULL;
318 if (!bset)
319 return NULL;
321 ctx = bset->ctx;
323 gbr_only_first = ctx->gbr_only_first;
324 ctx->gbr_only_first = 1;
325 *T = isl_basic_set_reduced_basis(bset);
326 ctx->gbr_only_first = gbr_only_first;
328 *T = isl_mat_lin_to_aff(bset->ctx, *T);
329 *T = isl_mat_right_inverse(bset->ctx, *T);
331 bset = isl_basic_set_preimage(bset, isl_mat_copy(bset->ctx, *T));
332 if (!bset)
333 goto error;
335 return bset;
336 error:
337 isl_mat_free(ctx, *T);
338 *T = NULL;
339 return NULL;
342 static struct isl_vec *sample_bounded(struct isl_basic_set *bset);
344 /* Given a basic set "bset" whose first coordinate ranges between
345 * "min" and "max", step through all values from min to max, until
346 * the slice of bset with the first coordinate fixed to one of these
347 * values contains an integer point. If such a point is found, return it.
348 * If none of the slices contains any integer point, then bset itself
349 * doesn't contain any integer point and an empty sample is returned.
351 static struct isl_vec *sample_scan(struct isl_basic_set *bset,
352 isl_int min, isl_int max)
354 unsigned total;
355 struct isl_basic_set *slice = NULL;
356 struct isl_vec *sample = NULL;
357 isl_int tmp;
359 total = isl_basic_set_total_dim(bset);
361 isl_int_init(tmp);
362 for (isl_int_set(tmp, min); isl_int_le(tmp, max);
363 isl_int_add_ui(tmp, tmp, 1)) {
364 int k;
366 slice = isl_basic_set_copy(bset);
367 slice = isl_basic_set_cow(slice);
368 slice = isl_basic_set_extend_constraints(slice, 1, 0);
369 k = isl_basic_set_alloc_equality(slice);
370 if (k < 0)
371 goto error;
372 isl_int_set(slice->eq[k][0], tmp);
373 isl_int_set_si(slice->eq[k][1], -1);
374 isl_seq_clr(slice->eq[k] + 2, total - 1);
375 slice = isl_basic_set_simplify(slice);
376 sample = sample_bounded(slice);
377 slice = NULL;
378 if (!sample)
379 goto error;
380 if (sample->size > 0)
381 break;
382 isl_vec_free(sample);
383 sample = NULL;
385 if (!sample)
386 sample = empty_sample(bset);
387 else
388 isl_basic_set_free(bset);
389 isl_int_clear(tmp);
390 return sample;
391 error:
392 isl_basic_set_free(bset);
393 isl_basic_set_free(slice);
394 isl_int_clear(tmp);
395 return NULL;
398 /* Given a basic set that is known to be bounded, find and return
399 * an integer point in the basic set, if there is any.
401 * After handling some trivial cases, we check the range of the
402 * first coordinate. If this coordinate can only attain one integer
403 * value, we are happy. Otherwise, we perform basis reduction and
404 * determine the new range.
406 * Then we step through all possible values in the range in sample_scan.
408 * If any basis reduction was performed, the sample value found, if any,
409 * is transformed back to the original space.
