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
10 #include <isl_ctx_private.h>
11 #include <isl_map_private.h>
12 #include "isl_sample.h"
13 #include "isl_sample_piplib.h"
17 #include "isl_equalities.h"
19 #include "isl_basis_reduction.h"
20 #include <isl_factorization.h>
21 #include <isl_point_private.h>
23 static struct isl_vec
*empty_sample(struct isl_basic_set
*bset
)
27 vec
= isl_vec_alloc(bset
->ctx
, 0);
28 isl_basic_set_free(bset
);
32 /* Construct a zero sample of the same dimension as bset.
33 * As a special case, if bset is zero-dimensional, this
34 * function creates a zero-dimensional sample point.
36 static struct isl_vec
*zero_sample(struct isl_basic_set
*bset
)
39 struct isl_vec
*sample
;
41 dim
= isl_basic_set_total_dim(bset
);
42 sample
= isl_vec_alloc(bset
->ctx
, 1 + dim
);
44 isl_int_set_si(sample
->el
[0], 1);
45 isl_seq_clr(sample
->el
+ 1, dim
);
47 isl_basic_set_free(bset
);
51 static struct isl_vec
*interval_sample(struct isl_basic_set
*bset
)
55 struct isl_vec
*sample
;
57 bset
= isl_basic_set_simplify(bset
);
60 if (isl_basic_set_plain_is_empty(bset
))
61 return empty_sample(bset
);
62 if (bset
->n_eq
== 0 && bset
->n_ineq
== 0)
63 return zero_sample(bset
);
65 sample
= isl_vec_alloc(bset
->ctx
, 2);
70 isl_int_set_si(sample
->block
.data
[0], 1);
73 isl_assert(bset
->ctx
, bset
->n_eq
== 1, goto error
);
74 isl_assert(bset
->ctx
, bset
->n_ineq
== 0, goto error
);
75 if (isl_int_is_one(bset
->eq
[0][1]))
76 isl_int_neg(sample
->el
[1], bset
->eq
[0][0]);
78 isl_assert(bset
->ctx
, isl_int_is_negone(bset
->eq
[0][1]),
80 isl_int_set(sample
->el
[1], bset
->eq
[0][0]);
82 isl_basic_set_free(bset
);
87 if (isl_int_is_one(bset
->ineq
[0][1]))
88 isl_int_neg(sample
->block
.data
[1], bset
->ineq
[0][0]);
90 isl_int_set(sample
->block
.data
[1], bset
->ineq
[0][0]);
91 for (i
= 1; i
< bset
->n_ineq
; ++i
) {
92 isl_seq_inner_product(sample
->block
.data
,
93 bset
->ineq
[i
], 2, &t
);
94 if (isl_int_is_neg(t
))
98 if (i
< bset
->n_ineq
) {
100 return empty_sample(bset
);
103 isl_basic_set_free(bset
);
106 isl_basic_set_free(bset
);
107 isl_vec_free(sample
);
111 static struct isl_mat
*independent_bounds(struct isl_basic_set
*bset
)
114 struct isl_mat
*dirs
= NULL
;
115 struct isl_mat
*bounds
= NULL
;
121 dim
= isl_basic_set_n_dim(bset
);
122 bounds
= isl_mat_alloc(bset
->ctx
, 1+dim
, 1+dim
);
126 isl_int_set_si(bounds
->row
[0][0], 1);
127 isl_seq_clr(bounds
->row
[0]+1, dim
);
130 if (bset
->n_ineq
== 0)
133 dirs
= isl_mat_alloc(bset
->ctx
, dim
, dim
);
135 isl_mat_free(bounds
);
138 isl_seq_cpy(dirs
->row
[0], bset
->ineq
[0]+1, dirs
->n_col
);
139 isl_seq_cpy(bounds
->row
[1], bset
->ineq
[0], bounds
->n_col
);
140 for (j
= 1, n
= 1; n
< dim
&& j
< bset
->n_ineq
; ++j
) {
143 isl_seq_cpy(dirs
->row
[n
], bset
->ineq
[j
]+1, dirs
->n_col
);
145 pos
= isl_seq_first_non_zero(dirs
->row
[n
], dirs
->n_col
);
148 for (i
= 0; i
< n
; ++i
) {
150 pos_i
= isl_seq_first_non_zero(dirs
->row
[i
], dirs
->n_col
);
155 isl_seq_elim(dirs
->row
[n
], dirs
->row
[i
], pos
,
157 pos
= isl_seq_first_non_zero(dirs
->row
[n
], dirs
->n_col
);
165 isl_int
*t
= dirs
->row
[n
];
166 for (k
= n
; k
> i
; --k
)
167 dirs
->row
[k
] = dirs
->row
[k
-1];
171 isl_seq_cpy(bounds
->row
[n
], bset
->ineq
[j
], bounds
->n_col
);
178 static void swap_inequality(struct isl_basic_set
*bset
, int a
, int b
)
180 isl_int
*t
= bset
->ineq
[a
];
181 bset
->ineq
[a
] = bset
->ineq
[b
];
185 /* Skew into positive orthant and project out lineality space.
187 * We perform a unimodular transformation that turns a selected
188 * maximal set of linearly independent bounds into constraints
189 * on the first dimensions that impose that these first dimensions
190 * are non-negative. In particular, the constraint matrix is lower
191 * triangular with positive entries on the diagonal and negative
193 * If "bset" has a lineality space then these constraints (and therefore
194 * all constraints in bset) only involve the first dimensions.
