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
12 #include "isl_map_private.h"
16 #include "isl_equalities.h"
19 static struct isl_basic_set
*uset_convex_hull_wrap_bounded(struct isl_set
*set
);
21 static void swap_ineq(struct isl_basic_map
*bmap
, unsigned i
, unsigned j
)
27 bmap
->ineq
[i
] = bmap
->ineq
[j
];
32 /* Return 1 if constraint c is redundant with respect to the constraints
33 * in bmap. If c is a lower [upper] bound in some variable and bmap
34 * does not have a lower [upper] bound in that variable, then c cannot
35 * be redundant and we do not need solve any lp.
37 int isl_basic_map_constraint_is_redundant(struct isl_basic_map
**bmap
,
38 isl_int
*c
, isl_int
*opt_n
, isl_int
*opt_d
)
40 enum isl_lp_result res
;
47 total
= isl_basic_map_total_dim(*bmap
);
48 for (i
= 0; i
< total
; ++i
) {
50 if (isl_int_is_zero(c
[1+i
]))
52 sign
= isl_int_sgn(c
[1+i
]);
53 for (j
= 0; j
< (*bmap
)->n_ineq
; ++j
)
54 if (sign
== isl_int_sgn((*bmap
)->ineq
[j
][1+i
]))
56 if (j
== (*bmap
)->n_ineq
)
62 res
= isl_basic_map_solve_lp(*bmap
, 0, c
, (*bmap
)->ctx
->one
,
64 if (res
== isl_lp_unbounded
)
66 if (res
== isl_lp_error
)
68 if (res
== isl_lp_empty
) {
69 *bmap
= isl_basic_map_set_to_empty(*bmap
);
72 return !isl_int_is_neg(*opt_n
);
75 int isl_basic_set_constraint_is_redundant(struct isl_basic_set
**bset
,
76 isl_int
*c
, isl_int
*opt_n
, isl_int
*opt_d
)
78 return isl_basic_map_constraint_is_redundant(
79 (struct isl_basic_map
**)bset
, c
, opt_n
, opt_d
);
82 /* Compute the convex hull of a basic map, by removing the redundant
83 * constraints. If the minimal value along the normal of a constraint
84 * is the same if the constraint is removed, then the constraint is redundant.
86 * Alternatively, we could have intersected the basic map with the
87 * corresponding equality and the checked if the dimension was that
90 struct isl_basic_map
*isl_basic_map_convex_hull(struct isl_basic_map
*bmap
)
97 bmap
= isl_basic_map_gauss(bmap
, NULL
);
98 if (ISL_F_ISSET(bmap
, ISL_BASIC_MAP_EMPTY
))
100 if (ISL_F_ISSET(bmap
, ISL_BASIC_MAP_NO_REDUNDANT
))
102 if (bmap
->n_ineq
<= 1)
105 tab
= isl_tab_from_basic_map(bmap
);
106 tab
= isl_tab_detect_implicit_equalities(tab
);
107 if (isl_tab_detect_redundant(tab
) < 0)
109 bmap
= isl_basic_map_update_from_tab(bmap
, tab
);
111 ISL_F_SET(bmap
, ISL_BASIC_MAP_NO_IMPLICIT
);
112 ISL_F_SET(bmap
, ISL_BASIC_MAP_NO_REDUNDANT
);
116 isl_basic_map_free(bmap
);
120 struct isl_basic_set
*isl_basic_set_convex_hull(struct isl_basic_set
*bset
)
122 return (struct isl_basic_set
*)
123 isl_basic_map_convex_hull((struct isl_basic_map
*)bset
);
126 /* Check if the set set is bound in the direction of the affine
127 * constraint c and if so, set the constant term such that the
128 * resulting constraint is a bounding constraint for the set.
130 static int uset_is_bound(struct isl_set
*set
, isl_int
*c
, unsigned len
)
138 isl_int_init(opt_denom
);
140 for (j
= 0; j
< set
->n
; ++j
) {
141 enum isl_lp_result res
;
143 if (ISL_F_ISSET(set
->p
[j
], ISL_BASIC_SET_EMPTY
))
146 res
= isl_basic_set_solve_lp(set
->p
[j
],
147 0, c
, set
->ctx
->one
, &opt
, &opt_denom
, NULL
);
148 if (res
== isl_lp_unbounded
)
150 if (res
== isl_lp_error
)
152 if (res
== isl_lp_empty
) {
153 set
->p
[j
] = isl_basic_set_set_to_empty(set
->p
[j
]);
158 if (first
|| isl_int_is_neg(opt
)) {
159 if (!isl_int_is_one(opt_denom
))
160 isl_seq_scale(c
, c
, opt_denom
, len
);
161 isl_int_sub(c
[0], c
[0], opt
);
166 isl_int_clear(opt_denom
);
170 isl_int_clear(opt_denom
);
174 /* Check if "c" is a direction that is independent of the previously found "n"
176 * If so, add it to the list, with the negative of the lower bound
177 * in the constant position, i.e., such that c corresponds to a bounding
178 * hyperplane (but not necessarily a facet).
179 * Assumes set "set" is bounded.
181 static int is_independent_bound(struct isl_set
*set
, isl_int
*c
,
182 struct isl_mat
*dirs
, int n
)
187 isl_seq_cpy(dirs
->row
[n
]+1, c
+1, dirs
->n_col
-1);
189 int pos
= isl_seq_first_non_zero(dirs
->row
[n
]+1, dirs
->n_col
-1);
192 for (i
= 0; i
< n
; ++i
) {
194 pos_i
= isl_seq_first_non_zero(dirs
->row
[i
]+1, dirs
->n_col
-1);
199 isl_seq_elim(dirs
->row
[n
]+1, dirs
->row
[i
]+1, pos
,
200 dirs
->n_col
-1, NULL
);
201 pos
= isl_seq_first_non_zero(dirs
->row
[n
]+1, dirs
->n_col
-1);
207 is_bound
= uset_is_bound(set
, dirs
->row
[n
], dirs
->n_col
);
210 isl_seq_normalize(set
->ctx
, dirs
->row
[n
], dirs
->n_col
);
213 isl_int
*t
= dirs
->row
[n
];
214 for (k
= n
; k
> i
; --k
)
215 dirs
->row
[k
] = dirs
->row
[k
-1];
221 /* Compute and return a maximal set of linearly independent bounds
222 * on the set "set", based on the constraints of the basic sets
225 static struct isl_mat
*independent_bounds(struct isl_set
*set
)
228 struct isl_mat
*dirs
= NULL
;
229 unsigned dim
= isl_set_n_dim(set
);
231 dirs
= isl_mat_alloc(set
->ctx
, dim
, 1+dim
);
236 for (i
= 0; n
< dim
&& i
< set
->n
; ++i
) {
238 struct isl_basic_set
*bset
= set
->p
[i
];
240 for (j
= 0; n
< dim
&& j
< bset
->n_eq
; ++j
) {
241 f
= is_independent_bound(set
, bset
->eq
[j
], dirs
, n
);
247 for (j
= 0; n
< dim
&& j
< bset
->n_ineq
; ++j
) {
248 f
= is_independent_bound(set
, bset
->ineq
[j
], dirs
, n
);
262 struct isl_basic_set
*isl_basic_set_set_rational(struct isl_basic_set
*bset
)
267 if (ISL_F_ISSET(bset
, ISL_BASIC_MAP_RATIONAL
))
270 bset
= isl_basic_set_cow(bset
);
274 ISL_F_SET(bset
, ISL_BASIC_MAP_RATIONAL
);
276 return isl_basic_set_finalize(bset
);
279 static struct isl_set
*isl_set_set_rational(struct isl_set
*set
)
283 set
= isl_set_cow(set
);
286 for (i
= 0; i
< set
->n
; ++i
) {
287 set
->p
[i
] = isl_basic_set_set_rational(set
->p
[i
]);
297 static struct isl_basic_set
*isl_basic_set_add_equality(
298 struct isl_basic_set
*bset
, isl_int
*c
)
303 if (ISL_F_ISSET(bset
, ISL_BASIC_SET_EMPTY
))
306 isl_assert(bset
->ctx
, isl_basic_set_n_param(bset
) == 0, goto error
);
307 isl_assert(bset
->ctx
, bset
->n_div
== 0, goto error
);
308 dim
= isl_basic_set_n_dim(bset
);
309 bset
= isl_basic_set_cow(bset
);
310 bset
= isl_basic_set_extend(bset
, 0, dim
, 0, 1, 0);
311 i
= isl_basic_set_alloc_equality(bset
);
314 isl_seq_cpy(bset
->eq
[i
], c
, 1 + dim
);
317 isl_basic_set_free(bset
);
321 static struct isl_set
*isl_set_add_equality(struct isl_set
*set
, isl_int
*c
)
325 set
= isl_set_cow(set
);
328 for (i
= 0; i
< set
->n
; ++i
) {
329 set
->p
[i
] = isl_basic_set_add_equality(set
->p
[i
], c
);
339 /* Given a union of basic sets, construct the constraints for wrapping
340 * a facet around one of its ridges.