411 static struct isl_vec *sample_bounded(struct isl_basic_set *bset)
413 unsigned dim;
414 struct isl_ctx *ctx;
415 struct isl_vec *sample;
416 struct isl_vec *obj = NULL;
417 struct isl_mat *T = NULL;
418 isl_int min, max;
419 enum isl_lp_result res;
421 if (!bset)
422 return NULL;
424 if (isl_basic_set_fast_is_empty(bset))
425 return empty_sample(bset);
427 ctx = bset->ctx;
428 dim = isl_basic_set_total_dim(bset);
429 if (dim == 0)
430 return zero_sample(bset);
431 if (dim == 1)
432 return interval_sample(bset);
433 if (bset->n_eq > 0)
434 return sample_eq(bset, sample_bounded);
436 isl_int_init(min);
437 isl_int_init(max);
438 obj = isl_vec_alloc(bset->ctx, 1 + dim);
439 if (!obj)
440 goto error;
441 isl_seq_clr(obj->el, 1+ dim);
442 isl_int_set_si(obj->el[1], 1);
444 res = basic_set_range(bset, obj->el, bset->ctx->one, &min, &max);
445 if (res == isl_lp_error)
446 goto error;
447 isl_assert(bset->ctx, res != isl_lp_unbounded, goto error);
448 if (bset->sample) {
449 sample = isl_vec_copy(bset->sample);
450 isl_basic_set_free(bset);
451 goto out;
453 if (res == isl_lp_empty || isl_int_lt(max, min)) {
454 sample = empty_sample(bset);
455 goto out;
458 if (isl_int_ne(min, max)) {
459 bset = basic_set_reduced(bset, &T);
460 if (!bset)
461 goto error;
463 res = basic_set_range(bset, obj->el, bset->ctx->one, &min, &max);
464 if (res == isl_lp_error)
465 goto error;
466 isl_assert(bset->ctx, res != isl_lp_unbounded, goto error);
467 if (bset->sample) {
468 sample = isl_vec_copy(bset->sample);
469 isl_basic_set_free(bset);
470 goto out;
472 if (res == isl_lp_empty || isl_int_lt(max, min)) {
473 sample = empty_sample(bset);
474 goto out;
478 sample = sample_scan(bset, min, max);
479 out:
480 if (T) {
481 if (!sample || sample->size == 0)
482 isl_mat_free(ctx, T);
483 else
484 sample = isl_mat_vec_product(ctx, T, sample);
486 isl_vec_free(obj);
487 isl_int_clear(min);
488 isl_int_clear(max);
489 return sample;
490 error:
491 isl_mat_free(ctx, T);
492 isl_basic_set_free(bset);
493 isl_vec_free(obj);
494 isl_int_clear(min);
495 isl_int_clear(max);
496 return NULL;
499 /* Given a basic set "bset" and a value "sample" for the first coordinates
500 * of bset, plug in these values and drop the corresponding coordinates.
502 * We do this by computing the preimage of the transformation
504 * [ 1 0 ]
505 * x = [ s 0 ] x'
506 * [ 0 I ]
508 * where [1 s] is the sample value and I is the identity matrix of the
509 * appropriate dimension.
511 static struct isl_basic_set *plug_in(struct isl_basic_set *bset,
512 struct isl_vec *sample)
514 int i;
515 unsigned total;
516 struct isl_mat *T;
518 if (!bset || !sample)
519 goto error;
521 total = isl_basic_set_total_dim(bset);
522 T = isl_mat_alloc(bset->ctx, 1 + total, 1 + total - (sample->size - 1));
523 if (!T)
524 goto error;
526 for (i = 0; i < sample->size; ++i) {
527 isl_int_set(T->row[i][0], sample->el[i]);
528 isl_seq_clr(T->row[i] + 1, T->n_col - 1);
530 for (i = 0; i < T->n_col - 1; ++i) {
531 isl_seq_clr(T->row[sample->size + i], T->n_col);
532 isl_int_set_si(T->row[sample->size + i][1 + i], 1);
534 isl_vec_free(sample);
536 bset = isl_basic_set_preimage(bset, T);
537 return bset;
538 error:
539 isl_basic_set_free(bset);
540 isl_vec_free(sample);
541 return NULL;
544 /* Given a basic set "bset", return any (possibly non-integer) point
545 * in the basic set.
547 static struct isl_vec *rational_sample(struct isl_basic_set *bset)
549 struct isl_tab *tab;
550 struct isl_vec *sample;
552 if (!bset)
553 return NULL;
555 tab = isl_tab_from_basic_set(bset);
556 sample = isl_tab_get_sample_value(bset->ctx, tab);
557 isl_tab_free(bset->ctx, tab);
559 isl_basic_set_free(bset);
561 return sample;
564 /* Given a rational vector, with the denominator in the first element
565 * of the vector, round up all coordinates.
