<filename>optlang/tests/abstract_test_cases.py
# Copyright 2016 Novo Nordisk Foundation Center for Biosustainability,
# Technical University of Denmark.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import division

import abc
import unittest

import six
from optlang import interface
from optlang import symbolics
import optlang
import pickle
import json
import copy
import os
import sympy
from functools import partial

__test__ = False

TESTMODELPATH = os.path.join(os.path.dirname(__file__), 'data/model.json')
TESTMILPMODELPATH = os.path.join(os.path.dirname(__file__), 'data/simple_milp.json')


@six.add_metaclass(abc.ABCMeta)
class AbstractVariableTestCase(unittest.TestCase):
    @unittest.skip('Abstract test method not implemented.')
    def test_magic(self):
        pass

    def setUp(self):
        self.var = self.interface.Variable('test')
        self.model = self.interface.Model()

    def test_set_wrong_type_raises(self):
        self.assertRaises(ValueError, self.interface.Variable, name="test", type="mayo")
        self.assertRaises(Exception, setattr, self.var, 'type', 'ketchup')
        self.model.add(self.var)
        self.model.update()
        self.assertRaises(ValueError, setattr, self.var, "type", "mustard")
        self.var.type = "integer"
        self.assertEqual(self.var.type, "integer")

    def test_change_type(self):
        var = self.interface.Variable("test")
        var.type = "binary"
        self.assertEqual(var.type, "binary")

    def test_change_name(self):
        self.model.add(self.var)
        self.model.update()
        self.var.name = "test_2"
        self.assertEqual(self.var.name, "test_2")
        self.assertEqual(str(self.var), self.var.name)
        self.model.remove(self.var)
        self.model.update()

    def test_non_string_name_raises(self):
        for name in [2, None, True, ["name1", "name2"]]:
            with self.assertRaises(TypeError):
                self.interface.Variable(name)

    @abc.abstractmethod
    def test_get_primal(self):
        pass

    def test_get_dual(self):
        with open(TESTMODELPATH) as infile:
            model = self.interface.Model.from_json(json.load(infile))
        model.optimize()
        self.assertEqual(model.status, 'optimal')
        self.assertAlmostEqual(model.objective.value, 0.8739215069684305)
        self.assertTrue(isinstance(model.variables[0].dual, float))

    def test_setting_lower_bound_higher_than_upper_bound_raises(self):
        self.model.add(self.var)
        self.var.ub = 0
        self.assertRaises(ValueError, setattr, self.model.variables[0], 'lb', 100.)

    def test_setting_nonnumerical_bounds_raises(self):
        self.assertRaises(TypeError, setattr, self.var, "lb", "Minestrone")
        self.assertRaises(TypeError, setattr, self.var, "ub", "Minestrone")
        self.model.add(self.var)
        self.assertRaises(TypeError, setattr, self.model.variables[0], 'lb', 'Chicken soup')
        self.assertRaises(TypeError, setattr, self.model.variables[0], 'ub', 'Chicken soup')

    @abc.abstractmethod
    def test_changing_variable_names_is_reflected_in_the_solver(self):
        pass

    def test_setting_bounds(self):
        self.var.ub = 5
        self.model.objective = self.interface.Objective(self.var)
        self.model.optimize()
        self.assertEqual(self.var.primal, 5)
        self.var.ub = 4
        self.model.optimize()
        self.assertEqual(self.var.primal, 4)
        self.var.lb = -3
        self.model.objective.direction = "min"
        self.model.optimize()
        self.assertEqual(self.var.primal, -3)
        self.var.lb = sympy.Number(-4)  # Sympy numbers should be valid bounds
        self.model.optimize()
        self.assertEqual(self.var.primal, -4)

    def test_set_bounds_method(self):
        var = self.interface.Variable("test", lb=-10)
        c = self.interface.Constraint(var, lb=-100)
        model = self.interface.Model()
        obj = self.interface.Objective(var)
        model.add(c)
        model.objective = obj

        for lb, ub in ((1, 10), (-1, 5), (11, 12)):
            obj.direction = "max"
            var.set_bounds(lb, ub)
            model.optimize()
            self.assertAlmostEqual(var.primal, ub)
            obj.direction = "min"
            model.optimize()
            self.assertAlmostEqual(var.primal, lb)

        var.set_bounds(None, 0)
        model.optimize()
        self.assertAlmostEqual(var.primal, -100)

        obj.direction = "max"
        var.set_bounds(1, None)
        self.assertEqual(model.optimize(), optlang.interface.UNBOUNDED)

        self.assertRaises(ValueError, var.set_bounds, 2, 1)

    def test_set_bounds_to_none(self):
        model = self.model
        var = self.var
        model.objective = self.interface.Objective(var)
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        var.ub = 10
        self.assertEqual(model.optimize(), interface.OPTIMAL)
        var.ub = None
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        self.model.objective.direction = "min"
        var.lb = -10
        self.assertEqual(model.optimize(), interface.OPTIMAL)
        var.lb = None
        self.assertEqual(model.optimize(), interface.UNBOUNDED)

    def test_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.interface.Variable("")
        with self.assertRaises(Exception):
            self.interface.Variable("This space")
        with self.assertRaises(Exception):
            self.interface.Variable("This\ttab")

    def test_new_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.var.name = ""
        with self.assertRaises(Exception):
            self.var.name = "This space"
        with self.assertRaises(Exception):
            self.var.name = "This\ttab"

        self.assertEqual(self.var.name, 'test')


@six.add_metaclass(abc.ABCMeta)
class AbstractConstraintTestCase(unittest.TestCase):

    def setUp(self):
        with open(TESTMODELPATH) as infile:
            self.model = self.interface.Model.from_json(json.load(infile))
        self.constraint = self.interface.Constraint(
            self.interface.Variable('chip') + self.interface.Variable('chap'),
            name='woodchips',
            lb=100
        )

    def test_indicator_constraint_support(self):
        if self.interface.Constraint._INDICATOR_CONSTRAINT_SUPPORT:
            constraint = self.interface.Constraint(
                self.interface.Variable('chip_2'),
                indicator_variable=self.interface.Variable('chip', type='binary'), active_when=0, lb=0,
                ub=0,
                name='indicator_constraint_fwd_1'
            )
            model = self.interface.Model()
            model.add(constraint)
            model.update()
            self.assertEqual(constraint.problem, model)
            self.assertIn(constraint, model.constraints)
            model.remove(constraint.name)
            model.update()
            self.assertEqual(constraint.problem, None)
            self.assertNotIn(constraint, model.constraints)
        else:
            self.assertRaises(
                optlang.exceptions.IndicatorConstraintsNotSupported,
                self.interface.Constraint,
                self.interface.Variable('chip') + self.interface.Variable('chap'),
                indicator_variable=self.interface.Variable('indicator', type='binary')
            )

    @abc.abstractmethod
    def test_get_primal(self):
        pass

    def test_get_dual(self):
        self.assertEqual(self.constraint.dual, None)
        self.model.optimize()
        self.assertEqual(self.model.status, 'optimal')
        self.assertAlmostEqual(self.model.objective.value, 0.8739215069684305)
        self.assertTrue(isinstance(self.model.constraints[0].dual, float))

    def test_change_constraint_name(self):
        constraint = self.interface.Constraint.clone(self.constraint)
        self.assertEqual(constraint.name, 'woodchips')
        constraint.name = 'ketchup'
        self.assertEqual(constraint.name, 'ketchup')
        self.assertEqual([constraint.name for constraint in self.model.constraints],
                         ['M_13dpg_c', 'M_2pg_c', 'M_3pg_c', 'M_6pgc_c', 'M_6pgl_c', 'M_ac_c', 'M_ac_e',
                          'M_acald_c', 'M_acald_e', 'M_accoa_c', 'M_acon_C_c', 'M_actp_c', 'M_adp_c', 'M_akg_c',
                          'M_akg_e', 'M_amp_c', 'M_atp_c', 'M_cit_c', 'M_co2_c', 'M_co2_e', 'M_coa_c', 'M_dhap_c',
                          'M_e4p_c', 'M_etoh_c', 'M_etoh_e', 'M_f6p_c', 'M_fdp_c', 'M_for_c', 'M_for_e', 'M_fru_e',
                          'M_fum_c', 'M_fum_e', 'M_g3p_c', 'M_g6p_c', 'M_glc_D_e', 'M_gln_L_c', 'M_gln_L_e',
                          'M_glu_L_c', 'M_glu_L_e', 'M_glx_c', 'M_h2o_c', 'M_h2o_e', 'M_h_c', 'M_h_e', 'M_icit_c',
                          'M_lac_D_c', 'M_lac_D_e', 'M_mal_L_c', 'M_mal_L_e', 'M_nad_c', 'M_nadh_c', 'M_nadp_c',
                          'M_nadph_c', 'M_nh4_c', 'M_nh4_e', 'M_o2_c', 'M_o2_e', 'M_oaa_c', 'M_pep_c', 'M_pi_c',
                          'M_pi_e', 'M_pyr_c', 'M_pyr_e', 'M_q8_c', 'M_q8h2_c', 'M_r5p_c', 'M_ru5p_D_c', 'M_s7p_c',
                          'M_succ_c', 'M_succ_e', 'M_succoa_c', 'M_xu5p_D_c'])
        for i, constraint in enumerate(self.model.constraints):
            constraint.name = 'c' + str(i)
        self.assertEqual([constraint.name for constraint in self.model.constraints],
                         ['c' + str(i) for i in range(0, len(self.model.constraints))])

    def test_setting_lower_bound_higher_than_upper_bound_raises(self):
        self.assertRaises(ValueError, setattr, self.model.constraints[0], 'lb', 10000000000.)
        self.assertRaises(ValueError, setattr, self.model.constraints[0], "ub", -1000000000.)