341 * In particular, if each of n the d-dimensional basic sets i in "set"
342 * contains the origin, satisfies the constraints x_1 >= 0 and x_2 >= 0
343 * and is defined by the constraints
347 * then the resulting set is of dimension n*(1+d) and has as constraints
356 static struct isl_basic_set
*wrap_constraints(struct isl_set
*set
)
358 struct isl_basic_set
*lp
;
362 unsigned dim
, lp_dim
;
367 dim
= 1 + isl_set_n_dim(set
);
370 for (i
= 0; i
< set
->n
; ++i
) {
371 n_eq
+= set
->p
[i
]->n_eq
;
372 n_ineq
+= set
->p
[i
]->n_ineq
;
374 lp
= isl_basic_set_alloc(set
->ctx
, 0, dim
* set
->n
, 0, n_eq
, n_ineq
);
377 lp_dim
= isl_basic_set_n_dim(lp
);
378 k
= isl_basic_set_alloc_equality(lp
);
379 isl_int_set_si(lp
->eq
[k
][0], -1);
380 for (i
= 0; i
< set
->n
; ++i
) {
381 isl_int_set_si(lp
->eq
[k
][1+dim
*i
], 0);
382 isl_int_set_si(lp
->eq
[k
][1+dim
*i
+1], 1);
383 isl_seq_clr(lp
->eq
[k
]+1+dim
*i
+2, dim
-2);
385 for (i
= 0; i
< set
->n
; ++i
) {
386 k
= isl_basic_set_alloc_inequality(lp
);
387 isl_seq_clr(lp
->ineq
[k
], 1+lp_dim
);
388 isl_int_set_si(lp
->ineq
[k
][1+dim
*i
], 1);
390 for (j
= 0; j
< set
->p
[i
]->n_eq
; ++j
) {
391 k
= isl_basic_set_alloc_equality(lp
);
392 isl_seq_clr(lp
->eq
[k
], 1+dim
*i
);
393 isl_seq_cpy(lp
->eq
[k
]+1+dim
*i
, set
->p
[i
]->eq
[j
], dim
);
394 isl_seq_clr(lp
->eq
[k
]+1+dim
*(i
+1), dim
*(set
->n
-i
-1));
397 for (j
= 0; j
< set
->p
[i
]->n_ineq
; ++j
) {
398 k
= isl_basic_set_alloc_inequality(lp
);
399 isl_seq_clr(lp
->ineq
[k
], 1+dim
*i
);
400 isl_seq_cpy(lp
->ineq
[k
]+1+dim
*i
, set
->p
[i
]->ineq
[j
], dim
);
401 isl_seq_clr(lp
->ineq
[k
]+1+dim
*(i
+1), dim
*(set
->n
-i
-1));
407 /* Given a facet "facet" of the convex hull of "set" and a facet "ridge"
408 * of that facet, compute the other facet of the convex hull that contains
411 * We first transform the set such that the facet constraint becomes
415 * I.e., the facet lies in
419 * and on that facet, the constraint that defines the ridge is
423 * (This transformation is not strictly needed, all that is needed is
424 * that the ridge contains the origin.)
426 * Since the ridge contains the origin, the cone of the convex hull
427 * will be of the form
432 * with this second constraint defining the new facet.
433 * The constant a is obtained by settting x_1 in the cone of the
434 * convex hull to 1 and minimizing x_2.
435 * Now, each element in the cone of the convex hull is the sum
436 * of elements in the cones of the basic sets.
437 * If a_i is the dilation factor of basic set i, then the problem
438 * we need to solve is
451 * the constraints of each (transformed) basic set.
452 * If a = n/d, then the constraint defining the new facet (in the transformed
455 * -n x_1 + d x_2 >= 0
457 * In the original space, we need to take the same combination of the
458 * corresponding constraints "facet" and "ridge".
460 * Note that a is always finite, since we only apply the wrapping
461 * technique to a union of polytopes.
463 static isl_int
*wrap_facet(struct isl_set
*set
, isl_int
*facet
, isl_int
*ridge
)
466 struct isl_mat
*T
= NULL
;
467 struct isl_basic_set
*lp
= NULL
;
469 enum isl_lp_result res
;
473 set
= isl_set_copy(set
);
475 dim
= 1 + isl_set_n_dim(set
);
476 T
= isl_mat_alloc(set
->ctx
, 3, dim
);
479 isl_int_set_si(T
->row
[0][0], 1);
480 isl_seq_clr(T
->row
[0]+1, dim
- 1);
481 isl_seq_cpy(T
->row
[1], facet
, dim
);
482 isl_seq_cpy(T
->row
[2], ridge
, dim
);
483 T
= isl_mat_right_inverse(T
);
484 set
= isl_set_preimage(set
, T
);
488 lp
= wrap_constraints(set
);
489 obj
= isl_vec_alloc(set
->ctx
, 1 + dim
*set
->n
);
492 isl_int_set_si(obj
->block
.data
[0], 0);
493 for (i
= 0; i
< set
->n
; ++i
) {
494 isl_seq_clr(obj
->block
.data
+ 1 + dim
*i
, 2);
495 isl_int_set_si(obj
->block
.data
[1 + dim
*i
+2], 1);
496 isl_seq_clr(obj
->block
.data
+ 1 + dim
*i
+3, dim
-3);
500 res
= isl_basic_set_solve_lp(lp
, 0,
501 obj
->block
.data
, set
->ctx
->one
, &num
, &den
, NULL
);
502 if (res
== isl_lp_ok
) {
503 isl_int_neg(num
, num
);
504 isl_seq_combine(facet
, num
, facet
, den
, ridge
, dim
);
509 isl_basic_set_free(lp
);
511 isl_assert(set
->ctx
, res
== isl_lp_ok
, return NULL
);
514 isl_basic_set_free(lp
);
520 /* Drop rows in "rows" that are redundant with respect to earlier rows,
521 * assuming that "rows" is of full column rank.
523 * We compute the column echelon form. The non-redundant rows are
524 * those that are the first to contain a non-zero entry in a column.
525 * All the other rows can be removed.
527 static __isl_give isl_mat
*drop_redundant_rows(__isl_take isl_mat
*rows
)
529 struct isl_mat
*H
= NULL
;
537 isl_assert(rows
->ctx
, rows
->n_row
>= rows
->n_col
, goto error
);
539 if (rows
->n_row
== rows
->n_col
)
542 H
= isl_mat_left_hermite(isl_mat_copy(rows
), 0, NULL
, NULL
);
546 last_row
= rows
->n_row
;
547 for (col
= rows
->n_col
- 1; col
>= 0; --col
) {
548 for (row
= col
; row
< last_row
; ++row
)
549 if (!isl_int_is_zero(H
->row
[row
][col
]))
551 isl_assert(rows
->ctx
, row
< last_row
, goto error
);
552 if (row
+ 1 < last_row
) {
553 rows
= isl_mat_drop_rows(rows
, row
+ 1, last_row
- (row
+ 1));
554 if (rows
->n_row
== rows
->n_col
)
569 /* Given a set of d linearly independent bounding constraints of the
570 * convex hull of "set", compute the constraint of a facet of "set".
572 * We first compute the intersection with the first bounding hyperplane
573 * and remove the component corresponding to this hyperplane from
574 * other bounds (in homogeneous space).
575 * We then wrap around one of the remaining bounding constraints
576 * and continue the process until all bounding constraints have been
577 * taken into account.
578 * The resulting linear combination of the bounding constraints will
579 * correspond to a facet of the convex hull.
581 static struct isl_mat
*initial_facet_constraint(struct isl_set
*set
,
582 struct isl_mat
*bounds
)
584 struct isl_set
*slice
= NULL
;
585 struct isl_basic_set
*face
= NULL
;
586 struct isl_mat
*m
, *U
, *Q
;
588 unsigned dim
= isl_set_n_dim(set
);
590 isl_assert(set
->ctx
, set
->n
> 0, goto error
);
591 isl_assert(set
->ctx
, bounds
->n_row
== dim
, goto error
);
593 while (bounds
->n_row
> 1) {
594 slice
= isl_set_copy(set
);
595 slice
= isl_set_add_equality(slice
, bounds
->row
[0]);
596 face
= isl_set_affine_hull(slice
);
599 if (face
->n_eq
== 1) {
600 isl_basic_set_free(face
);
603 m
= isl_mat_alloc(set
->ctx
, 1 + face
->n_eq
, 1 + dim
);
606 isl_int_set_si(m
->row
[0][0], 1);
607 isl_seq_clr(m
->row
[0]+1, dim
);
608 for (i
= 0; i
< face
->n_eq
; ++i
)
609 isl_seq_cpy(m
->row
[1 + i
], face
->eq
[i
], 1 + dim
);
610 U
= isl_mat_right_inverse(m
);
611 Q
= isl_mat_right_inverse(isl_mat_copy(U
));
612 U
= isl_mat_drop_cols(U
, 1 + face
->n_eq
, dim
- face
->n_eq
);
613 Q
= isl_mat_drop_rows(Q
, 1 + face
->n_eq
, dim
- face
->n_eq
);
614 U
= isl_mat_drop_cols(U
, 0, 1);
615 Q
= isl_mat_drop_rows(Q
, 0, 1);
616 bounds
= isl_mat_product(bounds
, U
);
617 bounds
= drop_redundant_rows(bounds
);
618 bounds
= isl_mat_product(bounds
, Q
);
619 isl_assert(set
->ctx
, bounds
->n_row
> 1, goto error
);
620 if (!wrap_facet(set
, bounds
->row
[0],
621 bounds
->row
[bounds
->n_row
-1]))
623 isl_basic_set_free(face
);
628 isl_basic_set_free(face
);
629 isl_mat_free(bounds
);
633 /* Given the bounding constraint "c" of a facet of the convex hull of "set",
634 * compute a hyperplane description of the facet, i.e., compute the facets
637 * We compute an affine transformation that transforms the constraint
646 * by computing the right inverse U of a matrix that starts with the rows
659 * Since z_1 is zero, we can drop this variable as well as the corresponding
660 * column of U to obtain
668 * with Q' equal to Q, but without the corresponding row.
669 * After computing the facets of the facet in the z' space,
670 * we convert them back to the x space through Q.
672 static struct isl_basic_set
*compute_facet(struct isl_set
*set
, isl_int
*c
)
674 struct isl_mat
*m
, *U
, *Q
;
675 struct isl_basic_set
*facet
= NULL
;
680 set
= isl_set_copy(set
);
681 dim
= isl_set_n_dim(set
);
682 m
= isl_mat_alloc(set
->ctx
, 2, 1 + dim
);
685 isl_int_set_si(m
->row
[0][0], 1);
686 isl_seq_clr(m
->row
[0]+1, dim
);
687 isl_seq_cpy(m
->row
[1], c
, 1+dim
);
688 U
= isl_mat_right_inverse(m
);
689 Q
= isl_mat_right_inverse(isl_mat_copy(U
));
690 U
= isl_mat_drop_cols(U
, 1, 1);
691 Q
= isl_mat_drop_rows(Q
, 1, 1);
692 set
= isl_set_preimage(set
, U
);
693 facet
= uset_convex_hull_wrap_bounded(set
);
694 facet
= isl_basic_set_preimage(facet
, Q
);
695 isl_assert(ctx
, facet
->n_eq
== 0, goto error
);
698 isl_basic_set_free(facet
);
703 /* Given an initial facet constraint, compute the remaining facets.
