2 #include "isl_map_private.h"
7 * The implementation of tableaus in this file was inspired by Section 8
8 * of David Detlefs, Greg Nelson and James B. Saxe, "Simplify: a theorem
9 * prover for program checking".
12 struct isl_tab *isl_tab_alloc(struct isl_ctx *ctx,
13 unsigned n_row, unsigned n_var, unsigned M)
19 tab = isl_calloc_type(ctx, struct isl_tab);
22 tab->mat = isl_mat_alloc(ctx, n_row, off + n_var);
25 tab->var = isl_alloc_array(ctx, struct isl_tab_var, n_var);
28 tab->con = isl_alloc_array(ctx, struct isl_tab_var, n_row);
31 tab->col_var = isl_alloc_array(ctx, int, n_var);
34 tab->row_var = isl_alloc_array(ctx, int, n_row);
37 for (i = 0; i < n_var; ++i) {
38 tab->var[i].index = i;
39 tab->var[i].is_row = 0;
40 tab->var[i].is_nonneg = 0;
41 tab->var[i].is_zero = 0;
42 tab->var[i].is_redundant = 0;
43 tab->var[i].frozen = 0;
44 tab->var[i].negated = 0;
64 tab->bottom.type = isl_tab_undo_bottom;
65 tab->bottom.next = NULL;
66 tab->top = &tab->bottom;
78 int isl_tab_extend_cons(struct isl_tab *tab, unsigned n_new)
80 unsigned off = 2 + tab->M;
85 if (tab->max_con < tab->n_con + n_new) {
86 struct isl_tab_var *con;
88 con = isl_realloc_array(tab->mat->ctx, tab->con,
89 struct isl_tab_var, tab->max_con + n_new);
93 tab->max_con += n_new;
95 if (tab->mat->n_row < tab->n_row + n_new) {
98 tab->mat = isl_mat_extend(tab->mat,
99 tab->n_row + n_new, off + tab->n_col);
102 row_var = isl_realloc_array(tab->mat->ctx, tab->row_var,
103 int, tab->mat->n_row);
106 tab->row_var = row_var;
108 enum isl_tab_row_sign *s;
109 s = isl_realloc_array(tab->mat->ctx, tab->row_sign,
110 enum isl_tab_row_sign, tab->mat->n_row);
119 /* Make room for at least n_new extra variables.
120 * Return -1 if anything went wrong.
122 int isl_tab_extend_vars(struct isl_tab *tab, unsigned n_new)
124 struct isl_tab_var *var;
125 unsigned off = 2 + tab->M;
127 if (tab->max_var < tab->n_var + n_new) {
128 var = isl_realloc_array(tab->mat->ctx, tab->var,
129 struct isl_tab_var, tab->n_var + n_new);
133 tab->max_var += n_new;
136 if (tab->mat->n_col < off + tab->n_col + n_new) {
139 tab->mat = isl_mat_extend(tab->mat,
140 tab->mat->n_row, off + tab->n_col + n_new);
143 p = isl_realloc_array(tab->mat->ctx, tab->col_var,
144 int, tab->n_col + n_new);
153 struct isl_tab *isl_tab_extend(struct isl_tab *tab, unsigned n_new)
155 if (isl_tab_extend_cons(tab, n_new) >= 0)
162 static void free_undo(struct isl_tab *tab)
164 struct isl_tab_undo *undo, *next;
166 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
173 void isl_tab_free(struct isl_tab *tab)
178 isl_mat_free(tab->mat);
179 isl_vec_free(tab->dual);
180 isl_basic_set_free(tab->bset);
186 isl_mat_free(tab->samples);
187 free(tab->sample_index);
188 isl_mat_free(tab->basis);
192 struct isl_tab *isl_tab_dup(struct isl_tab *tab)
202 dup = isl_calloc_type(tab->ctx, struct isl_tab);
205 dup->mat = isl_mat_dup(tab->mat);
208 dup->var = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->max_var);
211 for (i = 0; i < tab->n_var; ++i)
212 dup->var[i] = tab->var[i];
213 dup->con = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->max_con);
216 for (i = 0; i < tab->n_con; ++i)
217 dup->con[i] = tab->con[i];
218 dup->col_var = isl_alloc_array(tab->ctx, int, tab->mat->n_col - off);
221 for (i = 0; i < tab->n_col; ++i)
222 dup->col_var[i] = tab->col_var[i];
223 dup->row_var = isl_alloc_array(tab->ctx, int, tab->mat->n_row);
226 for (i = 0; i < tab->n_row; ++i)
227 dup->row_var[i] = tab->row_var[i];
229 dup->row_sign = isl_alloc_array(tab->ctx, enum isl_tab_row_sign,
233 for (i = 0; i < tab->n_row; ++i)
234 dup->row_sign[i] = tab->row_sign[i];
237 dup->samples = isl_mat_dup(tab->samples);
240 dup->sample_index = isl_alloc_array(tab->mat->ctx, int,
241 tab->samples->n_row);
242 if (!dup->sample_index)
244 dup->n_sample = tab->n_sample;
245 dup->n_outside = tab->n_outside;
247 dup->n_row = tab->n_row;
248 dup->n_con = tab->n_con;
249 dup->n_eq = tab->n_eq;
250 dup->max_con = tab->max_con;
251 dup->n_col = tab->n_col;
252 dup->n_var = tab->n_var;
253 dup->max_var = tab->max_var;
254 dup->n_param = tab->n_param;
255 dup->n_div = tab->n_div;
256 dup->n_dead = tab->n_dead;
257 dup->n_redundant = tab->n_redundant;
258 dup->rational = tab->rational;
259 dup->empty = tab->empty;
263 tab->cone = tab->cone;
264 dup->bottom.type = isl_tab_undo_bottom;
265 dup->bottom.next = NULL;
266 dup->top = &dup->bottom;
268 dup->n_zero = tab->n_zero;
269 dup->n_unbounded = tab->n_unbounded;
270 dup->basis = isl_mat_dup(tab->basis);
278 /* Construct the coefficient matrix of the product tableau
280 * mat{1,2} is the coefficient matrix of tableau {1,2}
281 * row{1,2} is the number of rows in tableau {1,2}
282 * col{1,2} is the number of columns in tableau {1,2}
283 * off is the offset to the coefficient column (skipping the
284 * denominator, the constant term and the big parameter if any)
285 * r{1,2} is the number of redundant rows in tableau {1,2}
286 * d{1,2} is the number of dead columns in tableau {1,2}
288 * The order of the rows and columns in the result is as explained
289 * in isl_tab_product.
291 static struct isl_mat *tab_mat_product(struct isl_mat *mat1,
292 struct isl_mat *mat2, unsigned row1, unsigned row2,
293 unsigned col1, unsigned col2,
294 unsigned off, unsigned r1, unsigned r2, unsigned d1, unsigned d2)
297 struct isl_mat *prod;
300 prod = isl_mat_alloc(mat1->ctx, mat1->n_row + mat2->n_row,
304 for (i = 0; i < r1; ++i) {
305 isl_seq_cpy(prod->row[n + i], mat1->row[i], off + d1);
306 isl_seq_clr(prod->row[n + i] + off + d1, d2);
307 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
308 mat1->row[i] + off + d1, col1 - d1);
309 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
313 for (i = 0; i < r2; ++i) {
314 isl_seq_cpy(prod->row[n + i], mat2->row[i], off);
315 isl_seq_clr(prod->row[n + i] + off, d1);
316 isl_seq_cpy(prod->row[n + i] + off + d1,
317 mat2->row[i] + off, d2);
318 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
319 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
320 mat2->row[i] + off + d2, col2 - d2);
324 for (i = 0; i < row1 - r1; ++i) {
325 isl_seq_cpy(prod->row[n + i], mat1->row[r1 + i], off + d1);
326 isl_seq_clr(prod->row[n + i] + off + d1, d2);
327 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
328 mat1->row[r1 + i] + off + d1, col1 - d1);
329 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
333 for (i = 0; i < row2 - r2; ++i) {
334 isl_seq_cpy(prod->row[n + i], mat2->row[r2 + i], off);
335 isl_seq_clr(prod->row[n + i] + off, d1);
336 isl_seq_cpy(prod->row[n + i] + off + d1,
337 mat2->row[r2 + i] + off, d2);
338 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
339 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
340 mat2->row[r2 + i] + off + d2, col2 - d2);
346 /* Update the row or column index of a variable that corresponds
347 * to a variable in the first input tableau.
349 static void update_index1(struct isl_tab_var *var,
350 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
352 if (var->index == -1)
354 if (var->is_row && var->index >= r1)
356 if (!var->is_row && var->index >= d1)
360 /* Update the row or column index of a variable that corresponds
361 * to a variable in the second input tableau.
363 static void update_index2(struct isl_tab_var *var,
364 unsigned row1, unsigned col1,
365 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
367 if (var->index == -1)
382 /* Create a tableau that represents the Cartesian product of the sets
383 * represented by tableaus tab1 and tab2.
384 * The order of the rows in the product is
385 * - redundant rows of tab1
386 * - redundant rows of tab2
387 * - non-redundant rows of tab1
388 * - non-redundant rows of tab2
389 * The order of the columns is
392 * - coefficient of big parameter, if any
393 * - dead columns of tab1
394 * - dead columns of tab2
395 * - live columns of tab1
396 * - live columns of tab2
397 * The order of the variables and the constraints is a concatenation
398 * of order in the two input tableaus.
