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
11 #include "isl_map_private.h"
16 * The implementation of tableaus in this file was inspired by Section 8
17 * of David Detlefs, Greg Nelson and James B. Saxe, "Simplify: a theorem
18 * prover for program checking".
21 struct isl_tab *isl_tab_alloc(struct isl_ctx *ctx,
22 unsigned n_row, unsigned n_var, unsigned M)
28 tab = isl_calloc_type(ctx, struct isl_tab);
31 tab->mat = isl_mat_alloc(ctx, n_row, off + n_var);
34 tab->var = isl_alloc_array(ctx, struct isl_tab_var, n_var);
37 tab->con = isl_alloc_array(ctx, struct isl_tab_var, n_row);
40 tab->col_var = isl_alloc_array(ctx, int, n_var);
43 tab->row_var = isl_alloc_array(ctx, int, n_row);
46 for (i = 0; i < n_var; ++i) {
47 tab->var[i].index = i;
48 tab->var[i].is_row = 0;
49 tab->var[i].is_nonneg = 0;
50 tab->var[i].is_zero = 0;
51 tab->var[i].is_redundant = 0;
52 tab->var[i].frozen = 0;
53 tab->var[i].negated = 0;
73 tab->bottom.type = isl_tab_undo_bottom;
74 tab->bottom.next = NULL;
75 tab->top = &tab->bottom;
87 int isl_tab_extend_cons(struct isl_tab *tab, unsigned n_new)
89 unsigned off = 2 + tab->M;
94 if (tab->max_con < tab->n_con + n_new) {
95 struct isl_tab_var *con;
97 con = isl_realloc_array(tab->mat->ctx, tab->con,
98 struct isl_tab_var, tab->max_con + n_new);
102 tab->max_con += n_new;
104 if (tab->mat->n_row < tab->n_row + n_new) {
107 tab->mat = isl_mat_extend(tab->mat,
108 tab->n_row + n_new, off + tab->n_col);
111 row_var = isl_realloc_array(tab->mat->ctx, tab->row_var,
112 int, tab->mat->n_row);
115 tab->row_var = row_var;
117 enum isl_tab_row_sign *s;
118 s = isl_realloc_array(tab->mat->ctx, tab->row_sign,
119 enum isl_tab_row_sign, tab->mat->n_row);
128 /* Make room for at least n_new extra variables.
129 * Return -1 if anything went wrong.
131 int isl_tab_extend_vars(struct isl_tab *tab, unsigned n_new)
133 struct isl_tab_var *var;
134 unsigned off = 2 + tab->M;
136 if (tab->max_var < tab->n_var + n_new) {
137 var = isl_realloc_array(tab->mat->ctx, tab->var,
138 struct isl_tab_var, tab->n_var + n_new);
142 tab->max_var += n_new;
145 if (tab->mat->n_col < off + tab->n_col + n_new) {
148 tab->mat = isl_mat_extend(tab->mat,
149 tab->mat->n_row, off + tab->n_col + n_new);
152 p = isl_realloc_array(tab->mat->ctx, tab->col_var,
153 int, tab->n_col + n_new);
162 struct isl_tab *isl_tab_extend(struct isl_tab *tab, unsigned n_new)
164 if (isl_tab_extend_cons(tab, n_new) >= 0)
171 static void free_undo(struct isl_tab *tab)
173 struct isl_tab_undo *undo, *next;
175 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
182 void isl_tab_free(struct isl_tab *tab)
187 isl_mat_free(tab->mat);
188 isl_vec_free(tab->dual);
189 isl_basic_map_free(tab->bmap);
195 isl_mat_free(tab->samples);
196 free(tab->sample_index);
197 isl_mat_free(tab->basis);
201 struct isl_tab *isl_tab_dup(struct isl_tab *tab)
211 dup = isl_calloc_type(tab->ctx, struct isl_tab);
214 dup->mat = isl_mat_dup(tab->mat);
217 dup->var = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->max_var);
220 for (i = 0; i < tab->n_var; ++i)
221 dup->var[i] = tab->var[i];
222 dup->con = isl_alloc_array(tab->ctx, struct isl_tab_var, tab->max_con);
225 for (i = 0; i < tab->n_con; ++i)
226 dup->con[i] = tab->con[i];
227 dup->col_var = isl_alloc_array(tab->ctx, int, tab->mat->n_col - off);
230 for (i = 0; i < tab->n_col; ++i)
231 dup->col_var[i] = tab->col_var[i];
232 dup->row_var = isl_alloc_array(tab->ctx, int, tab->mat->n_row);
235 for (i = 0; i < tab->n_row; ++i)
236 dup->row_var[i] = tab->row_var[i];
238 dup->row_sign = isl_alloc_array(tab->ctx, enum isl_tab_row_sign,
242 for (i = 0; i < tab->n_row; ++i)
243 dup->row_sign[i] = tab->row_sign[i];
246 dup->samples = isl_mat_dup(tab->samples);
249 dup->sample_index = isl_alloc_array(tab->mat->ctx, int,
250 tab->samples->n_row);
251 if (!dup->sample_index)
253 dup->n_sample = tab->n_sample;
254 dup->n_outside = tab->n_outside;
256 dup->n_row = tab->n_row;
257 dup->n_con = tab->n_con;
258 dup->n_eq = tab->n_eq;
259 dup->max_con = tab->max_con;
260 dup->n_col = tab->n_col;
261 dup->n_var = tab->n_var;
262 dup->max_var = tab->max_var;
263 dup->n_param = tab->n_param;
264 dup->n_div = tab->n_div;
265 dup->n_dead = tab->n_dead;
266 dup->n_redundant = tab->n_redundant;
267 dup->rational = tab->rational;
268 dup->empty = tab->empty;
272 tab->cone = tab->cone;
273 dup->bottom.type = isl_tab_undo_bottom;
274 dup->bottom.next = NULL;
275 dup->top = &dup->bottom;
277 dup->n_zero = tab->n_zero;
278 dup->n_unbounded = tab->n_unbounded;
279 dup->basis = isl_mat_dup(tab->basis);
287 /* Construct the coefficient matrix of the product tableau
289 * mat{1,2} is the coefficient matrix of tableau {1,2}
290 * row{1,2} is the number of rows in tableau {1,2}
291 * col{1,2} is the number of columns in tableau {1,2}
292 * off is the offset to the coefficient column (skipping the
293 * denominator, the constant term and the big parameter if any)
294 * r{1,2} is the number of redundant rows in tableau {1,2}
295 * d{1,2} is the number of dead columns in tableau {1,2}
297 * The order of the rows and columns in the result is as explained
298 * in isl_tab_product.
300 static struct isl_mat *tab_mat_product(struct isl_mat *mat1,
301 struct isl_mat *mat2, unsigned row1, unsigned row2,
302 unsigned col1, unsigned col2,
303 unsigned off, unsigned r1, unsigned r2, unsigned d1, unsigned d2)
306 struct isl_mat *prod;
309 prod = isl_mat_alloc(mat1->ctx, mat1->n_row + mat2->n_row,
313 for (i = 0; i < r1; ++i) {
314 isl_seq_cpy(prod->row[n + i], mat1->row[i], off + d1);
315 isl_seq_clr(prod->row[n + i] + off + d1, d2);
316 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
317 mat1->row[i] + off + d1, col1 - d1);
318 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
322 for (i = 0; i < r2; ++i) {
323 isl_seq_cpy(prod->row[n + i], mat2->row[i], off);
324 isl_seq_clr(prod->row[n + i] + off, d1);
325 isl_seq_cpy(prod->row[n + i] + off + d1,
326 mat2->row[i] + off, d2);
327 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
328 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
329 mat2->row[i] + off + d2, col2 - d2);
333 for (i = 0; i < row1 - r1; ++i) {
334 isl_seq_cpy(prod->row[n + i], mat1->row[r1 + i], off + d1);
335 isl_seq_clr(prod->row[n + i] + off + d1, d2);
336 isl_seq_cpy(prod->row[n + i] + off + d1 + d2,
337 mat1->row[r1 + i] + off + d1, col1 - d1);
338 isl_seq_clr(prod->row[n + i] + off + col1 + d1, col2 - d2);
342 for (i = 0; i < row2 - r2; ++i) {
343 isl_seq_cpy(prod->row[n + i], mat2->row[r2 + i], off);
344 isl_seq_clr(prod->row[n + i] + off, d1);
345 isl_seq_cpy(prod->row[n + i] + off + d1,
346 mat2->row[r2 + i] + off, d2);
347 isl_seq_clr(prod->row[n + i] + off + d1 + d2, col1 - d1);
348 isl_seq_cpy(prod->row[n + i] + off + col1 + d1,
349 mat2->row[r2 + i] + off + d2, col2 - d2);
355 /* Update the row or column index of a variable that corresponds
356 * to a variable in the first input tableau.
358 static void update_index1(struct isl_tab_var *var,
359 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
361 if (var->index == -1)
363 if (var->is_row && var->index >= r1)
365 if (!var->is_row && var->index >= d1)
369 /* Update the row or column index of a variable that corresponds
370 * to a variable in the second input tableau.
372 static void update_index2(struct isl_tab_var *var,
373 unsigned row1, unsigned col1,
374 unsigned r1, unsigned r2, unsigned d1, unsigned d2)
376 if (var->index == -1)
391 /* Create a tableau that represents the Cartesian product of the sets
392 * represented by tableaus tab1 and tab2.
393 * The order of the rows in the product is
394 * - redundant rows of tab1
395 * - redundant rows of tab2
396 * - non-redundant rows of tab1
397 * - non-redundant rows of tab2
398 * The order of the columns is
401 * - coefficient of big parameter, if any
402 * - dead columns of tab1
403 * - dead columns of tab2
404 * - live columns of tab1
405 * - live columns of tab2
406 * The order of the variables and the constraints is a concatenation
407 * of order in the two input tableaus.
