add isl_val_list
[isl.git] / isl_equalities.c
blob9589032c25a85c1110a8f98f74bef78671e33c85
1 /*
2 * Copyright 2008-2009 Katholieke Universiteit Leuven
3 * Copyright 2010 INRIA Saclay
5 * Use of this software is governed by the MIT license
7 * Written by Sven Verdoolaege, K.U.Leuven, Departement
8 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
9 * and INRIA Saclay - Ile-de-France, Parc Club Orsay Universite,
10 * ZAC des vignes, 4 rue Jacques Monod, 91893 Orsay, France
13 #include <isl_mat_private.h>
14 #include <isl/seq.h>
15 #include "isl_map_private.h"
16 #include "isl_equalities.h"
18 /* Given a set of modulo constraints
20 * c + A y = 0 mod d
22 * this function computes a particular solution y_0
24 * The input is given as a matrix B = [ c A ] and a vector d.
26 * The output is matrix containing the solution y_0 or
27 * a zero-column matrix if the constraints admit no integer solution.
29 * The given set of constrains is equivalent to
31 * c + A y = -D x
33 * with D = diag d and x a fresh set of variables.
34 * Reducing both c and A modulo d does not change the
35 * value of y in the solution and may lead to smaller coefficients.
36 * Let M = [ D A ] and [ H 0 ] = M U, the Hermite normal form of M.
37 * Then
38 * [ x ]
39 * M [ y ] = - c
40 * and so
41 * [ x ]
42 * [ H 0 ] U^{-1} [ y ] = - c
43 * Let
44 * [ A ] [ x ]
45 * [ B ] = U^{-1} [ y ]
46 * then
47 * H A + 0 B = -c
49 * so B may be chosen arbitrarily, e.g., B = 0, and then
51 * [ x ] = [ -c ]
52 * U^{-1} [ y ] = [ 0 ]
53 * or
54 * [ x ] [ -c ]
55 * [ y ] = U [ 0 ]
56 * specifically,
58 * y = U_{2,1} (-c)
60 * If any of the coordinates of this y are non-integer
61 * then the constraints admit no integer solution and
62 * a zero-column matrix is returned.
64 static struct isl_mat *particular_solution(struct isl_mat *B, struct isl_vec *d)
66 int i, j;
67 struct isl_mat *M = NULL;
68 struct isl_mat *C = NULL;
69 struct isl_mat *U = NULL;
70 struct isl_mat *H = NULL;
71 struct isl_mat *cst = NULL;
72 struct isl_mat *T = NULL;
74 M = isl_mat_alloc(B->ctx, B->n_row, B->n_row + B->n_col - 1);
75 C = isl_mat_alloc(B->ctx, 1 + B->n_row, 1);
76 if (!M || !C)
77 goto error;
78 isl_int_set_si(C->row[0][0], 1);
79 for (i = 0; i < B->n_row; ++i) {
80 isl_seq_clr(M->row[i], B->n_row);
81 isl_int_set(M->row[i][i], d->block.data[i]);
82 isl_int_neg(C->row[1 + i][0], B->row[i][0]);
83 isl_int_fdiv_r(C->row[1+i][0], C->row[1+i][0], M->row[i][i]);
84 for (j = 0; j < B->n_col - 1; ++j)
85 isl_int_fdiv_r(M->row[i][B->n_row + j],
86 B->row[i][1 + j], M->row[i][i]);
88 M = isl_mat_left_hermite(M, 0, &U, NULL);
89 if (!M || !U)
90 goto error;
91 H = isl_mat_sub_alloc(M, 0, B->n_row, 0, B->n_row);
92 H = isl_mat_lin_to_aff(H);
93 C = isl_mat_inverse_product(H, C);
94 if (!C)
95 goto error;
96 for (i = 0; i < B->n_row; ++i) {
97 if (!isl_int_is_divisible_by(C->row[1+i][0], C->row[0][0]))
98 break;
99 isl_int_divexact(C->row[1+i][0], C->row[1+i][0], C->row[0][0]);
101 if (i < B->n_row)
102 cst = isl_mat_alloc(B->ctx, B->n_row, 0);
103 else
104 cst = isl_mat_sub_alloc(C, 1, B->n_row, 0, 1);
105 T = isl_mat_sub_alloc(U, B->n_row, B->n_col - 1, 0, B->n_row);
106 cst = isl_mat_product(T, cst);
107 isl_mat_free(M);
108 isl_mat_free(C);
109 isl_mat_free(U);
110 return cst;
111 error:
112 isl_mat_free(M);
113 isl_mat_free(C);
114 isl_mat_free(U);
115 return NULL;
118 /* Compute and return the matrix
120 * U_1^{-1} diag(d_1, 1, ..., 1)
122 * with U_1 the unimodular completion of the first (and only) row of B.