195 * The remaining dimensions then do not appear in any constraints and
196 * we can select any value for them, say zero. We therefore project
197 * out this final dimensions and plug in the value zero later. This
198 * is accomplished by simply dropping the final columns of
199 * the unimodular transformation.
201 static struct isl_basic_set
*isl_basic_set_skew_to_positive_orthant(
202 struct isl_basic_set
*bset
, struct isl_mat
**T
)
204 struct isl_mat
*U
= NULL
;
205 struct isl_mat
*bounds
= NULL
;
207 unsigned old_dim
, new_dim
;
213 isl_assert(bset
->ctx
, isl_basic_set_n_param(bset
) == 0, goto error
);
214 isl_assert(bset
->ctx
, bset
->n_div
== 0, goto error
);
215 isl_assert(bset
->ctx
, bset
->n_eq
== 0, goto error
);
217 old_dim
= isl_basic_set_n_dim(bset
);
218 /* Try to move (multiples of) unit rows up. */
219 for (i
= 0, j
= 0; i
< bset
->n_ineq
; ++i
) {
220 int pos
= isl_seq_first_non_zero(bset
->ineq
[i
]+1, old_dim
);
223 if (isl_seq_first_non_zero(bset
->ineq
[i
]+1+pos
+1,
227 swap_inequality(bset
, i
, j
);
230 bounds
= independent_bounds(bset
);
233 new_dim
= bounds
->n_row
- 1;
234 bounds
= isl_mat_left_hermite(bounds
, 1, &U
, NULL
);
237 U
= isl_mat_drop_cols(U
, 1 + new_dim
, old_dim
- new_dim
);
238 bset
= isl_basic_set_preimage(bset
, isl_mat_copy(U
));
242 isl_mat_free(bounds
);
245 isl_mat_free(bounds
);
247 isl_basic_set_free(bset
);
251 /* Find a sample integer point, if any, in bset, which is known
252 * to have equalities. If bset contains no integer points, then
253 * return a zero-length vector.
254 * We simply remove the known equalities, compute a sample
255 * in the resulting bset, using the specified recurse function,
256 * and then transform the sample back to the original space.
258 static struct isl_vec
*sample_eq(struct isl_basic_set
*bset
,
259 struct isl_vec
*(*recurse
)(struct isl_basic_set
*))
262 struct isl_vec
*sample
;
267 bset
= isl_basic_set_remove_equalities(bset
, &T
, NULL
);
268 sample
= recurse(bset
);
269 if (!sample
|| sample
->size
== 0)
272 sample
= isl_mat_vec_product(T
, sample
);
276 /* Return a matrix containing the equalities of the tableau
277 * in constraint form. The tableau is assumed to have
278 * an associated bset that has been kept up-to-date.
280 static struct isl_mat
*tab_equalities(struct isl_tab
*tab
)
285 struct isl_basic_set
*bset
;
290 bset
= isl_tab_peek_bset(tab
);
291 isl_assert(tab
->mat
->ctx
, bset
, return NULL
);
293 n_eq
= tab
->n_var
- tab
->n_col
+ tab
->n_dead
;
294 if (tab
->empty
|| n_eq
== 0)
295 return isl_mat_alloc(tab
->mat
->ctx
, 0, tab
->n_var
);
296 if (n_eq
== tab
->n_var
)
297 return isl_mat_identity(tab
->mat
->ctx
, tab
->n_var
);
299 eq
= isl_mat_alloc(tab
->mat
->ctx
, n_eq
, tab
->n_var
);
302 for (i
= 0, j
= 0; i
< tab
->n_con
; ++i
) {
303 if (tab
->con
[i
].is_row
)
305 if (tab
->con
[i
].index
>= 0 && tab
->con
[i
].index
>= tab
->n_dead
)
308 isl_seq_cpy(eq
->row
[j
], bset
->eq
[i
] + 1, tab
->n_var
);
310 isl_seq_cpy(eq
->row
[j
],
311 bset
->ineq
[i
- bset
->n_eq
] + 1, tab
->n_var
);
314 isl_assert(bset
->ctx
, j
== n_eq
, goto error
);
321 /* Compute and return an initial basis for the bounded tableau "tab".
323 * If the tableau is either full-dimensional or zero-dimensional,
324 * the we simply return an identity matrix.
325 * Otherwise, we construct a basis whose first directions correspond
328 static struct isl_mat
*initial_basis(struct isl_tab
*tab
)
334 tab
->n_unbounded
= 0;
335 tab
->n_zero
= n_eq
= tab
->n_var
- tab
->n_col
+ tab
->n_dead
;
336 if (tab
->empty
|| n_eq
== 0 || n_eq
== tab
->n_var
)
337 return isl_mat_identity(tab
->mat
->ctx
, 1 + tab
->n_var
);
339 eq
= tab_equalities(tab
);
340 eq
= isl_mat_left_hermite(eq
, 0, NULL
, &Q
);
345 Q
= isl_mat_lin_to_aff(Q
);
349 /* Given a tableau representing a set, find and return
350 * an integer point in the set, if there is any.
352 * We perform a depth first search
353 * for an integer point, by scanning all possible values in the range
354 * attained by a basis vector, where an initial basis may have been set
355 * by the calling function. Otherwise an initial basis that exploits
356 * the equalities in the tableau is created.
