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;
54 tab->bottom.type = isl_tab_undo_bottom;
55 tab->bottom.next = NULL;
56 tab->top = &tab->bottom;
59 isl_tab_free(ctx, tab);
63 static int extend_cons(struct isl_ctx *ctx, struct isl_tab *tab, unsigned n_new)
65 if (tab->max_con < tab->n_con + n_new) {
66 struct isl_tab_var *con;
68 con = isl_realloc_array(ctx, tab->con,
69 struct isl_tab_var, tab->max_con + n_new);
73 tab->max_con += n_new;
75 if (tab->mat->n_row < tab->n_row + n_new) {
78 tab->mat = isl_mat_extend(ctx, tab->mat,
79 tab->n_row + n_new, tab->n_col);
82 row_var = isl_realloc_array(ctx, tab->row_var,
83 int, tab->mat->n_row);
86 tab->row_var = row_var;
91 struct isl_tab *isl_tab_extend(struct isl_ctx *ctx, struct isl_tab *tab,
94 if (extend_cons(ctx, tab, n_new) >= 0)
97 isl_tab_free(ctx, tab);
101 static void free_undo(struct isl_ctx *ctx, 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_ctx *ctx, struct isl_tab *tab)
117 isl_mat_free(ctx, tab->mat);
125 static struct isl_tab_var *var_from_index(struct isl_ctx *ctx,
126 struct isl_tab *tab, int i)
131 return &tab->con[~i];
134 static struct isl_tab_var *var_from_row(struct isl_ctx *ctx,
135 struct isl_tab *tab, int i)
137 return var_from_index(ctx, tab, tab->row_var[i]);
140 static struct isl_tab_var *var_from_col(struct isl_ctx *ctx,
141 struct isl_tab *tab, int i)
143 return var_from_index(ctx, tab, tab->col_var[i]);
146 /* Check if there are any upper bounds on column variable "var",
147 * i.e., non-negative rows where var appears with a negative coefficient.
148 * Return 1 if there are no such bounds.
150 static int max_is_manifestly_unbounded(struct isl_ctx *ctx,
151 struct isl_tab *tab, struct isl_tab_var *var)
157 for (i = tab->n_redundant; i < tab->n_row; ++i) {
158 if (!isl_int_is_neg(tab->mat->row[i][2 + var->index]))
160 if (var_from_row(ctx, tab, i)->is_nonneg)
166 /* Check if there are any lower bounds on column variable "var",
167 * i.e., non-negative rows where var appears with a positive coefficient.
168 * Return 1 if there are no such bounds.
170 static int min_is_manifestly_unbounded(struct isl_ctx *ctx,
171 struct isl_tab *tab, struct isl_tab_var *var)
177 for (i = tab->n_redundant; i < tab->n_row; ++i) {
178 if (!isl_int_is_pos(tab->mat->row[i][2 + var->index]))
180 if (var_from_row(ctx, tab, i)->is_nonneg)
186 /* Given the index of a column "c", return the index of a row
187 * that can be used to pivot the column in, with either an increase
188 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
189 * If "var" is not NULL, then the row returned will be different from
190 * the one associated with "var".
192 * Each row in the tableau is of the form
194 * x_r = a_r0 + \sum_i a_ri x_i
196 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
197 * impose any limit on the increase or decrease in the value of x_c
198 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
199 * for the row with the smallest (most stringent) such bound.
200 * Note that the common denominator of each row drops out of the fraction.
201 * To check if row j has a smaller bound than row r, i.e.,
202 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
203 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
204 * where -sign(a_jc) is equal to "sgn".
206 static int pivot_row(struct isl_ctx *ctx, struct isl_tab *tab,
207 struct isl_tab_var *var, int sgn, int c)
214 for (j = tab->n_redundant; j < tab->n_row; ++j) {
215 if (var && j == var->index)
217 if (!var_from_row(ctx, tab, j)->is_nonneg)
219 if (sgn * isl_int_sgn(tab->mat->row[j][2 + c]) >= 0)
225 isl_int_mul(t, tab->mat->row[r][1], tab->mat->row[j][2 + c]);
226 isl_int_submul(t, tab->mat->row[j][1], tab->mat->row[r][2 + c]);
227 tsgn = sgn * isl_int_sgn(t);
228 if (tsgn < 0 || (tsgn == 0 &&
229 tab->row_var[j] < tab->row_var[r]))
236 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
237 * (sgn < 0) the value of row variable var.
238 * If not NULL, then skip_var is a row variable that should be ignored
239 * while looking for a pivot row. It is usually equal to var.
241 * As the given row in the tableau is of the form
243 * x_r = a_r0 + \sum_i a_ri x_i
245 * we need to find a column such that the sign of a_ri is equal to "sgn"
246 * (such that an increase in x_i will have the desired effect) or a
247 * column with a variable that may attain negative values.
248 * If a_ri is positive, then we need to move x_i in the same direction
249 * to obtain the desired effect. Otherwise, x_i has to move in the
250 * opposite direction.
252 static void find_pivot(struct isl_ctx *ctx, struct isl_tab *tab,
253 struct isl_tab_var *var, struct isl_tab_var *skip_var,
254 int sgn, int *row, int *col)
261 isl_assert(ctx, var->is_row, return);
262 tr = tab->mat->row[var->index];
265 for (j = tab->n_dead; j < tab->n_col; ++j) {
266 if (isl_int_is_zero(tr[2 + j]))
268 if (isl_int_sgn(tr[2 + j]) != sgn &&
269 var_from_col(ctx, tab, j)->is_nonneg)
271 if (c < 0 || tab->col_var[j] < tab->col_var[c])
277 sgn *= isl_int_sgn(tr[2 + c]);
278 r = pivot_row(ctx, tab, skip_var, sgn, c);
279 *row = r < 0 ? var->index : r;
283 /* Return 1 if row "row" represents an obviously redundant inequality.