123 * The columns of this matrix generate the lattice that satisfies
124 * the single (linear) modulo constraint.
126 static struct isl_mat *parameter_compression_1(
127 struct isl_mat *B, struct isl_vec *d)
129 struct isl_mat *U;
131 U = isl_mat_alloc(B->ctx, B->n_col - 1, B->n_col - 1);
132 if (!U)
133 return NULL;
134 isl_seq_cpy(U->row[0], B->row[0] + 1, B->n_col - 1);
135 U = isl_mat_unimodular_complete(U, 1);
136 U = isl_mat_right_inverse(U);
137 if (!U)
138 return NULL;
139 isl_mat_col_mul(U, 0, d->block.data[0], 0);
140 U = isl_mat_lin_to_aff(U);
141 return U;
144 /* Compute a common lattice of solutions to the linear modulo
145 * constraints specified by B and d.
146 * See also the documentation of isl_mat_parameter_compression.
147 * We put the matrix
149 * A = [ L_1^{-T} L_2^{-T} ... L_k^{-T} ]
151 * on a common denominator. This denominator D is the lcm of modulos d.
152 * Since L_i = U_i^{-1} diag(d_i, 1, ... 1), we have
153 * L_i^{-T} = U_i^T diag(d_i, 1, ... 1)^{-T} = U_i^T diag(1/d_i, 1, ..., 1).
154 * Putting this on the common denominator, we have
155 * D * L_i^{-T} = U_i^T diag(D/d_i, D, ..., D).
157 static struct isl_mat *parameter_compression_multi(
158 struct isl_mat *B, struct isl_vec *d)
160 int i, j, k;
161 isl_int D;
162 struct isl_mat *A = NULL, *U = NULL;
163 struct isl_mat *T;
164 unsigned size;
166 isl_int_init(D);
168 isl_vec_lcm(d, &D);
170 size = B->n_col - 1;
171 A = isl_mat_alloc(B->ctx, size, B->n_row * size);
172 U = isl_mat_alloc(B->ctx, size, size);
173 if (!U || !A)
174 goto error;
175 for (i = 0; i < B->n_row; ++i) {
176 isl_seq_cpy(U->row[0], B->row[i] + 1, size);
177 U = isl_mat_unimodular_complete(U, 1);
178 if (!U)
179 goto error;
180 isl_int_divexact(D, D, d->block.data[i]);
181 for (k = 0; k < U->n_col; ++k)
182 isl_int_mul(A->row[k][i*size+0], D, U->row[0][k]);
183 isl_int_mul(D, D, d->block.data[i]);
184 for (j = 1; j < U->n_row; ++j)
185 for (k = 0; k < U->n_col; ++k)
186 isl_int_mul(A->row[k][i*size+j],
187 D, U->row[j][k]);
189 A = isl_mat_left_hermite(A, 0, NULL, NULL);
190 T = isl_mat_sub_alloc(A, 0, A->n_row, 0, A->n_row);
191 T = isl_mat_lin_to_aff(T);
192 if (!T)
193 goto error;
194 isl_int_set(T->row[0][0], D);
195 T = isl_mat_right_inverse(T);
196 if (!T)
197 goto error;
198 isl_assert(T->ctx, isl_int_is_one(T->row[0][0]), goto error);
199 T = isl_mat_transpose(T);
200 isl_mat_free(A);
201 isl_mat_free(U);
203 isl_int_clear(D);
204 return T;
205 error:
206 isl_mat_free(A);
207 isl_mat_free(U);
208 isl_int_clear(D);
209 return NULL;
212 /* Given a set of modulo constraints
214 * c + A y = 0 mod d
216 * this function returns an affine transformation T,
218 * y = T y'
220 * that bijectively maps the integer vectors y' to integer
221 * vectors y that satisfy the modulo constraints.