357 * tab->n_zero is currently ignored and is clobbered by this function.
359 * The tableau is allowed to have unbounded direction, but then
360 * the calling function needs to set an initial basis, with the
361 * unbounded directions last and with tab->n_unbounded set
362 * to the number of unbounded directions.
363 * Furthermore, the calling functions needs to add shifted copies
364 * of all constraints involving unbounded directions to ensure
365 * that any feasible rational value in these directions can be rounded
366 * up to yield a feasible integer value.
367 * In particular, let B define the given basis x' = B x
368 * and let T be the inverse of B, i.e., X = T x'.
369 * Let a x + c >= 0 be a constraint of the set represented by the tableau,
370 * or a T x' + c >= 0 in terms of the given basis. Assume that
371 * the bounded directions have an integer value, then we can safely
372 * round up the values for the unbounded directions if we make sure
373 * that x' not only satisfies the original constraint, but also
374 * the constraint "a T x' + c + s >= 0" with s the sum of all
375 * negative values in the last n_unbounded entries of "a T".
376 * The calling function therefore needs to add the constraint
377 * a x + c + s >= 0. The current function then scans the first
378 * directions for an integer value and once those have been found,
379 * it can compute "T ceil(B x)" to yield an integer point in the set.
380 * Note that during the search, the first rows of B may be changed
381 * by a basis reduction, but the last n_unbounded rows of B remain
382 * unaltered and are also not mixed into the first rows.
384 * The search is implemented iteratively. "level" identifies the current
385 * basis vector. "init" is true if we want the first value at the current
386 * level and false if we want the next value.
388 * The initial basis is the identity matrix. If the range in some direction
389 * contains more than one integer value, we perform basis reduction based
390 * on the value of ctx->opt->gbr
391 * - ISL_GBR_NEVER: never perform basis reduction
392 * - ISL_GBR_ONCE: only perform basis reduction the first
393 * time such a range is encountered
394 * - ISL_GBR_ALWAYS: always perform basis reduction when
395 * such a range is encountered
397 * When ctx->opt->gbr is set to ISL_GBR_ALWAYS, then we allow the basis
398 * reduction computation to return early. That is, as soon as it
399 * finds a reasonable first direction.
401 struct isl_vec
*isl_tab_sample(struct isl_tab
*tab
)
406 struct isl_vec
*sample
;
409 enum isl_lp_result res
;
413 struct isl_tab_undo
**snap
;
418 return isl_vec_alloc(tab
->mat
->ctx
, 0);
421 tab
->basis
= initial_basis(tab
);
424 isl_assert(tab
->mat
->ctx
, tab
->basis
->n_row
== tab
->n_var
+ 1,
426 isl_assert(tab
->mat
->ctx
, tab
->basis
->n_col
== tab
->n_var
+ 1,
433 if (tab
->n_unbounded
== tab
->n_var
) {
434 sample
= isl_tab_get_sample_value(tab
);
435 sample
= isl_mat_vec_product(isl_mat_copy(tab
->basis
), sample
);
436 sample
= isl_vec_ceil(sample
);
437 sample
= isl_mat_vec_inverse_product(isl_mat_copy(tab
->basis
),
442 if (isl_tab_extend_cons(tab
, dim
+ 1) < 0)
445 min
= isl_vec_alloc(ctx
, dim
);
446 max
= isl_vec_alloc(ctx
, dim
);
447 snap
= isl_alloc_array(ctx
, struct isl_tab_undo
*, dim
);
449 if (!min
|| !max
|| !snap
)
459 res
= isl_tab_min(tab
, tab
->basis
->row
[1 + level
],
460 ctx
->one
, &min
->el
[level
], NULL
, 0);
461 if (res
== isl_lp_empty
)
463 isl_assert(ctx
, res
!= isl_lp_unbounded
, goto error
);
464 if (res
== isl_lp_error
)
466 if (!empty
&& isl_tab_sample_is_integer(tab
))
468 isl_seq_neg(tab
->basis
->row
[1 + level
] + 1,
469 tab
->basis
->row
[1 + level
] + 1, dim
);
470 res
= isl_tab_min(tab
, tab
->basis
->row
[1 + level
],
471 ctx
->one
, &max
->el
[level
], NULL
, 0);
472 isl_seq_neg(tab
->basis
->row
[1 + level
] + 1,
473 tab
->basis
->row
[1 + level
] + 1, dim
);
474 isl_int_neg(max
->el
[level
], max
->el
[level
]);
475 if (res
== isl_lp_empty
)
477 isl_assert(ctx
, res
!= isl_lp_unbounded
, goto error
);
478 if (res
== isl_lp_error
)
480 if (!empty
&& isl_tab_sample_is_integer(tab
))
482 if (!empty
&& !reduced
&&
483 ctx
->opt
->gbr
