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;
67 tab
->strict_redundant
= 0;
74 tab
->bottom
.type
= isl_tab_undo_bottom
;
75 tab
->bottom
.next
= NULL
;
76 tab
->top
= &tab
->bottom
;
88 int isl_tab_extend_cons(struct isl_tab
*tab
, unsigned n_new
)
97 if (tab
->max_con
< tab
->n_con
+ n_new
) {
98 struct isl_tab_var
*con
;
100 con
= isl_realloc_array(tab
->mat
->ctx
, tab
->con
,
101 struct isl_tab_var
, tab
->max_con
+ n_new
);
105 tab
->max_con
+= n_new
;
107 if (tab
->mat
->n_row
< tab
->n_row
+ n_new
) {
110 tab
->mat
= isl_mat_extend(tab
->mat
,
111 tab
->n_row
+ n_new
, off
+ tab
->n_col
);
114 row_var
= isl_realloc_array(tab
->mat
->ctx
, tab
->row_var
,
115 int, tab
->mat
->n_row
);
118 tab
->row_var
= row_var
;
120 enum isl_tab_row_sign
*s
;
121 s
= isl_realloc_array(tab
->mat
->ctx
, tab
->row_sign
,
122 enum isl_tab_row_sign
, tab
->mat
->n_row
);
131 /* Make room for at least n_new extra variables.
132 * Return -1 if anything went wrong.
134 int isl_tab_extend_vars(struct isl_tab
*tab
, unsigned n_new
)
136 struct isl_tab_var
*var
;
137 unsigned off
= 2 + tab
->M
;
139 if (tab
->max_var
< tab
->n_var
+ n_new
) {
140 var
= isl_realloc_array(tab
->mat
->ctx
, tab
->var
,
141 struct isl_tab_var
, tab
->n_var
+ n_new
);
145 tab
->max_var
+= n_new
;
148 if (tab
->mat
->n_col
< off
+ tab
->n_col
+ n_new
) {
151 tab
->mat
= isl_mat_extend(tab
->mat
,
152 tab
->mat
->n_row
, off
+ tab
->n_col
+ n_new
);
155 p
= isl_realloc_array(tab
->mat
->ctx
, tab
->col_var
,
156 int, tab
->n_col
+ n_new
);
165 struct isl_tab
*isl_tab_extend(struct isl_tab
*tab
, unsigned n_new
)
167 if (isl_tab_extend_cons(tab
, n_new
) >= 0)
174 static void free_undo(struct isl_tab
*tab
)
176 struct isl_tab_undo
*undo
, *next
;
178 for (undo
= tab
->top
; undo
&& undo
!= &tab
->bottom
; undo
= next
) {
185 void isl_tab_free(struct isl_tab
*tab
)
190 isl_mat_free(tab
->mat
);
191 isl_vec_free(tab
->dual
);
192 isl_basic_map_free(tab
->bmap
);
198 isl_mat_free(tab
->samples
);
199 free(tab
->sample_index
);
200 isl_mat_free(tab
->basis
);
204 struct isl_tab
*isl_tab_dup(struct isl_tab
*tab
)
214 dup
= isl_calloc_type(tab
->mat
->ctx
, struct isl_tab
);
217 dup
->mat
= isl_mat_dup(tab
->mat
);
220 dup
->var
= isl_alloc_array(tab
->mat
->ctx
, struct isl_tab_var
, tab
->max_var
);
223 for (i
= 0; i
< tab
->n_var
; ++i
)
224 dup
->var
[i
] = tab
->var
[i
];
225 dup
->con
= isl_alloc_array(tab
->mat
->ctx
, struct isl_tab_var
, tab
->max_con
);
228 for (i
= 0; i
< tab
->n_con
; ++i
)
229 dup
->con
[i
] = tab
->con
[i
];
230 dup
->col_var
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->mat
->n_col
- off
);
233 for (i
= 0; i
< tab
->n_col
; ++i
)
234 dup
->col_var
[i
] = tab
->col_var
[i
];
235 dup
->row_var
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->mat
->n_row
);
238 for (i
= 0; i
< tab
->n_row
; ++i
)
239 dup
->row_var
[i
] = tab
->row_var
[i
];
241 dup
->row_sign
= isl_alloc_array(tab
->mat
->ctx
, enum isl_tab_row_sign
,
245 for (i
= 0; i
< tab
->n_row
; ++i
)
246 dup
->row_sign
[i
] = tab
->row_sign
[i
];
249 dup
->samples
= isl_mat_dup(tab
->samples
);
252 dup
->sample_index
= isl_alloc_array(tab
->mat
->ctx
, int,
253 tab
->samples
->n_row
);
254 if (!dup
->sample_index
)
256 dup
->n_sample
= tab
->n_sample
;
257 dup
->n_outside
= tab
->n_outside
;
259 dup
->n_row
= tab
->n_row
;
260 dup
->n_con
= tab
->n_con
;
261 dup
->n_eq
= tab
->n_eq
;
262 dup
->max_con
= tab
->max_con
;
263 dup
->n_col
= tab
->n_col
;
264 dup
->n_var
= tab
->n_var
;
265 dup
->max_var
= tab
->max_var
;
266 dup
->n_param
= tab
->n_param
;
267 dup
->n_div
= tab
->n_div
;
268 dup
->n_dead
= tab
->n_dead
;
269 dup
->n_redundant
= tab
->n_redundant
;
270 dup
->rational
= tab
->rational
;
271 dup
->empty
= tab
->empty
;
272 dup
->strict_redundant
= 0;
276 tab
->cone
= tab
->cone
;
277 dup
->bottom
.type
= isl_tab_undo_bottom
;
278 dup
->bottom
.next
= NULL
;
279 dup
->top
= &dup
->bottom
;
281 dup
->n_zero
= tab
->n_zero
;
282 dup
->n_unbounded
= tab
->n_unbounded
;
283 dup
->basis
= isl_mat_dup(tab
->basis
);
291 /* Construct the coefficient matrix of the product tableau
293 * mat{1,2} is the coefficient matrix of tableau {1,2}
294 * row{1,2} is the number of rows in tableau {1,2}
295 * col{1,2} is the number of columns in tableau {1,2}
296 * off is the offset to the coefficient column (skipping the
297 * denominator, the constant term and the big parameter if any)
298 * r{1,2} is the number of redundant rows in tableau {1,2}
299 * d{1,2} is the number of dead columns in tableau {1,2}
301 * The order of the rows and columns in the result is as explained
302 * in isl_tab_product.
304 static struct isl_mat
*tab_mat_product(struct isl_mat
*mat1
,
305 struct isl_mat
*mat2
, unsigned row1
, unsigned row2
,
306 unsigned col1
, unsigned col2
,
307 unsigned off
, unsigned r1
, unsigned r2
, unsigned d1
, unsigned d2
)
310 struct isl_mat
*prod
;
313 prod
= isl_mat_alloc(mat1
->ctx
, mat1
->n_row
+ mat2
->n_row
,
319 for (i
= 0; i
< r1
; ++i
) {
320 isl_seq_cpy(prod
->row
[n
+ i
], mat1
->row
[i
], off
+ d1
);
321 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
, d2
);
322 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
+ d2
,
323 mat1
->row
[i
] + off
+ d1
, col1
- d1
);
324 isl_seq_clr(prod
->row
[n
+ i
] + off
+ col1
+ d1
, col2
- d2
);
328 for (i
= 0; i
< r2
; ++i
) {
329 isl_seq_cpy(prod
->row
[n
+ i
], mat2
->row
[i
], off
);
330 isl_seq_clr(prod
->row
[n
+ i
] + off
, d1
);
331 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
,
332 mat2
->row
[i
] + off
, d2
);
333 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
+ d2
, col1
- d1
);
334 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ col1
+ d1
,
335 mat2
->row
[i
] + off
+ d2
, col2
- d2
);
339 for (i
= 0; i
< row1
- r1
; ++i
) {
340 isl_seq_cpy(prod
->row
[n
+ i
], mat1
->row
[r1
+ i
], off
+ d1
);
341 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
, d2
);
342 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
+ d2
,
343 mat1
->row
[r1
+ i
] + off
+ d1
, col1
- d1
);
344 isl_seq_clr(prod
->row
[n
+ i
] + off
+ col1
+ d1
, col2
- d2
);
348 for (i
= 0; i
< row2
- r2
; ++i
) {
349 isl_seq_cpy(prod
->row
[n
+ i
], mat2
->row
[r2
+ i
], off
);
350 isl_seq_clr(prod
->row
[n
+ i
] + off
, d1
);
351 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
,
352 mat2
->row
[r2
+ i
] + off
, d2
);
353 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
+ d2
, col1
- d1
);
354 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ col1
+ d1
,
355 mat2
->row
[r2
+ i
] + off
+ d2
, col2
- d2
);
361 /* Update the row or column index of a variable that corresponds
362 * to a variable in the first input tableau.
364 static void update_index1(struct isl_tab_var
*var
,
365 unsigned r1
, unsigned r2
, unsigned d1
, unsigned d2
)
367 if (var
->index
== -1)
369 if (var
->is_row
&& var
->index
>= r1
)
371 if (!var
->is_row
&& var
->index
>= d1
)
375 /* Update the row or column index of a variable that corresponds
376 * to a variable in the second input tableau.
378 static void update_index2(struct isl_tab_var
*var
,
379 unsigned row1
, unsigned col1
,
380 unsigned r1
, unsigned r2
, unsigned d1
, unsigned d2
)
382 if (var
->index
== -1)
397 /* Create a tableau that represents the Cartesian product of the sets
398 * represented by tableaus tab1 and tab2.
399 * The order of the rows in the product is
400 * - redundant rows of tab1
401 * - redundant rows of tab2
402 * - non-redundant rows of tab1
403 * - non-redundant rows of tab2
404 * The order of the columns is
407 * - coefficient of big parameter, if any
408 * - dead columns of tab1
409 * - dead columns of tab2
410 * - live columns of tab1
411 * - live columns of tab2
412 * The order of the variables and the constraints is a concatenation
413 * of order in the two input tableaus.