285 * - it represents an inequality or a variable
286 * - that is the sum of a non-negative sample value and a positive
287 * combination of zero or more non-negative variables.
289 static int is_redundant(struct isl_ctx *ctx, struct isl_tab *tab, int row)
293 if (tab->row_var[row] < 0 && !var_from_row(ctx, tab, row)->is_nonneg)
296 if (isl_int_is_neg(tab->mat->row[row][1]))
299 for (i = tab->n_dead; i < tab->n_col; ++i) {
300 if (isl_int_is_zero(tab->mat->row[row][2 + i]))
302 if (isl_int_is_neg(tab->mat->row[row][2 + i]))
304 if (!var_from_col(ctx, tab, i)->is_nonneg)
310 static void swap_rows(struct isl_ctx *ctx,
311 struct isl_tab *tab, int row1, int row2)
314 t = tab->row_var[row1];
315 tab->row_var[row1] = tab->row_var[row2];
316 tab->row_var[row2] = t;
317 var_from_row(ctx, tab, row1)->index = row1;
318 var_from_row(ctx, tab, row2)->index = row2;
319 tab->mat = isl_mat_swap_rows(ctx, tab->mat, row1, row2);
322 static void push(struct isl_ctx *ctx, struct isl_tab *tab,
323 enum isl_tab_undo_type type, struct isl_tab_var *var)
325 struct isl_tab_undo *undo;
330 undo = isl_alloc_type(ctx, struct isl_tab_undo);
338 undo->next = tab->top;
342 /* Mark row with index "row" as being redundant.
343 * If we may need to undo the operation or if the row represents
344 * a variable of the original problem, the row is kept,
345 * but no longer considered when looking for a pivot row.
346 * Otherwise, the row is simply removed.
348 * The row may be interchanged with some other row. If it
349 * is interchanged with a later row, return 1. Otherwise return 0.
350 * If the rows are checked in order in the calling function,
351 * then a return value of 1 means that the row with the given
352 * row number may now contain a different row that hasn't been checked yet.
354 static int mark_redundant(struct isl_ctx *ctx,
355 struct isl_tab *tab, int row)
357 struct isl_tab_var *var = var_from_row(ctx, tab, row);
358 var->is_redundant = 1;
359 isl_assert(ctx, row >= tab->n_redundant, return);
360 if (tab->need_undo || tab->row_var[row] >= 0) {
361 if (tab->row_var[row] >= 0) {
363 push(ctx, tab, isl_tab_undo_nonneg, var);
365 if (row != tab->n_redundant)
366 swap_rows(ctx, tab, row, tab->n_redundant);
367 push(ctx, tab, isl_tab_undo_redundant, var);
371 if (row != tab->n_row - 1)
372 swap_rows(ctx, tab, row, tab->n_row - 1);
373 var_from_row(ctx, tab, tab->n_row - 1)->index = -1;
379 static void mark_empty(struct isl_ctx *ctx, struct isl_tab *tab)
381 if (!tab->empty && tab->need_undo)
382 push(ctx, tab, isl_tab_undo_empty, NULL);
386 /* Given a row number "row" and a column number "col", pivot the tableau
387 * such that the associated variable are interchanged.
388 * The given row in the tableau expresses
390 * x_r = a_r0 + \sum_i a_ri x_i
394 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
396 * Substituting this equality into the other rows
398 * x_j = a_j0 + \sum_i a_ji x_i
400 * with a_jc \ne 0, we obtain
402 * 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
409 * where i is any other column and j is any other row,
410 * is therefore transformed into
412 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
413 * 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)
415 * The transformation is performed along the following steps
420 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
423 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
424 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
426 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
427 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
429 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
430 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
432 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
433 * 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)
436 static void pivot(struct isl_ctx *ctx,
437 struct isl_tab *tab, int row, int col)
442 struct isl_mat *mat = tab->mat;
443 struct isl_tab_var *var;
445 isl_int_swap(mat->row[row][0], mat->row[row][2 + col]);
446 sgn = isl_int_sgn(mat->row[row][0]);
448 isl_int_neg(mat->row[row][0], mat->row[row][0]);
449 isl_int_neg(mat->row[row][2 + col], mat->row[row][2 + col]);
451 for (j = 0; j < 1 + tab->n_col; ++j) {
454 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
456 if (!isl_int_is_one(mat->row[row][0]))
457 isl_seq_normalize(mat->row[row], 2 + tab->n_col);
458 for (i = 0; i < tab->n_row; ++i) {
461 if (isl_int_is_zero(mat->row[i][2 + col]))
463 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
464 for (j = 0; j < 1 + tab->n_col; ++j) {
467 isl_int_mul(mat->row[i][1 + j],
468 mat->row[i][1 + j], mat->row[row][0]);
469 isl_int_addmul(mat->row[i][1 + j],
470 mat->row[i][2 + col], mat->row[row][1 + j]);
472 isl_int_mul(mat->row[i][2 + col],
473 mat->row[i][2 + col], mat->row[row][2 + col]);
474 if (!isl_int_is_one(mat->row[row][0]))
475 isl_seq_normalize(mat->row[i], 2 + tab->n_col);
477 t = tab->row_var[row];
478 tab->row_var[row] = tab->col_var[col];
479 tab->col_var[col] = t;
480 var = var_from_row(ctx, tab, row);
483 var = var_from_col(ctx, tab, col);
486 for (i = tab->n_redundant; i < tab->n_row; ++i) {
487 if (isl_int_is_zero(mat->row[i][2 + col]))
489 if (!var_from_row(ctx, tab, i)->frozen &&
490 is_redundant(ctx, tab, i))
491 if (mark_redundant(ctx, tab, i))
496 /* If "var" represents a column variable, then pivot is up (sgn > 0)
497 * or down (sgn < 0) to a row. The variable is assumed not to be
498 * unbounded in the specified direction.