!= ISL_GBR_NEVER
&&
484 isl_int_lt(min
->el
[level
], max
->el
[level
])) {
485 unsigned gbr_only_first
;
486 if (ctx
->opt
->gbr
== ISL_GBR_ONCE
)
487 ctx
->opt
->gbr
= ISL_GBR_NEVER
;
489 gbr_only_first
= ctx
->opt
->gbr_only_first
;
490 ctx
->opt
->gbr_only_first
=
491 ctx
->opt
->gbr
== ISL_GBR_ALWAYS
;
492 tab
= isl_tab_compute_reduced_basis(tab
);
493 ctx
->opt
->gbr_only_first
= gbr_only_first
;
494 if (!tab
|| !tab
->basis
)
500 snap
[level
] = isl_tab_snap(tab
);
502 isl_int_add_ui(min
->el
[level
], min
->el
[level
], 1);
504 if (empty
|| isl_int_gt(min
->el
[level
], max
->el
[level
])) {
508 if (isl_tab_rollback(tab
, snap
[level
]) < 0)
512 isl_int_neg(tab
->basis
->row
[1 + level
][0], min
->el
[level
]);
513 if (isl_tab_add_valid_eq(tab
, tab
->basis
->row
[1 + level
]) < 0)
515 isl_int_set_si(tab
->basis
->row
[1 + level
][0], 0);
516 if (level
+ tab
->n_unbounded
< dim
- 1) {
525 sample
= isl_tab_get_sample_value(tab
);
528 if (tab
->n_unbounded
&& !isl_int_is_one(sample
->el
[0])) {
529 sample
= isl_mat_vec_product(isl_mat_copy(tab
->basis
),
531 sample
= isl_vec_ceil(sample
);
532 sample
= isl_mat_vec_inverse_product(
533 isl_mat_copy(tab
->basis
), sample
);
536 sample
= isl_vec_alloc(ctx
, 0);
551 static struct isl_vec
*sample_bounded(struct isl_basic_set
*bset
);
553 /* Compute a sample point of the given basic set, based on the given,
554 * non-trivial factorization.
556 static __isl_give isl_vec
*factored_sample(__isl_take isl_basic_set
*bset
,
557 __isl_take isl_factorizer
*f
)
560 isl_vec
*sample
= NULL
;
565 ctx
= isl_basic_set_get_ctx(bset
);
569 nparam
= isl_basic_set_dim(bset
, isl_dim_param
);
570 nvar
= isl_basic_set_dim(bset
, isl_dim_set
);
572 sample
= isl_vec_alloc(ctx
, 1 + isl_basic_set_total_dim(bset
));
575 isl_int_set_si(sample
->el
[0], 1);
577 bset
= isl_morph_basic_set(isl_morph_copy(f
->morph
), bset
);
579 for (i
= 0, n
= 0; i
< f
->n_group
; ++i
) {
580 isl_basic_set
*bset_i
;
583 bset_i
= isl_basic_set_copy(bset
);
584 bset_i
= isl_basic_set_drop_constraints_involving(bset_i
,
585 nparam
+ n
+ f
->len
[i
], nvar
- n
- f
->len
[i
]);
586 bset_i
= isl_basic_set_drop_constraints_involving(bset_i
,
588 bset_i
= isl_basic_set_drop(bset_i
, isl_dim_set
,
589 n
+ f
->len
[i
], nvar
- n
- f
->len
[i
]);
590 bset_i
= isl_basic_set_drop(bset_i
, isl_dim_set
, 0, n
);
592 sample_i
= sample_bounded(bset_i
);
595 if (sample_i
->size
== 0) {
596 isl_basic_set_free(bset
);
597 isl_factorizer_free(f
);
598 isl_vec_free(sample
);
601 isl_seq_cpy(sample
->el
+ 1 + nparam
+ n
,
602 sample_i
->el
+ 1, f
->len
[i
]);
603 isl_vec_free(sample_i
);
608 f
->morph
= isl_morph_inverse(f
->morph
);
609 sample
= isl_morph_vec(isl_morph_copy(f
->morph
), sample
);
611 isl_basic_set_free(bset
);
612 isl_factorizer_free(f
);
615 isl_basic_set_free(bset
);
616 isl_factorizer_free(f
);
617 isl_vec_free(sample
);
621 /* Given a basic set that is known to be bounded, find and return
622 * an integer point in the basic set, if there is any.
624 * After handling some trivial cases, we construct a tableau
625 * and then use isl_tab_sample to find a sample, passing it
626 * the identity matrix as initial basis.
628 static struct isl_vec
*sample_bounded(struct isl_basic_set
*bset
)
632 struct isl_vec
*sample
;
633 struct isl_tab
*tab
= NULL
;
639 if (isl_basic_set_plain_is_empty(bset
))
640 return empty_sample(bset
);
642 dim
= isl_basic_set_total_dim(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
);
659 tab
= isl_tab_from_basic_set(bset
);
660 if (tab
&& tab
->empty
) {
662 ISL_F_SET(bset
, ISL_BASIC_SET_EMPTY
);
663 sample
= isl_vec_alloc(bset
->ctx
, 0);
664 isl_basic_set_free(bset
);
668 if (isl_tab_track_bset(tab
, isl_basic_set_copy(bset
)) < 0)
670 if (!ISL_F_ISSET(bset
, ISL_BASIC_SET_NO_IMPLICIT
))
671 if (isl_tab_detect_implicit_equalities(tab
) < 0)
674 sample
= isl_tab_sample(tab
);
678 if (sample
->size
> 0) {
679 isl_vec_free(bset
->sample
);
680 bset
->sample
= isl_vec_copy(sample
);
683 isl_basic_set_free(bset
);
687 isl_basic_set_free(bset
);
692 /* Given a basic set "bset" and a value "sample" for the first coordinates
693 * of bset, plug in these values and drop the corresponding coordinates.
