set an evaluationType attribute to ants so that it can be understood if they...

set an evaluationType attribute to ants so that it can be understood if they were evaluated deterministically or stochastically

dream/plugins/Batches/BatchesStochasticACO.py

@@ -173,6 +173,7 @@ class BatchesStochasticACO(BatchesACO):
             self.rowIndex+=1
             ant['result'] = self.runOneScenario(ant['input'])['result']
             ant['score'] = self._calculateAntScore(ant)      
+            ant['evaluationType']='deterministic'
             self.outputSheet.write(self.rowIndex,2,'Units Throughput')
             self.outputSheet.write(self.rowIndex,3,-ant['score'])
             self.rowIndex+=1
@@ -203,6 +204,7 @@ class BatchesStochasticACO(BatchesACO):
             self.outputSheet.write(self.rowIndex,2,ant['key'])
             self.rowIndex+=1
             ant['result'] = self.runOneScenario(ant['input'])['result']
+            ant['evaluationType']='stochastic'
             ant['score'] = self.calculateStochasticAntScore(ant)
             self.outputSheet.write(self.rowIndex,2,'Average Units Throughput')
             self.outputSheet.write(self.rowIndex,3,-ant['score'])
@@ -210,11 +212,7 @@ class BatchesStochasticACO(BatchesACO):
         
         # for the ants that were not evaluated stochastically set score = 0
         for ant in antsInCurrentGeneration:
-            antEvaluatedStochastically=False
-            for stochasticAnt in antsForStochasticEvaluationInGeneration:
-                if ant['key'] == stochasticAnt['key']:
-                    antEvaluatedStochastically=True
-            if not antEvaluatedStochastically:
+            if ant['evaluationType']=='deterministic':
                 ant['score']=0
                   
         # if we had stochastic evaluation keep only those ants in sorting