1 #include "isl_map_private.h"
5 * The implementation of tableaus in this file was inspired by Section 8
6 * of David Detlefs, Greg Nelson and James B. Saxe, "Simplify: a theorem
7 * prover for program checking".
10 struct isl_tab *isl_tab_alloc(struct isl_ctx *ctx,
11 unsigned n_row, unsigned n_var)
16 tab = isl_calloc_type(ctx, struct isl_tab);
19 tab->mat = isl_mat_alloc(ctx, n_row, 2 + n_var);
22 tab->var = isl_alloc_array(ctx, struct isl_tab_var, n_var);
25 tab->con = isl_alloc_array(ctx, struct isl_tab_var, n_row);
28 tab->col_var = isl_alloc_array(ctx, int, n_var);
31 tab->row_var = isl_alloc_array(ctx, int, n_row);
34 for (i = 0; i < n_var; ++i) {
35 tab->var[i].index = i;
36 tab->var[i].is_row = 0;
37 tab->var[i].is_nonneg = 0;
38 tab->var[i].is_zero = 0;
39 tab->var[i].is_redundant = 0;
40 tab->var[i].frozen = 0;
55 tab->bottom.type = isl_tab_undo_bottom;
56 tab->bottom.next = NULL;
57 tab->top = &tab->bottom;
64 static int extend_cons(struct isl_tab *tab, unsigned n_new)
66 if (tab->max_con < tab->n_con + n_new) {
67 struct isl_tab_var *con;
69 con = isl_realloc_array(tab->mat->ctx, tab->con,
70 struct isl_tab_var, tab->max_con + n_new);
74 tab->max_con += n_new;
76 if (tab->mat->n_row < tab->n_row + n_new) {
79 tab->mat = isl_mat_extend(tab->mat,
80 tab->n_row + n_new, tab->n_col);
83 row_var = isl_realloc_array(tab->mat->ctx, tab->row_var,
84 int, tab->mat->n_row);
87 tab->row_var = row_var;
92 struct isl_tab *isl_tab_extend(struct isl_tab *tab, unsigned n_new)
94 if (extend_cons(tab, n_new) >= 0)
101 static void free_undo(struct isl_tab *tab)
103 struct isl_tab_undo *undo, *next;
105 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
112 void isl_tab_free(struct isl_tab *tab)
117 isl_mat_free(tab->mat);
118 isl_vec_free(tab->dual);
126 static struct isl_tab_var *var_from_index(struct isl_tab *tab, int i)
131 return &tab->con[~i];
134 static struct isl_tab_var *var_from_row(struct isl_tab *tab, int i)
136 return var_from_index(tab, tab->row_var[i]);
139 static struct isl_tab_var *var_from_col(struct isl_tab *tab, int i)
141 return var_from_index(tab, tab->col_var[i]);
144 /* Check if there are any upper bounds on column variable "var",
145 * i.e., non-negative rows where var appears with a negative coefficient.
146 * Return 1 if there are no such bounds.
148 static int max_is_manifestly_unbounded(struct isl_tab *tab,
149 struct isl_tab_var *var)
155 for (i = tab->n_redundant; i < tab->n_row; ++i) {
156 if (!isl_int_is_neg(tab->mat->row[i][2 + var->index]))
158 if (var_from_row(tab, i)->is_nonneg)
164 /* Check if there are any lower bounds on column variable "var",
165 * i.e., non-negative rows where var appears with a positive coefficient.
166 * Return 1 if there are no such bounds.
168 static int min_is_manifestly_unbounded(struct isl_tab *tab,
169 struct isl_tab_var *var)
175 for (i = tab->n_redundant; i < tab->n_row; ++i) {
176 if (!isl_int_is_pos(tab->mat->row[i][2 + var->index]))
178 if (var_from_row(tab, i)->is_nonneg)
184 /* Given the index of a column "c", return the index of a row
185 * that can be used to pivot the column in, with either an increase
186 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
187 * If "var" is not NULL, then the row returned will be different from
188 * the one associated with "var".
190 * Each row in the tableau is of the form
192 * x_r = a_r0 + \sum_i a_ri x_i
194 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
195 * impose any limit on the increase or decrease in the value of x_c
196 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
197 * for the row with the smallest (most stringent) such bound.
198 * Note that the common denominator of each row drops out of the fraction.
199 * To check if row j has a smaller bound than row r, i.e.,
200 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
201 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
202 * where -sign(a_jc) is equal to "sgn".
204 static int pivot_row(struct isl_tab *tab,
205 struct isl_tab_var *var, int sgn, int c)
212 for (j = tab->n_redundant; j < tab->n_row; ++j) {
213 if (var && j == var->index)
215 if (!var_from_row(tab, j)->is_nonneg)
217 if (sgn * isl_int_sgn(tab->mat->row[j][2 + c]) >= 0)
223 isl_int_mul(t, tab->mat->row[r][1], tab->mat->row[j][2 + c]);
224 isl_int_submul(t, tab->mat->row[j][1], tab->mat->row[r][2 + c]);
225 tsgn = sgn * isl_int_sgn(t);
226 if (tsgn < 0 || (tsgn == 0 &&
227 tab->row_var[j] < tab->row_var[r]))
234 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
235 * (sgn < 0) the value of row variable var.
236 * If not NULL, then skip_var is a row variable that should be ignored
237 * while looking for a pivot row. It is usually equal to var.
239 * As the given row in the tableau is of the form
241 * x_r = a_r0 + \sum_i a_ri x_i
243 * we need to find a column such that the sign of a_ri is equal to "sgn"
244 * (such that an increase in x_i will have the desired effect) or a
245 * column with a variable that may attain negative values.
246 * If a_ri is positive, then we need to move x_i in the same direction
247 * to obtain the desired effect. Otherwise, x_i has to move in the
248 * opposite direction.