500 static void to_row(struct isl_ctx *ctx,
501 struct isl_tab *tab, struct isl_tab_var *var, int sign)
508 r = pivot_row(ctx, tab, NULL, sign, var->index);
509 isl_assert(ctx, r >= 0, return);
510 pivot(ctx, tab, r, var->index);
513 static void check_table(struct isl_ctx *ctx, struct isl_tab *tab)
519 for (i = 0; i < tab->n_row; ++i) {
520 if (!var_from_row(ctx, tab, i)->is_nonneg)
522 assert(!isl_int_is_neg(tab->mat->row[i][1]));
526 /* Return the sign of the maximal value of "var".
527 * If the sign is not negative, then on return from this function,
528 * the sample value will also be non-negative.
530 * If "var" is manifestly unbounded wrt positive values, we are done.
531 * Otherwise, we pivot the variable up to a row if needed
532 * Then we continue pivoting down until either
533 * - no more down pivots can be performed
534 * - the sample value is positive
535 * - the variable is pivoted into a manifestly unbounded column
537 static int sign_of_max(struct isl_ctx *ctx,
538 struct isl_tab *tab, struct isl_tab_var *var)
542 if (max_is_manifestly_unbounded(ctx, tab, var))
544 to_row(ctx, tab, var, 1);
545 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
546 find_pivot(ctx, tab, var, var, 1, &row, &col);
548 return isl_int_sgn(tab->mat->row[var->index][1]);
549 pivot(ctx, tab, row, col);
550 if (!var->is_row) /* manifestly unbounded */
556 /* Perform pivots until the row variable "var" has a non-negative
557 * sample value or until no more upward pivots can be performed.
558 * Return the sign of the sample value after the pivots have been
561 static int restore_row(struct isl_ctx *ctx,
562 struct isl_tab *tab, struct isl_tab_var *var)
566 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
567 find_pivot(ctx, tab, var, var, 1, &row, &col);
570 pivot(ctx, tab, row, col);
571 if (!var->is_row) /* manifestly unbounded */
574 return isl_int_sgn(tab->mat->row[var->index][1]);
577 /* Perform pivots until we are sure that the row variable "var"
578 * can attain non-negative values. After return from this
579 * function, "var" is still a row variable, but its sample
580 * value may not be non-negative, even if the function returns 1.
582 static int at_least_zero(struct isl_ctx *ctx,
583 struct isl_tab *tab, struct isl_tab_var *var)
587 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
588 find_pivot(ctx, tab, var, var, 1, &row, &col);
591 if (row == var->index) /* manifestly unbounded */
593 pivot(ctx, tab, row, col);
595 return !isl_int_is_neg(tab->mat->row[var->index][1]);
598 /* Return a negative value if "var" can attain negative values.
599 * Return a non-negative value otherwise.
601 * If "var" is manifestly unbounded wrt negative values, we are done.
602 * Otherwise, if var is in a column, we can pivot it down to a row.
603 * Then we continue pivoting down until either
604 * - the pivot would result in a manifestly unbounded column
605 * => we don't perform the pivot, but simply return -1
606 * - no more down pivots can be performed
607 * - the sample value is negative
608 * If the sample value becomes negative and the variable is supposed
609 * to be nonnegative, then we undo the last pivot.
610 * However, if the last pivot has made the pivoting variable
611 * obviously redundant, then it may have moved to another row.
612 * In that case we look for upward pivots until we reach a non-negative
615 static int sign_of_min(struct isl_ctx *ctx,
616 struct isl_tab *tab, struct isl_tab_var *var)
619 struct isl_tab_var *pivot_var;
621 if (min_is_manifestly_unbounded(ctx, tab, var))
625 row = pivot_row(ctx, tab, NULL, -1, col);
626 pivot_var = var_from_col(ctx, tab, col);
627 pivot(ctx, tab, row, col);
628 if (var->is_redundant)
630 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
631 if (var->is_nonneg) {
632 if (!pivot_var->is_redundant &&
633 pivot_var->index == row)
634 pivot(ctx, tab, row, col);
636 restore_row(ctx, tab, var);
641 if (var->is_redundant)
643 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
644 find_pivot(ctx, tab, var, var, -1, &row, &col);
645 if (row == var->index)
648 return isl_int_sgn(tab->mat->row[var->index][1]);
649 pivot_var = var_from_col(ctx, tab, col);
650 pivot(ctx, tab, row, col);
651 if (var->is_redundant)
654 if (var->is_nonneg) {
655 /* pivot back to non-negative value */
656 if (!pivot_var->is_redundant && pivot_var->index == row)
657 pivot(ctx, tab, row, col);
659 restore_row(ctx, tab, var);
664 /* Return 1 if "var" can attain values <= -1.
665 * Return 0 otherwise.
667 * The sample value of "var" is assumed to be non-negative when the
668 * the function is called and will be made non-negative again before
669 * the function returns.
671 static int min_at_most_neg_one(struct isl_ctx *ctx,
672 struct isl_tab *tab, struct isl_tab_var *var)
675 struct isl_tab_var *pivot_var;
677 if (min_is_manifestly_unbounded(ctx, tab, var))
681 row = pivot_row(ctx, tab, NULL, -1, col);
682 pivot_var = var_from_col(ctx, tab, col);
683 pivot(ctx, tab, row, col);
684 if (var->is_redundant)
686 if (isl_int_is_neg(tab->mat->row[var->index][1]) &&
687 isl_int_abs_ge(tab->mat->row[var->index][1],
688 tab->mat->row[var->index][0])) {
689 if (var->is_nonneg) {
690 if (!pivot_var->is_redundant &&
691 pivot_var->index == row)
692 pivot(ctx, tab, row, col);
694 restore_row(ctx, tab, var);
699 if (var->is_redundant)
702 find_pivot(ctx, tab, var, var, -1, &row, &col);
703 if (row == var->index)
707 pivot_var = var_from_col(ctx, tab, col);
708 pivot(ctx, tab, row, col);
709 if (var->is_redundant)
711 } while (!isl_int_is_neg(tab->mat->row[var->index][1]) ||
712 isl_int_abs_lt(tab->mat->row[var->index][1],
713 tab->mat->row[var->index][0]));
714 if (var->is_nonneg) {
715 /* pivot back to non-negative value */
716 if (!pivot_var->is_redundant && pivot_var->index == row)
717 pivot(ctx, tab, row, col);
718 restore_row(ctx, tab, var);
723 /* Return 1 if "var" can attain values >= 1.
