/*
  Copyright (c) 2017 Microsoft Corporation
  Author: Lev Nachmanson
*/
#include "math/lp/int_solver.h"
#include "math/lp/lar_solver.h"
#include "math/lp/lp_utils.h"
#include "math/lp/monic.h"
#include "math/lp/gomory.h"
#include "math/lp/int_branch.h"
#include "math/lp/int_cube.h"
#include "math/lp/dioph_eq.h"

namespace lp {
    bool get_patching_deltas(const rational& x, const rational& alpha,
                             rational& delta_plus, rational& delta_minus);
    // this will allow to enable and disable tracking of the pivot rows
    struct check_return_helper {
        lar_solver&      lra;
        bool             m_track_touched_rows;
        check_return_helper(lar_solver& ls) :
            lra(ls),
            m_track_touched_rows(lra.touched_rows_are_tracked()) {
            lra.track_touched_rows(false);
        }
        ~check_return_helper() {
            lra.track_touched_rows(m_track_touched_rows);
        }

    };
    
    class int_solver::imp {
    public:
        int_solver&         lia;
        lar_solver&         lra;
        lar_core_solver&    lrac;
        unsigned            m_number_of_calls = 0;
        lar_term            m_t;  // the term to return in the cut
        bool                m_upper;           // cut is an upper bound
        explanation         *m_ex;             // the conflict explanation
        mpq                 m_k;               // the right side of the cut
        hnf_cutter          m_hnf_cutter;
        unsigned            m_hnf_cut_period;
        unsigned            m_dioph_eq_period;
        dioph_eq            m_dio;  
        int_gcd_test        m_gcd;

        bool column_is_int_inf(unsigned j) const {
            return lra.column_is_int(j) && (!lia.value_is_int(j));
        }

        imp(int_solver& lia): lia(lia), lra(lia.lra), lrac(lia.lrac), m_hnf_cutter(lia), m_dio(lia), m_gcd(lia) {
            m_hnf_cut_period = settings().hnf_cut_period();
            m_dioph_eq_period = settings().m_dioph_eq_period;
        } 

        bool has_lower(unsigned j) const {
            switch (lrac.m_column_types()[j]) {
            case column_type::fixed:
            case column_type::boxed:
            case column_type::lower_bound:
                return true;
            default:
                return false;
            }
        }

        bool has_upper(unsigned j) const {
            switch (lrac.m_column_types()[j]) {
            case column_type::fixed:
            case column_type::boxed:
            case column_type::upper_bound:
                return true;
            default:
                return false;
            }
        }
        const impq& upper_bound(unsigned j) const {
            return lra.column_upper_bound(j);
        }
        
        const impq& lower_bound(unsigned j) const {
            return lra.column_lower_bound(j);
        }

        void patch_basic_column(unsigned v) {
            SASSERT(!lia.is_fixed(v));
            for (auto const& c : lra.basic2row(v))
                if (patch_basic_column_on_row_cell(v, c))
                    return;    
        }
        bool try_patch_column(unsigned v, unsigned j, mpq const& delta) {
            const auto & A = lra.A_r();
            if (delta < 0) {
                if (has_lower(j) && lia.get_value(j) + impq(delta) < lra.get_lower_bound(j))
                    return false;
            }
            else {
                if (lia.has_upper(j) && lia.get_value(j) + impq(delta) > lra.get_upper_bound(j))
                    return false;
            }
            for (auto const& c : A.column(j)) {
                unsigned row_index = c.var();
                unsigned bj = lrac.m_r_basis[row_index];
                auto old_val = lia.get_value(bj);
                auto new_val = old_val - impq(c.coeff()*delta);
                if (has_lower(bj) && new_val < lra.get_lower_bound(bj))
                    return false;
                if (has_upper(bj) && new_val > lra.get_upper_bound(bj))
                    return false;
                if (old_val.is_int() && !new_val.is_int()){
                    return false; // do not waste resources on this case
                }
                // if bj == v, then, because we are patching the lra.get_value(v),
                // we just need to assert that the lra.get_value(v) would be integral.
                lp_assert(bj != v || lra.from_model_in_impq_to_mpq(new_val).is_int());
            }
        
            lra.set_value_for_nbasic_column(j, lia.get_value(j) + impq(delta));
            return true;
        }