409 struct isl_tab *isl_tab_product(struct isl_tab *tab1, struct isl_tab *tab2)
412 struct isl_tab *prod;
414 unsigned r1, r2, d1, d2;
419 isl_assert(tab1->mat->ctx, tab1->M == tab2->M, return NULL);
420 isl_assert(tab1->mat->ctx, tab1->rational == tab2->rational, return NULL);
421 isl_assert(tab1->mat->ctx, tab1->cone == tab2->cone, return NULL);
422 isl_assert(tab1->mat->ctx, !tab1->row_sign, return NULL);
423 isl_assert(tab1->mat->ctx, !tab2->row_sign, return NULL);
424 isl_assert(tab1->mat->ctx, tab1->n_param == 0, return NULL);
425 isl_assert(tab1->mat->ctx, tab2->n_param == 0, return NULL);
426 isl_assert(tab1->mat->ctx, tab1->n_div == 0, return NULL);
427 isl_assert(tab1->mat->ctx, tab2->n_div == 0, return NULL);
430 r1 = tab1->n_redundant;
431 r2 = tab2->n_redundant;
434 prod = isl_calloc_type(tab1->mat->ctx, struct isl_tab);
437 prod->mat = tab_mat_product(tab1->mat, tab2->mat,
438 tab1->n_row, tab2->n_row,
439 tab1->n_col, tab2->n_col, off, r1, r2, d1, d2);
442 prod->var = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
443 tab1->max_var + tab2->max_var);
446 for (i = 0; i < tab1->n_var; ++i) {
447 prod->var[i] = tab1->var[i];
448 update_index1(&prod->var[i], r1, r2, d1, d2);
450 for (i = 0; i < tab2->n_var; ++i) {
451 prod->var[tab1->n_var + i] = tab2->var[i];
452 update_index2(&prod->var[tab1->n_var + i],
453 tab1->n_row, tab1->n_col,
456 prod->con = isl_alloc_array(tab1->mat->ctx, struct isl_tab_var,
457 tab1->max_con + tab2->max_con);
460 for (i = 0; i < tab1->n_con; ++i) {
461 prod->con[i] = tab1->con[i];
462 update_index1(&prod->con[i], r1, r2, d1, d2);
464 for (i = 0; i < tab2->n_con; ++i) {
465 prod->con[tab1->n_con + i] = tab2->con[i];
466 update_index2(&prod->con[tab1->n_con + i],
467 tab1->n_row, tab1->n_col,
470 prod->col_var = isl_alloc_array(tab1->mat->ctx, int,
471 tab1->n_col + tab2->n_col);
474 for (i = 0; i < tab1->n_col; ++i) {
475 int pos = i < d1 ? i : i + d2;
476 prod->col_var[pos] = tab1->col_var[i];
478 for (i = 0; i < tab2->n_col; ++i) {
479 int pos = i < d2 ? d1 + i : tab1->n_col + i;
480 int t = tab2->col_var[i];
485 prod->col_var[pos] = t;
487 prod->row_var = isl_alloc_array(tab1->mat->ctx, int,
488 tab1->mat->n_row + tab2->mat->n_row);
491 for (i = 0; i < tab1->n_row; ++i) {
492 int pos = i < r1 ? i : i + r2;
493 prod->row_var[pos] = tab1->row_var[i];
495 for (i = 0; i < tab2->n_row; ++i) {
496 int pos = i < r2 ? r1 + i : tab1->n_row + i;
497 int t = tab2->row_var[i];
502 prod->row_var[pos] = t;
504 prod->samples = NULL;
505 prod->sample_index = NULL;
506 prod->n_row = tab1->n_row + tab2->n_row;
507 prod->n_con = tab1->n_con + tab2->n_con;
509 prod->max_con = tab1->max_con + tab2->max_con;
510 prod->n_col = tab1->n_col + tab2->n_col;
511 prod->n_var = tab1->n_var + tab2->n_var;
512 prod->max_var = tab1->max_var + tab2->max_var;
515 prod->n_dead = tab1->n_dead + tab2->n_dead;
516 prod->n_redundant = tab1->n_redundant + tab2->n_redundant;
517 prod->rational = tab1->rational;
518 prod->empty = tab1->empty || tab2->empty;
522 prod->cone = tab1->cone;
523 prod->bottom.type = isl_tab_undo_bottom;
524 prod->bottom.next = NULL;
525 prod->top = &prod->bottom;
528 prod->n_unbounded = 0;
537 static struct isl_tab_var *var_from_index(struct isl_tab *tab, int i)
542 return &tab->con[~i];
545 struct isl_tab_var *isl_tab_var_from_row(struct isl_tab *tab, int i)
547 return var_from_index(tab, tab->row_var[i]);
550 static struct isl_tab_var *var_from_col(struct isl_tab *tab, int i)
552 return var_from_index(tab, tab->col_var[i]);
555 /* Check if there are any upper bounds on column variable "var",
556 * i.e., non-negative rows where var appears with a negative coefficient.
557 * Return 1 if there are no such bounds.
559 static int max_is_manifestly_unbounded(struct isl_tab *tab,
560 struct isl_tab_var *var)
563 unsigned off = 2 + tab->M;
567 for (i = tab->n_redundant; i < tab->n_row; ++i) {
568 if (!isl_int_is_neg(tab->mat->row[i][off + var->index]))
570 if (isl_tab_var_from_row(tab, i)->is_nonneg)
576 /* Check if there are any lower bounds on column variable "var",
577 * i.e., non-negative rows where var appears with a positive coefficient.
578 * Return 1 if there are no such bounds.
580 static int min_is_manifestly_unbounded(struct isl_tab *tab,
581 struct isl_tab_var *var)
584 unsigned off = 2 + tab->M;
588 for (i = tab->n_redundant; i < tab->n_row; ++i) {
589 if (!isl_int_is_pos(tab->mat->row[i][off + var->index]))
591 if (isl_tab_var_from_row(tab, i)->is_nonneg)
597 static int row_cmp(struct isl_tab *tab, int r1, int r2, int c, isl_int t)
599 unsigned off = 2 + tab->M;
603 isl_int_mul(t, tab->mat->row[r1][2], tab->mat->row[r2][off+c]);
604 isl_int_submul(t, tab->mat->row[r2][2], tab->mat->row[r1][off+c]);
609 isl_int_mul(t, tab->mat->row[r1][1], tab->mat->row[r2][off + c]);
610 isl_int_submul(t, tab->mat->row[r2][1], tab->mat->row[r1][off + c]);
611 return isl_int_sgn(t);
614 /* Given the index of a column "c", return the index of a row
615 * that can be used to pivot the column in, with either an increase
616 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
617 * If "var" is not NULL, then the row returned will be different from
618 * the one associated with "var".
620 * Each row in the tableau is of the form
622 * x_r = a_r0 + \sum_i a_ri x_i
624 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
625 * impose any limit on the increase or decrease in the value of x_c
626 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
627 * for the row with the smallest (most stringent) such bound.
628 * Note that the common denominator of each row drops out of the fraction.
629 * To check if row j has a smaller bound than row r, i.e.,
630 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
631 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
632 * where -sign(a_jc) is equal to "sgn".
634 static int pivot_row(struct isl_tab *tab,
635 struct isl_tab_var *var, int sgn, int c)
639 unsigned off = 2 + tab->M;
643 for (j = tab->n_redundant; j < tab->n_row; ++j) {
644 if (var && j == var->index)
646 if (!isl_tab_var_from_row(tab, j)->is_nonneg)
648 if (sgn * isl_int_sgn(tab->mat->row[j][off + c]) >= 0)
654 tsgn = sgn * row_cmp(tab, r, j, c, t);
655 if (tsgn < 0 || (tsgn == 0 &&
656 tab->row_var[j] < tab->row_var[r]))
663 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
664 * (sgn < 0) the value of row variable var.
665 * If not NULL, then skip_var is a row variable that should be ignored
666 * while looking for a pivot row. It is usually equal to var.
668 * As the given row in the tableau is of the form
670 * x_r = a_r0 + \sum_i a_ri x_i
672 * we need to find a column such that the sign of a_ri is equal to "sgn"
673 * (such that an increase in x_i will have the desired effect) or a
674 * column with a variable that may attain negative values.
675 * If a_ri is positive, then we need to move x_i in the same direction
676 * to obtain the desired effect. Otherwise, x_i has to move in the
677 * opposite direction.
679 static void find_pivot(struct isl_tab *tab,
680 struct isl_tab_var *var, struct isl_tab_var *skip_var,
681 int sgn, int *row, int *col)
688 isl_assert(tab->mat->ctx, var->is_row, return);
689 tr = tab->mat->row[var->index] + 2 + tab->M;
692 for (j = tab->n_dead; j < tab->n_col; ++j) {
693 if (isl_int_is_zero(tr[j]))
695 if (isl_int_sgn(tr[j]) != sgn &&
696 var_from_col(tab, j)->is_nonneg)
698 if (c < 0 || tab->col_var[j] < tab->col_var[c])
704 sgn *= isl_int_sgn(tr[c]);
705 r = pivot_row(tab, skip_var, sgn, c);
706 *row = r < 0 ? var->index : r;
710 /* Return 1 if row "row" represents an obviously redundant inequality.
712 * - it represents an inequality or a variable
713 * - that is the sum of a non-negative sample value and a positive
714 * combination of zero or more non-negative constraints.
716 int isl_tab_row_is_redundant(struct isl_tab *tab, int row)
719 unsigned off = 2 + tab->M;
721 if (tab->row_var[row] < 0 && !isl_tab_var_from_row(tab, row)->is_nonneg)
724 if (isl_int_is_neg(tab->mat->row[row][1]))
726 if (tab->M && isl_int_is_neg(tab->mat->row[row][2]))
729 for (i = tab->n_dead; i < tab->n_col; ++i) {
730 if (isl_int_is_zero(tab->mat->row[row][off + i]))
732 if (tab->col_var[i] >= 0)
734 if (isl_int_is_neg(tab->mat->row[row][off + i]))
736 if (!var_from_col(tab, i)->is_nonneg)
742 static void swap_rows(struct isl_tab *tab, int row1, int row2)
745 enum isl_tab_row_sign s;
747 t = tab->row_var[row1];
748 tab->row_var[row1] = tab->row_var[row2];
749 tab->row_var[row2] = t;
750 isl_tab_var_from_row(tab, row1)->index = row1;
751 isl_tab_var_from_row(tab, row2)->index = row2;
752 tab->mat = isl_mat_swap_rows(tab->mat, row1, row2);
756 s = tab->row_sign[row1];
757 tab->row_sign[row1] = tab->row_sign[row2];
758 tab->row_sign[row2] = s;
761 static int push_union(struct isl_tab *tab,
762 enum isl_tab_undo_type type, union isl_tab_undo_val u) WARN_UNUSED;
763 static int push_union(struct isl_tab *tab,
764 enum isl_tab_undo_type type, union isl_tab_undo_val u)
766 struct isl_tab_undo *undo;
771 undo = isl_alloc_type(tab->mat->ctx, struct isl_tab_undo);
776 undo->next = tab->top;
782 int isl_tab_push_var(struct isl_tab *tab,
783 enum isl_tab_undo_type type, struct isl_tab_var *var)
785 union isl_tab_undo_val u;
787 u.var_index = tab->row_var[var->index];
789 u.var_index = tab->col_var[var->index];
790 return push_union(tab, type, u);
793 int isl_tab_push(struct isl_tab *tab, enum isl_tab_undo_type type)
795 union isl_tab_undo_val u = { 0 };
796 return push_union(tab, type, u);
799 /* Push a record on the undo stack describing the current basic
800 * variables, so that the this state can be restored during rollback.