400 struct isl_tab *isl_tab_product(struct isl_tab *tab1, struct isl_tab *tab2)
403 struct isl_tab *prod;
405 unsigned r1, r2, d1, d2;
410 isl_assert(tab1->mat->ctx, tab1->M == tab2->M, return NULL);
411 isl_assert(tab1->mat->ctx, tab1->rational == tab2->rational, return NULL);
412 isl_assert(tab1->mat->ctx, tab1->cone == tab2->cone, return NULL);
413 isl_assert(tab1->mat->ctx, !tab1->row_sign, return NULL);
414 isl_assert(tab1->mat->ctx, !tab2->row_sign, return NULL);
415 isl_assert(tab1->mat->ctx, tab1->n_param == 0, return NULL);
416 isl_assert(tab1->mat->ctx, tab2->n_param == 0, return NULL);
417 isl_assert(tab1->mat->ctx, tab1->n_div == 0, return NULL);
418 isl_assert(tab1->mat->ctx, tab2->n_div == 0, return NULL);
421 r1 = tab1->n_redundant;
422 r2 = tab2->n_redundant;
425 prod = isl_calloc_type(tab1->mat->ctx, struct isl_tab);
428 prod->mat = tab_mat_product(tab1->mat, tab2->mat,
429 tab1->n_row, tab2->n_row,
430 tab1->n_col, tab2->n_col, off, r1, r2, d1, d2);
433 prod->var = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
434 tab1->max_var + tab2->max_var);
437 for (i = 0; i < tab1->n_var; ++i) {
438 prod->var[i] = tab1->var[i];
439 update_index1(&prod->var[i], r1, r2, d1, d2);
441 for (i = 0; i < tab2->n_var; ++i) {
442 prod->var[tab1->n_var + i] = tab2->var[i];
443 update_index2(&prod->var[tab1->n_var + i],
444 tab1->n_row, tab1->n_col,
447 prod->con = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
448 tab1->max_con + tab2->max_con);
451 for (i = 0; i < tab1->n_con; ++i) {
452 prod->con[i] = tab1->con[i];
453 update_index1(&prod->con[i], r1, r2, d1, d2);
455 for (i = 0; i < tab2->n_con; ++i) {
456 prod->con[tab1->n_con + i] = tab2->con[i];
457 update_index2(&prod->con[tab1->n_con + i],
458 tab1->n_row, tab1->n_col,
461 prod->col_var = isl_alloc_array(tab1->mat->ctx, int,
462 tab1->n_col + tab2->n_col);
465 for (i = 0; i < tab1->n_col; ++i) {
466 int pos = i < d1 ? i : i + d2;
467 prod->col_var[pos] = tab1->col_var[i];
469 for (i = 0; i < tab2->n_col; ++i) {
470 int pos = i < d2 ? d1 + i : tab1->n_col + i;
471 int t = tab2->col_var[i];
476 prod->col_var[pos] = t;
478 prod->row_var = isl_alloc_array(tab1->mat->ctx, int,
479 tab1->mat->n_row + tab2->mat->n_row);
482 for (i = 0; i < tab1->n_row; ++i) {
483 int pos = i < r1 ? i : i + r2;
484 prod->row_var[pos] = tab1->row_var[i];
486 for (i = 0; i < tab2->n_row; ++i) {
487 int pos = i < r2 ? r1 + i : tab1->n_row + i;
488 int t = tab2->row_var[i];
493 prod->row_var[pos] = t;
495 prod->samples = NULL;
496 prod->sample_index = NULL;
497 prod->n_row = tab1->n_row + tab2->n_row;
498 prod->n_con = tab1->n_con + tab2->n_con;
500 prod->max_con = tab1->max_con + tab2->max_con;
501 prod->n_col = tab1->n_col + tab2->n_col;
502 prod->n_var = tab1->n_var + tab2->n_var;
503 prod->max_var = tab1->max_var + tab2->max_var;
506 prod->n_dead = tab1->n_dead + tab2->n_dead;
507 prod->n_redundant = tab1->n_redundant + tab2->n_redundant;
508 prod->rational = tab1->rational;
509 prod->empty = tab1->empty || tab2->empty;
513 prod->cone = tab1->cone;
514 prod->bottom.type = isl_tab_undo_bottom;
515 prod->bottom.next = NULL;
516 prod->top = &prod->bottom;
519 prod->n_unbounded = 0;
528 static struct isl_tab_var *var_from_index(struct isl_tab *tab, int i)
533 return &tab->con[~i];
536 struct isl_tab_var *isl_tab_var_from_row(struct isl_tab *tab, int i)
538 return var_from_index(tab, tab->row_var[i]);
541 static struct isl_tab_var *var_from_col(struct isl_tab *tab, int i)
543 return var_from_index(tab, tab->col_var[i]);
546 /* Check if there are any upper bounds on column variable "var",
547 * i.e., non-negative rows where var appears with a negative coefficient.
548 * Return 1 if there are no such bounds.
550 static int max_is_manifestly_unbounded(struct isl_tab *tab,
551 struct isl_tab_var *var)
554 unsigned off = 2 + tab->M;
558 for (i = tab->n_redundant; i < tab->n_row; ++i) {
559 if (!isl_int_is_neg(tab->mat->row[i][off + var->index]))
561 if (isl_tab_var_from_row(tab, i)->is_nonneg)
567 /* Check if there are any lower bounds on column variable "var",
568 * i.e., non-negative rows where var appears with a positive coefficient.
569 * Return 1 if there are no such bounds.
571 static int min_is_manifestly_unbounded(struct isl_tab *tab,
572 struct isl_tab_var *var)
575 unsigned off = 2 + tab->M;
579 for (i = tab->n_redundant; i < tab->n_row; ++i) {
580 if (!isl_int_is_pos(tab->mat->row[i][off + var->index]))
582 if (isl_tab_var_from_row(tab, i)->is_nonneg)
588 static int row_cmp(struct isl_tab *tab, int r1, int r2, int c, isl_int t)
590 unsigned off = 2 + tab->M;
594 isl_int_mul(t, tab->mat->row[r1][2], tab->mat->row[r2][off+c]);
595 isl_int_submul(t, tab->mat->row[r2][2], tab->mat->row[r1][off+c]);
600 isl_int_mul(t, tab->mat->row[r1][1], tab->mat->row[r2][off + c]);
601 isl_int_submul(t, tab->mat->row[r2][1], tab->mat->row[r1][off + c]);
602 return isl_int_sgn(t);
605 /* Given the index of a column "c", return the index of a row
606 * that can be used to pivot the column in, with either an increase
607 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
608 * If "var" is not NULL, then the row returned will be different from
609 * the one associated with "var".
611 * Each row in the tableau is of the form
613 * x_r = a_r0 + \sum_i a_ri x_i
615 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
616 * impose any limit on the increase or decrease in the value of x_c
617 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
618 * for the row with the smallest (most stringent) such bound.
619 * Note that the common denominator of each row drops out of the fraction.
620 * To check if row j has a smaller bound than row r, i.e.,
621 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
622 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
623 * where -sign(a_jc) is equal to "sgn".
625 static int pivot_row(struct isl_tab *tab,
626 struct isl_tab_var *var, int sgn, int c)
630 unsigned off = 2 + tab->M;
634 for (j = tab->n_redundant; j < tab->n_row; ++j) {
635 if (var && j == var->index)
637 if (!isl_tab_var_from_row(tab, j)->is_nonneg)
639 if (sgn * isl_int_sgn(tab->mat->row[j][off + c]) >= 0)
645 tsgn = sgn * row_cmp(tab, r, j, c, t);
646 if (tsgn < 0 || (tsgn == 0 &&
647 tab->row_var[j] < tab->row_var[r]))
654 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
655 * (sgn < 0) the value of row variable var.
656 * If not NULL, then skip_var is a row variable that should be ignored
657 * while looking for a pivot row. It is usually equal to var.
659 * As the given row in the tableau is of the form
661 * x_r = a_r0 + \sum_i a_ri x_i
663 * we need to find a column such that the sign of a_ri is equal to "sgn"
664 * (such that an increase in x_i will have the desired effect) or a
665 * column with a variable that may attain negative values.
666 * If a_ri is positive, then we need to move x_i in the same direction
667 * to obtain the desired effect. Otherwise, x_i has to move in the
668 * opposite direction.
670 static void find_pivot(struct isl_tab *tab,
671 struct isl_tab_var *var, struct isl_tab_var *skip_var,
672 int sgn, int *row, int *col)
679 isl_assert(tab->mat->ctx, var->is_row, return);
680 tr = tab->mat->row[var->index] + 2 + tab->M;
683 for (j = tab->n_dead; j < tab->n_col; ++j) {
684 if (isl_int_is_zero(tr[j]))
686 if (isl_int_sgn(tr[j]) != sgn &&
687 var_from_col(tab, j)->is_nonneg)
689 if (c < 0 || tab->col_var[j] < tab->col_var[c])
695 sgn *= isl_int_sgn(tr[c]);
696 r = pivot_row(tab, skip_var, sgn, c);
697 *row = r < 0 ? var->index : r;
701 /* Return 1 if row "row" represents an obviously redundant inequality.
703 * - it represents an inequality or a variable
704 * - that is the sum of a non-negative sample value and a positive
705 * combination of zero or more non-negative constraints.
