1 #include "isl_map_private.h"
6 * The implementation of parametric integer linear programming in this file
7 * was inspired by the paper "Parametric Integer Programming" and the
8 * report "Solving systems of affine (in)equalities" by Paul Feautrier
11 * The strategy used for obtaining a feasible solution is different
12 * from the one used in isl_tab.c. In particular, in isl_tab.c,
13 * upon finding a constraint that is not yet satisfied, we pivot
14 * in a row that increases the constant term of row holding the
15 * constraint, making sure the sample solution remains feasible
16 * for all the constraints it already satisfied.
17 * Here, we always pivot in the row holding the constraint,
18 * choosing a column that induces the lexicographically smallest
19 * increment to the sample solution.
21 * By starting out from a sample value that is lexicographically
22 * smaller than any integer point in the problem space, the first
23 * feasible integer sample point we find will also be the lexicographically
24 * smallest. If all variables can be assumed to be non-negative,
25 * then the initial sample value may be chosen equal to zero.
26 * However, we will not make this assumption. Instead, we apply
27 * the "big parameter" trick. Any variable x is then not directly
28 * used in the tableau, but instead it its represented by another
29 * variable x' = M + x, where M is an arbitrarily large (positive)
30 * value. x' is therefore always non-negative, whatever the value of x.
31 * Taking as initial smaple value x' = 0 corresponds to x = -M,
32 * which is always smaller than any possible value of x.
34 * We use the big parameter trick both in the main tableau and
35 * the context tableau, each of course having its own big parameter.
36 * Before doing any real work, we check if all the parameters
37 * happen to be non-negative. If so, we drop the column corresponding
38 * to M from the initial context tableau.
41 /* isl_sol is an interface for constructing a solution to
42 * a parametric integer linear programming problem.
43 * Every time the algorithm reaches a state where a solution
44 * can be read off from the tableau (including cases where the tableau
45 * is empty), the function "add" is called on the isl_sol passed
46 * to find_solutions_main.
48 * The context tableau is owned by isl_sol and is updated incrementally.
50 * There are currently two implementations of this interface,
51 * isl_sol_map, which simply collects the solutions in an isl_map
52 * and (optionally) the parts of the context where there is no solution
54 * isl_sol_for, which calls a user-defined function for each part of
58 struct isl_tab *context_tab;
59 struct isl_sol *(*add)(struct isl_sol *sol, struct isl_tab *tab);
60 void (*free)(struct isl_sol *sol);
63 static void sol_free(struct isl_sol *sol)
73 struct isl_set *empty;
77 static void sol_map_free(struct isl_sol_map *sol_map)
79 isl_tab_free(sol_map->sol.context_tab);
80 isl_map_free(sol_map->map);
81 isl_set_free(sol_map->empty);
85 static void sol_map_free_wrap(struct isl_sol *sol)
87 sol_map_free((struct isl_sol_map *)sol);
90 static struct isl_sol_map *add_empty(struct isl_sol_map *sol)
92 struct isl_basic_set *bset;
96 sol->empty = isl_set_grow(sol->empty, 1);
97 bset = isl_basic_set_copy(sol->sol.context_tab->bset);
98 bset = isl_basic_set_simplify(bset);
99 bset = isl_basic_set_finalize(bset);
100 sol->empty = isl_set_add(sol->empty, bset);
109 /* Add the solution identified by the tableau and the context tableau.
111 * The layout of the variables is as follows.
112 * tab->n_var is equal to the total number of variables in the input
113 * map (including divs that were copied from the context)
114 * + the number of extra divs constructed
115 * Of these, the first tab->n_param and the last tab->n_div variables
116 * correspond to the variables in the context, i.e.,
117 * tab->n_param + tab->n_div = context_tab->n_var
118 * tab->n_param is equal to the number of parameters and input
119 * dimensions in the input map
120 * tab->n_div is equal to the number of divs in the context
122 * If there is no solution, then the basic set corresponding to the
123 * context tableau is added to the set "empty".
125 * Otherwise, a basic map is constructed with the same parameters
126 * and divs as the context, the dimensions of the context as input
127 * dimensions and a number of output dimensions that is equal to
128 * the number of output dimensions in the input map.
129 * The divs in the input map (if any) that do not correspond to any
130 * div in the context do not appear in the solution.
131 * The algorithm will make sure that they have an integer value,
132 * but these values themselves are of no interest.
134 * The constraints and divs of the context are simply copied
135 * fron context_tab->bset.
136 * To extract the value of the output variables, it should be noted
137 * that we always use a big parameter M and so the variable stored
138 * in the tableau is not an output variable x itself, but
139 * x' = M + x (in case of minimization)
141 * x' = M - x (in case of maximization)
142 * If x' appears in a column, then its optimal value is zero,
143 * which means that the optimal value of x is an unbounded number
144 * (-M for minimization and M for maximization).
145 * We currently assume that the output dimensions in the original map
146 * are bounded, so this cannot occur.
147 * Similarly, when x' appears in a row, then the coefficient of M in that
148 * row is necessarily 1.
149 * If the row represents
150 * d x' = c + d M + e(y)
151 * then, in case of minimization, an equality
152 * c + e(y) - d x' = 0
153 * is added, and in case of maximization,
154 * c + e(y) + d x' = 0
156 static struct isl_sol_map *sol_map_add(struct isl_sol_map *sol,
160 struct isl_basic_map *bmap = NULL;
161 struct isl_tab *context_tab;
174 return add_empty(sol);
176 context_tab = sol->sol.context_tab;
178 n_out = isl_map_dim(sol->map, isl_dim_out);
179 n_eq = context_tab->bset->n_eq + n_out;
180 n_ineq = context_tab->bset->n_ineq;
181 nparam = tab->n_param;
182 total = isl_map_dim(sol->map, isl_dim_all);
183 bmap = isl_basic_map_alloc_dim(isl_map_get_dim(sol->map),
184 tab->n_div, n_eq, 2 * tab->n_div + n_ineq);
189 ISL_F_SET(bmap, ISL_BASIC_MAP_RATIONAL);
190 for (i = 0; i < context_tab->bset->n_div; ++i) {
191 int k = isl_basic_map_alloc_div(bmap);
194 isl_seq_cpy(bmap->div[k],
195 context_tab->bset->div[i], 1 + 1 + nparam);
196 isl_seq_clr(bmap->div[k] + 1 + 1 + nparam, total - nparam);
197 isl_seq_cpy(bmap->div[k] + 1 + 1 + total,
198 context_tab->bset->div[i] + 1 + 1 + nparam, i);
200 for (i = 0; i < context_tab->bset->n_eq; ++i) {
201 int k = isl_basic_map_alloc_equality(bmap);
204 isl_seq_cpy(bmap->eq[k], context_tab->bset->eq[i], 1 + nparam);
205 isl_seq_clr(bmap->eq[k] + 1 + nparam, total - nparam);
206 isl_seq_cpy(bmap->eq[k] + 1 + total,
207 context_tab->bset->eq[i] + 1 + nparam, n_div);
209 for (i = 0; i < context_tab->bset->n_ineq; ++i) {
210 int k = isl_basic_map_alloc_inequality(bmap);
213 isl_seq_cpy(bmap->ineq[k],
214 context_tab->bset->ineq[i], 1 + nparam);
215 isl_seq_clr(bmap->ineq[k] + 1 + nparam, total - nparam);
216 isl_seq_cpy(bmap->ineq[k] + 1 + total,
217 context_tab->bset->ineq[i] + 1 + nparam, n_div);
219 for (i = tab->n_param; i < total; ++i) {
220 int k = isl_basic_map_alloc_equality(bmap);
223 isl_seq_clr(bmap->eq[k] + 1, isl_basic_map_total_dim(bmap));
224 if (!tab->var[i].is_row) {
226 isl_assert(bmap->ctx, !tab->M, goto error);
227 isl_int_set_si(bmap->eq[k][0], 0);
229 isl_int_set_si(bmap->eq[k][1 + i], 1);
231 isl_int_set_si(bmap->eq[k][1 + i], -1);
234 row = tab->var[i].index;
237 isl_assert(bmap->ctx,
238 isl_int_eq(tab->mat->row[row][2],
239 tab->mat->row[row][0]),
241 isl_int_set(bmap->eq[k][0], tab->mat->row[row][1]);
242 for (j = 0; j < tab->n_param; ++j) {
244 if (tab->var[j].is_row)
246 col = tab->var[j].index;
247 isl_int_set(bmap->eq[k][1 + j],
248 tab->mat->row[row][off + col]);
250 for (j = 0; j < tab->n_div; ++j) {
252 if (tab->var[tab->n_var - tab->n_div+j].is_row)
254 col = tab->var[tab->n_var - tab->n_div+j].index;
255 isl_int_set(bmap->eq[k][1 + total + j],
256 tab->mat->row[row][off + col]);
259 isl_int_set(bmap->eq[k][1 + i],
260 tab->mat->row[row][0]);
262 isl_int_neg(bmap->eq[k][1 + i],
263 tab->mat->row[row][0]);
266 bmap = isl_basic_map_simplify(bmap);
267 bmap = isl_basic_map_finalize(bmap);
268 sol->map = isl_map_grow(sol->map, 1);
269 sol->map = isl_map_add(sol->map, bmap);
274 isl_basic_map_free(bmap);
279 static struct isl_sol *sol_map_add_wrap(struct isl_sol *sol,
282 return (struct isl_sol *)sol_map_add((struct isl_sol_map *)sol, tab);
286 /* Store the "parametric constant" of row "row" of tableau "tab" in "line",
287 * i.e., the constant term and the coefficients of all variables that
288 * appear in the context tableau.
289 * Note that the coefficient of the big parameter M is NOT copied.
290 * The context tableau may not have a big parameter and even when it
291 * does, it is a different big parameter.
293 static void get_row_parameter_line(struct isl_tab *tab, int row, isl_int *line)
296 unsigned off = 2 + tab->M;
298 isl_int_set(line[0], tab->mat->row[row][1]);
299 for (i = 0; i < tab->n_param; ++i) {
300 if (tab->var[i].is_row)
301 isl_int_set_si(line[1 + i], 0);
303 int col = tab->var[i].index;
304 isl_int_set(line[1 + i], tab->mat->row[row][off + col]);
307 for (i = 0; i < tab->n_div; ++i) {
308 if (tab->var[tab->n_var - tab->n_div + i].is_row)
309 isl_int_set_si(line[1 + tab->n_param + i], 0);
311 int col = tab->var[tab->n_var - tab->n_div + i].index;
312 isl_int_set(line[1 + tab->n_param + i],
313 tab->mat->row[row][off + col]);
318 /* Check if rows "row1" and "row2" have identical "parametric constants",
319 * as explained above.