704 * We do this by running through all facets found so far and computing
705 * the adjacent facets through wrapping, adding those facets that we
706 * hadn't already found before.
708 * For each facet we have found so far, we first compute its facets
709 * in the resulting convex hull. That is, we compute the ridges
710 * of the resulting convex hull contained in the facet.
711 * We also compute the corresponding facet in the current approximation
712 * of the convex hull. There is no need to wrap around the ridges
713 * in this facet since that would result in a facet that is already
714 * present in the current approximation.
716 * This function can still be significantly optimized by checking which of
717 * the facets of the basic sets are also facets of the convex hull and
718 * using all the facets so far to help in constructing the facets of the
721 * using the technique in section "3.1 Ridge Generation" of
722 * "Extended Convex Hull" by Fukuda et al.
724 static struct isl_basic_set
*extend(struct isl_basic_set
*hull
,
729 struct isl_basic_set
*facet
= NULL
;
730 struct isl_basic_set
*hull_facet
= NULL
;
736 isl_assert(set
->ctx
, set
->n
> 0, goto error
);
738 dim
= isl_set_n_dim(set
);
740 for (i
= 0; i
< hull
->n_ineq
; ++i
) {
741 facet
= compute_facet(set
, hull
->ineq
[i
]);
742 facet
= isl_basic_set_add_equality(facet
, hull
->ineq
[i
]);
743 facet
= isl_basic_set_gauss(facet
, NULL
);
744 facet
= isl_basic_set_normalize_constraints(facet
);
745 hull_facet
= isl_basic_set_copy(hull
);
746 hull_facet
= isl_basic_set_add_equality(hull_facet
, hull
->ineq
[i
]);
747 hull_facet
= isl_basic_set_gauss(hull_facet
, NULL
);
748 hull_facet
= isl_basic_set_normalize_constraints(hull_facet
);
751 hull
= isl_basic_set_cow(hull
);
752 hull
= isl_basic_set_extend_dim(hull
,
753 isl_dim_copy(hull
->dim
), 0, 0, facet
->n_ineq
);
754 for (j
= 0; j
< facet
->n_ineq
; ++j
) {
755 for (f
= 0; f
< hull_facet
->n_ineq
; ++f
)
756 if (isl_seq_eq(facet
->ineq
[j
],
757 hull_facet
->ineq
[f
], 1 + dim
))
759 if (f
< hull_facet
->n_ineq
)
761 k
= isl_basic_set_alloc_inequality(hull
);
764 isl_seq_cpy(hull
->ineq
[k
], hull
->ineq
[i
], 1+dim
);
765 if (!wrap_facet(set
, hull
->ineq
[k
], facet
->ineq
[j
]))
768 isl_basic_set_free(hull_facet
);
769 isl_basic_set_free(facet
);
771 hull
= isl_basic_set_simplify(hull
);
772 hull
= isl_basic_set_finalize(hull
);
775 isl_basic_set_free(hull_facet
);
776 isl_basic_set_free(facet
);
777 isl_basic_set_free(hull
);
781 /* Special case for computing the convex hull of a one dimensional set.
782 * We simply collect the lower and upper bounds of each basic set
783 * and the biggest of those.
785 static struct isl_basic_set
*convex_hull_1d(struct isl_set
*set
)
787 struct isl_mat
*c
= NULL
;
788 isl_int
*lower
= NULL
;
789 isl_int
*upper
= NULL
;
792 struct isl_basic_set
*hull
;
794 for (i
= 0; i
< set
->n
; ++i
) {
795 set
->p
[i
] = isl_basic_set_simplify(set
->p
[i
]);
799 set
= isl_set_remove_empty_parts(set
);
802 isl_assert(set
->ctx
, set
->n
> 0, goto error
);
803 c
= isl_mat_alloc(set
->ctx
, 2, 2);
807 if (set
->p
[0]->n_eq
> 0) {
808 isl_assert(set
->ctx
, set
->p
[0]->n_eq
== 1, goto error
);
811 if (isl_int_is_pos(set
->p
[0]->eq
[0][1])) {
812 isl_seq_cpy(lower
, set
->p
[0]->eq
[0], 2);
813 isl_seq_neg(upper
, set
->p
[0]->eq
[0], 2);
815 isl_seq_neg(lower
, set
->p
[0]->eq
[0], 2);
816 isl_seq_cpy(upper
, set
->p
[0]->eq
[0], 2);
819 for (j
= 0; j
< set
->p
[0]->n_ineq
; ++j
) {
820 if (isl_int_is_pos(set
->p
[0]->ineq
[j
][1])) {
822 isl_seq_cpy(lower
, set
->p
[0]->ineq
[j
], 2);
825 isl_seq_cpy(upper
, set
->p
[0]->ineq
[j
], 2);
832 for (i
= 0; i
< set
->n
; ++i
) {
833 struct isl_basic_set
*bset
= set
->p
[i
];
837 for (j
= 0; j
< bset
->n_eq
; ++j
) {
841 isl_int_mul(a
, lower
[0], bset
->eq
[j
][1]);
842 isl_int_mul(b
, lower
[1], bset
->eq
[j
][0]);
843 if (isl_int_lt(a
, b
) && isl_int_is_pos(bset
->eq
[j
][1]))
844 isl_seq_cpy(lower
, bset
->eq
[j
], 2);
845 if (isl_int_gt(a
, b
) && isl_int_is_neg(bset
->eq
[j
][1]))
846 isl_seq_neg(lower
, bset
->eq
[j
], 2);
849 isl_int_mul(a
, upper
[0], bset
->eq
[j
][1]);
850 isl_int_mul(b
, upper
[1], bset
->eq
[j
][0]);
851 if (isl_int_lt(a
, b
) && isl_int_is_pos(bset
->eq
[j
][1]))
852 isl_seq_neg(upper
, bset
->eq
[j
], 2);
853 if (isl_int_gt(a
, b
) && isl_int_is_neg(bset
->eq
[j
][1]))
854 isl_seq_cpy(upper
, bset
->eq
[j
], 2);
857 for (j
= 0; j
< bset
->n_ineq
; ++j
) {
858 if (isl_int_is_pos(bset
->ineq
[j
][1]))
860 if (isl_int_is_neg(bset
->ineq
[j
][1]))
862 if (lower
&& isl_int_is_pos(bset
->ineq
[j
][1])) {
863 isl_int_mul(a
, lower
[0], bset
->ineq
[j
][1]);
864 isl_int_mul(b
, lower
[1], bset
->ineq
[j
][0]);
865 if (isl_int_lt(a
, b
))
866 isl_seq_cpy(lower
, bset
->ineq
[j
], 2);
868 if (upper
&& isl_int_is_neg(bset
->ineq
[j
][1])) {
869 isl_int_mul(a
, upper
[0], bset
->ineq
[j
][1]);
870 isl_int_mul(b
, upper
[1], bset
->ineq
[j
][0]);
871 if (isl_int_gt(a
, b
))
872 isl_seq_cpy(upper
, bset
->ineq
[j
], 2);
883 hull
= isl_basic_set_alloc(set
->ctx
, 0, 1, 0, 0, 2);
884 hull
= isl_basic_set_set_rational(hull
);
888 k
= isl_basic_set_alloc_inequality(hull
);
889 isl_seq_cpy(hull
->ineq
[k
], lower
, 2);
892 k
= isl_basic_set_alloc_inequality(hull
);
893 isl_seq_cpy(hull
->ineq
[k
], upper
, 2);
895 hull
= isl_basic_set_finalize(hull
);
905 /* Project out final n dimensions using Fourier-Motzkin */
906 static struct isl_set
*set_project_out(struct isl_ctx
*ctx
,
907 struct isl_set
*set
, unsigned n
)
909 return isl_set_remove_dims(set
, isl_set_n_dim(set
) - n
, n
);
912 static struct isl_basic_set
*convex_hull_0d(struct isl_set
*set
)
914 struct isl_basic_set
*convex_hull
;
919 if (isl_set_is_empty(set
))
920 convex_hull
= isl_basic_set_empty(isl_dim_copy(set
->dim
));
922 convex_hull
= isl_basic_set_universe(isl_dim_copy(set
->dim
));
927 /* Compute the convex hull of a pair of basic sets without any parameters or
928 * integer divisions using Fourier-Motzkin elimination.
929 * The convex hull is the set of all points that can be written as
930 * the sum of points from both basic sets (in homogeneous coordinates).
931 * We set up the constraints in a space with dimensions for each of
932 * the three sets and then project out the dimensions corresponding
933 * to the two original basic sets, retaining only those corresponding
934 * to the convex hull.