707 int isl_tab_row_is_redundant(struct isl_tab *tab, int row)
710 unsigned off = 2 + tab->M;
712 if (tab->row_var[row] < 0 && !isl_tab_var_from_row(tab, row)->is_nonneg)
715 if (isl_int_is_neg(tab->mat->row[row][1]))
717 if (tab->M && isl_int_is_neg(tab->mat->row[row][2]))
720 for (i = tab->n_dead; i < tab->n_col; ++i) {
721 if (isl_int_is_zero(tab->mat->row[row][off + i]))
723 if (tab->col_var[i] >= 0)
725 if (isl_int_is_neg(tab->mat->row[row][off + i]))
727 if (!var_from_col(tab, i)->is_nonneg)
733 static void swap_rows(struct isl_tab *tab, int row1, int row2)
736 t = tab->row_var[row1];
737 tab->row_var[row1] = tab->row_var[row2];
738 tab->row_var[row2] = t;
739 isl_tab_var_from_row(tab, row1)->index = row1;
740 isl_tab_var_from_row(tab, row2)->index = row2;
741 tab->mat = isl_mat_swap_rows(tab->mat, row1, row2);
745 t = tab->row_sign[row1];
746 tab->row_sign[row1] = tab->row_sign[row2];
747 tab->row_sign[row2] = t;
750 static int push_union(struct isl_tab *tab,
751 enum isl_tab_undo_type type, union isl_tab_undo_val u) WARN_UNUSED;
752 static int push_union(struct isl_tab *tab,
753 enum isl_tab_undo_type type, union isl_tab_undo_val u)
755 struct isl_tab_undo *undo;
760 undo = isl_alloc_type(tab->mat->ctx, struct isl_tab_undo);
765 undo->next = tab->top;
771 int isl_tab_push_var(struct isl_tab *tab,
772 enum isl_tab_undo_type type, struct isl_tab_var *var)
774 union isl_tab_undo_val u;
776 u.var_index = tab->row_var[var->index];
778 u.var_index = tab->col_var[var->index];
779 return push_union(tab, type, u);
782 int isl_tab_push(struct isl_tab *tab, enum isl_tab_undo_type type)
784 union isl_tab_undo_val u = { 0 };
785 return push_union(tab, type, u);
788 /* Push a record on the undo stack describing the current basic
789 * variables, so that the this state can be restored during rollback.
791 int isl_tab_push_basis(struct isl_tab *tab)
794 union isl_tab_undo_val u;
796 u.col_var = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
799 for (i = 0; i < tab->n_col; ++i)
800 u.col_var[i] = tab->col_var[i];
801 return push_union(tab, isl_tab_undo_saved_basis, u);
804 int isl_tab_push_callback(struct isl_tab *tab, struct isl_tab_callback *callback)
806 union isl_tab_undo_val u;
807 u.callback = callback;
808 return push_union(tab, isl_tab_undo_callback, u);
811 struct isl_tab *isl_tab_init_samples(struct isl_tab *tab)
818 tab->samples = isl_mat_alloc(tab->mat->ctx, 1, 1 + tab->n_var);
821 tab->sample_index = isl_alloc_array(tab->mat->ctx, int, 1);
822 if (!tab->sample_index)
830 struct isl_tab *isl_tab_add_sample(struct isl_tab *tab,
831 __isl_take isl_vec *sample)
836 if (tab->n_sample + 1 > tab->samples->n_row) {
837 int *t = isl_realloc_array(tab->mat->ctx,
838 tab->sample_index, int, tab->n_sample + 1);
841 tab->sample_index = t;
844 tab->samples = isl_mat_extend(tab->samples,
845 tab->n_sample + 1, tab->samples->n_col);
849 isl_seq_cpy(tab->samples->row[tab->n_sample], sample->el, sample->size);
850 isl_vec_free(sample);
851 tab->sample_index[tab->n_sample] = tab->n_sample;
856 isl_vec_free(sample);
861 struct isl_tab *isl_tab_drop_sample(struct isl_tab *tab, int s)
863 if (s != tab->n_outside) {
864 int t = tab->sample_index[tab->n_outside];
865 tab->sample_index[tab->n_outside] = tab->sample_index[s];
866 tab->sample_index[s] = t;
867 isl_mat_swap_rows(tab->samples, tab->n_outside, s);
870 if (isl_tab_push(tab, isl_tab_undo_drop_sample) < 0) {
878 /* Record the current number of samples so that we can remove newer
879 * samples during a rollback.
881 int isl_tab_save_samples(struct isl_tab *tab)
883 union isl_tab_undo_val u;
889 return push_union(tab, isl_tab_undo_saved_samples, u);
892 /* Mark row with index "row" as being redundant.
893 * If we may need to undo the operation or if the row represents
894 * a variable of the original problem, the row is kept,
895 * but no longer considered when looking for a pivot row.
896 * Otherwise, the row is simply removed.
898 * The row may be interchanged with some other row. If it
899 * is interchanged with a later row, return 1. Otherwise return 0.
900 * If the rows are checked in order in the calling function,
901 * then a return value of 1 means that the row with the given
902 * row number may now contain a different row that hasn't been checked yet.
904 int isl_tab_mark_redundant(struct isl_tab *tab, int row)
906 struct isl_tab_var *var = isl_tab_var_from_row(tab, row);
907 var->is_redundant = 1;
908 isl_assert(tab->mat->ctx, row >= tab->n_redundant, return -1);
909 if (tab->need_undo || tab->row_var[row] >= 0) {
910 if (tab->row_var[row] >= 0 && !var->is_nonneg) {
912 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, var) < 0)
915 if (row != tab->n_redundant)
916 swap_rows(tab, row, tab->n_redundant);
918 return isl_tab_push_var(tab, isl_tab_undo_redundant, var);
920 if (row != tab->n_row - 1)
921 swap_rows(tab, row, tab->n_row - 1);
922 isl_tab_var_from_row(tab, tab->n_row - 1)->index = -1;
928 int isl_tab_mark_empty(struct isl_tab *tab)
932 if (!tab->empty && tab->need_undo)
933 if (isl_tab_push(tab, isl_tab_undo_empty) < 0)
939 int isl_tab_freeze_constraint(struct isl_tab *tab, int con)
941 struct isl_tab_var *var;
946 var = &tab->con[con];
954 return isl_tab_push_var(tab, isl_tab_undo_freeze, var);
959 /* Update the rows signs after a pivot of "row" and "col", with "row_sgn"
960 * the original sign of the pivot element.
961 * We only keep track of row signs during PILP solving and in this case
962 * we only pivot a row with negative sign (meaning the value is always
963 * non-positive) using a positive pivot element.
965 * For each row j, the new value of the parametric constant is equal to
967 * a_j0 - a_jc a_r0/a_rc
969 * where a_j0 is the original parametric constant, a_rc is the pivot element,
970 * a_r0 is the parametric constant of the pivot row and a_jc is the
971 * pivot column entry of the row j.
972 * Since a_r0 is non-positive and a_rc is positive, the sign of row j
973 * remains the same if a_jc has the same sign as the row j or if
974 * a_jc is zero. In all other cases, we reset the sign to "unknown".
976 static void update_row_sign(struct isl_tab *tab, int row, int col, int row_sgn)
979 struct isl_mat *mat = tab->mat;
980 unsigned off = 2 + tab->M;
985 if (tab->row_sign[row] == 0)
987 isl_assert(mat->ctx, row_sgn > 0, return);
988 isl_assert(mat->ctx, tab->row_sign[row] == isl_tab_row_neg, return);
989 tab->row_sign[row] = isl_tab_row_pos;
990 for (i = 0; i < tab->n_row; ++i) {
994 s = isl_int_sgn(mat->row[i][off + col]);
997 if (!tab->row_sign[i])
999 if (s < 0 && tab->row_sign[i] == isl_tab_row_neg)
1001 if (s > 0 && tab->row_sign[i] == isl_tab_row_pos)
1003 tab->row_sign[i] = isl_tab_row_unknown;
1007 /* Given a row number "row" and a column number "col", pivot the tableau
1008 * such that the associated variables are interchanged.
1009 * The given row in the tableau expresses
1011 * x_r = a_r0 + \sum_i a_ri x_i
1015 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
1017 * Substituting this equality into the other rows
1019 * x_j = a_j0 + \sum_i a_ji x_i
1021 * with a_jc \ne 0, we obtain
1023 * x_j = a_jc/a_rc x_r + a_j0 - a_jc a_r0/a_rc + sum a_ji - a_jc a_ri/a_rc
1030 * where i is any other column and j is any other row,
1031 * is therefore transformed into
1033 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1034 * s(n_rc)d_r n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1036 * The transformation is performed along the following steps
1038 * d_r/n_rc n_ri/n_rc
1041 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1044 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1045 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
1047 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1048 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
1050 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1051 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1053 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1054 * s(n_rc)d_r n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1057 int isl_tab_pivot(struct isl_tab *tab, int row, int col)
1062 struct isl_mat *mat = tab->mat;
1063 struct isl_tab_var *var;
1064 unsigned off = 2 + tab->M;
1066 isl_int_swap(mat->row[row][0], mat->row[row][off + col]);
1067 sgn = isl_int_sgn(mat->row[row][0]);
1069 isl_int_neg(mat->row[row][0], mat->row[row][0]);
1070 isl_int_neg(mat->row[row][off + col], mat->row[row][off + col]);
1072 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1073 if (j == off - 1 + col)
1075 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
1077 if (!isl_int_is_one(mat->row[row][0]))
1078 isl_seq_normalize(mat->ctx, mat->row[row], off + tab->n_col);
1079 for (i = 0; i < tab->n_row; ++i) {
1082 if (isl_int_is_zero(mat->row[i][off + col]))
1084 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
1085 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1086 if (j == off - 1 + col)
1088 isl_int_mul(mat->row[i][1 + j],
1089 mat->row[i][1 + j], mat->row[row][0]);
1090 isl_int_addmul(mat->row[i][1 + j],
1091 mat->row[i][off + col], mat->row[row][1 + j]);
1093 isl_int_mul(mat->row[i][off + col],
1094 mat->row[i][off + col], mat->row[row][off + col]);
1095 if (!isl_int_is_one(mat->row[i][0]))
1096 isl_seq_normalize(mat->ctx, mat->row[i], off + tab->n_col);
1098 t = tab->row_var[row];
1099 tab->row_var[row] = tab->col_var[col];
1100 tab->col_var[col] = t;
1101 var = isl_tab_var_from_row(tab, row);
1104 var = var_from_col(tab, col);
1107 update_row_sign(tab, row, col, sgn);
1110 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1111 if (isl_int_is_zero(mat->row[i][off + col]))
1113 if (!isl_tab_var_from_row(tab, i)->frozen &&
1114 isl_tab_row_is_redundant(tab, i)) {
1115 int redo = isl_tab_mark_redundant(tab, i);
1125 /* If "var" represents a column variable, then pivot is up (sgn > 0)
1126 * or down (sgn < 0) to a row. The variable is assumed not to be
1127 * unbounded in the specified direction.