320 * In this case, we also insist that the coefficients of the big parameter
321 * be the same as the values of the constants will only be the same
322 * if these coefficients are also the same.
324 static int identical_parameter_line(struct isl_tab *tab, int row1, int row2)
327 unsigned off = 2 + tab->M;
329 if (isl_int_ne(tab->mat->row[row1][1], tab->mat->row[row2][1]))
332 if (tab->M && isl_int_ne(tab->mat->row[row1][2],
333 tab->mat->row[row2][2]))
336 for (i = 0; i < tab->n_param + tab->n_div; ++i) {
337 int pos = i < tab->n_param ? i :
338 tab->n_var - tab->n_div + i - tab->n_param;
341 if (tab->var[pos].is_row)
343 col = tab->var[pos].index;
344 if (isl_int_ne(tab->mat->row[row1][off + col],
345 tab->mat->row[row2][off + col]))
351 /* Return an inequality that expresses that the "parametric constant"
352 * should be non-negative.
353 * This function is only called when the coefficient of the big parameter
356 static struct isl_vec *get_row_parameter_ineq(struct isl_tab *tab, int row)
358 struct isl_vec *ineq;
360 ineq = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_param + tab->n_div);
364 get_row_parameter_line(tab, row, ineq->el);
366 ineq = isl_vec_normalize(ineq);
371 /* Return a integer division for use in a parametric cut based on the given row.
372 * In particular, let the parametric constant of the row be
376 * where y_0 = 1, but none of the y_i corresponds to the big parameter M.
377 * The div returned is equal to
379 * floor(\sum_i {-a_i} y_i) = floor((\sum_i (-a_i mod d) y_i)/d)
381 static struct isl_vec *get_row_parameter_div(struct isl_tab *tab, int row)
385 div = isl_vec_alloc(tab->mat->ctx, 1 + 1 + tab->n_param + tab->n_div);
389 isl_int_set(div->el[0], tab->mat->row[row][0]);
390 get_row_parameter_line(tab, row, div->el + 1);
391 div = isl_vec_normalize(div);
392 isl_seq_neg(div->el + 1, div->el + 1, div->size - 1);
393 isl_seq_fdiv_r(div->el + 1, div->el + 1, div->el[0], div->size - 1);
398 /* Return a integer division for use in transferring an integrality constraint
400 * In particular, let the parametric constant of the row be
404 * where y_0 = 1, but none of the y_i corresponds to the big parameter M.
405 * The the returned div is equal to
407 * floor(\sum_i {a_i} y_i) = floor((\sum_i (a_i mod d) y_i)/d)
409 static struct isl_vec *get_row_split_div(struct isl_tab *tab, int row)
413 div = isl_vec_alloc(tab->mat->ctx, 1 + 1 + tab->n_param + tab->n_div);
417 isl_int_set(div->el[0], tab->mat->row[row][0]);
418 get_row_parameter_line(tab, row, div->el + 1);
419 div = isl_vec_normalize(div);
420 isl_seq_fdiv_r(div->el + 1, div->el + 1, div->el[0], div->size - 1);
425 /* Construct and return an inequality that expresses an upper bound
427 * In particular, if the div is given by
431 * then the inequality expresses
435 static struct isl_vec *ineq_for_div(struct isl_basic_set *bset, unsigned div)
439 struct isl_vec *ineq;
441 total = isl_basic_set_total_dim(bset);
442 div_pos = 1 + total - bset->n_div + div;
444 ineq = isl_vec_alloc(bset->ctx, 1 + total);
448 isl_seq_cpy(ineq->el, bset->div[div] + 1, 1 + total);
449 isl_int_neg(ineq->el[div_pos], bset->div[div][0]);
453 /* Given a row in the tableau and a div that was created
454 * using get_row_split_div and that been constrained to equality, i.e.,
456 * d = floor(\sum_i {a_i} y_i) = \sum_i {a_i} y_i
458 * replace the expression "\sum_i {a_i} y_i" in the row by d,
459 * i.e., we subtract "\sum_i {a_i} y_i" and add 1 d.
460 * The coefficients of the non-parameters in the tableau have been
461 * verified to be integral. We can therefore simply replace coefficient b
462 * by floor(b). For the coefficients of the parameters we have
463 * floor(a_i) = a_i - {a_i}, while for the other coefficients, we have
466 static struct isl_tab *set_row_cst_to_div(struct isl_tab *tab, int row, int div)
469 unsigned off = 2 + tab->M;
471 isl_seq_fdiv_q(tab->mat->row[row] + 1, tab->mat->row[row] + 1,
472 tab->mat->row[row][0], 1 + tab->M + tab->n_col);
474 isl_int_set_si(tab->mat->row[row][0], 1);
476 isl_assert(tab->mat->ctx,
477 !tab->var[tab->n_var - tab->n_div + div].is_row, goto error);
479 col = tab->var[tab->n_var - tab->n_div + div].index;
480 isl_int_set_si(tab->mat->row[row][off + col], 1);
488 /* Check if the (parametric) constant of the given row is obviously
489 * negative, meaning that we don't need to consult the context tableau.
490 * If there is a big parameter and its coefficient is non-zero,
491 * then this coefficient determines the outcome.
492 * Otherwise, we check whether the constant is negative and
493 * all non-zero coefficients of parameters are negative and
494 * belong to non-negative parameters.
496 static int is_obviously_neg(struct isl_tab *tab, int row)
500 unsigned off = 2 + tab->M;
503 if (isl_int_is_pos(tab->mat->row[row][2]))
505 if (isl_int_is_neg(tab->mat->row[row][2]))
509 if (isl_int_is_nonneg(tab->mat->row[row][1]))
511 for (i = 0; i < tab->n_param; ++i) {
512 /* Eliminated parameter */
513 if (tab->var[i].is_row)
515 col = tab->var[i].index;
516 if (isl_int_is_zero(tab->mat->row[row][off + col]))
518 if (!tab->var[i].is_nonneg)
520 if (isl_int_is_pos(tab->mat->row[row][off + col]))
523 for (i = 0; i < tab->n_div; ++i) {
524 if (tab->var[tab->n_var - tab->n_div + i].is_row)
526 col = tab->var[tab->n_var - tab->n_div + i].index;
527 if (isl_int_is_zero(tab->mat->row[row][off + col]))
529 if (!tab->var[tab->n_var - tab->n_div + i].is_nonneg)
531 if (isl_int_is_pos(tab->mat->row[row][off + col]))
537 /* Check if the (parametric) constant of the given row is obviously
538 * non-negative, meaning that we don't need to consult the context tableau.
539 * If there is a big parameter and its coefficient is non-zero,
540 * then this coefficient determines the outcome.
541 * Otherwise, we check whether the constant is non-negative and
542 * all non-zero coefficients of parameters are positive and
543 * belong to non-negative parameters.
545 static int is_obviously_nonneg(struct isl_tab *tab, int row)
549 unsigned off = 2 + tab->M;
552 if (isl_int_is_pos(tab->mat->row[row][2]))
554 if (isl_int_is_neg(tab->mat->row[row][2]))
558 if (isl_int_is_neg(tab->mat->row[row][1]))
560 for (i = 0; i < tab->n_param; ++i) {
561 /* Eliminated parameter */
562 if (tab->var[i].is_row)
564 col = tab->var[i].index;
565 if (isl_int_is_zero(tab->mat->row[row][off + col]))
567 if (!tab->var[i].is_nonneg)
569 if (isl_int_is_neg(tab->mat->row[row][off + col]))
572 for (i = 0; i < tab->n_div; ++i) {
573 if (tab->var[tab->n_var - tab->n_div + i].is_row)
575 col = tab->var[tab->n_var - tab->n_div + i].index;
576 if (isl_int_is_zero(tab->mat->row[row][off + col]))
578 if (!tab->var[tab->n_var - tab->n_div + i].is_nonneg)
580 if (isl_int_is_neg(tab->mat->row[row][off + col]))
586 /* Given a row r and two columns, return the column that would
587 * lead to the lexicographically smallest increment in the sample
588 * solution when leaving the basis in favor of the row.
589 * Pivoting with column c will increment the sample value by a non-negative
590 * constant times a_{V,c}/a_{r,c}, with a_{V,c} the elements of column c
591 * corresponding to the non-parametric variables.
592 * If variable v appears in a column c_v, the a_{v,c} = 1 iff c = c_v,
593 * with all other entries in this virtual row equal to zero.
594 * If variable v appears in a row, then a_{v,c} is the element in column c
597 * Let v be the first variable with a_{v,c1}/a_{r,c1} != a_{v,c2}/a_{r,c2}.
598 * Then if a_{v,c1}/a_{r,c1} < a_{v,c2}/a_{r,c2}, i.e.,
599 * a_{v,c2} a_{r,c1} - a_{v,c1} a_{r,c2} > 0, c1 results in the minimal
600 * increment. Otherwise, it's c2.
602 static int lexmin_col_pair(struct isl_tab *tab,
603 int row, int col1, int col2, isl_int tmp)
608 tr = tab->mat->row[row] + 2 + tab->M;
610 for (i = tab->n_param; i < tab->n_var - tab->n_div; ++i) {
614 if (!tab->var[i].is_row) {
615 if (tab->var[i].index == col1)
617 if (tab->var[i].index == col2)
622 if (tab->var[i].index == row)
625 r = tab->mat->row[tab->var[i].index] + 2 + tab->M;
626 s1 = isl_int_sgn(r[col1]);
627 s2 = isl_int_sgn(r[col2]);
628 if (s1 == 0 && s2 == 0)
635 isl_int_mul(tmp, r[col2], tr[col1]);
636 isl_int_submul(tmp, r[col1], tr[col2]);
637 if (isl_int_is_pos(tmp))
639 if (isl_int_is_neg(tmp))
645 /* Given a row in the tableau, find and return the column that would
646 * result in the lexicographically smallest, but positive, increment
647 * in the sample point.
648 * If there is no such column, then return tab->n_col.
649 * If anything goes wrong, return -1.
