2 #include "isl_map_private.h"
7 * The implementation of tableaus in this file was inspired by Section 8
8 * of David Detlefs, Greg Nelson and James B. Saxe, "Simplify: a theorem
9 * prover for program checking".
12 struct isl_tab *isl_tab_alloc(struct isl_ctx *ctx,
13 unsigned n_row, unsigned n_var, unsigned M)
19 tab = isl_calloc_type(ctx, struct isl_tab);
22 tab->mat = isl_mat_alloc(ctx, n_row, off + n_var);
25 tab->var = isl_alloc_array(ctx, struct isl_tab_var, n_var);
28 tab->con = isl_alloc_array(ctx, struct isl_tab_var, n_row);
31 tab->col_var = isl_alloc_array(ctx, int, n_var);
34 tab->row_var = isl_alloc_array(ctx, int, n_row);
37 for (i = 0; i < n_var; ++i) {
38 tab->var[i].index = i;
39 tab->var[i].is_row = 0;
40 tab->var[i].is_nonneg = 0;
41 tab->var[i].is_zero = 0;
42 tab->var[i].is_redundant = 0;
43 tab->var[i].frozen = 0;
44 tab->var[i].negated = 0;
63 tab->bottom.type = isl_tab_undo_bottom;
64 tab->bottom.next = NULL;
65 tab->top = &tab->bottom;
77 int isl_tab_extend_cons(struct isl_tab *tab, unsigned n_new)
79 unsigned off = 2 + tab->M;
84 if (tab->max_con < tab->n_con + n_new) {
85 struct isl_tab_var *con;
87 con = isl_realloc_array(tab->mat->ctx, tab->con,
88 struct isl_tab_var, tab->max_con + n_new);
92 tab->max_con += n_new;
94 if (tab->mat->n_row < tab->n_row + n_new) {
97 tab->mat = isl_mat_extend(tab->mat,
98 tab->n_row + n_new, off + tab->n_col);
101 row_var = isl_realloc_array(tab->mat->ctx, tab->row_var,
102 int, tab->mat->n_row);
105 tab->row_var = row_var;
107 enum isl_tab_row_sign *s;
108 s = isl_realloc_array(tab->mat->ctx, tab->row_sign,
109 enum isl_tab_row_sign, tab->mat->n_row);
118 /* Make room for at least n_new extra variables.
119 * Return -1 if anything went wrong.
121 int isl_tab_extend_vars(struct isl_tab *tab, unsigned n_new)
123 struct isl_tab_var *var;
124 unsigned off = 2 + tab->M;
126 if (tab->max_var < tab->n_var + n_new) {
127 var = isl_realloc_array(tab->mat->ctx, tab->var,
128 struct isl_tab_var, tab->n_var + n_new);
132 tab->max_var += n_new;
135 if (tab->mat->n_col < off + tab->n_col + n_new) {
138 tab->mat = isl_mat_extend(tab->mat,
139 tab->mat->n_row, off + tab->n_col + n_new);
142 p = isl_realloc_array(tab->mat->ctx, tab->col_var,
143 int, tab->n_col + n_new);
152 struct isl_tab *isl_tab_extend(struct isl_tab *tab, unsigned n_new)
154 if (isl_tab_extend_cons(tab, n_new) >= 0)
161 static void free_undo(struct isl_tab *tab)
163 struct isl_tab_undo *undo, *next;
165 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
172 void isl_tab_free(struct isl_tab *tab)
177 isl_mat_free(tab->mat);
178 isl_vec_free(tab->dual);
179 isl_basic_set_free(tab->bset);
185 isl_mat_free(tab->samples);
186 isl_mat_free(tab->basis);
190 struct isl_tab *isl_tab_dup(struct isl_tab *tab)
200 dup = isl_calloc_type(tab->ctx, struct isl_tab);
203 dup->mat = isl_mat_dup(tab->mat);
206 dup->var = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->max_var);
209 for (i = 0; i < tab->n_var; ++i)
210 dup->var[i] = tab->var[i];
211 dup->con = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->max_con);
214 for (i = 0; i < tab->n_con; ++i)
215 dup->con[i] = tab->con[i];
216 dup->col_var = isl_alloc_array(tab->ctx, int, tab->mat->n_col - off);
219 for (i = 0; i < tab->n_col; ++i)
220 dup->col_var[i] = tab->col_var[i];
221 dup->row_var = isl_alloc_array(tab->ctx, int, tab->mat->n_row);
224 for (i = 0; i < tab->n_row; ++i)
225 dup->row_var[i] = tab->row_var[i];
227 dup->row_sign = isl_alloc_array(tab->ctx, enum isl_tab_row_sign,
231 for (i = 0; i < tab->n_row; ++i)
232 dup->row_sign[i] = tab->row_sign[i];
235 dup->samples = isl_mat_dup(tab->samples);
238 dup->n_sample = tab->n_sample;
239 dup->n_outside = tab->n_outside;
241 dup->n_row = tab->n_row;
242 dup->n_con = tab->n_con;
243 dup->n_eq = tab->n_eq;
244 dup->max_con = tab->max_con;
245 dup->n_col = tab->n_col;
246 dup->n_var = tab->n_var;
247 dup->max_var = tab->max_var;
248 dup->n_param = tab->n_param;
249 dup->n_div = tab->n_div;
250 dup->n_dead = tab->n_dead;
251 dup->n_redundant = tab->n_redundant;
252 dup->rational = tab->rational;
253 dup->empty = tab->empty;
257 dup->bottom.type = isl_tab_undo_bottom;
258 dup->bottom.next = NULL;
259 dup->top = &dup->bottom;
261 dup->n_zero = tab->n_zero;
262 dup->n_unbounded = tab->n_unbounded;
263 dup->basis = isl_mat_dup(tab->basis);
271 /* Construct the coefficient matrix of the product tableau
273 * mat{1,2} is the coefficient matrix of tableau {1,2}
274 * row{1,2} is the number of rows in tableau {1,2}
275 * col{1,2} is the number of columns in tableau {1,2}
276 * off is the offset to the coefficient column (skipping the
277 * denominator, the constant term and the big parameter if any)
278 * r{1,2} is the number of redundant rows in tableau {1,2}
279 * d{1,2} is the number of dead columns in tableau {1,2}
281 * The order of the rows and columns in the result is as explained
282 * in isl_tab_product.
284 static struct isl_mat *tab_mat_product(struct isl_mat *mat1,
285 struct isl_mat *mat2, unsigned row1, unsigned row2,
286 unsigned col1, unsigned col2,
287 unsigned off, unsigned r1, unsigned r2, unsigned d1, unsigned d2)
290 struct isl_mat *prod;
293 prod = isl_mat_alloc(mat1->ctx, mat1->n_row + mat2->n_row,
297 for (i = 0; i < r1; ++i) {
298 isl_seq_cpy(prod->row[n + i], mat1->row[i], off + d1);
299 isl_seq_clr(prod->row[n + i] + off + d1, d2);
300 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
301 mat1->row[i] + off + d1, col1 - d1);
302 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
306 for (i = 0; i < r2; ++i) {
307 isl_seq_cpy(prod->row[n + i], mat2->row[i], off);
308 isl_seq_clr(prod->row[n + i] + off, d1);
309 isl_seq_cpy(prod->row[n + i] + off + d1,
310 mat2->row[i] + off, d2);
311 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
312 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
313 mat2->row[i] + off + d2, col2 - d2);
317 for (i = 0; i < row1 - r1; ++i) {
318 isl_seq_cpy(prod->row[n + i], mat1->row[r1 + i], off + d1);
319 isl_seq_clr(prod->row[n + i] + off + d1, d2);
320 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
321 mat1->row[r1 + i] + off + d1, col1 - d1);
322 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
326 for (i = 0; i < row2 - r2; ++i) {
327 isl_seq_cpy(prod->row[n + i], mat2->row[r2 + i], off);
328 isl_seq_clr(prod->row[n + i] + off, d1);
329 isl_seq_cpy(prod->row[n + i] + off + d1,
330 mat2->row[r2 + i] + off, d2);
331 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
332 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
333 mat2->row[r2 + i] + off + d2, col2 - d2);
339 /* Update the row or column index of a variable that corresponds
340 * to a variable in the first input tableau.
342 static void update_index1(struct isl_tab_var *var,
343 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
345 if (var->index == -1)
347 if (var->is_row && var->index >= r1)
349 if (!var->is_row && var->index >= d1)
353 /* Update the row or column index of a variable that corresponds
354 * to a variable in the second input tableau.
356 static void update_index2(struct isl_tab_var *var,
357 unsigned row1, unsigned col1,
358 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
360 if (var->index == -1)
375 /* Create a tableau that represents the Cartesian product of the sets
376 * represented by tableaus tab1 and tab2.
377 * The order of the rows in the product is
378 * - redundant rows of tab1
379 * - redundant rows of tab2
380 * - non-redundant rows of tab1
381 * - non-redundant rows of tab2
382 * The order of the columns is
385 * - coefficient of big parameter, if any
386 * - dead columns of tab1
387 * - dead columns of tab2
388 * - live columns of tab1
389 * - live columns of tab2
390 * The order of the variables and the constraints is a concatenation
391 * of order in the two input tableaus.
