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Merge pull request #36 from scipopt/issue-32-linexpr-ctors
Add new c'tors to LinExpr
2 parents 4e25acc + f9678e5 commit f547796

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‎.github/workflows/main.yml‎

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@@ -41,7 +41,7 @@ jobs:
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verbose: true # optional (default = false)
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fail_ci_if_error: true
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test_release_win:
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runs-on: windows-2019
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runs-on: windows-2022
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steps:
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- uses: actions/checkout@v3
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- uses: turtlebrowser/get-conan@main

‎changelog.md‎

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@@ -10,6 +10,18 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## Added
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- [PR36](https://github.com/scipopt/SCIPpp/pull/36)
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New c'tors for `LinExpr` to allow use-cases like
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```cpp
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const Var& [x1, x2] = ...
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const array A_VARS = ...
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const vector V_VARS = ...
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LinExpr le(A_VARS); // new c'tor for std::array
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le += V_VARS; // new c'tor for std::vector
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le += {x1, x2}; // new c'tor for std::initializer_list
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// all of them also available with a second argument for coefficients
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```
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- [PR31](https://github.com/scipopt/SCIPpp/pull/31) Add `InitialSolution` and `Model::addSolution`.
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- [PR28](https://github.com/scipopt/SCIPpp/pull/28) Add `Var::getVar`.
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‎include/scippp/lin_expr.hpp‎

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@@ -1,9 +1,14 @@
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#pragma once
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#include <array>
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#include <vector>
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#include "scippp/var.hpp"
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// just for tests, see test_linexpr.cpp
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namespace LinExpression { // NOLINT(readability-identifier-naming)
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struct CheckInternalsUsingFriendStruct;
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}
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namespace scippp {
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/**
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*/
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class LinExpr {
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friend class Model;
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friend struct LinExpression::CheckInternalsUsingFriendStruct; // just for tests, see test_linexpr.cpp
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//! Constant term.
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double m_constant { 0.0 };
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//! Variables in the linear combination.
@@ -39,12 +45,67 @@ class LinExpr {
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{
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}
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/**
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* Creates a linear expression with zero as constant the given variable with coefficient one.
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* Creates a linear expression with zero as constant and the given variable with coefficient one.
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* @since 1.0.0
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* @remark This is on purpose not an explicit c'tor to allow expressions like x <= 1.
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* @remark This is on purpose not an explicit c'tor to allow expressions like <code>x <= 1</code>.
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* @param var Variable to store with coefficient one in the expression.
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*/
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LinExpr(const Var& var);
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/**
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* Creates a linear expression with zero as constant and the given variables with coefficient one.
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* @since 1.3.0
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* @remark This is on purpose not an explicit c'tor to allow expressions like <code>... + {x1, x2}</code>.
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* @param vars Variables to store with coefficient one in the expression.
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*/
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LinExpr(std::initializer_list<Var> vars);
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/**
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* Creates a linear expression with zero as constant and the given variables with the provided coefficients.
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* @since 1.3.0
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* @param vars Variables to store in the expression.
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* @param coeffs Coefficients to store in the expression.
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* @pre \p vars and \p coeffs have the same length.
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*/
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LinExpr(std::initializer_list<Var> vars, std::initializer_list<double> coeffs);
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/**
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* @copybrief LinExpr(std::initializer_list<Var>)
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* @since 1.3.0
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* @remark This is on purpose not an explicit c'tor to allow expressions like <code>... + vars</code>.
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* @tparam N Size of the array \p vars.
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* @param vars Variables to store with coefficient one in the expression.
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*/
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template <std::size_t N>
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LinExpr(const std::array<Var, N>& vars)
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: m_vars { vars.begin(), vars.end() }
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, m_coeffs(vars.size(), 1)
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{
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}
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/**
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* @copybrief LinExpr(std::initializer_list<Var>, std::initializer_list<double>)
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* @since 1.3.0
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* @tparam N Size of the arrays \p vars and \p coeffs.
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* @param vars Variables to store in the expression.
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* @param coeffs Coefficients to store in the expression.
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*/
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template <std::size_t N>
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LinExpr(const std::array<Var, N>& vars, std::array<double, N>& coeffs)
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: m_vars { vars.begin(), vars.end() }
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, m_coeffs { coeffs.begin(), coeffs.end() }
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{
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}
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/**
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* @copybrief LinExpr(std::initializer_list<Var>)
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* @since 1.3.0
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* @remark This is on purpose not an explicit c'tor to allow expressions like <code>... + vars</code>.
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* @param vars Variables to store with coefficient one in the expression.
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*/
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LinExpr(const std::vector<Var>& vars);
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/**
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* @copybrief LinExpr(std::initializer_list<Var>, std::initializer_list<double>)
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* @since 1.3.0
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* @param vars Variables to store in the expression.
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* @param coeffs Coefficients to store in the expression.
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*/
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LinExpr(const std::vector<Var>& vars, const std::vector<double>& coeffs);
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/**
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* Returns the constant term of the expression.

