forked from OSchip/llvm-project
3064 lines
84 KiB
C
3064 lines
84 KiB
C
/*
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* Copyright 2008-2009 Katholieke Universiteit Leuven
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* Copyright 2014 INRIA Rocquencourt
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*
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* Use of this software is governed by the MIT license
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*
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* Written by Sven Verdoolaege, K.U.Leuven, Departement
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* Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
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* and Inria Paris - Rocquencourt, Domaine de Voluceau - Rocquencourt,
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* B.P. 105 - 78153 Le Chesnay, France
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*/
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#include <isl_ctx_private.h>
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#include <isl_map_private.h>
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#include <isl_lp_private.h>
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#include <isl/map.h>
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#include <isl_mat_private.h>
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#include <isl_vec_private.h>
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#include <isl/set.h>
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#include <isl_seq.h>
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#include <isl_options_private.h>
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#include "isl_equalities.h"
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#include "isl_tab.h"
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#include <isl_sort.h>
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#include <bset_to_bmap.c>
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#include <bset_from_bmap.c>
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#include <set_to_map.c>
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static __isl_give isl_basic_set *uset_convex_hull_wrap_bounded(
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__isl_take isl_set *set);
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/* Remove redundant
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* constraints. If the minimal value along the normal of a constraint
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* is the same if the constraint is removed, then the constraint is redundant.
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*
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* Since some constraints may be mutually redundant, sort the constraints
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* first such that constraints that involve existentially quantified
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* variables are considered for removal before those that do not.
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* The sorting is also needed for the use in map_simple_hull.
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*
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* Note that isl_tab_detect_implicit_equalities may also end up
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* marking some constraints as redundant. Make sure the constraints
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* are preserved and undo those marking such that isl_tab_detect_redundant
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* can consider the constraints in the sorted order.
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*
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* Alternatively, we could have intersected the basic map with the
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* corresponding equality and then checked if the dimension was that
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* of a facet.
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*/
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__isl_give isl_basic_map *isl_basic_map_remove_redundancies(
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__isl_take isl_basic_map *bmap)
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{
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struct isl_tab *tab;
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if (!bmap)
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return NULL;
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bmap = isl_basic_map_gauss(bmap, NULL);
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if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY))
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return bmap;
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if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_NO_REDUNDANT))
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return bmap;
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if (bmap->n_ineq <= 1)
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return bmap;
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bmap = isl_basic_map_sort_constraints(bmap);
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tab = isl_tab_from_basic_map(bmap, 0);
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if (!tab)
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goto error;
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tab->preserve = 1;
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if (isl_tab_detect_implicit_equalities(tab) < 0)
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goto error;
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if (isl_tab_restore_redundant(tab) < 0)
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goto error;
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tab->preserve = 0;
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if (isl_tab_detect_redundant(tab) < 0)
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goto error;
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bmap = isl_basic_map_update_from_tab(bmap, tab);
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isl_tab_free(tab);
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if (!bmap)
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return NULL;
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ISL_F_SET(bmap, ISL_BASIC_MAP_NO_IMPLICIT);
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ISL_F_SET(bmap, ISL_BASIC_MAP_NO_REDUNDANT);
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return bmap;
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error:
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isl_tab_free(tab);
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isl_basic_map_free(bmap);
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return NULL;
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}
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__isl_give isl_basic_set *isl_basic_set_remove_redundancies(
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__isl_take isl_basic_set *bset)
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{
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return bset_from_bmap(
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isl_basic_map_remove_redundancies(bset_to_bmap(bset)));
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}
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/* Remove redundant constraints in each of the basic maps.
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*/
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__isl_give isl_map *isl_map_remove_redundancies(__isl_take isl_map *map)
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{
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return isl_map_inline_foreach_basic_map(map,
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&isl_basic_map_remove_redundancies);
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}
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__isl_give isl_set *isl_set_remove_redundancies(__isl_take isl_set *set)
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{
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return isl_map_remove_redundancies(set);
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}
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/* Check if the set set is bound in the direction of the affine
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* constraint c and if so, set the constant term such that the
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* resulting constraint is a bounding constraint for the set.