651 static int lexmin_pivot_col(struct isl_tab *tab, int row)
654 int col = tab->n_col;
658 tr = tab->mat->row[row] + 2 + tab->M;
662 for (j = tab->n_dead; j < tab->n_col; ++j) {
663 if (tab->col_var[j] >= 0 &&
664 (tab->col_var[j] < tab->n_param ||
665 tab->col_var[j] >= tab->n_var - tab->n_div))
668 if (!isl_int_is_pos(tr[j]))
671 if (col == tab->n_col)
674 col = lexmin_col_pair(tab, row, col, j, tmp);
675 isl_assert(tab->mat->ctx, col >= 0, goto error);
685 /* Return the first known violated constraint, i.e., a non-negative
686 * contraint that currently has an either obviously negative value
687 * or a previously determined to be negative value.
689 * If any constraint has a negative coefficient for the big parameter,
690 * if any, then we return one of these first.
692 static int first_neg(struct isl_tab *tab)
697 for (row = tab->n_redundant; row < tab->n_row; ++row) {
698 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
700 if (isl_int_is_neg(tab->mat->row[row][2]))
703 for (row = tab->n_redundant; row < tab->n_row; ++row) {
704 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
707 if (tab->row_sign[row] == 0 &&
708 is_obviously_neg(tab, row))
709 tab->row_sign[row] = isl_tab_row_neg;
710 if (tab->row_sign[row] != isl_tab_row_neg)
712 } else if (!is_obviously_neg(tab, row))
719 /* Resolve all known or obviously violated constraints through pivoting.
720 * In particular, as long as we can find any violated constraint, we
721 * look for a pivoting column that would result in the lexicographicallly
722 * smallest increment in the sample point. If there is no such column
723 * then the tableau is infeasible.
725 static struct isl_tab *restore_lexmin(struct isl_tab *tab)
733 while ((row = first_neg(tab)) != -1) {
734 col = lexmin_pivot_col(tab, row);
735 if (col >= tab->n_col)
736 return isl_tab_mark_empty(tab);
739 isl_tab_pivot(tab, row, col);
747 /* Given a row that represents an equality, look for an appropriate
749 * In particular, if there are any non-zero coefficients among
750 * the non-parameter variables, then we take the last of these
751 * variables. Eliminating this variable in terms of the other
752 * variables and/or parameters does not influence the property
753 * that all column in the initial tableau are lexicographically
754 * positive. The row corresponding to the eliminated variable
755 * will only have non-zero entries below the diagonal of the
756 * initial tableau. That is, we transform
762 * If there is no such non-parameter variable, then we are dealing with
763 * pure parameter equality and we pick any parameter with coefficient 1 or -1
764 * for elimination. This will ensure that the eliminated parameter
765 * always has an integer value whenever all the other parameters are integral.
766 * If there is no such parameter then we return -1.
768 static int last_var_col_or_int_par_col(struct isl_tab *tab, int row)
770 unsigned off = 2 + tab->M;
773 for (i = tab->n_var - tab->n_div - 1; i >= 0 && i >= tab->n_param; --i) {
775 if (tab->var[i].is_row)
777 col = tab->var[i].index;
778 if (col <= tab->n_dead)
780 if (!isl_int_is_zero(tab->mat->row[row][off + col]))
783 for (i = tab->n_dead; i < tab->n_col; ++i) {
784 if (isl_int_is_one(tab->mat->row[row][off + i]))
786 if (isl_int_is_negone(tab->mat->row[row][off + i]))
792 /* Add an equality that is known to be valid to the tableau.
793 * We first check if we can eliminate a variable or a parameter.
794 * If not, we add the equality as two inequalities.
795 * In this case, the equality was a pure parameter equality and there
796 * is no need to resolve any constraint violations.
798 static struct isl_tab *add_lexmin_valid_eq(struct isl_tab *tab, isl_int *eq)
805 r = isl_tab_add_row(tab, eq);
809 r = tab->con[r].index;
810 i = last_var_col_or_int_par_col(tab, r);
812 tab->con[r].is_nonneg = 1;
813 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
814 isl_seq_neg(eq, eq, 1 + tab->n_var);
815 r = isl_tab_add_row(tab, eq);
818 tab->con[r].is_nonneg = 1;
819 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
821 isl_tab_pivot(tab, r, i);
822 isl_tab_kill_col(tab, i);
825 tab = restore_lexmin(tab);
834 /* Check if the given row is a pure constant.
836 static int is_constant(struct isl_tab *tab, int row)
838 unsigned off = 2 + tab->M;
840 return isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
841 tab->n_col - tab->n_dead) == -1;
844 /* Add an equality that may or may not be valid to the tableau.
845 * If the resulting row is a pure constant, then it must be zero.
846 * Otherwise, the resulting tableau is empty.
848 * If the row is not a pure constant, then we add two inequalities,
849 * each time checking that they can be satisfied.
850 * In the end we try to use one of the two constraints to eliminate
853 static struct isl_tab *add_lexmin_eq(struct isl_tab *tab, isl_int *eq)
861 tab->bset = isl_basic_set_add_eq(tab->bset, eq);
862 isl_tab_push(tab, isl_tab_undo_bset_eq);
866 r1 = isl_tab_add_row(tab, eq);
869 tab->con[r1].is_nonneg = 1;
870 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r1]);
872 row = tab->con[r1].index;
873 if (is_constant(tab, row)) {
874 if (!isl_int_is_zero(tab->mat->row[row][1]) ||
875 (tab->M && !isl_int_is_zero(tab->mat->row[row][2])))
876 return isl_tab_mark_empty(tab);
880 tab = restore_lexmin(tab);
881 if (!tab || tab->empty)
884 isl_seq_neg(eq, eq, 1 + tab->n_var);
886 r2 = isl_tab_add_row(tab, eq);
889 tab->con[r2].is_nonneg = 1;
890 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r2]);
892 tab = restore_lexmin(tab);
893 if (!tab || tab->empty)
896 if (!tab->con[r1].is_row)
897 isl_tab_kill_col(tab, tab->con[r1].index);
898 else if (!tab->con[r2].is_row)
899 isl_tab_kill_col(tab, tab->con[r2].index);
900 else if (isl_int_is_zero(tab->mat->row[tab->con[r1].index][1])) {
901 unsigned off = 2 + tab->M;
903 int row = tab->con[r1].index;
904 i = isl_seq_first_non_zero(tab->mat->row[row]+off+tab->n_dead,
905 tab->n_col - tab->n_dead);
907 isl_tab_pivot(tab, row, tab->n_dead + i);
908 isl_tab_kill_col(tab, tab->n_dead + i);
918 /* Add an inequality to the tableau, resolving violations using
921 static struct isl_tab *add_lexmin_ineq(struct isl_tab *tab, isl_int *ineq)
928 tab->bset = isl_basic_set_add_ineq(tab->bset, ineq);
929 isl_tab_push(tab, isl_tab_undo_bset_ineq);
933 r = isl_tab_add_row(tab, ineq);
936 tab->con[r].is_nonneg = 1;
937 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
938 if (isl_tab_row_is_redundant(tab, tab->con[r].index)) {
939 isl_tab_mark_redundant(tab, tab->con[r].index);
943 tab = restore_lexmin(tab);
944 if (tab && !tab->empty && tab->con[r].is_row &&
945 isl_tab_row_is_redundant(tab, tab->con[r].index))
946 isl_tab_mark_redundant(tab, tab->con[r].index);
953 /* Check if the coefficients of the parameters are all integral.
955 static int integer_parameter(struct isl_tab *tab, int row)
959 unsigned off = 2 + tab->M;
961 for (i = 0; i < tab->n_param; ++i) {
962 /* Eliminated parameter */
963 if (tab->var[i].is_row)
965 col = tab->var[i].index;
966 if (!isl_int_is_divisible_by(tab->mat->row[row][off + col],
967 tab->mat->row[row][0]))
970 for (i = 0; i < tab->n_div; ++i) {
971 if (tab->var[tab->n_var - tab->n_div + i].is_row)
973 col = tab->var[tab->n_var - tab->n_div + i].index;
974 if (!isl_int_is_divisible_by(tab->mat->row[row][off + col],
975 tab->mat->row[row][0]))
981 /* Check if the coefficients of the non-parameter variables are all integral.
983 static int integer_variable(struct isl_tab *tab, int row)
986 unsigned off = 2 + tab->M;
988 for (i = 0; i < tab->n_col; ++i) {
989 if (tab->col_var[i] >= 0 &&
990 (tab->col_var[i] < tab->n_param ||
991 tab->col_var[i] >= tab->n_var - tab->n_div))
993 if (!isl_int_is_divisible_by(tab->mat->row[row][off + i],
994 tab->mat->row[row][0]))
1000 /* Check if the constant term is integral.
1002 static int integer_constant(struct isl_tab *tab, int row)
1004 return isl_int_is_divisible_by(tab->mat->row[row][1],
1005 tab->mat->row[row][0]);
1008 #define I_CST 1 << 0
1009 #define I_PAR 1 << 1
1010 #define I_VAR 1 << 2
1012 /* Check for first (non-parameter) variable that is non-integer and
1013 * therefore requires a cut.
1014 * For parametric tableaus, there are three parts in a row,
1015 * the constant, the coefficients of the parameters and the rest.
1016 * For each part, we check whether the coefficients in that part
1017 * are all integral and if so, set the corresponding flag in *f.
1018 * If the constant and the parameter part are integral, then the
1019 * current sample value is integral and no cut is required
1020 * (irrespective of whether the variable part is integral).
1022 static int first_non_integer(struct isl_tab *tab, int *f)
1026 for (i = tab->n_param; i < tab->n_var - tab->n_div; ++i) {
1029 if (!tab->var[i].is_row)
1031 row = tab->var[i].index;
1032 if (integer_constant(tab, row))
1033 ISL_FL_SET(flags, I_CST);
1034 if (integer_parameter(tab, row))
1035 ISL_FL_SET(flags, I_PAR);
1036 if (ISL_FL_ISSET(flags, I_CST) && ISL_FL_ISSET(flags, I_PAR))
1038 if (integer_variable(tab, row))
1039 ISL_FL_SET(flags, I_VAR);
1046 /* Add a (non-parametric) cut to cut away the non-integral sample
1047 * value of the given row.
1049 * If the row is given by
1051 * m r = f + \sum_i a_i y_i
1055 * c = - {-f/m} + \sum_i {a_i/m} y_i >= 0
1057 * The big parameter, if any, is ignored, since it is assumed to be big
1058 * enough to be divisible by any integer.
1059 * If the tableau is actually a parametric tableau, then this function
1060 * is only called when all coefficients of the parameters are integral.
1061 * The cut therefore has zero coefficients for the parameters.
1063 * The current value is known to be negative, so row_sign, if it
1064 * exists, is set accordingly.