250 static void find_pivot(struct isl_tab *tab,
251 struct isl_tab_var *var, struct isl_tab_var *skip_var,
252 int sgn, int *row, int *col)
259 isl_assert(tab->mat->ctx, var->is_row, return);
260 tr = tab->mat->row[var->index];
263 for (j = tab->n_dead; j < tab->n_col; ++j) {
264 if (isl_int_is_zero(tr[2 + j]))
266 if (isl_int_sgn(tr[2 + j]) != sgn &&
267 var_from_col(tab, j)->is_nonneg)
269 if (c < 0 || tab->col_var[j] < tab->col_var[c])
275 sgn *= isl_int_sgn(tr[2 + c]);
276 r = pivot_row(tab, skip_var, sgn, c);
277 *row = r < 0 ? var->index : r;
281 /* Return 1 if row "row" represents an obviously redundant inequality.
283 * - it represents an inequality or a variable
284 * - that is the sum of a non-negative sample value and a positive
285 * combination of zero or more non-negative variables.
287 static int is_redundant(struct isl_tab *tab, int row)
291 if (tab->row_var[row] < 0 && !var_from_row(tab, row)->is_nonneg)
294 if (isl_int_is_neg(tab->mat->row[row][1]))
297 for (i = tab->n_dead; i < tab->n_col; ++i) {
298 if (isl_int_is_zero(tab->mat->row[row][2 + i]))
300 if (isl_int_is_neg(tab->mat->row[row][2 + i]))
302 if (!var_from_col(tab, i)->is_nonneg)
308 static void swap_rows(struct isl_tab *tab, int row1, int row2)
311 t = tab->row_var[row1];
312 tab->row_var[row1] = tab->row_var[row2];
313 tab->row_var[row2] = t;
314 var_from_row(tab, row1)->index = row1;
315 var_from_row(tab, row2)->index = row2;
316 tab->mat = isl_mat_swap_rows(tab->mat, row1, row2);
319 static void push(struct isl_tab *tab,
320 enum isl_tab_undo_type type, struct isl_tab_var *var)
322 struct isl_tab_undo *undo;
327 undo = isl_alloc_type(tab->mat->ctx, struct isl_tab_undo);
335 undo->next = tab->top;
339 /* Mark row with index "row" as being redundant.
340 * If we may need to undo the operation or if the row represents
341 * a variable of the original problem, the row is kept,
342 * but no longer considered when looking for a pivot row.
343 * Otherwise, the row is simply removed.
345 * The row may be interchanged with some other row. If it
346 * is interchanged with a later row, return 1. Otherwise return 0.
347 * If the rows are checked in order in the calling function,
348 * then a return value of 1 means that the row with the given
349 * row number may now contain a different row that hasn't been checked yet.
351 static int mark_redundant(struct isl_tab *tab, int row)
353 struct isl_tab_var *var = var_from_row(tab, row);
354 var->is_redundant = 1;
355 isl_assert(tab->mat->ctx, row >= tab->n_redundant, return);
356 if (tab->need_undo || tab->row_var[row] >= 0) {
357 if (tab->row_var[row] >= 0) {
359 push(tab, isl_tab_undo_nonneg, var);
361 if (row != tab->n_redundant)
362 swap_rows(tab, row, tab->n_redundant);
363 push(tab, isl_tab_undo_redundant, var);
367 if (row != tab->n_row - 1)
368 swap_rows(tab, row, tab->n_row - 1);
369 var_from_row(tab, tab->n_row - 1)->index = -1;
375 static void mark_empty(struct isl_tab *tab)
377 if (!tab->empty && tab->need_undo)
378 push(tab, isl_tab_undo_empty, NULL);
382 /* Given a row number "row" and a column number "col", pivot the tableau
383 * such that the associated variables are interchanged.
384 * The given row in the tableau expresses
386 * x_r = a_r0 + \sum_i a_ri x_i
390 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
392 * Substituting this equality into the other rows
394 * x_j = a_j0 + \sum_i a_ji x_i
396 * with a_jc \ne 0, we obtain
398 * 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
405 * where i is any other column and j is any other row,
406 * is therefore transformed into
408 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
409 * 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)
411 * The transformation is performed along the following steps
416 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
419 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
420 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
422 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
423 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
425 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
426 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
428 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
429 * 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)
432 static void pivot(struct isl_tab *tab, int row, int col)
437 struct isl_mat *mat = tab->mat;
438 struct isl_tab_var *var;
440 isl_int_swap(mat->row[row][0], mat->row[row][2 + col]);
441 sgn = isl_int_sgn(mat->row[row][0]);
443 isl_int_neg(mat->row[row][0], mat->row[row][0]);
444 isl_int_neg(mat->row[row][2 + col], mat->row[row][2 + col]);
446 for (j = 0; j < 1 + tab->n_col; ++j) {
449 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
451 if (!isl_int_is_one(mat->row[row][0]))
452 isl_seq_normalize(mat->row[row], 2 + tab->n_col);
453 for (i = 0; i < tab->n_row; ++i) {
456 if (isl_int_is_zero(mat->row[i][2 + col]))
458 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
459 for (j = 0; j < 1 + tab->n_col; ++j) {
462 isl_int_mul(mat->row[i][1 + j],
463 mat->row[i][1 + j], mat->row[row][0]);
464 isl_int_addmul(mat->row[i][1 + j],
465 mat->row[i][2 + col], mat->row[row][1 + j]);
467 isl_int_mul(mat->row[i][2 + col],
468 mat->row[i][2 + col], mat->row[row][2 + col]);
469 if (!isl_int_is_one(mat->row[row][0]))
470 isl_seq_normalize(mat->row[i], 2 + tab->n_col);
472 t = tab->row_var[row];
473 tab->row_var[row] = tab->col_var[col];
474 tab->col_var[col] = t;
475 var = var_from_row(tab, row);
478 var = var_from_col(tab, col);
483 for (i = tab->n_redundant; i < tab->n_row; ++i) {
484 if (isl_int_is_zero(mat->row[i][2 + col]))
486 if (!var_from_row(tab, i)->frozen &&
487 is_redundant(tab, i))
488 if (mark_redundant(tab, i))
493 /* If "var" represents a column variable, then pivot is up (sgn > 0)
494 * or down (sgn < 0) to a row. The variable is assumed not to be
495 * unbounded in the specified direction.
