2 #include "isl_map_private.h"
6 * The implementation of tableaus in this file was inspired by Section 8
7 * of David Detlefs, Greg Nelson and James B. Saxe, "Simplify: a theorem
8 * prover for program checking".
11 struct isl_tab *isl_tab_alloc(struct isl_ctx *ctx,
12 unsigned n_row, unsigned n_var)
17 tab = isl_calloc_type(ctx, struct isl_tab);
20 tab->mat = isl_mat_alloc(ctx, n_row, 2 + n_var);
23 tab->var = isl_alloc_array(ctx, struct isl_tab_var, n_var);
26 tab->con = isl_alloc_array(ctx, struct isl_tab_var, n_row);
29 tab->col_var = isl_alloc_array(ctx, int, n_var);
32 tab->row_var = isl_alloc_array(ctx, int, n_row);
35 for (i = 0; i < n_var; ++i) {
36 tab->var[i].index = i;
37 tab->var[i].is_row = 0;
38 tab->var[i].is_nonneg = 0;
39 tab->var[i].is_zero = 0;
40 tab->var[i].is_redundant = 0;
41 tab->var[i].frozen = 0;
56 tab->bottom.type = isl_tab_undo_bottom;
57 tab->bottom.next = NULL;
58 tab->top = &tab->bottom;
65 int isl_tab_extend_cons(struct isl_tab *tab, unsigned n_new)
67 if (tab->max_con < tab->n_con + n_new) {
68 struct isl_tab_var *con;
70 con = isl_realloc_array(tab->mat->ctx, tab->con,
71 struct isl_tab_var, tab->max_con + n_new);
75 tab->max_con += n_new;
77 if (tab->mat->n_row < tab->n_row + n_new) {
80 tab->mat = isl_mat_extend(tab->mat,
81 tab->n_row + n_new, tab->n_col);
84 row_var = isl_realloc_array(tab->mat->ctx, tab->row_var,
85 int, tab->mat->n_row);
88 tab->row_var = row_var;
93 struct isl_tab *isl_tab_extend(struct isl_tab *tab, unsigned n_new)
95 if (isl_tab_extend_cons(tab, n_new) >= 0)
102 static void free_undo(struct isl_tab *tab)
104 struct isl_tab_undo *undo, *next;
106 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
113 void isl_tab_free(struct isl_tab *tab)
118 isl_mat_free(tab->mat);
119 isl_vec_free(tab->dual);
127 struct isl_tab *isl_tab_dup(struct isl_tab *tab)
135 dup = isl_calloc_type(tab->ctx, struct isl_tab);
138 dup->mat = isl_mat_dup(tab->mat);
141 dup->var = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->n_var);
144 for (i = 0; i < tab->n_var; ++i)
145 dup->var[i] = tab->var[i];
146 dup->con = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->max_con);
149 for (i = 0; i < tab->n_con; ++i)
150 dup->con[i] = tab->con[i];
151 dup->col_var = isl_alloc_array(tab->ctx, int, tab->mat->n_col);
154 for (i = 0; i < tab->n_var; ++i)
155 dup->col_var[i] = tab->col_var[i];
156 dup->row_var = isl_alloc_array(tab->ctx, int, tab->mat->n_row);
159 for (i = 0; i < tab->n_row; ++i)
160 dup->row_var[i] = tab->row_var[i];
161 dup->n_row = tab->n_row;
162 dup->n_con = tab->n_con;
163 dup->n_eq = tab->n_eq;
164 dup->max_con = tab->max_con;
165 dup->n_col = tab->n_col;
166 dup->n_var = tab->n_var;
167 dup->n_dead = tab->n_dead;
168 dup->n_redundant = tab->n_redundant;
169 dup->rational = tab->rational;
170 dup->empty = tab->empty;
173 dup->bottom.type = isl_tab_undo_bottom;
174 dup->bottom.next = NULL;
175 dup->top = &dup->bottom;
182 static struct isl_tab_var *var_from_index(struct isl_tab *tab, int i)
187 return &tab->con[~i];
190 struct isl_tab_var *isl_tab_var_from_row(struct isl_tab *tab, int i)
192 return var_from_index(tab, tab->row_var[i]);
195 static struct isl_tab_var *var_from_col(struct isl_tab *tab, int i)
197 return var_from_index(tab, tab->col_var[i]);
200 /* Check if there are any upper bounds on column variable "var",
201 * i.e., non-negative rows where var appears with a negative coefficient.
202 * Return 1 if there are no such bounds.
204 static int max_is_manifestly_unbounded(struct isl_tab *tab,
205 struct isl_tab_var *var)
211 for (i = tab->n_redundant; i < tab->n_row; ++i) {
212 if (!isl_int_is_neg(tab->mat->row[i][2 + var->index]))
214 if (isl_tab_var_from_row(tab, i)->is_nonneg)
220 /* Check if there are any lower bounds on column variable "var",
221 * i.e., non-negative rows where var appears with a positive coefficient.
222 * Return 1 if there are no such bounds.
224 static int min_is_manifestly_unbounded(struct isl_tab *tab,
225 struct isl_tab_var *var)
231 for (i = tab->n_redundant; i < tab->n_row; ++i) {
232 if (!isl_int_is_pos(tab->mat->row[i][2 + var->index]))
234 if (isl_tab_var_from_row(tab, i)->is_nonneg)
240 /* Given the index of a column "c", return the index of a row
241 * that can be used to pivot the column in, with either an increase
242 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
243 * If "var" is not NULL, then the row returned will be different from
244 * the one associated with "var".
246 * Each row in the tableau is of the form
248 * x_r = a_r0 + \sum_i a_ri x_i
250 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
251 * impose any limit on the increase or decrease in the value of x_c
252 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
253 * for the row with the smallest (most stringent) such bound.
254 * Note that the common denominator of each row drops out of the fraction.
255 * To check if row j has a smaller bound than row r, i.e.,
256 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
257 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
258 * where -sign(a_jc) is equal to "sgn".
260 static int pivot_row(struct isl_tab *tab,
261 struct isl_tab_var *var, int sgn, int c)
268 for (j = tab->n_redundant; j < tab->n_row; ++j) {
269 if (var && j == var->index)
271 if (!isl_tab_var_from_row(tab, j)->is_nonneg)
273 if (sgn * isl_int_sgn(tab->mat->row[j][2 + c]) >= 0)
279 isl_int_mul(t, tab->mat->row[r][1], tab->mat->row[j][2 + c]);
280 isl_int_submul(t, tab->mat->row[j][1], tab->mat->row[r][2 + c]);
281 tsgn = sgn * isl_int_sgn(t);
282 if (tsgn < 0 || (tsgn == 0 &&
283 tab->row_var[j] < tab->row_var[r]))
290 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
291 * (sgn < 0) the value of row variable var.