724 * Return 0 otherwise.
726 static int at_least_one(struct isl_ctx *ctx,
727 struct isl_tab *tab, struct isl_tab_var *var)
732 if (max_is_manifestly_unbounded(ctx, tab, var))
734 to_row(ctx, tab, var, 1);
735 r = tab->mat->row[var->index];
736 while (isl_int_lt(r[1], r[0])) {
737 find_pivot(ctx, tab, var, var, 1, &row, &col);
739 return isl_int_ge(r[1], r[0]);
740 if (row == var->index) /* manifestly unbounded */
742 pivot(ctx, tab, row, col);
747 static void swap_cols(struct isl_ctx *ctx,
748 struct isl_tab *tab, int col1, int col2)
751 t = tab->col_var[col1];
752 tab->col_var[col1] = tab->col_var[col2];
753 tab->col_var[col2] = t;
754 var_from_col(ctx, tab, col1)->index = col1;
755 var_from_col(ctx, tab, col2)->index = col2;
756 tab->mat = isl_mat_swap_cols(ctx, tab->mat, 2 + col1, 2 + col2);
759 /* Mark column with index "col" as representing a zero variable.
760 * If we may need to undo the operation the column is kept,
761 * but no longer considered.
762 * Otherwise, the column is simply removed.
764 * The column may be interchanged with some other column. If it
765 * is interchanged with a later column, return 1. Otherwise return 0.
766 * If the columns are checked in order in the calling function,
767 * then a return value of 1 means that the column with the given
768 * column number may now contain a different column that
769 * hasn't been checked yet.
771 static int kill_col(struct isl_ctx *ctx,
772 struct isl_tab *tab, int col)
774 var_from_col(ctx, tab, col)->is_zero = 1;
775 if (tab->need_undo) {
776 push(ctx, tab, isl_tab_undo_zero, var_from_col(ctx, tab, col));
777 if (col != tab->n_dead)
778 swap_cols(ctx, tab, col, tab->n_dead);
782 if (col != tab->n_col - 1)
783 swap_cols(ctx, tab, col, tab->n_col - 1);
784 var_from_col(ctx, tab, tab->n_col - 1)->index = -1;
790 /* Row variable "var" is non-negative and cannot attain any values
791 * larger than zero. This means that the coefficients of the unrestricted
792 * column variables are zero and that the coefficients of the non-negative
793 * column variables are zero or negative.
794 * Each of the non-negative variables with a negative coefficient can
795 * then also be written as the negative sum of non-negative variables
796 * and must therefore also be zero.
798 static void close_row(struct isl_ctx *ctx,
799 struct isl_tab *tab, struct isl_tab_var *var)
802 struct isl_mat *mat = tab->mat;
804 isl_assert(ctx, var->is_nonneg, return);
806 for (j = tab->n_dead; j < tab->n_col; ++j) {
807 if (isl_int_is_zero(mat->row[var->index][2 + j]))
809 isl_assert(ctx, isl_int_is_neg(mat->row[var->index][2 + j]),
811 if (kill_col(ctx, tab, j))
814 mark_redundant(ctx, tab, var->index);
817 /* Add a row to the tableau. The row is given as an affine combination
818 * of the original variables and needs to be expressed in terms of the
821 * We add each term in turn.
822 * If r = n/d_r is the current sum and we need to add k x, then
823 * if x is a column variable, we increase the numerator of
824 * this column by k d_r
825 * if x = f/d_x is a row variable, then the new representation of r is
827 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
828 * --- + --- = ------------------- = -------------------
829 * d_r d_r d_r d_x/g m
831 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
833 static int add_row(struct isl_ctx *ctx, struct isl_tab *tab, isl_int *line)
840 isl_assert(ctx, tab->n_row < tab->mat->n_row, return -1);
845 tab->con[r].index = tab->n_row;
846 tab->con[r].is_row = 1;
847 tab->con[r].is_nonneg = 0;
848 tab->con[r].is_zero = 0;
849 tab->con[r].is_redundant = 0;
850 tab->con[r].frozen = 0;
851 tab->row_var[tab->n_row] = ~r;
852 row = tab->mat->row[tab->n_row];
853 isl_int_set_si(row[0], 1);
854 isl_int_set(row[1], line[0]);
855 isl_seq_clr(row + 2, tab->n_col);
856 for (i = 0; i < tab->n_var; ++i) {
857 if (tab->var[i].is_zero)
859 if (tab->var[i].is_row) {
861 row[0], tab->mat->row[tab->var[i].index][0]);
862 isl_int_swap(a, row[0]);
863 isl_int_divexact(a, row[0], a);
865 row[0], tab->mat->row[tab->var[i].index][0]);
866 isl_int_mul(b, b, line[1 + i]);
867 isl_seq_combine(row + 1, a, row + 1,
868 b, tab->mat->row[tab->var[i].index] + 1,
871 isl_int_addmul(row[2 + tab->var[i].index],
872 line[1 + i], row[0]);
874 isl_seq_normalize(row, 2 + tab->n_col);
877 push(ctx, tab, isl_tab_undo_allocate, &tab->con[r]);
884 static int drop_row(struct isl_ctx *ctx, struct isl_tab *tab, int row)
886 isl_assert(ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
887 if (row != tab->n_row - 1)
888 swap_rows(ctx, tab, row, tab->n_row - 1);
894 /* Add inequality "ineq" and check if it conflicts with the
895 * previously added constraints or if it is obviously redundant.