936 static struct isl_basic_set
*convex_hull_pair_elim(struct isl_basic_set
*bset1
,
937 struct isl_basic_set
*bset2
)
940 struct isl_basic_set
*bset
[2];
941 struct isl_basic_set
*hull
= NULL
;
944 if (!bset1
|| !bset2
)
947 dim
= isl_basic_set_n_dim(bset1
);
948 hull
= isl_basic_set_alloc(bset1
->ctx
, 0, 2 + 3 * dim
, 0,
949 1 + dim
+ bset1
->n_eq
+ bset2
->n_eq
,
950 2 + bset1
->n_ineq
+ bset2
->n_ineq
);
953 for (i
= 0; i
< 2; ++i
) {
954 for (j
= 0; j
< bset
[i
]->n_eq
; ++j
) {
955 k
= isl_basic_set_alloc_equality(hull
);
958 isl_seq_clr(hull
->eq
[k
], (i
+1) * (1+dim
));
959 isl_seq_clr(hull
->eq
[k
]+(i
+2)*(1+dim
), (1-i
)*(1+dim
));
960 isl_seq_cpy(hull
->eq
[k
]+(i
+1)*(1+dim
), bset
[i
]->eq
[j
],
963 for (j
= 0; j
< bset
[i
]->n_ineq
; ++j
) {
964 k
= isl_basic_set_alloc_inequality(hull
);
967 isl_seq_clr(hull
->ineq
[k
], (i
+1) * (1+dim
));
968 isl_seq_clr(hull
->ineq
[k
]+(i
+2)*(1+dim
), (1-i
)*(1+dim
));
969 isl_seq_cpy(hull
->ineq
[k
]+(i
+1)*(1+dim
),
970 bset
[i
]->ineq
[j
], 1+dim
);
972 k
= isl_basic_set_alloc_inequality(hull
);
975 isl_seq_clr(hull
->ineq
[k
], 1+2+3*dim
);
976 isl_int_set_si(hull
->ineq
[k
][(i
+1)*(1+dim
)], 1);
978 for (j
= 0; j
< 1+dim
; ++j
) {
979 k
= isl_basic_set_alloc_equality(hull
);
982 isl_seq_clr(hull
->eq
[k
], 1+2+3*dim
);
983 isl_int_set_si(hull
->eq
[k
][j
], -1);
984 isl_int_set_si(hull
->eq
[k
][1+dim
+j
], 1);
985 isl_int_set_si(hull
->eq
[k
][2*(1+dim
)+j
], 1);
987 hull
= isl_basic_set_set_rational(hull
);
988 hull
= isl_basic_set_remove_dims(hull
, dim
, 2*(1+dim
));
989 hull
= isl_basic_set_convex_hull(hull
);
990 isl_basic_set_free(bset1
);
991 isl_basic_set_free(bset2
);
994 isl_basic_set_free(bset1
);
995 isl_basic_set_free(bset2
);
996 isl_basic_set_free(hull
);
1000 static int isl_basic_set_is_bounded(struct isl_basic_set
*bset
)
1002 struct isl_tab
*tab
;
1005 tab
= isl_tab_from_recession_cone(bset
);
1006 bounded
= isl_tab_cone_is_bounded(tab
);
1011 static int isl_set_is_bounded(struct isl_set
*set
)
1015 for (i
= 0; i
< set
->n
; ++i
) {
1016 int bounded
= isl_basic_set_is_bounded(set
->p
[i
]);
1017 if (!bounded
|| bounded
< 0)
1023 /* Compute the lineality space of the convex hull of bset1 and bset2.
1025 * We first compute the intersection of the recession cone of bset1
1026 * with the negative of the recession cone of bset2 and then compute
1027 * the linear hull of the resulting cone.
1029 static struct isl_basic_set
*induced_lineality_space(
1030 struct isl_basic_set
*bset1
, struct isl_basic_set
*bset2
)
1033 struct isl_basic_set
*lin
= NULL
;
1036 if (!bset1
|| !bset2
)
1039 dim
= isl_basic_set_total_dim(bset1
);
1040 lin
= isl_basic_set_alloc_dim(isl_basic_set_get_dim(bset1
), 0,
1041 bset1
->n_eq
+ bset2
->n_eq
,
1042 bset1
->n_ineq
+ bset2
->n_ineq
);
1043 lin
= isl_basic_set_set_rational(lin
);
1046 for (i
= 0; i
< bset1
->n_eq
; ++i
) {
1047 k
= isl_basic_set_alloc_equality(lin
);
1050 isl_int_set_si(lin
->eq
[k
][0], 0);
1051 isl_seq_cpy(lin
->eq
[k
] + 1, bset1
->eq
[i
] + 1, dim
);
1053 for (i
= 0; i
< bset1
->n_ineq
; ++i
) {
1054 k
= isl_basic_set_alloc_inequality(lin
);
1057 isl_int_set_si(lin
->ineq
[k
][0], 0);
1058 isl_seq_cpy(lin
->ineq
[k
] + 1, bset1
->ineq
[i
] + 1, dim
);
1060 for (i
= 0; i
< bset2
->n_eq
; ++i
) {
1061 k
= isl_basic_set_alloc_equality(lin
);
1064 isl_int_set_si(lin
->eq
[k
][0], 0);
1065 isl_seq_neg(lin
->eq
[k
] + 1, bset2
->eq
[i
] + 1, dim
);
1067 for (i
= 0; i
< bset2
->n_ineq
; ++i
) {
1068 k
= isl_basic_set_alloc_inequality(lin
);
1071 isl_int_set_si(lin
->ineq
[k
][0], 0);
1072 isl_seq_neg(lin
->ineq
[k
] + 1, bset2
->ineq
[i
] + 1, dim
);
1075 isl_basic_set_free(bset1
);
1076 isl_basic_set_free(bset2
);
1077 return isl_basic_set_affine_hull(lin
);
1079 isl_basic_set_free(lin
);
1080 isl_basic_set_free(bset1
);
1081 isl_basic_set_free(bset2
);
1085 static struct isl_basic_set
*uset_convex_hull(struct isl_set
*set
);
1087 /* Given a set and a linear space "lin" of dimension n > 0,
1088 * project the linear space from the set, compute the convex hull
1089 * and then map the set back to the original space.
1095 * describe the linear space. We first compute the Hermite normal
1096 * form H = M U of M = H Q, to obtain
1100 * The last n rows of H will be zero, so the last n variables of x' = Q x
1101 * are the one we want to project out. We do this by transforming each
1102 * basic set A x >= b to A U x' >= b and then removing the last n dimensions.
1103 * After computing the convex hull in x'_1, i.e., A' x'_1 >= b',
1104 * we transform the hull back to the original space as A' Q_1 x >= b',
1105 * with Q_1 all but the last n rows of Q.
1107 static struct isl_basic_set
*modulo_lineality(struct isl_set
*set
,
1108 struct isl_basic_set
*lin
)
1110 unsigned total
= isl_basic_set_total_dim(lin
);
1112 struct isl_basic_set
*hull
;
1113 struct isl_mat
*M
, *U
, *Q
;
1117 lin_dim
= total
- lin
->n_eq
;
1118 M
= isl_mat_sub_alloc(set
->ctx
, lin
->eq
, 0, lin
->n_eq
, 1, total
);
1119 M
= isl_mat_left_hermite(M
, 0, &U
, &Q
);
1123 isl_basic_set_free(lin
);
1125 Q
= isl_mat_drop_rows(Q
, Q
->n_row
- lin_dim
, lin_dim
);
1127 U
= isl_mat_lin_to_aff(U
);
1128 Q
= isl_mat_lin_to_aff(Q
);
1130 set
= isl_set_preimage(set
, U
);
1131 set
= isl_set_remove_dims(set
, total
- lin_dim
, lin_dim
);
1132 hull
= uset_convex_hull(set
);
1133 hull
= isl_basic_set_preimage(hull
, Q
);
1137 isl_basic_set_free(lin
);
1142 /* Given two polyhedra with as constraints h_{ij} x >= 0 in homegeneous space,
1143 * set up an LP for solving
1145 * \sum_j \alpha_{1j} h_{1j} = \sum_j \alpha_{2j} h_{2j}
1147 * \alpha{i0} corresponds to the (implicit) positivity constraint 1 >= 0
1148 * The next \alpha{ij} correspond to the equalities and come in pairs.
1149 * The final \alpha{ij} correspond to the inequalities.
1151 static struct isl_basic_set
*valid_direction_lp(
1152 struct isl_basic_set
*bset1
, struct isl_basic_set
*bset2
)
1154 struct isl_dim
*dim
;
1155 struct isl_basic_set
*lp
;
1160 if (!bset1
|| !bset2
)
1162 d
= 1 + isl_basic_set_total_dim(bset1
);
1164 2 * bset1
->n_eq
+ bset1
->n_ineq
+ 2 * bset2
->n_eq
+ bset2
->n_ineq
;
1165 dim
= isl_dim_set_alloc(bset1
->ctx
, 0, n
);
1166 lp
= isl_basic_set_alloc_dim(dim
, 0, d
, n
);
1169 for (i
= 0; i
< n
; ++i
) {
1170 k
= isl_basic_set_alloc_inequality(lp
);
1173 isl_seq_clr(lp
->ineq
[k
] + 1, n
);
1174 isl_int_set_si(lp
->ineq
[k
][0], -1);
1175 isl_int_set_si(lp
->ineq
[k
][1 + i
], 1);
1177 for (i
= 0; i
< d
; ++i
) {
1178 k
= isl_basic_set_alloc_equality(lp
);
1182 isl_int_set_si(lp
->eq
[k
][n
++], 0);
1183 /* positivity constraint 1 >= 0 */
1184 isl_int_set_si(lp
->eq
[k
][n
++], i
== 0);
1185 for (j
= 0; j
< bset1
->n_eq
; ++j
) {
1186 isl_int_set(lp
->eq
[k
][n
++], bset1
->eq
[j
][i
]);
1187 isl_int_neg(lp
->eq
[k
][n
++], bset1
->eq
[j
][i
]);
1189 for (j
= 0; j
< bset1
->n_ineq
; ++j
)
1190 isl_int_set(lp
->eq
[k
][n
++], bset1
->ineq
[j
][i
]);
1191 /* positivity constraint 1 >= 0 */
1192 isl_int_set_si(lp
->eq
[k
][n
++], -(i
== 0));
1193 for (j
= 0; j
< bset2
->n_eq
; ++j
) {
1194 isl_int_neg(lp
->eq
[k
][n
++], bset2
->eq
[j
][i
]);
1195 isl_int_set(lp
->eq
[k
][n
++], bset2
->eq
[j
][i
]);
1197 for (j
= 0; j
< bset2
->n_ineq
; ++j
)
1198 isl_int_neg(lp
->eq
[k
][n
++], bset2
->ineq
[j
][i
]);
1200 lp
= isl_basic_set_gauss(lp
, NULL
);
1201 isl_basic_set_free(bset1
);
1202 isl_basic_set_free(bset2
);
1205 isl_basic_set_free(bset1
);
1206 isl_basic_set_free(bset2
);
1210 /* Compute a vector s in the homogeneous space such that <s, r> > 0
1211 * for all rays in the homogeneous space of the two cones that correspond
1212 * to the input polyhedra bset1 and bset2.
1214 * We compute s as a vector that satisfies
1216 * s = \sum_j \alpha_{ij} h_{ij} for i = 1,2 (*)
1218 * with h_{ij} the normals of the facets of polyhedron i
1219 * (including the "positivity constraint" 1 >= 0) and \alpha_{ij}
1220 * strictly positive numbers. For simplicity we impose \alpha_{ij} >= 1.