223 * This function is inspired by Section 2.5.3
224 * of B. Meister, "Stating and Manipulating Periodicity in the Polytope
225 * Model. Applications to Program Analysis and Optimization".
226 * However, the implementation only follows the algorithm of that
227 * section for computing a particular solution and not for computing
228 * a general homogeneous solution. The latter is incomplete and
229 * may remove some valid solutions.
230 * Instead, we use an adaptation of the algorithm in Section 7 of
231 * B. Meister, S. Verdoolaege, "Polynomial Approximations in the Polytope
232 * Model: Bringing the Power of Quasi-Polynomials to the Masses".
234 * The input is given as a matrix B = [ c A ] and a vector d.
235 * Each element of the vector d corresponds to a row in B.
236 * The output is a lower triangular matrix.
237 * If no integer vector y satisfies the given constraints then
238 * a matrix with zero columns is returned.
240 * We first compute a particular solution y_0 to the given set of
241 * modulo constraints in particular_solution. If no such solution
242 * exists, then we return a zero-columned transformation matrix.
243 * Otherwise, we compute the generic solution to
245 * A y = 0 mod d
247 * That is we want to compute G such that
249 * y = G y''
251 * with y'' integer, describes the set of solutions.
253 * We first remove the common factors of each row.
254 * In particular if gcd(A_i,d_i) != 1, then we divide the whole
255 * row i (including d_i) by this common factor. If afterwards gcd(A_i) != 1,
256 * then we divide this row of A by the common factor, unless gcd(A_i) = 0.
257 * In the later case, we simply drop the row (in both A and d).
259 * If there are no rows left in A, then G is the identity matrix. Otherwise,
260 * for each row i, we now determine the lattice of integer vectors
261 * that satisfies this row. Let U_i be the unimodular extension of the
262 * row A_i. This unimodular extension exists because gcd(A_i) = 1.
263 * The first component of
265 * y' = U_i y
267 * needs to be a multiple of d_i. Let y' = diag(d_i, 1, ..., 1) y''.
268 * Then,
270 * y = U_i^{-1} diag(d_i, 1, ..., 1) y''
272 * for arbitrary integer vectors y''. That is, y belongs to the lattice
273 * generated by the columns of L_i = U_i^{-1} diag(d_i, 1, ..., 1).
274 * If there is only one row, then G = L_1.
276 * If there is more than one row left, we need to compute the intersection
277 * of the lattices. That is, we need to compute an L such that
279 * L = L_i L_i' for all i
281 * with L_i' some integer matrices. Let A be constructed as follows
283 * A = [ L_1^{-T} L_2^{-T} ... L_k^{-T} ]
285 * and computed the Hermite Normal Form of A = [ H 0 ] U
286 * Then,
288 * L_i^{-T} = H U_{1,i}
290 * or
292 * H^{-T} = L_i U_{1,i}^T
294 * In other words G = L = H^{-T}.
295 * To ensure that G is lower triangular, we compute and use its Hermite
296 * normal form.
298 * The affine transformation matrix returned is then
300 * [ 1 0 ]
301 * [ y_0 G ]
303 * as any y = y_0 + G y' with y' integer is a solution to the original
304 * modulo constraints.
