| /* |
| * Copyright 2008-2009 Katholieke Universiteit Leuven |
| * Copyright 2014 INRIA Rocquencourt |
| * |
| * Use of this software is governed by the MIT license |
| * |
| * Written by Sven Verdoolaege, K.U.Leuven, Departement |
| * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium |
| * and Inria Paris - Rocquencourt, Domaine de Voluceau - Rocquencourt, |
| * B.P. 105 - 78153 Le Chesnay, France |
| */ |
| |
| #include <isl_ctx_private.h> |
| #include <isl_map_private.h> |
| #include <isl_lp_private.h> |
| #include <isl/map.h> |
| #include <isl_mat_private.h> |
| #include <isl_vec_private.h> |
| #include <isl/set.h> |
| #include <isl_seq.h> |
| #include <isl_options_private.h> |
| #include "isl_equalities.h" |
| #include "isl_tab.h" |
| #include <isl_sort.h> |
| |
| #include <bset_to_bmap.c> |
| #include <bset_from_bmap.c> |
| #include <set_to_map.c> |
| |
| static __isl_give isl_basic_set *uset_convex_hull_wrap_bounded( |
| __isl_take isl_set *set); |
| |
| /* Remove redundant |
| * constraints. If the minimal value along the normal of a constraint |
| * is the same if the constraint is removed, then the constraint is redundant. |
| * |
| * Since some constraints may be mutually redundant, sort the constraints |
| * first such that constraints that involve existentially quantified |
| * variables are considered for removal before those that do not. |
| * The sorting is also needed for the use in map_simple_hull. |
| * |
| * Note that isl_tab_detect_implicit_equalities may also end up |
| * marking some constraints as redundant. Make sure the constraints |
| * are preserved and undo those marking such that isl_tab_detect_redundant |
| * can consider the constraints in the sorted order. |
| * |
| * Alternatively, we could have intersected the basic map with the |
| * corresponding equality and then checked if the dimension was that |
| * of a facet. |
| */ |
| __isl_give isl_basic_map *isl_basic_map_remove_redundancies( |
| __isl_take isl_basic_map *bmap) |
| { |
| struct isl_tab *tab; |
| |
| if (!bmap) |
| return NULL; |
| |
| bmap = isl_basic_map_gauss(bmap, NULL); |
| if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY)) |
| return bmap; |
| if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_NO_REDUNDANT)) |
| return bmap; |
| if (bmap->n_ineq <= 1) |
| return bmap; |
| |
| bmap = isl_basic_map_sort_constraints(bmap); |
| tab = isl_tab_from_basic_map(bmap, 0); |
| if (!tab) |
| goto error; |
| tab->preserve = 1; |
| if (isl_tab_detect_implicit_equalities(tab) < 0) |
| goto error; |
| if (isl_tab_restore_redundant(tab) < 0) |
| goto error; |
| tab->preserve = 0; |
| if (isl_tab_detect_redundant(tab) < 0) |
| goto error; |
| bmap = isl_basic_map_update_from_tab(bmap, tab); |
| isl_tab_free(tab); |
| if (!bmap) |
| return NULL; |
| ISL_F_SET(bmap, ISL_BASIC_MAP_NO_IMPLICIT); |
| ISL_F_SET(bmap, ISL_BASIC_MAP_NO_REDUNDANT); |
| return bmap; |
| error: |
| isl_tab_free(tab); |
| isl_basic_map_free(bmap); |
| return NULL; |
| } |
| |
| __isl_give isl_basic_set *isl_basic_set_remove_redundancies( |
| __isl_take isl_basic_set *bset) |
| { |
| return bset_from_bmap( |
| isl_basic_map_remove_redundancies(bset_to_bmap(bset))); |
| } |
| |
| /* Remove redundant constraints in each of the basic maps. |
| */ |
| __isl_give isl_map *isl_map_remove_redundancies(__isl_take isl_map *map) |
| { |
| return isl_map_inline_foreach_basic_map(map, |
| &isl_basic_map_remove_redundancies); |
| } |
| |
| __isl_give isl_set *isl_set_remove_redundancies(__isl_take isl_set *set) |
| { |
| return isl_map_remove_redundancies(set); |
| } |
| |
| /* Check if the set set is bound in the direction of the affine |
| * constraint c and if so, set the constant term such that the |
| * resulting constraint is a bounding constraint for the set. |
| */ |
| static int uset_is_bound(__isl_keep isl_set *set, isl_int *c, unsigned len) |
| { |
| int first; |
| int j; |
| isl_int opt; |
| isl_int opt_denom; |
| |
| isl_int_init(opt); |
| isl_int_init(opt_denom); |
| first = 1; |
| for (j = 0; j < set->n; ++j) { |
| enum isl_lp_result res; |
| |
| if (ISL_F_ISSET(set->p[j], ISL_BASIC_SET_EMPTY)) |
| continue; |
| |
| res = isl_basic_set_solve_lp(set->p[j], |
| 0, c, set->ctx->one, &opt, &opt_denom, NULL); |
| if (res == isl_lp_unbounded) |
| break; |
| if (res == isl_lp_error) |
| goto error; |
| if (res == isl_lp_empty) { |
| set->p[j] = isl_basic_set_set_to_empty(set->p[j]); |
| if (!set->p[j]) |
| goto error; |
| continue; |
| } |
| if (first || isl_int_is_neg(opt)) { |
| if (!isl_int_is_one(opt_denom)) |
| isl_seq_scale(c, c, opt_denom, len); |
| isl_int_sub(c[0], c[0], opt); |
| } |
| first = 0; |
| } |
| isl_int_clear(opt); |
| isl_int_clear(opt_denom); |
| return j >= set->n; |
| error: |
| isl_int_clear(opt); |
| isl_int_clear(opt_denom); |
| return -1; |
| } |
| |
| static struct isl_basic_set *isl_basic_set_add_equality( |
| struct isl_basic_set *bset, isl_int *c) |
| { |
| int i; |
| unsigned dim; |
| |
| if (!bset) |
| return NULL; |
| |
| if (ISL_F_ISSET(bset, ISL_BASIC_SET_EMPTY)) |
| return bset; |
| |
| isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error); |
| isl_assert(bset->ctx, bset->n_div == 0, goto error); |
| dim = isl_basic_set_n_dim(bset); |
| bset = isl_basic_set_cow(bset); |
| bset = isl_basic_set_extend(bset, 0, dim, 0, 1, 0); |
| i = isl_basic_set_alloc_equality(bset); |
| if (i < 0) |
| goto error; |
| isl_seq_cpy(bset->eq[i], c, 1 + dim); |
| return bset; |
| error: |
| isl_basic_set_free(bset); |
| return NULL; |
| } |
| |
| static __isl_give isl_set *isl_set_add_basic_set_equality( |
| __isl_take isl_set *set, isl_int *c) |
| { |
| int i; |
| |
| set = isl_set_cow(set); |
| if (!set) |
| return NULL; |
| for (i = 0; i < set->n; ++i) { |
| set->p[i] = isl_basic_set_add_equality(set->p[i], c); |
| if (!set->p[i]) |
| goto error; |
| } |
| return set; |
| error: |
| isl_set_free(set); |
| return NULL; |
| } |
| |
| /* Given a union of basic sets, construct the constraints for wrapping |
| * a facet around one of its ridges. |
| * In particular, if each of n the d-dimensional basic sets i in "set" |
| * contains the origin, satisfies the constraints x_1 >= 0 and x_2 >= 0 |
| * and is defined by the constraints |
| * [ 1 ] |
| * A_i [ x ] >= 0 |
| * |
| * then the resulting set is of dimension n*(1+d) and has as constraints |
| * |
| * [ a_i ] |
| * A_i [ x_i ] >= 0 |
| * |
| * a_i >= 0 |
| * |
| * \sum_i x_{i,1} = 1 |
| */ |
| static __isl_give isl_basic_set *wrap_constraints(__isl_keep isl_set *set) |
| { |
| struct isl_basic_set *lp; |
| unsigned n_eq; |
| unsigned n_ineq; |
| int i, j, k; |
| unsigned dim, lp_dim; |
| |
| if (!set) |
| return NULL; |
| |
| dim = 1 + isl_set_n_dim(set); |
| n_eq = 1; |
| n_ineq = set->n; |
| for (i = 0; i < set->n; ++i) { |
| n_eq += set->p[i]->n_eq; |
| n_ineq += set->p[i]->n_ineq; |
| } |
| lp = isl_basic_set_alloc(set->ctx, 0, dim * set->n, 0, n_eq, n_ineq); |
| lp = isl_basic_set_set_rational(lp); |
| if (!lp) |
| return NULL; |
| lp_dim = isl_basic_set_n_dim(lp); |
| k = isl_basic_set_alloc_equality(lp); |
| isl_int_set_si(lp->eq[k][0], -1); |
| for (i = 0; i < set->n; ++i) { |
| isl_int_set_si(lp->eq[k][1+dim*i], 0); |
| isl_int_set_si(lp->eq[k][1+dim*i+1], 1); |
| isl_seq_clr(lp->eq[k]+1+dim*i+2, dim-2); |
| } |
| for (i = 0; i < set->n; ++i) { |
| k = isl_basic_set_alloc_inequality(lp); |
| isl_seq_clr(lp->ineq[k], 1+lp_dim); |
| isl_int_set_si(lp->ineq[k][1+dim*i], 1); |
| |
| for (j = 0; j < set->p[i]->n_eq; ++j) { |
| k = isl_basic_set_alloc_equality(lp); |
| isl_seq_clr(lp->eq[k], 1+dim*i); |
| isl_seq_cpy(lp->eq[k]+1+dim*i, set->p[i]->eq[j], dim); |
| isl_seq_clr(lp->eq[k]+1+dim*(i+1), dim*(set->n-i-1)); |
| } |
| |
| for (j = 0; j < set->p[i]->n_ineq; ++j) { |
| k = isl_basic_set_alloc_inequality(lp); |
| isl_seq_clr(lp->ineq[k], 1+dim*i); |
| isl_seq_cpy(lp->ineq[k]+1+dim*i, set->p[i]->ineq[j], dim); |
| isl_seq_clr(lp->ineq[k]+1+dim*(i+1), dim*(set->n-i-1)); |
| } |
| } |
| return lp; |
| } |
| |
| /* Given a facet "facet" of the convex hull of "set" and a facet "ridge" |
| * of that facet, compute the other facet of the convex hull that contains |
| * the ridge. |
| * |
| * We first transform the set such that the facet constraint becomes |
| * |
| * x_1 >= 0 |
| * |
| * I.e., the facet lies in |
| * |
| * x_1 = 0 |
| * |
| * and on that facet, the constraint that defines the ridge is |
| * |
| * x_2 >= 0 |
| * |
| * (This transformation is not strictly needed, all that is needed is |
| * that the ridge contains the origin.) |
| * |
| * Since the ridge contains the origin, the cone of the convex hull |
| * will be of the form |
| * |
| * x_1 >= 0 |
| * x_2 >= a x_1 |
| * |
| * with this second constraint defining the new facet. |
| * The constant a is obtained by settting x_1 in the cone of the |
| * convex hull to 1 and minimizing x_2. |
| * Now, each element in the cone of the convex hull is the sum |
| * of elements in the cones of the basic sets. |
| * If a_i is the dilation factor of basic set i, then the problem |
| * we need to solve is |
| * |
| * min \sum_i x_{i,2} |
| * st |
| * \sum_i x_{i,1} = 1 |
| * a_i >= 0 |
| * [ a_i ] |
| * A [ x_i ] >= 0 |
| * |
| * with |
| * [ 1 ] |
| * A_i [ x_i ] >= 0 |
| * |
| * the constraints of each (transformed) basic set. |
| * If a = n/d, then the constraint defining the new facet (in the transformed |
| * space) is |
| * |
| * -n x_1 + d x_2 >= 0 |
| * |
| * In the original space, we need to take the same combination of the |
| * corresponding constraints "facet" and "ridge". |
| * |
| * If a = -infty = "-1/0", then we just return the original facet constraint. |
| * This means that the facet is unbounded, but has a bounded intersection |
| * with the union of sets. |
| */ |
| isl_int *isl_set_wrap_facet(__isl_keep isl_set *set, |
| isl_int *facet, isl_int *ridge) |
| { |
| int i; |
| isl_ctx *ctx; |
| struct isl_mat *T = NULL; |
| struct isl_basic_set *lp = NULL; |
| struct isl_vec *obj; |
| enum isl_lp_result res; |
| isl_int num, den; |
| unsigned dim; |
| |
| if (!set) |
| return NULL; |
| ctx = set->ctx; |
| set = isl_set_copy(set); |
| set = isl_set_set_rational(set); |
| |
| dim = 1 + isl_set_n_dim(set); |
| T = isl_mat_alloc(ctx, 3, dim); |
| if (!T) |
| goto error; |
| isl_int_set_si(T->row[0][0], 1); |
| isl_seq_clr(T->row[0]+1, dim - 1); |
| isl_seq_cpy(T->row[1], facet, dim); |
| isl_seq_cpy(T->row[2], ridge, dim); |
| T = isl_mat_right_inverse(T); |
| set = isl_set_preimage(set, T); |
| T = NULL; |
| if (!set) |
| goto error; |
| lp = wrap_constraints(set); |
| obj = isl_vec_alloc(ctx, 1 + dim*set->n); |
| if (!obj) |
| goto error; |
| isl_int_set_si(obj->block.data[0], 0); |
| for (i = 0; i < set->n; ++i) { |
| isl_seq_clr(obj->block.data + 1 + dim*i, 2); |
| isl_int_set_si(obj->block.data[1 + dim*i+2], 1); |
| isl_seq_clr(obj->block.data + 1 + dim*i+3, dim-3); |
| } |
| isl_int_init(num); |
| isl_int_init(den); |
| res = isl_basic_set_solve_lp(lp, 0, |
| obj->block.data, ctx->one, &num, &den, NULL); |
| if (res == isl_lp_ok) { |
| isl_int_neg(num, num); |
| isl_seq_combine(facet, num, facet, den, ridge, dim); |
| isl_seq_normalize(ctx, facet, dim); |
| } |
| isl_int_clear(num); |
| isl_int_clear(den); |
| isl_vec_free(obj); |
| isl_basic_set_free(lp); |
| isl_set_free(set); |
| if (res == isl_lp_error) |
| return NULL; |
| isl_assert(ctx, res == isl_lp_ok || res == isl_lp_unbounded, |
| return NULL); |
| return facet; |
| error: |
| isl_basic_set_free(lp); |
| isl_mat_free(T); |
| isl_set_free(set); |
| return NULL; |
| } |
| |
| /* Compute the constraint of a facet of "set". |
| * |
| * We first compute the intersection with a bounding constraint |
| * that is orthogonal to one of the coordinate axes. |