802 int isl_tab_push_basis(struct isl_tab *tab)
805 union isl_tab_undo_val u;
807 u.col_var = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
810 for (i = 0; i < tab->n_col; ++i)
811 u.col_var[i] = tab->col_var[i];
812 return push_union(tab, isl_tab_undo_saved_basis, u);
815 int isl_tab_push_callback(struct isl_tab *tab, struct isl_tab_callback *callback)
817 union isl_tab_undo_val u;
818 u.callback = callback;
819 return push_union(tab, isl_tab_undo_callback, u);
822 struct isl_tab *isl_tab_init_samples(struct isl_tab *tab)
829 tab->samples = isl_mat_alloc(tab->mat->ctx, 1, 1 + tab->n_var);
832 tab->sample_index = isl_alloc_array(tab->mat->ctx, int, 1);
833 if (!tab->sample_index)
841 struct isl_tab *isl_tab_add_sample(struct isl_tab *tab,
842 __isl_take isl_vec *sample)
847 if (tab->n_sample + 1 > tab->samples->n_row) {
848 int *t = isl_realloc_array(tab->mat->ctx,
849 tab->sample_index, int, tab->n_sample + 1);
852 tab->sample_index = t;
855 tab->samples = isl_mat_extend(tab->samples,
856 tab->n_sample + 1, tab->samples->n_col);
860 isl_seq_cpy(tab->samples->row[tab->n_sample], sample->el, sample->size);
861 isl_vec_free(sample);
862 tab->sample_index[tab->n_sample] = tab->n_sample;
867 isl_vec_free(sample);
872 struct isl_tab *isl_tab_drop_sample(struct isl_tab *tab, int s)
874 if (s != tab->n_outside) {
875 int t = tab->sample_index[tab->n_outside];
876 tab->sample_index[tab->n_outside] = tab->sample_index[s];
877 tab->sample_index[s] = t;
878 isl_mat_swap_rows(tab->samples, tab->n_outside, s);
881 if (isl_tab_push(tab, isl_tab_undo_drop_sample) < 0) {
889 /* Record the current number of samples so that we can remove newer
890 * samples during a rollback.
892 int isl_tab_save_samples(struct isl_tab *tab)
894 union isl_tab_undo_val u;
900 return push_union(tab, isl_tab_undo_saved_samples, u);
903 /* Mark row with index "row" as being redundant.
904 * If we may need to undo the operation or if the row represents
905 * a variable of the original problem, the row is kept,
906 * but no longer considered when looking for a pivot row.
907 * Otherwise, the row is simply removed.
909 * The row may be interchanged with some other row. If it
910 * is interchanged with a later row, return 1. Otherwise return 0.
911 * If the rows are checked in order in the calling function,
912 * then a return value of 1 means that the row with the given
913 * row number may now contain a different row that hasn't been checked yet.
915 int isl_tab_mark_redundant(struct isl_tab *tab, int row)
917 struct isl_tab_var *var = isl_tab_var_from_row(tab, row);
918 var->is_redundant = 1;
919 isl_assert(tab->mat->ctx, row >= tab->n_redundant, return -1);
920 if (tab->need_undo || tab->row_var[row] >= 0) {
921 if (tab->row_var[row] >= 0 && !var->is_nonneg) {
923 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, var) < 0)
926 if (row != tab->n_redundant)
927 swap_rows(tab, row, tab->n_redundant);
929 return isl_tab_push_var(tab, isl_tab_undo_redundant, var);
931 if (row != tab->n_row - 1)
932 swap_rows(tab, row, tab->n_row - 1);
933 isl_tab_var_from_row(tab, tab->n_row - 1)->index = -1;
939 int isl_tab_mark_empty(struct isl_tab *tab)
943 if (!tab->empty && tab->need_undo)
944 if (isl_tab_push(tab, isl_tab_undo_empty) < 0)
950 int isl_tab_freeze_constraint(struct isl_tab *tab, int con)
952 struct isl_tab_var *var;
957 var = &tab->con[con];
965 return isl_tab_push_var(tab, isl_tab_undo_freeze, var);
970 /* Update the rows signs after a pivot of "row" and "col", with "row_sgn"
971 * the original sign of the pivot element.
972 * We only keep track of row signs during PILP solving and in this case
973 * we only pivot a row with negative sign (meaning the value is always
974 * non-positive) using a positive pivot element.
976 * For each row j, the new value of the parametric constant is equal to
978 * a_j0 - a_jc a_r0/a_rc
980 * where a_j0 is the original parametric constant, a_rc is the pivot element,
981 * a_r0 is the parametric constant of the pivot row and a_jc is the
982 * pivot column entry of the row j.
983 * Since a_r0 is non-positive and a_rc is positive, the sign of row j
984 * remains the same if a_jc has the same sign as the row j or if
985 * a_jc is zero. In all other cases, we reset the sign to "unknown".
987 static void update_row_sign(struct isl_tab *tab, int row, int col, int row_sgn)
990 struct isl_mat *mat = tab->mat;
991 unsigned off = 2 + tab->M;
996 if (tab->row_sign[row] == 0)
998 isl_assert(mat->ctx, row_sgn > 0, return);
999 isl_assert(mat->ctx, tab->row_sign[row] == isl_tab_row_neg, return);
1000 tab->row_sign[row] = isl_tab_row_pos;
1001 for (i = 0; i < tab->n_row; ++i) {
1005 s = isl_int_sgn(mat->row[i][off + col]);
1008 if (!tab->row_sign[i])
1010 if (s < 0 && tab->row_sign[i] == isl_tab_row_neg)
1012 if (s > 0 && tab->row_sign[i] == isl_tab_row_pos)
1014 tab->row_sign[i] = isl_tab_row_unknown;
1018 /* Given a row number "row" and a column number "col", pivot the tableau
1019 * such that the associated variables are interchanged.
1020 * The given row in the tableau expresses
1022 * x_r = a_r0 + \sum_i a_ri x_i
1026 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
1028 * Substituting this equality into the other rows
1030 * x_j = a_j0 + \sum_i a_ji x_i
1032 * with a_jc \ne 0, we obtain
1034 * 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
1041 * where i is any other column and j is any other row,
1042 * is therefore transformed into
1044 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1045 * 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)
1047 * The transformation is performed along the following steps
1049 * d_r/n_rc n_ri/n_rc
1052 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1055 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1056 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
1058 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1059 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
1061 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1062 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1064 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1065 * 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)
1068 int isl_tab_pivot(struct isl_tab *tab, int row, int col)
1073 struct isl_mat *mat = tab->mat;
1074 struct isl_tab_var *var;
1075 unsigned off = 2 + tab->M;
1077 isl_int_swap(mat->row[row][0], mat->row[row][off + col]);
1078 sgn = isl_int_sgn(mat->row[row][0]);
1080 isl_int_neg(mat->row[row][0], mat->row[row][0]);
1081 isl_int_neg(mat->row[row][off + col], mat->row[row][off + col]);
1083 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1084 if (j == off - 1 + col)
1086 isl_int_neg(mat->row[row][1 + j], mat->row[row][1 + j]);
1088 if (!isl_int_is_one(mat->row[row][0]))
1089 isl_seq_normalize(mat->ctx, mat->row[row], off + tab->n_col);
1090 for (i = 0; i < tab->n_row; ++i) {
1093 if (isl_int_is_zero(mat->row[i][off + col]))
1095 isl_int_mul(mat->row[i][0], mat->row[i][0], mat->row[row][0]);
1096 for (j = 0; j < off - 1 + tab->n_col; ++j) {
1097 if (j == off - 1 + col)
1099 isl_int_mul(mat->row[i][1 + j],
1100 mat->row[i][1 + j], mat->row[row][0]);
1101 isl_int_addmul(mat->row[i][1 + j],
1102 mat->row[i][off + col], mat->row[row][1 + j]);
1104 isl_int_mul(mat->row[i][off + col],
1105 mat->row[i][off + col], mat->row[row][off + col]);
1106 if (!isl_int_is_one(mat->row[i][0]))
1107 isl_seq_normalize(mat->ctx, mat->row[i], off + tab->n_col);
1109 t = tab->row_var[row];
1110 tab->row_var[row] = tab->col_var[col];
1111 tab->col_var[col] = t;
1112 var = isl_tab_var_from_row(tab, row);
1115 var = var_from_col(tab, col);
1118 update_row_sign(tab, row, col, sgn);
1121 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1122 if (isl_int_is_zero(mat->row[i][off + col]))
1124 if (!isl_tab_var_from_row(tab, i)->frozen &&
1125 isl_tab_row_is_redundant(tab, i)) {
1126 int redo = isl_tab_mark_redundant(tab, i);
1136 /* If "var" represents a column variable, then pivot is up (sgn > 0)
1137 * or down (sgn < 0) to a row. The variable is assumed not to be
1138 * unbounded in the specified direction.
1139 * If sgn = 0, then the variable is unbounded in both directions,
1140 * and we pivot with any row we can find.
1142 static int to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign) WARN_UNUSED;
1143 static int to_row(struct isl_tab *tab, struct isl_tab_var *var, int sign)
1146 unsigned off = 2 + tab->M;
1152 for (r = tab->n_redundant; r < tab->n_row; ++r)
1153 if (!isl_int_is_zero(tab->mat->row[r][off+var->index]))
1155 isl_assert(tab->mat->ctx, r < tab->n_row, return -1);
1157 r = pivot_row(tab, NULL, sign, var->index);
1158 isl_assert(tab->mat->ctx, r >= 0, return -1);
1161 return isl_tab_pivot(tab, r, var->index);
1164 static void check_table(struct isl_tab *tab)
1170 for (i = tab->n_redundant; i < tab->n_row; ++i) {
1171 struct isl_tab_var *var;
1172 var = isl_tab_var_from_row(tab, i);
1173 if (!var->is_nonneg)
1176 assert(!isl_int_is_neg(tab->mat->row[i][2]));
1177 if (isl_int_is_pos(tab->mat->row[i][2]))
1180 assert(!isl_int_is_neg(tab->mat->row[i][1]));
1184 /* Return the sign of the maximal value of "var".
1185 * If the sign is not negative, then on return from this function,
1186 * the sample value will also be non-negative.
1188 * If "var" is manifestly unbounded wrt positive values, we are done.
