/Users/buildslave/jenkins/workspace/clang-stage2-coverage-R/llvm/tools/polly/lib/External/isl/isl_convex_hull.c

Source (jump to first uncovered line)
/*
 * Copyright 2008-2009 Katholieke Universiteit Leuven
 * Copyright 2014      INRIA Rocquencourt
 *
 * Use of this software is governed by the MIT license
 *
 * Written by Sven Verdoolaege, K.U.Leuven, Departement
 * Computerwetenschappen, Celestijnenlaan 200A, B-3001 Leuven, Belgium
 * and Inria Paris - Rocquencourt, Domaine de Voluceau - Rocquencourt,
 * B.P. 105 - 78153 Le Chesnay, France
 */

#include <isl_ctx_private.h>
#include <isl_map_private.h>
#include <isl_lp_private.h>
#include <isl/map.h>
#include <isl_mat_private.h>
#include <isl_vec_private.h>
#include <isl/set.h>
#include <isl_seq.h>
#include <isl_options_private.h>
#include "isl_equalities.h"
#include "isl_tab.h"
#include <isl_sort.h>

#include <bset_to_bmap.c>
#include <bset_from_bmap.c>
#include <set_to_map.c>

static __isl_give isl_basic_set *uset_convex_hull_wrap_bounded(
  __isl_take isl_set *set);

/* Remove redundant
 * constraints.  If the minimal value along the normal of a constraint
 * is the same if the constraint is removed, then the constraint is redundant.
 *
 * Since some constraints may be mutually redundant, sort the constraints
 * first such that constraints that involve existentially quantified
 * variables are considered for removal before those that do not.
 * The sorting is also needed for the use in map_simple_hull.
 *
 * Note that isl_tab_detect_implicit_equalities may also end up
 * marking some constraints as redundant.  Make sure the constraints
 * are preserved and undo those marking such that isl_tab_detect_redundant
 * can consider the constraints in the sorted order.
 *
 * Alternatively, we could have intersected the basic map with the
 * corresponding equality and then checked if the dimension was that
 * of a facet.
 */
__isl_give isl_basic_map *isl_basic_map_remove_redundancies(
  __isl_take isl_basic_map *bmap)
{
  struct isl_tab *tab;

  if (!bmap)
    return NULL;

  bmap = isl_basic_map_gauss(bmap, NULL);
  if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_EMPTY))
    return bmap929;
  if (ISL_F_ISSET(bmap, ISL_BASIC_MAP_NO_REDUNDANT))
    return bmap120k;
  if (bmap->n_ineq <= 1)
    return bmap;

  bmap = isl_basic_map_sort_constraints(bmap);
  tab = isl_tab_from_basic_map(bmap, 0);
  if (!tab)
    goto error;
  tab->preserve = 1;
  if (isl_tab_detect_implicit_equalities(tab) < 0)
    goto error;
  if (isl_tab_restore_redundant(tab) < 0)
    goto error;
  tab->preserve = 0;
  if (isl_tab_detect_redundant(tab) < 0)
    goto error;
  bmap = isl_basic_map_update_from_tab(bmap, tab);
  isl_tab_free(tab);
  if (!bmap)
    return NULL;
  ISL_F_SET(bmap, ISL_BASIC_MAP_NO_IMPLICIT);
  ISL_F_SET(bmap, ISL_BASIC_MAP_NO_REDUNDANT);
  return bmap;
error:
  isl_tab_free(tab);
  isl_basic_map_free(bmap);
  return NULL;
}

__isl_give isl_basic_set *isl_basic_set_remove_redundancies(
  __isl_take isl_basic_set *bset)
{
  return bset_from_bmap(
    isl_basic_map_remove_redundancies(bset_to_bmap(bset)));
}

/* Remove redundant constraints in each of the basic maps.
 */
__isl_give isl_map *isl_map_remove_redundancies(__isl_take isl_map *map)
{
  return isl_map_inline_foreach_basic_map(map,
              &isl_basic_map_remove_redundancies);
}