1128 * If sgn = 0, then the variable is unbounded in both directions,
1129 * and we pivot with any row we can find.
1131 static int to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign) WARN_UNUSED;
1132 static int to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign)
1135 unsigned off = 2 + tab->M;
1141 for (r = tab->n_redundant; r < tab->n_row; ++r)
1142 if (!isl_int_is_zero(tab->mat->row[r][off+var->index]))
1144 isl_assert(tab->mat->ctx, r < tab->n_row, return -1);
1146 r = pivot_row(tab, NULL, sign, var->index);
1147 isl_assert(tab->mat->ctx, r >= 0, return -1);
1150 return isl_tab_pivot(tab, r, var->index);
1153 static void check_table(struct isl_tab *tab)
1159 for (i = 0; i < tab->n_row; ++i) {
1160 if (!isl_tab_var_from_row(tab, i)->is_nonneg)
1162 assert(!isl_int_is_neg(tab->mat->row[i][1]));
1166 /* Return the sign of the maximal value of "var".
1167 * If the sign is not negative, then on return from this function,
1168 * the sample value will also be non-negative.
1170 * If "var" is manifestly unbounded wrt positive values, we are done.
1171 * Otherwise, we pivot the variable up to a row if needed
1172 * Then we continue pivoting down until either
1173 * - no more down pivots can be performed
1174 * - the sample value is positive
1175 * - the variable is pivoted into a manifestly unbounded column
1177 static int sign_of_max(struct isl_tab *tab, struct isl_tab_var *var)
1181 if (max_is_manifestly_unbounded(tab, var))
1183 if (to_row(tab, var, 1) < 0)
1185 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
1186 find_pivot(tab, var, var, 1, &row, &col);
1188 return isl_int_sgn(tab->mat->row[var->index][1]);
1189 if (isl_tab_pivot(tab, row, col) < 0)
1191 if (!var->is_row) /* manifestly unbounded */
1197 static int row_is_neg(struct isl_tab *tab, int row)
1200 return isl_int_is_neg(tab->mat->row[row][1]);
1201 if (isl_int_is_pos(tab->mat->row[row][2]))
1203 if (isl_int_is_neg(tab->mat->row[row][2]))
1205 return isl_int_is_neg(tab->mat->row[row][1]);
1208 static int row_sgn(struct isl_tab *tab, int row)
1211 return isl_int_sgn(tab->mat->row[row][1]);
1212 if (!isl_int_is_zero(tab->mat->row[row][2]))
1213 return isl_int_sgn(tab->mat->row[row][2]);
1215 return isl_int_sgn(tab->mat->row[row][1]);
1218 /* Perform pivots until the row variable "var" has a non-negative
1219 * sample value or until no more upward pivots can be performed.
1220 * Return the sign of the sample value after the pivots have been
1223 static int restore_row(struct isl_tab *tab, struct isl_tab_var *var)
1227 while (row_is_neg(tab, var->index)) {
1228 find_pivot(tab, var, var, 1, &row, &col);
1231 if (isl_tab_pivot(tab, row, col) < 0)
1233 if (!var->is_row) /* manifestly unbounded */
1236 return row_sgn(tab, var->index);
1239 /* Perform pivots until we are sure that the row variable "var"
1240 * can attain non-negative values. After return from this
1241 * function, "var" is still a row variable, but its sample
1242 * value may not be non-negative, even if the function returns 1.
1244 static int at_least_zero(struct isl_tab *tab, struct isl_tab_var *var)
1248 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
1249 find_pivot(tab, var, var, 1, &row, &col);
1252 if (row == var->index) /* manifestly unbounded */
1254 if (isl_tab_pivot(tab, row, col) < 0)
1257 return !isl_int_is_neg(tab->mat->row[var->index][1]);
1260 /* Return a negative value if "var" can attain negative values.
1261 * Return a non-negative value otherwise.
1263 * If "var" is manifestly unbounded wrt negative values, we are done.
1264 * Otherwise, if var is in a column, we can pivot it down to a row.
1265 * Then we continue pivoting down until either
1266 * - the pivot would result in a manifestly unbounded column
1267 * => we don't perform the pivot, but simply return -1
1268 * - no more down pivots can be performed
1269 * - the sample value is negative
1270 * If the sample value becomes negative and the variable is supposed
1271 * to be nonnegative, then we undo the last pivot.
1272 * However, if the last pivot has made the pivoting variable
1273 * obviously redundant, then it may have moved to another row.
1274 * In that case we look for upward pivots until we reach a non-negative
1277 static int sign_of_min(struct isl_tab *tab, struct isl_tab_var *var)
1280 struct isl_tab_var *pivot_var = NULL;
1282 if (min_is_manifestly_unbounded(tab, var))
1286 row = pivot_row(tab, NULL, -1, col);
1287 pivot_var = var_from_col(tab, col);
1288 if (isl_tab_pivot(tab, row, col) < 0)
1290 if (var->is_redundant)
1292 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
1293 if (var->is_nonneg) {
1294 if (!pivot_var->is_redundant &&
1295 pivot_var->index == row) {
1296 if (isl_tab_pivot(tab, row, col) < 0)
1299 if (restore_row(tab, var) < -1)
1305 if (var->is_redundant)
1307 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
1308 find_pivot(tab, var, var, -1, &row, &col);
1309 if (row == var->index)
1312 return isl_int_sgn(tab->mat->row[var->index][1]);
1313 pivot_var = var_from_col(tab, col);
1314 if (isl_tab_pivot(tab, row, col) < 0)
1316 if (var->is_redundant)
1319 if (pivot_var && var->is_nonneg) {
1320 /* pivot back to non-negative value */
1321 if (!pivot_var->is_redundant && pivot_var->index == row) {
1322 if (isl_tab_pivot(tab, row, col) < 0)
1325 if (restore_row(tab, var) < -1)
1331 static int row_at_most_neg_one(struct isl_tab *tab, int row)
1334 if (isl_int_is_pos(tab->mat->row[row][2]))
1336 if (isl_int_is_neg(tab->mat->row[row][2]))
1339 return isl_int_is_neg(tab->mat->row[row][1]) &&
1340 isl_int_abs_ge(tab->mat->row[row][1],
1341 tab->mat->row[row][0]);
1344 /* Return 1 if "var" can attain values <= -1.
1345 * Return 0 otherwise.
1347 * The sample value of "var" is assumed to be non-negative when the
1348 * the function is called and will be made non-negative again before
1349 * the function returns.
1351 int isl_tab_min_at_most_neg_one(struct isl_tab *tab, struct isl_tab_var *var)
1354 struct isl_tab_var *pivot_var;
1356 if (min_is_manifestly_unbounded(tab, var))
1360 row = pivot_row(tab, NULL, -1, col);
1361 pivot_var = var_from_col(tab, col);
1362 if (isl_tab_pivot(tab, row, col) < 0)
1364 if (var->is_redundant)
1366 if (row_at_most_neg_one(tab, var->index)) {
1367 if (var->is_nonneg) {
1368 if (!pivot_var->is_redundant &&
1369 pivot_var->index == row) {
1370 if (isl_tab_pivot(tab, row, col) < 0)
1373 if (restore_row(tab, var) < -1)
1379 if (var->is_redundant)
1382 find_pivot(tab, var, var, -1, &row, &col);
1383 if (row == var->index)
1387 pivot_var = var_from_col(tab, col);
1388 if (isl_tab_pivot(tab, row, col) < 0)
1390 if (var->is_redundant)
1392 } while (!row_at_most_neg_one(tab, var->index));
1393 if (var->is_nonneg) {
1394 /* pivot back to non-negative value */
1395 if (!pivot_var->is_redundant && pivot_var->index == row)
1396 if (isl_tab_pivot(tab, row, col) < 0)
1398 if (restore_row(tab, var) < -1)
1404 /* Return 1 if "var" can attain values >= 1.
1405 * Return 0 otherwise.
