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 t
= tab
->row_var
[row1
];
746 tab
->row_var
[row1
] = tab
->row_var
[row2
];
747 tab
->row_var
[row2
] = t
;
748 isl_tab_var_from_row(tab
, row1
)->index
= row1
;
749 isl_tab_var_from_row(tab
, row2
)->index
= row2
;
750 tab
->mat
= isl_mat_swap_rows(tab
->mat
, row1
, row2
);
754 t
= tab
->row_sign
[row1
];
755 tab
->row_sign
[row1
] = tab
->row_sign
[row2
];
756 tab
->row_sign
[row2
] = t
;
759 static int push_union(struct isl_tab
*tab
,
760 enum isl_tab_undo_type type
, union isl_tab_undo_val u
) WARN_UNUSED
;
761 static int push_union(struct isl_tab
*tab
,
762 enum isl_tab_undo_type type
, union isl_tab_undo_val u
)
764 struct isl_tab_undo
*undo
;
769 undo
= isl_alloc_type(tab
->mat
->ctx
, struct isl_tab_undo
);
774 undo
->next
= tab
->top
;
780 int isl_tab_push_var(struct isl_tab
*tab
,
781 enum isl_tab_undo_type type
, struct isl_tab_var
*var
)
783 union isl_tab_undo_val u
;
785 u
.var_index
= tab
->row_var
[var
->index
];
787 u
.var_index
= tab
->col_var
[var
->index
];
788 return push_union(tab
, type
, u
);
791 int isl_tab_push(struct isl_tab
*tab
, enum isl_tab_undo_type type
)
793 union isl_tab_undo_val u
= { 0 };
794 return push_union(tab
, type
, u
);
797 /* Push a record on the undo stack describing the current basic
798 * variables, so that the this state can be restored during rollback.
800 int isl_tab_push_basis(struct isl_tab
*tab
)
803 union isl_tab_undo_val u
;
805 u
.col_var
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->n_col
);
808 for (i
= 0; i
< tab
->n_col
; ++i
)
809 u
.col_var
[i
] = tab
->col_var
[i
];
810 return push_union(tab
, isl_tab_undo_saved_basis
, u
);
813 int isl_tab_push_callback(struct isl_tab
*tab
, struct isl_tab_callback
*callback
)
815 union isl_tab_undo_val u
;
816 u
.callback
= callback
;
817 return push_union(tab
, isl_tab_undo_callback
, u
);
820 struct isl_tab
*isl_tab_init_samples(struct isl_tab
*tab
)
827 tab
->samples
= isl_mat_alloc(tab
->mat
->ctx
, 1, 1 + tab
->n_var
);
830 tab
->sample_index
= isl_alloc_array(tab
->mat
->ctx
, int, 1);
831 if (!tab
->sample_index
)
839 struct isl_tab
*isl_tab_add_sample(struct isl_tab
*tab
,
840 __isl_take isl_vec
*sample
)
845 if (tab
->n_sample
+ 1 > tab
->samples
->n_row
) {
846 int *t
= isl_realloc_array(tab
->mat
->ctx
,
847 tab
->sample_index
, int, tab
->n_sample
+ 1);
850 tab
->sample_index
= t
;
853 tab
->samples
= isl_mat_extend(tab
->samples
,
854 tab
->n_sample
+ 1, tab
->samples
->n_col
);
858 isl_seq_cpy(tab
->samples
->row
[tab
->n_sample
], sample
->el
, sample
->size
);
859 isl_vec_free(sample
);
860 tab
->sample_index
[tab
->n_sample
] = tab
->n_sample
;
865 isl_vec_free(sample
);
870 struct isl_tab
*isl_tab_drop_sample(struct isl_tab
*tab
, int s
)
872 if (s
!= tab
->n_outside
) {
873 int t
= tab
->sample_index
[tab
->n_outside
];
874 tab
->sample_index
[tab
->n_outside
] = tab
->sample_index
[s
];
875 tab
->sample_index
[s
] = t
;
876 isl_mat_swap_rows(tab
->samples
, tab
->n_outside
, s
);
879 if (isl_tab_push(tab
, isl_tab_undo_drop_sample
) < 0) {
887 /* Record the current number of samples so that we can remove newer
888 * samples during a rollback.
890 int isl_tab_save_samples(struct isl_tab
*tab
)
892 union isl_tab_undo_val u
;
898 return push_union(tab
, isl_tab_undo_saved_samples
, u
);
901 /* Mark row with index "row" as being redundant.
902 * If we may need to undo the operation or if the row represents
903 * a variable of the original problem, the row is kept,
904 * but no longer considered when looking for a pivot row.
905 * Otherwise, the row is simply removed.
907 * The row may be interchanged with some other row. If it
908 * is interchanged with a later row, return 1. Otherwise return 0.
909 * If the rows are checked in order in the calling function,
910 * then a return value of 1 means that the row with the given
911 * row number may now contain a different row that hasn't been checked yet.
913 int isl_tab_mark_redundant(struct isl_tab
*tab
, int row
)
915 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, row
);
916 var
->is_redundant
= 1;
917 isl_assert(tab
->mat
->ctx
, row
>= tab
->n_redundant
, return -1);
918 if (tab
->need_undo
|| tab
->row_var
[row
] >= 0) {
919 if (tab
->row_var
[row
] >= 0 && !var
->is_nonneg
) {
921 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, var
) < 0)
924 if (row
!= tab
->n_redundant
)
925 swap_rows(tab
, row
, tab
->n_redundant
);
927 return isl_tab_push_var(tab
, isl_tab_undo_redundant
, var
);
929 if (row
!= tab
->n_row
- 1)
930 swap_rows(tab
, row
, tab
->n_row
- 1);
931 isl_tab_var_from_row(tab
, tab
->n_row
- 1)->index
= -1;
937 int isl_tab_mark_empty(struct isl_tab
*tab
)
941 if (!tab
->empty
&& tab
->need_undo
)
942 if (isl_tab_push(tab
, isl_tab_undo_empty
) < 0)
948 int isl_tab_freeze_constraint(struct isl_tab
*tab
, int con
)
950 struct isl_tab_var
*var
;
955 var
= &tab
->con
[con
];
963 return isl_tab_push_var(tab
, isl_tab_undo_freeze
, var
);
968 /* Update the rows signs after a pivot of "row" and "col", with "row_sgn"
969 * the original sign of the pivot element.
970 * We only keep track of row signs during PILP solving and in this case
971 * we only pivot a row with negative sign (meaning the value is always
972 * non-positive) using a positive pivot element.
974 * For each row j, the new value of the parametric constant is equal to
976 * a_j0 - a_jc a_r0/a_rc
978 * where a_j0 is the original parametric constant, a_rc is the pivot element,
979 * a_r0 is the parametric constant of the pivot row and a_jc is the
980 * pivot column entry of the row j.
981 * Since a_r0 is non-positive and a_rc is positive, the sign of row j
982 * remains the same if a_jc has the same sign as the row j or if
983 * a_jc is zero. In all other cases, we reset the sign to "unknown".
985 static void update_row_sign(struct isl_tab
*tab
, int row
, int col
, int row_sgn
)
988 struct isl_mat
*mat
= tab
->mat
;
989 unsigned off
= 2 + tab
->M
;
994 if (tab
->row_sign
[row
] == 0)
996 isl_assert(mat
->ctx
, row_sgn
> 0, return);
997 isl_assert(mat
->ctx
, tab
->row_sign
[row
] == isl_tab_row_neg
, return);
998 tab
->row_sign
[row
] = isl_tab_row_pos
;
999 for (i
= 0; i
< tab
->n_row
; ++i
) {
1003 s
= isl_int_sgn(mat
->row
[i
][off
+ col
]);
1006 if (!tab
->row_sign
[i
])
1008 if (s
< 0 && tab
->row_sign
[i
] == isl_tab_row_neg
)
1010 if (s
> 0 && tab
->row_sign
[i
] == isl_tab_row_pos
)
1012 tab
->row_sign
[i
] = isl_tab_row_unknown
;
1016 /* Given a row number "row" and a column number "col", pivot the tableau
1017 * such that the associated variables are interchanged.