__isl_give isl_set *isl_set_remove_redundancies(__isl_take isl_set *set)
{
  return isl_map_remove_redundancies(set);
}

/* Check if the set set is bound in the direction of the affine
 * constraint c and if so, set the constant term such that the
 * resulting constraint is a bounding constraint for the set.
 */
static int uset_is_bound(__isl_keep isl_set *set, isl_int *c, unsigned len)
{
  int first;
  int j;
  isl_int opt;
  isl_int opt_denom;

  isl_int_init(opt);
  isl_int_init(opt_denom);
  first = 1;
  for (j = 0; j < set->n; ++j7.76k) {
    enum isl_lp_result res;

    if (ISL_F_ISSET(set->p[j], ISL_BASIC_SET_EMPTY))
      continue0;

    res = isl_basic_set_solve_lp(set->p[j],
        0, c, set->ctx->one, &opt, &opt_denom, NULL);
    if (res == isl_lp_unbounded)
      break;
    if (res == isl_lp_error)
      goto error;
    if (res == isl_lp_empty) {
      set->p[j] = isl_basic_set_set_to_empty(set->p[j]);
      if (!set->p[j])
        goto error;
      continue;
    }
    if (first || isl_int_is_neg3.88k(opt)) {
      if (!isl_int_is_one(opt_denom))
        isl_seq_scale(c, c, opt_denom, len)4.54k;
      isl_int_sub(c[0], c[0], opt);
    }
    first = 0;
  }
  isl_int_clear(opt);
  isl_int_clear(opt_denom);
  return j >= set->n;
error:
  isl_int_clear(opt);
  isl_int_clear(opt_denom);
  return -1;
}

static struct isl_basic_set *isl_basic_set_add_equality(
  struct isl_basic_set *bset, isl_int *c)
{
  int i;
  unsigned dim;

  if (!bset)
    return NULL;

  if (ISL_F_ISSET(bset, ISL_BASIC_SET_EMPTY))
    return bset0;

  isl_assert(bset->ctx, isl_basic_set_n_param(bset) == 0, goto error);
  isl_assert(bset->ctx, bset->n_div == 0, goto error);
  dim = isl_basic_set_n_dim(bset);
  bset = isl_basic_set_cow(bset);
  bset = isl_basic_set_extend(bset, 0, dim, 0, 1, 0);
  i = isl_basic_set_alloc_equality(bset);
  if (i < 0)
    goto error;
  isl_seq_cpy(bset->eq[i], c, 1 + dim);
  return bset;
error:
  isl_basic_set_free(bset);
  return NULL;
}

static __isl_give isl_set *isl_set_add_basic_set_equality(
  __isl_take isl_set *set, isl_int *c)
{
  int i;

  set = isl_set_cow(set);
  if (!set)
    return NULL;
  for (i = 0; 7.59ki < set->n; ++i15.1k) {
    set->p[i] = isl_basic_set_add_equality(set->p[i], c);
    if (!set->p[i])
      goto error;
  }
  return set;
error:
  isl_set_free(set);
  return NULL;
}

/* Given a union of basic sets, construct the constraints for wrapping
 * a facet around one of its ridges.
 * In particular, if each of n the d-dimensional basic sets i in "set"
 * contains the origin, satisfies the constraints x_1 >= 0 and x_2 >= 0
 * and is defined by the constraints
 *            [ 1 ]
 *        A_i [ x ]  >= 0
 *
 * then the resulting set is of dimension n*(1+d) and has as constraints
 *
 *            [ a_i ]
 *        A_i [ x_i ] >= 0
 *
 *              a_i   >= 0
 *
 *      \sum_i x_{i,1} = 1
 */
static __isl_give isl_basic_set *wrap_constraints(__isl_keep isl_set *set)
{
  struct isl_basic_set *lp;
  unsigned n_eq;
  unsigned n_ineq;
  int i, j, k;
  unsigned dim, lp_dim;