        
        unsigned random() {
            return settings().random_next();
        }

        bool all_columns_are_integral() const {
            for (lpvar j = 0; j < lra.number_of_vars(); j++)
                if (!lra.column_is_int(j))
                    return false;
            return true;
        }
        
        bool patch_basic_column_on_row_cell(unsigned v, row_cell<mpq> const& c) {
            if (v == c.var())
                return false;
            if (!lra.column_is_int(c.var()))  // could use real to patch integer
                return false;
            if (c.coeff().is_int())
                return false;
            mpq a = fractional_part(c.coeff());
            mpq r = fractional_part(lra.get_value(v));
            lp_assert(0 < r && r < 1);
            lp_assert(0 < a && a < 1);
            mpq delta_plus, delta_minus;
            if (!get_patching_deltas(r, a, delta_plus, delta_minus))
                return false;
            
            if (random() % 2) 
                return try_patch_column(v, c.var(), delta_plus) ||
                    try_patch_column(v, c.var(), delta_minus);
            else 
                return try_patch_column(v, c.var(), delta_minus) ||
                    try_patch_column(v, c.var(), delta_plus);
        }
        
        lia_move patch_basic_columns() {
            lia.settings().stats().m_patches++;
            lra.remove_fixed_vars_from_base();
            lp_assert(lia.is_feasible());
            for (unsigned j : lra.r_basis()) 
                if (!lra.get_value(j).is_int() && lra.column_is_int(j) && !lia.is_fixed(j))
                    patch_basic_column(j);
            if (!lra.has_inf_int()) {
                lia.settings().stats().m_patches_success++;
                return lia_move::sat;
            }
            return lia_move::undef;     
        }

        lia_move solve_dioph_eq() {
            lia_move r = m_dio.check();

            if (r == lia_move::conflict) {
                m_dio.explain(*this->m_ex);
                return lia_move::conflict;
            } else if (r == lia_move::branch)  {
                return lia_move::branch;
            } 
            return r;
        }

        lp_settings& settings() { return lra.settings(); }
        
        bool should_find_cube() {
            return m_number_of_calls % settings().m_int_find_cube_period == 0;
        }

        bool should_gomory_cut() {
            return (!settings().dio_eqs() || settings().dio_enable_gomory_cuts())
                && m_number_of_calls % settings().m_int_gomory_cut_period == 0;
        }

        bool should_solve_dioph_eq() {
            return lia.settings().dio_eqs() && m_number_of_calls % m_dioph_eq_period == 0;
        }

        // HNF

        bool should_hnf_cut() {
            return (!settings().dio_eqs() || settings().dio_enable_hnf_cuts())
                && settings().enable_hnf() && m_number_of_calls % settings().hnf_cut_period() == 0;
        }
        
        lia_move hnf_cut() {
            lia_move r = m_hnf_cutter.make_hnf_cut();
            if (r == lia_move::undef) 
                m_hnf_cut_period *= 2;
            else 
                m_hnf_cut_period = settings().hnf_cut_period();
            return r;
        }

        // Tighten bounds
        // expose at level of lar_solver so it can be invoked by theory_lra after back-jumping 
        // consider multi-round bound tightnening as well and deal with divergence issues.

        unsigned m_bounds_refine_depth = 0;

        lia_move tighten_bounds() {

            if (m_bounds_refine_depth > 10)
                return lia_move::undef;

            struct bound_consumer {
                imp& i;
                bound_consumer(imp& i) : i(i) {}
                lar_solver& lp() { return i.lra; }
                bool bound_is_interesting(unsigned vi, lp::lconstraint_kind kind, const rational& bval) const { return true; }
                bool add_eq(lpvar u, lpvar v, lp::explanation const& e, bool is_fixed) { return false; }
            };
            bound_consumer bc(*this);
            std_vector<implied_bound> ibounds;
            lp_bound_propagator<bound_consumer> bp(bc, ibounds);

            auto set_conflict = [&](u_dependency * d1, u_dependency * d2) {
                ++settings().stats().m_bounds_tightening_conflicts;
                for (auto e : lra.flatten(d1))
                    m_ex->push_back(e);
                for (auto e : lra.flatten(d2))
                    m_ex->push_back(e);
            };