306 struct isl_mat *isl_mat_parameter_compression(
307 struct isl_mat *B, struct isl_vec *d)
309 int i;
310 struct isl_mat *cst = NULL;
311 struct isl_mat *T = NULL;
312 isl_int D;
314 if (!B || !d)
315 goto error;
316 isl_assert(B->ctx, B->n_row == d->size, goto error);
317 cst = particular_solution(B, d);
318 if (!cst)
319 goto error;
320 if (cst->n_col == 0) {
321 T = isl_mat_alloc(B->ctx, B->n_col, 0);
322 isl_mat_free(cst);
323 isl_mat_free(B);
324 isl_vec_free(d);
325 return T;
327 isl_int_init(D);
328 /* Replace a*g*row = 0 mod g*m by row = 0 mod m */
329 for (i = 0; i < B->n_row; ++i) {
330 isl_seq_gcd(B->row[i] + 1, B->n_col - 1, &D);
331 if (isl_int_is_one(D))
332 continue;
333 if (isl_int_is_zero(D)) {
334 B = isl_mat_drop_rows(B, i, 1);
335 d = isl_vec_cow(d);
336 if (!B || !d)
337 goto error2;
338 isl_seq_cpy(d->block.data+i, d->block.data+i+1,
339 d->size - (i+1));
340 d->size--;
341 i--;
342 continue;
344 B = isl_mat_cow(B);
345 if (!B)
346 goto error2;
347 isl_seq_scale_down(B->row[i] + 1, B->row[i] + 1, D, B->n_col-1);
348 isl_int_gcd(D, D, d->block.data[i]);
349 d = isl_vec_cow(d);
350 if (!d)
351 goto error2;
352 isl_int_divexact(d->block.data[i], d->block.data[i], D);
354 isl_int_clear(D);
355 if (B->n_row == 0)
356 T = isl_mat_identity(B->ctx, B->n_col);
357 else if (B->n_row == 1)
358 T = parameter_compression_1(B, d);
359 else
360 T = parameter_compression_multi(B, d);
361 T = isl_mat_left_hermite(T, 0, NULL, NULL);
362 if (!T)
363 goto error;
364 isl_mat_sub_copy(T->ctx, T->row + 1, cst->row, cst->n_row, 0, 0, 1);
365 isl_mat_free(cst);
366 isl_mat_free(B);
367 isl_vec_free(d);
368 return T;
369 error2:
370 isl_int_clear(D);
371 error:
372 isl_mat_free(cst);
373 isl_mat_free(B);
374 isl_vec_free(d);
375 return NULL;
378 /* Given a set of equalities
380 * B(y) + A x = 0 (*)
382 * compute and return an affine transformation T,
384 * y = T y'
386 * that bijectively maps the integer vectors y' to integer
387 * vectors y that satisfy the modulo constraints for some value of x.
389 * Let [H 0] be the Hermite Normal Form of A, i.e.,
391 * A = [H 0] Q
393 * Then y is a solution of (*) iff
395 * H^-1 B(y) (= - [I 0] Q x)
397 * is an integer vector. Let d be the common denominator of H^-1.
398 * We impose
400 * d H^-1 B(y) = 0 mod d
402 * and compute the solution using isl_mat_parameter_compression.
404 __isl_give isl_mat *isl_mat_parameter_compression_ext(__isl_take isl_mat *B,
405 __isl_take isl_mat *A)
407 isl_ctx *ctx;
408 isl_vec *d;
409 int n_row, n_col;
411 if (!A)
412 return isl_mat_free(B);
414 ctx = isl_mat_get_ctx(A);
415 n_row = A->n_row;
416 n_col = A->n_col;
417 A = isl_mat_left_hermite(A, 0, NULL, NULL);
418 A = isl_mat_drop_cols(A, n_row, n_col - n_row);
419 A = isl_mat_lin_to_aff(A);
420 A = isl_mat_right_inverse(A);
421 d = isl_vec_alloc(ctx, n_row);
422 if (A)
423 d = isl_vec_set(d, A->row[0][0]);
424 A = isl_mat_drop_rows(A, 0, 1);
425 A = isl_mat_drop_cols(A, 0, 1);
426 B = isl_mat_product(A, B);
428 return isl_mat_parameter_compression(B, d);
431 /* Given a set of equalities
433 * M x - c = 0
435 * this function computes a unimodular transformation from a lower-dimensional
436 * space to the original space that bijectively maps the integer points x'
437 * in the lower-dimensional space to the integer points x in the original
438 * space that satisfy the equalities.