1189 * Otherwise, we pivot the variable up to a row if needed
1190 * Then we continue pivoting down until either
1191 * - no more down pivots can be performed
1192 * - the sample value is positive
1193 * - the variable is pivoted into a manifestly unbounded column
1195 static int sign_of_max(struct isl_tab *tab, struct isl_tab_var *var)
1199 if (max_is_manifestly_unbounded(tab, var))
1201 if (to_row(tab, var, 1) < 0)
1203 while (!isl_int_is_pos(tab->mat->row[var->index][1])) {
1204 find_pivot(tab, var, var, 1, &row, &col);
1206 return isl_int_sgn(tab->mat->row[var->index][1]);
1207 if (isl_tab_pivot(tab, row, col) < 0)
1209 if (!var->is_row) /* manifestly unbounded */
1215 int isl_tab_sign_of_max(struct isl_tab *tab, int con)
1217 struct isl_tab_var *var;
1222 var = &tab->con[con];
1223 isl_assert(tab->mat->ctx, !var->is_redundant, return -2);
1224 isl_assert(tab->mat->ctx, !var->is_zero, return -2);
1226 return sign_of_max(tab, var);
1229 static int row_is_neg(struct isl_tab *tab, int row)
1232 return isl_int_is_neg(tab->mat->row[row][1]);
1233 if (isl_int_is_pos(tab->mat->row[row][2]))
1235 if (isl_int_is_neg(tab->mat->row[row][2]))
1237 return isl_int_is_neg(tab->mat->row[row][1]);
1240 static int row_sgn(struct isl_tab *tab, int row)
1243 return isl_int_sgn(tab->mat->row[row][1]);
1244 if (!isl_int_is_zero(tab->mat->row[row][2]))
1245 return isl_int_sgn(tab->mat->row[row][2]);
1247 return isl_int_sgn(tab->mat->row[row][1]);
1250 /* Perform pivots until the row variable "var" has a non-negative
1251 * sample value or until no more upward pivots can be performed.
1252 * Return the sign of the sample value after the pivots have been
1255 static int restore_row(struct isl_tab *tab, struct isl_tab_var *var)
1259 while (row_is_neg(tab, var->index)) {
1260 find_pivot(tab, var, var, 1, &row, &col);
1263 if (isl_tab_pivot(tab, row, col) < 0)
1265 if (!var->is_row) /* manifestly unbounded */
1268 return row_sgn(tab, var->index);
1271 /* Perform pivots until we are sure that the row variable "var"
1272 * can attain non-negative values. After return from this
1273 * function, "var" is still a row variable, but its sample
1274 * value may not be non-negative, even if the function returns 1.
1276 static int at_least_zero(struct isl_tab *tab, struct isl_tab_var *var)
1280 while (isl_int_is_neg(tab->mat->row[var->index][1])) {
1281 find_pivot(tab, var, var, 1, &row, &col);
1284 if (row == var->index) /* manifestly unbounded */
1286 if (isl_tab_pivot(tab, row, col) < 0)
1289 return !isl_int_is_neg(tab->mat->row[var->index][1]);
1292 /* Return a negative value if "var" can attain negative values.
1293 * Return a non-negative value otherwise.
1295 * If "var" is manifestly unbounded wrt negative values, we are done.
1296 * Otherwise, if var is in a column, we can pivot it down to a row.
1297 * Then we continue pivoting down until either
1298 * - the pivot would result in a manifestly unbounded column
1299 * => we don't perform the pivot, but simply return -1
1300 * - no more down pivots can be performed
1301 * - the sample value is negative
1302 * If the sample value becomes negative and the variable is supposed
1303 * to be nonnegative, then we undo the last pivot.
1304 * However, if the last pivot has made the pivoting variable
1305 * obviously redundant, then it may have moved to another row.
1306 * In that case we look for upward pivots until we reach a non-negative
1309 static int sign_of_min(struct isl_tab *tab, struct isl_tab_var *var)
1312 struct isl_tab_var *pivot_var = NULL;
1314 if (min_is_manifestly_unbounded(tab, var))
1318 row = pivot_row(tab, NULL, -1, col);
1319 pivot_var = var_from_col(tab, col);
1320 if (isl_tab_pivot(tab, row, col) < 0)
1322 if (var->is_redundant)
1324 if (isl_int_is_neg(tab->mat->row[var->index][1])) {
1325 if (var->is_nonneg) {
1326 if (!pivot_var->is_redundant &&
1327 pivot_var->index == row) {
1328 if (isl_tab_pivot(tab, row, col) < 0)
1331 if (restore_row(tab, var) < -1)
1337 if (var->is_redundant)
1339 while (!isl_int_is_neg(tab->mat->row[var->index][1])) {
1340 find_pivot(tab, var, var, -1, &row, &col);
1341 if (row == var->index)
1344 return isl_int_sgn(tab->mat->row[var->index][1]);
1345 pivot_var = var_from_col(tab, col);
1346 if (isl_tab_pivot(tab, row, col) < 0)
1348 if (var->is_redundant)
1351 if (pivot_var && var->is_nonneg) {
1352 /* pivot back to non-negative value */
1353 if (!pivot_var->is_redundant && pivot_var->index == row) {
1354 if (isl_tab_pivot(tab, row, col) < 0)
1357 if (restore_row(tab, var) < -1)
1363 static int row_at_most_neg_one(struct isl_tab *tab, int row)
1366 if (isl_int_is_pos(tab->mat->row[row][2]))
1368 if (isl_int_is_neg(tab->mat->row[row][2]))
1371 return isl_int_is_neg(tab->mat->row[row][1]) &&
1372 isl_int_abs_ge(tab->mat->row[row][1],
1373 tab->mat->row[row][0]);
1376 /* Return 1 if "var" can attain values <= -1.
1377 * Return 0 otherwise.
1379 * The sample value of "var" is assumed to be non-negative when the
1380 * the function is called. If 1 is returned then the constraint
1381 * is not redundant and the sample value is made non-negative again before
1382 * the function returns.
1384 int isl_tab_min_at_most_neg_one(struct isl_tab *tab, struct isl_tab_var *var)
1387 struct isl_tab_var *pivot_var;
1389 if (min_is_manifestly_unbounded(tab, var))
1393 row = pivot_row(tab, NULL, -1, col);
1394 pivot_var = var_from_col(tab, col);
1395 if (isl_tab_pivot(tab, row, col) < 0)
1397 if (var->is_redundant)
1399 if (row_at_most_neg_one(tab, var->index)) {
1400 if (var->is_nonneg) {
1401 if (!pivot_var->is_redundant &&
1402 pivot_var->index == row) {
1403 if (isl_tab_pivot(tab, row, col) < 0)
1406 if (restore_row(tab, var) < -1)
1412 if (var->is_redundant)
1415 find_pivot(tab, var, var, -1, &row, &col);
1416 if (row == var->index) {
1417 if (restore_row(tab, var) < -1)
1423 pivot_var = var_from_col(tab, col);
1424 if (isl_tab_pivot(tab, row, col) < 0)
1426 if (var->is_redundant)
1428 } while (!row_at_most_neg_one(tab, var->index));
1429 if (var->is_nonneg) {
1430 /* pivot back to non-negative value */
1431 if (!pivot_var->is_redundant && pivot_var->index == row)
1432 if (isl_tab_pivot(tab, row, col) < 0)
1434 if (restore_row(tab, var) < -1)
1440 /* Return 1 if "var" can attain values >= 1.
1441 * Return 0 otherwise.
1443 static int at_least_one(struct isl_tab *tab, struct isl_tab_var *var)
1448 if (max_is_manifestly_unbounded(tab, var))
1450 if (to_row(tab, var, 1) < 0)
1452 r = tab->mat->row[var->index];
1453 while (isl_int_lt(r[1], r[0])) {
1454 find_pivot(tab, var, var, 1, &row, &col);
1456 return isl_int_ge(r[1], r[0]);
1457 if (row == var->index) /* manifestly unbounded */
1459 if (isl_tab_pivot(tab, row, col) < 0)
1465 static void swap_cols(struct isl_tab *tab, int col1, int col2)
1468 unsigned off = 2 + tab->M;
1469 t = tab->col_var[col1];
1470 tab->col_var[col1] = tab->col_var[col2];
1471 tab->col_var[col2] = t;
1472 var_from_col(tab, col1)->index = col1;
1473 var_from_col(tab, col2)->index = col2;
1474 tab->mat = isl_mat_swap_cols(tab->mat, off + col1, off + col2);
1477 /* Mark column with index "col" as representing a zero variable.
1478 * If we may need to undo the operation the column is kept,
1479 * but no longer considered.
1480 * Otherwise, the column is simply removed.
1482 * The column may be interchanged with some other column. If it
1483 * is interchanged with a later column, return 1. Otherwise return 0.
1484 * If the columns are checked in order in the calling function,
1485 * then a return value of 1 means that the column with the given
1486 * column number may now contain a different column that
1487 * hasn't been checked yet.
1489 int isl_tab_kill_col(struct isl_tab *tab, int col)
1491 var_from_col(tab, col)->is_zero = 1;
1492 if (tab->need_undo) {
1493 if (isl_tab_push_var(tab, isl_tab_undo_zero,
1494 var_from_col(tab, col)) < 0)
1496 if (col != tab->n_dead)
1497 swap_cols(tab, col, tab->n_dead);
1501 if (col != tab->n_col - 1)
1502 swap_cols(tab, col, tab->n_col - 1);
1503 var_from_col(tab, tab->n_col - 1)->index = -1;
1509 /* Row variable "var" is non-negative and cannot attain any values
1510 * larger than zero. This means that the coefficients of the unrestricted
1511 * column variables are zero and that the coefficients of the non-negative
1512 * column variables are zero or negative.
1513 * Each of the non-negative variables with a negative coefficient can
1514 * then also be written as the negative sum of non-negative variables
1515 * and must therefore also be zero.
1517 static int close_row(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
1518 static int close_row(struct isl_tab *tab, struct isl_tab_var *var)
1521 struct isl_mat *mat = tab->mat;
1522 unsigned off = 2 + tab->M;
1524 isl_assert(tab->mat->ctx, var->is_nonneg, return -1);
1527 if (isl_tab_push_var(tab, isl_tab_undo_zero, var) < 0)
1529 for (j = tab->n_dead; j < tab->n_col; ++j) {
1530 if (isl_int_is_zero(mat->row[var->index][off + j]))
1532 isl_assert(tab->mat->ctx,
1533 isl_int_is_neg(mat->row[var->index][off + j]), return -1);
1534 if (isl_tab_kill_col(tab, j))
1537 if (isl_tab_mark_redundant(tab, var->index) < 0)
1542 /* Add a constraint to the tableau and allocate a row for it.
1543 * Return the index into the constraint array "con".
1545 int isl_tab_allocate_con(struct isl_tab *tab)
1549 isl_assert(tab->mat->ctx, tab->n_row < tab->mat->n_row, return -1);
1550 isl_assert(tab->mat->ctx, tab->n_con < tab->max_con, return -1);
1553 tab->con[r].index = tab->n_row;
1554 tab->con[r].is_row = 1;
1555 tab->con[r].is_nonneg = 0;
1556 tab->con[r].is_zero = 0;
1557 tab->con[r].is_redundant = 0;
1558 tab->con[r].frozen = 0;
1559 tab->con[r].negated = 0;
1560 tab->row_var[tab->n_row] = ~r;
1564 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]) < 0)
1570 /* Add a variable to the tableau and allocate a column for it.
