Changeset 783

Timestamp:

02/18/15 08:17:08 (15 months ago)

Author:

mmckerns

Message:

fix: add _SetEvaluationLimits to ensemble CheckTermination?;
Step now expects settings at each call in Solve

Location:

mystic/mystic

Files:

• abstract_ensemble_solver.py (modified) (1 diff)
• abstract_solver.py (modified) (1 diff)
• differential_evolution.py (modified) (6 diffs)

mystic/mystic/abstract_ensemble_solver.py

@@ -225 +225 @@
         if termination is None:
             termination = solver._termination
-
+        # ensure evaluation limits have been imposed
+        self._SetEvaluationLimits()
         # check for termination messages
         msg = termination(solver, info=True)

mystic/mystic/abstract_solver.py

@@ -718 +718 @@
         # the initital optimization iteration
         if not len(self._stepmon): # do generation = 0
-            self.Step(callback=callback)
+            self.Step(**settings)  # includes settings['callback']
 
         # the main optimization loop

mystic/mystic/differential_evolution.py

@@ -216 +216 @@
         return cost
 
-    def Step(self, cost=None, ExtraArgs=None, strategy=None, **kwds):
+    def Step(self, cost=None, ExtraArgs=None, **kwds):
         """perform a single optimization iteration
         Note that ExtraArgs should be a *tuple* of extra arguments"""
@@ -222 +222 @@
         cost = self._bootstrap_objective(cost, ExtraArgs)
         # process and activate input settings
-        kwds['strategy'] = strategy  # override default strategy
         settings = self._process_inputs(kwds)
         for key in settings:
@@ -231 +230 @@
         if not len(self._stepmon): # do generation = 0
             init = True
+            strategy = None
             self.population[0] = asfarray(self.population[0])
             # decouple bestSolution from population and bestEnergy from popEnergy
@@ -381 +381 @@
         return cost
 
-    def Step(self, cost=None, ExtraArgs=None, strategy=None, **kwds):
+    def Step(self, cost=None, ExtraArgs=None, **kwds):
         """perform a single optimization iteration
         Note that ExtraArgs should be a *tuple* of extra arguments"""
@@ -387 +387 @@
         cost = self._bootstrap_objective(cost, ExtraArgs)
         # process and activate input settings
-        kwds['strategy'] = strategy  # override default strategy
         settings = self._process_inputs(kwds)
         for key in settings:
@@ -396 +395 @@
         if not len(self._stepmon): # do generation = 0
             init = True
+            strategy = None
             self.population[0] = asfarray(self.population[0])
             # decouple bestSolution from population and bestEnergy from popEnergy