1407 static int at_least_one(struct isl_tab *tab, struct isl_tab_var *var)
1412 if (max_is_manifestly_unbounded(tab, var))
1414 if (to_row(tab, var, 1) < 0)
1416 r = tab->mat->row[var->index];
1417 while (isl_int_lt(r[1], r[0])) {
1418 find_pivot(tab, var, var, 1, &row, &col);
1420 return isl_int_ge(r[1], r[0]);
1421 if (row == var->index) /* manifestly unbounded */
1423 if (isl_tab_pivot(tab, row, col) < 0)
1429 static void swap_cols(struct isl_tab *tab, int col1, int col2)
1432 unsigned off = 2 + tab->M;
1433 t = tab->col_var[col1];
1434 tab->col_var[col1] = tab->col_var[col2];
1435 tab->col_var[col2] = t;
1436 var_from_col(tab, col1)->index = col1;
1437 var_from_col(tab, col2)->index = col2;
1438 tab->mat = isl_mat_swap_cols(tab->mat, off + col1, off + col2);
1441 /* Mark column with index "col" as representing a zero variable.
1442 * If we may need to undo the operation the column is kept,
1443 * but no longer considered.
1444 * Otherwise, the column is simply removed.
1446 * The column may be interchanged with some other column. If it
1447 * is interchanged with a later column, return 1. Otherwise return 0.
1448 * If the columns are checked in order in the calling function,
1449 * then a return value of 1 means that the column with the given
1450 * column number may now contain a different column that
1451 * hasn't been checked yet.
1453 int isl_tab_kill_col(struct isl_tab *tab, int col)
1455 var_from_col(tab, col)->is_zero = 1;
1456 if (tab->need_undo) {
1457 if (isl_tab_push_var(tab, isl_tab_undo_zero,
1458 var_from_col(tab, col)) < 0)
1460 if (col != tab->n_dead)
1461 swap_cols(tab, col, tab->n_dead);
1465 if (col != tab->n_col - 1)
1466 swap_cols(tab, col, tab->n_col - 1);
1467 var_from_col(tab, tab->n_col - 1)->index = -1;
1473 /* Row variable "var" is non-negative and cannot attain any values
1474 * larger than zero. This means that the coefficients of the unrestricted
1475 * column variables are zero and that the coefficients of the non-negative
1476 * column variables are zero or negative.
1477 * Each of the non-negative variables with a negative coefficient can
1478 * then also be written as the negative sum of non-negative variables
1479 * and must therefore also be zero.
1481 static int close_row(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
1482 static int close_row(struct isl_tab *tab, struct isl_tab_var *var)
1485 struct isl_mat *mat = tab->mat;
1486 unsigned off = 2 + tab->M;
1488 isl_assert(tab->mat->ctx, var->is_nonneg, return -1);
1491 if (isl_tab_push_var(tab, isl_tab_undo_zero, var) < 0)
1493 for (j = tab->n_dead; j < tab->n_col; ++j) {
1494 if (isl_int_is_zero(mat->row[var->index][off + j]))
1496 isl_assert(tab->mat->ctx,
1497 isl_int_is_neg(mat->row[var->index][off + j]), return -1);
1498 if (isl_tab_kill_col(tab, j))
1501 if (isl_tab_mark_redundant(tab, var->index) < 0)
1506 /* Add a constraint to the tableau and allocate a row for it.
1507 * Return the index into the constraint array "con".
1509 int isl_tab_allocate_con(struct isl_tab *tab)
1513 isl_assert(tab->mat->ctx, tab->n_row < tab->mat->n_row, return -1);
1514 isl_assert(tab->mat->ctx, tab->n_con < tab->max_con, return -1);
1517 tab->con[r].index = tab->n_row;
1518 tab->con[r].is_row = 1;
1519 tab->con[r].is_nonneg = 0;
1520 tab->con[r].is_zero = 0;
1521 tab->con[r].is_redundant = 0;
1522 tab->con[r].frozen = 0;
1523 tab->con[r].negated = 0;
1524 tab->row_var[tab->n_row] = ~r;
1528 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]) < 0)
1534 /* Add a variable to the tableau and allocate a column for it.
1535 * Return the index into the variable array "var".
1537 int isl_tab_allocate_var(struct isl_tab *tab)
1541 unsigned off = 2 + tab->M;
1543 isl_assert(tab->mat->ctx, tab->n_col < tab->mat->n_col, return -1);
1544 isl_assert(tab->mat->ctx, tab->n_var < tab->max_var, return -1);
1547 tab->var[r].index = tab->n_col;
1548 tab->var[r].is_row = 0;
1549 tab->var[r].is_nonneg = 0;
1550 tab->var[r].is_zero = 0;
1551 tab->var[r].is_redundant = 0;
1552 tab->var[r].frozen = 0;
1553 tab->var[r].negated = 0;
1554 tab->col_var[tab->n_col] = r;
1556 for (i = 0; i < tab->n_row; ++i)
1557 isl_int_set_si(tab->mat->row[i][off + tab->n_col], 0);
1561 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->var[r]) < 0)
1567 /* Add a row to the tableau. The row is given as an affine combination
1568 * of the original variables and needs to be expressed in terms of the
1571 * We add each term in turn.
1572 * If r = n/d_r is the current sum and we need to add k x, then
1573 * if x is a column variable, we increase the numerator of
1574 * this column by k d_r
1575 * if x = f/d_x is a row variable, then the new representation of r is
1577 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1578 * --- + --- = ------------------- = -------------------
1579 * d_r d_r d_r d_x/g m
1581 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1583 int isl_tab_add_row(struct isl_tab *tab, isl_int *line)
1589 unsigned off = 2 + tab->M;
1591 r = isl_tab_allocate_con(tab);
1597 row = tab->mat->row[tab->con[r].index];
1598 isl_int_set_si(row[0], 1);
1599 isl_int_set(row[1], line[0]);
1600 isl_seq_clr(row + 2, tab->M + tab->n_col);
1601 for (i = 0; i < tab->n_var; ++i) {
1602 if (tab->var[i].is_zero)
1604 if (tab->var[i].is_row) {
1606 row[0], tab->mat->row[tab->var[i].index][0]);
1607 isl_int_swap(a, row[0]);
1608 isl_int_divexact(a, row[0], a);
1610 row[0], tab->mat->row[tab->var[i].index][0]);
1611 isl_int_mul(b, b, line[1 + i]);
1612 isl_seq_combine(row + 1, a, row + 1,
1613 b, tab->mat->row[tab->var[i].index] + 1,
1614 1 + tab->M + tab->n_col);
1616 isl_int_addmul(row[off + tab->var[i].index],
1617 line[1 + i], row[0]);
1618 if (tab->M && i >= tab->n_param && i < tab->n_var - tab->n_div)
1619 isl_int_submul(row[2], line[1 + i], row[0]);
1621 isl_seq_normalize(tab->mat->ctx, row, off + tab->n_col);
1626 tab->row_sign[tab->con[r].index] = 0;
1631 static int drop_row(struct isl_tab *tab, int row)
1633 isl_assert(tab->mat->ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
1634 if (row != tab->n_row - 1)
1635 swap_rows(tab, row, tab->n_row - 1);
1641 static int drop_col(struct isl_tab *tab, int col)
1643 isl_assert(tab->mat->ctx, tab->col_var[col] == tab->n_var - 1, return -1);
1644 if (col != tab->n_col - 1)
1645 swap_cols(tab, col, tab->n_col - 1);
1651 /* Add inequality "ineq" and check if it conflicts with the
1652 * previously added constraints or if it is obviously redundant.
1654 int isl_tab_add_ineq(struct isl_tab *tab, isl_int *ineq)
1663 struct isl_basic_set *bset = tab->bset;
1665 isl_assert(tab->mat->ctx, tab->n_eq == bset->n_eq, return -1);
1666 isl_assert(tab->mat->ctx,
1667 tab->n_con == bset->n_eq + bset->n_ineq, return -1);
1668 tab->bset = isl_basic_set_add_ineq(tab->bset, ineq);
1669 if (isl_tab_push(tab, isl_tab_undo_bset_ineq) < 0)
1676 isl_int_swap(ineq[0], cst);
1678 r = isl_tab_add_row(tab, ineq);
1680 isl_int_swap(ineq[0], cst);
1685 tab->con[r].is_nonneg = 1;
1686 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
1688 if (isl_tab_row_is_redundant(tab, tab->con[r].index)) {
1689 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1694 sgn = restore_row(tab, &tab->con[r]);
1698 return isl_tab_mark_empty(tab);
1699 if (tab->con[r].is_row && isl_tab_row_is_redundant(tab, tab->con[r].index))
1700 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1705 /* Pivot a non-negative variable down until it reaches the value zero
1706 * and then pivot the variable into a column position.
1708 static int to_col(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
1709 static int to_col(struct isl_tab *tab, struct isl_tab_var *var)
1713 unsigned off = 2 + tab->M;
1718 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
1719 find_pivot(tab, var, NULL, -1, &row, &col);
1720 isl_assert(tab->mat->ctx, row != -1, return -1);
1721 if (isl_tab_pivot(tab, row, col) < 0)
1727 for (i = tab->n_dead; i < tab->n_col; ++i)
1728 if (!isl_int_is_zero(tab->mat->row[var->index][off + i]))
1731 isl_assert(tab->mat->ctx, i < tab->n_col, return -1);
1732 if (isl_tab_pivot(tab, var->index, i) < 0)
1738 /* We assume Gaussian elimination has been performed on the equalities.
1739 * The equalities can therefore never conflict.
1740 * Adding the equalities is currently only really useful for a later call
1741 * to isl_tab_ineq_type.