292 * If not NULL, then skip_var is a row variable that should be ignored
293 * while looking for a pivot row. It is usually equal to var.
295 * As the given row in the tableau is of the form
297 * x_r = a_r0 + \sum_i a_ri x_i
299 * we need to find a column such that the sign of a_ri is equal to "sgn"
300 * (such that an increase in x_i will have the desired effect) or a
301 * column with a variable that may attain negative values.
302 * If a_ri is positive, then we need to move x_i in the same direction
303 * to obtain the desired effect. Otherwise, x_i has to move in the
304 * opposite direction.
306 static void find_pivot(struct isl_tab *tab,
307 struct isl_tab_var *var, struct isl_tab_var *skip_var,
308 int sgn, int *row, int *col)
315 isl_assert(tab->mat->ctx, var->is_row, return);
316 tr = tab->mat->row[var->index];
319 for (j = tab->n_dead; j < tab->n_col; ++j) {
320 if (isl_int_is_zero(tr[2 + j]))
322 if (isl_int_sgn(tr[2 + j]) != sgn &&
323 var_from_col(tab, j)->is_nonneg)
325 if (c < 0 || tab->col_var[j] < tab->col_var[c])
331 sgn *= isl_int_sgn(tr[2 + c]);
332 r = pivot_row(tab, skip_var, sgn, c);
333 *row = r < 0 ? var->index : r;
337 /* Return 1 if row "row" represents an obviously redundant inequality.
339 * - it represents an inequality or a variable
340 * - that is the sum of a non-negative sample value and a positive
341 * combination of zero or more non-negative variables.
343 int isl_tab_row_is_redundant(struct isl_tab *tab, int row)
347 if (tab->row_var[row] < 0 && !isl_tab_var_from_row(tab, row)->is_nonneg)
350 if (isl_int_is_neg(tab->mat->row[row][1]))
353 for (i = tab->n_dead; i < tab->n_col; ++i) {
354 if (isl_int_is_zero(tab->mat->row[row][2 + i]))
356 if (isl_int_is_neg(tab->mat->row[row][2 + i]))
358 if (!var_from_col(tab, i)->is_nonneg)
364 static void swap_rows(struct isl_tab *tab, int row1, int row2)
367 t = tab->row_var[row1];
368 tab->row_var[row1] = tab->row_var[row2];
369 tab->row_var[row2] = t;
370 isl_tab_var_from_row(tab, row1)->index = row1;
371 isl_tab_var_from_row(tab, row2)->index = row2;
372 tab->mat = isl_mat_swap_rows(tab->mat, row1, row2);
375 static void push_union(struct isl_tab *tab,
376 enum isl_tab_undo_type type, union isl_tab_undo_val u)
378 struct isl_tab_undo *undo;
383 undo = isl_alloc_type(tab->mat->ctx, struct isl_tab_undo);
391 undo->next = tab->top;
395 void isl_tab_push_var(struct isl_tab *tab,
396 enum isl_tab_undo_type type, struct isl_tab_var *var)
398 union isl_tab_undo_val u;
400 u.var_index = tab->row_var[var->index];
402 u.var_index = tab->col_var[var->index];
403 push_union(tab, type, u);
406 void isl_tab_push(struct isl_tab *tab, enum isl_tab_undo_type type)
408 union isl_tab_undo_val u = { 0 };
409 push_union(tab, type, u);
412 /* Push a record on the undo stack describing the current basic
413 * variables, so that the this state can be restored during rollback.
415 void isl_tab_push_basis(struct isl_tab *tab)
418 union isl_tab_undo_val u;
420 u.col_var = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
426 for (i = 0; i < tab->n_col; ++i)
427 u.col_var[i] = tab->col_var[i];
428 push_union(tab, isl_tab_undo_saved_basis, u);
431 /* Mark row with index "row" as being redundant.
432 * If we may need to undo the operation or if the row represents
433 * a variable of the original problem, the row is kept,
434 * but no longer considered when looking for a pivot row.
435 * Otherwise, the row is simply removed.
437 * The row may be interchanged with some other row. If it
438 * is interchanged with a later row, return 1. Otherwise return 0.
439 * If the rows are checked in order in the calling function,
440 * then a return value of 1 means that the row with the given
441 * row number may now contain a different row that hasn't been checked yet.
443 int isl_tab_mark_redundant(struct isl_tab *tab, int row)
445 struct isl_tab_var *var = isl_tab_var_from_row(tab, row);
446 var->is_redundant = 1;
447 isl_assert(tab->mat->ctx, row >= tab->n_redundant, return);
448 if (tab->need_undo || tab->row_var[row] >= 0) {
449 if (tab->row_var[row] >= 0 && !var->is_nonneg) {
451 isl_tab_push_var(tab, isl_tab_undo_nonneg, var);
453 if (row != tab->n_redundant)
454 swap_rows(tab, row, tab->n_redundant);
455 isl_tab_push_var(tab, isl_tab_undo_redundant, var);
459 if (row != tab->n_row - 1)
460 swap_rows(tab, row, tab->n_row - 1);
461 isl_tab_var_from_row(tab, tab->n_row - 1)->index = -1;
467 struct isl_tab *isl_tab_mark_empty(struct isl_tab *tab)
469 if (!tab->empty && tab->need_undo)
470 isl_tab_push(tab, isl_tab_undo_empty);
475 /* Given a row number "row" and a column number "col", pivot the tableau
476 * such that the associated variables are interchanged.
