2 * Copyright 2008-2009 Katholieke Universiteit Leuven
4 * Use of this software is governed by the GNU LGPLv2.1 license
6 * Written by Sven Verdoolaege, K.U.Leuven, Departement
7 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
10 #include <isl_mat_private.h>
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 static int row_is_manifestly_non_integral(struct isl_tab
*tab
, int row
)
1522 unsigned off
= 2 + tab
->M
;
1524 if (tab
->M
&& !isl_int_eq(tab
->mat
->row
[row
][2],
1525 tab
->mat
->row
[row
][0]))
1527 if (isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
1528 tab
->n_col
- tab
->n_dead
) != -1)
1531 return !isl_int_is_divisible_by(tab
->mat
->row
[row
][1],
1532 tab
->mat
->row
[row
][0]);
1535 /* For integer tableaus, check if any of the coordinates are stuck
1536 * at a non-integral value.
1538 static int tab_is_manifestly_empty(struct isl_tab
*tab
)
1547 for (i
= 0; i
< tab
->n_var
; ++i
) {
1548 if (!tab
->var
[i
].is_row
)
1550 if (row_is_manifestly_non_integral(tab
, tab
->var
[i
].index
))
1557 /* Row variable "var" is non-negative and cannot attain any values
1558 * larger than zero. This means that the coefficients of the unrestricted
1559 * column variables are zero and that the coefficients of the non-negative
1560 * column variables are zero or negative.
1561 * Each of the non-negative variables with a negative coefficient can
1562 * then also be written as the negative sum of non-negative variables
1563 * and must therefore also be zero.
1565 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1566 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1569 struct isl_mat
*mat
= tab
->mat
;
1570 unsigned off
= 2 + tab
->M
;
1572 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, return -1);
1575 if (isl_tab_push_var(tab
, isl_tab_undo_zero
, var
) < 0)
1577 for (j
= tab
->n_dead
; j
< tab
->n_col
; ++j
) {
1579 if (isl_int_is_zero(mat
->row
[var
->index
][off
+ j
]))
1581 isl_assert(tab
->mat
->ctx
,
1582 isl_int_is_neg(mat
->row
[var
->index
][off
+ j
]), return -1);
1583 recheck
= isl_tab_kill_col(tab
, j
);
1589 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
1591 if (tab_is_manifestly_empty(tab
) && isl_tab_mark_empty(tab
) < 0)
1596 /* Add a constraint to the tableau and allocate a row for it.
1597 * Return the index into the constraint array "con".
1599 int isl_tab_allocate_con(struct isl_tab
*tab
)
1603 isl_assert(tab
->mat
->ctx
, tab
->n_row
< tab
->mat
->n_row
, return -1);
1604 isl_assert(tab
->mat
->ctx
, tab
->n_con
< tab
->max_con
, return -1);
1607 tab
->con
[r
].index
= tab
->n_row
;
1608 tab
->con
[r
].is_row
= 1;
1609 tab
->con
[r
].is_nonneg
= 0;
1610 tab
->con
[r
].is_zero
= 0;
1611 tab
->con
[r
].is_redundant
= 0;
1612 tab
->con
[r
].frozen
= 0;
1613 tab
->con
[r
].negated
= 0;
1614 tab
->row_var
[tab
->n_row
] = ~r
;
1618 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
1624 /* Add a variable to the tableau and allocate a column for it.
1625 * Return the index into the variable array "var".
1627 int isl_tab_allocate_var(struct isl_tab
*tab
)
1631 unsigned off
= 2 + tab
->M
;
1633 isl_assert(tab
->mat
->ctx
, tab
->n_col
< tab
->mat
->n_col
, return -1);
1634 isl_assert(tab
->mat
->ctx
, tab
->n_var
< tab
->max_var
, return -1);
1637 tab
->var
[r
].index
= tab
->n_col
;
1638 tab
->var
[r
].is_row
= 0;
1639 tab
->var
[r
].is_nonneg
= 0;
1640 tab
->var
[r
].is_zero
= 0;
1641 tab
->var
[r
].is_redundant
= 0;
1642 tab
->var
[r
].frozen
= 0;
1643 tab
->var
[r
].negated
= 0;
1644 tab
->col_var
[tab
->n_col
] = r
;
1646 for (i
= 0; i
< tab
->n_row
; ++i
)
1647 isl_int_set_si(tab
->mat
->row
[i
][off
+ tab
->n_col
], 0);
1651 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->var
[r
]) < 0)
1657 /* Add a row to the tableau. The row is given as an affine combination
1658 * of the original variables and needs to be expressed in terms of the
1661 * We add each term in turn.
1662 * If r = n/d_r is the current sum and we need to add k x, then
1663 * if x is a column variable, we increase the numerator of
1664 * this column by k d_r
1665 * if x = f/d_x is a row variable, then the new representation of r is
1667 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1668 * --- + --- = ------------------- = -------------------
1669 * d_r d_r d_r d_x/g m
1671 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1673 * If tab->M is set, then, internally, each variable x is represented
1674 * as x' - M. We then also need no subtract k d_r from the coefficient of M.