1571 * Return the index into the variable array "var".
1573 int isl_tab_allocate_var(struct isl_tab *tab)
1577 unsigned off = 2 + tab->M;
1579 isl_assert(tab->mat->ctx, tab->n_col < tab->mat->n_col, return -1);
1580 isl_assert(tab->mat->ctx, tab->n_var < tab->max_var, return -1);
1583 tab->var[r].index = tab->n_col;
1584 tab->var[r].is_row = 0;
1585 tab->var[r].is_nonneg = 0;
1586 tab->var[r].is_zero = 0;
1587 tab->var[r].is_redundant = 0;
1588 tab->var[r].frozen = 0;
1589 tab->var[r].negated = 0;
1590 tab->col_var[tab->n_col] = r;
1592 for (i = 0; i < tab->n_row; ++i)
1593 isl_int_set_si(tab->mat->row[i][off + tab->n_col], 0);
1597 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->var[r]) < 0)
1603 /* Add a row to the tableau. The row is given as an affine combination
1604 * of the original variables and needs to be expressed in terms of the
1607 * We add each term in turn.
1608 * If r = n/d_r is the current sum and we need to add k x, then
1609 * if x is a column variable, we increase the numerator of
1610 * this column by k d_r
1611 * if x = f/d_x is a row variable, then the new representation of r is
1613 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1614 * --- + --- = ------------------- = -------------------
1615 * d_r d_r d_r d_x/g m
1617 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1619 int isl_tab_add_row(struct isl_tab *tab, isl_int *line)
1625 unsigned off = 2 + tab->M;
1627 r = isl_tab_allocate_con(tab);
1633 row = tab->mat->row[tab->con[r].index];
1634 isl_int_set_si(row[0], 1);
1635 isl_int_set(row[1], line[0]);
1636 isl_seq_clr(row + 2, tab->M + tab->n_col);
1637 for (i = 0; i < tab->n_var; ++i) {
1638 if (tab->var[i].is_zero)
1640 if (tab->var[i].is_row) {
1642 row[0], tab->mat->row[tab->var[i].index][0]);
1643 isl_int_swap(a, row[0]);
1644 isl_int_divexact(a, row[0], a);
1646 row[0], tab->mat->row[tab->var[i].index][0]);
1647 isl_int_mul(b, b, line[1 + i]);
1648 isl_seq_combine(row + 1, a, row + 1,
1649 b, tab->mat->row[tab->var[i].index] + 1,
1650 1 + tab->M + tab->n_col);
1652 isl_int_addmul(row[off + tab->var[i].index],
1653 line[1 + i], row[0]);
1654 if (tab->M && i >= tab->n_param && i < tab->n_var - tab->n_div)
1655 isl_int_submul(row[2], line[1 + i], row[0]);
1657 isl_seq_normalize(tab->mat->ctx, row, off + tab->n_col);
1662 tab->row_sign[tab->con[r].index] = isl_tab_row_unknown;
1667 static int drop_row(struct isl_tab *tab, int row)
1669 isl_assert(tab->mat->ctx, ~tab->row_var[row] == tab->n_con - 1, return -1);
1670 if (row != tab->n_row - 1)
1671 swap_rows(tab, row, tab->n_row - 1);
1677 static int drop_col(struct isl_tab *tab, int col)
1679 isl_assert(tab->mat->ctx, tab->col_var[col] == tab->n_var - 1, return -1);
1680 if (col != tab->n_col - 1)
1681 swap_cols(tab, col, tab->n_col - 1);
1687 /* Add inequality "ineq" and check if it conflicts with the
1688 * previously added constraints or if it is obviously redundant.
1690 int isl_tab_add_ineq(struct isl_tab *tab, isl_int *ineq)
1699 struct isl_basic_map *bmap = tab->bmap;
1701 isl_assert(tab->mat->ctx, tab->n_eq == bmap->n_eq, return -1);
1702 isl_assert(tab->mat->ctx,
1703 tab->n_con == bmap->n_eq + bmap->n_ineq, return -1);
1704 tab->bmap = isl_basic_map_add_ineq(tab->bmap, ineq);
1705 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1712 isl_int_swap(ineq[0], cst);
1714 r = isl_tab_add_row(tab, ineq);
1716 isl_int_swap(ineq[0], cst);
1721 tab->con[r].is_nonneg = 1;
1722 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
1724 if (isl_tab_row_is_redundant(tab, tab->con[r].index)) {
1725 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1730 sgn = restore_row(tab, &tab->con[r]);
1734 return isl_tab_mark_empty(tab);
1735 if (tab->con[r].is_row && isl_tab_row_is_redundant(tab, tab->con[r].index))
1736 if (isl_tab_mark_redundant(tab, tab->con[r].index) < 0)
1741 /* Pivot a non-negative variable down until it reaches the value zero
1742 * and then pivot the variable into a column position.
1744 static int to_col(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
1745 static int to_col(struct isl_tab *tab, struct isl_tab_var *var)
1749 unsigned off = 2 + tab->M;
1754 while (isl_int_is_pos(tab->mat->row[var->index][1])) {
1755 find_pivot(tab, var, NULL, -1, &row, &col);
1756 isl_assert(tab->mat->ctx, row != -1, return -1);
1757 if (isl_tab_pivot(tab, row, col) < 0)
1763 for (i = tab->n_dead; i < tab->n_col; ++i)
1764 if (!isl_int_is_zero(tab->mat->row[var->index][off + i]))
1767 isl_assert(tab->mat->ctx, i < tab->n_col, return -1);
1768 if (isl_tab_pivot(tab, var->index, i) < 0)
1774 /* We assume Gaussian elimination has been performed on the equalities.
1775 * The equalities can therefore never conflict.
1776 * Adding the equalities is currently only really useful for a later call
1777 * to isl_tab_ineq_type.
1779 static struct isl_tab *add_eq(struct isl_tab *tab, isl_int *eq)
1786 r = isl_tab_add_row(tab, eq);
1790 r = tab->con[r].index;
1791 i = isl_seq_first_non_zero(tab->mat->row[r] + 2 + tab->M + tab->n_dead,
1792 tab->n_col - tab->n_dead);
1793 isl_assert(tab->mat->ctx, i >= 0, goto error);
1795 if (isl_tab_pivot(tab, r, i) < 0)
1797 if (isl_tab_kill_col(tab, i) < 0)
1807 static int row_is_manifestly_zero(struct isl_tab *tab, int row)
1809 unsigned off = 2 + tab->M;
1811 if (!isl_int_is_zero(tab->mat->row[row][1]))
1813 if (tab->M && !isl_int_is_zero(tab->mat->row[row][2]))
1815 return isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
1816 tab->n_col - tab->n_dead) == -1;
1819 /* Add an equality that is known to be valid for the given tableau.
1821 struct isl_tab *isl_tab_add_valid_eq(struct isl_tab *tab, isl_int *eq)
1823 struct isl_tab_var *var;
1828 r = isl_tab_add_row(tab, eq);
1834 if (row_is_manifestly_zero(tab, r)) {
1836 if (isl_tab_mark_redundant(tab, r) < 0)
1841 if (isl_int_is_neg(tab->mat->row[r][1])) {
1842 isl_seq_neg(tab->mat->row[r] + 1, tab->mat->row[r] + 1,
1847 if (to_col(tab, var) < 0)
1850 if (isl_tab_kill_col(tab, var->index) < 0)
1859 static int add_zero_row(struct isl_tab *tab)
1864 r = isl_tab_allocate_con(tab);
1868 row = tab->mat->row[tab->con[r].index];
1869 isl_seq_clr(row + 1, 1 + tab->M + tab->n_col);
1870 isl_int_set_si(row[0], 1);
1875 /* Add equality "eq" and check if it conflicts with the
1876 * previously added constraints or if it is obviously redundant.
1878 struct isl_tab *isl_tab_add_eq(struct isl_tab *tab, isl_int *eq)
1880 struct isl_tab_undo *snap = NULL;
1881 struct isl_tab_var *var;
1889 isl_assert(tab->mat->ctx, !tab->M, goto error);
1892 snap = isl_tab_snap(tab);
1896 isl_int_swap(eq[0], cst);
1898 r = isl_tab_add_row(tab, eq);
1900 isl_int_swap(eq[0], cst);
1908 if (row_is_manifestly_zero(tab, row)) {
1910 if (isl_tab_rollback(tab, snap) < 0)
1918 tab->bmap = isl_basic_map_add_ineq(tab->bmap, eq);
1919 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1921 isl_seq_neg(eq, eq, 1 + tab->n_var);
1922 tab->bmap = isl_basic_map_add_ineq(tab->bmap, eq);
1923 isl_seq_neg(eq, eq, 1 + tab->n_var);
1924 if (isl_tab_push(tab, isl_tab_undo_bmap_ineq) < 0)
1928 if (add_zero_row(tab) < 0)
1932 sgn = isl_int_sgn(tab->mat->row[row][1]);
1935 isl_seq_neg(tab->mat->row[row] + 1, tab->mat->row[row] + 1,
1942 sgn = sign_of_max(tab, var);
1946 if (isl_tab_mark_empty(tab) < 0)
1953 if (to_col(tab, var) < 0)
1956 if (isl_tab_kill_col(tab, var->index) < 0)
1965 /* Construct and return an inequality that expresses an upper bound
1967 * In particular, if the div is given by
1971 * then the inequality expresses
1975 static struct isl_vec *ineq_for_div(struct isl_basic_map *bmap, unsigned div)
1979 struct isl_vec *ineq;
1984 total = isl_basic_map_total_dim(bmap);
1985 div_pos = 1 + total - bmap->n_div + div;
1987 ineq = isl_vec_alloc(bmap->ctx, 1 + total);
1991 isl_seq_cpy(ineq->el, bmap->div[div] + 1, 1 + total);
1992 isl_int_neg(ineq->el[div_pos], bmap->div[div][0]);
1996 /* For a div d = floor(f/m), add the constraints
1999 * -(f-(m-1)) + m d >= 0
2001 * Note that the second constraint is the negation of
2005 * If add_ineq is not NULL, then this function is used
2006 * instead of isl_tab_add_ineq to effectively add the inequalities.
2008 static int add_div_constraints(struct isl_tab *tab, unsigned div,
2009 int (*add_ineq)(void *user, isl_int *), void *user)
2013 struct isl_vec *ineq;
2015 total = isl_basic_map_total_dim(tab->bmap);
2016 div_pos = 1 + total - tab->bmap->n_div + div;
2018 ineq = ineq_for_div(tab->bmap, div);
2023 if (add_ineq(user, ineq->el) < 0)
2026 if (isl_tab_add_ineq(tab, ineq->el) < 0)
2030 isl_seq_neg(ineq->el, tab->bmap->div[div] + 1, 1 + total);
2031 isl_int_set(ineq->el[div_pos], tab->bmap->div[div][0]);
2032 isl_int_add(ineq->el[0], ineq->el[0], ineq->el[div_pos]);
2033 isl_int_sub_ui(ineq->el[0], ineq->el[0], 1);
2036 if (add_ineq(user, ineq->el) < 0)
2039 if (isl_tab_add_ineq(tab, ineq->el) < 0)
2051 /* Add an extra div, prescrived by "div" to the tableau and
2052 * the associated bmap (which is assumed to be non-NULL).
