update for change in arguments of clang's HeaderSearchOptions::AddPath
[isl.git] / isl_tab_pip.c
blobd5ed6548e9deed050deb9e484ee6de30588074f1
1 /*
2 * Copyright 2008-2009 Katholieke Universiteit Leuven
3 * Copyright 2010 INRIA Saclay
5 * Use of this software is governed by the MIT license
7 * Written by Sven Verdoolaege, K.U.Leuven, Departement
8 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
9 * and INRIA Saclay - Ile-de-France, Parc Club Orsay Universite,
10 * ZAC des vignes, 4 rue Jacques Monod, 91893 Orsay, France
13 #include <isl_ctx_private.h>
14 #include "isl_map_private.h"
15 #include <isl/seq.h>
16 #include "isl_tab.h"
17 #include "isl_sample.h"
18 #include <isl_mat_private.h>
19 #include <isl_aff_private.h>
20 #include <isl_options_private.h>
21 #include <isl_config.h>
24 * The implementation of parametric integer linear programming in this file
25 * was inspired by the paper "Parametric Integer Programming" and the
26 * report "Solving systems of affine (in)equalities" by Paul Feautrier
27 * (and others).
29 * The strategy used for obtaining a feasible solution is different
30 * from the one used in isl_tab.c. In particular, in isl_tab.c,
31 * upon finding a constraint that is not yet satisfied, we pivot
32 * in a row that increases the constant term of the row holding the
33 * constraint, making sure the sample solution remains feasible
34 * for all the constraints it already satisfied.
35 * Here, we always pivot in the row holding the constraint,
36 * choosing a column that induces the lexicographically smallest
37 * increment to the sample solution.
39 * By starting out from a sample value that is lexicographically
40 * smaller than any integer point in the problem space, the first
41 * feasible integer sample point we find will also be the lexicographically
42 * smallest. If all variables can be assumed to be non-negative,
43 * then the initial sample value may be chosen equal to zero.
44 * However, we will not make this assumption. Instead, we apply
45 * the "big parameter" trick. Any variable x is then not directly
46 * used in the tableau, but instead it is represented by another
47 * variable x' = M + x, where M is an arbitrarily large (positive)
48 * value. x' is therefore always non-negative, whatever the value of x.
49 * Taking as initial sample value x' = 0 corresponds to x = -M,
50 * which is always smaller than any possible value of x.
52 * The big parameter trick is used in the main tableau and
53 * also in the context tableau if isl_context_lex is used.
54 * In this case, each tableaus has its own big parameter.
55 * Before doing any real work, we check if all the parameters
56 * happen to be non-negative. If so, we drop the column corresponding
57 * to M from the initial context tableau.
58 * If isl_context_gbr is used, then the big parameter trick is only
59 * used in the main tableau.
62 struct isl_context;
63 struct isl_context_op {
64 /* detect nonnegative parameters in context and mark them in tab */
65 struct isl_tab *(*detect_nonnegative_parameters)(
66 struct isl_context *context, struct isl_tab *tab);
67 /* return temporary reference to basic set representation of context */
68 struct isl_basic_set *(*peek_basic_set)(struct isl_context *context);
69 /* return temporary reference to tableau representation of context */
70 struct isl_tab *(*peek_tab)(struct isl_context *context);
71 /* add equality; check is 1 if eq may not be valid;
72 * update is 1 if we may want to call ineq_sign on context later.
74 void (*add_eq)(struct isl_context *context, isl_int *eq,
75 int check, int update);
76 /* add inequality; check is 1 if ineq may not be valid;
77 * update is 1 if we may want to call ineq_sign on context later.
79 void (*add_ineq)(struct isl_context *context, isl_int *ineq,
80 int check, int update);
81 /* check sign of ineq based on previous information.
82 * strict is 1 if saturation should be treated as a positive sign.
84 enum isl_tab_row_sign (*ineq_sign)(struct isl_context *context,
85 isl_int *ineq, int strict);
86 /* check if inequality maintains feasibility */
87 int (*test_ineq)(struct isl_context *context, isl_int *ineq);
88 /* return index of a div that corresponds to "div" */
89 int (*get_div)(struct isl_context *context, struct isl_tab *tab,
90 struct isl_vec *div);
91 /* add div "div" to context and return non-negativity */
92 int (*add_div)(struct isl_context *context, struct isl_vec *div);
93 int (*detect_equalities)(struct isl_context *context,
94 struct isl_tab *tab);
95 /* return row index of "best" split */
96 int (*best_split)(struct isl_context *context, struct isl_tab *tab);
97 /* check if context has already been determined to be empty */
98 int (*is_empty)(struct isl_context *context);
99 /* check if context is still usable */
100 int (*is_ok)(struct isl_context *context);
101 /* save a copy/snapshot of context */
102 void *(*save)(struct isl_context *context);
103 /* restore saved context */
104 void (*restore)(struct isl_context *context, void *);
105 /* discard saved context */
106 void (*discard)(void *);
107 /* invalidate context */
108 void (*invalidate)(struct isl_context *context);
109 /* free context */
110 void (*free)(struct isl_context *context);
113 struct isl_context {
114 struct isl_context_op *op;
117 struct isl_context_lex {
118 struct isl_context context;
119 struct isl_tab *tab;
122 /* A stack (linked list) of solutions of subtrees of the search space.
124 * "M" describes the solution in terms of the dimensions of "dom".
125 * The number of columns of "M" is one more than the total number
126 * of dimensions of "dom".
128 struct isl_partial_sol {
129 int level;
130 struct isl_basic_set *dom;
131 struct isl_mat *M;
133 struct isl_partial_sol *next;
136 struct isl_sol;
137 struct isl_sol_callback {
138 struct isl_tab_callback callback;
139 struct isl_sol *sol;
142 /* isl_sol is an interface for constructing a solution to
143 * a parametric integer linear programming problem.
144 * Every time the algorithm reaches a state where a solution
145 * can be read off from the tableau (including cases where the tableau
146 * is empty), the function "add" is called on the isl_sol passed
147 * to find_solutions_main.
149 * The context tableau is owned by isl_sol and is updated incrementally.
151 * There are currently two implementations of this interface,
152 * isl_sol_map, which simply collects the solutions in an isl_map
153 * and (optionally) the parts of the context where there is no solution
154 * in an isl_set, and
155 * isl_sol_for, which calls a user-defined function for each part of
156 * the solution.
158 struct isl_sol {
159 int error;
160 int rational;
161 int level;
162 int max;
163 int n_out;
164 struct isl_context *context;
165 struct isl_partial_sol *partial;
166 void (*add)(struct isl_sol *sol,
167 struct isl_basic_set *dom, struct isl_mat *M);
168 void (*add_empty)(struct isl_sol *sol, struct isl_basic_set *bset);
169 void (*free)(struct isl_sol *sol);
170 struct isl_sol_callback dec_level;
173 static void sol_free(struct isl_sol *sol)
175 struct isl_partial_sol *partial, *next;
176 if (!sol)
177 return;
178 for (partial = sol->partial; partial; partial = next) {
179 next = partial->next;
180 isl_basic_set_free(partial->dom);
181 isl_mat_free(partial->M);
182 free(partial);
184 sol->free(sol);
187 /* Push a partial solution represented by a domain and mapping M
188 * onto the stack of partial solutions.
190 static void sol_push_sol(struct isl_sol *sol,
191 struct isl_basic_set *dom, struct isl_mat *M)
193 struct isl_partial_sol *partial;
195 if (sol->error || !dom)
196 goto error;
198 partial = isl_alloc_type(dom->ctx, struct isl_partial_sol);
199 if (!partial)
200 goto error;
202 partial->level = sol->level;
203 partial->dom = dom;
204 partial->M = M;
205 partial->next = sol->partial;
207 sol->partial = partial;
209 return;
210 error:
211 isl_basic_set_free(dom);
212 isl_mat_free(M);
213 sol->error = 1;
216 /* Pop one partial solution from the partial solution stack and
217 * pass it on to sol->add or sol->add_empty.
219 static void sol_pop_one(struct isl_sol *sol)
221 struct isl_partial_sol *partial;
223 partial = sol->partial;
224 sol->partial = partial->next;
226 if (partial->M)
227 sol->add(sol, partial->dom, partial->M);
228 else
229 sol->add_empty(sol, partial->dom);
230 free(partial);
233 /* Return a fresh copy of the domain represented by the context tableau.
235 static struct isl_basic_set *sol_domain(struct isl_sol *sol)
237 struct isl_basic_set *bset;
239 if (sol->error)
240 return NULL;
242 bset = isl_basic_set_dup(sol->context->op->peek_basic_set(sol->context));
243 bset = isl_basic_set_update_from_tab(bset,
244 sol->context->op->peek_tab(sol->context));
246 return bset;
249 /* Check whether two partial solutions have the same mapping, where n_div
250 * is the number of divs that the two partial solutions have in common.
252 static int same_solution(struct isl_partial_sol *s1, struct isl_partial_sol *s2,
253 unsigned n_div)
255 int i;
256 unsigned dim;
258 if (!s1->M != !s2->M)
259 return 0;
260 if (!s1->M)
261 return 1;
263 dim = isl_basic_set_total_dim(s1->dom) - s1->dom->n_div;
265 for (i = 0; i < s1->M->n_row; ++i) {
266 if (isl_seq_first_non_zero(s1->M->row[i]+1+dim+n_div,
267 s1->M->n_col-1-dim-n_div) != -1)
268 return 0;
269 if (isl_seq_first_non_zero(s2->M->row[i]+1+dim+n_div,
270 s2->M->n_col-1-dim-n_div) != -1)
271 return 0;
272 if (!isl_seq_eq(s1->M->row[i], s2->M->row[i], 1+dim+n_div))
273 return 0;
275 return 1;
278 /* Pop all solutions from the partial solution stack that were pushed onto
279 * the stack at levels that are deeper than the current level.
280 * If the two topmost elements on the stack have the same level
281 * and represent the same solution, then their domains are combined.
282 * This combined domain is the same as the current context domain
283 * as sol_pop is called each time we move back to a higher level.
285 static void sol_pop(struct isl_sol *sol)
287 struct isl_partial_sol *partial;
288 unsigned n_div;
290 if (sol->error)
291 return;
293 if (sol->level == 0) {
294 for (partial = sol->partial; partial; partial = sol->partial)
295 sol_pop_one(sol);
296 return;
299 partial = sol->partial;
300 if (!partial)
301 return;
303 if (partial->level <= sol->level)
304 return;
306 if (partial->next && partial->next->level == partial->level) {
307 n_div = isl_basic_set_dim(
308 sol->context->op->peek_basic_set(sol->context),
309 isl_dim_div);
311 if (!same_solution(partial, partial->next, n_div)) {
312 sol_pop_one(sol);
313 sol_pop_one(sol);
314 } else {
315 struct isl_basic_set *bset;
316 isl_mat *M;
317 unsigned n;
319 n = isl_basic_set_dim(partial->next->dom, isl_dim_div);
320 n -= n_div;
321 bset = sol_domain(sol);
322 isl_basic_set_free(partial->next->dom);
323 partial->next->dom = bset;
324 M = partial->next->M;
325 M = isl_mat_drop_cols(M, M->n_col - n, n);
326 partial->next->M = M;
327 partial->next->level = sol->level;
329 if (!bset || !M)
330 goto error;
332 sol->partial = partial->next;
333 isl_basic_set_free(partial->dom);
334 isl_mat_free(partial->M);
335 free(partial);
337 } else
338 sol_pop_one(sol);
340 if (0)
341 error: sol->error = 1;
344 static void sol_dec_level(struct isl_sol *sol)
346 if (sol->error)
347 return;
349 sol->level--;
351 sol_pop(sol);
354 static int sol_dec_level_wrap(struct isl_tab_callback *cb)
356 struct isl_sol_callback *callback = (struct isl_sol_callback *)cb;
358 sol_dec_level(callback->sol);
360 return callback->sol->error ? -1 : 0;
363 /* Move down to next level and push callback onto context tableau
364 * to decrease the level again when it gets rolled back across
365 * the current state. That is, dec_level will be called with
366 * the context tableau in the same state as it is when inc_level
367 * is called.
369 static void sol_inc_level(struct isl_sol *sol)
371 struct isl_tab *tab;
373 if (sol->error)
374 return;
376 sol->level++;
377 tab = sol->context->op->peek_tab(sol->context);
378 if (isl_tab_push_callback(tab, &sol->dec_level.callback) < 0)
379 sol->error = 1;
382 static void scale_rows(struct isl_mat *mat, isl_int m, int n_row)
384 int i;
386 if (isl_int_is_one(m))
387 return;
389 for (i = 0; i < n_row; ++i)
390 isl_seq_scale(mat->row[i], mat->row[i], m, mat->n_col);
393 /* Add the solution identified by the tableau and the context tableau.
395 * The layout of the variables is as follows.
396 * tab->n_var is equal to the total number of variables in the input
397 * map (including divs that were copied from the context)
398 * + the number of extra divs constructed
399 * Of these, the first tab->n_param and the last tab->n_div variables
400 * correspond to the variables in the context, i.e.,
401 * tab->n_param + tab->n_div = context_tab->n_var
402 * tab->n_param is equal to the number of parameters and input
403 * dimensions in the input map
404 * tab->n_div is equal to the number of divs in the context
406 * If there is no solution, then call add_empty with a basic set
407 * that corresponds to the context tableau. (If add_empty is NULL,
408 * then do nothing).
410 * If there is a solution, then first construct a matrix that maps
411 * all dimensions of the context to the output variables, i.e.,
412 * the output dimensions in the input map.
413 * The divs in the input map (if any) that do not correspond to any
414 * div in the context do not appear in the solution.
415 * The algorithm will make sure that they have an integer value,
416 * but these values themselves are of no interest.
417 * We have to be careful not to drop or rearrange any divs in the
418 * context because that would change the meaning of the matrix.
420 * To extract the value of the output variables, it should be noted
421 * that we always use a big parameter M in the main tableau and so
422 * the variable stored in this tableau is not an output variable x itself, but
423 * x' = M + x (in case of minimization)
424 * or
425 * x' = M - x (in case of maximization)
426 * If x' appears in a column, then its optimal value is zero,
427 * which means that the optimal value of x is an unbounded number
428 * (-M for minimization and M for maximization).
429 * We currently assume that the output dimensions in the original map
430 * are bounded, so this cannot occur.
431 * Similarly, when x' appears in a row, then the coefficient of M in that
432 * row is necessarily 1.
433 * If the row in the tableau represents
434 * d x' = c + d M + e(y)
435 * then, in case of minimization, the corresponding row in the matrix
436 * will be
437 * a c + a e(y)
438 * with a d = m, the (updated) common denominator of the matrix.
439 * In case of maximization, the row will be
440 * -a c - a e(y)
442 static void sol_add(struct isl_sol *sol, struct isl_tab *tab)
444 struct isl_basic_set *bset = NULL;
445 struct isl_mat *mat = NULL;
446 unsigned off;
447 int row;
448 isl_int m;
450 if (sol->error || !tab)
451 goto error;
453 if (tab->empty && !sol->add_empty)
454 return;
455 if (sol->context->op->is_empty(sol->context))
456 return;
458 bset = sol_domain(sol);
460 if (tab->empty) {
461 sol_push_sol(sol, bset, NULL);
462 return;
465 off = 2 + tab->M;
467 mat = isl_mat_alloc(tab->mat->ctx, 1 + sol->n_out,
468 1 + tab->n_param + tab->n_div);
469 if (!mat)
470 goto error;
472 isl_int_init(m);
474 isl_seq_clr(mat->row[0] + 1, mat->n_col - 1);
475 isl_int_set_si(mat->row[0][0], 1);
476 for (row = 0; row < sol->n_out; ++row) {
477 int i = tab->n_param + row;
478 int r, j;
480 isl_seq_clr(mat->row[1 + row], mat->n_col);
481 if (!tab->var[i].is_row) {
482 if (tab->M)
483 isl_die(mat->ctx, isl_error_invalid,
484 "unbounded optimum", goto error2);
485 continue;
488 r = tab->var[i].index;
489 if (tab->M &&
490 isl_int_ne(tab->mat->row[r][2], tab->mat->row[r][0]))
491 isl_die(mat->ctx, isl_error_invalid,
492 "unbounded optimum", goto error2);
493 isl_int_gcd(m, mat->row[0][0], tab->mat->row[r][0]);
494 isl_int_divexact(m, tab->mat->row[r][0], m);
495 scale_rows(mat, m, 1 + row);
496 isl_int_divexact(m, mat->row[0][0], tab->mat->row[r][0]);
497 isl_int_mul(mat->row[1 + row][0], m, tab->mat->row[r][1]);
498 for (j = 0; j < tab->n_param; ++j) {
499 int col;
500 if (tab->var[j].is_row)
501 continue;
502 col = tab->var[j].index;
503 isl_int_mul(mat->row[1 + row][1 + j], m,
504 tab->mat->row[r][off + col]);
506 for (j = 0; j < tab->n_div; ++j) {
507 int col;
508 if (tab->var[tab->n_var - tab->n_div+j].is_row)
509 continue;
510 col = tab->var[tab->n_var - tab->n_div+j].index;
511 isl_int_mul(mat->row[1 + row][1 + tab->n_param + j], m,
512 tab->mat->row[r][off + col]);
514 if (sol->max)
515 isl_seq_neg(mat->row[1 + row], mat->row[1 + row],
516 mat->n_col);
519 isl_int_clear(m);
521 sol_push_sol(sol, bset, mat);
522 return;
523 error2:
524 isl_int_clear(m);
525 error:
526 isl_basic_set_free(bset);
527 isl_mat_free(mat);
528 sol->error = 1;
531 struct isl_sol_map {
532 struct isl_sol sol;
533 struct isl_map *map;
534 struct isl_set *empty;
537 static void sol_map_free(struct isl_sol_map *sol_map)
539 if (!sol_map)
540 return;
541 if (sol_map->sol.context)
542 sol_map->sol.context->op->free(sol_map->sol.context);
543 isl_map_free(sol_map->map);
544 isl_set_free(sol_map->empty);
545 free(sol_map);
548 static void sol_map_free_wrap(struct isl_sol *sol)
550 sol_map_free((struct isl_sol_map *)sol);
553 /* This function is called for parts of the context where there is
554 * no solution, with "bset" corresponding to the context tableau.
555 * Simply add the basic set to the set "empty".
557 static void sol_map_add_empty(struct isl_sol_map *sol,
558 struct isl_basic_set *bset)
560 if (!bset)
561 goto error;
562 isl_assert(bset->ctx, sol->empty, goto error);
564 sol->empty = isl_set_grow(sol->empty, 1);
565 bset = isl_basic_set_simplify(bset);
566 bset = isl_basic_set_finalize(bset);
567 sol->empty = isl_set_add_basic_set(sol->empty, isl_basic_set_copy(bset));
568 if (!sol->empty)
569 goto error;
570 isl_basic_set_free(bset);
571 return;
572 error:
573 isl_basic_set_free(bset);
574 sol->sol.error = 1;
577 static void sol_map_add_empty_wrap(struct isl_sol *sol,
578 struct isl_basic_set *bset)
580 sol_map_add_empty((struct isl_sol_map *)sol, bset);
583 /* Given a basic map "dom" that represents the context and an affine
584 * matrix "M" that maps the dimensions of the context to the
585 * output variables, construct a basic map with the same parameters
586 * and divs as the context, the dimensions of the context as input
587 * dimensions and a number of output dimensions that is equal to
588 * the number of output dimensions in the input map.
590 * The constraints and divs of the context are simply copied
591 * from "dom". For each row
592 * x = c + e(y)
593 * an equality
594 * c + e(y) - d x = 0
595 * is added, with d the common denominator of M.
597 static void sol_map_add(struct isl_sol_map *sol,
598 struct isl_basic_set *dom, struct isl_mat *M)
600 int i;
601 struct isl_basic_map *bmap = NULL;
602 unsigned n_eq;
603 unsigned n_ineq;
604 unsigned nparam;
605 unsigned total;
606 unsigned n_div;
607 unsigned n_out;
609 if (sol->sol.error || !dom || !M)
610 goto error;
612 n_out = sol->sol.n_out;
613 n_eq = dom->n_eq + n_out;
614 n_ineq = dom->n_ineq;
615 n_div = dom->n_div;
616 nparam = isl_basic_set_total_dim(dom) - n_div;
617 total = isl_map_dim(sol->map, isl_dim_all);
618 bmap = isl_basic_map_alloc_space(isl_map_get_space(sol->map),
619 n_div, n_eq, 2 * n_div + n_ineq);
620 if (!bmap)
621 goto error;
622 if (sol->sol.rational)
623 ISL_F_SET(bmap, ISL_BASIC_MAP_RATIONAL);
624 for (i = 0; i < dom->n_div; ++i) {
625 int k = isl_basic_map_alloc_div(bmap);
626 if (k < 0)
627 goto error;
628 isl_seq_cpy(bmap->div[k], dom->div[i], 1 + 1 + nparam);
629 isl_seq_clr(bmap->div[k] + 1 + 1 + nparam, total - nparam);
630 isl_seq_cpy(bmap->div[k] + 1 + 1 + total,
631 dom->div[i] + 1 + 1 + nparam, i);
633 for (i = 0; i < dom->n_eq; ++i) {
634 int k = isl_basic_map_alloc_equality(bmap);
635 if (k < 0)
636 goto error;
637 isl_seq_cpy(bmap->eq[k], dom->eq[i], 1 + nparam);
638 isl_seq_clr(bmap->eq[k] + 1 + nparam, total - nparam);
639 isl_seq_cpy(bmap->eq[k] + 1 + total,
640 dom->eq[i] + 1 + nparam, n_div);
642 for (i = 0; i < dom->n_ineq; ++i) {
643 int k = isl_basic_map_alloc_inequality(bmap);
644 if (k < 0)
645 goto error;
646 isl_seq_cpy(bmap->ineq[k], dom->ineq[i], 1 + nparam);
647 isl_seq_clr(bmap->ineq[k] + 1 + nparam, total - nparam);
648 isl_seq_cpy(bmap->ineq[k] + 1 + total,
649 dom->ineq[i] + 1 + nparam, n_div);
651 for (i = 0; i < M->n_row - 1; ++i) {
652 int k = isl_basic_map_alloc_equality(bmap);
653 if (k < 0)
654 goto error;
655 isl_seq_cpy(bmap->eq[k], M->row[1 + i], 1 + nparam);
656 isl_seq_clr(bmap->eq[k] + 1 + nparam, n_out);
657 isl_int_neg(bmap->eq[k][1 + nparam + i], M->row[0][0]);
658 isl_seq_cpy(bmap->eq[k] + 1 + nparam + n_out,
659 M->row[1 + i] + 1 + nparam, n_div);
661 bmap = isl_basic_map_simplify(bmap);
662 bmap = isl_basic_map_finalize(bmap);
663 sol->map = isl_map_grow(sol->map, 1);
664 sol->map = isl_map_add_basic_map(sol->map, bmap);
665 isl_basic_set_free(dom);
666 isl_mat_free(M);
667 if (!sol->map)
668 sol->sol.error = 1;
669 return;
670 error:
671 isl_basic_set_free(dom);
672 isl_mat_free(M);
673 isl_basic_map_free(bmap);
674 sol->sol.error = 1;
677 static void sol_map_add_wrap(struct isl_sol *sol,
678 struct isl_basic_set *dom, struct isl_mat *M)
680 sol_map_add((struct isl_sol_map *)sol, dom, M);
684 /* Store the "parametric constant" of row "row" of tableau "tab" in "line",
685 * i.e., the constant term and the coefficients of all variables that
686 * appear in the context tableau.
687 * Note that the coefficient of the big parameter M is NOT copied.
688 * The context tableau may not have a big parameter and even when it
689 * does, it is a different big parameter.
691 static void get_row_parameter_line(struct isl_tab *tab, int row, isl_int *line)
693 int i;
694 unsigned off = 2 + tab->M;
696 isl_int_set(line[0], tab->mat->row[row][1]);
697 for (i = 0; i < tab->n_param; ++i) {
698 if (tab->var[i].is_row)
699 isl_int_set_si(line[1 + i], 0);
700 else {
701 int col = tab->var[i].index;
702 isl_int_set(line[1 + i], tab->mat->row[row][off + col]);
705 for (i = 0; i < tab->n_div; ++i) {
706 if (tab->var[tab->n_var - tab->n_div + i].is_row)
707 isl_int_set_si(line[1 + tab->n_param + i], 0);
708 else {
709 int col = tab->var[tab->n_var - tab->n_div + i].index;
710 isl_int_set(line[1 + tab->n_param + i],
711 tab->mat->row[row][off + col]);
716 /* Check if rows "row1" and "row2" have identical "parametric constants",
717 * as explained above.
