def test_running_NNAUTILUS():
method = NNAUTILUS(
PreGeneratedProblem(
filename=os.path.join(example_path, "AuxiliaryServices.csv")
),
PointSearch,
)
vals = run(method, [-43000, 2, -60], 6)
assert len(vals) == 6
def test_running_NIMBUS():
vals = []
method = NIMBUS(
PreGeneratedProblem(
filename=os.path.join(example_path, "AuxiliaryServices.csv")),
PointSearch)
run1 = run(
method,
NIMBUSClassification(method.problem, [("<", None), (">=", 1),
("<", None)]))
assert run1[0][1] < 1
assert len(run1) == 2
# When using point search, there should not be better solutions when projected
cls = []
for v in run1[0]:
cls.append(("<=", v))
run2 = run(method, NIMBUSClassification(method.problem, cls))
assert np.isclose(run1[0], run2[1]).all() # pylint: disable=E1101
def test_point_search():
method = NIMBUS(
PreGeneratedProblem(
filename=os.path.join(example_path, "AuxiliaryServices.csv")
),
PointSearch,
)
run1 = run(
method, NIMBUSClassification(method, [("<", None), (">=", 1), ("<", None)])
)
assert run1.objective_vars[0][1] >= 1
assert len(run1.items) == 4
# When using point search, there should not be better solutions when projected
cls = []
for v in run1.objective_vars[0]:
cls.append(("<=", v))
run2 = run(method, NIMBUSClassification(method, cls))
assert np.isclose(
run1.objective_vars[0], run2.objective_vars[1]
).all() # pylint: disable=E1101
import sys, os
example_path = os.path.dirname(os.path.realpath(__file__))
sys.path.append(os.path.join(example_path, ".."))
from desdeo.utils import tui
from desdeo.method.NAUTILUS import NAUTILUSv1, ENAUTILUS
from desdeo.optimization.OptimizationMethod import PointSearch
from desdeo.problem.Problem import PreGeneratedProblem
if __name__ == '__main__':
# SciPy breaks box constraints
method = ENAUTILUS(
PreGeneratedProblem(
filename=os.path.join(example_path, "AuxiliaryServices.csv")),
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(
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")
ci = method.current_iter
if ci > 0:
try:
from prompt_toolkit import prompt
weights = prompt(u'Weights (10 or 20): ',
default=u"20",
validator=tui.NumberValidator())
except:
weights = "20"
factory = IterationPointFactory(
SciPyDE(AchievementProblem(NaurulaWeistroffer())))
points = misc.new_points(factory, solution, WEIGHTS[weights])
method = ENAUTILUS(PreGeneratedProblem(points=points), PointSearch)
method.current_iter = ci
method.zh_prev = solution
print("E-NAUTILUS\nselected iteration point: %s:" %
",".join(map(str, method.zh_prev)))
while method.current_iter > 0:
if solution is None:
solution = method.problem.nadir
# Generate new points
# print solution
method.problem.nadir = nadir
method.problem.ideal = ideal
tui.iter_enautilus(method)
solution = method.zh_prev