415 struct isl_tab
*isl_tab_product(struct isl_tab
*tab1
, struct isl_tab
*tab2
)
418 struct isl_tab
*prod
;
420 unsigned r1
, r2
, d1
, d2
;
425 isl_assert(tab1
->mat
->ctx
, tab1
->M
== tab2
->M
, return NULL
);
426 isl_assert(tab1
->mat
->ctx
, tab1
->rational
== tab2
->rational
, return NULL
);
427 isl_assert(tab1
->mat
->ctx
, tab1
->cone
== tab2
->cone
, return NULL
);
428 isl_assert(tab1
->mat
->ctx
, !tab1
->row_sign
, return NULL
);
429 isl_assert(tab1
->mat
->ctx
, !tab2
->row_sign
, return NULL
);
430 isl_assert(tab1
->mat
->ctx
, tab1
->n_param
== 0, return NULL
);
431 isl_assert(tab1
->mat
->ctx
, tab2
->n_param
== 0, return NULL
);
432 isl_assert(tab1
->mat
->ctx
, tab1
->n_div
== 0, return NULL
);
433 isl_assert(tab1
->mat
->ctx
, tab2
->n_div
== 0, return NULL
);
436 r1
= tab1
->n_redundant
;
437 r2
= tab2
->n_redundant
;
440 prod
= isl_calloc_type(tab1
->mat
->ctx
, struct isl_tab
);
443 prod
->mat
= tab_mat_product(tab1
->mat
, tab2
->mat
,
444 tab1
->n_row
, tab2
->n_row
,
445 tab1
->n_col
, tab2
->n_col
, off
, r1
, r2
, d1
, d2
);
448 prod
->var
= isl_alloc_array(tab1
->mat
->ctx
, struct isl_tab_var
,
449 tab1
->max_var
+ tab2
->max_var
);
452 for (i
= 0; i
< tab1
->n_var
; ++i
) {
453 prod
->var
[i
] = tab1
->var
[i
];
454 update_index1(&prod
->var
[i
], r1
, r2
, d1
, d2
);
456 for (i
= 0; i
< tab2
->n_var
; ++i
) {
457 prod
->var
[tab1
->n_var
+ i
] = tab2
->var
[i
];
458 update_index2(&prod
->var
[tab1
->n_var
+ i
],
459 tab1
->n_row
, tab1
->n_col
,
462 prod
->con
= isl_alloc_array(tab1
->mat
->ctx
, struct isl_tab_var
,
463 tab1
->max_con
+ tab2
->max_con
);
466 for (i
= 0; i
< tab1
->n_con
; ++i
) {
467 prod
->con
[i
] = tab1
->con
[i
];
468 update_index1(&prod
->con
[i
], r1
, r2
, d1
, d2
);
470 for (i
= 0; i
< tab2
->n_con
; ++i
) {
471 prod
->con
[tab1
->n_con
+ i
] = tab2
->con
[i
];
472 update_index2(&prod
->con
[tab1
->n_con
+ i
],
473 tab1
->n_row
, tab1
->n_col
,
476 prod
->col_var
= isl_alloc_array(tab1
->mat
->ctx
, int,
477 tab1
->n_col
+ tab2
->n_col
);
480 for (i
= 0; i
< tab1
->n_col
; ++i
) {
481 int pos
= i
< d1
? i
: i
+ d2
;
482 prod
->col_var
[pos
] = tab1
->col_var
[i
];
484 for (i
= 0; i
< tab2
->n_col
; ++i
) {
485 int pos
= i
< d2
? d1
+ i
: tab1
->n_col
+ i
;
486 int t
= tab2
->col_var
[i
];
491 prod
->col_var
[pos
] = t
;
493 prod
->row_var
= isl_alloc_array(tab1
->mat
->ctx
, int,
494 tab1
->mat
->n_row
+ tab2
->mat
->n_row
);
497 for (i
= 0; i
< tab1
->n_row
; ++i
) {
498 int pos
= i
< r1
? i
: i
+ r2
;
499 prod
->row_var
[pos
] = tab1
->row_var
[i
];
501 for (i
= 0; i
< tab2
->n_row
; ++i
) {
502 int pos
= i
< r2
? r1
+ i
: tab1
->n_row
+ i
;
503 int t
= tab2
->row_var
[i
];
508 prod
->row_var
[pos
] = t
;
510 prod
->samples
= NULL
;
511 prod
->sample_index
= NULL
;
512 prod
->n_row
= tab1
->n_row
+ tab2
->n_row
;
513 prod
->n_con
= tab1
->n_con
+ tab2
->n_con
;
515 prod
->max_con
= tab1
->max_con
+ tab2
->max_con
;
516 prod
->n_col
= tab1
->n_col
+ tab2
->n_col
;
517 prod
->n_var
= tab1
->n_var
+ tab2
->n_var
;
518 prod
->max_var
= tab1
->max_var
+ tab2
->max_var
;
521 prod
->n_dead
= tab1
->n_dead
+ tab2
->n_dead
;
522 prod
->n_redundant
= tab1
->n_redundant
+ tab2
->n_redundant
;
523 prod
->rational
= tab1
->rational
;
524 prod
->empty
= tab1
->empty
|| tab2
->empty
;
525 prod
->strict_redundant
= tab1
->strict_redundant
|| tab2
->strict_redundant
;
529 prod
->cone
= tab1
->cone
;
530 prod
->bottom
.type
= isl_tab_undo_bottom
;
531 prod
->bottom
.next
= NULL
;
532 prod
->top
= &prod
->bottom
;
535 prod
->n_unbounded
= 0;
544 static struct isl_tab_var
*var_from_index(struct isl_tab
*tab
, int i
)
549 return &tab
->con
[~i
];
552 struct isl_tab_var
*isl_tab_var_from_row(struct isl_tab
*tab
, int i
)
554 return var_from_index(tab
, tab
->row_var
[i
]);
557 static struct isl_tab_var
*var_from_col(struct isl_tab
*tab
, int i
)
559 return var_from_index(tab
, tab
->col_var
[i
]);
562 /* Check if there are any upper bounds on column variable "var",
563 * i.e., non-negative rows where var appears with a negative coefficient.
564 * Return 1 if there are no such bounds.
566 static int max_is_manifestly_unbounded(struct isl_tab
*tab
,
567 struct isl_tab_var
*var
)
570 unsigned off
= 2 + tab
->M
;
574 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
575 if (!isl_int_is_neg(tab
->mat
->row
[i
][off
+ var
->index
]))
577 if (isl_tab_var_from_row(tab
, i
)->is_nonneg
)
583 /* Check if there are any lower bounds on column variable "var",
584 * i.e., non-negative rows where var appears with a positive coefficient.
585 * Return 1 if there are no such bounds.
587 static int min_is_manifestly_unbounded(struct isl_tab
*tab
,
588 struct isl_tab_var
*var
)
591 unsigned off
= 2 + tab
->M
;
595 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
596 if (!isl_int_is_pos(tab
->mat
->row
[i
][off
+ var
->index
]))
598 if (isl_tab_var_from_row(tab
, i
)->is_nonneg
)
604 static int row_cmp(struct isl_tab
*tab
, int r1
, int r2
, int c
, isl_int t
)
606 unsigned off
= 2 + tab
->M
;
610 isl_int_mul(t
, tab
->mat
->row
[r1
][2], tab
->mat
->row
[r2
][off
+c
]);
611 isl_int_submul(t
, tab
->mat
->row
[r2
][2], tab
->mat
->row
[r1
][off
+c
]);
616 isl_int_mul(t
, tab
->mat
->row
[r1
][1], tab
->mat
->row
[r2
][off
+ c
]);
617 isl_int_submul(t
, tab
->mat
->row
[r2
][1], tab
->mat
->row
[r1
][off
+ c
]);
618 return isl_int_sgn(t
);
621 /* Given the index of a column "c", return the index of a row
622 * that can be used to pivot the column in, with either an increase
623 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
624 * If "var" is not NULL, then the row returned will be different from
625 * the one associated with "var".
627 * Each row in the tableau is of the form
629 * x_r = a_r0 + \sum_i a_ri x_i
631 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
632 * impose any limit on the increase or decrease in the value of x_c
633 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
634 * for the row with the smallest (most stringent) such bound.
635 * Note that the common denominator of each row drops out of the fraction.
636 * To check if row j has a smaller bound than row r, i.e.,
637 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
638 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
639 * where -sign(a_jc) is equal to "sgn".
641 static int pivot_row(struct isl_tab
*tab
,
642 struct isl_tab_var
*var
, int sgn
, int c
)
646 unsigned off
= 2 + tab
->M
;
650 for (j
= tab
->n_redundant
; j
< tab
->n_row
; ++j
) {
651 if (var
&& j
== var
->index
)
653 if (!isl_tab_var_from_row(tab
, j
)->is_nonneg
)
655 if (sgn
* isl_int_sgn(tab
->mat
->row
[j
][off
+ c
]) >= 0)
661 tsgn
= sgn
* row_cmp(tab
, r
, j
, c
, t
);
662 if (tsgn
< 0 || (tsgn
== 0 &&
663 tab
->row_var
[j
] < tab
->row_var
[r
]))
670 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
671 * (sgn < 0) the value of row variable var.
672 * If not NULL, then skip_var is a row variable that should be ignored
673 * while looking for a pivot row. It is usually equal to var.
675 * As the given row in the tableau is of the form
677 * x_r = a_r0 + \sum_i a_ri x_i
679 * we need to find a column such that the sign of a_ri is equal to "sgn"
680 * (such that an increase in x_i will have the desired effect) or a
681 * column with a variable that may attain negative values.
682 * If a_ri is positive, then we need to move x_i in the same direction
683 * to obtain the desired effect. Otherwise, x_i has to move in the
684 * opposite direction.
686 static void find_pivot(struct isl_tab
*tab
,
687 struct isl_tab_var
*var
, struct isl_tab_var
*skip_var
,
688 int sgn
, int *row
, int *col
)
695 isl_assert(tab
->mat
->ctx
, var
->is_row
, return);
696 tr
= tab
->mat
->row
[var
->index
] + 2 + tab
->M
;
699 for (j
= tab
->n_dead
; j
< tab
->n_col
; ++j
) {
700 if (isl_int_is_zero(tr
[j
]))
702 if (isl_int_sgn(tr
[j
]) != sgn
&&
703 var_from_col(tab
, j
)->is_nonneg
)
705 if (c
< 0 || tab
->col_var
[j
] < tab
->col_var
[c
])
711 sgn
*= isl_int_sgn(tr
[c
]);
712 r
= pivot_row(tab
, skip_var
, sgn
, c
);
713 *row
= r
< 0 ? var
->index
: r
;
717 /* Return 1 if row "row" represents an obviously redundant inequality.
719 * - it represents an inequality or a variable
720 * - that is the sum of a non-negative sample value and a positive
721 * combination of zero or more non-negative constraints.
723 int isl_tab_row_is_redundant(struct isl_tab
*tab
, int row
)
726 unsigned off
= 2 + tab
->M
;
728 if (tab
->row_var
[row
] < 0 && !isl_tab_var_from_row(tab
, row
)->is_nonneg
)
731 if (isl_int_is_neg(tab
->mat
->row
[row
][1]))
733 if (tab
->strict_redundant
&& isl_int_is_zero(tab
->mat
->row
[row
][1]))
735 if (tab
->M
&& isl_int_is_neg(tab
->mat
->row
[row
][2]))
738 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
739 if (isl_int_is_zero(tab
->mat
->row
[row
][off
+ i
]))
741 if (tab
->col_var
[i
] >= 0)
743 if (isl_int_is_neg(tab
->mat
->row
[row
][off
+ i
]))
745 if (!var_from_col(tab
, i
)->is_nonneg
)
751 static void swap_rows(struct isl_tab
*tab
, int row1
, int row2
)
754 enum isl_tab_row_sign s
;
756 t
= tab
->row_var
[row1
];
757 tab
->row_var
[row1
] = tab
->row_var
[row2
];
758 tab
->row_var
[row2
] = t
;
759 isl_tab_var_from_row(tab
, row1
)->index
= row1
;
760 isl_tab_var_from_row(tab
, row2
)->index
= row2
;
761 tab
->mat
= isl_mat_swap_rows(tab
->mat
, row1
, row2
);
765 s
= tab
->row_sign
[row1
];
766 tab
->row_sign
[row1
] = tab
->row_sign
[row2
];
767 tab
->row_sign
[row2
] = s
;
770 static int push_union(struct isl_tab
*tab
,
771 enum isl_tab_undo_type type
, union isl_tab_undo_val u
) WARN_UNUSED
;
772 static int push_union(struct isl_tab
*tab
,
773 enum isl_tab_undo_type type
, union isl_tab_undo_val u
)
775 struct isl_tab_undo
*undo
;
780 undo
= isl_alloc_type(tab
->mat
->ctx
, struct isl_tab_undo
);
785 undo
->next
= tab
->top
;
791 int isl_tab_push_var(struct isl_tab
*tab
,
792 enum isl_tab_undo_type type
, struct isl_tab_var
*var
)
794 union isl_tab_undo_val u
;
796 u
.var_index
= tab
->row_var
[var
->index
];
798 u
.var_index
= tab
->col_var
[var
->index
];
799 return push_union(tab
, type
, u
);
802 int isl_tab_push(struct isl_tab
*tab
, enum isl_tab_undo_type type
)
804 union isl_tab_undo_val u
= { 0 };
805 return push_union(tab
, type
, u
);
808 /* Push a record on the undo stack describing the current basic
809 * variables, so that the this state can be restored during rollback.