718 * In this case, we also insist that the coefficients of the big parameter
719 * be the same as the values of the constants will only be the same
720 * if these coefficients are also the same.
722 static int identical_parameter_line(struct isl_tab *tab, int row1, int row2)
724 int i;
725 unsigned off = 2 + tab->M;
727 if (isl_int_ne(tab->mat->row[row1][1], tab->mat->row[row2][1]))
728 return 0;
730 if (tab->M && isl_int_ne(tab->mat->row[row1][2],
731 tab->mat->row[row2][2]))
732 return 0;
734 for (i = 0; i < tab->n_param + tab->n_div; ++i) {
735 int pos = i < tab->n_param ? i :
736 tab->n_var - tab->n_div + i - tab->n_param;
737 int col;
739 if (tab->var[pos].is_row)
740 continue;
741 col = tab->var[pos].index;
742 if (isl_int_ne(tab->mat->row[row1][off + col],
743 tab->mat->row[row2][off + col]))
744 return 0;
746 return 1;
749 /* Return an inequality that expresses that the "parametric constant"
750 * should be non-negative.
751 * This function is only called when the coefficient of the big parameter
752 * is equal to zero.
754 static struct isl_vec *get_row_parameter_ineq(struct isl_tab *tab, int row)
756 struct isl_vec *ineq;
758 ineq = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_param + tab->n_div);
759 if (!ineq)
760 return NULL;
762 get_row_parameter_line(tab, row, ineq->el);
763 if (ineq)
764 ineq = isl_vec_normalize(ineq);
766 return ineq;
769 /* Normalize a div expression of the form
771 * [(g*f(x) + c)/(g * m)]
773 * with c the constant term and f(x) the remaining coefficients, to
775 * [(f(x) + [c/g])/m]
777 static void normalize_div(__isl_keep isl_vec *div)
779 isl_ctx *ctx = isl_vec_get_ctx(div);
780 int len = div->size - 2;
782 isl_seq_gcd(div->el + 2, len, &ctx->normalize_gcd);
783 isl_int_gcd(ctx->normalize_gcd, ctx->normalize_gcd, div->el[0]);
785 if (isl_int_is_one(ctx->normalize_gcd))
786 return;
788 isl_int_divexact(div->el[0], div->el[0], ctx->normalize_gcd);
789 isl_int_fdiv_q(div->el[1], div->el[1], ctx->normalize_gcd);
790 isl_seq_scale_down(div->el + 2, div->el + 2, ctx->normalize_gcd, len);
793 /* Return a integer division for use in a parametric cut based on the given row.
794 * In particular, let the parametric constant of the row be
796 * \sum_i a_i y_i
798 * where y_0 = 1, but none of the y_i corresponds to the big parameter M.
799 * The div returned is equal to
801 * floor(\sum_i {-a_i} y_i) = floor((\sum_i (-a_i mod d) y_i)/d)
803 static struct isl_vec *get_row_parameter_div(struct isl_tab *tab, int row)
805 struct isl_vec *div;
807 div = isl_vec_alloc(tab->mat->ctx, 1 + 1 + tab->n_param + tab->n_div);
808 if (!div)
809 return NULL;
811 isl_int_set(div->el[0], tab->mat->row[row][0]);
812 get_row_parameter_line(tab, row, div->el + 1);
813 isl_seq_neg(div->el + 1, div->el + 1, div->size - 1);
814 normalize_div(div);
815 isl_seq_fdiv_r(div->el + 1, div->el + 1, div->el[0], div->size - 1);
817 return div;
820 /* Return a integer division for use in transferring an integrality constraint
821 * to the context.
822 * In particular, let the parametric constant of the row be
824 * \sum_i a_i y_i
826 * where y_0 = 1, but none of the y_i corresponds to the big parameter M.
827 * The the returned div is equal to
829 * floor(\sum_i {a_i} y_i) = floor((\sum_i (a_i mod d) y_i)/d)
831 static struct isl_vec *get_row_split_div(struct isl_tab *tab, int row)
833 struct isl_vec *div;
835 div = isl_vec_alloc(tab->mat->ctx, 1 + 1 + tab->n_param + tab->n_div);
836 if (!div)
837 return NULL;
839 isl_int_set(div->el[0], tab->mat->row[row][0]);
840 get_row_parameter_line(tab, row, div->el + 1);
841 normalize_div(div);
842 isl_seq_fdiv_r(div->el + 1, div->el + 1, div->el[0], div->size - 1);
844 return div;
847 /* Construct and return an inequality that expresses an upper bound
848 * on the given div.
849 * In particular, if the div is given by
851 * d = floor(e/m)
853 * then the inequality expresses
855 * m d <= e
857 static struct isl_vec *ineq_for_div(struct isl_basic_set *bset, unsigned div)
859 unsigned total;
860 unsigned div_pos;
861 struct isl_vec *ineq;
863 if (!bset)
864 return NULL;
866 total = isl_basic_set_total_dim(bset);
867 div_pos = 1 + total - bset->n_div + div;
869 ineq = isl_vec_alloc(bset->ctx, 1 + total);
870 if (!ineq)
871 return NULL;
873 isl_seq_cpy(ineq->el, bset->div[div] + 1, 1 + total);
874 isl_int_neg(ineq->el[div_pos], bset->div[div][0]);
875 return ineq;
878 /* Given a row in the tableau and a div that was created
879 * using get_row_split_div and that has been constrained to equality, i.e.,
881 * d = floor(\sum_i {a_i} y_i) = \sum_i {a_i} y_i
883 * replace the expression "\sum_i {a_i} y_i" in the row by d,
884 * i.e., we subtract "\sum_i {a_i} y_i" and add 1 d.
885 * The coefficients of the non-parameters in the tableau have been
886 * verified to be integral. We can therefore simply replace coefficient b
887 * by floor(b). For the coefficients of the parameters we have
888 * floor(a_i) = a_i - {a_i}, while for the other coefficients, we have
889 * floor(b) = b.
891 static struct isl_tab *set_row_cst_to_div(struct isl_tab *tab, int row, int div)
893 isl_seq_fdiv_q(tab->mat->row[row] + 1, tab->mat->row[row] + 1,
894 tab->mat->row[row][0], 1 + tab->M + tab->n_col);
896 isl_int_set_si(tab->mat->row[row][0], 1);
898 if (tab->var[tab->n_var - tab->n_div + div].is_row) {
899 int drow = tab->var[tab->n_var - tab->n_div + div].index;
901 isl_assert(tab->mat->ctx,
902 isl_int_is_one(tab->mat->row[drow][0]), goto error);
903 isl_seq_combine(tab->mat->row[row] + 1,
904 tab->mat->ctx->one, tab->mat->row[row] + 1,
905 tab->mat->ctx->one, tab->mat->row[drow] + 1,
906 1 + tab->M + tab->n_col);
907 } else {
908 int dcol = tab->var[tab->n_var - tab->n_div + div].index;
910 isl_int_add_ui(tab->mat->row[row][2 + tab->M + dcol],
911 tab->mat->row[row][2 + tab->M + dcol], 1);
914 return tab;
915 error:
916 isl_tab_free(tab);
917 return NULL;
920 /* Check if the (parametric) constant of the given row is obviously
921 * negative, meaning that we don't need to consult the context tableau.
922 * If there is a big parameter and its coefficient is non-zero,
923 * then this coefficient determines the outcome.
924 * Otherwise, we check whether the constant is negative and
925 * all non-zero coefficients of parameters are negative and
926 * belong to non-negative parameters.
928 static int is_obviously_neg(struct isl_tab *tab, int row)
930 int i;
931 int col;
932 unsigned off = 2 + tab->M;
934 if (tab->M) {
935 if (isl_int_is_pos(tab->mat->row[row][2]))
936 return 0;
937 if (isl_int_is_neg(tab->mat->row[row][2]))
938 return 1;
941 if (isl_int_is_nonneg(tab->mat->row[row][1]))
942 return 0;
943 for (i = 0; i < tab->n_param; ++i) {
944 /* Eliminated parameter */
945 if (tab->var[i].is_row)
946 continue;
947 col = tab->var[i].index;
948 if (isl_int_is_zero(tab->mat->row[row][off + col]))
949 continue;
950 if (!tab->var[i].is_nonneg)
951 return 0;
952 if (isl_int_is_pos(tab->mat->row[row][off + col]))
953 return 0;
955 for (i = 0; i < tab->n_div; ++i) {
956 if (tab->var[tab->n_var - tab->n_div + i].is_row)
957 continue;
958 col = tab->var[tab->n_var - tab->n_div + i].index;
959 if (isl_int_is_zero(tab->mat->row[row][off + col]))
960 continue;
961 if (!tab->var[tab->n_var - tab->n_div + i].is_nonneg)
962 return 0;
963 if (isl_int_is_pos(tab->mat->row[row][off + col]))
964 return 0;
966 return 1;
969 /* Check if the (parametric) constant of the given row is obviously
970 * non-negative, meaning that we don't need to consult the context tableau.
971 * If there is a big parameter and its coefficient is non-zero,
972 * then this coefficient determines the outcome.
973 * Otherwise, we check whether the constant is non-negative and
974 * all non-zero coefficients of parameters are positive and
975 * belong to non-negative parameters.
977 static int is_obviously_nonneg(struct isl_tab *tab, int row)
979 int i;
980 int col;
981 unsigned off = 2 + tab->M;
983 if (tab->M) {
984 if (isl_int_is_pos(tab->mat->row[row][2]))
985 return 1;
986 if (isl_int_is_neg(tab->mat->row[row][2]))
987 return 0;
990 if (isl_int_is_neg(tab->mat->row[row][1]))
991 return 0;
992 for (i = 0; i < tab->n_param; ++i) {
993 /* Eliminated parameter */
994 if (tab->var[i].is_row)
995 continue;
996 col = tab->var[i].index;
997 if (isl_int_is_zero(tab->mat->row[row][off + col]))
998 continue;
999 if (!tab->var[i].is_nonneg)
1000 return 0;
1001 if (isl_int_is_neg(tab->mat->row[row][off + col]))
1002 return 0;
1004 for (i = 0; i < tab->n_div; ++i) {
1005 if (tab->var[tab->n_var - tab->n_div + i].is_row)
1006 continue;
1007 col = tab->var[tab->n_var - tab->n_div + i].index;
1008 if (isl_int_is_zero(tab->mat->row[row][off + col]))
1009 continue;
1010 if (!tab->var[tab->n_var - tab->n_div + i].is_nonneg)
1011 return 0;
1012 if (isl_int_is_neg(tab->mat->row[row][off + col]))
1013 return 0;
1015 return 1;
1018 /* Given a row r and two columns, return the column that would
1019 * lead to the lexicographically smallest increment in the sample
1020 * solution when leaving the basis in favor of the row.
1021 * Pivoting with column c will increment the sample value by a non-negative
1022 * constant times a_{V,c}/a_{r,c}, with a_{V,c} the elements of column c
1023 * corresponding to the non-parametric variables.
1024 * If variable v appears in a column c_v, the a_{v,c} = 1 iff c = c_v,
1025 * with all other entries in this virtual row equal to zero.
1026 * If variable v appears in a row, then a_{v,c} is the element in column c
1027 * of that row.
1029 * Let v be the first variable with a_{v,c1}/a_{r,c1} != a_{v,c2}/a_{r,c2}.
1030 * Then if a_{v,c1}/a_{r,c1} < a_{v,c2}/a_{r,c2}, i.e.,
1031 * a_{v,c2} a_{r,c1} - a_{v,c1} a_{r,c2} > 0, c1 results in the minimal
1032 * increment. Otherwise, it's c2.
1034 static int lexmin_col_pair(struct isl_tab *tab,
1035 int row, int col1, int col2, isl_int tmp)
1037 int i;
1038 isl_int *tr;
1040 tr = tab->mat->row[row] + 2 + tab->M;
1042 for (i = tab->n_param; i < tab->n_var - tab->n_div; ++i) {
1043 int s1, s2;
1044 isl_int *r;
1046 if (!tab->var[i].is_row) {
1047 if (tab->var[i].index == col1)
1048 return col2;
1049 if (tab->var[i].index == col2)
1050 return col1;
1051 continue;
1054 if (tab->var[i].index == row)
1055 continue;
1057 r = tab->mat->row[tab->var[i].index] + 2 + tab->M;
1058 s1 = isl_int_sgn(r[col1]);
1059 s2 = isl_int_sgn(r[col2]);
1060 if (s1 == 0 && s2 == 0)
1061 continue;
1062 if (s1 < s2)
1063 return col1;
1064 if (s2 < s1)
1065 return col2;
1067 isl_int_mul(tmp, r[col2], tr[col1]);
1068 isl_int_submul(tmp, r[col1], tr[col2]);
1069 if (isl_int_is_pos(tmp))
1070 return col1;
1071 if (isl_int_is_neg(tmp))
1072 return col2;
1074 return -1;
1077 /* Given a row in the tableau, find and return the column that would
1078 * result in the lexicographically smallest, but positive, increment
1079 * in the sample point.
1080 * If there is no such column, then return tab->n_col.
1081 * If anything goes wrong, return -1.
1083 static int lexmin_pivot_col(struct isl_tab *tab, int row)
1085 int j;
1086 int col = tab->n_col;
1087 isl_int *tr;
1088 isl_int tmp;
1090 tr = tab->mat->row[row] + 2 + tab->M;
1092 isl_int_init(tmp);
1094 for (j = tab->n_dead; j < tab->n_col; ++j) {
1095 if (tab->col_var[j] >= 0 &&
1096 (tab->col_var[j] < tab->n_param ||
1097 tab->col_var[j] >= tab->n_var - tab->n_div))
1098 continue;
1100 if (!isl_int_is_pos(tr[j]))
1101 continue;
1103 if (col == tab->n_col)
1104 col = j;
1105 else
1106 col = lexmin_col_pair(tab, row, col, j, tmp);
1107 isl_assert(tab->mat->ctx, col >= 0, goto error);
1110 isl_int_clear(tmp);
1111 return col;
1112 error:
1113 isl_int_clear(tmp);
1114 return -1;
1117 /* Return the first known violated constraint, i.e., a non-negative
1118 * constraint that currently has an either obviously negative value
1119 * or a previously determined to be negative value.
1121 * If any constraint has a negative coefficient for the big parameter,
1122 * if any, then we return one of these first.
1124 static int first_neg(struct isl_tab *tab)
1126 int row;
1128 if (tab->M)
1129 for (row = tab->n_redundant; row < tab->n_row; ++row) {
1130 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
1131 continue;
1132 if (!isl_int_is_neg(tab->mat->row[row][2]))
1133 continue;
1134 if (tab->row_sign)
1135 tab->row_sign[row] = isl_tab_row_neg;
1136 return row;
1138 for (row = tab->n_redundant; row < tab->n_row; ++row) {
1139 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
1140 continue;
1141 if (tab->row_sign) {
1142 if (tab->row_sign[row] == 0 &&
1143 is_obviously_neg(tab, row))
1144 tab->row_sign[row] = isl_tab_row_neg;
1145 if (tab->row_sign[row] != isl_tab_row_neg)
1146 continue;
1147 } else if (!is_obviously_neg(tab, row))
1148 continue;
1149 return row;
1151 return -1;
1154 /* Check whether the invariant that all columns are lexico-positive
1155 * is satisfied. This function is not called from the current code
1156 * but is useful during debugging.
1158 static void check_lexpos(struct isl_tab *tab) __attribute__ ((unused));
1159 static void check_lexpos(struct isl_tab *tab)
1161 unsigned off = 2 + tab->M;
1162 int col;
1163 int var;
1164 int row;
1166 for (col = tab->n_dead; col < tab->n_col; ++col) {
1167 if (tab->col_var[col] >= 0 &&
1168 (tab->col_var[col] < tab->n_param ||
1169 tab->col_var[col] >= tab->n_var - tab->n_div))
1170 continue;
1171 for (var = tab->n_param; var < tab->n_var - tab->n_div; ++var) {
1172 if (!tab->var[var].is_row) {
1173 if (tab->var[var].index == col)
1174 break;
1175 else
1176 continue;
1178 row = tab->var[var].index;
1179 if (isl_int_is_zero(tab->mat->row[row][off + col]))
1180 continue;
1181 if (isl_int_is_pos(tab->mat->row[row][off + col]))
1182 break;
1183 fprintf(stderr, "lexneg column %d (row %d)\n",
1184 col, row);
1186 if (var >= tab->n_var - tab->n_div)
1187 fprintf(stderr, "zero column %d\n", col);
1191 /* Report to the caller that the given constraint is part of an encountered
1192 * conflict.
1194 static int report_conflicting_constraint(struct isl_tab *tab, int con)
1196 return tab->conflict(con, tab->conflict_user);
1199 /* Given a conflicting row in the tableau, report all constraints
1200 * involved in the row to the caller. That is, the row itself
1201 * (if it represents a constraint) and all constraint columns with
1202 * non-zero (and therefore negative) coefficients.
1204 static int report_conflict(struct isl_tab *tab, int row)
1206 int j;
1207 isl_int *tr;
1209 if (!tab->conflict)
1210 return 0;
1212 if (tab->row_var[row] < 0 &&
1213 report_conflicting_constraint(tab, ~tab->row_var[row]) < 0)
1214 return -1;
1216 tr = tab->mat->row[row] + 2 + tab->M;
1218 for (j = tab->n_dead; j < tab->n_col; ++j) {
1219 if (tab->col_var[j] >= 0 &&
1220 (tab->col_var[j] < tab->n_param ||
1221 tab->col_var[j] >= tab->n_var - tab->n_div))
1222 continue;
1224 if (!isl_int_is_neg(tr[j]))
1225 continue;
1227 if (tab->col_var[j] < 0 &&
1228 report_conflicting_constraint(tab, ~tab->col_var[j]) < 0)
1229 return -1;
1232 return 0;
1235 /* Resolve all known or obviously violated constraints through pivoting.
1236 * In particular, as long as we can find any violated constraint, we
1237 * look for a pivoting column that would result in the lexicographically
1238 * smallest increment in the sample point. If there is no such column
1239 * then the tableau is infeasible.
1241 static int restore_lexmin(struct isl_tab *tab) WARN_UNUSED;
1242 static int restore_lexmin(struct isl_tab *tab)
1244 int row, col;
1246 if (!tab)
1247 return -1;
1248 if (tab->empty)
1249 return 0;
1250 while ((row = first_neg(tab)) != -1) {
1251 col = lexmin_pivot_col(tab, row);
1252 if (col >= tab->n_col) {
1253 if (report_conflict(tab, row) < 0)
1254 return -1;
1255 if (isl_tab_mark_empty(tab) < 0)
1256 return -1;
1257 return 0;
1259 if (col < 0)
1260 return -1;
1261 if (isl_tab_pivot(tab, row, col) < 0)
1262 return -1;
1264 return 0;
1267 /* Given a row that represents an equality, look for an appropriate
1268 * pivoting column.
1269 * In particular, if there are any non-zero coefficients among
1270 * the non-parameter variables, then we take the last of these
1271 * variables. Eliminating this variable in terms of the other
1272 * variables and/or parameters does not influence the property
1273 * that all column in the initial tableau are lexicographically
1274 * positive. The row corresponding to the eliminated variable
1275 * will only have non-zero entries below the diagonal of the
1276 * initial tableau. That is, we transform
1278 * I I
1279 * 1 into a
1280 * I I
1282 * If there is no such non-parameter variable, then we are dealing with
1283 * pure parameter equality and we pick any parameter with coefficient 1 or -1
1284 * for elimination. This will ensure that the eliminated parameter
1285 * always has an integer value whenever all the other parameters are integral.
1286 * If there is no such parameter then we return -1.
1288 static int last_var_col_or_int_par_col(struct isl_tab *tab, int row)
1290 unsigned off = 2 + tab->M;
1291 int i;
1293 for (i = tab->n_var - tab->n_div - 1; i >= 0 && i >= tab->n_param; --i) {
1294 int col;
1295 if (tab->var[i].is_row)
1296 continue;
1297 col = tab->var[i].index;
1298 if (col <= tab->n_dead)
1299 continue;
1300 if (!isl_int_is_zero(tab->mat->row[row][off + col]))
1301 return col;
1303 for (i = tab->n_dead; i < tab->n_col; ++i) {
1304 if (isl_int_is_one(tab->mat->row[row][off + i]))
1305 return i;
1306 if (isl_int_is_negone(tab->mat->row[row][off + i]))
1307 return i;
1309 return -1;
1312 /* Add an equality that is known to be valid to the tableau.
1313 * We first check if we can eliminate a variable or a parameter.
1314 * If not, we add the equality as two inequalities.
1315 * In this case, the equality was a pure parameter equality and there
1316 * is no need to resolve any constraint violations.
1318 static struct isl_tab *add_lexmin_valid_eq(struct isl_tab *tab, isl_int *eq)
1320 int i;
1321 int r;
1323 if (!tab)
1324 return NULL;
1325 r = isl_tab_add_row(tab, eq);
1326 if (r < 0)
1327 goto error;
1329 r = tab->con[r].index;
1330 i = last_var_col_or_int_par_col(tab, r);
1331 if (i < 0) {
1332 tab->con[r].is_nonneg = 1;
1333 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
1334 goto error;
1335 isl_seq_neg(eq, eq, 1 + tab->n_var);
1336 r = isl_tab_add_row(tab, eq);
1337 if (r < 0)
1338 goto error;
1339 tab->con[r].is_nonneg = 1;
1340 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
1341 goto error;
1342 } else {
1343 if (isl_tab_pivot(tab, r, i) < 0)
1344 goto error;
1345 if (isl_tab_kill_col(tab, i) < 0)
1346 goto error;
1347 tab->n_eq++;
1350 return tab;
1351 error:
1352 isl_tab_free(tab);
1353 return NULL;
1356 /* Check if the given row is a pure constant.
1358 static int is_constant(struct isl_tab *tab, int row)
1360 unsigned off = 2 + tab->M;
1362 return isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
1363 tab->n_col - tab->n_dead) == -1;
1366 /* Add an equality that may or may not be valid to the tableau.
1367 * If the resulting row is a pure constant, then it must be zero.
1368 * Otherwise, the resulting tableau is empty.
1370 * If the row is not a pure constant, then we add two inequalities,
1371 * each time checking that they can be satisfied.
1372 * In the end we try to use one of the two constraints to eliminate
1373 * a column.
1375 static int add_lexmin_eq(struct isl_tab *tab, isl_int *eq) WARN_UNUSED;
1376 static int add_lexmin_eq(struct isl_tab *tab, isl_int *eq)
1378 int r1, r2;
1379 int row;
1380 struct isl_tab_undo *snap;
1382 if (!tab)
1383 return -1;
1384 snap = isl_tab_snap(tab);
1385 r1 = isl_tab_add_row(tab, eq);
1386 if (r1 < 0)
1387 return -1;
1388 tab->con[r1].is_nonneg = 1;
1389 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r1]) < 0)
1390 return -1;
1392 row = tab->con[r1].index;
1393 if (is_constant(tab, row)) {
1394 if (!isl_int_is_zero(tab->mat->row[row][1]) ||
1395 (tab->M && !isl_int_is_zero(tab->mat->row[row][2]))) {
1396 if (isl_tab_mark_empty(tab) < 0)
1397 return -1;
1398 return 0;
1400 if (isl_tab_rollback(tab, snap) < 0)
1401 return -1;
1402 return 0;
1405 if (restore_lexmin(tab) < 0)
1406 return -1;
1407 if (tab->empty)
1408 return 0;
1410 isl_seq_neg(eq, eq, 1 + tab->n_var);
1412 r2 = isl_tab_add_row(tab, eq);
1413 if (r2 < 0)
1414 return -1;
1415 tab->con[r2].is_nonneg = 1;
1416 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r2]) < 0)
1417 return -1;
1419 if (restore_lexmin(tab) < 0)
1420 return -1;
1421 if (tab->empty)
1422 return 0;
1424 if (!tab->con[r1].is_row) {
1425 if (isl_tab_kill_col(tab, tab->con[r1].index) < 0)
1426 return -1;
1427 } else if (!tab->con[r2].is_row) {
1428 if (isl_tab_kill_col(tab, tab->con[r2].index) < 0)
1429 return -1;
1432 if (tab->bmap) {
1433 tab->bmap = isl_basic_map_add_ineq(tab->bmap, eq);
1434 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1435 return -1;
1436 isl_seq_neg(eq, eq, 1 + tab->n_var);
1437 tab->bmap = isl_basic_map_add_ineq(tab->bmap, eq);
1438 isl_seq_neg(eq, eq, 1 + tab->n_var);
1439 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1440 return -1;
1441 if (!tab->bmap)
1442 return -1;
1445 return 0;
1448 /* Add an inequality to the tableau, resolving violations using
1449 * restore_lexmin.