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*/
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static int uset_is_bound(__isl_keep isl_set *set, isl_int *c, unsigned len)
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{
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int first;
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int j;
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isl_int opt;
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isl_int opt_denom;
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isl_int_init(opt);
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isl_int_init(opt_denom);
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first = 1;
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for (j = 0; j < set->n; ++j) {
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enum isl_lp_result res;
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if (ISL_F_ISSET(set->p[j], ISL_BASIC_SET_EMPTY))
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continue;
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res = isl_basic_set_solve_lp(set->p[j],
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0, c, set->ctx->one, &opt, &opt_denom, NULL);
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if (res == isl_lp_unbounded)
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break;
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if (res == isl_lp_error)
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goto error;
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if (res == isl_lp_empty) {
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set->p[j] = isl_basic_set_set_to_empty(set->p[j]);
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if (!set->p[j])
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goto error;
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continue;
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}
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if (first || isl_int_is_neg(opt)) {
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if (!isl_int_is_one(opt_denom))
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isl_seq_scale(c, c, opt_denom, len);
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isl_int_sub(c[0], c[0], opt);
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}
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first = 0;
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}
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isl_int_clear(opt);
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isl_int_clear(opt_denom);
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return j >= set->n;
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error:
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isl_int_clear(opt);
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isl_int_clear(opt_denom);
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return -1;
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}
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static struct isl_basic_set *isl_basic_set_add_equality(
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struct isl_basic_set *bset, isl_int *c)
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{
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int i;
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unsigned dim;
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if (!bset)
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return NULL;
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if (ISL_F_ISSET(bset, ISL_BASIC_SET_EMPTY))
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return bset;
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isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
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isl_assert(bset->ctx, bset->n_div == 0, goto error);
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dim = isl_basic_set_n_dim(bset);
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bset = isl_basic_set_cow(bset);
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bset = isl_basic_set_extend(bset, 0, dim, 0, 1, 0);
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i = isl_basic_set_alloc_equality(bset);
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if (i < 0)
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goto error;
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isl_seq_cpy(bset->eq[i], c, 1 + dim);
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return bset;
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error:
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isl_basic_set_free(bset);
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return NULL;
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}
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static __isl_give isl_set *isl_set_add_basic_set_equality(
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__isl_take isl_set *set, isl_int *c)
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{
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int i;
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set = isl_set_cow(set);
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if (!set)
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return NULL;
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for (i = 0; i < set->n; ++i) {
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set->p[i] = isl_basic_set_add_equality(set->p[i], c);
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if (!set->p[i])
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goto error;
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}
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return set;
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error:
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isl_set_free(set);
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return NULL;
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}
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/* Given a union of basic sets, construct the constraints for wrapping
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* a facet around one of its ridges.
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* In particular, if each of n the d-dimensional basic sets i in "set"
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* contains the origin, satisfies the constraints x_1 >= 0 and x_2 >= 0
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* and is defined by the constraints
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* [ 1 ]
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* A_i [ x ] >= 0
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*
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* then the resulting set is of dimension n*(1+d) and has as constraints
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*
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* [ a_i ]
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* A_i [ x_i ] >= 0
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*
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* a_i >= 0
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*
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* \sum_i x_{i,1} = 1
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*/
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static __isl_give isl_basic_set *wrap_constraints(__isl_keep isl_set *set)
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{
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struct isl_basic_set *lp;
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unsigned n_eq;
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unsigned n_ineq;
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int i, j, k;
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unsigned dim, lp_dim;
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if (!set)
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return NULL;
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dim = 1 + isl_set_n_dim(set);
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n_eq = 1;
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n_ineq = set->n;
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for (i = 0; i < set->n; ++i) {
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n_eq += set->p[i]->n_eq;
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n_ineq += set->p[i]->n_ineq;
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}
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lp = isl_basic_set_alloc(set->ctx, 0, dim * set->n, 0, n_eq, n_ineq);
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lp = isl_basic_set_set_rational(lp);
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if (!lp)
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return NULL;
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lp_dim = isl_basic_set_n_dim(lp);
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k = isl_basic_set_alloc_equality(lp);
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isl_int_set_si(lp->eq[k][0], -1);
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for (i = 0; i < set->n; ++i) {
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isl_int_set_si(lp->eq[k][1+dim*i], 0);
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isl_int_set_si(lp->eq[k][1+dim*i+1], 1);
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isl_seq_clr(lp->eq[k]+1+dim*i+2, dim-2);
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}
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for (i = 0; i < set->n; ++i) {
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k = isl_basic_set_alloc_inequality(lp);
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isl_seq_clr(lp->ineq[k], 1+lp_dim);
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isl_int_set_si(lp->ineq[k][1+dim*i], 1);
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for (j = 0; j < set->p[i]->n_eq; ++j) {
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k = isl_basic_set_alloc_equality(lp);
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isl_seq_clr(lp->eq[k], 1+dim*i);
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isl_seq_cpy(lp->eq[k]+1+dim*i, set->p[i]->eq[j], dim);
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isl_seq_clr(lp->eq[k]+1+dim*(i+1), dim*(set->n-i-1));
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}
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for (j = 0; j < set->p[i]->n_ineq; ++j) {
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k = isl_basic_set_alloc_inequality(lp);
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isl_seq_clr(lp->ineq[k], 1+dim*i);
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isl_seq_cpy(lp->ineq[k]+1+dim*i, set->p[i]->ineq[j], dim);
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isl_seq_clr(lp->ineq[k]+1+dim*(i+1), dim*(set->n-i-1));
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}
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}
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return lp;
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}
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/* Given a facet "facet" of the convex hull of "set" and a facet "ridge"
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* of that facet, compute the other facet of the convex hull that contains
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* the ridge.