1018 * The given row in the tableau expresses
1020 * x_r = a_r0 + \sum_i a_ri x_i
1024 * x_c = 1/a_rc x_r - a_r0/a_rc + sum_{i \ne r} -a_ri/a_rc
1026 * Substituting this equality into the other rows
1028 * x_j = a_j0 + \sum_i a_ji x_i
1030 * with a_jc \ne 0, we obtain
1032 * 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
1039 * where i is any other column and j is any other row,
1040 * is therefore transformed into
1042 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1043 * 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)
1045 * The transformation is performed along the following steps
1047 * d_r/n_rc n_ri/n_rc
1050 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1053 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1054 * n_jc/(|n_rc| d_j) n_ji/(|n_rc| d_j)
1056 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1057 * n_jc/(|n_rc| d_j) (n_ji |n_rc|)/(|n_rc| d_j)
1059 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1060 * n_jc/(|n_rc| d_j) (n_ji |n_rc| - s(n_rc)n_jc n_ri)/(|n_rc| d_j)
1062 * s(n_rc)d_r/|n_rc| -s(n_rc)n_ri/|n_rc|
1063 * 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)
1066 int isl_tab_pivot(struct isl_tab
*tab
, int row
, int col
)
1071 struct isl_mat
*mat
= tab
->mat
;
1072 struct isl_tab_var
*var
;
1073 unsigned off
= 2 + tab
->M
;
1075 isl_int_swap(mat
->row
[row
][0], mat
->row
[row
][off
+ col
]);
1076 sgn
= isl_int_sgn(mat
->row
[row
][0]);
1078 isl_int_neg(mat
->row
[row
][0], mat
->row
[row
][0]);
1079 isl_int_neg(mat
->row
[row
][off
+ col
], mat
->row
[row
][off
+ col
]);
1081 for (j
= 0; j
< off
- 1 + tab
->n_col
; ++j
) {
1082 if (j
== off
- 1 + col
)
1084 isl_int_neg(mat
->row
[row
][1 + j
], mat
->row
[row
][1 + j
]);
1086 if (!isl_int_is_one(mat
->row
[row
][0]))
1087 isl_seq_normalize(mat
->ctx
, mat
->row
[row
], off
+ tab
->n_col
);
1088 for (i
= 0; i
< tab
->n_row
; ++i
) {
1091 if (isl_int_is_zero(mat
->row
[i
][off
+ col
]))
1093 isl_int_mul(mat
->row
[i
][0], mat
->row
[i
][0], mat
->row
[row
][0]);
1094 for (j
= 0; j
< off
- 1 + tab
->n_col
; ++j
) {
1095 if (j
== off
- 1 + col
)
1097 isl_int_mul(mat
->row
[i
][1 + j
],
1098 mat
->row
[i
][1 + j
], mat
->row
[row
][0]);
1099 isl_int_addmul(mat
->row
[i
][1 + j
],
1100 mat
->row
[i
][off
+ col
], mat
->row
[row
][1 + j
]);
1102 isl_int_mul(mat
->row
[i
][off
+ col
],
1103 mat
->row
[i
][off
+ col
], mat
->row
[row
][off
+ col
]);
1104 if (!isl_int_is_one(mat
->row
[i
][0]))
1105 isl_seq_normalize(mat
->ctx
, mat
->row
[i
], off
+ tab
->n_col
);
1107 t
= tab
->row_var
[row
];
1108 tab
->row_var
[row
] = tab
->col_var
[col
];
1109 tab
->col_var
[col
] = t
;
1110 var
= isl_tab_var_from_row(tab
, row
);
1113 var
= var_from_col(tab
, col
);
1116 update_row_sign(tab
, row
, col
, sgn
);
1119 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
1120 if (isl_int_is_zero(mat
->row
[i
][off
+ col
]))
1122 if (!isl_tab_var_from_row(tab
, i
)->frozen
&&
1123 isl_tab_row_is_redundant(tab
, i
)) {
1124 int redo
= isl_tab_mark_redundant(tab
, i
);
1134 /* If "var" represents a column variable, then pivot is up (sgn > 0)
1135 * or down (sgn < 0) to a row. The variable is assumed not to be
1136 * unbounded in the specified direction.
1137 * If sgn = 0, then the variable is unbounded in both directions,
1138 * and we pivot with any row we can find.
1140 static int to_row(struct isl_tab
*tab
, struct isl_tab_var
*var
, int sign
) WARN_UNUSED
;
1141 static int to_row(struct isl_tab
*tab
, struct isl_tab_var
*var
, int sign
)
1144 unsigned off
= 2 + tab
->M
;
1150 for (r
= tab
->n_redundant
; r
< tab
->n_row
; ++r
)
1151 if (!isl_int_is_zero(tab
->mat
->row
[r
][off
+var
->index
]))
1153 isl_assert(tab
->mat
->ctx
, r
< tab
->n_row
, return -1);
1155 r
= pivot_row(tab
, NULL
, sign
, var
->index
);
1156 isl_assert(tab
->mat
->ctx
, r
>= 0, return -1);
1159 return isl_tab_pivot(tab
, r
, var
->index
);
1162 static void check_table(struct isl_tab
*tab
)
1168 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
1169 struct isl_tab_var
*var
;
1170 var
= isl_tab_var_from_row(tab
, i
);
1171 if (!var
->is_nonneg
)
1174 assert(!isl_int_is_neg(tab
->mat
->row
[i
][2]));
1175 if (isl_int_is_pos(tab
->mat
->row
[i
][2]))
1178 assert(!isl_int_is_neg(tab
->mat
->row
[i
][1]));
1182 /* Return the sign of the maximal value of "var".
1183 * If the sign is not negative, then on return from this function,
1184 * the sample value will also be non-negative.
1186 * If "var" is manifestly unbounded wrt positive values, we are done.
1187 * Otherwise, we pivot the variable up to a row if needed
1188 * Then we continue pivoting down until either
1189 * - no more down pivots can be performed
1190 * - the sample value is positive
1191 * - the variable is pivoted into a manifestly unbounded column
1193 static int sign_of_max(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1197 if (max_is_manifestly_unbounded(tab
, var
))
1199 if (to_row(tab
, var
, 1) < 0)
1201 while (!isl_int_is_pos(tab
->mat
->row
[var
->index
][1])) {
1202 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1204 return isl_int_sgn(tab
->mat
->row
[var
->index
][1]);
1205 if (isl_tab_pivot(tab
, row
, col
) < 0)
1207 if (!var
->is_row
) /* manifestly unbounded */
1213 static int row_is_neg(struct isl_tab
*tab
, int row
)
1216 return isl_int_is_neg(tab
->mat
->row
[row
][1]);
1217 if (isl_int_is_pos(tab
->mat
->row
[row
][2]))
1219 if (isl_int_is_neg(tab
->mat
->row
[row
][2]))
1221 return isl_int_is_neg(tab
->mat
->row
[row
][1]);
1224 static int row_sgn(struct isl_tab
*tab
, int row
)
1227 return isl_int_sgn(tab
->mat
->row
[row
][1]);
1228 if (!isl_int_is_zero(tab
->mat
->row
[row
][2]))
1229 return isl_int_sgn(tab
->mat
->row
[row
][2]);
1231 return isl_int_sgn(tab
->mat
->row
[row
][1]);
1234 /* Perform pivots until the row variable "var" has a non-negative
1235 * sample value or until no more upward pivots can be performed.
1236 * Return the sign of the sample value after the pivots have been
1239 static int restore_row(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1243 while (row_is_neg(tab
, var
->index
)) {
1244 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1247 if (isl_tab_pivot(tab
, row
, col
) < 0)
1249 if (!var
->is_row
) /* manifestly unbounded */
1252 return row_sgn(tab
, var
->index
);
1255 /* Perform pivots until we are sure that the row variable "var"
1256 * can attain non-negative values. After return from this
1257 * function, "var" is still a row variable, but its sample
1258 * value may not be non-negative, even if the function returns 1.
1260 static int at_least_zero(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1264 while (isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1265 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1268 if (row
== var
->index
) /* manifestly unbounded */
1270 if (isl_tab_pivot(tab
, row
, col
) < 0)
1273 return !isl_int_is_neg(tab
->mat
->row
[var
->index
][1]);
1276 /* Return a negative value if "var" can attain negative values.
1277 * Return a non-negative value otherwise.
1279 * If "var" is manifestly unbounded wrt negative values, we are done.
1280 * Otherwise, if var is in a column, we can pivot it down to a row.
1281 * Then we continue pivoting down until either
1282 * - the pivot would result in a manifestly unbounded column
1283 * => we don't perform the pivot, but simply return -1
1284 * - no more down pivots can be performed
1285 * - the sample value is negative
1286 * If the sample value becomes negative and the variable is supposed
1287 * to be nonnegative, then we undo the last pivot.
1288 * However, if the last pivot has made the pivoting variable
1289 * obviously redundant, then it may have moved to another row.