811 int isl_tab_push_basis(struct isl_tab
*tab
)
814 union isl_tab_undo_val u
;
816 u
.col_var
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->n_col
);
819 for (i
= 0; i
< tab
->n_col
; ++i
)
820 u
.col_var
[i
] = tab
->col_var
[i
];
821 return push_union(tab
, isl_tab_undo_saved_basis
, u
);
824 int isl_tab_push_callback(struct isl_tab
*tab
, struct isl_tab_callback
*callback
)
826 union isl_tab_undo_val u
;
827 u
.callback
= callback
;
828 return push_union(tab
, isl_tab_undo_callback
, u
);
831 struct isl_tab
*isl_tab_init_samples(struct isl_tab
*tab
)
838 tab
->samples
= isl_mat_alloc(tab
->mat
->ctx
, 1, 1 + tab
->n_var
);
841 tab
->sample_index
= isl_alloc_array(tab
->mat
->ctx
, int, 1);
842 if (!tab
->sample_index
)
850 struct isl_tab
*isl_tab_add_sample(struct isl_tab
*tab
,
851 __isl_take isl_vec
*sample
)
856 if (tab
->n_sample
+ 1 > tab
->samples
->n_row
) {
857 int *t
= isl_realloc_array(tab
->mat
->ctx
,
858 tab
->sample_index
, int, tab
->n_sample
+ 1);
861 tab
->sample_index
= t
;
864 tab
->samples
= isl_mat_extend(tab
->samples
,
865 tab
->n_sample
+ 1, tab
->samples
->n_col
);
869 isl_seq_cpy(tab
->samples
->row
[tab
->n_sample
], sample
->el
, sample
->size
);
870 isl_vec_free(sample
);
871 tab
->sample_index
[tab
->n_sample
] = tab
->n_sample
;
876 isl_vec_free(sample
);
881 struct isl_tab
*isl_tab_drop_sample(struct isl_tab
*tab
, int s
)
883 if (s
!= tab
->n_outside
) {
884 int t
= tab
->sample_index
[tab
->n_outside
];
885 tab
->sample_index
[tab
->n_outside
] = tab
->sample_index
[s
];
886 tab
->sample_index
[s
] = t
;
887 isl_mat_swap_rows(tab
->samples
, tab
->n_outside
, s
);
890 if (isl_tab_push(tab
, isl_tab_undo_drop_sample
) < 0) {
898 /* Record the current number of samples so that we can remove newer
899 * samples during a rollback.
901 int isl_tab_save_samples(struct isl_tab
*tab
)
903 union isl_tab_undo_val u
;
909 return push_union(tab
, isl_tab_undo_saved_samples
, u
);
912 /* Mark row with index "row" as being redundant.
913 * If we may need to undo the operation or if the row represents
914 * a variable of the original problem, the row is kept,
915 * but no longer considered when looking for a pivot row.
916 * Otherwise, the row is simply removed.
918 * The row may be interchanged with some other row. If it
919 * is interchanged with a later row, return 1. Otherwise return 0.
920 * If the rows are checked in order in the calling function,
921 * then a return value of 1 means that the row with the given
922 * row number may now contain a different row that hasn't been checked yet.
924 int isl_tab_mark_redundant(struct isl_tab
*tab
, int row
)
926 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, row
);
927 var
->is_redundant
= 1;
928 isl_assert(tab
->mat
->ctx
, row
>= tab
->n_redundant
, return -1);
929 if (tab
->need_undo
|| tab
->row_var
[row
] >= 0) {
930 if (tab
->row_var
[row
] >= 0 && !var
->is_nonneg
) {
932 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, var
) < 0)
935 if (row
!= tab
->n_redundant
)
936 swap_rows(tab
, row
, tab
->n_redundant
);
938 return isl_tab_push_var(tab
, isl_tab_undo_redundant
, var
);
940 if (row
!= tab
->n_row
- 1)
941 swap_rows(tab
, row
, tab
->n_row
- 1);
942 isl_tab_var_from_row(tab
, tab
->n_row
- 1)->index
= -1;
948 int isl_tab_mark_empty(struct isl_tab
*tab
)
952 if (!tab
->empty
&& tab
->need_undo
)
953 if (isl_tab_push(tab
, isl_tab_undo_empty
) < 0)
959 int isl_tab_freeze_constraint(struct isl_tab
*tab
, int con
)
961 struct isl_tab_var
*var
;
966 var
= &tab
->con
[con
];
974 return isl_tab_push_var(tab
, isl_tab_undo_freeze
, var
);
979 /* Update the rows signs after a pivot of "row" and "col", with "row_sgn"
980 * the original sign of the pivot element.
981 * We only keep track of row signs during PILP solving and in this case
982 * we only pivot a row with negative sign (meaning the value is always
983 * non-positive) using a positive pivot element.
985 * For each row j, the new value of the parametric constant is equal to
987 * a_j0 - a_jc a_r0/a_rc
989 * where a_j0 is the original parametric constant, a_rc is the pivot element,
990 * a_r0 is the parametric constant of the pivot row and a_jc is the
991 * pivot column entry of the row j.
992 * Since a_r0 is non-positive and a_rc is positive, the sign of row j
993 * remains the same if a_jc has the same sign as the row j or if
994 * a_jc is zero. In all other cases, we reset the sign to "unknown".
996 static void update_row_sign(struct isl_tab
*tab
, int row
, int col
, int row_sgn
)
999 struct isl_mat
*mat
= tab
->mat
;
1000 unsigned off
= 2 + tab
->M
;
1005 if (tab
->row_sign
[row
] == 0)
1007 isl_assert(mat
->ctx
, row_sgn
> 0, return);
1008 isl_assert(mat
->ctx
, tab
->row_sign
[row
] == isl_tab_row_neg
, return);
1009 tab
->row_sign
[row
] = isl_tab_row_pos
;
1010 for (i
= 0; i
< tab
->n_row
; ++i
) {
1014 s
= isl_int_sgn(mat
->row
[i
][off
+ col
]);
1017 if (!tab
->row_sign
[i
])
1019 if (s
< 0 && tab
->row_sign
[i
] == isl_tab_row_neg
)
1021 if (s
> 0 && tab
->row_sign
[i
] == isl_tab_row_pos
)
1023 tab
->row_sign
[i
] = isl_tab_row_unknown
;
1027 /* Given a row number "row" and a column number "col", pivot the tableau
1028 * such that the associated variables are interchanged.
1029 * The given row in the tableau expresses
1031 * x_r = a_r0 + \sum_i a_ri x_i
1035 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
1037 * Substituting this equality into the other rows
1039 * x_j = a_j0 + \sum_i a_ji x_i
1041 * with a_jc \ne 0, we obtain
1043 * 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
1050 * where i is any other column and j is any other row,
1051 * is therefore transformed into
1053 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1054 * 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)
1056 * The transformation is performed along the following steps
1058 * d_r/n_rc n_ri/n_rc
1061 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1064 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1065 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
1067 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1068 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
1070 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1071 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1073 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1074 * 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)
1077 int isl_tab_pivot(struct isl_tab
*tab
, int row
, int col
)
1082 struct isl_mat
*mat
= tab
->mat
;
1083 struct isl_tab_var
*var
;
1084 unsigned off
= 2 + tab
->M
;
1086 isl_int_swap(mat
->row
[row
][0], mat
->row
[row
][off
+ col
]);
1087 sgn
= isl_int_sgn(mat
->row
[row
][0]);
1089 isl_int_neg(mat
->row
[row
][0], mat
->row
[row
][0]);
1090 isl_int_neg(mat
->row
[row
][off
+ col
], mat
->row
[row
][off
+ col
]);
1092 for (j
= 0; j
< off
- 1 + tab
->n_col
; ++j
) {
1093 if (j
== off
- 1 + col
)
1095 isl_int_neg(mat
->row
[row
][1 + j
], mat
->row
[row
][1 + j
]);
1097 if (!isl_int_is_one(mat
->row
[row
][0]))
1098 isl_seq_normalize(mat
->ctx
, mat
->row
[row
], off
+ tab
->n_col
);
1099 for (i
= 0; i
< tab
->n_row
; ++i
) {
1102 if (isl_int_is_zero(mat
->row
[i
][off
+ col
]))
1104 isl_int_mul(mat
->row
[i
][0], mat
->row
[i
][0], mat
->row
[row
][0]);
1105 for (j
= 0; j
< off
- 1 + tab
->n_col
; ++j
) {
1106 if (j
== off
- 1 + col
)
1108 isl_int_mul(mat
->row
[i
][1 + j
],
1109 mat
->row
[i
][1 + j
], mat
->row
[row
][0]);
1110 isl_int_addmul(mat
->row
[i
][1 + j
],
1111 mat
->row
[i
][off
+ col
], mat
->row
[row
][1 + j
]);
1113 isl_int_mul(mat
->row
[i
][off
+ col
],
1114 mat
->row
[i
][off
+ col
], mat
->row
[row
][off
+ col
]);
1115 if (!isl_int_is_one(mat
->row
[i
][0]))
1116 isl_seq_normalize(mat
->ctx
, mat
->row
[i
], off
+ tab
->n_col
);
1118 t
= tab
->row_var
[row
];
1119 tab
->row_var
[row
] = tab
->col_var
[col
];
1120 tab
->col_var
[col
] = t
;
1121 var
= isl_tab_var_from_row(tab
, row
);
1124 var
= var_from_col(tab
, col
);
1127 update_row_sign(tab
, row
, col
, sgn
);
1130 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
1131 if (isl_int_is_zero(mat
->row
[i
][off
+ col
]))
1133 if (!isl_tab_var_from_row(tab
, i
)->frozen
&&
1134 isl_tab_row_is_redundant(tab
, i
)) {
1135 int redo
= isl_tab_mark_redundant(tab
, i
);
1145 /* If "var" represents a column variable, then pivot is up (sgn > 0)
1146 * or down (sgn < 0) to a row. The variable is assumed not to be
1147 * unbounded in the specified direction.
1148 * If sgn = 0, then the variable is unbounded in both directions,
1149 * and we pivot with any row we can find.