1743 static struct isl_tab *add_eq(struct isl_tab *tab, isl_int *eq)
1750 r = isl_tab_add_row(tab, eq);
1754 r = tab->con[r].index;
1755 i = isl_seq_first_non_zero(tab->mat->row[r] + 2 + tab->M + tab->n_dead,
1756 tab->n_col - tab->n_dead);
1757 isl_assert(tab->mat->ctx, i >= 0, goto error);
1759 if (isl_tab_pivot(tab, r, i) < 0)
1761 if (isl_tab_kill_col(tab, i) < 0)
1771 static int row_is_manifestly_zero(struct isl_tab *tab, int row)
1773 unsigned off = 2 + tab->M;
1775 if (!isl_int_is_zero(tab->mat->row[row][1]))
1777 if (tab->M && !isl_int_is_zero(tab->mat->row[row][2]))
1779 return isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
1780 tab->n_col - tab->n_dead) == -1;
1783 /* Add an equality that is known to be valid for the given tableau.
1785 struct isl_tab *isl_tab_add_valid_eq(struct isl_tab *tab, isl_int *eq)
1787 struct isl_tab_var *var;
1792 r = isl_tab_add_row(tab, eq);
1798 if (row_is_manifestly_zero(tab, r)) {
1800 if (isl_tab_mark_redundant(tab, r) < 0)
1805 if (isl_int_is_neg(tab->mat->row[r][1])) {
1806 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1811 if (to_col(tab, var) < 0)
1814 if (isl_tab_kill_col(tab, var->index) < 0)
1823 static int add_zero_row(struct isl_tab *tab)
1828 r = isl_tab_allocate_con(tab);
1832 row = tab->mat->row[tab->con[r].index];
1833 isl_seq_clr(row + 1, 1 + tab->M + tab->n_col);
1834 isl_int_set_si(row[0], 1);
1839 /* Add equality "eq" and check if it conflicts with the
1840 * previously added constraints or if it is obviously redundant.
1842 struct isl_tab *isl_tab_add_eq(struct isl_tab *tab, isl_int *eq)
1844 struct isl_tab_undo *snap = NULL;
1845 struct isl_tab_var *var;
1853 isl_assert(tab->mat->ctx, !tab->M, goto error);
1856 snap = isl_tab_snap(tab);
1860 isl_int_swap(eq[0], cst);
1862 r = isl_tab_add_row(tab, eq);
1864 isl_int_swap(eq[0], cst);
1872 if (row_is_manifestly_zero(tab, row)) {
1874 if (isl_tab_rollback(tab, snap) < 0)
1882 tab->bset = isl_basic_set_add_ineq(tab->bset, eq);
1883 if (isl_tab_push(tab, isl_tab_undo_bset_ineq) < 0)
1885 isl_seq_neg(eq, eq, 1 + tab->n_var);
1886 tab->bset = isl_basic_set_add_ineq(tab->bset, eq);
1887 isl_seq_neg(eq, eq, 1 + tab->n_var);
1888 if (isl_tab_push(tab, isl_tab_undo_bset_ineq) < 0)
1892 if (add_zero_row(tab) < 0)
1896 sgn = isl_int_sgn(tab->mat->row[row][1]);
1899 isl_seq_neg(tab->mat->row[row] + 1, tab->mat->row[row] + 1,
1906 sgn = sign_of_max(tab, var);
1910 if (isl_tab_mark_empty(tab) < 0)
1917 if (to_col(tab, var) < 0)
1920 if (isl_tab_kill_col(tab, var->index) < 0)
1929 struct isl_tab *isl_tab_from_basic_map(struct isl_basic_map *bmap)
1932 struct isl_tab *tab;
1936 tab = isl_tab_alloc(bmap->ctx,
1937 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
1938 isl_basic_map_total_dim(bmap), 0);
1941 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1942 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) {
1943 if (isl_tab_mark_empty(tab) < 0)
1947 for (i = 0; i < bmap->n_eq; ++i) {
1948 tab = add_eq(tab, bmap->eq[i]);
1952 for (i = 0; i < bmap->n_ineq; ++i) {
1953 if (isl_tab_add_ineq(tab, bmap->ineq[i]) < 0)
1964 struct isl_tab *isl_tab_from_basic_set(struct isl_basic_set *bset)
1966 return isl_tab_from_basic_map((struct isl_basic_map *)bset);
1969 /* Construct a tableau corresponding to the recession cone of "bset".
1971 struct isl_tab *isl_tab_from_recession_cone(struct isl_basic_set *bset)
1975 struct isl_tab *tab;
1979 tab = isl_tab_alloc(bset->ctx, bset->n_eq + bset->n_ineq,
1980 isl_basic_set_total_dim(bset), 0);
1983 tab->rational = ISL_F_ISSET(bset, ISL_BASIC_SET_RATIONAL);
1987 for (i = 0; i < bset->n_eq; ++i) {
1988 isl_int_swap(bset->eq[i][0], cst);
1989 tab = add_eq(tab, bset->eq[i]);
1990 isl_int_swap(bset->eq[i][0], cst);
1994 for (i = 0; i < bset->n_ineq; ++i) {
1996 isl_int_swap(bset->ineq[i][0], cst);
1997 r = isl_tab_add_row(tab, bset->ineq[i]);
1998 isl_int_swap(bset->ineq[i][0], cst);
2001 tab->con[r].is_nonneg = 1;
2002 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
2014 /* Assuming "tab" is the tableau of a cone, check if the cone is
2015 * bounded, i.e., if it is empty or only contains the origin.
2017 int isl_tab_cone_is_bounded(struct isl_tab *tab)
2025 if (tab->n_dead == tab->n_col)
2029 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2030 struct isl_tab_var *var;
2032 var = isl_tab_var_from_row(tab, i);
2033 if (!var->is_nonneg)
2035 sgn = sign_of_max(tab, var);
2040 if (close_row(tab, var) < 0)
2044 if (tab->n_dead == tab->n_col)
2046 if (i == tab->n_row)
2051 int isl_tab_sample_is_integer(struct isl_tab *tab)
2058 for (i = 0; i < tab->n_var; ++i) {
2060 if (!tab->var[i].is_row)
2062 row = tab->var[i].index;
2063 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
2064 tab->mat->row[row][0]))
2070 static struct isl_vec *extract_integer_sample(struct isl_tab *tab)
2073 struct isl_vec *vec;
2075 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
2079 isl_int_set_si(vec->block.data[0], 1);
2080 for (i = 0; i < tab->n_var; ++i) {
2081 if (!tab->var[i].is_row)
2082 isl_int_set_si(vec->block.data[1 + i], 0);
2084 int row = tab->var[i].index;
2085 isl_int_divexact(vec->block.data[1 + i],
2086 tab->mat->row[row][1], tab->mat->row[row][0]);
2093 struct isl_vec *isl_tab_get_sample_value(struct isl_tab *tab)
2096 struct isl_vec *vec;
2102 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
2108 isl_int_set_si(vec->block.data[0], 1);
2109 for (i = 0; i < tab->n_var; ++i) {
2111 if (!tab->var[i].is_row) {
2112 isl_int_set_si(vec->block.data[1 + i], 0);
2115 row = tab->var[i].index;
2116 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
2117 isl_int_divexact(m, tab->mat->row[row][0], m);
2118 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
2119 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
2120 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
2122 vec = isl_vec_normalize(vec);
2128 /* Update "bmap" based on the results of the tableau "tab".
2129 * In particular, implicit equalities are made explicit, redundant constraints
2130 * are removed and if the sample value happens to be integer, it is stored
2131 * in "bmap" (unless "bmap" already had an integer sample).
2133 * The tableau is assumed to have been created from "bmap" using
2134 * isl_tab_from_basic_map.
2136 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
2137 struct isl_tab *tab)
2149 bmap = isl_basic_map_set_to_empty(bmap);
2151 for (i = bmap->n_ineq - 1; i >= 0; --i) {
2152 if (isl_tab_is_equality(tab, n_eq + i))
2153 isl_basic_map_inequality_to_equality(bmap, i);
2154 else if (isl_tab_is_redundant(tab, n_eq + i))
2155 isl_basic_map_drop_inequality(bmap, i);
2157 if (!tab->rational &&
2158 !bmap->sample && isl_tab_sample_is_integer(tab))
2159 bmap->sample = extract_integer_sample(tab);
2163 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
2164 struct isl_tab *tab)
2166 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
2167 (struct isl_basic_map *)bset, tab);
2170 /* Given a non-negative variable "var", add a new non-negative variable
2171 * that is the opposite of "var", ensuring that var can only attain the
2173 * If var = n/d is a row variable, then the new variable = -n/d.
2174 * If var is a column variables, then the new variable = -var.
2175 * If the new variable cannot attain non-negative values, then
2176 * the resulting tableau is empty.
2177 * Otherwise, we know the value will be zero and we close the row.
2179 static struct isl_tab *cut_to_hyperplane(struct isl_tab *tab,
2180 struct isl_tab_var *var)
2185 unsigned off = 2 + tab->M;
2189 isl_assert(tab->mat->ctx, !var->is_redundant, goto error);
2191 if (isl_tab_extend_cons(tab, 1) < 0)
2195 tab->con[r].index = tab->n_row;
2196 tab->con[r].is_row = 1;
2197 tab->con[r].is_nonneg = 0;
2198 tab->con[r].is_zero = 0;
2199 tab->con[r].is_redundant = 0;
2200 tab->con[r].frozen = 0;
2201 tab->con[r].negated = 0;
2202 tab->row_var[tab->n_row] = ~r;
2203 row = tab->mat->row[tab->n_row];
2206 isl_int_set(row[0], tab->mat->row[var->index][0]);
2207 isl_seq_neg(row + 1,
2208 tab->mat->row[var->index] + 1, 1 + tab->n_col);
2210 isl_int_set_si(row[0], 1);
2211 isl_seq_clr(row + 1, 1 + tab->n_col);
2212 isl_int_set_si(row[off + var->index], -1);
2217 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]) < 0)
2220 sgn = sign_of_max(tab, &tab->con[r]);
2224 if (isl_tab_mark_empty(tab) < 0)
2228 tab->con[r].is_nonneg = 1;
2229 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
2232 if (close_row(tab, &tab->con[r]) < 0)
2241 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2242 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2243 * by r' = r + 1 >= 0.