1066 * Return the row of the cut or -1.
1068 static int add_cut(struct isl_tab *tab, int row)
1073 unsigned off = 2 + tab->M;
1075 if (isl_tab_extend_cons(tab, 1) < 0)
1077 r = isl_tab_allocate_con(tab);
1081 r_row = tab->mat->row[tab->con[r].index];
1082 isl_int_set(r_row[0], tab->mat->row[row][0]);
1083 isl_int_neg(r_row[1], tab->mat->row[row][1]);
1084 isl_int_fdiv_r(r_row[1], r_row[1], tab->mat->row[row][0]);
1085 isl_int_neg(r_row[1], r_row[1]);
1087 isl_int_set_si(r_row[2], 0);
1088 for (i = 0; i < tab->n_col; ++i)
1089 isl_int_fdiv_r(r_row[off + i],
1090 tab->mat->row[row][off + i], tab->mat->row[row][0]);
1092 tab->con[r].is_nonneg = 1;
1093 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
1095 tab->row_sign[tab->con[r].index] = isl_tab_row_neg;
1097 return tab->con[r].index;
1100 /* Given a non-parametric tableau, add cuts until an integer
1101 * sample point is obtained or until the tableau is determined
1102 * to be integer infeasible.
1103 * As long as there is any non-integer value in the sample point,
1104 * we add an appropriate cut, if possible and resolve the violated
1105 * cut constraint using restore_lexmin.
1106 * If one of the corresponding rows is equal to an integral
1107 * combination of variables/constraints plus a non-integral constant,
1108 * then there is no way to obtain an integer point an we return
1109 * a tableau that is marked empty.
1111 static struct isl_tab *cut_to_integer_lexmin(struct isl_tab *tab)
1121 while ((row = first_non_integer(tab, &flags)) != -1) {
1122 if (ISL_FL_ISSET(flags, I_VAR))
1123 return isl_tab_mark_empty(tab);
1124 row = add_cut(tab, row);
1127 tab = restore_lexmin(tab);
1128 if (!tab || tab->empty)
1137 static struct isl_tab *drop_sample(struct isl_tab *tab, int s)
1139 if (s != tab->n_outside)
1140 isl_mat_swap_rows(tab->samples, tab->n_outside, s);
1142 isl_tab_push(tab, isl_tab_undo_drop_sample);
1147 /* Check whether all the currently active samples also satisfy the inequality
1148 * "ineq" (treated as an equality if eq is set).
1149 * Remove those samples that do not.
1151 static struct isl_tab *check_samples(struct isl_tab *tab, isl_int *ineq, int eq)
1159 isl_assert(tab->mat->ctx, tab->bset, goto error);
1160 isl_assert(tab->mat->ctx, tab->samples, goto error);
1161 isl_assert(tab->mat->ctx, tab->samples->n_col == 1 + tab->n_var, goto error);
1164 for (i = tab->n_outside; i < tab->n_sample; ++i) {
1166 isl_seq_inner_product(ineq, tab->samples->row[i],
1167 1 + tab->n_var, &v);
1168 sgn = isl_int_sgn(v);
1169 if (eq ? (sgn == 0) : (sgn >= 0))
1171 tab = drop_sample(tab, i);
1183 /* Check whether the sample value of the tableau is finite,
1184 * i.e., either the tableau does not use a big parameter, or
1185 * all values of the variables are equal to the big parameter plus
1186 * some constant. This constant is the actual sample value.
1188 static int sample_is_finite(struct isl_tab *tab)
1195 for (i = 0; i < tab->n_var; ++i) {
1197 if (!tab->var[i].is_row)
1199 row = tab->var[i].index;
1200 if (isl_int_ne(tab->mat->row[row][0], tab->mat->row[row][2]))
1206 /* Check if the context tableau of sol has any integer points.
1207 * Returns -1 if an error occurred.
1208 * If an integer point can be found and if moreover it is finite,
1209 * then it is added to the list of sample values.
1211 * This function is only called when none of the currently active sample
1212 * values satisfies the most recently added constraint.
1214 static int context_is_feasible(struct isl_sol *sol)
1216 struct isl_tab_undo *snap;
1217 struct isl_tab *tab;
1220 if (!sol || !sol->context_tab)
1223 snap = isl_tab_snap(sol->context_tab);
1224 isl_tab_push_basis(sol->context_tab);
1226 sol->context_tab = cut_to_integer_lexmin(sol->context_tab);
1227 if (!sol->context_tab)
1230 tab = sol->context_tab;
1231 if (!tab->empty && sample_is_finite(tab)) {
1232 struct isl_vec *sample;
1234 tab->samples = isl_mat_extend(tab->samples,
1235 tab->n_sample + 1, tab->samples->n_col);
1239 sample = isl_tab_get_sample_value(tab);
1242 isl_seq_cpy(tab->samples->row[tab->n_sample],
1243 sample->el, sample->size);
1244 isl_vec_free(sample);
1248 feasible = !sol->context_tab->empty;
1249 if (isl_tab_rollback(sol->context_tab, snap) < 0)
1254 isl_tab_free(sol->context_tab);
1255 sol->context_tab = NULL;
1259 /* First check if any of the currently active sample values satisfies
1260 * the inequality "ineq" (an equality if eq is set).
1261 * If not, continue with check_integer_feasible.
1263 static int context_valid_sample_or_feasible(struct isl_sol *sol,
1264 isl_int *ineq, int eq)
1268 struct isl_tab *tab;
1270 if (!sol || !sol->context_tab)
1273 tab = sol->context_tab;
1274 isl_assert(tab->mat->ctx, tab->bset, return -1);
1275 isl_assert(tab->mat->ctx, tab->samples, return -1);
1276 isl_assert(tab->mat->ctx, tab->samples->n_col == 1 + tab->n_var, return -1);
1279 for (i = tab->n_outside; i < tab->n_sample; ++i) {
1281 isl_seq_inner_product(ineq, tab->samples->row[i],
1282 1 + tab->n_var, &v);
1283 sgn = isl_int_sgn(v);
1284 if (eq ? (sgn == 0) : (sgn >= 0))
1289 if (i < tab->n_sample)
1292 return context_is_feasible(sol);
1295 /* For a div d = floor(f/m), add the constraints
1298 * -(f-(m-1)) + m d >= 0
1300 * Note that the second constraint is the negation of
1304 static struct isl_tab *add_div_constraints(struct isl_tab *tab, unsigned div)
1308 struct isl_vec *ineq;
1313 total = isl_basic_set_total_dim(tab->bset);
1314 div_pos = 1 + total - tab->bset->n_div + div;
1316 ineq = ineq_for_div(tab->bset, div);
1320 tab = add_lexmin_ineq(tab, ineq->el);
1322 isl_seq_neg(ineq->el, tab->bset->div[div] + 1, 1 + total);
1323 isl_int_set(ineq->el[div_pos], tab->bset->div[div][0]);
1324 isl_int_add(ineq->el[0], ineq->el[0], ineq->el[div_pos]);
1325 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
1326 tab = add_lexmin_ineq(tab, ineq->el);
1336 /* Add a div specified by "div" to both the main tableau and
1337 * the context tableau. In case of the main tableau, we only
1338 * need to add an extra div. In the context tableau, we also
1339 * need to express the meaning of the div.
1340 * Return the index of the div or -1 if anything went wrong.
1342 static int add_div(struct isl_tab *tab, struct isl_tab **context_tab,
1343 struct isl_vec *div)
1348 struct isl_mat *samples;
1350 if (isl_tab_extend_vars(*context_tab, 1) < 0)
1352 r = isl_tab_allocate_var(*context_tab);
1355 (*context_tab)->var[r].is_nonneg = 1;
1356 (*context_tab)->var[r].frozen = 1;
1358 samples = isl_mat_extend((*context_tab)->samples,
1359 (*context_tab)->n_sample, 1 + (*context_tab)->n_var);
1360 (*context_tab)->samples = samples;
1363 for (i = (*context_tab)->n_outside; i < samples->n_row; ++i) {
1364 isl_seq_inner_product(div->el + 1, samples->row[i],
1365 div->size - 1, &samples->row[i][samples->n_col - 1]);
1366 isl_int_fdiv_q(samples->row[i][samples->n_col - 1],
1367 samples->row[i][samples->n_col - 1], div->el[0]);
1370 (*context_tab)->bset = isl_basic_set_extend_dim((*context_tab)->bset,
1371 isl_basic_set_get_dim((*context_tab)->bset), 1, 0, 2);
1372 k = isl_basic_set_alloc_div((*context_tab)->bset);
1375 isl_seq_cpy((*context_tab)->bset->div[k], div->el, div->size);
1376 isl_tab_push((*context_tab), isl_tab_undo_bset_div);
1377 *context_tab = add_div_constraints(*context_tab, k);
1381 if (isl_tab_extend_vars(tab, 1) < 0)
1383 r = isl_tab_allocate_var(tab);
1386 if (!(*context_tab)->M)
1387 tab->var[r].is_nonneg = 1;
1388 tab->var[r].frozen = 1;
1391 return tab->n_div - 1;
1393 isl_tab_free(*context_tab);
1394 *context_tab = NULL;
1398 static int find_div(struct isl_tab *tab, isl_int *div, isl_int denom)
1401 unsigned total = isl_basic_set_total_dim(tab->bset);
1403 for (i = 0; i < tab->bset->n_div; ++i) {
1404 if (isl_int_ne(tab->bset->div[i][0], denom))
1406 if (!isl_seq_eq(tab->bset->div[i] + 1, div, total))
1413 /* Return the index of a div that corresponds to "div".
1414 * We first check if we already have such a div and if not, we create one.
1416 static int get_div(struct isl_tab *tab, struct isl_tab **context_tab,
1417 struct isl_vec *div)
1421 d = find_div(*context_tab, div->el + 1, div->el[0]);
1425 return add_div(tab, context_tab, div);
1428 /* Add a parametric cut to cut away the non-integral sample value
1430 * Let a_i be the coefficients of the constant term and the parameters
1431 * and let b_i be the coefficients of the variables or constraints
1432 * in basis of the tableau.
1433 * Let q be the div q = floor(\sum_i {-a_i} y_i).
1435 * The cut is expressed as
1437 * c = \sum_i -{-a_i} y_i + \sum_i {b_i} x_i + q >= 0
1439 * If q did not already exist in the context tableau, then it is added first.
1440 * If q is in a column of the main tableau then the "+ q" can be accomplished
1441 * by setting the corresponding entry to the denominator of the constraint.