497 static void to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign)
504 r = pivot_row(tab, NULL, sign, var->index);
505 isl_assert(tab->mat->ctx, r >= 0, return);
506 pivot(tab, r, var->index);
509 static void check_table(struct isl_tab *tab)
515 for (i = 0; i < tab->n_row; ++i) {
516 if (!var_from_row(tab, i)->is_nonneg)
518 assert(!isl_int_is_neg(tab->mat->row[i][1]));
522 /* Return the sign of the maximal value of "var".
523 * If the sign is not negative, then on return from this function,
524 * the sample value will also be non-negative.
526 * If "var" is manifestly unbounded wrt positive values, we are done.
527 * Otherwise, we pivot the variable up to a row if needed
528 * Then we continue pivoting down until either
529 * - no more down pivots can be performed
530 * - the sample value is positive
531 * - the variable is pivoted into a manifestly unbounded column
533 static int sign_of_max(struct isl_tab *tab, struct isl_tab_var *var)
537 if (max_is_manifestly_unbounded(tab, var))
540 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
541 find_pivot(tab, var, var, 1, &row, &col);
543 return isl_int_sgn(tab->mat->row[var->index][1]);
544 pivot(tab, row, col);
545 if (!var->is_row) /* manifestly unbounded */
551 /* Perform pivots until the row variable "var" has a non-negative
552 * sample value or until no more upward pivots can be performed.
553 * Return the sign of the sample value after the pivots have been
556 static int restore_row(struct isl_tab *tab, struct isl_tab_var *var)
560 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
561 find_pivot(tab, var, var, 1, &row, &col);
564 pivot(tab, row, col);
565 if (!var->is_row) /* manifestly unbounded */
568 return isl_int_sgn(tab->mat->row[var->index][1]);
571 /* Perform pivots until we are sure that the row variable "var"
572 * can attain non-negative values. After return from this
573 * function, "var" is still a row variable, but its sample
574 * value may not be non-negative, even if the function returns 1.
576 static int at_least_zero(struct isl_tab *tab, struct isl_tab_var *var)
580 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
581 find_pivot(tab, var, var, 1, &row, &col);
584 if (row == var->index) /* manifestly unbounded */
586 pivot(tab, row, col);
588 return !isl_int_is_neg(tab->mat->row[var->index][1]);
591 /* Return a negative value if "var" can attain negative values.
592 * Return a non-negative value otherwise.
594 * If "var" is manifestly unbounded wrt negative values, we are done.
595 * Otherwise, if var is in a column, we can pivot it down to a row.
596 * Then we continue pivoting down until either
597 * - the pivot would result in a manifestly unbounded column
598 * => we don't perform the pivot, but simply return -1
599 * - no more down pivots can be performed
600 * - the sample value is negative
601 * If the sample value becomes negative and the variable is supposed
602 * to be nonnegative, then we undo the last pivot.
603 * However, if the last pivot has made the pivoting variable
604 * obviously redundant, then it may have moved to another row.
605 * In that case we look for upward pivots until we reach a non-negative
608 static int sign_of_min(struct isl_tab *tab, struct isl_tab_var *var)
611 struct isl_tab_var *pivot_var;
613 if (min_is_manifestly_unbounded(tab, var))
617 row = pivot_row(tab, NULL, -1, col);
618 pivot_var = var_from_col(tab, col);
619 pivot(tab, row, col);
620 if (var->is_redundant)
622 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
623 if (var->is_nonneg) {
624 if (!pivot_var->is_redundant &&
625 pivot_var->index == row)
626 pivot(tab, row, col);
628 restore_row(tab, var);
633 if (var->is_redundant)
635 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
636 find_pivot(tab, var, var, -1, &row, &col);
637 if (row == var->index)
640 return isl_int_sgn(tab->mat->row[var->index][1]);
641 pivot_var = var_from_col(tab, col);
642 pivot(tab, row, col);
643 if (var->is_redundant)
646 if (var->is_nonneg) {
647 /* pivot back to non-negative value */
648 if (!pivot_var->is_redundant && pivot_var->index == row)
649 pivot(tab, row, col);
651 restore_row(tab, var);
656 /* Return 1 if "var" can attain values <= -1.
657 * Return 0 otherwise.
659 * The sample value of "var" is assumed to be non-negative when the
660 * the function is called and will be made non-negative again before
661 * the function returns.
663 static int min_at_most_neg_one(struct isl_tab *tab, struct isl_tab_var *var)
666 struct isl_tab_var *pivot_var;
668 if (min_is_manifestly_unbounded(tab, var))
672 row = pivot_row(tab, NULL, -1, col);
673 pivot_var = var_from_col(tab, col);
674 pivot(tab, row, col);
675 if (var->is_redundant)
677 if (isl_int_is_neg(tab->mat->row[var->index][1]) &&
678 isl_int_abs_ge(tab->mat->row[var->index][1],
679 tab->mat->row[var->index][0])) {
680 if (var->is_nonneg) {
681 if (!pivot_var->is_redundant &&
682 pivot_var->index == row)
683 pivot(tab, row, col);
685 restore_row(tab, var);
690 if (var->is_redundant)
693 find_pivot(tab, var, var, -1, &row, &col);
694 if (row == var->index)
698 pivot_var = var_from_col(tab, col);
699 pivot(tab, row, col);
700 if (var->is_redundant)
702 } while (!isl_int_is_neg(tab->mat->row[var->index][1]) ||
703 isl_int_abs_lt(tab->mat->row[var->index][1],
704 tab->mat->row[var->index][0]));
705 if (var->is_nonneg) {
706 /* pivot back to non-negative value */
707 if (!pivot_var->is_redundant && pivot_var->index == row)
708 pivot(tab, row, col);
709 restore_row(tab, var);
714 /* Return 1 if "var" can attain values >= 1.
