def _generate_model(self):
self.model = pmo.block()
model = self.model
model._name = self.description
model.b = pmo.block()
model.B = pmo.block_dict((i, pmo.block())
for i in range(1,4))
model.a = pmo.parameter(value=1.0)
model.b.x = pmo.variable(lb=0)
model.B[1].x = pmo.variable(lb=0)
model.obj = pmo.objective(expr=model.b.x + 3.0*model.B[1].x)
model.obj.deactivate()
model.B[2].c = pmo.constraint(expr=-model.B[1].x <= -model.a)
model.B[2].obj = pmo.objective(expr=model.b.x + 3.0*model.B[1].x + 2)
model.B[3].c = pmo.constraint(expr=(2.0, model.b.x/model.a - model.B[1].x, 10))
def _generate_model(self):
self.model = pmo.block()
model = self.model
model._name = self.description
model.b = pmo.block()
model.B = pmo.block_dict((i, pmo.block()) for i in range(1, 4))
model.a = pmo.parameter(value=1.0)
model.b.x = pmo.variable(lb=0)
model.B[1].x = pmo.variable(lb=0)
model.obj = pmo.objective(expr=model.b.x + 3.0 * model.B[1].x)
model.obj.deactivate()
model.B[2].c = pmo.constraint(expr=-model.B[1].x <= -model.a)
model.B[2].obj = pmo.objective(expr=model.b.x + 3.0 * model.B[1].x + 2)
model.B[3].c = pmo.constraint(
expr=2.0 <= model.b.x / model.a - model.B[1].x <= 10)
def _generate_model(self):
self.model = pmo.block()
model = self.model
model._name = self.description
model.s = [1,2]
model.x = pmo.variable()
model.y = pmo.variable()
model.z = pmo.variable(lb=0)
model.obj = pmo.objective_dict()
for i in model.s:
model.obj[i] = pmo.objective(
inactive_index_LP_obj_rule(model,i))
model.OBJ = pmo.objective(model.x+model.y)
model.obj[1].deactivate()
model.OBJ.deactivate()
model.c1 = pmo.constraint_dict()
model.c1[1] = pmo.constraint(model.x<=1)
model.c1[2] = pmo.constraint(model.x>=-1)
model.c1[3] = pmo.constraint(model.y<=1)
model.c1[4] = pmo.constraint(model.y>=-1)
model.c1[1].deactivate()
model.c1[4].deactivate()
model.c2 = pmo.constraint_dict()
for i in model.s:
model.c2[i] = pmo.constraint(
inactive_index_LP_c2_rule(model, i))
model.b = pmo.block()
model.b.c = pmo.constraint(model.z >= 2)
model.B = pmo.block_dict()
model.B[1] = pmo.block()
model.B[1].c = pmo.constraint(model.z >= 3)
model.B[2] = pmo.block()
model.B[2].c = pmo.constraint(model.z >= 1)
model.b.deactivate()
model.B.deactivate()
model.B[2].activate()
def _generate_model(self):
self.model = pmo.block()
model = self.model
model._name = self.description
model.s = [1,2]
model.x = pmo.variable()
model.y = pmo.variable()
model.z = pmo.variable(lb=0)
model.obj = pmo.objective_dict()
for i in model.s:
model.obj[i] = pmo.objective(
inactive_index_LP_obj_rule(model,i))
model.OBJ = pmo.objective(model.x+model.y)
model.obj[1].deactivate()
model.OBJ.deactivate()
model.c1 = pmo.constraint_dict()
model.c1[1] = pmo.constraint(model.x<=1)
model.c1[2] = pmo.constraint(model.x>=-1)
model.c1[3] = pmo.constraint(model.y<=1)
model.c1[4] = pmo.constraint(model.y>=-1)
model.c1[1].deactivate()
model.c1[4].deactivate()
model.c2 = pmo.constraint_dict()
for i in model.s:
model.c2[i] = pmo.constraint(
inactive_index_LP_c2_rule(model, i))
model.b = pmo.block()
model.b.c = pmo.constraint(model.z >= 2)
model.B = pmo.block_dict()
model.B[1] = pmo.block()
model.B[1].c = pmo.constraint(model.z >= 3)
model.B[2] = pmo.block()
model.B[2].c = pmo.constraint(model.z >= 1)
model.b.deactivate()
model.B[1].deactivate()
def _generate_model(self):
self.model = pmo.block()
model = self.model
model._name = self.description
model.s = [1, 2]
model.x_unused = pmo.variable(domain=pmo.IntegerSet)
model.x_unused.stale = False
model.x_unused_initialy_stale = pmo.variable(domain=pmo.IntegerSet)
model.x_unused_initialy_stale.stale = True
model.X_unused = pmo.variable_dict(
(i, pmo.variable(domain=pmo.IntegerSet)) for i in model.s)
model.X_unused_initialy_stale = pmo.variable_dict(
(i, pmo.variable(domain=pmo.IntegerSet)) for i in model.s)
for i in model.s:
model.X_unused[i].stale = False
model.X_unused_initialy_stale[i].stale = True
model.x = pmo.variable(domain=RangeSet(None, None))
model.x.stale = False
model.x_initialy_stale = pmo.variable(domain=pmo.IntegerSet)
model.x_initialy_stale.stale = True
model.X = pmo.variable_dict(
(i, pmo.variable(domain=pmo.IntegerSet)) for i in model.s)
model.X_initialy_stale = pmo.variable_dict(
(i, pmo.variable(domain=pmo.IntegerSet)) for i in model.s)
for i in model.s:
model.X[i].stale = False
model.X_initialy_stale[i].stale = True
model.obj = pmo.objective(model.x + \
model.x_initialy_stale + \
sum(model.X.values()) + \