  if (!set)
    return NULL;

  dim = 1 + isl_set_n_dim(set);
  n_eq = 1;
  n_ineq = set->n;
  for (i = 0; i < set->n; ++i35.1k) {
    n_eq += set->p[i]->n_eq;
    n_ineq += set->p[i]->n_ineq;
  }
  lp = isl_basic_set_alloc(set->ctx, 0, dim * set->n, 0, n_eq, n_ineq);
  lp = isl_basic_set_set_rational(lp);
  if (!lp)
    return NULL;
  lp_dim = isl_basic_set_n_dim(lp);
  k = isl_basic_set_alloc_equality(lp);
  isl_int_set_si(lp->eq[k][0], -1);
  for (i = 0; i < set->n; ++i35.1k) {
    isl_int_set_si(lp->eq[k][1+dim*i], 0);
    isl_int_set_si(lp->eq[k][1+dim*i+1], 1);
    isl_seq_clr(lp->eq[k]+1+dim*i+2, dim-2);
  }
  for (i = 0; i < set->n; ++i35.1k) {
    k = isl_basic_set_alloc_inequality(lp);
    isl_seq_clr(lp->ineq[k], 1+lp_dim);
    isl_int_set_si(lp->ineq[k][1+dim*i], 1);

    for (j = 0; j < set->p[i]->n_eq; ++j52.1k) {
      k = isl_basic_set_alloc_equality(lp);
      isl_seq_clr(lp->eq[k], 1+dim*i);
      isl_seq_cpy(lp->eq[k]+1+dim*i, set->p[i]->eq[j], dim);
      isl_seq_clr(lp->eq[k]+1+dim*(i+1), dim*(set->n-i-1));
    }

    for (j = 0; j < set->p[i]->n_ineq; ++j107k) {
      k = isl_basic_set_alloc_inequality(lp);
      isl_seq_clr(lp->ineq[k], 1+dim*i);
      isl_seq_cpy(lp->ineq[k]+1+dim*i, set->p[i]->ineq[j], dim);
      isl_seq_clr(lp->ineq[k]+1+dim*(i+1), dim*(set->n-i-1));
    }
  }
  return lp;
}

/* Given a facet "facet" of the convex hull of "set" and a facet "ridge"
 * of that facet, compute the other facet of the convex hull that contains
 * the ridge.
 *
 * We first transform the set such that the facet constraint becomes
 *
 *      x_1 >= 0
 *
 * I.e., the facet lies in
 *
 *      x_1 = 0
 *
 * and on that facet, the constraint that defines the ridge is
 *
 *      x_2 >= 0
 *
 * (This transformation is not strictly needed, all that is needed is
 * that the ridge contains the origin.)
 *
 * Since the ridge contains the origin, the cone of the convex hull
 * will be of the form
 *
 *      x_1 >= 0
 *      x_2 >= a x_1
 *
 * with this second constraint defining the new facet.
 * The constant a is obtained by settting x_1 in the cone of the
 * convex hull to 1 and minimizing x_2.
 * Now, each element in the cone of the convex hull is the sum
 * of elements in the cones of the basic sets.
 * If a_i is the dilation factor of basic set i, then the problem
 * we need to solve is
 *
 *      min \sum_i x_{i,2}
 *      st
 *        \sum_i x_{i,1} = 1
 *            a_i   >= 0
 *          [ a_i ]
 *        A [ x_i ] >= 0
 *
 * with
 *            [  1  ]
 *        A_i [ x_i ] >= 0
 *
 * the constraints of each (transformed) basic set.
 * If a = n/d, then the constraint defining the new facet (in the transformed
 * space) is
 *
 *      -n x_1 + d x_2 >= 0
 *
 * In the original space, we need to take the same combination of the
 * corresponding constraints "facet" and "ridge".
 *
 * If a = -infty = "-1/0", then we just return the original facet constraint.
 * This means that the facet is unbounded, but has a bounded intersection
 * with the union of sets.
 */
isl_int *isl_set_wrap_facet(__isl_keep isl_set *set,
  isl_int *facet, isl_int *ridge)
{
  int i;
  isl_ctx *ctx;
  struct isl_mat *T = NULL;
  struct isl_basic_set *lp = NULL;
  struct isl_vec *obj;
  enum isl_lp_result res;
  isl_int num, den;
  unsigned dim;