        self.assertRaises(ValueError, self.interface.Constraint, 0, lb=0, ub=-1)

    def test_setting_bounds(self):
        var = self.interface.Variable("test", lb=-10)
        c = self.interface.Constraint(var, lb=0)
        model = self.interface.Model()
        obj = self.interface.Objective(var)
        model.add(c)
        model.objective = obj

        c.ub = 5
        model.optimize()
        self.assertEqual(var.primal, 5)
        c.ub = 4
        model.optimize()
        self.assertEqual(var.primal, 4)
        c.lb = -3
        model.objective.direction = "min"
        model.optimize()
        self.assertEqual(var.primal, -3)
        c.lb = sympy.Number(-4)  # Sympy numbers should be valid bounds
        model.optimize()
        self.assertEqual(var.primal, -4)

    def test_setting_nonnumerical_bounds_raises(self):
        var = self.interface.Variable("test")
        constraint = self.interface.Constraint(var, lb=0)
        self.assertRaises(TypeError, setattr, constraint, "lb", "noodle soup")
        self.assertRaises(TypeError, setattr, self.model.constraints[0], 'lb', 'Chicken soup')
        self.assertRaises(TypeError, setattr, constraint, "ub", "noodle soup")
        self.assertRaises(TypeError, setattr, self.model.constraints[0], 'ub', 'Chicken soup')

    def test_set_constraint_bounds_to_none(self):
        model = self.interface.Model()
        var = self.interface.Variable("test")
        const = self.interface.Constraint(var, lb=-10, ub=10)
        obj = self.interface.Objective(var)
        model.add(const)
        model.objective = obj
        self.assertEqual(model.optimize(), interface.OPTIMAL)
        const.ub = None
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        const.ub = 10
        const.lb = None
        obj.direction = "min"
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        const.lb = -10
        self.assertEqual(model.optimize(), interface.OPTIMAL)

    def test_constraint_get_linear_coefficients_raises(self):
        self.assertRaises(Exception, self.constraint.get_linear_coefficients, [])

    def test_constraint_set_linear_coefficients_raises(self):
        self.assertRaises(Exception, self.constraint.set_linear_coefficients, {})

    def test_move_constant_to_rhs(self):
        x = self.interface.Variable("x")
        c1 = self.interface.Constraint(x + 3, lb=0, ub=0)
        self.assertEqual(c1.expression - x, 0)
        self.assertEqual(c1.lb, -3)
        self.assertEqual(c1.ub, -3)

        c2 = self.interface.Constraint(x - 3, lb=0, ub=0)
        self.assertEqual(c2.expression - x, 0)
        self.assertEqual(c2.lb, 3)
        self.assertEqual(c2.ub, 3)

        c3 = self.interface.Constraint(x - 3, lb=0)
        self.assertEqual(c3.expression - x, 0)
        self.assertEqual(c3.lb, 3)

        c4 = self.interface.Constraint(x - 3, ub=0)
        self.assertEqual(c4.expression - x, 0)
        self.assertEqual(c4.ub, 3)

        c5 = self.interface.Constraint(x + 3, lb=0)
        self.assertEqual(c5.expression - x, 0)
        self.assertEqual(c5.lb, -3)

        c6 = self.interface.Constraint(x + 3, ub=0)
        self.assertEqual(c6.expression - x, 0)
        self.assertEqual(c6.ub, -3)

    def test_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.interface.Constraint(1, name="")
        with self.assertRaises(Exception):
            self.interface.Constraint(1, name="This space")
        with self.assertRaises(Exception):
            self.interface.Constraint(1, name="This\ttab")

    def test_new_invalid_name_raises(self):
        const = self.interface.Constraint(1, name="MyConstraint")
        with self.assertRaises(Exception):
            const.name = ""
        with self.assertRaises(Exception):
            const.name = "This space"
        with self.assertRaises(Exception):
            const.name = "This\ttab"

    def test_construct_with_sloppy(self):
        x, y, z, w = self.model.variables[:4]
        const = self.interface.Constraint(
            symbolics.add([symbolics.mul(symbolics.One, var) for var in [x, y, z]]),
            lb=0,
            sloppy=True
        )
        self.model.add(const)
        self.model.update()

        self.assertTrue(const.get_linear_coefficients([x, y, z, w]) == {x: 1, y: 1, z: 1, w: 0})


@six.add_metaclass(abc.ABCMeta)
class AbstractObjectiveTestCase(unittest.TestCase):
    @abc.abstractmethod
    def setUp(self):
        pass

    @abc.abstractmethod
    def test_change_direction(self):
        pass

    def test_objective_get_linear_coefficients_raises(self):
        objective = self.interface.Objective(0)
        self.assertRaises(Exception, objective.get_linear_coefficients, [])

    def test_objective_set_linear_coefficients_raises(self):
        objective = self.interface.Objective(0)
        self.assertRaises(Exception, objective.set_linear_coefficients, {})

    def test_objective_value_is_none(self):
        objective = self.interface.Objective(0)
        self.assertIs(objective.value, None)

    def test_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.interface.Objective(1, name="")
        with self.assertRaises(Exception):
            self.interface.Objective(1, name="This space")
        with self.assertRaises(Exception):
            self.interface.Objective(1, name="This\ttab")

    def test_new_invalid_name_raises(self):
        obj = self.interface.Objective(1, name="MyObjective")
        with self.assertRaises(Exception):
            obj.name = ""
        with self.assertRaises(Exception):
            obj.name = "This space"
        with self.assertRaises(Exception):
            obj.name = "This\ttab"

    def test_construct_with_sloppy(self):
        x, y, z, w = self.model.variables[:4]
        obj = self.interface.Objective(
            symbolics.add([symbolics.mul((symbolics.One, var)) for var in [x, y, z]]),
            direction="min",
            sloppy=True
        )
        self.model.objective = obj

        self.assertTrue(obj.get_linear_coefficients([x, y, z, w]) == {x: 1, y: 1, z: 1, w: 0})


@six.add_metaclass(abc.ABCMeta)
class AbstractModelTestCase(unittest.TestCase):

    def setUp(self):
        with open(TESTMODELPATH) as infile:
            self.model = self.interface.Model.from_json(json.load(infile))

    def test_create_empty_model(self):
        model = self.interface.Model()
        self.assertEqual(len(model.constraints), 0)
        self.assertEqual(len(model.variables), 0)
        self.assertEqual(model.objective.expression - 0, 0)

    @abc.abstractmethod
    def test_pickle_ability(self):
        pass

    def test_pickle_empty_model(self):
        model = self.interface.Model()
        self.assertEquals(model.objective.expression - 0, 0)
        self.assertEquals(len(model.variables), 0)
        self.assertEquals(len(model.constraints), 0)
        pickle_string = pickle.dumps(model)
        from_pickle = pickle.loads(pickle_string)
        self.assertEquals(from_pickle.objective.expression - 0, 0)
        self.assertEquals(len(from_pickle.variables), 0)
        self.assertEquals(len(from_pickle.constraints), 0)

    def test_copy(self):
        self.model.optimize()
        value = self.model.objective.value
        model_copy = copy.copy(self.model)
        self.assertIsNot(self.model, model_copy)
        model_copy.optimize()
        self.assertAlmostEqual(value, model_copy.objective.value)
        self.assertEqual([(var.lb, var.ub, var.name, var.type) for var in model_copy.variables.values()],
                         [(var.lb, var.ub, var.name, var.type) for var in self.model.variables.values()])
        self.assertEqual([(constr.lb, constr.ub, constr.name) for constr in model_copy.constraints],
                         [(constr.lb, constr.ub, constr.name) for constr in self.model.constraints])

    def test_deepcopy(self):
        self.model.optimize()
        value = self.model.objective.value
        model_copy = copy.deepcopy(self.model)
        self.assertIsNot(self.model, model_copy)
        self.assertIsNot(self.model.problem, model_copy.problem)
        model_copy.optimize()
        self.assertAlmostEqual(value, model_copy.objective.value)
        self.assertEqual([(var.lb, var.ub, var.name, var.type) for var in model_copy.variables.values()],
                         [(var.lb, var.ub, var.name, var.type) for var in self.model.variables.values()])
        self.assertEqual([(constr.lb, constr.ub, constr.name) for constr in model_copy.constraints],
                         [(constr.lb, constr.ub, constr.name) for constr in self.model.constraints])

    @abc.abstractmethod
    def test_config_gets_copied_too(self):
        pass

    @abc.abstractmethod
    def test_init_from_existing_problem(self):
        pass

    def test_add_variable(self):
        model = self.interface.Model()
        var = self.interface.Variable('x')
        self.assertEqual(var.problem, None)
        model.add(var)
        self.assertTrue(var in model.variables)
        self.assertEqual(model.variables['x'].problem, var.problem)
        self.assertEqual(model.variables['x'].problem, model)
        var = self.interface.Variable('y', lb=-13)
        model.add(var)
        self.assertTrue(var in model.variables)
        self.assertEqual(model.variables['x'].lb, None)
        self.assertEqual(model.variables['x'].ub, None)
        self.assertEqual(model.variables['y'].lb, -13)
        self.assertEqual(model.variables['x'].ub, None)

    def test_add_integer_var(self):
        var = self.interface.Variable('int_var', lb=-13, ub=499., type='integer')
        self.model.add(var)
        self.assertEqual(self.model.variables['int_var'].type, 'integer')
        self.assertEqual(self.model.variables['int_var'].ub, 499.)
        self.assertEqual(self.model.variables['int_var'].lb, -13)

