2 * Copyright 2008-2009 Katholieke Universiteit Leuven
4 * Use of this software is governed by the MIT license
6 * Written by Sven Verdoolaege, K.U.Leuven, Departement
7 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
10 #include <isl_ctx_private.h>
11 #include <isl_map_private.h>
12 #include "isl_sample.h"
16 #include "isl_equalities.h"
18 #include "isl_basis_reduction.h"
19 #include <isl_factorization.h>
20 #include <isl_point_private.h>
21 #include <isl_options_private.h>
22 #include <isl_vec_private.h>
24 #include <bset_from_bmap.c>
25 #include <set_to_map.c>
27 static __isl_give isl_vec
*isl_basic_set_sample_bounded(
28 __isl_take isl_basic_set
*bset
);
30 static __isl_give isl_vec
*empty_sample(__isl_take isl_basic_set
*bset
)
34 vec
= isl_vec_alloc(bset
->ctx
, 0);
35 isl_basic_set_free(bset
);
39 /* Construct a zero sample of the same dimension as bset.
40 * As a special case, if bset is zero-dimensional, this
41 * function creates a zero-dimensional sample point.
43 static __isl_give isl_vec
*zero_sample(__isl_take isl_basic_set
*bset
)
46 struct isl_vec
*sample
;
48 dim
= isl_basic_set_dim(bset
, isl_dim_all
);
51 sample
= isl_vec_alloc(bset
->ctx
, 1 + dim
);
53 isl_int_set_si(sample
->el
[0], 1);
54 isl_seq_clr(sample
->el
+ 1, dim
);
56 isl_basic_set_free(bset
);
59 isl_basic_set_free(bset
);
63 static __isl_give isl_vec
*interval_sample(__isl_take isl_basic_set
*bset
)
67 struct isl_vec
*sample
;
69 bset
= isl_basic_set_simplify(bset
);
72 if (isl_basic_set_plain_is_empty(bset
))
73 return empty_sample(bset
);
74 if (bset
->n_eq
== 0 && bset
->n_ineq
== 0)
75 return zero_sample(bset
);
77 sample
= isl_vec_alloc(bset
->ctx
, 2);
82 isl_int_set_si(sample
->block
.data
[0], 1);
85 isl_assert(bset
->ctx
, bset
->n_eq
== 1, goto error
);
86 isl_assert(bset
->ctx
, bset
->n_ineq
== 0, goto error
);
87 if (isl_int_is_one(bset
->eq
[0][1]))
88 isl_int_neg(sample
->el
[1], bset
->eq
[0][0]);
90 isl_assert(bset
->ctx
, isl_int_is_negone(bset
->eq
[0][1]),
92 isl_int_set(sample
->el
[1], bset
->eq
[0][0]);
94 isl_basic_set_free(bset
);
99 if (isl_int_is_one(bset
->ineq
[0][1]))
100 isl_int_neg(sample
->block
.data
[1], bset
->ineq
[0][0]);
102 isl_int_set(sample
->block
.data
[1], bset
->ineq
[0][0]);
103 for (i
= 1; i
< bset
->n_ineq
; ++i
) {
104 isl_seq_inner_product(sample
->block
.data
,
105 bset
->ineq
[i
], 2, &t
);
106 if (isl_int_is_neg(t
))
110 if (i
< bset
->n_ineq
) {
111 isl_vec_free(sample
);
112 return empty_sample(bset
);
115 isl_basic_set_free(bset
);
118 isl_basic_set_free(bset
);
119 isl_vec_free(sample
);
123 /* Find a sample integer point, if any, in bset, which is known
124 * to have equalities. If bset contains no integer points, then
125 * return a zero-length vector.
126 * We simply remove the known equalities, compute a sample
127 * in the resulting bset, using the specified recurse function,
128 * and then transform the sample back to the original space.
130 static __isl_give isl_vec
*sample_eq(__isl_take isl_basic_set
*bset
,
131 __isl_give isl_vec
*(*recurse
)(__isl_take isl_basic_set
*))
134 struct isl_vec
*sample
;
139 bset
= isl_basic_set_remove_equalities(bset
, &T
, NULL
);
140 sample
= recurse(bset
);
141 if (!sample
|| sample
->size
== 0)
144 sample
= isl_mat_vec_product(T
, sample
);
148 /* Return a matrix containing the equalities of the tableau
149 * in constraint form. The tableau is assumed to have
150 * an associated bset that has been kept up-to-date.
152 static struct isl_mat
*tab_equalities(struct isl_tab
*tab
)
157 struct isl_basic_set
*bset
;
162 bset
= isl_tab_peek_bset(tab
);
163 isl_assert(tab
->mat
->ctx
, bset
, return NULL
);
165 n_eq
= tab
->n_var
- tab
->n_col
+ tab
->n_dead
;
166 if (tab
->empty
|| n_eq
== 0)
167 return isl_mat_alloc(tab
->mat
->ctx
, 0, tab
->n_var
);
168 if (n_eq
== tab
->n_var
)
169 return isl_mat_identity(tab
->mat
->ctx
, tab
->n_var
);
171 eq
= isl_mat_alloc(tab
->mat
->ctx
, n_eq
, tab
->n_var
);
174 for (i
= 0, j
= 0; i
< tab
->n_con
; ++i
) {
175 if (tab
->con
[i
].is_row
)
177 if (tab
->con
[i
].index
>= 0 && tab
->con
[i
].index
>= tab
->n_dead
)
180 isl_seq_cpy(eq
->row
[j
], bset
->eq
[i
] + 1, tab
->n_var
);
182 isl_seq_cpy(eq
->row
[j
],
183 bset
->ineq
[i
- bset
->n_eq
] + 1, tab
->n_var
);
186 isl_assert(bset
->ctx
, j
== n_eq
, goto error
);
193 /* Compute and return an initial basis for the bounded tableau "tab".