| * If the affine hull of this intersection has only one equality, |
| * we have found a facet. |
| * Otherwise, we wrap the current bounding constraint around |
| * one of the equalities of the face (one that is not equal to |
| * the current bounding constraint). |
| * This process continues until we have found a facet. |
| * The dimension of the intersection increases by at least |
| * one on each iteration, so termination is guaranteed. |
| */ |
| static __isl_give isl_mat *initial_facet_constraint(__isl_keep isl_set *set) |
| { |
| struct isl_set *slice = NULL; |
| struct isl_basic_set *face = NULL; |
| int i; |
| unsigned dim = isl_set_n_dim(set); |
| int is_bound; |
| isl_mat *bounds = NULL; |
| |
| isl_assert(set->ctx, set->n > 0, goto error); |
| bounds = isl_mat_alloc(set->ctx, 1, 1 + dim); |
| if (!bounds) |
| return NULL; |
| |
| isl_seq_clr(bounds->row[0], dim); |
| isl_int_set_si(bounds->row[0][1 + dim - 1], 1); |
| is_bound = uset_is_bound(set, bounds->row[0], 1 + dim); |
| if (is_bound < 0) |
| goto error; |
| isl_assert(set->ctx, is_bound, goto error); |
| isl_seq_normalize(set->ctx, bounds->row[0], 1 + dim); |
| bounds->n_row = 1; |
| |
| for (;;) { |
| slice = isl_set_copy(set); |
| slice = isl_set_add_basic_set_equality(slice, bounds->row[0]); |
| face = isl_set_affine_hull(slice); |
| if (!face) |
| goto error; |
| if (face->n_eq == 1) { |
| isl_basic_set_free(face); |
| break; |
| } |
| for (i = 0; i < face->n_eq; ++i) |
| if (!isl_seq_eq(bounds->row[0], face->eq[i], 1 + dim) && |
| !isl_seq_is_neg(bounds->row[0], |
| face->eq[i], 1 + dim)) |
| break; |
| isl_assert(set->ctx, i < face->n_eq, goto error); |
| if (!isl_set_wrap_facet(set, bounds->row[0], face->eq[i])) |
| goto error; |
| isl_seq_normalize(set->ctx, bounds->row[0], bounds->n_col); |
| isl_basic_set_free(face); |
| } |
| |
| return bounds; |
| error: |
| isl_basic_set_free(face); |
| isl_mat_free(bounds); |
| return NULL; |
| } |
| |
| /* Given the bounding constraint "c" of a facet of the convex hull of "set", |
| * compute a hyperplane description of the facet, i.e., compute the facets |
| * of the facet. |
| * |
| * We compute an affine transformation that transforms the constraint |
| * |
| * [ 1 ] |
| * c [ x ] = 0 |
| * |
| * to the constraint |
| * |
| * z_1 = 0 |
| * |
| * by computing the right inverse U of a matrix that starts with the rows |
| * |
| * [ 1 0 ] |
| * [ c ] |
| * |
| * Then |
| * [ 1 ] [ 1 ] |
| * [ x ] = U [ z ] |
| * and |
| * [ 1 ] [ 1 ] |
| * [ z ] = Q [ x ] |
| * |
| * with Q = U^{-1} |
| * Since z_1 is zero, we can drop this variable as well as the corresponding |
| * column of U to obtain |
| * |
| * [ 1 ] [ 1 ] |
| * [ x ] = U' [ z' ] |
| * and |
| * [ 1 ] [ 1 ] |
| * [ z' ] = Q' [ x ] |
| * |
| * with Q' equal to Q, but without the corresponding row. |
| * After computing the facets of the facet in the z' space, |
| * we convert them back to the x space through Q. |
| */ |
| static __isl_give isl_basic_set *compute_facet(__isl_keep isl_set *set, |
| isl_int *c) |
| { |
| struct isl_mat *m, *U, *Q; |
| struct isl_basic_set *facet = NULL; |
| struct isl_ctx *ctx; |
| unsigned dim; |
| |
| ctx = set->ctx; |
| set = isl_set_copy(set); |
| dim = isl_set_n_dim(set); |
| m = isl_mat_alloc(set->ctx, 2, 1 + dim); |
| if (!m) |
| goto error; |
| isl_int_set_si(m->row[0][0], 1); |
| isl_seq_clr(m->row[0]+1, dim); |
| isl_seq_cpy(m->row[1], c, 1+dim); |
| U = isl_mat_right_inverse(m); |
| Q = isl_mat_right_inverse(isl_mat_copy(U)); |
| U = isl_mat_drop_cols(U, 1, 1); |
| Q = isl_mat_drop_rows(Q, 1, 1); |
| set = isl_set_preimage(set, U); |
| facet = uset_convex_hull_wrap_bounded(set); |
| facet = isl_basic_set_preimage(facet, Q); |
| if (facet && facet->n_eq != 0) |
| isl_die(ctx, isl_error_internal, "unexpected equality", |
| return isl_basic_set_free(facet)); |
| return facet; |
| error: |
| isl_basic_set_free(facet); |
| isl_set_free(set); |
| return NULL; |
| } |
| |
| /* Given an initial facet constraint, compute the remaining facets. |
| * We do this by running through all facets found so far and computing |
| * the adjacent facets through wrapping, adding those facets that we |
| * hadn't already found before. |
| * |
| * For each facet we have found so far, we first compute its facets |
| * in the resulting convex hull. That is, we compute the ridges |
| * of the resulting convex hull contained in the facet. |
| * We also compute the corresponding facet in the current approximation |
| * of the convex hull. There is no need to wrap around the ridges |
| * in this facet since that would result in a facet that is already |
| * present in the current approximation. |
| * |
| * This function can still be significantly optimized by checking which of |
| * the facets of the basic sets are also facets of the convex hull and |
| * using all the facets so far to help in constructing the facets of the |
| * facets |
| * and/or |
| * using the technique in section "3.1 Ridge Generation" of |
| * "Extended Convex Hull" by Fukuda et al. |
| */ |
| static __isl_give isl_basic_set *extend(__isl_take isl_basic_set *hull, |
| __isl_keep isl_set *set) |
| { |
| int i, j, f; |
| int k; |
| struct isl_basic_set *facet = NULL; |
| struct isl_basic_set *hull_facet = NULL; |
| unsigned dim; |
| |
| if (!hull) |
| return NULL; |
| |
| isl_assert(set->ctx, set->n > 0, goto error); |
| |
| dim = isl_set_n_dim(set); |
| |
| for (i = 0; i < hull->n_ineq; ++i) { |
| facet = compute_facet(set, hull->ineq[i]); |
| facet = isl_basic_set_add_equality(facet, hull->ineq[i]); |
| facet = isl_basic_set_gauss(facet, NULL); |
| facet = isl_basic_set_normalize_constraints(facet); |
| hull_facet = isl_basic_set_copy(hull); |
| hull_facet = isl_basic_set_add_equality(hull_facet, hull->ineq[i]); |
| hull_facet = isl_basic_set_gauss(hull_facet, NULL); |
| hull_facet = isl_basic_set_normalize_constraints(hull_facet); |
| if (!facet || !hull_facet) |
| goto error; |
| hull = isl_basic_set_cow(hull); |
| hull = isl_basic_set_extend_space(hull, |
| isl_space_copy(hull->dim), 0, 0, facet->n_ineq); |
| if (!hull) |
| goto error; |
| for (j = 0; j < facet->n_ineq; ++j) { |
| for (f = 0; f < hull_facet->n_ineq; ++f) |
| if (isl_seq_eq(facet->ineq[j], |
| hull_facet->ineq[f], 1 + dim)) |
| break; |
| if (f < hull_facet->n_ineq) |
| continue; |
| k = isl_basic_set_alloc_inequality(hull); |
| if (k < 0) |
| goto error; |
| isl_seq_cpy(hull->ineq[k], hull->ineq[i], 1+dim); |
| if (!isl_set_wrap_facet(set, hull->ineq[k], facet->ineq[j])) |
| goto error; |
| } |
| isl_basic_set_free(hull_facet); |
| isl_basic_set_free(facet); |
| } |
| hull = isl_basic_set_simplify(hull); |
| hull = isl_basic_set_finalize(hull); |
| return hull; |
| error: |
| isl_basic_set_free(hull_facet); |
| isl_basic_set_free(facet); |
| isl_basic_set_free(hull); |
| return NULL; |
| } |
| |
| /* Special case for computing the convex hull of a one dimensional set. |
| * We simply collect the lower and upper bounds of each basic set |
| * and the biggest of those. |
| */ |
| static __isl_give isl_basic_set *convex_hull_1d(__isl_take isl_set *set) |
| { |
| struct isl_mat *c = NULL; |
| isl_int *lower = NULL; |
| isl_int *upper = NULL; |
| int i, j, k; |
| isl_int a, b; |
| struct isl_basic_set *hull; |
| |
| for (i = 0; i < set->n; ++i) { |
| set->p[i] = isl_basic_set_simplify(set->p[i]); |
| if (!set->p[i]) |
| goto error; |
| } |
| set = isl_set_remove_empty_parts(set); |
| if (!set) |
| goto error; |
| isl_assert(set->ctx, set->n > 0, goto error); |
| c = isl_mat_alloc(set->ctx, 2, 2); |
| if (!c) |
| goto error; |
| |
| if (set->p[0]->n_eq > 0) { |
| isl_assert(set->ctx, set->p[0]->n_eq == 1, goto error); |
| lower = c->row[0]; |
| upper = c->row[1]; |
| if (isl_int_is_pos(set->p[0]->eq[0][1])) { |
| isl_seq_cpy(lower, set->p[0]->eq[0], 2); |
| isl_seq_neg(upper, set->p[0]->eq[0], 2); |
| } else { |
| isl_seq_neg(lower, set->p[0]->eq[0], 2); |
| isl_seq_cpy(upper, set->p[0]->eq[0], 2); |
| } |
| } else { |
| for (j = 0; j < set->p[0]->n_ineq; ++j) { |
| if (isl_int_is_pos(set->p[0]->ineq[j][1])) { |
| lower = c->row[0]; |
| isl_seq_cpy(lower, set->p[0]->ineq[j], 2); |
| } else { |
| upper = c->row[1]; |
| isl_seq_cpy(upper, set->p[0]->ineq[j], 2); |
| } |
| } |
| } |
| |
| isl_int_init(a); |
| isl_int_init(b); |
| for (i = 0; i < set->n; ++i) { |
| struct isl_basic_set *bset = set->p[i]; |
| int has_lower = 0; |
| int has_upper = 0; |
| |
| for (j = 0; j < bset->n_eq; ++j) { |
| has_lower = 1; |
| has_upper = 1; |
| if (lower) { |
| isl_int_mul(a, lower[0], bset->eq[j][1]); |
| isl_int_mul(b, lower[1], bset->eq[j][0]); |
| if (isl_int_lt(a, b) && isl_int_is_pos(bset->eq[j][1])) |
| isl_seq_cpy(lower, bset->eq[j], 2); |
| if (isl_int_gt(a, b) && isl_int_is_neg(bset->eq[j][1])) |
| isl_seq_neg(lower, bset->eq[j], 2); |
| } |
| if (upper) { |
| isl_int_mul(a, upper[0], bset->eq[j][1]); |
| isl_int_mul(b, upper[1], bset->eq[j][0]); |
| if (isl_int_lt(a, b) && isl_int_is_pos(bset->eq[j][1])) |
| isl_seq_neg(upper, bset->eq[j], 2); |
| if (isl_int_gt(a, b) && isl_int_is_neg(bset->eq[j][1])) |
| isl_seq_cpy(upper, bset->eq[j], 2); |
| } |
| } |
| for (j = 0; j < bset->n_ineq; ++j) { |
| if (isl_int_is_pos(bset->ineq[j][1])) |
| has_lower = 1; |
| if (isl_int_is_neg(bset->ineq[j][1])) |
| has_upper = 1; |
| if (lower && isl_int_is_pos(bset->ineq[j][1])) { |
| isl_int_mul(a, lower[0], bset->ineq[j][1]); |
| isl_int_mul(b, lower[1], bset->ineq[j][0]); |
| if (isl_int_lt(a, b)) |
| isl_seq_cpy(lower, bset->ineq[j], 2); |
| } |
| if (upper && isl_int_is_neg(bset->ineq[j][1])) { |
| isl_int_mul(a, upper[0], bset->ineq[j][1]); |
| isl_int_mul(b, upper[1], bset->ineq[j][0]); |
| if (isl_int_gt(a, b)) |
| isl_seq_cpy(upper, bset->ineq[j], 2); |
| } |
| } |
| if (!has_lower) |
| lower = NULL; |
| if (!has_upper) |
| upper = NULL; |
| } |
| isl_int_clear(a); |
| isl_int_clear(b); |
| |
| hull = isl_basic_set_alloc(set->ctx, 0, 1, 0, 0, 2); |
| hull = isl_basic_set_set_rational(hull); |
| if (!hull) |
| goto error; |
| if (lower) { |
| k = isl_basic_set_alloc_inequality(hull); |
| isl_seq_cpy(hull->ineq[k], lower, 2); |
| } |
| if (upper) { |
| k = isl_basic_set_alloc_inequality(hull); |
| isl_seq_cpy(hull->ineq[k], upper, 2); |
| } |
| hull = isl_basic_set_finalize(hull); |
| isl_set_free(set); |
| isl_mat_free(c); |
| return hull; |
| error: |
| isl_set_free(set); |
| isl_mat_free(c); |
| return NULL; |
| } |
| |
| static __isl_give isl_basic_set *convex_hull_0d(__isl_take isl_set *set) |
| { |
| struct isl_basic_set *convex_hull; |
| |
| if (!set) |
| return NULL; |
| |
| if (isl_set_is_empty(set)) |
| convex_hull = isl_basic_set_empty(isl_space_copy(set->dim)); |
| else |
| convex_hull = isl_basic_set_universe(isl_space_copy(set->dim)); |
| isl_set_free(set); |
| return convex_hull; |
| } |
| |
| /* Compute the convex hull of a pair of basic sets without any parameters or |
| * integer divisions using Fourier-Motzkin elimination. |
| * The convex hull is the set of all points that can be written as |
| * the sum of points from both basic sets (in homogeneous coordinates). |
| * We set up the constraints in a space with dimensions for each of |
| * the three sets and then project out the dimensions corresponding |
| * to the two original basic sets, retaining only those corresponding |
| * to the convex hull. |
| */ |
| static __isl_give isl_basic_set *convex_hull_pair_elim( |
| __isl_take isl_basic_set *bset1, __isl_take isl_basic_set *bset2) |
| { |
| int i, j, k; |
| struct isl_basic_set *bset[2]; |
| struct isl_basic_set *hull = NULL; |
| unsigned dim; |
| |
| if (!bset1 || !bset2) |
| goto error; |
| |
| dim = isl_basic_set_n_dim(bset1); |
| hull = isl_basic_set_alloc(bset1->ctx, 0, 2 + 3 * dim, 0, |
