2 * Copyright 2008-2009 Katholieke Universiteit Leuven
4 * Use of this software is governed by the GNU LGPLv2.1 license
6 * Written by Sven Verdoolaege, K.U.Leuven, Departement
7 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
10 #include <isl_ctx_private.h>
11 #include <isl_mat_private.h>
12 #include "isl_map_private.h"
15 #include <isl_config.h>
18 * The implementation of tableaus in this file was inspired by Section 8
19 * of David Detlefs, Greg Nelson and James B. Saxe, "Simplify: a theorem
20 * prover for program checking".
23 struct isl_tab *isl_tab_alloc(struct isl_ctx *ctx,
24 unsigned n_row, unsigned n_var, unsigned M)
30 tab = isl_calloc_type(ctx, struct isl_tab);
33 tab->mat = isl_mat_alloc(ctx, n_row, off + n_var);
36 tab->var = isl_alloc_array(ctx, struct isl_tab_var, n_var);
39 tab->con = isl_alloc_array(ctx, struct isl_tab_var, n_row);
42 tab->col_var = isl_alloc_array(ctx, int, n_var);
45 tab->row_var = isl_alloc_array(ctx, int, n_row);
48 for (i = 0; i < n_var; ++i) {
49 tab->var[i].index = i;
50 tab->var[i].is_row = 0;
51 tab->var[i].is_nonneg = 0;
52 tab->var[i].is_zero = 0;
53 tab->var[i].is_redundant = 0;
54 tab->var[i].frozen = 0;
55 tab->var[i].negated = 0;
69 tab->strict_redundant = 0;
76 tab->bottom.type = isl_tab_undo_bottom;
77 tab->bottom.next = NULL;
78 tab->top = &tab->bottom;
90 int isl_tab_extend_cons(struct isl_tab *tab, unsigned n_new)
99 if (tab->max_con < tab->n_con + n_new) {
100 struct isl_tab_var *con;
102 con = isl_realloc_array(tab->mat->ctx, tab->con,
103 struct isl_tab_var, tab->max_con + n_new);
107 tab->max_con += n_new;
109 if (tab->mat->n_row < tab->n_row + n_new) {
112 tab->mat = isl_mat_extend(tab->mat,
113 tab->n_row + n_new, off + tab->n_col);
116 row_var = isl_realloc_array(tab->mat->ctx, tab->row_var,
117 int, tab->mat->n_row);
120 tab->row_var = row_var;
122 enum isl_tab_row_sign *s;
123 s = isl_realloc_array(tab->mat->ctx, tab->row_sign,
124 enum isl_tab_row_sign, tab->mat->n_row);
133 /* Make room for at least n_new extra variables.
134 * Return -1 if anything went wrong.
136 int isl_tab_extend_vars(struct isl_tab *tab, unsigned n_new)
138 struct isl_tab_var *var;
139 unsigned off = 2 + tab->M;
141 if (tab->max_var < tab->n_var + n_new) {
142 var = isl_realloc_array(tab->mat->ctx, tab->var,
143 struct isl_tab_var, tab->n_var + n_new);
147 tab->max_var += n_new;
150 if (tab->mat->n_col < off + tab->n_col + n_new) {
153 tab->mat = isl_mat_extend(tab->mat,
154 tab->mat->n_row, off + tab->n_col + n_new);
157 p = isl_realloc_array(tab->mat->ctx, tab->col_var,
158 int, tab->n_col + n_new);
167 struct isl_tab *isl_tab_extend(struct isl_tab *tab, unsigned n_new)
169 if (isl_tab_extend_cons(tab, n_new) >= 0)
176 static void free_undo_record(struct isl_tab_undo *undo)
178 switch (undo->type) {
179 case isl_tab_undo_saved_basis:
180 free(undo->u.col_var);
187 static void free_undo(struct isl_tab *tab)
189 struct isl_tab_undo *undo, *next;
191 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
193 free_undo_record(undo);
198 void isl_tab_free(struct isl_tab *tab)
203 isl_mat_free(tab->mat);
204 isl_vec_free(tab->dual);
205 isl_basic_map_free(tab->bmap);
211 isl_mat_free(tab->samples);
212 free(tab->sample_index);
213 isl_mat_free(tab->basis);
217 struct isl_tab *isl_tab_dup(struct isl_tab *tab)
227 dup = isl_calloc_type(tab->mat->ctx, struct isl_tab);
230 dup->mat = isl_mat_dup(tab->mat);
233 dup->var = isl_alloc_array(tab->mat->ctx, struct isl_tab_var, tab->max_var);
236 for (i = 0; i < tab->n_var; ++i)
237 dup->var[i] = tab->var[i];
238 dup->con = isl_alloc_array(tab->mat->ctx, struct isl_tab_var, tab->max_con);
241 for (i = 0; i < tab->n_con; ++i)
242 dup->con[i] = tab->con[i];
243 dup->col_var = isl_alloc_array(tab->mat->ctx, int, tab->mat->n_col - off);
246 for (i = 0; i < tab->n_col; ++i)
247 dup->col_var[i] = tab->col_var[i];
248 dup->row_var = isl_alloc_array(tab->mat->ctx, int, tab->mat->n_row);
251 for (i = 0; i < tab->n_row; ++i)
252 dup->row_var[i] = tab->row_var[i];
254 dup->row_sign = isl_alloc_array(tab->mat->ctx, enum isl_tab_row_sign,
258 for (i = 0; i < tab->n_row; ++i)
259 dup->row_sign[i] = tab->row_sign[i];
262 dup->samples = isl_mat_dup(tab->samples);
265 dup->sample_index = isl_alloc_array(tab->mat->ctx, int,
266 tab->samples->n_row);
267 if (!dup->sample_index)
269 dup->n_sample = tab->n_sample;
270 dup->n_outside = tab->n_outside;
272 dup->n_row = tab->n_row;
273 dup->n_con = tab->n_con;
274 dup->n_eq = tab->n_eq;
275 dup->max_con = tab->max_con;
276 dup->n_col = tab->n_col;
277 dup->n_var = tab->n_var;
278 dup->max_var = tab->max_var;
279 dup->n_param = tab->n_param;
280 dup->n_div = tab->n_div;
281 dup->n_dead = tab->n_dead;
282 dup->n_redundant = tab->n_redundant;
283 dup->rational = tab->rational;
284 dup->empty = tab->empty;
285 dup->strict_redundant = 0;
289 tab->cone = tab->cone;
290 dup->bottom.type = isl_tab_undo_bottom;
291 dup->bottom.next = NULL;
292 dup->top = &dup->bottom;
294 dup->n_zero = tab->n_zero;
295 dup->n_unbounded = tab->n_unbounded;
296 dup->basis = isl_mat_dup(tab->basis);
304 /* Construct the coefficient matrix of the product tableau
306 * mat{1,2} is the coefficient matrix of tableau {1,2}
307 * row{1,2} is the number of rows in tableau {1,2}
308 * col{1,2} is the number of columns in tableau {1,2}
309 * off is the offset to the coefficient column (skipping the
310 * denominator, the constant term and the big parameter if any)
311 * r{1,2} is the number of redundant rows in tableau {1,2}
312 * d{1,2} is the number of dead columns in tableau {1,2}
314 * The order of the rows and columns in the result is as explained
315 * in isl_tab_product.
317 static struct isl_mat *tab_mat_product(struct isl_mat *mat1,
318 struct isl_mat *mat2, unsigned row1, unsigned row2,
319 unsigned col1, unsigned col2,
320 unsigned off, unsigned r1, unsigned r2, unsigned d1, unsigned d2)
323 struct isl_mat *prod;
326 prod = isl_mat_alloc(mat1->ctx, mat1->n_row + mat2->n_row,
332 for (i = 0; i < r1; ++i) {
333 isl_seq_cpy(prod->row[n + i], mat1->row[i], off + d1);
334 isl_seq_clr(prod->row[n + i] + off + d1, d2);
335 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
336 mat1->row[i] + off + d1, col1 - d1);
337 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
341 for (i = 0; i < r2; ++i) {
342 isl_seq_cpy(prod->row[n + i], mat2->row[i], off);
343 isl_seq_clr(prod->row[n + i] + off, d1);
344 isl_seq_cpy(prod->row[n + i] + off + d1,
345 mat2->row[i] + off, d2);
346 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
347 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
348 mat2->row[i] + off + d2, col2 - d2);
352 for (i = 0; i < row1 - r1; ++i) {
353 isl_seq_cpy(prod->row[n + i], mat1->row[r1 + i], off + d1);
354 isl_seq_clr(prod->row[n + i] + off + d1, d2);
355 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
356 mat1->row[r1 + i] + off + d1, col1 - d1);
357 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
361 for (i = 0; i < row2 - r2; ++i) {
362 isl_seq_cpy(prod->row[n + i], mat2->row[r2 + i], off);
363 isl_seq_clr(prod->row[n + i] + off, d1);
364 isl_seq_cpy(prod->row[n + i] + off + d1,
365 mat2->row[r2 + i] + off, d2);
366 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
367 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
368 mat2->row[r2 + i] + off + d2, col2 - d2);
374 /* Update the row or column index of a variable that corresponds
375 * to a variable in the first input tableau.
377 static void update_index1(struct isl_tab_var *var,
378 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
380 if (var->index == -1)
382 if (var->is_row && var->index >= r1)
384 if (!var->is_row && var->index >= d1)
388 /* Update the row or column index of a variable that corresponds
389 * to a variable in the second input tableau.
391 static void update_index2(struct isl_tab_var *var,
392 unsigned row1, unsigned col1,
393 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
395 if (var->index == -1)
410 /* Create a tableau that represents the Cartesian product of the sets
411 * represented by tableaus tab1 and tab2.
412 * The order of the rows in the product is
413 * - redundant rows of tab1
414 * - redundant rows of tab2
415 * - non-redundant rows of tab1
416 * - non-redundant rows of tab2
417 * The order of the columns is
420 * - coefficient of big parameter, if any
421 * - dead columns of tab1
422 * - dead columns of tab2
423 * - live columns of tab1
424 * - live columns of tab2
425 * The order of the variables and the constraints is a concatenation
426 * of order in the two input tableaus.
