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 static int 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 (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 static struct isl_tab_var *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 (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 (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 (!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 static int is_redundant(struct isl_tab *tab, int row)
347 if (tab->row_var[row] < 0 && !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 var_from_row(tab, row1)->index = row1;
371 var_from_row(tab, row2)->index = row2;
372 tab->mat = isl_mat_swap_rows(tab->mat, row1, row2);
375 static void push(struct isl_tab *tab,
376 enum isl_tab_undo_type type, struct isl_tab_var *var)
378 struct isl_tab_undo *undo;
383 undo = isl_alloc_type(tab->mat->ctx, struct isl_tab_undo);
392 else if (var->is_row)
393 undo->var_index = tab->row_var[var->index];
395 undo->var_index = tab->col_var[var->index];
396 undo->next = tab->top;
400 /* Mark row with index "row" as being redundant.
401 * If we may need to undo the operation or if the row represents
402 * a variable of the original problem, the row is kept,
403 * but no longer considered when looking for a pivot row.
404 * Otherwise, the row is simply removed.
406 * The row may be interchanged with some other row. If it
407 * is interchanged with a later row, return 1. Otherwise return 0.
408 * If the rows are checked in order in the calling function,
409 * then a return value of 1 means that the row with the given
410 * row number may now contain a different row that hasn't been checked yet.
412 static int mark_redundant(struct isl_tab *tab, int row)
414 struct isl_tab_var *var = var_from_row(tab, row);
415 var->is_redundant = 1;
416 isl_assert(tab->mat->ctx, row >= tab->n_redundant, return);
417 if (tab->need_undo || tab->row_var[row] >= 0) {
418 if (tab->row_var[row] >= 0 && !var->is_nonneg) {
420 push(tab, isl_tab_undo_nonneg, var);
422 if (row != tab->n_redundant)
423 swap_rows(tab, row, tab->n_redundant);
424 push(tab, isl_tab_undo_redundant, var);
428 if (row != tab->n_row - 1)
429 swap_rows(tab, row, tab->n_row - 1);
430 var_from_row(tab, tab->n_row - 1)->index = -1;
436 static struct isl_tab *mark_empty(struct isl_tab *tab)
438 if (!tab->empty && tab->need_undo)
439 push(tab, isl_tab_undo_empty, NULL);
444 /* Given a row number "row" and a column number "col", pivot the tableau
445 * such that the associated variables are interchanged.
446 * The given row in the tableau expresses
448 * x_r = a_r0 + \sum_i a_ri x_i
452 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
454 * Substituting this equality into the other rows
456 * x_j = a_j0 + \sum_i a_ji x_i
458 * with a_jc \ne 0, we obtain
460 * 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
467 * where i is any other column and j is any other row,
468 * is therefore transformed into
470 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
471 * 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)
473 * The transformation is performed along the following steps
478 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
481 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
482 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
484 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
485 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
487 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
488 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
490 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
491 * 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)
494 static void pivot(struct isl_tab *tab, int row, int col)
499 struct isl_mat *mat = tab->mat;
500 struct isl_tab_var *var;
502 isl_int_swap(mat->row[row][0], mat->row[row][2 + col]);
503 sgn = isl_int_sgn(mat->row[row][0]);
505 isl_int_neg(mat->row[row][0], mat->row[row][0]);
506 isl_int_neg(mat->row[row][2 + col], mat->row[row][2 + col]);
508 for (j = 0; j < 1 + tab->n_col; ++j) {
511 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
513 if (!isl_int_is_one(mat->row[row][0]))
514 isl_seq_normalize(mat->row[row], 2 + tab->n_col);
515 for (i = 0; i < tab->n_row; ++i) {
518 if (isl_int_is_zero(mat->row[i][2 + col]))
520 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
521 for (j = 0; j < 1 + tab->n_col; ++j) {
524 isl_int_mul(mat->row[i][1 + j],
525 mat->row[i][1 + j], mat->row[row][0]);
526 isl_int_addmul(mat->row[i][1 + j],
527 mat->row[i][2 + col], mat->row[row][1 + j]);
529 isl_int_mul(mat->row[i][2 + col],
530 mat->row[i][2 + col], mat->row[row][2 + col]);
531 if (!isl_int_is_one(mat->row[i][0]))
532 isl_seq_normalize(mat->row[i], 2 + tab->n_col);
534 t = tab->row_var[row];
535 tab->row_var[row] = tab->col_var[col];
536 tab->col_var[col] = t;
537 var = var_from_row(tab, row);
540 var = var_from_col(tab, col);
545 for (i = tab->n_redundant; i < tab->n_row; ++i) {
546 if (isl_int_is_zero(mat->row[i][2 + col]))
548 if (!var_from_row(tab, i)->frozen &&
549 is_redundant(tab, i))
550 if (mark_redundant(tab, i))
555 /* If "var" represents a column variable, then pivot is up (sgn > 0)
556 * or down (sgn < 0) to a row. The variable is assumed not to be
557 * unbounded in the specified direction.
