2 * Copyright 2008-2009 Katholieke Universiteit Leuven
4 * Use of this software is governed by the GNU LGPLv2.1 license
6 * Written by Sven Verdoolaege, K.U.Leuven, Departement
7 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
11 #include "isl_map_private.h"
16 * The implementation of tableaus in this file was inspired by Section 8
17 * of David Detlefs, Greg Nelson and James B. Saxe, "Simplify: a theorem
18 * prover for program checking".
21 struct isl_tab
*isl_tab_alloc(struct isl_ctx
*ctx
,
22 unsigned n_row
, unsigned n_var
, unsigned M
)
28 tab
= isl_calloc_type(ctx
, struct isl_tab
);
31 tab
->mat
= isl_mat_alloc(ctx
, n_row
, off
+ n_var
);
34 tab
->var
= isl_alloc_array(ctx
, struct isl_tab_var
, n_var
);
37 tab
->con
= isl_alloc_array(ctx
, struct isl_tab_var
, n_row
);
40 tab
->col_var
= isl_alloc_array(ctx
, int, n_var
);
43 tab
->row_var
= isl_alloc_array(ctx
, int, n_row
);
46 for (i
= 0; i
< n_var
; ++i
) {
47 tab
->var
[i
].index
= i
;
48 tab
->var
[i
].is_row
= 0;
49 tab
->var
[i
].is_nonneg
= 0;
50 tab
->var
[i
].is_zero
= 0;
51 tab
->var
[i
].is_redundant
= 0;
52 tab
->var
[i
].frozen
= 0;
53 tab
->var
[i
].negated
= 0;
73 tab
->bottom
.type
= isl_tab_undo_bottom
;
74 tab
->bottom
.next
= NULL
;
75 tab
->top
= &tab
->bottom
;
87 int isl_tab_extend_cons(struct isl_tab
*tab
, unsigned n_new
)
89 unsigned off
= 2 + tab
->M
;
94 if (tab
->max_con
< tab
->n_con
+ n_new
) {
95 struct isl_tab_var
*con
;
97 con
= isl_realloc_array(tab
->mat
->ctx
, tab
->con
,
98 struct isl_tab_var
, tab
->max_con
+ n_new
);
102 tab
->max_con
+= n_new
;
104 if (tab
->mat
->n_row
< tab
->n_row
+ n_new
) {
107 tab
->mat
= isl_mat_extend(tab
->mat
,
108 tab
->n_row
+ n_new
, off
+ tab
->n_col
);
111 row_var
= isl_realloc_array(tab
->mat
->ctx
, tab
->row_var
,
112 int, tab
->mat
->n_row
);
115 tab
->row_var
= row_var
;
117 enum isl_tab_row_sign
*s
;
118 s
= isl_realloc_array(tab
->mat
->ctx
, tab
->row_sign
,
119 enum isl_tab_row_sign
, tab
->mat
->n_row
);
128 /* Make room for at least n_new extra variables.
129 * Return -1 if anything went wrong.
131 int isl_tab_extend_vars(struct isl_tab
*tab
, unsigned n_new
)
133 struct isl_tab_var
*var
;
134 unsigned off
= 2 + tab
->M
;
136 if (tab
->max_var
< tab
->n_var
+ n_new
) {
137 var
= isl_realloc_array(tab
->mat
->ctx
, tab
->var
,
138 struct isl_tab_var
, tab
->n_var
+ n_new
);
142 tab
->max_var
+= n_new
;
145 if (tab
->mat
->n_col
< off
+ tab
->n_col
+ n_new
) {
148 tab
->mat
= isl_mat_extend(tab
->mat
,
149 tab
->mat
->n_row
, off
+ tab
->n_col
+ n_new
);
152 p
= isl_realloc_array(tab
->mat
->ctx
, tab
->col_var
,
153 int, tab
->n_col
+ n_new
);
162 struct isl_tab
*isl_tab_extend(struct isl_tab
*tab
, unsigned n_new
)
164 if (isl_tab_extend_cons(tab
, n_new
) >= 0)
171 static void free_undo(struct isl_tab
*tab
)
173 struct isl_tab_undo
*undo
, *next
;
175 for (undo
= tab
->top
; undo
&& undo
!= &tab
->bottom
; undo
= next
) {
182 void isl_tab_free(struct isl_tab
*tab
)
187 isl_mat_free(tab
->mat
);
188 isl_vec_free(tab
->dual
);
189 isl_basic_map_free(tab
->bmap
);
195 isl_mat_free(tab
->samples
);
196 free(tab
->sample_index
);
197 isl_mat_free(tab
->basis
);
201 struct isl_tab
*isl_tab_dup(struct isl_tab
*tab
)
211 dup
= isl_calloc_type(tab
->ctx
, struct isl_tab
);
214 dup
->mat
= isl_mat_dup(tab
->mat
);
217 dup
->var
= isl_alloc_array(tab
->ctx
, struct isl_tab_var
, tab
->max_var
);
220 for (i
= 0; i
< tab
->n_var
; ++i
)
221 dup
->var
[i
] = tab
->var
[i
];
222 dup
->con
= isl_alloc_array(tab
->ctx
, struct isl_tab_var
, tab
->max_con
);
225 for (i
= 0; i
< tab
->n_con
; ++i
)
226 dup
->con
[i
] = tab
->con
[i
];
227 dup
->col_var
= isl_alloc_array(tab
->ctx
, int, tab
->mat
->n_col
- off
);
230 for (i
= 0; i
< tab
->n_col
; ++i
)
231 dup
->col_var
[i
] = tab
->col_var
[i
];
232 dup
->row_var
= isl_alloc_array(tab
->ctx
, int, tab
->mat
->n_row
);
235 for (i
= 0; i
< tab
->n_row
; ++i
)
236 dup
->row_var
[i
] = tab
->row_var
[i
];
238 dup
->row_sign
= isl_alloc_array(tab
->ctx
, enum isl_tab_row_sign
,
242 for (i
= 0; i
< tab
->n_row
; ++i
)
243 dup
->row_sign
[i
] = tab
->row_sign
[i
];
246 dup
->samples
= isl_mat_dup(tab
->samples
);
249 dup
->sample_index
= isl_alloc_array(tab
->mat
->ctx
, int,
250 tab
->samples
->n_row
);
251 if (!dup
->sample_index
)
253 dup
->n_sample
= tab
->n_sample
;
254 dup
->n_outside
= tab
->n_outside
;
256 dup
->n_row
= tab
->n_row
;
257 dup
->n_con
= tab
->n_con
;
258 dup
->n_eq
= tab
->n_eq
;
259 dup
->max_con
= tab
->max_con
;
260 dup
->n_col
= tab
->n_col
;
261 dup
->n_var
= tab
->n_var
;
262 dup
->max_var
= tab
->max_var
;
263 dup
->n_param
= tab
->n_param
;
264 dup
->n_div
= tab
->n_div
;
265 dup
->n_dead
= tab
->n_dead
;
266 dup
->n_redundant
= tab
->n_redundant
;
267 dup
->rational
= tab
->rational
;
268 dup
->empty
= tab
->empty
;
272 tab
->cone
= tab
->cone
;
273 dup
->bottom
.type
= isl_tab_undo_bottom
;
274 dup
->bottom
.next
= NULL
;
275 dup
->top
= &dup
->bottom
;
277 dup
->n_zero
= tab
->n_zero
;
278 dup
->n_unbounded
= tab
->n_unbounded
;
279 dup
->basis
= isl_mat_dup(tab
->basis
);
287 /* Construct the coefficient matrix of the product tableau
289 * mat{1,2} is the coefficient matrix of tableau {1,2}
290 * row{1,2} is the number of rows in tableau {1,2}
291 * col{1,2} is the number of columns in tableau {1,2}
292 * off is the offset to the coefficient column (skipping the
293 * denominator, the constant term and the big parameter if any)
294 * r{1,2} is the number of redundant rows in tableau {1,2}
295 * d{1,2} is the number of dead columns in tableau {1,2}
297 * The order of the rows and columns in the result is as explained
298 * in isl_tab_product.
300 static struct isl_mat
*tab_mat_product(struct isl_mat
*mat1
,
301 struct isl_mat
*mat2
, unsigned row1
, unsigned row2
,
302 unsigned col1
, unsigned col2
,
303 unsigned off
, unsigned r1
, unsigned r2
, unsigned d1
, unsigned d2
)
306 struct isl_mat
*prod
;
309 prod
= isl_mat_alloc(mat1
->ctx
, mat1
->n_row
+ mat2
->n_row
,
313 for (i
= 0; i
< r1
; ++i
) {
314 isl_seq_cpy(prod
->row
[n
+ i
], mat1
->row
[i
], off
+ d1
);
315 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
, d2
);
316 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
+ d2
,
317 mat1
->row
[i
] + off
+ d1
, col1
- d1
);
318 isl_seq_clr(prod
->row
[n
+ i
] + off
+ col1
+ d1
, col2
- d2
);
322 for (i
= 0; i
< r2
; ++i
) {
323 isl_seq_cpy(prod
->row
[n
+ i
], mat2
->row
[i
], off
);
324 isl_seq_clr(prod
->row
[n
+ i
] + off
, d1
);
325 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
,
326 mat2
->row
[i
] + off
, d2
);
327 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
+ d2
, col1
- d1
);
328 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ col1
+ d1
,
329 mat2
->row
[i
] + off
+ d2
, col2
- d2
);
333 for (i
= 0; i
< row1
- r1
; ++i
) {
334 isl_seq_cpy(prod
->row
[n
+ i
], mat1
->row
[r1
+ i
], off
+ d1
);
335 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
, d2
);
336 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
+ d2
,
337 mat1
->row
[r1
+ i
] + off
+ d1
, col1
- d1
);
338 isl_seq_clr(prod
->row
[n
+ i
] + off
+ col1
+ d1
, col2
- d2
);
342 for (i
= 0; i
< row2
- r2
; ++i
) {
343 isl_seq_cpy(prod
->row
[n
+ i
], mat2
->row
[r2
+ i
], off
);
344 isl_seq_clr(prod
->row
[n
+ i
] + off
, d1
);
345 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ d1
,
346 mat2
->row
[r2
+ i
] + off
, d2
);
347 isl_seq_clr(prod
->row
[n
+ i
] + off
+ d1
+ d2
, col1
- d1
);
348 isl_seq_cpy(prod
->row
[n
+ i
] + off
+ col1
+ d1
,
349 mat2
->row
[r2
+ i
] + off
+ d2
, col2
- d2
);
355 /* Update the row or column index of a variable that corresponds
356 * to a variable in the first input tableau.
358 static void update_index1(struct isl_tab_var
*var
,
359 unsigned r1
, unsigned r2
, unsigned d1
, unsigned d2
)
361 if (var
->index
== -1)
363 if (var
->is_row
&& var
->index
>= r1
)
365 if (!var
->is_row
&& var
->index
>= d1
)
369 /* Update the row or column index of a variable that corresponds
370 * to a variable in the second input tableau.
372 static void update_index2(struct isl_tab_var
*var
,
373 unsigned row1
, unsigned col1
,
374 unsigned r1
, unsigned r2
, unsigned d1
, unsigned d2
)
376 if (var
->index
== -1)
391 /* Create a tableau that represents the Cartesian product of the sets
392 * represented by tableaus tab1 and tab2.