  if (!set)
    return NULL;
  ctx = set->ctx;
  set = isl_set_copy(set);
  set = isl_set_set_rational(set);

  dim = 1 + isl_set_n_dim(set);
  T = isl_mat_alloc(ctx, 3, dim);
  if (!T)
    goto error;
  isl_int_set_si(T->row[0][0], 1);
  isl_seq_clr(T->row[0]+1, dim - 1);
  isl_seq_cpy(T->row[1], facet, dim);
  isl_seq_cpy(T->row[2], ridge, dim);
  T = isl_mat_right_inverse(T);
  set = isl_set_preimage(set, T);
  T = NULL;
  if (!set)
    goto error;
  lp = wrap_constraints(set);
  obj = isl_vec_alloc(ctx, 1 + dim*set->n);
  if (!obj)
    goto error;
  isl_int_set_si(obj->block.data[0], 0);
  for (i = 0; i < set->n; ++i35.1k) {
    isl_seq_clr(obj->block.data + 1 + dim*i, 2);
    isl_int_set_si(obj->block.data[1 + dim*i+2], 1);
    isl_seq_clr(obj->block.data + 1 + dim*i+3, dim-3);
  }
  isl_int_init(num);
  isl_int_init(den);
  res = isl_basic_set_solve_lp(lp, 0,
          obj->block.data, ctx->one, &num, &den, NULL);
  if (res == isl_lp_ok) {
    isl_int_neg(num, num);
    isl_seq_combine(facet, num, facet, den, ridge, dim);
    isl_seq_normalize(ctx, facet, dim);
  }
  isl_int_clear(num);
  isl_int_clear(den);
  isl_vec_free(obj);
  isl_basic_set_free(lp);
  isl_set_free(set);
  if (res == isl_lp_error)
    return NULL;
  isl_assert(ctx, res == isl_lp_ok || res == isl_lp_unbounded, 
       return NULL);
  return facet;
error:
  isl_basic_set_free(lp);
  isl_mat_free(T);
  isl_set_free(set);
  return NULL;
}

/* Compute the constraint of a facet of "set".
 *
 * We first compute the intersection with a bounding constraint
 * that is orthogonal to one of the coordinate axes.
 * If the affine hull of this intersection has only one equality,
 * we have found a facet.
 * Otherwise, we wrap the current bounding constraint around
 * one of the equalities of the face (one that is not equal to
 * the current bounding constraint).
 * This process continues until we have found a facet.
 * The dimension of the intersection increases by at least
 * one on each iteration, so termination is guaranteed.
 */
static __isl_give isl_mat *initial_facet_constraint(__isl_keep isl_set *set)
{
  struct isl_set *slice = NULL;
  struct isl_basic_set *face = NULL;
  int i;
  unsigned dim = isl_set_n_dim(set);
  int is_bound;
  isl_mat *bounds = NULL;

  isl_assert(set->ctx, set->n > 0, goto error);
  bounds = isl_mat_alloc(set->ctx, 1, 1 + dim);
  if (!bounds)
    return NULL;

  isl_seq_clr(bounds->row[0], dim);
  isl_int_set_si(bounds->row[0][1 + dim - 1], 1);
  is_bound = uset_is_bound(set, bounds->row[0], 1 + dim);
  if (is_bound < 0)
    goto error;
  isl_assert(set->ctx, is_bound, goto error);
  isl_seq_normalize(set->ctx, bounds->row[0], 1 + dim);
  bounds->n_row = 1;