1442 * If q happens to be in a row of the main tableau, then the corresponding
1443 * row needs to be added instead (taking care of the denominators).
1444 * Note that this is very unlikely, but perhaps not entirely impossible.
1446 * The current value of the cut is known to be negative (or at least
1447 * non-positive), so row_sign is set accordingly.
1449 * Return the row of the cut or -1.
1451 static int add_parametric_cut(struct isl_tab *tab, int row,
1452 struct isl_tab **context_tab)
1454 struct isl_vec *div;
1460 unsigned off = 2 + tab->M;
1465 if (isl_tab_extend_cons(*context_tab, 3) < 0)
1468 div = get_row_parameter_div(tab, row);
1472 d = get_div(tab, context_tab, div);
1476 if (isl_tab_extend_cons(tab, 1) < 0)
1478 r = isl_tab_allocate_con(tab);
1482 r_row = tab->mat->row[tab->con[r].index];
1483 isl_int_set(r_row[0], tab->mat->row[row][0]);
1484 isl_int_neg(r_row[1], tab->mat->row[row][1]);
1485 isl_int_fdiv_r(r_row[1], r_row[1], tab->mat->row[row][0]);
1486 isl_int_neg(r_row[1], r_row[1]);
1488 isl_int_set_si(r_row[2], 0);
1489 for (i = 0; i < tab->n_param; ++i) {
1490 if (tab->var[i].is_row)
1492 col = tab->var[i].index;
1493 isl_int_neg(r_row[off + col], tab->mat->row[row][off + col]);
1494 isl_int_fdiv_r(r_row[off + col], r_row[off + col],
1495 tab->mat->row[row][0]);
1496 isl_int_neg(r_row[off + col], r_row[off + col]);
1498 for (i = 0; i < tab->n_div; ++i) {
1499 if (tab->var[tab->n_var - tab->n_div + i].is_row)
1501 col = tab->var[tab->n_var - tab->n_div + i].index;
1502 isl_int_neg(r_row[off + col], tab->mat->row[row][off + col]);
1503 isl_int_fdiv_r(r_row[off + col], r_row[off + col],
1504 tab->mat->row[row][0]);
1505 isl_int_neg(r_row[off + col], r_row[off + col]);
1507 for (i = 0; i < tab->n_col; ++i) {
1508 if (tab->col_var[i] >= 0 &&
1509 (tab->col_var[i] < tab->n_param ||
1510 tab->col_var[i] >= tab->n_var - tab->n_div))
1512 isl_int_fdiv_r(r_row[off + i],
1513 tab->mat->row[row][off + i], tab->mat->row[row][0]);
1515 if (tab->var[tab->n_var - tab->n_div + d].is_row) {
1517 int d_row = tab->var[tab->n_var - tab->n_div + d].index;
1519 isl_int_gcd(gcd, tab->mat->row[d_row][0], r_row[0]);
1520 isl_int_divexact(r_row[0], r_row[0], gcd);
1521 isl_int_divexact(gcd, tab->mat->row[d_row][0], gcd);
1522 isl_seq_combine(r_row + 1, gcd, r_row + 1,
1523 r_row[0], tab->mat->row[d_row] + 1,
1524 off - 1 + tab->n_col);
1525 isl_int_mul(r_row[0], r_row[0], tab->mat->row[d_row][0]);
1528 col = tab->var[tab->n_var - tab->n_div + d].index;
1529 isl_int_set(r_row[off + col], tab->mat->row[row][0]);
1532 tab->con[r].is_nonneg = 1;
1533 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
1535 tab->row_sign[tab->con[r].index] = isl_tab_row_neg;
1539 return tab->con[r].index;
1541 isl_tab_free(*context_tab);
1542 *context_tab = NULL;
1546 /* Construct a tableau for bmap that can be used for computing
1547 * the lexicographic minimum (or maximum) of bmap.
1548 * If not NULL, then dom is the domain where the minimum
1549 * should be computed. In this case, we set up a parametric
1550 * tableau with row signs (initialized to "unknown").
1551 * If M is set, then the tableau will use a big parameter.
1552 * If max is set, then a maximum should be computed instead of a minimum.
1553 * This means that for each variable x, the tableau will contain the variable
1554 * x' = M - x, rather than x' = M + x. This in turn means that the coefficient
1555 * of the variables in all constraints are negated prior to adding them
1558 static struct isl_tab *tab_for_lexmin(struct isl_basic_map *bmap,
1559 struct isl_basic_set *dom, unsigned M, int max)
1562 struct isl_tab *tab;
1564 tab = isl_tab_alloc(bmap->ctx, 2 * bmap->n_eq + bmap->n_ineq + 1,
1565 isl_basic_map_total_dim(bmap), M);
1569 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1571 tab->n_param = isl_basic_set_total_dim(dom) - dom->n_div;
1572 tab->n_div = dom->n_div;
1573 tab->row_sign = isl_calloc_array(bmap->ctx,
1574 enum isl_tab_row_sign, tab->mat->n_row);
1578 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY))
1579 return isl_tab_mark_empty(tab);
1581 for (i = tab->n_param; i < tab->n_var - tab->n_div; ++i) {
1582 tab->var[i].is_nonneg = 1;
1583 tab->var[i].frozen = 1;
1585 for (i = 0; i < bmap->n_eq; ++i) {
1587 isl_seq_neg(bmap->eq[i] + 1 + tab->n_param,
1588 bmap->eq[i] + 1 + tab->n_param,
1589 tab->n_var - tab->n_param - tab->n_div);
1590 tab = add_lexmin_valid_eq(tab, bmap->eq[i]);
1592 isl_seq_neg(bmap->eq[i] + 1 + tab->n_param,
1593 bmap->eq[i] + 1 + tab->n_param,
1594 tab->n_var - tab->n_param - tab->n_div);
1595 if (!tab || tab->empty)
1598 for (i = 0; i < bmap->n_ineq; ++i) {
1600 isl_seq_neg(bmap->ineq[i] + 1 + tab->n_param,
1601 bmap->ineq[i] + 1 + tab->n_param,
1602 tab->n_var - tab->n_param - tab->n_div);
1603 tab = add_lexmin_ineq(tab, bmap->ineq[i]);
1605 isl_seq_neg(bmap->ineq[i] + 1 + tab->n_param,
1606 bmap->ineq[i] + 1 + tab->n_param,
1607 tab->n_var - tab->n_param - tab->n_div);
1608 if (!tab || tab->empty)
1617 static struct isl_tab *context_tab_for_lexmin(struct isl_basic_set *bset)
1619 struct isl_tab *tab;
1621 bset = isl_basic_set_cow(bset);
1624 tab = tab_for_lexmin((struct isl_basic_map *)bset, NULL, 1, 0);
1630 tab->samples = isl_mat_alloc(bset->ctx, 1, 1 + tab->n_var);
1635 isl_basic_set_free(bset);
1639 /* Construct an isl_sol_map structure for accumulating the solution.
1640 * If track_empty is set, then we also keep track of the parts
1641 * of the context where there is no solution.
1642 * If max is set, then we are solving a maximization, rather than
1643 * a minimization problem, which means that the variables in the
1644 * tableau have value "M - x" rather than "M + x".
1646 static struct isl_sol_map *sol_map_init(struct isl_basic_map *bmap,
1647 struct isl_basic_set *dom, int track_empty, int max)
1649 struct isl_sol_map *sol_map;
1650 struct isl_tab *context_tab;
1653 sol_map = isl_calloc_type(bset->ctx, struct isl_sol_map);
1658 sol_map->sol.add = &sol_map_add_wrap;
1659 sol_map->sol.free = &sol_map_free_wrap;
1660 sol_map->map = isl_map_alloc_dim(isl_basic_map_get_dim(bmap), 1,
1665 context_tab = context_tab_for_lexmin(isl_basic_set_copy(dom));
1666 context_tab = restore_lexmin(context_tab);
1667 sol_map->sol.context_tab = context_tab;
1668 f = context_is_feasible(&sol_map->sol);
1673 sol_map->empty = isl_set_alloc_dim(isl_basic_set_get_dim(dom),
1674 1, ISL_SET_DISJOINT);
1675 if (!sol_map->empty)
1679 isl_basic_set_free(dom);
1682 isl_basic_set_free(dom);
1683 sol_map_free(sol_map);
1687 /* For each variable in the context tableau, check if the variable can
1688 * only attain non-negative values. If so, mark the parameter as non-negative
1689 * in the main tableau. This allows for a more direct identification of some
1690 * cases of violated constraints.
1692 static struct isl_tab *tab_detect_nonnegative_parameters(struct isl_tab *tab,
1693 struct isl_tab *context_tab)
1696 struct isl_tab_undo *snap, *snap2;
1697 struct isl_vec *ineq = NULL;
1698 struct isl_tab_var *var;
1701 if (context_tab->n_var == 0)
1704 ineq = isl_vec_alloc(tab->mat->ctx, 1 + context_tab->n_var);
1708 if (isl_tab_extend_cons(context_tab, 1) < 0)
1711 snap = isl_tab_snap(context_tab);
1712 isl_tab_push_basis(context_tab);
1714 snap2 = isl_tab_snap(context_tab);
1717 isl_seq_clr(ineq->el, ineq->size);
1718 for (i = 0; i < context_tab->n_var; ++i) {
1719 isl_int_set_si(ineq->el[1 + i], 1);
1720 context_tab = isl_tab_add_ineq(context_tab, ineq->el);
1721 var = &context_tab->con[context_tab->n_con - 1];
1722 if (!context_tab->empty &&
1723 !isl_tab_min_at_most_neg_one(context_tab, var)) {
1725 if (i >= tab->n_param)
1726 j = i - tab->n_param + tab->n_var - tab->n_div;
1727 tab->var[j].is_nonneg = 1;
1730 isl_int_set_si(ineq->el[1 + i], 0);
1731 if (isl_tab_rollback(context_tab, snap2) < 0)
1735 if (isl_tab_rollback(context_tab, snap) < 0)
1738 if (n == context_tab->n_var) {
1739 context_tab->mat = isl_mat_drop_cols(context_tab->mat, 2, 1);
1751 /* Check whether all coefficients of (non-parameter) variables
1752 * are non-positive, meaning that no pivots can be performed on the row.