393 * The order of the rows in the product is
394 * - redundant rows of tab1
395 * - redundant rows of tab2
396 * - non-redundant rows of tab1
397 * - non-redundant rows of tab2
398 * The order of the columns is
401 * - coefficient of big parameter, if any
402 * - dead columns of tab1
403 * - dead columns of tab2
404 * - live columns of tab1
405 * - live columns of tab2
406 * The order of the variables and the constraints is a concatenation
407 * of order in the two input tableaus.
409 struct isl_tab
*isl_tab_product(struct isl_tab
*tab1
, struct isl_tab
*tab2
)
412 struct isl_tab
*prod
;
414 unsigned r1
, r2
, d1
, d2
;
419 isl_assert(tab1
->mat
->ctx
, tab1
->M
== tab2
->M
, return NULL
);
420 isl_assert(tab1
->mat
->ctx
, tab1
->rational
== tab2
->rational
, return NULL
);
421 isl_assert(tab1
->mat
->ctx
, tab1
->cone
== tab2
->cone
, return NULL
);
422 isl_assert(tab1
->mat
->ctx
, !tab1
->row_sign
, return NULL
);
423 isl_assert(tab1
->mat
->ctx
, !tab2
->row_sign
, return NULL
);
424 isl_assert(tab1
->mat
->ctx
, tab1
->n_param
== 0, return NULL
);
425 isl_assert(tab1
->mat
->ctx
, tab2
->n_param
== 0, return NULL
);
426 isl_assert(tab1
->mat
->ctx
, tab1
->n_div
== 0, return NULL
);
427 isl_assert(tab1
->mat
->ctx
, tab2
->n_div
== 0, return NULL
);
430 r1
= tab1
->n_redundant
;
431 r2
= tab2
->n_redundant
;
434 prod
= isl_calloc_type(tab1
->mat
->ctx
, struct isl_tab
);
437 prod
->mat
= tab_mat_product(tab1
->mat
, tab2
->mat
,
438 tab1
->n_row
, tab2
->n_row
,
439 tab1
->n_col
, tab2
->n_col
, off
, r1
, r2
, d1
, d2
);
442 prod
->var
= isl_alloc_array(tab1
->mat
->ctx
, struct isl_tab_var
,
443 tab1
->max_var
+ tab2
->max_var
);
446 for (i
= 0; i
< tab1
->n_var
; ++i
) {
447 prod
->var
[i
] = tab1
->var
[i
];
448 update_index1(&prod
->var
[i
], r1
, r2
, d1
, d2
);
450 for (i
= 0; i
< tab2
->n_var
; ++i
) {
451 prod
->var
[tab1
->n_var
+ i
] = tab2
->var
[i
];
452 update_index2(&prod
->var
[tab1
->n_var
+ i
],
453 tab1
->n_row
, tab1
->n_col
,
456 prod
->con
= isl_alloc_array(tab1
->mat
->ctx
, struct isl_tab_var
,
457 tab1
->max_con
+ tab2
->max_con
);
460 for (i
= 0; i
< tab1
->n_con
; ++i
) {
461 prod
->con
[i
] = tab1
->con
[i
];
462 update_index1(&prod
->con
[i
], r1
, r2
, d1
, d2
);
464 for (i
= 0; i
< tab2
->n_con
; ++i
) {
465 prod
->con
[tab1
->n_con
+ i
] = tab2
->con
[i
];
466 update_index2(&prod
->con
[tab1
->n_con
+ i
],
467 tab1
->n_row
, tab1
->n_col
,
470 prod
->col_var
= isl_alloc_array(tab1
->mat
->ctx
, int,
471 tab1
->n_col
+ tab2
->n_col
);
474 for (i
= 0; i
< tab1
->n_col
; ++i
) {
475 int pos
= i
< d1
? i
: i
+ d2
;
476 prod
->col_var
[pos
] = tab1
->col_var
[i
];
478 for (i
= 0; i
< tab2
->n_col
; ++i
) {
479 int pos
= i
< d2
? d1
+ i
: tab1
->n_col
+ i
;
480 int t
= tab2
->col_var
[i
];
485 prod
->col_var
[pos
] = t
;
487 prod
->row_var
= isl_alloc_array(tab1
->mat
->ctx
, int,
488 tab1
->mat
->n_row
+ tab2
->mat
->n_row
);
491 for (i
= 0; i
< tab1
->n_row
; ++i
) {
492 int pos
= i
< r1
? i
: i
+ r2
;
493 prod
->row_var
[pos
] = tab1
->row_var
[i
];
495 for (i
= 0; i
< tab2
->n_row
; ++i
) {
496 int pos
= i
< r2
? r1
+ i
: tab1
->n_row
+ i
;
497 int t
= tab2
->row_var
[i
];
502 prod
->row_var
[pos
] = t
;
504 prod
->samples
= NULL
;
505 prod
->sample_index
= NULL
;
506 prod
->n_row
= tab1
->n_row
+ tab2
->n_row
;
507 prod
->n_con
= tab1
->n_con
+ tab2
->n_con
;
509 prod
->max_con
= tab1
->max_con
+ tab2
->max_con
;
510 prod
->n_col
= tab1
->n_col
+ tab2
->n_col
;
511 prod
->n_var
= tab1
->n_var
+ tab2
->n_var
;
512 prod
->max_var
= tab1
->max_var
+ tab2
->max_var
;
515 prod
->n_dead
= tab1
->n_dead
+ tab2
->n_dead
;
516 prod
->n_redundant
= tab1
->n_redundant
+ tab2
->n_redundant
;
517 prod
->rational
= tab1
->rational
;
518 prod
->empty
= tab1
->empty
|| tab2
->empty
;
522 prod
->cone
= tab1
->cone
;
523 prod
->bottom
.type
= isl_tab_undo_bottom
;
524 prod
->bottom
.next
= NULL
;
525 prod
->top
= &prod
->bottom
;
528 prod
->n_unbounded
= 0;
537 static struct isl_tab_var
*var_from_index(struct isl_tab
*tab
, int i
)
542 return &tab
->con
[~i
];
545 struct isl_tab_var
*isl_tab_var_from_row(struct isl_tab
*tab
, int i
)
547 return var_from_index(tab
, tab
->row_var
[i
]);
550 static struct isl_tab_var
*var_from_col(struct isl_tab
*tab
, int i
)
552 return var_from_index(tab
, tab
->col_var
[i
]);
555 /* Check if there are any upper bounds on column variable "var",
556 * i.e., non-negative rows where var appears with a negative coefficient.
557 * Return 1 if there are no such bounds.
559 static int max_is_manifestly_unbounded(struct isl_tab
*tab
,
560 struct isl_tab_var
*var
)
563 unsigned off
= 2 + tab
->M
;
567 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
568 if (!isl_int_is_neg(tab
->mat
->row
[i
][off
+ var
->index
]))
570 if (isl_tab_var_from_row(tab
, i
)->is_nonneg
)
576 /* Check if there are any lower bounds on column variable "var",
577 * i.e., non-negative rows where var appears with a positive coefficient.
578 * Return 1 if there are no such bounds.
580 static int min_is_manifestly_unbounded(struct isl_tab
*tab
,
581 struct isl_tab_var
*var
)
584 unsigned off
= 2 + tab
->M
;
588 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
589 if (!isl_int_is_pos(tab
->mat
->row
[i
][off
+ var
->index
]))
591 if (isl_tab_var_from_row(tab
, i
)->is_nonneg
)
597 static int row_cmp(struct isl_tab
*tab
, int r1
, int r2
, int c
, isl_int t
)
599 unsigned off
= 2 + tab
->M
;
603 isl_int_mul(t
, tab
->mat
->row
[r1
][2], tab
->mat
->row
[r2
][off
+c
]);
604 isl_int_submul(t
, tab
->mat
->row
[r2
][2], tab
->mat
->row
[r1
][off
+c
]);
609 isl_int_mul(t
, tab
->mat
->row
[r1
][1], tab
->mat
->row
[r2
][off
+ c
]);
610 isl_int_submul(t
, tab
->mat
->row
[r2
][1], tab
->mat
->row
[r1
][off
+ c
]);
611 return isl_int_sgn(t
);
614 /* Given the index of a column "c", return the index of a row
615 * that can be used to pivot the column in, with either an increase
616 * (sgn > 0) or a decrease (sgn < 0) of the corresponding variable.
617 * If "var" is not NULL, then the row returned will be different from
618 * the one associated with "var".
620 * Each row in the tableau is of the form
622 * x_r = a_r0 + \sum_i a_ri x_i
624 * Only rows with x_r >= 0 and with the sign of a_ri opposite to "sgn"
625 * impose any limit on the increase or decrease in the value of x_c
626 * and this bound is equal to a_r0 / |a_rc|. We are therefore looking
627 * for the row with the smallest (most stringent) such bound.
628 * Note that the common denominator of each row drops out of the fraction.
629 * To check if row j has a smaller bound than row r, i.e.,
630 * a_j0 / |a_jc| < a_r0 / |a_rc| or a_j0 |a_rc| < a_r0 |a_jc|,
631 * we check if -sign(a_jc) (a_j0 a_rc - a_r0 a_jc) < 0,
632 * where -sign(a_jc) is equal to "sgn".
634 static int pivot_row(struct isl_tab
*tab
,
635 struct isl_tab_var
*var
, int sgn
, int c
)
639 unsigned off
= 2 + tab
->M
;
643 for (j
= tab
->n_redundant
; j
< tab
->n_row
; ++j
) {
644 if (var
&& j
== var
->index
)
646 if (!isl_tab_var_from_row(tab
, j
)->is_nonneg
)
648 if (sgn
* isl_int_sgn(tab
->mat
->row
[j
][off
+ c
]) >= 0)
654 tsgn
= sgn
* row_cmp(tab
, r
, j
, c
, t
);
655 if (tsgn
< 0 || (tsgn
== 0 &&
656 tab
->row_var
[j
] < tab
->row_var
[r
]))
663 /* Find a pivot (row and col) that will increase (sgn > 0) or decrease
664 * (sgn < 0) the value of row variable var.
665 * If not NULL, then skip_var is a row variable that should be ignored
666 * while looking for a pivot row. It is usually equal to var.
668 * As the given row in the tableau is of the form
670 * x_r = a_r0 + \sum_i a_ri x_i
672 * we need to find a column such that the sign of a_ri is equal to "sgn"
673 * (such that an increase in x_i will have the desired effect) or a
674 * column with a variable that may attain negative values.
675 * If a_ri is positive, then we need to move x_i in the same direction
676 * to obtain the desired effect. Otherwise, x_i has to move in the
677 * opposite direction.
679 static void find_pivot(struct isl_tab
*tab
,
680 struct isl_tab_var
*var
, struct isl_tab_var
*skip_var
,
681 int sgn
, int *row
, int *col
)
688 isl_assert(tab
->mat
->ctx
, var
->is_row
, return);
689 tr
= tab
->mat
->row
[var
->index
] + 2 + tab
->M
;
692 for (j
= tab
->n_dead
; j
< tab
->n_col
; ++j
) {
693 if (isl_int_is_zero(tr
[j
]))
695 if (isl_int_sgn(tr
[j
]) != sgn
&&
696 var_from_col(tab
, j
)->is_nonneg
)
698 if (c
< 0 || tab
->col_var
[j
] < tab
->col_var
[c
])
704 sgn
*= isl_int_sgn(tr
[c
]);
705 r
= pivot_row(tab
, skip_var
, sgn
, c
);
706 *row
= r
< 0 ? var
->index
: r
;
710 /* Return 1 if row "row" represents an obviously redundant inequality.
712 * - it represents an inequality or a variable
713 * - that is the sum of a non-negative sample value and a positive
714 * combination of zero or more non-negative constraints.