897 struct isl_tab *isl_tab_add_ineq(struct isl_ctx *ctx,
898 struct isl_tab *tab, isl_int *ineq)
905 r = add_row(ctx, tab, ineq);
908 tab->con[r].is_nonneg = 1;
909 push(ctx, tab, isl_tab_undo_nonneg, &tab->con[r]);
910 if (is_redundant(ctx, tab, tab->con[r].index)) {
911 mark_redundant(ctx, tab, tab->con[r].index);
915 sgn = restore_row(ctx, tab, &tab->con[r]);
917 mark_empty(ctx, tab);
918 else if (tab->con[r].is_row &&
919 is_redundant(ctx, tab, tab->con[r].index))
920 mark_redundant(ctx, tab, tab->con[r].index);
923 isl_tab_free(ctx, tab);
927 /* Pivot a non-negative variable down until it reaches the value zero
928 * and then pivot the variable into a column position.
930 static int to_col(struct isl_ctx *ctx,
931 struct isl_tab *tab, struct isl_tab_var *var)
939 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
940 find_pivot(ctx, tab, var, NULL, -1, &row, &col);
941 isl_assert(ctx, row != -1, return -1);
942 pivot(ctx, tab, row, col);
947 for (i = tab->n_dead; i < tab->n_col; ++i)
948 if (!isl_int_is_zero(tab->mat->row[var->index][2 + i]))
951 isl_assert(ctx, i < tab->n_col, return -1);
952 pivot(ctx, tab, var->index, i);
957 /* We assume Gaussian elimination has been performed on the equalities.
958 * The equalities can therefore never conflict.
959 * Adding the equalities is currently only really useful for a later call
960 * to isl_tab_ineq_type.
962 static struct isl_tab *add_eq(struct isl_ctx *ctx,
963 struct isl_tab *tab, isl_int *eq)
970 r = add_row(ctx, tab, eq);
974 r = tab->con[r].index;
975 for (i = tab->n_dead; i < tab->n_col; ++i) {
976 if (isl_int_is_zero(tab->mat->row[r][2 + i]))
978 pivot(ctx, tab, r, i);
979 kill_col(ctx, tab, i);
986 isl_tab_free(ctx, tab);
990 /* Add an equality that is known to be valid for the given tableau.
992 struct isl_tab *isl_tab_add_valid_eq(struct isl_ctx *ctx,
993 struct isl_tab *tab, isl_int *eq)
995 struct isl_tab_var *var;
1001 r = add_row(ctx, tab, eq);
1007 if (isl_int_is_neg(tab->mat->row[r][1]))
1008 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1011 if (to_col(ctx, tab, var) < 0)
1014 kill_col(ctx, tab, var->index);
1018 isl_tab_free(ctx, tab);
1022 struct isl_tab *isl_tab_from_basic_map(struct isl_basic_map *bmap)
1025 struct isl_tab *tab;
1029 tab = isl_tab_alloc(bmap->ctx,
1030 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
1031 isl_basic_map_total_dim(bmap));
1034 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1035 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) {
1036 mark_empty(bmap->ctx, tab);
1039 for (i = 0; i < bmap->n_eq; ++i) {
1040 tab = add_eq(bmap->ctx, tab, bmap->eq[i]);
1044 for (i = 0; i < bmap->n_ineq; ++i) {
1045 tab = isl_tab_add_ineq(bmap->ctx, tab, bmap->ineq[i]);
1046 if (!tab || tab->empty)
1052 struct isl_tab *isl_tab_from_basic_set(struct isl_basic_set *bset)
1054 return isl_tab_from_basic_map((struct isl_basic_map *)bset);
1057 /* Construct a tableau corresponding to the recession cone of "bmap".
1059 struct isl_tab *isl_tab_from_recession_cone(struct isl_basic_map *bmap)
1063 struct isl_tab *tab;
1067 tab = isl_tab_alloc(bmap->ctx, bmap->n_eq + bmap->n_ineq,
1068 isl_basic_map_total_dim(bmap));
1071 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1074 for (i = 0; i < bmap->n_eq; ++i) {
1075 isl_int_swap(bmap->eq[i][0], cst);
1076 tab = add_eq(bmap->ctx, tab, bmap->eq[i]);
1077 isl_int_swap(bmap->eq[i][0], cst);
1081 for (i = 0; i < bmap->n_ineq; ++i) {
1083 isl_int_swap(bmap->ineq[i][0], cst);
1084 r = add_row(bmap->ctx, tab, bmap->ineq[i]);
1085 isl_int_swap(bmap->ineq[i][0], cst);
1088 tab->con[r].is_nonneg = 1;
1089 push(bmap->ctx, tab, isl_tab_undo_nonneg, &tab->con[r]);
1096 isl_tab_free(bmap->ctx, tab);
1100 /* Assuming "tab" is the tableau of a cone, check if the cone is
1101 * bounded, i.e., if it is empty or only contains the origin.