428 struct isl_tab *isl_tab_product(struct isl_tab *tab1, struct isl_tab *tab2)
431 struct isl_tab *prod;
433 unsigned r1, r2, d1, d2;
438 isl_assert(tab1->mat->ctx, tab1->M == tab2->M, return NULL);
439 isl_assert(tab1->mat->ctx, tab1->rational == tab2->rational, return NULL);
440 isl_assert(tab1->mat->ctx, tab1->cone == tab2->cone, return NULL);
441 isl_assert(tab1->mat->ctx, !tab1->row_sign, return NULL);
442 isl_assert(tab1->mat->ctx, !tab2->row_sign, return NULL);
443 isl_assert(tab1->mat->ctx, tab1->n_param == 0, return NULL);
444 isl_assert(tab1->mat->ctx, tab2->n_param == 0, return NULL);
445 isl_assert(tab1->mat->ctx, tab1->n_div == 0, return NULL);
446 isl_assert(tab1->mat->ctx, tab2->n_div == 0, return NULL);
449 r1 = tab1->n_redundant;
450 r2 = tab2->n_redundant;
453 prod = isl_calloc_type(tab1->mat->ctx, struct isl_tab);
456 prod->mat = tab_mat_product(tab1->mat, tab2->mat,
457 tab1->n_row, tab2->n_row,
458 tab1->n_col, tab2->n_col, off, r1, r2, d1, d2);
461 prod->var = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
462 tab1->max_var + tab2->max_var);
465 for (i = 0; i < tab1->n_var; ++i) {
466 prod->var[i] = tab1->var[i];
467 update_index1(&prod->var[i], r1, r2, d1, d2);
469 for (i = 0; i < tab2->n_var; ++i) {
470 prod->var[tab1->n_var + i] = tab2->var[i];
471 update_index2(&prod->var[tab1->n_var + i],
472 tab1->n_row, tab1->n_col,
475 prod->con = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
476 tab1->max_con + tab2->max_con);
479 for (i = 0; i < tab1->n_con; ++i) {
480 prod->con[i] = tab1->con[i];
481 update_index1(&prod->con[i], r1, r2, d1, d2);
483 for (i = 0; i < tab2->n_con; ++i) {
484 prod->con[tab1->n_con + i] = tab2->con[i];
485 update_index2(&prod->con[tab1->n_con + i],
486 tab1->n_row, tab1->n_col,
489 prod->col_var = isl_alloc_array(tab1->mat->ctx, int,
490 tab1->n_col + tab2->n_col);
493 for (i = 0; i < tab1->n_col; ++i) {
494 int pos = i < d1 ? i : i + d2;
495 prod->col_var[pos] = tab1->col_var[i];
497 for (i = 0; i < tab2->n_col; ++i) {
498 int pos = i < d2 ? d1 + i : tab1->n_col + i;
499 int t = tab2->col_var[i];
504 prod->col_var[pos] = t;
506 prod->row_var = isl_alloc_array(tab1->mat->ctx, int,
507 tab1->mat->n_row + tab2->mat->n_row);
510 for (i = 0; i < tab1->n_row; ++i) {
511 int pos = i < r1 ? i : i + r2;
512 prod->row_var[pos] = tab1->row_var[i];
514 for (i = 0; i < tab2->n_row; ++i) {
515 int pos = i < r2 ? r1 + i : tab1->n_row + i;
516 int t = tab2->row_var[i];
521 prod->row_var[pos] = t;
523 prod->samples = NULL;
524 prod->sample_index = NULL;
525 prod->n_row = tab1->n_row + tab2->n_row;
526 prod->n_con = tab1->n_con + tab2->n_con;
528 prod->max_con = tab1->max_con + tab2->max_con;
529 prod->n_col = tab1->n_col + tab2->n_col;
530 prod->n_var = tab1->n_var + tab2->n_var;
531 prod->max_var = tab1->max_var + tab2->max_var;
534 prod->n_dead = tab1->n_dead + tab2->n_dead;
535 prod->n_redundant = tab1->n_redundant + tab2->n_redundant;
536 prod->rational = tab1->rational;
537 prod->empty = tab1->empty || tab2->empty;
538 prod->strict_redundant = tab1->strict_redundant || tab2->strict_redundant;
542 prod->cone = tab1->cone;
543 prod->bottom.type = isl_tab_undo_bottom;
544 prod->bottom.next = NULL;
545 prod->top = &prod->bottom;
548 prod->n_unbounded = 0;
557 static struct isl_tab_var *var_from_index(struct isl_tab *tab, int i)
562 return &tab->con[~i];
565 struct isl_tab_var *isl_tab_var_from_row(struct isl_tab *tab, int i)
567 return var_from_index(tab, tab->row_var[i]);
570 static struct isl_tab_var *var_from_col(struct isl_tab *tab, int i)
572 return var_from_index(tab, tab->col_var[i]);
575 /* Check if there are any upper bounds on column variable "var",
576 * i.e., non-negative rows where var appears with a negative coefficient.
577 * Return 1 if there are no such bounds.
579 static int max_is_manifestly_unbounded(struct isl_tab *tab,
580 struct isl_tab_var *var)
583 unsigned off = 2 + tab->M;
587 for (i = tab->n_redundant; i < tab->n_row; ++i) {
588 if (!isl_int_is_neg(tab->mat->row[i][off + var->index]))
590 if (isl_tab_var_from_row(tab, i)->is_nonneg)
596 /* Check if there are any lower bounds on column variable "var",
597 * i.e., non-negative rows where var appears with a positive coefficient.
598 * Return 1 if there are no such bounds.
600 static int min_is_manifestly_unbounded(struct isl_tab *tab,
601 struct isl_tab_var *var)
604 unsigned off = 2 + tab->M;
608 for (i = tab->n_redundant; i < tab->n_row; ++i) {
609 if (!isl_int_is_pos(tab->mat->row[i][off + var->index]))
611 if (isl_tab_var_from_row(tab, i)->is_nonneg)
617 static int row_cmp(struct isl_tab *tab, int r1, int r2, int c, isl_int t)
619 unsigned off = 2 + tab->M;
623 isl_int_mul(t, tab->mat->row[r1][2], tab->mat->row[r2][off+c]);
624 isl_int_submul(t, tab->mat->row[r2][2], tab->mat->row[r1][off+c]);
629 isl_int_mul(t, tab->mat->row[r1][1], tab->mat->row[r2][off + c]);
630 isl_int_submul(t, tab->mat->row[r2][1], tab->mat->row[r1][off + c]);
631 return isl_int_sgn(t);
634 /* Given the index of a column "c", return the index of a row
635 * that can be used to pivot the column in, with either an increase
636 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
637 * If "var" is not NULL, then the row returned will be different from
638 * the one associated with "var".
640 * Each row in the tableau is of the form
642 * x_r = a_r0 + \sum_i a_ri x_i
644 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
645 * impose any limit on the increase or decrease in the value of x_c
646 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
647 * for the row with the smallest (most stringent) such bound.
648 * Note that the common denominator of each row drops out of the fraction.
649 * To check if row j has a smaller bound than row r, i.e.,
650 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
651 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
652 * where -sign(a_jc) is equal to "sgn".
654 static int pivot_row(struct isl_tab *tab,
655 struct isl_tab_var *var, int sgn, int c)
659 unsigned off = 2 + tab->M;
663 for (j = tab->n_redundant; j < tab->n_row; ++j) {
664 if (var && j == var->index)
666 if (!isl_tab_var_from_row(tab, j)->is_nonneg)
668 if (sgn * isl_int_sgn(tab->mat->row[j][off + c]) >= 0)
674 tsgn = sgn * row_cmp(tab, r, j, c, t);
675 if (tsgn < 0 || (tsgn == 0 &&
676 tab->row_var[j] < tab->row_var[r]))
683 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
684 * (sgn < 0) the value of row variable var.
685 * If not NULL, then skip_var is a row variable that should be ignored
686 * while looking for a pivot row. It is usually equal to var.
688 * As the given row in the tableau is of the form
690 * x_r = a_r0 + \sum_i a_ri x_i
692 * we need to find a column such that the sign of a_ri is equal to "sgn"
693 * (such that an increase in x_i will have the desired effect) or a
694 * column with a variable that may attain negative values.
695 * If a_ri is positive, then we need to move x_i in the same direction
696 * to obtain the desired effect. Otherwise, x_i has to move in the
697 * opposite direction.
699 static void find_pivot(struct isl_tab *tab,
700 struct isl_tab_var *var, struct isl_tab_var *skip_var,
701 int sgn, int *row, int *col)
708 isl_assert(tab->mat->ctx, var->is_row, return);
709 tr = tab->mat->row[var->index] + 2 + tab->M;
712 for (j = tab->n_dead; j < tab->n_col; ++j) {
713 if (isl_int_is_zero(tr[j]))
715 if (isl_int_sgn(tr[j]) != sgn &&
716 var_from_col(tab, j)->is_nonneg)
718 if (c < 0 || tab->col_var[j] < tab->col_var[c])
724 sgn *= isl_int_sgn(tr[c]);
725 r = pivot_row(tab, skip_var, sgn, c);
726 *row = r < 0 ? var->index : r;
730 /* Return 1 if row "row" represents an obviously redundant inequality.
732 * - it represents an inequality or a variable
733 * - that is the sum of a non-negative sample value and a positive
734 * combination of zero or more non-negative constraints.
736 int isl_tab_row_is_redundant(struct isl_tab *tab, int row)
739 unsigned off = 2 + tab->M;
741 if (tab->row_var[row] < 0 && !isl_tab_var_from_row(tab, row)->is_nonneg)
744 if (isl_int_is_neg(tab->mat->row[row][1]))
746 if (tab->strict_redundant && isl_int_is_zero(tab->mat->row[row][1]))
748 if (tab->M && isl_int_is_neg(tab->mat->row[row][2]))
751 for (i = tab->n_dead; i < tab->n_col; ++i) {
752 if (isl_int_is_zero(tab->mat->row[row][off + i]))
754 if (tab->col_var[i] >= 0)
756 if (isl_int_is_neg(tab->mat->row[row][off + i]))
758 if (!var_from_col(tab, i)->is_nonneg)
764 static void swap_rows(struct isl_tab *tab, int row1, int row2)
767 enum isl_tab_row_sign s;
769 t = tab->row_var[row1];
770 tab->row_var[row1] = tab->row_var[row2];
771 tab->row_var[row2] = t;
772 isl_tab_var_from_row(tab, row1)->index = row1;
773 isl_tab_var_from_row(tab, row2)->index = row2;
774 tab->mat = isl_mat_swap_rows(tab->mat, row1, row2);
778 s = tab->row_sign[row1];
779 tab->row_sign[row1] = tab->row_sign[row2];
780 tab->row_sign[row2] = s;
783 static int push_union(struct isl_tab *tab,
784 enum isl_tab_undo_type type, union isl_tab_undo_val u) WARN_UNUSED;
785 static int push_union(struct isl_tab *tab,
786 enum isl_tab_undo_type type, union isl_tab_undo_val u)
788 struct isl_tab_undo *undo;
793 undo = isl_alloc_type(tab->mat->ctx, struct isl_tab_undo);
798 undo->next = tab->top;
804 int isl_tab_push_var(struct isl_tab *tab,
805 enum isl_tab_undo_type type, struct isl_tab_var *var)
807 union isl_tab_undo_val u;
809 u.var_index = tab->row_var[var->index];
811 u.var_index = tab->col_var[var->index];
812 return push_union(tab, type, u);
815 int isl_tab_push(struct isl_tab *tab, enum isl_tab_undo_type type)
817 union isl_tab_undo_val u = { 0 };
818 return push_union(tab, type, u);
821 /* Push a record on the undo stack describing the current basic
822 * variables, so that the this state can be restored during rollback.