            bool bounds_refined = false;
            auto refine_bound = [&](implied_bound const& ib) {
                unsigned j = ib.m_j;
                rational bound = ib.m_bound;
                if (ib.m_is_lower_bound) {
                    if (lra.column_is_int(j))
                        bound = ceil(bound);
                    if (lra.column_has_lower_bound(j) && lra.column_lower_bound(j) >= bound)
                        return l_undef;
                    auto d = ib.explain_implied();
                    if (lra.column_has_upper_bound(j) && lra.column_upper_bound(j) < bound) {
                        set_conflict(d, lra.get_column_upper_bound_witness(j));
                        return l_false;
                    }
                    lra.update_column_type_and_bound(j, ib.m_strict ? lconstraint_kind::GT : lconstraint_kind::GE, bound, d);                    
                } 
                else {
                    if (lra.column_is_int(j))
                        bound = floor(bound);
                    if (lra.column_has_upper_bound(j) && lra.column_upper_bound(j) <= bound)
                        return l_undef;
                    auto d = ib.explain_implied();
                    if (lra.column_has_lower_bound(j) && lra.column_lower_bound(j) > bound) {                        
                        set_conflict(d, lra.get_column_lower_bound_witness(j));
                        return l_false;
                    }
                    lra.update_column_type_and_bound(j, ib.m_strict ? lconstraint_kind::LT : lconstraint_kind::LE, bound, d);
                }
                ++settings().stats().m_bounds_tightenings;
                bounds_refined = true;
                return l_true;
            };

            for (unsigned row_index = 0; row_index < lra.row_count(); ++row_index) {
                bp.init();
                bound_analyzer_on_row<row_strip<mpq>, lp_bound_propagator<bound_consumer>>::analyze_row(
                    lra.A_r().m_rows[row_index],
                    zero_of_type<numeric_pair<mpq>>(),                    
                    bp);

                for (auto const& ib : ibounds)
                    if (l_false == refine_bound(ib))
                        return lia_move::conflict;
            }
            
            if (bounds_refined) {
                lra.trail().push(value_trail(m_bounds_refine_depth));
                ++m_bounds_refine_depth;
            }

            return bounds_refined  ? lia_move::continue_with_check : lia_move::undef;
        }

        
        lia_move check(lp::explanation * e) {
            SASSERT(lra.ax_is_correct());
            if (!lra.has_inf_int())
                return lia_move::sat;

            m_t.clear();
            m_k.reset();
            m_ex = e;
            m_ex->clear();
            m_upper = false;
        
            lia_move r = lia_move::undef;

            if (m_gcd.should_apply())
                r = m_gcd();

            check_return_helper pc(lra);

            if (settings().get_cancel_flag())
                return lia_move::undef;

            ++m_number_of_calls;
            if (r == lia_move::undef) r = patch_basic_columns();
            if (r == lia_move::undef && should_find_cube()) r = int_cube(lia)();
            if (r == lia_move::undef) lra.move_non_basic_columns_to_bounds();
            // if (r == lia_move::undef) r = tighten_bounds();
            if (r == lia_move::undef && should_hnf_cut()) r = hnf_cut();
            if (r == lia_move::undef && should_gomory_cut()) r = gomory(lia).get_gomory_cuts(2);
            if (r == lia_move::undef && should_solve_dioph_eq()) r = solve_dioph_eq();
            if (r == lia_move::undef) r = int_branch(lia)();
            if (settings().get_cancel_flag()) r = lia_move::undef;        
            return r;
        }

        bool cut_indices_are_columns() const {
            for (lar_term::ival p : m_t) {
                if (p.j() >= lra.A_r().column_count())
                    return false;
            }
            return true;
        }

        bool current_solution_is_inf_on_cut() const {
            SASSERT(cut_indices_are_columns());
            const auto & x = lrac.r_x();
            impq v = m_t.apply(x);
            mpq sign = m_upper ? one_of_type<mpq>()  : -one_of_type<mpq>();
            CTRACE("current_solution_is_inf_on_cut", v * sign <= impq(m_k) * sign,
                   tout << "m_upper = " << m_upper << std::endl;
                   tout << "v = " << v << ", k = " << m_k << std::endl;
                   tout << "term:";lra.print_term(m_t, tout) << "\n";
                );
            return v * sign > impq(m_k) * sign;
        }
        