695 * We do this by computing the preimage of the transformation
701 * where [1 s] is the sample value and I is the identity matrix of the
702 * appropriate dimension.
704 static struct isl_basic_set
*plug_in(struct isl_basic_set
*bset
,
705 struct isl_vec
*sample
)
711 if (!bset
|| !sample
)
714 total
= isl_basic_set_total_dim(bset
);
715 T
= isl_mat_alloc(bset
->ctx
, 1 + total
, 1 + total
- (sample
->size
- 1));
719 for (i
= 0; i
< sample
->size
; ++i
) {
720 isl_int_set(T
->row
[i
][0], sample
->el
[i
]);
721 isl_seq_clr(T
->row
[i
] + 1, T
->n_col
- 1);
723 for (i
= 0; i
< T
->n_col
- 1; ++i
) {
724 isl_seq_clr(T
->row
[sample
->size
+ i
], T
->n_col
);
725 isl_int_set_si(T
->row
[sample
->size
+ i
][1 + i
], 1);
727 isl_vec_free(sample
);
729 bset
= isl_basic_set_preimage(bset
, T
);
732 isl_basic_set_free(bset
);
733 isl_vec_free(sample
);
737 /* Given a basic set "bset", return any (possibly non-integer) point
740 static struct isl_vec
*rational_sample(struct isl_basic_set
*bset
)
743 struct isl_vec
*sample
;
748 tab
= isl_tab_from_basic_set(bset
);
749 sample
= isl_tab_get_sample_value(tab
);
752 isl_basic_set_free(bset
);
757 /* Given a linear cone "cone" and a rational point "vec",
758 * construct a polyhedron with shifted copies of the constraints in "cone",
759 * i.e., a polyhedron with "cone" as its recession cone, such that each
760 * point x in this polyhedron is such that the unit box positioned at x
761 * lies entirely inside the affine cone 'vec + cone'.
762 * Any rational point in this polyhedron may therefore be rounded up
763 * to yield an integer point that lies inside said affine cone.
765 * Denote the constraints of cone by "<a_i, x> >= 0" and the rational
766 * point "vec" by v/d.
767 * Let b_i = <a_i, v>. Then the affine cone 'vec + cone' is given
768 * by <a_i, x> - b/d >= 0.
769 * The polyhedron <a_i, x> - ceil{b/d} >= 0 is a subset of this affine cone.
770 * We prefer this polyhedron over the actual affine cone because it doesn't
771 * require a scaling of the constraints.
772 * If each of the vertices of the unit cube positioned at x lies inside
773 * this polyhedron, then the whole unit cube at x lies inside the affine cone.
774 * We therefore impose that x' = x + \sum e_i, for any selection of unit
775 * vectors lies inside the polyhedron, i.e.,
777 * <a_i, x'> - ceil{b/d} = <a_i, x> + sum a_i - ceil{b/d} >= 0
779 * The most stringent of these constraints is the one that selects
780 * all negative a_i, so the polyhedron we are looking for has constraints
782 * <a_i, x> + sum_{a_i < 0} a_i - ceil{b/d} >= 0
784 * Note that if cone were known to have only non-negative rays
785 * (which can be accomplished by a unimodular transformation),
786 * then we would only have to check the points x' = x + e_i
787 * and we only have to add the smallest negative a_i (if any)
788 * instead of the sum of all negative a_i.
790 static struct isl_basic_set
*shift_cone(struct isl_basic_set
*cone
,
796 struct isl_basic_set
*shift
= NULL
;
801 isl_assert(cone
->ctx
, cone
->n_eq
== 0, goto error
);
803 total
= isl_basic_set_total_dim(cone
);
805 shift
= isl_basic_set_alloc_dim(isl_basic_set_get_dim(cone
),
808 for (i
= 0; i
< cone
->n_ineq
; ++i
) {
809 k
= isl_basic_set_alloc_inequality(shift
);
812 isl_seq_cpy(shift
->ineq
[k
] + 1, cone
->ineq
[i
] + 1, total
);
813 isl_seq_inner_product(shift
->ineq
[k
] + 1, vec
->el
+ 1, total
,
815 isl_int_cdiv_q(shift
->ineq
[k
][0],
816 shift
->ineq
[k
][0], vec
->el
[0]);
817 isl_int_neg(shift
->ineq
[k
][0], shift
->ineq
[k
][0]);
818 for (j
= 0; j
< total
; ++j
) {
819 if (isl_int_is_nonneg(shift
->ineq
[k
][1 + j
]))
821 isl_int_add(shift
->ineq
[k
][0],
822 shift
->ineq
[k
][0], shift
->ineq
[k
][1 + j
]);
826 isl_basic_set_free(cone
);
829 return isl_basic_set_finalize(shift
);
831 isl_basic_set_free(shift
);
832 isl_basic_set_free(cone
);
837 /* Given a rational point vec in a (transformed) basic set,
838 * such that cone is the recession cone of the original basic set,
839 * "round up" the rational point to an integer point.
841 * We first check if the rational point just happens to be integer.
842 * If not, we transform the cone in the same way as the basic set,
843 * pick a point x in this cone shifted to the rational point such that
844 * the whole unit cube at x is also inside this affine cone.
845 * Then we simply round up the coordinates of x and return the
846 * resulting integer point.