477 * The given row in the tableau expresses
479 * x_r = a_r0 + \sum_i a_ri x_i
483 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
485 * Substituting this equality into the other rows
487 * x_j = a_j0 + \sum_i a_ji x_i
489 * with a_jc \ne 0, we obtain
491 * 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
498 * where i is any other column and j is any other row,
499 * is therefore transformed into
501 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
502 * 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)
504 * The transformation is performed along the following steps
509 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
512 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
513 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
515 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
516 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
518 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
519 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
521 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
522 * 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)
525 void isl_tab_pivot(struct isl_tab *tab, int row, int col)
530 struct isl_mat *mat = tab->mat;
531 struct isl_tab_var *var;
533 isl_int_swap(mat->row[row][0], mat->row[row][2 + col]);
534 sgn = isl_int_sgn(mat->row[row][0]);
536 isl_int_neg(mat->row[row][0], mat->row[row][0]);
537 isl_int_neg(mat->row[row][2 + col], mat->row[row][2 + col]);
539 for (j = 0; j < 1 + tab->n_col; ++j) {
542 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
544 if (!isl_int_is_one(mat->row[row][0]))
545 isl_seq_normalize(mat->row[row], 2 + tab->n_col);
546 for (i = 0; i < tab->n_row; ++i) {
549 if (isl_int_is_zero(mat->row[i][2 + col]))
551 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
552 for (j = 0; j < 1 + tab->n_col; ++j) {
555 isl_int_mul(mat->row[i][1 + j],
556 mat->row[i][1 + j], mat->row[row][0]);
557 isl_int_addmul(mat->row[i][1 + j],
558 mat->row[i][2 + col], mat->row[row][1 + j]);
560 isl_int_mul(mat->row[i][2 + col],
561 mat->row[i][2 + col], mat->row[row][2 + col]);
562 if (!isl_int_is_one(mat->row[i][0]))
563 isl_seq_normalize(mat->row[i], 2 + tab->n_col);
565 t = tab->row_var[row];
566 tab->row_var[row] = tab->col_var[col];
567 tab->col_var[col] = t;
568 var = isl_tab_var_from_row(tab, row);
571 var = var_from_col(tab, col);
576 for (i = tab->n_redundant; i < tab->n_row; ++i) {
577 if (isl_int_is_zero(mat->row[i][2 + col]))
579 if (!isl_tab_var_from_row(tab, i)->frozen &&
580 isl_tab_row_is_redundant(tab, i))
581 if (isl_tab_mark_redundant(tab, i))
586 /* If "var" represents a column variable, then pivot is up (sgn > 0)
587 * or down (sgn < 0) to a row. The variable is assumed not to be
588 * unbounded in the specified direction.
589 * If sgn = 0, then the variable is unbounded in both directions,
590 * and we pivot with any row we can find.
592 static void to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign)
600 for (r = tab->n_redundant; r < tab->n_row; ++r)
601 if (!isl_int_is_zero(tab->mat->row[r][2 + var->index]))
603 isl_assert(tab->mat->ctx, r < tab->n_row, return);
605 r = pivot_row(tab, NULL, sign, var->index);
606 isl_assert(tab->mat->ctx, r >= 0, return);
609 isl_tab_pivot(tab, r, var->index);
612 static void check_table(struct isl_tab *tab)
618 for (i = 0; i < tab->n_row; ++i) {
619 if (!isl_tab_var_from_row(tab, i)->is_nonneg)
621 assert(!isl_int_is_neg(tab->mat->row[i][1]));
625 /* Return the sign of the maximal value of "var".
626 * If the sign is not negative, then on return from this function,
627 * the sample value will also be non-negative.
629 * If "var" is manifestly unbounded wrt positive values, we are done.
630 * Otherwise, we pivot the variable up to a row if needed
631 * Then we continue pivoting down until either
632 * - no more down pivots can be performed
633 * - the sample value is positive
634 * - the variable is pivoted into a manifestly unbounded column
636 static int sign_of_max(struct isl_tab *tab, struct isl_tab_var *var)
640 if (max_is_manifestly_unbounded(tab, var))
643 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
644 find_pivot(tab, var, var, 1, &row, &col);
646 return isl_int_sgn(tab->mat->row[var->index][1]);
647 isl_tab_pivot(tab, row, col);
648 if (!var->is_row) /* manifestly unbounded */
654 /* Perform pivots until the row variable "var" has a non-negative
655 * sample value or until no more upward pivots can be performed.
656 * Return the sign of the sample value after the pivots have been
659 static int restore_row(struct isl_tab *tab, struct isl_tab_var *var)
663 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
664 find_pivot(tab, var, var, 1, &row, &col);
667 isl_tab_pivot(tab, row, col);
668 if (!var->is_row) /* manifestly unbounded */
671 return isl_int_sgn(tab->mat->row[var->index][1]);
674 /* Perform pivots until we are sure that the row variable "var"
675 * can attain non-negative values. After return from this
676 * function, "var" is still a row variable, but its sample
677 * value may not be non-negative, even if the function returns 1.
679 static int at_least_zero(struct isl_tab *tab, struct isl_tab_var *var)
683 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
684 find_pivot(tab, var, var, 1, &row, &col);
687 if (row == var->index) /* manifestly unbounded */
689 isl_tab_pivot(tab, row, col);
691 return !isl_int_is_neg(tab->mat->row[var->index][1]);
694 /* Return a negative value if "var" can attain negative values.
695 * Return a non-negative value otherwise.
697 * If "var" is manifestly unbounded wrt negative values, we are done.
698 * Otherwise, if var is in a column, we can pivot it down to a row.
699 * Then we continue pivoting down until either
700 * - the pivot would result in a manifestly unbounded column
701 * => we don't perform the pivot, but simply return -1
702 * - no more down pivots can be performed
703 * - the sample value is negative
704 * If the sample value becomes negative and the variable is supposed
705 * to be nonnegative, then we undo the last pivot.
706 * However, if the last pivot has made the pivoting variable
707 * obviously redundant, then it may have moved to another row.
708 * In that case we look for upward pivots until we reach a non-negative
711 static int sign_of_min(struct isl_tab *tab, struct isl_tab_var *var)
714 struct isl_tab_var *pivot_var;
716 if (min_is_manifestly_unbounded(tab, var))
720 row = pivot_row(tab, NULL, -1, col);
721 pivot_var = var_from_col(tab, col);
722 isl_tab_pivot(tab, row, col);
723 if (var->is_redundant)
725 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
726 if (var->is_nonneg) {
727 if (!pivot_var->is_redundant &&
728 pivot_var->index == row)
729 isl_tab_pivot(tab, row, col);
731 restore_row(tab, var);
736 if (var->is_redundant)
738 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
739 find_pivot(tab, var, var, -1, &row, &col);
740 if (row == var->index)
743 return isl_int_sgn(tab->mat->row[var->index][1]);
744 pivot_var = var_from_col(tab, col);
745 isl_tab_pivot(tab, row, col);
746 if (var->is_redundant)
749 if (var->is_nonneg) {
750 /* pivot back to non-negative value */
751 if (!pivot_var->is_redundant && pivot_var->index == row)
752 isl_tab_pivot(tab, row, col);
754 restore_row(tab, var);
759 /* Return 1 if "var" can attain values <= -1.