1151 static int to_row(struct isl_tab
*tab
, struct isl_tab_var
*var
, int sign
) WARN_UNUSED
;
1152 static int to_row(struct isl_tab
*tab
, struct isl_tab_var
*var
, int sign
)
1155 unsigned off
= 2 + tab
->M
;
1161 for (r
= tab
->n_redundant
; r
< tab
->n_row
; ++r
)
1162 if (!isl_int_is_zero(tab
->mat
->row
[r
][off
+var
->index
]))
1164 isl_assert(tab
->mat
->ctx
, r
< tab
->n_row
, return -1);
1166 r
= pivot_row(tab
, NULL
, sign
, var
->index
);
1167 isl_assert(tab
->mat
->ctx
, r
>= 0, return -1);
1170 return isl_tab_pivot(tab
, r
, var
->index
);
1173 static void check_table(struct isl_tab
*tab
)
1179 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
1180 struct isl_tab_var
*var
;
1181 var
= isl_tab_var_from_row(tab
, i
);
1182 if (!var
->is_nonneg
)
1185 isl_assert(tab
->mat
->ctx
,
1186 !isl_int_is_neg(tab
->mat
->row
[i
][2]), abort());
1187 if (isl_int_is_pos(tab
->mat
->row
[i
][2]))
1190 isl_assert(tab
->mat
->ctx
, !isl_int_is_neg(tab
->mat
->row
[i
][1]),
1195 /* Return the sign of the maximal value of "var".
1196 * If the sign is not negative, then on return from this function,
1197 * the sample value will also be non-negative.
1199 * If "var" is manifestly unbounded wrt positive values, we are done.
1200 * Otherwise, we pivot the variable up to a row if needed
1201 * Then we continue pivoting down until either
1202 * - no more down pivots can be performed
1203 * - the sample value is positive
1204 * - the variable is pivoted into a manifestly unbounded column
1206 static int sign_of_max(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1210 if (max_is_manifestly_unbounded(tab
, var
))
1212 if (to_row(tab
, var
, 1) < 0)
1214 while (!isl_int_is_pos(tab
->mat
->row
[var
->index
][1])) {
1215 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1217 return isl_int_sgn(tab
->mat
->row
[var
->index
][1]);
1218 if (isl_tab_pivot(tab
, row
, col
) < 0)
1220 if (!var
->is_row
) /* manifestly unbounded */
1226 int isl_tab_sign_of_max(struct isl_tab
*tab
, int con
)
1228 struct isl_tab_var
*var
;
1233 var
= &tab
->con
[con
];
1234 isl_assert(tab
->mat
->ctx
, !var
->is_redundant
, return -2);
1235 isl_assert(tab
->mat
->ctx
, !var
->is_zero
, return -2);
1237 return sign_of_max(tab
, var
);
1240 static int row_is_neg(struct isl_tab
*tab
, int row
)
1243 return isl_int_is_neg(tab
->mat
->row
[row
][1]);
1244 if (isl_int_is_pos(tab
->mat
->row
[row
][2]))
1246 if (isl_int_is_neg(tab
->mat
->row
[row
][2]))
1248 return isl_int_is_neg(tab
->mat
->row
[row
][1]);
1251 static int row_sgn(struct isl_tab
*tab
, int row
)
1254 return isl_int_sgn(tab
->mat
->row
[row
][1]);
1255 if (!isl_int_is_zero(tab
->mat
->row
[row
][2]))
1256 return isl_int_sgn(tab
->mat
->row
[row
][2]);
1258 return isl_int_sgn(tab
->mat
->row
[row
][1]);
1261 /* Perform pivots until the row variable "var" has a non-negative
1262 * sample value or until no more upward pivots can be performed.
1263 * Return the sign of the sample value after the pivots have been
1266 static int restore_row(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1270 while (row_is_neg(tab
, var
->index
)) {
1271 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1274 if (isl_tab_pivot(tab
, row
, col
) < 0)
1276 if (!var
->is_row
) /* manifestly unbounded */
1279 return row_sgn(tab
, var
->index
);
1282 /* Perform pivots until we are sure that the row variable "var"
1283 * can attain non-negative values. After return from this
1284 * function, "var" is still a row variable, but its sample
1285 * value may not be non-negative, even if the function returns 1.
1287 static int at_least_zero(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1291 while (isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1292 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1295 if (row
== var
->index
) /* manifestly unbounded */
1297 if (isl_tab_pivot(tab
, row
, col
) < 0)
1300 return !isl_int_is_neg(tab
->mat
->row
[var
->index
][1]);
1303 /* Return a negative value if "var" can attain negative values.
1304 * Return a non-negative value otherwise.
1306 * If "var" is manifestly unbounded wrt negative values, we are done.
1307 * Otherwise, if var is in a column, we can pivot it down to a row.
1308 * Then we continue pivoting down until either
1309 * - the pivot would result in a manifestly unbounded column
1310 * => we don't perform the pivot, but simply return -1
1311 * - no more down pivots can be performed
1312 * - the sample value is negative
1313 * If the sample value becomes negative and the variable is supposed
1314 * to be nonnegative, then we undo the last pivot.
1315 * However, if the last pivot has made the pivoting variable
1316 * obviously redundant, then it may have moved to another row.
1317 * In that case we look for upward pivots until we reach a non-negative
1320 static int sign_of_min(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1323 struct isl_tab_var
*pivot_var
= NULL
;
1325 if (min_is_manifestly_unbounded(tab
, var
))
1329 row
= pivot_row(tab
, NULL
, -1, col
);
1330 pivot_var
= var_from_col(tab
, col
);
1331 if (isl_tab_pivot(tab
, row
, col
) < 0)
1333 if (var
->is_redundant
)
1335 if (isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1336 if (var
->is_nonneg
) {
1337 if (!pivot_var
->is_redundant
&&
1338 pivot_var
->index
== row
) {
1339 if (isl_tab_pivot(tab
, row
, col
) < 0)
1342 if (restore_row(tab
, var
) < -1)
1348 if (var
->is_redundant
)
1350 while (!isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1351 find_pivot(tab
, var
, var
, -1, &row
, &col
);
1352 if (row
== var
->index
)
1355 return isl_int_sgn(tab
->mat
->row
[var
->index
][1]);
1356 pivot_var
= var_from_col(tab
, col
);
1357 if (isl_tab_pivot(tab
, row
, col
) < 0)
1359 if (var
->is_redundant
)
1362 if (pivot_var
&& var
->is_nonneg
) {
1363 /* pivot back to non-negative value */
1364 if (!pivot_var
->is_redundant
&& pivot_var
->index
== row
) {
1365 if (isl_tab_pivot(tab
, row
, col
) < 0)
1368 if (restore_row(tab
, var
) < -1)
1374 static int row_at_most_neg_one(struct isl_tab
*tab
, int row
)
1377 if (isl_int_is_pos(tab
->mat
->row
[row
][2]))
1379 if (isl_int_is_neg(tab
->mat
->row
[row
][2]))
1382 return isl_int_is_neg(tab
->mat
->row
[row
][1]) &&
1383 isl_int_abs_ge(tab
->mat
->row
[row
][1],
1384 tab
->mat
->row
[row
][0]);
1387 /* Return 1 if "var" can attain values <= -1.
1388 * Return 0 otherwise.
1390 * The sample value of "var" is assumed to be non-negative when the
1391 * the function is called. If 1 is returned then the constraint
1392 * is not redundant and the sample value is made non-negative again before
1393 * the function returns.
1395 int isl_tab_min_at_most_neg_one(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1398 struct isl_tab_var
*pivot_var
;
1400 if (min_is_manifestly_unbounded(tab
, var
))
1404 row
= pivot_row(tab
, NULL
, -1, col
);
1405 pivot_var
= var_from_col(tab
, col
);
1406 if (isl_tab_pivot(tab
, row
, col
) < 0)
1408 if (var
->is_redundant
)
1410 if (row_at_most_neg_one(tab
, var
->index
)) {
1411 if (var
->is_nonneg
) {
1412 if (!pivot_var
->is_redundant
&&
1413 pivot_var
->index
== row
) {
1414 if (isl_tab_pivot(tab
, row
, col
) < 0)
1417 if (restore_row(tab
, var
) < -1)
1423 if (var
->is_redundant
)
1426 find_pivot(tab
, var
, var
, -1, &row
, &col
);
1427 if (row
== var
->index
) {
1428 if (restore_row(tab
, var
) < -1)
1434 pivot_var
= var_from_col(tab
, col
);
1435 if (isl_tab_pivot(tab
, row
, col
) < 0)
1437 if (var
->is_redundant
)
1439 } while (!row_at_most_neg_one(tab
, var
->index
));
1440 if (var
->is_nonneg
) {
1441 /* pivot back to non-negative value */
1442 if (!pivot_var
->is_redundant
&& pivot_var
->index
== row
)
1443 if (isl_tab_pivot(tab
, row
, col
) < 0)
1445 if (restore_row(tab
, var
) < -1)
1451 /* Return 1 if "var" can attain values >= 1.
1452 * Return 0 otherwise.
1454 static int at_least_one(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1459 if (max_is_manifestly_unbounded(tab
, var
))
1461 if (to_row(tab
, var
, 1) < 0)
1463 r
= tab
->mat
->row
[var
->index
];
1464 while (isl_int_lt(r
[1], r
[0])) {
1465 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1467 return isl_int_ge(r
[1], r
[0]);
1468 if (row
== var
->index
) /* manifestly unbounded */
1470 if (isl_tab_pivot(tab
, row
, col
) < 0)
1476 static void swap_cols(struct isl_tab
*tab
, int col1
, int col2
)
1479 unsigned off
= 2 + tab
->M
;
1480 t
= tab
->col_var
[col1
];
1481 tab
->col_var
[col1
] = tab
->col_var
[col2
];
1482 tab
->col_var
[col2
] = t
;
1483 var_from_col(tab
, col1
)->index
= col1
;
1484 var_from_col(tab
, col2
)->index
= col2
;
1485 tab
->mat
= isl_mat_swap_cols(tab
->mat
, off
+ col1
, off
+ col2
);
1488 /* Mark column with index "col" as representing a zero variable.
1489 * If we may need to undo the operation the column is kept,
1490 * but no longer considered.
1491 * Otherwise, the column is simply removed.
1493 * The column may be interchanged with some other column. If it
1494 * is interchanged with a later column, return 1. Otherwise return 0.
1495 * If the columns are checked in order in the calling function,
1496 * then a return value of 1 means that the column with the given
1497 * column number may now contain a different column that
1498 * hasn't been checked yet.
1500 int isl_tab_kill_col(struct isl_tab
*tab
, int col
)
1502 var_from_col(tab
, col
)->is_zero
= 1;
1503 if (tab
->need_undo
) {
1504 if (isl_tab_push_var(tab
, isl_tab_undo_zero
,
1505 var_from_col(tab
, col
)) < 0)
1507 if (col
!= tab
->n_dead
)
1508 swap_cols(tab
, col
, tab
->n_dead
);
1512 if (col
!= tab
->n_col
- 1)
1513 swap_cols(tab
, col
, tab
->n_col
- 1);
1514 var_from_col(tab
, tab
->n_col
- 1)->index
= -1;
1520 /* Row variable "var" is non-negative and cannot attain any values
1521 * larger than zero. This means that the coefficients of the unrestricted
1522 * column variables are zero and that the coefficients of the non-negative
1523 * column variables are zero or negative.
1524 * Each of the non-negative variables with a negative coefficient can
1525 * then also be written as the negative sum of non-negative variables
1526 * and must therefore also be zero.