558 * If sgn = 0, then the variable is unbounded in both directions,
559 * and we pivot with any row we can find.
561 static void to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign)
569 for (r = tab->n_redundant; r < tab->n_row; ++r)
570 if (!isl_int_is_zero(tab->mat->row[r][2 + var->index]))
572 isl_assert(tab->mat->ctx, r < tab->n_row, return);
574 r = pivot_row(tab, NULL, sign, var->index);
575 isl_assert(tab->mat->ctx, r >= 0, return);
578 pivot(tab, r, var->index);
581 static void check_table(struct isl_tab *tab)
587 for (i = 0; i < tab->n_row; ++i) {
588 if (!var_from_row(tab, i)->is_nonneg)
590 assert(!isl_int_is_neg(tab->mat->row[i][1]));
594 /* Return the sign of the maximal value of "var".
595 * If the sign is not negative, then on return from this function,
596 * the sample value will also be non-negative.
598 * If "var" is manifestly unbounded wrt positive values, we are done.
599 * Otherwise, we pivot the variable up to a row if needed
600 * Then we continue pivoting down until either
601 * - no more down pivots can be performed
602 * - the sample value is positive
603 * - the variable is pivoted into a manifestly unbounded column
605 static int sign_of_max(struct isl_tab *tab, struct isl_tab_var *var)
609 if (max_is_manifestly_unbounded(tab, var))
612 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
613 find_pivot(tab, var, var, 1, &row, &col);
615 return isl_int_sgn(tab->mat->row[var->index][1]);
616 pivot(tab, row, col);
617 if (!var->is_row) /* manifestly unbounded */
623 /* Perform pivots until the row variable "var" has a non-negative
624 * sample value or until no more upward pivots can be performed.
625 * Return the sign of the sample value after the pivots have been
628 static int restore_row(struct isl_tab *tab, struct isl_tab_var *var)
632 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
633 find_pivot(tab, var, var, 1, &row, &col);
636 pivot(tab, row, col);
637 if (!var->is_row) /* manifestly unbounded */
640 return isl_int_sgn(tab->mat->row[var->index][1]);
643 /* Perform pivots until we are sure that the row variable "var"
644 * can attain non-negative values. After return from this
645 * function, "var" is still a row variable, but its sample
646 * value may not be non-negative, even if the function returns 1.
648 static int at_least_zero(struct isl_tab *tab, struct isl_tab_var *var)
652 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
653 find_pivot(tab, var, var, 1, &row, &col);
656 if (row == var->index) /* manifestly unbounded */
658 pivot(tab, row, col);
660 return !isl_int_is_neg(tab->mat->row[var->index][1]);
663 /* Return a negative value if "var" can attain negative values.
664 * Return a non-negative value otherwise.
666 * If "var" is manifestly unbounded wrt negative values, we are done.
667 * Otherwise, if var is in a column, we can pivot it down to a row.
668 * Then we continue pivoting down until either
669 * - the pivot would result in a manifestly unbounded column
670 * => we don't perform the pivot, but simply return -1
671 * - no more down pivots can be performed
672 * - the sample value is negative
673 * If the sample value becomes negative and the variable is supposed
674 * to be nonnegative, then we undo the last pivot.
675 * However, if the last pivot has made the pivoting variable
676 * obviously redundant, then it may have moved to another row.
677 * In that case we look for upward pivots until we reach a non-negative
680 static int sign_of_min(struct isl_tab *tab, struct isl_tab_var *var)
683 struct isl_tab_var *pivot_var;
685 if (min_is_manifestly_unbounded(tab, var))
689 row = pivot_row(tab, NULL, -1, col);
690 pivot_var = var_from_col(tab, col);
691 pivot(tab, row, col);
692 if (var->is_redundant)
694 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
695 if (var->is_nonneg) {
696 if (!pivot_var->is_redundant &&
697 pivot_var->index == row)
698 pivot(tab, row, col);
700 restore_row(tab, var);
705 if (var->is_redundant)
707 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
708 find_pivot(tab, var, var, -1, &row, &col);
709 if (row == var->index)
712 return isl_int_sgn(tab->mat->row[var->index][1]);
713 pivot_var = var_from_col(tab, col);
714 pivot(tab, row, col);
715 if (var->is_redundant)
718 if (var->is_nonneg) {
719 /* pivot back to non-negative value */
720 if (!pivot_var->is_redundant && pivot_var->index == row)
721 pivot(tab, row, col);
723 restore_row(tab, var);
728 /* Return 1 if "var" can attain values <= -1.
729 * Return 0 otherwise.
731 * The sample value of "var" is assumed to be non-negative when the
732 * the function is called and will be made non-negative again before
733 * the function returns.