393 struct isl_tab *isl_tab_product(struct isl_tab *tab1, struct isl_tab *tab2)
396 struct isl_tab *prod;
398 unsigned r1, r2, d1, d2;
403 isl_assert(tab1->mat->ctx, tab1->M == tab2->M, return NULL);
404 isl_assert(tab1->mat->ctx, tab1->rational == tab2->rational, return NULL);
405 isl_assert(tab1->mat->ctx, !tab1->row_sign, return NULL);
406 isl_assert(tab1->mat->ctx, !tab2->row_sign, return NULL);
407 isl_assert(tab1->mat->ctx, tab1->n_param == 0, return NULL);
408 isl_assert(tab1->mat->ctx, tab2->n_param == 0, return NULL);
409 isl_assert(tab1->mat->ctx, tab1->n_div == 0, return NULL);
410 isl_assert(tab1->mat->ctx, tab2->n_div == 0, return NULL);
413 r1 = tab1->n_redundant;
414 r2 = tab2->n_redundant;
417 prod = isl_calloc_type(tab1->mat->ctx, struct isl_tab);
420 prod->mat = tab_mat_product(tab1->mat, tab2->mat,
421 tab1->n_row, tab2->n_row,
422 tab1->n_col, tab2->n_col, off, r1, r2, d1, d2);
425 prod->var = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
426 tab1->max_var + tab2->max_var);
429 for (i = 0; i < tab1->n_var; ++i) {
430 prod->var[i] = tab1->var[i];
431 update_index1(&prod->var[i], r1, r2, d1, d2);
433 for (i = 0; i < tab2->n_var; ++i) {
434 prod->var[tab1->n_var + i] = tab2->var[i];
435 update_index2(&prod->var[tab1->n_var + i],
436 tab1->n_row, tab1->n_col,
439 prod->con = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
440 tab1->max_con + tab2->max_con);
443 for (i = 0; i < tab1->n_con; ++i) {
444 prod->con[i] = tab1->con[i];
445 update_index1(&prod->con[i], r1, r2, d1, d2);
447 for (i = 0; i < tab2->n_con; ++i) {
448 prod->con[tab1->n_con + i] = tab2->con[i];
449 update_index2(&prod->con[tab1->n_con + i],
450 tab1->n_row, tab1->n_col,
453 prod->col_var = isl_alloc_array(tab1->mat->ctx, int,
454 tab1->n_col + tab2->n_col);
457 for (i = 0; i < tab1->n_col; ++i) {
458 int pos = i < d1 ? i : i + d2;
459 prod->col_var[pos] = tab1->col_var[i];
461 for (i = 0; i < tab2->n_col; ++i) {
462 int pos = i < d2 ? d1 + i : tab1->n_col + i;
463 int t = tab2->col_var[i];
468 prod->col_var[pos] = t;
470 prod->row_var = isl_alloc_array(tab1->mat->ctx, int,
471 tab1->mat->n_row + tab2->mat->n_row);
474 for (i = 0; i < tab1->n_row; ++i) {
475 int pos = i < r1 ? i : i + r2;
476 prod->row_var[pos] = tab1->row_var[i];
478 for (i = 0; i < tab2->n_row; ++i) {
479 int pos = i < r2 ? r1 + i : tab1->n_row + i;
480 int t = tab2->row_var[i];
485 prod->row_var[pos] = t;
487 prod->samples = NULL;
488 prod->n_row = tab1->n_row + tab2->n_row;
489 prod->n_con = tab1->n_con + tab2->n_con;
491 prod->max_con = tab1->max_con + tab2->max_con;
492 prod->n_col = tab1->n_col + tab2->n_col;
493 prod->n_var = tab1->n_var + tab2->n_var;
494 prod->max_var = tab1->max_var + tab2->max_var;
497 prod->n_dead = tab1->n_dead + tab2->n_dead;
498 prod->n_redundant = tab1->n_redundant + tab2->n_redundant;
499 prod->rational = tab1->rational;
500 prod->empty = tab1->empty || tab2->empty;
504 prod->bottom.type = isl_tab_undo_bottom;
505 prod->bottom.next = NULL;
506 prod->top = &prod->bottom;
509 prod->n_unbounded = 0;
518 static struct isl_tab_var *var_from_index(struct isl_tab *tab, int i)
523 return &tab->con[~i];
526 struct isl_tab_var *isl_tab_var_from_row(struct isl_tab *tab, int i)
528 return var_from_index(tab, tab->row_var[i]);
531 static struct isl_tab_var *var_from_col(struct isl_tab *tab, int i)
533 return var_from_index(tab, tab->col_var[i]);
536 /* Check if there are any upper bounds on column variable "var",
537 * i.e., non-negative rows where var appears with a negative coefficient.
538 * Return 1 if there are no such bounds.
540 static int max_is_manifestly_unbounded(struct isl_tab *tab,
541 struct isl_tab_var *var)
544 unsigned off = 2 + tab->M;
548 for (i = tab->n_redundant; i < tab->n_row; ++i) {
549 if (!isl_int_is_neg(tab->mat->row[i][off + var->index]))
551 if (isl_tab_var_from_row(tab, i)->is_nonneg)
557 /* Check if there are any lower bounds on column variable "var",
558 * i.e., non-negative rows where var appears with a positive coefficient.
559 * Return 1 if there are no such bounds.
561 static int min_is_manifestly_unbounded(struct isl_tab *tab,
562 struct isl_tab_var *var)
565 unsigned off = 2 + tab->M;
569 for (i = tab->n_redundant; i < tab->n_row; ++i) {
570 if (!isl_int_is_pos(tab->mat->row[i][off + var->index]))
572 if (isl_tab_var_from_row(tab, i)->is_nonneg)
578 static int row_cmp(struct isl_tab *tab, int r1, int r2, int c, isl_int t)
580 unsigned off = 2 + tab->M;
584 isl_int_mul(t, tab->mat->row[r1][2], tab->mat->row[r2][off+c]);
585 isl_int_submul(t, tab->mat->row[r2][2], tab->mat->row[r1][off+c]);
590 isl_int_mul(t, tab->mat->row[r1][1], tab->mat->row[r2][off + c]);
591 isl_int_submul(t, tab->mat->row[r2][1], tab->mat->row[r1][off + c]);
592 return isl_int_sgn(t);
595 /* Given the index of a column "c", return the index of a row
596 * that can be used to pivot the column in, with either an increase
597 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
598 * If "var" is not NULL, then the row returned will be different from
599 * the one associated with "var".
601 * Each row in the tableau is of the form
603 * x_r = a_r0 + \sum_i a_ri x_i
605 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
606 * impose any limit on the increase or decrease in the value of x_c
607 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
608 * for the row with the smallest (most stringent) such bound.
609 * Note that the common denominator of each row drops out of the fraction.
610 * To check if row j has a smaller bound than row r, i.e.,
611 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
612 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
613 * where -sign(a_jc) is equal to "sgn".
615 static int pivot_row(struct isl_tab *tab,
616 struct isl_tab_var *var, int sgn, int c)
620 unsigned off = 2 + tab->M;
624 for (j = tab->n_redundant; j < tab->n_row; ++j) {
625 if (var && j == var->index)
627 if (!isl_tab_var_from_row(tab, j)->is_nonneg)
629 if (sgn * isl_int_sgn(tab->mat->row[j][off + c]) >= 0)
635 tsgn = sgn * row_cmp(tab, r, j, c, t);
636 if (tsgn < 0 || (tsgn == 0 &&
637 tab->row_var[j] < tab->row_var[r]))
644 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
645 * (sgn < 0) the value of row variable var.
646 * If not NULL, then skip_var is a row variable that should be ignored
647 * while looking for a pivot row. It is usually equal to var.
649 * As the given row in the tableau is of the form
651 * x_r = a_r0 + \sum_i a_ri x_i
653 * we need to find a column such that the sign of a_ri is equal to "sgn"
654 * (such that an increase in x_i will have the desired effect) or a
655 * column with a variable that may attain negative values.
656 * If a_ri is positive, then we need to move x_i in the same direction
657 * to obtain the desired effect. Otherwise, x_i has to move in the
658 * opposite direction.
660 static void find_pivot(struct isl_tab *tab,
661 struct isl_tab_var *var, struct isl_tab_var *skip_var,
662 int sgn, int *row, int *col)
669 isl_assert(tab->mat->ctx, var->is_row, return);
670 tr = tab->mat->row[var->index] + 2 + tab->M;
673 for (j = tab->n_dead; j < tab->n_col; ++j) {
674 if (isl_int_is_zero(tr[j]))
676 if (isl_int_sgn(tr[j]) != sgn &&
677 var_from_col(tab, j)->is_nonneg)
679 if (c < 0 || tab->col_var[j] < tab->col_var[c])
685 sgn *= isl_int_sgn(tr[c]);
686 r = pivot_row(tab, skip_var, sgn, c);
687 *row = r < 0 ? var->index : r;
691 /* Return 1 if row "row" represents an obviously redundant inequality.