        int select_int_infeasible_var() {
            int r_small_box = -1;
            int r_small_value = -1;
            int r_any_value = -1;
            unsigned n_small_box = 1;
            unsigned n_small_value = 1;
            unsigned n_any_value = 1;
            mpq range;
            mpq new_range;
            mpq small_value(1024);
            unsigned prev_usage = 0;

            auto add_column = [&](bool improved, int& result, unsigned& n, unsigned j) {
                if (result == -1)
                    result = j;
                else if (improved && ((random() % (++n)) == 0))
                    result = j;            
            };
        
            for (unsigned j : lra.r_basis()) {
                if (!column_is_int_inf(j))
                    continue;
                if (settings().get_cancel_flag()){
                    return -1;
                }
                SASSERT(!lia.is_fixed(j));

                unsigned usage = lra.usage_in_terms(j);
                if (lia.is_boxed(j) && (new_range = lra.bound_span_x(j) - rational(2*usage)) <= small_value) {

                    bool improved = new_range <= range || r_small_box == -1;
                    if (improved)
                        range = new_range;
                    add_column(improved, r_small_box, n_small_box, j);
                    continue;
                }
                impq const& value = lia.get_value(j);
                if (abs(value.x) < small_value ||
                    (lra.column_has_upper_bound(j) && small_value > upper_bound(j).x - value.x) ||
                    (has_lower(j) && small_value > value.x - lower_bound(j).x)) {
                    TRACE("int_solver", tout << "small j" << j << "\n");
                    add_column(true, r_small_value, n_small_value, j);
                    continue;
                }
                TRACE("int_solver", tout << "any j" << j << "\n");
                add_column(usage >= prev_usage, r_any_value, n_any_value, j);
                if (usage > prev_usage) 
                    prev_usage = usage;
            }

            if (r_small_box != -1 && (random() % 3 != 0))
                return r_small_box;
            if (r_small_value != -1 && (random() % 3) != 0)
                return r_small_value;
            if (r_any_value != -1)
                return r_any_value;
            if (r_small_box != -1)
                return r_small_box;
            return r_small_value;
        }

        std::ostream & display_row(std::ostream & out, lp::row_strip<rational> const & row) const {
            bool first = true;
            auto & rslv = lrac.m_r_solver;
            for (const auto &c : row) {
                if (lia.is_fixed(c.var())) {
                    if (!lia.get_value(c.var()).is_zero()) {
                        impq val = lia.get_value(c.var()) * c.coeff();
                        if (!first && val.is_pos())
                            out << "+";
                        if (val.y.is_zero())
                            out << val.x << " ";
                        else
                            out << val << " ";
                    }
                    first = false;
                    continue;
                }
                if (c.coeff().is_one()) {
                    if (!first)
                        out << "+";
                }
                else if (c.coeff().is_minus_one())
                    out << "-";
                else {
                    if (c.coeff().is_pos() && !first)
                        out << "+";
                    if (c.coeff().is_big())
                        out << " b*";
                    else
                        out << c.coeff();
                }
                out << rslv.column_name(c.var()) << " ";
                first = false;
            }
            out << "\n";
            for (const auto &c : row) {
                if (lia.is_fixed(c.var()))
                    continue;
                rslv.print_column_info(c.var(), out);
                if (lia.is_base(c.var()))
                    out << "j" << c.var() << " base\n";
            }
            return out;
        }


    };

    
    
    // clang-format on
    /**
     * \brief find integral and minimal, in the absolute values, deltas such that x - alpha*delta is integral too.
     */
    bool get_patching_deltas(const rational& x, const rational& alpha,
                             rational& delta_plus, rational& delta_minus) {
        auto a1 = numerator(alpha);
        auto a2 = denominator(alpha);
        auto x1 = numerator(x);
        auto x2 = denominator(x);
        if (!divides(x2, a2))
            return false;