716 int isl_tab_row_is_redundant(struct isl_tab
*tab
, int row
)
719 unsigned off
= 2 + tab
->M
;
721 if (tab
->row_var
[row
] < 0 && !isl_tab_var_from_row(tab
, row
)->is_nonneg
)
724 if (isl_int_is_neg(tab
->mat
->row
[row
][1]))
726 if (tab
->M
&& isl_int_is_neg(tab
->mat
->row
[row
][2]))
729 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
730 if (isl_int_is_zero(tab
->mat
->row
[row
][off
+ i
]))
732 if (tab
->col_var
[i
] >= 0)
734 if (isl_int_is_neg(tab
->mat
->row
[row
][off
+ i
]))
736 if (!var_from_col(tab
, i
)->is_nonneg
)
742 static void swap_rows(struct isl_tab
*tab
, int row1
, int row2
)
745 enum isl_tab_row_sign s
;
747 t
= tab
->row_var
[row1
];
748 tab
->row_var
[row1
] = tab
->row_var
[row2
];
749 tab
->row_var
[row2
] = t
;
750 isl_tab_var_from_row(tab
, row1
)->index
= row1
;
751 isl_tab_var_from_row(tab
, row2
)->index
= row2
;
752 tab
->mat
= isl_mat_swap_rows(tab
->mat
, row1
, row2
);
756 s
= tab
->row_sign
[row1
];
757 tab
->row_sign
[row1
] = tab
->row_sign
[row2
];
758 tab
->row_sign
[row2
] = s
;
761 static int push_union(struct isl_tab
*tab
,
762 enum isl_tab_undo_type type
, union isl_tab_undo_val u
) WARN_UNUSED
;
763 static int push_union(struct isl_tab
*tab
,
764 enum isl_tab_undo_type type
, union isl_tab_undo_val u
)
766 struct isl_tab_undo
*undo
;
771 undo
= isl_alloc_type(tab
->mat
->ctx
, struct isl_tab_undo
);
776 undo
->next
= tab
->top
;
782 int isl_tab_push_var(struct isl_tab
*tab
,
783 enum isl_tab_undo_type type
, struct isl_tab_var
*var
)
785 union isl_tab_undo_val u
;
787 u
.var_index
= tab
->row_var
[var
->index
];
789 u
.var_index
= tab
->col_var
[var
->index
];
790 return push_union(tab
, type
, u
);
793 int isl_tab_push(struct isl_tab
*tab
, enum isl_tab_undo_type type
)
795 union isl_tab_undo_val u
= { 0 };
796 return push_union(tab
, type
, u
);
799 /* Push a record on the undo stack describing the current basic
800 * variables, so that the this state can be restored during rollback.
802 int isl_tab_push_basis(struct isl_tab
*tab
)
805 union isl_tab_undo_val u
;
807 u
.col_var
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->n_col
);
810 for (i
= 0; i
< tab
->n_col
; ++i
)
811 u
.col_var
[i
] = tab
->col_var
[i
];
812 return push_union(tab
, isl_tab_undo_saved_basis
, u
);
815 int isl_tab_push_callback(struct isl_tab
*tab
, struct isl_tab_callback
*callback
)
817 union isl_tab_undo_val u
;
818 u
.callback
= callback
;
819 return push_union(tab
, isl_tab_undo_callback
, u
);
822 struct isl_tab
*isl_tab_init_samples(struct isl_tab
*tab
)
829 tab
->samples
= isl_mat_alloc(tab
->mat
->ctx
, 1, 1 + tab
->n_var
);
832 tab
->sample_index
= isl_alloc_array(tab
->mat
->ctx
, int, 1);
833 if (!tab
->sample_index
)
841 struct isl_tab
*isl_tab_add_sample(struct isl_tab
*tab
,
842 __isl_take isl_vec
*sample
)
847 if (tab
->n_sample
+ 1 > tab
->samples
->n_row
) {
848 int *t
= isl_realloc_array(tab
->mat
->ctx
,
849 tab
->sample_index
, int, tab
->n_sample
+ 1);
852 tab
->sample_index
= t
;
855 tab
->samples
= isl_mat_extend(tab
->samples
,
856 tab
->n_sample
+ 1, tab
->samples
->n_col
);
860 isl_seq_cpy(tab
->samples
->row
[tab
->n_sample
], sample
->el
, sample
->size
);
861 isl_vec_free(sample
);
862 tab
->sample_index
[tab
->n_sample
] = tab
->n_sample
;
867 isl_vec_free(sample
);
872 struct isl_tab
*isl_tab_drop_sample(struct isl_tab
*tab
, int s
)
874 if (s
!= tab
->n_outside
) {
875 int t
= tab
->sample_index
[tab
->n_outside
];
876 tab
->sample_index
[tab
->n_outside
] = tab
->sample_index
[s
];
877 tab
->sample_index
[s
] = t
;
878 isl_mat_swap_rows(tab
->samples
, tab
->n_outside
, s
);
881 if (isl_tab_push(tab
, isl_tab_undo_drop_sample
) < 0) {
889 /* Record the current number of samples so that we can remove newer
890 * samples during a rollback.
892 int isl_tab_save_samples(struct isl_tab
*tab
)
894 union isl_tab_undo_val u
;
900 return push_union(tab
, isl_tab_undo_saved_samples
, u
);
903 /* Mark row with index "row" as being redundant.
904 * If we may need to undo the operation or if the row represents
905 * a variable of the original problem, the row is kept,
906 * but no longer considered when looking for a pivot row.
907 * Otherwise, the row is simply removed.
909 * The row may be interchanged with some other row. If it
910 * is interchanged with a later row, return 1. Otherwise return 0.
911 * If the rows are checked in order in the calling function,
912 * then a return value of 1 means that the row with the given
913 * row number may now contain a different row that hasn't been checked yet.
915 int isl_tab_mark_redundant(struct isl_tab
*tab
, int row
)
917 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, row
);
918 var
->is_redundant
= 1;
919 isl_assert(tab
->mat
->ctx
, row
>= tab
->n_redundant
, return -1);
920 if (tab
->need_undo
|| tab
->row_var
[row
] >= 0) {
921 if (tab
->row_var
[row
] >= 0 && !var
->is_nonneg
) {
923 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, var
) < 0)
926 if (row
!= tab
->n_redundant
)
927 swap_rows(tab
, row
, tab
->n_redundant
);
929 return isl_tab_push_var(tab
, isl_tab_undo_redundant
, var
);
931 if (row
!= tab
->n_row
- 1)
932 swap_rows(tab
, row
, tab
->n_row
- 1);
933 isl_tab_var_from_row(tab
, tab
->n_row
- 1)->index
= -1;
939 int isl_tab_mark_empty(struct isl_tab
*tab
)
943 if (!tab
->empty
&& tab
->need_undo
)
944 if (isl_tab_push(tab
, isl_tab_undo_empty
) < 0)
950 int isl_tab_freeze_constraint(struct isl_tab
*tab
, int con
)
952 struct isl_tab_var
*var
;
957 var
= &tab
->con
[con
];
965 return isl_tab_push_var(tab
, isl_tab_undo_freeze
, var
);
970 /* Update the rows signs after a pivot of "row" and "col", with "row_sgn"
971 * the original sign of the pivot element.
972 * We only keep track of row signs during PILP solving and in this case
973 * we only pivot a row with negative sign (meaning the value is always
974 * non-positive) using a positive pivot element.
976 * For each row j, the new value of the parametric constant is equal to
978 * a_j0 - a_jc a_r0/a_rc
980 * where a_j0 is the original parametric constant, a_rc is the pivot element,
981 * a_r0 is the parametric constant of the pivot row and a_jc is the
982 * pivot column entry of the row j.
983 * Since a_r0 is non-positive and a_rc is positive, the sign of row j
984 * remains the same if a_jc has the same sign as the row j or if
985 * a_jc is zero. In all other cases, we reset the sign to "unknown".
987 static void update_row_sign(struct isl_tab
*tab
, int row
, int col
, int row_sgn
)
990 struct isl_mat
*mat
= tab
->mat
;
991 unsigned off
= 2 + tab
->M
;
996 if (tab
->row_sign
[row
] == 0)
998 isl_assert(mat
->ctx
, row_sgn
> 0, return);
999 isl_assert(mat
->ctx
, tab
->row_sign
[row
] == isl_tab_row_neg
, return);
1000 tab
->row_sign
[row
] = isl_tab_row_pos
;
1001 for (i
= 0; i
< tab
->n_row
; ++i
) {
1005 s
= isl_int_sgn(mat
->row
[i
][off
+ col
]);
1008 if (!tab
->row_sign
[i
])
1010 if (s
< 0 && tab
->row_sign
[i
] == isl_tab_row_neg
)
1012 if (s
> 0 && tab
->row_sign
[i
] == isl_tab_row_pos
)
1014 tab
->row_sign
[i
] = isl_tab_row_unknown
;
1018 /* Given a row number "row" and a column number "col", pivot the tableau
1019 * such that the associated variables are interchanged.
1020 * The given row in the tableau expresses
1022 * x_r = a_r0 + \sum_i a_ri x_i
1026 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
1028 * Substituting this equality into the other rows
1030 * x_j = a_j0 + \sum_i a_ji x_i
1032 * with a_jc \ne 0, we obtain
1034 * x_j = a_jc/a_rc x_r + a_j0 - a_jc a_r0/a_rc + sum a_ji - a_jc a_ri/a_rc
1041 * where i is any other column and j is any other row,
1042 * is therefore transformed into
1044 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1045 * s(n_rc)d_r n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1047 * The transformation is performed along the following steps
1049 * d_r/n_rc n_ri/n_rc
1052 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1055 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1056 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
1058 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1059 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
1061 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1062 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1064 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1065 * s(n_rc)d_r n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1068 int isl_tab_pivot(struct isl_tab
*tab
, int row
, int col
)
1073 struct isl_mat
*mat
= tab
->mat
;
1074 struct isl_tab_var
*var
;
1075 unsigned off
= 2 + tab
->M
;
1077 isl_int_swap(mat
->row
[row
][0], mat
->row
[row
][off
+ col
]);
1078 sgn
= isl_int_sgn(mat
->row
[row
][0]);
1080 isl_int_neg(mat
->row
[row
][0], mat
->row
[row
][0]);
1081 isl_int_neg(mat
->row
[row
][off
+ col
], mat
->row
[row
][off
+ col
]);
1083 for (j
= 0; j
< off
- 1 + tab
->n_col
; ++j
) {
1084 if (j
== off
- 1 + col
)
1086 isl_int_neg(mat
->row
[row
][1 + j
], mat
->row
[row
][1 + j
]);
1088 if (!isl_int_is_one(mat
->row
[row
][0]))
1089 isl_seq_normalize(mat
->ctx
, mat
->row
[row
], off
+ tab
->n_col
);
1090 for (i
= 0; i
< tab
->n_row
; ++i
) {
1093 if (isl_int_is_zero(mat
->row
[i
][off
+ col
]))
1095 isl_int_mul(mat
->row
[i
][0], mat
->row
[i
][0], mat
->row
[row
][0]);
1096 for (j
= 0; j
< off
- 1 + tab
->n_col
; ++j
) {
1097 if (j
== off
- 1 + col
)
1099 isl_int_mul(mat
->row
[i
][1 + j
],
1100 mat
->row
[i
][1 + j
], mat
->row
[row
][0]);
1101 isl_int_addmul(mat
->row
[i
][1 + j
],
1102 mat
->row
[i
][off
+ col
], mat
->row
[row
][1 + j
]);
1104 isl_int_mul(mat
->row
[i
][off
+ col
],
1105 mat
->row
[i
][off
+ col
], mat
->row
[row
][off
+ col
]);
1106 if (!isl_int_is_one(mat
->row
[i
][0]))
1107 isl_seq_normalize(mat
->ctx
, mat
->row
[i
], off
+ tab
->n_col
);
1109 t
= tab
->row_var
[row
];
1110 tab
->row_var
[row
] = tab
->col_var
[col
];
1111 tab
->col_var
[col
] = t
;
1112 var
= isl_tab_var_from_row(tab
, row
);
1115 var
= var_from_col(tab
, col
);
1118 update_row_sign(tab
, row
, col
, sgn
);
1121 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
1122 if (isl_int_is_zero(mat
->row
[i
][off
+ col
]))
1124 if (!isl_tab_var_from_row(tab
, i
)->frozen
&&
1125 isl_tab_row_is_redundant(tab
, i
)) {
1126 int redo
= isl_tab_mark_redundant(tab
, i
);
1136 /* If "var" represents a column variable, then pivot is up (sgn > 0)
1137 * or down (sgn < 0) to a row. The variable is assumed not to be
1138 * unbounded in the specified direction.