1451 static struct isl_tab *add_lexmin_ineq(struct isl_tab *tab, isl_int *ineq)
1453 int r;
1455 if (!tab)
1456 return NULL;
1457 if (tab->bmap) {
1458 tab->bmap = isl_basic_map_add_ineq(tab->bmap, ineq);
1459 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1460 goto error;
1461 if (!tab->bmap)
1462 goto error;
1464 r = isl_tab_add_row(tab, ineq);
1465 if (r < 0)
1466 goto error;
1467 tab->con[r].is_nonneg = 1;
1468 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
1469 goto error;
1470 if (isl_tab_row_is_redundant(tab, tab->con[r].index)) {
1471 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1472 goto error;
1473 return tab;
1476 if (restore_lexmin(tab) < 0)
1477 goto error;
1478 if (!tab->empty && tab->con[r].is_row &&
1479 isl_tab_row_is_redundant(tab, tab->con[r].index))
1480 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1481 goto error;
1482 return tab;
1483 error:
1484 isl_tab_free(tab);
1485 return NULL;
1488 /* Check if the coefficients of the parameters are all integral.
1490 static int integer_parameter(struct isl_tab *tab, int row)
1492 int i;
1493 int col;
1494 unsigned off = 2 + tab->M;
1496 for (i = 0; i < tab->n_param; ++i) {
1497 /* Eliminated parameter */
1498 if (tab->var[i].is_row)
1499 continue;
1500 col = tab->var[i].index;
1501 if (!isl_int_is_divisible_by(tab->mat->row[row][off + col],
1502 tab->mat->row[row][0]))
1503 return 0;
1505 for (i = 0; i < tab->n_div; ++i) {
1506 if (tab->var[tab->n_var - tab->n_div + i].is_row)
1507 continue;
1508 col = tab->var[tab->n_var - tab->n_div + i].index;
1509 if (!isl_int_is_divisible_by(tab->mat->row[row][off + col],
1510 tab->mat->row[row][0]))
1511 return 0;
1513 return 1;
1516 /* Check if the coefficients of the non-parameter variables are all integral.
1518 static int integer_variable(struct isl_tab *tab, int row)
1520 int i;
1521 unsigned off = 2 + tab->M;
1523 for (i = tab->n_dead; i < tab->n_col; ++i) {
1524 if (tab->col_var[i] >= 0 &&
1525 (tab->col_var[i] < tab->n_param ||
1526 tab->col_var[i] >= tab->n_var - tab->n_div))
1527 continue;
1528 if (!isl_int_is_divisible_by(tab->mat->row[row][off + i],
1529 tab->mat->row[row][0]))
1530 return 0;
1532 return 1;
1535 /* Check if the constant term is integral.
1537 static int integer_constant(struct isl_tab *tab, int row)
1539 return isl_int_is_divisible_by(tab->mat->row[row][1],
1540 tab->mat->row[row][0]);
1543 #define I_CST 1 << 0
1544 #define I_PAR 1 << 1
1545 #define I_VAR 1 << 2
1547 /* Check for next (non-parameter) variable after "var" (first if var == -1)
1548 * that is non-integer and therefore requires a cut and return
1549 * the index of the variable.
1550 * For parametric tableaus, there are three parts in a row,
1551 * the constant, the coefficients of the parameters and the rest.
1552 * For each part, we check whether the coefficients in that part
1553 * are all integral and if so, set the corresponding flag in *f.
1554 * If the constant and the parameter part are integral, then the
1555 * current sample value is integral and no cut is required
1556 * (irrespective of whether the variable part is integral).
1558 static int next_non_integer_var(struct isl_tab *tab, int var, int *f)
1560 var = var < 0 ? tab->n_param : var + 1;
1562 for (; var < tab->n_var - tab->n_div; ++var) {
1563 int flags = 0;
1564 int row;
1565 if (!tab->var[var].is_row)
1566 continue;
1567 row = tab->var[var].index;
1568 if (integer_constant(tab, row))
1569 ISL_FL_SET(flags, I_CST);
1570 if (integer_parameter(tab, row))
1571 ISL_FL_SET(flags, I_PAR);
1572 if (ISL_FL_ISSET(flags, I_CST) && ISL_FL_ISSET(flags, I_PAR))
1573 continue;
1574 if (integer_variable(tab, row))
1575 ISL_FL_SET(flags, I_VAR);
1576 *f = flags;
1577 return var;
1579 return -1;
1582 /* Check for first (non-parameter) variable that is non-integer and
1583 * therefore requires a cut and return the corresponding row.
1584 * For parametric tableaus, there are three parts in a row,
1585 * the constant, the coefficients of the parameters and the rest.
1586 * For each part, we check whether the coefficients in that part
1587 * are all integral and if so, set the corresponding flag in *f.
1588 * If the constant and the parameter part are integral, then the
1589 * current sample value is integral and no cut is required
1590 * (irrespective of whether the variable part is integral).
1592 static int first_non_integer_row(struct isl_tab *tab, int *f)
1594 int var = next_non_integer_var(tab, -1, f);
1596 return var < 0 ? -1 : tab->var[var].index;
1599 /* Add a (non-parametric) cut to cut away the non-integral sample
1600 * value of the given row.
1602 * If the row is given by
1604 * m r = f + \sum_i a_i y_i
1606 * then the cut is
1608 * c = - {-f/m} + \sum_i {a_i/m} y_i >= 0
1610 * The big parameter, if any, is ignored, since it is assumed to be big
1611 * enough to be divisible by any integer.
1612 * If the tableau is actually a parametric tableau, then this function
1613 * is only called when all coefficients of the parameters are integral.
1614 * The cut therefore has zero coefficients for the parameters.
1616 * The current value is known to be negative, so row_sign, if it
1617 * exists, is set accordingly.
1619 * Return the row of the cut or -1.
1621 static int add_cut(struct isl_tab *tab, int row)
1623 int i;
1624 int r;
1625 isl_int *r_row;
1626 unsigned off = 2 + tab->M;
1628 if (isl_tab_extend_cons(tab, 1) < 0)
1629 return -1;
1630 r = isl_tab_allocate_con(tab);
1631 if (r < 0)
1632 return -1;
1634 r_row = tab->mat->row[tab->con[r].index];
1635 isl_int_set(r_row[0], tab->mat->row[row][0]);
1636 isl_int_neg(r_row[1], tab->mat->row[row][1]);
1637 isl_int_fdiv_r(r_row[1], r_row[1], tab->mat->row[row][0]);
1638 isl_int_neg(r_row[1], r_row[1]);
1639 if (tab->M)
1640 isl_int_set_si(r_row[2], 0);
1641 for (i = 0; i < tab->n_col; ++i)
1642 isl_int_fdiv_r(r_row[off + i],
1643 tab->mat->row[row][off + i], tab->mat->row[row][0]);
1645 tab->con[r].is_nonneg = 1;
1646 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
1647 return -1;
1648 if (tab->row_sign)
1649 tab->row_sign[tab->con[r].index] = isl_tab_row_neg;
1651 return tab->con[r].index;
1654 #define CUT_ALL 1
1655 #define CUT_ONE 0
1657 /* Given a non-parametric tableau, add cuts until an integer
1658 * sample point is obtained or until the tableau is determined
1659 * to be integer infeasible.
1660 * As long as there is any non-integer value in the sample point,
1661 * we add appropriate cuts, if possible, for each of these
1662 * non-integer values and then resolve the violated
1663 * cut constraints using restore_lexmin.
1664 * If one of the corresponding rows is equal to an integral
1665 * combination of variables/constraints plus a non-integral constant,
1666 * then there is no way to obtain an integer point and we return
1667 * a tableau that is marked empty.
1668 * The parameter cutting_strategy controls the strategy used when adding cuts
1669 * to remove non-integer points. CUT_ALL adds all possible cuts
1670 * before continuing the search. CUT_ONE adds only one cut at a time.
1672 static struct isl_tab *cut_to_integer_lexmin(struct isl_tab *tab,
1673 int cutting_strategy)
1675 int var;
1676 int row;
1677 int flags;
1679 if (!tab)
1680 return NULL;
1681 if (tab->empty)
1682 return tab;
1684 while ((var = next_non_integer_var(tab, -1, &flags)) != -1) {
1685 do {
1686 if (ISL_FL_ISSET(flags, I_VAR)) {
1687 if (isl_tab_mark_empty(tab) < 0)
1688 goto error;
1689 return tab;
1691 row = tab->var[var].index;
1692 row = add_cut(tab, row);
1693 if (row < 0)
1694 goto error;
1695 if (cutting_strategy == CUT_ONE)
1696 break;
1697 } while ((var = next_non_integer_var(tab, var, &flags)) != -1);
1698 if (restore_lexmin(tab) < 0)
1699 goto error;
1700 if (tab->empty)
1701 break;
1703 return tab;
1704 error:
1705 isl_tab_free(tab);
1706 return NULL;
1709 /* Check whether all the currently active samples also satisfy the inequality
1710 * "ineq" (treated as an equality if eq is set).
1711 * Remove those samples that do not.
1713 static struct isl_tab *check_samples(struct isl_tab *tab, isl_int *ineq, int eq)
1715 int i;
1716 isl_int v;
1718 if (!tab)
1719 return NULL;
1721 isl_assert(tab->mat->ctx, tab->bmap, goto error);
1722 isl_assert(tab->mat->ctx, tab->samples, goto error);
1723 isl_assert(tab->mat->ctx, tab->samples->n_col == 1 + tab->n_var, goto error);
1725 isl_int_init(v);
1726 for (i = tab->n_outside; i < tab->n_sample; ++i) {
1727 int sgn;
1728 isl_seq_inner_product(ineq, tab->samples->row[i],
1729 1 + tab->n_var, &v);
1730 sgn = isl_int_sgn(v);
1731 if (eq ? (sgn == 0) : (sgn >= 0))
1732 continue;
1733 tab = isl_tab_drop_sample(tab, i);
1734 if (!tab)
1735 break;
1737 isl_int_clear(v);
1739 return tab;
1740 error:
1741 isl_tab_free(tab);
1742 return NULL;
1745 /* Check whether the sample value of the tableau is finite,
1746 * i.e., either the tableau does not use a big parameter, or
1747 * all values of the variables are equal to the big parameter plus
1748 * some constant. This constant is the actual sample value.
1750 static int sample_is_finite(struct isl_tab *tab)
1752 int i;
1754 if (!tab->M)
1755 return 1;
1757 for (i = 0; i < tab->n_var; ++i) {
1758 int row;
1759 if (!tab->var[i].is_row)
1760 return 0;
1761 row = tab->var[i].index;
1762 if (isl_int_ne(tab->mat->row[row][0], tab->mat->row[row][2]))
1763 return 0;
1765 return 1;
1768 /* Check if the context tableau of sol has any integer points.
1769 * Leave tab in empty state if no integer point can be found.
1770 * If an integer point can be found and if moreover it is finite,
1771 * then it is added to the list of sample values.
1773 * This function is only called when none of the currently active sample
1774 * values satisfies the most recently added constraint.
1776 static struct isl_tab *check_integer_feasible(struct isl_tab *tab)
1778 struct isl_tab_undo *snap;
1780 if (!tab)
1781 return NULL;
1783 snap = isl_tab_snap(tab);
1784 if (isl_tab_push_basis(tab) < 0)
1785 goto error;
1787 tab = cut_to_integer_lexmin(tab, CUT_ALL);
1788 if (!tab)
1789 goto error;
1791 if (!tab->empty && sample_is_finite(tab)) {
1792 struct isl_vec *sample;
1794 sample = isl_tab_get_sample_value(tab);
1796 tab = isl_tab_add_sample(tab, sample);
1799 if (!tab->empty && isl_tab_rollback(tab, snap) < 0)
1800 goto error;
1802 return tab;
1803 error:
1804 isl_tab_free(tab);
1805 return NULL;
1808 /* Check if any of the currently active sample values satisfies
1809 * the inequality "ineq" (an equality if eq is set).
1811 static int tab_has_valid_sample(struct isl_tab *tab, isl_int *ineq, int eq)
1813 int i;
1814 isl_int v;
1816 if (!tab)
1817 return -1;
1819 isl_assert(tab->mat->ctx, tab->bmap, return -1);
1820 isl_assert(tab->mat->ctx, tab->samples, return -1);
1821 isl_assert(tab->mat->ctx, tab->samples->n_col == 1 + tab->n_var, return -1);
1823 isl_int_init(v);
1824 for (i = tab->n_outside; i < tab->n_sample; ++i) {
1825 int sgn;
1826 isl_seq_inner_product(ineq, tab->samples->row[i],
1827 1 + tab->n_var, &v);
1828 sgn = isl_int_sgn(v);
1829 if (eq ? (sgn == 0) : (sgn >= 0))
1830 break;
1832 isl_int_clear(v);
1834 return i < tab->n_sample;
1837 /* Add a div specified by "div" to the tableau "tab" and return
1838 * 1 if the div is obviously non-negative.
1840 static int context_tab_add_div(struct isl_tab *tab, struct isl_vec *div,
1841 int (*add_ineq)(void *user, isl_int *), void *user)
1843 int i;
1844 int r;
1845 struct isl_mat *samples;
1846 int nonneg;
1848 r = isl_tab_add_div(tab, div, add_ineq, user);
1849 if (r < 0)
1850 return -1;
1851 nonneg = tab->var[r].is_nonneg;
1852 tab->var[r].frozen = 1;
1854 samples = isl_mat_extend(tab->samples,
1855 tab->n_sample, 1 + tab->n_var);
1856 tab->samples = samples;
1857 if (!samples)
1858 return -1;
1859 for (i = tab->n_outside; i < samples->n_row; ++i) {
1860 isl_seq_inner_product(div->el + 1, samples->row[i],
1861 div->size - 1, &samples->row[i][samples->n_col - 1]);
1862 isl_int_fdiv_q(samples->row[i][samples->n_col - 1],
1863 samples->row[i][samples->n_col - 1], div->el[0]);
1866 return nonneg;
1869 /* Add a div specified by "div" to both the main tableau and
1870 * the context tableau. In case of the main tableau, we only
1871 * need to add an extra div. In the context tableau, we also
1872 * need to express the meaning of the div.
1873 * Return the index of the div or -1 if anything went wrong.
1875 static int add_div(struct isl_tab *tab, struct isl_context *context,
1876 struct isl_vec *div)
1878 int r;
1879 int nonneg;
1881 if ((nonneg = context->op->add_div(context, div)) < 0)
1882 goto error;
1884 if (!context->op->is_ok(context))
1885 goto error;
1887 if (isl_tab_extend_vars(tab, 1) < 0)
1888 goto error;
1889 r = isl_tab_allocate_var(tab);
1890 if (r < 0)
1891 goto error;
1892 if (nonneg)
1893 tab->var[r].is_nonneg = 1;
1894 tab->var[r].frozen = 1;
1895 tab->n_div++;
1897 return tab->n_div - 1;
1898 error:
1899 context->op->invalidate(context);
1900 return -1;
1903 static int find_div(struct isl_tab *tab, isl_int *div, isl_int denom)
1905 int i;
1906 unsigned total = isl_basic_map_total_dim(tab->bmap);
1908 for (i = 0; i < tab->bmap->n_div; ++i) {
1909 if (isl_int_ne(tab->bmap->div[i][0], denom))
1910 continue;
1911 if (!isl_seq_eq(tab->bmap->div[i] + 1, div, 1 + total))
1912 continue;
1913 return i;
1915 return -1;
1918 /* Return the index of a div that corresponds to "div".
1919 * We first check if we already have such a div and if not, we create one.
1921 static int get_div(struct isl_tab *tab, struct isl_context *context,
1922 struct isl_vec *div)
1924 int d;
1925 struct isl_tab *context_tab = context->op->peek_tab(context);
1927 if (!context_tab)
1928 return -1;
1930 d = find_div(context_tab, div->el + 1, div->el[0]);
1931 if (d != -1)
1932 return d;
1934 return add_div(tab, context, div);
1937 /* Add a parametric cut to cut away the non-integral sample value
1938 * of the give row.
1939 * Let a_i be the coefficients of the constant term and the parameters
1940 * and let b_i be the coefficients of the variables or constraints
1941 * in basis of the tableau.
1942 * Let q be the div q = floor(\sum_i {-a_i} y_i).
1944 * The cut is expressed as
1946 * c = \sum_i -{-a_i} y_i + \sum_i {b_i} x_i + q >= 0
1948 * If q did not already exist in the context tableau, then it is added first.
1949 * If q is in a column of the main tableau then the "+ q" can be accomplished
1950 * by setting the corresponding entry to the denominator of the constraint.
1951 * If q happens to be in a row of the main tableau, then the corresponding
1952 * row needs to be added instead (taking care of the denominators).
1953 * Note that this is very unlikely, but perhaps not entirely impossible.
1955 * The current value of the cut is known to be negative (or at least
1956 * non-positive), so row_sign is set accordingly.
1958 * Return the row of the cut or -1.
1960 static int add_parametric_cut(struct isl_tab *tab, int row,
1961 struct isl_context *context)
1963 struct isl_vec *div;
1964 int d;
1965 int i;
1966 int r;
1967 isl_int *r_row;
1968 int col;
1969 int n;
1970 unsigned off = 2 + tab->M;
1972 if (!context)
1973 return -1;
1975 div = get_row_parameter_div(tab, row);
1976 if (!div)
1977 return -1;
1979 n = tab->n_div;
1980 d = context->op->get_div(context, tab, div);
1981 isl_vec_free(div);
1982 if (d < 0)
1983 return -1;
1985 if (isl_tab_extend_cons(tab, 1) < 0)
1986 return -1;
1987 r = isl_tab_allocate_con(tab);
1988 if (r < 0)
1989 return -1;
1991 r_row = tab->mat->row[tab->con[r].index];
1992 isl_int_set(r_row[0], tab->mat->row[row][0]);
1993 isl_int_neg(r_row[1], tab->mat->row[row][1]);
1994 isl_int_fdiv_r(r_row[1], r_row[1], tab->mat->row[row][0]);
1995 isl_int_neg(r_row[1], r_row[1]);
1996 if (tab->M)
1997 isl_int_set_si(r_row[2], 0);
1998 for (i = 0; i < tab->n_param; ++i) {
1999 if (tab->var[i].is_row)
2000 continue;
2001 col = tab->var[i].index;
2002 isl_int_neg(r_row[off + col], tab->mat->row[row][off + col]);
2003 isl_int_fdiv_r(r_row[off + col], r_row[off + col],
2004 tab->mat->row[row][0]);
2005 isl_int_neg(r_row[off + col], r_row[off + col]);
2007 for (i = 0; i < tab->n_div; ++i) {
2008 if (tab->var[tab->n_var - tab->n_div + i].is_row)
2009 continue;
2010 col = tab->var[tab->n_var - tab->n_div + i].index;
2011 isl_int_neg(r_row[off + col], tab->mat->row[row][off + col]);
2012 isl_int_fdiv_r(r_row[off + col], r_row[off + col],
2013 tab->mat->row[row][0]);
2014 isl_int_neg(r_row[off + col], r_row[off + col]);
2016 for (i = 0; i < tab->n_col; ++i) {
2017 if (tab->col_var[i] >= 0 &&
2018 (tab->col_var[i] < tab->n_param ||
2019 tab->col_var[i] >= tab->n_var - tab->n_div))
2020 continue;
2021 isl_int_fdiv_r(r_row[off + i],
2022 tab->mat->row[row][off + i], tab->mat->row[row][0]);
2024 if (tab->var[tab->n_var - tab->n_div + d].is_row) {
2025 isl_int gcd;
2026 int d_row = tab->var[tab->n_var - tab->n_div + d].index;
2027 isl_int_init(gcd);
2028 isl_int_gcd(gcd, tab->mat->row[d_row][0], r_row[0]);
2029 isl_int_divexact(r_row[0], r_row[0], gcd);
2030 isl_int_divexact(gcd, tab->mat->row[d_row][0], gcd);
2031 isl_seq_combine(r_row + 1, gcd, r_row + 1,
2032 r_row[0], tab->mat->row[d_row] + 1,
2033 off - 1 + tab->n_col);
2034 isl_int_mul(r_row[0], r_row[0], tab->mat->row[d_row][0]);
2035 isl_int_clear(gcd);
2036 } else {
2037 col = tab->var[tab->n_var - tab->n_div + d].index;
2038 isl_int_set(r_row[off + col], tab->mat->row[row][0]);
2041 tab->con[r].is_nonneg = 1;
2042 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
2043 return -1;
2044 if (tab->row_sign)
2045 tab->row_sign[tab->con[r].index] = isl_tab_row_neg;
2047 row = tab->con[r].index;
2049 if (d >= n && context->op->detect_equalities(context, tab) < 0)
2050 return -1;
2052 return row;
2055 /* Construct a tableau for bmap that can be used for computing
2056 * the lexicographic minimum (or maximum) of bmap.
2057 * If not NULL, then dom is the domain where the minimum
2058 * should be computed. In this case, we set up a parametric
2059 * tableau with row signs (initialized to "unknown").
2060 * If M is set, then the tableau will use a big parameter.
2061 * If max is set, then a maximum should be computed instead of a minimum.
2062 * This means that for each variable x, the tableau will contain the variable
2063 * x' = M - x, rather than x' = M + x. This in turn means that the coefficient
2064 * of the variables in all constraints are negated prior to adding them
2065 * to the tableau.
2067 static struct isl_tab *tab_for_lexmin(struct isl_basic_map *bmap,
2068 struct isl_basic_set *dom, unsigned M, int max)
2070 int i;
2071 struct isl_tab *tab;
2073 tab = isl_tab_alloc(bmap->ctx, 2 * bmap->n_eq + bmap->n_ineq + 1,
2074 isl_basic_map_total_dim(bmap), M);
2075 if (!tab)
2076 return NULL;
2078 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
2079 if (dom) {
2080 tab->n_param = isl_basic_set_total_dim(dom) - dom->n_div;
2081 tab->n_div = dom->n_div;
2082 tab->row_sign = isl_calloc_array(bmap->ctx,
2083 enum isl_tab_row_sign, tab->mat->n_row);
2084 if (!tab->row_sign)
2085 goto error;
2087 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) {
2088 if (isl_tab_mark_empty(tab) < 0)
2089 goto error;
2090 return tab;
2093 for (i = tab->n_param; i < tab->n_var - tab->n_div; ++i) {
2094 tab->var[i].is_nonneg = 1;
2095 tab->var[i].frozen = 1;
2097 for (i = 0; i < bmap->n_eq; ++i) {
2098 if (max)
2099 isl_seq_neg(bmap->eq[i] + 1 + tab->n_param,
2100 bmap->eq[i] + 1 + tab->n_param,
2101 tab->n_var - tab->n_param - tab->n_div);
2102 tab = add_lexmin_valid_eq(tab, bmap->eq[i]);
2103 if (max)
2104 isl_seq_neg(bmap->eq[i] + 1 + tab->n_param,
2105 bmap->eq[i] + 1 + tab->n_param,
2106 tab->n_var - tab->n_param - tab->n_div);
2107 if (!tab || tab->empty)
2108 return tab;
2110 if (bmap->n_eq && restore_lexmin(tab) < 0)
2111 goto error;
2112 for (i = 0; i < bmap->n_ineq; ++i) {
2113 if (max)
2114 isl_seq_neg(bmap->ineq[i] + 1 + tab->n_param,
2115 bmap->ineq[i] + 1 + tab->n_param,
2116 tab->n_var - tab->n_param - tab->n_div);
2117 tab = add_lexmin_ineq(tab, bmap->ineq[i]);
2118 if (max)
2119 isl_seq_neg(bmap->ineq[i] + 1 + tab->n_param,
2120 bmap->ineq[i] + 1 + tab->n_param,
2121 tab->n_var - tab->n_param - tab->n_div);
2122 if (!tab || tab->empty)
2123 return tab;
2125 return tab;
2126 error:
2127 isl_tab_free(tab);
2128 return NULL;
2131 /* Given a main tableau where more than one row requires a split,
2132 * determine and return the "best" row to split on.