  for (;;) {
    slice = isl_set_copy(set);
    slice = isl_set_add_basic_set_equality(slice, bounds->row[0]);
    face = isl_set_affine_hull(slice);
    if (!face)
      goto error;
    if (face->n_eq == 1) {
      isl_basic_set_free(face);
      break;
    }
    for (i = 0; 3.71ki < face->n_eq; ++i3.27k)
      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_die0(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; ++i13.5k) {
    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; 13.5kj < facet->n_ineq; ++j34.7k) {
      for (f = 0; f < hull_facet->n_ineq; ++f32.4k)
        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; ++i8.13k) {
    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; ++j10) {
      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; ++i8.13k) {
    struct isl_basic_set *bset = set->p[i];
    int has_lower = 0;
    int has_upper = 0;

    for (j = 0; j < bset->n_eq; ++j7.59k) {
      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_pos1.64k(bset->eq[j][1]))
          isl_seq_cpy(lower, bset->eq[j], 2)1.64k;
        if (isl_int_gt(a, b) && isl_int_is_neg1.89k(bset->eq[j][1]))
          isl_seq_neg(lower, bset->eq[j], 2)0;
      }
      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_pos1.89k(bset->eq[j][1]))
          isl_seq_neg(upper, bset->eq[j], 2)1.89k;
        if (isl_int_gt(a, b) && isl_int_is_neg1.64k(bset->eq[j][1]))
          isl_seq_cpy(upper, bset->eq[j], 2)0;
      }
    }
    for (j = 0; j < bset->n_ineq; ++j1.07k) {
      if (isl_int_is_pos(bset->ineq[j][1]))
        has_lower = 1537;
      if (isl_int_is_neg(bset->ineq[j][1]))
        has_upper = 1535;
      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)286;
      }
      if (upper && isl_int_is_neg1.07k(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)245;
      }
    }
    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; ++i28) {
    for (j = 0; j < bset[i]->n_eq; ++j13) {
      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; 28j < bset[i]->n_ineq; ++j98) {
      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; 14j < 1+dim; ++j51) {
    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; 244i < set->n; ++i504) {
    isl_bool bounded = isl_basic_set_is_bounded(set->p[i]);
    if (!bounded || bounded < 0504)
      return bounded;
  }
  return isl_bool_true212;
}

/* 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; ++i0) {
    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; 4i < bset1->n_ineq; ++i21) {
    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; ++i0) {
    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; 4i < bset2->n_ineq; ++i25) {
    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; 8i < n; ++i97) {
    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; 8i < d; ++i30) {
    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; ++j14) {
      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; ++j150) {
      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; ++j14) {
      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; ++j174) {
      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; ++i4) {
    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; ++i31)
    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)14;

  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 && bounded24)
    return uset_convex_hull_wrap(isl_basic_set_union(bset1, bset2));

  if (bounded1 || bounded27)
    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; ++i0)
    if (isl_basic_set_alloc_div(lin) < 0)
      goto error;
  if (!lin)
    goto error;
  for (i = 0; 114i < bset->n_eq; ++i108) {
    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; 114i < bset->n_ineq && lin->n_eq < dim219; ++i184) {
    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; ++i110)
    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_die0(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 NULL0;
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]))
    return3;
  if (isl_int_eq(c->c->row[0][0], con[0])) {
    if (ineq)
      c->ineq = ineq;
    return;
  }
  c->c = isl_mat_cow(c->c);
  isl_int_set(c->c->row[0][0], con[0]);
  c->ineq = ineq;
}

/* Check whether the constraint hash table "table" contains the constraint
 * "con".
 */
static int has_constraint(struct isl_ctx *ctx, struct isl_hash_table *table,
  isl_int *con, unsigned len, int n)
{
  struct isl_hash_table_entry *entry;
  struct max_constraint *c;
  uint32_t c_hash;

  c_hash = isl_seq_get_hash(con + 1, len);
  entry = isl_hash_table_find(ctx, table, c_hash, max_constraint_equal,
      con + 1, 0);
  if (!entry)
    return 0;
  c = entry->data;
  if (c->count < n)
    return 0;
  return isl_int_eq(c->c->row[0][0], con[0]);
}