‎source/lin_expr.cpp‎

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#include "scippp/lin_expr.hpp"
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#include <cassert>
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namespace scippp {
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LinExpr::LinExpr(const Var& var)
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{
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}
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LinExpr::LinExpr(std::initializer_list<Var> vars)
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: m_vars { vars }
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, m_coeffs(vars.size(), 1)
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{
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}
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LinExpr::LinExpr(std::initializer_list<Var> vars, std::initializer_list<double> coeffs)
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: m_vars { vars }
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, m_coeffs { coeffs }
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{
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assert(vars.size() == coeffs.size()); // GCOVR_EXCL_LINE
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}
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LinExpr::LinExpr(const std::vector<Var>& vars)
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: m_vars { vars }
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, m_coeffs(vars.size(), 1)
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{
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}
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LinExpr::LinExpr(const std::vector<Var>& vars, const std::vector<double>& coeffs)
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: m_vars { vars }
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, m_coeffs { coeffs }
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{
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assert(vars.size() == coeffs.size()); // GCOVR_EXCL_LINE
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}
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double LinExpr::getConstant() const
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{
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return m_constant;

‎test/test_linexpr.cpp‎

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#include <boost/test/unit_test.hpp>
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#include <algorithm>
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#include "scippp/model.hpp"
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#include "scippp/solving_statistics.hpp"
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using namespace scippp;
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using namespace std;
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BOOST_AUTO_TEST_SUITE(LinExpression)
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BOOST_AUTO_TEST_CASE(AddOneVar)
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{
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Model model("Simple");
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array coeff { 1, 1 };
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const auto& [x1, x2] = model.addVars<2>("x_", coeff);
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LinExpr l;
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l += x1; // allocates memory, thus slow
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l += x2; // allocates memory again, thus slow
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model.addConstr(l <= 1, "capacity");
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model.setObjsense(Sense::MAXIMIZE);
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model.solve();
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BOOST_TEST(model.getSolvingStatistic(statistics::PRIMALBOUND) == 1);
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}
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BOOST_AUTO_TEST_CASE(CtorArray)
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{
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array objCoeff { 1.0, 1.0 };
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Model m1("m1");
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const auto VARS1 = m1.addVars<2>("x_", objCoeff);
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LinExpr l1(VARS1);
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m1.addConstr(l1 <= 1, "capacity");
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m1.setObjsense(Sense::MAXIMIZE);
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m1.solve();
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BOOST_TEST(m1.getSolvingStatistic(statistics::PRIMALBOUND) == 1.0);
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Model m2("m2");
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const auto VARS2 = m2.addVars<2>("x_", objCoeff);
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LinExpr l2(VARS2, objCoeff); // same as before, but different c'tor
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m2.addConstr(l2 <= 1, "capacity");
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m2.setObjsense(Sense::MAXIMIZE);
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m2.solve();
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BOOST_TEST(m2.getSolvingStatistic(statistics::PRIMALBOUND) == 1.0);
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const double FAC { 2.0 };
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array constrCoeff { FAC, FAC };
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Model m3("m3");
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const auto VARS3 = m3.addVars<2>("x_", objCoeff);