2134 * Given two rows in the main tableau, if the inequality corresponding
2135 * to the first row is redundant with respect to that of the second row
2136 * in the current tableau, then it is better to split on the second row,
2137 * since in the positive part, both row will be positive.
2138 * (In the negative part a pivot will have to be performed and just about
2139 * anything can happen to the sign of the other row.)
2141 * As a simple heuristic, we therefore select the row that makes the most
2142 * of the other rows redundant.
2144 * Perhaps it would also be useful to look at the number of constraints
2145 * that conflict with any given constraint.
2147 static int best_split(struct isl_tab *tab, struct isl_tab *context_tab)
2149 struct isl_tab_undo *snap;
2150 int split;
2151 int row;
2152 int best = -1;
2153 int best_r;
2155 if (isl_tab_extend_cons(context_tab, 2) < 0)
2156 return -1;
2158 snap = isl_tab_snap(context_tab);
2160 for (split = tab->n_redundant; split < tab->n_row; ++split) {
2161 struct isl_tab_undo *snap2;
2162 struct isl_vec *ineq = NULL;
2163 int r = 0;
2164 int ok;
2166 if (!isl_tab_var_from_row(tab, split)->is_nonneg)
2167 continue;
2168 if (tab->row_sign[split] != isl_tab_row_any)
2169 continue;
2171 ineq = get_row_parameter_ineq(tab, split);
2172 if (!ineq)
2173 return -1;
2174 ok = isl_tab_add_ineq(context_tab, ineq->el) >= 0;
2175 isl_vec_free(ineq);
2176 if (!ok)
2177 return -1;
2179 snap2 = isl_tab_snap(context_tab);
2181 for (row = tab->n_redundant; row < tab->n_row; ++row) {
2182 struct isl_tab_var *var;
2184 if (row == split)
2185 continue;
2186 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
2187 continue;
2188 if (tab->row_sign[row] != isl_tab_row_any)
2189 continue;
2191 ineq = get_row_parameter_ineq(tab, row);
2192 if (!ineq)
2193 return -1;
2194 ok = isl_tab_add_ineq(context_tab, ineq->el) >= 0;
2195 isl_vec_free(ineq);
2196 if (!ok)
2197 return -1;
2198 var = &context_tab->con[context_tab->n_con - 1];
2199 if (!context_tab->empty &&
2200 !isl_tab_min_at_most_neg_one(context_tab, var))
2201 r++;
2202 if (isl_tab_rollback(context_tab, snap2) < 0)
2203 return -1;
2205 if (best == -1 || r > best_r) {
2206 best = split;
2207 best_r = r;
2209 if (isl_tab_rollback(context_tab, snap) < 0)
2210 return -1;
2213 return best;
2216 static struct isl_basic_set *context_lex_peek_basic_set(
2217 struct isl_context *context)
2219 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2220 if (!clex->tab)
2221 return NULL;
2222 return isl_tab_peek_bset(clex->tab);
2225 static struct isl_tab *context_lex_peek_tab(struct isl_context *context)
2227 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2228 return clex->tab;
2231 static void context_lex_add_eq(struct isl_context *context, isl_int *eq,
2232 int check, int update)
2234 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2235 if (isl_tab_extend_cons(clex->tab, 2) < 0)
2236 goto error;
2237 if (add_lexmin_eq(clex->tab, eq) < 0)
2238 goto error;
2239 if (check) {
2240 int v = tab_has_valid_sample(clex->tab, eq, 1);
2241 if (v < 0)
2242 goto error;
2243 if (!v)
2244 clex->tab = check_integer_feasible(clex->tab);
2246 if (update)
2247 clex->tab = check_samples(clex->tab, eq, 1);
2248 return;
2249 error:
2250 isl_tab_free(clex->tab);
2251 clex->tab = NULL;
2254 static void context_lex_add_ineq(struct isl_context *context, isl_int *ineq,
2255 int check, int update)
2257 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2258 if (isl_tab_extend_cons(clex->tab, 1) < 0)
2259 goto error;
2260 clex->tab = add_lexmin_ineq(clex->tab, ineq);
2261 if (check) {
2262 int v = tab_has_valid_sample(clex->tab, ineq, 0);
2263 if (v < 0)
2264 goto error;
2265 if (!v)
2266 clex->tab = check_integer_feasible(clex->tab);
2268 if (update)
2269 clex->tab = check_samples(clex->tab, ineq, 0);
2270 return;
2271 error:
2272 isl_tab_free(clex->tab);
2273 clex->tab = NULL;
2276 static int context_lex_add_ineq_wrap(void *user, isl_int *ineq)
2278 struct isl_context *context = (struct isl_context *)user;
2279 context_lex_add_ineq(context, ineq, 0, 0);
2280 return context->op->is_ok(context) ? 0 : -1;
2283 /* Check which signs can be obtained by "ineq" on all the currently
2284 * active sample values. See row_sign for more information.
2286 static enum isl_tab_row_sign tab_ineq_sign(struct isl_tab *tab, isl_int *ineq,
2287 int strict)
2289 int i;
2290 int sgn;
2291 isl_int tmp;
2292 enum isl_tab_row_sign res = isl_tab_row_unknown;
2294 isl_assert(tab->mat->ctx, tab->samples, return isl_tab_row_unknown);
2295 isl_assert(tab->mat->ctx, tab->samples->n_col == 1 + tab->n_var,
2296 return isl_tab_row_unknown);
2298 isl_int_init(tmp);
2299 for (i = tab->n_outside; i < tab->n_sample; ++i) {
2300 isl_seq_inner_product(tab->samples->row[i], ineq,
2301 1 + tab->n_var, &tmp);
2302 sgn = isl_int_sgn(tmp);
2303 if (sgn > 0 || (sgn == 0 && strict)) {
2304 if (res == isl_tab_row_unknown)
2305 res = isl_tab_row_pos;
2306 if (res == isl_tab_row_neg)
2307 res = isl_tab_row_any;
2309 if (sgn < 0) {
2310 if (res == isl_tab_row_unknown)
2311 res = isl_tab_row_neg;
2312 if (res == isl_tab_row_pos)
2313 res = isl_tab_row_any;
2315 if (res == isl_tab_row_any)
2316 break;
2318 isl_int_clear(tmp);
2320 return res;
2323 static enum isl_tab_row_sign context_lex_ineq_sign(struct isl_context *context,
2324 isl_int *ineq, int strict)
2326 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2327 return tab_ineq_sign(clex->tab, ineq, strict);
2330 /* Check whether "ineq" can be added to the tableau without rendering
2331 * it infeasible.
2333 static int context_lex_test_ineq(struct isl_context *context, isl_int *ineq)
2335 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2336 struct isl_tab_undo *snap;
2337 int feasible;
2339 if (!clex->tab)
2340 return -1;
2342 if (isl_tab_extend_cons(clex->tab, 1) < 0)
2343 return -1;
2345 snap = isl_tab_snap(clex->tab);
2346 if (isl_tab_push_basis(clex->tab) < 0)
2347 return -1;
2348 clex->tab = add_lexmin_ineq(clex->tab, ineq);
2349 clex->tab = check_integer_feasible(clex->tab);
2350 if (!clex->tab)
2351 return -1;
2352 feasible = !clex->tab->empty;
2353 if (isl_tab_rollback(clex->tab, snap) < 0)
2354 return -1;
2356 return feasible;
2359 static int context_lex_get_div(struct isl_context *context, struct isl_tab *tab,
2360 struct isl_vec *div)
2362 return get_div(tab, context, div);
2365 /* Add a div specified by "div" to the context tableau and return
2366 * 1 if the div is obviously non-negative.
2367 * context_tab_add_div will always return 1, because all variables
2368 * in a isl_context_lex tableau are non-negative.
2369 * However, if we are using a big parameter in the context, then this only
2370 * reflects the non-negativity of the variable used to _encode_ the
2371 * div, i.e., div' = M + div, so we can't draw any conclusions.
2373 static int context_lex_add_div(struct isl_context *context, struct isl_vec *div)
2375 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2376 int nonneg;
2377 nonneg = context_tab_add_div(clex->tab, div,
2378 context_lex_add_ineq_wrap, context);
2379 if (nonneg < 0)
2380 return -1;
2381 if (clex->tab->M)
2382 return 0;
2383 return nonneg;
2386 static int context_lex_detect_equalities(struct isl_context *context,
2387 struct isl_tab *tab)
2389 return 0;
2392 static int context_lex_best_split(struct isl_context *context,
2393 struct isl_tab *tab)
2395 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2396 struct isl_tab_undo *snap;
2397 int r;
2399 snap = isl_tab_snap(clex->tab);
2400 if (isl_tab_push_basis(clex->tab) < 0)
2401 return -1;
2402 r = best_split(tab, clex->tab);
2404 if (r >= 0 && isl_tab_rollback(clex->tab, snap) < 0)
2405 return -1;
2407 return r;
2410 static int context_lex_is_empty(struct isl_context *context)
2412 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2413 if (!clex->tab)
2414 return -1;
2415 return clex->tab->empty;
2418 static void *context_lex_save(struct isl_context *context)
2420 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2421 struct isl_tab_undo *snap;
2423 snap = isl_tab_snap(clex->tab);
2424 if (isl_tab_push_basis(clex->tab) < 0)
2425 return NULL;
2426 if (isl_tab_save_samples(clex->tab) < 0)
2427 return NULL;
2429 return snap;
2432 static void context_lex_restore(struct isl_context *context, void *save)
2434 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2435 if (isl_tab_rollback(clex->tab, (struct isl_tab_undo *)save) < 0) {
2436 isl_tab_free(clex->tab);
2437 clex->tab = NULL;
2441 static void context_lex_discard(void *save)
2445 static int context_lex_is_ok(struct isl_context *context)
2447 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2448 return !!clex->tab;
2451 /* For each variable in the context tableau, check if the variable can
2452 * only attain non-negative values. If so, mark the parameter as non-negative
2453 * in the main tableau. This allows for a more direct identification of some
2454 * cases of violated constraints.
2456 static struct isl_tab *tab_detect_nonnegative_parameters(struct isl_tab *tab,
2457 struct isl_tab *context_tab)
2459 int i;
2460 struct isl_tab_undo *snap;
2461 struct isl_vec *ineq = NULL;
2462 struct isl_tab_var *var;
2463 int n;
2465 if (context_tab->n_var == 0)
2466 return tab;
2468 ineq = isl_vec_alloc(tab->mat->ctx, 1 + context_tab->n_var);
2469 if (!ineq)
2470 goto error;
2472 if (isl_tab_extend_cons(context_tab, 1) < 0)
2473 goto error;
2475 snap = isl_tab_snap(context_tab);
2477 n = 0;
2478 isl_seq_clr(ineq->el, ineq->size);
2479 for (i = 0; i < context_tab->n_var; ++i) {
2480 isl_int_set_si(ineq->el[1 + i], 1);
2481 if (isl_tab_add_ineq(context_tab, ineq->el) < 0)
2482 goto error;
2483 var = &context_tab->con[context_tab->n_con - 1];
2484 if (!context_tab->empty &&
2485 !isl_tab_min_at_most_neg_one(context_tab, var)) {
2486 int j = i;
2487 if (i >= tab->n_param)
2488 j = i - tab->n_param + tab->n_var - tab->n_div;
2489 tab->var[j].is_nonneg = 1;
2490 n++;
2492 isl_int_set_si(ineq->el[1 + i], 0);
2493 if (isl_tab_rollback(context_tab, snap) < 0)
2494 goto error;
2497 if (context_tab->M && n == context_tab->n_var) {
2498 context_tab->mat = isl_mat_drop_cols(context_tab->mat, 2, 1);
2499 context_tab->M = 0;
2502 isl_vec_free(ineq);
2503 return tab;
2504 error:
2505 isl_vec_free(ineq);
2506 isl_tab_free(tab);
2507 return NULL;
2510 static struct isl_tab *context_lex_detect_nonnegative_parameters(
2511 struct isl_context *context, struct isl_tab *tab)
2513 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2514 struct isl_tab_undo *snap;
2516 if (!tab)
2517 return NULL;
2519 snap = isl_tab_snap(clex->tab);
2520 if (isl_tab_push_basis(clex->tab) < 0)
2521 goto error;
2523 tab = tab_detect_nonnegative_parameters(tab, clex->tab);
2525 if (isl_tab_rollback(clex->tab, snap) < 0)
2526 goto error;
2528 return tab;
2529 error:
2530 isl_tab_free(tab);
2531 return NULL;
2534 static void context_lex_invalidate(struct isl_context *context)
2536 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2537 isl_tab_free(clex->tab);
2538 clex->tab = NULL;
2541 static void context_lex_free(struct isl_context *context)
2543 struct isl_context_lex *clex = (struct isl_context_lex *)context;
2544 isl_tab_free(clex->tab);
2545 free(clex);
2548 struct isl_context_op isl_context_lex_op = {
2549 context_lex_detect_nonnegative_parameters,
2550 context_lex_peek_basic_set,
2551 context_lex_peek_tab,
2552 context_lex_add_eq,
2553 context_lex_add_ineq,
2554 context_lex_ineq_sign,
2555 context_lex_test_ineq,
2556 context_lex_get_div,
2557 context_lex_add_div,
2558 context_lex_detect_equalities,
2559 context_lex_best_split,
2560 context_lex_is_empty,
2561 context_lex_is_ok,
2562 context_lex_save,
2563 context_lex_restore,
2564 context_lex_discard,
2565 context_lex_invalidate,
2566 context_lex_free,
2569 static struct isl_tab *context_tab_for_lexmin(struct isl_basic_set *bset)
2571 struct isl_tab *tab;
2573 if (!bset)
2574 return NULL;
2575 tab = tab_for_lexmin((struct isl_basic_map *)bset, NULL, 1, 0);
2576 if (!tab)
2577 goto error;
2578 if (isl_tab_track_bset(tab, bset) < 0)
2579 goto error;
2580 tab = isl_tab_init_samples(tab);
2581 return tab;
2582 error:
2583 isl_basic_set_free(bset);
2584 return NULL;
2587 static struct isl_context *isl_context_lex_alloc(struct isl_basic_set *dom)
2589 struct isl_context_lex *clex;
2591 if (!dom)
2592 return NULL;
2594 clex = isl_alloc_type(dom->ctx, struct isl_context_lex);
2595 if (!clex)
2596 return NULL;
2598 clex->context.op = &isl_context_lex_op;
2600 clex->tab = context_tab_for_lexmin(isl_basic_set_copy(dom));
2601 if (restore_lexmin(clex->tab) < 0)
2602 goto error;
2603 clex->tab = check_integer_feasible(clex->tab);
2604 if (!clex->tab)
2605 goto error;
2607 return &clex->context;
2608 error:
2609 clex->context.op->free(&clex->context);
2610 return NULL;
2613 /* Representation of the context when using generalized basis reduction.
2615 * "shifted" contains the offsets of the unit hypercubes that lie inside the
2616 * context. Any rational point in "shifted" can therefore be rounded
2617 * up to an integer point in the context.
2618 * If the context is constrained by any equality, then "shifted" is not used
2619 * as it would be empty.
2621 struct isl_context_gbr {
2622 struct isl_context context;
2623 struct isl_tab *tab;
2624 struct isl_tab *shifted;
2625 struct isl_tab *cone;
2628 static struct isl_tab *context_gbr_detect_nonnegative_parameters(
2629 struct isl_context *context, struct isl_tab *tab)
2631 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
2632 if (!tab)
2633 return NULL;
2634 return tab_detect_nonnegative_parameters(tab, cgbr->tab);
2637 static struct isl_basic_set *context_gbr_peek_basic_set(
2638 struct isl_context *context)
2640 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
2641 if (!cgbr->tab)
2642 return NULL;
2643 return isl_tab_peek_bset(cgbr->tab);
2646 static struct isl_tab *context_gbr_peek_tab(struct isl_context *context)
2648 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
2649 return cgbr->tab;
2652 /* Initialize the "shifted" tableau of the context, which
2653 * contains the constraints of the original tableau shifted
2654 * by the sum of all negative coefficients. This ensures
2655 * that any rational point in the shifted tableau can
2656 * be rounded up to yield an integer point in the original tableau.
2658 static void gbr_init_shifted(struct isl_context_gbr *cgbr)
2660 int i, j;
2661 struct isl_vec *cst;
2662 struct isl_basic_set *bset = isl_tab_peek_bset(cgbr->tab);
2663 unsigned dim = isl_basic_set_total_dim(bset);
2665 cst = isl_vec_alloc(cgbr->tab->mat->ctx, bset->n_ineq);
2666 if (!cst)
2667 return;
2669 for (i = 0; i < bset->n_ineq; ++i) {
2670 isl_int_set(cst->el[i], bset->ineq[i][0]);
2671 for (j = 0; j < dim; ++j) {
2672 if (!isl_int_is_neg(bset->ineq[i][1 + j]))
2673 continue;
2674 isl_int_add(bset->ineq[i][0], bset->ineq[i][0],
2675 bset->ineq[i][1 + j]);
2679 cgbr->shifted = isl_tab_from_basic_set(bset, 0);
2681 for (i = 0; i < bset->n_ineq; ++i)
2682 isl_int_set(bset->ineq[i][0], cst->el[i]);
2684 isl_vec_free(cst);
2687 /* Check if the shifted tableau is non-empty, and if so
2688 * use the sample point to construct an integer point
2689 * of the context tableau.
2691 static struct isl_vec *gbr_get_shifted_sample(struct isl_context_gbr *cgbr)
2693 struct isl_vec *sample;
2695 if (!cgbr->shifted)
2696 gbr_init_shifted(cgbr);
2697 if (!cgbr->shifted)
2698 return NULL;
2699 if (cgbr->shifted->empty)
2700 return isl_vec_alloc(cgbr->tab->mat->ctx, 0);
2702 sample = isl_tab_get_sample_value(cgbr->shifted);
2703 sample = isl_vec_ceil(sample);
2705 return sample;
2708 static struct isl_basic_set *drop_constant_terms(struct isl_basic_set *bset)
2710 int i;
2712 if (!bset)
2713 return NULL;
2715 for (i = 0; i < bset->n_eq; ++i)
2716 isl_int_set_si(bset->eq[i][0], 0);
2718 for (i = 0; i < bset->n_ineq; ++i)
2719 isl_int_set_si(bset->ineq[i][0], 0);
2721 return bset;
2724 static int use_shifted(struct isl_context_gbr *cgbr)
2726 return cgbr->tab->bmap->n_eq == 0 && cgbr->tab->bmap->n_div == 0;
2729 static struct isl_vec *gbr_get_sample(struct isl_context_gbr *cgbr)
2731 struct isl_basic_set *bset;
2732 struct isl_basic_set *cone;
2734 if (isl_tab_sample_is_integer(cgbr->tab))
2735 return isl_tab_get_sample_value(cgbr->tab);
2737 if (use_shifted(cgbr)) {
2738 struct isl_vec *sample;
2740 sample = gbr_get_shifted_sample(cgbr);
2741 if (!sample || sample->size > 0)
2742 return sample;
2744 isl_vec_free(sample);
2747 if (!cgbr->cone) {
2748 bset = isl_tab_peek_bset(cgbr->tab);
2749 cgbr->cone = isl_tab_from_recession_cone(bset, 0);
2750 if (!cgbr->cone)
2751 return NULL;
2752 if (isl_tab_track_bset(cgbr->cone,
2753 isl_basic_set_copy(bset)) < 0)
2754 return NULL;
2756 if (isl_tab_detect_implicit_equalities(cgbr->cone) < 0)
2757 return NULL;
2759 if (cgbr->cone->n_dead == cgbr->cone->n_col) {
2760 struct isl_vec *sample;
2761 struct isl_tab_undo *snap;
2763 if (cgbr->tab->basis) {
2764 if (cgbr->tab->basis->n_col != 1 + cgbr->tab->n_var) {
2765 isl_mat_free(cgbr->tab->basis);
2766 cgbr->tab->basis = NULL;
2768 cgbr->tab->n_zero = 0;
2769 cgbr->tab->n_unbounded = 0;
2772 snap = isl_tab_snap(cgbr->tab);
2774 sample = isl_tab_sample(cgbr->tab);
2776 if (isl_tab_rollback(cgbr->tab, snap) < 0) {
2777 isl_vec_free(sample);
2778 return NULL;
2781 return sample;
2784 cone = isl_basic_set_dup(isl_tab_peek_bset(cgbr->cone));
2785 cone = drop_constant_terms(cone);
2786 cone = isl_basic_set_update_from_tab(cone, cgbr->cone);
2787 cone = isl_basic_set_underlying_set(cone);
2788 cone = isl_basic_set_gauss(cone, NULL);
2790 bset = isl_basic_set_dup(isl_tab_peek_bset(cgbr->tab));
2791 bset = isl_basic_set_update_from_tab(bset, cgbr->tab);
2792 bset = isl_basic_set_underlying_set(bset);
2793 bset = isl_basic_set_gauss(bset, NULL);
2795 return isl_basic_set_sample_with_cone(bset, cone);
2798 static void check_gbr_integer_feasible(struct isl_context_gbr *cgbr)
2800 struct isl_vec *sample;
2802 if (!cgbr->tab)
2803 return;
2805 if (cgbr->tab->empty)
2806 return;
2808 sample = gbr_get_sample(cgbr);
2809 if (!sample)
2810 goto error;
2812 if (sample->size == 0) {
2813 isl_vec_free(sample);
2814 if (isl_tab_mark_empty(cgbr->tab) < 0)
2815 goto error;
2816 return;
2819 cgbr->tab = isl_tab_add_sample(cgbr->tab, sample);
2821 return;
2822 error:
2823 isl_tab_free(cgbr->tab);
2824 cgbr->tab = NULL;
2827 static struct isl_tab *add_gbr_eq(struct isl_tab *tab, isl_int *eq)
2829 if (!tab)
2830 return NULL;
2832 if (isl_tab_extend_cons(tab, 2) < 0)
2833 goto error;
2835 if (isl_tab_add_eq(tab, eq) < 0)
2836 goto error;
2838 return tab;
2839 error:
2840 isl_tab_free(tab);
2841 return NULL;
2844 /* Add the equality described by "eq" to the context.
2845 * If "check" is set, then we check if the context is empty after
2846 * adding the equality.
2847 * If "update" is set, then we check if the samples are still valid.
2849 * We do not explicitly add shifted copies of the equality to
2850 * cgbr->shifted since they would conflict with each other.
2851 * Instead, we directly mark cgbr->shifted empty.