760 * Return 0 otherwise.
762 * The sample value of "var" is assumed to be non-negative when the
763 * the function is called and will be made non-negative again before
764 * the function returns.
766 int isl_tab_min_at_most_neg_one(struct isl_tab *tab, struct isl_tab_var *var)
769 struct isl_tab_var *pivot_var;
771 if (min_is_manifestly_unbounded(tab, var))
775 row = pivot_row(tab, NULL, -1, col);
776 pivot_var = var_from_col(tab, col);
777 isl_tab_pivot(tab, row, col);
778 if (var->is_redundant)
780 if (isl_int_is_neg(tab->mat->row[var->index][1]) &&
781 isl_int_abs_ge(tab->mat->row[var->index][1],
782 tab->mat->row[var->index][0])) {
783 if (var->is_nonneg) {
784 if (!pivot_var->is_redundant &&
785 pivot_var->index == row)
786 isl_tab_pivot(tab, row, col);
788 restore_row(tab, var);
793 if (var->is_redundant)
796 find_pivot(tab, var, var, -1, &row, &col);
797 if (row == var->index)
801 pivot_var = var_from_col(tab, col);
802 isl_tab_pivot(tab, row, col);
803 if (var->is_redundant)
805 } while (!isl_int_is_neg(tab->mat->row[var->index][1]) ||
806 isl_int_abs_lt(tab->mat->row[var->index][1],
807 tab->mat->row[var->index][0]));
808 if (var->is_nonneg) {
809 /* pivot back to non-negative value */
810 if (!pivot_var->is_redundant && pivot_var->index == row)
811 isl_tab_pivot(tab, row, col);
812 restore_row(tab, var);
817 /* Return 1 if "var" can attain values >= 1.
818 * Return 0 otherwise.
820 static int at_least_one(struct isl_tab *tab, struct isl_tab_var *var)
825 if (max_is_manifestly_unbounded(tab, var))
828 r = tab->mat->row[var->index];
829 while (isl_int_lt(r[1], r[0])) {
830 find_pivot(tab, var, var, 1, &row, &col);
832 return isl_int_ge(r[1], r[0]);
833 if (row == var->index) /* manifestly unbounded */
835 isl_tab_pivot(tab, row, col);
840 static void swap_cols(struct isl_tab *tab, int col1, int col2)
843 t = tab->col_var[col1];
844 tab->col_var[col1] = tab->col_var[col2];
845 tab->col_var[col2] = t;
846 var_from_col(tab, col1)->index = col1;
847 var_from_col(tab, col2)->index = col2;
848 tab->mat = isl_mat_swap_cols(tab->mat, 2 + col1, 2 + col2);
851 /* Mark column with index "col" as representing a zero variable.
852 * If we may need to undo the operation the column is kept,
853 * but no longer considered.
854 * Otherwise, the column is simply removed.
856 * The column may be interchanged with some other column. If it
857 * is interchanged with a later column, return 1. Otherwise return 0.
858 * If the columns are checked in order in the calling function,
859 * then a return value of 1 means that the column with the given
860 * column number may now contain a different column that
861 * hasn't been checked yet.
863 int isl_tab_kill_col(struct isl_tab *tab, int col)
865 var_from_col(tab, col)->is_zero = 1;
866 if (tab->need_undo) {
867 isl_tab_push_var(tab, isl_tab_undo_zero, var_from_col(tab, col));
868 if (col != tab->n_dead)
869 swap_cols(tab, col, tab->n_dead);
873 if (col != tab->n_col - 1)
874 swap_cols(tab, col, tab->n_col - 1);
875 var_from_col(tab, tab->n_col - 1)->index = -1;
881 /* Row variable "var" is non-negative and cannot attain any values
882 * larger than zero. This means that the coefficients of the unrestricted
883 * column variables are zero and that the coefficients of the non-negative
884 * column variables are zero or negative.
885 * Each of the non-negative variables with a negative coefficient can
886 * then also be written as the negative sum of non-negative variables
887 * and must therefore also be zero.
889 static void close_row(struct isl_tab *tab, struct isl_tab_var *var)
892 struct isl_mat *mat = tab->mat;
894 isl_assert(tab->mat->ctx, var->is_nonneg, return);
896 for (j = tab->n_dead; j < tab->n_col; ++j) {
897 if (isl_int_is_zero(mat->row[var->index][2 + j]))
899 isl_assert(tab->mat->ctx,
900 isl_int_is_neg(mat->row[var->index][2 + j]), return);
901 if (isl_tab_kill_col(tab, j))
904 isl_tab_mark_redundant(tab, var->index);
907 /* Add a constraint to the tableau and allocate a row for it.
908 * Return the index into the constraint array "con".
910 int isl_tab_allocate_con(struct isl_tab *tab)
914 isl_assert(tab->mat->ctx, tab->n_row < tab->mat->n_row, return -1);
917 tab->con[r].index = tab->n_row;
918 tab->con[r].is_row = 1;
919 tab->con[r].is_nonneg = 0;
920 tab->con[r].is_zero = 0;
921 tab->con[r].is_redundant = 0;
922 tab->con[r].frozen = 0;
923 tab->row_var[tab->n_row] = ~r;
927 isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]);
932 /* Add a row to the tableau. The row is given as an affine combination
933 * of the original variables and needs to be expressed in terms of the
936 * We add each term in turn.
937 * If r = n/d_r is the current sum and we need to add k x, then
938 * if x is a column variable, we increase the numerator of
939 * this column by k d_r
940 * if x = f/d_x is a row variable, then the new representation of r is
942 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
943 * --- + --- = ------------------- = -------------------
944 * d_r d_r d_r d_x/g m
946 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
948 int isl_tab_add_row(struct isl_tab *tab, isl_int *line)
955 r = isl_tab_allocate_con(tab);
961 row = tab->mat->row[tab->con[r].index];
962 isl_int_set_si(row[0], 1);
963 isl_int_set(row[1], line[0]);
964 isl_seq_clr(row + 2, tab->n_col);
965 for (i = 0; i < tab->n_var; ++i) {
966 if (tab->var[i].is_zero)
968 if (tab->var[i].is_row) {
970 row[0], tab->mat->row[tab->var[i].index][0]);
971 isl_int_swap(a, row[0]);
972 isl_int_divexact(a, row[0], a);
974 row[0], tab->mat->row[tab->var[i].index][0]);
975 isl_int_mul(b, b, line[1 + i]);
976 isl_seq_combine(row + 1, a, row + 1,
977 b, tab->mat->row[tab->var[i].index] + 1,
980 isl_int_addmul(row[2 + tab->var[i].index],
981 line[1 + i], row[0]);
983 isl_seq_normalize(row, 2 + tab->n_col);
990 static int drop_row(struct isl_tab *tab, int row)
992 isl_assert(tab->mat->ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
993 if (row != tab->n_row - 1)
994 swap_rows(tab, row, tab->n_row - 1);
1000 /* Add inequality "ineq" and check if it conflicts with the
1001 * previously added constraints or if it is obviously redundant.