1676 int isl_tab_add_row(struct isl_tab
*tab
, isl_int
*line
)
1682 unsigned off
= 2 + tab
->M
;
1684 r
= isl_tab_allocate_con(tab
);
1690 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1691 isl_int_set_si(row
[0], 1);
1692 isl_int_set(row
[1], line
[0]);
1693 isl_seq_clr(row
+ 2, tab
->M
+ tab
->n_col
);
1694 for (i
= 0; i
< tab
->n_var
; ++i
) {
1695 if (tab
->var
[i
].is_zero
)
1697 if (tab
->var
[i
].is_row
) {
1699 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1700 isl_int_swap(a
, row
[0]);
1701 isl_int_divexact(a
, row
[0], a
);
1703 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1704 isl_int_mul(b
, b
, line
[1 + i
]);
1705 isl_seq_combine(row
+ 1, a
, row
+ 1,
1706 b
, tab
->mat
->row
[tab
->var
[i
].index
] + 1,
1707 1 + tab
->M
+ tab
->n_col
);
1709 isl_int_addmul(row
[off
+ tab
->var
[i
].index
],
1710 line
[1 + i
], row
[0]);
1711 if (tab
->M
&& i
>= tab
->n_param
&& i
< tab
->n_var
- tab
->n_div
)
1712 isl_int_submul(row
[2], line
[1 + i
], row
[0]);
1714 isl_seq_normalize(tab
->mat
->ctx
, row
, off
+ tab
->n_col
);
1719 tab
->row_sign
[tab
->con
[r
].index
] = isl_tab_row_unknown
;
1724 static int drop_row(struct isl_tab
*tab
, int row
)
1726 isl_assert(tab
->mat
->ctx
, ~tab
->row_var
[row
] == tab
->n_con
- 1, return -1);
1727 if (row
!= tab
->n_row
- 1)
1728 swap_rows(tab
, row
, tab
->n_row
- 1);
1734 static int drop_col(struct isl_tab
*tab
, int col
)
1736 isl_assert(tab
->mat
->ctx
, tab
->col_var
[col
] == tab
->n_var
- 1, return -1);
1737 if (col
!= tab
->n_col
- 1)
1738 swap_cols(tab
, col
, tab
->n_col
- 1);
1744 /* Add inequality "ineq" and check if it conflicts with the
1745 * previously added constraints or if it is obviously redundant.
1747 int isl_tab_add_ineq(struct isl_tab
*tab
, isl_int
*ineq
)
1756 struct isl_basic_map
*bmap
= tab
->bmap
;
1758 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
1759 isl_assert(tab
->mat
->ctx
,
1760 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
1761 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, ineq
);
1762 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1769 isl_int_swap(ineq
[0], cst
);
1771 r
= isl_tab_add_row(tab
, ineq
);
1773 isl_int_swap(ineq
[0], cst
);
1778 tab
->con
[r
].is_nonneg
= 1;
1779 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
1781 if (isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
)) {
1782 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1787 sgn
= restore_row(tab
, &tab
->con
[r
]);
1791 return isl_tab_mark_empty(tab
);
1792 if (tab
->con
[r
].is_row
&& isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
))
1793 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1798 /* Pivot a non-negative variable down until it reaches the value zero
1799 * and then pivot the variable into a column position.
1801 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1802 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1806 unsigned off
= 2 + tab
->M
;
1811 while (isl_int_is_pos(tab
->mat
->row
[var
->index
][1])) {
1812 find_pivot(tab
, var
, NULL
, -1, &row
, &col
);
1813 isl_assert(tab
->mat
->ctx
, row
!= -1, return -1);
1814 if (isl_tab_pivot(tab
, row
, col
) < 0)
1820 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
)
1821 if (!isl_int_is_zero(tab
->mat
->row
[var
->index
][off
+ i
]))
1824 isl_assert(tab
->mat
->ctx
, i
< tab
->n_col
, return -1);
1825 if (isl_tab_pivot(tab
, var
->index
, i
) < 0)
1831 /* We assume Gaussian elimination has been performed on the equalities.
1832 * The equalities can therefore never conflict.
1833 * Adding the equalities is currently only really useful for a later call
1834 * to isl_tab_ineq_type.
1836 static struct isl_tab
*add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1843 r
= isl_tab_add_row(tab
, eq
);
1847 r
= tab
->con
[r
].index
;
1848 i
= isl_seq_first_non_zero(tab
->mat
->row
[r
] + 2 + tab
->M
+ tab
->n_dead
,
1849 tab
->n_col
- tab
->n_dead
);
1850 isl_assert(tab
->mat
->ctx
, i
>= 0, goto error
);
1852 if (isl_tab_pivot(tab
, r
, i
) < 0)
1854 if (isl_tab_kill_col(tab
, i
) < 0)
1864 static int row_is_manifestly_zero(struct isl_tab
*tab
, int row
)
1866 unsigned off
= 2 + tab
->M
;
1868 if (!isl_int_is_zero(tab
->mat
->row
[row
][1]))
1870 if (tab
->M
&& !isl_int_is_zero(tab
->mat
->row
[row
][2]))
1872 return isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
1873 tab
->n_col
- tab
->n_dead
) == -1;
1876 /* Add an equality that is known to be valid for the given tableau.
1878 int isl_tab_add_valid_eq(struct isl_tab
*tab
, isl_int
*eq
)
1880 struct isl_tab_var
*var
;
1885 r
= isl_tab_add_row(tab
, eq
);
1891 if (row_is_manifestly_zero(tab
, r
)) {
1893 if (isl_tab_mark_redundant(tab
, r
) < 0)
1898 if (isl_int_is_neg(tab
->mat
->row
[r
][1])) {
1899 isl_seq_neg(tab
->mat
->row
[r
] + 1, tab
->mat
->row
[r
] + 1,
1904 if (to_col(tab
, var
) < 0)
1907 if (isl_tab_kill_col(tab
, var
->index
) < 0)
1913 static int add_zero_row(struct isl_tab
*tab
)
1918 r
= isl_tab_allocate_con(tab
);
1922 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1923 isl_seq_clr(row
+ 1, 1 + tab
->M
+ tab
->n_col
);
1924 isl_int_set_si(row
[0], 1);
1929 /* Add equality "eq" and check if it conflicts with the
1930 * previously added constraints or if it is obviously redundant.