440 * The input is given as a matrix B = [ -c M ] and the output is a
441 * matrix that maps [1 x'] to [1 x].
442 * If T2 is not NULL, then *T2 is set to a matrix mapping [1 x] to [1 x'].
444 * First compute the (left) Hermite normal form of M,
446 * M [U1 U2] = M U = H = [H1 0]
447 * or
448 * M = H Q = [H1 0] [Q1]
449 * [Q2]
451 * with U, Q unimodular, Q = U^{-1} (and H lower triangular).
452 * Define the transformed variables as
454 * x = [U1 U2] [ x1' ] = [U1 U2] [Q1] x
455 * [ x2' ] [Q2]
457 * The equalities then become
459 * H1 x1' - c = 0 or x1' = H1^{-1} c = c'
461 * If any of the c' is non-integer, then the original set has no
462 * integer solutions (since the x' are a unimodular transformation
463 * of the x) and a zero-column matrix is returned.
464 * Otherwise, the transformation is given by
466 * x = U1 H1^{-1} c + U2 x2'
468 * The inverse transformation is simply
470 * x2' = Q2 x
472 __isl_give isl_mat *isl_mat_variable_compression(__isl_take isl_mat *B,
473 __isl_give isl_mat **T2)
475 int i;
476 struct isl_mat *H = NULL, *C = NULL, *H1, *U = NULL, *U1, *U2, *TC;
477 unsigned dim;
479 if (T2)
480 *T2 = NULL;
481 if (!B)
482 goto error;
484 dim = B->n_col - 1;
485 H = isl_mat_sub_alloc(B, 0, B->n_row, 1, dim);
486 H = isl_mat_left_hermite(H, 0, &U, T2);
487 if (!H || !U || (T2 && !*T2))
488 goto error;
489 if (T2) {
490 *T2 = isl_mat_drop_rows(*T2, 0, B->n_row);
491 *T2 = isl_mat_lin_to_aff(*T2);
492 if (!*T2)
493 goto error;
495 C = isl_mat_alloc(B->ctx, 1+B->n_row, 1);
496 if (!C)
497 goto error;
498 isl_int_set_si(C->row[0][0], 1);
499 isl_mat_sub_neg(C->ctx, C->row+1, B->row, B->n_row, 0, 0, 1);
500 H1 = isl_mat_sub_alloc(H, 0, H->n_row, 0, H->n_row);
501 H1 = isl_mat_lin_to_aff(H1);
502 TC = isl_mat_inverse_product(H1, C);
503 if (!TC)
504 goto error;
505 isl_mat_free(H);
506 if (!isl_int_is_one(TC->row[0][0])) {
507 for (i = 0; i < B->n_row; ++i) {
508 if (!isl_int_is_divisible_by(TC->row[1+i][0], TC->row[0][0])) {
509 struct isl_ctx *ctx = B->ctx;
510 isl_mat_free(B);
511 isl_mat_free(TC);
512 isl_mat_free(U);
513 if (T2) {
514 isl_mat_free(*T2);
515 *T2 = NULL;
517 return isl_mat_alloc(ctx, 1 + dim, 0);
519 isl_seq_scale_down(TC->row[1+i], TC->row[1+i], TC->row[0][0], 1);
521 isl_int_set_si(TC->row[0][0], 1);
523 U1 = isl_mat_sub_alloc(U, 0, U->n_row, 0, B->n_row);
524 U1 = isl_mat_lin_to_aff(U1);
525 U2 = isl_mat_sub_alloc(U, 0, U->n_row, B->n_row, U->n_row - B->n_row);
526 U2 = isl_mat_lin_to_aff(U2);
527 isl_mat_free(U);
528 TC = isl_mat_product(U1, TC);
529 TC = isl_mat_aff_direct_sum(TC, U2);
531 isl_mat_free(B);
533 return TC;
534 error:
535 isl_mat_free(B);
536 isl_mat_free(H);
537 isl_mat_free(U);
538 if (T2) {
539 isl_mat_free(*T2);
540 *T2 = NULL;
542 return NULL;
545 /* Use the n equalities of bset to unimodularly transform the
546 * variables x such that n transformed variables x1' have a constant value
547 * and rewrite the constraints of bset in terms of the remaining
548 * transformed variables x2'. The matrix pointed to by T maps
549 * the new variables x2' back to the original variables x, while T2
550 * maps the original variables to the new variables.