1528 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1529 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1532 struct isl_mat
*mat
= tab
->mat
;
1533 unsigned off
= 2 + tab
->M
;
1535 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, return -1);
1538 if (isl_tab_push_var(tab
, isl_tab_undo_zero
, var
) < 0)
1540 for (j
= tab
->n_dead
; j
< tab
->n_col
; ++j
) {
1542 if (isl_int_is_zero(mat
->row
[var
->index
][off
+ j
]))
1544 isl_assert(tab
->mat
->ctx
,
1545 isl_int_is_neg(mat
->row
[var
->index
][off
+ j
]), return -1);
1546 recheck
= isl_tab_kill_col(tab
, j
);
1552 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
1557 /* Add a constraint to the tableau and allocate a row for it.
1558 * Return the index into the constraint array "con".
1560 int isl_tab_allocate_con(struct isl_tab
*tab
)
1564 isl_assert(tab
->mat
->ctx
, tab
->n_row
< tab
->mat
->n_row
, return -1);
1565 isl_assert(tab
->mat
->ctx
, tab
->n_con
< tab
->max_con
, return -1);
1568 tab
->con
[r
].index
= tab
->n_row
;
1569 tab
->con
[r
].is_row
= 1;
1570 tab
->con
[r
].is_nonneg
= 0;
1571 tab
->con
[r
].is_zero
= 0;
1572 tab
->con
[r
].is_redundant
= 0;
1573 tab
->con
[r
].frozen
= 0;
1574 tab
->con
[r
].negated
= 0;
1575 tab
->row_var
[tab
->n_row
] = ~r
;
1579 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
1585 /* Add a variable to the tableau and allocate a column for it.
1586 * Return the index into the variable array "var".
1588 int isl_tab_allocate_var(struct isl_tab
*tab
)
1592 unsigned off
= 2 + tab
->M
;
1594 isl_assert(tab
->mat
->ctx
, tab
->n_col
< tab
->mat
->n_col
, return -1);
1595 isl_assert(tab
->mat
->ctx
, tab
->n_var
< tab
->max_var
, return -1);
1598 tab
->var
[r
].index
= tab
->n_col
;
1599 tab
->var
[r
].is_row
= 0;
1600 tab
->var
[r
].is_nonneg
= 0;
1601 tab
->var
[r
].is_zero
= 0;
1602 tab
->var
[r
].is_redundant
= 0;
1603 tab
->var
[r
].frozen
= 0;
1604 tab
->var
[r
].negated
= 0;
1605 tab
->col_var
[tab
->n_col
] = r
;
1607 for (i
= 0; i
< tab
->n_row
; ++i
)
1608 isl_int_set_si(tab
->mat
->row
[i
][off
+ tab
->n_col
], 0);
1612 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->var
[r
]) < 0)
1618 /* Add a row to the tableau. The row is given as an affine combination
1619 * of the original variables and needs to be expressed in terms of the
1622 * We add each term in turn.
1623 * If r = n/d_r is the current sum and we need to add k x, then
1624 * if x is a column variable, we increase the numerator of
1625 * this column by k d_r
1626 * if x = f/d_x is a row variable, then the new representation of r is
1628 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1629 * --- + --- = ------------------- = -------------------
1630 * d_r d_r d_r d_x/g m
1632 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1634 int isl_tab_add_row(struct isl_tab
*tab
, isl_int
*line
)
1640 unsigned off
= 2 + tab
->M
;
1642 r
= isl_tab_allocate_con(tab
);
1648 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1649 isl_int_set_si(row
[0], 1);
1650 isl_int_set(row
[1], line
[0]);
1651 isl_seq_clr(row
+ 2, tab
->M
+ tab
->n_col
);
1652 for (i
= 0; i
< tab
->n_var
; ++i
) {
1653 if (tab
->var
[i
].is_zero
)
1655 if (tab
->var
[i
].is_row
) {
1657 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1658 isl_int_swap(a
, row
[0]);
1659 isl_int_divexact(a
, row
[0], a
);
1661 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1662 isl_int_mul(b
, b
, line
[1 + i
]);
1663 isl_seq_combine(row
+ 1, a
, row
+ 1,
1664 b
, tab
->mat
->row
[tab
->var
[i
].index
] + 1,
1665 1 + tab
->M
+ tab
->n_col
);
1667 isl_int_addmul(row
[off
+ tab
->var
[i
].index
],
1668 line
[1 + i
], row
[0]);
1669 if (tab
->M
&& i
>= tab
->n_param
&& i
< tab
->n_var
- tab
->n_div
)
1670 isl_int_submul(row
[2], line
[1 + i
], row
[0]);
1672 isl_seq_normalize(tab
->mat
->ctx
, row
, off
+ tab
->n_col
);
1677 tab
->row_sign
[tab
->con
[r
].index
] = isl_tab_row_unknown
;
1682 static int drop_row(struct isl_tab
*tab
, int row
)
1684 isl_assert(tab
->mat
->ctx
, ~tab
->row_var
[row
] == tab
->n_con
- 1, return -1);
1685 if (row
!= tab
->n_row
- 1)
1686 swap_rows(tab
, row
, tab
->n_row
- 1);
1692 static int drop_col(struct isl_tab
*tab
, int col
)
1694 isl_assert(tab
->mat
->ctx
, tab
->col_var
[col
] == tab
->n_var
- 1, return -1);
1695 if (col
!= tab
->n_col
- 1)
1696 swap_cols(tab
, col
, tab
->n_col
- 1);
1702 /* Add inequality "ineq" and check if it conflicts with the
1703 * previously added constraints or if it is obviously redundant.
1705 int isl_tab_add_ineq(struct isl_tab
*tab
, isl_int
*ineq
)
1714 struct isl_basic_map
*bmap
= tab
->bmap
;
1716 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
1717 isl_assert(tab
->mat
->ctx
,
1718 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
1719 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, ineq
);
1720 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1727 isl_int_swap(ineq
[0], cst
);
1729 r
= isl_tab_add_row(tab
, ineq
);
1731 isl_int_swap(ineq
[0], cst
);
1736 tab
->con
[r
].is_nonneg
= 1;
1737 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
1739 if (isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
)) {
1740 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1745 sgn
= restore_row(tab
, &tab
->con
[r
]);
1749 return isl_tab_mark_empty(tab
);
1750 if (tab
->con
[r
].is_row
&& isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
))
1751 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1756 /* Pivot a non-negative variable down until it reaches the value zero
1757 * and then pivot the variable into a column position.
1759 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1760 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1764 unsigned off
= 2 + tab
->M
;
1769 while (isl_int_is_pos(tab
->mat
->row
[var
->index
][1])) {
1770 find_pivot(tab
, var
, NULL
, -1, &row
, &col
);
1771 isl_assert(tab
->mat
->ctx
, row
!= -1, return -1);
1772 if (isl_tab_pivot(tab
, row
, col
) < 0)
1778 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
)
1779 if (!isl_int_is_zero(tab
->mat
->row
[var
->index
][off
+ i
]))
1782 isl_assert(tab
->mat
->ctx
, i
< tab
->n_col
, return -1);
1783 if (isl_tab_pivot(tab
, var
->index
, i
) < 0)
1789 /* We assume Gaussian elimination has been performed on the equalities.
1790 * The equalities can therefore never conflict.
1791 * Adding the equalities is currently only really useful for a later call
1792 * to isl_tab_ineq_type.
1794 static struct isl_tab
*add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1801 r
= isl_tab_add_row(tab
, eq
);
1805 r
= tab
->con
[r
].index
;
1806 i
= isl_seq_first_non_zero(tab
->mat
->row
[r
] + 2 + tab
->M
+ tab
->n_dead
,
1807 tab
->n_col
- tab
->n_dead
);
1808 isl_assert(tab
->mat
->ctx
, i
>= 0, goto error
);
1810 if (isl_tab_pivot(tab
, r
, i
) < 0)
1812 if (isl_tab_kill_col(tab
, i
) < 0)
1822 static int row_is_manifestly_zero(struct isl_tab
*tab
, int row
)
1824 unsigned off
= 2 + tab
->M
;
1826 if (!isl_int_is_zero(tab
->mat
->row
[row
][1]))
1828 if (tab
->M
&& !isl_int_is_zero(tab
->mat
->row
[row
][2]))
1830 return isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
1831 tab
->n_col
- tab
->n_dead
) == -1;
1834 /* Add an equality that is known to be valid for the given tableau.
1836 int isl_tab_add_valid_eq(struct isl_tab
*tab
, isl_int
*eq
)
1838 struct isl_tab_var
*var
;
1843 r
= isl_tab_add_row(tab
, eq
);
1849 if (row_is_manifestly_zero(tab
, r
)) {
1851 if (isl_tab_mark_redundant(tab
, r
) < 0)
1856 if (isl_int_is_neg(tab
->mat
->row
[r
][1])) {
1857 isl_seq_neg(tab
->mat
->row
[r
] + 1, tab
->mat
->row
[r
] + 1,
1862 if (to_col(tab
, var
) < 0)
1865 if (isl_tab_kill_col(tab
, var
->index
) < 0)
1871 static int add_zero_row(struct isl_tab
*tab
)
1876 r
= isl_tab_allocate_con(tab
);
1880 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1881 isl_seq_clr(row
+ 1, 1 + tab
->M
+ tab
->n_col
);
1882 isl_int_set_si(row
[0], 1);
1887 /* Add equality "eq" and check if it conflicts with the
1888 * previously added constraints or if it is obviously redundant.
1890 int isl_tab_add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1892 struct isl_tab_undo
*snap
= NULL
;
1893 struct isl_tab_var
*var
;
1901 isl_assert(tab
->mat
->ctx
, !tab
->M
, return -1);
1904 snap
= isl_tab_snap(tab
);
1908 isl_int_swap(eq
[0], cst
);
1910 r
= isl_tab_add_row(tab
, eq
);
1912 isl_int_swap(eq
[0], cst
);
1920 if (row_is_manifestly_zero(tab
, row
)) {
1922 if (isl_tab_rollback(tab
, snap
) < 0)
1930 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1931 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1933 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1934 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1935 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1936 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1940 if (add_zero_row(tab
) < 0)
1944 sgn
= isl_int_sgn(tab
->mat
->row
[row
][1]);
1947 isl_seq_neg(tab
->mat
->row
[row
] + 1, tab
->mat
->row
[row
] + 1,
1954 sgn
= sign_of_max(tab
, var
);
1958 if (isl_tab_mark_empty(tab
) < 0)
1965 if (to_col(tab
, var
) < 0)
1968 if (isl_tab_kill_col(tab
, var
->index
) < 0)
1974 /* Construct and return an inequality that expresses an upper bound
1976 * In particular, if the div is given by
1980 * then the inequality expresses
1984 static struct isl_vec
*ineq_for_div(struct isl_basic_map
*bmap
, unsigned div
)
1988 struct isl_vec
*ineq
;
1993 total
= isl_basic_map_total_dim(bmap
);
1994 div_pos
= 1 + total
- bmap
->n_div
+ div
;
1996 ineq
= isl_vec_alloc(bmap
->ctx
, 1 + total
);
2000 isl_seq_cpy(ineq
->el
, bmap
->div
[div
] + 1, 1 + total
);
2001 isl_int_neg(ineq
->el
[div_pos
], bmap
->div
[div
][0]);
2005 /* For a div d = floor(f/m), add the constraints
2008 * -(f-(m-1)) + m d >= 0
2010 * Note that the second constraint is the negation of
2014 * If add_ineq is not NULL, then this function is used
2015 * instead of isl_tab_add_ineq to effectively add the inequalities.
