Changeset 783
- Timestamp:
- 02/18/15 08:17:08 (15 months ago)
- Location:
- mystic/mystic
- Files:
-
- 3 edited
Legend:
- Unmodified
- Added
- Removed
-
mystic/mystic/abstract_ensemble_solver.py
r776 r783 225 225 if termination is None: 226 226 termination = solver._termination 227 227 # ensure evaluation limits have been imposed 228 self._SetEvaluationLimits() 228 229 # check for termination messages 229 230 msg = termination(solver, info=True) -
mystic/mystic/abstract_solver.py
r782 r783 718 718 # the initital optimization iteration 719 719 if not len(self._stepmon): # do generation = 0 720 self.Step( callback=callback)720 self.Step(**settings) # includes settings['callback'] 721 721 722 722 # the main optimization loop -
mystic/mystic/differential_evolution.py
r782 r783 216 216 return cost 217 217 218 def Step(self, cost=None, ExtraArgs=None, strategy=None,**kwds):218 def Step(self, cost=None, ExtraArgs=None, **kwds): 219 219 """perform a single optimization iteration 220 220 Note that ExtraArgs should be a *tuple* of extra arguments""" … … 222 222 cost = self._bootstrap_objective(cost, ExtraArgs) 223 223 # process and activate input settings 224 kwds['strategy'] = strategy # override default strategy225 224 settings = self._process_inputs(kwds) 226 225 for key in settings: … … 231 230 if not len(self._stepmon): # do generation = 0 232 231 init = True 232 strategy = None 233 233 self.population[0] = asfarray(self.population[0]) 234 234 # decouple bestSolution from population and bestEnergy from popEnergy … … 381 381 return cost 382 382 383 def Step(self, cost=None, ExtraArgs=None, strategy=None,**kwds):383 def Step(self, cost=None, ExtraArgs=None, **kwds): 384 384 """perform a single optimization iteration 385 385 Note that ExtraArgs should be a *tuple* of extra arguments""" … … 387 387 cost = self._bootstrap_objective(cost, ExtraArgs) 388 388 # process and activate input settings 389 kwds['strategy'] = strategy # override default strategy390 389 settings = self._process_inputs(kwds) 391 390 for key in settings: … … 396 395 if not len(self._stepmon): # do generation = 0 397 396 init = True 397 strategy = None 398 398 self.population[0] = asfarray(self.population[0]) 399 399 # decouple bestSolution from population and bestEnergy from popEnergy
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