| 1 + dim + bset1->n_eq + bset2->n_eq, |
| 2 + bset1->n_ineq + bset2->n_ineq); |
| bset[0] = bset1; |
| bset[1] = bset2; |
| for (i = 0; i < 2; ++i) { |
| for (j = 0; j < bset[i]->n_eq; ++j) { |
| k = isl_basic_set_alloc_equality(hull); |
| if (k < 0) |
| goto error; |
| isl_seq_clr(hull->eq[k], (i+1) * (1+dim)); |
| isl_seq_clr(hull->eq[k]+(i+2)*(1+dim), (1-i)*(1+dim)); |
| isl_seq_cpy(hull->eq[k]+(i+1)*(1+dim), bset[i]->eq[j], |
| 1+dim); |
| } |
| for (j = 0; j < bset[i]->n_ineq; ++j) { |
| k = isl_basic_set_alloc_inequality(hull); |
| if (k < 0) |
| goto error; |
| isl_seq_clr(hull->ineq[k], (i+1) * (1+dim)); |
| isl_seq_clr(hull->ineq[k]+(i+2)*(1+dim), (1-i)*(1+dim)); |
| isl_seq_cpy(hull->ineq[k]+(i+1)*(1+dim), |
| bset[i]->ineq[j], 1+dim); |
| } |
| k = isl_basic_set_alloc_inequality(hull); |
| if (k < 0) |
| goto error; |
| isl_seq_clr(hull->ineq[k], 1+2+3*dim); |
| isl_int_set_si(hull->ineq[k][(i+1)*(1+dim)], 1); |
| } |
| for (j = 0; j < 1+dim; ++j) { |
| k = isl_basic_set_alloc_equality(hull); |
| if (k < 0) |
| goto error; |
| isl_seq_clr(hull->eq[k], 1+2+3*dim); |
| isl_int_set_si(hull->eq[k][j], -1); |
| isl_int_set_si(hull->eq[k][1+dim+j], 1); |
| isl_int_set_si(hull->eq[k][2*(1+dim)+j], 1); |
| } |
| hull = isl_basic_set_set_rational(hull); |
| hull = isl_basic_set_remove_dims(hull, isl_dim_set, dim, 2*(1+dim)); |
| hull = isl_basic_set_remove_redundancies(hull); |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return hull; |
| error: |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| isl_basic_set_free(hull); |
| return NULL; |
| } |
| |
| /* Is the set bounded for each value of the parameters? |
| */ |
| isl_bool isl_basic_set_is_bounded(__isl_keep isl_basic_set *bset) |
| { |
| struct isl_tab *tab; |
| isl_bool bounded; |
| |
| if (!bset) |
| return isl_bool_error; |
| if (isl_basic_set_plain_is_empty(bset)) |
| return isl_bool_true; |
| |
| tab = isl_tab_from_recession_cone(bset, 1); |
| bounded = isl_tab_cone_is_bounded(tab); |
| isl_tab_free(tab); |
| return bounded; |
| } |
| |
| /* Is the image bounded for each value of the parameters and |
| * the domain variables? |
| */ |
| isl_bool isl_basic_map_image_is_bounded(__isl_keep isl_basic_map *bmap) |
| { |
| unsigned nparam = isl_basic_map_dim(bmap, isl_dim_param); |
| unsigned n_in = isl_basic_map_dim(bmap, isl_dim_in); |
| isl_bool bounded; |
| |
| bmap = isl_basic_map_copy(bmap); |
| bmap = isl_basic_map_cow(bmap); |
| bmap = isl_basic_map_move_dims(bmap, isl_dim_param, nparam, |
| isl_dim_in, 0, n_in); |
| bounded = isl_basic_set_is_bounded(bset_from_bmap(bmap)); |
| isl_basic_map_free(bmap); |
| |
| return bounded; |
| } |
| |
| /* Is the set bounded for each value of the parameters? |
| */ |
| isl_bool isl_set_is_bounded(__isl_keep isl_set *set) |
| { |
| int i; |
| |
| if (!set) |
| return isl_bool_error; |
| |
| for (i = 0; i < set->n; ++i) { |
| isl_bool bounded = isl_basic_set_is_bounded(set->p[i]); |
| if (!bounded || bounded < 0) |
| return bounded; |
| } |
| return isl_bool_true; |
| } |
| |
| /* Compute the lineality space of the convex hull of bset1 and bset2. |
| * |
| * We first compute the intersection of the recession cone of bset1 |
| * with the negative of the recession cone of bset2 and then compute |
| * the linear hull of the resulting cone. |
| */ |
| static __isl_give isl_basic_set *induced_lineality_space( |
| __isl_take isl_basic_set *bset1, __isl_take isl_basic_set *bset2) |
| { |
| int i, k; |
| struct isl_basic_set *lin = NULL; |
| unsigned dim; |
| |
| if (!bset1 || !bset2) |
| goto error; |
| |
| dim = isl_basic_set_total_dim(bset1); |
| lin = isl_basic_set_alloc_space(isl_basic_set_get_space(bset1), 0, |
| bset1->n_eq + bset2->n_eq, |
| bset1->n_ineq + bset2->n_ineq); |
| lin = isl_basic_set_set_rational(lin); |
| if (!lin) |
| goto error; |
| for (i = 0; i < bset1->n_eq; ++i) { |
| k = isl_basic_set_alloc_equality(lin); |
| if (k < 0) |
| goto error; |
| isl_int_set_si(lin->eq[k][0], 0); |
| isl_seq_cpy(lin->eq[k] + 1, bset1->eq[i] + 1, dim); |
| } |
| for (i = 0; i < bset1->n_ineq; ++i) { |
| k = isl_basic_set_alloc_inequality(lin); |
| if (k < 0) |
| goto error; |
| isl_int_set_si(lin->ineq[k][0], 0); |
| isl_seq_cpy(lin->ineq[k] + 1, bset1->ineq[i] + 1, dim); |
| } |
| for (i = 0; i < bset2->n_eq; ++i) { |
| k = isl_basic_set_alloc_equality(lin); |
| if (k < 0) |
| goto error; |
| isl_int_set_si(lin->eq[k][0], 0); |
| isl_seq_neg(lin->eq[k] + 1, bset2->eq[i] + 1, dim); |
| } |
| for (i = 0; i < bset2->n_ineq; ++i) { |
| k = isl_basic_set_alloc_inequality(lin); |
| if (k < 0) |
| goto error; |
| isl_int_set_si(lin->ineq[k][0], 0); |
| isl_seq_neg(lin->ineq[k] + 1, bset2->ineq[i] + 1, dim); |
| } |
| |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return isl_basic_set_affine_hull(lin); |
| error: |
| isl_basic_set_free(lin); |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return NULL; |
| } |
| |
| static __isl_give isl_basic_set *uset_convex_hull(__isl_take isl_set *set); |
| |
| /* Given a set and a linear space "lin" of dimension n > 0, |
| * project the linear space from the set, compute the convex hull |
| * and then map the set back to the original space. |
| * |
| * Let |
| * |
| * M x = 0 |
| * |
| * describe the linear space. We first compute the Hermite normal |
| * form H = M U of M = H Q, to obtain |
| * |
| * H Q x = 0 |
| * |
| * The last n rows of H will be zero, so the last n variables of x' = Q x |
| * are the one we want to project out. We do this by transforming each |
| * basic set A x >= b to A U x' >= b and then removing the last n dimensions. |
| * After computing the convex hull in x'_1, i.e., A' x'_1 >= b', |
| * we transform the hull back to the original space as A' Q_1 x >= b', |
| * with Q_1 all but the last n rows of Q. |
| */ |
| static __isl_give isl_basic_set *modulo_lineality(__isl_take isl_set *set, |
| __isl_take isl_basic_set *lin) |
| { |
| unsigned total = isl_basic_set_total_dim(lin); |
| unsigned lin_dim; |
| struct isl_basic_set *hull; |
| struct isl_mat *M, *U, *Q; |
| |
| if (!set || !lin) |
| goto error; |
| lin_dim = total - lin->n_eq; |
| M = isl_mat_sub_alloc6(set->ctx, lin->eq, 0, lin->n_eq, 1, total); |
| M = isl_mat_left_hermite(M, 0, &U, &Q); |
| if (!M) |
| goto error; |
| isl_mat_free(M); |
| isl_basic_set_free(lin); |
| |
| Q = isl_mat_drop_rows(Q, Q->n_row - lin_dim, lin_dim); |
| |
| U = isl_mat_lin_to_aff(U); |
| Q = isl_mat_lin_to_aff(Q); |
| |
| set = isl_set_preimage(set, U); |
| set = isl_set_remove_dims(set, isl_dim_set, total - lin_dim, lin_dim); |
| hull = uset_convex_hull(set); |
| hull = isl_basic_set_preimage(hull, Q); |
| |
| return hull; |
| error: |
| isl_basic_set_free(lin); |
| isl_set_free(set); |
| return NULL; |
| } |
| |
| /* Given two polyhedra with as constraints h_{ij} x >= 0 in homegeneous space, |
| * set up an LP for solving |
| * |
| * \sum_j \alpha_{1j} h_{1j} = \sum_j \alpha_{2j} h_{2j} |
| * |
| * \alpha{i0} corresponds to the (implicit) positivity constraint 1 >= 0 |
| * The next \alpha{ij} correspond to the equalities and come in pairs. |
| * The final \alpha{ij} correspond to the inequalities. |
| */ |
| static __isl_give isl_basic_set *valid_direction_lp( |
| __isl_take isl_basic_set *bset1, __isl_take isl_basic_set *bset2) |
| { |
| isl_space *dim; |
| struct isl_basic_set *lp; |
| unsigned d; |
| int n; |
| int i, j, k; |
| |
| if (!bset1 || !bset2) |
| goto error; |
| d = 1 + isl_basic_set_total_dim(bset1); |
| n = 2 + |
| 2 * bset1->n_eq + bset1->n_ineq + 2 * bset2->n_eq + bset2->n_ineq; |
| dim = isl_space_set_alloc(bset1->ctx, 0, n); |
| lp = isl_basic_set_alloc_space(dim, 0, d, n); |
| if (!lp) |
| goto error; |
| for (i = 0; i < n; ++i) { |
| k = isl_basic_set_alloc_inequality(lp); |
| if (k < 0) |
| goto error; |
| isl_seq_clr(lp->ineq[k] + 1, n); |
| isl_int_set_si(lp->ineq[k][0], -1); |
| isl_int_set_si(lp->ineq[k][1 + i], 1); |
| } |
| for (i = 0; i < d; ++i) { |
| k = isl_basic_set_alloc_equality(lp); |
| if (k < 0) |
| goto error; |
| n = 0; |
| isl_int_set_si(lp->eq[k][n], 0); n++; |
| /* positivity constraint 1 >= 0 */ |
| isl_int_set_si(lp->eq[k][n], i == 0); n++; |
| for (j = 0; j < bset1->n_eq; ++j) { |
| isl_int_set(lp->eq[k][n], bset1->eq[j][i]); n++; |
| isl_int_neg(lp->eq[k][n], bset1->eq[j][i]); n++; |
| } |
| for (j = 0; j < bset1->n_ineq; ++j) { |
| isl_int_set(lp->eq[k][n], bset1->ineq[j][i]); n++; |
| } |
| /* positivity constraint 1 >= 0 */ |
| isl_int_set_si(lp->eq[k][n], -(i == 0)); n++; |
| for (j = 0; j < bset2->n_eq; ++j) { |
| isl_int_neg(lp->eq[k][n], bset2->eq[j][i]); n++; |
| isl_int_set(lp->eq[k][n], bset2->eq[j][i]); n++; |
| } |
| for (j = 0; j < bset2->n_ineq; ++j) { |
| isl_int_neg(lp->eq[k][n], bset2->ineq[j][i]); n++; |
| } |
| } |
| lp = isl_basic_set_gauss(lp, NULL); |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return lp; |
| error: |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return NULL; |
| } |
| |
| /* Compute a vector s in the homogeneous space such that <s, r> > 0 |
| * for all rays in the homogeneous space of the two cones that correspond |
| * to the input polyhedra bset1 and bset2. |
| * |
| * We compute s as a vector that satisfies |
| * |
| * s = \sum_j \alpha_{ij} h_{ij} for i = 1,2 (*) |
| * |
| * with h_{ij} the normals of the facets of polyhedron i |
| * (including the "positivity constraint" 1 >= 0) and \alpha_{ij} |
| * strictly positive numbers. For simplicity we impose \alpha_{ij} >= 1. |
| * We first set up an LP with as variables the \alpha{ij}. |
| * In this formulation, for each polyhedron i, |
| * the first constraint is the positivity constraint, followed by pairs |
| * of variables for the equalities, followed by variables for the inequalities. |
| * We then simply pick a feasible solution and compute s using (*). |
| * |
| * Note that we simply pick any valid direction and make no attempt |
| * to pick a "good" or even the "best" valid direction. |
| */ |
| static __isl_give isl_vec *valid_direction( |
| __isl_take isl_basic_set *bset1, __isl_take isl_basic_set *bset2) |
| { |
| struct isl_basic_set *lp; |
| struct isl_tab *tab; |
| struct isl_vec *sample = NULL; |
| struct isl_vec *dir; |
| unsigned d; |
| int i; |
| int n; |
| |
| if (!bset1 || !bset2) |
| goto error; |
| lp = valid_direction_lp(isl_basic_set_copy(bset1), |
| isl_basic_set_copy(bset2)); |
| tab = isl_tab_from_basic_set(lp, 0); |
| sample = isl_tab_get_sample_value(tab); |
| isl_tab_free(tab); |
| isl_basic_set_free(lp); |
| if (!sample) |
| goto error; |
| d = isl_basic_set_total_dim(bset1); |
| dir = isl_vec_alloc(bset1->ctx, 1 + d); |
| if (!dir) |
| goto error; |
| isl_seq_clr(dir->block.data + 1, dir->size - 1); |
| n = 1; |
| /* positivity constraint 1 >= 0 */ |
| isl_int_set(dir->block.data[0], sample->block.data[n]); n++; |
| for (i = 0; i < bset1->n_eq; ++i) { |
| isl_int_sub(sample->block.data[n], |
| sample->block.data[n], sample->block.data[n+1]); |
| isl_seq_combine(dir->block.data, |
| bset1->ctx->one, dir->block.data, |
| sample->block.data[n], bset1->eq[i], 1 + d); |
| |
| n += 2; |
| } |
| for (i = 0; i < bset1->n_ineq; ++i) |
| isl_seq_combine(dir->block.data, |
| bset1->ctx->one, dir->block.data, |
| sample->block.data[n++], bset1->ineq[i], 1 + d); |
| isl_vec_free(sample); |
| isl_seq_normalize(bset1->ctx, dir->el, dir->size); |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return dir; |
| error: |
| isl_vec_free(sample); |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return NULL; |
| } |
| |
| /* Given a polyhedron b_i + A_i x >= 0 and a map T = S^{-1}, |
| * compute b_i' + A_i' x' >= 0, with |
| * |
| * [ b_i A_i ] [ y' ] [ y' ] |
| * [ 1 0 ] S^{-1} [ x' ] >= 0 or [ b_i' A_i' ] [ x' ] >= 0 |
| * |