693 * - it represents an inequality or a variable
694 * - that is the sum of a non-negative sample value and a positive
695 * combination of zero or more non-negative variables.
697 int isl_tab_row_is_redundant(struct isl_tab *tab, int row)
700 unsigned off = 2 + tab->M;
702 if (tab->row_var[row] < 0 && !isl_tab_var_from_row(tab, row)->is_nonneg)
705 if (isl_int_is_neg(tab->mat->row[row][1]))
707 if (tab->M && isl_int_is_neg(tab->mat->row[row][2]))
710 for (i = tab->n_dead; i < tab->n_col; ++i) {
711 if (isl_int_is_zero(tab->mat->row[row][off + i]))
713 if (isl_int_is_neg(tab->mat->row[row][off + i]))
715 if (!var_from_col(tab, i)->is_nonneg)
721 static void swap_rows(struct isl_tab *tab, int row1, int row2)
724 t = tab->row_var[row1];
725 tab->row_var[row1] = tab->row_var[row2];
726 tab->row_var[row2] = t;
727 isl_tab_var_from_row(tab, row1)->index = row1;
728 isl_tab_var_from_row(tab, row2)->index = row2;
729 tab->mat = isl_mat_swap_rows(tab->mat, row1, row2);
733 t = tab->row_sign[row1];
734 tab->row_sign[row1] = tab->row_sign[row2];
735 tab->row_sign[row2] = t;
738 static void push_union(struct isl_tab *tab,
739 enum isl_tab_undo_type type, union isl_tab_undo_val u)
741 struct isl_tab_undo *undo;
746 undo = isl_alloc_type(tab->mat->ctx, struct isl_tab_undo);
754 undo->next = tab->top;
758 void isl_tab_push_var(struct isl_tab *tab,
759 enum isl_tab_undo_type type, struct isl_tab_var *var)
761 union isl_tab_undo_val u;
763 u.var_index = tab->row_var[var->index];
765 u.var_index = tab->col_var[var->index];
766 push_union(tab, type, u);
769 void isl_tab_push(struct isl_tab *tab, enum isl_tab_undo_type type)
771 union isl_tab_undo_val u = { 0 };
772 push_union(tab, type, u);
775 /* Push a record on the undo stack describing the current basic
776 * variables, so that the this state can be restored during rollback.
778 void isl_tab_push_basis(struct isl_tab *tab)
781 union isl_tab_undo_val u;
783 u.col_var = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
789 for (i = 0; i < tab->n_col; ++i)
790 u.col_var[i] = tab->col_var[i];
791 push_union(tab, isl_tab_undo_saved_basis, u);
794 struct isl_tab *isl_tab_init_samples(struct isl_tab *tab)
801 tab->samples = isl_mat_alloc(tab->mat->ctx, 1, 1 + tab->n_var);
810 struct isl_tab *isl_tab_add_sample(struct isl_tab *tab,
811 __isl_take isl_vec *sample)
816 tab->samples = isl_mat_extend(tab->samples,
817 tab->n_sample + 1, tab->samples->n_col);
821 isl_seq_cpy(tab->samples->row[tab->n_sample], sample->el, sample->size);
822 isl_vec_free(sample);
827 isl_vec_free(sample);
832 struct isl_tab *isl_tab_drop_sample(struct isl_tab *tab, int s)
834 if (s != tab->n_outside)
835 isl_mat_swap_rows(tab->samples, tab->n_outside, s);
837 isl_tab_push(tab, isl_tab_undo_drop_sample);
842 /* Mark row with index "row" as being redundant.
843 * If we may need to undo the operation or if the row represents
844 * a variable of the original problem, the row is kept,
845 * but no longer considered when looking for a pivot row.
846 * Otherwise, the row is simply removed.
848 * The row may be interchanged with some other row. If it
849 * is interchanged with a later row, return 1. Otherwise return 0.
850 * If the rows are checked in order in the calling function,
851 * then a return value of 1 means that the row with the given
852 * row number may now contain a different row that hasn't been checked yet.
854 int isl_tab_mark_redundant(struct isl_tab *tab, int row)
856 struct isl_tab_var *var = isl_tab_var_from_row(tab, row);
857 var->is_redundant = 1;
858 isl_assert(tab->mat->ctx, row >= tab->n_redundant, return -1);
859 if (tab->need_undo || tab->row_var[row] >= 0) {
860 if (tab->row_var[row] >= 0 && !var->is_nonneg) {
862 isl_tab_push_var(tab, isl_tab_undo_nonneg, var);
864 if (row != tab->n_redundant)
865 swap_rows(tab, row, tab->n_redundant);
866 isl_tab_push_var(tab, isl_tab_undo_redundant, var);
870 if (row != tab->n_row - 1)
871 swap_rows(tab, row, tab->n_row - 1);
872 isl_tab_var_from_row(tab, tab->n_row - 1)->index = -1;
878 struct isl_tab *isl_tab_mark_empty(struct isl_tab *tab)
880 if (!tab->empty && tab->need_undo)
881 isl_tab_push(tab, isl_tab_undo_empty);
886 /* Update the rows signs after a pivot of "row" and "col", with "row_sgn"
887 * the original sign of the pivot element.
888 * We only keep track of row signs during PILP solving and in this case
889 * we only pivot a row with negative sign (meaning the value is always
890 * non-positive) using a positive pivot element.
892 * For each row j, the new value of the parametric constant is equal to
894 * a_j0 - a_jc a_r0/a_rc
896 * where a_j0 is the original parametric constant, a_rc is the pivot element,
897 * a_r0 is the parametric constant of the pivot row and a_jc is the
898 * pivot column entry of the row j.
899 * Since a_r0 is non-positive and a_rc is positive, the sign of row j
900 * remains the same if a_jc has the same sign as the row j or if
901 * a_jc is zero. In all other cases, we reset the sign to "unknown".
903 static void update_row_sign(struct isl_tab *tab, int row, int col, int row_sgn)
906 struct isl_mat *mat = tab->mat;
907 unsigned off = 2 + tab->M;
912 if (tab->row_sign[row] == 0)
914 isl_assert(mat->ctx, row_sgn > 0, return);
915 isl_assert(mat->ctx, tab->row_sign[row] == isl_tab_row_neg, return);
916 tab->row_sign[row] = isl_tab_row_pos;
917 for (i = 0; i < tab->n_row; ++i) {
921 s = isl_int_sgn(mat->row[i][off + col]);
924 if (!tab->row_sign[i])
926 if (s < 0 && tab->row_sign[i] == isl_tab_row_neg)
928 if (s > 0 && tab->row_sign[i] == isl_tab_row_pos)
930 tab->row_sign[i] = isl_tab_row_unknown;
934 /* Given a row number "row" and a column number "col", pivot the tableau
935 * such that the associated variables are interchanged.
936 * The given row in the tableau expresses
938 * x_r = a_r0 + \sum_i a_ri x_i
942 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
944 * Substituting this equality into the other rows
946 * x_j = a_j0 + \sum_i a_ji x_i
948 * with a_jc \ne 0, we obtain
950 * 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
957 * where i is any other column and j is any other row,
958 * is therefore transformed into
960 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
961 * 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)
963 * The transformation is performed along the following steps
968 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
971 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
972 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
974 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
975 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
977 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
978 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
980 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
981 * 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)
984 void isl_tab_pivot(struct isl_tab *tab, int row, int col)
989 struct isl_mat *mat = tab->mat;
990 struct isl_tab_var *var;
991 unsigned off = 2 + tab->M;
993 isl_int_swap(mat->row[row][0], mat->row[row][off + col]);
994 sgn = isl_int_sgn(mat->row[row][0]);
996 isl_int_neg(mat->row[row][0], mat->row[row][0]);
997 isl_int_neg(mat->row[row][off + col], mat->row[row][off + col]);
999 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1000 if (j == off - 1 + col)
1002 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
1004 if (!isl_int_is_one(mat->row[row][0]))
1005 isl_seq_normalize(mat->ctx, mat->row[row], off + tab->n_col);
1006 for (i = 0; i < tab->n_row; ++i) {
1009 if (isl_int_is_zero(mat->row[i][off + col]))
1011 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
1012 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1013 if (j == off - 1 + col)
1015 isl_int_mul(mat->row[i][1 + j],
1016 mat->row[i][1 + j], mat->row[row][0]);
1017 isl_int_addmul(mat->row[i][1 + j],
1018 mat->row[i][off + col], mat->row[row][1 + j]);
1020 isl_int_mul(mat->row[i][off + col],
1021 mat->row[i][off + col], mat->row[row][off + col]);
1022 if (!isl_int_is_one(mat->row[i][0]))
1023 isl_seq_normalize(mat->ctx, mat->row[i], off + tab->n_col);
1025 t = tab->row_var[row];
1026 tab->row_var[row] = tab->col_var[col];
1027 tab->col_var[col] = t;
1028 var = isl_tab_var_from_row(tab, row);
1031 var = var_from_col(tab, col);
1034 update_row_sign(tab, row, col, sgn);
1037 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1038 if (isl_int_is_zero(mat->row[i][off + col]))
1040 if (!isl_tab_var_from_row(tab, i)->frozen &&
1041 isl_tab_row_is_redundant(tab, i))
1042 if (isl_tab_mark_redundant(tab, i))
1047 /* If "var" represents a column variable, then pivot is up (sgn > 0)
1048 * or down (sgn < 0) to a row. The variable is assumed not to be
1049 * unbounded in the specified direction.