195 * If the tableau is either full-dimensional or zero-dimensional,
196 * the we simply return an identity matrix.
197 * Otherwise, we construct a basis whose first directions correspond
200 static struct isl_mat
*initial_basis(struct isl_tab
*tab
)
206 tab
->n_unbounded
= 0;
207 tab
->n_zero
= n_eq
= tab
->n_var
- tab
->n_col
+ tab
->n_dead
;
208 if (tab
->empty
|| n_eq
== 0 || n_eq
== tab
->n_var
)
209 return isl_mat_identity(tab
->mat
->ctx
, 1 + tab
->n_var
);
211 eq
= tab_equalities(tab
);
212 eq
= isl_mat_left_hermite(eq
, 0, NULL
, &Q
);
217 Q
= isl_mat_lin_to_aff(Q
);
221 /* Compute the minimum of the current ("level") basis row over "tab"
222 * and store the result in position "level" of "min".
224 * This function assumes that at least one more row and at least
225 * one more element in the constraint array are available in the tableau.
227 static enum isl_lp_result
compute_min(isl_ctx
*ctx
, struct isl_tab
*tab
,
228 __isl_keep isl_vec
*min
, int level
)
230 return isl_tab_min(tab
, tab
->basis
->row
[1 + level
],
231 ctx
->one
, &min
->el
[level
], NULL
, 0);
234 /* Compute the maximum of the current ("level") basis row over "tab"
235 * and store the result in position "level" of "max".
237 * This function assumes that at least one more row and at least
238 * one more element in the constraint array are available in the tableau.
240 static enum isl_lp_result
compute_max(isl_ctx
*ctx
, struct isl_tab
*tab
,
241 __isl_keep isl_vec
*max
, int level
)
243 enum isl_lp_result res
;
244 unsigned dim
= tab
->n_var
;
246 isl_seq_neg(tab
->basis
->row
[1 + level
] + 1,
247 tab
->basis
->row
[1 + level
] + 1, dim
);
248 res
= isl_tab_min(tab
, tab
->basis
->row
[1 + level
],
249 ctx
->one
, &max
->el
[level
], NULL
, 0);
250 isl_seq_neg(tab
->basis
->row
[1 + level
] + 1,
251 tab
->basis
->row
[1 + level
] + 1, dim
);
252 isl_int_neg(max
->el
[level
], max
->el
[level
]);
257 /* Perform a greedy search for an integer point in the set represented
258 * by "tab", given that the minimal rational value (rounded up to the
259 * nearest integer) at "level" is smaller than the maximal rational
260 * value (rounded down to the nearest integer).
262 * Return 1 if we have found an integer point (if tab->n_unbounded > 0
263 * then we may have only found integer values for the bounded dimensions
264 * and it is the responsibility of the caller to extend this solution
265 * to the unbounded dimensions).
266 * Return 0 if greedy search did not result in a solution.
267 * Return -1 if some error occurred.
269 * We assign a value half-way between the minimum and the maximum
270 * to the current dimension and check if the minimal value of the
271 * next dimension is still smaller than (or equal) to the maximal value.
272 * We continue this process until either
273 * - the minimal value (rounded up) is greater than the maximal value
274 * (rounded down). In this case, greedy search has failed.
275 * - we have exhausted all bounded dimensions, meaning that we have
277 * - the sample value of the tableau is integral.
278 * - some error has occurred.
280 static int greedy_search(isl_ctx
*ctx
, struct isl_tab
*tab
,
281 __isl_keep isl_vec
*min
, __isl_keep isl_vec
*max
, int level
)
283 struct isl_tab_undo
*snap
;
284 enum isl_lp_result res
;
286 snap
= isl_tab_snap(tab
);
289 isl_int_add(tab
->basis
->row
[1 + level
][0],
290 min
->el
[level
], max
->el
[level
]);
291 isl_int_fdiv_q_ui(tab
->basis
->row
[1 + level
][0],
292 tab
->basis
->row
[1 + level
][0], 2);
293 isl_int_neg(tab
->basis
->row
[1 + level
][0],
294 tab
->basis
->row
[1 + level
][0]);
295 if (isl_tab_add_valid_eq(tab
, tab
->basis
->row
[1 + level
]) < 0)
297 isl_int_set_si(tab
->basis
->row
[1 + level
][0], 0);
299 if (++level
>= tab
->n_var
- tab
->n_unbounded
)
301 if (isl_tab_sample_is_integer(tab
))
304 res
= compute_min(ctx
, tab
, min
, level
);
305 if (res
== isl_lp_error
)
307 if (res
!= isl_lp_ok
)
308 isl_die(ctx
, isl_error_internal
,
309 "expecting bounded rational solution",
311 res
= compute_max(ctx
, tab
, max
, level
);
312 if (res
== isl_lp_error
)
314 if (res
!= isl_lp_ok
)
315 isl_die(ctx
, isl_error_internal
,
316 "expecting bounded rational solution",
318 } while (isl_int_le(min
->el
[level
], max
->el
[level
]));
320 if (isl_tab_rollback(tab
, snap
) < 0)
326 /* Given a tableau representing a set, find and return
327 * an integer point in the set, if there is any.