| * In particular, add the "positivity constraint" and then perform |
| * the mapping. |
| */ |
| static __isl_give isl_basic_set *homogeneous_map(__isl_take isl_basic_set *bset, |
| __isl_take isl_mat *T) |
| { |
| int k; |
| |
| if (!bset) |
| goto error; |
| bset = isl_basic_set_extend_constraints(bset, 0, 1); |
| k = isl_basic_set_alloc_inequality(bset); |
| if (k < 0) |
| goto error; |
| isl_seq_clr(bset->ineq[k] + 1, isl_basic_set_total_dim(bset)); |
| isl_int_set_si(bset->ineq[k][0], 1); |
| bset = isl_basic_set_preimage(bset, T); |
| return bset; |
| error: |
| isl_mat_free(T); |
| isl_basic_set_free(bset); |
| return NULL; |
| } |
| |
| /* Compute the convex hull of a pair of basic sets without any parameters or |
| * integer divisions, where the convex hull is known to be pointed, |
| * but the basic sets may be unbounded. |
| * |
| * We turn this problem into the computation of a convex hull of a pair |
| * _bounded_ polyhedra by "changing the direction of the homogeneous |
| * dimension". This idea is due to Matthias Koeppe. |
| * |
| * Consider the cones in homogeneous space that correspond to the |
| * input polyhedra. The rays of these cones are also rays of the |
| * polyhedra if the coordinate that corresponds to the homogeneous |
| * dimension is zero. That is, if the inner product of the rays |
| * with the homogeneous direction is zero. |
| * The cones in the homogeneous space can also be considered to |
| * correspond to other pairs of polyhedra by chosing a different |
| * homogeneous direction. To ensure that both of these polyhedra |
| * are bounded, we need to make sure that all rays of the cones |
| * correspond to vertices and not to rays. |
| * Let s be a direction such that <s, r> > 0 for all rays r of both cones. |
| * Then using s as a homogeneous direction, we obtain a pair of polytopes. |
| * The vector s is computed in valid_direction. |
| * |
| * Note that we need to consider _all_ rays of the cones and not just |
| * the rays that correspond to rays in the polyhedra. If we were to |
| * only consider those rays and turn them into vertices, then we |
| * may inadvertently turn some vertices into rays. |
| * |
| * The standard homogeneous direction is the unit vector in the 0th coordinate. |
| * We therefore transform the two polyhedra such that the selected |
| * direction is mapped onto this standard direction and then proceed |
| * with the normal computation. |
| * Let S be a non-singular square matrix with s as its first row, |
| * then we want to map the polyhedra to the space |
| * |
| * [ y' ] [ y ] [ y ] [ y' ] |
| * [ x' ] = S [ x ] i.e., [ x ] = S^{-1} [ x' ] |
| * |
| * We take S to be the unimodular completion of s to limit the growth |
| * of the coefficients in the following computations. |
| * |
| * Let b_i + A_i x >= 0 be the constraints of polyhedron i. |
| * We first move to the homogeneous dimension |
| * |
| * b_i y + A_i x >= 0 [ b_i A_i ] [ y ] [ 0 ] |
| * y >= 0 or [ 1 0 ] [ x ] >= [ 0 ] |
| * |
| * Then we change directoin |
| * |
| * [ b_i A_i ] [ y' ] [ y' ] |
| * [ 1 0 ] S^{-1} [ x' ] >= 0 or [ b_i' A_i' ] [ x' ] >= 0 |
| * |
| * Then we compute the convex hull of the polytopes b_i' + A_i' x' >= 0 |
| * resulting in b' + A' x' >= 0, which we then convert back |
| * |
| * [ y ] [ y ] |
| * [ b' A' ] S [ x ] >= 0 or [ b A ] [ x ] >= 0 |
| * |
| * The polyhedron b + A x >= 0 is then the convex hull of the input polyhedra. |
| */ |
| static __isl_give isl_basic_set *convex_hull_pair_pointed( |
| __isl_take isl_basic_set *bset1, __isl_take isl_basic_set *bset2) |
| { |
| struct isl_ctx *ctx = NULL; |
| struct isl_vec *dir = NULL; |
| struct isl_mat *T = NULL; |
| struct isl_mat *T2 = NULL; |
| struct isl_basic_set *hull; |
| struct isl_set *set; |
| |
| if (!bset1 || !bset2) |
| goto error; |
| ctx = isl_basic_set_get_ctx(bset1); |
| dir = valid_direction(isl_basic_set_copy(bset1), |
| isl_basic_set_copy(bset2)); |
| if (!dir) |
| goto error; |
| T = isl_mat_alloc(ctx, dir->size, dir->size); |
| if (!T) |
| goto error; |
| isl_seq_cpy(T->row[0], dir->block.data, dir->size); |
| T = isl_mat_unimodular_complete(T, 1); |
| T2 = isl_mat_right_inverse(isl_mat_copy(T)); |
| |
| bset1 = homogeneous_map(bset1, isl_mat_copy(T2)); |
| bset2 = homogeneous_map(bset2, T2); |
| set = isl_set_alloc_space(isl_basic_set_get_space(bset1), 2, 0); |
| set = isl_set_add_basic_set(set, bset1); |
| set = isl_set_add_basic_set(set, bset2); |
| hull = uset_convex_hull(set); |
| hull = isl_basic_set_preimage(hull, T); |
| |
| isl_vec_free(dir); |
| |
| return hull; |
| error: |
| isl_vec_free(dir); |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return NULL; |
| } |
| |
| static __isl_give isl_basic_set *uset_convex_hull_wrap(__isl_take isl_set *set); |
| static __isl_give isl_basic_set *modulo_affine_hull( |
| __isl_take isl_set *set, __isl_take isl_basic_set *affine_hull); |
| |
| /* Compute the convex hull of a pair of basic sets without any parameters or |
| * integer divisions. |
| * |
| * This function is called from uset_convex_hull_unbounded, which |
| * means that the complete convex hull is unbounded. Some pairs |
| * of basic sets may still be bounded, though. |
| * They may even lie inside a lower dimensional space, in which |
| * case they need to be handled inside their affine hull since |
| * the main algorithm assumes that the result is full-dimensional. |
| * |
| * If the convex hull of the two basic sets would have a non-trivial |
| * lineality space, we first project out this lineality space. |
| */ |
| static __isl_give isl_basic_set *convex_hull_pair( |
| __isl_take isl_basic_set *bset1, __isl_take isl_basic_set *bset2) |
| { |
| isl_basic_set *lin, *aff; |
| int bounded1, bounded2; |
| |
| if (bset1->ctx->opt->convex == ISL_CONVEX_HULL_FM) |
| return convex_hull_pair_elim(bset1, bset2); |
| |
| aff = isl_set_affine_hull(isl_basic_set_union(isl_basic_set_copy(bset1), |
| isl_basic_set_copy(bset2))); |
| if (!aff) |
| goto error; |
| if (aff->n_eq != 0) |
| return modulo_affine_hull(isl_basic_set_union(bset1, bset2), aff); |
| isl_basic_set_free(aff); |
| |
| bounded1 = isl_basic_set_is_bounded(bset1); |
| bounded2 = isl_basic_set_is_bounded(bset2); |
| |
| if (bounded1 < 0 || bounded2 < 0) |
| goto error; |
| |
| if (bounded1 && bounded2) |
| return uset_convex_hull_wrap(isl_basic_set_union(bset1, bset2)); |
| |
| if (bounded1 || bounded2) |
| return convex_hull_pair_pointed(bset1, bset2); |
| |
| lin = induced_lineality_space(isl_basic_set_copy(bset1), |
| isl_basic_set_copy(bset2)); |
| if (!lin) |
| goto error; |
| if (isl_basic_set_plain_is_universe(lin)) { |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return lin; |
| } |
| if (lin->n_eq < isl_basic_set_total_dim(lin)) { |
| struct isl_set *set; |
| set = isl_set_alloc_space(isl_basic_set_get_space(bset1), 2, 0); |
| set = isl_set_add_basic_set(set, bset1); |
| set = isl_set_add_basic_set(set, bset2); |
| return modulo_lineality(set, lin); |
| } |
| isl_basic_set_free(lin); |
| |
| return convex_hull_pair_pointed(bset1, bset2); |
| error: |
| isl_basic_set_free(bset1); |
| isl_basic_set_free(bset2); |
| return NULL; |
| } |
| |
| /* Compute the lineality space of a basic set. |
| * We basically just drop the constants and turn every inequality |
| * into an equality. |
| * Any explicit representations of local variables are removed |
| * because they may no longer be valid representations |
| * in the lineality space. |
| */ |
| __isl_give isl_basic_set *isl_basic_set_lineality_space( |
| __isl_take isl_basic_set *bset) |
| { |
| int i, k; |
| struct isl_basic_set *lin = NULL; |
| unsigned n_div, dim; |
| |
| if (!bset) |
| goto error; |
| n_div = isl_basic_set_dim(bset, isl_dim_div); |
| dim = isl_basic_set_total_dim(bset); |
| |
| lin = isl_basic_set_alloc_space(isl_basic_set_get_space(bset), |
| n_div, dim, 0); |
| for (i = 0; i < n_div; ++i) |
| if (isl_basic_set_alloc_div(lin) < 0) |
| goto error; |
| if (!lin) |
| goto error; |
| for (i = 0; i < bset->n_eq; ++i) { |
| k = isl_basic_set_alloc_equality(lin); |
| if (k < 0) |
| goto error; |
| isl_int_set_si(lin->eq[k][0], 0); |
| isl_seq_cpy(lin->eq[k] + 1, bset->eq[i] + 1, dim); |
| } |
| lin = isl_basic_set_gauss(lin, NULL); |
| if (!lin) |
| goto error; |
| for (i = 0; i < bset->n_ineq && lin->n_eq < dim; ++i) { |
| k = isl_basic_set_alloc_equality(lin); |
| if (k < 0) |
| goto error; |
| isl_int_set_si(lin->eq[k][0], 0); |
| isl_seq_cpy(lin->eq[k] + 1, bset->ineq[i] + 1, dim); |
| lin = isl_basic_set_gauss(lin, NULL); |
| if (!lin) |
| goto error; |
| } |
| isl_basic_set_free(bset); |
| return lin; |
| error: |
| isl_basic_set_free(lin); |
| isl_basic_set_free(bset); |
| return NULL; |
| } |
| |
| /* Compute the (linear) hull of the lineality spaces of the basic sets in the |
| * set "set". |
| */ |
| __isl_give isl_basic_set *isl_set_combined_lineality_space( |
| __isl_take isl_set *set) |
| { |
| int i; |
| struct isl_set *lin = NULL; |
| |
| if (!set) |
| return NULL; |
| if (set->n == 0) { |
| isl_space *space = isl_set_get_space(set); |
| isl_set_free(set); |
| return isl_basic_set_empty(space); |
| } |
| |
| lin = isl_set_alloc_space(isl_set_get_space(set), set->n, 0); |
| for (i = 0; i < set->n; ++i) |
| lin = isl_set_add_basic_set(lin, |
| isl_basic_set_lineality_space(isl_basic_set_copy(set->p[i]))); |
| isl_set_free(set); |
| return isl_set_affine_hull(lin); |
| } |
| |
| /* Compute the convex hull of a set without any parameters or |
| * integer divisions. |
| * In each step, we combined two basic sets until only one |
| * basic set is left. |
| * The input basic sets are assumed not to have a non-trivial |
| * lineality space. If any of the intermediate results has |
| * a non-trivial lineality space, it is projected out. |
| */ |
| static __isl_give isl_basic_set *uset_convex_hull_unbounded( |
| __isl_take isl_set *set) |
| { |
| isl_basic_set_list *list; |
| |
| list = isl_set_get_basic_set_list(set); |
| isl_set_free(set); |
| |
| while (list) { |
| int n; |
| struct isl_basic_set *t; |
| isl_basic_set *bset1, *bset2; |
| |
| n = isl_basic_set_list_n_basic_set(list); |
| if (n < 2) |
| isl_die(isl_basic_set_list_get_ctx(list), |
| isl_error_internal, |
| "expecting at least two elements", goto error); |
| bset1 = isl_basic_set_list_get_basic_set(list, n - 1); |
| bset2 = isl_basic_set_list_get_basic_set(list, n - 2); |
| bset1 = convex_hull_pair(bset1, bset2); |
| if (n == 2) { |
| isl_basic_set_list_free(list); |
| return bset1; |
| } |
| bset1 = isl_basic_set_underlying_set(bset1); |
| list = isl_basic_set_list_drop(list, n - 2, 2); |
| list = isl_basic_set_list_add(list, bset1); |
| |
| t = isl_basic_set_list_get_basic_set(list, n - 2); |
| t = isl_basic_set_lineality_space(t); |
| if (!t) |
| goto error; |
| if (isl_basic_set_plain_is_universe(t)) { |
| isl_basic_set_list_free(list); |
| return t; |
| } |
| if (t->n_eq < isl_basic_set_total_dim(t)) { |
| set = isl_basic_set_list_union(list); |
| return modulo_lineality(set, t); |
| } |
| isl_basic_set_free(t); |
| } |
| |
| return NULL; |
| error: |
| isl_basic_set_list_free(list); |
| return NULL; |
| } |
| |
| /* Compute an initial hull for wrapping containing a single initial |
| * facet. |
| * This function assumes that the given set is bounded. |
| */ |
| static __isl_give isl_basic_set *initial_hull(__isl_take isl_basic_set *hull, |
| __isl_keep isl_set *set) |
| { |
| struct isl_mat *bounds = NULL; |
| unsigned dim; |
| int k; |
| |
| if (!hull) |
| goto error; |
| bounds = initial_facet_constraint(set); |
| if (!bounds) |
| goto error; |
| k = isl_basic_set_alloc_inequality(hull); |
| if (k < 0) |
| goto error; |
| dim = isl_set_n_dim(set); |
| isl_assert(set->ctx, 1 + dim == bounds->n_col, goto error); |