2054 * If add_ineq is not NULL, then this function is used instead
2055 * of isl_tab_add_ineq to add the div constraints.
2056 * This complication is needed because the code in isl_tab_pip
2057 * wants to perform some extra processing when an inequality
2058 * is added to the tableau.
2060 int isl_tab_add_div(struct isl_tab *tab, __isl_keep isl_vec *div,
2061 int (*add_ineq)(void *user, isl_int *), void *user)
2071 isl_assert(tab->mat->ctx, tab->bmap, return -1);
2073 for (i = 0; i < tab->n_var; ++i) {
2074 if (isl_int_is_neg(div->el[2 + i]))
2076 if (isl_int_is_zero(div->el[2 + i]))
2078 if (!tab->var[i].is_nonneg)
2081 nonneg = i == tab->n_var && !isl_int_is_neg(div->el[1]);
2083 if (isl_tab_extend_cons(tab, 3) < 0)
2085 if (isl_tab_extend_vars(tab, 1) < 0)
2087 r = isl_tab_allocate_var(tab);
2092 tab->var[r].is_nonneg = 1;
2094 tab->bmap = isl_basic_map_extend_dim(tab->bmap,
2095 isl_basic_map_get_dim(tab->bmap), 1, 0, 2);
2096 k = isl_basic_map_alloc_div(tab->bmap);
2099 isl_seq_cpy(tab->bmap->div[k], div->el, div->size);
2100 if (isl_tab_push(tab, isl_tab_undo_bmap_div) < 0)
2103 if (add_div_constraints(tab, k, add_ineq, user) < 0)
2109 struct isl_tab *isl_tab_from_basic_map(struct isl_basic_map *bmap)
2112 struct isl_tab *tab;
2116 tab = isl_tab_alloc(bmap->ctx,
2117 isl_basic_map_total_dim(bmap) + bmap->n_ineq + 1,
2118 isl_basic_map_total_dim(bmap), 0);
2121 tab->rational = ISL_F_ISSET(bmap, ISL_BASIC_MAP_RATIONAL);
2122 if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) {
2123 if (isl_tab_mark_empty(tab) < 0)
2127 for (i = 0; i < bmap->n_eq; ++i) {
2128 tab = add_eq(tab, bmap->eq[i]);
2132 for (i = 0; i < bmap->n_ineq; ++i) {
2133 if (isl_tab_add_ineq(tab, bmap->ineq[i]) < 0)
2144 struct isl_tab *isl_tab_from_basic_set(struct isl_basic_set *bset)
2146 return isl_tab_from_basic_map((struct isl_basic_map *)bset);
2149 /* Construct a tableau corresponding to the recession cone of "bset".
2151 struct isl_tab *isl_tab_from_recession_cone(__isl_keep isl_basic_set *bset,
2156 struct isl_tab *tab;
2157 unsigned offset = 0;
2162 offset = isl_basic_set_dim(bset, isl_dim_param);
2163 tab = isl_tab_alloc(bset->ctx, bset->n_eq + bset->n_ineq,
2164 isl_basic_set_total_dim(bset) - offset, 0);
2167 tab->rational = ISL_F_ISSET(bset, ISL_BASIC_SET_RATIONAL);
2171 for (i = 0; i < bset->n_eq; ++i) {
2172 isl_int_swap(bset->eq[i][offset], cst);
2174 tab = isl_tab_add_eq(tab, bset->eq[i] + offset);
2176 tab = add_eq(tab, bset->eq[i]);
2177 isl_int_swap(bset->eq[i][offset], cst);
2181 for (i = 0; i < bset->n_ineq; ++i) {
2183 isl_int_swap(bset->ineq[i][offset], cst);
2184 r = isl_tab_add_row(tab, bset->ineq[i] + offset);
2185 isl_int_swap(bset->ineq[i][offset], cst);
2188 tab->con[r].is_nonneg = 1;
2189 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
2201 /* Assuming "tab" is the tableau of a cone, check if the cone is
2202 * bounded, i.e., if it is empty or only contains the origin.
2204 int isl_tab_cone_is_bounded(struct isl_tab *tab)
2212 if (tab->n_dead == tab->n_col)
2216 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2217 struct isl_tab_var *var;
2219 var = isl_tab_var_from_row(tab, i);
2220 if (!var->is_nonneg)
2222 sgn = sign_of_max(tab, var);
2227 if (close_row(tab, var) < 0)
2231 if (tab->n_dead == tab->n_col)
2233 if (i == tab->n_row)
2238 int isl_tab_sample_is_integer(struct isl_tab *tab)
2245 for (i = 0; i < tab->n_var; ++i) {
2247 if (!tab->var[i].is_row)
2249 row = tab->var[i].index;
2250 if (!isl_int_is_divisible_by(tab->mat->row[row][1],
2251 tab->mat->row[row][0]))
2257 static struct isl_vec *extract_integer_sample(struct isl_tab *tab)
2260 struct isl_vec *vec;
2262 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
2266 isl_int_set_si(vec->block.data[0], 1);
2267 for (i = 0; i < tab->n_var; ++i) {
2268 if (!tab->var[i].is_row)
2269 isl_int_set_si(vec->block.data[1 + i], 0);
2271 int row = tab->var[i].index;
2272 isl_int_divexact(vec->block.data[1 + i],
2273 tab->mat->row[row][1], tab->mat->row[row][0]);
2280 struct isl_vec *isl_tab_get_sample_value(struct isl_tab *tab)
2283 struct isl_vec *vec;
2289 vec = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_var);
2295 isl_int_set_si(vec->block.data[0], 1);
2296 for (i = 0; i < tab->n_var; ++i) {
2298 if (!tab->var[i].is_row) {
2299 isl_int_set_si(vec->block.data[1 + i], 0);
2302 row = tab->var[i].index;
2303 isl_int_gcd(m, vec->block.data[0], tab->mat->row[row][0]);
2304 isl_int_divexact(m, tab->mat->row[row][0], m);
2305 isl_seq_scale(vec->block.data, vec->block.data, m, 1 + i);
2306 isl_int_divexact(m, vec->block.data[0], tab->mat->row[row][0]);
2307 isl_int_mul(vec->block.data[1 + i], m, tab->mat->row[row][1]);
2309 vec = isl_vec_normalize(vec);
2315 /* Update "bmap" based on the results of the tableau "tab".
2316 * In particular, implicit equalities are made explicit, redundant constraints
2317 * are removed and if the sample value happens to be integer, it is stored
2318 * in "bmap" (unless "bmap" already had an integer sample).
2320 * The tableau is assumed to have been created from "bmap" using
2321 * isl_tab_from_basic_map.
2323 struct isl_basic_map *isl_basic_map_update_from_tab(struct isl_basic_map *bmap,
2324 struct isl_tab *tab)
2336 bmap = isl_basic_map_set_to_empty(bmap);
2338 for (i = bmap->n_ineq - 1; i >= 0; --i) {
2339 if (isl_tab_is_equality(tab, n_eq + i))
2340 isl_basic_map_inequality_to_equality(bmap, i);
2341 else if (isl_tab_is_redundant(tab, n_eq + i))
2342 isl_basic_map_drop_inequality(bmap, i);
2344 if (bmap->n_eq != n_eq)
2345 isl_basic_map_gauss(bmap, NULL);
2346 if (!tab->rational &&
2347 !bmap->sample && isl_tab_sample_is_integer(tab))
2348 bmap->sample = extract_integer_sample(tab);
2352 struct isl_basic_set *isl_basic_set_update_from_tab(struct isl_basic_set *bset,
2353 struct isl_tab *tab)
2355 return (struct isl_basic_set *)isl_basic_map_update_from_tab(
2356 (struct isl_basic_map *)bset, tab);
2359 /* Given a non-negative variable "var", add a new non-negative variable
2360 * that is the opposite of "var", ensuring that var can only attain the
2362 * If var = n/d is a row variable, then the new variable = -n/d.
2363 * If var is a column variables, then the new variable = -var.
2364 * If the new variable cannot attain non-negative values, then
2365 * the resulting tableau is empty.
2366 * Otherwise, we know the value will be zero and we close the row.
2368 static int cut_to_hyperplane(struct isl_tab *tab, struct isl_tab_var *var)
2373 unsigned off = 2 + tab->M;
2377 isl_assert(tab->mat->ctx, !var->is_redundant, return -1);
2378 isl_assert(tab->mat->ctx, var->is_nonneg, return -1);
2380 if (isl_tab_extend_cons(tab, 1) < 0)
2384 tab->con[r].index = tab->n_row;
2385 tab->con[r].is_row = 1;
2386 tab->con[r].is_nonneg = 0;
2387 tab->con[r].is_zero = 0;
2388 tab->con[r].is_redundant = 0;
2389 tab->con[r].frozen = 0;
2390 tab->con[r].negated = 0;
2391 tab->row_var[tab->n_row] = ~r;
2392 row = tab->mat->row[tab->n_row];
2395 isl_int_set(row[0], tab->mat->row[var->index][0]);
2396 isl_seq_neg(row + 1,
2397 tab->mat->row[var->index] + 1, 1 + tab->n_col);
2399 isl_int_set_si(row[0], 1);
2400 isl_seq_clr(row + 1, 1 + tab->n_col);
2401 isl_int_set_si(row[off + var->index], -1);
2406 if (isl_tab_push_var(tab, isl_tab_undo_allocate, &tab->con[r]) < 0)
2409 sgn = sign_of_max(tab, &tab->con[r]);
2413 if (isl_tab_mark_empty(tab) < 0)
2417 tab->con[r].is_nonneg = 1;
2418 if (isl_tab_push_var(tab, isl_tab_undo_nonneg, &tab->con[r]) < 0)
2421 if (close_row(tab, &tab->con[r]) < 0)
2427 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2428 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2429 * by r' = r + 1 >= 0.
2430 * If r is a row variable, we simply increase the constant term by one
2431 * (taking into account the denominator).
2432 * If r is a column variable, then we need to modify each row that
2433 * refers to r = r' - 1 by substituting this equality, effectively
2434 * subtracting the coefficient of the column from the constant.
2435 * We should only do this if the minimum is manifestly unbounded,
2436 * however. Otherwise, we may end up with negative sample values
2437 * for non-negative variables.