1139 * If sgn = 0, then the variable is unbounded in both directions,
1140 * and we pivot with any row we can find.
1142 static int to_row(struct isl_tab
*tab
, struct isl_tab_var
*var
, int sign
) WARN_UNUSED
;
1143 static int to_row(struct isl_tab
*tab
, struct isl_tab_var
*var
, int sign
)
1146 unsigned off
= 2 + tab
->M
;
1152 for (r
= tab
->n_redundant
; r
< tab
->n_row
; ++r
)
1153 if (!isl_int_is_zero(tab
->mat
->row
[r
][off
+var
->index
]))
1155 isl_assert(tab
->mat
->ctx
, r
< tab
->n_row
, return -1);
1157 r
= pivot_row(tab
, NULL
, sign
, var
->index
);
1158 isl_assert(tab
->mat
->ctx
, r
>= 0, return -1);
1161 return isl_tab_pivot(tab
, r
, var
->index
);
1164 static void check_table(struct isl_tab
*tab
)
1170 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
1171 struct isl_tab_var
*var
;
1172 var
= isl_tab_var_from_row(tab
, i
);
1173 if (!var
->is_nonneg
)
1176 assert(!isl_int_is_neg(tab
->mat
->row
[i
][2]));
1177 if (isl_int_is_pos(tab
->mat
->row
[i
][2]))
1180 assert(!isl_int_is_neg(tab
->mat
->row
[i
][1]));
1184 /* Return the sign of the maximal value of "var".
1185 * If the sign is not negative, then on return from this function,
1186 * the sample value will also be non-negative.
1188 * If "var" is manifestly unbounded wrt positive values, we are done.
1189 * Otherwise, we pivot the variable up to a row if needed
1190 * Then we continue pivoting down until either
1191 * - no more down pivots can be performed
1192 * - the sample value is positive
1193 * - the variable is pivoted into a manifestly unbounded column
1195 static int sign_of_max(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1199 if (max_is_manifestly_unbounded(tab
, var
))
1201 if (to_row(tab
, var
, 1) < 0)
1203 while (!isl_int_is_pos(tab
->mat
->row
[var
->index
][1])) {
1204 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1206 return isl_int_sgn(tab
->mat
->row
[var
->index
][1]);
1207 if (isl_tab_pivot(tab
, row
, col
) < 0)
1209 if (!var
->is_row
) /* manifestly unbounded */
1215 static int row_is_neg(struct isl_tab
*tab
, int row
)
1218 return isl_int_is_neg(tab
->mat
->row
[row
][1]);
1219 if (isl_int_is_pos(tab
->mat
->row
[row
][2]))
1221 if (isl_int_is_neg(tab
->mat
->row
[row
][2]))
1223 return isl_int_is_neg(tab
->mat
->row
[row
][1]);
1226 static int row_sgn(struct isl_tab
*tab
, int row
)
1229 return isl_int_sgn(tab
->mat
->row
[row
][1]);
1230 if (!isl_int_is_zero(tab
->mat
->row
[row
][2]))
1231 return isl_int_sgn(tab
->mat
->row
[row
][2]);
1233 return isl_int_sgn(tab
->mat
->row
[row
][1]);
1236 /* Perform pivots until the row variable "var" has a non-negative
1237 * sample value or until no more upward pivots can be performed.
1238 * Return the sign of the sample value after the pivots have been
1241 static int restore_row(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1245 while (row_is_neg(tab
, var
->index
)) {
1246 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1249 if (isl_tab_pivot(tab
, row
, col
) < 0)
1251 if (!var
->is_row
) /* manifestly unbounded */
1254 return row_sgn(tab
, var
->index
);
1257 /* Perform pivots until we are sure that the row variable "var"
1258 * can attain non-negative values. After return from this
1259 * function, "var" is still a row variable, but its sample
1260 * value may not be non-negative, even if the function returns 1.
1262 static int at_least_zero(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1266 while (isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1267 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1270 if (row
== var
->index
) /* manifestly unbounded */
1272 if (isl_tab_pivot(tab
, row
, col
) < 0)
1275 return !isl_int_is_neg(tab
->mat
->row
[var
->index
][1]);
1278 /* Return a negative value if "var" can attain negative values.
1279 * Return a non-negative value otherwise.
1281 * If "var" is manifestly unbounded wrt negative values, we are done.
1282 * Otherwise, if var is in a column, we can pivot it down to a row.
1283 * Then we continue pivoting down until either
1284 * - the pivot would result in a manifestly unbounded column
1285 * => we don't perform the pivot, but simply return -1
1286 * - no more down pivots can be performed
1287 * - the sample value is negative
1288 * If the sample value becomes negative and the variable is supposed
1289 * to be nonnegative, then we undo the last pivot.
1290 * However, if the last pivot has made the pivoting variable
1291 * obviously redundant, then it may have moved to another row.
1292 * In that case we look for upward pivots until we reach a non-negative
1295 static int sign_of_min(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1298 struct isl_tab_var
*pivot_var
= NULL
;
1300 if (min_is_manifestly_unbounded(tab
, var
))
1304 row
= pivot_row(tab
, NULL
, -1, col
);
1305 pivot_var
= var_from_col(tab
, col
);
1306 if (isl_tab_pivot(tab
, row
, col
) < 0)
1308 if (var
->is_redundant
)
1310 if (isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1311 if (var
->is_nonneg
) {
1312 if (!pivot_var
->is_redundant
&&
1313 pivot_var
->index
== row
) {
1314 if (isl_tab_pivot(tab
, row
, col
) < 0)
1317 if (restore_row(tab
, var
) < -1)
1323 if (var
->is_redundant
)
1325 while (!isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1326 find_pivot(tab
, var
, var
, -1, &row
, &col
);
1327 if (row
== var
->index
)
1330 return isl_int_sgn(tab
->mat
->row
[var
->index
][1]);
1331 pivot_var
= var_from_col(tab
, col
);
1332 if (isl_tab_pivot(tab
, row
, col
) < 0)
1334 if (var
->is_redundant
)
1337 if (pivot_var
&& var
->is_nonneg
) {
1338 /* pivot back to non-negative value */
1339 if (!pivot_var
->is_redundant
&& pivot_var
->index
== row
) {
1340 if (isl_tab_pivot(tab
, row
, col
) < 0)
1343 if (restore_row(tab
, var
) < -1)
1349 static int row_at_most_neg_one(struct isl_tab
*tab
, int row
)
1352 if (isl_int_is_pos(tab
->mat
->row
[row
][2]))
1354 if (isl_int_is_neg(tab
->mat
->row
[row
][2]))
1357 return isl_int_is_neg(tab
->mat
->row
[row
][1]) &&
1358 isl_int_abs_ge(tab
->mat
->row
[row
][1],
1359 tab
->mat
->row
[row
][0]);
1362 /* Return 1 if "var" can attain values <= -1.
1363 * Return 0 otherwise.
1365 * The sample value of "var" is assumed to be non-negative when the
1366 * the function is called. If 1 is returned then the constraint
1367 * is not redundant and the sample value is made non-negative again before
1368 * the function returns.
1370 int isl_tab_min_at_most_neg_one(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1373 struct isl_tab_var
*pivot_var
;
1375 if (min_is_manifestly_unbounded(tab
, var
))
1379 row
= pivot_row(tab
, NULL
, -1, col
);
1380 pivot_var
= var_from_col(tab
, col
);
1381 if (isl_tab_pivot(tab
, row
, col
) < 0)
1383 if (var
->is_redundant
)
1385 if (row_at_most_neg_one(tab
, var
->index
)) {
1386 if (var
->is_nonneg
) {
1387 if (!pivot_var
->is_redundant
&&
1388 pivot_var
->index
== row
) {
1389 if (isl_tab_pivot(tab
, row
, col
) < 0)
1392 if (restore_row(tab
, var
) < -1)
1398 if (var
->is_redundant
)
1401 find_pivot(tab
, var
, var
, -1, &row
, &col
);
1402 if (row
== var
->index
) {
1403 if (restore_row(tab
, var
) < -1)
1409 pivot_var
= var_from_col(tab
, col
);
1410 if (isl_tab_pivot(tab
, row
, col
) < 0)
1412 if (var
->is_redundant
)
1414 } while (!row_at_most_neg_one(tab
, var
->index
));
1415 if (var
->is_nonneg
) {
1416 /* pivot back to non-negative value */
1417 if (!pivot_var
->is_redundant
&& pivot_var
->index
== row
)
1418 if (isl_tab_pivot(tab
, row
, col
) < 0)
1420 if (restore_row(tab
, var
) < -1)
1426 /* Return 1 if "var" can attain values >= 1.
1427 * Return 0 otherwise.
1429 static int at_least_one(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1434 if (max_is_manifestly_unbounded(tab
, var
))
1436 if (to_row(tab
, var
, 1) < 0)
1438 r
= tab
->mat
->row
[var
->index
];
1439 while (isl_int_lt(r
[1], r
[0])) {
1440 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1442 return isl_int_ge(r
[1], r
[0]);
1443 if (row
== var
->index
) /* manifestly unbounded */
1445 if (isl_tab_pivot(tab
, row
, col
) < 0)
1451 static void swap_cols(struct isl_tab
*tab
, int col1
, int col2
)
1454 unsigned off
= 2 + tab
->M
;
1455 t
= tab
->col_var
[col1
];
1456 tab
->col_var
[col1
] = tab
->col_var
[col2
];
1457 tab
->col_var
[col2
] = t
;
1458 var_from_col(tab
, col1
)->index
= col1
;
1459 var_from_col(tab
, col2
)->index
= col2
;
1460 tab
->mat
= isl_mat_swap_cols(tab
->mat
, off
+ col1
, off
+ col2
);
1463 /* Mark column with index "col" as representing a zero variable.
1464 * If we may need to undo the operation the column is kept,
1465 * but no longer considered.
1466 * Otherwise, the column is simply removed.
1468 * The column may be interchanged with some other column. If it
1469 * is interchanged with a later column, return 1. Otherwise return 0.
1470 * If the columns are checked in order in the calling function,
1471 * then a return value of 1 means that the column with the given
1472 * column number may now contain a different column that
1473 * hasn't been checked yet.