1932 int isl_tab_add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1934 struct isl_tab_undo
*snap
= NULL
;
1935 struct isl_tab_var
*var
;
1943 isl_assert(tab
->mat
->ctx
, !tab
->M
, return -1);
1946 snap
= isl_tab_snap(tab
);
1950 isl_int_swap(eq
[0], cst
);
1952 r
= isl_tab_add_row(tab
, eq
);
1954 isl_int_swap(eq
[0], cst
);
1962 if (row_is_manifestly_zero(tab
, row
)) {
1964 if (isl_tab_rollback(tab
, snap
) < 0)
1972 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1973 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1975 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1976 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1977 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1978 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1982 if (add_zero_row(tab
) < 0)
1986 sgn
= isl_int_sgn(tab
->mat
->row
[row
][1]);
1989 isl_seq_neg(tab
->mat
->row
[row
] + 1, tab
->mat
->row
[row
] + 1,
1996 sgn
= sign_of_max(tab
, var
);
2000 if (isl_tab_mark_empty(tab
) < 0)
2007 if (to_col(tab
, var
) < 0)
2010 if (isl_tab_kill_col(tab
, var
->index
) < 0)
2016 /* Construct and return an inequality that expresses an upper bound
2018 * In particular, if the div is given by
2022 * then the inequality expresses
2026 static struct isl_vec
*ineq_for_div(struct isl_basic_map
*bmap
, unsigned div
)
2030 struct isl_vec
*ineq
;
2035 total
= isl_basic_map_total_dim(bmap
);
2036 div_pos
= 1 + total
- bmap
->n_div
+ div
;
2038 ineq
= isl_vec_alloc(bmap
->ctx
, 1 + total
);
2042 isl_seq_cpy(ineq
->el
, bmap
->div
[div
] + 1, 1 + total
);
2043 isl_int_neg(ineq
->el
[div_pos
], bmap
->div
[div
][0]);
2047 /* For a div d = floor(f/m), add the constraints
2050 * -(f-(m-1)) + m d >= 0
2052 * Note that the second constraint is the negation of
2056 * If add_ineq is not NULL, then this function is used
2057 * instead of isl_tab_add_ineq to effectively add the inequalities.
2059 static int add_div_constraints(struct isl_tab
*tab
, unsigned div
,
2060 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
2064 struct isl_vec
*ineq
;
2066 total
= isl_basic_map_total_dim(tab
->bmap
);
2067 div_pos
= 1 + total
- tab
->bmap
->n_div
+ div
;
2069 ineq
= ineq_for_div(tab
->bmap
, div
);
2074 if (add_ineq(user
, ineq
->el
) < 0)
2077 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2081 isl_seq_neg(ineq
->el
, tab
->bmap
->div
[div
] + 1, 1 + total
);
2082 isl_int_set(ineq
->el
[div_pos
], tab
->bmap
->div
[div
][0]);
2083 isl_int_add(ineq
->el
[0], ineq
->el
[0], ineq
->el
[div_pos
]);
2084 isl_int_sub_ui(ineq
->el
[0], ineq
->el
[0], 1);
2087 if (add_ineq(user
, ineq
->el
) < 0)
2090 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2102 /* Check whether the div described by "div" is obviously non-negative.
2103 * If we are using a big parameter, then we will encode the div
2104 * as div' = M + div, which is always non-negative.
2105 * Otherwise, we check whether div is a non-negative affine combination
2106 * of non-negative variables.
2108 static int div_is_nonneg(struct isl_tab
*tab
, __isl_keep isl_vec
*div
)
2115 if (isl_int_is_neg(div
->el
[1]))
2118 for (i
= 0; i
< tab
->n_var
; ++i
) {
2119 if (isl_int_is_neg(div
->el
[2 + i
]))
2121 if (isl_int_is_zero(div
->el
[2 + i
]))
2123 if (!tab
->var
[i
].is_nonneg
)
2130 /* Add an extra div, prescribed by "div" to the tableau and
2131 * the associated bmap (which is assumed to be non-NULL).
2133 * If add_ineq is not NULL, then this function is used instead
2134 * of isl_tab_add_ineq to add the div constraints.
2135 * This complication is needed because the code in isl_tab_pip
2136 * wants to perform some extra processing when an inequality
2137 * is added to the tableau.
2139 int isl_tab_add_div(struct isl_tab
*tab
, __isl_keep isl_vec
*div
,
2140 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
2149 isl_assert(tab
->mat
->ctx
, tab
->bmap
, return -1);
2151 nonneg
= div_is_nonneg(tab
, div
);
2153 if (isl_tab_extend_cons(tab
, 3) < 0)
2155 if (isl_tab_extend_vars(tab
, 1) < 0)
2157 r
= isl_tab_allocate_var(tab
);
2162 tab
->var
[r
].is_nonneg
= 1;
2164 tab
->bmap
= isl_basic_map_extend_dim(tab
->bmap
,
2165 isl_basic_map_get_dim(tab
->bmap
), 1, 0, 2);
2166 k
= isl_basic_map_alloc_div(tab
->bmap
);
2169 isl_seq_cpy(tab
->bmap
->div
[k
], div
->el
, div
->size
);
2170 if (isl_tab_push(tab
, isl_tab_undo_bmap_div
) < 0)
2173 if (add_div_constraints(tab
, k
, add_ineq
, user
) < 0)
2179 struct isl_tab
*isl_tab_from_basic_map(struct isl_basic_map
*bmap
)
2182 struct isl_tab
*tab
;
2186 tab
= isl_tab_alloc(bmap
->ctx
,
2187 isl_basic_map_total_dim(bmap
) + bmap
->n_ineq
+ 1,
2188 isl_basic_map_total_dim(bmap
), 0);
2191 tab
->rational
= ISL_F_ISSET(bmap
, ISL_BASIC_MAP_RATIONAL
);
2192 if (ISL_F_ISSET(bmap
, ISL_BASIC_MAP_EMPTY
)) {
2193 if (isl_tab_mark_empty(tab
) < 0)
2197 for (i
= 0; i
< bmap
->n_eq
; ++i
) {
2198 tab
= add_eq(tab
, bmap
->eq
[i
]);
2202 for (i
= 0; i
< bmap
->n_ineq
; ++i
) {
2203 if (isl_tab_add_ineq(tab
, bmap
->ineq
[i
]) < 0)
2214 struct isl_tab
*isl_tab_from_basic_set(struct isl_basic_set
*bset
)
2216 return isl_tab_from_basic_map((struct isl_basic_map
*)bset
);
2219 /* Construct a tableau corresponding to the recession cone of "bset".