2017 static int add_div_constraints(struct isl_tab
*tab
, unsigned div
,
2018 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
2022 struct isl_vec
*ineq
;
2024 total
= isl_basic_map_total_dim(tab
->bmap
);
2025 div_pos
= 1 + total
- tab
->bmap
->n_div
+ div
;
2027 ineq
= ineq_for_div(tab
->bmap
, div
);
2032 if (add_ineq(user
, ineq
->el
) < 0)
2035 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2039 isl_seq_neg(ineq
->el
, tab
->bmap
->div
[div
] + 1, 1 + total
);
2040 isl_int_set(ineq
->el
[div_pos
], tab
->bmap
->div
[div
][0]);
2041 isl_int_add(ineq
->el
[0], ineq
->el
[0], ineq
->el
[div_pos
]);
2042 isl_int_sub_ui(ineq
->el
[0], ineq
->el
[0], 1);
2045 if (add_ineq(user
, ineq
->el
) < 0)
2048 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2060 /* Add an extra div, prescrived by "div" to the tableau and
2061 * the associated bmap (which is assumed to be non-NULL).
2063 * If add_ineq is not NULL, then this function is used instead
2064 * of isl_tab_add_ineq to add the div constraints.
2065 * This complication is needed because the code in isl_tab_pip
2066 * wants to perform some extra processing when an inequality
2067 * is added to the tableau.
2069 int isl_tab_add_div(struct isl_tab
*tab
, __isl_keep isl_vec
*div
,
2070 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
2080 isl_assert(tab
->mat
->ctx
, tab
->bmap
, return -1);
2082 for (i
= 0; i
< tab
->n_var
; ++i
) {
2083 if (isl_int_is_neg(div
->el
[2 + i
]))
2085 if (isl_int_is_zero(div
->el
[2 + i
]))
2087 if (!tab
->var
[i
].is_nonneg
)
2090 nonneg
= i
== tab
->n_var
&& !isl_int_is_neg(div
->el
[1]);
2092 if (isl_tab_extend_cons(tab
, 3) < 0)
2094 if (isl_tab_extend_vars(tab
, 1) < 0)
2096 r
= isl_tab_allocate_var(tab
);
2101 tab
->var
[r
].is_nonneg
= 1;
2103 tab
->bmap
= isl_basic_map_extend_dim(tab
->bmap
,
2104 isl_basic_map_get_dim(tab
->bmap
), 1, 0, 2);
2105 k
= isl_basic_map_alloc_div(tab
->bmap
);
2108 isl_seq_cpy(tab
->bmap
->div
[k
], div
->el
, div
->size
);
2109 if (isl_tab_push(tab
, isl_tab_undo_bmap_div
) < 0)
2112 if (add_div_constraints(tab
, k
, add_ineq
, user
) < 0)
2118 struct isl_tab
*isl_tab_from_basic_map(struct isl_basic_map
*bmap
)
2121 struct isl_tab
*tab
;
2125 tab
= isl_tab_alloc(bmap
->ctx
,
2126 isl_basic_map_total_dim(bmap
) + bmap
->n_ineq
+ 1,
2127 isl_basic_map_total_dim(bmap
), 0);
2130 tab
->rational
= ISL_F_ISSET(bmap
, ISL_BASIC_MAP_RATIONAL
);
2131 if (ISL_F_ISSET(bmap
, ISL_BASIC_MAP_EMPTY
)) {
2132 if (isl_tab_mark_empty(tab
) < 0)
2136 for (i
= 0; i
< bmap
->n_eq
; ++i
) {
2137 tab
= add_eq(tab
, bmap
->eq
[i
]);
2141 for (i
= 0; i
< bmap
->n_ineq
; ++i
) {
2142 if (isl_tab_add_ineq(tab
, bmap
->ineq
[i
]) < 0)
2153 struct isl_tab
*isl_tab_from_basic_set(struct isl_basic_set
*bset
)
2155 return isl_tab_from_basic_map((struct isl_basic_map
*)bset
);
2158 /* Construct a tableau corresponding to the recession cone of "bset".
2160 struct isl_tab
*isl_tab_from_recession_cone(__isl_keep isl_basic_set
*bset
,
2165 struct isl_tab
*tab
;
2166 unsigned offset
= 0;
2171 offset
= isl_basic_set_dim(bset
, isl_dim_param
);
2172 tab
= isl_tab_alloc(bset
->ctx
, bset
->n_eq
+ bset
->n_ineq
,
2173 isl_basic_set_total_dim(bset
) - offset
, 0);
2176 tab
->rational
= ISL_F_ISSET(bset
, ISL_BASIC_SET_RATIONAL
);
2180 for (i
= 0; i
< bset
->n_eq
; ++i
) {
2181 isl_int_swap(bset
->eq
[i
][offset
], cst
);
2183 if (isl_tab_add_eq(tab
, bset
->eq
[i
] + offset
) < 0)
2186 tab
= add_eq(tab
, bset
->eq
[i
]);
2187 isl_int_swap(bset
->eq
[i
][offset
], cst
);
2191 for (i
= 0; i
< bset
->n_ineq
; ++i
) {
2193 isl_int_swap(bset
->ineq
[i
][offset
], cst
);
2194 r
= isl_tab_add_row(tab
, bset
->ineq
[i
] + offset
);
2195 isl_int_swap(bset
->ineq
[i
][offset
], cst
);
2198 tab
->con
[r
].is_nonneg
= 1;
2199 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2211 /* Assuming "tab" is the tableau of a cone, check if the cone is
2212 * bounded, i.e., if it is empty or only contains the origin.
2214 int isl_tab_cone_is_bounded(struct isl_tab
*tab
)
2222 if (tab
->n_dead
== tab
->n_col
)
2226 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2227 struct isl_tab_var
*var
;
2229 var
= isl_tab_var_from_row(tab
, i
);
2230 if (!var
->is_nonneg
)
2232 sgn
= sign_of_max(tab
, var
);
2237 if (close_row(tab
, var
) < 0)
2241 if (tab
->n_dead
== tab
->n_col
)
2243 if (i
== tab
->n_row
)
2248 int isl_tab_sample_is_integer(struct isl_tab
*tab
)
2255 for (i
= 0; i
< tab
->n_var
; ++i
) {
2257 if (!tab
->var
[i
].is_row
)
2259 row
= tab
->var
[i
].index
;
2260 if (!isl_int_is_divisible_by(tab
->mat
->row
[row
][1],
2261 tab
->mat
->row
[row
][0]))
2267 static struct isl_vec
*extract_integer_sample(struct isl_tab
*tab
)
2270 struct isl_vec
*vec
;
2272 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2276 isl_int_set_si(vec
->block
.data
[0], 1);
2277 for (i
= 0; i
< tab
->n_var
; ++i
) {
2278 if (!tab
->var
[i
].is_row
)
2279 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2281 int row
= tab
->var
[i
].index
;
2282 isl_int_divexact(vec
->block
.data
[1 + i
],
2283 tab
->mat
->row
[row
][1], tab
->mat
->row
[row
][0]);
2290 struct isl_vec
*isl_tab_get_sample_value(struct isl_tab
*tab
)
2293 struct isl_vec
*vec
;
2299 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2305 isl_int_set_si(vec
->block
.data
[0], 1);
2306 for (i
= 0; i
< tab
->n_var
; ++i
) {
2308 if (!tab
->var
[i
].is_row
) {
2309 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2312 row
= tab
->var
[i
].index
;
2313 isl_int_gcd(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2314 isl_int_divexact(m
, tab
->mat
->row
[row
][0], m
);
2315 isl_seq_scale(vec
->block
.data
, vec
->block
.data
, m
, 1 + i
);
2316 isl_int_divexact(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2317 isl_int_mul(vec
->block
.data
[1 + i
], m
, tab
->mat
->row
[row
][1]);
2319 vec
= isl_vec_normalize(vec
);
2325 /* Update "bmap" based on the results of the tableau "tab".
2326 * In particular, implicit equalities are made explicit, redundant constraints
2327 * are removed and if the sample value happens to be integer, it is stored
2328 * in "bmap" (unless "bmap" already had an integer sample).
2330 * The tableau is assumed to have been created from "bmap" using
2331 * isl_tab_from_basic_map.
2333 struct isl_basic_map
*isl_basic_map_update_from_tab(struct isl_basic_map
*bmap
,
2334 struct isl_tab
*tab
)
2346 bmap
= isl_basic_map_set_to_empty(bmap
);
2348 for (i
= bmap
->n_ineq
- 1; i
>= 0; --i
) {
2349 if (isl_tab_is_equality(tab
, n_eq
+ i
))
2350 isl_basic_map_inequality_to_equality(bmap
, i
);
2351 else if (isl_tab_is_redundant(tab
, n_eq
+ i
))
2352 isl_basic_map_drop_inequality(bmap
, i
);
2354 if (bmap
->n_eq
!= n_eq
)
2355 isl_basic_map_gauss(bmap
, NULL
);
2356 if (!tab
->rational
&&
2357 !bmap
->sample
&& isl_tab_sample_is_integer(tab
))
2358 bmap
->sample
= extract_integer_sample(tab
);
2362 struct isl_basic_set
*isl_basic_set_update_from_tab(struct isl_basic_set
*bset
,
2363 struct isl_tab
*tab
)
2365 return (struct isl_basic_set
*)isl_basic_map_update_from_tab(
2366 (struct isl_basic_map
*)bset
, tab
);
2369 /* Given a non-negative variable "var", add a new non-negative variable
2370 * that is the opposite of "var", ensuring that var can only attain the
2372 * If var = n/d is a row variable, then the new variable = -n/d.
2373 * If var is a column variables, then the new variable = -var.
2374 * If the new variable cannot attain non-negative values, then
2375 * the resulting tableau is empty.
2376 * Otherwise, we know the value will be zero and we close the row.
2378 static int cut_to_hyperplane(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2383 unsigned off
= 2 + tab
->M
;
2387 isl_assert(tab
->mat
->ctx
, !var
->is_redundant
, return -1);
2388 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, return -1);
2390 if (isl_tab_extend_cons(tab
, 1) < 0)
2394 tab
->con
[r
].index
= tab
->n_row
;
2395 tab
->con
[r
].is_row
= 1;
2396 tab
->con
[r
].is_nonneg
= 0;
2397 tab
->con
[r
].is_zero
= 0;
2398 tab
->con
[r
].is_redundant
= 0;
2399 tab
->con
[r
].frozen
= 0;
2400 tab
->con
[r
].negated
= 0;
2401 tab
->row_var
[tab
->n_row
] = ~r
;
2402 row
= tab
->mat
->row
[tab
->n_row
];
2405 isl_int_set(row
[0], tab
->mat
->row
[var
->index
][0]);
2406 isl_seq_neg(row
+ 1,
2407 tab
->mat
->row
[var
->index
] + 1, 1 + tab
->n_col
);
2409 isl_int_set_si(row
[0], 1);
2410 isl_seq_clr(row
+ 1, 1 + tab
->n_col
);
2411 isl_int_set_si(row
[off
+ var
->index
], -1);
2416 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
2419 sgn
= sign_of_max(tab
, &tab
->con
[r
]);
2423 if (isl_tab_mark_empty(tab
) < 0)
2427 tab
->con
[r
].is_nonneg
= 1;
2428 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2431 if (close_row(tab
, &tab
->con
[r
]) < 0)
2437 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2438 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2439 * by r' = r + 1 >= 0.