824 int isl_tab_push_basis(struct isl_tab *tab)
827 union isl_tab_undo_val u;
829 u.col_var = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
832 for (i = 0; i < tab->n_col; ++i)
833 u.col_var[i] = tab->col_var[i];
834 return push_union(tab, isl_tab_undo_saved_basis, u);
837 int isl_tab_push_callback(struct isl_tab *tab, struct isl_tab_callback *callback)
839 union isl_tab_undo_val u;
840 u.callback = callback;
841 return push_union(tab, isl_tab_undo_callback, u);
844 struct isl_tab *isl_tab_init_samples(struct isl_tab *tab)
851 tab->samples = isl_mat_alloc(tab->mat->ctx, 1, 1 + tab->n_var);
854 tab->sample_index = isl_alloc_array(tab->mat->ctx, int, 1);
855 if (!tab->sample_index)
863 struct isl_tab *isl_tab_add_sample(struct isl_tab *tab,
864 __isl_take isl_vec *sample)
869 if (tab->n_sample + 1 > tab->samples->n_row) {
870 int *t = isl_realloc_array(tab->mat->ctx,
871 tab->sample_index, int, tab->n_sample + 1);
874 tab->sample_index = t;
877 tab->samples = isl_mat_extend(tab->samples,
878 tab->n_sample + 1, tab->samples->n_col);
882 isl_seq_cpy(tab->samples->row[tab->n_sample], sample->el, sample->size);
883 isl_vec_free(sample);
884 tab->sample_index[tab->n_sample] = tab->n_sample;
889 isl_vec_free(sample);
894 struct isl_tab *isl_tab_drop_sample(struct isl_tab *tab, int s)
896 if (s != tab->n_outside) {
897 int t = tab->sample_index[tab->n_outside];
898 tab->sample_index[tab->n_outside] = tab->sample_index[s];
899 tab->sample_index[s] = t;
900 isl_mat_swap_rows(tab->samples, tab->n_outside, s);
903 if (isl_tab_push(tab, isl_tab_undo_drop_sample) < 0) {
911 /* Record the current number of samples so that we can remove newer
912 * samples during a rollback.
914 int isl_tab_save_samples(struct isl_tab *tab)
916 union isl_tab_undo_val u;
922 return push_union(tab, isl_tab_undo_saved_samples, u);
925 /* Mark row with index "row" as being redundant.
926 * If we may need to undo the operation or if the row represents
927 * a variable of the original problem, the row is kept,
928 * but no longer considered when looking for a pivot row.
929 * Otherwise, the row is simply removed.
931 * The row may be interchanged with some other row. If it
932 * is interchanged with a later row, return 1. Otherwise return 0.
933 * If the rows are checked in order in the calling function,
934 * then a return value of 1 means that the row with the given
935 * row number may now contain a different row that hasn't been checked yet.
937 int isl_tab_mark_redundant(struct isl_tab *tab, int row)
939 struct isl_tab_var *var = isl_tab_var_from_row(tab, row);
940 var->is_redundant = 1;
941 isl_assert(tab->mat->ctx, row >= tab->n_redundant, return -1);
942 if (tab->preserve || tab->need_undo || tab->row_var[row] >= 0) {
943 if (tab->row_var[row] >= 0 && !var->is_nonneg) {
945 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, var) < 0)
948 if (row != tab->n_redundant)
949 swap_rows(tab, row, tab->n_redundant);
951 return isl_tab_push_var(tab, isl_tab_undo_redundant, var);
953 if (row != tab->n_row - 1)
954 swap_rows(tab, row, tab->n_row - 1);
955 isl_tab_var_from_row(tab, tab->n_row - 1)->index = -1;
961 int isl_tab_mark_empty(struct isl_tab *tab)
965 if (!tab->empty && tab->need_undo)
966 if (isl_tab_push(tab, isl_tab_undo_empty) < 0)
972 int isl_tab_freeze_constraint(struct isl_tab *tab, int con)
974 struct isl_tab_var *var;
979 var = &tab->con[con];
987 return isl_tab_push_var(tab, isl_tab_undo_freeze, var);
992 /* Update the rows signs after a pivot of "row" and "col", with "row_sgn"
993 * the original sign of the pivot element.
994 * We only keep track of row signs during PILP solving and in this case
995 * we only pivot a row with negative sign (meaning the value is always
996 * non-positive) using a positive pivot element.
998 * For each row j, the new value of the parametric constant is equal to
1000 * a_j0 - a_jc a_r0/a_rc
1002 * where a_j0 is the original parametric constant, a_rc is the pivot element,
1003 * a_r0 is the parametric constant of the pivot row and a_jc is the
1004 * pivot column entry of the row j.
1005 * Since a_r0 is non-positive and a_rc is positive, the sign of row j
1006 * remains the same if a_jc has the same sign as the row j or if
1007 * a_jc is zero. In all other cases, we reset the sign to "unknown".
1009 static void update_row_sign(struct isl_tab *tab, int row, int col, int row_sgn)
1012 struct isl_mat *mat = tab->mat;
1013 unsigned off = 2 + tab->M;
1018 if (tab->row_sign[row] == 0)
1020 isl_assert(mat->ctx, row_sgn > 0, return);
1021 isl_assert(mat->ctx, tab->row_sign[row] == isl_tab_row_neg, return);
1022 tab->row_sign[row] = isl_tab_row_pos;
1023 for (i = 0; i < tab->n_row; ++i) {
1027 s = isl_int_sgn(mat->row[i][off + col]);
1030 if (!tab->row_sign[i])
1032 if (s < 0 && tab->row_sign[i] == isl_tab_row_neg)
1034 if (s > 0 && tab->row_sign[i] == isl_tab_row_pos)
1036 tab->row_sign[i] = isl_tab_row_unknown;
1040 /* Given a row number "row" and a column number "col", pivot the tableau
1041 * such that the associated variables are interchanged.
1042 * The given row in the tableau expresses
1044 * x_r = a_r0 + \sum_i a_ri x_i
1048 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
1050 * Substituting this equality into the other rows
1052 * x_j = a_j0 + \sum_i a_ji x_i
1054 * with a_jc \ne 0, we obtain
1056 * 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
1063 * where i is any other column and j is any other row,
1064 * is therefore transformed into
1066 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1067 * 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)
1069 * The transformation is performed along the following steps
1071 * d_r/n_rc n_ri/n_rc
1074 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1077 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1078 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
1080 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1081 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
1083 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1084 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1086 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1087 * 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)
1090 int isl_tab_pivot(struct isl_tab *tab, int row, int col)
1095 struct isl_mat *mat = tab->mat;
1096 struct isl_tab_var *var;
1097 unsigned off = 2 + tab->M;
1099 if (tab->mat->ctx->abort) {
1100 isl_ctx_set_error(tab->mat->ctx, isl_error_abort);
1104 isl_int_swap(mat->row[row][0], mat->row[row][off + col]);
1105 sgn = isl_int_sgn(mat->row[row][0]);
1107 isl_int_neg(mat->row[row][0], mat->row[row][0]);
1108 isl_int_neg(mat->row[row][off + col], mat->row[row][off + col]);
1110 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1111 if (j == off - 1 + col)
1113 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
1115 if (!isl_int_is_one(mat->row[row][0]))
1116 isl_seq_normalize(mat->ctx, mat->row[row], off + tab->n_col);
1117 for (i = 0; i < tab->n_row; ++i) {
1120 if (isl_int_is_zero(mat->row[i][off + col]))
1122 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
1123 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1124 if (j == off - 1 + col)
1126 isl_int_mul(mat->row[i][1 + j],
1127 mat->row[i][1 + j], mat->row[row][0]);
1128 isl_int_addmul(mat->row[i][1 + j],
1129 mat->row[i][off + col], mat->row[row][1 + j]);
1131 isl_int_mul(mat->row[i][off + col],
1132 mat->row[i][off + col], mat->row[row][off + col]);
1133 if (!isl_int_is_one(mat->row[i][0]))
1134 isl_seq_normalize(mat->ctx, mat->row[i], off + tab->n_col);
1136 t = tab->row_var[row];
1137 tab->row_var[row] = tab->col_var[col];
1138 tab->col_var[col] = t;
1139 var = isl_tab_var_from_row(tab, row);
1142 var = var_from_col(tab, col);
1145 update_row_sign(tab, row, col, sgn);
1148 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1149 if (isl_int_is_zero(mat->row[i][off + col]))
1151 if (!isl_tab_var_from_row(tab, i)->frozen &&
1152 isl_tab_row_is_redundant(tab, i)) {
1153 int redo = isl_tab_mark_redundant(tab, i);
1163 /* If "var" represents a column variable, then pivot is up (sgn > 0)
1164 * or down (sgn < 0) to a row. The variable is assumed not to be
1165 * unbounded in the specified direction.
1166 * If sgn = 0, then the variable is unbounded in both directions,
1167 * and we pivot with any row we can find.
1169 static int to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign) WARN_UNUSED;
1170 static int to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign)
1173 unsigned off = 2 + tab->M;
1179 for (r = tab->n_redundant; r < tab->n_row; ++r)
1180 if (!isl_int_is_zero(tab->mat->row[r][off+var->index]))
1182 isl_assert(tab->mat->ctx, r < tab->n_row, return -1);
1184 r = pivot_row(tab, NULL, sign, var->index);
1185 isl_assert(tab->mat->ctx, r >= 0, return -1);
1188 return isl_tab_pivot(tab, r, var->index);
1191 /* Check whether all variables that are marked as non-negative
1192 * also have a non-negative sample value. This function is not
1193 * called from the current code but is useful during debugging.
1195 static void check_table(struct isl_tab *tab) __attribute__ ((unused));
1196 static void check_table(struct isl_tab *tab)
1202 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1203 struct isl_tab_var *var;
1204 var = isl_tab_var_from_row(tab, i);
1205 if (!var->is_nonneg)
1208 isl_assert(tab->mat->ctx,
1209 !isl_int_is_neg(tab->mat->row[i][2]), abort());
1210 if (isl_int_is_pos(tab->mat->row[i][2]))
1213 isl_assert(tab->mat->ctx, !isl_int_is_neg(tab->mat->row[i][1]),
1218 /* Return the sign of the maximal value of "var".
1219 * If the sign is not negative, then on return from this function,
1220 * the sample value will also be non-negative.
1222 * If "var" is manifestly unbounded wrt positive values, we are done.