1003 struct isl_tab *isl_tab_add_ineq(struct isl_tab *tab, isl_int *ineq)
1010 r = isl_tab_add_row(tab, ineq);
1013 tab->con[r].is_nonneg = 1;
1014 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
1015 if (isl_tab_row_is_redundant(tab, tab->con[r].index)) {
1016 isl_tab_mark_redundant(tab, tab->con[r].index);
1020 sgn = restore_row(tab, &tab->con[r]);
1022 return isl_tab_mark_empty(tab);
1023 if (tab->con[r].is_row && isl_tab_row_is_redundant(tab, tab->con[r].index))
1024 isl_tab_mark_redundant(tab, tab->con[r].index);
1031 /* Pivot a non-negative variable down until it reaches the value zero
1032 * and then pivot the variable into a column position.
1034 int to_col(struct isl_tab *tab, struct isl_tab_var *var)
1042 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
1043 find_pivot(tab, var, NULL, -1, &row, &col);
1044 isl_assert(tab->mat->ctx, row != -1, return -1);
1045 isl_tab_pivot(tab, row, col);
1050 for (i = tab->n_dead; i < tab->n_col; ++i)
1051 if (!isl_int_is_zero(tab->mat->row[var->index][2 + i]))
1054 isl_assert(tab->mat->ctx, i < tab->n_col, return -1);
1055 isl_tab_pivot(tab, var->index, i);
1060 /* We assume Gaussian elimination has been performed on the equalities.
1061 * The equalities can therefore never conflict.
1062 * Adding the equalities is currently only really useful for a later call
1063 * to isl_tab_ineq_type.
1065 static struct isl_tab *add_eq(struct isl_tab *tab, isl_int *eq)
1072 r = isl_tab_add_row(tab, eq);
1076 r = tab->con[r].index;
1077 i = isl_seq_first_non_zero(tab->mat->row[r] + 2 + tab->n_dead,
1078 tab->n_col - tab->n_dead);
1079 isl_assert(tab->mat->ctx, i >= 0, goto error);
1081 isl_tab_pivot(tab, r, i);
1082 isl_tab_kill_col(tab, i);
1091 /* Add an equality that is known to be valid for the given tableau.
1093 struct isl_tab *isl_tab_add_valid_eq(struct isl_tab *tab, isl_int *eq)
1095 struct isl_tab_var *var;
1101 r = isl_tab_add_row(tab, eq);
1107 if (isl_int_is_neg(tab->mat->row[r][1]))
1108 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1111 if (to_col(tab, var) < 0)
1114 isl_tab_kill_col(tab, var->index);
1122 struct isl_tab *isl_tab_from_basic_map(struct isl_basic_map *bmap)
1125 struct isl_tab *tab;
1129 tab = isl_tab_alloc(bmap->ctx,
1130 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
1131 isl_basic_map_total_dim(bmap));
1134 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1135 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY))
1136 return isl_tab_mark_empty(tab);
1137 for (i = 0; i < bmap->n_eq; ++i) {
1138 tab = add_eq(tab, bmap->eq[i]);
1142 for (i = 0; i < bmap->n_ineq; ++i) {
1143 tab = isl_tab_add_ineq(tab, bmap->ineq[i]);
1144 if (!tab || tab->empty)
1150 struct isl_tab *isl_tab_from_basic_set(struct isl_basic_set *bset)
1152 return isl_tab_from_basic_map((struct isl_basic_map *)bset);
1155 /* Construct a tableau corresponding to the recession cone of "bmap".
1157 struct isl_tab *isl_tab_from_recession_cone(struct isl_basic_map *bmap)
1161 struct isl_tab *tab;
1165 tab = isl_tab_alloc(bmap->ctx, bmap->n_eq + bmap->n_ineq,
1166 isl_basic_map_total_dim(bmap));
1169 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1172 for (i = 0; i < bmap->n_eq; ++i) {
1173 isl_int_swap(bmap->eq[i][0], cst);
1174 tab = add_eq(tab, bmap->eq[i]);
1175 isl_int_swap(bmap->eq[i][0], cst);
1179 for (i = 0; i < bmap->n_ineq; ++i) {
1181 isl_int_swap(bmap->ineq[i][0], cst);
1182 r = isl_tab_add_row(tab, bmap->ineq[i]);
1183 isl_int_swap(bmap->ineq[i][0], cst);
1186 tab->con[r].is_nonneg = 1;
1187 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
1198 /* Assuming "tab" is the tableau of a cone, check if the cone is
1199 * bounded, i.e., if it is empty or only contains the origin.
1201 int isl_tab_cone_is_bounded(struct isl_tab *tab)
1209 if (tab->n_dead == tab->n_col)
1213 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1214 struct isl_tab_var *var;
1215 var = isl_tab_var_from_row(tab, i);
1216 if (!var->is_nonneg)
1218 if (sign_of_max(tab, var) != 0)
1220 close_row(tab, var);
1223 if (tab->n_dead == tab->n_col)
1225 if (i == tab->n_row)
1230 int isl_tab_sample_is_integer(struct isl_tab *tab)
1237 for (i = 0; i < tab->n_var; ++i) {
1239 if (!tab->var[i].is_row)
1241 row = tab->var[i].index;
1242 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
1243 tab->mat->row[row][0]))
1249 static struct isl_vec *extract_integer_sample(struct isl_tab *tab)
1252 struct isl_vec *vec;
1254 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1258 isl_int_set_si(vec->block.data[0], 1);
1259 for (i = 0; i < tab->n_var; ++i) {
1260 if (!tab->var[i].is_row)
1261 isl_int_set_si(vec->block.data[1 + i], 0);
1263 int row = tab->var[i].index;
1264 isl_int_divexact(vec->block.data[1 + i],
1265 tab->mat->row[row][1], tab->mat->row[row][0]);
1272 struct isl_vec *isl_tab_get_sample_value(struct isl_tab *tab)
1275 struct isl_vec *vec;
1281 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1287 isl_int_set_si(vec->block.data[0], 1);
1288 for (i = 0; i < tab->n_var; ++i) {
1290 if (!tab->var[i].is_row) {
1291 isl_int_set_si(vec->block.data[1 + i], 0);
1294 row = tab->var[i].index;
1295 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
1296 isl_int_divexact(m, tab->mat->row[row][0], m);
1297 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
1298 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
1299 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
1301 isl_seq_normalize(vec->block.data, vec->size);
1307 /* Update "bmap" based on the results of the tableau "tab".