2221 struct isl_tab
*isl_tab_from_recession_cone(__isl_keep isl_basic_set
*bset
,
2226 struct isl_tab
*tab
;
2227 unsigned offset
= 0;
2232 offset
= isl_basic_set_dim(bset
, isl_dim_param
);
2233 tab
= isl_tab_alloc(bset
->ctx
, bset
->n_eq
+ bset
->n_ineq
,
2234 isl_basic_set_total_dim(bset
) - offset
, 0);
2237 tab
->rational
= ISL_F_ISSET(bset
, ISL_BASIC_SET_RATIONAL
);
2241 for (i
= 0; i
< bset
->n_eq
; ++i
) {
2242 isl_int_swap(bset
->eq
[i
][offset
], cst
);
2244 if (isl_tab_add_eq(tab
, bset
->eq
[i
] + offset
) < 0)
2247 tab
= add_eq(tab
, bset
->eq
[i
]);
2248 isl_int_swap(bset
->eq
[i
][offset
], cst
);
2252 for (i
= 0; i
< bset
->n_ineq
; ++i
) {
2254 isl_int_swap(bset
->ineq
[i
][offset
], cst
);
2255 r
= isl_tab_add_row(tab
, bset
->ineq
[i
] + offset
);
2256 isl_int_swap(bset
->ineq
[i
][offset
], cst
);
2259 tab
->con
[r
].is_nonneg
= 1;
2260 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2272 /* Assuming "tab" is the tableau of a cone, check if the cone is
2273 * bounded, i.e., if it is empty or only contains the origin.
2275 int isl_tab_cone_is_bounded(struct isl_tab
*tab
)
2283 if (tab
->n_dead
== tab
->n_col
)
2287 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2288 struct isl_tab_var
*var
;
2290 var
= isl_tab_var_from_row(tab
, i
);
2291 if (!var
->is_nonneg
)
2293 sgn
= sign_of_max(tab
, var
);
2298 if (close_row(tab
, var
) < 0)
2302 if (tab
->n_dead
== tab
->n_col
)
2304 if (i
== tab
->n_row
)
2309 int isl_tab_sample_is_integer(struct isl_tab
*tab
)
2316 for (i
= 0; i
< tab
->n_var
; ++i
) {
2318 if (!tab
->var
[i
].is_row
)
2320 row
= tab
->var
[i
].index
;
2321 if (!isl_int_is_divisible_by(tab
->mat
->row
[row
][1],
2322 tab
->mat
->row
[row
][0]))
2328 static struct isl_vec
*extract_integer_sample(struct isl_tab
*tab
)
2331 struct isl_vec
*vec
;
2333 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2337 isl_int_set_si(vec
->block
.data
[0], 1);
2338 for (i
= 0; i
< tab
->n_var
; ++i
) {
2339 if (!tab
->var
[i
].is_row
)
2340 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2342 int row
= tab
->var
[i
].index
;
2343 isl_int_divexact(vec
->block
.data
[1 + i
],
2344 tab
->mat
->row
[row
][1], tab
->mat
->row
[row
][0]);
2351 struct isl_vec
*isl_tab_get_sample_value(struct isl_tab
*tab
)
2354 struct isl_vec
*vec
;
2360 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2366 isl_int_set_si(vec
->block
.data
[0], 1);
2367 for (i
= 0; i
< tab
->n_var
; ++i
) {
2369 if (!tab
->var
[i
].is_row
) {
2370 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2373 row
= tab
->var
[i
].index
;
2374 isl_int_gcd(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2375 isl_int_divexact(m
, tab
->mat
->row
[row
][0], m
);
2376 isl_seq_scale(vec
->block
.data
, vec
->block
.data
, m
, 1 + i
);
2377 isl_int_divexact(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2378 isl_int_mul(vec
->block
.data
[1 + i
], m
, tab
->mat
->row
[row
][1]);
2380 vec
= isl_vec_normalize(vec
);
2386 /* Update "bmap" based on the results of the tableau "tab".
2387 * In particular, implicit equalities are made explicit, redundant constraints
2388 * are removed and if the sample value happens to be integer, it is stored
2389 * in "bmap" (unless "bmap" already had an integer sample).
2391 * The tableau is assumed to have been created from "bmap" using
2392 * isl_tab_from_basic_map.
2394 struct isl_basic_map
*isl_basic_map_update_from_tab(struct isl_basic_map
*bmap
,
2395 struct isl_tab
*tab
)
2407 bmap
= isl_basic_map_set_to_empty(bmap
);
2409 for (i
= bmap
->n_ineq
- 1; i
>= 0; --i
) {
2410 if (isl_tab_is_equality(tab
, n_eq
+ i
))
2411 isl_basic_map_inequality_to_equality(bmap
, i
);
2412 else if (isl_tab_is_redundant(tab
, n_eq
+ i
))
2413 isl_basic_map_drop_inequality(bmap
, i
);
2415 if (bmap
->n_eq
!= n_eq
)
2416 isl_basic_map_gauss(bmap
, NULL
);
2417 if (!tab
->rational
&&
2418 !bmap
->sample
&& isl_tab_sample_is_integer(tab
))
2419 bmap
->sample
= extract_integer_sample(tab
);
2423 struct isl_basic_set
*isl_basic_set_update_from_tab(struct isl_basic_set
*bset
,
2424 struct isl_tab
*tab
)
2426 return (struct isl_basic_set
*)isl_basic_map_update_from_tab(
2427 (struct isl_basic_map
*)bset
, tab
);
2430 /* Given a non-negative variable "var", add a new non-negative variable
2431 * that is the opposite of "var", ensuring that var can only attain the
2433 * If var = n/d is a row variable, then the new variable = -n/d.
2434 * If var is a column variables, then the new variable = -var.
2435 * If the new variable cannot attain non-negative values, then
2436 * the resulting tableau is empty.
2437 * Otherwise, we know the value will be zero and we close the row.