1221 * We first set up an LP with as variables the \alpha{ij}.
1222 * In this formulateion, for each polyhedron i,
1223 * the first constraint is the positivity constraint, followed by pairs
1224 * of variables for the equalities, followed by variables for the inequalities.
1225 * We then simply pick a feasible solution and compute s using (*).
1227 * Note that we simply pick any valid direction and make no attempt
1228 * to pick a "good" or even the "best" valid direction.
1230 static struct isl_vec
*valid_direction(
1231 struct isl_basic_set
*bset1
, struct isl_basic_set
*bset2
)
1233 struct isl_basic_set
*lp
;
1234 struct isl_tab
*tab
;
1235 struct isl_vec
*sample
= NULL
;
1236 struct isl_vec
*dir
;
1241 if (!bset1
|| !bset2
)
1243 lp
= valid_direction_lp(isl_basic_set_copy(bset1
),
1244 isl_basic_set_copy(bset2
));
1245 tab
= isl_tab_from_basic_set(lp
);
1246 sample
= isl_tab_get_sample_value(tab
);
1248 isl_basic_set_free(lp
);
1251 d
= isl_basic_set_total_dim(bset1
);
1252 dir
= isl_vec_alloc(bset1
->ctx
, 1 + d
);
1255 isl_seq_clr(dir
->block
.data
+ 1, dir
->size
- 1);
1257 /* positivity constraint 1 >= 0 */
1258 isl_int_set(dir
->block
.data
[0], sample
->block
.data
[n
++]);
1259 for (i
= 0; i
< bset1
->n_eq
; ++i
) {
1260 isl_int_sub(sample
->block
.data
[n
],
1261 sample
->block
.data
[n
], sample
->block
.data
[n
+1]);
1262 isl_seq_combine(dir
->block
.data
,
1263 bset1
->ctx
->one
, dir
->block
.data
,
1264 sample
->block
.data
[n
], bset1
->eq
[i
], 1 + d
);
1268 for (i
= 0; i
< bset1
->n_ineq
; ++i
)
1269 isl_seq_combine(dir
->block
.data
,
1270 bset1
->ctx
->one
, dir
->block
.data
,
1271 sample
->block
.data
[n
++], bset1
->ineq
[i
], 1 + d
);
1272 isl_vec_free(sample
);
1273 isl_seq_normalize(bset1
->ctx
, dir
->block
.data
+ 1, dir
->size
- 1);
1274 isl_basic_set_free(bset1
);
1275 isl_basic_set_free(bset2
);
1278 isl_vec_free(sample
);
1279 isl_basic_set_free(bset1
);
1280 isl_basic_set_free(bset2
);
1284 /* Given a polyhedron b_i + A_i x >= 0 and a map T = S^{-1},
1285 * compute b_i' + A_i' x' >= 0, with
1287 * [ b_i A_i ] [ y' ] [ y' ]
1288 * [ 1 0 ] S^{-1} [ x' ] >= 0 or [ b_i' A_i' ] [ x' ] >= 0
1290 * In particular, add the "positivity constraint" and then perform
1293 static struct isl_basic_set
*homogeneous_map(struct isl_basic_set
*bset
,
1300 bset
= isl_basic_set_extend_constraints(bset
, 0, 1);
1301 k
= isl_basic_set_alloc_inequality(bset
);
1304 isl_seq_clr(bset
->ineq
[k
] + 1, isl_basic_set_total_dim(bset
));
1305 isl_int_set_si(bset
->ineq
[k
][0], 1);
1306 bset
= isl_basic_set_preimage(bset
, T
);
1310 isl_basic_set_free(bset
);
1314 /* Compute the convex hull of a pair of basic sets without any parameters or
1315 * integer divisions, where the convex hull is known to be pointed,
1316 * but the basic sets may be unbounded.
1318 * We turn this problem into the computation of a convex hull of a pair
1319 * _bounded_ polyhedra by "changing the direction of the homogeneous
1320 * dimension". This idea is due to Matthias Koeppe.
1322 * Consider the cones in homogeneous space that correspond to the
1323 * input polyhedra. The rays of these cones are also rays of the
1324 * polyhedra if the coordinate that corresponds to the homogeneous
1325 * dimension is zero. That is, if the inner product of the rays
1326 * with the homogeneous direction is zero.
1327 * The cones in the homogeneous space can also be considered to
1328 * correspond to other pairs of polyhedra by chosing a different
1329 * homogeneous direction. To ensure that both of these polyhedra
1330 * are bounded, we need to make sure that all rays of the cones
1331 * correspond to vertices and not to rays.
1332 * Let s be a direction such that <s, r> > 0 for all rays r of both cones.
1333 * Then using s as a homogeneous direction, we obtain a pair of polytopes.
1334 * The vector s is computed in valid_direction.
1336 * Note that we need to consider _all_ rays of the cones and not just
1337 * the rays that correspond to rays in the polyhedra. If we were to
1338 * only consider those rays and turn them into vertices, then we
1339 * may inadvertently turn some vertices into rays.
1341 * The standard homogeneous direction is the unit vector in the 0th coordinate.
1342 * We therefore transform the two polyhedra such that the selected
1343 * direction is mapped onto this standard direction and then proceed
1344 * with the normal computation.
1345 * Let S be a non-singular square matrix with s as its first row,
1346 * then we want to map the polyhedra to the space
1348 * [ y' ] [ y ] [ y ] [ y' ]
1349 * [ x' ] = S [ x ] i.e., [ x ] = S^{-1} [ x' ]
1351 * We take S to be the unimodular completion of s to limit the growth
1352 * of the coefficients in the following computations.
1354 * Let b_i + A_i x >= 0 be the constraints of polyhedron i.
1355 * We first move to the homogeneous dimension
1357 * b_i y + A_i x >= 0 [ b_i A_i ] [ y ] [ 0 ]
1358 * y >= 0 or [ 1 0 ] [ x ] >= [ 0 ]
1360 * Then we change directoin
1362 * [ b_i A_i ] [ y' ] [ y' ]
1363 * [ 1 0 ] S^{-1} [ x' ] >= 0 or [ b_i' A_i' ] [ x' ] >= 0
1365 * Then we compute the convex hull of the polytopes b_i' + A_i' x' >= 0
1366 * resulting in b' + A' x' >= 0, which we then convert back
1369 * [ b' A' ] S [ x ] >= 0 or [ b A ] [ x ] >= 0
1371 * The polyhedron b + A x >= 0 is then the convex hull of the input polyhedra.
1373 static struct isl_basic_set
*convex_hull_pair_pointed(
1374 struct isl_basic_set
*bset1
, struct isl_basic_set
*bset2
)
1376 struct isl_ctx
*ctx
= NULL
;
1377 struct isl_vec
*dir
= NULL
;
1378 struct isl_mat
*T
= NULL
;
1379 struct isl_mat
*T2
= NULL
;
1380 struct isl_basic_set
*hull
;
1381 struct isl_set
*set
;
1383 if (!bset1
|| !bset2
)
1386 dir
= valid_direction(isl_basic_set_copy(bset1
),
1387 isl_basic_set_copy(bset2
));
1390 T
= isl_mat_alloc(bset1
->ctx
, dir
->size
, dir
->size
);
1393 isl_seq_cpy(T
->row
[0], dir
->block
.data
, dir
->size
);
1394 T
= isl_mat_unimodular_complete(T
, 1);
1395 T2
= isl_mat_right_inverse(isl_mat_copy(T
));
1397 bset1
= homogeneous_map(bset1
, isl_mat_copy(T2
));
1398 bset2
= homogeneous_map(bset2
, T2
);
1399 set
= isl_set_alloc_dim(isl_basic_set_get_dim(bset1
), 2, 0);
1400 set
= isl_set_add(set
, bset1
);
1401 set
= isl_set_add(set
, bset2
);
1402 hull
= uset_convex_hull(set
);
1403 hull
= isl_basic_set_preimage(hull
, T
);
1410 isl_basic_set_free(bset1
);
1411 isl_basic_set_free(bset2
);
1415 /* Compute the convex hull of a pair of basic sets without any parameters or
1416 * integer divisions.
1418 * If the convex hull of the two basic sets would have a non-trivial
1419 * lineality space, we first project out this lineality space.
1421 static struct isl_basic_set
*convex_hull_pair(struct isl_basic_set
*bset1
,
1422 struct isl_basic_set
*bset2
)
1424 struct isl_basic_set
*lin
;
1426 if (isl_basic_set_is_bounded(bset1
) || isl_basic_set_is_bounded(bset2
))
1427 return convex_hull_pair_pointed(bset1
, bset2
);
1429 lin
= induced_lineality_space(isl_basic_set_copy(bset1
),
1430 isl_basic_set_copy(bset2
));
1433 if (isl_basic_set_is_universe(lin
)) {
1434 isl_basic_set_free(bset1
);
1435 isl_basic_set_free(bset2
);
1438 if (lin
->n_eq
< isl_basic_set_total_dim(lin
)) {
1439 struct isl_set
*set
;
1440 set
= isl_set_alloc_dim(isl_basic_set_get_dim(bset1
), 2, 0);
1441 set
= isl_set_add(set
, bset1
);
1442 set
= isl_set_add(set
, bset2
);
1443 return modulo_lineality(set
, lin
);
1445 isl_basic_set_free(lin
);
1447 return convex_hull_pair_pointed(bset1
, bset2
);
1449 isl_basic_set_free(bset1
);
1450 isl_basic_set_free(bset2
);
1454 /* Compute the lineality space of a basic set.
1455 * We currently do not allow the basic set to have any divs.