sum(model.X_initialy_stale.values()))
model.c = pmo.constraint_dict()
model.c[1] = pmo.constraint(model.x >= 1)
model.c[2] = pmo.constraint(model.x_initialy_stale >= 1)
model.c[3] = pmo.constraint(model.X[1] >= 0)
model.c[4] = pmo.constraint(model.X[2] >= 1)
model.c[5] = pmo.constraint(model.X_initialy_stale[1] >= 0)
model.c[6] = pmo.constraint(model.X_initialy_stale[2] >= 1)
# Test that stale flags do not get updated
# on inactive blocks (where "inactive blocks" mean blocks
# that do NOT follow a path of all active parent blocks
# up to the top-level model)
flat_model = model.clone()
model.b = pmo.block()
model.B = pmo.block_dict()
model.b.b = flat_model.clone()
model.B[1] = pmo.block()
model.B[1].b = flat_model.clone()
model.B[2] = pmo.block()
model.B[2].b = flat_model.clone()
model.b.deactivate()
model.B.deactivate(shallow=False)
model.b.b.activate()
model.B[1].b.activate()
model.B[2].b.deactivate()
assert model.b.active is False
assert model.B[1].active is False
assert model.B[1].active is False
assert model.b.b.active is True
assert model.B[1].b.active is True
assert model.B[2].b.active is False
#
# uses OrderedDict when ordered=True
vd = pmo.variable_dict(((str(i), pmo.variable()) for i in range(10)),
ordered=True)
cd = pmo.constraint_dict((i, pmo.constraint(v == 1)) for i, v in vd.items())
cd = pmo.constraint_dict()
for i, v in vd.items():
cd[i] = pmo.constraint(v == 1)
cd = pmo.constraint_dict()
cd.update((i, pmo.constraint()) for i, v in vd.items())
cd[None] = pmo.constraint()
del cd[None]
#
# Nesting containers
#
b = pmo.block()
b.bd = pmo.block_dict()
b.bd[None] = pmo.block_dict()
b.bd[None][1] = pmo.block()
b.bd[None][1].x = pmo.variable()
b.bd['a'] = pmo.block_list()
b.bd['a'].append(pmo.block())
#
vd = pmo.variable_dict(
((str(i), pmo.variable()) for i in range(10)))
cd = pmo.constraint_dict(
(i, pmo.constraint(v == 1)) for i,v in vd.items())
cd = pmo.constraint_dict()
for i, v in vd.items():
cd[i] = pmo.constraint(v == 1)
cd = pmo.constraint_dict()
cd.update((i, pmo.constraint()) for i,v in vd.items())
cd[None] = pmo.constraint()
del cd[None]
#
# Nesting containers
#
b = pmo.block()
b.bd = pmo.block_dict()
b.bd[None] = pmo.block_dict()
b.bd[None][1] = pmo.block()
b.bd[None][1].x = pmo.variable()
b.bd['a'] = pmo.block_list()
b.bd['a'].append(pmo.block())
def _generate_model(self):
self.model = None
self.model = pmo.block()
model = self.model
model._name = self.description
model.s = [1,2]
model.x_unused = pmo.variable()
model.x_unused.stale = False
model.x_unused_initialy_stale = pmo.variable()
model.x_unused_initialy_stale.stale = True
model.X_unused = pmo.variable_dict(
(i, pmo.variable()) for i in model.s)
model.X_unused_initialy_stale = pmo.variable_dict(
(i, pmo.variable()) for i in model.s)
for i in model.X_unused:
model.X_unused[i].stale = False
model.X_unused_initialy_stale[i].stale = True
model.x = pmo.variable()
model.x.stale = False
model.x_initialy_stale = pmo.variable()
model.x_initialy_stale.stale = True
model.X = pmo.variable_dict(
(i, pmo.variable()) for i in model.s)
model.X_initialy_stale = pmo.variable_dict(
(i, pmo.variable()) for i in model.s)
for i in model.X:
model.X[i].stale = False
model.X_initialy_stale[i].stale = True
model.obj = pmo.objective(model.x + \
model.x_initialy_stale + \
sum(model.X.values()) + \
sum(model.X_initialy_stale.values()))
model.c = pmo.constraint_dict()
model.c[1] = pmo.constraint(model.x >= 1)
model.c[2] = pmo.constraint(model.x_initialy_stale >= 1)
model.c[3] = pmo.constraint(model.X[1] >= 0)
model.c[4] = pmo.constraint(model.X[2] >= 1)
model.c[5] = pmo.constraint(model.X_initialy_stale[1] >= 0)
model.c[6] = pmo.constraint(model.X_initialy_stale[2] >= 1)
# Test that stale flags do not get updated
# on inactive blocks (where "inactive blocks" mean blocks
# that do NOT follow a path of all active parent blocks
# up to the top-level model)
flat_model = model.clone()
model.b = pmo.block()
model.B = pmo.block_dict()
model.B[1] = pmo.block()
model.B[2] = pmo.block()
model.b.b = flat_model.clone()
model.B[1].b = flat_model.clone()
model.B[2].b = flat_model.clone()
model.b.deactivate()
model.B.deactivate(shallow=False)
model.b.b.activate()
model.B[1].b.activate()
model.B[2].b.deactivate()
assert model.b.active is False
assert model.B[1].active is False
assert model.B[1].active is False
assert model.b.b.active is True
assert model.B[1].b.active is True
assert model.B[2].b.active is False