1754 static int is_critical(struct isl_tab *tab, int row)
1757 unsigned off = 2 + tab->M;
1759 for (j = tab->n_dead; j < tab->n_col; ++j) {
1760 if (tab->col_var[j] >= 0 &&
1761 (tab->col_var[j] < tab->n_param ||
1762 tab->col_var[j] >= tab->n_var - tab->n_div))
1765 if (isl_int_is_pos(tab->mat->row[row][off + j]))
1772 /* Check whether the inequality represented by vec is strict over the integers,
1773 * i.e., there are no integer values satisfying the constraint with
1774 * equality. This happens if the gcd of the coefficients is not a divisor
1775 * of the constant term. If so, scale the constraint down by the gcd
1776 * of the coefficients.
1778 static int is_strict(struct isl_vec *vec)
1784 isl_seq_gcd(vec->el + 1, vec->size - 1, &gcd);
1785 if (!isl_int_is_one(gcd)) {
1786 strict = !isl_int_is_divisible_by(vec->el[0], gcd);
1787 isl_int_fdiv_q(vec->el[0], vec->el[0], gcd);
1788 isl_seq_scale_down(vec->el + 1, vec->el + 1, gcd, vec->size-1);
1795 /* Determine the sign of the given row of the main tableau.
1796 * The result is one of
1797 * isl_tab_row_pos: always non-negative; no pivot needed
1798 * isl_tab_row_neg: always non-positive; pivot
1799 * isl_tab_row_any: can be both positive and negative; split
1801 * We first handle some simple cases
1802 * - the row sign may be known already
1803 * - the row may be obviously non-negative
1804 * - the parametric constant may be equal to that of another row
1805 * for which we know the sign. This sign will be either "pos" or
1806 * "any". If it had been "neg" then we would have pivoted before.
1808 * If none of these cases hold, we check the value of the row for each
1809 * of the currently active samples. Based on the signs of these values
1810 * we make an initial determination of the sign of the row.
1812 * all zero -> unk(nown)
1813 * all non-negative -> pos
1814 * all non-positive -> neg
1815 * both negative and positive -> all
1817 * If we end up with "all", we are done.
1818 * Otherwise, we perform a check for positive and/or negative
1819 * values as follows.
1821 * samples neg unk pos
1827 * There is no special sign for "zero", because we can usually treat zero
1828 * as either non-negative or non-positive, whatever works out best.
1829 * However, if the row is "critical", meaning that pivoting is impossible
1830 * then we don't want to limp zero with the non-positive case, because
1831 * then we we would lose the solution for those values of the parameters
1832 * where the value of the row is zero. Instead, we treat 0 as non-negative
1833 * ensuring a split if the row can attain both zero and negative values.
1834 * The same happens when the original constraint was one that could not
1835 * be satisfied with equality by any integer values of the parameters.
1836 * In this case, we normalize the constraint, but then a value of zero
1837 * for the normalized constraint is actually a positive value for the
1838 * original constraint, so again we need to treat zero as non-negative.
1839 * In both these cases, we have the following decision tree instead:
1841 * all non-negative -> pos
1842 * all negative -> neg
1843 * both negative and non-negative -> all
1851 static int row_sign(struct isl_tab *tab, struct isl_sol *sol, int row)
1854 struct isl_tab_undo *snap = NULL;
1855 struct isl_vec *ineq = NULL;
1856 int res = isl_tab_row_unknown;
1862 struct isl_tab *context_tab = sol->context_tab;
1864 if (tab->row_sign[row] != isl_tab_row_unknown)
1865 return tab->row_sign[row];
1866 if (is_obviously_nonneg(tab, row))
1867 return isl_tab_row_pos;
1868 for (row2 = tab->n_redundant; row2 < tab->n_row; ++row2) {
1869 if (tab->row_sign[row2] == isl_tab_row_unknown)
1871 if (identical_parameter_line(tab, row, row2))
1872 return tab->row_sign[row2];
1875 critical = is_critical(tab, row);
1877 isl_assert(tab->mat->ctx, context_tab->samples, goto error);
1878 isl_assert(tab->mat->ctx, context_tab->samples->n_col == 1 + context_tab->n_var, goto error);
1880 ineq = get_row_parameter_ineq(tab, row);
1884 strict = is_strict(ineq);
1887 for (i = context_tab->n_outside; i < context_tab->n_sample; ++i) {
1888 isl_seq_inner_product(context_tab->samples->row[i], ineq->el,
1890 sgn = isl_int_sgn(tmp);
1891 if (sgn > 0 || (sgn == 0 && (critical || strict))) {
1892 if (res == isl_tab_row_unknown)
1893 res = isl_tab_row_pos;
1894 if (res == isl_tab_row_neg)
1895 res = isl_tab_row_any;
1898 if (res == isl_tab_row_unknown)
1899 res = isl_tab_row_neg;
1900 if (res == isl_tab_row_pos)
1901 res = isl_tab_row_any;
1903 if (res == isl_tab_row_any)
1908 if (res != isl_tab_row_any) {
1909 if (isl_tab_extend_cons(context_tab, 1) < 0)
1912 snap = isl_tab_snap(context_tab);
1913 isl_tab_push_basis(context_tab);
1916 if (res == isl_tab_row_unknown || res == isl_tab_row_pos) {
1917 /* test for negative values */
1919 isl_seq_neg(ineq->el, ineq->el, ineq->size);
1920 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
1922 isl_tab_push_basis(context_tab);
1923 sol->context_tab = add_lexmin_ineq(sol->context_tab, ineq->el);
1924 feasible = context_is_feasible(sol);
1927 context_tab = sol->context_tab;
1929 res = isl_tab_row_pos;
1931 res = (res == isl_tab_row_unknown) ? isl_tab_row_neg
1933 if (isl_tab_rollback(context_tab, snap) < 0)
1936 if (res == isl_tab_row_neg) {
1937 isl_seq_neg(ineq->el, ineq->el, ineq->size);
1938 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
1942 if (res == isl_tab_row_neg) {
1943 /* test for positive values */
1945 if (!critical && !strict)
1946 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
1948 isl_tab_push_basis(context_tab);
1949 sol->context_tab = add_lexmin_ineq(sol->context_tab, ineq->el);
1950 feasible = context_is_feasible(sol);
1953 context_tab = sol->context_tab;
1955 res = isl_tab_row_any;
1956 if (isl_tab_rollback(context_tab, snap) < 0)
1967 static struct isl_sol *find_solutions(struct isl_sol *sol, struct isl_tab *tab);
1969 /* Find solutions for values of the parameters that satisfy the given
1972 * We currently take a snapshot of the context tableau that is reset
1973 * when we return from this function, while we make a copy of the main
1974 * tableau, leaving the original main tableau untouched.
1975 * These are fairly arbitrary choices. Making a copy also of the context
1976 * tableau would obviate the need to undo any changes made to it later,
1977 * while taking a snapshot of the main tableau could reduce memory usage.
1978 * If we were to switch to taking a snapshot of the main tableau,
1979 * we would have to keep in mind that we need to save the row signs
1980 * and that we need to do this before saving the current basis
1981 * such that the basis has been restore before we restore the row signs.
1983 static struct isl_sol *find_in_pos(struct isl_sol *sol,
1984 struct isl_tab *tab, isl_int *ineq)
1986 struct isl_tab_undo *snap;
1988 snap = isl_tab_snap(sol->context_tab);
1989 isl_tab_push_basis(sol->context_tab);
1990 if (isl_tab_extend_cons(sol->context_tab, 1) < 0)
1993 tab = isl_tab_dup(tab);
1997 sol->context_tab = add_lexmin_ineq(sol->context_tab, ineq);
1998 sol->context_tab = check_samples(sol->context_tab, ineq, 0);
2000 sol = find_solutions(sol, tab);
2002 isl_tab_rollback(sol->context_tab, snap);
2005 isl_tab_rollback(sol->context_tab, snap);
2010 /* Record the absence of solutions for those values of the parameters
2011 * that do not satisfy the given inequality with equality.
2013 static struct isl_sol *no_sol_in_strict(struct isl_sol *sol,
2014 struct isl_tab *tab, struct isl_vec *ineq)
2018 struct isl_tab_undo *snap;
2019 snap = isl_tab_snap(sol->context_tab);
2020 isl_tab_push_basis(sol->context_tab);
2021 if (isl_tab_extend_cons(sol->context_tab, 1) < 0)
2024 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
2026 sol->context_tab = add_lexmin_ineq(sol->context_tab, ineq->el);
2027 f = context_valid_sample_or_feasible(sol, ineq->el, 0);
2033 sol = sol->add(sol, tab);
2036 isl_int_add_ui(ineq->el[0], ineq->el[0], 1);
2038 if (isl_tab_rollback(sol->context_tab, snap) < 0)
2046 /* Given a main tableau where more than one row requires a split,
2047 * determine and return the "best" row to split on.
2049 * Given two rows in the main tableau, if the inequality corresponding
2050 * to the first row is redundant with respect to that of the second row
2051 * in the current tableau, then it is better to split on the second row,
2052 * since in the positive part, both row will be positive.
2053 * (In the negative part a pivot will have to be performed and just about
2054 * anything can happen to the sign of the other row.)
2056 * As a simple heuristic, we therefore select the row that makes the most
2057 * of the other rows redundant.
2059 * Perhaps it would also be useful to look at the number of constraints
2060 * that conflict with any given constraint.
2062 static int best_split(struct isl_tab *tab, struct isl_tab *context_tab)
2064 struct isl_tab_undo *snap, *snap2;
2070 if (isl_tab_extend_cons(context_tab, 2) < 0)
2073 snap = isl_tab_snap(context_tab);
2074 isl_tab_push_basis(context_tab);
2075 snap2 = isl_tab_snap(context_tab);
2077 for (split = tab->n_redundant; split < tab->n_row; ++split) {
2078 struct isl_tab_undo *snap3;
2079 struct isl_vec *ineq = NULL;
2082 if (!isl_tab_var_from_row(tab, split)->is_nonneg)
2084 if (tab->row_sign[split] != isl_tab_row_any)
2087 ineq = get_row_parameter_ineq(tab, split);
2090 context_tab = isl_tab_add_ineq(context_tab, ineq->el);
2093 snap3 = isl_tab_snap(context_tab);
2095 for (row = tab->n_redundant; row < tab->n_row; ++row) {
2096 struct isl_tab_var *var;
2100 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
2102 if (tab->row_sign[row] != isl_tab_row_any)
2105 ineq = get_row_parameter_ineq(tab, row);
2108 context_tab = isl_tab_add_ineq(context_tab, ineq->el);
2110 var = &context_tab->con[context_tab->n_con - 1];
2111 if (!context_tab->empty &&
2112 !isl_tab_min_at_most_neg_one(context_tab, var))
2114 if (isl_tab_rollback(context_tab, snap3) < 0)
2117 if (best == -1 || r > best_r) {
2121 if (isl_tab_rollback(context_tab, snap2) < 0)
2125 if (isl_tab_rollback(context_tab, snap) < 0)
2131 /* Compute the lexicographic minimum of the set represented by the main
2132 * tableau "tab" within the context "sol->context_tab".