1290 * In that case we look for upward pivots until we reach a non-negative
1293 static int sign_of_min(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1296 struct isl_tab_var
*pivot_var
= NULL
;
1298 if (min_is_manifestly_unbounded(tab
, var
))
1302 row
= pivot_row(tab
, NULL
, -1, col
);
1303 pivot_var
= var_from_col(tab
, col
);
1304 if (isl_tab_pivot(tab
, row
, col
) < 0)
1306 if (var
->is_redundant
)
1308 if (isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1309 if (var
->is_nonneg
) {
1310 if (!pivot_var
->is_redundant
&&
1311 pivot_var
->index
== row
) {
1312 if (isl_tab_pivot(tab
, row
, col
) < 0)
1315 if (restore_row(tab
, var
) < -1)
1321 if (var
->is_redundant
)
1323 while (!isl_int_is_neg(tab
->mat
->row
[var
->index
][1])) {
1324 find_pivot(tab
, var
, var
, -1, &row
, &col
);
1325 if (row
== var
->index
)
1328 return isl_int_sgn(tab
->mat
->row
[var
->index
][1]);
1329 pivot_var
= var_from_col(tab
, col
);
1330 if (isl_tab_pivot(tab
, row
, col
) < 0)
1332 if (var
->is_redundant
)
1335 if (pivot_var
&& var
->is_nonneg
) {
1336 /* pivot back to non-negative value */
1337 if (!pivot_var
->is_redundant
&& pivot_var
->index
== row
) {
1338 if (isl_tab_pivot(tab
, row
, col
) < 0)
1341 if (restore_row(tab
, var
) < -1)
1347 static int row_at_most_neg_one(struct isl_tab
*tab
, int row
)
1350 if (isl_int_is_pos(tab
->mat
->row
[row
][2]))
1352 if (isl_int_is_neg(tab
->mat
->row
[row
][2]))
1355 return isl_int_is_neg(tab
->mat
->row
[row
][1]) &&
1356 isl_int_abs_ge(tab
->mat
->row
[row
][1],
1357 tab
->mat
->row
[row
][0]);
1360 /* Return 1 if "var" can attain values <= -1.
1361 * Return 0 otherwise.
1363 * The sample value of "var" is assumed to be non-negative when the
1364 * the function is called. If 1 is returned then the constraint
1365 * is not redundant and the sample value is made non-negative again before
1366 * the function returns.
1368 int isl_tab_min_at_most_neg_one(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1371 struct isl_tab_var
*pivot_var
;
1373 if (min_is_manifestly_unbounded(tab
, var
))
1377 row
= pivot_row(tab
, NULL
, -1, col
);
1378 pivot_var
= var_from_col(tab
, col
);
1379 if (isl_tab_pivot(tab
, row
, col
) < 0)
1381 if (var
->is_redundant
)
1383 if (row_at_most_neg_one(tab
, var
->index
)) {
1384 if (var
->is_nonneg
) {
1385 if (!pivot_var
->is_redundant
&&
1386 pivot_var
->index
== row
) {
1387 if (isl_tab_pivot(tab
, row
, col
) < 0)
1390 if (restore_row(tab
, var
) < -1)
1396 if (var
->is_redundant
)
1399 find_pivot(tab
, var
, var
, -1, &row
, &col
);
1400 if (row
== var
->index
) {
1401 if (restore_row(tab
, var
) < -1)
1407 pivot_var
= var_from_col(tab
, col
);
1408 if (isl_tab_pivot(tab
, row
, col
) < 0)
1410 if (var
->is_redundant
)
1412 } while (!row_at_most_neg_one(tab
, var
->index
));
1413 if (var
->is_nonneg
) {
1414 /* pivot back to non-negative value */
1415 if (!pivot_var
->is_redundant
&& pivot_var
->index
== row
)
1416 if (isl_tab_pivot(tab
, row
, col
) < 0)
1418 if (restore_row(tab
, var
) < -1)
1424 /* Return 1 if "var" can attain values >= 1.
1425 * Return 0 otherwise.
1427 static int at_least_one(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1432 if (max_is_manifestly_unbounded(tab
, var
))
1434 if (to_row(tab
, var
, 1) < 0)
1436 r
= tab
->mat
->row
[var
->index
];
1437 while (isl_int_lt(r
[1], r
[0])) {
1438 find_pivot(tab
, var
, var
, 1, &row
, &col
);
1440 return isl_int_ge(r
[1], r
[0]);
1441 if (row
== var
->index
) /* manifestly unbounded */
1443 if (isl_tab_pivot(tab
, row
, col
) < 0)
1449 static void swap_cols(struct isl_tab
*tab
, int col1
, int col2
)
1452 unsigned off
= 2 + tab
->M
;
1453 t
= tab
->col_var
[col1
];
1454 tab
->col_var
[col1
] = tab
->col_var
[col2
];
1455 tab
->col_var
[col2
] = t
;
1456 var_from_col(tab
, col1
)->index
= col1
;
1457 var_from_col(tab
, col2
)->index
= col2
;
1458 tab
->mat
= isl_mat_swap_cols(tab
->mat
, off
+ col1
, off
+ col2
);
1461 /* Mark column with index "col" as representing a zero variable.
1462 * If we may need to undo the operation the column is kept,
1463 * but no longer considered.
1464 * Otherwise, the column is simply removed.
1466 * The column may be interchanged with some other column. If it
1467 * is interchanged with a later column, return 1. Otherwise return 0.
1468 * If the columns are checked in order in the calling function,
1469 * then a return value of 1 means that the column with the given
1470 * column number may now contain a different column that
1471 * hasn't been checked yet.
1473 int isl_tab_kill_col(struct isl_tab
*tab
, int col
)
1475 var_from_col(tab
, col
)->is_zero
= 1;
1476 if (tab
->need_undo
) {
1477 if (isl_tab_push_var(tab
, isl_tab_undo_zero
,
1478 var_from_col(tab
, col
)) < 0)
1480 if (col
!= tab
->n_dead
)
1481 swap_cols(tab
, col
, tab
->n_dead
);
1485 if (col
!= tab
->n_col
- 1)
1486 swap_cols(tab
, col
, tab
->n_col
- 1);
1487 var_from_col(tab
, tab
->n_col
- 1)->index
= -1;
1493 /* Row variable "var" is non-negative and cannot attain any values
1494 * larger than zero. This means that the coefficients of the unrestricted
1495 * column variables are zero and that the coefficients of the non-negative
1496 * column variables are zero or negative.
1497 * Each of the non-negative variables with a negative coefficient can
1498 * then also be written as the negative sum of non-negative variables
1499 * and must therefore also be zero.
1501 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1502 static int close_row(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1505 struct isl_mat
*mat
= tab
->mat
;
1506 unsigned off
= 2 + tab
->M
;
1508 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, return -1);
1511 if (isl_tab_push_var(tab
, isl_tab_undo_zero
, var
) < 0)
1513 for (j
= tab
->n_dead
; j
< tab
->n_col
; ++j
) {
1514 if (isl_int_is_zero(mat
->row
[var
->index
][off
+ j
]))
1516 isl_assert(tab
->mat
->ctx
,
1517 isl_int_is_neg(mat
->row
[var
->index
][off
+ j
]), return -1);
1518 if (isl_tab_kill_col(tab
, j
))
1521 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
1526 /* Add a constraint to the tableau and allocate a row for it.
1527 * Return the index into the constraint array "con".
1529 int isl_tab_allocate_con(struct isl_tab
*tab
)
1533 isl_assert(tab
->mat
->ctx
, tab
->n_row
< tab
->mat
->n_row
, return -1);
1534 isl_assert(tab
->mat
->ctx
, tab
->n_con
< tab
->max_con
, return -1);
1537 tab
->con
[r
].index
= tab
->n_row
;
1538 tab
->con
[r
].is_row
= 1;
1539 tab
->con
[r
].is_nonneg
= 0;
1540 tab
->con
[r
].is_zero
= 0;
1541 tab
->con
[r
].is_redundant
= 0;
1542 tab
->con
[r
].frozen
= 0;
1543 tab
->con
[r
].negated
= 0;
1544 tab
->row_var
[tab
->n_row
] = ~r
;
1548 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
1554 /* Add a variable to the tableau and allocate a column for it.
1555 * Return the index into the variable array "var".
1557 int isl_tab_allocate_var(struct isl_tab
*tab
)
1561 unsigned off
= 2 + tab
->M
;
1563 isl_assert(tab
->mat
->ctx
, tab
->n_col
< tab
->mat
->n_col
, return -1);
1564 isl_assert(tab
->mat
->ctx
, tab
->n_var
< tab
->max_var
, return -1);
1567 tab
->var
[r
].index
= tab
->n_col
;
1568 tab
->var
[r
].is_row
= 0;
1569 tab
->var
[r
].is_nonneg
= 0;
1570 tab
->var
[r
].is_zero
= 0;
1571 tab
->var
[r
].is_redundant
= 0;
1572 tab
->var
[r
].frozen
= 0;
1573 tab
->var
[r
].negated
= 0;
1574 tab
->col_var
[tab
->n_col
] = r
;
1576 for (i
= 0; i
< tab
->n_row
; ++i
)
1577 isl_int_set_si(tab
->mat
->row
[i
][off
+ tab
->n_col
], 0);
1581 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->var
[r
]) < 0)
1587 /* Add a row to the tableau. The row is given as an affine combination
1588 * of the original variables and needs to be expressed in terms of the
1591 * We add each term in turn.
1592 * If r = n/d_r is the current sum and we need to add k x, then
1593 * if x is a column variable, we increase the numerator of
1594 * this column by k d_r
1595 * if x = f/d_x is a row variable, then the new representation of r is
1597 * n k f d_x/g n + d_r/g k f m/d_r n + m/d_g k f
1598 * --- + --- = ------------------- = -------------------
1599 * d_r d_r d_r d_x/g m
1601 * with g the gcd of d_r and d_x and m the lcm of d_r and d_x.