735 static int min_at_most_neg_one(struct isl_tab *tab, struct isl_tab_var *var)
738 struct isl_tab_var *pivot_var;
740 if (min_is_manifestly_unbounded(tab, var))
744 row = pivot_row(tab, NULL, -1, col);
745 pivot_var = var_from_col(tab, col);
746 pivot(tab, row, col);
747 if (var->is_redundant)
749 if (isl_int_is_neg(tab->mat->row[var->index][1]) &&
750 isl_int_abs_ge(tab->mat->row[var->index][1],
751 tab->mat->row[var->index][0])) {
752 if (var->is_nonneg) {
753 if (!pivot_var->is_redundant &&
754 pivot_var->index == row)
755 pivot(tab, row, col);
757 restore_row(tab, var);
762 if (var->is_redundant)
765 find_pivot(tab, var, var, -1, &row, &col);
766 if (row == var->index)
770 pivot_var = var_from_col(tab, col);
771 pivot(tab, row, col);
772 if (var->is_redundant)
774 } while (!isl_int_is_neg(tab->mat->row[var->index][1]) ||
775 isl_int_abs_lt(tab->mat->row[var->index][1],
776 tab->mat->row[var->index][0]));
777 if (var->is_nonneg) {
778 /* pivot back to non-negative value */
779 if (!pivot_var->is_redundant && pivot_var->index == row)
780 pivot(tab, row, col);
781 restore_row(tab, var);
786 /* Return 1 if "var" can attain values >= 1.
787 * Return 0 otherwise.
789 static int at_least_one(struct isl_tab *tab, struct isl_tab_var *var)
794 if (max_is_manifestly_unbounded(tab, var))
797 r = tab->mat->row[var->index];
798 while (isl_int_lt(r[1], r[0])) {
799 find_pivot(tab, var, var, 1, &row, &col);
801 return isl_int_ge(r[1], r[0]);
802 if (row == var->index) /* manifestly unbounded */
804 pivot(tab, row, col);
809 static void swap_cols(struct isl_tab *tab, int col1, int col2)
812 t = tab->col_var[col1];
813 tab->col_var[col1] = tab->col_var[col2];
814 tab->col_var[col2] = t;
815 var_from_col(tab, col1)->index = col1;
816 var_from_col(tab, col2)->index = col2;
817 tab->mat = isl_mat_swap_cols(tab->mat, 2 + col1, 2 + col2);
820 /* Mark column with index "col" as representing a zero variable.
821 * If we may need to undo the operation the column is kept,
822 * but no longer considered.
823 * Otherwise, the column is simply removed.
825 * The column may be interchanged with some other column. If it
826 * is interchanged with a later column, return 1. Otherwise return 0.
827 * If the columns are checked in order in the calling function,
828 * then a return value of 1 means that the column with the given
829 * column number may now contain a different column that
830 * hasn't been checked yet.
832 static int kill_col(struct isl_tab *tab, int col)
834 var_from_col(tab, col)->is_zero = 1;
835 if (tab->need_undo) {
836 push(tab, isl_tab_undo_zero, var_from_col(tab, col));
837 if (col != tab->n_dead)
838 swap_cols(tab, col, tab->n_dead);
842 if (col != tab->n_col - 1)
843 swap_cols(tab, col, tab->n_col - 1);
844 var_from_col(tab, tab->n_col - 1)->index = -1;
850 /* Row variable "var" is non-negative and cannot attain any values
851 * larger than zero. This means that the coefficients of the unrestricted
852 * column variables are zero and that the coefficients of the non-negative
853 * column variables are zero or negative.
854 * Each of the non-negative variables with a negative coefficient can
855 * then also be written as the negative sum of non-negative variables
856 * and must therefore also be zero.
858 static void close_row(struct isl_tab *tab, struct isl_tab_var *var)
861 struct isl_mat *mat = tab->mat;
863 isl_assert(tab->mat->ctx, var->is_nonneg, return);
865 for (j = tab->n_dead; j < tab->n_col; ++j) {
866 if (isl_int_is_zero(mat->row[var->index][2 + j]))
868 isl_assert(tab->mat->ctx,
869 isl_int_is_neg(mat->row[var->index][2 + j]), return);
870 if (kill_col(tab, j))
873 mark_redundant(tab, var->index);
876 /* Add a constraint to the tableau and allocate a row for it.
877 * Return the index into the constraint array "con".
879 static int allocate_con(struct isl_tab *tab)
883 isl_assert(tab->mat->ctx, tab->n_row < tab->mat->n_row, return -1);
886 tab->con[r].index = tab->n_row;
887 tab->con[r].is_row = 1;
888 tab->con[r].is_nonneg = 0;
889 tab->con[r].is_zero = 0;
890 tab->con[r].is_redundant = 0;
891 tab->con[r].frozen = 0;
892 tab->row_var[tab->n_row] = ~r;
896 push(tab, isl_tab_undo_allocate, &tab->con[r]);
901 /* Add a row to the tableau. The row is given as an affine combination
902 * of the original variables and needs to be expressed in terms of the
905 * We add each term in turn.