1223 * Otherwise, we pivot the variable up to a row if needed
1224 * Then we continue pivoting down until either
1225 * - no more down pivots can be performed
1226 * - the sample value is positive
1227 * - the variable is pivoted into a manifestly unbounded column
1229 static int sign_of_max(struct isl_tab *tab, struct isl_tab_var *var)
1233 if (max_is_manifestly_unbounded(tab, var))
1235 if (to_row(tab, var, 1) < 0)
1237 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
1238 find_pivot(tab, var, var, 1, &row, &col);
1240 return isl_int_sgn(tab->mat->row[var->index][1]);
1241 if (isl_tab_pivot(tab, row, col) < 0)
1243 if (!var->is_row) /* manifestly unbounded */
1249 int isl_tab_sign_of_max(struct isl_tab *tab, int con)
1251 struct isl_tab_var *var;
1256 var = &tab->con[con];
1257 isl_assert(tab->mat->ctx, !var->is_redundant, return -2);
1258 isl_assert(tab->mat->ctx, !var->is_zero, return -2);
1260 return sign_of_max(tab, var);
1263 static int row_is_neg(struct isl_tab *tab, int row)
1266 return isl_int_is_neg(tab->mat->row[row][1]);
1267 if (isl_int_is_pos(tab->mat->row[row][2]))
1269 if (isl_int_is_neg(tab->mat->row[row][2]))
1271 return isl_int_is_neg(tab->mat->row[row][1]);
1274 static int row_sgn(struct isl_tab *tab, int row)
1277 return isl_int_sgn(tab->mat->row[row][1]);
1278 if (!isl_int_is_zero(tab->mat->row[row][2]))
1279 return isl_int_sgn(tab->mat->row[row][2]);
1281 return isl_int_sgn(tab->mat->row[row][1]);
1284 /* Perform pivots until the row variable "var" has a non-negative
1285 * sample value or until no more upward pivots can be performed.
1286 * Return the sign of the sample value after the pivots have been
1289 static int restore_row(struct isl_tab *tab, struct isl_tab_var *var)
1293 while (row_is_neg(tab, var->index)) {
1294 find_pivot(tab, var, var, 1, &row, &col);
1297 if (isl_tab_pivot(tab, row, col) < 0)
1299 if (!var->is_row) /* manifestly unbounded */
1302 return row_sgn(tab, var->index);
1305 /* Perform pivots until we are sure that the row variable "var"
1306 * can attain non-negative values. After return from this
1307 * function, "var" is still a row variable, but its sample
1308 * value may not be non-negative, even if the function returns 1.
1310 static int at_least_zero(struct isl_tab *tab, struct isl_tab_var *var)
1314 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
1315 find_pivot(tab, var, var, 1, &row, &col);
1318 if (row == var->index) /* manifestly unbounded */
1320 if (isl_tab_pivot(tab, row, col) < 0)
1323 return !isl_int_is_neg(tab->mat->row[var->index][1]);
1326 /* Return a negative value if "var" can attain negative values.
1327 * Return a non-negative value otherwise.
1329 * If "var" is manifestly unbounded wrt negative values, we are done.
1330 * Otherwise, if var is in a column, we can pivot it down to a row.
1331 * Then we continue pivoting down until either
1332 * - the pivot would result in a manifestly unbounded column
1333 * => we don't perform the pivot, but simply return -1
1334 * - no more down pivots can be performed
1335 * - the sample value is negative
1336 * If the sample value becomes negative and the variable is supposed
1337 * to be nonnegative, then we undo the last pivot.
1338 * However, if the last pivot has made the pivoting variable
1339 * obviously redundant, then it may have moved to another row.
1340 * In that case we look for upward pivots until we reach a non-negative
1343 static int sign_of_min(struct isl_tab *tab, struct isl_tab_var *var)
1346 struct isl_tab_var *pivot_var = NULL;
1348 if (min_is_manifestly_unbounded(tab, var))
1352 row = pivot_row(tab, NULL, -1, col);
1353 pivot_var = var_from_col(tab, col);
1354 if (isl_tab_pivot(tab, row, col) < 0)
1356 if (var->is_redundant)
1358 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
1359 if (var->is_nonneg) {
1360 if (!pivot_var->is_redundant &&
1361 pivot_var->index == row) {
1362 if (isl_tab_pivot(tab, row, col) < 0)
1365 if (restore_row(tab, var) < -1)
1371 if (var->is_redundant)
1373 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
1374 find_pivot(tab, var, var, -1, &row, &col);
1375 if (row == var->index)
1378 return isl_int_sgn(tab->mat->row[var->index][1]);
1379 pivot_var = var_from_col(tab, col);
1380 if (isl_tab_pivot(tab, row, col) < 0)
1382 if (var->is_redundant)
1385 if (pivot_var && var->is_nonneg) {
1386 /* pivot back to non-negative value */
1387 if (!pivot_var->is_redundant && pivot_var->index == row) {
1388 if (isl_tab_pivot(tab, row, col) < 0)
1391 if (restore_row(tab, var) < -1)
1397 static int row_at_most_neg_one(struct isl_tab *tab, int row)
1400 if (isl_int_is_pos(tab->mat->row[row][2]))
1402 if (isl_int_is_neg(tab->mat->row[row][2]))
1405 return isl_int_is_neg(tab->mat->row[row][1]) &&
1406 isl_int_abs_ge(tab->mat->row[row][1],
1407 tab->mat->row[row][0]);
1410 /* Return 1 if "var" can attain values <= -1.
1411 * Return 0 otherwise.
1413 * The sample value of "var" is assumed to be non-negative when the
1414 * the function is called. If 1 is returned then the constraint
1415 * is not redundant and the sample value is made non-negative again before
1416 * the function returns.
1418 int isl_tab_min_at_most_neg_one(struct isl_tab *tab, struct isl_tab_var *var)
1421 struct isl_tab_var *pivot_var;
1423 if (min_is_manifestly_unbounded(tab, var))
1427 row = pivot_row(tab, NULL, -1, col);
1428 pivot_var = var_from_col(tab, col);
1429 if (isl_tab_pivot(tab, row, col) < 0)
1431 if (var->is_redundant)
1433 if (row_at_most_neg_one(tab, var->index)) {
1434 if (var->is_nonneg) {
1435 if (!pivot_var->is_redundant &&
1436 pivot_var->index == row) {
1437 if (isl_tab_pivot(tab, row, col) < 0)
1440 if (restore_row(tab, var) < -1)
1446 if (var->is_redundant)
1449 find_pivot(tab, var, var, -1, &row, &col);
1450 if (row == var->index) {
1451 if (restore_row(tab, var) < -1)
1457 pivot_var = var_from_col(tab, col);
1458 if (isl_tab_pivot(tab, row, col) < 0)
1460 if (var->is_redundant)
1462 } while (!row_at_most_neg_one(tab, var->index));
1463 if (var->is_nonneg) {
1464 /* pivot back to non-negative value */
1465 if (!pivot_var->is_redundant && pivot_var->index == row)
1466 if (isl_tab_pivot(tab, row, col) < 0)
1468 if (restore_row(tab, var) < -1)
1474 /* Return 1 if "var" can attain values >= 1.
1475 * Return 0 otherwise.
1477 static int at_least_one(struct isl_tab *tab, struct isl_tab_var *var)
1482 if (max_is_manifestly_unbounded(tab, var))
1484 if (to_row(tab, var, 1) < 0)
1486 r = tab->mat->row[var->index];
1487 while (isl_int_lt(r[1], r[0])) {
1488 find_pivot(tab, var, var, 1, &row, &col);
1490 return isl_int_ge(r[1], r[0]);
1491 if (row == var->index) /* manifestly unbounded */
1493 if (isl_tab_pivot(tab, row, col) < 0)
1499 static void swap_cols(struct isl_tab *tab, int col1, int col2)
1502 unsigned off = 2 + tab->M;
1503 t = tab->col_var[col1];
1504 tab->col_var[col1] = tab->col_var[col2];
1505 tab->col_var[col2] = t;
1506 var_from_col(tab, col1)->index = col1;
1507 var_from_col(tab, col2)->index = col2;
1508 tab->mat = isl_mat_swap_cols(tab->mat, off + col1, off + col2);
1511 /* Mark column with index "col" as representing a zero variable.
1512 * If we may need to undo the operation the column is kept,
1513 * but no longer considered.
1514 * Otherwise, the column is simply removed.
1516 * The column may be interchanged with some other column. If it
1517 * is interchanged with a later column, return 1. Otherwise return 0.
1518 * If the columns are checked in order in the calling function,
1519 * then a return value of 1 means that the column with the given
1520 * column number may now contain a different column that
1521 * hasn't been checked yet.
1523 int isl_tab_kill_col(struct isl_tab *tab, int col)
1525 var_from_col(tab, col)->is_zero = 1;
1526 if (tab->need_undo) {
1527 if (isl_tab_push_var(tab, isl_tab_undo_zero,
1528 var_from_col(tab, col)) < 0)
1530 if (col != tab->n_dead)
1531 swap_cols(tab, col, tab->n_dead);
1535 if (col != tab->n_col - 1)
1536 swap_cols(tab, col, tab->n_col - 1);
1537 var_from_col(tab, tab->n_col - 1)->index = -1;
1543 static int row_is_manifestly_non_integral(struct isl_tab *tab, int row)
1545 unsigned off = 2 + tab->M;
1547 if (tab->M && !isl_int_eq(tab->mat->row[row][2],
1548 tab->mat->row[row][0]))
1550 if (isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
1551 tab->n_col - tab->n_dead) != -1)
1554 return !isl_int_is_divisible_by(tab->mat->row[row][1],
1555 tab->mat->row[row][0]);
1558 /* For integer tableaus, check if any of the coordinates are stuck
1559 * at a non-integral value.
1561 static int tab_is_manifestly_empty(struct isl_tab *tab)
1570 for (i = 0; i < tab->n_var; ++i) {
1571 if (!tab->var[i].is_row)
1573 if (row_is_manifestly_non_integral(tab, tab->var[i].index))
1580 /* Row variable "var" is non-negative and cannot attain any values
1581 * larger than zero. This means that the coefficients of the unrestricted
1582 * column variables are zero and that the coefficients of the non-negative
1583 * column variables are zero or negative.
1584 * Each of the non-negative variables with a negative coefficient can
1585 * then also be written as the negative sum of non-negative variables
1586 * and must therefore also be zero.