329 * We perform a depth first search
330 * for an integer point, by scanning all possible values in the range
331 * attained by a basis vector, where an initial basis may have been set
332 * by the calling function. Otherwise an initial basis that exploits
333 * the equalities in the tableau is created.
334 * tab->n_zero is currently ignored and is clobbered by this function.
336 * The tableau is allowed to have unbounded direction, but then
337 * the calling function needs to set an initial basis, with the
338 * unbounded directions last and with tab->n_unbounded set
339 * to the number of unbounded directions.
340 * Furthermore, the calling functions needs to add shifted copies
341 * of all constraints involving unbounded directions to ensure
342 * that any feasible rational value in these directions can be rounded
343 * up to yield a feasible integer value.
344 * In particular, let B define the given basis x' = B x
345 * and let T be the inverse of B, i.e., X = T x'.
346 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
347 * or a T x' + c >= 0 in terms of the given basis. Assume that
348 * the bounded directions have an integer value, then we can safely
349 * round up the values for the unbounded directions if we make sure
350 * that x' not only satisfies the original constraint, but also
351 * the constraint "a T x' + c + s >= 0" with s the sum of all
352 * negative values in the last n_unbounded entries of "a T".
353 * The calling function therefore needs to add the constraint
354 * a x + c + s >= 0. The current function then scans the first
355 * directions for an integer value and once those have been found,
356 * it can compute "T ceil(B x)" to yield an integer point in the set.
357 * Note that during the search, the first rows of B may be changed
358 * by a basis reduction, but the last n_unbounded rows of B remain
359 * unaltered and are also not mixed into the first rows.
361 * The search is implemented iteratively. "level" identifies the current
362 * basis vector. "init" is true if we want the first value at the current
363 * level and false if we want the next value.
365 * At the start of each level, we first check if we can find a solution
366 * using greedy search. If not, we continue with the exhaustive search.
368 * The initial basis is the identity matrix. If the range in some direction
369 * contains more than one integer value, we perform basis reduction based
370 * on the value of ctx->opt->gbr
371 * - ISL_GBR_NEVER: never perform basis reduction
372 * - ISL_GBR_ONCE: only perform basis reduction the first
373 * time such a range is encountered
374 * - ISL_GBR_ALWAYS: always perform basis reduction when
375 * such a range is encountered
377 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
378 * reduction computation to return early. That is, as soon as it
379 * finds a reasonable first direction.
381 __isl_give isl_vec
*isl_tab_sample(struct isl_tab
*tab
)
386 struct isl_vec
*sample
;
389 enum isl_lp_result res
;
393 struct isl_tab_undo
**snap
;
398 return isl_vec_alloc(tab
->mat
->ctx
, 0);
401 tab
->basis
= initial_basis(tab
);
404 isl_assert(tab
->mat
->ctx
, tab
->basis
->n_row
== tab
->n_var
+ 1,
406 isl_assert(tab
->mat
->ctx
, tab
->basis
->n_col
== tab
->n_var
+ 1,
413 if (tab
->n_unbounded
== tab
->n_var
) {
414 sample
= isl_tab_get_sample_value(tab
);
415 sample
= isl_mat_vec_product(isl_mat_copy(tab
->basis
), sample
);
416 sample
= isl_vec_ceil(sample
);
417 sample
= isl_mat_vec_inverse_product(isl_mat_copy(tab
->basis
),
422 if (isl_tab_extend_cons(tab
, dim
+ 1) < 0)
425 min
= isl_vec_alloc(ctx
, dim
);
426 max
= isl_vec_alloc(ctx
, dim
);
427 snap
= isl_alloc_array(ctx
, struct isl_tab_undo
*, dim
);
429 if (!min
|| !max
|| !snap
)
440 res
= compute_min(ctx
, tab
, min
, level
);
441 if (res
== isl_lp_error
)
443 if (res
!= isl_lp_ok
)
444 isl_die(ctx
, isl_error_internal
,
445 "expecting bounded rational solution",
447 if (isl_tab_sample_is_integer(tab
))
449 res
= compute_max(ctx
, tab
, max
, level
);
450 if (res
== isl_lp_error
)
452 if (res
!= isl_lp_ok
)
453 isl_die(ctx
, isl_error_internal
,
454 "expecting bounded rational solution",
456 if (isl_tab_sample_is_integer(tab
))
458 choice
= isl_int_lt(min
->el
[level
], max
->el
[level
]);
461 g
= greedy_search(ctx
, tab
, min
, max
, level
);
467 if (!reduced
&& choice
&&
468 ctx
->opt
->gbr
!= ISL_GBR_NEVER
) {
469 unsigned gbr_only_first
;
470 if (ctx
->opt
->gbr
== ISL_GBR_ONCE
)
471 ctx
->opt
->gbr
= ISL_GBR_NEVER
;
473 gbr_only_first
= ctx
->opt
->gbr_only_first