906 * If r = n/d_r is the current sum and we need to add k x, then
907 * if x is a column variable, we increase the numerator of
908 * this column by k d_r
909 * if x = f/d_x is a row variable, then the new representation of r is
911 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
912 * --- + --- = ------------------- = -------------------
913 * d_r d_r d_r d_x/g m
915 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
917 static int add_row(struct isl_tab *tab, isl_int *line)
924 r = allocate_con(tab);
930 row = tab->mat->row[tab->con[r].index];
931 isl_int_set_si(row[0], 1);
932 isl_int_set(row[1], line[0]);
933 isl_seq_clr(row + 2, tab->n_col);
934 for (i = 0; i < tab->n_var; ++i) {
935 if (tab->var[i].is_zero)
937 if (tab->var[i].is_row) {
939 row[0], tab->mat->row[tab->var[i].index][0]);
940 isl_int_swap(a, row[0]);
941 isl_int_divexact(a, row[0], a);
943 row[0], tab->mat->row[tab->var[i].index][0]);
944 isl_int_mul(b, b, line[1 + i]);
945 isl_seq_combine(row + 1, a, row + 1,
946 b, tab->mat->row[tab->var[i].index] + 1,
949 isl_int_addmul(row[2 + tab->var[i].index],
950 line[1 + i], row[0]);
952 isl_seq_normalize(row, 2 + tab->n_col);
959 static int drop_row(struct isl_tab *tab, int row)
961 isl_assert(tab->mat->ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
962 if (row != tab->n_row - 1)
963 swap_rows(tab, row, tab->n_row - 1);
969 /* Add inequality "ineq" and check if it conflicts with the
970 * previously added constraints or if it is obviously redundant.
972 struct isl_tab *isl_tab_add_ineq(struct isl_tab *tab, isl_int *ineq)
979 r = add_row(tab, ineq);
982 tab->con[r].is_nonneg = 1;
983 push(tab, isl_tab_undo_nonneg, &tab->con[r]);
984 if (is_redundant(tab, tab->con[r].index)) {
985 mark_redundant(tab, tab->con[r].index);
989 sgn = restore_row(tab, &tab->con[r]);
991 return mark_empty(tab);
992 if (tab->con[r].is_row && is_redundant(tab, tab->con[r].index))
993 mark_redundant(tab, tab->con[r].index);
1000 /* Pivot a non-negative variable down until it reaches the value zero
1001 * and then pivot the variable into a column position.
1003 static int to_col(struct isl_tab *tab, struct isl_tab_var *var)
1011 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
1012 find_pivot(tab, var, NULL, -1, &row, &col);
1013 isl_assert(tab->mat->ctx, row != -1, return -1);
1014 pivot(tab, row, col);
1019 for (i = tab->n_dead; i < tab->n_col; ++i)
1020 if (!isl_int_is_zero(tab->mat->row[var->index][2 + i]))
1023 isl_assert(tab->mat->ctx, i < tab->n_col, return -1);
1024 pivot(tab, var->index, i);
1029 /* We assume Gaussian elimination has been performed on the equalities.
1030 * The equalities can therefore never conflict.
1031 * Adding the equalities is currently only really useful for a later call
1032 * to isl_tab_ineq_type.
1034 static struct isl_tab *add_eq(struct isl_tab *tab, isl_int *eq)
1041 r = add_row(tab, eq);
1045 r = tab->con[r].index;
1046 i = isl_seq_first_non_zero(tab->mat->row[r] + 2 + tab->n_dead,
1047 tab->n_col - tab->n_dead);
1048 isl_assert(tab->mat->ctx, i >= 0, goto error);
1060 /* Add an equality that is known to be valid for the given tableau.
1062 struct isl_tab *isl_tab_add_valid_eq(struct isl_tab *tab, isl_int *eq)
1064 struct isl_tab_var *var;
1070 r = add_row(tab, eq);
1076 if (isl_int_is_neg(tab->mat->row[r][1]))
1077 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1080 if (to_col(tab, var) < 0)
1083 kill_col(tab, var->index);
1091 struct isl_tab *isl_tab_from_basic_map(struct isl_basic_map *bmap)
1094 struct isl_tab *tab;
1098 tab = isl_tab_alloc(bmap->ctx,
1099 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
1100 isl_basic_map_total_dim(bmap));
1103 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1104 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY))
1105 return mark_empty(tab);
1106 for (i = 0; i < bmap->n_eq; ++i) {
1107 tab = add_eq(tab, bmap->eq[i]);
1111 for (i = 0; i < bmap->n_ineq; ++i) {
1112 tab = isl_tab_add_ineq(tab, bmap->ineq[i]);
1113 if (!tab || tab->empty)
1119 struct isl_tab *isl_tab_from_basic_set(struct isl_basic_set *bset)
1121 return isl_tab_from_basic_map((struct isl_basic_map *)bset);
1124 /* Construct a tableau corresponding to the recession cone of "bmap".