1603 int isl_tab_add_row(struct isl_tab
*tab
, isl_int
*line
)
1609 unsigned off
= 2 + tab
->M
;
1611 r
= isl_tab_allocate_con(tab
);
1617 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1618 isl_int_set_si(row
[0], 1);
1619 isl_int_set(row
[1], line
[0]);
1620 isl_seq_clr(row
+ 2, tab
->M
+ tab
->n_col
);
1621 for (i
= 0; i
< tab
->n_var
; ++i
) {
1622 if (tab
->var
[i
].is_zero
)
1624 if (tab
->var
[i
].is_row
) {
1626 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1627 isl_int_swap(a
, row
[0]);
1628 isl_int_divexact(a
, row
[0], a
);
1630 row
[0], tab
->mat
->row
[tab
->var
[i
].index
][0]);
1631 isl_int_mul(b
, b
, line
[1 + i
]);
1632 isl_seq_combine(row
+ 1, a
, row
+ 1,
1633 b
, tab
->mat
->row
[tab
->var
[i
].index
] + 1,
1634 1 + tab
->M
+ tab
->n_col
);
1636 isl_int_addmul(row
[off
+ tab
->var
[i
].index
],
1637 line
[1 + i
], row
[0]);
1638 if (tab
->M
&& i
>= tab
->n_param
&& i
< tab
->n_var
- tab
->n_div
)
1639 isl_int_submul(row
[2], line
[1 + i
], row
[0]);
1641 isl_seq_normalize(tab
->mat
->ctx
, row
, off
+ tab
->n_col
);
1646 tab
->row_sign
[tab
->con
[r
].index
] = 0;
1651 static int drop_row(struct isl_tab
*tab
, int row
)
1653 isl_assert(tab
->mat
->ctx
, ~tab
->row_var
[row
] == tab
->n_con
- 1, return -1);
1654 if (row
!= tab
->n_row
- 1)
1655 swap_rows(tab
, row
, tab
->n_row
- 1);
1661 static int drop_col(struct isl_tab
*tab
, int col
)
1663 isl_assert(tab
->mat
->ctx
, tab
->col_var
[col
] == tab
->n_var
- 1, return -1);
1664 if (col
!= tab
->n_col
- 1)
1665 swap_cols(tab
, col
, tab
->n_col
- 1);
1671 /* Add inequality "ineq" and check if it conflicts with the
1672 * previously added constraints or if it is obviously redundant.
1674 int isl_tab_add_ineq(struct isl_tab
*tab
, isl_int
*ineq
)
1683 struct isl_basic_map
*bmap
= tab
->bmap
;
1685 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
1686 isl_assert(tab
->mat
->ctx
,
1687 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
1688 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, ineq
);
1689 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1696 isl_int_swap(ineq
[0], cst
);
1698 r
= isl_tab_add_row(tab
, ineq
);
1700 isl_int_swap(ineq
[0], cst
);
1705 tab
->con
[r
].is_nonneg
= 1;
1706 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
1708 if (isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
)) {
1709 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1714 sgn
= restore_row(tab
, &tab
->con
[r
]);
1718 return isl_tab_mark_empty(tab
);
1719 if (tab
->con
[r
].is_row
&& isl_tab_row_is_redundant(tab
, tab
->con
[r
].index
))
1720 if (isl_tab_mark_redundant(tab
, tab
->con
[r
].index
) < 0)
1725 /* Pivot a non-negative variable down until it reaches the value zero
1726 * and then pivot the variable into a column position.
1728 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
1729 static int to_col(struct isl_tab
*tab
, struct isl_tab_var
*var
)
1733 unsigned off
= 2 + tab
->M
;
1738 while (isl_int_is_pos(tab
->mat
->row
[var
->index
][1])) {
1739 find_pivot(tab
, var
, NULL
, -1, &row
, &col
);
1740 isl_assert(tab
->mat
->ctx
, row
!= -1, return -1);
1741 if (isl_tab_pivot(tab
, row
, col
) < 0)
1747 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
)
1748 if (!isl_int_is_zero(tab
->mat
->row
[var
->index
][off
+ i
]))
1751 isl_assert(tab
->mat
->ctx
, i
< tab
->n_col
, return -1);
1752 if (isl_tab_pivot(tab
, var
->index
, i
) < 0)
1758 /* We assume Gaussian elimination has been performed on the equalities.
1759 * The equalities can therefore never conflict.
1760 * Adding the equalities is currently only really useful for a later call
1761 * to isl_tab_ineq_type.
1763 static struct isl_tab
*add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1770 r
= isl_tab_add_row(tab
, eq
);
1774 r
= tab
->con
[r
].index
;
1775 i
= isl_seq_first_non_zero(tab
->mat
->row
[r
] + 2 + tab
->M
+ tab
->n_dead
,
1776 tab
->n_col
- tab
->n_dead
);
1777 isl_assert(tab
->mat
->ctx
, i
>= 0, goto error
);
1779 if (isl_tab_pivot(tab
, r
, i
) < 0)
1781 if (isl_tab_kill_col(tab
, i
) < 0)
1791 static int row_is_manifestly_zero(struct isl_tab
*tab
, int row
)
1793 unsigned off
= 2 + tab
->M
;
1795 if (!isl_int_is_zero(tab
->mat
->row
[row
][1]))
1797 if (tab
->M
&& !isl_int_is_zero(tab
->mat
->row
[row
][2]))
1799 return isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
1800 tab
->n_col
- tab
->n_dead
) == -1;
1803 /* Add an equality that is known to be valid for the given tableau.
1805 struct isl_tab
*isl_tab_add_valid_eq(struct isl_tab
*tab
, isl_int
*eq
)
1807 struct isl_tab_var
*var
;
1812 r
= isl_tab_add_row(tab
, eq
);
1818 if (row_is_manifestly_zero(tab
, r
)) {
1820 if (isl_tab_mark_redundant(tab
, r
) < 0)
1825 if (isl_int_is_neg(tab
->mat
->row
[r
][1])) {
1826 isl_seq_neg(tab
->mat
->row
[r
] + 1, tab
->mat
->row
[r
] + 1,
1831 if (to_col(tab
, var
) < 0)
1834 if (isl_tab_kill_col(tab
, var
->index
) < 0)
1843 static int add_zero_row(struct isl_tab
*tab
)
1848 r
= isl_tab_allocate_con(tab
);
1852 row
= tab
->mat
->row
[tab
->con
[r
].index
];
1853 isl_seq_clr(row
+ 1, 1 + tab
->M
+ tab
->n_col
);
1854 isl_int_set_si(row
[0], 1);
1859 /* Add equality "eq" and check if it conflicts with the
1860 * previously added constraints or if it is obviously redundant.
1862 struct isl_tab
*isl_tab_add_eq(struct isl_tab
*tab
, isl_int
*eq
)
1864 struct isl_tab_undo
*snap
= NULL
;
1865 struct isl_tab_var
*var
;
1873 isl_assert(tab
->mat
->ctx
, !tab
->M
, goto error
);
1876 snap
= isl_tab_snap(tab
);
1880 isl_int_swap(eq
[0], cst
);
1882 r
= isl_tab_add_row(tab
, eq
);
1884 isl_int_swap(eq
[0], cst
);
1892 if (row_is_manifestly_zero(tab
, row
)) {
1894 if (isl_tab_rollback(tab
, snap
) < 0)
1902 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1903 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1905 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1906 tab
->bmap
= isl_basic_map_add_ineq(tab
->bmap
, eq
);
1907 isl_seq_neg(eq
, eq
, 1 + tab
->n_var
);
1908 if (isl_tab_push(tab
, isl_tab_undo_bmap_ineq
) < 0)
1912 if (add_zero_row(tab
) < 0)
1916 sgn
= isl_int_sgn(tab
->mat
->row
[row
][1]);
1919 isl_seq_neg(tab
->mat
->row
[row
] + 1, tab
->mat
->row
[row
] + 1,
1926 sgn
= sign_of_max(tab
, var
);
1930 if (isl_tab_mark_empty(tab
) < 0)
1937 if (to_col(tab
, var
) < 0)
1940 if (isl_tab_kill_col(tab
, var
->index
) < 0)
1949 /* Construct and return an inequality that expresses an upper bound
1951 * In particular, if the div is given by
1955 * then the inequality expresses
1959 static struct isl_vec
*ineq_for_div(struct isl_basic_map
*bmap
, unsigned div
)
1963 struct isl_vec
*ineq
;
1968 total
= isl_basic_map_total_dim(bmap
);
1969 div_pos
= 1 + total
- bmap
->n_div
+ div
;
1971 ineq
= isl_vec_alloc(bmap
->ctx
, 1 + total
);
1975 isl_seq_cpy(ineq
->el
, bmap
->div
[div
] + 1, 1 + total
);
1976 isl_int_neg(ineq
->el
[div_pos
], bmap
->div
[div
][0]);
1980 /* For a div d = floor(f/m), add the constraints
1983 * -(f-(m-1)) + m d >= 0
1985 * Note that the second constraint is the negation of
1989 * If add_ineq is not NULL, then this function is used
1990 * instead of isl_tab_add_ineq to effectively add the inequalities.