715 * Return 0 otherwise.
717 static int at_least_one(struct isl_tab *tab, struct isl_tab_var *var)
722 if (max_is_manifestly_unbounded(tab, var))
725 r = tab->mat->row[var->index];
726 while (isl_int_lt(r[1], r[0])) {
727 find_pivot(tab, var, var, 1, &row, &col);
729 return isl_int_ge(r[1], r[0]);
730 if (row == var->index) /* manifestly unbounded */
732 pivot(tab, row, col);
737 static void swap_cols(struct isl_tab *tab, int col1, int col2)
740 t = tab->col_var[col1];
741 tab->col_var[col1] = tab->col_var[col2];
742 tab->col_var[col2] = t;
743 var_from_col(tab, col1)->index = col1;
744 var_from_col(tab, col2)->index = col2;
745 tab->mat = isl_mat_swap_cols(tab->mat, 2 + col1, 2 + col2);
748 /* Mark column with index "col" as representing a zero variable.
749 * If we may need to undo the operation the column is kept,
750 * but no longer considered.
751 * Otherwise, the column is simply removed.
753 * The column may be interchanged with some other column. If it
754 * is interchanged with a later column, return 1. Otherwise return 0.
755 * If the columns are checked in order in the calling function,
756 * then a return value of 1 means that the column with the given
757 * column number may now contain a different column that
758 * hasn't been checked yet.
760 static int kill_col(struct isl_tab *tab, int col)
762 var_from_col(tab, col)->is_zero = 1;
763 if (tab->need_undo) {
764 push(tab, isl_tab_undo_zero, var_from_col(tab, col));
765 if (col != tab->n_dead)
766 swap_cols(tab, col, tab->n_dead);
770 if (col != tab->n_col - 1)
771 swap_cols(tab, col, tab->n_col - 1);
772 var_from_col(tab, tab->n_col - 1)->index = -1;
778 /* Row variable "var" is non-negative and cannot attain any values
779 * larger than zero. This means that the coefficients of the unrestricted
780 * column variables are zero and that the coefficients of the non-negative
781 * column variables are zero or negative.
782 * Each of the non-negative variables with a negative coefficient can
783 * then also be written as the negative sum of non-negative variables
784 * and must therefore also be zero.
786 static void close_row(struct isl_tab *tab, struct isl_tab_var *var)
789 struct isl_mat *mat = tab->mat;
791 isl_assert(tab->mat->ctx, var->is_nonneg, return);
793 for (j = tab->n_dead; j < tab->n_col; ++j) {
794 if (isl_int_is_zero(mat->row[var->index][2 + j]))
796 isl_assert(tab->mat->ctx,
797 isl_int_is_neg(mat->row[var->index][2 + j]), return);
798 if (kill_col(tab, j))
801 mark_redundant(tab, var->index);
804 /* Add a constraint to the tableau and allocate a row for it.
805 * Return the index into the constraint array "con".
807 static int allocate_con(struct isl_tab *tab)
811 isl_assert(tab->mat->ctx, tab->n_row < tab->mat->n_row, return -1);
814 tab->con[r].index = tab->n_row;
815 tab->con[r].is_row = 1;
816 tab->con[r].is_nonneg = 0;
817 tab->con[r].is_zero = 0;
818 tab->con[r].is_redundant = 0;
819 tab->con[r].frozen = 0;
820 tab->row_var[tab->n_row] = ~r;
824 push(tab, isl_tab_undo_allocate, &tab->con[r]);
829 /* Add a row to the tableau. The row is given as an affine combination
830 * of the original variables and needs to be expressed in terms of the
833 * We add each term in turn.
834 * If r = n/d_r is the current sum and we need to add k x, then
835 * if x is a column variable, we increase the numerator of
836 * this column by k d_r
837 * if x = f/d_x is a row variable, then the new representation of r is
839 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
840 * --- + --- = ------------------- = -------------------
841 * d_r d_r d_r d_x/g m
843 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
845 static int add_row(struct isl_tab *tab, isl_int *line)
852 r = allocate_con(tab);
858 row = tab->mat->row[tab->con[r].index];
859 isl_int_set_si(row[0], 1);
860 isl_int_set(row[1], line[0]);
861 isl_seq_clr(row + 2, tab->n_col);
862 for (i = 0; i < tab->n_var; ++i) {
863 if (tab->var[i].is_zero)
865 if (tab->var[i].is_row) {
867 row[0], tab->mat->row[tab->var[i].index][0]);
868 isl_int_swap(a, row[0]);
869 isl_int_divexact(a, row[0], a);
871 row[0], tab->mat->row[tab->var[i].index][0]);
872 isl_int_mul(b, b, line[1 + i]);
873 isl_seq_combine(row + 1, a, row + 1,
874 b, tab->mat->row[tab->var[i].index] + 1,
877 isl_int_addmul(row[2 + tab->var[i].index],
878 line[1 + i], row[0]);
880 isl_seq_normalize(row, 2 + tab->n_col);
887 static int drop_row(struct isl_tab *tab, int row)
889 isl_assert(tab->mat->ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
890 if (row != tab->n_row - 1)
891 swap_rows(tab, row, tab->n_row - 1);
897 /* Add inequality "ineq" and check if it conflicts with the
898 * previously added constraints or if it is obviously redundant.