1126 struct isl_tab *isl_tab_from_recession_cone(struct isl_basic_map *bmap)
1130 struct isl_tab *tab;
1134 tab = isl_tab_alloc(bmap->ctx, bmap->n_eq + bmap->n_ineq,
1135 isl_basic_map_total_dim(bmap));
1138 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1141 for (i = 0; i < bmap->n_eq; ++i) {
1142 isl_int_swap(bmap->eq[i][0], cst);
1143 tab = add_eq(tab, bmap->eq[i]);
1144 isl_int_swap(bmap->eq[i][0], cst);
1148 for (i = 0; i < bmap->n_ineq; ++i) {
1150 isl_int_swap(bmap->ineq[i][0], cst);
1151 r = add_row(tab, bmap->ineq[i]);
1152 isl_int_swap(bmap->ineq[i][0], cst);
1155 tab->con[r].is_nonneg = 1;
1156 push(tab, isl_tab_undo_nonneg, &tab->con[r]);
1167 /* Assuming "tab" is the tableau of a cone, check if the cone is
1168 * bounded, i.e., if it is empty or only contains the origin.
1170 int isl_tab_cone_is_bounded(struct isl_tab *tab)
1178 if (tab->n_dead == tab->n_col)
1182 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1183 struct isl_tab_var *var;
1184 var = var_from_row(tab, i);
1185 if (!var->is_nonneg)
1187 if (sign_of_max(tab, var) != 0)
1189 close_row(tab, var);
1192 if (tab->n_dead == tab->n_col)
1194 if (i == tab->n_row)
1199 int isl_tab_sample_is_integer(struct isl_tab *tab)
1206 for (i = 0; i < tab->n_var; ++i) {
1208 if (!tab->var[i].is_row)
1210 row = tab->var[i].index;
1211 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
1212 tab->mat->row[row][0]))
1218 static struct isl_vec *extract_integer_sample(struct isl_tab *tab)
1221 struct isl_vec *vec;
1223 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1227 isl_int_set_si(vec->block.data[0], 1);
1228 for (i = 0; i < tab->n_var; ++i) {
1229 if (!tab->var[i].is_row)
1230 isl_int_set_si(vec->block.data[1 + i], 0);
1232 int row = tab->var[i].index;
1233 isl_int_divexact(vec->block.data[1 + i],
1234 tab->mat->row[row][1], tab->mat->row[row][0]);
1241 struct isl_vec *isl_tab_get_sample_value(struct isl_tab *tab)
1244 struct isl_vec *vec;
1250 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1256 isl_int_set_si(vec->block.data[0], 1);
1257 for (i = 0; i < tab->n_var; ++i) {
1259 if (!tab->var[i].is_row) {
1260 isl_int_set_si(vec->block.data[1 + i], 0);
1263 row = tab->var[i].index;
1264 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
1265 isl_int_divexact(m, tab->mat->row[row][0], m);
1266 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
1267 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
1268 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
1270 isl_seq_normalize(vec->block.data, vec->size);
1276 /* Update "bmap" based on the results of the tableau "tab".
1277 * In particular, implicit equalities are made explicit, redundant constraints
1278 * are removed and if the sample value happens to be integer, it is stored
1279 * in "bmap" (unless "bmap" already had an integer sample).
1281 * The tableau is assumed to have been created from "bmap" using
1282 * isl_tab_from_basic_map.
1284 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
1285 struct isl_tab *tab)
1297 bmap = isl_basic_map_set_to_empty(bmap);
1299 for (i = bmap->n_ineq - 1; i >= 0; --i) {
1300 if (isl_tab_is_equality(tab, n_eq + i))
1301 isl_basic_map_inequality_to_equality(bmap, i);
1302 else if (isl_tab_is_redundant(tab, n_eq + i))
1303 isl_basic_map_drop_inequality(bmap, i);
1305 if (!tab->rational &&
1306 !bmap->sample && isl_tab_sample_is_integer(tab))
1307 bmap->sample = extract_integer_sample(tab);
1311 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
1312 struct isl_tab *tab)
1314 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
1315 (struct isl_basic_map *)bset, tab);
1318 /* Given a non-negative variable "var", add a new non-negative variable
1319 * that is the opposite of "var", ensuring that var can only attain the
1321 * If var = n/d is a row variable, then the new variable = -n/d.
1322 * If var is a column variables, then the new variable = -var.
1323 * If the new variable cannot attain non-negative values, then
1324 * the resulting tableau is empty.
1325 * Otherwise, we know the value will be zero and we close the row.