| isl_seq_cpy(hull->ineq[k], bounds->row[0], bounds->n_col); |
| isl_mat_free(bounds); |
| |
| return hull; |
| error: |
| isl_basic_set_free(hull); |
| isl_mat_free(bounds); |
| return NULL; |
| } |
| |
| struct max_constraint { |
| struct isl_mat *c; |
| int count; |
| int ineq; |
| }; |
| |
| static int max_constraint_equal(const void *entry, const void *val) |
| { |
| struct max_constraint *a = (struct max_constraint *)entry; |
| isl_int *b = (isl_int *)val; |
| |
| return isl_seq_eq(a->c->row[0] + 1, b, a->c->n_col - 1); |
| } |
| |
| static void update_constraint(struct isl_ctx *ctx, struct isl_hash_table *table, |
| isl_int *con, unsigned len, int n, int ineq) |
| { |
| struct isl_hash_table_entry *entry; |
| struct max_constraint *c; |
| uint32_t c_hash; |
| |
| c_hash = isl_seq_get_hash(con + 1, len); |
| entry = isl_hash_table_find(ctx, table, c_hash, max_constraint_equal, |
| con + 1, 0); |
| if (!entry) |
| return; |
| c = entry->data; |
| if (c->count < n) { |
| isl_hash_table_remove(ctx, table, entry); |
| return; |
| } |
| c->count++; |
| if (isl_int_gt(c->c->row[0][0], con[0])) |
| return; |
| if (isl_int_eq(c->c->row[0][0], con[0])) { |
| if (ineq) |
| c->ineq = ineq; |
| return; |
| } |
| c->c = isl_mat_cow(c->c); |
| isl_int_set(c->c->row[0][0], con[0]); |
| c->ineq = ineq; |
| } |
| |
| /* Check whether the constraint hash table "table" contains the constraint |
| * "con". |
| */ |
| static int has_constraint(struct isl_ctx *ctx, struct isl_hash_table *table, |
| isl_int *con, unsigned len, int n) |
| { |
| struct isl_hash_table_entry *entry; |
| struct max_constraint *c; |
| uint32_t c_hash; |
| |
| c_hash = isl_seq_get_hash(con + 1, len); |
| entry = isl_hash_table_find(ctx, table, c_hash, max_constraint_equal, |
| con + 1, 0); |
| if (!entry) |
| return 0; |
| c = entry->data; |
| if (c->count < n) |
| return 0; |
| return isl_int_eq(c->c->row[0][0], con[0]); |
| } |
| |
| /* Check for inequality constraints of a basic set without equalities |
| * such that the same or more stringent copies of the constraint appear |
| * in all of the basic sets. Such constraints are necessarily facet |
| * constraints of the convex hull. |
| * |
| * If the resulting basic set is by chance identical to one of |
| * the basic sets in "set", then we know that this basic set contains |
| * all other basic sets and is therefore the convex hull of set. |
| * In this case we set *is_hull to 1. |
| */ |
| static __isl_give isl_basic_set *common_constraints( |
| __isl_take isl_basic_set *hull, __isl_keep isl_set *set, int *is_hull) |
| { |
| int i, j, s, n; |
| int min_constraints; |
| int best; |
| struct max_constraint *constraints = NULL; |
| struct isl_hash_table *table = NULL; |
| unsigned total; |
| |
| *is_hull = 0; |
| |
| for (i = 0; i < set->n; ++i) |
| if (set->p[i]->n_eq == 0) |
| break; |
| if (i >= set->n) |
| return hull; |
| min_constraints = set->p[i]->n_ineq; |
| best = i; |
| for (i = best + 1; i < set->n; ++i) { |
| if (set->p[i]->n_eq != 0) |
| continue; |
| if (set->p[i]->n_ineq >= min_constraints) |
| continue; |
| min_constraints = set->p[i]->n_ineq; |
| best = i; |
| } |
| constraints = isl_calloc_array(hull->ctx, struct max_constraint, |
| min_constraints); |
| if (!constraints) |
| return hull; |
| table = isl_alloc_type(hull->ctx, struct isl_hash_table); |
| if (isl_hash_table_init(hull->ctx, table, min_constraints)) |
| goto error; |
| |
| total = isl_space_dim(set->dim, isl_dim_all); |
| for (i = 0; i < set->p[best]->n_ineq; ++i) { |
| constraints[i].c = isl_mat_sub_alloc6(hull->ctx, |
| set->p[best]->ineq + i, 0, 1, 0, 1 + total); |
| if (!constraints[i].c) |
| goto error; |
| constraints[i].ineq = 1; |
| } |
| for (i = 0; i < min_constraints; ++i) { |
| struct isl_hash_table_entry *entry; |
| uint32_t c_hash; |
| c_hash = isl_seq_get_hash(constraints[i].c->row[0] + 1, total); |
| entry = isl_hash_table_find(hull->ctx, table, c_hash, |
| max_constraint_equal, constraints[i].c->row[0] + 1, 1); |
| if (!entry) |
| goto error; |
| isl_assert(hull->ctx, !entry->data, goto error); |
| entry->data = &constraints[i]; |
| } |
| |
| n = 0; |
| for (s = 0; s < set->n; ++s) { |
| if (s == best) |
| continue; |
| |
| for (i = 0; i < set->p[s]->n_eq; ++i) { |
| isl_int *eq = set->p[s]->eq[i]; |
| for (j = 0; j < 2; ++j) { |
| isl_seq_neg(eq, eq, 1 + total); |
| update_constraint(hull->ctx, table, |
| eq, total, n, 0); |
| } |
| } |
| for (i = 0; i < set->p[s]->n_ineq; ++i) { |
| isl_int *ineq = set->p[s]->ineq[i]; |
| update_constraint(hull->ctx, table, ineq, total, n, |
| set->p[s]->n_eq == 0); |
| } |
| ++n; |
| } |
| |
| for (i = 0; i < min_constraints; ++i) { |
| if (constraints[i].count < n) |
| continue; |
| if (!constraints[i].ineq) |
| continue; |
| j = isl_basic_set_alloc_inequality(hull); |
| if (j < 0) |
| goto error; |
| isl_seq_cpy(hull->ineq[j], constraints[i].c->row[0], 1 + total); |
| } |
| |
| for (s = 0; s < set->n; ++s) { |
| if (set->p[s]->n_eq) |
| continue; |
| if (set->p[s]->n_ineq != hull->n_ineq) |
| continue; |
| for (i = 0; i < set->p[s]->n_ineq; ++i) { |
| isl_int *ineq = set->p[s]->ineq[i]; |
| if (!has_constraint(hull->ctx, table, ineq, total, n)) |
| break; |
| } |
| if (i == set->p[s]->n_ineq) |
| *is_hull = 1; |
| } |
| |
| isl_hash_table_clear(table); |
| for (i = 0; i < min_constraints; ++i) |
| isl_mat_free(constraints[i].c); |
| free(constraints); |
| free(table); |
| return hull; |
| error: |
| isl_hash_table_clear(table); |
| free(table); |
| if (constraints) |
| for (i = 0; i < min_constraints; ++i) |
| isl_mat_free(constraints[i].c); |
| free(constraints); |
| return hull; |
| } |
| |
| /* Create a template for the convex hull of "set" and fill it up |
| * obvious facet constraints, if any. If the result happens to |
| * be the convex hull of "set" then *is_hull is set to 1. |
| */ |
| static __isl_give isl_basic_set *proto_hull(__isl_keep isl_set *set, |
| int *is_hull) |
| { |
| struct isl_basic_set *hull; |
| unsigned n_ineq; |
| int i; |
| |
| n_ineq = 1; |
| for (i = 0; i < set->n; ++i) { |
| n_ineq += set->p[i]->n_eq; |
| n_ineq += set->p[i]->n_ineq; |
| } |
| hull = isl_basic_set_alloc_space(isl_space_copy(set->dim), 0, 0, n_ineq); |
| hull = isl_basic_set_set_rational(hull); |
| if (!hull) |
| return NULL; |
| return common_constraints(hull, set, is_hull); |
| } |
| |
| static __isl_give isl_basic_set *uset_convex_hull_wrap(__isl_take isl_set *set) |
| { |
| struct isl_basic_set *hull; |
| int is_hull; |
| |
| hull = proto_hull(set, &is_hull); |
| if (hull && !is_hull) { |
| if (hull->n_ineq == 0) |
| hull = initial_hull(hull, set); |
| hull = extend(hull, set); |
| } |
| isl_set_free(set); |
| |
| return hull; |
| } |
| |
| /* Compute the convex hull of a set without any parameters or |
| * integer divisions. Depending on whether the set is bounded, |
| * we pass control to the wrapping based convex hull or |
| * the Fourier-Motzkin elimination based convex hull. |
| * We also handle a few special cases before checking the boundedness. |
| */ |
| static __isl_give isl_basic_set *uset_convex_hull(__isl_take isl_set *set) |
| { |
| isl_bool bounded; |
| struct isl_basic_set *convex_hull = NULL; |
| struct isl_basic_set *lin; |
| |
| if (isl_set_n_dim(set) == 0) |
| return convex_hull_0d(set); |
| |
| set = isl_set_coalesce(set); |
| set = isl_set_set_rational(set); |
| |
| if (!set) |
| return NULL; |
| if (set->n == 1) { |
| convex_hull = isl_basic_set_copy(set->p[0]); |
| isl_set_free(set); |
| return convex_hull; |
| } |
| if (isl_set_n_dim(set) == 1) |
| return convex_hull_1d(set); |
| |
| bounded = isl_set_is_bounded(set); |
| if (bounded < 0) |
| goto error; |
| if (bounded && set->ctx->opt->convex == ISL_CONVEX_HULL_WRAP) |
| return uset_convex_hull_wrap(set); |
| |
| lin = isl_set_combined_lineality_space(isl_set_copy(set)); |
| if (!lin) |
| goto error; |
| if (isl_basic_set_plain_is_universe(lin)) { |
| isl_set_free(set); |
| return lin; |
| } |
| if (lin->n_eq < isl_basic_set_total_dim(lin)) |
| return modulo_lineality(set, lin); |
| isl_basic_set_free(lin); |
| |
| return uset_convex_hull_unbounded(set); |
| error: |
| isl_set_free(set); |
| isl_basic_set_free(convex_hull); |
| return NULL; |
| } |
| |
| /* This is the core procedure, where "set" is a "pure" set, i.e., |
| * without parameters or divs and where the convex hull of set is |
| * known to be full-dimensional. |
| */ |
| static __isl_give isl_basic_set *uset_convex_hull_wrap_bounded( |
| __isl_take isl_set *set) |
| { |
| struct isl_basic_set *convex_hull = NULL; |
| |
| if (!set) |
| goto error; |
| |
| if (isl_set_n_dim(set) == 0) { |
| convex_hull = isl_basic_set_universe(isl_space_copy(set->dim)); |
| isl_set_free(set); |
| convex_hull = isl_basic_set_set_rational(convex_hull); |
| return convex_hull; |
| } |
| |
| set = isl_set_set_rational(set); |
| set = isl_set_coalesce(set); |
| if (!set) |
| goto error; |
| if (set->n == 1) { |
| convex_hull = isl_basic_set_copy(set->p[0]); |
| isl_set_free(set); |
| convex_hull = isl_basic_map_remove_redundancies(convex_hull); |
| return convex_hull; |
| } |
| if (isl_set_n_dim(set) == 1) |
| return convex_hull_1d(set); |
| |
| return uset_convex_hull_wrap(set); |
| error: |
| isl_set_free(set); |
| return NULL; |
| } |
| |
| /* Compute the convex hull of set "set" with affine hull "affine_hull", |
| * We first remove the equalities (transforming the set), compute the |
| * convex hull of the transformed set and then add the equalities back |
| * (after performing the inverse transformation. |
| */ |
| static __isl_give isl_basic_set *modulo_affine_hull( |
| __isl_take isl_set *set, __isl_take isl_basic_set *affine_hull) |
| { |
| struct isl_mat *T; |
| struct isl_mat *T2; |
| struct isl_basic_set *dummy; |
| struct isl_basic_set *convex_hull; |
| |
| dummy = isl_basic_set_remove_equalities( |
| isl_basic_set_copy(affine_hull), &T, &T2); |
| if (!dummy) |
| goto error; |
| isl_basic_set_free(dummy); |
| set = isl_set_preimage(set, T); |
| convex_hull = uset_convex_hull(set); |
| convex_hull = isl_basic_set_preimage(convex_hull, T2); |
| convex_hull = isl_basic_set_intersect(convex_hull, affine_hull); |
| return convex_hull; |
| error: |
| isl_mat_free(T); |
| isl_mat_free(T2); |
| isl_basic_set_free(affine_hull); |
| isl_set_free(set); |
| return NULL; |
| } |
| |
| /* Return an empty basic map living in the same space as "map". |
| */ |
| static __isl_give isl_basic_map *replace_map_by_empty_basic_map( |
| __isl_take isl_map *map) |
| { |
| isl_space *space; |
| |
| space = isl_map_get_space(map); |
| isl_map_free(map); |
| return isl_basic_map_empty(space); |
| } |
| |
| /* Compute the convex hull of a map. |
| * |
| * The implementation was inspired by "Extended Convex Hull" by Fukuda et al., |
| * specifically, the wrapping of facets to obtain new facets. |
| */ |
| __isl_give isl_basic_map *isl_map_convex_hull(__isl_take isl_map *map) |
| { |
| struct isl_basic_set *bset; |
| struct isl_basic_map *model = NULL; |
| struct isl_basic_set *affine_hull = NULL; |
| struct isl_basic_map *convex_hull = NULL; |
| struct isl_set *set = NULL; |
| |
| map = isl_map_detect_equalities(map); |
| map = isl_map_align_divs_internal(map); |
| if (!map) |
| goto error; |
| |
| if (map->n == 0) |
| return replace_map_by_empty_basic_map(map); |
| |
| model = isl_basic_map_copy(map->p[0]); |
| set = isl_map_underlying_set(map); |
| if (!set) |
| goto error; |
| |
| affine_hull = isl_set_affine_hull(isl_set_copy(set)); |
| if (!affine_hull) |
| goto error; |
| if (affine_hull->n_eq != 0) |
| bset = modulo_affine_hull(set, affine_hull); |
| else { |
| isl_basic_set_free(affine_hull); |
| bset = uset_convex_hull(set); |
| } |
| |
| convex_hull = isl_basic_map_overlying_set(bset, model); |