1456 * We basically just drop the constants and turn every inequality
1459 struct isl_basic_set
*isl_basic_set_lineality_space(struct isl_basic_set
*bset
)
1462 struct isl_basic_set
*lin
= NULL
;
1467 isl_assert(bset
->ctx
, bset
->n_div
== 0, goto error
);
1468 dim
= isl_basic_set_total_dim(bset
);
1470 lin
= isl_basic_set_alloc_dim(isl_basic_set_get_dim(bset
), 0, dim
, 0);
1473 for (i
= 0; i
< bset
->n_eq
; ++i
) {
1474 k
= isl_basic_set_alloc_equality(lin
);
1477 isl_int_set_si(lin
->eq
[k
][0], 0);
1478 isl_seq_cpy(lin
->eq
[k
] + 1, bset
->eq
[i
] + 1, dim
);
1480 lin
= isl_basic_set_gauss(lin
, NULL
);
1483 for (i
= 0; i
< bset
->n_ineq
&& lin
->n_eq
< dim
; ++i
) {
1484 k
= isl_basic_set_alloc_equality(lin
);
1487 isl_int_set_si(lin
->eq
[k
][0], 0);
1488 isl_seq_cpy(lin
->eq
[k
] + 1, bset
->ineq
[i
] + 1, dim
);
1489 lin
= isl_basic_set_gauss(lin
, NULL
);
1493 isl_basic_set_free(bset
);
1496 isl_basic_set_free(lin
);
1497 isl_basic_set_free(bset
);
1501 /* Compute the (linear) hull of the lineality spaces of the basic sets in the
1502 * "underlying" set "set".
1504 static struct isl_basic_set
*uset_combined_lineality_space(struct isl_set
*set
)
1507 struct isl_set
*lin
= NULL
;
1512 struct isl_dim
*dim
= isl_set_get_dim(set
);
1514 return isl_basic_set_empty(dim
);
1517 lin
= isl_set_alloc_dim(isl_set_get_dim(set
), set
->n
, 0);
1518 for (i
= 0; i
< set
->n
; ++i
)
1519 lin
= isl_set_add(lin
,
1520 isl_basic_set_lineality_space(isl_basic_set_copy(set
->p
[i
])));
1522 return isl_set_affine_hull(lin
);
1525 /* Compute the convex hull of a set without any parameters or
1526 * integer divisions.
1527 * In each step, we combined two basic sets until only one
1528 * basic set is left.
1529 * The input basic sets are assumed not to have a non-trivial
1530 * lineality space. If any of the intermediate results has
1531 * a non-trivial lineality space, it is projected out.
1533 static struct isl_basic_set
*uset_convex_hull_unbounded(struct isl_set
*set
)
1535 struct isl_basic_set
*convex_hull
= NULL
;
1537 convex_hull
= isl_set_copy_basic_set(set
);
1538 set
= isl_set_drop_basic_set(set
, convex_hull
);
1541 while (set
->n
> 0) {
1542 struct isl_basic_set
*t
;
1543 t
= isl_set_copy_basic_set(set
);
1546 set
= isl_set_drop_basic_set(set
, t
);
1549 convex_hull
= convex_hull_pair(convex_hull
, t
);
1552 t
= isl_basic_set_lineality_space(isl_basic_set_copy(convex_hull
));
1555 if (isl_basic_set_is_universe(t
)) {
1556 isl_basic_set_free(convex_hull
);
1560 if (t
->n_eq
< isl_basic_set_total_dim(t
)) {
1561 set
= isl_set_add(set
, convex_hull
);
1562 return modulo_lineality(set
, t
);
1564 isl_basic_set_free(t
);
1570 isl_basic_set_free(convex_hull
);
1574 /* Compute an initial hull for wrapping containing a single initial
1575 * facet by first computing bounds on the set and then using these
1576 * bounds to construct an initial facet.
1577 * This function is a remnant of an older implementation where the
1578 * bounds were also used to check whether the set was bounded.
1579 * Since this function will now only be called when we know the
1580 * set to be bounded, the initial facet should probably be constructed
1581 * by simply using the coordinate directions instead.
1583 static struct isl_basic_set
*initial_hull(struct isl_basic_set
*hull
,
1584 struct isl_set
*set
)
1586 struct isl_mat
*bounds
= NULL
;
1592 bounds
= independent_bounds(set
);
1595 isl_assert(set
->ctx
, bounds
->n_row
== isl_set_n_dim(set
), goto error
);
1596 bounds
= initial_facet_constraint(set
, bounds
);
1599 k
= isl_basic_set_alloc_inequality(hull
);
1602 dim
= isl_set_n_dim(set
);
1603 isl_assert(set
->ctx
, 1 + dim
== bounds
->n_col
, goto error
);
1604 isl_seq_cpy(hull
->ineq
[k
], bounds
->row
[0], bounds
->n_col
);
1605 isl_mat_free(bounds
);
1609 isl_basic_set_free(hull
);
1610 isl_mat_free(bounds
);
1614 struct max_constraint
{
1620 static int max_constraint_equal(const void *entry
, const void *val
)
1622 struct max_constraint
*a
= (struct max_constraint
*)entry
;
1623 isl_int
*b
= (isl_int
*)val
;
1625 return isl_seq_eq(a
->c
->row
[0] + 1, b
, a
->c
->n_col
- 1);
1628 static void update_constraint(struct isl_ctx
*ctx
, struct isl_hash_table
*table
,
1629 isl_int
*con
, unsigned len
, int n
, int ineq
)
1631 struct isl_hash_table_entry
*entry
;
1632 struct max_constraint
*c
;
1635 c_hash
= isl_seq_get_hash(con
+ 1, len
);
1636 entry
= isl_hash_table_find(ctx
, table
, c_hash
, max_constraint_equal
,
1642 isl_hash_table_remove(ctx
, table
, entry
);
1646 if (isl_int_gt(c
->c
->row
[0][0], con
[0]))
1648 if (isl_int_eq(c
->c
->row
[0][0], con
[0])) {
1653 c
->c
= isl_mat_cow(c
->c
);
1654 isl_int_set(c
->c
->row
[0][0], con
[0]);
1658 /* Check whether the constraint hash table "table" constains the constraint
1661 static int has_constraint(struct isl_ctx
*ctx
, struct isl_hash_table
*table
,
1662 isl_int
*con
, unsigned len
, int n
)
1664 struct isl_hash_table_entry
*entry
;
1665 struct max_constraint
*c
;
1668 c_hash
= isl_seq_get_hash(con
+ 1, len
);
1669 entry
= isl_hash_table_find(ctx
, table
, c_hash
, max_constraint_equal
,
1676 return isl_int_eq(c
->c
->row
[0][0], con
[0]);
1679 /* Check for inequality constraints of a basic set without equalities
1680 * such that the same or more stringent copies of the constraint appear
1681 * in all of the basic sets. Such constraints are necessarily facet
1682 * constraints of the convex hull.
1684 * If the resulting basic set is by chance identical to one of
1685 * the basic sets in "set", then we know that this basic set contains
1686 * all other basic sets and is therefore the convex hull of set.
1687 * In this case we set *is_hull to 1.
1689 static struct isl_basic_set
*common_constraints(struct isl_basic_set
*hull
,
1690 struct isl_set
*set
, int *is_hull
)
1693 int min_constraints
;
1695 struct max_constraint
*constraints
= NULL
;
1696 struct isl_hash_table
*table
= NULL
;
1701 for (i
= 0; i
< set
->n
; ++i
)
1702 if (set
->p
[i
]->n_eq
== 0)
1706 min_constraints
= set
->p
[i
]->n_ineq
;
1708 for (i
= best
+ 1; i
< set
->n
; ++i
) {
1709 if (set
->p
[i
]->n_eq
!= 0)
1711 if (set
->p
[i
]->n_ineq
>= min_constraints
)
1713 min_constraints
= set
->p
[i
]->n_ineq
;
1716 constraints
= isl_calloc_array(hull
->ctx
, struct max_constraint
,
1720 table
= isl_alloc_type(hull
->ctx
, struct isl_hash_table
);
1721 if (isl_hash_table_init(hull
->ctx
, table
, min_constraints
))
1724 total
= isl_dim_total(set
->dim
);
1725 for (i
= 0; i
< set
->p
[best
]->n_ineq
; ++i
) {
1726 constraints
[i
].c
= isl_mat_sub_alloc(hull
->ctx
,
1727 set
->p
[best
]->ineq
+ i
, 0, 1, 0, 1 + total
);
1728 if (!constraints
[i
].c
)
1730 constraints
[i
].ineq
= 1;
1732 for (i
= 0; i
< min_constraints
; ++i
) {
1733 struct isl_hash_table_entry
*entry
;
1735 c_hash
= isl_seq_get_hash(constraints
[i
].c
->row
[0] + 1, total
);
1736 entry
= isl_hash_table_find(hull
->ctx
, table
, c_hash
,
1737 max_constraint_equal
, constraints
[i
].c
->row
[0] + 1, 1);
1740 isl_assert(hull
->ctx
, !entry
->data
, goto error
);
1741 entry
->data
= &constraints
[i
];
1745 for (s
= 0; s
< set
->n
; ++s
) {
1749 for (i
= 0; i
< set
->p
[s
]->n_eq
; ++i
) {
1750 isl_int
*eq
= set
->p
[s
]->eq
[i
];
1751 for (j
= 0; j
< 2; ++j
) {
1752 isl_seq_neg(eq
, eq
, 1 + total
);
1753 update_constraint(hull
->ctx
, table
,
1757 for (i
= 0; i
< set
->p
[s
]->n_ineq
; ++i
) {
1758 isl_int
*ineq
= set
->p
[s
]->ineq
[i
];
1759 update_constraint(hull
->ctx
, table
, ineq
, total
, n
,
1760 set
->p
[s
]->n_eq
== 0);
1765 for (i
= 0; i
< min_constraints
; ++i
) {
1766 if (constraints
[i
].count
< n
)
1768 if (!constraints
[i
].ineq
)
1770 j
= isl_basic_set_alloc_inequality(hull
);
1773 isl_seq_cpy(hull
->ineq
[j
], constraints
[i
].c
->row
[0], 1 + total
);
1776 for (s
= 0; s
< set
->n
; ++s
) {
1777 if (set
->p
[s
]->n_eq
)
1779 if (set
->p
[s
]->n_ineq
!= hull
->n_ineq
)
1781 for (i
= 0; i
< set
->p
[s
]->n_ineq
; ++i
) {
1782 isl_int
*ineq
= set
->p
[s
]->ineq
[i
];
1783 if (!has_constraint(hull
->ctx
, table
, ineq
, total
, n
))
1786 if (i
== set
->p
[s
]->n_ineq
)
1790 isl_hash_table_clear(table
);
1791 for (i
= 0; i
< min_constraints
; ++i
)
1792 isl_mat_free(constraints
[i
].c
);
1797 isl_hash_table_clear(table
);
1800 for (i
= 0; i
< min_constraints
; ++i
)
1801 isl_mat_free(constraints
[i
].c
);
1806 /* Create a template for the convex hull of "set" and fill it up
1807 * obvious facet constraints, if any. If the result happens to
1808 * be the convex hull of "set" then *is_hull is set to 1.