1308 * In particular, implicit equalities are made explicit, redundant constraints
1309 * are removed and if the sample value happens to be integer, it is stored
1310 * in "bmap" (unless "bmap" already had an integer sample).
1312 * The tableau is assumed to have been created from "bmap" using
1313 * isl_tab_from_basic_map.
1315 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
1316 struct isl_tab *tab)
1328 bmap = isl_basic_map_set_to_empty(bmap);
1330 for (i = bmap->n_ineq - 1; i >= 0; --i) {
1331 if (isl_tab_is_equality(tab, n_eq + i))
1332 isl_basic_map_inequality_to_equality(bmap, i);
1333 else if (isl_tab_is_redundant(tab, n_eq + i))
1334 isl_basic_map_drop_inequality(bmap, i);
1336 if (!tab->rational &&
1337 !bmap->sample && isl_tab_sample_is_integer(tab))
1338 bmap->sample = extract_integer_sample(tab);
1342 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
1343 struct isl_tab *tab)
1345 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
1346 (struct isl_basic_map *)bset, tab);
1349 /* Given a non-negative variable "var", add a new non-negative variable
1350 * that is the opposite of "var", ensuring that var can only attain the
1352 * If var = n/d is a row variable, then the new variable = -n/d.
1353 * If var is a column variables, then the new variable = -var.
1354 * If the new variable cannot attain non-negative values, then
1355 * the resulting tableau is empty.
1356 * Otherwise, we know the value will be zero and we close the row.
1358 static struct isl_tab *cut_to_hyperplane(struct isl_tab *tab,
1359 struct isl_tab_var *var)
1365 if (isl_tab_extend_cons(tab, 1) < 0)
1369 tab->con[r].index = tab->n_row;
1370 tab->con[r].is_row = 1;
1371 tab->con[r].is_nonneg = 0;
1372 tab->con[r].is_zero = 0;
1373 tab->con[r].is_redundant = 0;
1374 tab->con[r].frozen = 0;
1375 tab->row_var[tab->n_row] = ~r;
1376 row = tab->mat->row[tab->n_row];
1379 isl_int_set(row[0], tab->mat->row[var->index][0]);
1380 isl_seq_neg(row + 1,
1381 tab->mat->row[var->index] + 1, 1 + tab->n_col);
1383 isl_int_set_si(row[0], 1);
1384 isl_seq_clr(row + 1, 1 + tab->n_col);
1385 isl_int_set_si(row[2 + var->index], -1);
1390 isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]);
1392 sgn = sign_of_max(tab, &tab->con[r]);
1394 return isl_tab_mark_empty(tab);
1395 tab->con[r].is_nonneg = 1;
1396 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
1398 close_row(tab, &tab->con[r]);
1406 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
1407 * relax the inequality by one. That is, the inequality r >= 0 is replaced
1408 * by r' = r + 1 >= 0.
1409 * If r is a row variable, we simply increase the constant term by one
1410 * (taking into account the denominator).
1411 * If r is a column variable, then we need to modify each row that
1412 * refers to r = r' - 1 by substituting this equality, effectively
1413 * subtracting the coefficient of the column from the constant.
1415 struct isl_tab *isl_tab_relax(struct isl_tab *tab, int con)
1417 struct isl_tab_var *var;
1421 var = &tab->con[con];
1423 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
1424 to_row(tab, var, 1);
1427 isl_int_add(tab->mat->row[var->index][1],
1428 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1432 for (i = 0; i < tab->n_row; ++i) {
1433 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1435 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
1436 tab->mat->row[i][2 + var->index]);
1441 isl_tab_push_var(tab, isl_tab_undo_relax, var);
1446 struct isl_tab *isl_tab_select_facet(struct isl_tab *tab, int con)
1451 return cut_to_hyperplane(tab, &tab->con[con]);
1454 static int may_be_equality(struct isl_tab *tab, int row)
1456 return (tab->rational ? isl_int_is_zero(tab->mat->row[row][1])
1457 : isl_int_lt(tab->mat->row[row][1],
1458 tab->mat->row[row][0])) &&
1459 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1460 tab->n_col - tab->n_dead) != -1;
1463 /* Check for (near) equalities among the constraints.
1464 * A constraint is an equality if it is non-negative and if
1465 * its maximal value is either
1466 * - zero (in case of rational tableaus), or
1467 * - strictly less than 1 (in case of integer tableaus)
1469 * We first mark all non-redundant and non-dead variables that
1470 * are not frozen and not obviously not an equality.
1471 * Then we iterate over all marked variables if they can attain
1472 * any values larger than zero or at least one.
1473 * If the maximal value is zero, we mark any column variables
1474 * that appear in the row as being zero and mark the row as being redundant.
1475 * Otherwise, if the maximal value is strictly less than one (and the
1476 * tableau is integer), then we restrict the value to being zero
1477 * by adding an opposite non-negative variable.
1479 struct isl_tab *isl_tab_detect_equalities(struct isl_tab *tab)
1488 if (tab->n_dead == tab->n_col)
1492 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1493 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
1494 var->marked = !var->frozen && var->is_nonneg &&
1495 may_be_equality(tab, i);
1499 for (i = tab->n_dead; i < tab->n_col; ++i) {
1500 struct isl_tab_var *var = var_from_col(tab, i);
1501 var->marked = !var->frozen && var->is_nonneg;
1506 struct isl_tab_var *var;
1507 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1508 var = isl_tab_var_from_row(tab, i);
1512 if (i == tab->n_row) {
1513 for (i = tab->n_dead; i < tab->n_col; ++i) {
1514 var = var_from_col(tab, i);
1518 if (i == tab->n_col)
1523 if (sign_of_max(tab, var) == 0)
1524 close_row(tab, var);
1525 else if (!tab->rational && !at_least_one(tab, var)) {
1526 tab = cut_to_hyperplane(tab, var);
1527 return isl_tab_detect_equalities(tab);
1529 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1530 var = isl_tab_var_from_row(tab, i);
1533 if (may_be_equality(tab, i))
1543 /* Check for (near) redundant constraints.