900 struct isl_tab *isl_tab_add_ineq(struct isl_tab *tab, isl_int *ineq)
907 r = add_row(tab, ineq);
910 tab->con[r].is_nonneg = 1;
911 push(tab, isl_tab_undo_nonneg, &tab->con[r]);
912 if (is_redundant(tab, tab->con[r].index)) {
913 mark_redundant(tab, tab->con[r].index);
917 sgn = restore_row(tab, &tab->con[r]);
920 else if (tab->con[r].is_row &&
921 is_redundant(tab, tab->con[r].index))
922 mark_redundant(tab, tab->con[r].index);
929 /* Pivot a non-negative variable down until it reaches the value zero
930 * and then pivot the variable into a column position.
932 static int to_col(struct isl_tab *tab, struct isl_tab_var *var)
940 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
941 find_pivot(tab, var, NULL, -1, &row, &col);
942 isl_assert(tab->mat->ctx, row != -1, return -1);
943 pivot(tab, row, col);
948 for (i = tab->n_dead; i < tab->n_col; ++i)
949 if (!isl_int_is_zero(tab->mat->row[var->index][2 + i]))
952 isl_assert(tab->mat->ctx, i < tab->n_col, return -1);
953 pivot(tab, var->index, i);
958 /* We assume Gaussian elimination has been performed on the equalities.
959 * The equalities can therefore never conflict.
960 * Adding the equalities is currently only really useful for a later call
961 * to isl_tab_ineq_type.
963 static struct isl_tab *add_eq(struct isl_tab *tab, isl_int *eq)
970 r = add_row(tab, eq);
974 r = tab->con[r].index;
975 i = isl_seq_first_non_zero(tab->mat->row[r] + 2 + tab->n_dead,
976 tab->n_col - tab->n_dead);
977 isl_assert(tab->mat->ctx, i >= 0, goto error);
989 /* Add an equality that is known to be valid for the given tableau.
991 struct isl_tab *isl_tab_add_valid_eq(struct isl_tab *tab, isl_int *eq)
993 struct isl_tab_var *var;
999 r = add_row(tab, eq);
1005 if (isl_int_is_neg(tab->mat->row[r][1]))
1006 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1009 if (to_col(tab, var) < 0)
1012 kill_col(tab, var->index);
1020 struct isl_tab *isl_tab_from_basic_map(struct isl_basic_map *bmap)
1023 struct isl_tab *tab;
1027 tab = isl_tab_alloc(bmap->ctx,
1028 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
1029 isl_basic_map_total_dim(bmap));
1032 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1033 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) {
1037 for (i = 0; i < bmap->n_eq; ++i) {
1038 tab = add_eq(tab, bmap->eq[i]);
1042 for (i = 0; i < bmap->n_ineq; ++i) {
1043 tab = isl_tab_add_ineq(tab, bmap->ineq[i]);
1044 if (!tab || tab->empty)
1050 struct isl_tab *isl_tab_from_basic_set(struct isl_basic_set *bset)
1052 return isl_tab_from_basic_map((struct isl_basic_map *)bset);
1055 /* Construct a tableau corresponding to the recession cone of "bmap".
1057 struct isl_tab *isl_tab_from_recession_cone(struct isl_basic_map *bmap)
1061 struct isl_tab *tab;
1065 tab = isl_tab_alloc(bmap->ctx, bmap->n_eq + bmap->n_ineq,
1066 isl_basic_map_total_dim(bmap));
1069 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1072 for (i = 0; i < bmap->n_eq; ++i) {
1073 isl_int_swap(bmap->eq[i][0], cst);
1074 tab = add_eq(tab, bmap->eq[i]);
1075 isl_int_swap(bmap->eq[i][0], cst);
1079 for (i = 0; i < bmap->n_ineq; ++i) {
1081 isl_int_swap(bmap->ineq[i][0], cst);
1082 r = add_row(tab, bmap->ineq[i]);
1083 isl_int_swap(bmap->ineq[i][0], cst);
1086 tab->con[r].is_nonneg = 1;
1087 push(tab, isl_tab_undo_nonneg, &tab->con[r]);
1098 /* Assuming "tab" is the tableau of a cone, check if the cone is
1099 * bounded, i.e., if it is empty or only contains the origin.
1101 int isl_tab_cone_is_bounded(struct isl_tab *tab)
1109 if (tab->n_dead == tab->n_col)
1113 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1114 struct isl_tab_var *var;
1115 var = var_from_row(tab, i);
1116 if (!var->is_nonneg)
1118 if (sign_of_max(tab, var) != 0)
1120 close_row(tab, var);
1123 if (tab->n_dead == tab->n_col)
1125 if (i == tab->n_row)
1130 int isl_tab_sample_is_integer(struct isl_tab *tab)
1137 for (i = 0; i < tab->n_var; ++i) {
1139 if (!tab->var[i].is_row)
1141 row = tab->var[i].index;
1142 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
1143 tab->mat->row[row][0]))
1149 static struct isl_vec *extract_integer_sample(struct isl_tab *tab)
1152 struct isl_vec *vec;
1154 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1158 isl_int_set_si(vec->block.data[0], 1);
1159 for (i = 0; i < tab->n_var; ++i) {
1160 if (!tab->var[i].is_row)
1161 isl_int_set_si(vec->block.data[1 + i], 0);
1163 int row = tab->var[i].index;
1164 isl_int_divexact(vec->block.data[1 + i],
1165 tab->mat->row[row][1], tab->mat->row[row][0]);
1172 struct isl_vec *isl_tab_get_sample_value(struct isl_tab *tab)
1175 struct isl_vec *vec;
1181 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1187 isl_int_set_si(vec->block.data[0], 1);
1188 for (i = 0; i < tab->n_var; ++i) {
1190 if (!tab->var[i].is_row) {
1191 isl_int_set_si(vec->block.data[1 + i], 0);
1194 row = tab->var[i].index;
1195 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
1196 isl_int_divexact(m, tab->mat->row[row][0], m);
1197 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
1198 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
1199 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
1201 isl_seq_normalize(vec->block.data, vec->size);
1207 /* Update "bmap" based on the results of the tableau "tab".