2440 * If r is a row variable, we simply increase the constant term by one
2441 * (taking into account the denominator).
2442 * If r is a column variable, then we need to modify each row that
2443 * refers to r = r' - 1 by substituting this equality, effectively
2444 * subtracting the coefficient of the column from the constant.
2445 * We should only do this if the minimum is manifestly unbounded,
2446 * however. Otherwise, we may end up with negative sample values
2447 * for non-negative variables.
2448 * So, if r is a column variable with a minimum that is not
2449 * manifestly unbounded, then we need to move it to a row.
2450 * However, the sample value of this row may be negative,
2451 * even after the relaxation, so we need to restore it.
2452 * We therefore prefer to pivot a column up to a row, if possible.
2454 struct isl_tab
*isl_tab_relax(struct isl_tab
*tab
, int con
)
2456 struct isl_tab_var
*var
;
2457 unsigned off
= 2 + tab
->M
;
2462 var
= &tab
->con
[con
];
2464 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2465 if (to_row(tab
, var
, 1) < 0)
2467 if (!var
->is_row
&& !min_is_manifestly_unbounded(tab
, var
))
2468 if (to_row(tab
, var
, -1) < 0)
2472 isl_int_add(tab
->mat
->row
[var
->index
][1],
2473 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2474 if (restore_row(tab
, var
) < 0)
2479 for (i
= 0; i
< tab
->n_row
; ++i
) {
2480 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2482 isl_int_sub(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2483 tab
->mat
->row
[i
][off
+ var
->index
]);
2488 if (isl_tab_push_var(tab
, isl_tab_undo_relax
, var
) < 0)
2497 int isl_tab_select_facet(struct isl_tab
*tab
, int con
)
2502 return cut_to_hyperplane(tab
, &tab
->con
[con
]);
2505 static int may_be_equality(struct isl_tab
*tab
, int row
)
2507 unsigned off
= 2 + tab
->M
;
2508 return tab
->rational
? isl_int_is_zero(tab
->mat
->row
[row
][1])
2509 : isl_int_lt(tab
->mat
->row
[row
][1],
2510 tab
->mat
->row
[row
][0]);
2513 /* Check for (near) equalities among the constraints.
2514 * A constraint is an equality if it is non-negative and if
2515 * its maximal value is either
2516 * - zero (in case of rational tableaus), or
2517 * - strictly less than 1 (in case of integer tableaus)
2519 * We first mark all non-redundant and non-dead variables that
2520 * are not frozen and not obviously not an equality.
2521 * Then we iterate over all marked variables if they can attain
2522 * any values larger than zero or at least one.
2523 * If the maximal value is zero, we mark any column variables
2524 * that appear in the row as being zero and mark the row as being redundant.
2525 * Otherwise, if the maximal value is strictly less than one (and the
2526 * tableau is integer), then we restrict the value to being zero
2527 * by adding an opposite non-negative variable.
2529 int isl_tab_detect_implicit_equalities(struct isl_tab
*tab
)
2538 if (tab
->n_dead
== tab
->n_col
)
2542 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2543 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2544 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2545 may_be_equality(tab
, i
);
2549 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2550 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2551 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2556 struct isl_tab_var
*var
;
2558 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2559 var
= isl_tab_var_from_row(tab
, i
);
2563 if (i
== tab
->n_row
) {
2564 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2565 var
= var_from_col(tab
, i
);
2569 if (i
== tab
->n_col
)
2574 sgn
= sign_of_max(tab
, var
);
2578 if (close_row(tab
, var
) < 0)
2580 } else if (!tab
->rational
&& !at_least_one(tab
, var
)) {
2581 if (cut_to_hyperplane(tab
, var
) < 0)
2583 return isl_tab_detect_implicit_equalities(tab
);
2585 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2586 var
= isl_tab_var_from_row(tab
, i
);
2589 if (may_be_equality(tab
, i
))
2599 static int con_is_redundant(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2603 if (tab
->rational
) {
2604 int sgn
= sign_of_min(tab
, var
);
2609 int irred
= isl_tab_min_at_most_neg_one(tab
, var
);
2616 /* Check for (near) redundant constraints.
2617 * A constraint is redundant if it is non-negative and if
2618 * its minimal value (temporarily ignoring the non-negativity) is either
2619 * - zero (in case of rational tableaus), or
2620 * - strictly larger than -1 (in case of integer tableaus)
2622 * We first mark all non-redundant and non-dead variables that
2623 * are not frozen and not obviously negatively unbounded.
2624 * Then we iterate over all marked variables if they can attain
2625 * any values smaller than zero or at most negative one.
2626 * If not, we mark the row as being redundant (assuming it hasn't
2627 * been detected as being obviously redundant in the mean time).
2629 int isl_tab_detect_redundant(struct isl_tab
*tab
)
2638 if (tab
->n_redundant
== tab
->n_row
)
2642 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2643 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2644 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2648 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2649 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2650 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2651 !min_is_manifestly_unbounded(tab
, var
);
2656 struct isl_tab_var
*var
;
2658 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2659 var
= isl_tab_var_from_row(tab
, i
);
2663 if (i
== tab
->n_row
) {
2664 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2665 var
= var_from_col(tab
, i
);
2669 if (i
== tab
->n_col
)
2674 red
= con_is_redundant(tab
, var
);
2677 if (red
&& !var
->is_redundant
)
2678 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
2680 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2681 var
= var_from_col(tab
, i
);
2684 if (!min_is_manifestly_unbounded(tab
, var
))
2694 int isl_tab_is_equality(struct isl_tab
*tab
, int con
)
2701 if (tab
->con
[con
].is_zero
)
2703 if (tab
->con
[con
].is_redundant
)
2705 if (!tab
->con
[con
].is_row
)
2706 return tab
->con
[con
].index
< tab
->n_dead
;
2708 row
= tab
->con
[con
].index
;
2711 return isl_int_is_zero(tab
->mat
->row
[row
][1]) &&
2712 isl_seq_first_non_zero(tab
->mat
->row
[row
] + 2 + tab
->n_dead
,
2713 tab
->n_col
- tab
->n_dead
) == -1;
2716 /* Return the minimial value of the affine expression "f" with denominator
2717 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2718 * the expression cannot attain arbitrarily small values.
2719 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2720 * The return value reflects the nature of the result (empty, unbounded,
2721 * minmimal value returned in *opt).
2723 enum isl_lp_result
isl_tab_min(struct isl_tab
*tab
,
2724 isl_int
*f
, isl_int denom
, isl_int
*opt
, isl_int
*opt_denom
,
2728 enum isl_lp_result res
= isl_lp_ok
;
2729 struct isl_tab_var
*var
;
2730 struct isl_tab_undo
*snap
;
2733 return isl_lp_error
;
2736 return isl_lp_empty
;
2738 snap
= isl_tab_snap(tab
);
2739 r
= isl_tab_add_row(tab
, f
);
2741 return isl_lp_error
;
2743 isl_int_mul(tab
->mat
->row
[var
->index
][0],
2744 tab
->mat
->row
[var
->index
][0], denom
);
2747 find_pivot(tab
, var
, var
, -1, &row
, &col
);
2748 if (row
== var
->index
) {
2749 res
= isl_lp_unbounded
;
2754 if (isl_tab_pivot(tab
, row
, col
) < 0)
2755 return isl_lp_error
;
2757 if (ISL_FL_ISSET(flags
, ISL_TAB_SAVE_DUAL
)) {
2760 isl_vec_free(tab
->dual
);
2761 tab
->dual
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_con
);
2763 return isl_lp_error
;
2764 isl_int_set(tab
->dual
->el
[0], tab
->mat
->row
[var
->index
][0]);
2765 for (i
= 0; i
< tab
->n_con
; ++i
) {
2767 if (tab
->con
[i
].is_row
) {
2768 isl_int_set_si(tab
->dual
->el
[1 + i
], 0);
2771 pos
= 2 + tab
->M
+ tab
->con
[i
].index
;
2772 if (tab
->con
[i
].negated
)
2773 isl_int_neg(tab
->dual
->el
[1 + i
],
2774 tab
->mat
->row
[var
->index
][pos
]);
2776 isl_int_set(tab
->dual
->el
[1 + i
],
2777 tab
->mat
->row
[var
->index
][pos
]);
2780 if (opt
&& res
== isl_lp_ok
) {
2782 isl_int_set(*opt
, tab
->mat
->row
[var
->index
][1]);
2783 isl_int_set(*opt_denom
, tab
->mat
->row
[var
->index
][0]);
2785 isl_int_cdiv_q(*opt
, tab
->mat
->row
[var
->index
][1],
2786 tab
->mat
->row
[var
->index
][0]);
2788 if (isl_tab_rollback(tab
, snap
) < 0)
2789 return isl_lp_error
;
2793 int isl_tab_is_redundant(struct isl_tab
*tab
, int con
)
2797 if (tab
->con
[con
].is_zero
)
2799 if (tab
->con
[con
].is_redundant
)
2801 return tab
->con
[con
].is_row
&& tab
->con
[con
].index
< tab
->n_redundant
;
2804 /* Take a snapshot of the tableau that can be restored by s call to
2807 struct isl_tab_undo
*isl_tab_snap(struct isl_tab
*tab
)
2815 /* Undo the operation performed by isl_tab_relax.
2817 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
2818 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2820 unsigned off
= 2 + tab
->M
;
2822 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2823 if (to_row(tab
, var
, 1) < 0)
2827 isl_int_sub(tab
->mat
->row
[var
->index
][1],
2828 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2829 if (var
->is_nonneg
) {
2830 int sgn
= restore_row(tab
, var
);
2831 isl_assert(tab
->mat
->ctx
, sgn
>= 0, return -1);
2836 for (i
= 0; i
< tab
->n_row
; ++i
) {
2837 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2839 isl_int_add(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2840 tab
->mat
->row
[i
][off
+ var
->index
]);
2848 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
2849 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
2851 struct isl_tab_var
*var
= var_from_index(tab
, undo
->u
.var_index
);
2852 switch(undo
->type
) {
2853 case isl_tab_undo_nonneg
:
2856 case isl_tab_undo_redundant
:
2857 var
->is_redundant
= 0;
2859 restore_row(tab
, isl_tab_var_from_row(tab
, tab
->n_redundant
));
2861 case isl_tab_undo_freeze
:
2864 case isl_tab_undo_zero
:
2869 case isl_tab_undo_allocate
:
2870 if (undo
->u
.var_index
>= 0) {
2871 isl_assert(tab
->mat
->ctx
, !var
->is_row
, return -1);
2872 drop_col(tab
, var
->index
);
2876 if (!max_is_manifestly_unbounded(tab
, var
)) {
2877 if (to_row(tab
, var
, 1) < 0)
2879 } else if (!min_is_manifestly_unbounded(tab
, var
)) {
2880 if (to_row(tab
, var
, -1) < 0)
2883 if (to_row(tab
, var
, 0) < 0)
2886 drop_row(tab
, var
->index
);
2888 case isl_tab_undo_relax
:
2889 return unrelax(tab
, var
);
2895 /* Restore the tableau to the state where the basic variables
2896 * are those in "col_var".