        // delta has to be integral.
        // We need to find delta such that x1/x2 + (a1/a2)*delta is integral (we are going to flip the delta sign later).
        // Then a2*x1/x2 + a1*delta is integral, but x2 and x1 are coprime:
        // that means that t = a2/x2 is
        // integral. We established that a2 = x2*t Then x1 + a1*delta*(x2/a2)  = x1
        // + a1*(delta/t)  is integral. Taking into account that t and a1 are
        // coprime we have delta = t*k, where k is an integer.
        rational t = a2 / x2;
        // Now we have x1/x2 + (a1/x2)*k is integral, or (x1 + a1*k)/x2 is integral.
        // It is equivalent to x1 + a1*k = x2*m, where m is an integer
        // We know that a2 and a1 are coprime, and x2 divides a2, so x2 and a1 are
        // coprime. We can find u and v such that u*a1 + v*x2 = 1.
        rational u, v;
        gcd(a1, x2, u, v);
        lp_assert(gcd(a1, x2, u, v).is_one());
        lp_assert((x + (a1 / a2) * (-u * t) * x1).is_int());
        // 1 = (u- l*x2 ) * a1 + (v + l*a1)*x2, for every integer l.
        rational d = u * t * x1;
        // We can prove that x+alpha*d is integral,
        // and any other delta, satisfying x+alpha*delta, is equal to d modulo a2.
        delta_plus = mod(d, a2);
        lp_assert(delta_plus > 0);
        delta_minus = delta_plus - a2;
        lp_assert(delta_minus < 0);

        return true;
    }
    
        
    
    int_solver::int_solver(lar_solver& lar_slv) :
        lra(lar_slv),
        lrac(lra.m_mpq_lar_core_solver) {
        m_imp = alloc(imp, *this);
        lra.set_int_solver(this);
    }
    
    int_solver::~int_solver() { 
        dealloc(m_imp); 
    }
    
    
    lia_move int_solver::check(lp::explanation * e) {
        return m_imp->check(e);
    }

    
    std::ostream& int_solver::display_inf_rows(std::ostream& out) const {
        unsigned num = lra.A_r().column_count();
        for (unsigned v = 0; v < num; v++) {
            if (column_is_int(v) && !get_value(v).is_int()) {
                display_column(out, v);
            }
        }

        num = 0;
        for (unsigned i = 0; i < lra.A_r().row_count(); i++) {
            unsigned j = lrac.m_r_basis[i];
            if (column_is_int_inf(j)) {
                num++;
                lra.print_row(lra.A_r().m_rows[i], out);
                out << "\n";
            }
        }
        out << "num of int infeasible: " << num << "\n";
        return out;
    }


    u_dependency* int_solver::column_upper_bound_constraint(unsigned j) const {
        return lra.get_column_upper_bound_witness(j);
    }

    u_dependency* int_solver::column_lower_bound_constraint(unsigned j) const {
        return lra.get_column_lower_bound_witness(j);
    }

    unsigned int_solver::row_of_basic_column(unsigned j) const {
        return lra.row_of_basic_column(j);
    }

    lp_settings& int_solver::settings() {
        return lra.settings();
    }

    const lp_settings& int_solver::settings() const {
        return lra.settings();
    }

    bool int_solver::column_is_int(lpvar j) const {
        return lra.column_is_int(j);
    }

    bool int_solver::is_real(unsigned j) const {
        return !column_is_int(j);
    }

    bool int_solver::value_is_int(unsigned j) const {
        return lra.column_value_is_int(j);
    }

    bool int_solver::is_term(unsigned j) const {
        return lra.column_has_term(j);
    }

    unsigned int_solver::column_count() const  {
        return lra.column_count();
    }


    static void set_lower(impq & l, bool & inf_l, impq const & v ) {
        if (inf_l || v > l) {
            l = v;
            inf_l = false;
        }
    }

    static void set_upper(impq & u, bool & inf_u, impq const & v) {
        if (inf_u || v < u) {
            u = v;
            inf_u = false;
        }
    }

    // this function assumes that all basic columns dependend on j are feasible
    bool int_solver::get_freedom_interval_for_column(unsigned j, bool & inf_l, impq & l, bool & inf_u, impq & u, mpq & m) {
        if (lrac.m_r_heading[j] >= 0 || is_fixed(j)) // basic or fixed var
            return false;