1810 static struct isl_basic_set
*proto_hull(struct isl_set
*set
, int *is_hull
)
1812 struct isl_basic_set
*hull
;
1817 for (i
= 0; i
< set
->n
; ++i
) {
1818 n_ineq
+= set
->p
[i
]->n_eq
;
1819 n_ineq
+= set
->p
[i
]->n_ineq
;
1821 hull
= isl_basic_set_alloc_dim(isl_dim_copy(set
->dim
), 0, 0, n_ineq
);
1822 hull
= isl_basic_set_set_rational(hull
);
1825 return common_constraints(hull
, set
, is_hull
);
1828 static struct isl_basic_set
*uset_convex_hull_wrap(struct isl_set
*set
)
1830 struct isl_basic_set
*hull
;
1833 hull
= proto_hull(set
, &is_hull
);
1834 if (hull
&& !is_hull
) {
1835 if (hull
->n_ineq
== 0)
1836 hull
= initial_hull(hull
, set
);
1837 hull
= extend(hull
, set
);
1844 /* Compute the convex hull of a set without any parameters or
1845 * integer divisions. Depending on whether the set is bounded,
1846 * we pass control to the wrapping based convex hull or
1847 * the Fourier-Motzkin elimination based convex hull.
1848 * We also handle a few special cases before checking the boundedness.
1850 static struct isl_basic_set
*uset_convex_hull(struct isl_set
*set
)
1852 struct isl_basic_set
*convex_hull
= NULL
;
1853 struct isl_basic_set
*lin
;
1855 if (isl_set_n_dim(set
) == 0)
1856 return convex_hull_0d(set
);
1858 set
= isl_set_coalesce(set
);
1859 set
= isl_set_set_rational(set
);
1866 convex_hull
= isl_basic_set_copy(set
->p
[0]);
1870 if (isl_set_n_dim(set
) == 1)
1871 return convex_hull_1d(set
);
1873 if (isl_set_is_bounded(set
))
1874 return uset_convex_hull_wrap(set
);
1876 lin
= uset_combined_lineality_space(isl_set_copy(set
));
1879 if (isl_basic_set_is_universe(lin
)) {
1883 if (lin
->n_eq
< isl_basic_set_total_dim(lin
))
1884 return modulo_lineality(set
, lin
);
1885 isl_basic_set_free(lin
);
1887 return uset_convex_hull_unbounded(set
);
1890 isl_basic_set_free(convex_hull
);
1894 /* This is the core procedure, where "set" is a "pure" set, i.e.,
1895 * without parameters or divs and where the convex hull of set is
1896 * known to be full-dimensional.
1898 static struct isl_basic_set
*uset_convex_hull_wrap_bounded(struct isl_set
*set
)
1900 struct isl_basic_set
*convex_hull
= NULL
;
1902 if (isl_set_n_dim(set
) == 0) {
1903 convex_hull
= isl_basic_set_universe(isl_dim_copy(set
->dim
));
1905 convex_hull
= isl_basic_set_set_rational(convex_hull
);
1909 set
= isl_set_set_rational(set
);
1913 set
= isl_set_coalesce(set
);
1917 convex_hull
= isl_basic_set_copy(set
->p
[0]);
1921 if (isl_set_n_dim(set
) == 1)
1922 return convex_hull_1d(set
);
1924 return uset_convex_hull_wrap(set
);
1930 /* Compute the convex hull of set "set" with affine hull "affine_hull",
1931 * We first remove the equalities (transforming the set), compute the
1932 * convex hull of the transformed set and then add the equalities back
1933 * (after performing the inverse transformation.
1935 static struct isl_basic_set
*modulo_affine_hull(struct isl_ctx
*ctx
,
1936 struct isl_set
*set
, struct isl_basic_set
*affine_hull
)
1940 struct isl_basic_set
*dummy
;
1941 struct isl_basic_set
*convex_hull
;
1943 dummy
= isl_basic_set_remove_equalities(
1944 isl_basic_set_copy(affine_hull
), &T
, &T2
);
1947 isl_basic_set_free(dummy
);
1948 set
= isl_set_preimage(set
, T
);
1949 convex_hull
= uset_convex_hull(set
);
1950 convex_hull
= isl_basic_set_preimage(convex_hull
, T2
);
1951 convex_hull
= isl_basic_set_intersect(convex_hull
, affine_hull
);
1954 isl_basic_set_free(affine_hull
);
1959 /* Compute the convex hull of a map.
1961 * The implementation was inspired by "Extended Convex Hull" by Fukuda et al.,
1962 * specifically, the wrapping of facets to obtain new facets.
1964 struct isl_basic_map
*isl_map_convex_hull(struct isl_map
*map
)
1966 struct isl_basic_set
*bset
;
1967 struct isl_basic_map
*model
= NULL
;
1968 struct isl_basic_set
*affine_hull
= NULL
;
1969 struct isl_basic_map
*convex_hull
= NULL
;
1970 struct isl_set
*set
= NULL
;
1971 struct isl_ctx
*ctx
;
1978 convex_hull
= isl_basic_map_empty_like_map(map
);
1983 map
= isl_map_detect_equalities(map
);
1984 map
= isl_map_align_divs(map
);
1985 model
= isl_basic_map_copy(map
->p
[0]);
1986 set
= isl_map_underlying_set(map
);
1990 affine_hull
= isl_set_affine_hull(isl_set_copy(set
));
1993 if (affine_hull
->n_eq
!= 0)
1994 bset
= modulo_affine_hull(ctx
, set
, affine_hull
);
1996 isl_basic_set_free(affine_hull
);
1997 bset
= uset_convex_hull(set
);
2000 convex_hull
= isl_basic_map_overlying_set(bset
, model
);
2002 ISL_F_SET(convex_hull
, ISL_BASIC_MAP_NO_IMPLICIT
);
2003 ISL_F_SET(convex_hull
, ISL_BASIC_MAP_ALL_EQUALITIES
);
2004 ISL_F_CLR(convex_hull
, ISL_BASIC_MAP_RATIONAL
);
2008 isl_basic_map_free(model
);
2012 struct isl_basic_set
*isl_set_convex_hull(struct isl_set
*set
)
2014 return (struct isl_basic_set
*)
2015 isl_map_convex_hull((struct isl_map
*)set
);
2018 struct sh_data_entry
{
2019 struct isl_hash_table
*table
;
2020 struct isl_tab
*tab
;
2023 /* Holds the data needed during the simple hull computation.
2025 * n the number of basic sets in the original set
2026 * hull_table a hash table of already computed constraints
2027 * in the simple hull
2028 * p for each basic set,
2029 * table a hash table of the constraints
2030 * tab the tableau corresponding to the basic set
2033 struct isl_ctx
*ctx
;
2035 struct isl_hash_table
*hull_table
;
2036 struct sh_data_entry p
[1];
2039 static void sh_data_free(struct sh_data
*data
)
2045 isl_hash_table_free(data
->ctx
, data
->hull_table
);
2046 for (i
= 0; i
< data
->n
; ++i
) {
2047 isl_hash_table_free(data
->ctx
, data
->p
[i
].table
);
2048 isl_tab_free(data
->p
[i
].tab
);
2053 struct ineq_cmp_data
{
2058 static int has_ineq(const void *entry
, const void *val
)
2060 isl_int
*row
= (isl_int
*)entry
;
2061 struct ineq_cmp_data
*v
= (struct ineq_cmp_data
*)val
;
2063 return isl_seq_eq(row
+ 1, v
->p
+ 1, v
->len
) ||
2064 isl_seq_is_neg(row
+ 1, v
->p
+ 1, v
->len
);
2067 static int hash_ineq(struct isl_ctx
*ctx
, struct isl_hash_table
*table
,
2068 isl_int
*ineq
, unsigned len
)
2071 struct ineq_cmp_data v
;
2072 struct isl_hash_table_entry
*entry
;
2076 c_hash
= isl_seq_get_hash(ineq
+ 1, len
);
2077 entry
= isl_hash_table_find(ctx
, table
, c_hash
, has_ineq
, &v
, 1);
2084 /* Fill hash table "table" with the constraints of "bset".
2085 * Equalities are added as two inequalities.
2086 * The value in the hash table is a pointer to the (in)equality of "bset".