1050 * If sgn = 0, then the variable is unbounded in both directions,
1051 * and we pivot with any row we can find.
1053 static void to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign)
1056 unsigned off = 2 + tab->M;
1062 for (r = tab->n_redundant; r < tab->n_row; ++r)
1063 if (!isl_int_is_zero(tab->mat->row[r][off+var->index]))
1065 isl_assert(tab->mat->ctx, r < tab->n_row, return);
1067 r = pivot_row(tab, NULL, sign, var->index);
1068 isl_assert(tab->mat->ctx, r >= 0, return);
1071 isl_tab_pivot(tab, r, var->index);
1074 static void check_table(struct isl_tab *tab)
1080 for (i = 0; i < tab->n_row; ++i) {
1081 if (!isl_tab_var_from_row(tab, i)->is_nonneg)
1083 assert(!isl_int_is_neg(tab->mat->row[i][1]));
1087 /* Return the sign of the maximal value of "var".
1088 * If the sign is not negative, then on return from this function,
1089 * the sample value will also be non-negative.
1091 * If "var" is manifestly unbounded wrt positive values, we are done.
1092 * Otherwise, we pivot the variable up to a row if needed
1093 * Then we continue pivoting down until either
1094 * - no more down pivots can be performed
1095 * - the sample value is positive
1096 * - the variable is pivoted into a manifestly unbounded column
1098 static int sign_of_max(struct isl_tab *tab, struct isl_tab_var *var)
1102 if (max_is_manifestly_unbounded(tab, var))
1104 to_row(tab, var, 1);
1105 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
1106 find_pivot(tab, var, var, 1, &row, &col);
1108 return isl_int_sgn(tab->mat->row[var->index][1]);
1109 isl_tab_pivot(tab, row, col);
1110 if (!var->is_row) /* manifestly unbounded */
1116 static int row_is_neg(struct isl_tab *tab, int row)
1119 return isl_int_is_neg(tab->mat->row[row][1]);
1120 if (isl_int_is_pos(tab->mat->row[row][2]))
1122 if (isl_int_is_neg(tab->mat->row[row][2]))
1124 return isl_int_is_neg(tab->mat->row[row][1]);
1127 static int row_sgn(struct isl_tab *tab, int row)
1130 return isl_int_sgn(tab->mat->row[row][1]);
1131 if (!isl_int_is_zero(tab->mat->row[row][2]))
1132 return isl_int_sgn(tab->mat->row[row][2]);
1134 return isl_int_sgn(tab->mat->row[row][1]);
1137 /* Perform pivots until the row variable "var" has a non-negative
1138 * sample value or until no more upward pivots can be performed.
1139 * Return the sign of the sample value after the pivots have been
1142 static int restore_row(struct isl_tab *tab, struct isl_tab_var *var)
1146 while (row_is_neg(tab, var->index)) {
1147 find_pivot(tab, var, var, 1, &row, &col);
1150 isl_tab_pivot(tab, row, col);
1151 if (!var->is_row) /* manifestly unbounded */
1154 return row_sgn(tab, var->index);
1157 /* Perform pivots until we are sure that the row variable "var"
1158 * can attain non-negative values. After return from this
1159 * function, "var" is still a row variable, but its sample
1160 * value may not be non-negative, even if the function returns 1.
1162 static int at_least_zero(struct isl_tab *tab, struct isl_tab_var *var)
1166 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
1167 find_pivot(tab, var, var, 1, &row, &col);
1170 if (row == var->index) /* manifestly unbounded */
1172 isl_tab_pivot(tab, row, col);
1174 return !isl_int_is_neg(tab->mat->row[var->index][1]);
1177 /* Return a negative value if "var" can attain negative values.
1178 * Return a non-negative value otherwise.
1180 * If "var" is manifestly unbounded wrt negative values, we are done.
1181 * Otherwise, if var is in a column, we can pivot it down to a row.
1182 * Then we continue pivoting down until either
1183 * - the pivot would result in a manifestly unbounded column
1184 * => we don't perform the pivot, but simply return -1
1185 * - no more down pivots can be performed
1186 * - the sample value is negative
1187 * If the sample value becomes negative and the variable is supposed
1188 * to be nonnegative, then we undo the last pivot.
1189 * However, if the last pivot has made the pivoting variable
1190 * obviously redundant, then it may have moved to another row.
1191 * In that case we look for upward pivots until we reach a non-negative
1194 static int sign_of_min(struct isl_tab *tab, struct isl_tab_var *var)
1197 struct isl_tab_var *pivot_var = NULL;
1199 if (min_is_manifestly_unbounded(tab, var))
1203 row = pivot_row(tab, NULL, -1, col);
1204 pivot_var = var_from_col(tab, col);
1205 isl_tab_pivot(tab, row, col);
1206 if (var->is_redundant)
1208 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
1209 if (var->is_nonneg) {
1210 if (!pivot_var->is_redundant &&
1211 pivot_var->index == row)
1212 isl_tab_pivot(tab, row, col);
1214 restore_row(tab, var);
1219 if (var->is_redundant)
1221 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
1222 find_pivot(tab, var, var, -1, &row, &col);
1223 if (row == var->index)
1226 return isl_int_sgn(tab->mat->row[var->index][1]);
1227 pivot_var = var_from_col(tab, col);
1228 isl_tab_pivot(tab, row, col);
1229 if (var->is_redundant)
1232 if (pivot_var && var->is_nonneg) {
1233 /* pivot back to non-negative value */
1234 if (!pivot_var->is_redundant && pivot_var->index == row)
1235 isl_tab_pivot(tab, row, col);
1237 restore_row(tab, var);
1242 static int row_at_most_neg_one(struct isl_tab *tab, int row)
1245 if (isl_int_is_pos(tab->mat->row[row][2]))
1247 if (isl_int_is_neg(tab->mat->row[row][2]))
1250 return isl_int_is_neg(tab->mat->row[row][1]) &&
1251 isl_int_abs_ge(tab->mat->row[row][1],
1252 tab->mat->row[row][0]);
1255 /* Return 1 if "var" can attain values <= -1.
1256 * Return 0 otherwise.
1258 * The sample value of "var" is assumed to be non-negative when the
1259 * the function is called and will be made non-negative again before
1260 * the function returns.
1262 int isl_tab_min_at_most_neg_one(struct isl_tab *tab, struct isl_tab_var *var)
1265 struct isl_tab_var *pivot_var;
1267 if (min_is_manifestly_unbounded(tab, var))
1271 row = pivot_row(tab, NULL, -1, col);
1272 pivot_var = var_from_col(tab, col);
1273 isl_tab_pivot(tab, row, col);
1274 if (var->is_redundant)
1276 if (row_at_most_neg_one(tab, var->index)) {
1277 if (var->is_nonneg) {
1278 if (!pivot_var->is_redundant &&
1279 pivot_var->index == row)
1280 isl_tab_pivot(tab, row, col);
1282 restore_row(tab, var);
1287 if (var->is_redundant)
1290 find_pivot(tab, var, var, -1, &row, &col);
1291 if (row == var->index)
1295 pivot_var = var_from_col(tab, col);
1296 isl_tab_pivot(tab, row, col);
1297 if (var->is_redundant)
1299 } while (!row_at_most_neg_one(tab, var->index));
1300 if (var->is_nonneg) {
1301 /* pivot back to non-negative value */
1302 if (!pivot_var->is_redundant && pivot_var->index == row)
1303 isl_tab_pivot(tab, row, col);
1304 restore_row(tab, var);
1309 /* Return 1 if "var" can attain values >= 1.
1310 * Return 0 otherwise.
1312 static int at_least_one(struct isl_tab *tab, struct isl_tab_var *var)
1317 if (max_is_manifestly_unbounded(tab, var))
1319 to_row(tab, var, 1);
1320 r = tab->mat->row[var->index];
1321 while (isl_int_lt(r[1], r[0])) {
1322 find_pivot(tab, var, var, 1, &row, &col);
1324 return isl_int_ge(r[1], r[0]);
1325 if (row == var->index) /* manifestly unbounded */
1327 isl_tab_pivot(tab, row, col);
1332 static void swap_cols(struct isl_tab *tab, int col1, int col2)
1335 unsigned off = 2 + tab->M;
1336 t = tab->col_var[col1];
1337 tab->col_var[col1] = tab->col_var[col2];
1338 tab->col_var[col2] = t;
1339 var_from_col(tab, col1)->index = col1;
1340 var_from_col(tab, col2)->index = col2;
1341 tab->mat = isl_mat_swap_cols(tab->mat, off + col1, off + col2);
1344 /* Mark column with index "col" as representing a zero variable.
