z3-z3-4.13.0.src.math.lp.lar_term.h Maven / Gradle / Ivy
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/*++
Copyright (c) 2017 Microsoft Corporation
Module Name:
Abstract:
Author:
Lev Nachmanson (levnach)
Revision History:
--*/
#pragma once
#include "math/lp/indexed_vector.h"
#include "util/map.h"
namespace lp {
// represents a linear expressieon
class lar_term {
typedef unsigned lpvar;
u_map m_coeffs;
// the column index related to the term
lpvar m_j = -1;
public:
// the column index related to the term
lpvar j() const { return m_j; }
lpvar& j() { return m_j; }
void add_monomial(const mpq& c, unsigned j) {
if (c.is_zero())
return;
auto *e = m_coeffs.find_core(j);
if (e == nullptr) {
m_coeffs.insert(j, c);
} else {
e->get_data().m_value += c;
if (e->get_data().m_value.is_zero())
m_coeffs.erase(j);
}
}
void add_var(lpvar j) {
rational c(1);
add_monomial(c, j);
}
bool is_empty() const {
return m_coeffs.empty(); // && is_zero(m_v);
}
unsigned size() const { return static_cast(m_coeffs.size()); }
u_map const & coeffs() const {
return m_coeffs;
}
void subst_by_term(const lar_term& t, unsigned term_column) {
auto it = this->m_coeffs.find_core(term_column);
if (it == nullptr) return;
mpq a = it->get_data().m_value;
this->m_coeffs.erase(term_column);
for (auto p : t) {
this->add_monomial(a * p.coeff(), p.j());
}
}
// constructors
lar_term() {}
lar_term(const vector>& coeffs) {
for (auto const& p : coeffs) {
add_monomial(p.first, p.second);
}
}
lar_term(lpvar v1, lpvar v2) {
add_monomial(rational::one(), v1);
add_monomial(rational::one(), v2);
}
lar_term(lpvar v1) {
add_monomial(rational::one(), v1);
}
lar_term(rational const& a, lpvar v1) {
add_monomial(a, v1);
}
lar_term(lpvar v1, rational const& b, lpvar v2) {
add_monomial(rational::one(), v1);
add_monomial(b, v2);
}
lar_term(rational const& a, lpvar v1, rational const& b, lpvar v2) {
add_monomial(a, v1);
add_monomial(b, v2);
}
bool operator==(const lar_term & a) const { return false; } // take care not to create identical terms
bool operator!=(const lar_term & a) const { return ! (*this == a);}
// some terms get used in add constraint
// it is the same as the offset in the m_constraints
vector> coeffs_as_vector() const {
vector> ret;
for (const auto & [c, v] : m_coeffs)
ret.push_back({v, c});
return ret;
}
// j is the basic variable to substitute
void subst_in_row(unsigned j, indexed_vector & li) {
auto* it = m_coeffs.find_core(j);
if (it == nullptr) return;
const mpq & b = it->get_data().m_value;
for (unsigned it_j :li.m_index) {
add_monomial(- b * li.m_data[it_j], it_j);
}
m_coeffs.erase(j);
}
// the monomial ax[j] is substituted by ax[k]
void subst_index(unsigned j, unsigned k) {
auto* it = m_coeffs.find_core(j);
if (it == nullptr) return;
mpq b = it->get_data().m_value;
m_coeffs.erase(j);
m_coeffs.insert(k, b);
}
bool contains(unsigned j) const {
return m_coeffs.contains(j);
}
void negate() {
for (auto & t : m_coeffs)
t.m_value.neg();
}
template
T apply(const vector& x) const {
T ret(0);
for (const auto & t : m_coeffs) {
ret += t.m_value * x[t.m_key];
}
return ret;
}
lar_term& operator*=(mpq const& k) {
for (auto & t : m_coeffs)
t.m_value *= k;
return *this;
}
void clear() {
m_coeffs.reset();
}
class ival {
lpvar m_var;
const mpq & m_coeff;
public:
ival(lpvar var, const mpq & val) : m_var(var), m_coeff(val) { }
lpvar j() const { return m_var; }
const mpq & coeff() const { return m_coeff; }
};
class const_iterator {
u_map::iterator m_it;
public:
ival operator*() const { return ival(m_it->m_key, m_it->m_value); }
const_iterator operator++() { const_iterator i = *this; m_it++; return i; }
const_iterator operator++(int) { m_it++; return *this; }
const_iterator(u_map::iterator it) : m_it(it) {}
bool operator==(const const_iterator &other) const { return m_it == other.m_it; }
bool operator!=(const const_iterator &other) const { return !(*this == other); }
};
bool is_normalized() const {
lpvar min_var = -1;
mpq c;
for (ival p : *this) {
if (p.j() < min_var) {
min_var = p.j();
}
}
lar_term r;
for (ival p : *this) {
if (p.j() == min_var) {
return p.coeff().is_one();
}
}
UNREACHABLE();
return false;
}
// a is the coefficient by which we divided the term to normalize it
lar_term get_normalized_by_min_var(mpq& a) const {
if (m_coeffs.empty()) {
a = mpq(1, 1);
return *this;
}
a = m_coeffs.begin()->m_value;
if (a.is_one()) {
return *this;
}
lar_term r;
auto it = m_coeffs.begin();
r.add_var(it->m_key);
it++;
for(;it != m_coeffs.end(); it++) {
r.add_monomial(it->m_value / a, it->m_key);
}
return r;
}
const_iterator begin() const { return m_coeffs.begin();}
const_iterator end() const { return m_coeffs.end(); }
};
}