2244 * If r is a row variable, we simply increase the constant term by one
2245 * (taking into account the denominator).
2246 * If r is a column variable, then we need to modify each row that
2247 * refers to r = r' - 1 by substituting this equality, effectively
2248 * subtracting the coefficient of the column from the constant.
2250 struct isl_tab *isl_tab_relax(struct isl_tab *tab, int con)
2252 struct isl_tab_var *var;
2253 unsigned off = 2 + tab->M;
2258 var = &tab->con[con];
2260 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2261 if (to_row(tab, var, 1) < 0)
2265 isl_int_add(tab->mat->row[var->index][1],
2266 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2270 for (i = 0; i < tab->n_row; ++i) {
2271 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2273 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
2274 tab->mat->row[i][off + var->index]);
2279 if (isl_tab_push_var(tab, isl_tab_undo_relax, var) < 0)
2288 struct isl_tab *isl_tab_select_facet(struct isl_tab *tab, int con)
2293 return cut_to_hyperplane(tab, &tab->con[con]);
2296 static int may_be_equality(struct isl_tab *tab, int row)
2298 unsigned off = 2 + tab->M;
2299 return (tab->rational ? isl_int_is_zero(tab->mat->row[row][1])
2300 : isl_int_lt(tab->mat->row[row][1],
2301 tab->mat->row[row][0])) &&
2302 isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
2303 tab->n_col - tab->n_dead) != -1;
2306 /* Check for (near) equalities among the constraints.
2307 * A constraint is an equality if it is non-negative and if
2308 * its maximal value is either
2309 * - zero (in case of rational tableaus), or
2310 * - strictly less than 1 (in case of integer tableaus)
2312 * We first mark all non-redundant and non-dead variables that
2313 * are not frozen and not obviously not an equality.
2314 * Then we iterate over all marked variables if they can attain
2315 * any values larger than zero or at least one.
2316 * If the maximal value is zero, we mark any column variables
2317 * that appear in the row as being zero and mark the row as being redundant.
2318 * Otherwise, if the maximal value is strictly less than one (and the
2319 * tableau is integer), then we restrict the value to being zero
2320 * by adding an opposite non-negative variable.
2322 struct isl_tab *isl_tab_detect_implicit_equalities(struct isl_tab *tab)
2331 if (tab->n_dead == tab->n_col)
2335 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2336 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2337 var->marked = !var->frozen && var->is_nonneg &&
2338 may_be_equality(tab, i);
2342 for (i = tab->n_dead; i < tab->n_col; ++i) {
2343 struct isl_tab_var *var = var_from_col(tab, i);
2344 var->marked = !var->frozen && var->is_nonneg;
2349 struct isl_tab_var *var;
2351 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2352 var = isl_tab_var_from_row(tab, i);
2356 if (i == tab->n_row) {
2357 for (i = tab->n_dead; i < tab->n_col; ++i) {
2358 var = var_from_col(tab, i);
2362 if (i == tab->n_col)
2367 sgn = sign_of_max(tab, var);
2371 if (close_row(tab, var) < 0)
2373 } else if (!tab->rational && !at_least_one(tab, var)) {
2374 tab = cut_to_hyperplane(tab, var);
2375 return isl_tab_detect_implicit_equalities(tab);
2377 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2378 var = isl_tab_var_from_row(tab, i);
2381 if (may_be_equality(tab, i))
2394 static int con_is_redundant(struct isl_tab *tab, struct isl_tab_var *var)
2398 if (tab->rational) {
2399 int sgn = sign_of_min(tab, var);
2404 int irred = isl_tab_min_at_most_neg_one(tab, var);
2411 /* Check for (near) redundant constraints.
2412 * A constraint is redundant if it is non-negative and if
2413 * its minimal value (temporarily ignoring the non-negativity) is either
2414 * - zero (in case of rational tableaus), or
2415 * - strictly larger than -1 (in case of integer tableaus)
2417 * We first mark all non-redundant and non-dead variables that
2418 * are not frozen and not obviously negatively unbounded.
2419 * Then we iterate over all marked variables if they can attain
2420 * any values smaller than zero or at most negative one.
2421 * If not, we mark the row as being redundant (assuming it hasn't
2422 * been detected as being obviously redundant in the mean time).
2424 int isl_tab_detect_redundant(struct isl_tab *tab)
2433 if (tab->n_redundant == tab->n_row)
2437 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2438 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2439 var->marked = !var->frozen && var->is_nonneg;
2443 for (i = tab->n_dead; i < tab->n_col; ++i) {
2444 struct isl_tab_var *var = var_from_col(tab, i);
2445 var->marked = !var->frozen && var->is_nonneg &&
2446 !min_is_manifestly_unbounded(tab, var);
2451 struct isl_tab_var *var;
2453 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2454 var = isl_tab_var_from_row(tab, i);
2458 if (i == tab->n_row) {
2459 for (i = tab->n_dead; i < tab->n_col; ++i) {
2460 var = var_from_col(tab, i);
2464 if (i == tab->n_col)
2469 red = con_is_redundant(tab, var);
2472 if (red && !var->is_redundant)
2473 if (isl_tab_mark_redundant(tab, var->index) < 0)
2475 for (i = tab->n_dead; i < tab->n_col; ++i) {
2476 var = var_from_col(tab, i);
2479 if (!min_is_manifestly_unbounded(tab, var))
2489 int isl_tab_is_equality(struct isl_tab *tab, int con)
2496 if (tab->con[con].is_zero)
2498 if (tab->con[con].is_redundant)
2500 if (!tab->con[con].is_row)
2501 return tab->con[con].index < tab->n_dead;
2503 row = tab->con[con].index;
2506 return isl_int_is_zero(tab->mat->row[row][1]) &&
2507 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
2508 tab->n_col - tab->n_dead) == -1;
2511 /* Return the minimial value of the affine expression "f" with denominator
2512 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2513 * the expression cannot attain arbitrarily small values.
2514 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2515 * The return value reflects the nature of the result (empty, unbounded,
2516 * minmimal value returned in *opt).
2518 enum isl_lp_result isl_tab_min(struct isl_tab *tab,
2519 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom,
2523 enum isl_lp_result res = isl_lp_ok;
2524 struct isl_tab_var *var;
2525 struct isl_tab_undo *snap;
2528 return isl_lp_empty;
2530 snap = isl_tab_snap(tab);
2531 r = isl_tab_add_row(tab, f);
2533 return isl_lp_error;
2535 isl_int_mul(tab->mat->row[var->index][0],
2536 tab->mat->row[var->index][0], denom);
2539 find_pivot(tab, var, var, -1, &row, &col);
2540 if (row == var->index) {
2541 res = isl_lp_unbounded;
2546 if (isl_tab_pivot(tab, row, col) < 0)
2547 return isl_lp_error;
2549 if (ISL_FL_ISSET(flags, ISL_TAB_SAVE_DUAL)) {
2552 isl_vec_free(tab->dual);
2553 tab->dual = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_con);
2555 return isl_lp_error;
2556 isl_int_set(tab->dual->el[0], tab->mat->row[var->index][0]);
2557 for (i = 0; i < tab->n_con; ++i) {
2559 if (tab->con[i].is_row) {
2560 isl_int_set_si(tab->dual->el[1 + i], 0);
2563 pos = 2 + tab->M + tab->con[i].index;
2564 if (tab->con[i].negated)
2565 isl_int_neg(tab->dual->el[1 + i],
2566 tab->mat->row[var->index][pos]);
2568 isl_int_set(tab->dual->el[1 + i],
2569 tab->mat->row[var->index][pos]);
2572 if (opt && res == isl_lp_ok) {
2574 isl_int_set(*opt, tab->mat->row[var->index][1]);
2575 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
2577 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
2578 tab->mat->row[var->index][0]);
2580 if (isl_tab_rollback(tab, snap) < 0)
2581 return isl_lp_error;
2585 int isl_tab_is_redundant(struct isl_tab *tab, int con)
2589 if (tab->con[con].is_zero)
2591 if (tab->con[con].is_redundant)
2593 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
2596 /* Take a snapshot of the tableau that can be restored by s call to
2599 struct isl_tab_undo *isl_tab_snap(struct isl_tab *tab)
2607 /* Undo the operation performed by isl_tab_relax.
2609 static int unrelax(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
2610 static int unrelax(struct isl_tab *tab, struct isl_tab_var *var)
2612 unsigned off = 2 + tab->M;
2614 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2615 if (to_row(tab, var, 1) < 0)
2619 isl_int_sub(tab->mat->row[var->index][1],
2620 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2624 for (i = 0; i < tab->n_row; ++i) {
2625 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2627 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
2628 tab->mat->row[i][off + var->index]);
2636 static int perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo) WARN_UNUSED;
2637 static int perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo)
2639 struct isl_tab_var *var = var_from_index(tab, undo->u.var_index);
2640 switch(undo->type) {
2641 case isl_tab_undo_nonneg:
2644 case isl_tab_undo_redundant:
2645 var->is_redundant = 0;
2648 case isl_tab_undo_freeze:
2651 case isl_tab_undo_zero:
2656 case isl_tab_undo_allocate:
2657 if (undo->u.var_index >= 0) {
2658 isl_assert(tab->mat->ctx, !var->is_row, return -1);
2659 drop_col(tab, var->index);
2663 if (!max_is_manifestly_unbounded(tab, var)) {
2664 if (to_row(tab, var, 1) < 0)
2666 } else if (!min_is_manifestly_unbounded(tab, var)) {
2667 if (to_row(tab, var, -1) < 0)
2670 if (to_row(tab, var, 0) < 0)
2673 drop_row(tab, var->index);
2675 case isl_tab_undo_relax:
2676 return unrelax(tab, var);
2682 /* Restore the tableau to the state where the basic variables
2683 * are those in "col_var".
