def test_inequality_binary(self): """ Test InequalityToEqualityConverter with binary variables """ op = QuadraticProgram() for i in range(3): op.binary_var(name='x{}'.format(i)) # Linear constraints linear_constraint = {'x0': 1, 'x1': 1} op.linear_constraint(linear_constraint, Constraint.Sense.EQ, 1, 'x0x1') linear_constraint = {'x1': 1, 'x2': -1} op.linear_constraint(linear_constraint, Constraint.Sense.LE, 2, 'x1x2') linear_constraint = {'x0': 1, 'x2': 3} op.linear_constraint(linear_constraint, Constraint.Sense.GE, 2, 'x0x2') # Quadratic constraints quadratic = {('x0', 'x1'): 1, ('x1', 'x2'): 2} op.quadratic_constraint({}, quadratic, Constraint.Sense.LE, 3, 'x0x1_x1x2LE') quadratic = {('x0', 'x1'): 3, ('x1', 'x2'): 4} op.quadratic_constraint({}, quadratic, Constraint.Sense.GE, 3, 'x0x1_x1x2GE') # Convert inequality constraints into equality constraints conv = InequalityToEquality() op2 = conv.convert(op) self.assertListEqual([v.name for v in op2.variables], [ 'x0', 'x1', 'x2', 'x1x2@int_slack', 'x0x2@int_slack', 'x0x1_x1x2LE@int_slack', 'x0x1_x1x2GE@int_slack' ]) # Check names and objective senses self.assertEqual(op.name, op2.name) self.assertEqual(op.objective.sense, op2.objective.sense) # For linear constraints lst = [ op2.linear_constraints[0].linear.to_dict()[0], op2.linear_constraints[0].linear.to_dict()[1], ] self.assertListEqual(lst, [1, 1]) self.assertEqual(op2.linear_constraints[0].sense, Constraint.Sense.EQ) lst = [ op2.linear_constraints[1].linear.to_dict()[1], op2.linear_constraints[1].linear.to_dict()[2], op2.linear_constraints[1].linear.to_dict()[3], ] self.assertListEqual(lst, [1, -1, 1]) lst = [op2.variables[3].lowerbound, op2.variables[3].upperbound] self.assertListEqual(lst, [0, 3]) self.assertEqual(op2.linear_constraints[1].sense, Constraint.Sense.EQ) lst = [ op2.linear_constraints[2].linear.to_dict()[0], op2.linear_constraints[2].linear.to_dict()[2], op2.linear_constraints[2].linear.to_dict()[4], ] self.assertListEqual(lst, [1, 3, -1]) lst = [op2.variables[4].lowerbound, op2.variables[4].upperbound] self.assertListEqual(lst, [0, 2]) self.assertEqual(op2.linear_constraints[2].sense, Constraint.Sense.EQ) # For quadratic constraints lst = [ op2.quadratic_constraints[0].quadratic.to_dict()[(0, 1)], op2.quadratic_constraints[0].quadratic.to_dict()[(1, 2)], op2.quadratic_constraints[0].linear.to_dict()[5], ] self.assertListEqual(lst, [1, 2, 1]) lst = [op2.variables[5].lowerbound, op2.variables[5].upperbound] self.assertListEqual(lst, [0, 3]) lst = [ op2.quadratic_constraints[1].quadratic.to_dict()[(0, 1)], op2.quadratic_constraints[1].quadratic.to_dict()[(1, 2)], op2.quadratic_constraints[1].linear.to_dict()[6], ] self.assertListEqual(lst, [3, 4, -1]) lst = [op2.variables[6].lowerbound, op2.variables[6].upperbound] self.assertListEqual(lst, [0, 4]) new_x = conv.interpret(np.arange(7)) np.testing.assert_array_almost_equal(new_x, np.arange(3))
def test_inequality_integer(self): """ Test InequalityToEqualityConverter with integer variables """ op = QuadraticProgram() for i in range(3): op.integer_var(name='x{}'.format(i), lowerbound=-3, upperbound=3) # Linear constraints linear_constraint = {'x0': 1, 'x1': 1} op.linear_constraint(linear_constraint, Constraint.Sense.EQ, 1, 'x0x1') linear_constraint = {'x1': 1, 'x2': -1} op.linear_constraint(linear_constraint, Constraint.Sense.LE, 2, 'x1x2') linear_constraint = {'x0': 1, 'x2': 3} op.linear_constraint(linear_constraint, Constraint.Sense.GE, 2, 'x0x2') # Quadratic constraints quadratic = {('x0', 'x1'): 1, ('x1', 'x2'): 2} op.quadratic_constraint({}, quadratic, Constraint.Sense.LE, 3, 'x0x1_x1x2LE') quadratic = {('x0', 'x1'): 3, ('x1', 'x2'): 4} op.quadratic_constraint({}, quadratic, Constraint.Sense.GE, 3, 'x0x1_x1x2GE') conv = InequalityToEquality() op2 = conv.convert(op) self.assertListEqual([v.name for v in op2.variables], [ 'x0', 'x1', 'x2', 'x1x2@int_slack', 'x0x2@int_slack', 'x0x1_x1x2LE@int_slack', 'x0x1_x1x2GE@int_slack' ]) # For linear constraints lst = [ op2.linear_constraints[0].linear.to_dict()[0], op2.linear_constraints[0].linear.to_dict()[1], ] self.assertListEqual(lst, [1, 1]) self.assertEqual(op2.linear_constraints[0].sense, Constraint.Sense.EQ) lst = [ op2.linear_constraints[1].linear.to_dict()[1], op2.linear_constraints[1].linear.to_dict()[2], op2.linear_constraints[1].linear.to_dict()[3], ] self.assertListEqual(lst, [1, -1, 1]) lst = [op2.variables[3].lowerbound, op2.variables[3].upperbound] self.assertListEqual(lst, [0, 8]) self.assertEqual(op2.linear_constraints[1].sense, Constraint.Sense.EQ) lst = [ op2.linear_constraints[2].linear.to_dict()[0], op2.linear_constraints[2].linear.to_dict()[2], op2.linear_constraints[2].linear.to_dict()[4], ] self.assertListEqual(lst, [1, 3, -1]) lst = [op2.variables[4].lowerbound, op2.variables[4].upperbound] self.assertListEqual(lst, [0, 10]) self.assertEqual(op2.linear_constraints[2].sense, Constraint.Sense.EQ) # For quadratic constraints lst = [ op2.quadratic_constraints[0].quadratic.to_dict()[(0, 1)], op2.quadratic_constraints[0].quadratic.to_dict()[(1, 2)], op2.quadratic_constraints[0].linear.to_dict()[5], ] self.assertListEqual(lst, [1, 2, 1]) lst = [op2.variables[5].lowerbound, op2.variables[5].upperbound] self.assertListEqual(lst, [0, 30]) lst = [ op2.quadratic_constraints[1].quadratic.to_dict()[(0, 1)], op2.quadratic_constraints[1].quadratic.to_dict()[(1, 2)], op2.quadratic_constraints[1].linear.to_dict()[6], ] self.assertListEqual(lst, [3, 4, -1]) lst = [op2.variables[6].lowerbound, op2.variables[6].upperbound] self.assertListEqual(lst, [0, 60]) result = OptimizationResult(x=np.arange(7), fval=0, variables=op2.variables) new_result = conv.interpret(result) np.testing.assert_array_almost_equal(new_result.x, np.arange(3)) self.assertListEqual(new_result.variable_names, ['x0', 'x1', 'x2']) self.assertDictEqual(new_result.variables_dict, { 'x0': 0, 'x1': 1, 'x2': 2 })