PointSearch)
zh = tui.iter_enautilus(method)
ci = method.current_iter
if ci > 0:
if zh is None:
fh = zh = method.problem.nadir
fh_lo = method.problem.ideal
else:
zh = method.zh_prev
fh_lo = method.fh_lo_prev
fh = method.nsPoint_prev
method = NAUTILUSv1(
PreGeneratedProblem(
filename=os.path.join(example_path, "AuxiliaryServices.csv")),
PointSearch)
method.current_iter = ci + 1
method.zh_prev = method.zh = zh
method.fh = fh
method.fh_lo = fh_lo
# method.fh_lo=list(method.bounds_factory.result(method.zh_prev))
solution = tui.iter_nautilus(method)
method.printCurrentIteration()
try:
from prompt_toolkit import prompt
a = prompt(u'Press ENTER to exit')
except:
pass
* River pollution problem
"""
from desdeo.method import NIMBUS, NAUTILUSv1
from desdeo.optimization import SciPyDE
from desdeo.preference import NIMBUSClassification
from desdeo.problem.toy import RiverPollution
from desdeo.utils import tui
if __name__ == "__main__":
# Solve River Pollution problem using NAUTILUS
# Using tui
print("Solve with NAUTILUS method")
natmeth = NAUTILUSv1(RiverPollution(), SciPyDE)
NAUTILUS_solution = tui.iter_nautilus(natmeth)
print("NAUTILUS solution")
print(NAUTILUS_solution)
# Output:
# [-6.2927077117830965, -3.4038593790999485,
# -7.401394350956817, 1.6201876469013787]
# Continue solving River Pollution problem
# From NAUTILUS solution
nimmeth = NIMBUS(RiverPollution(), SciPyDE)
nimmeth.init_iteration()
print("Solving with NIMBUS method")
class1 = NIMBUSClassification(nimmeth, [(">=", -5.5), (">=", -3.0),
("<=", -6.5), ("<=", -2.0)])
iter1 = nimmeth.next_iteration(preference=class1)
def main(logfile=False):
""" Solve River Pollution problem with NAUTILUS V1 and E-NAUTILUS Methods
"""
# Duplicate output to log file
class NAUTILUSOptionValidator(Validator):
def validate(self, document):
if document.text not in "ao":
raise ValidationError(
message=
"Please select a for apriori or o for optimization option",
cursor_position=0,
)
if logfile:
Tee(logfile)
first = True
current_iter = 0
while first or current_iter:
# SciPy breaks box constraints
nautilus_v1 = NAUTILUSv1(RiverPollution(), SciPyDE)
if not first:
nautilus_v1.current_iter = current_iter
first = False
nadir = nautilus_v1.problem.nadir
ideal = nautilus_v1.problem.ideal
solution = tui.iter_nautilus(nautilus_v1)
current_iter = nautilus_v1.current_iter
# TODO: Move to tui module
method_e = None
if current_iter > 0:
option = _prompt_wrapper(
"select a for apriori or o for optimization option: ",
default="o",
validator=NAUTILUSOptionValidator(),
)
if option.lower() == "a":
wi = _prompt_wrapper(
"Number of PO solutions (10 or 20): ",
default="20",
validator=tui.NumberValidator(),
)
weights = WEIGHTS[wi]
factory = IterationPointFactory(
SciPyDE(NautilusAchievementProblem(RiverPollution())))
points = misc.new_points(factory, solution, weights=weights)
method_e = ENAUTILUS(PreGeneratedProblem(points=points),
PointSearch)
method_e.zh_prev = solution
else:
method_e = ENAUTILUS(RiverPollution(), SciPyDE)
# method_e.zh = solution
method_e.current_iter = nautilus_v1.current_iter
method_e.user_iters = nautilus_v1.user_iters
print("E-NAUTILUS\nselected iteration point: %s:" %
",".join(map(str, solution)))
while method_e and method_e.current_iter > 0:
if solution is None:
solution = method_e.problem.nadir
method_e.problem.nadir = nadir
method_e.problem.ideal = ideal
cmd = tui.iter_enautilus(method_e,
initial_iterpoint=solution,
initial_bound=method_e.fh_lo)
if cmd:
print(method_e.current_iter)
current_iter = method_e.current_iter
break
if tui.HAS_INPUT:
input("Press ENTER to exit")
[0.5, 0.1, 0.3, 0.1],
[0.5, 0.3, 0.1, 0.1],
[0.7, 0.1, 0.1, 0.1],
]
}
if __name__ == '__main__':
from desdeo.utils import tui
from desdeo.method import NAUTILUSv1
from desdeo.optimization import SciPyDE
# Solve River Pollution problem using NAUTILUS
# Using tui
method = NAUTILUSv1(RiverPollution(), SciPyDE)
NAUTILUS_solution = tui.iter_nautilus(method)[0]
print(method.problem.to_ui(NAUTILUS_solution))
# Output:
# [-6.2927077117830965, -3.4038593790999485,
# -7.401394350956817, 1.6201876469013787]
# Continue solving River Pollution problem
# From NAUTILUS solution
from desdeo.method import NIMBUS
from desdeo.preference import NIMBUSClassification
method = NIMBUS(RiverPollution(), SciPyDE)
method.selected_solution = NAUTILUS_solution[0]