1208 * In particular, implicit equalities are made explicit, redundant constraints
1209 * are removed and if the sample value happens to be integer, it is stored
1210 * in "bmap" (unless "bmap" already had an integer sample).
1212 * The tableau is assumed to have been created from "bmap" using
1213 * isl_tab_from_basic_map.
1215 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
1216 struct isl_tab *tab)
1228 bmap = isl_basic_map_set_to_empty(bmap);
1230 for (i = bmap->n_ineq - 1; i >= 0; --i) {
1231 if (isl_tab_is_equality(tab, n_eq + i))
1232 isl_basic_map_inequality_to_equality(bmap, i);
1233 else if (isl_tab_is_redundant(tab, n_eq + i))
1234 isl_basic_map_drop_inequality(bmap, i);
1236 if (!tab->rational &&
1237 !bmap->sample && isl_tab_sample_is_integer(tab))
1238 bmap->sample = extract_integer_sample(tab);
1242 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
1243 struct isl_tab *tab)
1245 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
1246 (struct isl_basic_map *)bset, tab);
1249 /* Given a non-negative variable "var", add a new non-negative variable
1250 * that is the opposite of "var", ensuring that var can only attain the
1252 * If var = n/d is a row variable, then the new variable = -n/d.
1253 * If var is a column variables, then the new variable = -var.
1254 * If the new variable cannot attain non-negative values, then
1255 * the resulting tableau is empty.
1256 * Otherwise, we know the value will be zero and we close the row.
1258 static struct isl_tab *cut_to_hyperplane(struct isl_tab *tab,
1259 struct isl_tab_var *var)
1265 if (extend_cons(tab, 1) < 0)
1269 tab->con[r].index = tab->n_row;
1270 tab->con[r].is_row = 1;
1271 tab->con[r].is_nonneg = 0;
1272 tab->con[r].is_zero = 0;
1273 tab->con[r].is_redundant = 0;
1274 tab->con[r].frozen = 0;
1275 tab->row_var[tab->n_row] = ~r;
1276 row = tab->mat->row[tab->n_row];
1279 isl_int_set(row[0], tab->mat->row[var->index][0]);
1280 isl_seq_neg(row + 1,
1281 tab->mat->row[var->index] + 1, 1 + tab->n_col);
1283 isl_int_set_si(row[0], 1);
1284 isl_seq_clr(row + 1, 1 + tab->n_col);
1285 isl_int_set_si(row[2 + var->index], -1);
1290 push(tab, isl_tab_undo_allocate, &tab->con[r]);
1292 sgn = sign_of_max(tab, &tab->con[r]);
1296 tab->con[r].is_nonneg = 1;
1297 push(tab, isl_tab_undo_nonneg, &tab->con[r]);
1299 close_row(tab, &tab->con[r]);
1308 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
1309 * relax the inequality by one. That is, the inequality r >= 0 is replaced
1310 * by r' = r + 1 >= 0.
1311 * If r is a row variable, we simply increase the constant term by one
1312 * (taking into account the denominator).
1313 * If r is a column variable, then we need to modify each row that
1314 * refers to r = r' - 1 by substituting this equality, effectively
1315 * subtracting the coefficient of the column from the constant.
1317 struct isl_tab *isl_tab_relax(struct isl_tab *tab, int con)
1319 struct isl_tab_var *var;
1323 var = &tab->con[con];
1325 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
1326 to_row(tab, var, 1);
1329 isl_int_add(tab->mat->row[var->index][1],
1330 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1334 for (i = 0; i < tab->n_row; ++i) {
1335 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1337 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
1338 tab->mat->row[i][2 + var->index]);
1343 push(tab, isl_tab_undo_relax, var);
1348 struct isl_tab *isl_tab_select_facet(struct isl_tab *tab, int con)
1353 return cut_to_hyperplane(tab, &tab->con[con]);
1356 static int may_be_equality(struct isl_tab *tab, int row)
1358 return (tab->rational ? isl_int_is_zero(tab->mat->row[row][1])
1359 : isl_int_lt(tab->mat->row[row][1],
1360 tab->mat->row[row][0])) &&
1361 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1362 tab->n_col - tab->n_dead) != -1;
1365 /* Check for (near) equalities among the constraints.
1366 * A constraint is an equality if it is non-negative and if
1367 * its maximal value is either
1368 * - zero (in case of rational tableaus), or
1369 * - strictly less than 1 (in case of integer tableaus)
1371 * We first mark all non-redundant and non-dead variables that
1372 * are not frozen and not obviously not an equality.
1373 * Then we iterate over all marked variables if they can attain
1374 * any values larger than zero or at least one.
1375 * If the maximal value is zero, we mark any column variables
1376 * that appear in the row as being zero and mark the row as being redundant.
1377 * Otherwise, if the maximal value is strictly less than one (and the
1378 * tableau is integer), then we restrict the value to being zero
1379 * by adding an opposite non-negative variable.