2439 static int cut_to_hyperplane(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2444 unsigned off
= 2 + tab
->M
;
2448 isl_assert(tab
->mat
->ctx
, !var
->is_redundant
, return -1);
2449 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, return -1);
2451 if (isl_tab_extend_cons(tab
, 1) < 0)
2455 tab
->con
[r
].index
= tab
->n_row
;
2456 tab
->con
[r
].is_row
= 1;
2457 tab
->con
[r
].is_nonneg
= 0;
2458 tab
->con
[r
].is_zero
= 0;
2459 tab
->con
[r
].is_redundant
= 0;
2460 tab
->con
[r
].frozen
= 0;
2461 tab
->con
[r
].negated
= 0;
2462 tab
->row_var
[tab
->n_row
] = ~r
;
2463 row
= tab
->mat
->row
[tab
->n_row
];
2466 isl_int_set(row
[0], tab
->mat
->row
[var
->index
][0]);
2467 isl_seq_neg(row
+ 1,
2468 tab
->mat
->row
[var
->index
] + 1, 1 + tab
->n_col
);
2470 isl_int_set_si(row
[0], 1);
2471 isl_seq_clr(row
+ 1, 1 + tab
->n_col
);
2472 isl_int_set_si(row
[off
+ var
->index
], -1);
2477 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
2480 sgn
= sign_of_max(tab
, &tab
->con
[r
]);
2484 if (isl_tab_mark_empty(tab
) < 0)
2488 tab
->con
[r
].is_nonneg
= 1;
2489 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2492 if (close_row(tab
, &tab
->con
[r
]) < 0)
2498 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2499 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2500 * by r' = r + 1 >= 0.
2501 * If r is a row variable, we simply increase the constant term by one
2502 * (taking into account the denominator).
2503 * If r is a column variable, then we need to modify each row that
2504 * refers to r = r' - 1 by substituting this equality, effectively
2505 * subtracting the coefficient of the column from the constant.
2506 * We should only do this if the minimum is manifestly unbounded,
2507 * however. Otherwise, we may end up with negative sample values
2508 * for non-negative variables.
2509 * So, if r is a column variable with a minimum that is not
2510 * manifestly unbounded, then we need to move it to a row.
2511 * However, the sample value of this row may be negative,
2512 * even after the relaxation, so we need to restore it.
2513 * We therefore prefer to pivot a column up to a row, if possible.
2515 struct isl_tab
*isl_tab_relax(struct isl_tab
*tab
, int con
)
2517 struct isl_tab_var
*var
;
2518 unsigned off
= 2 + tab
->M
;
2523 var
= &tab
->con
[con
];
2525 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2526 if (to_row(tab
, var
, 1) < 0)
2528 if (!var
->is_row
&& !min_is_manifestly_unbounded(tab
, var
))
2529 if (to_row(tab
, var
, -1) < 0)
2533 isl_int_add(tab
->mat
->row
[var
->index
][1],
2534 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2535 if (restore_row(tab
, var
) < 0)
2540 for (i
= 0; i
< tab
->n_row
; ++i
) {
2541 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2543 isl_int_sub(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2544 tab
->mat
->row
[i
][off
+ var
->index
]);
2549 if (isl_tab_push_var(tab
, isl_tab_undo_relax
, var
) < 0)
2558 int isl_tab_select_facet(struct isl_tab
*tab
, int con
)
2563 return cut_to_hyperplane(tab
, &tab
->con
[con
]);
2566 static int may_be_equality(struct isl_tab
*tab
, int row
)
2568 unsigned off
= 2 + tab
->M
;
2569 return tab
->rational
? isl_int_is_zero(tab
->mat
->row
[row
][1])
2570 : isl_int_lt(tab
->mat
->row
[row
][1],
2571 tab
->mat
->row
[row
][0]);
2574 /* Check for (near) equalities among the constraints.
2575 * A constraint is an equality if it is non-negative and if
2576 * its maximal value is either
2577 * - zero (in case of rational tableaus), or
2578 * - strictly less than 1 (in case of integer tableaus)
2580 * We first mark all non-redundant and non-dead variables that
2581 * are not frozen and not obviously not an equality.
2582 * Then we iterate over all marked variables if they can attain
2583 * any values larger than zero or at least one.
2584 * If the maximal value is zero, we mark any column variables
2585 * that appear in the row as being zero and mark the row as being redundant.
2586 * Otherwise, if the maximal value is strictly less than one (and the
2587 * tableau is integer), then we restrict the value to being zero
2588 * by adding an opposite non-negative variable.
2590 int isl_tab_detect_implicit_equalities(struct isl_tab
*tab
)
2599 if (tab
->n_dead
== tab
->n_col
)
2603 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2604 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2605 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2606 may_be_equality(tab
, i
);
2610 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2611 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2612 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2617 struct isl_tab_var
*var
;
2619 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2620 var
= isl_tab_var_from_row(tab
, i
);
2624 if (i
== tab
->n_row
) {
2625 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2626 var
= var_from_col(tab
, i
);
2630 if (i
== tab
->n_col
)
2635 sgn
= sign_of_max(tab
, var
);
2639 if (close_row(tab
, var
) < 0)
2641 } else if (!tab
->rational
&& !at_least_one(tab
, var
)) {
2642 if (cut_to_hyperplane(tab
, var
) < 0)
2644 return isl_tab_detect_implicit_equalities(tab
);
2646 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2647 var
= isl_tab_var_from_row(tab
, i
);
2650 if (may_be_equality(tab
, i
))
2660 static int con_is_redundant(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2664 if (tab
->rational
) {
2665 int sgn
= sign_of_min(tab
, var
);
2670 int irred
= isl_tab_min_at_most_neg_one(tab
, var
);
2677 /* Check for (near) redundant constraints.
2678 * A constraint is redundant if it is non-negative and if
2679 * its minimal value (temporarily ignoring the non-negativity) is either
2680 * - zero (in case of rational tableaus), or
2681 * - strictly larger than -1 (in case of integer tableaus)
2683 * We first mark all non-redundant and non-dead variables that
2684 * are not frozen and not obviously negatively unbounded.
2685 * Then we iterate over all marked variables if they can attain
2686 * any values smaller than zero or at most negative one.