1992 static int add_div_constraints(struct isl_tab
*tab
, unsigned div
,
1993 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
1997 struct isl_vec
*ineq
;
1999 total
= isl_basic_map_total_dim(tab
->bmap
);
2000 div_pos
= 1 + total
- tab
->bmap
->n_div
+ div
;
2002 ineq
= ineq_for_div(tab
->bmap
, div
);
2007 if (add_ineq(user
, ineq
->el
) < 0)
2010 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2014 isl_seq_neg(ineq
->el
, tab
->bmap
->div
[div
] + 1, 1 + total
);
2015 isl_int_set(ineq
->el
[div_pos
], tab
->bmap
->div
[div
][0]);
2016 isl_int_add(ineq
->el
[0], ineq
->el
[0], ineq
->el
[div_pos
]);
2017 isl_int_sub_ui(ineq
->el
[0], ineq
->el
[0], 1);
2020 if (add_ineq(user
, ineq
->el
) < 0)
2023 if (isl_tab_add_ineq(tab
, ineq
->el
) < 0)
2035 /* Add an extra div, prescrived by "div" to the tableau and
2036 * the associated bmap (which is assumed to be non-NULL).
2038 * If add_ineq is not NULL, then this function is used instead
2039 * of isl_tab_add_ineq to add the div constraints.
2040 * This complication is needed because the code in isl_tab_pip
2041 * wants to perform some extra processing when an inequality
2042 * is added to the tableau.
2044 int isl_tab_add_div(struct isl_tab
*tab
, __isl_keep isl_vec
*div
,
2045 int (*add_ineq
)(void *user
, isl_int
*), void *user
)
2055 isl_assert(tab
->mat
->ctx
, tab
->bmap
, return -1);
2057 for (i
= 0; i
< tab
->n_var
; ++i
) {
2058 if (isl_int_is_neg(div
->el
[2 + i
]))
2060 if (isl_int_is_zero(div
->el
[2 + i
]))
2062 if (!tab
->var
[i
].is_nonneg
)
2065 nonneg
= i
== tab
->n_var
&& !isl_int_is_neg(div
->el
[1]);
2067 if (isl_tab_extend_cons(tab
, 3) < 0)
2069 if (isl_tab_extend_vars(tab
, 1) < 0)
2071 r
= isl_tab_allocate_var(tab
);
2076 tab
->var
[r
].is_nonneg
= 1;
2078 tab
->bmap
= isl_basic_map_extend_dim(tab
->bmap
,
2079 isl_basic_map_get_dim(tab
->bmap
), 1, 0, 2);
2080 k
= isl_basic_map_alloc_div(tab
->bmap
);
2083 isl_seq_cpy(tab
->bmap
->div
[k
], div
->el
, div
->size
);
2084 if (isl_tab_push(tab
, isl_tab_undo_bmap_div
) < 0)
2087 if (add_div_constraints(tab
, k
, add_ineq
, user
) < 0)
2093 struct isl_tab
*isl_tab_from_basic_map(struct isl_basic_map
*bmap
)
2096 struct isl_tab
*tab
;
2100 tab
= isl_tab_alloc(bmap
->ctx
,
2101 isl_basic_map_total_dim(bmap
) + bmap
->n_ineq
+ 1,
2102 isl_basic_map_total_dim(bmap
), 0);
2105 tab
->rational
= ISL_F_ISSET(bmap
, ISL_BASIC_MAP_RATIONAL
);
2106 if (ISL_F_ISSET(bmap
, ISL_BASIC_MAP_EMPTY
)) {
2107 if (isl_tab_mark_empty(tab
) < 0)
2111 for (i
= 0; i
< bmap
->n_eq
; ++i
) {
2112 tab
= add_eq(tab
, bmap
->eq
[i
]);
2116 for (i
= 0; i
< bmap
->n_ineq
; ++i
) {
2117 if (isl_tab_add_ineq(tab
, bmap
->ineq
[i
]) < 0)
2128 struct isl_tab
*isl_tab_from_basic_set(struct isl_basic_set
*bset
)
2130 return isl_tab_from_basic_map((struct isl_basic_map
*)bset
);
2133 /* Construct a tableau corresponding to the recession cone of "bset".
2135 struct isl_tab
*isl_tab_from_recession_cone(struct isl_basic_set
*bset
)
2139 struct isl_tab
*tab
;
2143 tab
= isl_tab_alloc(bset
->ctx
, bset
->n_eq
+ bset
->n_ineq
,
2144 isl_basic_set_total_dim(bset
), 0);
2147 tab
->rational
= ISL_F_ISSET(bset
, ISL_BASIC_SET_RATIONAL
);
2151 for (i
= 0; i
< bset
->n_eq
; ++i
) {
2152 isl_int_swap(bset
->eq
[i
][0], cst
);
2153 tab
= add_eq(tab
, bset
->eq
[i
]);
2154 isl_int_swap(bset
->eq
[i
][0], cst
);
2158 for (i
= 0; i
< bset
->n_ineq
; ++i
) {
2160 isl_int_swap(bset
->ineq
[i
][0], cst
);
2161 r
= isl_tab_add_row(tab
, bset
->ineq
[i
]);
2162 isl_int_swap(bset
->ineq
[i
][0], cst
);
2165 tab
->con
[r
].is_nonneg
= 1;
2166 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2178 /* Assuming "tab" is the tableau of a cone, check if the cone is
2179 * bounded, i.e., if it is empty or only contains the origin.
2181 int isl_tab_cone_is_bounded(struct isl_tab
*tab
)
2189 if (tab
->n_dead
== tab
->n_col
)
2193 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2194 struct isl_tab_var
*var
;
2196 var
= isl_tab_var_from_row(tab
, i
);
2197 if (!var
->is_nonneg
)
2199 sgn
= sign_of_max(tab
, var
);
2204 if (close_row(tab
, var
) < 0)
2208 if (tab
->n_dead
== tab
->n_col
)
2210 if (i
== tab
->n_row
)
2215 int isl_tab_sample_is_integer(struct isl_tab
*tab
)
2222 for (i
= 0; i
< tab
->n_var
; ++i
) {
2224 if (!tab
->var
[i
].is_row
)
2226 row
= tab
->var
[i
].index
;
2227 if (!isl_int_is_divisible_by(tab
->mat
->row
[row
][1],
2228 tab
->mat
->row
[row
][0]))
2234 static struct isl_vec
*extract_integer_sample(struct isl_tab
*tab
)
2237 struct isl_vec
*vec
;
2239 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2243 isl_int_set_si(vec
->block
.data
[0], 1);
2244 for (i
= 0; i
< tab
->n_var
; ++i
) {
2245 if (!tab
->var
[i
].is_row
)
2246 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2248 int row
= tab
->var
[i
].index
;
2249 isl_int_divexact(vec
->block
.data
[1 + i
],
2250 tab
->mat
->row
[row
][1], tab
->mat
->row
[row
][0]);
2257 struct isl_vec
*isl_tab_get_sample_value(struct isl_tab
*tab
)
2260 struct isl_vec
*vec
;
2266 vec
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_var
);
2272 isl_int_set_si(vec
->block
.data
[0], 1);
2273 for (i
= 0; i
< tab
->n_var
; ++i
) {
2275 if (!tab
->var
[i
].is_row
) {
2276 isl_int_set_si(vec
->block
.data
[1 + i
], 0);
2279 row
= tab
->var
[i
].index
;
2280 isl_int_gcd(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2281 isl_int_divexact(m
, tab
->mat
->row
[row
][0], m
);
2282 isl_seq_scale(vec
->block
.data
, vec
->block
.data
, m
, 1 + i
);
2283 isl_int_divexact(m
, vec
->block
.data
[0], tab
->mat
->row
[row
][0]);
2284 isl_int_mul(vec
->block
.data
[1 + i
], m
, tab
->mat
->row
[row
][1]);
2286 vec
= isl_vec_normalize(vec
);
2292 /* Update "bmap" based on the results of the tableau "tab".
2293 * In particular, implicit equalities are made explicit, redundant constraints
2294 * are removed and if the sample value happens to be integer, it is stored
2295 * in "bmap" (unless "bmap" already had an integer sample).
2297 * The tableau is assumed to have been created from "bmap" using
2298 * isl_tab_from_basic_map.
2300 struct isl_basic_map
*isl_basic_map_update_from_tab(struct isl_basic_map
*bmap
,
2301 struct isl_tab
*tab
)
2313 bmap
= isl_basic_map_set_to_empty(bmap
);
2315 for (i
= bmap
->n_ineq
- 1; i
>= 0; --i
) {
2316 if (isl_tab_is_equality(tab
, n_eq
+ i
))
2317 isl_basic_map_inequality_to_equality(bmap
, i
);
2318 else if (isl_tab_is_redundant(tab
, n_eq
+ i
))
2319 isl_basic_map_drop_inequality(bmap
, i
);
2321 if (bmap
->n_eq
!= n_eq
)
2322 isl_basic_map_gauss(bmap
, NULL
);
2323 if (!tab
->rational
&&
2324 !bmap
->sample
&& isl_tab_sample_is_integer(tab
))
2325 bmap
->sample
= extract_integer_sample(tab
);
2329 struct isl_basic_set
*isl_basic_set_update_from_tab(struct isl_basic_set
*bset
,
2330 struct isl_tab
*tab
)
2332 return (struct isl_basic_set
*)isl_basic_map_update_from_tab(
2333 (struct isl_basic_map
*)bset
, tab
);
2336 /* Given a non-negative variable "var", add a new non-negative variable
2337 * that is the opposite of "var", ensuring that var can only attain the
2339 * If var = n/d is a row variable, then the new variable = -n/d.