1588 static int close_row(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
1589 static int close_row(struct isl_tab *tab, struct isl_tab_var *var)
1592 struct isl_mat *mat = tab->mat;
1593 unsigned off = 2 + tab->M;
1595 isl_assert(tab->mat->ctx, var->is_nonneg, return -1);
1598 if (isl_tab_push_var(tab, isl_tab_undo_zero, var) < 0)
1600 for (j = tab->n_dead; j < tab->n_col; ++j) {
1602 if (isl_int_is_zero(mat->row[var->index][off + j]))
1604 isl_assert(tab->mat->ctx,
1605 isl_int_is_neg(mat->row[var->index][off + j]), return -1);
1606 recheck = isl_tab_kill_col(tab, j);
1612 if (isl_tab_mark_redundant(tab, var->index) < 0)
1614 if (tab_is_manifestly_empty(tab) && isl_tab_mark_empty(tab) < 0)
1619 /* Add a constraint to the tableau and allocate a row for it.
1620 * Return the index into the constraint array "con".
1622 int isl_tab_allocate_con(struct isl_tab *tab)
1626 isl_assert(tab->mat->ctx, tab->n_row < tab->mat->n_row, return -1);
1627 isl_assert(tab->mat->ctx, tab->n_con < tab->max_con, return -1);
1630 tab->con[r].index = tab->n_row;
1631 tab->con[r].is_row = 1;
1632 tab->con[r].is_nonneg = 0;
1633 tab->con[r].is_zero = 0;
1634 tab->con[r].is_redundant = 0;
1635 tab->con[r].frozen = 0;
1636 tab->con[r].negated = 0;
1637 tab->row_var[tab->n_row] = ~r;
1641 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]) < 0)
1647 /* Add a variable to the tableau and allocate a column for it.
1648 * Return the index into the variable array "var".
1650 int isl_tab_allocate_var(struct isl_tab *tab)
1654 unsigned off = 2 + tab->M;
1656 isl_assert(tab->mat->ctx, tab->n_col < tab->mat->n_col, return -1);
1657 isl_assert(tab->mat->ctx, tab->n_var < tab->max_var, return -1);
1660 tab->var[r].index = tab->n_col;
1661 tab->var[r].is_row = 0;
1662 tab->var[r].is_nonneg = 0;
1663 tab->var[r].is_zero = 0;
1664 tab->var[r].is_redundant = 0;
1665 tab->var[r].frozen = 0;
1666 tab->var[r].negated = 0;
1667 tab->col_var[tab->n_col] = r;
1669 for (i = 0; i < tab->n_row; ++i)
1670 isl_int_set_si(tab->mat->row[i][off + tab->n_col], 0);
1674 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->var[r]) < 0)
1680 /* Add a row to the tableau. The row is given as an affine combination
1681 * of the original variables and needs to be expressed in terms of the
1684 * We add each term in turn.
1685 * If r = n/d_r is the current sum and we need to add k x, then
1686 * if x is a column variable, we increase the numerator of
1687 * this column by k d_r
1688 * if x = f/d_x is a row variable, then the new representation of r is
1690 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1691 * --- + --- = ------------------- = -------------------
1692 * d_r d_r d_r d_x/g m
1694 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1696 * If tab->M is set, then, internally, each variable x is represented
1697 * as x' - M. We then also need no subtract k d_r from the coefficient of M.
1699 int isl_tab_add_row(struct isl_tab *tab, isl_int *line)
1705 unsigned off = 2 + tab->M;
1707 r = isl_tab_allocate_con(tab);
1713 row = tab->mat->row[tab->con[r].index];
1714 isl_int_set_si(row[0], 1);
1715 isl_int_set(row[1], line[0]);
1716 isl_seq_clr(row + 2, tab->M + tab->n_col);
1717 for (i = 0; i < tab->n_var; ++i) {
1718 if (tab->var[i].is_zero)
1720 if (tab->var[i].is_row) {
1722 row[0], tab->mat->row[tab->var[i].index][0]);
1723 isl_int_swap(a, row[0]);
1724 isl_int_divexact(a, row[0], a);
1726 row[0], tab->mat->row[tab->var[i].index][0]);
1727 isl_int_mul(b, b, line[1 + i]);
1728 isl_seq_combine(row + 1, a, row + 1,
1729 b, tab->mat->row[tab->var[i].index] + 1,
1730 1 + tab->M + tab->n_col);
1732 isl_int_addmul(row[off + tab->var[i].index],
1733 line[1 + i], row[0]);
1734 if (tab->M && i >= tab->n_param && i < tab->n_var - tab->n_div)
1735 isl_int_submul(row[2], line[1 + i], row[0]);
1737 isl_seq_normalize(tab->mat->ctx, row, off + tab->n_col);
1742 tab->row_sign[tab->con[r].index] = isl_tab_row_unknown;
1747 static int drop_row(struct isl_tab *tab, int row)
1749 isl_assert(tab->mat->ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
1750 if (row != tab->n_row - 1)
1751 swap_rows(tab, row, tab->n_row - 1);
1757 static int drop_col(struct isl_tab *tab, int col)
1759 isl_assert(tab->mat->ctx, tab->col_var[col] == tab->n_var - 1, return -1);
1760 if (col != tab->n_col - 1)
1761 swap_cols(tab, col, tab->n_col - 1);
1767 /* Add inequality "ineq" and check if it conflicts with the
1768 * previously added constraints or if it is obviously redundant.
1770 int isl_tab_add_ineq(struct isl_tab *tab, isl_int *ineq)
1779 struct isl_basic_map *bmap = tab->bmap;
1781 isl_assert(tab->mat->ctx, tab->n_eq == bmap->n_eq, return -1);
1782 isl_assert(tab->mat->ctx,
1783 tab->n_con == bmap->n_eq + bmap->n_ineq, return -1);
1784 tab->bmap = isl_basic_map_add_ineq(tab->bmap, ineq);
1785 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1792 isl_int_swap(ineq[0], cst);
1794 r = isl_tab_add_row(tab, ineq);
1796 isl_int_swap(ineq[0], cst);
1801 tab->con[r].is_nonneg = 1;
1802 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
1804 if (isl_tab_row_is_redundant(tab, tab->con[r].index)) {
1805 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1810 sgn = restore_row(tab, &tab->con[r]);
1814 return isl_tab_mark_empty(tab);
1815 if (tab->con[r].is_row && isl_tab_row_is_redundant(tab, tab->con[r].index))
1816 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1821 /* Pivot a non-negative variable down until it reaches the value zero
1822 * and then pivot the variable into a column position.
1824 static int to_col(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
1825 static int to_col(struct isl_tab *tab, struct isl_tab_var *var)
1829 unsigned off = 2 + tab->M;
1834 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
1835 find_pivot(tab, var, NULL, -1, &row, &col);
1836 isl_assert(tab->mat->ctx, row != -1, return -1);
1837 if (isl_tab_pivot(tab, row, col) < 0)
1843 for (i = tab->n_dead; i < tab->n_col; ++i)
1844 if (!isl_int_is_zero(tab->mat->row[var->index][off + i]))
1847 isl_assert(tab->mat->ctx, i < tab->n_col, return -1);
1848 if (isl_tab_pivot(tab, var->index, i) < 0)
1854 /* We assume Gaussian elimination has been performed on the equalities.
1855 * The equalities can therefore never conflict.
1856 * Adding the equalities is currently only really useful for a later call
1857 * to isl_tab_ineq_type.
1859 static struct isl_tab *add_eq(struct isl_tab *tab, isl_int *eq)
1866 r = isl_tab_add_row(tab, eq);
1870 r = tab->con[r].index;
1871 i = isl_seq_first_non_zero(tab->mat->row[r] + 2 + tab->M + tab->n_dead,
1872 tab->n_col - tab->n_dead);
1873 isl_assert(tab->mat->ctx, i >= 0, goto error);
1875 if (isl_tab_pivot(tab, r, i) < 0)
1877 if (isl_tab_kill_col(tab, i) < 0)
1887 static int row_is_manifestly_zero(struct isl_tab *tab, int row)
1889 unsigned off = 2 + tab->M;
1891 if (!isl_int_is_zero(tab->mat->row[row][1]))
1893 if (tab->M && !isl_int_is_zero(tab->mat->row[row][2]))
1895 return isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
1896 tab->n_col - tab->n_dead) == -1;
1899 /* Add an equality that is known to be valid for the given tableau.
1901 int isl_tab_add_valid_eq(struct isl_tab *tab, isl_int *eq)
1903 struct isl_tab_var *var;
1908 r = isl_tab_add_row(tab, eq);
1914 if (row_is_manifestly_zero(tab, r)) {
1916 if (isl_tab_mark_redundant(tab, r) < 0)
1921 if (isl_int_is_neg(tab->mat->row[r][1])) {
1922 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1927 if (to_col(tab, var) < 0)
1930 if (isl_tab_kill_col(tab, var->index) < 0)
1936 static int add_zero_row(struct isl_tab *tab)
1941 r = isl_tab_allocate_con(tab);
1945 row = tab->mat->row[tab->con[r].index];
1946 isl_seq_clr(row + 1, 1 + tab->M + tab->n_col);
1947 isl_int_set_si(row[0], 1);
1952 /* Add equality "eq" and check if it conflicts with the
1953 * previously added constraints or if it is obviously redundant.
1955 int isl_tab_add_eq(struct isl_tab *tab, isl_int *eq)
1957 struct isl_tab_undo *snap = NULL;
1958 struct isl_tab_var *var;
1966 isl_assert(tab->mat->ctx, !tab->M, return -1);
1969 snap = isl_tab_snap(tab);
1973 isl_int_swap(eq[0], cst);
1975 r = isl_tab_add_row(tab, eq);
1977 isl_int_swap(eq[0], cst);
1985 if (row_is_manifestly_zero(tab, row)) {
1987 if (isl_tab_rollback(tab, snap) < 0)
1995 tab->bmap = isl_basic_map_add_ineq(tab->bmap, eq);
1996 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1998 isl_seq_neg(eq, eq, 1 + tab->n_var);
1999 tab->bmap = isl_basic_map_add_ineq(tab->bmap, eq);
2000 isl_seq_neg(eq, eq, 1 + tab->n_var);
2001 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
2005 if (add_zero_row(tab) < 0)
2009 sgn = isl_int_sgn(tab->mat->row[row][1]);
2012 isl_seq_neg(tab->mat->row[row] + 1, tab->mat->row[row] + 1,
2019 sgn = sign_of_max(tab, var);
2023 if (isl_tab_mark_empty(tab) < 0)
2030 if (to_col(tab, var) < 0)
2033 if (isl_tab_kill_col(tab, var->index) < 0)
2039 /* Construct and return an inequality that expresses an upper bound
2041 * In particular, if the div is given by
2045 * then the inequality expresses
2049 static struct isl_vec *ineq_for_div(struct isl_basic_map *bmap, unsigned div)
2053 struct isl_vec *ineq;
2058 total = isl_basic_map_total_dim(bmap);
2059 div_pos = 1 + total - bmap->n_div + div;
2061 ineq = isl_vec_alloc(bmap->ctx, 1 + total);
2065 isl_seq_cpy(ineq->el, bmap->div[div] + 1, 1 + total);
2066 isl_int_neg(ineq->el[div_pos], bmap->div[div][0]);
2070 /* For a div d = floor(f/m), add the constraints
2073 * -(f-(m-1)) + m d >= 0
2075 * Note that the second constraint is the negation of
2079 * If add_ineq is not NULL, then this function is used
2080 * instead of isl_tab_add_ineq to effectively add the inequalities.