2438 * So, if r is a column variable with a minimum that is not
2439 * manifestly unbounded, then we need to move it to a row.
2440 * However, the sample value of this row may be negative,
2441 * even after the relaxation, so we need to restore it.
2442 * We therefore prefer to pivot a column up to a row, if possible.
2444 struct isl_tab *isl_tab_relax(struct isl_tab *tab, int con)
2446 struct isl_tab_var *var;
2447 unsigned off = 2 + tab->M;
2452 var = &tab->con[con];
2454 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2455 if (to_row(tab, var, 1) < 0)
2457 if (!var->is_row && !min_is_manifestly_unbounded(tab, var))
2458 if (to_row(tab, var, -1) < 0)
2462 isl_int_add(tab->mat->row[var->index][1],
2463 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2464 if (restore_row(tab, var) < 0)
2469 for (i = 0; i < tab->n_row; ++i) {
2470 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2472 isl_int_sub(tab->mat->row[i][1], tab->mat->row[i][1],
2473 tab->mat->row[i][off + var->index]);
2478 if (isl_tab_push_var(tab, isl_tab_undo_relax, var) < 0)
2487 int isl_tab_select_facet(struct isl_tab *tab, int con)
2492 return cut_to_hyperplane(tab, &tab->con[con]);
2495 static int may_be_equality(struct isl_tab *tab, int row)
2497 unsigned off = 2 + tab->M;
2498 return (tab->rational ? isl_int_is_zero(tab->mat->row[row][1])
2499 : isl_int_lt(tab->mat->row[row][1],
2500 tab->mat->row[row][0])) &&
2501 isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
2502 tab->n_col - tab->n_dead) != -1;
2505 /* Check for (near) equalities among the constraints.
2506 * A constraint is an equality if it is non-negative and if
2507 * its maximal value is either
2508 * - zero (in case of rational tableaus), or
2509 * - strictly less than 1 (in case of integer tableaus)
2511 * We first mark all non-redundant and non-dead variables that
2512 * are not frozen and not obviously not an equality.
2513 * Then we iterate over all marked variables if they can attain
2514 * any values larger than zero or at least one.
2515 * If the maximal value is zero, we mark any column variables
2516 * that appear in the row as being zero and mark the row as being redundant.
2517 * Otherwise, if the maximal value is strictly less than one (and the
2518 * tableau is integer), then we restrict the value to being zero
2519 * by adding an opposite non-negative variable.
2521 int isl_tab_detect_implicit_equalities(struct isl_tab *tab)
2530 if (tab->n_dead == tab->n_col)
2534 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2535 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2536 var->marked = !var->frozen && var->is_nonneg &&
2537 may_be_equality(tab, i);
2541 for (i = tab->n_dead; i < tab->n_col; ++i) {
2542 struct isl_tab_var *var = var_from_col(tab, i);
2543 var->marked = !var->frozen && var->is_nonneg;
2548 struct isl_tab_var *var;
2550 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2551 var = isl_tab_var_from_row(tab, i);
2555 if (i == tab->n_row) {
2556 for (i = tab->n_dead; i < tab->n_col; ++i) {
2557 var = var_from_col(tab, i);
2561 if (i == tab->n_col)
2566 sgn = sign_of_max(tab, var);
2570 if (close_row(tab, var) < 0)
2572 } else if (!tab->rational && !at_least_one(tab, var)) {
2573 if (cut_to_hyperplane(tab, var) < 0)
2575 return isl_tab_detect_implicit_equalities(tab);
2577 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2578 var = isl_tab_var_from_row(tab, i);
2581 if (may_be_equality(tab, i))
2591 static int con_is_redundant(struct isl_tab *tab, struct isl_tab_var *var)
2595 if (tab->rational) {
2596 int sgn = sign_of_min(tab, var);
2601 int irred = isl_tab_min_at_most_neg_one(tab, var);
2608 /* Check for (near) redundant constraints.
2609 * A constraint is redundant if it is non-negative and if
2610 * its minimal value (temporarily ignoring the non-negativity) is either
2611 * - zero (in case of rational tableaus), or
2612 * - strictly larger than -1 (in case of integer tableaus)
2614 * We first mark all non-redundant and non-dead variables that
2615 * are not frozen and not obviously negatively unbounded.
2616 * Then we iterate over all marked variables if they can attain
2617 * any values smaller than zero or at most negative one.
2618 * If not, we mark the row as being redundant (assuming it hasn't
2619 * been detected as being obviously redundant in the mean time).
2621 int isl_tab_detect_redundant(struct isl_tab *tab)
2630 if (tab->n_redundant == tab->n_row)
2634 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2635 struct isl_tab_var *var = isl_tab_var_from_row(tab, i);
2636 var->marked = !var->frozen && var->is_nonneg;
2640 for (i = tab->n_dead; i < tab->n_col; ++i) {
2641 struct isl_tab_var *var = var_from_col(tab, i);
2642 var->marked = !var->frozen && var->is_nonneg &&
2643 !min_is_manifestly_unbounded(tab, var);
2648 struct isl_tab_var *var;
2650 for (i = tab->n_redundant; i < tab->n_row; ++i) {
2651 var = isl_tab_var_from_row(tab, i);
2655 if (i == tab->n_row) {
2656 for (i = tab->n_dead; i < tab->n_col; ++i) {
2657 var = var_from_col(tab, i);
2661 if (i == tab->n_col)
2666 red = con_is_redundant(tab, var);
2669 if (red && !var->is_redundant)
2670 if (isl_tab_mark_redundant(tab, var->index) < 0)
2672 for (i = tab->n_dead; i < tab->n_col; ++i) {
2673 var = var_from_col(tab, i);
2676 if (!min_is_manifestly_unbounded(tab, var))
2686 int isl_tab_is_equality(struct isl_tab *tab, int con)
2693 if (tab->con[con].is_zero)
2695 if (tab->con[con].is_redundant)
2697 if (!tab->con[con].is_row)
2698 return tab->con[con].index < tab->n_dead;
2700 row = tab->con[con].index;
2703 return isl_int_is_zero(tab->mat->row[row][1]) &&
2704 isl_seq_first_non_zero(tab->mat->row[row] + 2 + tab->n_dead,
2705 tab->n_col - tab->n_dead) == -1;
2708 /* Return the minimial value of the affine expression "f" with denominator
2709 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2710 * the expression cannot attain arbitrarily small values.
2711 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2712 * The return value reflects the nature of the result (empty, unbounded,
2713 * minmimal value returned in *opt).
2715 enum isl_lp_result isl_tab_min(struct isl_tab *tab,
2716 isl_int *f, isl_int denom, isl_int *opt, isl_int *opt_denom,
2720 enum isl_lp_result res = isl_lp_ok;
2721 struct isl_tab_var *var;
2722 struct isl_tab_undo *snap;
2725 return isl_lp_empty;
2727 snap = isl_tab_snap(tab);
2728 r = isl_tab_add_row(tab, f);
2730 return isl_lp_error;
2732 isl_int_mul(tab->mat->row[var->index][0],
2733 tab->mat->row[var->index][0], denom);
2736 find_pivot(tab, var, var, -1, &row, &col);
2737 if (row == var->index) {
2738 res = isl_lp_unbounded;
2743 if (isl_tab_pivot(tab, row, col) < 0)
2744 return isl_lp_error;
2746 if (ISL_FL_ISSET(flags, ISL_TAB_SAVE_DUAL)) {
2749 isl_vec_free(tab->dual);
2750 tab->dual = isl_vec_alloc(tab->mat->ctx, 1 + tab->n_con);
2752 return isl_lp_error;
2753 isl_int_set(tab->dual->el[0], tab->mat->row[var->index][0]);
2754 for (i = 0; i < tab->n_con; ++i) {
2756 if (tab->con[i].is_row) {
2757 isl_int_set_si(tab->dual->el[1 + i], 0);
2760 pos = 2 + tab->M + tab->con[i].index;
2761 if (tab->con[i].negated)
2762 isl_int_neg(tab->dual->el[1 + i],
2763 tab->mat->row[var->index][pos]);
2765 isl_int_set(tab->dual->el[1 + i],
2766 tab->mat->row[var->index][pos]);
2769 if (opt && res == isl_lp_ok) {
2771 isl_int_set(*opt, tab->mat->row[var->index][1]);
2772 isl_int_set(*opt_denom, tab->mat->row[var->index][0]);
2774 isl_int_cdiv_q(*opt, tab->mat->row[var->index][1],
2775 tab->mat->row[var->index][0]);
2777 if (isl_tab_rollback(tab, snap) < 0)
2778 return isl_lp_error;
2782 int isl_tab_is_redundant(struct isl_tab *tab, int con)
2786 if (tab->con[con].is_zero)
2788 if (tab->con[con].is_redundant)
2790 return tab->con[con].is_row && tab->con[con].index < tab->n_redundant;
2793 /* Take a snapshot of the tableau that can be restored by s call to
2796 struct isl_tab_undo *isl_tab_snap(struct isl_tab *tab)
2804 /* Undo the operation performed by isl_tab_relax.
2806 static int unrelax(struct isl_tab *tab, struct isl_tab_var *var) WARN_UNUSED;
2807 static int unrelax(struct isl_tab *tab, struct isl_tab_var *var)
2809 unsigned off = 2 + tab->M;
2811 if (!var->is_row && !max_is_manifestly_unbounded(tab, var))
2812 if (to_row(tab, var, 1) < 0)
2816 isl_int_sub(tab->mat->row[var->index][1],
2817 tab->mat->row[var->index][1], tab->mat->row[var->index][0]);
2818 if (var->is_nonneg) {
2819 int sgn = restore_row(tab, var);
2820 isl_assert(tab->mat->ctx, sgn >= 0, return -1);
2825 for (i = 0; i < tab->n_row; ++i) {
2826 if (isl_int_is_zero(tab->mat->row[i][off + var->index]))
2828 isl_int_add(tab->mat->row[i][1], tab->mat->row[i][1],
2829 tab->mat->row[i][off + var->index]);
2837 static int perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo) WARN_UNUSED;
2838 static int perform_undo_var(struct isl_tab *tab, struct isl_tab_undo *undo)
2840 struct isl_tab_var *var = var_from_index(tab, undo->u.var_index);
2841 switch(undo->type) {
2842 case isl_tab_undo_nonneg:
2845 case isl_tab_undo_redundant:
2846 var->is_redundant = 0;
2848 restore_row(tab, isl_tab_var_from_row(tab, tab->n_redundant));
2850 case isl_tab_undo_freeze:
2853 case isl_tab_undo_zero:
2858 case isl_tab_undo_allocate:
2859 if (undo->u.var_index >= 0) {
2860 isl_assert(tab->mat->ctx, !var->is_row, return -1);
2861 drop_col(tab, var->index);
2865 if (!max_is_manifestly_unbounded(tab, var)) {
2866 if (to_row(tab, var, 1) < 0)
2868 } else if (!min_is_manifestly_unbounded(tab, var)) {
2869 if (to_row(tab, var, -1) < 0)
2872 if (to_row(tab, var, 0) < 0)
2875 drop_row(tab, var->index);
2877 case isl_tab_undo_relax:
2878 return unrelax(tab, var);
2884 /* Restore the tableau to the state where the basic variables
2885 * are those in "col_var".