2897 * We first construct a list of variables that are currently in
2898 * the basis, but shouldn't. Then we iterate over all variables
2899 * that should be in the basis and for each one that is currently
2900 * not in the basis, we exchange it with one of the elements of the
2901 * list constructed before.
2902 * We can always find an appropriate variable to pivot with because
2903 * the current basis is mapped to the old basis by a non-singular
2904 * matrix and so we can never end up with a zero row.
2906 static int restore_basis(struct isl_tab
*tab
, int *col_var
)
2910 int *extra
= NULL
; /* current columns that contain bad stuff */
2911 unsigned off
= 2 + tab
->M
;
2913 extra
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->n_col
);
2916 for (i
= 0; i
< tab
->n_col
; ++i
) {
2917 for (j
= 0; j
< tab
->n_col
; ++j
)
2918 if (tab
->col_var
[i
] == col_var
[j
])
2922 extra
[n_extra
++] = i
;
2924 for (i
= 0; i
< tab
->n_col
&& n_extra
> 0; ++i
) {
2925 struct isl_tab_var
*var
;
2928 for (j
= 0; j
< tab
->n_col
; ++j
)
2929 if (col_var
[i
] == tab
->col_var
[j
])
2933 var
= var_from_index(tab
, col_var
[i
]);
2935 for (j
= 0; j
< n_extra
; ++j
)
2936 if (!isl_int_is_zero(tab
->mat
->row
[row
][off
+extra
[j
]]))
2938 isl_assert(tab
->mat
->ctx
, j
< n_extra
, goto error
);
2939 if (isl_tab_pivot(tab
, row
, extra
[j
]) < 0)
2941 extra
[j
] = extra
[--n_extra
];
2953 /* Remove all samples with index n or greater, i.e., those samples
2954 * that were added since we saved this number of samples in
2955 * isl_tab_save_samples.
2957 static void drop_samples_since(struct isl_tab
*tab
, int n
)
2961 for (i
= tab
->n_sample
- 1; i
>= 0 && tab
->n_sample
> n
; --i
) {
2962 if (tab
->sample_index
[i
] < n
)
2965 if (i
!= tab
->n_sample
- 1) {
2966 int t
= tab
->sample_index
[tab
->n_sample
-1];
2967 tab
->sample_index
[tab
->n_sample
-1] = tab
->sample_index
[i
];
2968 tab
->sample_index
[i
] = t
;
2969 isl_mat_swap_rows(tab
->samples
, tab
->n_sample
-1, i
);
2975 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
2976 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
2978 switch (undo
->type
) {
2979 case isl_tab_undo_empty
:
2982 case isl_tab_undo_nonneg
:
2983 case isl_tab_undo_redundant
:
2984 case isl_tab_undo_freeze
:
2985 case isl_tab_undo_zero
:
2986 case isl_tab_undo_allocate
:
2987 case isl_tab_undo_relax
:
2988 return perform_undo_var(tab
, undo
);
2989 case isl_tab_undo_bmap_eq
:
2990 return isl_basic_map_free_equality(tab
->bmap
, 1);
2991 case isl_tab_undo_bmap_ineq
:
2992 return isl_basic_map_free_inequality(tab
->bmap
, 1);
2993 case isl_tab_undo_bmap_div
:
2994 if (isl_basic_map_free_div(tab
->bmap
, 1) < 0)
2997 tab
->samples
->n_col
--;
2999 case isl_tab_undo_saved_basis
:
3000 if (restore_basis(tab
, undo
->u
.col_var
) < 0)
3003 case isl_tab_undo_drop_sample
:
3006 case isl_tab_undo_saved_samples
:
3007 drop_samples_since(tab
, undo
->u
.n
);
3009 case isl_tab_undo_callback
:
3010 return undo
->u
.callback
->run(undo
->u
.callback
);
3012 isl_assert(tab
->mat
->ctx
, 0, return -1);
3017 /* Return the tableau to the state it was in when the snapshot "snap"
3020 int isl_tab_rollback(struct isl_tab
*tab
, struct isl_tab_undo
*snap
)
3022 struct isl_tab_undo
*undo
, *next
;
3028 for (undo
= tab
->top
; undo
&& undo
!= &tab
->bottom
; undo
= next
) {
3032 if (perform_undo(tab
, undo
) < 0) {
3047 /* The given row "row" represents an inequality violated by all
3048 * points in the tableau. Check for some special cases of such
3049 * separating constraints.
3050 * In particular, if the row has been reduced to the constant -1,
3051 * then we know the inequality is adjacent (but opposite) to
3052 * an equality in the tableau.
3053 * If the row has been reduced to r = -1 -r', with r' an inequality
3054 * of the tableau, then the inequality is adjacent (but opposite)
3055 * to the inequality r'.
3057 static enum isl_ineq_type
separation_type(struct isl_tab
*tab
, unsigned row
)
3060 unsigned off
= 2 + tab
->M
;
3063 return isl_ineq_separate
;
3065 if (!isl_int_is_one(tab
->mat
->row
[row
][0]))
3066 return isl_ineq_separate
;
3067 if (!isl_int_is_negone(tab
->mat
->row
[row
][1]))
3068 return isl_ineq_separate
;
3070 pos
= isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
3071 tab
->n_col
- tab
->n_dead
);
3073 return isl_ineq_adj_eq
;
3075 if (!isl_int_is_negone(tab
->mat
->row
[row
][off
+ tab
->n_dead
+ pos
]))
3076 return isl_ineq_separate
;
3078 pos
= isl_seq_first_non_zero(
3079 tab
->mat
->row
[row
] + off
+ tab
->n_dead
+ pos
+ 1,
3080 tab
->n_col
- tab
->n_dead
- pos
- 1);
3082 return pos
== -1 ? isl_ineq_adj_ineq
: isl_ineq_separate
;
3085 /* Check the effect of inequality "ineq" on the tableau "tab".
3087 * isl_ineq_redundant: satisfied by all points in the tableau
3088 * isl_ineq_separate: satisfied by no point in the tableau
3089 * isl_ineq_cut: satisfied by some by not all points
3090 * isl_ineq_adj_eq: adjacent to an equality
3091 * isl_ineq_adj_ineq: adjacent to an inequality.
3093 enum isl_ineq_type
isl_tab_ineq_type(struct isl_tab
*tab
, isl_int
*ineq
)
3095 enum isl_ineq_type type
= isl_ineq_error
;
3096 struct isl_tab_undo
*snap
= NULL
;
3101 return isl_ineq_error
;
3103 if (isl_tab_extend_cons(tab
, 1) < 0)
3104 return isl_ineq_error
;
3106 snap
= isl_tab_snap(tab
);
3108 con
= isl_tab_add_row(tab
, ineq
);
3112 row
= tab
->con
[con
].index
;
3113 if (isl_tab_row_is_redundant(tab
, row
))
3114 type
= isl_ineq_redundant
;
3115 else if (isl_int_is_neg(tab
->mat
->row
[row
][1]) &&
3117 isl_int_abs_ge(tab
->mat
->row
[row
][1],
3118 tab
->mat
->row
[row
][0]))) {
3119 int nonneg
= at_least_zero(tab
, &tab
->con
[con
]);
3123 type
= isl_ineq_cut
;
3125 type
= separation_type(tab
, row
);
3127 int red
= con_is_redundant(tab
, &tab
->con
[con
]);
3131 type
= isl_ineq_cut
;
3133 type
= isl_ineq_redundant
;
3136 if (isl_tab_rollback(tab
, snap
))
3137 return isl_ineq_error
;
3140 return isl_ineq_error
;
3143 int isl_tab_track_bmap(struct isl_tab
*tab
, __isl_take isl_basic_map
*bmap
)
3148 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
3149 isl_assert(tab
->mat
->ctx
,
3150 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
3156 isl_basic_map_free(bmap
);
3160 int isl_tab_track_bset(struct isl_tab
*tab
, __isl_take isl_basic_set
*bset
)
3162 return isl_tab_track_bmap(tab
, (isl_basic_map
*)bset
);
3165 __isl_keep isl_basic_set
*isl_tab_peek_bset(struct isl_tab
*tab
)
3170 return (isl_basic_set
*)tab
->bmap
;
3173 void isl_tab_dump(struct isl_tab
*tab
, FILE *out
, int indent
)
3179 fprintf(out
, "%*snull tab\n", indent
, "");
3182 fprintf(out
, "%*sn_redundant: %d, n_dead: %d", indent
, "",
3183 tab
->n_redundant
, tab
->n_dead
);
3185 fprintf(out
, ", rational");
3187 fprintf(out
, ", empty");
3189 fprintf(out
, "%*s[", indent
, "");
3190 for (i
= 0; i
< tab
->n_var
; ++i
) {
3192 fprintf(out
, (i
== tab
->n_param
||
3193 i
== tab
->n_var
- tab
->n_div
) ? "; "
3195 fprintf(out
, "%c%d%s", tab
->var
[i
].is_row
? 'r' : 'c',
3197 tab
->var
[i
].is_zero
? " [=0]" :
3198 tab
->var
[i
].is_redundant
? " [R]" : "");
3200 fprintf(out
, "]\n");
3201 fprintf(out
, "%*s[", indent
, "");
3202 for (i
= 0; i
< tab
->n_con
; ++i
) {
3205 fprintf(out
, "%c%d%s", tab
->con
[i
].is_row
? 'r' : 'c',
3207 tab
->con
[i
].is_zero
? " [=0]" :
3208 tab
->con
[i
].is_redundant
? " [R]" : "");
3210 fprintf(out
, "]\n");
3211 fprintf(out
, "%*s[", indent
, "");
3212 for (i
= 0; i
< tab
->n_row
; ++i
) {
3213 const char *sign
= "";
3216 if (tab
->row_sign
) {
3217 if (tab
->row_sign
[i
] == isl_tab_row_unknown
)
3219 else if (tab
->row_sign
[i
] == isl_tab_row_neg
)
3221 else if (tab
->row_sign
[i
] == isl_tab_row_pos
)
3226 fprintf(out
, "r%d: %d%s%s", i
, tab
->row_var
[i
],
3227 isl_tab_var_from_row(tab
, i
)->is_nonneg
? " [>=0]" : "", sign
);
3229 fprintf(out
, "]\n");
3230 fprintf(out
, "%*s[", indent
, "");
3231 for (i
= 0; i
< tab
->n_col
; ++i
) {
3234 fprintf(out
, "c%d: %d%s", i
, tab
->col_var
[i
],
3235 var_from_col(tab
, i
)->is_nonneg
? " [>=0]" : "");
3237 fprintf(out
, "]\n");
3238 r
= tab
->mat
->n_row
;
3239 tab
->mat
->n_row
= tab
->n_row
;
3240 c
= tab
->mat
->n_col
;
3241 tab
->mat
->n_col
= 2 + tab
->M
+ tab
->n_col
;
3242 isl_mat_dump(tab
->mat
, out
, indent
);
3243 tab
->mat
->n_row
= r
;
3244 tab
->mat
->n_col
= c
;
3246 isl_basic_map_dump(tab
->bmap
, out
, indent
);