2340 * If var is a column variables, then the new variable = -var.
2341 * If the new variable cannot attain non-negative values, then
2342 * the resulting tableau is empty.
2343 * Otherwise, we know the value will be zero and we close the row.
2345 static struct isl_tab
*cut_to_hyperplane(struct isl_tab
*tab
,
2346 struct isl_tab_var
*var
)
2351 unsigned off
= 2 + tab
->M
;
2355 isl_assert(tab
->mat
->ctx
, !var
->is_redundant
, goto error
);
2356 isl_assert(tab
->mat
->ctx
, var
->is_nonneg
, goto error
);
2358 if (isl_tab_extend_cons(tab
, 1) < 0)
2362 tab
->con
[r
].index
= tab
->n_row
;
2363 tab
->con
[r
].is_row
= 1;
2364 tab
->con
[r
].is_nonneg
= 0;
2365 tab
->con
[r
].is_zero
= 0;
2366 tab
->con
[r
].is_redundant
= 0;
2367 tab
->con
[r
].frozen
= 0;
2368 tab
->con
[r
].negated
= 0;
2369 tab
->row_var
[tab
->n_row
] = ~r
;
2370 row
= tab
->mat
->row
[tab
->n_row
];
2373 isl_int_set(row
[0], tab
->mat
->row
[var
->index
][0]);
2374 isl_seq_neg(row
+ 1,
2375 tab
->mat
->row
[var
->index
] + 1, 1 + tab
->n_col
);
2377 isl_int_set_si(row
[0], 1);
2378 isl_seq_clr(row
+ 1, 1 + tab
->n_col
);
2379 isl_int_set_si(row
[off
+ var
->index
], -1);
2384 if (isl_tab_push_var(tab
, isl_tab_undo_allocate
, &tab
->con
[r
]) < 0)
2387 sgn
= sign_of_max(tab
, &tab
->con
[r
]);
2391 if (isl_tab_mark_empty(tab
) < 0)
2395 tab
->con
[r
].is_nonneg
= 1;
2396 if (isl_tab_push_var(tab
, isl_tab_undo_nonneg
, &tab
->con
[r
]) < 0)
2399 if (close_row(tab
, &tab
->con
[r
]) < 0)
2408 /* Given a tableau "tab" and an inequality constraint "con" of the tableau,
2409 * relax the inequality by one. That is, the inequality r >= 0 is replaced
2410 * by r' = r + 1 >= 0.
2411 * If r is a row variable, we simply increase the constant term by one
2412 * (taking into account the denominator).
2413 * If r is a column variable, then we need to modify each row that
2414 * refers to r = r' - 1 by substituting this equality, effectively
2415 * subtracting the coefficient of the column from the constant.
2416 * We should only do this if the minimum is manifestly unbounded,
2417 * however. Otherwise, we may end up with negative sample values
2418 * for non-negative variables.
2419 * So, if r is a column variable with a minimum that is not
2420 * manifestly unbounded, then we need to move it to a row.
2421 * However, the sample value of this row may be negative,
2422 * even after the relaxation, so we need to restore it.
2423 * We therefore prefer to pivot a column up to a row, if possible.
2425 struct isl_tab
*isl_tab_relax(struct isl_tab
*tab
, int con
)
2427 struct isl_tab_var
*var
;
2428 unsigned off
= 2 + tab
->M
;
2433 var
= &tab
->con
[con
];
2435 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2436 if (to_row(tab
, var
, 1) < 0)
2438 if (!var
->is_row
&& !min_is_manifestly_unbounded(tab
, var
))
2439 if (to_row(tab
, var
, -1) < 0)
2443 isl_int_add(tab
->mat
->row
[var
->index
][1],
2444 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2445 if (restore_row(tab
, var
) < 0)
2450 for (i
= 0; i
< tab
->n_row
; ++i
) {
2451 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2453 isl_int_sub(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2454 tab
->mat
->row
[i
][off
+ var
->index
]);
2459 if (isl_tab_push_var(tab
, isl_tab_undo_relax
, var
) < 0)
2468 struct isl_tab
*isl_tab_select_facet(struct isl_tab
*tab
, int con
)
2473 return cut_to_hyperplane(tab
, &tab
->con
[con
]);
2476 static int may_be_equality(struct isl_tab
*tab
, int row
)
2478 unsigned off
= 2 + tab
->M
;
2479 return (tab
->rational
? isl_int_is_zero(tab
->mat
->row
[row
][1])
2480 : isl_int_lt(tab
->mat
->row
[row
][1],
2481 tab
->mat
->row
[row
][0])) &&
2482 isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
2483 tab
->n_col
- tab
->n_dead
) != -1;
2486 /* Check for (near) equalities among the constraints.
2487 * A constraint is an equality if it is non-negative and if
2488 * its maximal value is either
2489 * - zero (in case of rational tableaus), or
2490 * - strictly less than 1 (in case of integer tableaus)
2492 * We first mark all non-redundant and non-dead variables that
2493 * are not frozen and not obviously not an equality.
2494 * Then we iterate over all marked variables if they can attain
2495 * any values larger than zero or at least one.
2496 * If the maximal value is zero, we mark any column variables
2497 * that appear in the row as being zero and mark the row as being redundant.
2498 * Otherwise, if the maximal value is strictly less than one (and the
2499 * tableau is integer), then we restrict the value to being zero
2500 * by adding an opposite non-negative variable.
2502 struct isl_tab
*isl_tab_detect_implicit_equalities(struct isl_tab
*tab
)
2511 if (tab
->n_dead
== tab
->n_col
)
2515 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2516 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2517 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2518 may_be_equality(tab
, i
);
2522 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2523 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2524 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2529 struct isl_tab_var
*var
;
2531 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2532 var
= isl_tab_var_from_row(tab
, i
);
2536 if (i
== tab
->n_row
) {
2537 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2538 var
= var_from_col(tab
, i
);
2542 if (i
== tab
->n_col
)
2547 sgn
= sign_of_max(tab
, var
);
2551 if (close_row(tab
, var
) < 0)
2553 } else if (!tab
->rational
&& !at_least_one(tab
, var
)) {
2554 tab
= cut_to_hyperplane(tab
, var
);
2555 return isl_tab_detect_implicit_equalities(tab
);
2557 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2558 var
= isl_tab_var_from_row(tab
, i
);
2561 if (may_be_equality(tab
, i
))
2574 static int con_is_redundant(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2578 if (tab
->rational
) {
2579 int sgn
= sign_of_min(tab
, var
);
2584 int irred
= isl_tab_min_at_most_neg_one(tab
, var
);
2591 /* Check for (near) redundant constraints.
2592 * A constraint is redundant if it is non-negative and if
2593 * its minimal value (temporarily ignoring the non-negativity) is either
2594 * - zero (in case of rational tableaus), or
2595 * - strictly larger than -1 (in case of integer tableaus)
2597 * We first mark all non-redundant and non-dead variables that
2598 * are not frozen and not obviously negatively unbounded.
2599 * Then we iterate over all marked variables if they can attain
2600 * any values smaller than zero or at most negative one.
2601 * If not, we mark the row as being redundant (assuming it hasn't
2602 * been detected as being obviously redundant in the mean time).
2604 int isl_tab_detect_redundant(struct isl_tab
*tab
)
2613 if (tab
->n_redundant
== tab
->n_row
)
2617 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2618 struct isl_tab_var
*var
= isl_tab_var_from_row(tab
, i
);
2619 var
->marked
= !var
->frozen
&& var
->is_nonneg
;
2623 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2624 struct isl_tab_var
*var
= var_from_col(tab
, i
);
2625 var
->marked
= !var
->frozen
&& var
->is_nonneg
&&
2626 !min_is_manifestly_unbounded(tab
, var
);
2631 struct isl_tab_var
*var
;
2633 for (i
= tab
->n_redundant
; i
< tab
->n_row
; ++i
) {
2634 var
= isl_tab_var_from_row(tab
, i
);
2638 if (i
== tab
->n_row
) {
2639 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2640 var
= var_from_col(tab
, i
);
2644 if (i
== tab
->n_col
)
2649 red
= con_is_redundant(tab
, var
);
2652 if (red
&& !var
->is_redundant
)
2653 if (isl_tab_mark_redundant(tab
, var
->index
) < 0)
2655 for (i
= tab
->n_dead
; i
< tab
->n_col
; ++i
) {
2656 var
= var_from_col(tab
, i
);
2659 if (!min_is_manifestly_unbounded(tab
, var
))
2669 int isl_tab_is_equality(struct isl_tab
*tab
, int con
)
2676 if (tab
->con
[con
].is_zero
)
2678 if (tab
->con
[con
].is_redundant
)
2680 if (!tab
->con
[con
].is_row
)
2681 return tab
->con
[con
].index
< tab
->n_dead
;
2683 row
= tab
->con
[con
].index
;
2686 return isl_int_is_zero(tab
->mat
->row
[row
][1]) &&
2687 isl_seq_first_non_zero(tab
->mat
->row
[row
] + 2 + tab
->n_dead
,
2688 tab
->n_col
- tab
->n_dead
) == -1;
2691 /* Return the minimial value of the affine expression "f" with denominator
2692 * "denom" in *opt, *opt_denom, assuming the tableau is not empty and
2693 * the expression cannot attain arbitrarily small values.