2133 * On entry the sample value of the main tableau is lexicographically
2134 * less than or equal to this lexicographic minimum.
2135 * Pivots are performed until a feasible point is found, which is then
2136 * necessarily equal to the minimum, or until the tableau is found to
2137 * be infeasible. Some pivots may need to be performed for only some
2138 * feasible values of the context tableau. If so, the context tableau
2139 * is split into a part where the pivot is needed and a part where it is not.
2141 * Whenever we enter the main loop, the main tableau is such that no
2142 * "obvious" pivots need to be performed on it, where "obvious" means
2143 * that the given row can be seen to be negative without looking at
2144 * the context tableau. In particular, for non-parametric problems,
2145 * no pivots need to be performed on the main tableau.
2146 * The caller of find_solutions is responsible for making this property
2147 * hold prior to the first iteration of the loop, while restore_lexmin
2148 * is called before every other iteration.
2150 * Inside the main loop, we first examine the signs of the rows of
2151 * the main tableau within the context of the context tableau.
2152 * If we find a row that is always non-positive for all values of
2153 * the parameters satisfying the context tableau and negative for at
2154 * least one value of the parameters, we perform the appropriate pivot
2155 * and start over. An exception is the case where no pivot can be
2156 * performed on the row. In this case, we require that the sign of
2157 * the row is negative for all values of the parameters (rather than just
2158 * non-positive). This special case is handled inside row_sign, which
2159 * will say that the row can have any sign if it determines that it can
2160 * attain both negative and zero values.
2162 * If we can't find a row that always requires a pivot, but we can find
2163 * one or more rows that require a pivot for some values of the parameters
2164 * (i.e., the row can attain both positive and negative signs), then we split
2165 * the context tableau into two parts, one where we force the sign to be
2166 * non-negative and one where we force is to be negative.
2167 * The non-negative part is handled by a recursive call (through find_in_pos).
2168 * Upon returning from this call, we continue with the negative part and
2169 * perform the required pivot.
2171 * If no such rows can be found, all rows are non-negative and we have
2172 * found a (rational) feasible point. If we only wanted a rational point
2174 * Otherwise, we check if all values of the sample point of the tableau
2175 * are integral for the variables. If so, we have found the minimal
2176 * integral point and we are done.
2177 * If the sample point is not integral, then we need to make a distinction
2178 * based on whether the constant term is non-integral or the coefficients
2179 * of the parameters. Furthermore, in order to decide how to handle
2180 * the non-integrality, we also need to know whether the coefficients
2181 * of the other columns in the tableau are integral. This leads
2182 * to the following table. The first two rows do not correspond
2183 * to a non-integral sample point and are only mentioned for completeness.
2185 * constant parameters other
2188 * int int rat | -> no problem
2190 * rat int int -> fail
2192 * rat int rat -> cut
2195 * rat rat rat | -> parametric cut
2198 * rat rat int | -> split context
2200 * If the parametric constant is completely integral, then there is nothing
2201 * to be done. If the constant term is non-integral, but all the other
2202 * coefficient are integral, then there is nothing that can be done
2203 * and the tableau has no integral solution.
2204 * If, on the other hand, one or more of the other columns have rational
2205 * coeffcients, but the parameter coefficients are all integral, then
2206 * we can perform a regular (non-parametric) cut.
2207 * Finally, if there is any parameter coefficient that is non-integral,
2208 * then we need to involve the context tableau. There are two cases here.
2209 * If at least one other column has a rational coefficient, then we
2210 * can perform a parametric cut in the main tableau by adding a new
2211 * integer division in the context tableau.
2212 * If all other columns have integral coefficients, then we need to
2213 * enforce that the rational combination of parameters (c + \sum a_i y_i)/m
2214 * is always integral. We do this by introducing an integer division
2215 * q = floor((c + \sum a_i y_i)/m) and stipulating that its argument should
2216 * always be integral in the context tableau, i.e., m q = c + \sum a_i y_i.
2217 * Since q is expressed in the tableau as
2218 * c + \sum a_i y_i - m q >= 0
2219 * -c - \sum a_i y_i + m q + m - 1 >= 0
2220 * it is sufficient to add the inequality
2221 * -c - \sum a_i y_i + m q >= 0
2222 * In the part of the context where this inequality does not hold, the
2223 * main tableau is marked as being empty.
2225 static struct isl_sol *find_solutions(struct isl_sol *sol, struct isl_tab *tab)
2227 struct isl_tab **context_tab;
2232 context_tab = &sol->context_tab;
2236 if ((*context_tab)->empty)
2239 for (; tab && !tab->empty; tab = restore_lexmin(tab)) {
2246 for (row = tab->n_redundant; row < tab->n_row; ++row) {
2247 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
2249 sgn = row_sign(tab, sol, row);
2252 tab->row_sign[row] = sgn;
2253 if (sgn == isl_tab_row_any)
2255 if (sgn == isl_tab_row_any && split == -1)
2257 if (sgn == isl_tab_row_neg)
2260 if (row < tab->n_row)
2263 struct isl_vec *ineq;
2265 split = best_split(tab, *context_tab);
2268 ineq = get_row_parameter_ineq(tab, split);
2272 for (row = tab->n_redundant; row < tab->n_row; ++row) {
2273 if (!isl_tab_var_from_row(tab, row)->is_nonneg)
2275 if (tab->row_sign[row] == isl_tab_row_any)
2276 tab->row_sign[row] = isl_tab_row_unknown;
2278 tab->row_sign[split] = isl_tab_row_pos;
2279 sol = find_in_pos(sol, tab, ineq->el);
2280 tab->row_sign[split] = isl_tab_row_neg;
2282 isl_seq_neg(ineq->el, ineq->el, ineq->size);
2283 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
2284 *context_tab = add_lexmin_ineq(*context_tab, ineq->el);
2285 *context_tab = check_samples(*context_tab, ineq->el, 0);
2293 row = first_non_integer(tab, &flags);
2296 if (ISL_FL_ISSET(flags, I_PAR)) {
2297 if (ISL_FL_ISSET(flags, I_VAR)) {
2298 tab = isl_tab_mark_empty(tab);
2301 row = add_cut(tab, row);
2302 } else if (ISL_FL_ISSET(flags, I_VAR)) {
2303 struct isl_vec *div;
2304 struct isl_vec *ineq;
2306 if (isl_tab_extend_cons(*context_tab, 3) < 0)
2308 div = get_row_split_div(tab, row);
2311 d = get_div(tab, context_tab, div);
2315 ineq = ineq_for_div((*context_tab)->bset, d);
2316 sol = no_sol_in_strict(sol, tab, ineq);
2317 isl_seq_neg(ineq->el, ineq->el, ineq->size);
2318 *context_tab = add_lexmin_ineq(*context_tab, ineq->el);
2319 *context_tab = check_samples(*context_tab, ineq->el, 0);
2323 tab = set_row_cst_to_div(tab, row, d);
2325 row = add_parametric_cut(tab, row, context_tab);
2330 sol = sol->add(sol, tab);
2339 /* Compute the lexicographic minimum of the set represented by the main
2340 * tableau "tab" within the context "sol->context_tab".
2342 * As a preprocessing step, we first transfer all the purely parametric
2343 * equalities from the main tableau to the context tableau, i.e.,
2344 * parameters that have been pivoted to a row.
2345 * These equalities are ignored by the main algorithm, because the
2346 * corresponding rows may not be marked as being non-negative.
2347 * In parts of the context where the added equality does not hold,
2348 * the main tableau is marked as being empty.
2350 static struct isl_sol *find_solutions_main(struct isl_sol *sol,
2351 struct isl_tab *tab)
2355 for (row = tab->n_redundant; row < tab->n_row; ++row) {
2359 if (tab->row_var[row] < 0)
2361 if (tab->row_var[row] >= tab->n_param &&
2362 tab->row_var[row] < tab->n_var - tab->n_div)
2364 if (tab->row_var[row] < tab->n_param)
2365 p = tab->row_var[row];
2367 p = tab->row_var[row]
2368 + tab->n_param - (tab->n_var - tab->n_div);
2370 if (isl_tab_extend_cons(sol->context_tab, 2) < 0)
2373 eq = isl_vec_alloc(tab->mat->ctx, 1+tab->n_param+tab->n_div);
2374 get_row_parameter_line(tab, row, eq->el);
2375 isl_int_neg(eq->el[1 + p], tab->mat->row[row][0]);
2376 eq = isl_vec_normalize(eq);
2378 sol = no_sol_in_strict(sol, tab, eq);
2380 isl_seq_neg(eq->el, eq->el, eq->size);
2381 sol = no_sol_in_strict(sol, tab, eq);
2382 isl_seq_neg(eq->el, eq->el, eq->size);
2384 sol->context_tab = add_lexmin_eq(sol->context_tab, eq->el);
2385 context_valid_sample_or_feasible(sol, eq->el, 1);
2386 sol->context_tab = check_samples(sol->context_tab, eq->el, 1);
2390 isl_tab_mark_redundant(tab, row);
2392 if (!sol->context_tab)
2394 if (sol->context_tab->empty)
2397 row = tab->n_redundant - 1;
2400 return find_solutions(sol, tab);
2407 static struct isl_sol_map *sol_map_find_solutions(struct isl_sol_map *sol_map,
2408 struct isl_tab *tab)
2410 return (struct isl_sol_map *)find_solutions_main(&sol_map->sol, tab);
2413 /* Check if integer division "div" of "dom" also occurs in "bmap".
2414 * If so, return its position within the divs.
2415 * If not, return -1.
2417 static int find_context_div(struct isl_basic_map *bmap,
2418 struct isl_basic_set *dom, unsigned div)
2421 unsigned b_dim = isl_dim_total(bmap->dim);
2422 unsigned d_dim = isl_dim_total(dom->dim);
2424 if (isl_int_is_zero(dom->div[div][0]))
2426 if (isl_seq_first_non_zero(dom->div[div] + 2 + d_dim, dom->n_div) != -1)
2429 for (i = 0; i < bmap->n_div; ++i) {
2430 if (isl_int_is_zero(bmap->div[i][0]))
2432 if (isl_seq_first_non_zero(bmap->div[i] + 2 + d_dim,
2433 (b_dim - d_dim) + bmap->n_div) != -1)
2435 if (isl_seq_eq(bmap->div[i], dom->div[div], 2 + d_dim))
2441 /* The correspondence between the variables in the main tableau,
2442 * the context tableau, and the input map and domain is as follows.