| if (!convex_hull) |
| return NULL; |
| |
| ISL_F_SET(convex_hull, ISL_BASIC_MAP_NO_IMPLICIT); |
| ISL_F_SET(convex_hull, ISL_BASIC_MAP_ALL_EQUALITIES); |
| ISL_F_CLR(convex_hull, ISL_BASIC_MAP_RATIONAL); |
| return convex_hull; |
| error: |
| isl_set_free(set); |
| isl_basic_map_free(model); |
| return NULL; |
| } |
| |
| struct isl_basic_set *isl_set_convex_hull(struct isl_set *set) |
| { |
| return bset_from_bmap(isl_map_convex_hull(set_to_map(set))); |
| } |
| |
| __isl_give isl_basic_map *isl_map_polyhedral_hull(__isl_take isl_map *map) |
| { |
| isl_basic_map *hull; |
| |
| hull = isl_map_convex_hull(map); |
| return isl_basic_map_remove_divs(hull); |
| } |
| |
| __isl_give isl_basic_set *isl_set_polyhedral_hull(__isl_take isl_set *set) |
| { |
| return bset_from_bmap(isl_map_polyhedral_hull(set_to_map(set))); |
| } |
| |
| struct sh_data_entry { |
| struct isl_hash_table *table; |
| struct isl_tab *tab; |
| }; |
| |
| /* Holds the data needed during the simple hull computation. |
| * In particular, |
| * n the number of basic sets in the original set |
| * hull_table a hash table of already computed constraints |
| * in the simple hull |
| * p for each basic set, |
| * table a hash table of the constraints |
| * tab the tableau corresponding to the basic set |
| */ |
| struct sh_data { |
| struct isl_ctx *ctx; |
| unsigned n; |
| struct isl_hash_table *hull_table; |
| struct sh_data_entry p[1]; |
| }; |
| |
| static void sh_data_free(struct sh_data *data) |
| { |
| int i; |
| |
| if (!data) |
| return; |
| isl_hash_table_free(data->ctx, data->hull_table); |
| for (i = 0; i < data->n; ++i) { |
| isl_hash_table_free(data->ctx, data->p[i].table); |
| isl_tab_free(data->p[i].tab); |
| } |
| free(data); |
| } |
| |
| struct ineq_cmp_data { |
| unsigned len; |
| isl_int *p; |
| }; |
| |
| static int has_ineq(const void *entry, const void *val) |
| { |
| isl_int *row = (isl_int *)entry; |
| struct ineq_cmp_data *v = (struct ineq_cmp_data *)val; |
| |
| return isl_seq_eq(row + 1, v->p + 1, v->len) || |
| isl_seq_is_neg(row + 1, v->p + 1, v->len); |
| } |
| |
| static int hash_ineq(struct isl_ctx *ctx, struct isl_hash_table *table, |
| isl_int *ineq, unsigned len) |
| { |
| uint32_t c_hash; |
| struct ineq_cmp_data v; |
| struct isl_hash_table_entry *entry; |
| |
| v.len = len; |
| v.p = ineq; |
| c_hash = isl_seq_get_hash(ineq + 1, len); |
| entry = isl_hash_table_find(ctx, table, c_hash, has_ineq, &v, 1); |
| if (!entry) |
| return - 1; |
| entry->data = ineq; |
| return 0; |
| } |
| |
| /* Fill hash table "table" with the constraints of "bset". |
| * Equalities are added as two inequalities. |
| * The value in the hash table is a pointer to the (in)equality of "bset". |
| */ |
| static int hash_basic_set(struct isl_hash_table *table, |
| __isl_keep isl_basic_set *bset) |
| { |
| int i, j; |
| unsigned dim = isl_basic_set_total_dim(bset); |
| |
| for (i = 0; i < bset->n_eq; ++i) { |
| for (j = 0; j < 2; ++j) { |
| isl_seq_neg(bset->eq[i], bset->eq[i], 1 + dim); |
| if (hash_ineq(bset->ctx, table, bset->eq[i], dim) < 0) |
| return -1; |
| } |
| } |
| for (i = 0; i < bset->n_ineq; ++i) { |
| if (hash_ineq(bset->ctx, table, bset->ineq[i], dim) < 0) |
| return -1; |
| } |
| return 0; |
| } |
| |
| static struct sh_data *sh_data_alloc(__isl_keep isl_set *set, unsigned n_ineq) |
| { |
| struct sh_data *data; |
| int i; |
| |
| data = isl_calloc(set->ctx, struct sh_data, |
| sizeof(struct sh_data) + |
| (set->n - 1) * sizeof(struct sh_data_entry)); |
| if (!data) |
| return NULL; |
| data->ctx = set->ctx; |
| data->n = set->n; |
| data->hull_table = isl_hash_table_alloc(set->ctx, n_ineq); |
| if (!data->hull_table) |
| goto error; |
| for (i = 0; i < set->n; ++i) { |
| data->p[i].table = isl_hash_table_alloc(set->ctx, |
| 2 * set->p[i]->n_eq + set->p[i]->n_ineq); |
| if (!data->p[i].table) |
| goto error; |
| if (hash_basic_set(data->p[i].table, set->p[i]) < 0) |
| goto error; |
| } |
| return data; |
| error: |
| sh_data_free(data); |
| return NULL; |
| } |
| |
| /* Check if inequality "ineq" is a bound for basic set "j" or if |
| * it can be relaxed (by increasing the constant term) to become |
| * a bound for that basic set. In the latter case, the constant |
| * term is updated. |
| * Relaxation of the constant term is only allowed if "shift" is set. |
| * |
| * Return 1 if "ineq" is a bound |
| * 0 if "ineq" may attain arbitrarily small values on basic set "j" |
| * -1 if some error occurred |
| */ |
| static int is_bound(struct sh_data *data, __isl_keep isl_set *set, int j, |
| isl_int *ineq, int shift) |
| { |
| enum isl_lp_result res; |
| isl_int opt; |
| |
| if (!data->p[j].tab) { |
| data->p[j].tab = isl_tab_from_basic_set(set->p[j], 0); |
| if (!data->p[j].tab) |
| return -1; |
| } |
| |
| isl_int_init(opt); |
| |
| res = isl_tab_min(data->p[j].tab, ineq, data->ctx->one, |
| &opt, NULL, 0); |
| if (res == isl_lp_ok && isl_int_is_neg(opt)) { |
| if (shift) |
| isl_int_sub(ineq[0], ineq[0], opt); |
| else |
| res = isl_lp_unbounded; |
| } |
| |
| isl_int_clear(opt); |
| |
| return (res == isl_lp_ok || res == isl_lp_empty) ? 1 : |
| res == isl_lp_unbounded ? 0 : -1; |
| } |
| |
| /* Set the constant term of "ineq" to the maximum of those of the constraints |
| * in the basic sets of "set" following "i" that are parallel to "ineq". |
| * That is, if any of the basic sets of "set" following "i" have a more |
| * relaxed copy of "ineq", then replace "ineq" by the most relaxed copy. |
| * "c_hash" is the hash value of the linear part of "ineq". |
| * "v" has been set up for use by has_ineq. |
| * |
| * Note that the two inequality constraints corresponding to an equality are |
| * represented by the same inequality constraint in data->p[j].table |
| * (but with different hash values). This means the constraint (or at |
| * least its constant term) may need to be temporarily negated to get |
| * the actually hashed constraint. |
| */ |
| static void set_max_constant_term(struct sh_data *data, __isl_keep isl_set *set, |
| int i, isl_int *ineq, uint32_t c_hash, struct ineq_cmp_data *v) |
| { |
| int j; |
| isl_ctx *ctx; |
| struct isl_hash_table_entry *entry; |
| |
| ctx = isl_set_get_ctx(set); |
| for (j = i + 1; j < set->n; ++j) { |
| int neg; |
| isl_int *ineq_j; |
| |
| entry = isl_hash_table_find(ctx, data->p[j].table, |
| c_hash, &has_ineq, v, 0); |
| if (!entry) |
| continue; |
| |
| ineq_j = entry->data; |
| neg = isl_seq_is_neg(ineq_j + 1, ineq + 1, v->len); |
| if (neg) |
| isl_int_neg(ineq_j[0], ineq_j[0]); |
| if (isl_int_gt(ineq_j[0], ineq[0])) |
| isl_int_set(ineq[0], ineq_j[0]); |
| if (neg) |
| isl_int_neg(ineq_j[0], ineq_j[0]); |
| } |
| } |
| |
| /* Check if inequality "ineq" from basic set "i" is or can be relaxed to |
| * become a bound on the whole set. If so, add the (relaxed) inequality |
| * to "hull". Relaxation is only allowed if "shift" is set. |
| * |
| * We first check if "hull" already contains a translate of the inequality. |
| * If so, we are done. |
| * Then, we check if any of the previous basic sets contains a translate |
| * of the inequality. If so, then we have already considered this |
| * inequality and we are done. |
| * Otherwise, for each basic set other than "i", we check if the inequality |
| * is a bound on the basic set, but first replace the constant term |
| * by the maximal value of any translate of the inequality in any |
| * of the following basic sets. |
| * For previous basic sets, we know that they do not contain a translate |
| * of the inequality, so we directly call is_bound. |
| * For following basic sets, we first check if a translate of the |
| * inequality appears in its description. If so, the constant term |
| * of the inequality has already been updated with respect to this |
| * translate and the inequality is therefore known to be a bound |
| * of this basic set. |
| */ |
| static __isl_give isl_basic_set *add_bound(__isl_take isl_basic_set *hull, |
| struct sh_data *data, __isl_keep isl_set *set, int i, isl_int *ineq, |
| int shift) |
| { |
| uint32_t c_hash; |
| struct ineq_cmp_data v; |
| struct isl_hash_table_entry *entry; |
| int j, k; |
| |
| if (!hull) |
| return NULL; |
| |
| v.len = isl_basic_set_total_dim(hull); |
| v.p = ineq; |
| c_hash = isl_seq_get_hash(ineq + 1, v.len); |
| |
| entry = isl_hash_table_find(hull->ctx, data->hull_table, c_hash, |
| has_ineq, &v, 0); |
| if (entry) |
| return hull; |
| |
| for (j = 0; j < i; ++j) { |
| entry = isl_hash_table_find(hull->ctx, data->p[j].table, |
| c_hash, has_ineq, &v, 0); |
| if (entry) |
| break; |
| } |
| if (j < i) |
| return hull; |
| |
| k = isl_basic_set_alloc_inequality(hull); |
| if (k < 0) |
| goto error; |
| isl_seq_cpy(hull->ineq[k], ineq, 1 + v.len); |
| |
| set_max_constant_term(data, set, i, hull->ineq[k], c_hash, &v); |
| for (j = 0; j < i; ++j) { |
| int bound; |
| bound = is_bound(data, set, j, hull->ineq[k], shift); |
| if (bound < 0) |
| goto error; |
| if (!bound) |
| break; |
| } |
| if (j < i) { |
| isl_basic_set_free_inequality(hull, 1); |
| return hull; |
| } |
| |
| for (j = i + 1; j < set->n; ++j) { |
| int bound; |
| entry = isl_hash_table_find(hull->ctx, data->p[j].table, |
| c_hash, has_ineq, &v, 0); |
| if (entry) |
| continue; |
| bound = is_bound(data, set, j, hull->ineq[k], shift); |
| if (bound < 0) |
| goto error; |
| if (!bound) |
| break; |
| } |
| if (j < set->n) { |
| isl_basic_set_free_inequality(hull, 1); |
| return hull; |
| } |
| |
| entry = isl_hash_table_find(hull->ctx, data->hull_table, c_hash, |
| has_ineq, &v, 1); |
| if (!entry) |
| goto error; |
| entry->data = hull->ineq[k]; |
| |
| return hull; |
| error: |
| isl_basic_set_free(hull); |
| return NULL; |
| } |
| |
| /* Check if any inequality from basic set "i" is or can be relaxed to |
| * become a bound on the whole set. If so, add the (relaxed) inequality |
| * to "hull". Relaxation is only allowed if "shift" is set. |
| */ |
| static __isl_give isl_basic_set *add_bounds(__isl_take isl_basic_set *bset, |
| struct sh_data *data, __isl_keep isl_set *set, int i, int shift) |
| { |
| int j, k; |
| unsigned dim = isl_basic_set_total_dim(bset); |
| |
| for (j = 0; j < set->p[i]->n_eq; ++j) { |
| for (k = 0; k < 2; ++k) { |
| isl_seq_neg(set->p[i]->eq[j], set->p[i]->eq[j], 1+dim); |
| bset = add_bound(bset, data, set, i, set->p[i]->eq[j], |
| shift); |
| } |
| } |
| for (j = 0; j < set->p[i]->n_ineq; ++j) |
| bset = add_bound(bset, data, set, i, set->p[i]->ineq[j], shift); |
| return bset; |
| } |
| |
| /* Compute a superset of the convex hull of set that is described |
| * by only (translates of) the constraints in the constituents of set. |
| * Translation is only allowed if "shift" is set. |
| */ |
| static __isl_give isl_basic_set *uset_simple_hull(__isl_take isl_set *set, |
| int shift) |
| { |
| struct sh_data *data = NULL; |
| struct isl_basic_set *hull = NULL; |
| unsigned n_ineq; |
| int i; |
| |
| if (!set) |
| return NULL; |
| |
| n_ineq = 0; |
| for (i = 0; i < set->n; ++i) { |
| if (!set->p[i]) |
| goto error; |
| n_ineq += 2 * set->p[i]->n_eq + set->p[i]->n_ineq; |
| } |
| |
| hull = isl_basic_set_alloc_space(isl_space_copy(set->dim), 0, 0, n_ineq); |
| if (!hull) |
| goto error; |
| |
| data = sh_data_alloc(set, n_ineq); |
| if (!data) |
| goto error; |
| |
| for (i = 0; i < set->n; ++i) |
| hull = add_bounds(hull, data, set, i, shift); |
| |
| sh_data_free(data); |
| isl_set_free(set); |
| |
| return hull; |
| error: |
| sh_data_free(data); |
| isl_basic_set_free(hull); |
| isl_set_free(set); |
| return NULL; |
| } |
| |
| /* Compute a superset of the convex hull of map that is described |
| * by only (translates of) the constraints in the constituents of map. |