1327 static struct isl_tab *cut_to_hyperplane(struct isl_tab *tab,
1328 struct isl_tab_var *var)
1334 if (extend_cons(tab, 1) < 0)
1338 tab->con[r].index = tab->n_row;
1339 tab->con[r].is_row = 1;
1340 tab->con[r].is_nonneg = 0;
1341 tab->con[r].is_zero = 0;
1342 tab->con[r].is_redundant = 0;
1343 tab->con[r].frozen = 0;
1344 tab->row_var[tab->n_row] = ~r;
1345 row = tab->mat->row[tab->n_row];
1348 isl_int_set(row[0], tab->mat->row[var->index][0]);
1349 isl_seq_neg(row + 1,
1350 tab->mat->row[var->index] + 1, 1 + tab->n_col);
1352 isl_int_set_si(row[0], 1);
1353 isl_seq_clr(row + 1, 1 + tab->n_col);
1354 isl_int_set_si(row[2 + var->index], -1);
1359 push(tab, isl_tab_undo_allocate, &tab->con[r]);
1361 sgn = sign_of_max(tab, &tab->con[r]);
1363 return mark_empty(tab);
1364 tab->con[r].is_nonneg = 1;
1365 push(tab, isl_tab_undo_nonneg, &tab->con[r]);
1367 close_row(tab, &tab->con[r]);
1375 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
1376 * relax the inequality by one. That is, the inequality r >= 0 is replaced
1377 * by r' = r + 1 >= 0.
1378 * If r is a row variable, we simply increase the constant term by one
1379 * (taking into account the denominator).
1380 * If r is a column variable, then we need to modify each row that
1381 * refers to r = r' - 1 by substituting this equality, effectively
1382 * subtracting the coefficient of the column from the constant.
1384 struct isl_tab *isl_tab_relax(struct isl_tab *tab, int con)
1386 struct isl_tab_var *var;
1390 var = &tab->con[con];
1392 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
1393 to_row(tab, var, 1);
1396 isl_int_add(tab->mat->row[var->index][1],
1397 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1401 for (i = 0; i < tab->n_row; ++i) {
1402 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1404 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
1405 tab->mat->row[i][2 + var->index]);
1410 push(tab, isl_tab_undo_relax, var);
1415 struct isl_tab *isl_tab_select_facet(struct isl_tab *tab, int con)
1420 return cut_to_hyperplane(tab, &tab->con[con]);
1423 static int may_be_equality(struct isl_tab *tab, int row)
1425 return (tab->rational ? isl_int_is_zero(tab->mat->row[row][1])
1426 : isl_int_lt(tab->mat->row[row][1],
1427 tab->mat->row[row][0])) &&
1428 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1429 tab->n_col - tab->n_dead) != -1;
1432 /* Check for (near) equalities among the constraints.
1433 * A constraint is an equality if it is non-negative and if
1434 * its maximal value is either
1435 * - zero (in case of rational tableaus), or
1436 * - strictly less than 1 (in case of integer tableaus)
1438 * We first mark all non-redundant and non-dead variables that
1439 * are not frozen and not obviously not an equality.
1440 * Then we iterate over all marked variables if they can attain
1441 * any values larger than zero or at least one.
1442 * If the maximal value is zero, we mark any column variables
1443 * that appear in the row as being zero and mark the row as being redundant.
1444 * Otherwise, if the maximal value is strictly less than one (and the
1445 * tableau is integer), then we restrict the value to being zero
1446 * by adding an opposite non-negative variable.
1448 struct isl_tab *isl_tab_detect_equalities(struct isl_tab *tab)
1457 if (tab->n_dead == tab->n_col)
1461 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1462 struct isl_tab_var *var = var_from_row(tab, i);
1463 var->marked = !var->frozen && var->is_nonneg &&
1464 may_be_equality(tab, i);
1468 for (i = tab->n_dead; i < tab->n_col; ++i) {
1469 struct isl_tab_var *var = var_from_col(tab, i);
1470 var->marked = !var->frozen && var->is_nonneg;
1475 struct isl_tab_var *var;
1476 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1477 var = var_from_row(tab, i);
1481 if (i == tab->n_row) {
1482 for (i = tab->n_dead; i < tab->n_col; ++i) {
1483 var = var_from_col(tab, i);
1487 if (i == tab->n_col)
1492 if (sign_of_max(tab, var) == 0)
1493 close_row(tab, var);
1494 else if (!tab->rational && !at_least_one(tab, var)) {
1495 tab = cut_to_hyperplane(tab, var);
1496 return isl_tab_detect_equalities(tab);
1498 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1499 var = var_from_row(tab, i);
1502 if (may_be_equality(tab, i))
1512 /* Check for (near) redundant constraints.
1513 * A constraint is redundant if it is non-negative and if
1514 * its minimal value (temporarily ignoring the non-negativity) is either
1515 * - zero (in case of rational tableaus), or
1516 * - strictly larger than -1 (in case of integer tableaus)
1518 * We first mark all non-redundant and non-dead variables that
1519 * are not frozen and not obviously negatively unbounded.
1520 * Then we iterate over all marked variables if they can attain
1521 * any values smaller than zero or at most negative one.
1522 * If not, we mark the row as being redundant (assuming it hasn't
1523 * been detected as being obviously redundant in the mean time).