552 static struct isl_basic_set *compress_variables(
553 struct isl_basic_set *bset, struct isl_mat **T, struct isl_mat **T2)
555 struct isl_mat *B, *TC;
556 unsigned dim;
558 if (T)
559 *T = NULL;
560 if (T2)
561 *T2 = NULL;
562 if (!bset)
563 goto error;
564 isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
565 isl_assert(bset->ctx, bset->n_div == 0, goto error);
566 dim = isl_basic_set_n_dim(bset);
567 isl_assert(bset->ctx, bset->n_eq <= dim, goto error);
568 if (bset->n_eq == 0)
569 return bset;
571 B = isl_mat_sub_alloc6(bset->ctx, bset->eq, 0, bset->n_eq, 0, 1 + dim);
572 TC = isl_mat_variable_compression(B, T2);
573 if (!TC)
574 goto error;
575 if (TC->n_col == 0) {
576 isl_mat_free(TC);
577 if (T2) {
578 isl_mat_free(*T2);
579 *T2 = NULL;
581 return isl_basic_set_set_to_empty(bset);
584 bset = isl_basic_set_preimage(bset, T ? isl_mat_copy(TC) : TC);
585 if (T)
586 *T = TC;
587 return bset;
588 error:
589 isl_basic_set_free(bset);
590 return NULL;
593 struct isl_basic_set *isl_basic_set_remove_equalities(
594 struct isl_basic_set *bset, struct isl_mat **T, struct isl_mat **T2)
596 if (T)
597 *T = NULL;
598 if (T2)
599 *T2 = NULL;
600 if (!bset)
601 return NULL;
602 isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
603 bset = isl_basic_set_gauss(bset, NULL);
604 if (ISL_F_ISSET(bset, ISL_BASIC_SET_EMPTY))
605 return bset;
606 bset = compress_variables(bset, T, T2);
607 return bset;
608 error:
609 isl_basic_set_free(bset);
610 *T = NULL;
611 return NULL;
614 /* Check if dimension dim belongs to a residue class
615 * i_dim \equiv r mod m
616 * with m != 1 and if so return m in *modulo and r in *residue.
617 * As a special case, when i_dim has a fixed value v, then
618 * *modulo is set to 0 and *residue to v.
620 * If i_dim does not belong to such a residue class, then *modulo
621 * is set to 1 and *residue is set to 0.