2684 * We first construct a list of variables that are currently in
2685 * the basis, but shouldn't. Then we iterate over all variables
2686 * that should be in the basis and for each one that is currently
2687 * not in the basis, we exchange it with one of the elements of the
2688 * list constructed before.
2689 * We can always find an appropriate variable to pivot with because
2690 * the current basis is mapped to the old basis by a non-singular
2691 * matrix and so we can never end up with a zero row.
2693 static int restore_basis(struct isl_tab *tab, int *col_var)
2697 int *extra = NULL; /* current columns that contain bad stuff */
2698 unsigned off = 2 + tab->M;
2700 extra = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
2703 for (i = 0; i < tab->n_col; ++i) {
2704 for (j = 0; j < tab->n_col; ++j)
2705 if (tab->col_var[i] == col_var[j])
2709 extra[n_extra++] = i;
2711 for (i = 0; i < tab->n_col && n_extra > 0; ++i) {
2712 struct isl_tab_var *var;
2715 for (j = 0; j < tab->n_col; ++j)
2716 if (col_var[i] == tab->col_var[j])
2720 var = var_from_index(tab, col_var[i]);
2722 for (j = 0; j < n_extra; ++j)
2723 if (!isl_int_is_zero(tab->mat->row[row][off+extra[j]]))
2725 isl_assert(tab->mat->ctx, j < n_extra, goto error);
2726 if (isl_tab_pivot(tab, row, extra[j]) < 0)
2728 extra[j] = extra[--n_extra];
2740 /* Remove all samples with index n or greater, i.e., those samples
2741 * that were added since we saved this number of samples in
2742 * isl_tab_save_samples.
2744 static void drop_samples_since(struct isl_tab *tab, int n)
2748 for (i = tab->n_sample - 1; i >= 0 && tab->n_sample > n; --i) {
2749 if (tab->sample_index[i] < n)
2752 if (i != tab->n_sample - 1) {
2753 int t = tab->sample_index[tab->n_sample-1];
2754 tab->sample_index[tab->n_sample-1] = tab->sample_index[i];
2755 tab->sample_index[i] = t;
2756 isl_mat_swap_rows(tab->samples, tab->n_sample-1, i);
2762 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo) WARN_UNUSED;
2763 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo)
2765 switch (undo->type) {
2766 case isl_tab_undo_empty:
2769 case isl_tab_undo_nonneg:
2770 case isl_tab_undo_redundant:
2771 case isl_tab_undo_freeze:
2772 case isl_tab_undo_zero:
2773 case isl_tab_undo_allocate:
2774 case isl_tab_undo_relax:
2775 return perform_undo_var(tab, undo);
2776 case isl_tab_undo_bset_eq:
2777 return isl_basic_set_free_equality(tab->bset, 1);
2778 case isl_tab_undo_bset_ineq:
2779 return isl_basic_set_free_inequality(tab->bset, 1);
2780 case isl_tab_undo_bset_div:
2781 if (isl_basic_set_free_div(tab->bset, 1) < 0)
2784 tab->samples->n_col--;
2786 case isl_tab_undo_saved_basis:
2787 if (restore_basis(tab, undo->u.col_var) < 0)
2790 case isl_tab_undo_drop_sample:
2793 case isl_tab_undo_saved_samples:
2794 drop_samples_since(tab, undo->u.n);
2796 case isl_tab_undo_callback:
2797 return undo->u.callback->run(undo->u.callback);
2799 isl_assert(tab->mat->ctx, 0, return -1);
2804 /* Return the tableau to the state it was in when the snapshot "snap"
2807 int isl_tab_rollback(struct isl_tab *tab, struct isl_tab_undo *snap)
2809 struct isl_tab_undo *undo, *next;
2815 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
2819 if (perform_undo(tab, undo) < 0) {
2833 /* The given row "row" represents an inequality violated by all
2834 * points in the tableau. Check for some special cases of such
2835 * separating constraints.
2836 * In particular, if the row has been reduced to the constant -1,
2837 * then we know the inequality is adjacent (but opposite) to
2838 * an equality in the tableau.
2839 * If the row has been reduced to r = -1 -r', with r' an inequality
2840 * of the tableau, then the inequality is adjacent (but opposite)
2841 * to the inequality r'.
2843 static enum isl_ineq_type separation_type(struct isl_tab *tab, unsigned row)
2846 unsigned off = 2 + tab->M;
2849 return isl_ineq_separate;
2851 if (!isl_int_is_one(tab->mat->row[row][0]))
2852 return isl_ineq_separate;
2853 if (!isl_int_is_negone(tab->mat->row[row][1]))
2854 return isl_ineq_separate;
2856 pos = isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
2857 tab->n_col - tab->n_dead);
2859 return isl_ineq_adj_eq;
2861 if (!isl_int_is_negone(tab->mat->row[row][off + tab->n_dead + pos]))
2862 return isl_ineq_separate;
2864 pos = isl_seq_first_non_zero(
2865 tab->mat->row[row] + off + tab->n_dead + pos + 1,
2866 tab->n_col - tab->n_dead - pos - 1);
2868 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
2871 /* Check the effect of inequality "ineq" on the tableau "tab".
2873 * isl_ineq_redundant: satisfied by all points in the tableau
2874 * isl_ineq_separate: satisfied by no point in the tableau
2875 * isl_ineq_cut: satisfied by some by not all points
2876 * isl_ineq_adj_eq: adjacent to an equality
2877 * isl_ineq_adj_ineq: adjacent to an inequality.
2879 enum isl_ineq_type isl_tab_ineq_type(struct isl_tab *tab, isl_int *ineq)
2881 enum isl_ineq_type type = isl_ineq_error;
2882 struct isl_tab_undo *snap = NULL;
2887 return isl_ineq_error;
2889 if (isl_tab_extend_cons(tab, 1) < 0)
2890 return isl_ineq_error;
2892 snap = isl_tab_snap(tab);
2894 con = isl_tab_add_row(tab, ineq);
2898 row = tab->con[con].index;
2899 if (isl_tab_row_is_redundant(tab, row))
2900 type = isl_ineq_redundant;
2901 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
2903 isl_int_abs_ge(tab->mat->row[row][1],
2904 tab->mat->row[row][0]))) {
2905 int nonneg = at_least_zero(tab, &tab->con[con]);
2909 type = isl_ineq_cut;
2911 type = separation_type(tab, row);
2913 int red = con_is_redundant(tab, &tab->con[con]);
2917 type = isl_ineq_cut;
2919 type = isl_ineq_redundant;
2922 if (isl_tab_rollback(tab, snap))
2923 return isl_ineq_error;
2926 return isl_ineq_error;
2929 void isl_tab_dump(struct isl_tab *tab, FILE *out, int indent)
2935 fprintf(out, "%*snull tab\n", indent, "");
2938 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
2939 tab->n_redundant, tab->n_dead);
2941 fprintf(out, ", rational");
2943 fprintf(out, ", empty");
2945 fprintf(out, "%*s[", indent, "");
2946 for (i = 0; i < tab->n_var; ++i) {
2948 fprintf(out, (i == tab->n_param ||
2949 i == tab->n_var - tab->n_div) ? "; "
2951 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
2953 tab->var[i].is_zero ? " [=0]" :
2954 tab->var[i].is_redundant ? " [R]" : "");
2956 fprintf(out, "]\n");
2957 fprintf(out, "%*s[", indent, "");
2958 for (i = 0; i < tab->n_con; ++i) {
2961 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
2963 tab->con[i].is_zero ? " [=0]" :
2964 tab->con[i].is_redundant ? " [R]" : "");
2966 fprintf(out, "]\n");
2967 fprintf(out, "%*s[", indent, "");
2968 for (i = 0; i < tab->n_row; ++i) {
2969 const char *sign = "";
2972 if (tab->row_sign) {
2973 if (tab->row_sign[i] == isl_tab_row_unknown)
2975 else if (tab->row_sign[i] == isl_tab_row_neg)
2977 else if (tab->row_sign[i] == isl_tab_row_pos)
2982 fprintf(out, "r%d: %d%s%s", i, tab->row_var[i],
2983 isl_tab_var_from_row(tab, i)->is_nonneg ? " [>=0]" : "", sign);
2985 fprintf(out, "]\n");
2986 fprintf(out, "%*s[", indent, "");
2987 for (i = 0; i < tab->n_col; ++i) {
2990 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
2991 var_from_col(tab, i)->is_nonneg ? " [>=0]" : "");
2993 fprintf(out, "]\n");
2994 r = tab->mat->n_row;
2995 tab->mat->n_row = tab->n_row;
2996 c = tab->mat->n_col;
2997 tab->mat->n_col = 2 + tab->M + tab->n_col;
2998 isl_mat_dump(tab->mat, out, indent);
2999 tab->mat->n_row = r;
3000 tab->mat->n_col = c;
3002 isl_basic_set_dump(tab->bset, out, indent);