;
474 ctx
->opt
->gbr_only_first
=
475 ctx
->opt
->gbr
== ISL_GBR_ALWAYS
;
476 tab
= isl_tab_compute_reduced_basis(tab
);
477 ctx
->opt
->gbr_only_first
= gbr_only_first
;
478 if (!tab
|| !tab
->basis
)
484 snap
[level
] = isl_tab_snap(tab
);
486 isl_int_add_ui(min
->el
[level
], min
->el
[level
], 1);
488 if (isl_int_gt(min
->el
[level
], max
->el
[level
])) {
492 if (isl_tab_rollback(tab
, snap
[level
]) < 0)
496 isl_int_neg(tab
->basis
->row
[1 + level
][0], min
->el
[level
]);
497 if (isl_tab_add_valid_eq(tab
, tab
->basis
->row
[1 + level
]) < 0)
499 isl_int_set_si(tab
->basis
->row
[1 + level
][0], 0);
500 if (level
+ tab
->n_unbounded
< dim
- 1) {
509 sample
= isl_tab_get_sample_value(tab
);
512 if (tab
->n_unbounded
&& !isl_int_is_one(sample
->el
[0])) {
513 sample
= isl_mat_vec_product(isl_mat_copy(tab
->basis
),
515 sample
= isl_vec_ceil(sample
);
516 sample
= isl_mat_vec_inverse_product(
517 isl_mat_copy(tab
->basis
), sample
);
520 sample
= isl_vec_alloc(ctx
, 0);
535 static __isl_give isl_vec
*sample_bounded(__isl_take isl_basic_set
*bset
);
537 /* Internal data for factored_sample.
538 * "sample" collects the sample and may get reset to a zero-length vector
539 * signaling the absence of a sample vector.
540 * "pos" is the position of the contribution of the next factor.
542 struct isl_factored_sample_data
{
547 /* isl_factorizer_every_factor_basic_set callback that extends
548 * the sample in data->sample with the contribution
549 * of the factor "bset".
550 * If "bset" turns out to be empty, then the product is empty too and
551 * no further factors need to be considered.
553 static isl_bool
factor_sample(__isl_keep isl_basic_set
*bset
, void *user
)
555 struct isl_factored_sample_data
*data
= user
;
559 n
= isl_basic_set_dim(bset
, isl_dim_set
);
561 return isl_bool_error
;
563 sample
= sample_bounded(isl_basic_set_copy(bset
));
565 return isl_bool_error
;
566 if (sample
->size
== 0) {
567 isl_vec_free(data
->sample
);
568 data
->sample
= sample
;
569 return isl_bool_false
;
571 isl_seq_cpy(data
->sample
->el
+ data
->pos
, sample
->el
+ 1, n
);
572 isl_vec_free(sample
);
575 return isl_bool_true
;
578 /* Compute a sample point of the given basic set, based on the given,
579 * non-trivial factorization.
581 static __isl_give isl_vec
*factored_sample(__isl_take isl_basic_set
*bset
,
582 __isl_take isl_factorizer
*f
)
584 struct isl_factored_sample_data data
= { NULL
};
589 ctx
= isl_basic_set_get_ctx(bset
);
590 total
= isl_basic_set_dim(bset
, isl_dim_all
);
591 if (!ctx
|| total
< 0)
594 data
.sample
= isl_vec_alloc(ctx
, 1 + total
);
597 isl_int_set_si(data
.sample
->el
[0], 1);
600 every
= isl_factorizer_every_factor_basic_set(f
, &factor_sample
, &data
);
602 data
.sample
= isl_vec_free(data
.sample
);
606 morph
= isl_morph_inverse(isl_morph_copy(f
->morph
));
607 data
.sample
= isl_morph_vec(morph
, data
.sample
);
610 isl_basic_set_free(bset
);
611 isl_factorizer_free(f
);
614 isl_basic_set_free(bset
);
615 isl_factorizer_free(f
);
616 isl_vec_free(data
.sample
);
620 /* Given a basic set that is known to be bounded, find and return
621 * an integer point in the basic set, if there is any.
623 * After handling some trivial cases, we construct a tableau
624 * and then use isl_tab_sample to find a sample, passing it
625 * the identity matrix as initial basis.
627 static __isl_give isl_vec
*sample_bounded(__isl_take isl_basic_set
*bset
)
630 struct isl_vec
*sample
;
631 struct isl_tab
*tab
= NULL
;
637 if (isl_basic_set_plain_is_empty(bset
))
638 return empty_sample(bset
);
640 dim
= isl_basic_set_dim(bset
, isl_dim_all
);
642 bset
= isl_basic_set_free(bset
);
644 return zero_sample(bset
);
646 return interval_sample(bset
);
648 return sample_eq(bset
, sample_bounded
);
650 f
= isl_basic_set_factorizer(bset
);
654 return factored_sample(bset
, f
);
655 isl_factorizer_free(f
);
657 tab
= isl_tab_from_basic_set(bset
, 1);
658 if (tab
&& tab
->empty
) {
660 ISL_F_SET(bset
, ISL_BASIC_SET_EMPTY
);
661 sample
= isl_vec_alloc(isl_basic_set_get_ctx(bset
), 0);
662 isl_basic_set_free(bset
);
666 if (!ISL_F_ISSET(bset
, ISL_BASIC_SET_NO_IMPLICIT
))
667 if (isl_tab_detect_implicit_equalities(tab
) < 0)
670 sample
= isl_tab_sample(tab
);
674 if (sample
->size
> 0) {
675 isl_vec_free(bset
->sample
);
676 bset
->sample
= isl_vec_copy(sample
);
679 isl_basic_set_free(bset
);
683 isl_basic_set_free(bset
);
688 /* Given a basic set "bset" and a value "sample" for the first coordinates
689 * of bset, plug in these values and drop the corresponding coordinates.