    @abc.abstractmethod
    def test_add_non_cplex_conform_variable(self):
        pass

    def test_remove_variable(self):
        var = self.model.variables[0]
        self.assertEqual(var.problem, self.model)
        self.model.remove(var)
        self.assertNotIn(var, self.model.variables)
        self.assertEqual(var.problem, None)

    def test_remove_variable_str(self):
        var = self.model.variables.values()[0]
        self.model.remove(var.name)
        self.assertNotIn(var, self.model.variables)
        self.assertEqual(var.problem, None)

    def test_add_constraints(self):
        x = self.interface.Variable('x', type='binary')
        y = self.interface.Variable('y', lb=-181133.3, ub=12000., type='continuous')
        z = self.interface.Variable('z', lb=0., ub=3, type='integer')
        constr1 = self.interface.Constraint(0.3 * x + 0.4 * y + 66. * z, lb=-100, ub=0., name='test')
        constr2 = self.interface.Constraint(2.333 * x + y + 3.333, ub=100.33, name='test2')
        constr3 = self.interface.Constraint(2.333 * x + y + z, ub=100.33, lb=-300)
        constr4 = self.interface.Constraint(77 * x, lb=10, name='Mul_constraint')
        constr5 = self.interface.Constraint(x, ub=-10, name='Only_var_constraint')
        constr6 = self.interface.Constraint(3, ub=88., name='Number_constraint')
        self.model.add(constr1)
        self.model.update()
        self.model.add(constr2)
        self.model.update()
        self.model.add(constr3, sloppy=True)
        self.model.update()
        self.model.add([constr4, constr5, constr6])
        self.model.update()
        self.assertIn(constr1.name, self.model.constraints)
        self.assertIn(constr2.name, self.model.constraints)
        self.assertIn(constr3.name, self.model.constraints)
        self.assertIn(constr4.name, self.model.constraints)
        self.assertIn(constr5.name, self.model.constraints)
        self.assertIn(constr6.name, self.model.constraints)

    def test_remove_constraints(self):
        x = self.interface.Variable('x', type='binary')
        y = self.interface.Variable('y', lb=-181133.3, ub=12000., type='continuous')
        z = self.interface.Variable('z', lb=4, ub=4, type='integer')
        constr1 = self.interface.Constraint(0.3 * x + 0.4 * y + 66. * z, lb=-100, ub=0., name='test')
        self.assertEqual(constr1.problem, None)
        self.model.add(constr1)
        self.model.update()
        self.assertEqual(constr1.problem, self.model)
        self.assertIn(constr1, self.model.constraints)
        self.model.remove(constr1.name)
        self.model.update()
        self.assertEqual(constr1.problem, None)
        self.assertNotIn(constr1, self.model.constraints)

    def test_add_nonlinear_constraint_raises(self):
        x = self.interface.Variable('x', type='binary')
        y = self.interface.Variable('y', lb=-181133.3, ub=12000., type='continuous')
        z = self.interface.Variable('z', lb=3, ub=3, type='integer')
        with self.assertRaises(ValueError):
            constraint = self.interface.Constraint(0.3 * x + 0.4 * y ** x + 66. * z, lb=-100, ub=0., name='test')
            self.model.add(constraint)
            self.model.update()

    def test_objective_get_linear_coefficients(self):
        coefs = self.model.objective.get_linear_coefficients(self.model.variables)
        self.assertEqual(len(coefs), len(self.model.variables))
        expr = sum(c * v for v, c in coefs.items())
        self.assertEqual((expr - self.model.objective.expression).expand() - 0, 0)

    def test_constraint_get_linear_coefficients(self):
        constraint = self.model.constraints[5]
        coefs = constraint.get_linear_coefficients(self.model.variables)
        self.assertEqual(len(coefs), len(self.model.variables))
        expr = sum(c * v for v, c in coefs.items())
        self.assertEqual((expr - constraint.expression).expand() - 0, 0)

    @abc.abstractmethod
    def test_change_of_constraint_is_reflected_in_low_level_solver(self):
        pass

    @abc.abstractmethod
    def test_constraint_set_problem_to_None_caches_the_latest_expression_from_solver_instance(self):
        pass

    @abc.abstractmethod
    def test_change_of_objective_is_reflected_in_low_level_solver(self):
        pass

    @abc.abstractmethod
    def test_change_variable_bounds(self):
        pass

    def test_change_variable_type(self):
        self.model.variables[-1].type = "integer"
        self.assertEqual(self.model.variables[-1].type, "integer")

    @abc.abstractmethod
    def test_change_constraint_bounds(self):
        pass

    def test_initial_objective(self):
        self.assertEqual(self.model.objective.expression, 1.0 * self.model.variables["R_Biomass_Ecoli_core_w_GAM"])

    def test_optimize(self):
        self.model.optimize()
        self.assertEqual(self.model.status, 'optimal')
        self.assertAlmostEqual(self.model.objective.value, 0.8739215069684303)

    def test_optimize_milp(self):
        with open(TESTMILPMODELPATH) as infile:
            milp_model = self.interface.Model.from_json(json.load(infile))
        milp_model.optimize()
        self.assertEqual(milp_model.status, 'optimal')
        self.assertAlmostEqual(milp_model.objective.value, 122.5)
        for variable in milp_model.variables:
            if variable.type == 'integer':
                self.assertEqual(variable.primal % 1, 0)

    def test_change_objective(self):
        v1, v2 = self.model.variables.values()[0:2]
        self.model.objective = self.interface.Objective(1. * v1 + 1. * v2)
        self.assertEqual(self.model.objective.direction, "max")
        self.assertEqual(
            (self.model.objective.expression -
             (1.0 * self.model.variables["R_PGK"] + 1.0 * self.model.variables["R_Biomass_Ecoli_core_w_GAM"])).expand(),
            0.
        )
        self.model.objective = self.interface.Objective(v1 + v2)
        self.assertEqual(self.model.objective.direction, "max")
        self.assertEqual(
            (self.model.objective.expression -
             (1.0 * self.model.variables["R_PGK"] + 1.0 * self.model.variables["R_Biomass_Ecoli_core_w_GAM"])).expand(),
            0.
        )

    def test_number_objective(self):
        self.model.objective = self.interface.Objective(0.)
        self.assertEqual(self.model.objective.expression - 0, 0)
        self.assertEqual(self.model.objective.direction, "max")
        self.assertEqual(self.model.optimize(), "optimal")

    def test_raise_on_non_linear_objective(self):
        """Test that an exception is raised when a non-linear objective is added to the model."""
        v1, v2 = self.model.variables.values()[0:2]
        self.assertRaises(ValueError, self.interface.Objective, v1 * v2 ** 3)

    @abc.abstractmethod
    def test_iadd_objective(self):
        pass

    @abc.abstractmethod
    def test_imul_objective(self):
        pass

    @abc.abstractmethod
    def test_set_copied_objective(self):
        pass

    @abc.abstractmethod
    def test_timeout(self):
        pass

    @abc.abstractmethod
    def test_set_linear_coefficients_objective(self):
        pass

    def test_instantiating_model_with_different_solver_problem_raises(self):
        self.assertRaises(TypeError, self.interface.Model, problem='Chicken soup')

    @abc.abstractmethod
    def test_set_linear_coefficients_constraint(self):
        pass

    def test_primal_values(self):
        self.model.optimize()
        primals = self.model.primal_values
        for var in self.model.variables:
            self.assertEqual(var.primal, primals[var.name])
        self.assertEqual(set(var.name for var in self.model.variables), set(primals))

    def test_reduced_costs(self):
        self.model.optimize()
        reduced_costs = self.model.reduced_costs
        for var in self.model.variables:
            self.assertEqual(var.dual, reduced_costs[var.name])
        self.assertEqual(set(var.name for var in self.model.variables), set(reduced_costs))

    def test_dual_values(self):
        self.model.optimize()
        constraint_primals = self.model.constraint_values  # TODO Fix this method name
        for constraint in self.model.constraints:
            self.assertEqual(constraint.primal, constraint_primals[constraint.name])
        self.assertEqual(set(const.name for const in self.model.constraints), set(constraint_primals))

    def test_shadow_prices(self):
        self.model.optimize()
        shadow_prices = self.model.shadow_prices
        for constraint in self.model.constraints:
            self.assertEqual(constraint.dual, shadow_prices[constraint.name])
        self.assertEqual(set(const.name for const in self.model.constraints), set(shadow_prices))

    def test_change_objective_can_handle_removed_vars(self):
        self.model.objective = self.interface.Objective(self.model.variables[0])
        self.model.remove(self.model.variables[0])
        self.model.update()
        self.model.objective = self.interface.Objective(self.model.variables[1] * 2)