2687 * If not, we mark the row as being redundant (assuming it hasn't
2688 * been detected as being obviously redundant in the mean time).
2690 int isl_tab_detect_redundant(struct isl_tab
*tab
)
2699 if (tab
->n_redundant
== tab
->n_row
)
2703 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2704 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2705 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2709 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2710 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2711 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2712 !min_is_manifestly_unbounded(tab
, var
);
2717 struct isl_tab_var
*var
;
2719 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2720 var
= isl_tab_var_from_row(tab
, i
);
2724 if (i
== tab
->n_row
) {
2725 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2726 var
= var_from_col(tab
, i
);
2730 if (i
== tab
->n_col
)
2735 red
= con_is_redundant(tab
, var
);
2738 if (red
&& !var
->is_redundant
)
2739 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
2741 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2742 var
= var_from_col(tab
, i
);
2745 if (!min_is_manifestly_unbounded(tab
, var
))
2755 int isl_tab_is_equality(struct isl_tab
*tab
, int con
)
2762 if (tab
->con
[con
].is_zero
)
2764 if (tab
->con
[con
].is_redundant
)
2766 if (!tab
->con
[con
].is_row
)
2767 return tab
->con
[con
].index
< tab
->n_dead
;
2769 row
= tab
->con
[con
].index
;
2772 return isl_int_is_zero(tab
->mat
->row
[row
][1]) &&
2773 (!tab
->M
|| isl_int_is_zero(tab
->mat
->row
[row
][2])) &&
2774 isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
2775 tab
->n_col
- tab
->n_dead
) == -1;
2778 /* Return the minimal value of the affine expression "f" with denominator
2779 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2780 * the expression cannot attain arbitrarily small values.
2781 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2782 * The return value reflects the nature of the result (empty, unbounded,
2783 * minimal value returned in *opt).
2785 enum isl_lp_result
isl_tab_min(struct isl_tab
*tab
,
2786 isl_int
*f
, isl_int denom
, isl_int
*opt
, isl_int
*opt_denom
,
2790 enum isl_lp_result res
= isl_lp_ok
;
2791 struct isl_tab_var
*var
;
2792 struct isl_tab_undo
*snap
;
2795 return isl_lp_error
;
2798 return isl_lp_empty
;
2800 snap
= isl_tab_snap(tab
);
2801 r
= isl_tab_add_row(tab
, f
);
2803 return isl_lp_error
;
2807 find_pivot(tab
, var
, var
, -1, &row
, &col
);
2808 if (row
== var
->index
) {
2809 res
= isl_lp_unbounded
;
2814 if (isl_tab_pivot(tab
, row
, col
) < 0)
2815 return isl_lp_error
;
2817 isl_int_mul(tab
->mat
->row
[var
->index
][0],
2818 tab
->mat
->row
[var
->index
][0], denom
);
2819 if (ISL_FL_ISSET(flags
, ISL_TAB_SAVE_DUAL
)) {
2822 isl_vec_free(tab
->dual
);
2823 tab
->dual
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_con
);
2825 return isl_lp_error
;
2826 isl_int_set(tab
->dual
->el
[0], tab
->mat
->row
[var
->index
][0]);
2827 for (i
= 0; i
< tab
->n_con
; ++i
) {
2829 if (tab
->con
[i
].is_row
) {
2830 isl_int_set_si(tab
->dual
->el
[1 + i
], 0);
2833 pos
= 2 + tab
->M
+ tab
->con
[i
].index
;
2834 if (tab
->con
[i
].negated
)
2835 isl_int_neg(tab
->dual
->el
[1 + i
],
2836 tab
->mat
->row
[var
->index
][pos
]);
2838 isl_int_set(tab
->dual
->el
[1 + i
],
2839 tab
->mat
->row
[var
->index
][pos
]);
2842 if (opt
&& res
== isl_lp_ok
) {
2844 isl_int_set(*opt
, tab
->mat
->row
[var
->index
][1]);
2845 isl_int_set(*opt_denom
, tab
->mat
->row
[var
->index
][0]);
2847 isl_int_cdiv_q(*opt
, tab
->mat
->row
[var
->index
][1],
2848 tab
->mat
->row
[var
->index
][0]);
2850 if (isl_tab_rollback(tab
, snap
) < 0)
2851 return isl_lp_error
;
2855 int isl_tab_is_redundant(struct isl_tab
*tab
, int con
)
2859 if (tab
->con
[con
].is_zero
)
2861 if (tab
->con
[con
].is_redundant
)
2863 return tab
->con
[con
].is_row
&& tab
->con
[con
].index
< tab
->n_redundant
;
2866 /* Take a snapshot of the tableau that can be restored by s call to
2869 struct isl_tab_undo
*isl_tab_snap(struct isl_tab
*tab
)
2877 /* Undo the operation performed by isl_tab_relax.
2879 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
2880 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2882 unsigned off
= 2 + tab
->M
;
2884 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2885 if (to_row(tab
, var
, 1) < 0)
2889 isl_int_sub(tab
->mat
->row
[var
->index
][1],
2890 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2891 if (var
->is_nonneg
) {
2892 int sgn
= restore_row(tab
, var
);
2893 isl_assert(tab
->mat
->ctx
, sgn
>= 0, return -1);
2898 for (i
= 0; i
< tab
->n_row
; ++i
) {
2899 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2901 isl_int_add(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2902 tab
->mat
->row
[i
][off
+ var
->index
]);
2910 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
2911 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
2913 struct isl_tab_var
*var
= var_from_index(tab
, undo
->u
.var_index
);
2914 switch(undo
->type
) {
2915 case isl_tab_undo_nonneg
:
2918 case isl_tab_undo_redundant
:
2919 var
->is_redundant
= 0;
2921 restore_row(tab
, isl_tab_var_from_row(tab
, tab
->n_redundant
));
2923 case isl_tab_undo_freeze
:
2926 case isl_tab_undo_zero
:
2931 case isl_tab_undo_allocate
:
2932 if (undo
->u
.var_index
>= 0) {
2933 isl_assert(tab
->mat
->ctx
, !var
->is_row
, return -1);
2934 drop_col(tab
, var
->index
);
2938 if (!max_is_manifestly_unbounded(tab
, var
)) {
2939 if (to_row(tab
, var
, 1) < 0)
2941 } else if (!min_is_manifestly_unbounded(tab
, var
)) {
2942 if (to_row(tab
, var
, -1) < 0)
2945 if (to_row(tab
, var
, 0) < 0)
2948 drop_row(tab
, var
->index
);
2950 case isl_tab_undo_relax
:
2951 return unrelax(tab
, var
);
2957 /* Restore the tableau to the state where the basic variables
2958 * are those in "col_var".