        TRACE("random_update", display_column(tout, j) << ", is_int = " << column_is_int(j) << "\n";);
        impq const & xj = get_value(j);

        inf_l = true;
        inf_u = true;
        l = u = zero_of_type<impq>();
        m = mpq(1);

        if (has_lower(j)) 
            set_lower(l, inf_l, lower_bound(j) - xj);
    
        if (has_upper(j)) 
            set_upper(u, inf_u, upper_bound(j) - xj);
    

        const auto & A = lra.A_r();
        TRACE("random_update", tout <<  "m = " << m << "\n";);

        auto delta = [](mpq const& x, impq const& y, impq const& z) {
            if (x.is_one())
                return y - z;
            if (x.is_minus_one())
                return z - y;
            return (y - z) / x;
        };

        for (auto c : A.column(j)) {
            unsigned row_index = c.var();
            const mpq & a = c.coeff();
            unsigned i = lrac.m_r_basis[row_index];
            impq const & xi = get_value(i);
            lp_assert(lrac.m_r_solver.column_is_feasible(i));
            if (column_is_int(i) && !a.is_int() && xi.is_int()) 
                m = lcm(m, denominator(a));
        
            if (!inf_l && !inf_u && l == u) 
                continue;                        

            if (a.is_neg()) {
                if (has_lower(i)) 
                    set_lower(l, inf_l, delta(a, xi, lra.get_lower_bound(i)));
                if (has_upper(i)) 
                    set_upper(u, inf_u, delta(a, xi, lra.get_upper_bound(i)));
            }
            else {
                if (has_upper(i)) 
                    set_lower(l, inf_l, delta(a, xi, lra.get_upper_bound(i)));
                if (has_lower(i)) 
                    set_upper(u, inf_u, delta(a, xi, lra.get_lower_bound(i)));
            }
        }

        l += xj;
        u += xj;

        TRACE("freedom_interval",
              tout << "freedom variable for:\n";
              tout << lra.get_variable_name(j);
              tout << "[";
              if (inf_l) tout << "-oo"; else tout << l;
              tout << "; ";
              if (inf_u) tout << "oo";  else tout << u;
              tout << "]\n";
              tout << "val = " << get_value(j) << "\n";
              tout << "return " << (inf_l || inf_u || l <= u);
              );
        return (inf_l || inf_u || l <= u);
    }


    bool int_solver::is_feasible() const {
        lp_assert(
            lrac.m_r_solver.calc_current_x_is_feasible_include_non_basis() ==
            lrac.m_r_solver.current_x_is_feasible());
        return lrac.m_r_solver.current_x_is_feasible();
    }

    const impq & int_solver::get_value(unsigned j) const {
        return lrac.r_x(j);
    }

    std::ostream& int_solver::display_column(std::ostream & out, unsigned j) const {
        return lrac.m_r_solver.print_column_info(j, out);
    }

    bool int_solver::is_base(unsigned j) const {
        return lrac.m_r_heading[j] >= 0;
    }

    bool int_solver::is_boxed(unsigned j) const {
        return lrac.m_column_types[j] == column_type::boxed;
    }

    bool int_solver::is_fixed(unsigned j) const {
        return lrac.m_column_types[j] == column_type::fixed;
    }

    bool int_solver::is_free(unsigned j) const {
        return lrac.m_column_types[j] == column_type::free_column;
    }

    bool int_solver::at_bound(unsigned j) const {
        auto & mpq_solver = lrac.m_r_solver;
        switch (mpq_solver.m_column_types[j] ) {
        case column_type::fixed:
        case column_type::boxed:
            return
                mpq_solver.m_lower_bounds[j] == get_value(j) ||
                mpq_solver.m_upper_bounds[j] == get_value(j);
        case column_type::lower_bound:
            return mpq_solver.m_lower_bounds[j] == get_value(j);
        case column_type::upper_bound:
            return  mpq_solver.m_upper_bounds[j] == get_value(j);
        default:
            return false;
        }
    }

    bool int_solver::at_lower(unsigned j) const {
        auto & mpq_solver = lrac.m_r_solver;
        switch (mpq_solver.m_column_types[j] ) {
        case column_type::fixed:
        case column_type::boxed:
        case column_type::lower_bound:
            return mpq_solver.m_lower_bounds[j] == get_value(j);
        default:
            return false;
        }
    }

    bool int_solver::at_upper(unsigned j) const {
        auto & mpq_solver = lrac.m_r_solver;
        switch (mpq_solver.m_column_types[j] ) {
        case column_type::fixed:
        case column_type::boxed:
        case column_type::upper_bound:
            return mpq_solver.m_upper_bounds[j] == get_value(j);
        default:
            return false;
        }
    }