1525 struct isl_tab *isl_tab_detect_redundant(struct isl_tab *tab)
1534 if (tab->n_redundant == tab->n_row)
1538 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1539 struct isl_tab_var *var = var_from_row(tab, i);
1540 var->marked = !var->frozen && var->is_nonneg;
1544 for (i = tab->n_dead; i < tab->n_col; ++i) {
1545 struct isl_tab_var *var = var_from_col(tab, i);
1546 var->marked = !var->frozen && var->is_nonneg &&
1547 !min_is_manifestly_unbounded(tab, var);
1552 struct isl_tab_var *var;
1553 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1554 var = var_from_row(tab, i);
1558 if (i == tab->n_row) {
1559 for (i = tab->n_dead; i < tab->n_col; ++i) {
1560 var = var_from_col(tab, i);
1564 if (i == tab->n_col)
1569 if ((tab->rational ? (sign_of_min(tab, var) >= 0)
1570 : !min_at_most_neg_one(tab, var)) &&
1572 mark_redundant(tab, var->index);
1573 for (i = tab->n_dead; i < tab->n_col; ++i) {
1574 var = var_from_col(tab, i);
1577 if (!min_is_manifestly_unbounded(tab, var))
1587 int isl_tab_is_equality(struct isl_tab *tab, int con)
1593 if (tab->con[con].is_zero)
1595 if (tab->con[con].is_redundant)
1597 if (!tab->con[con].is_row)
1598 return tab->con[con].index < tab->n_dead;
1600 row = tab->con[con].index;
1602 return isl_int_is_zero(tab->mat->row[row][1]) &&
1603 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1604 tab->n_col - tab->n_dead) == -1;
1607 /* Return the minimial value of the affine expression "f" with denominator
1608 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
1609 * the expression cannot attain arbitrarily small values.
1610 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
1611 * The return value reflects the nature of the result (empty, unbounded,
1612 * minmimal value returned in *opt).
1614 enum isl_lp_result isl_tab_min(struct isl_tab *tab,
1615 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom,
1619 enum isl_lp_result res = isl_lp_ok;
1620 struct isl_tab_var *var;
1621 struct isl_tab_undo *snap;
1624 return isl_lp_empty;
1626 snap = isl_tab_snap(tab);
1627 r = add_row(tab, f);
1629 return isl_lp_error;
1631 isl_int_mul(tab->mat->row[var->index][0],
1632 tab->mat->row[var->index][0], denom);
1635 find_pivot(tab, var, var, -1, &row, &col);
1636 if (row == var->index) {
1637 res = isl_lp_unbounded;
1642 pivot(tab, row, col);
1644 if (isl_tab_rollback(tab, snap) < 0)
1645 return isl_lp_error;
1646 if (ISL_FL_ISSET(flags, ISL_TAB_SAVE_DUAL)) {
1649 isl_vec_free(tab->dual);
1650 tab->dual = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_con);
1652 return isl_lp_error;
1653 isl_int_set(tab->dual->el[0], tab->mat->row[var->index][0]);
1654 for (i = 0; i < tab->n_con; ++i) {
1655 if (tab->con[i].is_row)
1656 isl_int_set_si(tab->dual->el[1 + i], 0);
1658 int pos = 2 + tab->con[i].index;
1659 isl_int_set(tab->dual->el[1 + i],
1660 tab->mat->row[var->index][pos]);
1664 if (res == isl_lp_ok) {
1666 isl_int_set(*opt, tab->mat->row[var->index][1]);
1667 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
1669 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
1670 tab->mat->row[var->index][0]);
1675 int isl_tab_is_redundant(struct isl_tab *tab, int con)
1682 if (tab->con[con].is_zero)
1684 if (tab->con[con].is_redundant)
1686 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
1689 /* Take a snapshot of the tableau that can be restored by s call to
1692 struct isl_tab_undo *isl_tab_snap(struct isl_tab *tab)
1700 /* Undo the operation performed by isl_tab_relax.
1702 static void unrelax(struct isl_tab *tab, struct isl_tab_var *var)
1704 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
1705 to_row(tab, var, 1);
1708 isl_int_sub(tab->mat->row[var->index][1],
1709 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1713 for (i = 0; i < tab->n_row; ++i) {
1714 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1716 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
1717 tab->mat->row[i][2 + var->index]);
1723 static void perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo)
1725 struct isl_tab_var *var = var_from_index(tab, undo->var_index);
1726 switch(undo->type) {
1727 case isl_tab_undo_empty:
1730 case isl_tab_undo_nonneg:
1733 case isl_tab_undo_redundant:
1734 var->is_redundant = 0;
1737 case isl_tab_undo_zero:
1741 case isl_tab_undo_allocate:
1743 if (!max_is_manifestly_unbounded(tab, var))
1744 to_row(tab, var, 1);
1745 else if (!min_is_manifestly_unbounded(tab, var))
1746 to_row(tab, var, -1);
1748 to_row(tab, var, 0);
1750 drop_row(tab, var->index);
1752 case isl_tab_undo_relax:
1758 /* Return the tableau to the state it was in when the snapshot "snap"
1761 int isl_tab_rollback(struct isl_tab *tab, struct isl_tab_undo *snap)
1763 struct isl_tab_undo *undo, *next;
1769 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
1773 perform_undo(tab, undo);
1783 /* The given row "row" represents an inequality violated by all
1784 * points in the tableau. Check for some special cases of such
1785 * separating constraints.