2694 * If opt_denom is NULL, then *opt is rounded up to the nearest integer.
2695 * The return value reflects the nature of the result (empty, unbounded,
2696 * minmimal value returned in *opt).
2698 enum isl_lp_result
isl_tab_min(struct isl_tab
*tab
,
2699 isl_int
*f
, isl_int denom
, isl_int
*opt
, isl_int
*opt_denom
,
2703 enum isl_lp_result res
= isl_lp_ok
;
2704 struct isl_tab_var
*var
;
2705 struct isl_tab_undo
*snap
;
2708 return isl_lp_empty
;
2710 snap
= isl_tab_snap(tab
);
2711 r
= isl_tab_add_row(tab
, f
);
2713 return isl_lp_error
;
2715 isl_int_mul(tab
->mat
->row
[var
->index
][0],
2716 tab
->mat
->row
[var
->index
][0], denom
);
2719 find_pivot(tab
, var
, var
, -1, &row
, &col
);
2720 if (row
== var
->index
) {
2721 res
= isl_lp_unbounded
;
2726 if (isl_tab_pivot(tab
, row
, col
) < 0)
2727 return isl_lp_error
;
2729 if (ISL_FL_ISSET(flags
, ISL_TAB_SAVE_DUAL
)) {
2732 isl_vec_free(tab
->dual
);
2733 tab
->dual
= isl_vec_alloc(tab
->mat
->ctx
, 1 + tab
->n_con
);
2735 return isl_lp_error
;
2736 isl_int_set(tab
->dual
->el
[0], tab
->mat
->row
[var
->index
][0]);
2737 for (i
= 0; i
< tab
->n_con
; ++i
) {
2739 if (tab
->con
[i
].is_row
) {
2740 isl_int_set_si(tab
->dual
->el
[1 + i
], 0);
2743 pos
= 2 + tab
->M
+ tab
->con
[i
].index
;
2744 if (tab
->con
[i
].negated
)
2745 isl_int_neg(tab
->dual
->el
[1 + i
],
2746 tab
->mat
->row
[var
->index
][pos
]);
2748 isl_int_set(tab
->dual
->el
[1 + i
],
2749 tab
->mat
->row
[var
->index
][pos
]);
2752 if (opt
&& res
== isl_lp_ok
) {
2754 isl_int_set(*opt
, tab
->mat
->row
[var
->index
][1]);
2755 isl_int_set(*opt_denom
, tab
->mat
->row
[var
->index
][0]);
2757 isl_int_cdiv_q(*opt
, tab
->mat
->row
[var
->index
][1],
2758 tab
->mat
->row
[var
->index
][0]);
2760 if (isl_tab_rollback(tab
, snap
) < 0)
2761 return isl_lp_error
;
2765 int isl_tab_is_redundant(struct isl_tab
*tab
, int con
)
2769 if (tab
->con
[con
].is_zero
)
2771 if (tab
->con
[con
].is_redundant
)
2773 return tab
->con
[con
].is_row
&& tab
->con
[con
].index
< tab
->n_redundant
;
2776 /* Take a snapshot of the tableau that can be restored by s call to
2779 struct isl_tab_undo
*isl_tab_snap(struct isl_tab
*tab
)
2787 /* Undo the operation performed by isl_tab_relax.
2789 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
) WARN_UNUSED
;
2790 static int unrelax(struct isl_tab
*tab
, struct isl_tab_var
*var
)
2792 unsigned off
= 2 + tab
->M
;
2794 if (!var
->is_row
&& !max_is_manifestly_unbounded(tab
, var
))
2795 if (to_row(tab
, var
, 1) < 0)
2799 isl_int_sub(tab
->mat
->row
[var
->index
][1],
2800 tab
->mat
->row
[var
->index
][1], tab
->mat
->row
[var
->index
][0]);
2801 if (var
->is_nonneg
) {
2802 int sgn
= restore_row(tab
, var
);
2803 isl_assert(tab
->mat
->ctx
, sgn
>= 0, return -1);
2808 for (i
= 0; i
< tab
->n_row
; ++i
) {
2809 if (isl_int_is_zero(tab
->mat
->row
[i
][off
+ var
->index
]))
2811 isl_int_add(tab
->mat
->row
[i
][1], tab
->mat
->row
[i
][1],
2812 tab
->mat
->row
[i
][off
+ var
->index
]);
2820 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
2821 static int perform_undo_var(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
2823 struct isl_tab_var
*var
= var_from_index(tab
, undo
->u
.var_index
);
2824 switch(undo
->type
) {
2825 case isl_tab_undo_nonneg
:
2828 case isl_tab_undo_redundant
:
2829 var
->is_redundant
= 0;
2832 case isl_tab_undo_freeze
:
2835 case isl_tab_undo_zero
:
2840 case isl_tab_undo_allocate
:
2841 if (undo
->u
.var_index
>= 0) {
2842 isl_assert(tab
->mat
->ctx
, !var
->is_row
, return -1);
2843 drop_col(tab
, var
->index
);
2847 if (!max_is_manifestly_unbounded(tab
, var
)) {
2848 if (to_row(tab
, var
, 1) < 0)
2850 } else if (!min_is_manifestly_unbounded(tab
, var
)) {
2851 if (to_row(tab
, var
, -1) < 0)
2854 if (to_row(tab
, var
, 0) < 0)
2857 drop_row(tab
, var
->index
);
2859 case isl_tab_undo_relax
:
2860 return unrelax(tab
, var
);
2866 /* Restore the tableau to the state where the basic variables
2867 * are those in "col_var".
2868 * We first construct a list of variables that are currently in
2869 * the basis, but shouldn't. Then we iterate over all variables
2870 * that should be in the basis and for each one that is currently
2871 * not in the basis, we exchange it with one of the elements of the
2872 * list constructed before.
2873 * We can always find an appropriate variable to pivot with because
2874 * the current basis is mapped to the old basis by a non-singular
2875 * matrix and so we can never end up with a zero row.
2877 static int restore_basis(struct isl_tab
*tab
, int *col_var
)
2881 int *extra
= NULL
; /* current columns that contain bad stuff */
2882 unsigned off
= 2 + tab
->M
;
2884 extra
= isl_alloc_array(tab
->mat
->ctx
, int, tab
->n_col
);
2887 for (i
= 0; i
< tab
->n_col
; ++i
) {
2888 for (j
= 0; j
< tab
->n_col
; ++j
)
2889 if (tab
->col_var
[i
] == col_var
[j
])
2893 extra
[n_extra
++] = i
;
2895 for (i
= 0; i
< tab
->n_col
&& n_extra
> 0; ++i
) {
2896 struct isl_tab_var
*var
;
2899 for (j
= 0; j
< tab
->n_col
; ++j
)
2900 if (col_var
[i
] == tab
->col_var
[j
])
2904 var
= var_from_index(tab
, col_var
[i
]);
2906 for (j
= 0; j
< n_extra
; ++j
)
2907 if (!isl_int_is_zero(tab
->mat
->row
[row
][off
+extra
[j
]]))
2909 isl_assert(tab
->mat
->ctx
, j
< n_extra
, goto error
);
2910 if (isl_tab_pivot(tab
, row
, extra
[j
]) < 0)
2912 extra
[j
] = extra
[--n_extra
];
2924 /* Remove all samples with index n or greater, i.e., those samples
2925 * that were added since we saved this number of samples in
2926 * isl_tab_save_samples.