2959 * We first construct a list of variables that are currently in
2960 * the basis, but shouldn't. Then we iterate over all variables
2961 * that should be in the basis and for each one that is currently
2962 * not in the basis, we exchange it with one of the elements of the
2963 * list constructed before.
2964 * We can always find an appropriate variable to pivot with because
2965 * the current basis is mapped to the old basis by a non-singular
2966 * matrix and so we can never end up with a zero row.
2968 static int restore_basis(struct isl_tab
*tab
, int *col_var
)
2972 int *extra
= NULL
; /* current columns that contain bad stuff */
2973 unsigned off
= 2 + tab
->M
;
2975 extra
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->n_col
);
2978 for (i
= 0; i
< tab
->n_col
; ++i
) {
2979 for (j
= 0; j
< tab
->n_col
; ++j
)
2980 if (tab
->col_var
[i
] == col_var
[j
])
2984 extra
[n_extra
++] = i
;
2986 for (i
= 0; i
< tab
->n_col
&& n_extra
> 0; ++i
) {
2987 struct isl_tab_var
*var
;
2990 for (j
= 0; j
< tab
->n_col
; ++j
)
2991 if (col_var
[i
] == tab
->col_var
[j
])
2995 var
= var_from_index(tab
, col_var
[i
]);
2997 for (j
= 0; j
< n_extra
; ++j
)
2998 if (!isl_int_is_zero(tab
->mat
->row
[row
][off
+extra
[j
]]))
3000 isl_assert(tab
->mat
->ctx
, j
< n_extra
, goto error
);
3001 if (isl_tab_pivot(tab
, row
, extra
[j
]) < 0)
3003 extra
[j
] = extra
[--n_extra
];
3015 /* Remove all samples with index n or greater, i.e., those samples
3016 * that were added since we saved this number of samples in
3017 * isl_tab_save_samples.
3019 static void drop_samples_since(struct isl_tab
*tab
, int n
)
3023 for (i
= tab
->n_sample
- 1; i
>= 0 && tab
->n_sample
> n
; --i
) {
3024 if (tab
->sample_index
[i
] < n
)
3027 if (i
!= tab
->n_sample
- 1) {
3028 int t
= tab
->sample_index
[tab
->n_sample
-1];
3029 tab
->sample_index
[tab
->n_sample
-1] = tab
->sample_index
[i
];
3030 tab
->sample_index
[i
] = t
;
3031 isl_mat_swap_rows(tab
->samples
, tab
->n_sample
-1, i
);
3037 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
3038 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
3040 switch (undo
->type
) {
3041 case isl_tab_undo_empty
:
3044 case isl_tab_undo_nonneg
:
3045 case isl_tab_undo_redundant
:
3046 case isl_tab_undo_freeze
:
3047 case isl_tab_undo_zero
:
3048 case isl_tab_undo_allocate
:
3049 case isl_tab_undo_relax
:
3050 return perform_undo_var(tab
, undo
);
3051 case isl_tab_undo_bmap_eq
:
3052 return isl_basic_map_free_equality(tab
->bmap
, 1);
3053 case isl_tab_undo_bmap_ineq
:
3054 return isl_basic_map_free_inequality(tab
->bmap
, 1);
3055 case isl_tab_undo_bmap_div
:
3056 if (isl_basic_map_free_div(tab
->bmap
, 1) < 0)
3059 tab
->samples
->n_col
--;
3061 case isl_tab_undo_saved_basis
:
3062 if (restore_basis(tab
, undo
->u
.col_var
) < 0)
3065 case isl_tab_undo_drop_sample
:
3068 case isl_tab_undo_saved_samples
:
3069 drop_samples_since(tab
, undo
->u
.n
);
3071 case isl_tab_undo_callback
:
3072 return undo
->u
.callback
->run(undo
->u
.callback
);
3074 isl_assert(tab
->mat
->ctx
, 0, return -1);
3079 /* Return the tableau to the state it was in when the snapshot "snap"
3082 int isl_tab_rollback(struct isl_tab
*tab
, struct isl_tab_undo
*snap
)
3084 struct isl_tab_undo
*undo
, *next
;
3090 for (undo
= tab
->top
; undo
&& undo
!= &tab
->bottom
; undo
= next
) {
3094 if (perform_undo(tab
, undo
) < 0) {
3109 /* The given row "row" represents an inequality violated by all
3110 * points in the tableau. Check for some special cases of such
3111 * separating constraints.
3112 * In particular, if the row has been reduced to the constant -1,
3113 * then we know the inequality is adjacent (but opposite) to
3114 * an equality in the tableau.
3115 * If the row has been reduced to r = c*(-1 -r'), with r' an inequality
3116 * of the tableau and c a positive constant, then the inequality
3117 * is adjacent (but opposite) to the inequality r'.