    def test_clone_model_with_json(self):
        self.assertEquals(self.model.configuration.verbosity, 0)
        self.model.configuration.verbosity = 3
        self.model.optimize()
        opt = self.model.objective.value
        cloned_model = self.interface.Model.clone(self.model)
        self.assertEquals(cloned_model.configuration.verbosity, 3)
        self.assertEquals(len(cloned_model.variables), len(self.model.variables))
        self.assertEquals(len(cloned_model.constraints), len(self.model.constraints))
        cloned_model.optimize()
        self.assertAlmostEqual(cloned_model.objective.value, opt)

    def test_clone_model_with_lp(self):
        self.assertEquals(self.model.configuration.verbosity, 0)
        self.model.configuration.verbosity = 3
        self.model.optimize()
        opt = self.model.objective.value
        cloned_model = self.interface.Model.clone(self.model, use_lp=True)
        self.assertEquals(cloned_model.configuration.verbosity, 3)
        self.assertEquals(len(cloned_model.variables), len(self.model.variables))
        self.assertEquals(len(cloned_model.constraints), len(self.model.constraints))
        cloned_model.optimize()
        self.assertAlmostEqual(cloned_model.objective.value, opt)

    def test_clone_model_without_json(self):
        self.assertEquals(self.model.configuration.verbosity, 0)
        self.model.configuration.verbosity = 3
        self.model.optimize()
        opt = self.model.objective.value
        cloned_model = self.interface.Model.clone(self.model, use_json=False)
        self.assertEquals(cloned_model.configuration.verbosity, 3)
        self.assertEquals(len(cloned_model.variables), len(self.model.variables))
        self.assertEquals(len(cloned_model.constraints), len(self.model.constraints))
        cloned_model.optimize()
        self.assertAlmostEqual(cloned_model.objective.value, opt)

    def test_remove_variable_not_in_model_raises(self):
        var = self.interface.Variable("test")
        self.assertRaises(Exception, self.model._remove_variables, [var])

    def test_objective_set_linear_coefficients(self):
        x = self.interface.Variable("x", lb=0)
        y = self.interface.Variable("y", lb=0)
        c1 = self.interface.Constraint((y + 2 * (x - 3)).expand(), ub=0)
        c2 = self.interface.Constraint(y + (1 / 2) * x - 3, ub=0)
        obj = self.interface.Objective(x)
        model = self.interface.Model()
        model.add([c1, c2])
        model.objective = obj

        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 3)
        self.assertAlmostEqual(y.primal, 0)

        obj.set_linear_coefficients({y: 1})
        self.assertEqual(float((obj.expression - (x + y)).expand()), 0.0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 2)
        self.assertAlmostEqual(y.primal, 2)

        obj.set_linear_coefficients({x: 0})
        self.assertEqual(float((obj.expression - y).expand()), 0.0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 0)
        self.assertAlmostEqual(y.primal, 3)

    def test_constraint_set_linear_coefficients(self):
        x = self.interface.Variable("x", lb=0, ub=1000)
        y = self.interface.Variable("y", lb=0)
        c1 = self.interface.Constraint(y, ub=1)
        obj = self.interface.Objective(x)
        model = self.interface.Model()
        model.add([c1])
        model.objective = obj

        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, x.ub)

        c1.set_linear_coefficients({x: 1})
        self.assertEqual((c1.expression - (x + y)).expand() - 0, 0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 1)

        c1.set_linear_coefficients({x: 2})
        self.assertEqual((c1.expression - (2 * x + y)).expand() - 0, 0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 0.5)

    def test_objective_handles_constants_2(self):
        offset = 2
        self.model.optimize()
        optimal = self.model.objective.value
        objective = self.interface.Objective(self.model.objective.expression + offset)
        self.model.objective = objective
        self.model.optimize()
        self.assertAlmostEqual(self.model.objective.value, optimal + offset)

    # def test_objective_handles_constants_3(self):
    #     offset = 3
    #     self.model.optimize()
    #     optimal = self.model.objective.value
    #     self.model.objective += offset
    #     self.model.optimize()
    #     self.assertEqual(self.model.objective.value, optimal + offset)

    def test_objective_expression_includes_constant(self):
        objective = self.model.objective
        self.model.objective = self.interface.Objective(objective.expression + 3)
        self.model.update()
        self.assertEqual((self.model.objective.expression - (objective.expression + 3.)).expand(), 0.)

    def test_is_integer(self):
        model = self.model
        self.assertFalse(model.is_integer)
        self.assertFalse(optlang.interface.Model.is_integer.fget(model))

        model.variables[0].type = "integer"
        self.assertTrue(model.is_integer)
        self.assertTrue(optlang.interface.Model.is_integer.fget(model))

        model.variables[0].type = "continuous"
        model.variables[1].type = "binary"
        self.assertTrue(model.is_integer)

        model.variables[1].type = "continuous"
        self.assertFalse(model.is_integer)

    def test_binary_variables(self):
        model = self.interface.Model()
        var = self.interface.Variable("x", type="binary")
        obj = self.interface.Objective(var)
        model.objective = obj

        for lb, ub in ((0, 0), (0, 1), (1, 1)):
            var.ub = ub
            var.lb = lb

            obj.direction = "max"
            model.optimize()
            self.assertAlmostEqual(var.primal, ub)

            obj.direction = "min"
            model.optimize()
            self.assertAlmostEqual(var.primal, lb)

    def test_integer_variable_dual(self):
        model = self.interface.Model()
        x = self.interface.Variable("x", lb=0)
        y = self.interface.Variable("y", lb=0)
        c = self.interface.Constraint(x + y, ub=1)
        model.add(c)
        model.objective = self.interface.Objective(x)

        model.optimize()
        self.assertEqual(y.dual, -1)

        x.type = "integer"
        model.optimize()
        self.assertRaises(ValueError, partial(getattr, y, "dual"))

        x.type = "continuous"
        model.optimize()
        self.assertEqual(y.dual, -1)

    def test_integer_constraint_dual(self):
        model = self.interface.Model()
        x = self.interface.Variable("x")
        c = self.interface.Constraint(x, ub=1)
        model.add(c)
        model.objective = self.interface.Objective(x)

        model.optimize()
        self.assertEqual(c.dual, 1)

        x.type = "integer"
        model.optimize()
        self.assertRaises(ValueError, partial(getattr, c, "dual"))

        x.type = "continuous"
        model.optimize()
        self.assertEqual(c.dual, 1)

    def test_integer_batch_duals(self):
        model = self.interface.Model()
        x = self.interface.Variable("x")
        c = self.interface.Constraint(x, ub=1)
        model.add(c)
        model.objective = self.interface.Objective(x)
        model.optimize()

        self.assertEqual(model.reduced_costs[x.name], 0)
        self.assertEqual(model.shadow_prices[c.name], 1)

        x.type = "integer"
        model.optimize()

        with self.assertRaises(ValueError):
            model.reduced_costs
        with self.assertRaises(ValueError):
            model.shadow_prices

        x.type = "continuous"
        model.optimize()

        self.assertEqual(model.reduced_costs[x.name], 0)
        self.assertEqual(model.shadow_prices[c.name], 1)

    def test_large_objective(self):
        model = self.interface.Model()
        model.add([self.interface.Variable(str(i), lb=1) for i in range(1100)])
        model.optimize()

        obj = self.interface.Objective(
            optlang.symbolics.add([optlang.symbolics.mul((optlang.symbolics.One, v)) for v in model.variables]),
            direction="min"
        )
        model.objective = obj
        model.optimize()
        self.assertAlmostEqual(model.objective.value, len(model.variables))

    def test_implicitly_convert_milp_to_lp(self):
        model = self.interface.Model()
        var1 = self.interface.Variable("x", ub=1)
        var2 = self.interface.Variable("y", type="integer")
        var3 = self.interface.Variable("z", type="integer")
        model.add([var1, var2])
        model.optimize()
        self.assertTrue(model.is_integer)

        var2.type = "continuous"
        model.optimize()
        self.assertAlmostEqual(model.reduced_costs["x"], 0)

        var2.type = "integer"
        model.add(var3)
        model.optimize()
        self.assertTrue(model.is_integer)

        model.remove(var2)
        model.optimize()
        model.remove(var3)
        model.optimize()
        self.assertAlmostEqual(model.reduced_costs["x"], 0)



@six.add_metaclass(abc.ABCMeta)
class AbstractConfigurationTestCase(unittest.TestCase):

    def setUp(self):
        pass

    def test_tolerance_parameters(self):
        model = self.interface.Model()
        params = dir(model.configuration.tolerances)
        for param in params:
            val = getattr(model.configuration.tolerances, param)
            setattr(model.configuration.tolerances, param, 2 * val)
            self.assertEqual(
                getattr(model.configuration.tolerances, param), 2 * val
            )


@six.add_metaclass(abc.ABCMeta)
class AbstractQuadraticProgrammingTestCase(unittest.TestCase):
    @abc.abstractmethod
    def setUp(self):
        pass

    @abc.abstractmethod
    def test_convex_obj(self):
        pass

    @abc.abstractmethod
    def test_non_convex_obj(self):
        pass

    @abc.abstractmethod
    def test_qp_convex(self):
        pass

    @abc.abstractmethod
    def test_qp_non_convex(self):
        pass

<filename>optlang/tests/abstract_test_cases.py
# Copyright 2016 Novo Nordisk Foundation Center for Biosustainability,
# Technical University of Denmark.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import division

import abc
import unittest

import six
from optlang import interface
from optlang import symbolics
import optlang
import pickle
import json
import copy
import os
import sympy
from functools import partial