623 int isl_basic_set_dim_residue_class(struct isl_basic_set *bset,
624 int pos, isl_int *modulo, isl_int *residue)
626 struct isl_ctx *ctx;
627 struct isl_mat *H = NULL, *U = NULL, *C, *H1, *U1;
628 unsigned total;
629 unsigned nparam;
631 if (!bset || !modulo || !residue)
632 return -1;
634 if (isl_basic_set_plain_dim_is_fixed(bset, pos, residue)) {
635 isl_int_set_si(*modulo, 0);
636 return 0;
639 ctx = bset->ctx;
640 total = isl_basic_set_total_dim(bset);
641 nparam = isl_basic_set_n_param(bset);
642 H = isl_mat_sub_alloc6(bset->ctx, bset->eq, 0, bset->n_eq, 1, total);
643 H = isl_mat_left_hermite(H, 0, &U, NULL);
644 if (!H)
645 return -1;
647 isl_seq_gcd(U->row[nparam + pos]+bset->n_eq,
648 total-bset->n_eq, modulo);
649 if (isl_int_is_zero(*modulo))
650 isl_int_set_si(*modulo, 1);
651 if (isl_int_is_one(*modulo)) {
652 isl_int_set_si(*residue, 0);
653 isl_mat_free(H);
654 isl_mat_free(U);
655 return 0;
658 C = isl_mat_alloc(bset->ctx, 1+bset->n_eq, 1);
659 if (!C)
660 goto error;
661 isl_int_set_si(C->row[0][0], 1);
662 isl_mat_sub_neg(C->ctx, C->row+1, bset->eq, bset->n_eq, 0, 0, 1);
663 H1 = isl_mat_sub_alloc(H, 0, H->n_row, 0, H->n_row);
664 H1 = isl_mat_lin_to_aff(H1);
665 C = isl_mat_inverse_product(H1, C);
666 isl_mat_free(H);
667 U1 = isl_mat_sub_alloc(U, nparam+pos, 1, 0, bset->n_eq);
668 U1 = isl_mat_lin_to_aff(U1);
669 isl_mat_free(U);
670 C = isl_mat_product(U1, C);
671 if (!C)
672 goto error;
673 if (!isl_int_is_divisible_by(C->row[1][0], C->row[0][0])) {
674 bset = isl_basic_set_copy(bset);
675 bset = isl_basic_set_set_to_empty(bset);
676 isl_basic_set_free(bset);
677 isl_int_set_si(*modulo, 1);
678 isl_int_set_si(*residue, 0);
679 return 0;
681 isl_int_divexact(*residue, C->row[1][0], C->row[0][0]);
682 isl_int_fdiv_r(*residue, *residue, *modulo);
683 isl_mat_free(C);
684 return 0;
685 error:
686 isl_mat_free(H);
687 isl_mat_free(U);
688 return -1;
691 /* Check if dimension dim belongs to a residue class
692 * i_dim \equiv r mod m
693 * with m != 1 and if so return m in *modulo and r in *residue.
694 * As a special case, when i_dim has a fixed value v, then
695 * *modulo is set to 0 and *residue to v.
697 * If i_dim does not belong to such a residue class, then *modulo
698 * is set to 1 and *residue is set to 0.
700 int isl_set_dim_residue_class(struct isl_set *set,
701 int pos, isl_int *modulo, isl_int *residue)
703 isl_int m;
704 isl_int r;
705 int i;
707 if (!set || !modulo || !residue)
708 return -1;
710 if (set->n == 0) {
711 isl_int_set_si(*modulo, 0);
712 isl_int_set_si(*residue, 0);
713 return 0;
716 if (isl_basic_set_dim_residue_class(set->p[0], pos, modulo, residue)<0)
717 return -1;
719 if (set->n == 1)
720 return 0;
722 if (isl_int_is_one(*modulo))
723 return 0;
725 isl_int_init(m);
726 isl_int_init(r);
728 for (i = 1; i < set->n; ++i) {
729 if (isl_basic_set_dim_residue_class(set->p[i], pos, &m, &r) < 0)
730 goto error;
731 isl_int_gcd(*modulo, *modulo, m);
732 isl_int_sub(m, *residue, r);
733 isl_int_gcd(*modulo, *modulo, m);
734 if (!isl_int_is_zero(*modulo))
735 isl_int_fdiv_r(*residue, *residue, *modulo);
736 if (isl_int_is_one(*modulo))
737 break;
740 isl_int_clear(m);
741 isl_int_clear(r);
743 return 0;
744 error:
745 isl_int_clear(m);
746 isl_int_clear(r);
747 return -1;