1475 int isl_tab_kill_col(struct isl_tab
*tab
, int col
)
1477 var_from_col(tab
, col
)->is_zero
= 1;
1478 if (tab
->need_undo
) {
1479 if (isl_tab_push_var(tab
, isl_tab_undo_zero
,
1480 var_from_col(tab
, col
)) < 0)
1482 if (col
!= tab
->n_dead
)
1483 swap_cols(tab
, col
, tab
->n_dead
);
1487 if (col
!= tab
->n_col
- 1)
1488 swap_cols(tab
, col
, tab
->n_col
- 1);
1489 var_from_col(tab
, tab
->n_col
- 1)->index
= -1;
1495 /* Row variable "var" is non-negative and cannot attain any values
1496 * larger than zero. This means that the coefficients of the unrestricted
1497 * column variables are zero and that the coefficients of the non-negative
1498 * column variables are zero or negative.
1499 * Each of the non-negative variables with a negative coefficient can
1500 * then also be written as the negative sum of non-negative variables
1501 * and must therefore also be zero.
1503 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1504 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1507 struct isl_mat
*mat
= tab
->mat
;
1508 unsigned off
= 2 + tab
->M
;
1510 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, return -1);
1513 if (isl_tab_push_var(tab
, isl_tab_undo_zero
, var
) < 0)
1515 for (j
= tab
->n_dead
; j
< tab
->n_col
; ++j
) {
1516 if (isl_int_is_zero(mat
->row
[var
->index
][off
+ j
]))
1518 isl_assert(tab
->mat
->ctx
,
1519 isl_int_is_neg(mat
->row
[var
->index
][off
+ j
]), return -1);
1520 if (isl_tab_kill_col(tab
, j
))
1523 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
1528 /* Add a constraint to the tableau and allocate a row for it.
1529 * Return the index into the constraint array "con".
1531 int isl_tab_allocate_con(struct isl_tab
*tab
)
1535 isl_assert(tab
->mat
->ctx
, tab
->n_row
< tab
->mat
->n_row
, return -1);
1536 isl_assert(tab
->mat
->ctx
, tab
->n_con
< tab
->max_con
, return -1);
1539 tab
->con
[r
].index
= tab
->n_row
;
1540 tab
->con
[r
].is_row
= 1;
1541 tab
->con
[r
].is_nonneg
= 0;
1542 tab
->con
[r
].is_zero
= 0;
1543 tab
->con
[r
].is_redundant
= 0;
1544 tab
->con
[r
].frozen
= 0;
1545 tab
->con
[r
].negated
= 0;
1546 tab
->row_var
[tab
->n_row
] = ~r
;
1550 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
1556 /* Add a variable to the tableau and allocate a column for it.
1557 * Return the index into the variable array "var".
1559 int isl_tab_allocate_var(struct isl_tab
*tab
)
1563 unsigned off
= 2 + tab
->M
;
1565 isl_assert(tab
->mat
->ctx
, tab
->n_col
< tab
->mat
->n_col
, return -1);
1566 isl_assert(tab
->mat
->ctx
, tab
->n_var
< tab
->max_var
, return -1);
1569 tab
->var
[r
].index
= tab
->n_col
;
1570 tab
->var
[r
].is_row
= 0;
1571 tab
->var
[r
].is_nonneg
= 0;
1572 tab
->var
[r
].is_zero
= 0;
1573 tab
->var
[r
].is_redundant
= 0;
1574 tab
->var
[r
].frozen
= 0;
1575 tab
->var
[r
].negated
= 0;
1576 tab
->col_var
[tab
->n_col
] = r
;
1578 for (i
= 0; i
< tab
->n_row
; ++i
)
1579 isl_int_set_si(tab
->mat
->row
[i
][off
+ tab
->n_col
], 0);
1583 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->var
[r
]) < 0)
1589 /* Add a row to the tableau. The row is given as an affine combination
1590 * of the original variables and needs to be expressed in terms of the
1593 * We add each term in turn.
1594 * If r = n/d_r is the current sum and we need to add k x, then
1595 * if x is a column variable, we increase the numerator of
1596 * this column by k d_r
1597 * if x = f/d_x is a row variable, then the new representation of r is
1599 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1600 * --- + --- = ------------------- = -------------------
1601 * d_r d_r d_r d_x/g m
1603 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1605 int isl_tab_add_row(struct isl_tab
*tab
, isl_int
*line
)
1611 unsigned off
= 2 + tab
->M
;
1613 r
= isl_tab_allocate_con(tab
);
1619 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1620 isl_int_set_si(row
[0], 1);
1621 isl_int_set(row
[1], line
[0]);
1622 isl_seq_clr(row
+ 2, tab
->M
+ tab
->n_col
);
1623 for (i
= 0; i
< tab
->n_var
; ++i
) {
1624 if (tab
->var
[i
].is_zero
)
1626 if (tab
->var
[i
].is_row
) {
1628 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1629 isl_int_swap(a
, row
[0]);
1630 isl_int_divexact(a
, row
[0], a
);
1632 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1633 isl_int_mul(b
, b
, line
[1 + i
]);
1634 isl_seq_combine(row
+ 1, a
, row
+ 1,
1635 b
, tab
->mat
->row
[tab
->var
[i
].index
] + 1,
1636 1 + tab
->M
+ tab
->n_col
);
1638 isl_int_addmul(row
[off
+ tab
->var
[i
].index
],
1639 line
[1 + i
], row
[0]);
1640 if (tab
->M
&& i
>= tab
->n_param
&& i
< tab
->n_var
- tab
->n_div
)
1641 isl_int_submul(row
[2], line
[1 + i
], row
[0]);
1643 isl_seq_normalize(tab
->mat
->ctx
, row
, off
+ tab
->n_col
);
1648 tab
->row_sign
[tab
->con
[r
].index
] = isl_tab_row_unknown
;
1653 static int drop_row(struct isl_tab
*tab
, int row
)
1655 isl_assert(tab
->mat
->ctx
, ~tab
->row_var
[row
] == tab
->n_con
- 1, return -1);
1656 if (row
!= tab
->n_row
- 1)
1657 swap_rows(tab
, row
, tab
->n_row
- 1);
1663 static int drop_col(struct isl_tab
*tab
, int col
)
1665 isl_assert(tab
->mat
->ctx
, tab
->col_var
[col
] == tab
->n_var
- 1, return -1);
1666 if (col
!= tab
->n_col
- 1)
1667 swap_cols(tab
, col
, tab
->n_col
- 1);
1673 /* Add inequality "ineq" and check if it conflicts with the
1674 * previously added constraints or if it is obviously redundant.
1676 int isl_tab_add_ineq(struct isl_tab
*tab
, isl_int
*ineq
)
1685 struct isl_basic_map
*bmap
= tab
->bmap
;
1687 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
1688 isl_assert(tab
->mat
->ctx
,
1689 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
1690 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, ineq
);
1691 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1698 isl_int_swap(ineq
[0], cst
);
1700 r
= isl_tab_add_row(tab
, ineq
);
1702 isl_int_swap(ineq
[0], cst
);
1707 tab
->con
[r
].is_nonneg
= 1;
1708 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
1710 if (isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
)) {
1711 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1716 sgn
= restore_row(tab
, &tab
->con
[r
]);
1720 return isl_tab_mark_empty(tab
);
1721 if (tab
->con
[r
].is_row
&& isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
))
1722 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1727 /* Pivot a non-negative variable down until it reaches the value zero
1728 * and then pivot the variable into a column position.
1730 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1731 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1735 unsigned off
= 2 + tab
->M
;
1740 while (isl_int_is_pos(tab
->mat
->row
[var
->index
][1])) {
1741 find_pivot(tab
, var
, NULL
, -1, &row
, &col
);
1742 isl_assert(tab
->mat
->ctx
, row
!= -1, return -1);
1743 if (isl_tab_pivot(tab
, row
, col
) < 0)
1749 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
)
1750 if (!isl_int_is_zero(tab
->mat
->row
[var
->index
][off
+ i
]))
1753 isl_assert(tab
->mat
->ctx
, i
< tab
->n_col
, return -1);
1754 if (isl_tab_pivot(tab
, var
->index
, i
) < 0)
1760 /* We assume Gaussian elimination has been performed on the equalities.
1761 * The equalities can therefore never conflict.
1762 * Adding the equalities is currently only really useful for a later call
1763 * to isl_tab_ineq_type.
1765 static struct isl_tab
*add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1772 r
= isl_tab_add_row(tab
, eq
);
1776 r
= tab
->con
[r
].index
;
1777 i
= isl_seq_first_non_zero(tab
->mat
->row
[r
] + 2 + tab
->M
+ tab
->n_dead
,
1778 tab
->n_col
- tab
->n_dead
);
1779 isl_assert(tab
->mat
->ctx
, i
>= 0, goto error
);
1781 if (isl_tab_pivot(tab
, r
, i
) < 0)
1783 if (isl_tab_kill_col(tab
, i
) < 0)
1793 static int row_is_manifestly_zero(struct isl_tab
*tab
, int row
)
1795 unsigned off
= 2 + tab
->M
;
1797 if (!isl_int_is_zero(tab
->mat
->row
[row
][1]))
1799 if (tab
->M
&& !isl_int_is_zero(tab
->mat
->row
[row
][2]))
1801 return isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
1802 tab
->n_col
- tab
->n_dead
) == -1;
1805 /* Add an equality that is known to be valid for the given tableau.
1807 struct isl_tab
*isl_tab_add_valid_eq(struct isl_tab
*tab
, isl_int
*eq
)
1809 struct isl_tab_var
*var
;
1814 r
= isl_tab_add_row(tab
, eq
);
1820 if (row_is_manifestly_zero(tab
, r
)) {
1822 if (isl_tab_mark_redundant(tab
, r
) < 0)
1827 if (isl_int_is_neg(tab
->mat
->row
[r
][1])) {
1828 isl_seq_neg(tab
->mat
->row
[r
] + 1, tab
->mat
->row
[r
] + 1,
1833 if (to_col(tab
, var
) < 0)
1836 if (isl_tab_kill_col(tab
, var
->index
) < 0)
1845 static int add_zero_row(struct isl_tab
*tab
)
1850 r
= isl_tab_allocate_con(tab
);
1854 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1855 isl_seq_clr(row
+ 1, 1 + tab
->M
+ tab
->n_col
);
1856 isl_int_set_si(row
[0], 1);
1861 /* Add equality "eq" and check if it conflicts with the
1862 * previously added constraints or if it is obviously redundant.
1864 struct isl_tab
*isl_tab_add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1866 struct isl_tab_undo
*snap
= NULL
;
1867 struct isl_tab_var
*var
;
1875 isl_assert(tab
->mat
->ctx
, !tab
->M
, goto error
);
1878 snap
= isl_tab_snap(tab
);
1882 isl_int_swap(eq
[0], cst
);
1884 r
= isl_tab_add_row(tab
, eq
);
1886 isl_int_swap(eq
[0], cst
);
1894 if (row_is_manifestly_zero(tab
, row
)) {
1896 if (isl_tab_rollback(tab
, snap
) < 0)
1904 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1905 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1907 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1908 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1909 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1910 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1914 if (add_zero_row(tab
) < 0)
1918 sgn
= isl_int_sgn(tab
->mat
->row
[row
][1]);
1921 isl_seq_neg(tab
->mat
->row
[row
] + 1, tab
->mat
->row
[row
] + 1,
1928 sgn
= sign_of_max(tab
, var
);
1932 if (isl_tab_mark_empty(tab
) < 0)
1939 if (to_col(tab
, var
) < 0)
1942 if (isl_tab_kill_col(tab
, var
->index
) < 0)
1951 /* Construct and return an inequality that expresses an upper bound
1953 * In particular, if the div is given by
1957 * then the inequality expresses
1961 static struct isl_vec
*ineq_for_div(struct isl_basic_map
*bmap
, unsigned div
)
1965 struct isl_vec
*ineq
;
1970 total
= isl_basic_map_total_dim(bmap
);
1971 div_pos
= 1 + total
- bmap
->n_div
+ div
;
1973 ineq
= isl_vec_alloc(bmap
->ctx
, 1 + total
);
1977 isl_seq_cpy(ineq
->el
, bmap
->div
[div
] + 1, 1 + total
);
1978 isl_int_neg(ineq
->el
[div_pos
], bmap
->div
[div
][0]);
1982 /* For a div d = floor(f/m), add the constraints
1985 * -(f-(m-1)) + m d >= 0
1987 * Note that the second constraint is the negation of
1991 * If add_ineq is not NULL, then this function is used
1992 * instead of isl_tab_add_ineq to effectively add the inequalities.