1544 * A constraint is redundant if it is non-negative and if
1545 * its minimal value (temporarily ignoring the non-negativity) is either
1546 * - zero (in case of rational tableaus), or
1547 * - strictly larger than -1 (in case of integer tableaus)
1549 * We first mark all non-redundant and non-dead variables that
1550 * are not frozen and not obviously negatively unbounded.
1551 * Then we iterate over all marked variables if they can attain
1552 * any values smaller than zero or at most negative one.
1553 * If not, we mark the row as being redundant (assuming it hasn't
1554 * been detected as being obviously redundant in the mean time).
1556 struct isl_tab *isl_tab_detect_redundant(struct isl_tab *tab)
1565 if (tab->n_redundant == tab->n_row)
1569 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1570 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
1571 var->marked = !var->frozen && var->is_nonneg;
1575 for (i = tab->n_dead; i < tab->n_col; ++i) {
1576 struct isl_tab_var *var = var_from_col(tab, i);
1577 var->marked = !var->frozen && var->is_nonneg &&
1578 !min_is_manifestly_unbounded(tab, var);
1583 struct isl_tab_var *var;
1584 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1585 var = isl_tab_var_from_row(tab, i);
1589 if (i == tab->n_row) {
1590 for (i = tab->n_dead; i < tab->n_col; ++i) {
1591 var = var_from_col(tab, i);
1595 if (i == tab->n_col)
1600 if ((tab->rational ? (sign_of_min(tab, var) >= 0)
1601 : !isl_tab_min_at_most_neg_one(tab, var)) &&
1603 isl_tab_mark_redundant(tab, var->index);
1604 for (i = tab->n_dead; i < tab->n_col; ++i) {
1605 var = var_from_col(tab, i);
1608 if (!min_is_manifestly_unbounded(tab, var))
1618 int isl_tab_is_equality(struct isl_tab *tab, int con)
1624 if (tab->con[con].is_zero)
1626 if (tab->con[con].is_redundant)
1628 if (!tab->con[con].is_row)
1629 return tab->con[con].index < tab->n_dead;
1631 row = tab->con[con].index;
1633 return isl_int_is_zero(tab->mat->row[row][1]) &&
1634 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1635 tab->n_col - tab->n_dead) == -1;
1638 /* Return the minimial value of the affine expression "f" with denominator
1639 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
1640 * the expression cannot attain arbitrarily small values.
1641 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
1642 * The return value reflects the nature of the result (empty, unbounded,
1643 * minmimal value returned in *opt).
1645 enum isl_lp_result isl_tab_min(struct isl_tab *tab,
1646 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom,
1650 enum isl_lp_result res = isl_lp_ok;
1651 struct isl_tab_var *var;
1652 struct isl_tab_undo *snap;
1655 return isl_lp_empty;
1657 snap = isl_tab_snap(tab);
1658 r = isl_tab_add_row(tab, f);
1660 return isl_lp_error;
1662 isl_int_mul(tab->mat->row[var->index][0],
1663 tab->mat->row[var->index][0], denom);
1666 find_pivot(tab, var, var, -1, &row, &col);
1667 if (row == var->index) {
1668 res = isl_lp_unbounded;
1673 isl_tab_pivot(tab, row, col);
1675 if (isl_tab_rollback(tab, snap) < 0)
1676 return isl_lp_error;
1677 if (ISL_FL_ISSET(flags, ISL_TAB_SAVE_DUAL)) {
1680 isl_vec_free(tab->dual);
1681 tab->dual = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_con);
1683 return isl_lp_error;
1684 isl_int_set(tab->dual->el[0], tab->mat->row[var->index][0]);
1685 for (i = 0; i < tab->n_con; ++i) {
1686 if (tab->con[i].is_row)
1687 isl_int_set_si(tab->dual->el[1 + i], 0);
1689 int pos = 2 + tab->con[i].index;
1690 isl_int_set(tab->dual->el[1 + i],
1691 tab->mat->row[var->index][pos]);
1695 if (res == isl_lp_ok) {
1697 isl_int_set(*opt, tab->mat->row[var->index][1]);
1698 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
1700 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
1701 tab->mat->row[var->index][0]);
1706 int isl_tab_is_redundant(struct isl_tab *tab, int con)
1713 if (tab->con[con].is_zero)
1715 if (tab->con[con].is_redundant)
1717 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
1720 /* Take a snapshot of the tableau that can be restored by s call to
1723 struct isl_tab_undo *isl_tab_snap(struct isl_tab *tab)
1731 /* Undo the operation performed by isl_tab_relax.
1733 static void unrelax(struct isl_tab *tab, struct isl_tab_var *var)
1735 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
1736 to_row(tab, var, 1);
1739 isl_int_sub(tab->mat->row[var->index][1],
1740 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1744 for (i = 0; i < tab->n_row; ++i) {
1745 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1747 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
1748 tab->mat->row[i][2 + var->index]);
1754 static void perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo)
1756 struct isl_tab_var *var = var_from_index(tab, undo->u.var_index);
1757 switch(undo->type) {
1758 case isl_tab_undo_nonneg:
1761 case isl_tab_undo_redundant:
1762 var->is_redundant = 0;
1765 case isl_tab_undo_zero:
1769 case isl_tab_undo_allocate:
1771 if (!max_is_manifestly_unbounded(tab, var))
1772 to_row(tab, var, 1);
1773 else if (!min_is_manifestly_unbounded(tab, var))
1774 to_row(tab, var, -1);
1776 to_row(tab, var, 0);
1778 drop_row(tab, var->index);
1780 case isl_tab_undo_relax:
1786 /* Restore the tableau to the state where the basic variables
1787 * are those in "col_var".
1788 * We first construct a list of variables that are currently in
1789 * the basis, but shouldn't. Then we iterate over all variables
1790 * that should be in the basis and for each one that is currently
1791 * not in the basis, we exchange it with one of the elements of the
1792 * list constructed before.
1793 * We can always find an appropriate variable to pivot with because
1794 * the current basis is mapped to the old basis by a non-singular
1795 * matrix and so we can never end up with a zero row.