| * Handle trivial cases where map is NULL or contains at most one disjunct. |
| */ |
| static __isl_give isl_basic_map *map_simple_hull_trivial( |
| __isl_take isl_map *map) |
| { |
| isl_basic_map *hull; |
| |
| if (!map) |
| return NULL; |
| if (map->n == 0) |
| return replace_map_by_empty_basic_map(map); |
| |
| hull = isl_basic_map_copy(map->p[0]); |
| isl_map_free(map); |
| return hull; |
| } |
| |
| /* Return a copy of the simple hull cached inside "map". |
| * "shift" determines whether to return the cached unshifted or shifted |
| * simple hull. |
| */ |
| static __isl_give isl_basic_map *cached_simple_hull(__isl_take isl_map *map, |
| int shift) |
| { |
| isl_basic_map *hull; |
| |
| hull = isl_basic_map_copy(map->cached_simple_hull[shift]); |
| isl_map_free(map); |
| |
| return hull; |
| } |
| |
| /* Compute a superset of the convex hull of map that is described |
| * by only (translates of) the constraints in the constituents of map. |
| * Translation is only allowed if "shift" is set. |
| * |
| * The constraints are sorted while removing redundant constraints |
| * in order to indicate a preference of which constraints should |
| * be preserved. In particular, pairs of constraints that are |
| * sorted together are preferred to either both be preserved |
| * or both be removed. The sorting is performed inside |
| * isl_basic_map_remove_redundancies. |
| * |
| * The result of the computation is stored in map->cached_simple_hull[shift] |
| * such that it can be reused in subsequent calls. The cache is cleared |
| * whenever the map is modified (in isl_map_cow). |
| * Note that the results need to be stored in the input map for there |
| * to be any chance that they may get reused. In particular, they |
| * are stored in a copy of the input map that is saved before |
| * the integer division alignment. |
| */ |
| static __isl_give isl_basic_map *map_simple_hull(__isl_take isl_map *map, |
| int shift) |
| { |
| struct isl_set *set = NULL; |
| struct isl_basic_map *model = NULL; |
| struct isl_basic_map *hull; |
| struct isl_basic_map *affine_hull; |
| struct isl_basic_set *bset = NULL; |
| isl_map *input; |
| |
| if (!map || map->n <= 1) |
| return map_simple_hull_trivial(map); |
| |
| if (map->cached_simple_hull[shift]) |
| return cached_simple_hull(map, shift); |
| |
| map = isl_map_detect_equalities(map); |
| if (!map || map->n <= 1) |
| return map_simple_hull_trivial(map); |
| affine_hull = isl_map_affine_hull(isl_map_copy(map)); |
| input = isl_map_copy(map); |
| map = isl_map_align_divs_internal(map); |
| model = map ? isl_basic_map_copy(map->p[0]) : NULL; |
| |
| set = isl_map_underlying_set(map); |
| |
| bset = uset_simple_hull(set, shift); |
| |
| hull = isl_basic_map_overlying_set(bset, model); |
| |
| hull = isl_basic_map_intersect(hull, affine_hull); |
| hull = isl_basic_map_remove_redundancies(hull); |
| |
| if (hull) { |
| ISL_F_SET(hull, ISL_BASIC_MAP_NO_IMPLICIT); |
| ISL_F_SET(hull, ISL_BASIC_MAP_ALL_EQUALITIES); |
| } |
| |
| hull = isl_basic_map_finalize(hull); |
| if (input) |
| input->cached_simple_hull[shift] = isl_basic_map_copy(hull); |
| isl_map_free(input); |
| |
| return hull; |
| } |
| |
| /* Compute a superset of the convex hull of map that is described |
| * by only translates of the constraints in the constituents of map. |
| */ |
| __isl_give isl_basic_map *isl_map_simple_hull(__isl_take isl_map *map) |
| { |
| return map_simple_hull(map, 1); |
| } |
| |
| struct isl_basic_set *isl_set_simple_hull(struct isl_set *set) |
| { |
| return bset_from_bmap(isl_map_simple_hull(set_to_map(set))); |
| } |
| |
| /* Compute a superset of the convex hull of map that is described |
| * by only the constraints in the constituents of map. |
| */ |
| __isl_give isl_basic_map *isl_map_unshifted_simple_hull( |
| __isl_take isl_map *map) |
| { |
| return map_simple_hull(map, 0); |
| } |
| |
| __isl_give isl_basic_set *isl_set_unshifted_simple_hull( |
| __isl_take isl_set *set) |
| { |
| return isl_map_unshifted_simple_hull(set); |
| } |
| |
| /* Drop all inequalities from "bmap1" that do not also appear in "bmap2". |
| * A constraint that appears with different constant terms |
| * in "bmap1" and "bmap2" is also kept, with the least restrictive |
| * (i.e., greatest) constant term. |
| * "bmap1" and "bmap2" are assumed to have the same (known) |
| * integer divisions. |
| * The constraints of both "bmap1" and "bmap2" are assumed |
| * to have been sorted using isl_basic_map_sort_constraints. |
| * |
| * Run through the inequality constraints of "bmap1" and "bmap2" |
| * in sorted order. |
| * Each constraint of "bmap1" without a matching constraint in "bmap2" |
| * is removed. |
| * If a match is found, the constraint is kept. If needed, the constant |
| * term of the constraint is adjusted. |
| */ |
| static __isl_give isl_basic_map *select_shared_inequalities( |
| __isl_take isl_basic_map *bmap1, __isl_keep isl_basic_map *bmap2) |
| { |
| int i1, i2; |
| |
| bmap1 = isl_basic_map_cow(bmap1); |
| if (!bmap1 || !bmap2) |
| return isl_basic_map_free(bmap1); |
| |
| i1 = bmap1->n_ineq - 1; |
| i2 = bmap2->n_ineq - 1; |
| while (bmap1 && i1 >= 0 && i2 >= 0) { |
| int cmp; |
| |
| cmp = isl_basic_map_constraint_cmp(bmap1, bmap1->ineq[i1], |
| bmap2->ineq[i2]); |
| if (cmp < 0) { |
| --i2; |
| continue; |
| } |
| if (cmp > 0) { |
| if (isl_basic_map_drop_inequality(bmap1, i1) < 0) |
| bmap1 = isl_basic_map_free(bmap1); |
| --i1; |
| continue; |
| } |
| if (isl_int_lt(bmap1->ineq[i1][0], bmap2->ineq[i2][0])) |
| isl_int_set(bmap1->ineq[i1][0], bmap2->ineq[i2][0]); |
| --i1; |
| --i2; |
| } |
| for (; i1 >= 0; --i1) |
| if (isl_basic_map_drop_inequality(bmap1, i1) < 0) |
| bmap1 = isl_basic_map_free(bmap1); |
| |
| return bmap1; |
| } |
| |
| /* Drop all equalities from "bmap1" that do not also appear in "bmap2". |
| * "bmap1" and "bmap2" are assumed to have the same (known) |
| * integer divisions. |
| * |
| * Run through the equality constraints of "bmap1" and "bmap2". |
| * Each constraint of "bmap1" without a matching constraint in "bmap2" |
| * is removed. |
| */ |
| static __isl_give isl_basic_map *select_shared_equalities( |
| __isl_take isl_basic_map *bmap1, __isl_keep isl_basic_map *bmap2) |
| { |
| int i1, i2; |
| unsigned total; |
| |
| bmap1 = isl_basic_map_cow(bmap1); |
| if (!bmap1 || !bmap2) |
| return isl_basic_map_free(bmap1); |
| |
| total = isl_basic_map_total_dim(bmap1); |
| |
| i1 = bmap1->n_eq - 1; |
| i2 = bmap2->n_eq - 1; |
| while (bmap1 && i1 >= 0 && i2 >= 0) { |
| int last1, last2; |
| |
| last1 = isl_seq_last_non_zero(bmap1->eq[i1] + 1, total); |
| last2 = isl_seq_last_non_zero(bmap2->eq[i2] + 1, total); |
| if (last1 > last2) { |
| --i2; |
| continue; |
| } |
| if (last1 < last2) { |
| if (isl_basic_map_drop_equality(bmap1, i1) < 0) |
| bmap1 = isl_basic_map_free(bmap1); |
| --i1; |
| continue; |
| } |
| if (!isl_seq_eq(bmap1->eq[i1], bmap2->eq[i2], 1 + total)) { |
| if (isl_basic_map_drop_equality(bmap1, i1) < 0) |
| bmap1 = isl_basic_map_free(bmap1); |
| } |
| --i1; |
| --i2; |
| } |
| for (; i1 >= 0; --i1) |
| if (isl_basic_map_drop_equality(bmap1, i1) < 0) |
| bmap1 = isl_basic_map_free(bmap1); |
| |
| return bmap1; |
| } |
| |
| /* Compute a superset of "bmap1" and "bmap2" that is described |
| * by only the constraints that appear in both "bmap1" and "bmap2". |
| * |
| * First drop constraints that involve unknown integer divisions |
| * since it is not trivial to check whether two such integer divisions |
| * in different basic maps are the same. |
| * Then align the remaining (known) divs and sort the constraints. |
| * Finally drop all inequalities and equalities from "bmap1" that |
| * do not also appear in "bmap2". |
| */ |
| __isl_give isl_basic_map *isl_basic_map_plain_unshifted_simple_hull( |
| __isl_take isl_basic_map *bmap1, __isl_take isl_basic_map *bmap2) |
| { |
| bmap1 = isl_basic_map_drop_constraint_involving_unknown_divs(bmap1); |
| bmap2 = isl_basic_map_drop_constraint_involving_unknown_divs(bmap2); |
| bmap2 = isl_basic_map_align_divs(bmap2, bmap1); |
| bmap1 = isl_basic_map_align_divs(bmap1, bmap2); |
| bmap1 = isl_basic_map_gauss(bmap1, NULL); |
| bmap2 = isl_basic_map_gauss(bmap2, NULL); |
| bmap1 = isl_basic_map_sort_constraints(bmap1); |
| bmap2 = isl_basic_map_sort_constraints(bmap2); |
| |
| bmap1 = select_shared_inequalities(bmap1, bmap2); |
| bmap1 = select_shared_equalities(bmap1, bmap2); |
| |
| isl_basic_map_free(bmap2); |
| bmap1 = isl_basic_map_finalize(bmap1); |
| return bmap1; |
| } |
| |
| /* Compute a superset of the convex hull of "map" that is described |
| * by only the constraints in the constituents of "map". |
| * In particular, the result is composed of constraints that appear |
| * in each of the basic maps of "map" |
| * |
| * Constraints that involve unknown integer divisions are dropped |
| * since it is not trivial to check whether two such integer divisions |
| * in different basic maps are the same. |
| * |
| * The hull is initialized from the first basic map and then |
| * updated with respect to the other basic maps in turn. |
| */ |
| __isl_give isl_basic_map *isl_map_plain_unshifted_simple_hull( |
| __isl_take isl_map *map) |
| { |
| int i; |
| isl_basic_map *hull; |
| |
| if (!map) |
| return NULL; |
| if (map->n <= 1) |
| return map_simple_hull_trivial(map); |
| map = isl_map_drop_constraint_involving_unknown_divs(map); |
| hull = isl_basic_map_copy(map->p[0]); |
| for (i = 1; i < map->n; ++i) { |
| isl_basic_map *bmap_i; |
| |
| bmap_i = isl_basic_map_copy(map->p[i]); |
| hull = isl_basic_map_plain_unshifted_simple_hull(hull, bmap_i); |
| } |
| |
| isl_map_free(map); |
| return hull; |
| } |
| |
| /* Compute a superset of the convex hull of "set" that is described |
| * by only the constraints in the constituents of "set". |
| * In particular, the result is composed of constraints that appear |
| * in each of the basic sets of "set" |
| */ |
| __isl_give isl_basic_set *isl_set_plain_unshifted_simple_hull( |
| __isl_take isl_set *set) |
| { |
| return isl_map_plain_unshifted_simple_hull(set); |
| } |
| |
| /* Check if "ineq" is a bound on "set" and, if so, add it to "hull". |
| * |
| * For each basic set in "set", we first check if the basic set |
| * contains a translate of "ineq". If this translate is more relaxed, |
| * then we assume that "ineq" is not a bound on this basic set. |
| * Otherwise, we know that it is a bound. |
| * If the basic set does not contain a translate of "ineq", then |
| * we call is_bound to perform the test. |
| */ |
| static __isl_give isl_basic_set *add_bound_from_constraint( |
| __isl_take isl_basic_set *hull, struct sh_data *data, |
| __isl_keep isl_set *set, isl_int *ineq) |
| { |
| int i, k; |
| isl_ctx *ctx; |
| uint32_t c_hash; |
| struct ineq_cmp_data v; |
| |
| if (!hull || !set) |
| return isl_basic_set_free(hull); |
| |
| v.len = isl_basic_set_total_dim(hull); |
| v.p = ineq; |
| c_hash = isl_seq_get_hash(ineq + 1, v.len); |
| |
| ctx = isl_basic_set_get_ctx(hull); |
| for (i = 0; i < set->n; ++i) { |
| int bound; |
| struct isl_hash_table_entry *entry; |
| |
| entry = isl_hash_table_find(ctx, data->p[i].table, |
| c_hash, &has_ineq, &v, 0); |
| if (entry) { |
| isl_int *ineq_i = entry->data; |
| int neg, more_relaxed; |
| |
| neg = isl_seq_is_neg(ineq_i + 1, ineq + 1, v.len); |
| if (neg) |
| isl_int_neg(ineq_i[0], ineq_i[0]); |
| more_relaxed = isl_int_gt(ineq_i[0], ineq[0]); |
| if (neg) |
| isl_int_neg(ineq_i[0], ineq_i[0]); |
| if (more_relaxed) |
| break; |
| else |
| continue; |
| } |
| bound = is_bound(data, set, i, ineq, 0); |
| if (bound < 0) |
| return isl_basic_set_free(hull); |
| if (!bound) |
| break; |
| } |
| if (i < set->n) |
| return hull; |
| |
| k = isl_basic_set_alloc_inequality(hull); |