    
    std::ostream& int_solver::display_row_info(std::ostream & out, unsigned row_index) const  {    
        auto & rslv = lrac.m_r_solver;
        auto const& row = rslv.m_A.m_rows[row_index];
        return display_row(out, row);
    }

    std::ostream & int_solver::display_row(std::ostream & out, std_vector<row_cell<rational>> const & row) const {
        return m_imp->display_row(out, row);
}
    
    bool int_solver::shift_var(unsigned j, unsigned range) {
        if (is_fixed(j) || is_base(j))
            return false;
        if (settings().get_cancel_flag())
            return false;
        bool inf_l = false, inf_u = false;
        impq l, u;
        mpq m;
        if (!get_freedom_interval_for_column(j, inf_l, l, inf_u, u, m))
            return false;
        if (settings().get_cancel_flag())
            return false;
        const impq & x = get_value(j);
        // x, the value of j column, might be shifted on a multiple of m

        if (inf_l && inf_u) {
            impq new_val = m * impq(lra.settings().random_next() % (range + 1)) + x;
            lra.set_value_for_nbasic_column(j, new_val);
            return true;
        }
        if (column_is_int(j)) {
            if (!inf_l) 
                l = impq(ceil(l));
            if (!inf_u) 
                u = impq(floor(u));
        }
        if (!inf_l && !inf_u && l >= u)
            return false;


        if (inf_u) {
            SASSERT(!inf_l);
            impq new_val = x + m * impq(lra.settings().random_next() % (range + 1));
            lra.set_value_for_nbasic_column(j, new_val);
            return true;
        }

        if (inf_l) {
            SASSERT(!inf_u);
            impq new_val = x - m * impq(lra.settings().random_next() % (range + 1));
            lra.set_value_for_nbasic_column(j, new_val);
            return true;
        }

        SASSERT(!inf_l && !inf_u);
        // The shift has to be a multiple of m: let us look for s, such that the shift is m*s.
        // We have new_val = x+m*s <= u, so m*s <= u-x and, finally, s <= floor((u- x)/m) = a
        // The symmetric reasoning gives us s >= ceil((l-x)/m) = b
        // We randomly pick s in the segment [b, a]
        mpq a = floor((u - x) / m);
        mpq b = ceil((l - x) / m);
        mpq r = a - b;
        if (!r.is_pos())
            return false;
        TRACE("int_solver", tout << "a = " << a << ", b = " << b << ", r = " << r<< ", m = " << m << "\n";);
        if (r < mpq(range))
            range = static_cast<unsigned>(r.get_uint64());

        mpq s = b + mpq(lra.settings().random_next() % (range + 1));
        impq new_val = x + m * impq(s);
        TRACE("int_solver", tout << "new_val = " << new_val << "\n";);
        SASSERT(l <= new_val && new_val <= u);
        lra.set_value_for_nbasic_column(j, new_val);
        return true;
    }



    void int_solver::simplify(std::function<bool(unsigned)>& is_root) {
        return;

#if 0

        // in-processing simplification can go here, such as bounds improvements.

        if (!lra.is_feasible()) {
            lra.find_feasible_solution();
            if (!lra.is_feasible())
                return;
        }

        
        lp::explanation exp;
        m_ex = &exp;
        m_t.clear();
        m_k.reset();

        if (has_inf_int()) 
            local_gomory(5);            

        stopwatch sw;
        explanation exp1, exp2;

        // 
        // identify equalities
        //

        m_equalities.reset();
        map<rational, unsigned_vector, rational::hash_proc, rational::eq_proc> value2roots;

        vector<std::pair<lp::mpq, unsigned>> coeffs;        
        coeffs.push_back({-rational::one(), 0});
        coeffs.push_back({rational::one(), 0});

        num_checks = 0;