691 * We do this by computing the preimage of the transformation
697 * where [1 s] is the sample value and I is the identity matrix of the
698 * appropriate dimension.
700 static __isl_give isl_basic_set
*plug_in(__isl_take isl_basic_set
*bset
,
701 __isl_take isl_vec
*sample
)
707 total
= isl_basic_set_dim(bset
, isl_dim_all
);
708 if (total
< 0 || !sample
)
711 T
= isl_mat_alloc(bset
->ctx
, 1 + total
, 1 + total
- (sample
->size
- 1));
715 for (i
= 0; i
< sample
->size
; ++i
) {
716 isl_int_set(T
->row
[i
][0], sample
->el
[i
]);
717 isl_seq_clr(T
->row
[i
] + 1, T
->n_col
- 1);
719 for (i
= 0; i
< T
->n_col
- 1; ++i
) {
720 isl_seq_clr(T
->row
[sample
->size
+ i
], T
->n_col
);
721 isl_int_set_si(T
->row
[sample
->size
+ i
][1 + i
], 1);
723 isl_vec_free(sample
);
725 bset
= isl_basic_set_preimage(bset
, T
);
728 isl_basic_set_free(bset
);
729 isl_vec_free(sample
);
733 /* Given a basic set "bset", return any (possibly non-integer) point
736 static __isl_give isl_vec
*rational_sample(__isl_take isl_basic_set
*bset
)
739 struct isl_vec
*sample
;
744 tab
= isl_tab_from_basic_set(bset
, 0);
745 sample
= isl_tab_get_sample_value(tab
);
748 isl_basic_set_free(bset
);
753 /* Given a linear cone "cone" and a rational point "vec",
754 * construct a polyhedron with shifted copies of the constraints in "cone",
755 * i.e., a polyhedron with "cone" as its recession cone, such that each
756 * point x in this polyhedron is such that the unit box positioned at x
757 * lies entirely inside the affine cone 'vec + cone'.
758 * Any rational point in this polyhedron may therefore be rounded up
759 * to yield an integer point that lies inside said affine cone.
761 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
762 * point "vec" by v/d.
763 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
764 * by <a_i, x> - b/d >= 0.
765 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
766 * We prefer this polyhedron over the actual affine cone because it doesn't
767 * require a scaling of the constraints.
768 * If each of the vertices of the unit cube positioned at x lies inside
769 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
770 * We therefore impose that x' = x + \sum e_i, for any selection of unit
771 * vectors lies inside the polyhedron, i.e.,
773 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
775 * The most stringent of these constraints is the one that selects
776 * all negative a_i, so the polyhedron we are looking for has constraints
778 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
780 * Note that if cone were known to have only non-negative rays
781 * (which can be accomplished by a unimodular transformation),
782 * then we would only have to check the points x' = x + e_i
783 * and we only have to add the smallest negative a_i (if any)
784 * instead of the sum of all negative a_i.
786 static __isl_give isl_basic_set
*shift_cone(__isl_take isl_basic_set
*cone
,
787 __isl_take isl_vec
*vec
)
792 struct isl_basic_set
*shift
= NULL
;
794 total
= isl_basic_set_dim(cone
, isl_dim_all
);
795 if (total
< 0 || !vec
)
798 isl_assert(cone
->ctx
, cone
->n_eq
== 0, goto error
);
800 shift
= isl_basic_set_alloc_space(isl_basic_set_get_space(cone
),
803 for (i
= 0; i
< cone
->n_ineq
; ++i
) {
804 k
= isl_basic_set_alloc_inequality(shift
);
807 isl_seq_cpy(shift
->ineq
[k
] + 1, cone
->ineq
[i
] + 1, total
);
808 isl_seq_inner_product(shift
->ineq
[k
] + 1, vec
->el
+ 1, total
,
810 isl_int_cdiv_q(shift
->ineq
[k
][0],
811 shift
->ineq
[k
][0], vec
->el
[0]);
812 isl_int_neg(shift
->ineq
[k
][0], shift
->ineq
[k
][0]);
813 for (j
= 0; j
< total
; ++j
) {
814 if (isl_int_is_nonneg(shift
->ineq
[k
][1 + j
]))
816 isl_int_add(shift
->ineq
[k
][0],
817 shift
->ineq
[k
][0], shift
->ineq
[k
][1 + j
]);
821 isl_basic_set_free(cone
);
824 return isl_basic_set_finalize(shift
);
826 isl_basic_set_free(shift
);
827 isl_basic_set_free(cone
);
832 /* Given a rational point vec in a (transformed) basic set,
833 * such that cone is the recession cone of the original basic set,
834 * "round up" the rational point to an integer point.
