Multiple Inputs for dummy models

doc/workshop/optimizer/GeneticAlgorithms/Inputs/myConstraints.py

@@ -87,4 +87,4 @@ def impConstr2(Input):
     @ out, g, float, implicit constraint 2 evaluation function
   """
   g = Input.x1**2 + Input.obj - 10
-  return g
+  return g

doc/workshop/optimizer/GeneticAlgorithms/Models/Constraints.py

@@ -86,4 +86,4 @@ def impConstr2(Input):
     @ out, g, float, implicit constraint 2 evaluation function
   """
   g = Input.x1**2 + Input.obj - 10
-  return g
+  return g

doc/workshop/optimizer/GeneticAlgorithms/Models/LocalSum.py

@@ -40,4 +40,4 @@ def run(self,Inputs):
     @ In, Inputs, dict, additional inputs
     @ Out, None
   """
-  self.?? = evaluate(Inputs) # Complete This # make sure the name of the objective is consistent obj
+  self.?? = evaluate(Inputs) # Complete This # make sure the name of the objective is consistent obj

ravenframework/Models/Dummy.py

@@ -83,8 +83,6 @@ def _manipulateInput(self,dataIn):
       @ In, dataIn, object, the object that needs to be manipulated
       @ Out, inRun, dict, the manipulated input
     """
-    if len(dataIn)>1:
-      self.raiseAnError(IOError,'Only one input is accepted by the model type '+self.type+' with name '+self.name)
     if type(dataIn[0])!=tuple:
       inRun = self._inputToInternal(dataIn[0]) #this might happen when a single run is used and the input it does not come from self.createNewInput
     else:
@@ -152,9 +150,6 @@ def createNewInput(self,myInput,samplerType,**kwargs):
            a mandatory key is the sampledVars'that contains a dictionary {'name variable':value}
       @ Out, ([(inputDict)],copy.deepcopy(kwargs)), tuple, return the new input in a tuple form
     """
-    if len(myInput)>1:
-      self.raiseAnError(IOError,'Only one input is accepted by the model type '+self.type+' with name'+self.name)
-
     inputDict   = self._inputToInternal(myInput[0])
     self._replaceVariablesNamesWithAliasSystem(inputDict,'input',False)
 

ravenframework/Models/ROM.py

@@ -172,6 +172,23 @@ def applyRunInfo(self, runInfo):
     """
     self.numThreads = runInfo.get('NumThreads', 1)
 
+  def createNewInput(self,myInput,samplerType,**kwargs):
+    """
+      This function will return a new input to be submitted to the model, it is called by the sampler.
+      here only a PointSet is accepted a local copy of the values is performed.
+      For a PointSet, only the last set of entries are copied
+      The copied values are returned as a dictionary back
+      @ In, myInput, list, the inputs (list) to start from to generate the new one
+      @ In, samplerType, string, is the type of sampler that is calling to generate a new input
+      @ In, **kwargs, dict,  is a dictionary that contains the information coming from the sampler,
+           a mandatory key is the sampledVars'that contains a dictionary {'name variable':value}
+      @ Out, ([(inputDict)],copy.deepcopy(kwargs)), tuple, return the new input in a tuple form
+    """
+    if len(myInput)>1:
+      self.raiseAnError(IOError,'Only one input is accepted by the model type '+self.type+' with name'+self.name)
+    [(inputDict)],kwargs = super().createNewInput(myInput,samplerType,**kwargs)
+    return ([(inputDict)],kwargs)
+
   def _readMoreXML(self,xmlNode):
     """
       Function to read the portion of the xml input that belongs to this specialized class

tests/framework/AnalyticModels/linModel.py

@@ -44,4 +44,4 @@ def main(Input):
   Input['x1'] = 5.5
   Input['x2'] = 8
   a,b,c = main(Input)
-  print(a,b,c)
+  print(a,b,c)

tests/framework/ROM/pickleTests/eRl_setAddtlParams.py

@@ -108,4 +108,4 @@ def main():
     sys.exit(results['fail'])
 
 if __name__ == '__main__':
-    main()
+    main()