def test_changing_variable_names_is_reflected_in_the_solver(self):
model = Model(problem=glpk_read_cplex(TESTMODELPATH))
for i, variable in enumerate(model.variables):
variable.name = "var" + str(i)
self.assertEqual(variable.name, "var" + str(i))
self.assertEqual(glp_get_col_name(model.problem, variable._index),
"var" + str(i))
def test_get_primal(self):
self.assertEqual(self.var.primal, None)
model = Model(problem=glpk_read_cplex(TESTMODELPATH))
model.optimize()
for i, j in zip([var.primal for var in model.variables], [
0.8739215069684306, -16.023526143167608, 16.023526143167604,
-14.71613956874283, 14.71613956874283, 4.959984944574658,
4.959984944574657, 4.959984944574658, 3.1162689467973905e-29,
2.926716099010601e-29, 0.0, 0.0, -6.112235045340358e-30,
-5.6659435396316186e-30, 0.0, -4.922925402711085e-29, 0.0,
9.282532599166613, 0.0, 6.00724957535033, 6.007249575350331,
6.00724957535033, -5.064375661482091, 1.7581774441067828, 0.0,
7.477381962160285, 0.0, 0.22346172933182767,
45.514009774517454, 8.39, 0.0, 6.007249575350331, 0.0,
-4.541857463865631, 0.0, 5.064375661482091, 0.0, 0.0,
2.504309470368734, 0.0, 0.0, -22.809833310204958,
22.809833310204958, 7.477381962160285, 7.477381962160285,
1.1814980932459636, 1.496983757261567, -0.0, 0.0,
4.860861146496815, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
5.064375661482091, 0.0, 5.064375661482091, 0.0, 0.0,
1.496983757261567, 10.000000000000002, -10.0, 0.0, 0.0, 0.0,
0.0, 0.0, -29.175827135565804, 43.598985311997524,
29.175827135565804, 0.0, 0.0, 0.0, -1.2332237321082153e-29,
3.2148950476847613, 38.53460965051542, 5.064375661482091, 0.0,
-1.2812714099825612e-29, -1.1331887079263237e-29,
17.530865429786694, 0.0, 0.0, 0.0, 4.765319193197458,
-4.765319193197457, 21.79949265599876, -21.79949265599876,
-3.2148950476847613, 0.0, -2.281503094067127,
2.6784818505075303, 0.0
]):
self.assertAlmostEqual(i, j)
def test_setting_bounds(self):
model = Model(problem=glpk_read_cplex(TESTMODELPATH))
var = model.variables[0]
var.lb = 1
self.assertEqual(var.lb, 1)
self.assertEqual(glpk_interface.glp_get_col_lb(model.problem, var.index), 1)
var.ub = 2
self.assertEqual(var.ub, 2)
self.assertEqual(glpk_interface.glp_get_col_ub(model.problem, var.index), 2)
def test_optimize_milp(self):
problem = glpk_read_cplex(TESTMILPMODELPATH)
milp_model = Model(problem=problem)
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_get_primal(self):
self.assertEqual(self.var.primal, None)
model = glpk_interface.Model(problem=glpk_read_cplex(TESTMODELPATH))
model.optimize()
for i, j in zip([var.primal for var in model.variables],
[0.8739215069684306, -16.023526143167608, 16.023526143167604, -14.71613956874283,
14.71613956874283, 4.959984944574658, 4.959984944574657, 4.959984944574658,
3.1162689467973905e-29, 2.926716099010601e-29, 0.0, 0.0, -6.112235045340358e-30,
-5.6659435396316186e-30, 0.0, -4.922925402711085e-29, 0.0, 9.282532599166613, 0.0,
6.00724957535033, 6.007249575350331, 6.00724957535033, -5.064375661482091, 1.7581774441067828,
0.0, 7.477381962160285, 0.0, 0.22346172933182767, 45.514009774517454, 8.39, 0.0,
6.007249575350331, 0.0, -4.541857463865631, 0.0, 5.064375661482091, 0.0, 0.0,
2.504309470368734, 0.0, 0.0, -22.809833310204958, 22.809833310204958, 7.477381962160285,
7.477381962160285, 1.1814980932459636, 1.496983757261567, -0.0, 0.0, 4.860861146496815, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 5.064375661482091, 0.0, 5.064375661482091, 0.0, 0.0,