1994 static int add_div_constraints(struct isl_tab
*tab
, unsigned div
,
1995 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
1999 struct isl_vec
*ineq
;
2001 total
= isl_basic_map_total_dim(tab
->bmap
);
2002 div_pos
= 1 + total
- tab
->bmap
->n_div
+ div
;
2004 ineq
= ineq_for_div(tab
->bmap
, div
);
2009 if (add_ineq(user
, ineq
->el
) < 0)
2012 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2016 isl_seq_neg(ineq
->el
, tab
->bmap
->div
[div
] + 1, 1 + total
);
2017 isl_int_set(ineq
->el
[div_pos
], tab
->bmap
->div
[div
][0]);
2018 isl_int_add(ineq
->el
[0], ineq
->el
[0], ineq
->el
[div_pos
]);
2019 isl_int_sub_ui(ineq
->el
[0], ineq
->el
[0], 1);
2022 if (add_ineq(user
, ineq
->el
) < 0)
2025 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2037 /* Add an extra div, prescrived by "div" to the tableau and
2038 * the associated bmap (which is assumed to be non-NULL).
2040 * If add_ineq is not NULL, then this function is used instead
2041 * of isl_tab_add_ineq to add the div constraints.
2042 * This complication is needed because the code in isl_tab_pip
2043 * wants to perform some extra processing when an inequality
2044 * is added to the tableau.
2046 int isl_tab_add_div(struct isl_tab
*tab
, __isl_keep isl_vec
*div
,
2047 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
2057 isl_assert(tab
->mat
->ctx
, tab
->bmap
, return -1);
2059 for (i
= 0; i
< tab
->n_var
; ++i
) {
2060 if (isl_int_is_neg(div
->el
[2 + i
]))
2062 if (isl_int_is_zero(div
->el
[2 + i
]))
2064 if (!tab
->var
[i
].is_nonneg
)
2067 nonneg
= i
== tab
->n_var
&& !isl_int_is_neg(div
->el
[1]);
2069 if (isl_tab_extend_cons(tab
, 3) < 0)
2071 if (isl_tab_extend_vars(tab
, 1) < 0)
2073 r
= isl_tab_allocate_var(tab
);
2078 tab
->var
[r
].is_nonneg
= 1;
2080 tab
->bmap
= isl_basic_map_extend_dim(tab
->bmap
,
2081 isl_basic_map_get_dim(tab
->bmap
), 1, 0, 2);
2082 k
= isl_basic_map_alloc_div(tab
->bmap
);
2085 isl_seq_cpy(tab
->bmap
->div
[k
], div
->el
, div
->size
);
2086 if (isl_tab_push(tab
, isl_tab_undo_bmap_div
) < 0)
2089 if (add_div_constraints(tab
, k
, add_ineq
, user
) < 0)
2095 struct isl_tab
*isl_tab_from_basic_map(struct isl_basic_map
*bmap
)
2098 struct isl_tab
*tab
;
2102 tab
= isl_tab_alloc(bmap
->ctx
,
2103 isl_basic_map_total_dim(bmap
) + bmap
->n_ineq
+ 1,
2104 isl_basic_map_total_dim(bmap
), 0);
2107 tab
->rational
= ISL_F_ISSET(bmap
, ISL_BASIC_MAP_RATIONAL
);
2108 if (ISL_F_ISSET(bmap
, ISL_BASIC_MAP_EMPTY
)) {
2109 if (isl_tab_mark_empty(tab
) < 0)
2113 for (i
= 0; i
< bmap
->n_eq
; ++i
) {
2114 tab
= add_eq(tab
, bmap
->eq
[i
]);
2118 for (i
= 0; i
< bmap
->n_ineq
; ++i
) {
2119 if (isl_tab_add_ineq(tab
, bmap
->ineq
[i
]) < 0)
2130 struct isl_tab
*isl_tab_from_basic_set(struct isl_basic_set
*bset
)
2132 return isl_tab_from_basic_map((struct isl_basic_map
*)bset
);
2135 /* Construct a tableau corresponding to the recession cone of "bset".
2137 struct isl_tab
*isl_tab_from_recession_cone(struct isl_basic_set
*bset
)
2141 struct isl_tab
*tab
;
2145 tab
= isl_tab_alloc(bset
->ctx
, bset
->n_eq
+ bset
->n_ineq
,
2146 isl_basic_set_total_dim(bset
), 0);
2149 tab
->rational
= ISL_F_ISSET(bset
, ISL_BASIC_SET_RATIONAL
);
2153 for (i
= 0; i
< bset
->n_eq
; ++i
) {
2154 isl_int_swap(bset
->eq
[i
][0], cst
);
2155 tab
= add_eq(tab
, bset
->eq
[i
]);
2156 isl_int_swap(bset
->eq
[i
][0], cst
);
2160 for (i
= 0; i
< bset
->n_ineq
; ++i
) {
2162 isl_int_swap(bset
->ineq
[i
][0], cst
);
2163 r
= isl_tab_add_row(tab
, bset
->ineq
[i
]);
2164 isl_int_swap(bset
->ineq
[i
][0], cst
);
2167 tab
->con
[r
].is_nonneg
= 1;
2168 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2180 /* Assuming "tab" is the tableau of a cone, check if the cone is
2181 * bounded, i.e., if it is empty or only contains the origin.
2183 int isl_tab_cone_is_bounded(struct isl_tab
*tab
)
2191 if (tab
->n_dead
== tab
->n_col
)
2195 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2196 struct isl_tab_var
*var
;
2198 var
= isl_tab_var_from_row(tab
, i
);
2199 if (!var
->is_nonneg
)
2201 sgn
= sign_of_max(tab
, var
);
2206 if (close_row(tab
, var
) < 0)
2210 if (tab
->n_dead
== tab
->n_col
)
2212 if (i
== tab
->n_row
)
2217 int isl_tab_sample_is_integer(struct isl_tab
*tab
)
2224 for (i
= 0; i
< tab
->n_var
; ++i
) {
2226 if (!tab
->var
[i
].is_row
)
2228 row
= tab
->var
[i
].index
;
2229 if (!isl_int_is_divisible_by(tab
->mat
->row
[row
][1],
2230 tab
->mat
->row
[row
][0]))
2236 static struct isl_vec
*extract_integer_sample(struct isl_tab
*tab
)
2239 struct isl_vec
*vec
;
2241 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2245 isl_int_set_si(vec
->block
.data
[0], 1);
2246 for (i
= 0; i
< tab
->n_var
; ++i
) {
2247 if (!tab
->var
[i
].is_row
)
2248 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2250 int row
= tab
->var
[i
].index
;
2251 isl_int_divexact(vec
->block
.data
[1 + i
],
2252 tab
->mat
->row
[row
][1], tab
->mat
->row
[row
][0]);
2259 struct isl_vec
*isl_tab_get_sample_value(struct isl_tab
*tab
)
2262 struct isl_vec
*vec
;
2268 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2274 isl_int_set_si(vec
->block
.data
[0], 1);
2275 for (i
= 0; i
< tab
->n_var
; ++i
) {
2277 if (!tab
->var
[i
].is_row
) {
2278 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2281 row
= tab
->var
[i
].index
;
2282 isl_int_gcd(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2283 isl_int_divexact(m
, tab
->mat
->row
[row
][0], m
);
2284 isl_seq_scale(vec
->block
.data
, vec
->block
.data
, m
, 1 + i
);
2285 isl_int_divexact(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2286 isl_int_mul(vec
->block
.data
[1 + i
], m
, tab
->mat
->row
[row
][1]);
2288 vec
= isl_vec_normalize(vec
);
2294 /* Update "bmap" based on the results of the tableau "tab".
2295 * In particular, implicit equalities are made explicit, redundant constraints
2296 * are removed and if the sample value happens to be integer, it is stored
2297 * in "bmap" (unless "bmap" already had an integer sample).
2299 * The tableau is assumed to have been created from "bmap" using
2300 * isl_tab_from_basic_map.
2302 struct isl_basic_map
*isl_basic_map_update_from_tab(struct isl_basic_map
*bmap
,
2303 struct isl_tab
*tab
)
2315 bmap
= isl_basic_map_set_to_empty(bmap
);
2317 for (i
= bmap
->n_ineq
- 1; i
>= 0; --i
) {
2318 if (isl_tab_is_equality(tab
, n_eq
+ i
))
2319 isl_basic_map_inequality_to_equality(bmap
, i
);
2320 else if (isl_tab_is_redundant(tab
, n_eq
+ i
))
2321 isl_basic_map_drop_inequality(bmap
, i
);
2323 if (bmap
->n_eq
!= n_eq
)
2324 isl_basic_map_gauss(bmap
, NULL
);
2325 if (!tab
->rational
&&
2326 !bmap
->sample
&& isl_tab_sample_is_integer(tab
))
2327 bmap
->sample
= extract_integer_sample(tab
);
2331 struct isl_basic_set
*isl_basic_set_update_from_tab(struct isl_basic_set
*bset
,
2332 struct isl_tab
*tab
)
2334 return (struct isl_basic_set
*)isl_basic_map_update_from_tab(
2335 (struct isl_basic_map
*)bset
, tab
);
2338 /* Given a non-negative variable "var", add a new non-negative variable
2339 * that is the opposite of "var", ensuring that var can only attain the
2341 * If var = n/d is a row variable, then the new variable = -n/d.
2342 * If var is a column variables, then the new variable = -var.
2343 * If the new variable cannot attain non-negative values, then
2344 * the resulting tableau is empty.
2345 * Otherwise, we know the value will be zero and we close the row.
2347 static struct isl_tab
*cut_to_hyperplane(struct isl_tab
*tab
,
2348 struct isl_tab_var
*var
)
2353 unsigned off
= 2 + tab
->M
;
2357 isl_assert(tab
->mat
->ctx
, !var
->is_redundant
, goto error
);
2358 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, goto error
);
2360 if (isl_tab_extend_cons(tab
, 1) < 0)
2364 tab
->con
[r
].index
= tab
->n_row
;
2365 tab
->con
[r
].is_row
= 1;
2366 tab
->con
[r
].is_nonneg
= 0;
2367 tab
->con
[r
].is_zero
= 0;
2368 tab
->con
[r
].is_redundant
= 0;
2369 tab
->con
[r
].frozen
= 0;
2370 tab
->con
[r
].negated
= 0;
2371 tab
->row_var
[tab
->n_row
] = ~r
;
2372 row
= tab
->mat
->row
[tab
->n_row
];
2375 isl_int_set(row
[0], tab
->mat
->row
[var
->index
][0]);
2376 isl_seq_neg(row
+ 1,
2377 tab
->mat
->row
[var
->index
] + 1, 1 + tab
->n_col
);
2379 isl_int_set_si(row
[0], 1);
2380 isl_seq_clr(row
+ 1, 1 + tab
->n_col
);
2381 isl_int_set_si(row
[off
+ var
->index
], -1);
2386 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
2389 sgn
= sign_of_max(tab
, &tab
->con
[r
]);
2393 if (isl_tab_mark_empty(tab
) < 0)
2397 tab
->con
[r
].is_nonneg
= 1;
2398 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2401 if (close_row(tab
, &tab
->con
[r
]) < 0)
2410 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2411 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2412 * by r' = r + 1 >= 0.