2853 static void context_gbr_add_eq(struct isl_context *context, isl_int *eq,
2854 int check, int update)
2856 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
2858 cgbr->tab = add_gbr_eq(cgbr->tab, eq);
2860 if (cgbr->shifted && !cgbr->shifted->empty && use_shifted(cgbr)) {
2861 if (isl_tab_mark_empty(cgbr->shifted) < 0)
2862 goto error;
2865 if (cgbr->cone && cgbr->cone->n_col != cgbr->cone->n_dead) {
2866 if (isl_tab_extend_cons(cgbr->cone, 2) < 0)
2867 goto error;
2868 if (isl_tab_add_eq(cgbr->cone, eq) < 0)
2869 goto error;
2872 if (check) {
2873 int v = tab_has_valid_sample(cgbr->tab, eq, 1);
2874 if (v < 0)
2875 goto error;
2876 if (!v)
2877 check_gbr_integer_feasible(cgbr);
2879 if (update)
2880 cgbr->tab = check_samples(cgbr->tab, eq, 1);
2881 return;
2882 error:
2883 isl_tab_free(cgbr->tab);
2884 cgbr->tab = NULL;
2887 static void add_gbr_ineq(struct isl_context_gbr *cgbr, isl_int *ineq)
2889 if (!cgbr->tab)
2890 return;
2892 if (isl_tab_extend_cons(cgbr->tab, 1) < 0)
2893 goto error;
2895 if (isl_tab_add_ineq(cgbr->tab, ineq) < 0)
2896 goto error;
2898 if (cgbr->shifted && !cgbr->shifted->empty && use_shifted(cgbr)) {
2899 int i;
2900 unsigned dim;
2901 dim = isl_basic_map_total_dim(cgbr->tab->bmap);
2903 if (isl_tab_extend_cons(cgbr->shifted, 1) < 0)
2904 goto error;
2906 for (i = 0; i < dim; ++i) {
2907 if (!isl_int_is_neg(ineq[1 + i]))
2908 continue;
2909 isl_int_add(ineq[0], ineq[0], ineq[1 + i]);
2912 if (isl_tab_add_ineq(cgbr->shifted, ineq) < 0)
2913 goto error;
2915 for (i = 0; i < dim; ++i) {
2916 if (!isl_int_is_neg(ineq[1 + i]))
2917 continue;
2918 isl_int_sub(ineq[0], ineq[0], ineq[1 + i]);
2922 if (cgbr->cone && cgbr->cone->n_col != cgbr->cone->n_dead) {
2923 if (isl_tab_extend_cons(cgbr->cone, 1) < 0)
2924 goto error;
2925 if (isl_tab_add_ineq(cgbr->cone, ineq) < 0)
2926 goto error;
2929 return;
2930 error:
2931 isl_tab_free(cgbr->tab);
2932 cgbr->tab = NULL;
2935 static void context_gbr_add_ineq(struct isl_context *context, isl_int *ineq,
2936 int check, int update)
2938 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
2940 add_gbr_ineq(cgbr, ineq);
2941 if (!cgbr->tab)
2942 return;
2944 if (check) {
2945 int v = tab_has_valid_sample(cgbr->tab, ineq, 0);
2946 if (v < 0)
2947 goto error;
2948 if (!v)
2949 check_gbr_integer_feasible(cgbr);
2951 if (update)
2952 cgbr->tab = check_samples(cgbr->tab, ineq, 0);
2953 return;
2954 error:
2955 isl_tab_free(cgbr->tab);
2956 cgbr->tab = NULL;
2959 static int context_gbr_add_ineq_wrap(void *user, isl_int *ineq)
2961 struct isl_context *context = (struct isl_context *)user;
2962 context_gbr_add_ineq(context, ineq, 0, 0);
2963 return context->op->is_ok(context) ? 0 : -1;
2966 static enum isl_tab_row_sign context_gbr_ineq_sign(struct isl_context *context,
2967 isl_int *ineq, int strict)
2969 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
2970 return tab_ineq_sign(cgbr->tab, ineq, strict);
2973 /* Check whether "ineq" can be added to the tableau without rendering
2974 * it infeasible.
2976 static int context_gbr_test_ineq(struct isl_context *context, isl_int *ineq)
2978 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
2979 struct isl_tab_undo *snap;
2980 struct isl_tab_undo *shifted_snap = NULL;
2981 struct isl_tab_undo *cone_snap = NULL;
2982 int feasible;
2984 if (!cgbr->tab)
2985 return -1;
2987 if (isl_tab_extend_cons(cgbr->tab, 1) < 0)
2988 return -1;
2990 snap = isl_tab_snap(cgbr->tab);
2991 if (cgbr->shifted)
2992 shifted_snap = isl_tab_snap(cgbr->shifted);
2993 if (cgbr->cone)
2994 cone_snap = isl_tab_snap(cgbr->cone);
2995 add_gbr_ineq(cgbr, ineq);
2996 check_gbr_integer_feasible(cgbr);
2997 if (!cgbr->tab)
2998 return -1;
2999 feasible = !cgbr->tab->empty;
3000 if (isl_tab_rollback(cgbr->tab, snap) < 0)
3001 return -1;
3002 if (shifted_snap) {
3003 if (isl_tab_rollback(cgbr->shifted, shifted_snap))
3004 return -1;
3005 } else if (cgbr->shifted) {
3006 isl_tab_free(cgbr->shifted);
3007 cgbr->shifted = NULL;
3009 if (cone_snap) {
3010 if (isl_tab_rollback(cgbr->cone, cone_snap))
3011 return -1;
3012 } else if (cgbr->cone) {
3013 isl_tab_free(cgbr->cone);
3014 cgbr->cone = NULL;
3017 return feasible;
3020 /* Return the column of the last of the variables associated to
3021 * a column that has a non-zero coefficient.
3022 * This function is called in a context where only coefficients
3023 * of parameters or divs can be non-zero.
3025 static int last_non_zero_var_col(struct isl_tab *tab, isl_int *p)
3027 int i;
3028 int col;
3030 if (tab->n_var == 0)
3031 return -1;
3033 for (i = tab->n_var - 1; i >= 0; --i) {
3034 if (i >= tab->n_param && i < tab->n_var - tab->n_div)
3035 continue;
3036 if (tab->var[i].is_row)
3037 continue;
3038 col = tab->var[i].index;
3039 if (!isl_int_is_zero(p[col]))
3040 return col;
3043 return -1;
3046 /* Look through all the recently added equalities in the context
3047 * to see if we can propagate any of them to the main tableau.
3049 * The newly added equalities in the context are encoded as pairs
3050 * of inequalities starting at inequality "first".
3052 * We tentatively add each of these equalities to the main tableau
3053 * and if this happens to result in a row with a final coefficient
3054 * that is one or negative one, we use it to kill a column
3055 * in the main tableau. Otherwise, we discard the tentatively
3056 * added row.
3058 static void propagate_equalities(struct isl_context_gbr *cgbr,
3059 struct isl_tab *tab, unsigned first)
3061 int i;
3062 struct isl_vec *eq = NULL;
3064 eq = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
3065 if (!eq)
3066 goto error;
3068 if (isl_tab_extend_cons(tab, (cgbr->tab->bmap->n_ineq - first)/2) < 0)
3069 goto error;
3071 isl_seq_clr(eq->el + 1 + tab->n_param,
3072 tab->n_var - tab->n_param - tab->n_div);
3073 for (i = first; i < cgbr->tab->bmap->n_ineq; i += 2) {
3074 int j;
3075 int r;
3076 struct isl_tab_undo *snap;
3077 snap = isl_tab_snap(tab);
3079 isl_seq_cpy(eq->el, cgbr->tab->bmap->ineq[i], 1 + tab->n_param);
3080 isl_seq_cpy(eq->el + 1 + tab->n_var - tab->n_div,
3081 cgbr->tab->bmap->ineq[i] + 1 + tab->n_param,
3082 tab->n_div);
3084 r = isl_tab_add_row(tab, eq->el);
3085 if (r < 0)
3086 goto error;
3087 r = tab->con[r].index;
3088 j = last_non_zero_var_col(tab, tab->mat->row[r] + 2 + tab->M);
3089 if (j < 0 || j < tab->n_dead ||
3090 !isl_int_is_one(tab->mat->row[r][0]) ||
3091 (!isl_int_is_one(tab->mat->row[r][2 + tab->M + j]) &&
3092 !isl_int_is_negone(tab->mat->row[r][2 + tab->M + j]))) {
3093 if (isl_tab_rollback(tab, snap) < 0)
3094 goto error;
3095 continue;
3097 if (isl_tab_pivot(tab, r, j) < 0)
3098 goto error;
3099 if (isl_tab_kill_col(tab, j) < 0)
3100 goto error;
3102 if (restore_lexmin(tab) < 0)
3103 goto error;
3106 isl_vec_free(eq);
3108 return;
3109 error:
3110 isl_vec_free(eq);
3111 isl_tab_free(cgbr->tab);
3112 cgbr->tab = NULL;
3115 static int context_gbr_detect_equalities(struct isl_context *context,
3116 struct isl_tab *tab)
3118 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3119 struct isl_ctx *ctx;
3120 unsigned n_ineq;
3122 ctx = cgbr->tab->mat->ctx;
3124 if (!cgbr->cone) {
3125 struct isl_basic_set *bset = isl_tab_peek_bset(cgbr->tab);
3126 cgbr->cone = isl_tab_from_recession_cone(bset, 0);
3127 if (!cgbr->cone)
3128 goto error;
3129 if (isl_tab_track_bset(cgbr->cone,
3130 isl_basic_set_copy(bset)) < 0)
3131 goto error;
3133 if (isl_tab_detect_implicit_equalities(cgbr->cone) < 0)
3134 goto error;
3136 n_ineq = cgbr->tab->bmap->n_ineq;
3137 cgbr->tab = isl_tab_detect_equalities(cgbr->tab, cgbr->cone);
3138 if (!cgbr->tab)
3139 return -1;
3140 if (cgbr->tab->bmap->n_ineq > n_ineq)
3141 propagate_equalities(cgbr, tab, n_ineq);
3143 return 0;
3144 error:
3145 isl_tab_free(cgbr->tab);
3146 cgbr->tab = NULL;
3147 return -1;
3150 static int context_gbr_get_div(struct isl_context *context, struct isl_tab *tab,
3151 struct isl_vec *div)
3153 return get_div(tab, context, div);
3156 static int context_gbr_add_div(struct isl_context *context, struct isl_vec *div)
3158 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3159 if (cgbr->cone) {
3160 int k;
3162 if (isl_tab_extend_cons(cgbr->cone, 3) < 0)
3163 return -1;
3164 if (isl_tab_extend_vars(cgbr->cone, 1) < 0)
3165 return -1;
3166 if (isl_tab_allocate_var(cgbr->cone) <0)
3167 return -1;
3169 cgbr->cone->bmap = isl_basic_map_extend_space(cgbr->cone->bmap,
3170 isl_basic_map_get_space(cgbr->cone->bmap), 1, 0, 2);
3171 k = isl_basic_map_alloc_div(cgbr->cone->bmap);
3172 if (k < 0)
3173 return -1;
3174 isl_seq_cpy(cgbr->cone->bmap->div[k], div->el, div->size);
3175 if (isl_tab_push(cgbr->cone, isl_tab_undo_bmap_div) < 0)
3176 return -1;
3178 return context_tab_add_div(cgbr->tab, div,
3179 context_gbr_add_ineq_wrap, context);
3182 static int context_gbr_best_split(struct isl_context *context,
3183 struct isl_tab *tab)
3185 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3186 struct isl_tab_undo *snap;
3187 int r;
3189 snap = isl_tab_snap(cgbr->tab);
3190 r = best_split(tab, cgbr->tab);
3192 if (r >= 0 && isl_tab_rollback(cgbr->tab, snap) < 0)
3193 return -1;
3195 return r;
3198 static int context_gbr_is_empty(struct isl_context *context)
3200 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3201 if (!cgbr->tab)
3202 return -1;
3203 return cgbr->tab->empty;
3206 struct isl_gbr_tab_undo {
3207 struct isl_tab_undo *tab_snap;
3208 struct isl_tab_undo *shifted_snap;
3209 struct isl_tab_undo *cone_snap;
3212 static void *context_gbr_save(struct isl_context *context)
3214 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3215 struct isl_gbr_tab_undo *snap;
3217 snap = isl_alloc_type(cgbr->tab->mat->ctx, struct isl_gbr_tab_undo);
3218 if (!snap)
3219 return NULL;
3221 snap->tab_snap = isl_tab_snap(cgbr->tab);
3222 if (isl_tab_save_samples(cgbr->tab) < 0)
3223 goto error;
3225 if (cgbr->shifted)
3226 snap->shifted_snap = isl_tab_snap(cgbr->shifted);
3227 else
3228 snap->shifted_snap = NULL;
3230 if (cgbr->cone)
3231 snap->cone_snap = isl_tab_snap(cgbr->cone);
3232 else
3233 snap->cone_snap = NULL;
3235 return snap;
3236 error:
3237 free(snap);
3238 return NULL;
3241 static void context_gbr_restore(struct isl_context *context, void *save)
3243 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3244 struct isl_gbr_tab_undo *snap = (struct isl_gbr_tab_undo *)save;
3245 if (!snap)
3246 goto error;
3247 if (isl_tab_rollback(cgbr->tab, snap->tab_snap) < 0) {
3248 isl_tab_free(cgbr->tab);
3249 cgbr->tab = NULL;
3252 if (snap->shifted_snap) {
3253 if (isl_tab_rollback(cgbr->shifted, snap->shifted_snap) < 0)
3254 goto error;
3255 } else if (cgbr->shifted) {
3256 isl_tab_free(cgbr->shifted);
3257 cgbr->shifted = NULL;
3260 if (snap->cone_snap) {
3261 if (isl_tab_rollback(cgbr->cone, snap->cone_snap) < 0)
3262 goto error;
3263 } else if (cgbr->cone) {
3264 isl_tab_free(cgbr->cone);
3265 cgbr->cone = NULL;
3268 free(snap);
3270 return;
3271 error:
3272 free(snap);
3273 isl_tab_free(cgbr->tab);
3274 cgbr->tab = NULL;
3277 static void context_gbr_discard(void *save)
3279 struct isl_gbr_tab_undo *snap = (struct isl_gbr_tab_undo *)save;
3280 free(snap);
3283 static int context_gbr_is_ok(struct isl_context *context)
3285 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3286 return !!cgbr->tab;
3289 static void context_gbr_invalidate(struct isl_context *context)
3291 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3292 isl_tab_free(cgbr->tab);
3293 cgbr->tab = NULL;
3296 static void context_gbr_free(struct isl_context *context)
3298 struct isl_context_gbr *cgbr = (struct isl_context_gbr *)context;
3299 isl_tab_free(cgbr->tab);
3300 isl_tab_free(cgbr->shifted);
3301 isl_tab_free(cgbr->cone);
3302 free(cgbr);
3305 struct isl_context_op isl_context_gbr_op = {
3306 context_gbr_detect_nonnegative_parameters,
3307 context_gbr_peek_basic_set,
3308 context_gbr_peek_tab,
3309 context_gbr_add_eq,
3310 context_gbr_add_ineq,
3311 context_gbr_ineq_sign,
3312 context_gbr_test_ineq,
3313 context_gbr_get_div,
3314 context_gbr_add_div,
3315 context_gbr_detect_equalities,
3316 context_gbr_best_split,
3317 context_gbr_is_empty,
3318 context_gbr_is_ok,
3319 context_gbr_save,
3320 context_gbr_restore,
3321 context_gbr_discard,
3322 context_gbr_invalidate,
3323 context_gbr_free,
3326 static struct isl_context *isl_context_gbr_alloc(struct isl_basic_set *dom)
3328 struct isl_context_gbr *cgbr;
3330 if (!dom)
3331 return NULL;
3333 cgbr = isl_calloc_type(dom->ctx, struct isl_context_gbr);
3334 if (!cgbr)
3335 return NULL;
3337 cgbr->context.op = &isl_context_gbr_op;
3339 cgbr->shifted = NULL;
3340 cgbr->cone = NULL;
3341 cgbr->tab = isl_tab_from_basic_set(dom, 1);
3342 cgbr->tab = isl_tab_init_samples(cgbr->tab);
3343 if (!cgbr->tab)
3344 goto error;
3345 check_gbr_integer_feasible(cgbr);
3347 return &cgbr->context;
3348 error:
3349 cgbr->context.op->free(&cgbr->context);
3350 return NULL;
3353 static struct isl_context *isl_context_alloc(struct isl_basic_set *dom)
3355 if (!dom)
3356 return NULL;
3358 if (dom->ctx->opt->context == ISL_CONTEXT_LEXMIN)
3359 return isl_context_lex_alloc(dom);
3360 else
3361 return isl_context_gbr_alloc(dom);
3364 /* Construct an isl_sol_map structure for accumulating the solution.
3365 * If track_empty is set, then we also keep track of the parts
3366 * of the context where there is no solution.
3367 * If max is set, then we are solving a maximization, rather than
3368 * a minimization problem, which means that the variables in the
3369 * tableau have value "M - x" rather than "M + x".
3371 static struct isl_sol *sol_map_init(struct isl_basic_map *bmap,
3372 struct isl_basic_set *dom, int track_empty, int max)
3374 struct isl_sol_map *sol_map = NULL;
3376 if (!bmap)
3377 goto error;
3379 sol_map = isl_calloc_type(bmap->ctx, struct isl_sol_map);
3380 if (!sol_map)
3381 goto error;
3383 sol_map->sol.rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
3384 sol_map->sol.dec_level.callback.run = &sol_dec_level_wrap;
3385 sol_map->sol.dec_level.sol = &sol_map->sol;
3386 sol_map->sol.max = max;
3387 sol_map->sol.n_out = isl_basic_map_dim(bmap, isl_dim_out);
3388 sol_map->sol.add = &sol_map_add_wrap;
3389 sol_map->sol.add_empty = track_empty ? &sol_map_add_empty_wrap : NULL;
3390 sol_map->sol.free = &sol_map_free_wrap;
3391 sol_map->map = isl_map_alloc_space(isl_basic_map_get_space(bmap), 1,
3392 ISL_MAP_DISJOINT);
3393 if (!sol_map->map)
3394 goto error;
3396 sol_map->sol.context = isl_context_alloc(dom);
3397 if (!sol_map->sol.context)
3398 goto error;
3400 if (track_empty) {
3401 sol_map->empty = isl_set_alloc_space(isl_basic_set_get_space(dom),
3402 1, ISL_SET_DISJOINT);
3403 if (!sol_map->empty)
3404 goto error;
3407 isl_basic_set_free(dom);
3408 return &sol_map->sol;
3409 error:
3410 isl_basic_set_free(dom);
3411 sol_map_free(sol_map);
3412 return NULL;
3415 /* Check whether all coefficients of (non-parameter) variables
3416 * are non-positive, meaning that no pivots can be performed on the row.
3418 static int is_critical(struct isl_tab *tab, int row)
3420 int j;
3421 unsigned off = 2 + tab->M;
3423 for (j = tab->n_dead; j < tab->n_col; ++j) {
3424 if (tab->col_var[j] >= 0 &&
3425 (tab->col_var[j] < tab->n_param ||
3426 tab->col_var[j] >= tab->n_var - tab->n_div))
3427 continue;
3429 if (isl_int_is_pos(tab->mat->row[row][off + j]))
3430 return 0;
3433 return 1;
3436 /* Check whether the inequality represented by vec is strict over the integers,
3437 * i.e., there are no integer values satisfying the constraint with
3438 * equality. This happens if the gcd of the coefficients is not a divisor
3439 * of the constant term. If so, scale the constraint down by the gcd
3440 * of the coefficients.
3442 static int is_strict(struct isl_vec *vec)
3444 isl_int gcd;
3445 int strict = 0;
3447 isl_int_init(gcd);
3448 isl_seq_gcd(vec->el + 1, vec->size - 1, &gcd);
3449 if (!isl_int_is_one(gcd)) {
3450 strict = !isl_int_is_divisible_by(vec->el[0], gcd);
3451 isl_int_fdiv_q(vec->el[0], vec->el[0], gcd);
3452 isl_seq_scale_down(vec->el + 1, vec->el + 1, gcd, vec->size-1);
3454 isl_int_clear(gcd);
3456 return strict;
3459 /* Determine the sign of the given row of the main tableau.
3460 * The result is one of
3461 * isl_tab_row_pos: always non-negative; no pivot needed
3462 * isl_tab_row_neg: always non-positive; pivot
3463 * isl_tab_row_any: can be both positive and negative; split
3465 * We first handle some simple cases
3466 * - the row sign may be known already
3467 * - the row may be obviously non-negative
3468 * - the parametric constant may be equal to that of another row
3469 * for which we know the sign. This sign will be either "pos" or
3470 * "any". If it had been "neg" then we would have pivoted before.
3472 * If none of these cases hold, we check the value of the row for each
3473 * of the currently active samples. Based on the signs of these values
3474 * we make an initial determination of the sign of the row.
3476 * all zero -> unk(nown)
3477 * all non-negative -> pos
3478 * all non-positive -> neg
3479 * both negative and positive -> all
3481 * If we end up with "all", we are done.
3482 * Otherwise, we perform a check for positive and/or negative
3483 * values as follows.
3485 * samples neg unk pos
3486 * <0 ? Y N Y N
3487 * pos any pos
3488 * >0 ? Y N Y N
3489 * any neg any neg
3491 * There is no special sign for "zero", because we can usually treat zero
3492 * as either non-negative or non-positive, whatever works out best.
3493 * However, if the row is "critical", meaning that pivoting is impossible
3494 * then we don't want to limp zero with the non-positive case, because
3495 * then we we would lose the solution for those values of the parameters
3496 * where the value of the row is zero. Instead, we treat 0 as non-negative
3497 * ensuring a split if the row can attain both zero and negative values.
3498 * The same happens when the original constraint was one that could not
3499 * be satisfied with equality by any integer values of the parameters.
3500 * In this case, we normalize the constraint, but then a value of zero
3501 * for the normalized constraint is actually a positive value for the
3502 * original constraint, so again we need to treat zero as non-negative.
3503 * In both these cases, we have the following decision tree instead:
3505 * all non-negative -> pos
3506 * all negative -> neg
3507 * both negative and non-negative -> all
3509 * samples neg pos
3510 * <0 ? Y N
3511 * any pos
3512 * >=0 ? Y N
3513 * any neg
3515 static enum isl_tab_row_sign row_sign(struct isl_tab *tab,
3516 struct isl_sol *sol, int row)
3518 struct isl_vec *ineq = NULL;
3519 enum isl_tab_row_sign res = isl_tab_row_unknown;
3520 int critical;
3521 int strict;
3522 int row2;
3524 if (tab->row_sign[row] != isl_tab_row_unknown)
3525 return tab->row_sign[row];
3526 if (is_obviously_nonneg(tab, row))
3527 return isl_tab_row_pos;
3528 for (row2 = tab->n_redundant; row2 < tab->n_row; ++row2) {
3529 if (tab->row_sign[row2] == isl_tab_row_unknown)
3530 continue;
3531 if (identical_parameter_line(tab, row, row2))
3532 return tab->row_sign[row2];
3535 critical = is_critical(tab, row);
3537 ineq = get_row_parameter_ineq(tab, row);
3538 if (!ineq)
3539 goto error;
3541 strict = is_strict(ineq);
3543 res = sol->context->op->ineq_sign(sol->context, ineq->el,
3544 critical || strict);
3546 if (res == isl_tab_row_unknown || res == isl_tab_row_pos) {
3547 /* test for negative values */
3548 int feasible;
3549 isl_seq_neg(ineq->el, ineq->el, ineq->size);
3550 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
3552 feasible = sol->context->op->test_ineq(sol->context, ineq->el);
3553 if (feasible < 0)
3554 goto error;
3555 if (!feasible)
3556 res = isl_tab_row_pos;
3557 else
3558 res = (res == isl_tab_row_unknown) ? isl_tab_row_neg
3559 : isl_tab_row_any;
3560 if (res == isl_tab_row_neg) {
3561 isl_seq_neg(ineq->el, ineq->el, ineq->size);
3562 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
3566 if (res == isl_tab_row_neg) {
3567 /* test for positive values */
3568 int feasible;
3569 if (!critical && !strict)
3570 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
3572 feasible = sol->context->op->test_ineq(sol->context, ineq->el);
3573 if (feasible < 0)
3574 goto error;
3575 if (feasible)
3576 res = isl_tab_row_any;
3579 isl_vec_free(ineq);
3580 return res;
3581 error:
3582 isl_vec_free(ineq);
3583 return isl_tab_row_unknown;
3586 static void find_solutions(struct isl_sol *sol, struct isl_tab *tab);
3588 /* Find solutions for values of the parameters that satisfy the given
3589 * inequality.
3591 * We currently take a snapshot of the context tableau that is reset
3592 * when we return from this function, while we make a copy of the main
3593 * tableau, leaving the original main tableau untouched.
3594 * These are fairly arbitrary choices. Making a copy also of the context
3595 * tableau would obviate the need to undo any changes made to it later,
3596 * while taking a snapshot of the main tableau could reduce memory usage.
3597 * If we were to switch to taking a snapshot of the main tableau,
3598 * we would have to keep in mind that we need to save the row signs
3599 * and that we need to do this before saving the current basis
3600 * such that the basis has been restore before we restore the row signs.