1345 * If we may need to undo the operation the column is kept,
1346 * but no longer considered.
1347 * Otherwise, the column is simply removed.
1349 * The column may be interchanged with some other column. If it
1350 * is interchanged with a later column, return 1. Otherwise return 0.
1351 * If the columns are checked in order in the calling function,
1352 * then a return value of 1 means that the column with the given
1353 * column number may now contain a different column that
1354 * hasn't been checked yet.
1356 int isl_tab_kill_col(struct isl_tab *tab, int col)
1358 var_from_col(tab, col)->is_zero = 1;
1359 if (tab->need_undo) {
1360 isl_tab_push_var(tab, isl_tab_undo_zero, var_from_col(tab, col));
1361 if (col != tab->n_dead)
1362 swap_cols(tab, col, tab->n_dead);
1366 if (col != tab->n_col - 1)
1367 swap_cols(tab, col, tab->n_col - 1);
1368 var_from_col(tab, tab->n_col - 1)->index = -1;
1374 /* Row variable "var" is non-negative and cannot attain any values
1375 * larger than zero. This means that the coefficients of the unrestricted
1376 * column variables are zero and that the coefficients of the non-negative
1377 * column variables are zero or negative.
1378 * Each of the non-negative variables with a negative coefficient can
1379 * then also be written as the negative sum of non-negative variables
1380 * and must therefore also be zero.
1382 static void close_row(struct isl_tab *tab, struct isl_tab_var *var)
1385 struct isl_mat *mat = tab->mat;
1386 unsigned off = 2 + tab->M;
1388 isl_assert(tab->mat->ctx, var->is_nonneg, return);
1391 isl_tab_push_var(tab, isl_tab_undo_zero, var);
1392 for (j = tab->n_dead; j < tab->n_col; ++j) {
1393 if (isl_int_is_zero(mat->row[var->index][off + j]))
1395 isl_assert(tab->mat->ctx,
1396 isl_int_is_neg(mat->row[var->index][off + j]), return);
1397 if (isl_tab_kill_col(tab, j))
1400 isl_tab_mark_redundant(tab, var->index);
1403 /* Add a constraint to the tableau and allocate a row for it.
1404 * Return the index into the constraint array "con".
1406 int isl_tab_allocate_con(struct isl_tab *tab)
1410 isl_assert(tab->mat->ctx, tab->n_row < tab->mat->n_row, return -1);
1411 isl_assert(tab->mat->ctx, tab->n_con < tab->max_con, return -1);
1414 tab->con[r].index = tab->n_row;
1415 tab->con[r].is_row = 1;
1416 tab->con[r].is_nonneg = 0;
1417 tab->con[r].is_zero = 0;
1418 tab->con[r].is_redundant = 0;
1419 tab->con[r].frozen = 0;
1420 tab->con[r].negated = 0;
1421 tab->row_var[tab->n_row] = ~r;
1425 isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]);
1430 /* Add a variable to the tableau and allocate a column for it.
1431 * Return the index into the variable array "var".
1433 int isl_tab_allocate_var(struct isl_tab *tab)
1437 unsigned off = 2 + tab->M;
1439 isl_assert(tab->mat->ctx, tab->n_col < tab->mat->n_col, return -1);
1440 isl_assert(tab->mat->ctx, tab->n_var < tab->max_var, return -1);
1443 tab->var[r].index = tab->n_col;
1444 tab->var[r].is_row = 0;
1445 tab->var[r].is_nonneg = 0;
1446 tab->var[r].is_zero = 0;
1447 tab->var[r].is_redundant = 0;
1448 tab->var[r].frozen = 0;
1449 tab->var[r].negated = 0;
1450 tab->col_var[tab->n_col] = r;
1452 for (i = 0; i < tab->n_row; ++i)
1453 isl_int_set_si(tab->mat->row[i][off + tab->n_col], 0);
1457 isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->var[r]);
1462 /* Add a row to the tableau. The row is given as an affine combination
1463 * of the original variables and needs to be expressed in terms of the
1466 * We add each term in turn.
1467 * If r = n/d_r is the current sum and we need to add k x, then
1468 * if x is a column variable, we increase the numerator of
1469 * this column by k d_r
1470 * if x = f/d_x is a row variable, then the new representation of r is
1472 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1473 * --- + --- = ------------------- = -------------------
1474 * d_r d_r d_r d_x/g m
1476 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1478 int isl_tab_add_row(struct isl_tab *tab, isl_int *line)
1484 unsigned off = 2 + tab->M;
1486 r = isl_tab_allocate_con(tab);
1492 row = tab->mat->row[tab->con[r].index];
1493 isl_int_set_si(row[0], 1);
1494 isl_int_set(row[1], line[0]);
1495 isl_seq_clr(row + 2, tab->M + tab->n_col);
1496 for (i = 0; i < tab->n_var; ++i) {
1497 if (tab->var[i].is_zero)
1499 if (tab->var[i].is_row) {
1501 row[0], tab->mat->row[tab->var[i].index][0]);
1502 isl_int_swap(a, row[0]);
1503 isl_int_divexact(a, row[0], a);
1505 row[0], tab->mat->row[tab->var[i].index][0]);
1506 isl_int_mul(b, b, line[1 + i]);
1507 isl_seq_combine(row + 1, a, row + 1,
1508 b, tab->mat->row[tab->var[i].index] + 1,
1509 1 + tab->M + tab->n_col);
1511 isl_int_addmul(row[off + tab->var[i].index],
1512 line[1 + i], row[0]);
1513 if (tab->M && i >= tab->n_param && i < tab->n_var - tab->n_div)
1514 isl_int_submul(row[2], line[1 + i], row[0]);
1516 isl_seq_normalize(tab->mat->ctx, row, off + tab->n_col);
1521 tab->row_sign[tab->con[r].index] = 0;
1526 static int drop_row(struct isl_tab *tab, int row)
1528 isl_assert(tab->mat->ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
1529 if (row != tab->n_row - 1)
1530 swap_rows(tab, row, tab->n_row - 1);
1536 static int drop_col(struct isl_tab *tab, int col)
1538 isl_assert(tab->mat->ctx, tab->col_var[col] == tab->n_var - 1, return -1);
1539 if (col != tab->n_col - 1)
1540 swap_cols(tab, col, tab->n_col - 1);
1546 /* Add inequality "ineq" and check if it conflicts with the
1547 * previously added constraints or if it is obviously redundant.
1549 struct isl_tab *isl_tab_add_ineq(struct isl_tab *tab, isl_int *ineq)
1557 struct isl_basic_set *bset = tab->bset;
1559 isl_assert(tab->mat->ctx, tab->n_eq == bset->n_eq, goto error);
1560 isl_assert(tab->mat->ctx,
1561 tab->n_con == bset->n_eq + bset->n_ineq, goto error);
1562 tab->bset = isl_basic_set_add_ineq(tab->bset, ineq);
1563 isl_tab_push(tab, isl_tab_undo_bset_ineq);
1567 r = isl_tab_add_row(tab, ineq);
1570 tab->con[r].is_nonneg = 1;
1571 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
1572 if (isl_tab_row_is_redundant(tab, tab->con[r].index)) {
1573 isl_tab_mark_redundant(tab, tab->con[r].index);
1577 sgn = restore_row(tab, &tab->con[r]);
1579 return isl_tab_mark_empty(tab);
1580 if (tab->con[r].is_row && isl_tab_row_is_redundant(tab, tab->con[r].index))
1581 isl_tab_mark_redundant(tab, tab->con[r].index);
1588 /* Pivot a non-negative variable down until it reaches the value zero
1589 * and then pivot the variable into a column position.
1591 static int to_col(struct isl_tab *tab, struct isl_tab_var *var)
1595 unsigned off = 2 + tab->M;
1600 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
1601 find_pivot(tab, var, NULL, -1, &row, &col);
1602 isl_assert(tab->mat->ctx, row != -1, return -1);
1603 isl_tab_pivot(tab, row, col);
1608 for (i = tab->n_dead; i < tab->n_col; ++i)
1609 if (!isl_int_is_zero(tab->mat->row[var->index][off + i]))
1612 isl_assert(tab->mat->ctx, i < tab->n_col, return -1);
1613 isl_tab_pivot(tab, var->index, i);
1618 /* We assume Gaussian elimination has been performed on the equalities.
1619 * The equalities can therefore never conflict.
1620 * Adding the equalities is currently only really useful for a later call
1621 * to isl_tab_ineq_type.