__test__ = False

TESTMODELPATH = os.path.join(os.path.dirname(__file__), 'data/model.json')
TESTMILPMODELPATH = os.path.join(os.path.dirname(__file__), 'data/simple_milp.json')


@six.add_metaclass(abc.ABCMeta)
class AbstractVariableTestCase(unittest.TestCase):
    @unittest.skip('Abstract test method not implemented.')
    def test_magic(self):
        pass

    def setUp(self):
        self.var = self.interface.Variable('test')
        self.model = self.interface.Model()

    def test_set_wrong_type_raises(self):
        self.assertRaises(ValueError, self.interface.Variable, name="test", type="mayo")
        self.assertRaises(Exception, setattr, self.var, 'type', 'ketchup')
        self.model.add(self.var)
        self.model.update()
        self.assertRaises(ValueError, setattr, self.var, "type", "mustard")
        self.var.type = "integer"
        self.assertEqual(self.var.type, "integer")

    def test_change_type(self):
        var = self.interface.Variable("test")
        var.type = "binary"
        self.assertEqual(var.type, "binary")

    def test_change_name(self):
        self.model.add(self.var)
        self.model.update()
        self.var.name = "test_2"
        self.assertEqual(self.var.name, "test_2")
        self.assertEqual(str(self.var), self.var.name)
        self.model.remove(self.var)
        self.model.update()

    def test_non_string_name_raises(self):
        for name in [2, None, True, ["name1", "name2"]]:
            with self.assertRaises(TypeError):
                self.interface.Variable(name)

    @abc.abstractmethod
    def test_get_primal(self):
        pass

    def test_get_dual(self):
        with open(TESTMODELPATH) as infile:
            model = self.interface.Model.from_json(json.load(infile))
        model.optimize()
        self.assertEqual(model.status, 'optimal')
        self.assertAlmostEqual(model.objective.value, 0.8739215069684305)
        self.assertTrue(isinstance(model.variables[0].dual, float))

    def test_setting_lower_bound_higher_than_upper_bound_raises(self):
        self.model.add(self.var)
        self.var.ub = 0
        self.assertRaises(ValueError, setattr, self.model.variables[0], 'lb', 100.)

    def test_setting_nonnumerical_bounds_raises(self):
        self.assertRaises(TypeError, setattr, self.var, "lb", "Minestrone")
        self.assertRaises(TypeError, setattr, self.var, "ub", "Minestrone")
        self.model.add(self.var)
        self.assertRaises(TypeError, setattr, self.model.variables[0], 'lb', 'Chicken soup')
        self.assertRaises(TypeError, setattr, self.model.variables[0], 'ub', 'Chicken soup')

    @abc.abstractmethod
    def test_changing_variable_names_is_reflected_in_the_solver(self):
        pass

    def test_setting_bounds(self):
        self.var.ub = 5
        self.model.objective = self.interface.Objective(self.var)
        self.model.optimize()
        self.assertEqual(self.var.primal, 5)
        self.var.ub = 4
        self.model.optimize()
        self.assertEqual(self.var.primal, 4)
        self.var.lb = -3
        self.model.objective.direction = "min"
        self.model.optimize()
        self.assertEqual(self.var.primal, -3)
        self.var.lb = sympy.Number(-4)  # Sympy numbers should be valid bounds
        self.model.optimize()
        self.assertEqual(self.var.primal, -4)

    def test_set_bounds_method(self):
        var = self.interface.Variable("test", lb=-10)
        c = self.interface.Constraint(var, lb=-100)
        model = self.interface.Model()
        obj = self.interface.Objective(var)
        model.add(c)
        model.objective = obj

        for lb, ub in ((1, 10), (-1, 5), (11, 12)):
            obj.direction = "max"
            var.set_bounds(lb, ub)
            model.optimize()
            self.assertAlmostEqual(var.primal, ub)
            obj.direction = "min"
            model.optimize()
            self.assertAlmostEqual(var.primal, lb)

        var.set_bounds(None, 0)
        model.optimize()
        self.assertAlmostEqual(var.primal, -100)

        obj.direction = "max"
        var.set_bounds(1, None)
        self.assertEqual(model.optimize(), optlang.interface.UNBOUNDED)

        self.assertRaises(ValueError, var.set_bounds, 2, 1)

    def test_set_bounds_to_none(self):
        model = self.model
        var = self.var
        model.objective = self.interface.Objective(var)
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        var.ub = 10
        self.assertEqual(model.optimize(), interface.OPTIMAL)
        var.ub = None
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        self.model.objective.direction = "min"
        var.lb = -10
        self.assertEqual(model.optimize(), interface.OPTIMAL)
        var.lb = None
        self.assertEqual(model.optimize(), interface.UNBOUNDED)

    def test_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.interface.Variable("")
        with self.assertRaises(Exception):
            self.interface.Variable("This space")
        with self.assertRaises(Exception):
            self.interface.Variable("This\ttab")

    def test_new_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.var.name = ""
        with self.assertRaises(Exception):
            self.var.name = "This space"
        with self.assertRaises(Exception):
            self.var.name = "This\ttab"

        self.assertEqual(self.var.name, 'test')


@six.add_metaclass(abc.ABCMeta)
class AbstractConstraintTestCase(unittest.TestCase):

    def setUp(self):
        with open(TESTMODELPATH) as infile:
            self.model = self.interface.Model.from_json(json.load(infile))
        self.constraint = self.interface.Constraint(
            self.interface.Variable('chip') + self.interface.Variable('chap'),
            name='woodchips',
            lb=100
        )

    def test_indicator_constraint_support(self):
        if self.interface.Constraint._INDICATOR_CONSTRAINT_SUPPORT:
            constraint = self.interface.Constraint(
                self.interface.Variable('chip_2'),
                indicator_variable=self.interface.Variable('chip', type='binary'), active_when=0, lb=0,
                ub=0,
                name='indicator_constraint_fwd_1'
            )
            model = self.interface.Model()
            model.add(constraint)
            model.update()
            self.assertEqual(constraint.problem, model)
            self.assertIn(constraint, model.constraints)
            model.remove(constraint.name)
            model.update()
            self.assertEqual(constraint.problem, None)
            self.assertNotIn(constraint, model.constraints)
        else:
            self.assertRaises(
                optlang.exceptions.IndicatorConstraintsNotSupported,
                self.interface.Constraint,
                self.interface.Variable('chip') + self.interface.Variable('chap'),
                indicator_variable=self.interface.Variable('indicator', type='binary')
            )

    @abc.abstractmethod
    def test_get_primal(self):
        pass

    def test_get_dual(self):
        self.assertEqual(self.constraint.dual, None)
        self.model.optimize()
        self.assertEqual(self.model.status, 'optimal')
        self.assertAlmostEqual(self.model.objective.value, 0.8739215069684305)
        self.assertTrue(isinstance(self.model.constraints[0].dual, float))

    def test_change_constraint_name(self):
        constraint = self.interface.Constraint.clone(self.constraint)
        self.assertEqual(constraint.name, 'woodchips')
        constraint.name = 'ketchup'
        self.assertEqual(constraint.name, 'ketchup')
        self.assertEqual([constraint.name for constraint in self.model.constraints],
                         ['M_13dpg_c', 'M_2pg_c', 'M_3pg_c', 'M_6pgc_c', 'M_6pgl_c', 'M_ac_c', 'M_ac_e',
                          'M_acald_c', 'M_acald_e', 'M_accoa_c', 'M_acon_C_c', 'M_actp_c', 'M_adp_c', 'M_akg_c',
                          'M_akg_e', 'M_amp_c', 'M_atp_c', 'M_cit_c', 'M_co2_c', 'M_co2_e', 'M_coa_c', 'M_dhap_c',
                          'M_e4p_c', 'M_etoh_c', 'M_etoh_e', 'M_f6p_c', 'M_fdp_c', 'M_for_c', 'M_for_e', 'M_fru_e',
                          'M_fum_c', 'M_fum_e', 'M_g3p_c', 'M_g6p_c', 'M_glc_D_e', 'M_gln_L_c', 'M_gln_L_e',
                          'M_glu_L_c', 'M_glu_L_e', 'M_glx_c', 'M_h2o_c', 'M_h2o_e', 'M_h_c', 'M_h_e', 'M_icit_c',
                          'M_lac_D_c', 'M_lac_D_e', 'M_mal_L_c', 'M_mal_L_e', 'M_nad_c', 'M_nadh_c', 'M_nadp_c',
                          'M_nadph_c', 'M_nh4_c', 'M_nh4_e', 'M_o2_c', 'M_o2_e', 'M_oaa_c', 'M_pep_c', 'M_pi_c',
                          'M_pi_e', 'M_pyr_c', 'M_pyr_e', 'M_q8_c', 'M_q8h2_c', 'M_r5p_c', 'M_ru5p_D_c', 'M_s7p_c',
                          'M_succ_c', 'M_succ_e', 'M_succoa_c', 'M_xu5p_D_c'])
        for i, constraint in enumerate(self.model.constraints):
            constraint.name = 'c' + str(i)
        self.assertEqual([constraint.name for constraint in self.model.constraints],
                         ['c' + str(i) for i in range(0, len(self.model.constraints))])

    def test_setting_lower_bound_higher_than_upper_bound_raises(self):
        self.assertRaises(ValueError, setattr, self.model.constraints[0], 'lb', 10000000000.)
        self.assertRaises(ValueError, setattr, self.model.constraints[0], "ub", -1000000000.)