3602 static void find_in_pos(struct isl_sol *sol, struct isl_tab *tab, isl_int *ineq)
3604 void *saved;
3606 if (!sol->context)
3607 goto error;
3608 saved = sol->context->op->save(sol->context);
3610 tab = isl_tab_dup(tab);
3611 if (!tab)
3612 goto error;
3614 sol->context->op->add_ineq(sol->context, ineq, 0, 1);
3616 find_solutions(sol, tab);
3618 if (!sol->error)
3619 sol->context->op->restore(sol->context, saved);
3620 else
3621 sol->context->op->discard(saved);
3622 return;
3623 error:
3624 sol->error = 1;
3627 /* Record the absence of solutions for those values of the parameters
3628 * that do not satisfy the given inequality with equality.
3630 static void no_sol_in_strict(struct isl_sol *sol,
3631 struct isl_tab *tab, struct isl_vec *ineq)
3633 int empty;
3634 void *saved;
3636 if (!sol->context || sol->error)
3637 goto error;
3638 saved = sol->context->op->save(sol->context);
3640 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
3642 sol->context->op->add_ineq(sol->context, ineq->el, 1, 0);
3643 if (!sol->context)
3644 goto error;
3646 empty = tab->empty;
3647 tab->empty = 1;
3648 sol_add(sol, tab);
3649 tab->empty = empty;
3651 isl_int_add_ui(ineq->el[0], ineq->el[0], 1);
3653 sol->context->op->restore(sol->context, saved);
3654 return;
3655 error:
3656 sol->error = 1;
3659 /* Compute the lexicographic minimum of the set represented by the main
3660 * tableau "tab" within the context "sol->context_tab".
3661 * On entry the sample value of the main tableau is lexicographically
3662 * less than or equal to this lexicographic minimum.
3663 * Pivots are performed until a feasible point is found, which is then
3664 * necessarily equal to the minimum, or until the tableau is found to
3665 * be infeasible. Some pivots may need to be performed for only some
3666 * feasible values of the context tableau. If so, the context tableau
3667 * is split into a part where the pivot is needed and a part where it is not.
3669 * Whenever we enter the main loop, the main tableau is such that no
3670 * "obvious" pivots need to be performed on it, where "obvious" means
3671 * that the given row can be seen to be negative without looking at
3672 * the context tableau. In particular, for non-parametric problems,
3673 * no pivots need to be performed on the main tableau.
3674 * The caller of find_solutions is responsible for making this property
3675 * hold prior to the first iteration of the loop, while restore_lexmin
3676 * is called before every other iteration.
3678 * Inside the main loop, we first examine the signs of the rows of
3679 * the main tableau within the context of the context tableau.
3680 * If we find a row that is always non-positive for all values of
3681 * the parameters satisfying the context tableau and negative for at
3682 * least one value of the parameters, we perform the appropriate pivot
3683 * and start over. An exception is the case where no pivot can be
3684 * performed on the row. In this case, we require that the sign of
3685 * the row is negative for all values of the parameters (rather than just
3686 * non-positive). This special case is handled inside row_sign, which
3687 * will say that the row can have any sign if it determines that it can
3688 * attain both negative and zero values.
3690 * If we can't find a row that always requires a pivot, but we can find
3691 * one or more rows that require a pivot for some values of the parameters
3692 * (i.e., the row can attain both positive and negative signs), then we split
3693 * the context tableau into two parts, one where we force the sign to be
3694 * non-negative and one where we force is to be negative.
3695 * The non-negative part is handled by a recursive call (through find_in_pos).
3696 * Upon returning from this call, we continue with the negative part and
3697 * perform the required pivot.
3699 * If no such rows can be found, all rows are non-negative and we have
3700 * found a (rational) feasible point. If we only wanted a rational point
3701 * then we are done.
3702 * Otherwise, we check if all values of the sample point of the tableau
3703 * are integral for the variables. If so, we have found the minimal
3704 * integral point and we are done.
3705 * If the sample point is not integral, then we need to make a distinction
3706 * based on whether the constant term is non-integral or the coefficients
3707 * of the parameters. Furthermore, in order to decide how to handle
3708 * the non-integrality, we also need to know whether the coefficients
3709 * of the other columns in the tableau are integral. This leads
3710 * to the following table. The first two rows do not correspond
3711 * to a non-integral sample point and are only mentioned for completeness.
3713 * constant parameters other
3715 * int int int |
3716 * int int rat | -> no problem
3718 * rat int int -> fail
3720 * rat int rat -> cut
3722 * int rat rat |
3723 * rat rat rat | -> parametric cut
3725 * int rat int |
3726 * rat rat int | -> split context
3728 * If the parametric constant is completely integral, then there is nothing
3729 * to be done. If the constant term is non-integral, but all the other
3730 * coefficient are integral, then there is nothing that can be done
3731 * and the tableau has no integral solution.
3732 * If, on the other hand, one or more of the other columns have rational
3733 * coefficients, but the parameter coefficients are all integral, then
3734 * we can perform a regular (non-parametric) cut.
3735 * Finally, if there is any parameter coefficient that is non-integral,
3736 * then we need to involve the context tableau. There are two cases here.
3737 * If at least one other column has a rational coefficient, then we
3738 * can perform a parametric cut in the main tableau by adding a new
3739 * integer division in the context tableau.
3740 * If all other columns have integral coefficients, then we need to
3741 * enforce that the rational combination of parameters (c + \sum a_i y_i)/m
3742 * is always integral. We do this by introducing an integer division
3743 * q = floor((c + \sum a_i y_i)/m) and stipulating that its argument should
3744 * always be integral in the context tableau, i.e., m q = c + \sum a_i y_i.
3745 * Since q is expressed in the tableau as
3746 * c + \sum a_i y_i - m q >= 0
3747 * -c - \sum a_i y_i + m q + m - 1 >= 0
3748 * it is sufficient to add the inequality
3749 * -c - \sum a_i y_i + m q >= 0
3750 * In the part of the context where this inequality does not hold, the
3751 * main tableau is marked as being empty.
3753 static void find_solutions(struct isl_sol *sol, struct isl_tab *tab)
3755 struct isl_context *context;
3756 int r;
3758 if (!tab || sol->error)
3759 goto error;
3761 context = sol->context;
3763 if (tab->empty)
3764 goto done;
3765 if (context->op->is_empty(context))
3766 goto done;
3768 for (r = 0; r >= 0 && tab && !tab->empty; r = restore_lexmin(tab)) {
3769 int flags;
3770 int row;
3771 enum isl_tab_row_sign sgn;
3772 int split = -1;
3773 int n_split = 0;
3775 for (row = tab->n_redundant; row < tab->n_row; ++row) {
3776 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
3777 continue;
3778 sgn = row_sign(tab, sol, row);
3779 if (!sgn)
3780 goto error;
3781 tab->row_sign[row] = sgn;
3782 if (sgn == isl_tab_row_any)
3783 n_split++;
3784 if (sgn == isl_tab_row_any && split == -1)
3785 split = row;
3786 if (sgn == isl_tab_row_neg)
3787 break;
3789 if (row < tab->n_row)
3790 continue;
3791 if (split != -1) {
3792 struct isl_vec *ineq;
3793 if (n_split != 1)
3794 split = context->op->best_split(context, tab);
3795 if (split < 0)
3796 goto error;
3797 ineq = get_row_parameter_ineq(tab, split);
3798 if (!ineq)
3799 goto error;
3800 is_strict(ineq);
3801 for (row = tab->n_redundant; row < tab->n_row; ++row) {
3802 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
3803 continue;
3804 if (tab->row_sign[row] == isl_tab_row_any)
3805 tab->row_sign[row] = isl_tab_row_unknown;
3807 tab->row_sign[split] = isl_tab_row_pos;
3808 sol_inc_level(sol);
3809 find_in_pos(sol, tab, ineq->el);
3810 tab->row_sign[split] = isl_tab_row_neg;
3811 row = split;
3812 isl_seq_neg(ineq->el, ineq->el, ineq->size);
3813 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
3814 if (!sol->error)
3815 context->op->add_ineq(context, ineq->el, 0, 1);
3816 isl_vec_free(ineq);
3817 if (sol->error)
3818 goto error;
3819 continue;
3821 if (tab->rational)
3822 break;
3823 row = first_non_integer_row(tab, &flags);
3824 if (row < 0)
3825 break;
3826 if (ISL_FL_ISSET(flags, I_PAR)) {
3827 if (ISL_FL_ISSET(flags, I_VAR)) {
3828 if (isl_tab_mark_empty(tab) < 0)
3829 goto error;
3830 break;
3832 row = add_cut(tab, row);
3833 } else if (ISL_FL_ISSET(flags, I_VAR)) {
3834 struct isl_vec *div;
3835 struct isl_vec *ineq;
3836 int d;
3837 div = get_row_split_div(tab, row);
3838 if (!div)
3839 goto error;
3840 d = context->op->get_div(context, tab, div);
3841 isl_vec_free(div);
3842 if (d < 0)
3843 goto error;
3844 ineq = ineq_for_div(context->op->peek_basic_set(context), d);
3845 if (!ineq)
3846 goto error;
3847 sol_inc_level(sol);
3848 no_sol_in_strict(sol, tab, ineq);
3849 isl_seq_neg(ineq->el, ineq->el, ineq->size);
3850 context->op->add_ineq(context, ineq->el, 1, 1);
3851 isl_vec_free(ineq);
3852 if (sol->error || !context->op->is_ok(context))
3853 goto error;
3854 tab = set_row_cst_to_div(tab, row, d);
3855 if (context->op->is_empty(context))
3856 break;
3857 } else
3858 row = add_parametric_cut(tab, row, context);
3859 if (row < 0)
3860 goto error;
3862 if (r < 0)
3863 goto error;
3864 done:
3865 sol_add(sol, tab);
3866 isl_tab_free(tab);
3867 return;
3868 error:
3869 isl_tab_free(tab);
3870 sol->error = 1;
3873 /* Compute the lexicographic minimum of the set represented by the main
3874 * tableau "tab" within the context "sol->context_tab".
3876 * As a preprocessing step, we first transfer all the purely parametric
3877 * equalities from the main tableau to the context tableau, i.e.,
3878 * parameters that have been pivoted to a row.
3879 * These equalities are ignored by the main algorithm, because the
3880 * corresponding rows may not be marked as being non-negative.
3881 * In parts of the context where the added equality does not hold,
3882 * the main tableau is marked as being empty.
3884 static void find_solutions_main(struct isl_sol *sol, struct isl_tab *tab)
3886 int row;
3888 if (!tab)
3889 goto error;
3891 sol->level = 0;
3893 for (row = tab->n_redundant; row < tab->n_row; ++row) {
3894 int p;
3895 struct isl_vec *eq;
3897 if (tab->row_var[row] < 0)
3898 continue;
3899 if (tab->row_var[row] >= tab->n_param &&
3900 tab->row_var[row] < tab->n_var - tab->n_div)
3901 continue;
3902 if (tab->row_var[row] < tab->n_param)
3903 p = tab->row_var[row];
3904 else
3905 p = tab->row_var[row]
3906 + tab->n_param - (tab->n_var - tab->n_div);
3908 eq = isl_vec_alloc(tab->mat->ctx, 1+tab->n_param+tab->n_div);
3909 if (!eq)
3910 goto error;
3911 get_row_parameter_line(tab, row, eq->el);
3912 isl_int_neg(eq->el[1 + p], tab->mat->row[row][0]);
3913 eq = isl_vec_normalize(eq);
3915 sol_inc_level(sol);
3916 no_sol_in_strict(sol, tab, eq);
3918 isl_seq_neg(eq->el, eq->el, eq->size);
3919 sol_inc_level(sol);
3920 no_sol_in_strict(sol, tab, eq);
3921 isl_seq_neg(eq->el, eq->el, eq->size);
3923 sol->context->op->add_eq(sol->context, eq->el, 1, 1);
3925 isl_vec_free(eq);
3927 if (isl_tab_mark_redundant(tab, row) < 0)
3928 goto error;
3930 if (sol->context->op->is_empty(sol->context))
3931 break;
3933 row = tab->n_redundant - 1;
3936 find_solutions(sol, tab);
3938 sol->level = 0;
3939 sol_pop(sol);
3941 return;
3942 error:
3943 isl_tab_free(tab);
3944 sol->error = 1;
3947 /* Check if integer division "div" of "dom" also occurs in "bmap".
3948 * If so, return its position within the divs.
3949 * If not, return -1.
3951 static int find_context_div(struct isl_basic_map *bmap,
3952 struct isl_basic_set *dom, unsigned div)
3954 int i;
3955 unsigned b_dim = isl_space_dim(bmap->dim, isl_dim_all);
3956 unsigned d_dim = isl_space_dim(dom->dim, isl_dim_all);
3958 if (isl_int_is_zero(dom->div[div][0]))
3959 return -1;
3960 if (isl_seq_first_non_zero(dom->div[div] + 2 + d_dim, dom->n_div) != -1)
3961 return -1;
3963 for (i = 0; i < bmap->n_div; ++i) {
3964 if (isl_int_is_zero(bmap->div[i][0]))
3965 continue;
3966 if (isl_seq_first_non_zero(bmap->div[i] + 2 + d_dim,
3967 (b_dim - d_dim) + bmap->n_div) != -1)
3968 continue;
3969 if (isl_seq_eq(bmap->div[i], dom->div[div], 2 + d_dim))
3970 return i;
3972 return -1;
3975 /* The correspondence between the variables in the main tableau,
3976 * the context tableau, and the input map and domain is as follows.
3977 * The first n_param and the last n_div variables of the main tableau
3978 * form the variables of the context tableau.
3979 * In the basic map, these n_param variables correspond to the
3980 * parameters and the input dimensions. In the domain, they correspond
3981 * to the parameters and the set dimensions.
3982 * The n_div variables correspond to the integer divisions in the domain.
3983 * To ensure that everything lines up, we may need to copy some of the
3984 * integer divisions of the domain to the map. These have to be placed
3985 * in the same order as those in the context and they have to be placed
3986 * after any other integer divisions that the map may have.
3987 * This function performs the required reordering.
3989 static struct isl_basic_map *align_context_divs(struct isl_basic_map *bmap,
3990 struct isl_basic_set *dom)
3992 int i;
3993 int common = 0;
3994 int other;
3996 for (i = 0; i < dom->n_div; ++i)
3997 if (find_context_div(bmap, dom, i) != -1)
3998 common++;
3999 other = bmap->n_div - common;
4000 if (dom->n_div - common > 0) {
4001 bmap = isl_basic_map_extend_space(bmap, isl_space_copy(bmap->dim),
4002 dom->n_div - common, 0, 0);
4003 if (!bmap)
4004 return NULL;
4006 for (i = 0; i < dom->n_div; ++i) {
4007 int pos = find_context_div(bmap, dom, i);
4008 if (pos < 0) {
4009 pos = isl_basic_map_alloc_div(bmap);
4010 if (pos < 0)
4011 goto error;
4012 isl_int_set_si(bmap->div[pos][0], 0);
4014 if (pos != other + i)
4015 isl_basic_map_swap_div(bmap, pos, other + i);
4017 return bmap;
4018 error:
4019 isl_basic_map_free(bmap);
4020 return NULL;
4023 /* Base case of isl_tab_basic_map_partial_lexopt, after removing
4024 * some obvious symmetries.
4026 * We make sure the divs in the domain are properly ordered,
4027 * because they will be added one by one in the given order
4028 * during the construction of the solution map.
4030 static struct isl_sol *basic_map_partial_lexopt_base(
4031 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
4032 __isl_give isl_set **empty, int max,
4033 struct isl_sol *(*init)(__isl_keep isl_basic_map *bmap,
4034 __isl_take isl_basic_set *dom, int track_empty, int max))
4036 struct isl_tab *tab;
4037 struct isl_sol *sol = NULL;
4038 struct isl_context *context;
4040 if (dom->n_div) {
4041 dom = isl_basic_set_order_divs(dom);
4042 bmap = align_context_divs(bmap, dom);
4044 sol = init(bmap, dom, !!empty, max);
4045 if (!sol)
4046 goto error;
4048 context = sol->context;
4049 if (isl_basic_set_plain_is_empty(context->op->peek_basic_set(context)))
4050 /* nothing */;
4051 else if (isl_basic_map_plain_is_empty(bmap)) {
4052 if (sol->add_empty)
4053 sol->add_empty(sol,
4054 isl_basic_set_copy(context->op->peek_basic_set(context)));
4055 } else {
4056 tab = tab_for_lexmin(bmap,
4057 context->op->peek_basic_set(context), 1, max);
4058 tab = context->op->detect_nonnegative_parameters(context, tab);
4059 find_solutions_main(sol, tab);
4061 if (sol->error)
4062 goto error;
4064 isl_basic_map_free(bmap);
4065 return sol;
4066 error:
4067 sol_free(sol);
4068 isl_basic_map_free(bmap);
4069 return NULL;
4072 /* Base case of isl_tab_basic_map_partial_lexopt, after removing
4073 * some obvious symmetries.
4075 * We call basic_map_partial_lexopt_base and extract the results.
4077 static __isl_give isl_map *basic_map_partial_lexopt_base_map(
4078 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
4079 __isl_give isl_set **empty, int max)
4081 isl_map *result = NULL;
4082 struct isl_sol *sol;
4083 struct isl_sol_map *sol_map;
4085 sol = basic_map_partial_lexopt_base(bmap, dom, empty, max,
4086 &sol_map_init);
4087 if (!sol)
4088 return NULL;
4089 sol_map = (struct isl_sol_map *) sol;
4091 result = isl_map_copy(sol_map->map);
4092 if (empty)
4093 *empty = isl_set_copy(sol_map->empty);
4094 sol_free(&sol_map->sol);
4095 return result;
4098 /* Structure used during detection of parallel constraints.
4099 * n_in: number of "input" variables: isl_dim_param + isl_dim_in
4100 * n_out: number of "output" variables: isl_dim_out + isl_dim_div
4101 * val: the coefficients of the output variables
4103 struct isl_constraint_equal_info {
4104 isl_basic_map *bmap;
4105 unsigned n_in;
4106 unsigned n_out;
4107 isl_int *val;
4110 /* Check whether the coefficients of the output variables
4111 * of the constraint in "entry" are equal to info->val.
4113 static int constraint_equal(const void *entry, const void *val)
4115 isl_int **row = (isl_int **)entry;
4116 const struct isl_constraint_equal_info *info = val;
4118 return isl_seq_eq((*row) + 1 + info->n_in, info->val, info->n_out);
4121 /* Check whether "bmap" has a pair of constraints that have
4122 * the same coefficients for the output variables.
4123 * Note that the coefficients of the existentially quantified
4124 * variables need to be zero since the existentially quantified
4125 * of the result are usually not the same as those of the input.
4126 * the isl_dim_out and isl_dim_div dimensions.
4127 * If so, return 1 and return the row indices of the two constraints
4128 * in *first and *second.
4130 static int parallel_constraints(__isl_keep isl_basic_map *bmap,
4131 int *first, int *second)
4133 int i;
4134 isl_ctx *ctx = isl_basic_map_get_ctx(bmap);
4135 struct isl_hash_table *table = NULL;
4136 struct isl_hash_table_entry *entry;
4137 struct isl_constraint_equal_info info;
4138 unsigned n_out;
4139 unsigned n_div;
4141 ctx = isl_basic_map_get_ctx(bmap);
4142 table = isl_hash_table_alloc(ctx, bmap->n_ineq);
4143 if (!table)
4144 goto error;
4146 info.n_in = isl_basic_map_dim(bmap, isl_dim_param) +
4147 isl_basic_map_dim(bmap, isl_dim_in);
4148 info.bmap = bmap;
4149 n_out = isl_basic_map_dim(bmap, isl_dim_out);
4150 n_div = isl_basic_map_dim(bmap, isl_dim_div);
4151 info.n_out = n_out + n_div;
4152 for (i = 0; i < bmap->n_ineq; ++i) {
4153 uint32_t hash;
4155 info.val = bmap->ineq[i] + 1 + info.n_in;
4156 if (isl_seq_first_non_zero(info.val, n_out) < 0)
4157 continue;
4158 if (isl_seq_first_non_zero(info.val + n_out, n_div) >= 0)
4159 continue;
4160 hash = isl_seq_get_hash(info.val, info.n_out);
4161 entry = isl_hash_table_find(ctx, table, hash,
4162 constraint_equal, &info, 1);
4163 if (!entry)
4164 goto error;
4165 if (entry->data)
4166 break;
4167 entry->data = &bmap->ineq[i];
4170 if (i < bmap->n_ineq) {
4171 *first = ((isl_int **)entry->data) - bmap->ineq;
4172 *second = i;
4175 isl_hash_table_free(ctx, table);
4177 return i < bmap->n_ineq;
4178 error:
4179 isl_hash_table_free(ctx, table);
4180 return -1;
4183 /* Given a set of upper bounds in "var", add constraints to "bset"
4184 * that make the i-th bound smallest.
4186 * In particular, if there are n bounds b_i, then add the constraints
4188 * b_i <= b_j for j > i
4189 * b_i < b_j for j < i
4191 static __isl_give isl_basic_set *select_minimum(__isl_take isl_basic_set *bset,
4192 __isl_keep isl_mat *var, int i)
4194 isl_ctx *ctx;
4195 int j, k;
4197 ctx = isl_mat_get_ctx(var);
4199 for (j = 0; j < var->n_row; ++j) {
4200 if (j == i)
4201 continue;
4202 k = isl_basic_set_alloc_inequality(bset);
4203 if (k < 0)
4204 goto error;
4205 isl_seq_combine(bset->ineq[k], ctx->one, var->row[j],
4206 ctx->negone, var->row[i], var->n_col);
4207 isl_int_set_si(bset->ineq[k][var->n_col], 0);
4208 if (j < i)
4209 isl_int_sub_ui(bset->ineq[k][0], bset->ineq[k][0], 1);
4212 bset = isl_basic_set_finalize(bset);
4214 return bset;
4215 error:
4216 isl_basic_set_free(bset);
4217 return NULL;
4220 /* Given a set of upper bounds on the last "input" variable m,
4221 * construct a set that assigns the minimal upper bound to m, i.e.,
4222 * construct a set that divides the space into cells where one
4223 * of the upper bounds is smaller than all the others and assign
4224 * this upper bound to m.
4226 * In particular, if there are n bounds b_i, then the result
4227 * consists of n basic sets, each one of the form
4229 * m = b_i
4230 * b_i <= b_j for j > i
4231 * b_i < b_j for j < i
4233 static __isl_give isl_set *set_minimum(__isl_take isl_space *dim,
4234 __isl_take isl_mat *var)
4236 int i, k;
4237 isl_basic_set *bset = NULL;
4238 isl_ctx *ctx;
4239 isl_set *set = NULL;
4241 if (!dim || !var)
4242 goto error;
4244 ctx = isl_space_get_ctx(dim);
4245 set = isl_set_alloc_space(isl_space_copy(dim),
4246 var->n_row, ISL_SET_DISJOINT);
4248 for (i = 0; i < var->n_row; ++i) {
4249 bset = isl_basic_set_alloc_space(isl_space_copy(dim), 0,
4250 1, var->n_row - 1);
4251 k = isl_basic_set_alloc_equality(bset);
4252 if (k < 0)
4253 goto error;
4254 isl_seq_cpy(bset->eq[k], var->row[i], var->n_col);
4255 isl_int_set_si(bset->eq[k][var->n_col], -1);
4256 bset = select_minimum(bset, var, i);
4257 set = isl_set_add_basic_set(set, bset);
4260 isl_space_free(dim);
4261 isl_mat_free(var);
4262 return set;
4263 error:
4264 isl_basic_set_free(bset);
4265 isl_set_free(set);
4266 isl_space_free(dim);
4267 isl_mat_free(var);
4268 return NULL;
4271 /* Given that the last input variable of "bmap" represents the minimum
4272 * of the bounds in "cst", check whether we need to split the domain
4273 * based on which bound attains the minimum.
4275 * A split is needed when the minimum appears in an integer division
4276 * or in an equality. Otherwise, it is only needed if it appears in
4277 * an upper bound that is different from the upper bounds on which it
4278 * is defined.