836 * We first check if the rational point just happens to be integer.
837 * If not, we transform the cone in the same way as the basic set,
838 * pick a point x in this cone shifted to the rational point such that
839 * the whole unit cube at x is also inside this affine cone.
840 * Then we simply round up the coordinates of x and return the
841 * resulting integer point.
843 static __isl_give isl_vec
*round_up_in_cone(__isl_take isl_vec
*vec
,
844 __isl_take isl_basic_set
*cone
, __isl_take isl_mat
*U
)
848 if (!vec
|| !cone
|| !U
)
851 isl_assert(vec
->ctx
, vec
->size
!= 0, goto error
);
852 if (isl_int_is_one(vec
->el
[0])) {
854 isl_basic_set_free(cone
);
858 total
= isl_basic_set_dim(cone
, isl_dim_all
);
861 cone
= isl_basic_set_preimage(cone
, U
);
862 cone
= isl_basic_set_remove_dims(cone
, isl_dim_set
,
863 0, total
- (vec
->size
- 1));
865 cone
= shift_cone(cone
, vec
);
867 vec
= rational_sample(cone
);
868 vec
= isl_vec_ceil(vec
);
873 isl_basic_set_free(cone
);
877 /* Concatenate two integer vectors, i.e., two vectors with denominator
878 * (stored in element 0) equal to 1.
880 static __isl_give isl_vec
*vec_concat(__isl_take isl_vec
*vec1
,
881 __isl_take isl_vec
*vec2
)
887 isl_assert(vec1
->ctx
, vec1
->size
> 0, goto error
);
888 isl_assert(vec2
->ctx
, vec2
->size
> 0, goto error
);
889 isl_assert(vec1
->ctx
, isl_int_is_one(vec1
->el
[0]), goto error
);
890 isl_assert(vec2
->ctx
, isl_int_is_one(vec2
->el
[0]), goto error
);
892 vec
= isl_vec_alloc(vec1
->ctx
, vec1
->size
+ vec2
->size
- 1);
896 isl_seq_cpy(vec
->el
, vec1
->el
, vec1
->size
);
897 isl_seq_cpy(vec
->el
+ vec1
->size
, vec2
->el
+ 1, vec2
->size
- 1);
909 /* Give a basic set "bset" with recession cone "cone", compute and
910 * return an integer point in bset, if any.
912 * If the recession cone is full-dimensional, then we know that
913 * bset contains an infinite number of integer points and it is
914 * fairly easy to pick one of them.
915 * If the recession cone is not full-dimensional, then we first
916 * transform bset such that the bounded directions appear as
917 * the first dimensions of the transformed basic set.
918 * We do this by using a unimodular transformation that transforms
919 * the equalities in the recession cone to equalities on the first
922 * The transformed set is then projected onto its bounded dimensions.
923 * Note that to compute this projection, we can simply drop all constraints
924 * involving any of the unbounded dimensions since these constraints
925 * cannot be combined to produce a constraint on the bounded dimensions.
926 * To see this, assume that there is such a combination of constraints
927 * that produces a constraint on the bounded dimensions. This means
928 * that some combination of the unbounded dimensions has both an upper
929 * bound and a lower bound in terms of the bounded dimensions, but then
930 * this combination would be a bounded direction too and would have been
931 * transformed into a bounded dimensions.
933 * We then compute a sample value in the bounded dimensions.
934 * If no such value can be found, then the original set did not contain
935 * any integer points and we are done.
936 * Otherwise, we plug in the value we found in the bounded dimensions,
937 * project out these bounded dimensions and end up with a set with
938 * a full-dimensional recession cone.
939 * A sample point in this set is computed by "rounding up" any
940 * rational point in the set.
942 * The sample points in the bounded and unbounded dimensions are
943 * then combined into a single sample point and transformed back
944 * to the original space.
946 __isl_give isl_vec
*isl_basic_set_sample_with_cone(
947 __isl_take isl_basic_set
*bset
, __isl_take isl_basic_set
*cone
)
951 struct isl_mat
*M
, *U
;
952 struct isl_vec
*sample
;
953 struct isl_vec
*cone_sample
;
955 struct isl_basic_set
*bounded
;
957 total
= isl_basic_set_dim(cone
, isl_dim_all
);
958 if (!bset
|| total
< 0)
961 ctx
= isl_basic_set_get_ctx(bset
);
962 cone_dim
= total
- cone
->n_eq
;
964 M
= isl_mat_sub_alloc6(ctx
, cone
->eq
, 0, cone
->n_eq
, 1, total
);
965 M
= isl_mat_left_hermite(M
, 0, &U
, NULL
);
970 U
= isl_mat_lin_to_aff(U
);
971 bset
= isl_basic_set_preimage(bset
, isl_mat_copy(U
));
973 bounded
= isl_basic_set_copy(bset
);
974 bounded
= isl_basic_set_drop_constraints_involving(bounded
,
975 total
- cone_dim
, cone_dim
);
976 bounded
= isl_basic_set_drop_dims(bounded
, total
- cone_dim
, cone_dim
);
977 sample
= sample_bounded(bounded
);
978 if (!sample
|| sample
->size
== 0) {
979 isl_basic_set_free(bset
);
980 isl_basic_set_free(cone
);
984 bset
= plug_in(bset
, isl_vec_copy(sample
));
985 cone_sample
= rational_sample(bset
);
986 cone_sample
= round_up_in_cone(cone_sample
, cone
, isl_mat_copy(U
));
987 sample
= vec_concat(sample
, cone_sample
);
988 sample
= isl_mat_vec_product(U
, sample
);
991 isl_basic_set_free(cone
);
992 isl_basic_set_free(bset
);
996 static void vec_sum_of_neg(__isl_keep isl_vec
*v
, isl_int
*s
)
1000 isl_int_set_si(*s
, 0);
1002 for (i
= 0; i
< v
->size
; ++i
)
1003 if (isl_int_is_neg(v
->el
[i
]))
1004 isl_int_add(*s
, *s
, v
->el
[i
]);
1007 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
1008 * to the recession cone and the inverse of a new basis U = inv(B),
1009 * with the unbounded directions in B last,
1010 * add constraints to "tab" that ensure any rational value
1011 * in the unbounded directions can be rounded up to an integer value.