567 struct isl_vec *isl_vec_ceil(struct isl_vec *vec)
569 int i;
571 vec = isl_vec_cow(vec);
572 if (!vec)
573 return NULL;
575 isl_seq_cdiv_q(vec->el + 1, vec->el + 1, vec->el[0], vec->size - 1);
577 isl_int_set_si(vec->el[0], 1);
579 return vec;
582 /* Given a linear cone "cone" and a rational point "vec",
583 * construct a polyhedron with shifted copies of the constraints in "cone",
584 * i.e., a polyhedron with "cone" as its recession cone, such that each
585 * point x in this polyhedron is such that the unit box positioned at x
586 * lies entirely inside the affine cone 'vec + cone'.
587 * Any rational point in this polyhedron may therefore be rounded up
588 * to yield an integer point that lies inside said affine cone.
590 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
591 * point "vec" by v/d.
592 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
593 * by <a_i, x> - b/d >= 0.
594 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
595 * We prefer this polyhedron over the actual affine cone because it doesn't
596 * require a scaling of the constraints.
597 * If each of the vertices of the unit cube positioned at x lies inside
598 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
599 * We therefore impose that x' = x + \sum e_i, for any selection of unit
600 * vectors lies inside the polyhedron, i.e.,
602 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
604 * The most stringent of these constraints is the one that selects
605 * all negative a_i, so the polyhedron we are looking for has constraints
607 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
609 * Note that if cone were known to have only non-negative rays
610 * (which can be accomplished by a unimodular transformation),
611 * then we would only have to check the points x' = x + e_i
612 * and we only have to add the smallest negative a_i (if any)
613 * instead of the sum of all negative a_i.
615 static struct isl_basic_set *shift_cone(struct isl_basic_set *cone,
616 struct isl_vec *vec)
618 int i, j, k;
619 unsigned total;
621 struct isl_basic_set *shift = NULL;
623 if (!cone || !vec)
624 goto error;
626 isl_assert(cone->ctx, cone->n_eq == 0, goto error);
628 total = isl_basic_set_total_dim(cone);
630 shift = isl_basic_set_alloc_dim(isl_basic_set_get_dim(cone),
631 0, 0, cone->n_ineq);
633 for (i = 0; i < cone->n_ineq; ++i) {
634 k = isl_basic_set_alloc_inequality(shift);
635 if (k < 0)
636 goto error;
637 isl_seq_cpy(shift->ineq[k] + 1, cone->ineq[i] + 1, total);
638 isl_seq_inner_product(shift->ineq[k] + 1, vec->el + 1, total,
639 &shift->ineq[k][0]);
640 isl_int_cdiv_q(shift->ineq[k][0],
641 shift->ineq[k][0], vec->el[0]);
642 isl_int_neg(shift->ineq[k][0], shift->ineq[k][0]);
643 for (j = 0; j < total; ++j) {
644 if (isl_int_is_nonneg(shift->ineq[k][1 + j]))
645 continue;
646 isl_int_add(shift->ineq[k][0],
647 shift->ineq[k][0], shift->ineq[k][1 + j]);
651 isl_basic_set_free(cone);
652 isl_vec_free(vec);
654 return isl_basic_set_finalize(shift);
655 error:
656 isl_basic_set_free(shift);
657 isl_basic_set_free(cone);
658 isl_vec_free(vec);
659 return NULL;
662 /* Given a rational point vec in a (transformed) basic set,
663 * such that cone is the recession cone of the original basic set,
664 * "round up" the rational point to an integer point.
666 * We first check if the rational point just happens to be integer.
667 * If not, we transform the cone in the same way as the basic set,
668 * pick a point x in this cone shifted to the rational point such that
669 * the whole unit cube at x is also inside this affine cone.
670 * Then we simply round up the coordinates of x and return the
671 * resulting integer point.