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LinExpr l3(VARS3, constrCoeff);
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m3.addConstr(l3 <= 1, "capacity");
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m3.setObjsense(Sense::MAXIMIZE);
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m3.solve();
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BOOST_TEST(m3.getSolvingStatistic(statistics::PRIMALBOUND) == 1.0 / FAC);
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}
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BOOST_AUTO_TEST_CASE(AddArray)
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{
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Model model("Simple");
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array coeff { 1, 1 };
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const auto VARS = model.addVars<2>("x_", coeff);
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LinExpr l;
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l += VARS;
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model.addConstr(l <= 1, "capacity");
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model.setObjsense(Sense::MAXIMIZE);
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model.solve();
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BOOST_TEST(model.getSolvingStatistic(statistics::PRIMALBOUND) == 1);
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}
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BOOST_AUTO_TEST_CASE(AddVector)
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{
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Model model("Simple");
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array coeff { 1, 1 };
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const auto A_VARS { model.addVars<2>("x_", coeff) };
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const vector<Var> VARS { A_VARS.begin(), A_VARS.end() };
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LinExpr l1;
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l1 += VARS;
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model.addConstr(l1 <= 1, "capacity1");
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LinExpr l2(VARS, vector { 2.0, 2.0 });
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model.addConstr(l2 <= 2, "capacity2"); // duplicate, but different c'tor
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model.setObjsense(Sense::MAXIMIZE);
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model.solve();
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BOOST_TEST(model.getSolvingStatistic(statistics::PRIMALBOUND) == 1);
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}
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BOOST_AUTO_TEST_CASE(AddInitializerList)
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{
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Model model("Simple");
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array coeff { 1, 1 };
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const auto& [x1, x2] = model.addVars<2>("x_", coeff);
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LinExpr l;
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l += { x1, x2 };
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model.addConstr(l <= 1, "capacity");
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// duplicate, but different c'tor:
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model.addConstr(LinExpr({ x1, x2 }, { 2.0, 2.0 }) <= 2, "capacity2");
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model.setObjsense(Sense::MAXIMIZE);
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model.solve();
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BOOST_TEST(model.getSolvingStatistic(statistics::PRIMALBOUND) == 1);
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}
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BOOST_AUTO_TEST_CASE(CheckInternalsUsingFriendStruct)
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{
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const double VAL { 2.0 };
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for (size_t num { 1 }; num < 4; ++num) {
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Model m("m");
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const auto VARS = m.addVars("x", num);
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LinExpr lDef(VARS);
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BOOST_TEST(lDef.getConstant() == 0);
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BOOST_TEST(lDef.m_constant == 0);
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BOOST_TEST(lDef.m_vars.size() == num);
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BOOST_TEST(lDef.m_coeffs.size() == num);
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BOOST_TEST(all_of(lDef.m_coeffs.begin(), lDef.m_coeffs.end(), [](double d) { return d == 1; }));
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const vector COEFF(num, VAL);
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LinExpr lCoeff(VARS, COEFF);
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BOOST_TEST(lCoeff.getConstant() == 0);
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BOOST_TEST(lCoeff.m_constant == 0);
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BOOST_TEST(lCoeff.m_vars.size() == num);
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BOOST_TEST(lCoeff.m_coeffs.size() == num);
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BOOST_TEST(all_of(lCoeff.m_coeffs.begin(), lCoeff.m_coeffs.end(), [&VAL](double d) { return d == VAL; }));
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}
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}
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BOOST_AUTO_TEST_SUITE_END()

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