| if (k < 0) |
| return isl_basic_set_free(hull); |
| isl_seq_cpy(hull->ineq[k], ineq, 1 + v.len); |
| |
| return hull; |
| } |
| |
| /* Compute a superset of the convex hull of "set" that is described |
| * by only some of the "n_ineq" constraints in the list "ineq", where "set" |
| * has no parameters or integer divisions. |
| * |
| * The inequalities in "ineq" are assumed to have been sorted such |
| * that constraints with the same linear part appear together and |
| * that among constraints with the same linear part, those with |
| * smaller constant term appear first. |
| * |
| * We reuse the same data structure that is used by uset_simple_hull, |
| * but we do not need the hull table since we will not consider the |
| * same constraint more than once. We therefore allocate it with zero size. |
| * |
| * We run through the constraints and try to add them one by one, |
| * skipping identical constraints. If we have added a constraint and |
| * the next constraint is a more relaxed translate, then we skip this |
| * next constraint as well. |
| */ |
| static __isl_give isl_basic_set *uset_unshifted_simple_hull_from_constraints( |
| __isl_take isl_set *set, int n_ineq, isl_int **ineq) |
| { |
| int i; |
| int last_added = 0; |
| struct sh_data *data = NULL; |
| isl_basic_set *hull = NULL; |
| unsigned dim; |
| |
| hull = isl_basic_set_alloc_space(isl_set_get_space(set), 0, 0, n_ineq); |
| if (!hull) |
| goto error; |
| |
| data = sh_data_alloc(set, 0); |
| if (!data) |
| goto error; |
| |
| dim = isl_set_dim(set, isl_dim_set); |
| for (i = 0; i < n_ineq; ++i) { |
| int hull_n_ineq = hull->n_ineq; |
| int parallel; |
| |
| parallel = i > 0 && isl_seq_eq(ineq[i - 1] + 1, ineq[i] + 1, |
| dim); |
| if (parallel && |
| (last_added || isl_int_eq(ineq[i - 1][0], ineq[i][0]))) |
| continue; |
| hull = add_bound_from_constraint(hull, data, set, ineq[i]); |
| if (!hull) |
| goto error; |
| last_added = hull->n_ineq > hull_n_ineq; |
| } |
| |
| sh_data_free(data); |
| isl_set_free(set); |
| return hull; |
| error: |
| sh_data_free(data); |
| isl_set_free(set); |
| isl_basic_set_free(hull); |
| return NULL; |
| } |
| |
| /* Collect pointers to all the inequalities in the elements of "list" |
| * in "ineq". For equalities, store both a pointer to the equality and |
| * a pointer to its opposite, which is first copied to "mat". |
| * "ineq" and "mat" are assumed to have been preallocated to the right size |
| * (the number of inequalities + 2 times the number of equalites and |
| * the number of equalities, respectively). |
| */ |
| static __isl_give isl_mat *collect_inequalities(__isl_take isl_mat *mat, |
| __isl_keep isl_basic_set_list *list, isl_int **ineq) |
| { |
| int i, j, n, n_eq, n_ineq; |
| |
| if (!mat) |
| return NULL; |
| |
| n_eq = 0; |
| n_ineq = 0; |
| n = isl_basic_set_list_n_basic_set(list); |
| for (i = 0; i < n; ++i) { |
| isl_basic_set *bset; |
| bset = isl_basic_set_list_get_basic_set(list, i); |
| if (!bset) |
| return isl_mat_free(mat); |
| for (j = 0; j < bset->n_eq; ++j) { |
| ineq[n_ineq++] = mat->row[n_eq]; |
| ineq[n_ineq++] = bset->eq[j]; |
| isl_seq_neg(mat->row[n_eq++], bset->eq[j], mat->n_col); |
| } |
| for (j = 0; j < bset->n_ineq; ++j) |
| ineq[n_ineq++] = bset->ineq[j]; |
| isl_basic_set_free(bset); |
| } |
| |
| return mat; |
| } |
| |
| /* Comparison routine for use as an isl_sort callback. |
| * |
| * Constraints with the same linear part are sorted together and |
| * among constraints with the same linear part, those with smaller |
| * constant term are sorted first. |
| */ |
| static int cmp_ineq(const void *a, const void *b, void *arg) |
| { |
| unsigned dim = *(unsigned *) arg; |
| isl_int * const *ineq1 = a; |
| isl_int * const *ineq2 = b; |
| int cmp; |
| |
| cmp = isl_seq_cmp((*ineq1) + 1, (*ineq2) + 1, dim); |
| if (cmp != 0) |
| return cmp; |
| return isl_int_cmp((*ineq1)[0], (*ineq2)[0]); |
| } |
| |
| /* Compute a superset of the convex hull of "set" that is described |
| * by only constraints in the elements of "list", where "set" has |
| * no parameters or integer divisions. |
| * |
| * We collect all the constraints in those elements and then |
| * sort the constraints such that constraints with the same linear part |
| * are sorted together and that those with smaller constant term are |
| * sorted first. |
| */ |
| static __isl_give isl_basic_set *uset_unshifted_simple_hull_from_basic_set_list( |
| __isl_take isl_set *set, __isl_take isl_basic_set_list *list) |
| { |
| int i, n, n_eq, n_ineq; |
| unsigned dim; |
| isl_ctx *ctx; |
| isl_mat *mat = NULL; |
| isl_int **ineq = NULL; |
| isl_basic_set *hull; |
| |
| if (!set) |
| goto error; |
| ctx = isl_set_get_ctx(set); |
| |
| n_eq = 0; |
| n_ineq = 0; |
| n = isl_basic_set_list_n_basic_set(list); |
| for (i = 0; i < n; ++i) { |
| isl_basic_set *bset; |
| bset = isl_basic_set_list_get_basic_set(list, i); |
| if (!bset) |
| goto error; |
| n_eq += bset->n_eq; |
| n_ineq += 2 * bset->n_eq + bset->n_ineq; |
| isl_basic_set_free(bset); |
| } |
| |
| ineq = isl_alloc_array(ctx, isl_int *, n_ineq); |
| if (n_ineq > 0 && !ineq) |
| goto error; |
| |
| dim = isl_set_dim(set, isl_dim_set); |
| mat = isl_mat_alloc(ctx, n_eq, 1 + dim); |
| mat = collect_inequalities(mat, list, ineq); |
| if (!mat) |
| goto error; |
| |
| if (isl_sort(ineq, n_ineq, sizeof(ineq[0]), &cmp_ineq, &dim) < 0) |
| goto error; |
| |
| hull = uset_unshifted_simple_hull_from_constraints(set, n_ineq, ineq); |
| |
| isl_mat_free(mat); |
| free(ineq); |
| isl_basic_set_list_free(list); |
| return hull; |
| error: |
| isl_mat_free(mat); |
| free(ineq); |
| isl_set_free(set); |
| isl_basic_set_list_free(list); |
| return NULL; |
| } |
| |
| /* Compute a superset of the convex hull of "map" that is described |
| * by only constraints in the elements of "list". |
| * |
| * If the list is empty, then we can only describe the universe set. |
| * If the input map is empty, then all constraints are valid, so |
| * we return the intersection of the elements in "list". |
| * |
| * Otherwise, we align all divs and temporarily treat them |
| * as regular variables, computing the unshifted simple hull in |
| * uset_unshifted_simple_hull_from_basic_set_list. |
| */ |
| static __isl_give isl_basic_map *map_unshifted_simple_hull_from_basic_map_list( |
| __isl_take isl_map *map, __isl_take isl_basic_map_list *list) |
| { |
| isl_basic_map *model; |
| isl_basic_map *hull; |
| isl_set *set; |
| isl_basic_set_list *bset_list; |
| |
| if (!map || !list) |
| goto error; |
| |
| if (isl_basic_map_list_n_basic_map(list) == 0) { |
| isl_space *space; |
| |
| space = isl_map_get_space(map); |
| isl_map_free(map); |
| isl_basic_map_list_free(list); |
| return isl_basic_map_universe(space); |
| } |
| if (isl_map_plain_is_empty(map)) { |
| isl_map_free(map); |
| return isl_basic_map_list_intersect(list); |
| } |
| |
| map = isl_map_align_divs_to_basic_map_list(map, list); |
| if (!map) |
| goto error; |
| list = isl_basic_map_list_align_divs_to_basic_map(list, map->p[0]); |
| |
| model = isl_basic_map_list_get_basic_map(list, 0); |
| |
| set = isl_map_underlying_set(map); |
| bset_list = isl_basic_map_list_underlying_set(list); |
| |
| hull = uset_unshifted_simple_hull_from_basic_set_list(set, bset_list); |
| hull = isl_basic_map_overlying_set(hull, model); |
| |
| return hull; |
| error: |
| isl_map_free(map); |
| isl_basic_map_list_free(list); |
| return NULL; |
| } |
| |
| /* Return a sequence of the basic maps that make up the maps in "list". |
| */ |
| static __isl_give isl_basic_map_list *collect_basic_maps( |
| __isl_take isl_map_list *list) |
| { |
| int i, n; |
| isl_ctx *ctx; |
| isl_basic_map_list *bmap_list; |
| |
| if (!list) |
| return NULL; |
| n = isl_map_list_n_map(list); |
| ctx = isl_map_list_get_ctx(list); |
| bmap_list = isl_basic_map_list_alloc(ctx, 0); |
| |
| for (i = 0; i < n; ++i) { |
| isl_map *map; |
| isl_basic_map_list *list_i; |
| |
| map = isl_map_list_get_map(list, i); |
| map = isl_map_compute_divs(map); |
| list_i = isl_map_get_basic_map_list(map); |
| isl_map_free(map); |
| bmap_list = isl_basic_map_list_concat(bmap_list, list_i); |
| } |
| |
| isl_map_list_free(list); |
| return bmap_list; |
| } |
| |
| /* Compute a superset of the convex hull of "map" that is described |
| * by only constraints in the elements of "list". |
| * |
| * If "map" is the universe, then the convex hull (and therefore |
| * any superset of the convexhull) is the universe as well. |
| * |
| * Otherwise, we collect all the basic maps in the map list and |
| * continue with map_unshifted_simple_hull_from_basic_map_list. |
| */ |
| __isl_give isl_basic_map *isl_map_unshifted_simple_hull_from_map_list( |
| __isl_take isl_map *map, __isl_take isl_map_list *list) |
| { |
| isl_basic_map_list *bmap_list; |
| int is_universe; |
| |
| is_universe = isl_map_plain_is_universe(map); |
| if (is_universe < 0) |
| map = isl_map_free(map); |
| if (is_universe < 0 || is_universe) { |
| isl_map_list_free(list); |
| return isl_map_unshifted_simple_hull(map); |
| } |
| |
| bmap_list = collect_basic_maps(list); |
| return map_unshifted_simple_hull_from_basic_map_list(map, bmap_list); |
| } |
| |
| /* Compute a superset of the convex hull of "set" that is described |
| * by only constraints in the elements of "list". |
| */ |
| __isl_give isl_basic_set *isl_set_unshifted_simple_hull_from_set_list( |
| __isl_take isl_set *set, __isl_take isl_set_list *list) |
| { |
| return isl_map_unshifted_simple_hull_from_map_list(set, list); |
| } |
| |
| /* Given a set "set", return parametric bounds on the dimension "dim". |
| */ |
| static struct isl_basic_set *set_bounds(struct isl_set *set, int dim) |
| { |
| unsigned set_dim = isl_set_dim(set, isl_dim_set); |
| set = isl_set_copy(set); |
| set = isl_set_eliminate_dims(set, dim + 1, set_dim - (dim + 1)); |
| set = isl_set_eliminate_dims(set, 0, dim); |
| return isl_set_convex_hull(set); |
| } |
| |
| /* Computes a "simple hull" and then check if each dimension in the |
| * resulting hull is bounded by a symbolic constant. If not, the |
| * hull is intersected with the corresponding bounds on the whole set. |
| */ |
| __isl_give isl_basic_set *isl_set_bounded_simple_hull(__isl_take isl_set *set) |
| { |
| int i, j; |
| struct isl_basic_set *hull; |
| unsigned nparam, left; |
| int removed_divs = 0; |
| |
| hull = isl_set_simple_hull(isl_set_copy(set)); |
| if (!hull) |
| goto error; |
| |
| nparam = isl_basic_set_dim(hull, isl_dim_param); |
| for (i = 0; i < isl_basic_set_dim(hull, isl_dim_set); ++i) { |
| int lower = 0, upper = 0; |
| struct isl_basic_set *bounds; |
| |
| left = isl_basic_set_total_dim(hull) - nparam - i - 1; |
| for (j = 0; j < hull->n_eq; ++j) { |
| if (isl_int_is_zero(hull->eq[j][1 + nparam + i])) |
| continue; |
| if (isl_seq_first_non_zero(hull->eq[j]+1+nparam+i+1, |
| left) == -1) |
| break; |
| } |
| if (j < hull->n_eq) |
| continue; |
| |
| for (j = 0; j < hull->n_ineq; ++j) { |
| if (isl_int_is_zero(hull->ineq[j][1 + nparam + i])) |
| continue; |
| if (isl_seq_first_non_zero(hull->ineq[j]+1+nparam+i+1, |
| left) != -1 || |
| isl_seq_first_non_zero(hull->ineq[j]+1+nparam, |
| i) != -1) |
| continue; |
| if (isl_int_is_pos(hull->ineq[j][1 + nparam + i])) |
| lower = 1; |
| else |
| upper = 1; |
| if (lower && upper) |
| break; |
| } |
| |
| if (lower && upper) |
| continue; |
| |
| if (!removed_divs) { |
| set = isl_set_remove_divs(set); |
| if (!set) |
| goto error; |
| removed_divs = 1; |
| } |
| bounds = set_bounds(set, i); |
| hull = isl_basic_set_intersect(hull, bounds); |
| if (!hull) |
| goto error; |
| } |
| |
| isl_set_free(set); |
| return hull; |
| error: |
| isl_set_free(set); |
| isl_basic_set_free(hull); |
| return NULL; |
| } |