2082 static int add_div_constraints(struct isl_tab *tab, unsigned div,
2083 int (*add_ineq)(void *user, isl_int *), void *user)
2087 struct isl_vec *ineq;
2089 total = isl_basic_map_total_dim(tab->bmap);
2090 div_pos = 1 + total - tab->bmap->n_div + div;
2092 ineq = ineq_for_div(tab->bmap, div);
2097 if (add_ineq(user, ineq->el) < 0)
2100 if (isl_tab_add_ineq(tab, ineq->el) < 0)
2104 isl_seq_neg(ineq->el, tab->bmap->div[div] + 1, 1 + total);
2105 isl_int_set(ineq->el[div_pos], tab->bmap->div[div][0]);
2106 isl_int_add(ineq->el[0], ineq->el[0], ineq->el[div_pos]);
2107 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
2110 if (add_ineq(user, ineq->el) < 0)
2113 if (isl_tab_add_ineq(tab, ineq->el) < 0)
2125 /* Check whether the div described by "div" is obviously non-negative.
2126 * If we are using a big parameter, then we will encode the div
2127 * as div' = M + div, which is always non-negative.
2128 * Otherwise, we check whether div is a non-negative affine combination
2129 * of non-negative variables.
2131 static int div_is_nonneg(struct isl_tab *tab, __isl_keep isl_vec *div)
2138 if (isl_int_is_neg(div->el[1]))
2141 for (i = 0; i < tab->n_var; ++i) {
2142 if (isl_int_is_neg(div->el[2 + i]))
2144 if (isl_int_is_zero(div->el[2 + i]))
2146 if (!tab->var[i].is_nonneg)
2153 /* Add an extra div, prescribed by "div" to the tableau and
2154 * the associated bmap (which is assumed to be non-NULL).
2156 * If add_ineq is not NULL, then this function is used instead
2157 * of isl_tab_add_ineq to add the div constraints.
2158 * This complication is needed because the code in isl_tab_pip
2159 * wants to perform some extra processing when an inequality
2160 * is added to the tableau.
2162 int isl_tab_add_div(struct isl_tab *tab, __isl_keep isl_vec *div,
2163 int (*add_ineq)(void *user, isl_int *), void *user)
2172 isl_assert(tab->mat->ctx, tab->bmap, return -1);
2174 nonneg = div_is_nonneg(tab, div);
2176 if (isl_tab_extend_cons(tab, 3) < 0)
2178 if (isl_tab_extend_vars(tab, 1) < 0)
2180 r = isl_tab_allocate_var(tab);
2185 tab->var[r].is_nonneg = 1;
2187 tab->bmap = isl_basic_map_extend_space(tab->bmap,
2188 isl_basic_map_get_space(tab->bmap), 1, 0, 2);
2189 k = isl_basic_map_alloc_div(tab->bmap);
2192 isl_seq_cpy(tab->bmap->div[k], div->el, div->size);
2193 if (isl_tab_push(tab, isl_tab_undo_bmap_div) < 0)
2196 if (add_div_constraints(tab, k, add_ineq, user) < 0)
2202 /* If "track" is set, then we want to keep track of all constraints in tab
2203 * in its bmap field. This field is initialized from a copy of "bmap",
2204 * so we need to make sure that all constraints in "bmap" also appear
2205 * in the constructed tab.
2207 __isl_give struct isl_tab *isl_tab_from_basic_map(
2208 __isl_keep isl_basic_map *bmap, int track)
2211 struct isl_tab *tab;
2215 tab = isl_tab_alloc(bmap->ctx,
2216 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
2217 isl_basic_map_total_dim(bmap), 0);
2220 tab->preserve = track;
2221 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
2222 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) {
2223 if (isl_tab_mark_empty(tab) < 0)
2227 for (i = 0; i < bmap->n_eq; ++i) {
2228 tab = add_eq(tab, bmap->eq[i]);
2232 for (i = 0; i < bmap->n_ineq; ++i) {
2233 if (isl_tab_add_ineq(tab, bmap->ineq[i]) < 0)
2239 if (track && isl_tab_track_bmap(tab, isl_basic_map_copy(bmap)) < 0)
2247 __isl_give struct isl_tab *isl_tab_from_basic_set(
2248 __isl_keep isl_basic_set *bset, int track)
2250 return isl_tab_from_basic_map(bset, track);
2253 /* Construct a tableau corresponding to the recession cone of "bset".
2255 struct isl_tab *isl_tab_from_recession_cone(__isl_keep isl_basic_set *bset,
2260 struct isl_tab *tab;
2261 unsigned offset = 0;
2266 offset = isl_basic_set_dim(bset, isl_dim_param);
2267 tab = isl_tab_alloc(bset->ctx, bset->n_eq + bset->n_ineq,
2268 isl_basic_set_total_dim(bset) - offset, 0);
2271 tab->rational = ISL_F_ISSET(bset, ISL_BASIC_SET_RATIONAL);
2275 for (i = 0; i < bset->n_eq; ++i) {
2276 isl_int_swap(bset->eq[i][offset], cst);
2278 if (isl_tab_add_eq(tab, bset->eq[i] + offset) < 0)
2281 tab = add_eq(tab, bset->eq[i]);
2282 isl_int_swap(bset->eq[i][offset], cst);
2286 for (i = 0; i < bset->n_ineq; ++i) {
2288 isl_int_swap(bset->ineq[i][offset], cst);
2289 r = isl_tab_add_row(tab, bset->ineq[i] + offset);
2290 isl_int_swap(bset->ineq[i][offset], cst);
2293 tab->con[r].is_nonneg = 1;
2294 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
2306 /* Assuming "tab" is the tableau of a cone, check if the cone is
2307 * bounded, i.e., if it is empty or only contains the origin.
2309 int isl_tab_cone_is_bounded(struct isl_tab *tab)
2317 if (tab->n_dead == tab->n_col)
2321 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2322 struct isl_tab_var *var;
2324 var = isl_tab_var_from_row(tab, i);
2325 if (!var->is_nonneg)
2327 sgn = sign_of_max(tab, var);
2332 if (close_row(tab, var) < 0)
2336 if (tab->n_dead == tab->n_col)
2338 if (i == tab->n_row)
2343 int isl_tab_sample_is_integer(struct isl_tab *tab)
2350 for (i = 0; i < tab->n_var; ++i) {
2352 if (!tab->var[i].is_row)
2354 row = tab->var[i].index;
2355 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
2356 tab->mat->row[row][0]))
2362 static struct isl_vec *extract_integer_sample(struct isl_tab *tab)
2365 struct isl_vec *vec;
2367 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
2371 isl_int_set_si(vec->block.data[0], 1);
2372 for (i = 0; i < tab->n_var; ++i) {
2373 if (!tab->var[i].is_row)
2374 isl_int_set_si(vec->block.data[1 + i], 0);
2376 int row = tab->var[i].index;
2377 isl_int_divexact(vec->block.data[1 + i],
2378 tab->mat->row[row][1], tab->mat->row[row][0]);
2385 struct isl_vec *isl_tab_get_sample_value(struct isl_tab *tab)
2388 struct isl_vec *vec;
2394 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
2400 isl_int_set_si(vec->block.data[0], 1);
2401 for (i = 0; i < tab->n_var; ++i) {
2403 if (!tab->var[i].is_row) {
2404 isl_int_set_si(vec->block.data[1 + i], 0);
2407 row = tab->var[i].index;
2408 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
2409 isl_int_divexact(m, tab->mat->row[row][0], m);
2410 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
2411 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
2412 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
2414 vec = isl_vec_normalize(vec);
2420 /* Update "bmap" based on the results of the tableau "tab".
2421 * In particular, implicit equalities are made explicit, redundant constraints
2422 * are removed and if the sample value happens to be integer, it is stored
2423 * in "bmap" (unless "bmap" already had an integer sample).
2425 * The tableau is assumed to have been created from "bmap" using
2426 * isl_tab_from_basic_map.
2428 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
2429 struct isl_tab *tab)
2441 bmap = isl_basic_map_set_to_empty(bmap);
2443 for (i = bmap->n_ineq - 1; i >= 0; --i) {
2444 if (isl_tab_is_equality(tab, n_eq + i))
2445 isl_basic_map_inequality_to_equality(bmap, i);
2446 else if (isl_tab_is_redundant(tab, n_eq + i))
2447 isl_basic_map_drop_inequality(bmap, i);
2449 if (bmap->n_eq != n_eq)
2450 isl_basic_map_gauss(bmap, NULL);
2451 if (!tab->rational &&
2452 !bmap->sample && isl_tab_sample_is_integer(tab))
2453 bmap->sample = extract_integer_sample(tab);
2457 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
2458 struct isl_tab *tab)
2460 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
2461 (struct isl_basic_map *)bset, tab);
2464 /* Given a non-negative variable "var", add a new non-negative variable
2465 * that is the opposite of "var", ensuring that var can only attain the
2467 * If var = n/d is a row variable, then the new variable = -n/d.
2468 * If var is a column variables, then the new variable = -var.
2469 * If the new variable cannot attain non-negative values, then
2470 * the resulting tableau is empty.
2471 * Otherwise, we know the value will be zero and we close the row.
2473 static int cut_to_hyperplane(struct isl_tab *tab, struct isl_tab_var *var)
2478 unsigned off = 2 + tab->M;
2482 isl_assert(tab->mat->ctx, !var->is_redundant, return -1);
2483 isl_assert(tab->mat->ctx, var->is_nonneg, return -1);
2485 if (isl_tab_extend_cons(tab, 1) < 0)
2489 tab->con[r].index = tab->n_row;
2490 tab->con[r].is_row = 1;
2491 tab->con[r].is_nonneg = 0;
2492 tab->con[r].is_zero = 0;
2493 tab->con[r].is_redundant = 0;
2494 tab->con[r].frozen = 0;
2495 tab->con[r].negated = 0;
2496 tab->row_var[tab->n_row] = ~r;
2497 row = tab->mat->row[tab->n_row];
2500 isl_int_set(row[0], tab->mat->row[var->index][0]);
2501 isl_seq_neg(row + 1,
2502 tab->mat->row[var->index] + 1, 1 + tab->n_col);
2504 isl_int_set_si(row[0], 1);
2505 isl_seq_clr(row + 1, 1 + tab->n_col);
2506 isl_int_set_si(row[off + var->index], -1);
2511 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]) < 0)
2514 sgn = sign_of_max(tab, &tab->con[r]);
2518 if (isl_tab_mark_empty(tab) < 0)
2522 tab->con[r].is_nonneg = 1;
2523 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
2526 if (close_row(tab, &tab->con[r]) < 0)
2532 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2533 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2534 * by r' = r + 1 >= 0.
