def test_backmap_deprecated(self):
m = ConcreteModel()
m.s = RangeSet(3)
m.Y = BooleanVar(m.s)
TransformationFactory('core.logical_to_linear').apply_to(m)
output = StringIO()
with LoggingIntercept(output, 'pyomo.core.base', logging.WARNING):
y1 = m.Y[1].get_associated_binary()
self.assertIn(
"DEPRECATED: Relying on core.logical_to_linear to "
"transform BooleanVars that do not appear in "
"LogicalConstraints is deprecated. Please "
"associate your own binaries if you have BooleanVars "
"not used in logical expressions.",
output.getvalue().replace('\n', ' '))
output = StringIO()
with LoggingIntercept(output, 'pyomo.core.base', logging.WARNING):
y2 = m.Y[2].get_associated_binary()
self.assertIn(
"DEPRECATED: Relying on core.logical_to_linear to "
"transform BooleanVars that do not appear in "
"LogicalConstraints is deprecated. Please "
"associate your own binaries if you have BooleanVars "
"not used in logical expressions.",
output.getvalue().replace('\n', ' '))
y1.value = 1
y2.value = 0
update_boolean_vars_from_binary(m)
self.assertTrue(m.Y[1].value)
self.assertFalse(m.Y[2].value)
self.assertIsNone(m.Y[3].value)
def test_backmap(self):
m = _generate_boolean_model(3)
TransformationFactory('core.logical_to_linear').apply_to(m)
m.Y_asbinary[1].value = 1
m.Y_asbinary[2].value = 0
update_boolean_vars_from_binary(m)
self.assertTrue(m.Y[1].value)
self.assertFalse(m.Y[2].value)
self.assertIsNone(m.Y[3].value)
def test_backmap_noninteger(self):
m = _generate_boolean_model(2)
TransformationFactory('core.logical_to_linear').apply_to(m)
m.Y_asbinary[1].value = 0.9
update_boolean_vars_from_binary(m, integer_tolerance=0.1)
self.assertTrue(m.Y[1].value)
# Now try it without the tolerance set
with self.assertRaisesRegexp(ValueError, r"Binary variable has non-\{0,1\} value"):
update_boolean_vars_from_binary(m)
def test_backmap_hierarchical_model(self):
m = _generate_boolean_model(3)
m.b = Block()
m.b.Y = BooleanVar()
m.b.lc = LogicalConstraint(expr=m.Y[1].lor(m.b.Y))
TransformationFactory('core.logical_to_linear').apply_to(m)
m.Y_asbinary[1].value = 1
m.Y_asbinary[2].value = 0
m.b.Y.get_associated_binary().value = 1
update_boolean_vars_from_binary(m)
self.assertTrue(m.Y[1].value)
self.assertFalse(m.Y[2].value)
self.assertIsNone(m.Y[3].value)
self.assertTrue(m.b.Y.value)
m.use4implies6or7 = LogicalConstraint(
expr=m.Y[4].implies(lor(m.Y[6], m.Y[7])))
m.use3implies8 = LogicalConstraint(expr=m.Y[3].implies(m.Y[8]))
m.use6or7implies4 = LogicalConstraint(
expr=lor(m.Y[6], m.Y[7]).implies(m.Y[4]))
m.use6or7 = LogicalConstraint(expr=m.Y[6].xor(m.Y[7]))
"""Profit (objective) function definition"""
m.profit = Objective(expr=sum(m.yCF[unit] for unit in m.units) +
sum(m.flow[stream] * CV[stream]
for stream in m.streams) + CONSTANT,
sense=minimize)
"""Bound definitions"""
# x (flow) upper bounds
x_ubs = {3: 2, 5: 2, 9: 2, 10: 1, 14: 1, 17: 2, 19: 2, 21: 2, 25: 3}
for i, x_ub in x_ubs.item():
m.flow[i].setub(x_ub)
# Optimal solution uses units 2, 4, 6, 8 with objective value 68.
return m
if __name__ == "__main__":
m = build_eight_process_flowsheet()
from pyomo.environ import TransformationFactory
TransformationFactory('core.logical_to_linear').apply_to(m)
SolverFactory('gdpopt').solve(m, tee=True)
update_boolean_vars_from_binary(m)
m.Y.display()
m.flow.display()