1103 int isl_tab_cone_is_bounded(struct isl_ctx *ctx, struct isl_tab *tab)
1111 if (tab->n_dead == tab->n_col)
1114 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1115 struct isl_tab_var *var;
1116 var = var_from_row(ctx, tab, i);
1117 if (!var->is_nonneg)
1119 if (sign_of_max(ctx, tab, var) == 0)
1120 close_row(ctx, tab, var);
1123 if (tab->n_dead == tab->n_col)
1129 static int sample_is_integer(struct isl_ctx *ctx, struct isl_tab *tab)
1133 for (i = 0; i < tab->n_var; ++i) {
1135 if (!tab->var[i].is_row)
1137 row = tab->var[i].index;
1138 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
1139 tab->mat->row[row][0]))
1145 static struct isl_vec *extract_integer_sample(struct isl_ctx *ctx,
1146 struct isl_tab *tab)
1149 struct isl_vec *vec;
1151 vec = isl_vec_alloc(ctx, 1 + tab->n_var);
1155 isl_int_set_si(vec->block.data[0], 1);
1156 for (i = 0; i < tab->n_var; ++i) {
1157 if (!tab->var[i].is_row)
1158 isl_int_set_si(vec->block.data[1 + i], 0);
1160 int row = tab->var[i].index;
1161 isl_int_divexact(vec->block.data[1 + i],
1162 tab->mat->row[row][1], tab->mat->row[row][0]);
1169 struct isl_vec *isl_tab_get_sample_value(struct isl_ctx *ctx,
1170 struct isl_tab *tab)
1173 struct isl_vec *vec;
1179 vec = isl_vec_alloc(ctx, 1 + tab->n_var);
1185 isl_int_set_si(vec->block.data[0], 1);
1186 for (i = 0; i < tab->n_var; ++i) {
1188 if (!tab->var[i].is_row) {
1189 isl_int_set_si(vec->block.data[1 + i], 0);
1192 row = tab->var[i].index;
1193 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
1194 isl_int_divexact(m, tab->mat->row[row][0], m);
1195 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
1196 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
1197 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
1199 isl_seq_normalize(vec->block.data, vec->size);
1205 /* Update "bmap" based on the results of the tableau "tab".
1206 * In particular, implicit equalities are made explicit, redundant constraints
1207 * are removed and if the sample value happens to be integer, it is stored
1208 * in "bmap" (unless "bmap" already had an integer sample).
1210 * The tableau is assumed to have been created from "bmap" using
1211 * isl_tab_from_basic_map.
1213 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
1214 struct isl_tab *tab)
1226 bmap = isl_basic_map_set_to_empty(bmap);
1228 for (i = bmap->n_ineq - 1; i >= 0; --i) {
1229 if (isl_tab_is_equality(bmap->ctx, tab, n_eq + i))
1230 isl_basic_map_inequality_to_equality(bmap, i);
1231 else if (isl_tab_is_redundant(bmap->ctx, tab, n_eq + i))
1232 isl_basic_map_drop_inequality(bmap, i);
1234 if (!tab->rational &&
1235 !bmap->sample && sample_is_integer(bmap->ctx, tab))
1236 bmap->sample = extract_integer_sample(bmap->ctx, tab);
1240 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
1241 struct isl_tab *tab)
1243 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
1244 (struct isl_basic_map *)bset, tab);
1247 /* Given a non-negative variable "var", add a new non-negative variable
1248 * that is the opposite of "var", ensuring that var can only attain the
1250 * If var = n/d is a row variable, then the new variable = -n/d.
1251 * If var is a column variables, then the new variable = -var.
1252 * If the new variable cannot attain non-negative values, then
1253 * the resulting tableau is empty.
1254 * Otherwise, we know the value will be zero and we close the row.
1256 static struct isl_tab *cut_to_hyperplane(struct isl_ctx *ctx,
1257 struct isl_tab *tab, struct isl_tab_var *var)
1263 if (extend_cons(ctx, tab, 1) < 0)
1267 tab->con[r].index = tab->n_row;
1268 tab->con[r].is_row = 1;
1269 tab->con[r].is_nonneg = 0;
1270 tab->con[r].is_zero = 0;
1271 tab->con[r].is_redundant = 0;
1272 tab->con[r].frozen = 0;
1273 tab->row_var[tab->n_row] = ~r;
1274 row = tab->mat->row[tab->n_row];
1277 isl_int_set(row[0], tab->mat->row[var->index][0]);
1278 isl_seq_neg(row + 1,
1279 tab->mat->row[var->index] + 1, 1 + tab->n_col);
1281 isl_int_set_si(row[0], 1);
1282 isl_seq_clr(row + 1, 1 + tab->n_col);
1283 isl_int_set_si(row[2 + var->index], -1);
1288 push(ctx, tab, isl_tab_undo_allocate, &tab->con[r]);
1290 sgn = sign_of_max(ctx, tab, &tab->con[r]);
1292 mark_empty(ctx, tab);
1294 tab->con[r].is_nonneg = 1;
1295 push(ctx, tab, isl_tab_undo_nonneg, &tab->con[r]);
1297 close_row(ctx, tab, &tab->con[r]);
1302 isl_tab_free(ctx, tab);
1306 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
1307 * relax the inequality by one. That is, the inequality r >= 0 is replaced
1308 * by r' = r + 1 >= 0.
1309 * If r is a row variable, we simply increase the constant term by one
1310 * (taking into account the denominator).
1311 * If r is a column variable, then we need to modify each row that
1312 * refers to r = r' - 1 by substituting this equality, effectively
1313 * subtracting the coefficient of the column from the constant.
1315 struct isl_tab *isl_tab_relax(struct isl_ctx *ctx,
1316 struct isl_tab *tab, int con)
1318 struct isl_tab_var *var;
1322 var = &tab->con[con];
1324 if (!var->is_row && !max_is_manifestly_unbounded(ctx, tab, var))
1325 to_row(ctx, tab, var, 1);
1328 isl_int_add(tab->mat->row[var->index][1],
1329 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1333 for (i = 0; i < tab->n_row; ++i) {
1334 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1336 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
1337 tab->mat->row[i][2 + var->index]);
1342 push(ctx, tab, isl_tab_undo_relax, var);
1347 struct isl_tab *isl_tab_select_facet(struct isl_ctx *ctx,
1348 struct isl_tab *tab, int con)
1353 return cut_to_hyperplane(ctx, 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_ctx *ctx,
1382 struct isl_tab *tab)
1391 if (tab->n_dead == tab->n_col)
1395 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1396 struct isl_tab_var *var = var_from_row(ctx, tab, i);
1397 var->marked = !var->frozen && var->is_nonneg &&
1398 may_be_equality(tab, i);
1402 for (i = tab->n_dead; i < tab->n_col; ++i) {
1403 struct isl_tab_var *var = var_from_col(ctx, tab, i);
1404 var->marked = !var->frozen && var->is_nonneg;
1409 struct isl_tab_var *var;
1410 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1411 var = var_from_row(ctx, tab, i);
1415 if (i == tab->n_row) {
1416 for (i = tab->n_dead; i < tab->n_col; ++i) {
1417 var = var_from_col(ctx, tab, i);
1421 if (i == tab->n_col)
1426 if (sign_of_max(ctx, tab, var) == 0)
1427 close_row(ctx, tab, var);
1428 else if (!tab->rational && !at_least_one(ctx, tab, var)) {
1429 tab = cut_to_hyperplane(ctx, tab, var);
1430 return isl_tab_detect_equalities(ctx, tab);
1432 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1433 var = var_from_row(ctx, tab, i);
1436 if (may_be_equality(tab, i))
1446 /* Check for (near) redundant constraints.