2535 * If r is a row variable, we simply increase the constant term by one
2536 * (taking into account the denominator).
2537 * If r is a column variable, then we need to modify each row that
2538 * refers to r = r' - 1 by substituting this equality, effectively
2539 * subtracting the coefficient of the column from the constant.
2540 * We should only do this if the minimum is manifestly unbounded,
2541 * however. Otherwise, we may end up with negative sample values
2542 * for non-negative variables.
2543 * So, if r is a column variable with a minimum that is not
2544 * manifestly unbounded, then we need to move it to a row.
2545 * However, the sample value of this row may be negative,
2546 * even after the relaxation, so we need to restore it.
2547 * We therefore prefer to pivot a column up to a row, if possible.
2549 struct isl_tab *isl_tab_relax(struct isl_tab *tab, int con)
2551 struct isl_tab_var *var;
2552 unsigned off = 2 + tab->M;
2557 var = &tab->con[con];
2559 if (var->is_row && (var->index < 0 || var->index < tab->n_redundant))
2560 isl_die(tab->mat->ctx, isl_error_invalid,
2561 "cannot relax redundant constraint", goto error);
2562 if (!var->is_row && (var->index < 0 || var->index < tab->n_dead))
2563 isl_die(tab->mat->ctx, isl_error_invalid,
2564 "cannot relax dead constraint", goto error);
2566 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2567 if (to_row(tab, var, 1) < 0)
2569 if (!var->is_row && !min_is_manifestly_unbounded(tab, var))
2570 if (to_row(tab, var, -1) < 0)
2574 isl_int_add(tab->mat->row[var->index][1],
2575 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2576 if (restore_row(tab, var) < 0)
2581 for (i = 0; i < tab->n_row; ++i) {
2582 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2584 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
2585 tab->mat->row[i][off + var->index]);
2590 if (isl_tab_push_var(tab, isl_tab_undo_relax, var) < 0)
2599 int isl_tab_select_facet(struct isl_tab *tab, int con)
2604 return cut_to_hyperplane(tab, &tab->con[con]);
2607 static int may_be_equality(struct isl_tab *tab, int row)
2609 return tab->rational ? isl_int_is_zero(tab->mat->row[row][1])
2610 : isl_int_lt(tab->mat->row[row][1],
2611 tab->mat->row[row][0]);
2614 /* Check for (near) equalities among the constraints.
2615 * A constraint is an equality if it is non-negative and if
2616 * its maximal value is either
2617 * - zero (in case of rational tableaus), or
2618 * - strictly less than 1 (in case of integer tableaus)
2620 * We first mark all non-redundant and non-dead variables that
2621 * are not frozen and not obviously not an equality.
2622 * Then we iterate over all marked variables if they can attain
2623 * any values larger than zero or at least one.
2624 * If the maximal value is zero, we mark any column variables
2625 * that appear in the row as being zero and mark the row as being redundant.
2626 * Otherwise, if the maximal value is strictly less than one (and the
2627 * tableau is integer), then we restrict the value to being zero
2628 * by adding an opposite non-negative variable.
2630 int isl_tab_detect_implicit_equalities(struct isl_tab *tab)
2639 if (tab->n_dead == tab->n_col)
2643 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2644 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2645 var->marked = !var->frozen && var->is_nonneg &&
2646 may_be_equality(tab, i);
2650 for (i = tab->n_dead; i < tab->n_col; ++i) {
2651 struct isl_tab_var *var = var_from_col(tab, i);
2652 var->marked = !var->frozen && var->is_nonneg;
2657 struct isl_tab_var *var;
2659 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2660 var = isl_tab_var_from_row(tab, i);
2664 if (i == tab->n_row) {
2665 for (i = tab->n_dead; i < tab->n_col; ++i) {
2666 var = var_from_col(tab, i);
2670 if (i == tab->n_col)
2675 sgn = sign_of_max(tab, var);
2679 if (close_row(tab, var) < 0)
2681 } else if (!tab->rational && !at_least_one(tab, var)) {
2682 if (cut_to_hyperplane(tab, var) < 0)
2684 return isl_tab_detect_implicit_equalities(tab);
2686 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2687 var = isl_tab_var_from_row(tab, i);
2690 if (may_be_equality(tab, i))
2700 static int con_is_redundant(struct isl_tab *tab, struct isl_tab_var *var)
2704 if (tab->rational) {
2705 int sgn = sign_of_min(tab, var);
2710 int irred = isl_tab_min_at_most_neg_one(tab, var);
2717 /* Check for (near) redundant constraints.
2718 * A constraint is redundant if it is non-negative and if
2719 * its minimal value (temporarily ignoring the non-negativity) is either
2720 * - zero (in case of rational tableaus), or
2721 * - strictly larger than -1 (in case of integer tableaus)
2723 * We first mark all non-redundant and non-dead variables that
2724 * are not frozen and not obviously negatively unbounded.
2725 * Then we iterate over all marked variables if they can attain
2726 * any values smaller than zero or at most negative one.
2727 * If not, we mark the row as being redundant (assuming it hasn't
2728 * been detected as being obviously redundant in the mean time).
2730 int isl_tab_detect_redundant(struct isl_tab *tab)
2739 if (tab->n_redundant == tab->n_row)
2743 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2744 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2745 var->marked = !var->frozen && var->is_nonneg;
2749 for (i = tab->n_dead; i < tab->n_col; ++i) {
2750 struct isl_tab_var *var = var_from_col(tab, i);
2751 var->marked = !var->frozen && var->is_nonneg &&
2752 !min_is_manifestly_unbounded(tab, var);
2757 struct isl_tab_var *var;
2759 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2760 var = isl_tab_var_from_row(tab, i);
2764 if (i == tab->n_row) {
2765 for (i = tab->n_dead; i < tab->n_col; ++i) {
2766 var = var_from_col(tab, i);
2770 if (i == tab->n_col)
2775 red = con_is_redundant(tab, var);
2778 if (red && !var->is_redundant)
2779 if (isl_tab_mark_redundant(tab, var->index) < 0)
2781 for (i = tab->n_dead; i < tab->n_col; ++i) {
2782 var = var_from_col(tab, i);
2785 if (!min_is_manifestly_unbounded(tab, var))
2795 int isl_tab_is_equality(struct isl_tab *tab, int con)
2802 if (tab->con[con].is_zero)
2804 if (tab->con[con].is_redundant)
2806 if (!tab->con[con].is_row)
2807 return tab->con[con].index < tab->n_dead;
2809 row = tab->con[con].index;
2812 return isl_int_is_zero(tab->mat->row[row][1]) &&
2813 (!tab->M || isl_int_is_zero(tab->mat->row[row][2])) &&
2814 isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
2815 tab->n_col - tab->n_dead) == -1;
2818 /* Return the minimal value of the affine expression "f" with denominator
2819 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2820 * the expression cannot attain arbitrarily small values.
2821 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2822 * The return value reflects the nature of the result (empty, unbounded,
2823 * minimal value returned in *opt).
2825 enum isl_lp_result isl_tab_min(struct isl_tab *tab,
2826 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom,
2830 enum isl_lp_result res = isl_lp_ok;
2831 struct isl_tab_var *var;
2832 struct isl_tab_undo *snap;
2835 return isl_lp_error;
2838 return isl_lp_empty;
2840 snap = isl_tab_snap(tab);
2841 r = isl_tab_add_row(tab, f);
2843 return isl_lp_error;
2847 find_pivot(tab, var, var, -1, &row, &col);
2848 if (row == var->index) {
2849 res = isl_lp_unbounded;
2854 if (isl_tab_pivot(tab, row, col) < 0)
2855 return isl_lp_error;
2857 isl_int_mul(tab->mat->row[var->index][0],
2858 tab->mat->row[var->index][0], denom);
2859 if (ISL_FL_ISSET(flags, ISL_TAB_SAVE_DUAL)) {
2862 isl_vec_free(tab->dual);
2863 tab->dual = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_con);
2865 return isl_lp_error;
2866 isl_int_set(tab->dual->el[0], tab->mat->row[var->index][0]);
2867 for (i = 0; i < tab->n_con; ++i) {
2869 if (tab->con[i].is_row) {
2870 isl_int_set_si(tab->dual->el[1 + i], 0);
2873 pos = 2 + tab->M + tab->con[i].index;
2874 if (tab->con[i].negated)
2875 isl_int_neg(tab->dual->el[1 + i],
2876 tab->mat->row[var->index][pos]);
2878 isl_int_set(tab->dual->el[1 + i],
2879 tab->mat->row[var->index][pos]);
2882 if (opt && res == isl_lp_ok) {
2884 isl_int_set(*opt, tab->mat->row[var->index][1]);
2885 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
2887 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
2888 tab->mat->row[var->index][0]);
2890 if (isl_tab_rollback(tab, snap) < 0)
2891 return isl_lp_error;
2895 int isl_tab_is_redundant(struct isl_tab *tab, int con)
2899 if (tab->con[con].is_zero)
2901 if (tab->con[con].is_redundant)
2903 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
2906 /* Take a snapshot of the tableau that can be restored by s call to
2909 struct isl_tab_undo *isl_tab_snap(struct isl_tab *tab)
2917 /* Undo the operation performed by isl_tab_relax.
2919 static int unrelax(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
2920 static int unrelax(struct isl_tab *tab, struct isl_tab_var *var)
2922 unsigned off = 2 + tab->M;
2924 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2925 if (to_row(tab, var, 1) < 0)
2929 isl_int_sub(tab->mat->row[var->index][1],
2930 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2931 if (var->is_nonneg) {
2932 int sgn = restore_row(tab, var);
2933 isl_assert(tab->mat->ctx, sgn >= 0, return -1);
2938 for (i = 0; i < tab->n_row; ++i) {
2939 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2941 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
2942 tab->mat->row[i][off + var->index]);
2950 static int perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo) WARN_UNUSED;
2951 static int perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo)
2953 struct isl_tab_var *var = var_from_index(tab, undo->u.var_index);
2954 switch (undo->type) {
2955 case isl_tab_undo_nonneg:
2958 case isl_tab_undo_redundant:
2959 var->is_redundant = 0;
2961 restore_row(tab, isl_tab_var_from_row(tab, tab->n_redundant));
2963 case isl_tab_undo_freeze:
2966 case isl_tab_undo_zero:
2971 case isl_tab_undo_allocate:
2972 if (undo->u.var_index >= 0) {
2973 isl_assert(tab->mat->ctx, !var->is_row, return -1);
2974 drop_col(tab, var->index);
2978 if (!max_is_manifestly_unbounded(tab, var)) {
2979 if (to_row(tab, var, 1) < 0)
2981 } else if (!min_is_manifestly_unbounded(tab, var)) {
2982 if (to_row(tab, var, -1) < 0)
2985 if (to_row(tab, var, 0) < 0)
2988 drop_row(tab, var->index);
2990 case isl_tab_undo_relax:
2991 return unrelax(tab, var);
2993 isl_die(tab->mat->ctx, isl_error_internal,
2994 "perform_undo_var called on invalid undo record",
3001 /* Restore the tableau to the state where the basic variables
3002 * are those in "col_var".