673 static struct isl_vec *round_up_in_cone(struct isl_vec *vec,
674 struct isl_basic_set *cone, struct isl_mat *U)
676 unsigned total;
678 if (!vec || !cone || !U)
679 goto error;
681 isl_assert(vec->ctx, vec->size != 0, goto error);
682 if (isl_int_is_one(vec->el[0])) {
683 isl_mat_free(vec->ctx, U);
684 isl_basic_set_free(cone);
685 return vec;
688 total = isl_basic_set_total_dim(cone);
689 cone = isl_basic_set_preimage(cone, U);
690 cone = isl_basic_set_remove_dims(cone, 0, total - (vec->size - 1));
692 cone = shift_cone(cone, vec);
694 vec = rational_sample(cone);
695 vec = isl_vec_ceil(vec);
696 return vec;
697 error:
698 isl_mat_free(vec ? vec->ctx : cone ? cone->ctx : NULL, U);
699 isl_vec_free(vec);
700 isl_basic_set_free(cone);
701 return NULL;
704 /* Concatenate two integer vectors, i.e., two vectors with denominator
705 * (stored in element 0) equal to 1.
707 static struct isl_vec *vec_concat(struct isl_vec *vec1, struct isl_vec *vec2)
709 struct isl_vec *vec;
711 if (!vec1 || !vec2)
712 goto error;
713 isl_assert(vec1->ctx, vec1->size > 0, goto error);
714 isl_assert(vec2->ctx, vec2->size > 0, goto error);
715 isl_assert(vec1->ctx, isl_int_is_one(vec1->el[0]), goto error);
716 isl_assert(vec2->ctx, isl_int_is_one(vec2->el[0]), goto error);
718 vec = isl_vec_alloc(vec1->ctx, vec1->size + vec2->size - 1);
719 if (!vec)
720 goto error;
722 isl_seq_cpy(vec->el, vec1->el, vec1->size);
723 isl_seq_cpy(vec->el + vec1->size, vec2->el + 1, vec2->size - 1);
725 isl_vec_free(vec1);
726 isl_vec_free(vec2);
728 return vec;
729 error:
730 isl_vec_free(vec1);
731 isl_vec_free(vec2);
732 return NULL;
735 /* Drop all constraints in bset that involve any of the dimensions
736 * first to first+n-1.
738 static struct isl_basic_set *drop_constraints_involving
739 (struct isl_basic_set *bset, unsigned first, unsigned n)
741 int i;
743 if (!bset)
744 return NULL;
746 bset = isl_basic_set_cow(bset);
748 for (i = bset->n_ineq - 1; i >= 0; --i) {
749 if (isl_seq_first_non_zero(bset->ineq[i] + 1 + first, n) == -1)
750 continue;
751 isl_basic_set_drop_inequality(bset, i);
754 return bset;
757 /* Give a basic set "bset" with recession cone "cone", compute and
758 * return an integer point in bset, if any.
760 * If the recession cone is full-dimensional, then we know that
761 * bset contains an infinite number of integer points and it is
762 * fairly easy to pick one of them.
763 * If the recession cone is not full-dimensional, then we first
764 * transform bset such that the bounded directions appear as
765 * the first dimensions of the transformed basic set.
766 * We do this by using a unimodular transformation that transforms
767 * the equalities in the recession cone to equalities on the first
768 * dimensions.
770 * The transformed set is then projected onto its bounded dimensions.
771 * Note that to compute this projection, we can simply drop all constraints
772 * involving any of the unbounded dimensions since these constraints
773 * cannot be combined to produce a constraint on the bounded dimensions.
774 * To see this, assume that there is such a combination of constraints
775 * that produces a constraint on the bounded dimensions. This means
776 * that some combination of the unbounded dimensions has both an upper
777 * bound and a lower bound in terms of the bounded dimensions, but then
778 * this combination would be a bounded direction too and would have been
779 * transformed into a bounded dimensions.
781 * We then compute a sample value in the bounded dimensions.
782 * If no such value can be found, then the original set did not contain
783 * any integer points and we are done.