1797 static int restore_basis(struct isl_tab *tab, int *col_var)
1801 int *extra = NULL; /* current columns that contain bad stuff */
1804 extra = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
1807 for (i = 0; i < tab->n_col; ++i) {
1808 for (j = 0; j < tab->n_col; ++j)
1809 if (tab->col_var[i] == col_var[j])
1813 extra[n_extra++] = i;
1815 for (i = 0; i < tab->n_col && n_extra > 0; ++i) {
1816 struct isl_tab_var *var;
1819 for (j = 0; j < tab->n_col; ++j)
1820 if (col_var[i] == tab->col_var[j])
1824 var = var_from_index(tab, col_var[i]);
1826 for (j = 0; j < n_extra; ++j)
1827 if (!isl_int_is_zero(tab->mat->row[row][off+extra[j]]))
1829 isl_assert(tab->mat->ctx, j < n_extra, goto error);
1830 isl_tab_pivot(tab, row, extra[j]);
1831 extra[j] = extra[--n_extra];
1843 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo)
1845 switch (undo->type) {
1846 case isl_tab_undo_empty:
1849 case isl_tab_undo_nonneg:
1850 case isl_tab_undo_redundant:
1851 case isl_tab_undo_zero:
1852 case isl_tab_undo_allocate:
1853 case isl_tab_undo_relax:
1854 perform_undo_var(tab, undo);
1856 case isl_tab_undo_saved_basis:
1857 if (restore_basis(tab, undo->u.col_var) < 0)
1861 isl_assert(tab->mat->ctx, 0, return -1);
1866 /* Return the tableau to the state it was in when the snapshot "snap"
1869 int isl_tab_rollback(struct isl_tab *tab, struct isl_tab_undo *snap)
1871 struct isl_tab_undo *undo, *next;
1877 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
1881 if (perform_undo(tab, undo) < 0) {
1895 /* The given row "row" represents an inequality violated by all
1896 * points in the tableau. Check for some special cases of such
1897 * separating constraints.
1898 * In particular, if the row has been reduced to the constant -1,
1899 * then we know the inequality is adjacent (but opposite) to
1900 * an equality in the tableau.
1901 * If the row has been reduced to r = -1 -r', with r' an inequality
1902 * of the tableau, then the inequality is adjacent (but opposite)
1903 * to the inequality r'.
1905 static enum isl_ineq_type separation_type(struct isl_tab *tab, unsigned row)
1910 return isl_ineq_separate;
1912 if (!isl_int_is_one(tab->mat->row[row][0]))
1913 return isl_ineq_separate;
1914 if (!isl_int_is_negone(tab->mat->row[row][1]))
1915 return isl_ineq_separate;
1917 pos = isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1918 tab->n_col - tab->n_dead);
1920 return isl_ineq_adj_eq;
1922 if (!isl_int_is_negone(tab->mat->row[row][2 + tab->n_dead + pos]))
1923 return isl_ineq_separate;
1925 pos = isl_seq_first_non_zero(
1926 tab->mat->row[row] + 2 + tab->n_dead + pos + 1,
1927 tab->n_col - tab->n_dead - pos - 1);
1929 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
1932 /* Check the effect of inequality "ineq" on the tableau "tab".
1934 * isl_ineq_redundant: satisfied by all points in the tableau
1935 * isl_ineq_separate: satisfied by no point in the tableau
1936 * isl_ineq_cut: satisfied by some by not all points
1937 * isl_ineq_adj_eq: adjacent to an equality
1938 * isl_ineq_adj_ineq: adjacent to an inequality.
1940 enum isl_ineq_type isl_tab_ineq_type(struct isl_tab *tab, isl_int *ineq)
1942 enum isl_ineq_type type = isl_ineq_error;
1943 struct isl_tab_undo *snap = NULL;
1948 return isl_ineq_error;
1950 if (isl_tab_extend_cons(tab, 1) < 0)
1951 return isl_ineq_error;
1953 snap = isl_tab_snap(tab);
1955 con = isl_tab_add_row(tab, ineq);
1959 row = tab->con[con].index;
1960 if (isl_tab_row_is_redundant(tab, row))
1961 type = isl_ineq_redundant;
1962 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
1964 isl_int_abs_ge(tab->mat->row[row][1],
1965 tab->mat->row[row][0]))) {
1966 if (at_least_zero(tab, &tab->con[con]))
1967 type = isl_ineq_cut;
1969 type = separation_type(tab, row);
1970 } else if (tab->rational ? (sign_of_min(tab, &tab->con[con]) < 0)
1971 : isl_tab_min_at_most_neg_one(tab, &tab->con[con]))
1972 type = isl_ineq_cut;
1974 type = isl_ineq_redundant;
1976 if (isl_tab_rollback(tab, snap))
1977 return isl_ineq_error;
1980 isl_tab_rollback(tab, snap);
1981 return isl_ineq_error;
1984 void isl_tab_dump(struct isl_tab *tab, FILE *out, int indent)
1990 fprintf(out, "%*snull tab\n", indent, "");
1993 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
1994 tab->n_redundant, tab->n_dead);
1996 fprintf(out, ", rational");
1998 fprintf(out, ", empty");
2000 fprintf(out, "%*s[", indent, "");
2001 for (i = 0; i < tab->n_var; ++i) {
2004 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
2006 tab->var[i].is_zero ? " [=0]" :
2007 tab->var[i].is_redundant ? " [R]" : "");
2009 fprintf(out, "]\n");
2010 fprintf(out, "%*s[", indent, "");
2011 for (i = 0; i < tab->n_con; ++i) {
2014 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
2016 tab->con[i].is_zero ? " [=0]" :
2017 tab->con[i].is_redundant ? " [R]" : "");
2019 fprintf(out, "]\n");
2020 fprintf(out, "%*s[", indent, "");
2021 for (i = 0; i < tab->n_row; ++i) {
2024 fprintf(out, "r%d: %d%s", i, tab->row_var[i],
2025 isl_tab_var_from_row(tab, i)->is_nonneg ? " [>=0]" : "");
2027 fprintf(out, "]\n");
2028 fprintf(out, "%*s[", indent, "");
2029 for (i = 0; i < tab->n_col; ++i) {
2032 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
2033 var_from_col(tab, i)->is_nonneg ? " [>=0]" : "");
2035 fprintf(out, "]\n");
2036 r = tab->mat->n_row;
2037 tab->mat->n_row = tab->n_row;
2038 c = tab->mat->n_col;
2039 tab->mat->n_col = 2 + tab->n_col;
2040 isl_mat_dump(tab->mat, out, indent);
2041 tab->mat->n_row = r;
2042 tab->mat->n_col = c;