4280 static int need_split_basic_map(__isl_keep isl_basic_map *bmap,
4281 __isl_keep isl_mat *cst)
4283 int i, j;
4284 unsigned total;
4285 unsigned pos;
4287 pos = cst->n_col - 1;
4288 total = isl_basic_map_dim(bmap, isl_dim_all);
4290 for (i = 0; i < bmap->n_div; ++i)
4291 if (!isl_int_is_zero(bmap->div[i][2 + pos]))
4292 return 1;
4294 for (i = 0; i < bmap->n_eq; ++i)
4295 if (!isl_int_is_zero(bmap->eq[i][1 + pos]))
4296 return 1;
4298 for (i = 0; i < bmap->n_ineq; ++i) {
4299 if (isl_int_is_nonneg(bmap->ineq[i][1 + pos]))
4300 continue;
4301 if (!isl_int_is_negone(bmap->ineq[i][1 + pos]))
4302 return 1;
4303 if (isl_seq_first_non_zero(bmap->ineq[i] + 1 + pos + 1,
4304 total - pos - 1) >= 0)
4305 return 1;
4307 for (j = 0; j < cst->n_row; ++j)
4308 if (isl_seq_eq(bmap->ineq[i], cst->row[j], cst->n_col))
4309 break;
4310 if (j >= cst->n_row)
4311 return 1;
4314 return 0;
4317 /* Given that the last set variable of "bset" represents the minimum
4318 * of the bounds in "cst", check whether we need to split the domain
4319 * based on which bound attains the minimum.
4321 * We simply call need_split_basic_map here. This is safe because
4322 * the position of the minimum is computed from "cst" and not
4323 * from "bmap".
4325 static int need_split_basic_set(__isl_keep isl_basic_set *bset,
4326 __isl_keep isl_mat *cst)
4328 return need_split_basic_map((isl_basic_map *)bset, cst);
4331 /* Given that the last set variable of "set" represents the minimum
4332 * of the bounds in "cst", check whether we need to split the domain
4333 * based on which bound attains the minimum.
4335 static int need_split_set(__isl_keep isl_set *set, __isl_keep isl_mat *cst)
4337 int i;
4339 for (i = 0; i < set->n; ++i)
4340 if (need_split_basic_set(set->p[i], cst))
4341 return 1;
4343 return 0;
4346 /* Given a set of which the last set variable is the minimum
4347 * of the bounds in "cst", split each basic set in the set
4348 * in pieces where one of the bounds is (strictly) smaller than the others.
4349 * This subdivision is given in "min_expr".
4350 * The variable is subsequently projected out.
4352 * We only do the split when it is needed.
4353 * For example if the last input variable m = min(a,b) and the only
4354 * constraints in the given basic set are lower bounds on m,
4355 * i.e., l <= m = min(a,b), then we can simply project out m
4356 * to obtain l <= a and l <= b, without having to split on whether
4357 * m is equal to a or b.
4359 static __isl_give isl_set *split(__isl_take isl_set *empty,
4360 __isl_take isl_set *min_expr, __isl_take isl_mat *cst)
4362 int n_in;
4363 int i;
4364 isl_space *dim;
4365 isl_set *res;
4367 if (!empty || !min_expr || !cst)
4368 goto error;
4370 n_in = isl_set_dim(empty, isl_dim_set);
4371 dim = isl_set_get_space(empty);
4372 dim = isl_space_drop_dims(dim, isl_dim_set, n_in - 1, 1);
4373 res = isl_set_empty(dim);
4375 for (i = 0; i < empty->n; ++i) {
4376 isl_set *set;
4378 set = isl_set_from_basic_set(isl_basic_set_copy(empty->p[i]));
4379 if (need_split_basic_set(empty->p[i], cst))
4380 set = isl_set_intersect(set, isl_set_copy(min_expr));
4381 set = isl_set_remove_dims(set, isl_dim_set, n_in - 1, 1);
4383 res = isl_set_union_disjoint(res, set);
4386 isl_set_free(empty);
4387 isl_set_free(min_expr);
4388 isl_mat_free(cst);
4389 return res;
4390 error:
4391 isl_set_free(empty);
4392 isl_set_free(min_expr);
4393 isl_mat_free(cst);
4394 return NULL;
4397 /* Given a map of which the last input variable is the minimum
4398 * of the bounds in "cst", split each basic set in the set
4399 * in pieces where one of the bounds is (strictly) smaller than the others.
4400 * This subdivision is given in "min_expr".
4401 * The variable is subsequently projected out.
4403 * The implementation is essentially the same as that of "split".
4405 static __isl_give isl_map *split_domain(__isl_take isl_map *opt,
4406 __isl_take isl_set *min_expr, __isl_take isl_mat *cst)
4408 int n_in;
4409 int i;
4410 isl_space *dim;
4411 isl_map *res;
4413 if (!opt || !min_expr || !cst)
4414 goto error;
4416 n_in = isl_map_dim(opt, isl_dim_in);
4417 dim = isl_map_get_space(opt);
4418 dim = isl_space_drop_dims(dim, isl_dim_in, n_in - 1, 1);
4419 res = isl_map_empty(dim);
4421 for (i = 0; i < opt->n; ++i) {
4422 isl_map *map;
4424 map = isl_map_from_basic_map(isl_basic_map_copy(opt->p[i]));
4425 if (need_split_basic_map(opt->p[i], cst))
4426 map = isl_map_intersect_domain(map,
4427 isl_set_copy(min_expr));
4428 map = isl_map_remove_dims(map, isl_dim_in, n_in - 1, 1);
4430 res = isl_map_union_disjoint(res, map);
4433 isl_map_free(opt);
4434 isl_set_free(min_expr);
4435 isl_mat_free(cst);
4436 return res;
4437 error:
4438 isl_map_free(opt);
4439 isl_set_free(min_expr);
4440 isl_mat_free(cst);
4441 return NULL;
4444 static __isl_give isl_map *basic_map_partial_lexopt(
4445 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
4446 __isl_give isl_set **empty, int max);
4448 union isl_lex_res {
4449 void *p;
4450 isl_map *map;
4451 isl_pw_multi_aff *pma;
4454 /* This function is called from basic_map_partial_lexopt_symm.
4455 * The last variable of "bmap" and "dom" corresponds to the minimum
4456 * of the bounds in "cst". "map_space" is the space of the original
4457 * input relation (of basic_map_partial_lexopt_symm) and "set_space"
4458 * is the space of the original domain.
4460 * We recursively call basic_map_partial_lexopt and then plug in
4461 * the definition of the minimum in the result.
4463 static __isl_give union isl_lex_res basic_map_partial_lexopt_symm_map_core(
4464 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
4465 __isl_give isl_set **empty, int max, __isl_take isl_mat *cst,
4466 __isl_take isl_space *map_space, __isl_take isl_space *set_space)
4468 isl_map *opt;
4469 isl_set *min_expr;
4470 union isl_lex_res res;
4472 min_expr = set_minimum(isl_basic_set_get_space(dom), isl_mat_copy(cst));
4474 opt = basic_map_partial_lexopt(bmap, dom, empty, max);
4476 if (empty) {
4477 *empty = split(*empty,
4478 isl_set_copy(min_expr), isl_mat_copy(cst));
4479 *empty = isl_set_reset_space(*empty, set_space);
4482 opt = split_domain(opt, min_expr, cst);
4483 opt = isl_map_reset_space(opt, map_space);
4485 res.map = opt;
4486 return res;
4489 /* Given a basic map with at least two parallel constraints (as found
4490 * by the function parallel_constraints), first look for more constraints
4491 * parallel to the two constraint and replace the found list of parallel
4492 * constraints by a single constraint with as "input" part the minimum
4493 * of the input parts of the list of constraints. Then, recursively call
4494 * basic_map_partial_lexopt (possibly finding more parallel constraints)
4495 * and plug in the definition of the minimum in the result.
4497 * More specifically, given a set of constraints
4499 * a x + b_i(p) >= 0
4501 * Replace this set by a single constraint
4503 * a x + u >= 0
4505 * with u a new parameter with constraints
4507 * u <= b_i(p)
4509 * Any solution to the new system is also a solution for the original system
4510 * since
4512 * a x >= -u >= -b_i(p)
4514 * Moreover, m = min_i(b_i(p)) satisfies the constraints on u and can
4515 * therefore be plugged into the solution.
4517 static union isl_lex_res basic_map_partial_lexopt_symm(
4518 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
4519 __isl_give isl_set **empty, int max, int first, int second,
4520 __isl_give union isl_lex_res (*core)(__isl_take isl_basic_map *bmap,
4521 __isl_take isl_basic_set *dom,
4522 __isl_give isl_set **empty,
4523 int max, __isl_take isl_mat *cst,
4524 __isl_take isl_space *map_space,
4525 __isl_take isl_space *set_space))
4527 int i, n, k;
4528 int *list = NULL;
4529 unsigned n_in, n_out, n_div;
4530 isl_ctx *ctx;
4531 isl_vec *var = NULL;
4532 isl_mat *cst = NULL;
4533 isl_space *map_space, *set_space;
4534 union isl_lex_res res;
4536 map_space = isl_basic_map_get_space(bmap);
4537 set_space = empty ? isl_basic_set_get_space(dom) : NULL;
4539 n_in = isl_basic_map_dim(bmap, isl_dim_param) +
4540 isl_basic_map_dim(bmap, isl_dim_in);
4541 n_out = isl_basic_map_dim(bmap, isl_dim_all) - n_in;
4543 ctx = isl_basic_map_get_ctx(bmap);
4544 list = isl_alloc_array(ctx, int, bmap->n_ineq);
4545 var = isl_vec_alloc(ctx, n_out);
4546 if (!list || !var)
4547 goto error;
4549 list[0] = first;
4550 list[1] = second;
4551 isl_seq_cpy(var->el, bmap->ineq[first] + 1 + n_in, n_out);
4552 for (i = second + 1, n = 2; i < bmap->n_ineq; ++i) {
4553 if (isl_seq_eq(var->el, bmap->ineq[i] + 1 + n_in, n_out))
4554 list[n++] = i;
4557 cst = isl_mat_alloc(ctx, n, 1 + n_in);
4558 if (!cst)
4559 goto error;
4561 for (i = 0; i < n; ++i)
4562 isl_seq_cpy(cst->row[i], bmap->ineq[list[i]], 1 + n_in);
4564 bmap = isl_basic_map_cow(bmap);
4565 if (!bmap)
4566 goto error;
4567 for (i = n - 1; i >= 0; --i)
4568 if (isl_basic_map_drop_inequality(bmap, list[i]) < 0)
4569 goto error;
4571 bmap = isl_basic_map_add(bmap, isl_dim_in, 1);
4572 bmap = isl_basic_map_extend_constraints(bmap, 0, 1);
4573 k = isl_basic_map_alloc_inequality(bmap);
4574 if (k < 0)
4575 goto error;
4576 isl_seq_clr(bmap->ineq[k], 1 + n_in);
4577 isl_int_set_si(bmap->ineq[k][1 + n_in], 1);
4578 isl_seq_cpy(bmap->ineq[k] + 1 + n_in + 1, var->el, n_out);
4579 bmap = isl_basic_map_finalize(bmap);
4581 n_div = isl_basic_set_dim(dom, isl_dim_div);
4582 dom = isl_basic_set_add_dims(dom, isl_dim_set, 1);
4583 dom = isl_basic_set_extend_constraints(dom, 0, n);
4584 for (i = 0; i < n; ++i) {
4585 k = isl_basic_set_alloc_inequality(dom);
4586 if (k < 0)
4587 goto error;
4588 isl_seq_cpy(dom->ineq[k], cst->row[i], 1 + n_in);
4589 isl_int_set_si(dom->ineq[k][1 + n_in], -1);
4590 isl_seq_clr(dom->ineq[k] + 1 + n_in + 1, n_div);
4593 isl_vec_free(var);
4594 free(list);
4596 return core(bmap, dom, empty, max, cst, map_space, set_space);
4597 error:
4598 isl_space_free(map_space);
4599 isl_space_free(set_space);
4600 isl_mat_free(cst);
4601 isl_vec_free(var);
4602 free(list);
4603 isl_basic_set_free(dom);
4604 isl_basic_map_free(bmap);
4605 res.p = NULL;
4606 return res;
4609 static __isl_give isl_map *basic_map_partial_lexopt_symm_map(
4610 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
4611 __isl_give isl_set **empty, int max, int first, int second)
4613 return basic_map_partial_lexopt_symm(bmap, dom, empty, max,
4614 first, second, &basic_map_partial_lexopt_symm_map_core).map;
4617 /* Recursive part of isl_tab_basic_map_partial_lexopt, after detecting
4618 * equalities and removing redundant constraints.
4620 * We first check if there are any parallel constraints (left).
4621 * If not, we are in the base case.
4622 * If there are parallel constraints, we replace them by a single
4623 * constraint in basic_map_partial_lexopt_symm and then call
4624 * this function recursively to look for more parallel constraints.
4626 static __isl_give isl_map *basic_map_partial_lexopt(
4627 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
4628 __isl_give isl_set **empty, int max)
4630 int par = 0;
4631 int first, second;
4633 if (!bmap)
4634 goto error;
4636 if (bmap->ctx->opt->pip_symmetry)
4637 par = parallel_constraints(bmap, &first, &second);
4638 if (par < 0)
4639 goto error;
4640 if (!par)
4641 return basic_map_partial_lexopt_base_map(bmap, dom, empty, max);
4643 return basic_map_partial_lexopt_symm_map(bmap, dom, empty, max,
4644 first, second);
4645 error:
4646 isl_basic_set_free(dom);
4647 isl_basic_map_free(bmap);
4648 return NULL;
4651 /* Compute the lexicographic minimum (or maximum if "max" is set)
4652 * of "bmap" over the domain "dom" and return the result as a map.
4653 * If "empty" is not NULL, then *empty is assigned a set that
4654 * contains those parts of the domain where there is no solution.
4655 * If "bmap" is marked as rational (ISL_BASIC_MAP_RATIONAL),
4656 * then we compute the rational optimum. Otherwise, we compute
4657 * the integral optimum.
4659 * We perform some preprocessing. As the PILP solver does not
4660 * handle implicit equalities very well, we first make sure all
4661 * the equalities are explicitly available.
4663 * We also add context constraints to the basic map and remove
4664 * redundant constraints. This is only needed because of the
4665 * way we handle simple symmetries. In particular, we currently look
4666 * for symmetries on the constraints, before we set up the main tableau.
4667 * It is then no good to look for symmetries on possibly redundant constraints.
4669 struct isl_map *isl_tab_basic_map_partial_lexopt(
4670 struct isl_basic_map *bmap, struct isl_basic_set *dom,
4671 struct isl_set **empty, int max)
4673 if (empty)
4674 *empty = NULL;
4675 if (!bmap || !dom)
4676 goto error;
4678 isl_assert(bmap->ctx,
4679 isl_basic_map_compatible_domain(bmap, dom), goto error);
4681 if (isl_basic_set_dim(dom, isl_dim_all) == 0)
4682 return basic_map_partial_lexopt(bmap, dom, empty, max);
4684 bmap = isl_basic_map_intersect_domain(bmap, isl_basic_set_copy(dom));
4685 bmap = isl_basic_map_detect_equalities(bmap);
4686 bmap = isl_basic_map_remove_redundancies(bmap);
4688 return basic_map_partial_lexopt(bmap, dom, empty, max);
4689 error:
4690 isl_basic_set_free(dom);
4691 isl_basic_map_free(bmap);
4692 return NULL;
4695 struct isl_sol_for {
4696 struct isl_sol sol;
4697 int (*fn)(__isl_take isl_basic_set *dom,
4698 __isl_take isl_aff_list *list, void *user);
4699 void *user;
4702 static void sol_for_free(struct isl_sol_for *sol_for)
4704 if (sol_for->sol.context)
4705 sol_for->sol.context->op->free(sol_for->sol.context);
4706 free(sol_for);
4709 static void sol_for_free_wrap(struct isl_sol *sol)
4711 sol_for_free((struct isl_sol_for *)sol);
4714 /* Add the solution identified by the tableau and the context tableau.
4716 * See documentation of sol_add for more details.
4718 * Instead of constructing a basic map, this function calls a user
4719 * defined function with the current context as a basic set and
4720 * a list of affine expressions representing the relation between
4721 * the input and output. The space over which the affine expressions
4722 * are defined is the same as that of the domain. The number of
4723 * affine expressions in the list is equal to the number of output variables.
4725 static void sol_for_add(struct isl_sol_for *sol,
4726 struct isl_basic_set *dom, struct isl_mat *M)
4728 int i;
4729 isl_ctx *ctx;
4730 isl_local_space *ls;
4731 isl_aff *aff;
4732 isl_aff_list *list;
4734 if (sol->sol.error || !dom || !M)
4735 goto error;
4737 ctx = isl_basic_set_get_ctx(dom);
4738 ls = isl_basic_set_get_local_space(dom);
4739 list = isl_aff_list_alloc(ctx, M->n_row - 1);
4740 for (i = 1; i < M->n_row; ++i) {
4741 aff = isl_aff_alloc(isl_local_space_copy(ls));
4742 if (aff) {
4743 isl_int_set(aff->v->el[0], M->row[0][0]);
4744 isl_seq_cpy(aff->v->el + 1, M->row[i], M->n_col);
4746 aff = isl_aff_normalize(aff);
4747 list = isl_aff_list_add(list, aff);
4749 isl_local_space_free(ls);
4751 dom = isl_basic_set_finalize(dom);
4753 if (sol->fn(isl_basic_set_copy(dom), list, sol->user) < 0)
4754 goto error;
4756 isl_basic_set_free(dom);
4757 isl_mat_free(M);
4758 return;
4759 error:
4760 isl_basic_set_free(dom);
4761 isl_mat_free(M);
4762 sol->sol.error = 1;
4765 static void sol_for_add_wrap(struct isl_sol *sol,
4766 struct isl_basic_set *dom, struct isl_mat *M)
4768 sol_for_add((struct isl_sol_for *)sol, dom, M);
4771 static struct isl_sol_for *sol_for_init(struct isl_basic_map *bmap, int max,
4772 int (*fn)(__isl_take isl_basic_set *dom, __isl_take isl_aff_list *list,
4773 void *user),
4774 void *user)
4776 struct isl_sol_for *sol_for = NULL;
4777 isl_space *dom_dim;
4778 struct isl_basic_set *dom = NULL;
4780 sol_for = isl_calloc_type(bmap->ctx, struct isl_sol_for);
4781 if (!sol_for)
4782 goto error;
4784 dom_dim = isl_space_domain(isl_space_copy(bmap->dim));
4785 dom = isl_basic_set_universe(dom_dim);
4787 sol_for->sol.rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
4788 sol_for->sol.dec_level.callback.run = &sol_dec_level_wrap;
4789 sol_for->sol.dec_level.sol = &sol_for->sol;
4790 sol_for->fn = fn;
4791 sol_for->user = user;
4792 sol_for->sol.max = max;
4793 sol_for->sol.n_out = isl_basic_map_dim(bmap, isl_dim_out);
4794 sol_for->sol.add = &sol_for_add_wrap;
4795 sol_for->sol.add_empty = NULL;
4796 sol_for->sol.free = &sol_for_free_wrap;
4798 sol_for->sol.context = isl_context_alloc(dom);
4799 if (!sol_for->sol.context)
4800 goto error;
4802 isl_basic_set_free(dom);
4803 return sol_for;
4804 error:
4805 isl_basic_set_free(dom);
4806 sol_for_free(sol_for);
4807 return NULL;
4810 static void sol_for_find_solutions(struct isl_sol_for *sol_for,
4811 struct isl_tab *tab)
4813 find_solutions_main(&sol_for->sol, tab);
4816 int isl_basic_map_foreach_lexopt(__isl_keep isl_basic_map *bmap, int max,
4817 int (*fn)(__isl_take isl_basic_set *dom, __isl_take isl_aff_list *list,
4818 void *user),
4819 void *user)
4821 struct isl_sol_for *sol_for = NULL;
4823 bmap = isl_basic_map_copy(bmap);
4824 bmap = isl_basic_map_detect_equalities(bmap);
4825 if (!bmap)
4826 return -1;
4828 sol_for = sol_for_init(bmap, max, fn, user);
4829 if (!sol_for)
4830 goto error;
4832 if (isl_basic_map_plain_is_empty(bmap))
4833 /* nothing */;
4834 else {
4835 struct isl_tab *tab;
4836 struct isl_context *context = sol_for->sol.context;
4837 tab = tab_for_lexmin(bmap,
4838 context->op->peek_basic_set(context), 1, max);
4839 tab = context->op->detect_nonnegative_parameters(context, tab);
4840 sol_for_find_solutions(sol_for, tab);
4841 if (sol_for->sol.error)
4842 goto error;
4845 sol_free(&sol_for->sol);
4846 isl_basic_map_free(bmap);
4847 return 0;
4848 error:
4849 sol_free(&sol_for->sol);
4850 isl_basic_map_free(bmap);
4851 return -1;
4854 int isl_basic_set_foreach_lexopt(__isl_keep isl_basic_set *bset, int max,
4855 int (*fn)(__isl_take isl_basic_set *dom, __isl_take isl_aff_list *list,
4856 void *user),
4857 void *user)
4859 return isl_basic_map_foreach_lexopt(bset, max, fn, user);
4862 /* Check if the given sequence of len variables starting at pos
4863 * represents a trivial (i.e., zero) solution.
4864 * The variables are assumed to be non-negative and to come in pairs,
4865 * with each pair representing a variable of unrestricted sign.
4866 * The solution is trivial if each such pair in the sequence consists
4867 * of two identical values, meaning that the variable being represented
4868 * has value zero.
4870 static int region_is_trivial(struct isl_tab *tab, int pos, int len)
4872 int i;
4874 if (len == 0)
4875 return 0;
4877 for (i = 0; i < len; i += 2) {
4878 int neg_row;
4879 int pos_row;
4881 neg_row = tab->var[pos + i].is_row ?
4882 tab->var[pos + i].index : -1;
4883 pos_row = tab->var[pos + i + 1].is_row ?
4884 tab->var[pos + i + 1].index : -1;
4886 if ((neg_row < 0 ||
4887 isl_int_is_zero(tab->mat->row[neg_row][1])) &&
4888 (pos_row < 0 ||
4889 isl_int_is_zero(tab->mat->row[pos_row][1])))
4890 continue;
4892 if (neg_row < 0 || pos_row < 0)
4893 return 0;
4894 if (isl_int_ne(tab->mat->row[neg_row][1],
4895 tab->mat->row[pos_row][1]))
4896 return 0;
4899 return 1;
4902 /* Return the index of the first trivial region or -1 if all regions
4903 * are non-trivial.
4905 static int first_trivial_region(struct isl_tab *tab,
4906 int n_region, struct isl_region *region)
4908 int i;
4910 for (i = 0; i < n_region; ++i) {
4911 if (region_is_trivial(tab, region[i].pos, region[i].len))
4912 return i;
4915 return -1;
4918 /* Check if the solution is optimal, i.e., whether the first
4919 * n_op entries are zero.
4921 static int is_optimal(__isl_keep isl_vec *sol, int n_op)
4923 int i;
4925 for (i = 0; i < n_op; ++i)
4926 if (!isl_int_is_zero(sol->el[1 + i]))
4927 return 0;
4928 return 1;
4931 /* Add constraints to "tab" that ensure that any solution is significantly
4932 * better that that represented by "sol". That is, find the first
4933 * relevant (within first n_op) non-zero coefficient and force it (along
4934 * with all previous coefficients) to be zero.
4935 * If the solution is already optimal (all relevant coefficients are zero),
4936 * then just mark the table as empty.
4938 static int force_better_solution(struct isl_tab *tab,
4939 __isl_keep isl_vec *sol, int n_op)
4941 int i;
4942 isl_ctx *ctx;
4943 isl_vec *v = NULL;
4945 if (!sol)
4946 return -1;
4948 for (i = 0; i < n_op; ++i)
4949 if (!isl_int_is_zero(sol->el[1 + i]))
4950 break;
4952 if (i == n_op) {
4953 if (isl_tab_mark_empty(tab) < 0)
4954 return -1;
4955 return 0;
4958 ctx = isl_vec_get_ctx(sol);
4959 v = isl_vec_alloc(ctx, 1 + tab->n_var);
4960 if (!v)
4961 return -1;
4963 for (; i >= 0; --i) {
4964 v = isl_vec_clr(v);
4965 isl_int_set_si(v->el[1 + i], -1);
4966 if (add_lexmin_eq(tab, v->el) < 0)
4967 goto error;
4970 isl_vec_free(v);
4971 return 0;
4972 error:
4973 isl_vec_free(v);
4974 return -1;
4977 struct isl_trivial {
4978 int update;
4979 int region;
4980 int side;
4981 struct isl_tab_undo *snap;
4984 /* Return the lexicographically smallest non-trivial solution of the
4985 * given ILP problem.