        self.assertRaises(ValueError, self.interface.Constraint, 0, lb=0, ub=-1)

    def test_setting_bounds(self):
        var = self.interface.Variable("test", lb=-10)
        c = self.interface.Constraint(var, lb=0)
        model = self.interface.Model()
        obj = self.interface.Objective(var)
        model.add(c)
        model.objective = obj

        c.ub = 5
        model.optimize()
        self.assertEqual(var.primal, 5)
        c.ub = 4
        model.optimize()
        self.assertEqual(var.primal, 4)
        c.lb = -3
        model.objective.direction = "min"
        model.optimize()
        self.assertEqual(var.primal, -3)
        c.lb = sympy.Number(-4)  # Sympy numbers should be valid bounds
        model.optimize()
        self.assertEqual(var.primal, -4)

    def test_setting_nonnumerical_bounds_raises(self):
        var = self.interface.Variable("test")
        constraint = self.interface.Constraint(var, lb=0)
        self.assertRaises(TypeError, setattr, constraint, "lb", "noodle soup")
        self.assertRaises(TypeError, setattr, self.model.constraints[0], 'lb', 'Chicken soup')
        self.assertRaises(TypeError, setattr, constraint, "ub", "noodle soup")
        self.assertRaises(TypeError, setattr, self.model.constraints[0], 'ub', 'Chicken soup')

    def test_set_constraint_bounds_to_none(self):
        model = self.interface.Model()
        var = self.interface.Variable("test")
        const = self.interface.Constraint(var, lb=-10, ub=10)
        obj = self.interface.Objective(var)
        model.add(const)
        model.objective = obj
        self.assertEqual(model.optimize(), interface.OPTIMAL)
        const.ub = None
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        const.ub = 10
        const.lb = None
        obj.direction = "min"
        self.assertEqual(model.optimize(), interface.UNBOUNDED)
        const.lb = -10
        self.assertEqual(model.optimize(), interface.OPTIMAL)

    def test_constraint_get_linear_coefficients_raises(self):
        self.assertRaises(Exception, self.constraint.get_linear_coefficients, [])

    def test_constraint_set_linear_coefficients_raises(self):
        self.assertRaises(Exception, self.constraint.set_linear_coefficients, {})

    def test_move_constant_to_rhs(self):
        x = self.interface.Variable("x")
        c1 = self.interface.Constraint(x + 3, lb=0, ub=0)
        self.assertEqual(c1.expression - x, 0)
        self.assertEqual(c1.lb, -3)
        self.assertEqual(c1.ub, -3)

        c2 = self.interface.Constraint(x - 3, lb=0, ub=0)
        self.assertEqual(c2.expression - x, 0)
        self.assertEqual(c2.lb, 3)
        self.assertEqual(c2.ub, 3)

        c3 = self.interface.Constraint(x - 3, lb=0)
        self.assertEqual(c3.expression - x, 0)
        self.assertEqual(c3.lb, 3)

        c4 = self.interface.Constraint(x - 3, ub=0)
        self.assertEqual(c4.expression - x, 0)
        self.assertEqual(c4.ub, 3)

        c5 = self.interface.Constraint(x + 3, lb=0)
        self.assertEqual(c5.expression - x, 0)
        self.assertEqual(c5.lb, -3)

        c6 = self.interface.Constraint(x + 3, ub=0)
        self.assertEqual(c6.expression - x, 0)
        self.assertEqual(c6.ub, -3)

    def test_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.interface.Constraint(1, name="")
        with self.assertRaises(Exception):
            self.interface.Constraint(1, name="This space")
        with self.assertRaises(Exception):
            self.interface.Constraint(1, name="This\ttab")

    def test_new_invalid_name_raises(self):
        const = self.interface.Constraint(1, name="MyConstraint")
        with self.assertRaises(Exception):
            const.name = ""
        with self.assertRaises(Exception):
            const.name = "This space"
        with self.assertRaises(Exception):
            const.name = "This\ttab"

    def test_construct_with_sloppy(self):
        x, y, z, w = self.model.variables[:4]
        const = self.interface.Constraint(
            symbolics.add([symbolics.mul(symbolics.One, var) for var in [x, y, z]]),
            lb=0,
            sloppy=True
        )
        self.model.add(const)
        self.model.update()

        self.assertTrue(const.get_linear_coefficients([x, y, z, w]) == {x: 1, y: 1, z: 1, w: 0})


@six.add_metaclass(abc.ABCMeta)
class AbstractObjectiveTestCase(unittest.TestCase):
    @abc.abstractmethod
    def setUp(self):
        pass

    @abc.abstractmethod
    def test_change_direction(self):
        pass

    def test_objective_get_linear_coefficients_raises(self):
        objective = self.interface.Objective(0)
        self.assertRaises(Exception, objective.get_linear_coefficients, [])

    def test_objective_set_linear_coefficients_raises(self):
        objective = self.interface.Objective(0)
        self.assertRaises(Exception, objective.set_linear_coefficients, {})

    def test_objective_value_is_none(self):
        objective = self.interface.Objective(0)
        self.assertIs(objective.value, None)

    def test_invalid_name_raises(self):
        with self.assertRaises(Exception):
            self.interface.Objective(1, name="")
        with self.assertRaises(Exception):
            self.interface.Objective(1, name="This space")
        with self.assertRaises(Exception):
            self.interface.Objective(1, name="This\ttab")

    def test_new_invalid_name_raises(self):
        obj = self.interface.Objective(1, name="MyObjective")
        with self.assertRaises(Exception):
            obj.name = ""
        with self.assertRaises(Exception):
            obj.name = "This space"
        with self.assertRaises(Exception):
            obj.name = "This\ttab"

    def test_construct_with_sloppy(self):
        x, y, z, w = self.model.variables[:4]
        obj = self.interface.Objective(
            symbolics.add([symbolics.mul((symbolics.One, var)) for var in [x, y, z]]),
            direction="min",
            sloppy=True
        )
        self.model.objective = obj

        self.assertTrue(obj.get_linear_coefficients([x, y, z, w]) == {x: 1, y: 1, z: 1, w: 0})


@six.add_metaclass(abc.ABCMeta)
class AbstractModelTestCase(unittest.TestCase):

    def setUp(self):
        with open(TESTMODELPATH) as infile:
            self.model = self.interface.Model.from_json(json.load(infile))

    def test_create_empty_model(self):
        model = self.interface.Model()
        self.assertEqual(len(model.constraints), 0)
        self.assertEqual(len(model.variables), 0)
        self.assertEqual(model.objective.expression - 0, 0)

    @abc.abstractmethod
    def test_pickle_ability(self):
        pass

    def test_pickle_empty_model(self):
        model = self.interface.Model()
        self.assertEquals(model.objective.expression - 0, 0)
        self.assertEquals(len(model.variables), 0)
        self.assertEquals(len(model.constraints), 0)
        pickle_string = pickle.dumps(model)
        from_pickle = pickle.loads(pickle_string)
        self.assertEquals(from_pickle.objective.expression - 0, 0)
        self.assertEquals(len(from_pickle.variables), 0)
        self.assertEquals(len(from_pickle.constraints), 0)

    def test_copy(self):
        self.model.optimize()
        value = self.model.objective.value
        model_copy = copy.copy(self.model)
        self.assertIsNot(self.model, model_copy)
        model_copy.optimize()
        self.assertAlmostEqual(value, model_copy.objective.value)
        self.assertEqual([(var.lb, var.ub, var.name, var.type) for var in model_copy.variables.values()],
                         [(var.lb, var.ub, var.name, var.type) for var in self.model.variables.values()])
        self.assertEqual([(constr.lb, constr.ub, constr.name) for constr in model_copy.constraints],
                         [(constr.lb, constr.ub, constr.name) for constr in self.model.constraints])

    def test_deepcopy(self):
        self.model.optimize()
        value = self.model.objective.value
        model_copy = copy.deepcopy(self.model)
        self.assertIsNot(self.model, model_copy)
        self.assertIsNot(self.model.problem, model_copy.problem)
        model_copy.optimize()
        self.assertAlmostEqual(value, model_copy.objective.value)
        self.assertEqual([(var.lb, var.ub, var.name, var.type) for var in model_copy.variables.values()],
                         [(var.lb, var.ub, var.name, var.type) for var in self.model.variables.values()])
        self.assertEqual([(constr.lb, constr.ub, constr.name) for constr in model_copy.constraints],
                         [(constr.lb, constr.ub, constr.name) for constr in self.model.constraints])

    @abc.abstractmethod
    def test_config_gets_copied_too(self):
        pass

    @abc.abstractmethod
    def test_init_from_existing_problem(self):
        pass

    def test_add_variable(self):
        model = self.interface.Model()
        var = self.interface.Variable('x')
        self.assertEqual(var.problem, None)
        model.add(var)
        self.assertTrue(var in model.variables)
        self.assertEqual(model.variables['x'].problem, var.problem)
        self.assertEqual(model.variables['x'].problem, model)
        var = self.interface.Variable('y', lb=-13)
        model.add(var)
        self.assertTrue(var in model.variables)
        self.assertEqual(model.variables['x'].lb, None)
        self.assertEqual(model.variables['x'].ub, None)
        self.assertEqual(model.variables['y'].lb, -13)
        self.assertEqual(model.variables['x'].ub, None)

    def test_add_integer_var(self):
        var = self.interface.Variable('int_var', lb=-13, ub=499., type='integer')
        self.model.add(var)
        self.assertEqual(self.model.variables['int_var'].type, 'integer')
        self.assertEqual(self.model.variables['int_var'].ub, 499.)
        self.assertEqual(self.model.variables['int_var'].lb, -13)

