def __init__(self,
evaluation_object,
evaluator=None,
name=None,
save_log=False):
if evaluator is not None:
self.evaluator = evaluator
else:
self._evaluator = None
self.evaluation_object = evaluation_object
if name is None:
try:
name = evaluation_object.name + '_optimization'
except AttributeError:
msg = '__init__() missing 1 required positional argument: \'name\''
raise TypeError(msg)
self.name = name
if save_log:
self.logger = log.get_logger(self.name, log_directory=self.name)
else:
self.logger = log.get_logger(self.name)
self._variables = []
self._objectives = []
self._nonlinear_constraints = []
self._linear_constraints = []
self._linear_equality_constraints = []
self._x0 = None
def __init__(self, stationarity_evaluator=None):
self.logger = get_logger('Simulation')
if stationarity_evaluator is None:
self._stationarity_evaluator = StationarityEvaluator()
else:
self.stationarity_evaluator = stationarity_evaluator
self.evaluate_stationarity = True
def optimize(self, optimization_problem, save_results=False, *args, **kwargs):
"""
"""
if not isinstance(optimization_problem, OptimizationProblem):
raise TypeError('Expected OptimizationProblem')
if save_results:
results_directory = optimization_problem.name
self.logger = get_logger(str(self), log_directory=results_directory)
log_time('Optimization', self.logger.level)(self.run)
log_results('Optimization', self.logger.level)(self.run)
log_exceptions('Optimization', self.logger.level)(self.run)
results = self.run(optimization_problem, *args, **kwargs)
if save_results:
results.save(results_directory)
return results
def __init__(self):
self.logger = get_logger(str(self))
def __init__(self):
self.logger = log.get_logger('StationarityEvaluator')