2886 * We first construct a list of variables that are currently in
2887 * the basis, but shouldn't. Then we iterate over all variables
2888 * that should be in the basis and for each one that is currently
2889 * not in the basis, we exchange it with one of the elements of the
2890 * list constructed before.
2891 * We can always find an appropriate variable to pivot with because
2892 * the current basis is mapped to the old basis by a non-singular
2893 * matrix and so we can never end up with a zero row.
2895 static int restore_basis(struct isl_tab *tab, int *col_var)
2899 int *extra = NULL; /* current columns that contain bad stuff */
2900 unsigned off = 2 + tab->M;
2902 extra = isl_alloc_array(tab->mat->ctx, int, tab->n_col);
2905 for (i = 0; i < tab->n_col; ++i) {
2906 for (j = 0; j < tab->n_col; ++j)
2907 if (tab->col_var[i] == col_var[j])
2911 extra[n_extra++] = i;
2913 for (i = 0; i < tab->n_col && n_extra > 0; ++i) {
2914 struct isl_tab_var *var;
2917 for (j = 0; j < tab->n_col; ++j)
2918 if (col_var[i] == tab->col_var[j])
2922 var = var_from_index(tab, col_var[i]);
2924 for (j = 0; j < n_extra; ++j)
2925 if (!isl_int_is_zero(tab->mat->row[row][off+extra[j]]))
2927 isl_assert(tab->mat->ctx, j < n_extra, goto error);
2928 if (isl_tab_pivot(tab, row, extra[j]) < 0)
2930 extra[j] = extra[--n_extra];
2942 /* Remove all samples with index n or greater, i.e., those samples
2943 * that were added since we saved this number of samples in
2944 * isl_tab_save_samples.
2946 static void drop_samples_since(struct isl_tab *tab, int n)
2950 for (i = tab->n_sample - 1; i >= 0 && tab->n_sample > n; --i) {
2951 if (tab->sample_index[i] < n)
2954 if (i != tab->n_sample - 1) {
2955 int t = tab->sample_index[tab->n_sample-1];
2956 tab->sample_index[tab->n_sample-1] = tab->sample_index[i];
2957 tab->sample_index[i] = t;
2958 isl_mat_swap_rows(tab->samples, tab->n_sample-1, i);
2964 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo) WARN_UNUSED;
2965 static int perform_undo(struct isl_tab *tab, struct isl_tab_undo *undo)
2967 switch (undo->type) {
2968 case isl_tab_undo_empty:
2971 case isl_tab_undo_nonneg:
2972 case isl_tab_undo_redundant:
2973 case isl_tab_undo_freeze:
2974 case isl_tab_undo_zero:
2975 case isl_tab_undo_allocate:
2976 case isl_tab_undo_relax:
2977 return perform_undo_var(tab, undo);
2978 case isl_tab_undo_bmap_eq:
2979 return isl_basic_map_free_equality(tab->bmap, 1);
2980 case isl_tab_undo_bmap_ineq:
2981 return isl_basic_map_free_inequality(tab->bmap, 1);
2982 case isl_tab_undo_bmap_div:
2983 if (isl_basic_map_free_div(tab->bmap, 1) < 0)
2986 tab->samples->n_col--;
2988 case isl_tab_undo_saved_basis:
2989 if (restore_basis(tab, undo->u.col_var) < 0)
2992 case isl_tab_undo_drop_sample:
2995 case isl_tab_undo_saved_samples:
2996 drop_samples_since(tab, undo->u.n);
2998 case isl_tab_undo_callback:
2999 return undo->u.callback->run(undo->u.callback);
3001 isl_assert(tab->mat->ctx, 0, return -1);
3006 /* Return the tableau to the state it was in when the snapshot "snap"
3009 int isl_tab_rollback(struct isl_tab *tab, struct isl_tab_undo *snap)
3011 struct isl_tab_undo *undo, *next;
3017 for (undo = tab->top; undo && undo != &tab->bottom; undo = next) {
3021 if (perform_undo(tab, undo) < 0) {
3035 /* The given row "row" represents an inequality violated by all
3036 * points in the tableau. Check for some special cases of such
3037 * separating constraints.
3038 * In particular, if the row has been reduced to the constant -1,
3039 * then we know the inequality is adjacent (but opposite) to
3040 * an equality in the tableau.
3041 * If the row has been reduced to r = -1 -r', with r' an inequality
3042 * of the tableau, then the inequality is adjacent (but opposite)
3043 * to the inequality r'.
3045 static enum isl_ineq_type separation_type(struct isl_tab *tab, unsigned row)
3048 unsigned off = 2 + tab->M;
3051 return isl_ineq_separate;
3053 if (!isl_int_is_one(tab->mat->row[row][0]))
3054 return isl_ineq_separate;
3055 if (!isl_int_is_negone(tab->mat->row[row][1]))
3056 return isl_ineq_separate;
3058 pos = isl_seq_first_non_zero(tab->mat->row[row] + off + tab->n_dead,
3059 tab->n_col - tab->n_dead);
3061 return isl_ineq_adj_eq;
3063 if (!isl_int_is_negone(tab->mat->row[row][off + tab->n_dead + pos]))
3064 return isl_ineq_separate;
3066 pos = isl_seq_first_non_zero(
3067 tab->mat->row[row] + off + tab->n_dead + pos + 1,
3068 tab->n_col - tab->n_dead - pos - 1);
3070 return pos == -1 ? isl_ineq_adj_ineq : isl_ineq_separate;
3073 /* Check the effect of inequality "ineq" on the tableau "tab".
3075 * isl_ineq_redundant: satisfied by all points in the tableau
3076 * isl_ineq_separate: satisfied by no point in the tableau
3077 * isl_ineq_cut: satisfied by some by not all points
3078 * isl_ineq_adj_eq: adjacent to an equality
3079 * isl_ineq_adj_ineq: adjacent to an inequality.
3081 enum isl_ineq_type isl_tab_ineq_type(struct isl_tab *tab, isl_int *ineq)
3083 enum isl_ineq_type type = isl_ineq_error;
3084 struct isl_tab_undo *snap = NULL;
3089 return isl_ineq_error;
3091 if (isl_tab_extend_cons(tab, 1) < 0)
3092 return isl_ineq_error;
3094 snap = isl_tab_snap(tab);
3096 con = isl_tab_add_row(tab, ineq);
3100 row = tab->con[con].index;
3101 if (isl_tab_row_is_redundant(tab, row))
3102 type = isl_ineq_redundant;
3103 else if (isl_int_is_neg(tab->mat->row[row][1]) &&
3105 isl_int_abs_ge(tab->mat->row[row][1],
3106 tab->mat->row[row][0]))) {
3107 int nonneg = at_least_zero(tab, &tab->con[con]);
3111 type = isl_ineq_cut;
3113 type = separation_type(tab, row);
3115 int red = con_is_redundant(tab, &tab->con[con]);
3119 type = isl_ineq_cut;
3121 type = isl_ineq_redundant;
3124 if (isl_tab_rollback(tab, snap))
3125 return isl_ineq_error;
3128 return isl_ineq_error;
3131 int isl_tab_track_bmap(struct isl_tab *tab, __isl_take isl_basic_map *bmap)
3136 isl_assert(tab->mat->ctx, tab->n_eq == bmap->n_eq, return -1);
3137 isl_assert(tab->mat->ctx,
3138 tab->n_con == bmap->n_eq + bmap->n_ineq, return -1);
3144 isl_basic_map_free(bmap);
3148 int isl_tab_track_bset(struct isl_tab *tab, __isl_take isl_basic_set *bset)
3150 return isl_tab_track_bmap(tab, (isl_basic_map *)bset);
3153 __isl_keep isl_basic_set *isl_tab_peek_bset(struct isl_tab *tab)
3158 return (isl_basic_set *)tab->bmap;
3161 void isl_tab_dump(struct isl_tab *tab, FILE *out, int indent)
3167 fprintf(out, "%*snull tab\n", indent, "");
3170 fprintf(out, "%*sn_redundant: %d, n_dead: %d", indent, "",
3171 tab->n_redundant, tab->n_dead);
3173 fprintf(out, ", rational");
3175 fprintf(out, ", empty");
3177 fprintf(out, "%*s[", indent, "");
3178 for (i = 0; i < tab->n_var; ++i) {
3180 fprintf(out, (i == tab->n_param ||
3181 i == tab->n_var - tab->n_div) ? "; "
3183 fprintf(out, "%c%d%s", tab->var[i].is_row ? 'r' : 'c',
3185 tab->var[i].is_zero ? " [=0]" :
3186 tab->var[i].is_redundant ? " [R]" : "");
3188 fprintf(out, "]\n");
3189 fprintf(out, "%*s[", indent, "");
3190 for (i = 0; i < tab->n_con; ++i) {
3193 fprintf(out, "%c%d%s", tab->con[i].is_row ? 'r' : 'c',
3195 tab->con[i].is_zero ? " [=0]" :
3196 tab->con[i].is_redundant ? " [R]" : "");
3198 fprintf(out, "]\n");
3199 fprintf(out, "%*s[", indent, "");
3200 for (i = 0; i < tab->n_row; ++i) {
3201 const char *sign = "";
3204 if (tab->row_sign) {
3205 if (tab->row_sign[i] == isl_tab_row_unknown)
3207 else if (tab->row_sign[i] == isl_tab_row_neg)
3209 else if (tab->row_sign[i] == isl_tab_row_pos)
3214 fprintf(out, "r%d: %d%s%s", i, tab->row_var[i],
3215 isl_tab_var_from_row(tab, i)->is_nonneg ? " [>=0]" : "", sign);
3217 fprintf(out, "]\n");
3218 fprintf(out, "%*s[", indent, "");
3219 for (i = 0; i < tab->n_col; ++i) {
3222 fprintf(out, "c%d: %d%s", i, tab->col_var[i],
3223 var_from_col(tab, i)->is_nonneg ? " [>=0]" : "");
3225 fprintf(out, "]\n");
3226 r = tab->mat->n_row;
3227 tab->mat->n_row = tab->n_row;
3228 c = tab->mat->n_col;
3229 tab->mat->n_col = 2 + tab->M + tab->n_col;
3230 isl_mat_dump(tab->mat, out, indent);
3231 tab->mat->n_row = r;
3232 tab->mat->n_col = c;
3234 isl_basic_map_dump(tab->bmap, out, indent);