    @abc.abstractmethod
    def test_add_non_cplex_conform_variable(self):
        pass

    def test_remove_variable(self):
        var = self.model.variables[0]
        self.assertEqual(var.problem, self.model)
        self.model.remove(var)
        self.assertNotIn(var, self.model.variables)
        self.assertEqual(var.problem, None)

    def test_remove_variable_str(self):
        var = self.model.variables.values()[0]
        self.model.remove(var.name)
        self.assertNotIn(var, self.model.variables)
        self.assertEqual(var.problem, None)

    def test_add_constraints(self):
        x = self.interface.Variable('x', type='binary')
        y = self.interface.Variable('y', lb=-181133.3, ub=12000., type='continuous')
        z = self.interface.Variable('z', lb=0., ub=3, type='integer')
        constr1 = self.interface.Constraint(0.3 * x + 0.4 * y + 66. * z, lb=-100, ub=0., name='test')
        constr2 = self.interface.Constraint(2.333 * x + y + 3.333, ub=100.33, name='test2')
        constr3 = self.interface.Constraint(2.333 * x + y + z, ub=100.33, lb=-300)
        constr4 = self.interface.Constraint(77 * x, lb=10, name='Mul_constraint')
        constr5 = self.interface.Constraint(x, ub=-10, name='Only_var_constraint')
        constr6 = self.interface.Constraint(3, ub=88., name='Number_constraint')
        self.model.add(constr1)
        self.model.update()
        self.model.add(constr2)
        self.model.update()
        self.model.add(constr3, sloppy=True)
        self.model.update()
        self.model.add([constr4, constr5, constr6])
        self.model.update()
        self.assertIn(constr1.name, self.model.constraints)
        self.assertIn(constr2.name, self.model.constraints)
        self.assertIn(constr3.name, self.model.constraints)
        self.assertIn(constr4.name, self.model.constraints)
        self.assertIn(constr5.name, self.model.constraints)
        self.assertIn(constr6.name, self.model.constraints)

    def test_remove_constraints(self):
        x = self.interface.Variable('x', type='binary')
        y = self.interface.Variable('y', lb=-181133.3, ub=12000., type='continuous')
        z = self.interface.Variable('z', lb=4, ub=4, type='integer')
        constr1 = self.interface.Constraint(0.3 * x + 0.4 * y + 66. * z, lb=-100, ub=0., name='test')
        self.assertEqual(constr1.problem, None)
        self.model.add(constr1)
        self.model.update()
        self.assertEqual(constr1.problem, self.model)
        self.assertIn(constr1, self.model.constraints)
        self.model.remove(constr1.name)
        self.model.update()
        self.assertEqual(constr1.problem, None)
        self.assertNotIn(constr1, self.model.constraints)

    def test_add_nonlinear_constraint_raises(self):
        x = self.interface.Variable('x', type='binary')
        y = self.interface.Variable('y', lb=-181133.3, ub=12000., type='continuous')
        z = self.interface.Variable('z', lb=3, ub=3, type='integer')
        with self.assertRaises(ValueError):
            constraint = self.interface.Constraint(0.3 * x + 0.4 * y ** x + 66. * z, lb=-100, ub=0., name='test')
            self.model.add(constraint)
            self.model.update()

    def test_objective_get_linear_coefficients(self):
        coefs = self.model.objective.get_linear_coefficients(self.model.variables)
        self.assertEqual(len(coefs), len(self.model.variables))
        expr = sum(c * v for v, c in coefs.items())
        self.assertEqual((expr - self.model.objective.expression).expand() - 0, 0)

    def test_constraint_get_linear_coefficients(self):
        constraint = self.model.constraints[5]
        coefs = constraint.get_linear_coefficients(self.model.variables)
        self.assertEqual(len(coefs), len(self.model.variables))
        expr = sum(c * v for v, c in coefs.items())
        self.assertEqual((expr - constraint.expression).expand() - 0, 0)

    @abc.abstractmethod
    def test_change_of_constraint_is_reflected_in_low_level_solver(self):
        pass

    @abc.abstractmethod
    def test_constraint_set_problem_to_None_caches_the_latest_expression_from_solver_instance(self):
        pass

    @abc.abstractmethod
    def test_change_of_objective_is_reflected_in_low_level_solver(self):
        pass

    @abc.abstractmethod
    def test_change_variable_bounds(self):
        pass

    def test_change_variable_type(self):
        self.model.variables[-1].type = "integer"
        self.assertEqual(self.model.variables[-1].type, "integer")

    @abc.abstractmethod
    def test_change_constraint_bounds(self):
        pass

    def test_initial_objective(self):
        self.assertEqual(self.model.objective.expression, 1.0 * self.model.variables["R_Biomass_Ecoli_core_w_GAM"])

    def test_optimize(self):
        self.model.optimize()
        self.assertEqual(self.model.status, 'optimal')
        self.assertAlmostEqual(self.model.objective.value, 0.8739215069684303)

    def test_optimize_milp(self):
        with open(TESTMILPMODELPATH) as infile:
            milp_model = self.interface.Model.from_json(json.load(infile))
        milp_model.optimize()
        self.assertEqual(milp_model.status, 'optimal')
        self.assertAlmostEqual(milp_model.objective.value, 122.5)
        for variable in milp_model.variables:
            if variable.type == 'integer':
                self.assertEqual(variable.primal % 1, 0)

    def test_change_objective(self):
        v1, v2 = self.model.variables.values()[0:2]
        self.model.objective = self.interface.Objective(1. * v1 + 1. * v2)
        self.assertEqual(self.model.objective.direction, "max")
        self.assertEqual(
            (self.model.objective.expression -
             (1.0 * self.model.variables["R_PGK"] + 1.0 * self.model.variables["R_Biomass_Ecoli_core_w_GAM"])).expand(),
            0.
        )
        self.model.objective = self.interface.Objective(v1 + v2)
        self.assertEqual(self.model.objective.direction, "max")
        self.assertEqual(
            (self.model.objective.expression -
             (1.0 * self.model.variables["R_PGK"] + 1.0 * self.model.variables["R_Biomass_Ecoli_core_w_GAM"])).expand(),
            0.
        )

    def test_number_objective(self):
        self.model.objective = self.interface.Objective(0.)
        self.assertEqual(self.model.objective.expression - 0, 0)
        self.assertEqual(self.model.objective.direction, "max")
        self.assertEqual(self.model.optimize(), "optimal")

    def test_raise_on_non_linear_objective(self):
        """Test that an exception is raised when a non-linear objective is added to the model."""
        v1, v2 = self.model.variables.values()[0:2]
        self.assertRaises(ValueError, self.interface.Objective, v1 * v2 ** 3)

    @abc.abstractmethod
    def test_iadd_objective(self):
        pass

    @abc.abstractmethod
    def test_imul_objective(self):
        pass

    @abc.abstractmethod
    def test_set_copied_objective(self):
        pass

    @abc.abstractmethod
    def test_timeout(self):
        pass

    @abc.abstractmethod
    def test_set_linear_coefficients_objective(self):
        pass

    def test_instantiating_model_with_different_solver_problem_raises(self):
        self.assertRaises(TypeError, self.interface.Model, problem='Chicken soup')

    @abc.abstractmethod
    def test_set_linear_coefficients_constraint(self):
        pass

    def test_primal_values(self):
        self.model.optimize()
        primals = self.model.primal_values
        for var in self.model.variables:
            self.assertEqual(var.primal, primals[var.name])
        self.assertEqual(set(var.name for var in self.model.variables), set(primals))

    def test_reduced_costs(self):
        self.model.optimize()
        reduced_costs = self.model.reduced_costs
        for var in self.model.variables:
            self.assertEqual(var.dual, reduced_costs[var.name])
        self.assertEqual(set(var.name for var in self.model.variables), set(reduced_costs))

    def test_dual_values(self):
        self.model.optimize()
        constraint_primals = self.model.constraint_values  # TODO Fix this method name
        for constraint in self.model.constraints:
            self.assertEqual(constraint.primal, constraint_primals[constraint.name])
        self.assertEqual(set(const.name for const in self.model.constraints), set(constraint_primals))

    def test_shadow_prices(self):
        self.model.optimize()
        shadow_prices = self.model.shadow_prices
        for constraint in self.model.constraints:
            self.assertEqual(constraint.dual, shadow_prices[constraint.name])
        self.assertEqual(set(const.name for const in self.model.constraints), set(shadow_prices))

    def test_change_objective_can_handle_removed_vars(self):
        self.model.objective = self.interface.Objective(self.model.variables[0])
        self.model.remove(self.model.variables[0])
        self.model.update()
        self.model.objective = self.interface.Objective(self.model.variables[1] * 2)

    def test_clone_model_with_json(self):
        self.assertEquals(self.model.configuration.verbosity, 0)
        self.model.configuration.verbosity = 3
        self.model.optimize()
        opt = self.model.objective.value
        cloned_model = self.interface.Model.clone(self.model)
        self.assertEquals(cloned_model.configuration.verbosity, 3)
        self.assertEquals(len(cloned_model.variables), len(self.model.variables))
        self.assertEquals(len(cloned_model.constraints), len(self.model.constraints))
        cloned_model.optimize()
        self.assertAlmostEqual(cloned_model.objective.value, opt)