1623 static struct isl_tab *add_eq(struct isl_tab *tab, isl_int *eq)
1630 r = isl_tab_add_row(tab, eq);
1634 r = tab->con[r].index;
1635 i = isl_seq_first_non_zero(tab->mat->row[r] + 2 + tab->M + tab->n_dead,
1636 tab->n_col - tab->n_dead);
1637 isl_assert(tab->mat->ctx, i >= 0, goto error);
1639 isl_tab_pivot(tab, r, i);
1640 isl_tab_kill_col(tab, i);
1649 static int row_is_manifestly_zero(struct isl_tab *tab, int row)
1651 unsigned off = 2 + tab->M;
1653 if (!isl_int_is_zero(tab->mat->row[row][1]))
1655 if (tab->M && !isl_int_is_zero(tab->mat->row[row][2]))
1657 return isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
1658 tab->n_col - tab->n_dead) == -1;
1661 /* Add an equality that is known to be valid for the given tableau.
1663 struct isl_tab *isl_tab_add_valid_eq(struct isl_tab *tab, isl_int *eq)
1665 struct isl_tab_var *var;
1670 r = isl_tab_add_row(tab, eq);
1676 if (row_is_manifestly_zero(tab, r)) {
1678 isl_tab_mark_redundant(tab, r);
1682 if (isl_int_is_neg(tab->mat->row[r][1])) {
1683 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1688 if (to_col(tab, var) < 0)
1691 isl_tab_kill_col(tab, var->index);
1699 static int add_zero_row(struct isl_tab *tab)
1704 r = isl_tab_allocate_con(tab);
1708 row = tab->mat->row[tab->con[r].index];
1709 isl_seq_clr(row + 1, 1 + tab->M + tab->n_col);
1710 isl_int_set_si(row[0], 1);
1715 /* Add equality "eq" and check if it conflicts with the
1716 * previously added constraints or if it is obviously redundant.
1718 struct isl_tab *isl_tab_add_eq(struct isl_tab *tab, isl_int *eq)
1720 struct isl_tab_undo *snap = NULL;
1721 struct isl_tab_var *var;
1728 isl_assert(tab->mat->ctx, !tab->M, goto error);
1731 snap = isl_tab_snap(tab);
1733 r = isl_tab_add_row(tab, eq);
1739 if (row_is_manifestly_zero(tab, row)) {
1741 if (isl_tab_rollback(tab, snap) < 0)
1749 tab->bset = isl_basic_set_add_ineq(tab->bset, eq);
1750 isl_tab_push(tab, isl_tab_undo_bset_ineq);
1751 isl_seq_neg(eq, eq, 1 + tab->n_var);
1752 tab->bset = isl_basic_set_add_ineq(tab->bset, eq);
1753 isl_seq_neg(eq, eq, 1 + tab->n_var);
1754 isl_tab_push(tab, isl_tab_undo_bset_ineq);
1757 if (add_zero_row(tab) < 0)
1761 sgn = isl_int_sgn(tab->mat->row[row][1]);
1764 isl_seq_neg(tab->mat->row[row] + 1, tab->mat->row[row] + 1,
1770 if (sgn < 0 && sign_of_max(tab, var) < 0)
1771 return isl_tab_mark_empty(tab);
1774 if (to_col(tab, var) < 0)
1777 isl_tab_kill_col(tab, var->index);
1785 struct isl_tab *isl_tab_from_basic_map(struct isl_basic_map *bmap)
1788 struct isl_tab *tab;
1792 tab = isl_tab_alloc(bmap->ctx,
1793 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
1794 isl_basic_map_total_dim(bmap), 0);
1797 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
1798 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY))
1799 return isl_tab_mark_empty(tab);
1800 for (i = 0; i < bmap->n_eq; ++i) {
1801 tab = add_eq(tab, bmap->eq[i]);
1805 for (i = 0; i < bmap->n_ineq; ++i) {
1806 tab = isl_tab_add_ineq(tab, bmap->ineq[i]);
1807 if (!tab || tab->empty)
1813 struct isl_tab *isl_tab_from_basic_set(struct isl_basic_set *bset)
1815 return isl_tab_from_basic_map((struct isl_basic_map *)bset);
1818 /* Construct a tableau corresponding to the recession cone of "bset".
1820 struct isl_tab *isl_tab_from_recession_cone(struct isl_basic_set *bset)
1824 struct isl_tab *tab;
1828 tab = isl_tab_alloc(bset->ctx, bset->n_eq + bset->n_ineq,
1829 isl_basic_set_total_dim(bset), 0);
1832 tab->rational = ISL_F_ISSET(bset, ISL_BASIC_SET_RATIONAL);
1835 for (i = 0; i < bset->n_eq; ++i) {
1836 isl_int_swap(bset->eq[i][0], cst);
1837 tab = add_eq(tab, bset->eq[i]);
1838 isl_int_swap(bset->eq[i][0], cst);
1842 for (i = 0; i < bset->n_ineq; ++i) {
1844 isl_int_swap(bset->ineq[i][0], cst);
1845 r = isl_tab_add_row(tab, bset->ineq[i]);
1846 isl_int_swap(bset->ineq[i][0], cst);
1849 tab->con[r].is_nonneg = 1;
1850 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
1861 /* Assuming "tab" is the tableau of a cone, check if the cone is
1862 * bounded, i.e., if it is empty or only contains the origin.
1864 int isl_tab_cone_is_bounded(struct isl_tab *tab)
1872 if (tab->n_dead == tab->n_col)
1876 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1877 struct isl_tab_var *var;
1878 var = isl_tab_var_from_row(tab, i);
1879 if (!var->is_nonneg)
1881 if (sign_of_max(tab, var) != 0)
1883 close_row(tab, var);
1886 if (tab->n_dead == tab->n_col)
1888 if (i == tab->n_row)
1893 int isl_tab_sample_is_integer(struct isl_tab *tab)
1900 for (i = 0; i < tab->n_var; ++i) {
1902 if (!tab->var[i].is_row)
1904 row = tab->var[i].index;
1905 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
1906 tab->mat->row[row][0]))
1912 static struct isl_vec *extract_integer_sample(struct isl_tab *tab)
1915 struct isl_vec *vec;
1917 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1921 isl_int_set_si(vec->block.data[0], 1);
1922 for (i = 0; i < tab->n_var; ++i) {
1923 if (!tab->var[i].is_row)
1924 isl_int_set_si(vec->block.data[1 + i], 0);
1926 int row = tab->var[i].index;
1927 isl_int_divexact(vec->block.data[1 + i],
1928 tab->mat->row[row][1], tab->mat->row[row][0]);
1935 struct isl_vec *isl_tab_get_sample_value(struct isl_tab *tab)
1938 struct isl_vec *vec;
1944 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
1950 isl_int_set_si(vec->block.data[0], 1);
1951 for (i = 0; i < tab->n_var; ++i) {
1953 if (!tab->var[i].is_row) {
1954 isl_int_set_si(vec->block.data[1 + i], 0);
1957 row = tab->var[i].index;
1958 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
1959 isl_int_divexact(m, tab->mat->row[row][0], m);
1960 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
1961 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
1962 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
1964 vec = isl_vec_normalize(vec);
1970 /* Update "bmap" based on the results of the tableau "tab".
1971 * In particular, implicit equalities are made explicit, redundant constraints
1972 * are removed and if the sample value happens to be integer, it is stored
1973 * in "bmap" (unless "bmap" already had an integer sample).
1975 * The tableau is assumed to have been created from "bmap" using
1976 * isl_tab_from_basic_map.
1978 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
1979 struct isl_tab *tab)
1991 bmap = isl_basic_map_set_to_empty(bmap);
1993 for (i = bmap->n_ineq - 1; i >= 0; --i) {
1994 if (isl_tab_is_equality(tab, n_eq + i))
1995 isl_basic_map_inequality_to_equality(bmap, i);
1996 else if (isl_tab_is_redundant(tab, n_eq + i))
1997 isl_basic_map_drop_inequality(bmap, i);
1999 if (!tab->rational &&
2000 !bmap->sample && isl_tab_sample_is_integer(tab))
2001 bmap->sample = extract_integer_sample(tab);
2005 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
2006 struct isl_tab *tab)
2008 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
2009 (struct isl_basic_map *)bset, tab);
2012 /* Given a non-negative variable "var", add a new non-negative variable
2013 * that is the opposite of "var", ensuring that var can only attain the
2015 * If var = n/d is a row variable, then the new variable = -n/d.
2016 * If var is a column variables, then the new variable = -var.
2017 * If the new variable cannot attain non-negative values, then
2018 * the resulting tableau is empty.
2019 * Otherwise, we know the value will be zero and we close the row.
2021 static struct isl_tab *cut_to_hyperplane(struct isl_tab *tab,
2022 struct isl_tab_var *var)
2027 unsigned off = 2 + tab->M;
2031 isl_assert(tab->mat->ctx, !var->is_redundant, goto error);
2033 if (isl_tab_extend_cons(tab, 1) < 0)
2037 tab->con[r].index = tab->n_row;
2038 tab->con[r].is_row = 1;
2039 tab->con[r].is_nonneg = 0;
2040 tab->con[r].is_zero = 0;
2041 tab->con[r].is_redundant = 0;
2042 tab->con[r].frozen = 0;
2043 tab->con[r].negated = 0;
2044 tab->row_var[tab->n_row] = ~r;
2045 row = tab->mat->row[tab->n_row];
2048 isl_int_set(row[0], tab->mat->row[var->index][0]);
2049 isl_seq_neg(row + 1,
2050 tab->mat->row[var->index] + 1, 1 + tab->n_col);
2052 isl_int_set_si(row[0], 1);
2053 isl_seq_clr(row + 1, 1 + tab->n_col);
2054 isl_int_set_si(row[off + var->index], -1);
2059 isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]);
2061 sgn = sign_of_max(tab, &tab->con[r]);
2063 return isl_tab_mark_empty(tab);
2064 tab->con[r].is_nonneg = 1;
2065 isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]);
2067 close_row(tab, &tab->con[r]);
2075 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2076 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2077 * by r' = r + 1 >= 0.