848 static struct isl_vec
*round_up_in_cone(struct isl_vec
*vec
,
849 struct isl_basic_set
*cone
, struct isl_mat
*U
)
853 if (!vec
|| !cone
|| !U
)
856 isl_assert(vec
->ctx
, vec
->size
!= 0, goto error
);
857 if (isl_int_is_one(vec
->el
[0])) {
859 isl_basic_set_free(cone
);
863 total
= isl_basic_set_total_dim(cone
);
864 cone
= isl_basic_set_preimage(cone
, U
);
865 cone
= isl_basic_set_remove_dims(cone
, isl_dim_set
,
866 0, total
- (vec
->size
- 1));
868 cone
= shift_cone(cone
, vec
);
870 vec
= rational_sample(cone
);
871 vec
= isl_vec_ceil(vec
);
876 isl_basic_set_free(cone
);
880 /* Concatenate two integer vectors, i.e., two vectors with denominator
881 * (stored in element 0) equal to 1.
883 static struct isl_vec
*vec_concat(struct isl_vec
*vec1
, struct isl_vec
*vec2
)
889 isl_assert(vec1
->ctx
, vec1
->size
> 0, goto error
);
890 isl_assert(vec2
->ctx
, vec2
->size
> 0, goto error
);
891 isl_assert(vec1
->ctx
, isl_int_is_one(vec1
->el
[0]), goto error
);
892 isl_assert(vec2
->ctx
, isl_int_is_one(vec2
->el
[0]), goto error
);
894 vec
= isl_vec_alloc(vec1
->ctx
, vec1
->size
+ vec2
->size
- 1);
898 isl_seq_cpy(vec
->el
, vec1
->el
, vec1
->size
);
899 isl_seq_cpy(vec
->el
+ vec1
->size
, vec2
->el
+ 1, vec2
->size
- 1);
911 /* Give a basic set "bset" with recession cone "cone", compute and
912 * return an integer point in bset, if any.
914 * If the recession cone is full-dimensional, then we know that
915 * bset contains an infinite number of integer points and it is
916 * fairly easy to pick one of them.
917 * If the recession cone is not full-dimensional, then we first
918 * transform bset such that the bounded directions appear as
919 * the first dimensions of the transformed basic set.
920 * We do this by using a unimodular transformation that transforms
921 * the equalities in the recession cone to equalities on the first
924 * The transformed set is then projected onto its bounded dimensions.
925 * Note that to compute this projection, we can simply drop all constraints
926 * involving any of the unbounded dimensions since these constraints
927 * cannot be combined to produce a constraint on the bounded dimensions.
928 * To see this, assume that there is such a combination of constraints
929 * that produces a constraint on the bounded dimensions. This means
930 * that some combination of the unbounded dimensions has both an upper
931 * bound and a lower bound in terms of the bounded dimensions, but then
932 * this combination would be a bounded direction too and would have been
933 * transformed into a bounded dimensions.
935 * We then compute a sample value in the bounded dimensions.
936 * If no such value can be found, then the original set did not contain
937 * any integer points and we are done.
938 * Otherwise, we plug in the value we found in the bounded dimensions,
939 * project out these bounded dimensions and end up with a set with
940 * a full-dimensional recession cone.
941 * A sample point in this set is computed by "rounding up" any
942 * rational point in the set.
944 * The sample points in the bounded and unbounded dimensions are
945 * then combined into a single sample point and transformed back
946 * to the original space.
948 __isl_give isl_vec
*isl_basic_set_sample_with_cone(
949 __isl_take isl_basic_set
*bset
, __isl_take isl_basic_set
*cone
)
953 struct isl_mat
*M
, *U
;
954 struct isl_vec
*sample
;
955 struct isl_vec
*cone_sample
;
957 struct isl_basic_set
*bounded
;
963 total
= isl_basic_set_total_dim(cone
);
964 cone_dim
= total
- cone
->n_eq
;
966 M
= isl_mat_sub_alloc6(bset
->ctx
, cone
->eq
, 0, cone
->n_eq
, 1, total
);
967 M
= isl_mat_left_hermite(M
, 0, &U
, NULL
);
972 U
= isl_mat_lin_to_aff(U
);
973 bset
= isl_basic_set_preimage(bset
, isl_mat_copy(U
));
975 bounded
= isl_basic_set_copy(bset
);
976 bounded
= isl_basic_set_drop_constraints_involving(bounded
,
977 total
- cone_dim
, cone_dim
);
978 bounded
= isl_basic_set_drop_dims(bounded
, total
- cone_dim
, cone_dim
);
979 sample
= sample_bounded(bounded
);
980 if (!sample
|| sample
->size
== 0) {
981 isl_basic_set_free(bset
);
982 isl_basic_set_free(cone
);
986 bset
= plug_in(bset
, isl_vec_copy(sample
));
987 cone_sample
= rational_sample(bset
);
988 cone_sample
= round_up_in_cone(cone_sample
, cone
, isl_mat_copy(U
));
989 sample
= vec_concat(sample
, cone_sample
);
990 sample
= isl_mat_vec_product(U
, sample
);
993 isl_basic_set_free(cone
);
994 isl_basic_set_free(bset
);
998 static void vec_sum_of_neg(struct isl_vec
*v
, isl_int
*s
)
1002 isl_int_set_si(*s
, 0);
1004 for (i
= 0; i
< v
->size
; ++i
)
1005 if (isl_int_is_neg(v
->el
[i
]))
1006 isl_int_add(*s
, *s
, v
->el
[i
]);
1009 /* Given a tableau "tab", a tableau "tab_cone" that corresponds
1010 * to the recession cone and the inverse of a new basis U = inv(B),
1011 * with the unbounded directions in B last,
1012 * add constraints to "tab" that ensure any rational value
1013 * in the unbounded directions can be rounded up to an integer value.