1381 struct isl_tab *isl_tab_detect_equalities(struct isl_tab *tab)
1390 if (tab->n_dead == tab->n_col)
1394 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1395 struct isl_tab_var *var = var_from_row(tab, i);
1396 var->marked = !var->frozen && var->is_nonneg &&
1397 may_be_equality(tab, i);
1401 for (i = tab->n_dead; i < tab->n_col; ++i) {
1402 struct isl_tab_var *var = var_from_col(tab, i);
1403 var->marked = !var->frozen && var->is_nonneg;
1408 struct isl_tab_var *var;
1409 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1410 var = var_from_row(tab, i);
1414 if (i == tab->n_row) {
1415 for (i = tab->n_dead; i < tab->n_col; ++i) {
1416 var = var_from_col(tab, i);
1420 if (i == tab->n_col)
1425 if (sign_of_max(tab, var) == 0)
1426 close_row(tab, var);
1427 else if (!tab->rational && !at_least_one(tab, var)) {
1428 tab = cut_to_hyperplane(tab, var);
1429 return isl_tab_detect_equalities(tab);
1431 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1432 var = var_from_row(tab, i);
1435 if (may_be_equality(tab, i))
1445 /* Check for (near) redundant constraints.
1446 * A constraint is redundant if it is non-negative and if
1447 * its minimal value (temporarily ignoring the non-negativity) is either
1448 * - zero (in case of rational tableaus), or
1449 * - strictly larger than -1 (in case of integer tableaus)
1451 * We first mark all non-redundant and non-dead variables that
1452 * are not frozen and not obviously negatively unbounded.
1453 * Then we iterate over all marked variables if they can attain
1454 * any values smaller than zero or at most negative one.
1455 * If not, we mark the row as being redundant (assuming it hasn't
1456 * been detected as being obviously redundant in the mean time).
1458 struct isl_tab *isl_tab_detect_redundant(struct isl_tab *tab)
1467 if (tab->n_redundant == tab->n_row)
1471 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1472 struct isl_tab_var *var = var_from_row(tab, i);
1473 var->marked = !var->frozen && var->is_nonneg;
1477 for (i = tab->n_dead; i < tab->n_col; ++i) {
1478 struct isl_tab_var *var = var_from_col(tab, i);
1479 var->marked = !var->frozen && var->is_nonneg &&
1480 !min_is_manifestly_unbounded(tab, var);
1485 struct isl_tab_var *var;
1486 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1487 var = var_from_row(tab, i);
1491 if (i == tab->n_row) {
1492 for (i = tab->n_dead; i < tab->n_col; ++i) {
1493 var = var_from_col(tab, i);
1497 if (i == tab->n_col)
1502 if ((tab->rational ? (sign_of_min(tab, var) >= 0)
1503 : !min_at_most_neg_one(tab, var)) &&
1505 mark_redundant(tab, var->index);
1506 for (i = tab->n_dead; i < tab->n_col; ++i) {
1507 var = var_from_col(tab, i);
1510 if (!min_is_manifestly_unbounded(tab, var))
1520 int isl_tab_is_equality(struct isl_tab *tab, int con)
1526 if (tab->con[con].is_zero)
1528 if (tab->con[con].is_redundant)
1530 if (!tab->con[con].is_row)
1531 return tab->con[con].index < tab->n_dead;
1533 row = tab->con[con].index;
1535 return isl_int_is_zero(tab->mat->row[row][1]) &&
1536 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1537 tab->n_col - tab->n_dead) == -1;
1540 /* Return the minimial value of the affine expression "f" with denominator
1541 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
1542 * the expression cannot attain arbitrarily small values.
1543 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
1544 * The return value reflects the nature of the result (empty, unbounded,
1545 * minmimal value returned in *opt).
1547 enum isl_lp_result isl_tab_min(struct isl_tab *tab,
1548 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom,
1552 enum isl_lp_result res = isl_lp_ok;
1553 struct isl_tab_var *var;
1554 struct isl_tab_undo *snap;
1557 return isl_lp_empty;
1559 snap = isl_tab_snap(tab);
1560 r = add_row(tab, f);
1562 return isl_lp_error;
1564 isl_int_mul(tab->mat->row[var->index][0],
1565 tab->mat->row[var->index][0], denom);
1568 find_pivot(tab, var, var, -1, &row, &col);
1569 if (row == var->index) {
1570 res = isl_lp_unbounded;
1575 pivot(tab, row, col);
1577 if (isl_tab_rollback(tab, snap) < 0)
1578 return isl_lp_error;
1579 if (ISL_FL_ISSET(flags, ISL_TAB_SAVE_DUAL)) {
1582 isl_vec_free(tab->dual);
1583 tab->dual = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_con);
1585 return isl_lp_error;
1586 isl_int_set(tab->dual->el[0], tab->mat->row[var->index][0]);
1587 for (i = 0; i < tab->n_con; ++i) {
1588 if (tab->con[i].is_row)
1589 isl_int_set_si(tab->dual->el[1 + i], 0);
1591 int pos = 2 + tab->con[i].index;
1592 isl_int_set(tab->dual->el[1 + i],
1593 tab->mat->row[var->index][pos]);
1597 if (res == isl_lp_ok) {
1599 isl_int_set(*opt, tab->mat->row[var->index][1]);
1600 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
1602 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
1603 tab->mat->row[var->index][0]);
1608 int isl_tab_is_redundant(struct isl_tab *tab, int con)
1615 if (tab->con[con].is_zero)
1617 if (tab->con[con].is_redundant)
1619 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
1622 /* Take a snapshot of the tableau that can be restored by s call to
1625 struct isl_tab_undo *isl_tab_snap(struct isl_tab *tab)
1633 /* Undo the operation performed by isl_tab_relax.