1447 * A constraint is redundant if it is non-negative and if
1448 * its minimal value (temporarily ignoring the non-negativity) is either
1449 * - zero (in case of rational tableaus), or
1450 * - strictly larger than -1 (in case of integer tableaus)
1452 * We first mark all non-redundant and non-dead variables that
1453 * are not frozen and not obviously negatively unbounded.
1454 * Then we iterate over all marked variables if they can attain
1455 * any values smaller than zero or at most negative one.
1456 * If not, we mark the row as being redundant (assuming it hasn't
1457 * been detected as being obviously redundant in the mean time).
1459 struct isl_tab *isl_tab_detect_redundant(struct isl_ctx *ctx,
1460 struct isl_tab *tab)
1469 if (tab->n_redundant == tab->n_row)
1473 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1474 struct isl_tab_var *var = var_from_row(ctx, tab, i);
1475 var->marked = !var->frozen && var->is_nonneg;
1479 for (i = tab->n_dead; i < tab->n_col; ++i) {
1480 struct isl_tab_var *var = var_from_col(ctx, tab, i);
1481 var->marked = !var->frozen && var->is_nonneg &&
1482 !min_is_manifestly_unbounded(ctx, tab, var);
1487 struct isl_tab_var *var;
1488 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1489 var = var_from_row(ctx, tab, i);
1493 if (i == tab->n_row) {
1494 for (i = tab->n_dead; i < tab->n_col; ++i) {
1495 var = var_from_col(ctx, tab, i);
1499 if (i == tab->n_col)
1504 if ((tab->rational ? (sign_of_min(ctx, tab, var) >= 0)
1505 : !min_at_most_neg_one(ctx, tab, var)) &&
1507 mark_redundant(ctx, tab, var->index);
1508 for (i = tab->n_dead; i < tab->n_col; ++i) {
1509 var = var_from_col(ctx, tab, i);
1512 if (!min_is_manifestly_unbounded(ctx, tab, var))
1522 int isl_tab_is_equality(struct isl_ctx *ctx, struct isl_tab *tab, int con)
1528 if (tab->con[con].is_zero)
1530 if (tab->con[con].is_redundant)
1532 if (!tab->con[con].is_row)
1533 return tab->con[con].index < tab->n_dead;
1535 row = tab->con[con].index;
1537 return isl_int_is_zero(tab->mat->row[row][1]) &&
1538 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1539 tab->n_col - tab->n_dead) == -1;
1542 /* Return the minimial value of the affine expression "f" with denominator
1543 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
1544 * the expression cannot attain arbitrarily small values.
1545 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
1546 * The return value reflects the nature of the result (empty, unbounded,
1547 * minmimal value returned in *opt).
1549 enum isl_lp_result isl_tab_min(struct isl_ctx *ctx, struct isl_tab *tab,
1550 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom)
1553 enum isl_lp_result res = isl_lp_ok;
1554 struct isl_tab_var *var;
1557 return isl_lp_empty;
1559 r = add_row(ctx, tab, f);
1561 return isl_lp_error;
1563 isl_int_mul(tab->mat->row[var->index][0],
1564 tab->mat->row[var->index][0], denom);
1567 find_pivot(ctx, tab, var, var, -1, &row, &col);
1568 if (row == var->index) {
1569 res = isl_lp_unbounded;
1574 pivot(ctx, tab, row, col);
1576 if (drop_row(ctx, tab, var->index) < 0)
1577 return isl_lp_error;
1578 if (res == isl_lp_ok) {
1580 isl_int_set(*opt, tab->mat->row[var->index][1]);
1581 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
1583 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
1584 tab->mat->row[var->index][0]);
1589 int isl_tab_is_redundant(struct isl_ctx *ctx, struct isl_tab *tab, int con)
1596 if (tab->con[con].is_zero)
1598 if (tab->con[con].is_redundant)
1600 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
1603 /* Take a snapshot of the tableau that can be restored by s call to
1606 struct isl_tab_undo *isl_tab_snap(struct isl_ctx *ctx, struct isl_tab *tab)
1614 /* Undo the operation performed by isl_tab_relax.