1015 * The new basis is given by x' = B x, i.e., x = U x'.
1016 * For any rational value of the last tab->n_unbounded coordinates
1017 * in the update tableau, the value that is obtained by rounding
1018 * up this value should be contained in the original tableau.
1019 * For any constraint "a x + c >= 0", we therefore need to add
1020 * a constraint "a x + c + s >= 0", with s the sum of all negative
1021 * entries in the last elements of "a U".
1023 * Since we are not interested in the first entries of any of the "a U",
1024 * we first drop the columns of U that correpond to bounded directions.
1026 static int tab_shift_cone(struct isl_tab
*tab
,
1027 struct isl_tab
*tab_cone
, struct isl_mat
*U
)
1031 struct isl_basic_set
*bset
= NULL
;
1033 if (tab
&& tab
->n_unbounded
== 0) {
1038 if (!tab
|| !tab_cone
|| !U
)
1040 bset
= isl_tab_peek_bset(tab_cone
);
1041 U
= isl_mat_drop_cols(U
, 0, tab
->n_var
- tab
->n_unbounded
);
1042 for (i
= 0; i
< bset
->n_ineq
; ++i
) {
1044 struct isl_vec
*row
= NULL
;
1045 if (isl_tab_is_equality(tab_cone
, tab_cone
->n_eq
+ i
))
1047 row
= isl_vec_alloc(bset
->ctx
, tab_cone
->n_var
);
1050 isl_seq_cpy(row
->el
, bset
->ineq
[i
] + 1, tab_cone
->n_var
);
1051 row
= isl_vec_mat_product(row
, isl_mat_copy(U
));
1054 vec_sum_of_neg(row
, &v
);
1056 if (isl_int_is_zero(v
))
1058 tab
= isl_tab_extend(tab
, 1);
1059 isl_int_add(bset
->ineq
[i
][0], bset
->ineq
[i
][0], v
);
1060 ok
= isl_tab_add_ineq(tab
, bset
->ineq
[i
]) >= 0;
1061 isl_int_sub(bset
->ineq
[i
][0], bset
->ineq
[i
][0], v
);
1075 /* Compute and return an initial basis for the possibly
1076 * unbounded tableau "tab". "tab_cone" is a tableau
1077 * for the corresponding recession cone.
1078 * Additionally, add constraints to "tab" that ensure
1079 * that any rational value for the unbounded directions
1080 * can be rounded up to an integer value.
1082 * If the tableau is bounded, i.e., if the recession cone
1083 * is zero-dimensional, then we just use inital_basis.
1084 * Otherwise, we construct a basis whose first directions
1085 * correspond to equalities, followed by bounded directions,
1086 * i.e., equalities in the recession cone.
1087 * The remaining directions are then unbounded.
1089 int isl_tab_set_initial_basis_with_cone(struct isl_tab
*tab
,
1090 struct isl_tab
*tab_cone
)
1093 struct isl_mat
*cone_eq
;
1094 struct isl_mat
*U
, *Q
;
1096 if (!tab
|| !tab_cone
)
1099 if (tab_cone
->n_col
== tab_cone
->n_dead
) {
1100 tab
->basis
= initial_basis(tab
);
1101 return tab
->basis
? 0 : -1;
1104 eq
= tab_equalities(tab
);
1107 tab
->n_zero
= eq
->n_row
;
1108 cone_eq
= tab_equalities(tab_cone
);
1109 eq
= isl_mat_concat(eq
, cone_eq
);
1112 tab
->n_unbounded
= tab
->n_var
- (eq
->n_row
- tab
->n_zero
);
1113 eq
= isl_mat_left_hermite(eq
, 0, &U
, &Q
);
1117 tab
->basis
= isl_mat_lin_to_aff(Q
);
1118 if (tab_shift_cone(tab
, tab_cone
, U
) < 0)
1125 /* Compute and return a sample point in bset using generalized basis
1126 * reduction. We first check if the input set has a non-trivial
1127 * recession cone. If so, we perform some extra preprocessing in
1128 * sample_with_cone. Otherwise, we directly perform generalized basis
1131 static struct isl_vec
*gbr_sample(struct isl_basic_set
*bset
)
1134 struct isl_basic_set
*cone
;
1136 dim
= isl_basic_set_total_dim(bset
);
1138 cone
= isl_basic_set_recession_cone(isl_basic_set_copy(bset
));
1142 if (cone
->n_eq
< dim
)
1143 return isl_basic_set_sample_with_cone(bset
, cone
);
1145 isl_basic_set_free(cone
);
1146 return sample_bounded(bset
);
1148 isl_basic_set_free(bset
);
1152 static struct isl_vec
*pip_sample(struct isl_basic_set
*bset
)
1155 struct isl_ctx
*ctx
;
1156 struct isl_vec
*sample
;
1158 bset
= isl_basic_set_skew_to_positive_orthant(bset