1013 * The new basis is given by x' = B x, i.e., x = U x'.
1014 * For any rational value of the last tab->n_unbounded coordinates
1015 * in the update tableau, the value that is obtained by rounding
1016 * up this value should be contained in the original tableau.
1017 * For any constraint "a x + c >= 0", we therefore need to add
1018 * a constraint "a x + c + s >= 0", with s the sum of all negative
1019 * entries in the last elements of "a U".
1021 * Since we are not interested in the first entries of any of the "a U",
1022 * we first drop the columns of U that correpond to bounded directions.
1024 static int tab_shift_cone(struct isl_tab
*tab
,
1025 struct isl_tab
*tab_cone
, struct isl_mat
*U
)
1029 struct isl_basic_set
*bset
= NULL
;
1031 if (tab
&& tab
->n_unbounded
== 0) {
1036 if (!tab
|| !tab_cone
|| !U
)
1038 bset
= isl_tab_peek_bset(tab_cone
);
1039 U
= isl_mat_drop_cols(U
, 0, tab
->n_var
- tab
->n_unbounded
);
1040 for (i
= 0; i
< bset
->n_ineq
; ++i
) {
1042 struct isl_vec
*row
= NULL
;
1043 if (isl_tab_is_equality(tab_cone
, tab_cone
->n_eq
+ i
))
1045 row
= isl_vec_alloc(bset
->ctx
, tab_cone
->n_var
);
1048 isl_seq_cpy(row
->el
, bset
->ineq
[i
] + 1, tab_cone
->n_var
);
1049 row
= isl_vec_mat_product(row
, isl_mat_copy(U
));
1052 vec_sum_of_neg(row
, &v
);
1054 if (isl_int_is_zero(v
))
1056 if (isl_tab_extend_cons(tab
, 1) < 0)
1058 isl_int_add(bset
->ineq
[i
][0], bset
->ineq
[i
][0], v
);
1059 ok
= isl_tab_add_ineq(tab
, bset
->ineq
[i
]) >= 0;
1060 isl_int_sub(bset
->ineq
[i
][0], bset
->ineq
[i
][0], v
);
1074 /* Compute and return an initial basis for the possibly
1075 * unbounded tableau "tab". "tab_cone" is a tableau
1076 * for the corresponding recession cone.
1077 * Additionally, add constraints to "tab" that ensure
1078 * that any rational value for the unbounded directions
1079 * can be rounded up to an integer value.
1081 * If the tableau is bounded, i.e., if the recession cone
1082 * is zero-dimensional, then we just use inital_basis.
1083 * Otherwise, we construct a basis whose first directions
1084 * correspond to equalities, followed by bounded directions,
1085 * i.e., equalities in the recession cone.
1086 * The remaining directions are then unbounded.