2413 * If r is a row variable, we simply increase the constant term by one
2414 * (taking into account the denominator).
2415 * If r is a column variable, then we need to modify each row that
2416 * refers to r = r' - 1 by substituting this equality, effectively
2417 * subtracting the coefficient of the column from the constant.
2418 * We should only do this if the minimum is manifestly unbounded,
2419 * however. Otherwise, we may end up with negative sample values
2420 * for non-negative variables.
2421 * So, if r is a column variable with a minimum that is not
2422 * manifestly unbounded, then we need to move it to a row.
2423 * However, the sample value of this row may be negative,
2424 * even after the relaxation, so we need to restore it.
2425 * We therefore prefer to pivot a column up to a row, if possible.
2427 struct isl_tab
*isl_tab_relax(struct isl_tab
*tab
, int con
)
2429 struct isl_tab_var
*var
;
2430 unsigned off
= 2 + tab
->M
;
2435 var
= &tab
->con
[con
];
2437 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2438 if (to_row(tab
, var
, 1) < 0)
2440 if (!var
->is_row
&& !min_is_manifestly_unbounded(tab
, var
))
2441 if (to_row(tab
, var
, -1) < 0)
2445 isl_int_add(tab
->mat
->row
[var
->index
][1],
2446 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2447 if (restore_row(tab
, var
) < 0)
2452 for (i
= 0; i
< tab
->n_row
; ++i
) {
2453 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2455 isl_int_sub(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2456 tab
->mat
->row
[i
][off
+ var
->index
]);
2461 if (isl_tab_push_var(tab
, isl_tab_undo_relax
, var
) < 0)
2470 struct isl_tab
*isl_tab_select_facet(struct isl_tab
*tab
, int con
)
2475 return cut_to_hyperplane(tab
, &tab
->con
[con
]);
2478 static int may_be_equality(struct isl_tab
*tab
, int row
)
2480 unsigned off
= 2 + tab
->M
;
2481 return (tab
->rational
? isl_int_is_zero(tab
->mat
->row
[row
][1])
2482 : isl_int_lt(tab
->mat
->row
[row
][1],
2483 tab
->mat
->row
[row
][0])) &&
2484 isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
2485 tab
->n_col
- tab
->n_dead
) != -1;
2488 /* Check for (near) equalities among the constraints.
2489 * A constraint is an equality if it is non-negative and if
2490 * its maximal value is either
2491 * - zero (in case of rational tableaus), or
2492 * - strictly less than 1 (in case of integer tableaus)
2494 * We first mark all non-redundant and non-dead variables that
2495 * are not frozen and not obviously not an equality.
2496 * Then we iterate over all marked variables if they can attain
2497 * any values larger than zero or at least one.
2498 * If the maximal value is zero, we mark any column variables
2499 * that appear in the row as being zero and mark the row as being redundant.
2500 * Otherwise, if the maximal value is strictly less than one (and the
2501 * tableau is integer), then we restrict the value to being zero
2502 * by adding an opposite non-negative variable.
2504 struct isl_tab
*isl_tab_detect_implicit_equalities(struct isl_tab
*tab
)
2513 if (tab
->n_dead
== tab
->n_col
)
2517 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2518 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2519 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2520 may_be_equality(tab
, i
);
2524 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2525 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2526 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2531 struct isl_tab_var
*var
;
2533 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2534 var
= isl_tab_var_from_row(tab
, i
);
2538 if (i
== tab
->n_row
) {
2539 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2540 var
= var_from_col(tab
, i
);
2544 if (i
== tab
->n_col
)
2549 sgn
= sign_of_max(tab
, var
);
2553 if (close_row(tab
, var
) < 0)
2555 } else if (!tab
->rational
&& !at_least_one(tab
, var
)) {
2556 tab
= cut_to_hyperplane(tab
, var
);
2557 return isl_tab_detect_implicit_equalities(tab
);
2559 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2560 var
= isl_tab_var_from_row(tab
, i
);
2563 if (may_be_equality(tab
, i
))
2576 static int con_is_redundant(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2580 if (tab
->rational
) {
2581 int sgn
= sign_of_min(tab
, var
);
2586 int irred
= isl_tab_min_at_most_neg_one(tab
, var
);
2593 /* Check for (near) redundant constraints.
2594 * A constraint is redundant if it is non-negative and if
2595 * its minimal value (temporarily ignoring the non-negativity) is either
2596 * - zero (in case of rational tableaus), or
2597 * - strictly larger than -1 (in case of integer tableaus)
2599 * We first mark all non-redundant and non-dead variables that
2600 * are not frozen and not obviously negatively unbounded.
2601 * Then we iterate over all marked variables if they can attain
2602 * any values smaller than zero or at most negative one.
2603 * If not, we mark the row as being redundant (assuming it hasn't
2604 * been detected as being obviously redundant in the mean time).
2606 int isl_tab_detect_redundant(struct isl_tab
*tab
)
2615 if (tab
->n_redundant
== tab
->n_row
)
2619 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2620 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2621 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2625 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2626 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2627 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2628 !min_is_manifestly_unbounded(tab
, var
);
2633 struct isl_tab_var
*var
;
2635 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2636 var
= isl_tab_var_from_row(tab
, i
);
2640 if (i
== tab
->n_row
) {
2641 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2642 var
= var_from_col(tab
, i
);
2646 if (i
== tab
->n_col
)
2651 red
= con_is_redundant(tab
, var
);
2654 if (red
&& !var
->is_redundant
)
2655 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
2657 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2658 var
= var_from_col(tab
, i
);
2661 if (!min_is_manifestly_unbounded(tab
, var
))
2671 int isl_tab_is_equality(struct isl_tab
*tab
, int con
)
2678 if (tab
->con
[con
].is_zero
)
2680 if (tab
->con
[con
].is_redundant
)
2682 if (!tab
->con
[con
].is_row
)
2683 return tab
->con
[con
].index
< tab
->n_dead
;
2685 row
= tab
->con
[con
].index
;
2688 return isl_int_is_zero(tab
->mat
->row
[row
][1]) &&
2689 isl_seq_first_non_zero(tab
->mat
->row
[row
] + 2 + tab
->n_dead
,
2690 tab
->n_col
- tab
->n_dead
) == -1;
2693 /* Return the minimial value of the affine expression "f" with denominator
2694 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2695 * the expression cannot attain arbitrarily small values.
2696 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2697 * The return value reflects the nature of the result (empty, unbounded,
2698 * minmimal value returned in *opt).
2700 enum isl_lp_result
isl_tab_min(struct isl_tab
*tab
,
2701 isl_int
*f
, isl_int denom
, isl_int
*opt
, isl_int
*opt_denom
,
2705 enum isl_lp_result res
= isl_lp_ok
;
2706 struct isl_tab_var
*var
;
2707 struct isl_tab_undo
*snap
;
2710 return isl_lp_empty
;
2712 snap
= isl_tab_snap(tab
);
2713 r
= isl_tab_add_row(tab
, f
);
2715 return isl_lp_error
;
2717 isl_int_mul(tab
->mat
->row
[var
->index
][0],
2718 tab
->mat
->row
[var
->index
][0], denom
);
2721 find_pivot(tab
, var
, var
, -1, &row
, &col
);
2722 if (row
== var
->index
) {
2723 res
= isl_lp_unbounded
;
2728 if (isl_tab_pivot(tab
, row
, col
) < 0)
2729 return isl_lp_error
;
2731 if (ISL_FL_ISSET(flags
, ISL_TAB_SAVE_DUAL
)) {
2734 isl_vec_free(tab
->dual
);
2735 tab
->dual
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_con
);
2737 return isl_lp_error
;
2738 isl_int_set(tab
->dual
->el
[0], tab
->mat
->row
[var
->index
][0]);
2739 for (i
= 0; i
< tab
->n_con
; ++i
) {
2741 if (tab
->con
[i
].is_row
) {
2742 isl_int_set_si(tab
->dual
->el
[1 + i
], 0);
2745 pos
= 2 + tab
->M
+ tab
->con
[i
].index
;
2746 if (tab
->con
[i
].negated
)
2747 isl_int_neg(tab
->dual
->el
[1 + i
],
2748 tab
->mat
->row
[var
->index
][pos
]);
2750 isl_int_set(tab
->dual
->el
[1 + i
],
2751 tab
->mat
->row
[var
->index
][pos
]);
2754 if (opt
&& res
== isl_lp_ok
) {
2756 isl_int_set(*opt
, tab
->mat
->row
[var
->index
][1]);
2757 isl_int_set(*opt_denom
, tab
->mat
->row
[var
->index
][0]);
2759 isl_int_cdiv_q(*opt
, tab
->mat
->row
[var
->index
][1],
2760 tab
->mat
->row
[var
->index
][0]);
2762 if (isl_tab_rollback(tab
, snap
) < 0)
2763 return isl_lp_error
;
2767 int isl_tab_is_redundant(struct isl_tab
*tab
, int con
)
2771 if (tab
->con
[con
].is_zero
)
2773 if (tab
->con
[con
].is_redundant
)
2775 return tab
->con
[con
].is_row
&& tab
->con
[con
].index
< tab
->n_redundant
;
2778 /* Take a snapshot of the tableau that can be restored by s call to
2781 struct isl_tab_undo
*isl_tab_snap(struct isl_tab
*tab
)
2789 /* Undo the operation performed by isl_tab_relax.
2791 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
2792 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2794 unsigned off
= 2 + tab
->M
;
2796 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2797 if (to_row(tab
, var
, 1) < 0)
2801 isl_int_sub(tab
->mat
->row
[var
->index
][1],
2802 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2803 if (var
->is_nonneg
) {
2804 int sgn
= restore_row(tab
, var
);
2805 isl_assert(tab
->mat
->ctx
, sgn
>= 0, return -1);
2810 for (i
= 0; i
< tab
->n_row
; ++i
) {
2811 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2813 isl_int_add(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2814 tab
->mat
->row
[i
][off
+ var
->index
]);
2822 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
2823 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
2825 struct isl_tab_var
*var
= var_from_index(tab
, undo
->u
.var_index
);
2826 switch(undo
->type
) {
2827 case isl_tab_undo_nonneg
:
2830 case isl_tab_undo_redundant
:
2831 var
->is_redundant
= 0;
2833 restore_row(tab
, isl_tab_var_from_row(tab
, tab
->n_redundant
));
2835 case isl_tab_undo_freeze
:
2838 case isl_tab_undo_zero
:
2843 case isl_tab_undo_allocate
:
2844 if (undo
->u
.var_index
>= 0) {
2845 isl_assert(tab
->mat
->ctx
, !var
->is_row
, return -1);
2846 drop_col(tab
, var
->index
);
2850 if (!max_is_manifestly_unbounded(tab
, var
)) {
2851 if (to_row(tab
, var
, 1) < 0)
2853 } else if (!min_is_manifestly_unbounded(tab
, var
)) {
2854 if (to_row(tab
, var
, -1) < 0)
2857 if (to_row(tab
, var
, 0) < 0)
2860 drop_row(tab
, var
->index
);
2862 case isl_tab_undo_relax
:
2863 return unrelax(tab
, var
);
2869 /* Restore the tableau to the state where the basic variables
2870 * are those in "col_var".