, &T
);
1163 sample
= isl_pip_basic_set_sample(bset
);
1165 if (sample
&& sample
->size
!= 0)
1166 sample
= isl_mat_vec_product(T
, sample
);
1173 static struct isl_vec
*basic_set_sample(struct isl_basic_set
*bset
, int bounded
)
1175 struct isl_ctx
*ctx
;
1181 if (isl_basic_set_plain_is_empty(bset
))
1182 return empty_sample(bset
);
1184 dim
= isl_basic_set_n_dim(bset
);
1185 isl_assert(ctx
, isl_basic_set_n_param(bset
) == 0, goto error
);
1186 isl_assert(ctx
, bset
->n_div
== 0, goto error
);
1188 if (bset
->sample
&& bset
->sample
->size
== 1 + dim
) {
1189 int contains
= isl_basic_set_contains(bset
, bset
->sample
);
1193 struct isl_vec
*sample
= isl_vec_copy(bset
->sample
);
1194 isl_basic_set_free(bset
);
1198 isl_vec_free(bset
->sample
);
1199 bset
->sample
= NULL
;
1202 return sample_eq(bset
, bounded
? isl_basic_set_sample_bounded
1203 : isl_basic_set_sample_vec
);
1205 return zero_sample(bset
);
1207 return interval_sample(bset
);
1209 switch (bset
->ctx
->opt
->ilp_solver
) {
1211 return pip_sample(bset
);
1213 return bounded
? sample_bounded(bset
) : gbr_sample(bset
);
1215 isl_assert(bset
->ctx
, 0, );
1217 isl_basic_set_free(bset
);
1221 __isl_give isl_vec
*isl_basic_set_sample_vec(__isl_take isl_basic_set
*bset
)
1223 return basic_set_sample(bset
, 0);
1226 /* Compute an integer sample in "bset", where the caller guarantees
1227 * that "bset" is bounded.
1229 struct isl_vec
*isl_basic_set_sample_bounded(struct isl_basic_set
*bset
)
1231 return basic_set_sample(bset
, 1);
1234 __isl_give isl_basic_set
*isl_basic_set_from_vec(__isl_take isl_vec
*vec
)
1238 struct isl_basic_set
*bset
= NULL
;
1239 struct isl_ctx
*ctx
;
1245 isl_assert(ctx
, vec
->size
!= 0, goto error
);
1247 bset
= isl_basic_set_alloc(ctx
, 0, vec
->size
- 1, 0, vec
->size
- 1, 0);
1250 dim
= isl_basic_set_n_dim(bset
);
1251 for (i
= dim
- 1; i
>= 0; --i
) {
1252 k
= isl_basic_set_alloc_equality(bset
);
1255 isl_seq_clr(bset
->eq
[k
], 1 + dim
);
1256 isl_int_neg(bset
->eq
[k
][0], vec
->el
[1 + i
]);
1257 isl_int_set(bset
->eq
[k
][1 + i
], vec
->el
[0]);
1263 isl_basic_set_free(bset
);
1268 __isl_give isl_basic_map
*isl_basic_map_sample(__isl_take isl_basic_map
*bmap
)
1270 struct isl_basic_set
*bset
;
1271 struct isl_vec
*sample_vec
;
1273 bset
= isl_basic_map_underlying_set(isl_basic_map_copy(bmap
));
1274 sample_vec
= isl_basic_set_sample_vec(bset
);
1277 if (sample_vec
->size
== 0) {
1278 struct isl_basic_map
*sample
;
1279 sample
= isl_basic_map_empty_like(bmap
);
1280 isl_vec_free(sample_vec
);
1281 isl_basic_map_free(bmap
);
1284 bset
= isl_basic_set_from_vec(sample_vec
);
1285 return isl_basic_map_overlying_set(bset
, bmap
);
1287 isl_basic_map_free(bmap
);
1291 __isl_give isl_basic_map
*isl_map_sample(__isl_take isl_map
*map
)
1294 isl_basic_map
*sample
= NULL
;
1299 for (i
= 0; i
< map
->n
; ++i
) {
1300 sample
= isl_basic_map_sample(isl_basic_map_copy(map
->p
[i
]));
1303 if (!ISL_F_ISSET(sample
, ISL_BASIC_MAP_EMPTY
))
1305 isl_basic_map_free(sample
);
1308 sample
= isl_basic_map_empty_like_map(map
);
1316 __isl_give isl_basic_set
*isl_set_sample(__isl_take isl_set
*set
)
1318 return (isl_basic_set
*) isl_map_sample((isl_map
*)set
);
1321 __isl_give isl_point
*isl_basic_set_sample_point(__isl_take isl_basic_set
*bset
)
1326 dim
= isl_basic_set_get_dim(bset
);
1327 bset
= isl_basic_set_underlying_set(bset
);
1328 vec
= isl_basic_set_sample_vec(bset
);
1330 return isl_point_alloc(dim
, vec
);
1333 __isl_give isl_point
*isl_set_sample_point(__isl_take isl_set
*set
)
1341 for (i
= 0; i
< set
->n
; ++i
) {
1342 pnt
= isl_basic_set_sample_point(isl_basic_set_copy(set
->p
[i
]));
1345 if (!isl_point_is_void(pnt
))
1347 isl_point_free(pnt
);
1350 pnt
= isl_point_void(isl_set_get_dim(set
));