    def test_clone_model_with_lp(self):
        self.assertEquals(self.model.configuration.verbosity, 0)
        self.model.configuration.verbosity = 3
        self.model.optimize()
        opt = self.model.objective.value
        cloned_model = self.interface.Model.clone(self.model, use_lp=True)
        self.assertEquals(cloned_model.configuration.verbosity, 3)
        self.assertEquals(len(cloned_model.variables), len(self.model.variables))
        self.assertEquals(len(cloned_model.constraints), len(self.model.constraints))
        cloned_model.optimize()
        self.assertAlmostEqual(cloned_model.objective.value, opt)

    def test_clone_model_without_json(self):
        self.assertEquals(self.model.configuration.verbosity, 0)
        self.model.configuration.verbosity = 3
        self.model.optimize()
        opt = self.model.objective.value
        cloned_model = self.interface.Model.clone(self.model, use_json=False)
        self.assertEquals(cloned_model.configuration.verbosity, 3)
        self.assertEquals(len(cloned_model.variables), len(self.model.variables))
        self.assertEquals(len(cloned_model.constraints), len(self.model.constraints))
        cloned_model.optimize()
        self.assertAlmostEqual(cloned_model.objective.value, opt)

    def test_remove_variable_not_in_model_raises(self):
        var = self.interface.Variable("test")
        self.assertRaises(Exception, self.model._remove_variables, [var])

    def test_objective_set_linear_coefficients(self):
        x = self.interface.Variable("x", lb=0)
        y = self.interface.Variable("y", lb=0)
        c1 = self.interface.Constraint((y + 2 * (x - 3)).expand(), ub=0)
        c2 = self.interface.Constraint(y + (1 / 2) * x - 3, ub=0)
        obj = self.interface.Objective(x)
        model = self.interface.Model()
        model.add([c1, c2])
        model.objective = obj

        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 3)
        self.assertAlmostEqual(y.primal, 0)

        obj.set_linear_coefficients({y: 1})
        self.assertEqual(float((obj.expression - (x + y)).expand()), 0.0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 2)
        self.assertAlmostEqual(y.primal, 2)

        obj.set_linear_coefficients({x: 0})
        self.assertEqual(float((obj.expression - y).expand()), 0.0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 0)
        self.assertAlmostEqual(y.primal, 3)

    def test_constraint_set_linear_coefficients(self):
        x = self.interface.Variable("x", lb=0, ub=1000)
        y = self.interface.Variable("y", lb=0)
        c1 = self.interface.Constraint(y, ub=1)
        obj = self.interface.Objective(x)
        model = self.interface.Model()
        model.add([c1])
        model.objective = obj

        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, x.ub)

        c1.set_linear_coefficients({x: 1})
        self.assertEqual((c1.expression - (x + y)).expand() - 0, 0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 1)

        c1.set_linear_coefficients({x: 2})
        self.assertEqual((c1.expression - (2 * x + y)).expand() - 0, 0)
        self.assertEqual(model.optimize(), optlang.interface.OPTIMAL)
        self.assertAlmostEqual(x.primal, 0.5)

    def test_objective_handles_constants_2(self):
        offset = 2
        self.model.optimize()
        optimal = self.model.objective.value
        objective = self.interface.Objective(self.model.objective.expression + offset)
        self.model.objective = objective
        self.model.optimize()
        self.assertAlmostEqual(self.model.objective.value, optimal + offset)

    # def test_objective_handles_constants_3(self):
    #     offset = 3
    #     self.model.optimize()
    #     optimal = self.model.objective.value
    #     self.model.objective += offset
    #     self.model.optimize()
    #     self.assertEqual(self.model.objective.value, optimal + offset)

    def test_objective_expression_includes_constant(self):
        objective = self.model.objective
        self.model.objective = self.interface.Objective(objective.expression + 3)
        self.model.update()
        self.assertEqual((self.model.objective.expression - (objective.expression + 3.)).expand(), 0.)

    def test_is_integer(self):
        model = self.model
        self.assertFalse(model.is_integer)
        self.assertFalse(optlang.interface.Model.is_integer.fget(model))

        model.variables[0].type = "integer"
        self.assertTrue(model.is_integer)
        self.assertTrue(optlang.interface.Model.is_integer.fget(model))

        model.variables[0].type = "continuous"
        model.variables[1].type = "binary"
        self.assertTrue(model.is_integer)

        model.variables[1].type = "continuous"
        self.assertFalse(model.is_integer)

    def test_binary_variables(self):
        model = self.interface.Model()
        var = self.interface.Variable("x", type="binary")
        obj = self.interface.Objective(var)
        model.objective = obj

        for lb, ub in ((0, 0), (0, 1), (1, 1)):
            var.ub = ub
            var.lb = lb

            obj.direction = "max"
            model.optimize()
            self.assertAlmostEqual(var.primal, ub)

            obj.direction = "min"
            model.optimize()
            self.assertAlmostEqual(var.primal, lb)

    def test_integer_variable_dual(self):
        model = self.interface.Model()
        x = self.interface.Variable("x", lb=0)
        y = self.interface.Variable("y", lb=0)
        c = self.interface.Constraint(x + y, ub=1)
        model.add(c)
        model.objective = self.interface.Objective(x)

        model.optimize()
        self.assertEqual(y.dual, -1)

        x.type = "integer"
        model.optimize()
        self.assertRaises(ValueError, partial(getattr, y, "dual"))

        x.type = "continuous"
        model.optimize()
        self.assertEqual(y.dual, -1)

    def test_integer_constraint_dual(self):
        model = self.interface.Model()
        x = self.interface.Variable("x")
        c = self.interface.Constraint(x, ub=1)
        model.add(c)
        model.objective = self.interface.Objective(x)

        model.optimize()
        self.assertEqual(c.dual, 1)

        x.type = "integer"
        model.optimize()
        self.assertRaises(ValueError, partial(getattr, c, "dual"))

        x.type = "continuous"
        model.optimize()
        self.assertEqual(c.dual, 1)

    def test_integer_batch_duals(self):
        model = self.interface.Model()
        x = self.interface.Variable("x")
        c = self.interface.Constraint(x, ub=1)
        model.add(c)
        model.objective = self.interface.Objective(x)
        model.optimize()

        self.assertEqual(model.reduced_costs[x.name], 0)
        self.assertEqual(model.shadow_prices[c.name], 1)

        x.type = "integer"
        model.optimize()

        with self.assertRaises(ValueError):
            model.reduced_costs
        with self.assertRaises(ValueError):
            model.shadow_prices

        x.type = "continuous"
        model.optimize()

        self.assertEqual(model.reduced_costs[x.name], 0)
        self.assertEqual(model.shadow_prices[c.name], 1)

    def test_large_objective(self):
        model = self.interface.Model()
        model.add([self.interface.Variable(str(i), lb=1) for i in range(1100)])
        model.optimize()

        obj = self.interface.Objective(
            optlang.symbolics.add([optlang.symbolics.mul((optlang.symbolics.One, v)) for v in model.variables]),
            direction="min"
        )
        model.objective = obj
        model.optimize()
        self.assertAlmostEqual(model.objective.value, len(model.variables))

    def test_implicitly_convert_milp_to_lp(self):
        model = self.interface.Model()
        var1 = self.interface.Variable("x", ub=1)
        var2 = self.interface.Variable("y", type="integer")
        var3 = self.interface.Variable("z", type="integer")
        model.add([var1, var2])
        model.optimize()
        self.assertTrue(model.is_integer)

        var2.type = "continuous"
        model.optimize()
        self.assertAlmostEqual(model.reduced_costs["x"], 0)

        var2.type = "integer"
        model.add(var3)
        model.optimize()
        self.assertTrue(model.is_integer)

        model.remove(var2)
        model.optimize()
        model.remove(var3)
        model.optimize()
        self.assertAlmostEqual(model.reduced_costs["x"], 0)



@six.add_metaclass(abc.ABCMeta)
class AbstractConfigurationTestCase(unittest.TestCase):

    def setUp(self):
        pass

    def test_tolerance_parameters(self):
        model = self.interface.Model()
        params = dir(model.configuration.tolerances)
        for param in params:
            val = getattr(model.configuration.tolerances, param)
            setattr(model.configuration.tolerances, param, 2 * val)
            self.assertEqual(
                getattr(model.configuration.tolerances, param), 2 * val
            )


@six.add_metaclass(abc.ABCMeta)
class AbstractQuadraticProgrammingTestCase(unittest.TestCase):
    @abc.abstractmethod
    def setUp(self):
        pass

    @abc.abstractmethod
    def test_convex_obj(self):
        pass

    @abc.abstractmethod
    def test_non_convex_obj(self):
        pass

    @abc.abstractmethod
    def test_qp_convex(self):
        pass

    @abc.abstractmethod
    def test_qp_non_convex(self):
        pass

# Copyright 2016 Novo Nordisk Foundation Center for Biosustainability, # Technical University of Denmark. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # Sympy numbers should be valid bounds # Sympy numbers should be valid bounds Test that an exception is raised when a non-linear objective is added to the model. # TODO Fix this method name # def test_objective_handles_constants_3(self): #     offset = 3 #     self.model.optimize() #     optimal = self.model.objective.value #     self.model.objective += offset #     self.model.optimize() #     self.assertEqual(self.model.objective.value, optimal + offset)