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*
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* We first transform the set such that the facet constraint becomes
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*
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* x_1 >= 0
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*
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* I.e., the facet lies in
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*
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* x_1 = 0
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*
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* and on that facet, the constraint that defines the ridge is
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*
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* x_2 >= 0
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*
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* (This transformation is not strictly needed, all that is needed is
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* that the ridge contains the origin.)
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*
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* Since the ridge contains the origin, the cone of the convex hull
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* will be of the form
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*
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* x_1 >= 0
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* x_2 >= a x_1
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*
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* with this second constraint defining the new facet.
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* The constant a is obtained by settting x_1 in the cone of the
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* convex hull to 1 and minimizing x_2.
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* Now, each element in the cone of the convex hull is the sum
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* of elements in the cones of the basic sets.
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* If a_i is the dilation factor of basic set i, then the problem
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* we need to solve is
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*
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* min \sum_i x_{i,2}
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* st
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* \sum_i x_{i,1} = 1
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* a_i >= 0
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* [ a_i ]
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* A [ x_i ] >= 0
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*
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* with
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* [ 1 ]
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* A_i [ x_i ] >= 0
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*
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* the constraints of each (transformed) basic set.
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* If a = n/d, then the constraint defining the new facet (in the transformed
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* space) is
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*
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* -n x_1 + d x_2 >= 0
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*
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* In the original space, we need to take the same combination of the
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* corresponding constraints "facet" and "ridge".
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*
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* If a = -infty = "-1/0", then we just return the original facet constraint.
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* This means that the facet is unbounded, but has a bounded intersection
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* with the union of sets.
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*/
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isl_int *isl_set_wrap_facet(__isl_keep isl_set *set,
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isl_int *facet, isl_int *ridge)
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{
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int i;
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isl_ctx *ctx;
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struct isl_mat *T = NULL;
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struct isl_basic_set *lp = NULL;
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struct isl_vec *obj;
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enum isl_lp_result res;
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isl_int num, den;
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unsigned dim;
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if (!set)
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return NULL;
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ctx = set->ctx;
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set = isl_set_copy(set);
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set = isl_set_set_rational(set);
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dim = 1 + isl_set_n_dim(set);
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T = isl_mat_alloc(ctx, 3, dim);
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if (!T)
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goto error;
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isl_int_set_si(T->row[0][0], 1);
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isl_seq_clr(T->row[0]+1, dim - 1);
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isl_seq_cpy(T->row[1], facet, dim);
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isl_seq_cpy(T->row[2], ridge, dim);
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T = isl_mat_right_inverse(T);
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set = isl_set_preimage(set, T);
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T = NULL;
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if (!set)
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goto error;
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lp = wrap_constraints(set);
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obj = isl_vec_alloc(ctx, 1 + dim*set->n);
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if (!obj)
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goto error;
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isl_int_set_si(obj->block.data[0], 0);
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for (i = 0; i < set->n; ++i) {
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isl_seq_clr(obj->block.data + 1 + dim*i, 2);
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isl_int_set_si(obj->block.data[1 + dim*i+2], 1);
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isl_seq_clr(obj->block.data + 1 + dim*i+3, dim-3);
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}
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isl_int_init(num);
|
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isl_int_init(den);
|
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res = isl_basic_set_solve_lp(lp, 0,
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obj->block.data, ctx->one, &num, &den, NULL);
|
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if (res == isl_lp_ok) {
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isl_int_neg(num, num);
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isl_seq_combine(facet, num, facet, den, ridge, dim);
|
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isl_seq_normalize(ctx, facet, dim);
|
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}
|
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isl_int_clear(num);
|
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isl_int_clear(den);
|
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isl_vec_free(obj);
|
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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);
|
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isl_mat_free(T);
|
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isl_set_free(set);
|
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return NULL;
|
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}
|
|
|
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/* Compute the constraint of a facet of "set".
|
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*
|
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* We first compute the intersection with a bounding constraint
|
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* that is orthogonal to one of the coordinate axes.
|
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* If the affine hull of this intersection has only one equality,
|
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* we have found a facet.
|
|
* Otherwise, we wrap the current bounding constraint around
|
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* one of the equalities of the face (one that is not equal to
|
|
* the current bounding constraint).
|
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* This process continues until we have found a facet.
|
|
* The dimension of the intersection increases by at least
|
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* 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" constains 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;
|
|
}
|