3003 * We first construct a list of variables that are currently in
3004 * the basis, but shouldn't. Then we iterate over all variables
3005 * that should be in the basis and for each one that is currently
3006 * not in the basis, we exchange it with one of the elements of the
3007 * list constructed before.
3008 * We can always find an appropriate variable to pivot with because
3009 * the current basis is mapped to the old basis by a non-singular
3010 * matrix and so we can never end up with a zero row.
3012 static int restore_basis(struct isl_tab *tab, int *col_var)
3016 int *extra = NULL; /* current columns that contain bad stuff */
3017 unsigned off = 2 + tab->M;
3019 extra = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
3022 for (i = 0; i < tab->n_col; ++i) {
3023 for (j = 0; j < tab->n_col; ++j)
3024 if (tab->col_var[i] == col_var[j])
3028 extra[n_extra++] = i;
3030 for (i = 0; i < tab->n_col && n_extra > 0; ++i) {
3031 struct isl_tab_var *var;
3034 for (j = 0; j < tab->n_col; ++j)
3035 if (col_var[i] == tab->col_var[j])
3039 var = var_from_index(tab, col_var[i]);
3041 for (j = 0; j < n_extra; ++j)
3042 if (!isl_int_is_zero(tab->mat->row[row][off+extra[j]]))
3044 isl_assert(tab->mat->ctx, j < n_extra, goto error);
3045 if (isl_tab_pivot(tab, row, extra[j]) < 0)
3047 extra[j] = extra[--n_extra];
3057 /* Remove all samples with index n or greater, i.e., those samples
3058 * that were added since we saved this number of samples in
3059 * isl_tab_save_samples.
3061 static void drop_samples_since(struct isl_tab *tab, int n)
3065 for (i = tab->n_sample - 1; i >= 0 && tab->n_sample > n; --i) {
3066 if (tab->sample_index[i] < n)
3069 if (i != tab->n_sample - 1) {
3070 int t = tab->sample_index[tab->n_sample-1];
3071 tab->sample_index[tab->n_sample-1] = tab->sample_index[i];
3072 tab->sample_index[i] = t;
3073 isl_mat_swap_rows(tab->samples, tab->n_sample-1, i);
3079 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo) WARN_UNUSED;
3080 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo)
3082 switch (undo->type) {
3083 case isl_tab_undo_empty:
3086 case isl_tab_undo_nonneg:
3087 case isl_tab_undo_redundant:
3088 case isl_tab_undo_freeze:
3089 case isl_tab_undo_zero:
3090 case isl_tab_undo_allocate:
3091 case isl_tab_undo_relax:
3092 return perform_undo_var(tab, undo);
3093 case isl_tab_undo_bmap_eq:
3094 return isl_basic_map_free_equality(tab->bmap, 1);
3095 case isl_tab_undo_bmap_ineq:
3096 return isl_basic_map_free_inequality(tab->bmap, 1);
3097 case isl_tab_undo_bmap_div:
3098 if (isl_basic_map_free_div(tab->bmap, 1) < 0)
3101 tab->samples->n_col--;
3103 case isl_tab_undo_saved_basis:
3104 if (restore_basis(tab, undo->u.col_var) < 0)
3107 case isl_tab_undo_drop_sample:
3110 case isl_tab_undo_saved_samples:
3111 drop_samples_since(tab, undo->u.n);
3113 case isl_tab_undo_callback:
3114 return undo->u.callback->run(undo->u.callback);
3116 isl_assert(tab->mat->ctx, 0, return -1);
3121 /* Return the tableau to the state it was in when the snapshot "snap"
3124 int isl_tab_rollback(struct isl_tab *tab, struct isl_tab_undo *snap)
3126 struct isl_tab_undo *undo, *next;
3132 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
3136 if (perform_undo(tab, undo) < 0) {
3142 free_undo_record(undo);
3151 /* The given row "row" represents an inequality violated by all
3152 * points in the tableau. Check for some special cases of such
3153 * separating constraints.
3154 * In particular, if the row has been reduced to the constant -1,
3155 * then we know the inequality is adjacent (but opposite) to
3156 * an equality in the tableau.
3157 * If the row has been reduced to r = c*(-1 -r'), with r' an inequality
3158 * of the tableau and c a positive constant, then the inequality
3159 * is adjacent (but opposite) to the inequality r'.
3161 static enum isl_ineq_type separation_type(struct isl_tab *tab, unsigned row)
3164 unsigned off = 2 + tab->M;
3167 return isl_ineq_separate;
3169 if (!isl_int_is_one(tab->mat->row[row][0]))
3170 return isl_ineq_separate;
3172 pos = isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
3173 tab->n_col - tab->n_dead);
3175 if (isl_int_is_negone(tab->mat->row[row][1]))
3176 return isl_ineq_adj_eq;
3178 return isl_ineq_separate;
3181 if (!isl_int_eq(tab->mat->row[row][1],
3182 tab->mat->row[row][off + tab->n_dead + pos]))
3183 return isl_ineq_separate;
3185 pos = isl_seq_first_non_zero(
3186 tab->mat->row[row] + off + tab->n_dead + pos + 1,
3187 tab->n_col - tab->n_dead - pos - 1);
3189 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
3192 /* Check the effect of inequality "ineq" on the tableau "tab".
3194 * isl_ineq_redundant: satisfied by all points in the tableau
3195 * isl_ineq_separate: satisfied by no point in the tableau
3196 * isl_ineq_cut: satisfied by some by not all points
3197 * isl_ineq_adj_eq: adjacent to an equality
3198 * isl_ineq_adj_ineq: adjacent to an inequality.
3200 enum isl_ineq_type isl_tab_ineq_type(struct isl_tab *tab, isl_int *ineq)
3202 enum isl_ineq_type type = isl_ineq_error;
3203 struct isl_tab_undo *snap = NULL;
3208 return isl_ineq_error;
3210 if (isl_tab_extend_cons(tab, 1) < 0)
3211 return isl_ineq_error;
3213 snap = isl_tab_snap(tab);
3215 con = isl_tab_add_row(tab, ineq);
3219 row = tab->con[con].index;
3220 if (isl_tab_row_is_redundant(tab, row))
3221 type = isl_ineq_redundant;
3222 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
3224 isl_int_abs_ge(tab->mat->row[row][1],
3225 tab->mat->row[row][0]))) {
3226 int nonneg = at_least_zero(tab, &tab->con[con]);
3230 type = isl_ineq_cut;
3232 type = separation_type(tab, row);
3234 int red = con_is_redundant(tab, &tab->con[con]);
3238 type = isl_ineq_cut;
3240 type = isl_ineq_redundant;
3243 if (isl_tab_rollback(tab, snap))
3244 return isl_ineq_error;
3247 return isl_ineq_error;
3250 int isl_tab_track_bmap(struct isl_tab *tab, __isl_take isl_basic_map *bmap)
3252 bmap = isl_basic_map_cow(bmap);
3257 bmap = isl_basic_map_set_to_empty(bmap);
3264 isl_assert(tab->mat->ctx, tab->n_eq == bmap->n_eq, goto error);
3265 isl_assert(tab->mat->ctx,
3266 tab->n_con == bmap->n_eq + bmap->n_ineq, goto error);
3272 isl_basic_map_free(bmap);
3276 int isl_tab_track_bset(struct isl_tab *tab, __isl_take isl_basic_set *bset)
3278 return isl_tab_track_bmap(tab, (isl_basic_map *)bset);
3281 __isl_keep isl_basic_set *isl_tab_peek_bset(struct isl_tab *tab)
3286 return (isl_basic_set *)tab->bmap;
3289 static void isl_tab_print_internal(__isl_keep struct isl_tab *tab,
3290 FILE *out, int indent)
3296 fprintf(out, "%*snull tab\n", indent, "");
3299 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
3300 tab->n_redundant, tab->n_dead);
3302 fprintf(out, ", rational");
3304 fprintf(out, ", empty");
3306 fprintf(out, "%*s[", indent, "");
3307 for (i = 0; i < tab->n_var; ++i) {
3309 fprintf(out, (i == tab->n_param ||
3310 i == tab->n_var - tab->n_div) ? "; "
3312 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
3314 tab->var[i].is_zero ? " [=0]" :
3315 tab->var[i].is_redundant ? " [R]" : "");
3317 fprintf(out, "]\n");
3318 fprintf(out, "%*s[", indent, "");
3319 for (i = 0; i < tab->n_con; ++i) {
3322 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
3324 tab->con[i].is_zero ? " [=0]" :
3325 tab->con[i].is_redundant ? " [R]" : "");
3327 fprintf(out, "]\n");
3328 fprintf(out, "%*s[", indent, "");
3329 for (i = 0; i < tab->n_row; ++i) {
3330 const char *sign = "";
3333 if (tab->row_sign) {
3334 if (tab->row_sign[i] == isl_tab_row_unknown)
3336 else if (tab->row_sign[i] == isl_tab_row_neg)
3338 else if (tab->row_sign[i] == isl_tab_row_pos)
3343 fprintf(out, "r%d: %d%s%s", i, tab->row_var[i],
3344 isl_tab_var_from_row(tab, i)->is_nonneg ? " [>=0]" : "", sign);
3346 fprintf(out, "]\n");
3347 fprintf(out, "%*s[", indent, "");
3348 for (i = 0; i < tab->n_col; ++i) {
3351 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
3352 var_from_col(tab, i)->is_nonneg ? " [>=0]" : "");
3354 fprintf(out, "]\n");
3355 r = tab->mat->n_row;
3356 tab->mat->n_row = tab->n_row;
3357 c = tab->mat->n_col;
3358 tab->mat->n_col = 2 + tab->M + tab->n_col;
3359 isl_mat_print_internal(tab->mat, out, indent);
3360 tab->mat->n_row = r;
3361 tab->mat->n_col = c;
3363 isl_basic_map_print_internal(tab->bmap, out, indent);
3366 void isl_tab_dump(__isl_keep struct isl_tab *tab)
3368 isl_tab_print_internal(tab, stderr, 0);