1635 static void unrelax(struct isl_tab *tab, struct isl_tab_var *var)
1637 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
1638 to_row(tab, var, 1);
1641 isl_int_sub(tab->mat->row[var->index][1],
1642 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1646 for (i = 0; i < tab->n_row; ++i) {
1647 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1649 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
1650 tab->mat->row[i][2 + var->index]);
1656 static void perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo)
1658 switch(undo->type) {
1659 case isl_tab_undo_empty:
1662 case isl_tab_undo_nonneg:
1663 undo->var->is_nonneg = 0;
1665 case isl_tab_undo_redundant:
1666 undo->var->is_redundant = 0;
1669 case isl_tab_undo_zero:
1670 undo->var->is_zero = 0;
1673 case isl_tab_undo_allocate:
1674 if (!undo->var->is_row) {
1675 if (max_is_manifestly_unbounded(tab, undo->var))
1676 to_row(tab, undo->var, -1);
1678 to_row(tab, undo->var, 1);
1680 drop_row(tab, undo->var->index);
1682 case isl_tab_undo_relax:
1683 unrelax(tab, undo->var);
1688 /* Return the tableau to the state it was in when the snapshot "snap"
1691 int isl_tab_rollback(struct isl_tab *tab, struct isl_tab_undo *snap)
1693 struct isl_tab_undo *undo, *next;
1699 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
1703 perform_undo(tab, undo);
1713 /* The given row "row" represents an inequality violated by all
1714 * points in the tableau. Check for some special cases of such
1715 * separating constraints.
1716 * In particular, if the row has been reduced to the constant -1,
1717 * then we know the inequality is adjacent (but opposite) to
1718 * an equality in the tableau.
1719 * If the row has been reduced to r = -1 -r', with r' an inequality
1720 * of the tableau, then the inequality is adjacent (but opposite)
1721 * to the inequality r'.
1723 static enum isl_ineq_type separation_type(struct isl_tab *tab, unsigned row)
1728 return isl_ineq_separate;
1730 if (!isl_int_is_one(tab->mat->row[row][0]))
1731 return isl_ineq_separate;
1732 if (!isl_int_is_negone(tab->mat->row[row][1]))
1733 return isl_ineq_separate;
1735 pos = isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1736 tab->n_col - tab->n_dead);
1738 return isl_ineq_adj_eq;
1740 if (!isl_int_is_negone(tab->mat->row[row][2 + tab->n_dead + pos]))
1741 return isl_ineq_separate;
1743 pos = isl_seq_first_non_zero(
1744 tab->mat->row[row] + 2 + tab->n_dead + pos + 1,
1745 tab->n_col - tab->n_dead - pos - 1);
1747 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
1750 /* Check the effect of inequality "ineq" on the tableau "tab".
1752 * isl_ineq_redundant: satisfied by all points in the tableau
1753 * isl_ineq_separate: satisfied by no point in the tableau
1754 * isl_ineq_cut: satisfied by some by not all points
1755 * isl_ineq_adj_eq: adjacent to an equality
1756 * isl_ineq_adj_ineq: adjacent to an inequality.
1758 enum isl_ineq_type isl_tab_ineq_type(struct isl_tab *tab, isl_int *ineq)
1760 enum isl_ineq_type type = isl_ineq_error;
1761 struct isl_tab_undo *snap = NULL;
1766 return isl_ineq_error;
1768 if (extend_cons(tab, 1) < 0)
1769 return isl_ineq_error;
1771 snap = isl_tab_snap(tab);
1773 con = add_row(tab, ineq);
1777 row = tab->con[con].index;
1778 if (is_redundant(tab, row))
1779 type = isl_ineq_redundant;
1780 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
1782 isl_int_abs_ge(tab->mat->row[row][1],
1783 tab->mat->row[row][0]))) {
1784 if (at_least_zero(tab, &tab->con[con]))
1785 type = isl_ineq_cut;
1787 type = separation_type(tab, row);
1788 } else if (tab->rational ? (sign_of_min(tab, &tab->con[con]) < 0)
1789 : min_at_most_neg_one(tab, &tab->con[con]))
1790 type = isl_ineq_cut;
1792 type = isl_ineq_redundant;
1794 if (isl_tab_rollback(tab, snap))
1795 return isl_ineq_error;
1798 isl_tab_rollback(tab, snap);
1799 return isl_ineq_error;
1802 void isl_tab_dump(struct isl_tab *tab, FILE *out, int indent)
1808 fprintf(out, "%*snull tab\n", indent, "");
1811 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
1812 tab->n_redundant, tab->n_dead);
1814 fprintf(out, ", rational");
1816 fprintf(out, ", empty");
1818 fprintf(out, "%*s[", indent, "");
1819 for (i = 0; i < tab->n_var; ++i) {
1822 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
1824 tab->var[i].is_zero ? " [=0]" :
1825 tab->var[i].is_redundant ? " [R]" : "");
1827 fprintf(out, "]\n");
1828 fprintf(out, "%*s[", indent, "");
1829 for (i = 0; i < tab->n_con; ++i) {
1832 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
1834 tab->con[i].is_zero ? " [=0]" :
1835 tab->con[i].is_redundant ? " [R]" : "");
1837 fprintf(out, "]\n");
1838 fprintf(out, "%*s[", indent, "");
1839 for (i = 0; i < tab->n_row; ++i) {
1842 fprintf(out, "r%d: %d%s", i, tab->row_var[i],
1843 var_from_row(tab, i)->is_nonneg ? " [>=0]" : "");
1845 fprintf(out, "]\n");
1846 fprintf(out, "%*s[", indent, "");
1847 for (i = 0; i < tab->n_col; ++i) {
1850 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
1851 var_from_col(tab, i)->is_nonneg ? " [>=0]" : "");
1853 fprintf(out, "]\n");
1854 r = tab->mat->n_row;
1855 tab->mat->n_row = tab->n_row;
1856 c = tab->mat->n_col;
1857 tab->mat->n_col = 2 + tab->n_col;
1858 isl_mat_dump(tab->mat, out, indent);
1859 tab->mat->n_row = r;
1860 tab->mat->n_col = c;