784 * Otherwise, we plug in the value we found in the bounded dimensions,
785 * project out these bounded dimensions and end up with a set with
786 * a full-dimensional recession cone.
787 * A sample point in this set is computed by "rounding up" any
788 * rational point in the set.
790 * The sample points in the bounded and unbounded dimensions are
791 * then combined into a single sample point and transformed back
792 * to the original space.
794 static struct isl_vec *sample_with_cone(struct isl_basic_set *bset,
795 struct isl_basic_set *cone)
797 unsigned total;
798 unsigned cone_dim;
799 struct isl_mat *M, *U;
800 struct isl_vec *sample;
801 struct isl_vec *cone_sample;
802 struct isl_ctx *ctx;
803 struct isl_basic_set *bounded;
805 if (!bset || !cone)
806 goto error;
808 ctx = bset->ctx;
809 total = isl_basic_set_total_dim(cone);
810 cone_dim = total - cone->n_eq;
812 M = isl_mat_sub_alloc(bset->ctx, cone->eq, 0, cone->n_eq, 1, total);
813 M = isl_mat_left_hermite(bset->ctx, M, 0, &U, NULL);
814 if (!M)
815 goto error;
816 isl_mat_free(bset->ctx, M);
818 U = isl_mat_lin_to_aff(bset->ctx, U);
819 bset = isl_basic_set_preimage(bset, isl_mat_copy(bset->ctx, U));
821 bounded = isl_basic_set_copy(bset);
822 bounded = drop_constraints_involving(bounded, total - cone_dim, cone_dim);
823 bounded = isl_basic_set_drop_dims(bounded, total - cone_dim, cone_dim);
824 sample = sample_bounded(bounded);
825 if (!sample || sample->size == 0) {
826 isl_basic_set_free(bset);
827 isl_basic_set_free(cone);
828 isl_mat_free(ctx, U);
829 return sample;
831 bset = plug_in(bset, isl_vec_copy(sample));
832 cone_sample = rational_sample(bset);
833 cone_sample = round_up_in_cone(cone_sample, cone, isl_mat_copy(ctx, U));
834 sample = vec_concat(sample, cone_sample);
835 sample = isl_mat_vec_product(ctx, U, sample);
836 return sample;
837 error:
838 isl_basic_set_free(cone);
839 isl_basic_set_free(bset);
840 return NULL;
843 /* Compute and return a sample point in bset using generalized basis
844 * reduction. We first check if the input set has a non-trivial
845 * recession cone. If so, we perform some extra preprocessing in
846 * sample_with_cone. Otherwise, we directly perform generalized basis
847 * reduction.
849 static struct isl_vec *gbr_sample_no_lineality(struct isl_basic_set *bset)
851 unsigned dim;
852 struct isl_basic_set *cone;
854 dim = isl_basic_set_total_dim(bset);
856 cone = isl_basic_set_recession_cone(isl_basic_set_copy(bset));
858 if (cone->n_eq < dim)
859 return sample_with_cone(bset, cone);
861 isl_basic_set_free(cone);
862 return sample_bounded(bset);
865 static struct isl_vec *pip_sample_no_lineality(struct isl_basic_set *bset)
867 struct isl_mat *T;
868 struct isl_ctx *ctx;
869 struct isl_vec *sample;
871 bset = isl_basic_set_skew_to_positive_orthant(bset, &T);
872 if (!bset)
873 return NULL;
875 ctx = bset->ctx;
876 sample = isl_pip_basic_set_sample(bset);
878 if (sample && sample->size != 0)
879 sample = isl_mat_vec_product(ctx, T, sample);
880 else
881 isl_mat_free(ctx, T);
883 return sample;
886 static struct isl_vec *sample_no_lineality(struct isl_basic_set *bset)
888 unsigned dim;
890 if (isl_basic_set_fast_is_empty(bset))
891 return empty_sample(bset);
892 if (bset->n_eq > 0)
893 return sample_eq(bset, sample_no_lineality);
894 dim = isl_basic_set_total_dim(bset);
895 if (dim == 0)
896 return zero_sample(bset);
897 if (dim == 1)
898 return interval_sample(bset);
900 switch (bset->ctx->ilp_solver) {
901 case ISL_ILP_PIP:
902 return pip_sample_no_lineality(bset);
903 case ISL_ILP_GBR:
904 return gbr_sample_no_lineality(bset);
906 isl_assert(bset->ctx, 0, );
907 isl_basic_set_free(bset);
908 return NULL;
911 /* Compute an integer point in "bset" with a lineality space that
912 * is orthogonal to the constraints in "bounds".