        // make sure values are sampled with respect to the same state of the Simplex.
        vector<rational> values;
        for (lpvar j = 0; j < lra.column_count(); ++j) 
            values.push_back(get_value(j).x);

        sw.reset();
        sw.start();
        start = random();
        for (lpvar j0 = 0; j0 < lra.column_count(); ++j0) {
            lpvar j = (j0 + start) % lra.column_count();
            if (is_fixed(j))
                continue;
            if (!lra.column_is_int(j))
                continue;
            if (!is_root(j))
                continue;
            rational value = values[j];
            if (!value2roots.contains(value)) {
                unsigned_vector vec;
                vec.push_back(j);
                value2roots.insert(value, vec);
                continue;
            }
            auto& roots = value2roots.find(value);
            bool has_eq = false;
            //
            // Super inefficient check. There are better ways.
            // 1. call into equality finder:
            // the cheap equality finder can also be used.
            // 2. value sweeping:
            // update partitions of values based on feasible tableaus
            // instead of having just the values vector use the values 
            // collected when the find_feasible_solution succeeds with
            // a new assignment. 
            // 3. a more expensive equality finder:
            // use the tableau to extract equalities from tight rows.
            // If x = y is implied, there is a set of rows that link x and y
            // and such that the variables are at their bounds.
            // 4. retain information between calls:
            // If simplification is invoked at the same backtracking level (or above)
            // form the previous call and it is established that x <= y (but not x == y), then no need to
            // recheck the inequality x <= y.
            for (auto k : roots) {
                bool le = false, ge = false;
                u_dependency* dep = nullptr;
                lra.push();
                coeffs[0].second = j;
                coeffs[1].second = k;
                lp::lpvar term_index = lra.add_term(coeffs, UINT_MAX);
                term_index = lra.map_term_index_to_column_index(term_index);
                lra.push();
                lra.update_column_type_and_bound(term_index, lp::lconstraint_kind::GE, mpq(1), nullptr);
                lra.find_feasible_solution();
                if (!lra.is_feasible()) {
                    lra.get_infeasibility_explanation(exp1);
                    le = true;
                }
                lra.pop(1);
                ++num_checks;
                if (le) {
                    lra.push();
                    lra.update_column_type_and_bound(term_index, lp::lconstraint_kind::LE, mpq(-1), nullptr);
                    lra.find_feasible_solution();
                    if (!lra.is_feasible()) {
                        lra.get_infeasibility_explanation(exp2);
                        exp1.add_expl(exp2);
                        ge = true;           
                    }                             
                    lra.pop(1);
                    ++num_checks;
                }
                lra.pop(1);
                if (le && ge) {
                    has_eq = true;
                    m_equalities.push_back({j, k, exp1});
                    break;
                }
                // artificial throttle.
                if (num_checks > 10000)
                    break;
            }
            if (!has_eq) 
                roots.push_back(j);

            // artificial throttle.
            if (num_checks > 10000)
                break;
        }

        sw.stop();
        std::cout << "equalities " << m_equalities.size() << " num checks " << num_checks << " time: " << sw.get_seconds() << "\n";
        std::cout.flush();

        //
        // Cuts? Eg. for 0-1 variables or bounded integers?
        // 

#endif
    }
    lar_term const& int_solver::get_term() const { return m_imp->m_t; }
    lar_term & int_solver::get_term() { return m_imp->m_t; }
    mpq const& int_solver::offset() const  { return m_imp->m_k; }
    mpq & int_solver::offset() { return m_imp->m_k; }
    
    bool int_solver::is_upper() const { return m_imp->m_upper; }
    bool& int_solver::is_upper() { return m_imp->m_upper; }
    explanation* int_solver::expl() { return m_imp->m_ex; }
    void int_solver::set_expl(lp::explanation * ex) { m_imp->m_ex = ex; }
    bool int_solver::column_is_int_inf(unsigned j) const {
        return m_imp->column_is_int_inf(j);
    }
    
    bool int_solver::has_lower(unsigned j) const {
        return m_imp->has_lower(j);
    }

    bool int_solver::has_upper(unsigned j) const {
        return m_imp->has_upper(j);
    }

    int int_solver::select_int_infeasible_var() { return m_imp->select_int_infeasible_var(); }
    bool int_solver::current_solution_is_inf_on_cut() const { return m_imp->current_solution_is_inf_on_cut(); }
    const impq & int_solver::lower_bound(unsigned j) const { return m_imp->lower_bound(j);}
    const impq & int_solver::upper_bound(unsigned j) const { return m_imp->upper_bound(j);}
    #if Z3DEBUG
    lia_move int_solver::dio_test() {return m_imp->solve_dioph_eq();}
    #endif
}