2078 * If r is a row variable, we simply increase the constant term by one
2079 * (taking into account the denominator).
2080 * If r is a column variable, then we need to modify each row that
2081 * refers to r = r' - 1 by substituting this equality, effectively
2082 * subtracting the coefficient of the column from the constant.
2084 struct isl_tab *isl_tab_relax(struct isl_tab *tab, int con)
2086 struct isl_tab_var *var;
2087 unsigned off = 2 + tab->M;
2092 var = &tab->con[con];
2094 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2095 to_row(tab, var, 1);
2098 isl_int_add(tab->mat->row[var->index][1],
2099 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2103 for (i = 0; i < tab->n_row; ++i) {
2104 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2106 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
2107 tab->mat->row[i][off + var->index]);
2112 isl_tab_push_var(tab, isl_tab_undo_relax, var);
2117 struct isl_tab *isl_tab_select_facet(struct isl_tab *tab, int con)
2122 return cut_to_hyperplane(tab, &tab->con[con]);
2125 static int may_be_equality(struct isl_tab *tab, int row)
2127 unsigned off = 2 + tab->M;
2128 return (tab->rational ? isl_int_is_zero(tab->mat->row[row][1])
2129 : isl_int_lt(tab->mat->row[row][1],
2130 tab->mat->row[row][0])) &&
2131 isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
2132 tab->n_col - tab->n_dead) != -1;
2135 /* Check for (near) equalities among the constraints.
2136 * A constraint is an equality if it is non-negative and if
2137 * its maximal value is either
2138 * - zero (in case of rational tableaus), or
2139 * - strictly less than 1 (in case of integer tableaus)
2141 * We first mark all non-redundant and non-dead variables that
2142 * are not frozen and not obviously not an equality.
2143 * Then we iterate over all marked variables if they can attain
2144 * any values larger than zero or at least one.
2145 * If the maximal value is zero, we mark any column variables
2146 * that appear in the row as being zero and mark the row as being redundant.
2147 * Otherwise, if the maximal value is strictly less than one (and the
2148 * tableau is integer), then we restrict the value to being zero
2149 * by adding an opposite non-negative variable.
2151 struct isl_tab *isl_tab_detect_implicit_equalities(struct isl_tab *tab)
2160 if (tab->n_dead == tab->n_col)
2164 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2165 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2166 var->marked = !var->frozen && var->is_nonneg &&
2167 may_be_equality(tab, i);
2171 for (i = tab->n_dead; i < tab->n_col; ++i) {
2172 struct isl_tab_var *var = var_from_col(tab, i);
2173 var->marked = !var->frozen && var->is_nonneg;
2178 struct isl_tab_var *var;
2179 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2180 var = isl_tab_var_from_row(tab, i);
2184 if (i == tab->n_row) {
2185 for (i = tab->n_dead; i < tab->n_col; ++i) {
2186 var = var_from_col(tab, i);
2190 if (i == tab->n_col)
2195 if (sign_of_max(tab, var) == 0)
2196 close_row(tab, var);
2197 else if (!tab->rational && !at_least_one(tab, var)) {
2198 tab = cut_to_hyperplane(tab, var);
2199 return isl_tab_detect_implicit_equalities(tab);
2201 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2202 var = isl_tab_var_from_row(tab, i);
2205 if (may_be_equality(tab, i))
2215 /* Check for (near) redundant constraints.
2216 * A constraint is redundant if it is non-negative and if
2217 * its minimal value (temporarily ignoring the non-negativity) is either
2218 * - zero (in case of rational tableaus), or
2219 * - strictly larger than -1 (in case of integer tableaus)
2221 * We first mark all non-redundant and non-dead variables that
2222 * are not frozen and not obviously negatively unbounded.
2223 * Then we iterate over all marked variables if they can attain
2224 * any values smaller than zero or at most negative one.
2225 * If not, we mark the row as being redundant (assuming it hasn't
2226 * been detected as being obviously redundant in the mean time).
2228 struct isl_tab *isl_tab_detect_redundant(struct isl_tab *tab)
2237 if (tab->n_redundant == tab->n_row)
2241 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2242 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2243 var->marked = !var->frozen && var->is_nonneg;
2247 for (i = tab->n_dead; i < tab->n_col; ++i) {
2248 struct isl_tab_var *var = var_from_col(tab, i);
2249 var->marked = !var->frozen && var->is_nonneg &&
2250 !min_is_manifestly_unbounded(tab, var);
2255 struct isl_tab_var *var;
2256 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2257 var = isl_tab_var_from_row(tab, i);
2261 if (i == tab->n_row) {
2262 for (i = tab->n_dead; i < tab->n_col; ++i) {
2263 var = var_from_col(tab, i);
2267 if (i == tab->n_col)
2272 if ((tab->rational ? (sign_of_min(tab, var) >= 0)
2273 : !isl_tab_min_at_most_neg_one(tab, var)) &&
2275 isl_tab_mark_redundant(tab, var->index);
2276 for (i = tab->n_dead; i < tab->n_col; ++i) {
2277 var = var_from_col(tab, i);
2280 if (!min_is_manifestly_unbounded(tab, var))
2290 int isl_tab_is_equality(struct isl_tab *tab, int con)
2297 if (tab->con[con].is_zero)
2299 if (tab->con[con].is_redundant)
2301 if (!tab->con[con].is_row)
2302 return tab->con[con].index < tab->n_dead;
2304 row = tab->con[con].index;
2307 return isl_int_is_zero(tab->mat->row[row][1]) &&
2308 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
2309 tab->n_col - tab->n_dead) == -1;
2312 /* Return the minimial value of the affine expression "f" with denominator
2313 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2314 * the expression cannot attain arbitrarily small values.
2315 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2316 * The return value reflects the nature of the result (empty, unbounded,
2317 * minmimal value returned in *opt).
2319 enum isl_lp_result isl_tab_min(struct isl_tab *tab,
2320 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom,
2324 enum isl_lp_result res = isl_lp_ok;
2325 struct isl_tab_var *var;
2326 struct isl_tab_undo *snap;
2329 return isl_lp_empty;
2331 snap = isl_tab_snap(tab);
2332 r = isl_tab_add_row(tab, f);
2334 return isl_lp_error;
2336 isl_int_mul(tab->mat->row[var->index][0],
2337 tab->mat->row[var->index][0], denom);
2340 find_pivot(tab, var, var, -1, &row, &col);
2341 if (row == var->index) {
2342 res = isl_lp_unbounded;
2347 isl_tab_pivot(tab, row, col);
2349 if (ISL_FL_ISSET(flags, ISL_TAB_SAVE_DUAL)) {
2352 isl_vec_free(tab->dual);
2353 tab->dual = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_con);
2355 return isl_lp_error;
2356 isl_int_set(tab->dual->el[0], tab->mat->row[var->index][0]);
2357 for (i = 0; i < tab->n_con; ++i) {
2359 if (tab->con[i].is_row) {
2360 isl_int_set_si(tab->dual->el[1 + i], 0);
2363 pos = 2 + tab->M + tab->con[i].index;
2364 if (tab->con[i].negated)
2365 isl_int_neg(tab->dual->el[1 + i],
2366 tab->mat->row[var->index][pos]);
2368 isl_int_set(tab->dual->el[1 + i],
2369 tab->mat->row[var->index][pos]);
2372 if (opt && res == isl_lp_ok) {
2374 isl_int_set(*opt, tab->mat->row[var->index][1]);
2375 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
2377 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
2378 tab->mat->row[var->index][0]);
2380 if (isl_tab_rollback(tab, snap) < 0)
2381 return isl_lp_error;
2385 int isl_tab_is_redundant(struct isl_tab *tab, int con)
2389 if (tab->con[con].is_zero)
2391 if (tab->con[con].is_redundant)
2393 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
2396 /* Take a snapshot of the tableau that can be restored by s call to
2399 struct isl_tab_undo *isl_tab_snap(struct isl_tab *tab)
2407 /* Undo the operation performed by isl_tab_relax.