1.496983757261567, 10.000000000000002, -10.0, 0.0, 0.0, 0.0, 0.0, 0.0, -29.175827135565804,
43.598985311997524, 29.175827135565804, 0.0, 0.0, 0.0, -1.2332237321082153e-29,
3.2148950476847613, 38.53460965051542, 5.064375661482091, 0.0, -1.2812714099825612e-29,
-1.1331887079263237e-29, 17.530865429786694, 0.0, 0.0, 0.0, 4.765319193197458,
-4.765319193197457, 21.79949265599876, -21.79949265599876, -3.2148950476847613, 0.0,
-2.281503094067127, 2.6784818505075303, 0.0]):
self.assertAlmostEqual(i, j)
def setUp(self):
self.model = Model(problem=glpk_read_cplex(TESTMODELPATH))
self.obj = self.model.objective
def setUp(self):
self.model = optlang.glpk_interface.Model(problem=glpk_read_cplex(TESTMODELPATH))
def setUp(self):
self.model = self.interface.Model(problem=glpk_read_cplex(TESTMODELPATH))
self.obj = self.model.objective
def test_changing_variable_names_is_reflected_in_the_solver(self):
model = self.interface.Model(problem=glpk_read_cplex(TESTMODELPATH))
for i, variable in enumerate(model.variables):
variable.name = "var" + str(i)
self.assertEqual(variable.name, "var" + str(i))
self.assertEqual(glp_get_col_name(model.problem, variable._index), "var" + str(i))
def test_get_dual(self):
self.assertEqual(self.var.dual, None)
model = Model(problem=glpk_read_cplex(TESTMODELPATH))
model.optimize()
for i, j in zip([var.dual for var in model.variables], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.022916186593776235, 0.0, 0.0, 0.0, -0.03437427989066435, 0.0, -0.007638728864592075, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.005092485909728057, 0.0, 0.0, 0.0, 0.0, -0.005092485909728046, 0.0, 0.0, -0.005092485909728045, 0.0, 0.0, 0.0, -0.0611098309167366, -0.005092485909728045, 0.0, -0.003819364432296033, -0.00509248590972805, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.03946676580039239, 0.0, 0.0, -0.005092485909728042, -0.0, -0.0012731214774320113, 0.0, -0.0916647463751049, 0.0, 0.0, 0.0, -0.0, -0.04583237318755246, 0.0, 0.0, -0.0916647463751049, -0.005092485909728045, -0.07002168125876067, 0.0, -0.06874855978132867, -0.0012731214774320113, 0.0, 0.0, 0.0, -0.001273121477432006, -0.0038193644322960392, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.040739887277824405, -0.04583237318755245, -0.0012731214774320163, 0.0, 0.0, 0.0, 0.0, 0.0, -0.03437427989066435, 0.0, 0.0, -0.04837861614241648]):
self.assertAlmostEqual(i, j)
def test_glpk_read_cplex():
problem = glpk_read_cplex(TESTMODELPATH)
nose.tools.assert_equal(glp_get_num_rows(problem), 72)
nose.tools.assert_equal(glp_get_num_cols(problem), 95)
def setUp(self):
self.model = Model(problem=glpk_read_cplex(TESTMODELPATH))
self.constraint = Constraint(Variable('chip') + Variable('chap'), name='woodchips', lb=100)
def test_setting_nonnumerical_bounds_raises(self):
model = Model(problem=glpk_read_cplex(TESTMODELPATH))
self.assertRaises(Exception, setattr, model.variables[0], 'lb', 'Chicken soup')
def test_setting_lower_bound_higher_than_upper_bound_raises(self):
model = Model(problem=glpk_read_cplex(TESTMODELPATH))
self.assertRaises(ValueError, setattr, model.variables[0], 'lb', 10000000000.)
def setUp(self):
self.model = optlang.glpk_interface.Model(
problem=glpk_read_cplex(TESTMODELPATH))
def test_glpk_read_cplex():
problem = glpk_read_cplex(TESTMODELPATH)
nose.tools.assert_equal(glp_get_num_rows(problem), 72)
nose.tools.assert_equal(glp_get_num_cols(problem), 95)
def setUp(self):
problem = glpk_read_cplex(TESTMODELPATH)
self.model = Model(problem=problem)