/* Check for inequality constraints of a basic set without equalities
 * such that the same or more stringent copies of the constraint appear
 * in all of the basic sets.  Such constraints are necessarily facet
 * constraints of the convex hull.
 *
 * If the resulting basic set is by chance identical to one of
 * the basic sets in "set", then we know that this basic set contains
 * all other basic sets and is therefore the convex hull of set.
 * In this case we set *is_hull to 1.
 */
static __isl_give isl_basic_set *common_constraints(
  __isl_take isl_basic_set *hull, __isl_keep isl_set *set, int *is_hull)
{
  int i, j, s, n;
  int min_constraints;
  int best;
  struct max_constraint *constraints = NULL;
  struct isl_hash_table *table = NULL;
  unsigned total;

  *is_hull = 0;

  for (i = 0; i < set->n; ++i7.10k)
    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; ++i36) {
    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; ++i2.48k) {
    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; 674i < min_constraints; ++i2.48k) {
    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; ++s1.34k) {
    if (s == best)
      continue;

    for (i = 0; 674i < set->p[s]->n_eq; ++i696) {
      isl_int *eq = set->p[s]->eq[i];
      for (j = 0; j < 2; ++j1.39k) {
        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; ++i1.69k) {
      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; ++i2.48k) {
    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; 674s < set->n; ++s1.34k) {
    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; ++i2.48k)
    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; ++i7.81k) {
    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 == 14ISL_CONVEX_HULL_WRAP14)
    return uset_convex_hull_wrap(set)11;

  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; ++i73.5k) {
    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)284k;
}

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; ++i157k) {
    for (j = 0; j < 2; ++j315k) {
      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; 73.5ki < bset->n_ineq; ++i609k) {
    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; 13.7ki < set->n; ++i73.5k) {
    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_neg61.2k(opt)) {
    if (shift)
      isl_int_sub288(ineq[0], ineq[0], opt);
    else
      res = isl_lp_unbounded1.97k;
  }

  isl_int_clear(opt);

  return (res == isl_lp_ok || res == isl_lp_empty9.49k) ? 159.2k :
         res == isl_lp_unbounded 9.49k? 09.49k : -10;
}

/* 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; ++j787k) {
    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_neg142k(ineq_j[0], ineq_j[0]);
    if (isl_int_gt(ineq_j[0], ineq[0]))
      isl_int_set27.3k(ineq[0], ineq_j[0]);
    if (neg)
      isl_int_neg142k(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; 170kj < i; ++j27.3k) {
    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; ++j11.6k) {
    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; 144kj < set->n; ++j738k) {
    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; ++j156k) {
    for (k = 0; k < 2; ++k313k) {
      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; ++j549k)
    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; ++i69.7k) {
    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; 12.4ki < set->n; ++i69.7k)
    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 >= 01.62k) {
    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_set30(bmap1->ineq[i1][0], bmap2->ineq[i2][0]);
    --i1;
    --i2;
  }
  for (; i1 >= 0; --i1197)
    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 >= 040) {
    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; --i18)
    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; ++i666) {
    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; ++i61.2k) {
    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_neg472(ineq_i[0], ineq_i[0]);
      more_relaxed = isl_int_gt(ineq_i[0], ineq[0]);
      if (neg)
        isl_int_neg472(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; ++i68.9k) {
    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 &&
        (50.6klast_added50.6k || isl_int_eq9.24k(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; ++i5.21k) {
    isl_basic_set *bset;
    bset = isl_basic_set_list_get_basic_set(list, i);
    if (!bset)
      return isl_mat_free(mat);
    for (j = 0; 5.21kj < bset->n_eq; ++j1.66k) {
      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; ++j65.6k)
      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; ++i5.21k) {
    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; ++i2.71k) {
    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;
}

Coverage Report

Created: 2019-07-24 05:18