def test_abstract_model_example():
import pyomo.environ as pyomo
import os
def square(m):
return pyomo.quicksum((m.x[i] - 0.5)**2 for i in m.x)
abstract_model = pyomo.AbstractModel()
abstract_model.F = pyomo.Set()
abstract_model.Xmin = pyomo.Param(abstract_model.F,
within=pyomo.Reals,
default=0.0)
abstract_model.x = pyomo.Var(abstract_model.F, within=pyomo.Reals)
abstract_model.constraints = pyomo.Constraint(
abstract_model.F, rule=lambda m, i: m.x[i] >= m.Xmin[i])
abstract_model.obj = pyomo.Objective(rule=square)
import nevergrad as ng
import nevergrad.functions.pyomo as ng_pyomo
# Load the values of the parameters from external file
dirname = os.path.dirname(__file__)
data_path = os.path.join(dirname, "test_model_1.dat")
# DOC_ABSTRACT_100
data = pyomo.DataPortal()
data.load(filename=data_path, model=abstract_model)
model = abstract_model.create_instance(data)
# DOC_ABSTRACT_101
func = ng_pyomo.Pyomo(model)
optimizer = ng.optimizers.OnePlusOne(parametrization=func.parametrization,
budget=200)
recommendation = optimizer.minimize(func.function)
np.testing.assert_almost_equal(recommendation.kwargs['x["New York"]'],
model.Xmin["New York"],
decimal=1)
np.testing.assert_almost_equal(recommendation.kwargs['x["Hong Kong"]'],
model.Xmin["Hong Kong"],
decimal=1)
def test_concrete_model_example() -> None:
# DOC_CONCRETE_0
import pyomo.environ as pyomo
def square(m):
return pyomo.quicksum((m.x[i] - 0.5)**2 for i in m.x)
model = pyomo.ConcreteModel()
model.x = pyomo.Var([0, 1], domain=pyomo.Reals)
model.obj = pyomo.Objective(rule=square)
model.Constraint1 = pyomo.Constraint(rule=lambda m: m.x[0] >= 1)
model.Constraint2 = pyomo.Constraint(rule=lambda m: m.x[1] >= 0.8)
# DOC_CONCRETE_1
# DOC_CONCRETE_10
import nevergrad as ng
import nevergrad.functions.pyomo as ng_pyomo
# DOC_CONCRETE_11
# DOC_CONCRETE_100
func = ng_pyomo.Pyomo(model)
optimizer = ng.optimizers.OnePlusOne(parametrization=func.parametrization,
budget=100)
recommendation = optimizer.minimize(func.function)
# DOC_CONCRETE_101
# DOC_CONCRETE_1000
print(recommendation.kwargs["x[0]"])
print(recommendation.kwargs["x[1]"])
# DOC_CONCRETE_1001
np.testing.assert_almost_equal(recommendation.kwargs["x[0]"],
1.0,
decimal=1)
np.testing.assert_almost_equal(recommendation.kwargs["x[1]"],
0.8,
decimal=1)