914 * We first perform a unimodular transformation on bset that
915 * make the constraints in bounds (and therefore all constraints in bset)
916 * only involve the first dimensions. The remaining dimensions
917 * then do not appear in any constraints and we can select any value
918 * for them, say zero. We therefore project out this final dimensions
919 * and plug in the value zero later. This is accomplished by simply
920 * dropping the final columns of the unimodular transformation.
922 static struct isl_vec *sample_lineality(struct isl_basic_set *bset,
923 struct isl_mat *bounds)
925 struct isl_mat *U = NULL;
926 unsigned old_dim, new_dim;
927 struct isl_vec *sample;
928 struct isl_ctx *ctx;
930 if (!bset || !bounds)
931 goto error;
933 ctx = bset->ctx;
934 old_dim = isl_basic_set_n_dim(bset);
935 new_dim = bounds->n_row - 1;
936 bounds = isl_mat_left_hermite(ctx, bounds, 0, &U, NULL);
937 if (!bounds)
938 goto error;
939 U = isl_mat_drop_cols(ctx, U, 1 + new_dim, old_dim - new_dim);
940 bset = isl_basic_set_preimage(bset, isl_mat_copy(ctx, U));
941 if (!bset)
942 goto error;
943 isl_mat_free(ctx, bounds);
945 sample = sample_no_lineality(bset);
946 if (sample && sample->size != 0)
947 sample = isl_mat_vec_product(ctx, U, sample);
948 else
949 isl_mat_free(ctx, U);
950 return sample;
951 error:
952 isl_mat_free(ctx, bounds);
953 isl_mat_free(ctx, U);
954 isl_basic_set_free(bset);
955 return NULL;
958 struct isl_vec *isl_basic_set_sample(struct isl_basic_set *bset)
960 struct isl_ctx *ctx;
961 struct isl_mat *bounds;
962 unsigned dim;
963 if (!bset)
964 return NULL;
966 ctx = bset->ctx;
967 if (isl_basic_set_fast_is_empty(bset))
968 return empty_sample(bset);
970 dim = isl_basic_set_n_dim(bset);
971 isl_assert(ctx, isl_basic_set_n_param(bset) == 0, goto error);
972 isl_assert(ctx, bset->n_div == 0, goto error);
974 if (bset->sample && bset->sample->size == 1 + dim) {
975 int contains = isl_basic_set_contains(bset, bset->sample);
976 if (contains < 0)
977 goto error;
978 if (contains) {
979 struct isl_vec *sample = isl_vec_copy(bset->sample);
980 isl_basic_set_free(bset);
981 return sample;
984 isl_vec_free(bset->sample);
985 bset->sample = NULL;
987 if (bset->n_eq > 0)
988 return sample_eq(bset, isl_basic_set_sample);
989 if (dim == 0)
990 return zero_sample(bset);
991 if (dim == 1)
992 return interval_sample(bset);
993 bounds = independent_bounds(ctx, bset);
994 if (!bounds)
995 goto error;
997 if (bounds->n_row == 1) {
998 isl_mat_free(ctx, bounds);
999 return zero_sample(bset);
1001 if (bounds->n_row < 1 + dim)
1002 return sample_lineality(bset, bounds);
1004 isl_mat_free(ctx, bounds);
1005 return sample_no_lineality(bset);
1006 error:
1007 isl_basic_set_free(bset);
1008 return NULL;