2443 * The first n_param and the last n_div variables of the main tableau
2444 * form the variables of the context tableau.
2445 * In the basic map, these n_param variables correspond to the
2446 * parameters and the input dimensions. In the domain, they correspond
2447 * to the parameters and the set dimensions.
2448 * The n_div variables correspond to the integer divisions in the domain.
2449 * To ensure that everything lines up, we may need to copy some of the
2450 * integer divisions of the domain to the map. These have to be placed
2451 * in the same order as those in the context and they have to be placed
2452 * after any other integer divisions that the map may have.
2453 * This function performs the required reordering.
2455 static struct isl_basic_map *align_context_divs(struct isl_basic_map *bmap,
2456 struct isl_basic_set *dom)
2462 for (i = 0; i < dom->n_div; ++i)
2463 if (find_context_div(bmap, dom, i) != -1)
2465 other = bmap->n_div - common;
2466 if (dom->n_div - common > 0) {
2467 bmap = isl_basic_map_extend_dim(bmap, isl_dim_copy(bmap->dim),
2468 dom->n_div - common, 0, 0);
2472 for (i = 0; i < dom->n_div; ++i) {
2473 int pos = find_context_div(bmap, dom, i);
2475 pos = isl_basic_map_alloc_div(bmap);
2478 isl_int_set_si(bmap->div[pos][0], 0);
2480 if (pos != other + i)
2481 isl_basic_map_swap_div(bmap, pos, other + i);
2485 isl_basic_map_free(bmap);
2489 /* Compute the lexicographic minimum (or maximum if "max" is set)
2490 * of "bmap" over the domain "dom" and return the result as a map.
2491 * If "empty" is not NULL, then *empty is assigned a set that
2492 * contains those parts of the domain where there is no solution.
2493 * If "bmap" is marked as rational (ISL_BASIC_MAP_RATIONAL),
2494 * then we compute the rational optimum. Otherwise, we compute
2495 * the integral optimum.
2497 * We perform some preprocessing. As the PILP solver does not
2498 * handle implicit equalities very well, we first make sure all
2499 * the equalities are explicitly available.
2500 * We also make sure the divs in the domain are properly order,
2501 * because they will be added one by one in the given order
2502 * during the construction of the solution map.
2504 struct isl_map *isl_tab_basic_map_partial_lexopt(
2505 struct isl_basic_map *bmap, struct isl_basic_set *dom,
2506 struct isl_set **empty, int max)
2508 struct isl_tab *tab;
2509 struct isl_map *result = NULL;
2510 struct isl_sol_map *sol_map = NULL;
2517 isl_assert(bmap->ctx,
2518 isl_basic_map_compatible_domain(bmap, dom), goto error);
2520 bmap = isl_basic_map_detect_equalities(bmap);
2523 dom = isl_basic_set_order_divs(dom);
2524 bmap = align_context_divs(bmap, dom);
2526 sol_map = sol_map_init(bmap, dom, !!empty, max);
2530 if (isl_basic_set_fast_is_empty(sol_map->sol.context_tab->bset))
2532 else if (isl_basic_map_fast_is_empty(bmap))
2533 sol_map = add_empty(sol_map);
2535 tab = tab_for_lexmin(bmap,
2536 sol_map->sol.context_tab->bset, 1, max);
2537 tab = tab_detect_nonnegative_parameters(tab,
2538 sol_map->sol.context_tab);
2539 sol_map = sol_map_find_solutions(sol_map, tab);
2544 result = isl_map_copy(sol_map->map);
2546 *empty = isl_set_copy(sol_map->empty);
2547 sol_map_free(sol_map);
2548 isl_basic_map_free(bmap);
2551 sol_map_free(sol_map);
2552 isl_basic_map_free(bmap);
2556 struct isl_sol_for {
2558 int (*fn)(__isl_take isl_basic_set *dom,
2559 __isl_take isl_mat *map, void *user);
2564 static void sol_for_free(struct isl_sol_for *sol_for)
2566 isl_tab_free(sol_for->sol.context_tab);
2570 static void sol_for_free_wrap(struct isl_sol *sol)
2572 sol_for_free((struct isl_sol_for *)sol);
2575 /* Add the solution identified by the tableau and the context tableau.
2577 * See documentation of sol_map_add for more details.
2579 * Instead of constructing a basic map, this function calls a user
2580 * defined function with the current context as a basic set and
2581 * an affine matrix reprenting the relation between the input and output.
2582 * The number of rows in this matrix is equal to one plus the number
2583 * of output variables. The number of columns is equal to one plus
2584 * the total dimension of the context, i.e., the number of parameters,
2585 * input variables and divs. Since some of the columns in the matrix
2586 * may refer to the divs, the basic set is not simplified.
2587 * (Simplification may reorder or remove divs.)
2589 static struct isl_sol_for *sol_for_add(struct isl_sol_for *sol,
2590 struct isl_tab *tab)
2592 struct isl_tab *context_tab;
2593 struct isl_basic_set *bset;
2594 struct isl_mat *mat = NULL;
2606 context_tab = sol->sol.context_tab;
2608 n_out = tab->n_var - tab->n_param - tab->n_div;
2609 mat = isl_mat_alloc(tab->mat->ctx, 1 + n_out, 1 + tab->n_param + tab->n_div);
2613 isl_seq_clr(mat->row[0] + 1, mat->n_col - 1);
2614 isl_int_set_si(mat->row[0][0], 1);
2615 for (row = 0; row < n_out; ++row) {
2616 int i = tab->n_param + row;
2619 isl_seq_clr(mat->row[1 + row], mat->n_col);
2620 if (!tab->var[i].is_row)
2623 r = tab->var[i].index;
2626 isl_assert(mat->ctx, isl_int_eq(tab->mat->row[r][2],
2627 tab->mat->row[r][0]),
2629 isl_int_set(mat->row[1 + row][0], tab->mat->row[r][1]);
2630 for (j = 0; j < tab->n_param; ++j) {
2632 if (tab->var[j].is_row)
2634 col = tab->var[j].index;
2635 isl_int_set(mat->row[1 + row][1 + j],
2636 tab->mat->row[r][off + col]);
2638 for (j = 0; j < tab->n_div; ++j) {
2640 if (tab->var[tab->n_var - tab->n_div+j].is_row)
2642 col = tab->var[tab->n_var - tab->n_div+j].index;
2643 isl_int_set(mat->row[1 + row][1 + tab->n_param + j],
2644 tab->mat->row[r][off + col]);
2646 if (!isl_int_is_one(tab->mat->row[r][0]))
2647 isl_seq_scale_down(mat->row[1 + row], mat->row[1 + row],
2648 tab->mat->row[r][0], mat->n_col);
2650 isl_seq_neg(mat->row[1 + row], mat->row[1 + row],
2654 bset = isl_basic_set_dup(context_tab->bset);
2655 bset = isl_basic_set_finalize(bset);
2657 if (sol->fn(bset, isl_mat_copy(mat), sol->user) < 0)
2664 sol_free(&sol->sol);
2668 static struct isl_sol *sol_for_add_wrap(struct isl_sol *sol,
2669 struct isl_tab *tab)
2671 return (struct isl_sol *)sol_for_add((struct isl_sol_for *)sol, tab);
2674 static struct isl_sol_for *sol_for_init(struct isl_basic_map *bmap, int max,
2675 int (*fn)(__isl_take isl_basic_set *dom, __isl_take isl_mat *map,
2679 struct isl_sol_for *sol_for = NULL;
2680 struct isl_dim *dom_dim;
2681 struct isl_basic_set *dom = NULL;
2682 struct isl_tab *context_tab;
2685 sol_for = isl_calloc_type(bset->ctx, struct isl_sol_for);
2689 dom_dim = isl_dim_domain(isl_dim_copy(bmap->dim));
2690 dom = isl_basic_set_universe(dom_dim);
2693 sol_for->user = user;
2695 sol_for->sol.add = &sol_for_add_wrap;
2696 sol_for->sol.free = &sol_for_free_wrap;
2698 context_tab = context_tab_for_lexmin(isl_basic_set_copy(dom));
2699 context_tab = restore_lexmin(context_tab);
2700 sol_for->sol.context_tab = context_tab;
2701 f = context_is_feasible(&sol_for->sol);
2705 isl_basic_set_free(dom);
2708 isl_basic_set_free(dom);
2709 sol_for_free(sol_for);
2713 static struct isl_sol_for *sol_for_find_solutions(struct isl_sol_for *sol_for,
2714 struct isl_tab *tab)
2716 return (struct isl_sol_for *)find_solutions_main(&sol_for->sol, tab);
2719 int isl_basic_map_foreach_lexopt(__isl_keep isl_basic_map *bmap, int max,
2720 int (*fn)(__isl_take isl_basic_set *dom, __isl_take isl_mat *map,
2724 struct isl_sol_for *sol_for = NULL;
2726 bmap = isl_basic_map_copy(bmap);
2730 bmap = isl_basic_map_detect_equalities(bmap);
2731 sol_for = sol_for_init(bmap, max, fn, user);
2733 if (isl_basic_map_fast_is_empty(bmap))
2736 struct isl_tab *tab;
2737 tab = tab_for_lexmin(bmap,
2738 sol_for->sol.context_tab->bset, 1, max);
2739 tab = tab_detect_nonnegative_parameters(tab,
2740 sol_for->sol.context_tab);
2741 sol_for = sol_for_find_solutions(sol_for, tab);
2746 sol_for_free(sol_for);
2747 isl_basic_map_free(bmap);
2750 sol_for_free(sol_for);
2751 isl_basic_map_free(bmap);
2755 int isl_basic_map_foreach_lexmin(__isl_keep isl_basic_map *bmap,
2756 int (*fn)(__isl_take isl_basic_set *dom, __isl_take isl_mat *map,
2760 return isl_basic_map_foreach_lexopt(bmap, 0, fn, user);
2763 int isl_basic_map_foreach_lexmax(__isl_keep isl_basic_map *bmap,
2764 int (*fn)(__isl_take isl_basic_set *dom, __isl_take isl_mat *map,
2768 return isl_basic_map_foreach_lexopt(bmap, 1, fn, user);