2088 static int hash_basic_set(struct isl_hash_table
*table
,
2089 struct isl_basic_set
*bset
)
2092 unsigned dim
= isl_basic_set_total_dim(bset
);
2094 for (i
= 0; i
< bset
->n_eq
; ++i
) {
2095 for (j
= 0; j
< 2; ++j
) {
2096 isl_seq_neg(bset
->eq
[i
], bset
->eq
[i
], 1 + dim
);
2097 if (hash_ineq(bset
->ctx
, table
, bset
->eq
[i
], dim
) < 0)
2101 for (i
= 0; i
< bset
->n_ineq
; ++i
) {
2102 if (hash_ineq(bset
->ctx
, table
, bset
->ineq
[i
], dim
) < 0)
2108 static struct sh_data
*sh_data_alloc(struct isl_set
*set
, unsigned n_ineq
)
2110 struct sh_data
*data
;
2113 data
= isl_calloc(set
->ctx
, struct sh_data
,
2114 sizeof(struct sh_data
) +
2115 (set
->n
- 1) * sizeof(struct sh_data_entry
));
2118 data
->ctx
= set
->ctx
;
2120 data
->hull_table
= isl_hash_table_alloc(set
->ctx
, n_ineq
);
2121 if (!data
->hull_table
)
2123 for (i
= 0; i
< set
->n
; ++i
) {
2124 data
->p
[i
].table
= isl_hash_table_alloc(set
->ctx
,
2125 2 * set
->p
[i
]->n_eq
+ set
->p
[i
]->n_ineq
);
2126 if (!data
->p
[i
].table
)
2128 if (hash_basic_set(data
->p
[i
].table
, set
->p
[i
]) < 0)
2137 /* Check if inequality "ineq" is a bound for basic set "j" or if
2138 * it can be relaxed (by increasing the constant term) to become
2139 * a bound for that basic set. In the latter case, the constant
2141 * Return 1 if "ineq" is a bound
2142 * 0 if "ineq" may attain arbitrarily small values on basic set "j"
2143 * -1 if some error occurred
2145 static int is_bound(struct sh_data
*data
, struct isl_set
*set
, int j
,
2148 enum isl_lp_result res
;
2151 if (!data
->p
[j
].tab
) {
2152 data
->p
[j
].tab
= isl_tab_from_basic_set(set
->p
[j
]);
2153 if (!data
->p
[j
].tab
)
2159 res
= isl_tab_min(data
->p
[j
].tab
, ineq
, data
->ctx
->one
,
2161 if (res
== isl_lp_ok
&& isl_int_is_neg(opt
))
2162 isl_int_sub(ineq
[0], ineq
[0], opt
);
2166 return res
== isl_lp_ok
? 1 :
2167 res
== isl_lp_unbounded
? 0 : -1;
2170 /* Check if inequality "ineq" from basic set "i" can be relaxed to
2171 * become a bound on the whole set. If so, add the (relaxed) inequality
2174 * We first check if "hull" already contains a translate of the inequality.
2175 * If so, we are done.
2176 * Then, we check if any of the previous basic sets contains a translate
2177 * of the inequality. If so, then we have already considered this
2178 * inequality and we are done.
2179 * Otherwise, for each basic set other than "i", we check if the inequality
2180 * is a bound on the basic set.
2181 * For previous basic sets, we know that they do not contain a translate
2182 * of the inequality, so we directly call is_bound.
2183 * For following basic sets, we first check if a translate of the
2184 * inequality appears in its description and if so directly update
2185 * the inequality accordingly.
2187 static struct isl_basic_set
*add_bound(struct isl_basic_set
*hull
,
2188 struct sh_data
*data
, struct isl_set
*set
, int i
, isl_int
*ineq
)
2191 struct ineq_cmp_data v
;
2192 struct isl_hash_table_entry
*entry
;
2198 v
.len
= isl_basic_set_total_dim(hull
);
2200 c_hash
= isl_seq_get_hash(ineq
+ 1, v
.len
);
2202 entry
= isl_hash_table_find(hull
->ctx
, data
->hull_table
, c_hash
,
2207 for (j
= 0; j
< i
; ++j
) {
2208 entry
= isl_hash_table_find(hull
->ctx
, data
->p
[j
].table
,
2209 c_hash
, has_ineq
, &v
, 0);
2216 k
= isl_basic_set_alloc_inequality(hull
);
2217 isl_seq_cpy(hull
->ineq
[k
], ineq
, 1 + v
.len
);
2221 for (j
= 0; j
< i
; ++j
) {
2223 bound
= is_bound(data
, set
, j
, hull
->ineq
[k
]);
2230 isl_basic_set_free_inequality(hull
, 1);
2234 for (j
= i
+ 1; j
< set
->n
; ++j
) {
2237 entry
= isl_hash_table_find(hull
->ctx
, data
->p
[j
].table
,
2238 c_hash
, has_ineq
, &v
, 0);
2240 ineq_j
= entry
->data
;
2241 neg
= isl_seq_is_neg(ineq_j
+ 1,
2242 hull
->ineq
[k
] + 1, v
.len
);
2244 isl_int_neg(ineq_j
[0], ineq_j
[0]);
2245 if (isl_int_gt(ineq_j
[0], hull
->ineq
[k
][0]))
2246 isl_int_set(hull
->ineq
[k
][0], ineq_j
[0]);
2248 isl_int_neg(ineq_j
[0], ineq_j
[0]);
2251 bound
= is_bound(data
, set
, j
, hull
->ineq
[k
]);
2258 isl_basic_set_free_inequality(hull
, 1);
2262 entry
= isl_hash_table_find(hull
->ctx
, data
->hull_table
, c_hash
,
2266 entry
->data
= hull
->ineq
[k
];
2270 isl_basic_set_free(hull
);
2274 /* Check if any inequality from basic set "i" can be relaxed to
2275 * become a bound on the whole set. If so, add the (relaxed) inequality
2278 static struct isl_basic_set
*add_bounds(struct isl_basic_set
*bset
,
2279 struct sh_data
*data
, struct isl_set
*set
, int i
)
2282 unsigned dim
= isl_basic_set_total_dim(bset
);
2284 for (j
= 0; j
< set
->p
[i
]->n_eq
; ++j
) {
2285 for (k
= 0; k
< 2; ++k
) {
2286 isl_seq_neg(set
->p
[i
]->eq
[j
], set
->p
[i
]->eq
[j
], 1+dim
);
2287 add_bound(bset
, data
, set
, i
, set
->p
[i
]->eq
[j
]);
2290 for (j
= 0; j
< set
->p
[i
]->n_ineq
; ++j
)
2291 add_bound(bset
, data
, set
, i
, set
->p
[i
]->ineq
[j
]);
2295 /* Compute a superset of the convex hull of set that is described
2296 * by only translates of the constraints in the constituents of set.
2298 static struct isl_basic_set
*uset_simple_hull(struct isl_set
*set
)
2300 struct sh_data
*data
= NULL
;
2301 struct isl_basic_set
*hull
= NULL
;
2309 for (i
= 0; i
< set
->n
; ++i
) {
2312 n_ineq
+= 2 * set
->p
[i
]->n_eq
+ set
->p
[i
]->n_ineq
;
2315 hull
= isl_basic_set_alloc_dim(isl_dim_copy(set
->dim
), 0, 0, n_ineq
);
2319 data
= sh_data_alloc(set
, n_ineq
);
2323 for (i
= 0; i
< set
->n
; ++i
)
2324 hull
= add_bounds(hull
, data
, set
, i
);
2332 isl_basic_set_free(hull
);
2337 /* Compute a superset of the convex hull of map that is described
2338 * by only translates of the constraints in the constituents of map.
2340 struct isl_basic_map
*isl_map_simple_hull(struct isl_map
*map
)
2342 struct isl_set
*set
= NULL
;
2343 struct isl_basic_map
*model
= NULL
;
2344 struct isl_basic_map
*hull
;
2345 struct isl_basic_map
*affine_hull
;
2346 struct isl_basic_set
*bset
= NULL
;
2351 hull
= isl_basic_map_empty_like_map(map
);
2356 hull
= isl_basic_map_copy(map
->p
[0]);
2361 map
= isl_map_detect_equalities(map
);
2362 affine_hull
= isl_map_affine_hull(isl_map_copy(map
));
2363 map
= isl_map_align_divs(map
);
2364 model
= isl_basic_map_copy(map
->p
[0]);
2366 set
= isl_map_underlying_set(map
);
2368 bset
= uset_simple_hull(set
);
2370 hull
= isl_basic_map_overlying_set(bset
, model
);
2372 hull
= isl_basic_map_intersect(hull
, affine_hull
);
2373 hull
= isl_basic_map_convex_hull(hull
);
2374 ISL_F_SET(hull
, ISL_BASIC_MAP_NO_IMPLICIT
);
2375 ISL_F_SET(hull
, ISL_BASIC_MAP_ALL_EQUALITIES
);
2380 struct isl_basic_set
*isl_set_simple_hull(struct isl_set
*set
)
2382 return (struct isl_basic_set
*)
2383 isl_map_simple_hull((struct isl_map
*)set
);
2386 /* Given a set "set", return parametric bounds on the dimension "dim".
2388 static struct isl_basic_set
*set_bounds(struct isl_set
*set
, int dim
)
2390 unsigned set_dim
= isl_set_dim(set
, isl_dim_set
);
2391 set
= isl_set_copy(set
);
2392 set
= isl_set_eliminate_dims(set
, dim
+ 1, set_dim
- (dim
+ 1));
2393 set
= isl_set_eliminate_dims(set
, 0, dim
);
2394 return isl_set_convex_hull(set
);
2397 /* Computes a "simple hull" and then check if each dimension in the
2398 * resulting hull is bounded by a symbolic constant. If not, the
2399 * hull is intersected with the corresponding bounds on the whole set.
2401 struct isl_basic_set
*isl_set_bounded_simple_hull(struct isl_set
*set
)
2404 struct isl_basic_set
*hull
;
2405 unsigned nparam
, left
;
2406 int removed_divs
= 0;
2408 hull
= isl_set_simple_hull(isl_set_copy(set
));
2412 nparam
= isl_basic_set_dim(hull
, isl_dim_param
);
2413 for (i
= 0; i
< isl_basic_set_dim(hull
, isl_dim_set
); ++i
) {
2414 int lower
= 0, upper
= 0;
2415 struct isl_basic_set
*bounds
;
2417 left
= isl_basic_set_total_dim(hull
) - nparam
- i
- 1;
2418 for (j
= 0; j
< hull
->n_eq
; ++j
) {
2419 if (isl_int_is_zero(hull
->eq
[j
][1 + nparam
+ i
]))
2421 if (isl_seq_first_non_zero(hull
->eq
[j
]+1+nparam
+i
+1,
2428 for (j
= 0; j
< hull
->n_ineq
; ++j
) {
2429 if (isl_int_is_zero(hull
->ineq
[j
][1 + nparam
+ i
]))
2431 if (isl_seq_first_non_zero(hull
->ineq
[j
]+1+nparam
+i
+1,
2433 isl_seq_first_non_zero(hull
->ineq
[j
]+1+nparam
,
2436 if (isl_int_is_pos(hull
->ineq
[j
][1 + nparam
+ i
]))
2447 if (!removed_divs
) {
2448 set
= isl_set_remove_divs(set
);
2453 bounds
= set_bounds(set
, i
);
2454 hull
= isl_basic_set_intersect(hull
, bounds
);