2409 static void unrelax(struct isl_tab *tab, struct isl_tab_var *var)
2411 unsigned off = 2 + tab->M;
2413 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2414 to_row(tab, var, 1);
2417 isl_int_sub(tab->mat->row[var->index][1],
2418 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2422 for (i = 0; i < tab->n_row; ++i) {
2423 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2425 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
2426 tab->mat->row[i][off + var->index]);
2432 static void perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo)
2434 struct isl_tab_var *var = var_from_index(tab, undo->u.var_index);
2435 switch(undo->type) {
2436 case isl_tab_undo_nonneg:
2439 case isl_tab_undo_redundant:
2440 var->is_redundant = 0;
2443 case isl_tab_undo_zero:
2448 case isl_tab_undo_allocate:
2449 if (undo->u.var_index >= 0) {
2450 isl_assert(tab->mat->ctx, !var->is_row, return);
2451 drop_col(tab, var->index);
2455 if (!max_is_manifestly_unbounded(tab, var))
2456 to_row(tab, var, 1);
2457 else if (!min_is_manifestly_unbounded(tab, var))
2458 to_row(tab, var, -1);
2460 to_row(tab, var, 0);
2462 drop_row(tab, var->index);
2464 case isl_tab_undo_relax:
2470 /* Restore the tableau to the state where the basic variables
2471 * are those in "col_var".
2472 * We first construct a list of variables that are currently in
2473 * the basis, but shouldn't. Then we iterate over all variables
2474 * that should be in the basis and for each one that is currently
2475 * not in the basis, we exchange it with one of the elements of the
2476 * list constructed before.
2477 * We can always find an appropriate variable to pivot with because
2478 * the current basis is mapped to the old basis by a non-singular
2479 * matrix and so we can never end up with a zero row.
2481 static int restore_basis(struct isl_tab *tab, int *col_var)
2485 int *extra = NULL; /* current columns that contain bad stuff */
2486 unsigned off = 2 + tab->M;
2488 extra = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
2491 for (i = 0; i < tab->n_col; ++i) {
2492 for (j = 0; j < tab->n_col; ++j)
2493 if (tab->col_var[i] == col_var[j])
2497 extra[n_extra++] = i;
2499 for (i = 0; i < tab->n_col && n_extra > 0; ++i) {
2500 struct isl_tab_var *var;
2503 for (j = 0; j < tab->n_col; ++j)
2504 if (col_var[i] == tab->col_var[j])
2508 var = var_from_index(tab, col_var[i]);
2510 for (j = 0; j < n_extra; ++j)
2511 if (!isl_int_is_zero(tab->mat->row[row][off+extra[j]]))
2513 isl_assert(tab->mat->ctx, j < n_extra, goto error);
2514 isl_tab_pivot(tab, row, extra[j]);
2515 extra[j] = extra[--n_extra];
2527 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo)
2529 switch (undo->type) {
2530 case isl_tab_undo_empty:
2533 case isl_tab_undo_nonneg:
2534 case isl_tab_undo_redundant:
2535 case isl_tab_undo_zero:
2536 case isl_tab_undo_allocate:
2537 case isl_tab_undo_relax:
2538 perform_undo_var(tab, undo);
2540 case isl_tab_undo_bset_eq:
2541 isl_basic_set_free_equality(tab->bset, 1);
2543 case isl_tab_undo_bset_ineq:
2544 isl_basic_set_free_inequality(tab->bset, 1);
2546 case isl_tab_undo_bset_div:
2547 isl_basic_set_free_div(tab->bset, 1);
2549 tab->samples->n_col--;
2551 case isl_tab_undo_saved_basis:
2552 if (restore_basis(tab, undo->u.col_var) < 0)
2555 case isl_tab_undo_drop_sample:
2559 isl_assert(tab->mat->ctx, 0, return -1);
2564 /* Return the tableau to the state it was in when the snapshot "snap"
2567 int isl_tab_rollback(struct isl_tab *tab, struct isl_tab_undo *snap)
2569 struct isl_tab_undo *undo, *next;
2575 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
2579 if (perform_undo(tab, undo) < 0) {
2593 /* The given row "row" represents an inequality violated by all
2594 * points in the tableau. Check for some special cases of such
2595 * separating constraints.
2596 * In particular, if the row has been reduced to the constant -1,
2597 * then we know the inequality is adjacent (but opposite) to
2598 * an equality in the tableau.
2599 * If the row has been reduced to r = -1 -r', with r' an inequality
2600 * of the tableau, then the inequality is adjacent (but opposite)
2601 * to the inequality r'.
2603 static enum isl_ineq_type separation_type(struct isl_tab *tab, unsigned row)
2606 unsigned off = 2 + tab->M;
2609 return isl_ineq_separate;
2611 if (!isl_int_is_one(tab->mat->row[row][0]))
2612 return isl_ineq_separate;
2613 if (!isl_int_is_negone(tab->mat->row[row][1]))
2614 return isl_ineq_separate;
2616 pos = isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
2617 tab->n_col - tab->n_dead);
2619 return isl_ineq_adj_eq;
2621 if (!isl_int_is_negone(tab->mat->row[row][off + tab->n_dead + pos]))
2622 return isl_ineq_separate;
2624 pos = isl_seq_first_non_zero(
2625 tab->mat->row[row] + off + tab->n_dead + pos + 1,
2626 tab->n_col - tab->n_dead - pos - 1);
2628 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
2631 /* Check the effect of inequality "ineq" on the tableau "tab".
2633 * isl_ineq_redundant: satisfied by all points in the tableau
2634 * isl_ineq_separate: satisfied by no point in the tableau
2635 * isl_ineq_cut: satisfied by some by not all points
2636 * isl_ineq_adj_eq: adjacent to an equality
2637 * isl_ineq_adj_ineq: adjacent to an inequality.
2639 enum isl_ineq_type isl_tab_ineq_type(struct isl_tab *tab, isl_int *ineq)
2641 enum isl_ineq_type type = isl_ineq_error;
2642 struct isl_tab_undo *snap = NULL;
2647 return isl_ineq_error;
2649 if (isl_tab_extend_cons(tab, 1) < 0)
2650 return isl_ineq_error;
2652 snap = isl_tab_snap(tab);
2654 con = isl_tab_add_row(tab, ineq);
2658 row = tab->con[con].index;
2659 if (isl_tab_row_is_redundant(tab, row))
2660 type = isl_ineq_redundant;
2661 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
2663 isl_int_abs_ge(tab->mat->row[row][1],
2664 tab->mat->row[row][0]))) {
2665 if (at_least_zero(tab, &tab->con[con]))
2666 type = isl_ineq_cut;
2668 type = separation_type(tab, row);
2669 } else if (tab->rational ? (sign_of_min(tab, &tab->con[con]) < 0)
2670 : isl_tab_min_at_most_neg_one(tab, &tab->con[con]))
2671 type = isl_ineq_cut;
2673 type = isl_ineq_redundant;
2675 if (isl_tab_rollback(tab, snap))
2676 return isl_ineq_error;
2679 isl_tab_rollback(tab, snap);
2680 return isl_ineq_error;
2683 void isl_tab_dump(struct isl_tab *tab, FILE *out, int indent)
2689 fprintf(out, "%*snull tab\n", indent, "");
2692 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
2693 tab->n_redundant, tab->n_dead);
2695 fprintf(out, ", rational");
2697 fprintf(out, ", empty");
2699 fprintf(out, "%*s[", indent, "");
2700 for (i = 0; i < tab->n_var; ++i) {
2702 fprintf(out, (i == tab->n_param ||
2703 i == tab->n_var - tab->n_div) ? "; "
2705 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
2707 tab->var[i].is_zero ? " [=0]" :
2708 tab->var[i].is_redundant ? " [R]" : "");
2710 fprintf(out, "]\n");
2711 fprintf(out, "%*s[", indent, "");
2712 for (i = 0; i < tab->n_con; ++i) {
2715 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
2717 tab->con[i].is_zero ? " [=0]" :
2718 tab->con[i].is_redundant ? " [R]" : "");
2720 fprintf(out, "]\n");
2721 fprintf(out, "%*s[", indent, "");
2722 for (i = 0; i < tab->n_row; ++i) {
2723 const char *sign = "";
2726 if (tab->row_sign) {
2727 if (tab->row_sign[i] == isl_tab_row_unknown)
2729 else if (tab->row_sign[i] == isl_tab_row_neg)
2731 else if (tab->row_sign[i] == isl_tab_row_pos)
2736 fprintf(out, "r%d: %d%s%s", i, tab->row_var[i],
2737 isl_tab_var_from_row(tab, i)->is_nonneg ? " [>=0]" : "", sign);
2739 fprintf(out, "]\n");
2740 fprintf(out, "%*s[", indent, "");
2741 for (i = 0; i < tab->n_col; ++i) {
2744 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
2745 var_from_col(tab, i)->is_nonneg ? " [>=0]" : "");
2747 fprintf(out, "]\n");
2748 r = tab->mat->n_row;
2749 tab->mat->n_row = tab->n_row;
2750 c = tab->mat->n_col;
2751 tab->mat->n_col = 2 + tab->M + tab->n_col;
2752 isl_mat_dump(tab->mat, out, indent);
2753 tab->mat->n_row = r;
2754 tab->mat->n_col = c;
2756 isl_basic_set_dump(tab->bset, out, indent);