1088 int isl_tab_set_initial_basis_with_cone(struct isl_tab
*tab
,
1089 struct isl_tab
*tab_cone
)
1092 struct isl_mat
*cone_eq
;
1093 struct isl_mat
*U
, *Q
;
1095 if (!tab
|| !tab_cone
)
1098 if (tab_cone
->n_col
== tab_cone
->n_dead
) {
1099 tab
->basis
= initial_basis(tab
);
1100 return tab
->basis
? 0 : -1;
1103 eq
= tab_equalities(tab
);
1106 tab
->n_zero
= eq
->n_row
;
1107 cone_eq
= tab_equalities(tab_cone
);
1108 eq
= isl_mat_concat(eq
, cone_eq
);
1111 tab
->n_unbounded
= tab
->n_var
- (eq
->n_row
- tab
->n_zero
);
1112 eq
= isl_mat_left_hermite(eq
, 0, &U
, &Q
);
1116 tab
->basis
= isl_mat_lin_to_aff(Q
);
1117 if (tab_shift_cone(tab
, tab_cone
, U
) < 0)
1124 /* Compute and return a sample point in bset using generalized basis
1125 * reduction. We first check if the input set has a non-trivial
1126 * recession cone. If so, we perform some extra preprocessing in
1127 * sample_with_cone. Otherwise, we directly perform generalized basis
1130 static __isl_give isl_vec
*gbr_sample(__isl_take isl_basic_set
*bset
)
1133 struct isl_basic_set
*cone
;
1135 dim
= isl_basic_set_dim(bset
, isl_dim_all
);
1139 cone
= isl_basic_set_recession_cone(isl_basic_set_copy(bset
));
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
);
1149 isl_basic_set_free(bset
);
1153 static __isl_give isl_vec
*basic_set_sample(__isl_take isl_basic_set
*bset
,
1160 if (isl_basic_set_plain_is_empty(bset
))
1161 return empty_sample(bset
);
1163 dim
= isl_basic_set_dim(bset
, isl_dim_set
);
1165 isl_basic_set_check_no_params(bset
) < 0 ||
1166 isl_basic_set_check_no_locals(bset
) < 0)
1169 if (bset
->sample
&& bset
->sample
->size
== 1 + dim
) {
1170 int contains
= isl_basic_set_contains(bset
, bset
->sample
);
1174 struct isl_vec
*sample
= isl_vec_copy(bset
->sample
);
1175 isl_basic_set_free(bset
);
1179 isl_vec_free(bset
->sample
);
1180 bset
->sample
= NULL
;
1183 return sample_eq(bset
, bounded
? isl_basic_set_sample_bounded
1184 : isl_basic_set_sample_vec
);
1186 return zero_sample(bset
);
1188 return interval_sample(bset
);
1190 return bounded
? sample_bounded(bset
) : gbr_sample(bset
);
1192 isl_basic_set_free(bset
);
1196 __isl_give isl_vec
*isl_basic_set_sample_vec(__isl_take isl_basic_set
*bset
)
1198 return basic_set_sample(bset
, 0);
1201 /* Compute an integer sample in "bset", where the caller guarantees
1202 * that "bset" is bounded.
1204 __isl_give isl_vec
*isl_basic_set_sample_bounded(__isl_take isl_basic_set
*bset
)
1206 return basic_set_sample(bset
, 1);
1209 __isl_give isl_basic_set
*isl_basic_set_from_vec(__isl_take isl_vec
*vec
)
1213 struct isl_basic_set
*bset
= NULL
;
1214 struct isl_ctx
*ctx
;
1220 isl_assert(ctx
, vec
->size
!= 0, goto error
);
1222 bset
= isl_basic_set_alloc(ctx
, 0, vec
->size
- 1, 0, vec
->size
- 1, 0);
1223 dim
= isl_basic_set_dim(bset
, isl_dim_set
);
1226 for (i
= dim
- 1; i
>= 0; --i
) {
1227 k
= isl_basic_set_alloc_equality(bset
);
1230 isl_seq_clr(bset
->eq
[k
], 1 + dim
);
1231 isl_int_neg(bset
->eq
[k
][0], vec
->el
[1 + i
]);
1232 isl_int_set(bset
->eq
[k
][1 + i
], vec
->el
[0]);
1238 isl_basic_set_free(bset
);
1243 __isl_give isl_basic_map
*isl_basic_map_sample(__isl_take isl_basic_map
*bmap
)
1245 struct isl_basic_set
*bset
;
1246 struct isl_vec
*sample_vec
;
1248 bset
= isl_basic_map_underlying_set(isl_basic_map_copy(bmap
));
1249 sample_vec
= isl_basic_set_sample_vec(bset
);
1252 if (sample_vec
->size
== 0) {
1253 isl_vec_free(sample_vec
);
1254 return isl_basic_map_set_to_empty(bmap
);
1256 isl_vec_free(bmap
->sample
);
1257 bmap
->sample
= isl_vec_copy(sample_vec
);
1258 bset
= isl_basic_set_from_vec(sample_vec
);
1259 return isl_basic_map_overlying_set(bset
, bmap
);
1261 isl_basic_map_free(bmap
);
1265 __isl_give isl_basic_set
*isl_basic_set_sample(__isl_take isl_basic_set
*bset
)
1267 return isl_basic_map_sample(bset
);
1270 __isl_give isl_basic_map
*isl_map_sample(__isl_take isl_map
*map
)
1273 isl_basic_map
*sample
= NULL
;
1278 for (i
= 0; i
< map
->n
; ++i
) {
1279 sample
= isl_basic_map_sample(isl_basic_map_copy(map
->p
[i
]));
1282 if (!ISL_F_ISSET(sample
, ISL_BASIC_MAP_EMPTY
))
1284 isl_basic_map_free(sample
);
1287 sample
= isl_basic_map_empty(isl_map_get_space(map
));
1295 __isl_give isl_basic_set
*isl_set_sample(__isl_take isl_set
*set
)
1297 return bset_from_bmap(isl_map_sample(set_to_map(set
)));
1300 __isl_give isl_point
*isl_basic_set_sample_point(__isl_take isl_basic_set
*bset
)
1305 space
= isl_basic_set_get_space(bset
);
1306 bset
= isl_basic_set_underlying_set(bset
);
1307 vec
= isl_basic_set_sample_vec(bset
);
1309 return isl_point_alloc(space
, vec
);
1312 __isl_give isl_point
*isl_set_sample_point(__isl_take isl_set
*set
)
1320 for (i
= 0; i
< set
->n
; ++i
) {
1321 pnt
= isl_basic_set_sample_point(isl_basic_set_copy(set
->p
[i
]));
1324 if (!isl_point_is_void(pnt
))
1326 isl_point_free(pnt
);
1329 pnt
= isl_point_void(isl_set_get_space(set
));