3119 static enum isl_ineq_type
separation_type(struct isl_tab
*tab
, unsigned row
)
3122 unsigned off
= 2 + tab
->M
;
3125 return isl_ineq_separate
;
3127 if (!isl_int_is_one(tab
->mat
->row
[row
][0]))
3128 return isl_ineq_separate
;
3130 pos
= isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
3131 tab
->n_col
- tab
->n_dead
);
3133 if (isl_int_is_negone(tab
->mat
->row
[row
][1]))
3134 return isl_ineq_adj_eq
;
3136 return isl_ineq_separate
;
3139 if (!isl_int_eq(tab
->mat
->row
[row
][1],
3140 tab
->mat
->row
[row
][off
+ tab
->n_dead
+ pos
]))
3141 return isl_ineq_separate
;
3143 pos
= isl_seq_first_non_zero(
3144 tab
->mat
->row
[row
] + off
+ tab
->n_dead
+ pos
+ 1,
3145 tab
->n_col
- tab
->n_dead
- pos
- 1);
3147 return pos
== -1 ? isl_ineq_adj_ineq
: isl_ineq_separate
;
3150 /* Check the effect of inequality "ineq" on the tableau "tab".
3152 * isl_ineq_redundant: satisfied by all points in the tableau
3153 * isl_ineq_separate: satisfied by no point in the tableau
3154 * isl_ineq_cut: satisfied by some by not all points
3155 * isl_ineq_adj_eq: adjacent to an equality
3156 * isl_ineq_adj_ineq: adjacent to an inequality.
3158 enum isl_ineq_type
isl_tab_ineq_type(struct isl_tab
*tab
, isl_int
*ineq
)
3160 enum isl_ineq_type type
= isl_ineq_error
;
3161 struct isl_tab_undo
*snap
= NULL
;
3166 return isl_ineq_error
;
3168 if (isl_tab_extend_cons(tab
, 1) < 0)
3169 return isl_ineq_error
;
3171 snap
= isl_tab_snap(tab
);
3173 con
= isl_tab_add_row(tab
, ineq
);
3177 row
= tab
->con
[con
].index
;
3178 if (isl_tab_row_is_redundant(tab
, row
))
3179 type
= isl_ineq_redundant
;
3180 else if (isl_int_is_neg(tab
->mat
->row
[row
][1]) &&
3182 isl_int_abs_ge(tab
->mat
->row
[row
][1],
3183 tab
->mat
->row
[row
][0]))) {
3184 int nonneg
= at_least_zero(tab
, &tab
->con
[con
]);
3188 type
= isl_ineq_cut
;
3190 type
= separation_type(tab
, row
);
3192 int red
= con_is_redundant(tab
, &tab
->con
[con
]);
3196 type
= isl_ineq_cut
;
3198 type
= isl_ineq_redundant
;
3201 if (isl_tab_rollback(tab
, snap
))
3202 return isl_ineq_error
;
3205 return isl_ineq_error
;
3208 int isl_tab_track_bmap(struct isl_tab
*tab
, __isl_take isl_basic_map
*bmap
)
3213 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
3214 isl_assert(tab
->mat
->ctx
,
3215 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
3221 isl_basic_map_free(bmap
);
3225 int isl_tab_track_bset(struct isl_tab
*tab
, __isl_take isl_basic_set
*bset
)
3227 return isl_tab_track_bmap(tab
, (isl_basic_map
*)bset
);
3230 __isl_keep isl_basic_set
*isl_tab_peek_bset(struct isl_tab
*tab
)
3235 return (isl_basic_set
*)tab
->bmap
;
3238 void isl_tab_dump(struct isl_tab
*tab
, FILE *out
, int indent
)
3244 fprintf(out
, "%*snull tab\n", indent
, "");
3247 fprintf(out
, "%*sn_redundant: %d, n_dead: %d", indent
, "",
3248 tab
->n_redundant
, tab
->n_dead
);
3250 fprintf(out
, ", rational");
3252 fprintf(out
, ", empty");
3254 fprintf(out
, "%*s[", indent
, "");
3255 for (i
= 0; i
< tab
->n_var
; ++i
) {
3257 fprintf(out
, (i
== tab
->n_param
||
3258 i
== tab
->n_var
- tab
->n_div
) ? "; "
3260 fprintf(out
, "%c%d%s", tab
->var
[i
].is_row
? 'r' : 'c',
3262 tab
->var
[i
].is_zero
? " [=0]" :
3263 tab
->var
[i
].is_redundant
? " [R]" : "");
3265 fprintf(out
, "]\n");
3266 fprintf(out
, "%*s[", indent
, "");
3267 for (i
= 0; i
< tab
->n_con
; ++i
) {
3270 fprintf(out
, "%c%d%s", tab
->con
[i
].is_row
? 'r' : 'c',
3272 tab
->con
[i
].is_zero
? " [=0]" :
3273 tab
->con
[i
].is_redundant
? " [R]" : "");
3275 fprintf(out
, "]\n");
3276 fprintf(out
, "%*s[", indent
, "");
3277 for (i
= 0; i
< tab
->n_row
; ++i
) {
3278 const char *sign
= "";
3281 if (tab
->row_sign
) {
3282 if (tab
->row_sign
[i
] == isl_tab_row_unknown
)
3284 else if (tab
->row_sign
[i
] == isl_tab_row_neg
)
3286 else if (tab
->row_sign
[i
] == isl_tab_row_pos
)
3291 fprintf(out
, "r%d: %d%s%s", i
, tab
->row_var
[i
],
3292 isl_tab_var_from_row(tab
, i
)->is_nonneg
? " [>=0]" : "", sign
);
3294 fprintf(out
, "]\n");
3295 fprintf(out
, "%*s[", indent
, "");
3296 for (i
= 0; i
< tab
->n_col
; ++i
) {
3299 fprintf(out
, "c%d: %d%s", i
, tab
->col_var
[i
],
3300 var_from_col(tab
, i
)->is_nonneg
? " [>=0]" : "");
3302 fprintf(out
, "]\n");
3303 r
= tab
->mat
->n_row
;
3304 tab
->mat
->n_row
= tab
->n_row
;
3305 c
= tab
->mat
->n_col
;
3306 tab
->mat
->n_col
= 2 + tab
->M
+ tab
->n_col
;
3307 isl_mat_dump(tab
->mat
, out
, indent
);
3308 tab
->mat
->n_row
= r
;
3309 tab
->mat
->n_col
= c
;
3311 isl_basic_map_print_internal(tab
->bmap
, out
, indent
);