4987 * All variables are assumed to be non-negative.
4989 * n_op is the number of initial coordinates to optimize.
4990 * That is, once a solution has been found, we will only continue looking
4991 * for solution that result in significantly better values for those
4992 * initial coordinates. That is, we only continue looking for solutions
4993 * that increase the number of initial zeros in this sequence.
4995 * A solution is non-trivial, if it is non-trivial on each of the
4996 * specified regions. Each region represents a sequence of pairs
4997 * of variables. A solution is non-trivial on such a region if
4998 * at least one of these pairs consists of different values, i.e.,
4999 * such that the non-negative variable represented by the pair is non-zero.
5001 * Whenever a conflict is encountered, all constraints involved are
5002 * reported to the caller through a call to "conflict".
5004 * We perform a simple branch-and-bound backtracking search.
5005 * Each level in the search represents initially trivial region that is forced
5006 * to be non-trivial.
5007 * At each level we consider n cases, where n is the length of the region.
5008 * In terms of the n/2 variables of unrestricted signs being encoded by
5009 * the region, we consider the cases
5010 * x_0 >= 1
5011 * x_0 <= -1
5012 * x_0 = 0 and x_1 >= 1
5013 * x_0 = 0 and x_1 <= -1
5014 * x_0 = 0 and x_1 = 0 and x_2 >= 1
5015 * x_0 = 0 and x_1 = 0 and x_2 <= -1
5016 * ...
5017 * The cases are considered in this order, assuming that each pair
5018 * x_i_a x_i_b represents the value x_i_b - x_i_a.
5019 * That is, x_0 >= 1 is enforced by adding the constraint
5020 * x_0_b - x_0_a >= 1
5022 __isl_give isl_vec *isl_tab_basic_set_non_trivial_lexmin(
5023 __isl_take isl_basic_set *bset, int n_op, int n_region,
5024 struct isl_region *region,
5025 int (*conflict)(int con, void *user), void *user)
5027 int i, j;
5028 int r;
5029 isl_ctx *ctx;
5030 isl_vec *v = NULL;
5031 isl_vec *sol = NULL;
5032 struct isl_tab *tab;
5033 struct isl_trivial *triv = NULL;
5034 int level, init;
5036 if (!bset)
5037 return NULL;
5039 ctx = isl_basic_set_get_ctx(bset);
5040 sol = isl_vec_alloc(ctx, 0);
5042 tab = tab_for_lexmin(bset, NULL, 0, 0);
5043 if (!tab)
5044 goto error;
5045 tab->conflict = conflict;
5046 tab->conflict_user = user;
5048 v = isl_vec_alloc(ctx, 1 + tab->n_var);
5049 triv = isl_calloc_array(ctx, struct isl_trivial, n_region);
5050 if (!v || !triv)
5051 goto error;
5053 level = 0;
5054 init = 1;
5056 while (level >= 0) {
5057 int side, base;
5059 if (init) {
5060 tab = cut_to_integer_lexmin(tab, CUT_ONE);
5061 if (!tab)
5062 goto error;
5063 if (tab->empty)
5064 goto backtrack;
5065 r = first_trivial_region(tab, n_region, region);
5066 if (r < 0) {
5067 for (i = 0; i < level; ++i)
5068 triv[i].update = 1;
5069 isl_vec_free(sol);
5070 sol = isl_tab_get_sample_value(tab);
5071 if (!sol)
5072 goto error;
5073 if (is_optimal(sol, n_op))
5074 break;
5075 goto backtrack;
5077 if (level >= n_region)
5078 isl_die(ctx, isl_error_internal,
5079 "nesting level too deep", goto error);
5080 if (isl_tab_extend_cons(tab,
5081 2 * region[r].len + 2 * n_op) < 0)
5082 goto error;
5083 triv[level].region = r;
5084 triv[level].side = 0;
5087 r = triv[level].region;
5088 side = triv[level].side;
5089 base = 2 * (side/2);
5091 if (side >= region[r].len) {
5092 backtrack:
5093 level--;
5094 init = 0;
5095 if (level >= 0)
5096 if (isl_tab_rollback(tab, triv[level].snap) < 0)
5097 goto error;
5098 continue;
5101 if (triv[level].update) {
5102 if (force_better_solution(tab, sol, n_op) < 0)
5103 goto error;
5104 triv[level].update = 0;
5107 if (side == base && base >= 2) {
5108 for (j = base - 2; j < base; ++j) {
5109 v = isl_vec_clr(v);
5110 isl_int_set_si(v->el[1 + region[r].pos + j], 1);
5111 if (add_lexmin_eq(tab, v->el) < 0)
5112 goto error;
5116 triv[level].snap = isl_tab_snap(tab);
5117 if (isl_tab_push_basis(tab) < 0)
5118 goto error;
5120 v = isl_vec_clr(v);
5121 isl_int_set_si(v->el[0], -1);
5122 isl_int_set_si(v->el[1 + region[r].pos + side], -1);
5123 isl_int_set_si(v->el[1 + region[r].pos + (side ^ 1)], 1);
5124 tab = add_lexmin_ineq(tab, v->el);
5126 triv[level].side++;
5127 level++;
5128 init = 1;
5131 free(triv);
5132 isl_vec_free(v);
5133 isl_tab_free(tab);
5134 isl_basic_set_free(bset);
5136 return sol;
5137 error:
5138 free(triv);
5139 isl_vec_free(v);
5140 isl_tab_free(tab);
5141 isl_basic_set_free(bset);
5142 isl_vec_free(sol);
5143 return NULL;
5146 /* Return the lexicographically smallest rational point in "bset",
5147 * assuming that all variables are non-negative.
5148 * If "bset" is empty, then return a zero-length vector.
5150 __isl_give isl_vec *isl_tab_basic_set_non_neg_lexmin(
5151 __isl_take isl_basic_set *bset)
5153 struct isl_tab *tab;
5154 isl_ctx *ctx = isl_basic_set_get_ctx(bset);
5155 isl_vec *sol;
5157 if (!bset)
5158 return NULL;
5160 tab = tab_for_lexmin(bset, NULL, 0, 0);
5161 if (!tab)
5162 goto error;
5163 if (tab->empty)
5164 sol = isl_vec_alloc(ctx, 0);
5165 else
5166 sol = isl_tab_get_sample_value(tab);
5167 isl_tab_free(tab);
5168 isl_basic_set_free(bset);
5169 return sol;
5170 error:
5171 isl_tab_free(tab);
5172 isl_basic_set_free(bset);
5173 return NULL;
5176 struct isl_sol_pma {
5177 struct isl_sol sol;
5178 isl_pw_multi_aff *pma;
5179 isl_set *empty;
5182 static void sol_pma_free(struct isl_sol_pma *sol_pma)
5184 if (!sol_pma)
5185 return;
5186 if (sol_pma->sol.context)
5187 sol_pma->sol.context->op->free(sol_pma->sol.context);
5188 isl_pw_multi_aff_free(sol_pma->pma);
5189 isl_set_free(sol_pma->empty);
5190 free(sol_pma);
5193 /* This function is called for parts of the context where there is
5194 * no solution, with "bset" corresponding to the context tableau.
5195 * Simply add the basic set to the set "empty".
5197 static void sol_pma_add_empty(struct isl_sol_pma *sol,
5198 __isl_take isl_basic_set *bset)
5200 if (!bset)
5201 goto error;
5202 isl_assert(bset->ctx, sol->empty, goto error);
5204 sol->empty = isl_set_grow(sol->empty, 1);
5205 bset = isl_basic_set_simplify(bset);
5206 bset = isl_basic_set_finalize(bset);
5207 sol->empty = isl_set_add_basic_set(sol->empty, bset);
5208 if (!sol->empty)
5209 sol->sol.error = 1;
5210 return;
5211 error:
5212 isl_basic_set_free(bset);
5213 sol->sol.error = 1;
5216 /* Given a basic map "dom" that represents the context and an affine
5217 * matrix "M" that maps the dimensions of the context to the
5218 * output variables, construct an isl_pw_multi_aff with a single
5219 * cell corresponding to "dom" and affine expressions copied from "M".
5221 static void sol_pma_add(struct isl_sol_pma *sol,
5222 __isl_take isl_basic_set *dom, __isl_take isl_mat *M)
5224 int i;
5225 isl_local_space *ls;
5226 isl_aff *aff;
5227 isl_multi_aff *maff;
5228 isl_pw_multi_aff *pma;
5230 maff = isl_multi_aff_alloc(isl_pw_multi_aff_get_space(sol->pma));
5231 ls = isl_basic_set_get_local_space(dom);
5232 for (i = 1; i < M->n_row; ++i) {
5233 aff = isl_aff_alloc(isl_local_space_copy(ls));
5234 if (aff) {
5235 isl_int_set(aff->v->el[0], M->row[0][0]);
5236 isl_seq_cpy(aff->v->el + 1, M->row[i], M->n_col);
5238 aff = isl_aff_normalize(aff);
5239 maff = isl_multi_aff_set_aff(maff, i - 1, aff);
5241 isl_local_space_free(ls);
5242 isl_mat_free(M);
5243 dom = isl_basic_set_simplify(dom);
5244 dom = isl_basic_set_finalize(dom);
5245 pma = isl_pw_multi_aff_alloc(isl_set_from_basic_set(dom), maff);
5246 sol->pma = isl_pw_multi_aff_add_disjoint(sol->pma, pma);
5247 if (!sol->pma)
5248 sol->sol.error = 1;
5251 static void sol_pma_free_wrap(struct isl_sol *sol)
5253 sol_pma_free((struct isl_sol_pma *)sol);
5256 static void sol_pma_add_empty_wrap(struct isl_sol *sol,
5257 __isl_take isl_basic_set *bset)
5259 sol_pma_add_empty((struct isl_sol_pma *)sol, bset);
5262 static void sol_pma_add_wrap(struct isl_sol *sol,
5263 __isl_take isl_basic_set *dom, __isl_take isl_mat *M)
5265 sol_pma_add((struct isl_sol_pma *)sol, dom, M);
5268 /* Construct an isl_sol_pma structure for accumulating the solution.
5269 * If track_empty is set, then we also keep track of the parts
5270 * of the context where there is no solution.
5271 * If max is set, then we are solving a maximization, rather than
5272 * a minimization problem, which means that the variables in the
5273 * tableau have value "M - x" rather than "M + x".
5275 static struct isl_sol *sol_pma_init(__isl_keep isl_basic_map *bmap,
5276 __isl_take isl_basic_set *dom, int track_empty, int max)
5278 struct isl_sol_pma *sol_pma = NULL;
5280 if (!bmap)
5281 goto error;
5283 sol_pma = isl_calloc_type(bmap->ctx, struct isl_sol_pma);
5284 if (!sol_pma)
5285 goto error;
5287 sol_pma->sol.rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
5288 sol_pma->sol.dec_level.callback.run = &sol_dec_level_wrap;
5289 sol_pma->sol.dec_level.sol = &sol_pma->sol;
5290 sol_pma->sol.max = max;
5291 sol_pma->sol.n_out = isl_basic_map_dim(bmap, isl_dim_out);
5292 sol_pma->sol.add = &sol_pma_add_wrap;
5293 sol_pma->sol.add_empty = track_empty ? &sol_pma_add_empty_wrap : NULL;
5294 sol_pma->sol.free = &sol_pma_free_wrap;
5295 sol_pma->pma = isl_pw_multi_aff_empty(isl_basic_map_get_space(bmap));
5296 if (!sol_pma->pma)
5297 goto error;
5299 sol_pma->sol.context = isl_context_alloc(dom);
5300 if (!sol_pma->sol.context)
5301 goto error;
5303 if (track_empty) {
5304 sol_pma->empty = isl_set_alloc_space(isl_basic_set_get_space(dom),
5305 1, ISL_SET_DISJOINT);
5306 if (!sol_pma->empty)
5307 goto error;
5310 isl_basic_set_free(dom);
5311 return &sol_pma->sol;
5312 error:
5313 isl_basic_set_free(dom);
5314 sol_pma_free(sol_pma);
5315 return NULL;
5318 /* Base case of isl_tab_basic_map_partial_lexopt, after removing
5319 * some obvious symmetries.
5321 * We call basic_map_partial_lexopt_base and extract the results.
5323 static __isl_give isl_pw_multi_aff *basic_map_partial_lexopt_base_pma(
5324 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
5325 __isl_give isl_set **empty, int max)
5327 isl_pw_multi_aff *result = NULL;
5328 struct isl_sol *sol;
5329 struct isl_sol_pma *sol_pma;
5331 sol = basic_map_partial_lexopt_base(bmap, dom, empty, max,
5332 &sol_pma_init);
5333 if (!sol)
5334 return NULL;
5335 sol_pma = (struct isl_sol_pma *) sol;
5337 result = isl_pw_multi_aff_copy(sol_pma->pma);
5338 if (empty)
5339 *empty = isl_set_copy(sol_pma->empty);
5340 sol_free(&sol_pma->sol);
5341 return result;
5344 /* Given that the last input variable of "maff" represents the minimum
5345 * of some bounds, check whether we need to plug in the expression
5346 * of the minimum.
5348 * In particular, check if the last input variable appears in any
5349 * of the expressions in "maff".
5351 static int need_substitution(__isl_keep isl_multi_aff *maff)
5353 int i;
5354 unsigned pos;
5356 pos = isl_multi_aff_dim(maff, isl_dim_in) - 1;
5358 for (i = 0; i < maff->n; ++i)
5359 if (isl_aff_involves_dims(maff->p[i], isl_dim_in, pos, 1))
5360 return 1;
5362 return 0;
5365 /* Given a set of upper bounds on the last "input" variable m,
5366 * construct a piecewise affine expression that selects
5367 * the minimal upper bound to m, i.e.,
5368 * divide the space into cells where one
5369 * of the upper bounds is smaller than all the others and select
5370 * this upper bound on that cell.
5372 * In particular, if there are n bounds b_i, then the result
5373 * consists of n cell, each one of the form
5375 * b_i <= b_j for j > i
5376 * b_i < b_j for j < i
5378 * The affine expression on this cell is
5380 * b_i
5382 static __isl_give isl_pw_aff *set_minimum_pa(__isl_take isl_space *space,
5383 __isl_take isl_mat *var)
5385 int i;
5386 isl_aff *aff = NULL;
5387 isl_basic_set *bset = NULL;
5388 isl_ctx *ctx;
5389 isl_pw_aff *paff = NULL;
5390 isl_space *pw_space;
5391 isl_local_space *ls = NULL;
5393 if (!space || !var)
5394 goto error;
5396 ctx = isl_space_get_ctx(space);
5397 ls = isl_local_space_from_space(isl_space_copy(space));
5398 pw_space = isl_space_copy(space);
5399 pw_space = isl_space_from_domain(pw_space);
5400 pw_space = isl_space_add_dims(pw_space, isl_dim_out, 1);
5401 paff = isl_pw_aff_alloc_size(pw_space, var->n_row);
5403 for (i = 0; i < var->n_row; ++i) {
5404 isl_pw_aff *paff_i;
5406 aff = isl_aff_alloc(isl_local_space_copy(ls));
5407 bset = isl_basic_set_alloc_space(isl_space_copy(space), 0,
5408 0, var->n_row - 1);
5409 if (!aff || !bset)
5410 goto error;
5411 isl_int_set_si(aff->v->el[0], 1);
5412 isl_seq_cpy(aff->v->el + 1, var->row[i], var->n_col);
5413 isl_int_set_si(aff->v->el[1 + var->n_col], 0);
5414 bset = select_minimum(bset, var, i);
5415 paff_i = isl_pw_aff_alloc(isl_set_from_basic_set(bset), aff);
5416 paff = isl_pw_aff_add_disjoint(paff, paff_i);
5419 isl_local_space_free(ls);
5420 isl_space_free(space);
5421 isl_mat_free(var);
5422 return paff;
5423 error:
5424 isl_aff_free(aff);
5425 isl_basic_set_free(bset);
5426 isl_pw_aff_free(paff);
5427 isl_local_space_free(ls);
5428 isl_space_free(space);
5429 isl_mat_free(var);
5430 return NULL;
5433 /* Given a piecewise multi-affine expression of which the last input variable
5434 * is the minimum of the bounds in "cst", plug in the value of the minimum.
5435 * This minimum expression is given in "min_expr_pa".
5436 * The set "min_expr" contains the same information, but in the form of a set.
5437 * The variable is subsequently projected out.
5439 * The implementation is similar to those of "split" and "split_domain".
5440 * If the variable appears in a given expression, then minimum expression
5441 * is plugged in. Otherwise, if the variable appears in the constraints
5442 * and a split is required, then the domain is split. Otherwise, no split
5443 * is performed.
5445 static __isl_give isl_pw_multi_aff *split_domain_pma(
5446 __isl_take isl_pw_multi_aff *opt, __isl_take isl_pw_aff *min_expr_pa,
5447 __isl_take isl_set *min_expr, __isl_take isl_mat *cst)
5449 int n_in;
5450 int i;
5451 isl_space *space;
5452 isl_pw_multi_aff *res;
5454 if (!opt || !min_expr || !cst)
5455 goto error;
5457 n_in = isl_pw_multi_aff_dim(opt, isl_dim_in);
5458 space = isl_pw_multi_aff_get_space(opt);
5459 space = isl_space_drop_dims(space, isl_dim_in, n_in - 1, 1);
5460 res = isl_pw_multi_aff_empty(space);
5462 for (i = 0; i < opt->n; ++i) {
5463 isl_pw_multi_aff *pma;
5465 pma = isl_pw_multi_aff_alloc(isl_set_copy(opt->p[i].set),
5466 isl_multi_aff_copy(opt->p[i].maff));
5467 if (need_substitution(opt->p[i].maff))
5468 pma = isl_pw_multi_aff_substitute(pma,
5469 isl_dim_in, n_in - 1, min_expr_pa);
5470 else if (need_split_set(opt->p[i].set, cst))
5471 pma = isl_pw_multi_aff_intersect_domain(pma,
5472 isl_set_copy(min_expr));
5473 pma = isl_pw_multi_aff_project_out(pma,
5474 isl_dim_in, n_in - 1, 1);
5476 res = isl_pw_multi_aff_add_disjoint(res, pma);
5479 isl_pw_multi_aff_free(opt);
5480 isl_pw_aff_free(min_expr_pa);
5481 isl_set_free(min_expr);
5482 isl_mat_free(cst);
5483 return res;
5484 error:
5485 isl_pw_multi_aff_free(opt);
5486 isl_pw_aff_free(min_expr_pa);
5487 isl_set_free(min_expr);
5488 isl_mat_free(cst);
5489 return NULL;
5492 static __isl_give isl_pw_multi_aff *basic_map_partial_lexopt_pma(
5493 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
5494 __isl_give isl_set **empty, int max);
5496 /* This function is called from basic_map_partial_lexopt_symm.
5497 * The last variable of "bmap" and "dom" corresponds to the minimum
5498 * of the bounds in "cst". "map_space" is the space of the original
5499 * input relation (of basic_map_partial_lexopt_symm) and "set_space"
5500 * is the space of the original domain.
5502 * We recursively call basic_map_partial_lexopt and then plug in
5503 * the definition of the minimum in the result.
5505 static __isl_give union isl_lex_res basic_map_partial_lexopt_symm_pma_core(
5506 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
5507 __isl_give isl_set **empty, int max, __isl_take isl_mat *cst,
5508 __isl_take isl_space *map_space, __isl_take isl_space *set_space)
5510 isl_pw_multi_aff *opt;
5511 isl_pw_aff *min_expr_pa;
5512 isl_set *min_expr;
5513 union isl_lex_res res;
5515 min_expr = set_minimum(isl_basic_set_get_space(dom), isl_mat_copy(cst));
5516 min_expr_pa = set_minimum_pa(isl_basic_set_get_space(dom),
5517 isl_mat_copy(cst));
5519 opt = basic_map_partial_lexopt_pma(bmap, dom, empty, max);
5521 if (empty) {
5522 *empty = split(*empty,
5523 isl_set_copy(min_expr), isl_mat_copy(cst));
5524 *empty = isl_set_reset_space(*empty, set_space);
5527 opt = split_domain_pma(opt, min_expr_pa, min_expr, cst);
5528 opt = isl_pw_multi_aff_reset_space(opt, map_space);
5530 res.pma = opt;
5531 return res;
5534 static __isl_give isl_pw_multi_aff *basic_map_partial_lexopt_symm_pma(
5535 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
5536 __isl_give isl_set **empty, int max, int first, int second)
5538 return basic_map_partial_lexopt_symm(bmap, dom, empty, max,
5539 first, second, &basic_map_partial_lexopt_symm_pma_core).pma;
5542 /* Recursive part of isl_basic_map_partial_lexopt_pw_multi_aff, after detecting
5543 * equalities and removing redundant constraints.
5545 * We first check if there are any parallel constraints (left).
5546 * If not, we are in the base case.
5547 * If there are parallel constraints, we replace them by a single
5548 * constraint in basic_map_partial_lexopt_symm_pma and then call
5549 * this function recursively to look for more parallel constraints.
5551 static __isl_give isl_pw_multi_aff *basic_map_partial_lexopt_pma(
5552 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
5553 __isl_give isl_set **empty, int max)
5555 int par = 0;
5556 int first, second;
5558 if (!bmap)
5559 goto error;
5561 if (bmap->ctx->opt->pip_symmetry)
5562 par = parallel_constraints(bmap, &first, &second);
5563 if (par < 0)
5564 goto error;
5565 if (!par)
5566 return basic_map_partial_lexopt_base_pma(bmap, dom, empty, max);
5568 return basic_map_partial_lexopt_symm_pma(bmap, dom, empty, max,
5569 first, second);
5570 error:
5571 isl_basic_set_free(dom);
5572 isl_basic_map_free(bmap);
5573 return NULL;
5576 /* Compute the lexicographic minimum (or maximum if "max" is set)
5577 * of "bmap" over the domain "dom" and return the result as a piecewise
5578 * multi-affine expression.
5579 * If "empty" is not NULL, then *empty is assigned a set that
5580 * contains those parts of the domain where there is no solution.
5581 * If "bmap" is marked as rational (ISL_BASIC_MAP_RATIONAL),
5582 * then we compute the rational optimum. Otherwise, we compute
5583 * the integral optimum.
5585 * We perform some preprocessing. As the PILP solver does not
5586 * handle implicit equalities very well, we first make sure all
5587 * the equalities are explicitly available.
5589 * We also add context constraints to the basic map and remove
5590 * redundant constraints. This is only needed because of the
5591 * way we handle simple symmetries. In particular, we currently look
5592 * for symmetries on the constraints, before we set up the main tableau.
5593 * It is then no good to look for symmetries on possibly redundant constraints.
5595 __isl_give isl_pw_multi_aff *isl_basic_map_partial_lexopt_pw_multi_aff(
5596 __isl_take isl_basic_map *bmap, __isl_take isl_basic_set *dom,
5597 __isl_give isl_set **empty, int max)
5599 if (empty)
5600 *empty = NULL;
5601 if (!bmap || !dom)
5602 goto error;
5604 isl_assert(bmap->ctx,
5605 isl_basic_map_compatible_domain(bmap, dom), goto error);
5607 if (isl_basic_set_dim(dom, isl_dim_all) == 0)
5608 return basic_map_partial_lexopt_pma(bmap, dom, empty, max);
5610 bmap = isl_basic_map_intersect_domain(bmap, isl_basic_set_copy(dom));
5611 bmap = isl_basic_map_detect_equalities(bmap);
5612 bmap = isl_basic_map_remove_redundancies(bmap);
5614 return basic_map_partial_lexopt_pma(bmap, dom, empty, max);
5615 error:
5616 isl_basic_set_free(dom);
5617 isl_basic_map_free(bmap);
5618 return NULL;