1786 * In particular, if the row has been reduced to the constant -1,
1787 * then we know the inequality is adjacent (but opposite) to
1788 * an equality in the tableau.
1789 * If the row has been reduced to r = -1 -r', with r' an inequality
1790 * of the tableau, then the inequality is adjacent (but opposite)
1791 * to the inequality r'.
1793 static enum isl_ineq_type separation_type(struct isl_tab *tab, unsigned row)
1798 return isl_ineq_separate;
1800 if (!isl_int_is_one(tab->mat->row[row][0]))
1801 return isl_ineq_separate;
1802 if (!isl_int_is_negone(tab->mat->row[row][1]))
1803 return isl_ineq_separate;
1805 pos = isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1806 tab->n_col - tab->n_dead);
1808 return isl_ineq_adj_eq;
1810 if (!isl_int_is_negone(tab->mat->row[row][2 + tab->n_dead + pos]))
1811 return isl_ineq_separate;
1813 pos = isl_seq_first_non_zero(
1814 tab->mat->row[row] + 2 + tab->n_dead + pos + 1,
1815 tab->n_col - tab->n_dead - pos - 1);
1817 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
1820 /* Check the effect of inequality "ineq" on the tableau "tab".
1822 * isl_ineq_redundant: satisfied by all points in the tableau
1823 * isl_ineq_separate: satisfied by no point in the tableau
1824 * isl_ineq_cut: satisfied by some by not all points
1825 * isl_ineq_adj_eq: adjacent to an equality
1826 * isl_ineq_adj_ineq: adjacent to an inequality.
1828 enum isl_ineq_type isl_tab_ineq_type(struct isl_tab *tab, isl_int *ineq)
1830 enum isl_ineq_type type = isl_ineq_error;
1831 struct isl_tab_undo *snap = NULL;
1836 return isl_ineq_error;
1838 if (extend_cons(tab, 1) < 0)
1839 return isl_ineq_error;
1841 snap = isl_tab_snap(tab);
1843 con = add_row(tab, ineq);
1847 row = tab->con[con].index;
1848 if (is_redundant(tab, row))
1849 type = isl_ineq_redundant;
1850 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
1852 isl_int_abs_ge(tab->mat->row[row][1],
1853 tab->mat->row[row][0]))) {
1854 if (at_least_zero(tab, &tab->con[con]))
1855 type = isl_ineq_cut;
1857 type = separation_type(tab, row);
1858 } else if (tab->rational ? (sign_of_min(tab, &tab->con[con]) < 0)
1859 : min_at_most_neg_one(tab, &tab->con[con]))
1860 type = isl_ineq_cut;
1862 type = isl_ineq_redundant;
1864 if (isl_tab_rollback(tab, snap))
1865 return isl_ineq_error;
1868 isl_tab_rollback(tab, snap);
1869 return isl_ineq_error;
1872 void isl_tab_dump(struct isl_tab *tab, FILE *out, int indent)
1878 fprintf(out, "%*snull tab\n", indent, "");
1881 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
1882 tab->n_redundant, tab->n_dead);
1884 fprintf(out, ", rational");
1886 fprintf(out, ", empty");
1888 fprintf(out, "%*s[", indent, "");
1889 for (i = 0; i < tab->n_var; ++i) {
1892 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
1894 tab->var[i].is_zero ? " [=0]" :
1895 tab->var[i].is_redundant ? " [R]" : "");
1897 fprintf(out, "]\n");
1898 fprintf(out, "%*s[", indent, "");
1899 for (i = 0; i < tab->n_con; ++i) {
1902 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
1904 tab->con[i].is_zero ? " [=0]" :
1905 tab->con[i].is_redundant ? " [R]" : "");
1907 fprintf(out, "]\n");
1908 fprintf(out, "%*s[", indent, "");
1909 for (i = 0; i < tab->n_row; ++i) {
1912 fprintf(out, "r%d: %d%s", i, tab->row_var[i],
1913 var_from_row(tab, i)->is_nonneg ? " [>=0]" : "");
1915 fprintf(out, "]\n");
1916 fprintf(out, "%*s[", indent, "");
1917 for (i = 0; i < tab->n_col; ++i) {
1920 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
1921 var_from_col(tab, i)->is_nonneg ? " [>=0]" : "");
1923 fprintf(out, "]\n");
1924 r = tab->mat->n_row;
1925 tab->mat->n_row = tab->n_row;
1926 c = tab->mat->n_col;
1927 tab->mat->n_col = 2 + tab->n_col;
1928 isl_mat_dump(tab->mat, out, indent);
1929 tab->mat->n_row = r;
1930 tab->mat->n_col = c;