2871 * We first construct a list of variables that are currently in
2872 * the basis, but shouldn't. Then we iterate over all variables
2873 * that should be in the basis and for each one that is currently
2874 * not in the basis, we exchange it with one of the elements of the
2875 * list constructed before.
2876 * We can always find an appropriate variable to pivot with because
2877 * the current basis is mapped to the old basis by a non-singular
2878 * matrix and so we can never end up with a zero row.
2880 static int restore_basis(struct isl_tab
*tab
, int *col_var
)
2884 int *extra
= NULL
; /* current columns that contain bad stuff */
2885 unsigned off
= 2 + tab
->M
;
2887 extra
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->n_col
);
2890 for (i
= 0; i
< tab
->n_col
; ++i
) {
2891 for (j
= 0; j
< tab
->n_col
; ++j
)
2892 if (tab
->col_var
[i
] == col_var
[j
])
2896 extra
[n_extra
++] = i
;
2898 for (i
= 0; i
< tab
->n_col
&& n_extra
> 0; ++i
) {
2899 struct isl_tab_var
*var
;
2902 for (j
= 0; j
< tab
->n_col
; ++j
)
2903 if (col_var
[i
] == tab
->col_var
[j
])
2907 var
= var_from_index(tab
, col_var
[i
]);
2909 for (j
= 0; j
< n_extra
; ++j
)
2910 if (!isl_int_is_zero(tab
->mat
->row
[row
][off
+extra
[j
]]))
2912 isl_assert(tab
->mat
->ctx
, j
< n_extra
, goto error
);
2913 if (isl_tab_pivot(tab
, row
, extra
[j
]) < 0)
2915 extra
[j
] = extra
[--n_extra
];
2927 /* Remove all samples with index n or greater, i.e., those samples
2928 * that were added since we saved this number of samples in
2929 * isl_tab_save_samples.
2931 static void drop_samples_since(struct isl_tab
*tab
, int n
)
2935 for (i
= tab
->n_sample
- 1; i
>= 0 && tab
->n_sample
> n
; --i
) {
2936 if (tab
->sample_index
[i
] < n
)
2939 if (i
!= tab
->n_sample
- 1) {
2940 int t
= tab
->sample_index
[tab
->n_sample
-1];
2941 tab
->sample_index
[tab
->n_sample
-1] = tab
->sample_index
[i
];
2942 tab
->sample_index
[i
] = t
;
2943 isl_mat_swap_rows(tab
->samples
, tab
->n_sample
-1, i
);
2949 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
2950 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
2952 switch (undo
->type
) {
2953 case isl_tab_undo_empty
:
2956 case isl_tab_undo_nonneg
:
2957 case isl_tab_undo_redundant
:
2958 case isl_tab_undo_freeze
:
2959 case isl_tab_undo_zero
:
2960 case isl_tab_undo_allocate
:
2961 case isl_tab_undo_relax
:
2962 return perform_undo_var(tab
, undo
);
2963 case isl_tab_undo_bmap_eq
:
2964 return isl_basic_map_free_equality(tab
->bmap
, 1);
2965 case isl_tab_undo_bmap_ineq
:
2966 return isl_basic_map_free_inequality(tab
->bmap
, 1);
2967 case isl_tab_undo_bmap_div
:
2968 if (isl_basic_map_free_div(tab
->bmap
, 1) < 0)
2971 tab
->samples
->n_col
--;
2973 case isl_tab_undo_saved_basis
:
2974 if (restore_basis(tab
, undo
->u
.col_var
) < 0)
2977 case isl_tab_undo_drop_sample
:
2980 case isl_tab_undo_saved_samples
:
2981 drop_samples_since(tab
, undo
->u
.n
);
2983 case isl_tab_undo_callback
:
2984 return undo
->u
.callback
->run(undo
->u
.callback
);
2986 isl_assert(tab
->mat
->ctx
, 0, return -1);
2991 /* Return the tableau to the state it was in when the snapshot "snap"
2994 int isl_tab_rollback(struct isl_tab
*tab
, struct isl_tab_undo
*snap
)
2996 struct isl_tab_undo
*undo
, *next
;
3002 for (undo
= tab
->top
; undo
&& undo
!= &tab
->bottom
; undo
= next
) {
3006 if (perform_undo(tab
, undo
) < 0) {
3020 /* The given row "row" represents an inequality violated by all
3021 * points in the tableau. Check for some special cases of such
3022 * separating constraints.
3023 * In particular, if the row has been reduced to the constant -1,
3024 * then we know the inequality is adjacent (but opposite) to
3025 * an equality in the tableau.
3026 * If the row has been reduced to r = -1 -r', with r' an inequality
3027 * of the tableau, then the inequality is adjacent (but opposite)
3028 * to the inequality r'.
3030 static enum isl_ineq_type
separation_type(struct isl_tab
*tab
, unsigned row
)
3033 unsigned off
= 2 + tab
->M
;
3036 return isl_ineq_separate
;
3038 if (!isl_int_is_one(tab
->mat
->row
[row
][0]))
3039 return isl_ineq_separate
;
3040 if (!isl_int_is_negone(tab
->mat
->row
[row
][1]))
3041 return isl_ineq_separate
;
3043 pos
= isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
3044 tab
->n_col
- tab
->n_dead
);
3046 return isl_ineq_adj_eq
;
3048 if (!isl_int_is_negone(tab
->mat
->row
[row
][off
+ tab
->n_dead
+ pos
]))
3049 return isl_ineq_separate
;
3051 pos
= isl_seq_first_non_zero(
3052 tab
->mat
->row
[row
] + off
+ tab
->n_dead
+ pos
+ 1,
3053 tab
->n_col
- tab
->n_dead
- pos
- 1);
3055 return pos
== -1 ? isl_ineq_adj_ineq
: isl_ineq_separate
;
3058 /* Check the effect of inequality "ineq" on the tableau "tab".
3060 * isl_ineq_redundant: satisfied by all points in the tableau
3061 * isl_ineq_separate: satisfied by no point in the tableau
3062 * isl_ineq_cut: satisfied by some by not all points
3063 * isl_ineq_adj_eq: adjacent to an equality
3064 * isl_ineq_adj_ineq: adjacent to an inequality.
3066 enum isl_ineq_type
isl_tab_ineq_type(struct isl_tab
*tab
, isl_int
*ineq
)
3068 enum isl_ineq_type type
= isl_ineq_error
;
3069 struct isl_tab_undo
*snap
= NULL
;
3074 return isl_ineq_error
;
3076 if (isl_tab_extend_cons(tab
, 1) < 0)
3077 return isl_ineq_error
;
3079 snap
= isl_tab_snap(tab
);
3081 con
= isl_tab_add_row(tab
, ineq
);
3085 row
= tab
->con
[con
].index
;
3086 if (isl_tab_row_is_redundant(tab
, row
))
3087 type
= isl_ineq_redundant
;
3088 else if (isl_int_is_neg(tab
->mat
->row
[row
][1]) &&
3090 isl_int_abs_ge(tab
->mat
->row
[row
][1],
3091 tab
->mat
->row
[row
][0]))) {
3092 int nonneg
= at_least_zero(tab
, &tab
->con
[con
]);
3096 type
= isl_ineq_cut
;
3098 type
= separation_type(tab
, row
);
3100 int red
= con_is_redundant(tab
, &tab
->con
[con
]);
3104 type
= isl_ineq_cut
;
3106 type
= isl_ineq_redundant
;
3109 if (isl_tab_rollback(tab
, snap
))
3110 return isl_ineq_error
;
3113 return isl_ineq_error
;
3116 int isl_tab_track_bmap(struct isl_tab
*tab
, __isl_take isl_basic_map
*bmap
)
3121 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
3122 isl_assert(tab
->mat
->ctx
,
3123 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
3129 isl_basic_map_free(bmap
);
3133 int isl_tab_track_bset(struct isl_tab
*tab
, __isl_take isl_basic_set
*bset
)
3135 return isl_tab_track_bmap(tab
, (isl_basic_map
*)bset
);
3138 __isl_keep isl_basic_set
*isl_tab_peek_bset(struct isl_tab
*tab
)
3143 return (isl_basic_set
*)tab
->bmap
;
3146 void isl_tab_dump(struct isl_tab
*tab
, FILE *out
, int indent
)
3152 fprintf(out
, "%*snull tab\n", indent
, "");
3155 fprintf(out
, "%*sn_redundant: %d, n_dead: %d", indent
, "",
3156 tab
->n_redundant
, tab
->n_dead
);
3158 fprintf(out
, ", rational");
3160 fprintf(out
, ", empty");
3162 fprintf(out
, "%*s[", indent
, "");
3163 for (i
= 0; i
< tab
->n_var
; ++i
) {
3165 fprintf(out
, (i
== tab
->n_param
||
3166 i
== tab
->n_var
- tab
->n_div
) ? "; "
3168 fprintf(out
, "%c%d%s", tab
->var
[i
].is_row
? 'r' : 'c',
3170 tab
->var
[i
].is_zero
? " [=0]" :
3171 tab
->var
[i
].is_redundant
? " [R]" : "");
3173 fprintf(out
, "]\n");
3174 fprintf(out
, "%*s[", indent
, "");
3175 for (i
= 0; i
< tab
->n_con
; ++i
) {
3178 fprintf(out
, "%c%d%s", tab
->con
[i
].is_row
? 'r' : 'c',
3180 tab
->con
[i
].is_zero
? " [=0]" :
3181 tab
->con
[i
].is_redundant
? " [R]" : "");
3183 fprintf(out
, "]\n");
3184 fprintf(out
, "%*s[", indent
, "");
3185 for (i
= 0; i
< tab
->n_row
; ++i
) {
3186 const char *sign
= "";
3189 if (tab
->row_sign
) {
3190 if (tab
->row_sign
[i
] == isl_tab_row_unknown
)
3192 else if (tab
->row_sign
[i
] == isl_tab_row_neg
)
3194 else if (tab
->row_sign
[i
] == isl_tab_row_pos
)
3199 fprintf(out
, "r%d: %d%s%s", i
, tab
->row_var
[i
],
3200 isl_tab_var_from_row(tab
, i
)->is_nonneg
? " [>=0]" : "", sign
);
3202 fprintf(out
, "]\n");
3203 fprintf(out
, "%*s[", indent
, "");
3204 for (i
= 0; i
< tab
->n_col
; ++i
) {
3207 fprintf(out
, "c%d: %d%s", i
, tab
->col_var
[i
],
3208 var_from_col(tab
, i
)->is_nonneg
? " [>=0]" : "");
3210 fprintf(out
, "]\n");
3211 r
= tab
->mat
->n_row
;
3212 tab
->mat
->n_row
= tab
->n_row
;
3213 c
= tab
->mat
->n_col
;
3214 tab
->mat
->n_col
= 2 + tab
->M
+ tab
->n_col
;
3215 isl_mat_dump(tab
->mat
, out
, indent
);
3216 tab
->mat
->n_row
= r
;
3217 tab
->mat
->n_col
= c
;
3219 isl_basic_map_dump(tab
->bmap
, out
, indent
);