2928 static void drop_samples_since(struct isl_tab
*tab
, int n
)
2932 for (i
= tab
->n_sample
- 1; i
>= 0 && tab
->n_sample
> n
; --i
) {
2933 if (tab
->sample_index
[i
] < n
)
2936 if (i
!= tab
->n_sample
- 1) {
2937 int t
= tab
->sample_index
[tab
->n_sample
-1];
2938 tab
->sample_index
[tab
->n_sample
-1] = tab
->sample_index
[i
];
2939 tab
->sample_index
[i
] = t
;
2940 isl_mat_swap_rows(tab
->samples
, tab
->n_sample
-1, i
);
2946 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
) WARN_UNUSED
;
2947 static int perform_undo(struct isl_tab
*tab
, struct isl_tab_undo
*undo
)
2949 switch (undo
->type
) {
2950 case isl_tab_undo_empty
:
2953 case isl_tab_undo_nonneg
:
2954 case isl_tab_undo_redundant
:
2955 case isl_tab_undo_freeze
:
2956 case isl_tab_undo_zero
:
2957 case isl_tab_undo_allocate
:
2958 case isl_tab_undo_relax
:
2959 return perform_undo_var(tab
, undo
);
2960 case isl_tab_undo_bmap_eq
:
2961 return isl_basic_map_free_equality(tab
->bmap
, 1);
2962 case isl_tab_undo_bmap_ineq
:
2963 return isl_basic_map_free_inequality(tab
->bmap
, 1);
2964 case isl_tab_undo_bmap_div
:
2965 if (isl_basic_map_free_div(tab
->bmap
, 1) < 0)
2968 tab
->samples
->n_col
--;
2970 case isl_tab_undo_saved_basis
:
2971 if (restore_basis(tab
, undo
->u
.col_var
) < 0)
2974 case isl_tab_undo_drop_sample
:
2977 case isl_tab_undo_saved_samples
:
2978 drop_samples_since(tab
, undo
->u
.n
);
2980 case isl_tab_undo_callback
:
2981 return undo
->u
.callback
->run(undo
->u
.callback
);
2983 isl_assert(tab
->mat
->ctx
, 0, return -1);
2988 /* Return the tableau to the state it was in when the snapshot "snap"
2991 int isl_tab_rollback(struct isl_tab
*tab
, struct isl_tab_undo
*snap
)
2993 struct isl_tab_undo
*undo
, *next
;
2999 for (undo
= tab
->top
; undo
&& undo
!= &tab
->bottom
; undo
= next
) {
3003 if (perform_undo(tab
, undo
) < 0) {
3017 /* The given row "row" represents an inequality violated by all
3018 * points in the tableau. Check for some special cases of such
3019 * separating constraints.
3020 * In particular, if the row has been reduced to the constant -1,
3021 * then we know the inequality is adjacent (but opposite) to
3022 * an equality in the tableau.
3023 * If the row has been reduced to r = -1 -r', with r' an inequality
3024 * of the tableau, then the inequality is adjacent (but opposite)
3025 * to the inequality r'.
3027 static enum isl_ineq_type
separation_type(struct isl_tab
*tab
, unsigned row
)
3030 unsigned off
= 2 + tab
->M
;
3033 return isl_ineq_separate
;
3035 if (!isl_int_is_one(tab
->mat
->row
[row
][0]))
3036 return isl_ineq_separate
;
3037 if (!isl_int_is_negone(tab
->mat
->row
[row
][1]))
3038 return isl_ineq_separate
;
3040 pos
= isl_seq_first_non_zero(tab
->mat
->row
[row
] + off
+ tab
->n_dead
,
3041 tab
->n_col
- tab
->n_dead
);
3043 return isl_ineq_adj_eq
;
3045 if (!isl_int_is_negone(tab
->mat
->row
[row
][off
+ tab
->n_dead
+ pos
]))
3046 return isl_ineq_separate
;
3048 pos
= isl_seq_first_non_zero(
3049 tab
->mat
->row
[row
] + off
+ tab
->n_dead
+ pos
+ 1,
3050 tab
->n_col
- tab
->n_dead
- pos
- 1);
3052 return pos
== -1 ? isl_ineq_adj_ineq
: isl_ineq_separate
;
3055 /* Check the effect of inequality "ineq" on the tableau "tab".
3057 * isl_ineq_redundant: satisfied by all points in the tableau
3058 * isl_ineq_separate: satisfied by no point in the tableau
3059 * isl_ineq_cut: satisfied by some by not all points
3060 * isl_ineq_adj_eq: adjacent to an equality
3061 * isl_ineq_adj_ineq: adjacent to an inequality.
3063 enum isl_ineq_type
isl_tab_ineq_type(struct isl_tab
*tab
, isl_int
*ineq
)
3065 enum isl_ineq_type type
= isl_ineq_error
;
3066 struct isl_tab_undo
*snap
= NULL
;
3071 return isl_ineq_error
;
3073 if (isl_tab_extend_cons(tab
, 1) < 0)
3074 return isl_ineq_error
;
3076 snap
= isl_tab_snap(tab
);
3078 con
= isl_tab_add_row(tab
, ineq
);
3082 row
= tab
->con
[con
].index
;
3083 if (isl_tab_row_is_redundant(tab
, row
))
3084 type
= isl_ineq_redundant
;
3085 else if (isl_int_is_neg(tab
->mat
->row
[row
][1]) &&
3087 isl_int_abs_ge(tab
->mat
->row
[row
][1],
3088 tab
->mat
->row
[row
][0]))) {
3089 int nonneg
= at_least_zero(tab
, &tab
->con
[con
]);
3093 type
= isl_ineq_cut
;
3095 type
= separation_type(tab
, row
);
3097 int red
= con_is_redundant(tab
, &tab
->con
[con
]);
3101 type
= isl_ineq_cut
;
3103 type
= isl_ineq_redundant
;
3106 if (isl_tab_rollback(tab
, snap
))
3107 return isl_ineq_error
;
3110 return isl_ineq_error
;
3113 int isl_tab_track_bmap(struct isl_tab
*tab
, __isl_take isl_basic_map
*bmap
)
3118 isl_assert(tab
->mat
->ctx
, tab
->n_eq
== bmap
->n_eq
, return -1);
3119 isl_assert(tab
->mat
->ctx
,
3120 tab
->n_con
== bmap
->n_eq
+ bmap
->n_ineq
, return -1);
3126 isl_basic_map_free(bmap
);
3130 int isl_tab_track_bset(struct isl_tab
*tab
, __isl_take isl_basic_set
*bset
)
3132 return isl_tab_track_bmap(tab
, (isl_basic_map
*)bset
);
3135 __isl_keep isl_basic_set
*isl_tab_peek_bset(struct isl_tab
*tab
)
3140 return (isl_basic_set
*)tab
->bmap
;
3143 void isl_tab_dump(struct isl_tab
*tab
, FILE *out
, int indent
)
3149 fprintf(out
, "%*snull tab\n", indent
, "");
3152 fprintf(out
, "%*sn_redundant: %d, n_dead: %d", indent
, "",
3153 tab
->n_redundant
, tab
->n_dead
);
3155 fprintf(out
, ", rational");
3157 fprintf(out
, ", empty");
3159 fprintf(out
, "%*s[", indent
, "");
3160 for (i
= 0; i
< tab
->n_var
; ++i
) {
3162 fprintf(out
, (i
== tab
->n_param
||
3163 i
== tab
->n_var
- tab
->n_div
) ? "; "
3165 fprintf(out
, "%c%d%s", tab
->var
[i
].is_row
? 'r' : 'c',
3167 tab
->var
[i
].is_zero
? " [=0]" :
3168 tab
->var
[i
].is_redundant
? " [R]" : "");
3170 fprintf(out
, "]\n");
3171 fprintf(out
, "%*s[", indent
, "");
3172 for (i
= 0; i
< tab
->n_con
; ++i
) {
3175 fprintf(out
, "%c%d%s", tab
->con
[i
].is_row
? 'r' : 'c',
3177 tab
->con
[i
].is_zero
? " [=0]" :
3178 tab
->con
[i
].is_redundant
? " [R]" : "");
3180 fprintf(out
, "]\n");
3181 fprintf(out
, "%*s[", indent
, "");
3182 for (i
= 0; i
< tab
->n_row
; ++i
) {
3183 const char *sign
= "";
3186 if (tab
->row_sign
) {
3187 if (tab
->row_sign
[i
] == isl_tab_row_unknown
)
3189 else if (tab
->row_sign
[i
] == isl_tab_row_neg
)
3191 else if (tab
->row_sign
[i
] == isl_tab_row_pos
)
3196 fprintf(out
, "r%d: %d%s%s", i
, tab
->row_var
[i
],
3197 isl_tab_var_from_row(tab
, i
)->is_nonneg
? " [>=0]" : "", sign
);
3199 fprintf(out
, "]\n");
3200 fprintf(out
, "%*s[", indent
, "");
3201 for (i
= 0; i
< tab
->n_col
; ++i
) {
3204 fprintf(out
, "c%d: %d%s", i
, tab
->col_var
[i
],
3205 var_from_col(tab
, i
)->is_nonneg
? " [>=0]" : "");
3207 fprintf(out
, "]\n");
3208 r
= tab
->mat
->n_row
;
3209 tab
->mat
->n_row
= tab
->n_row
;
3210 c
= tab
->mat
->n_col
;
3211 tab
->mat
->n_col
= 2 + tab
->M
+ tab
->n_col
;
3212 isl_mat_dump(tab
->mat
, out
, indent
);
3213 tab
->mat
->n_row
= r
;
3214 tab
->mat
->n_col
= c
;
3216 isl_basic_map_dump(tab
->bmap
, out
, indent
);