1616 static void unrelax(struct isl_ctx *ctx,
1617 struct isl_tab *tab, struct isl_tab_var *var)
1619 if (!var->is_row && !max_is_manifestly_unbounded(ctx, tab, var))
1620 to_row(ctx, tab, var, 1);
1623 isl_int_sub(tab->mat->row[var->index][1],
1624 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
1628 for (i = 0; i < tab->n_row; ++i) {
1629 if (isl_int_is_zero(tab->mat->row[i][2 + var->index]))
1631 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
1632 tab->mat->row[i][2 + var->index]);
1638 static void perform_undo(struct isl_ctx *ctx, struct isl_tab *tab,
1639 struct isl_tab_undo *undo)
1641 switch(undo->type) {
1642 case isl_tab_undo_empty:
1645 case isl_tab_undo_nonneg:
1646 undo->var->is_nonneg = 0;
1648 case isl_tab_undo_redundant:
1649 undo->var->is_redundant = 0;
1652 case isl_tab_undo_zero:
1653 undo->var->is_zero = 0;
1656 case isl_tab_undo_allocate:
1657 if (!undo->var->is_row) {
1658 if (max_is_manifestly_unbounded(ctx, tab, undo->var))
1659 to_row(ctx, tab, undo->var, -1);
1661 to_row(ctx, tab, undo->var, 1);
1663 drop_row(ctx, tab, undo->var->index);
1665 case isl_tab_undo_relax:
1666 unrelax(ctx, tab, undo->var);
1671 /* Return the tableau to the state it was in when the snapshot "snap"
1674 int isl_tab_rollback(struct isl_ctx *ctx, struct isl_tab *tab,
1675 struct isl_tab_undo *snap)
1677 struct isl_tab_undo *undo, *next;
1682 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
1686 perform_undo(ctx, tab, undo);
1695 /* The given row "row" represents an inequality violated by all
1696 * points in the tableau. Check for some special cases of such
1697 * separating constraints.
1698 * In particular, if the row has been reduced to the constant -1,
1699 * then we know the inequality is adjacent (but opposite) to
1700 * an equality in the tableau.
1701 * If the row has been reduced to r = -1 -r', with r' an inequality
1702 * of the tableau, then the inequality is adjacent (but opposite)
1703 * to the inequality r'.
1705 static enum isl_ineq_type separation_type(struct isl_ctx *ctx,
1706 struct isl_tab *tab, unsigned row)
1711 return isl_ineq_separate;
1713 if (!isl_int_is_one(tab->mat->row[row][0]))
1714 return isl_ineq_separate;
1715 if (!isl_int_is_negone(tab->mat->row[row][1]))
1716 return isl_ineq_separate;
1718 pos = isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
1719 tab->n_col - tab->n_dead);
1721 return isl_ineq_adj_eq;
1723 if (!isl_int_is_negone(tab->mat->row[row][2 + tab->n_dead + pos]))
1724 return isl_ineq_separate;
1726 pos = isl_seq_first_non_zero(
1727 tab->mat->row[row] + 2 + tab->n_dead + pos + 1,
1728 tab->n_col - tab->n_dead - pos - 1);
1730 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
1733 /* Check the effect of inequality "ineq" on the tableau "tab".
1735 * isl_ineq_redundant: satisfied by all points in the tableau
1736 * isl_ineq_separate: satisfied by no point in the tableau
1737 * isl_ineq_cut: satisfied by some by not all points
1738 * isl_ineq_adj_eq: adjacent to an equality
1739 * isl_ineq_adj_ineq: adjacent to an inequality.
1741 enum isl_ineq_type isl_tab_ineq_type(struct isl_ctx *ctx, struct isl_tab *tab,
1744 enum isl_ineq_type type = isl_ineq_error;
1745 struct isl_tab_undo *snap = NULL;
1750 return isl_ineq_error;
1752 if (extend_cons(ctx, tab, 1) < 0)
1753 return isl_ineq_error;
1755 snap = isl_tab_snap(ctx, tab);
1757 con = add_row(ctx, tab, ineq);
1761 row = tab->con[con].index;
1762 if (is_redundant(ctx, tab, row))
1763 type = isl_ineq_redundant;
1764 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
1766 isl_int_abs_ge(tab->mat->row[row][1],
1767 tab->mat->row[row][0]))) {
1768 if (at_least_zero(ctx, tab, &tab->con[con]))
1769 type = isl_ineq_cut;
1771 type = separation_type(ctx, tab, row);
1772 } else if (tab->rational ? (sign_of_min(ctx, tab, &tab->con[con]) < 0)
1773 : min_at_most_neg_one(ctx, tab, &tab->con[con]))
1774 type = isl_ineq_cut;
1776 type = isl_ineq_redundant;
1778 if (isl_tab_rollback(ctx, tab, snap))
1779 return isl_ineq_error;
1782 isl_tab_rollback(ctx, tab, snap);
1783 return isl_ineq_error;
1786 void isl_tab_dump(struct isl_ctx *ctx, struct isl_tab *tab,
1787 FILE *out, int indent)
1793 fprintf(out, "%*snull tab\n", indent, "");
1796 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
1797 tab->n_redundant, tab->n_dead);
1799 fprintf(out, ", rational");
1801 fprintf(out, ", empty");
1803 fprintf(out, "%*s[", indent, "");
1804 for (i = 0; i < tab->n_var; ++i) {
1807 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
1809 tab->var[i].is_zero ? " [=0]" :
1810 tab->var[i].is_redundant ? " [R]" : "");
1812 fprintf(out, "]\n");
1813 fprintf(out, "%*s[", indent, "");
1814 for (i = 0; i < tab->n_con; ++i) {
1817 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
1819 tab->con[i].is_zero ? " [=0]" :
1820 tab->con[i].is_redundant ? " [R]" : "");
1822 fprintf(out, "]\n");
1823 fprintf(out, "%*s[", indent, "");
1824 for (i = 0; i < tab->n_row; ++i) {
1827 fprintf(out, "r%d: %d%s", i, tab->row_var[i],
1828 var_from_row(ctx, tab, i)->is_nonneg ? " [>=0]" : "");
1830 fprintf(out, "]\n");
1831 fprintf(out, "%*s[", indent, "");
1832 for (i = 0; i < tab->n_col; ++i) {
1835 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
1836 var_from_col(ctx, tab, i)->is_nonneg ? " [>=0]" : "");
1838 fprintf(out, "]\n");
1839 r = tab->mat->n_row;
1840 tab->mat->n_row = tab->n_row;
1841 c = tab->mat->n_col;
1842 tab->mat->n_col = 2 + tab->n_col;
1843 isl_mat_dump(ctx, tab->mat, out, indent);
1844 tab->mat->n_row = r;
1845 tab->mat->n_col = c;