Improvement of interface post processor performance (#746)

* update dict converstion in DataSet, fix HistorySetSampling

* update test and regold for issue #739

* remove unused xml files

* PointSet is handled differently in the _convertToDict of DataSets

framework/DataObjects/DataSet.py

@@ -998,25 +998,30 @@ def _convertToDict(self):
     dataDict['dims']     = self.getDimensions()
     dataDict['metadata'] = self.getMeta(general=True)
     # main data
-    ## initialize with np arrays of objects
-    dataDict['data'] = dict((var,np.zeros(self.size,dtype=object)) for var in self.vars+self.indexes)
-    ## loop over realizations to get distinct values without NaNs
-    for var in self.vars:
-      # how we get and store variables depends on the dimensionality of the variable
-      dims=self.getDimensions(var)[var]
-      # if scalar (no dims and not an index), just grab the values
-      if len(dims)==0 and var not in self.indexes:
+    if self.type == "PointSet":
+      ## initialize with np arrays of objects
+      dataDict['data'] = dict((var,np.zeros(self.size,dtype=object)) for var in self.vars)
+      for var in self.vars:
         dataDict['data'][var] = self.asDataset()[var].values
-        continue
-      # otherwise, need to remove NaNs, so loop over slices
+    else:
+      dataDict['data'] = dict((var,np.zeros(self.size,dtype=object)) for var in self.vars+self.indexes)
+      # need to remove NaNs, so loop over slices
       for s,rlz in enumerate(self.sliceByIndex(self.sampleTag)):
-        # get data specific to this var for this realization (slice)
-        data = rlz[var]
-        # need to drop indexes for which no values are present
-        for index in dims:
-          data = data.dropna(index)
-          dataDict['data'][index][s] = data[index].values
-        dataDict['data'][var][s] = data.values
+        ## loop over realizations to get distinct values without NaNs
+        for var in self.vars:
+          # how we get and store variables depends on the dimensionality of the variable
+          dims=self.getDimensions(var)[var]
+          # if scalar (no dims and not an index), just grab the values
+          if len(dims)==0 and var not in self.indexes:
+            dataDict['data'][var] = self.asDataset()[var].values
+            continue
+          # get data specific to this var for this realization (slice)
+          data = rlz[var]
+          # need to drop indexes for which no values are present
+          for index in dims:
+            data = data.dropna(index)
+            dataDict['data'][index][s] = data[index].values
+          dataDict['data'][var][s] = data.values
     return dataDict
 
   def _convertToXrDataset(self):

framework/PostProcessorFunctions/HistorySetSampling.py

@@ -125,7 +125,8 @@ def run(self,inputDic):
         self.raiseAnError(IOError, 'HistorySetSampling Interfaced Post-Processor ' + str(self.name) + ' : not recognized samplingType')
 
       for var in outData.keys():
-        outputDic['data'][var] = np.zeros(inputDic['numberRealizations'], dtype=object)
+        if hist == 0:
+          outputDic['data'][var] = np.zeros(inputDic['numberRealizations'], dtype=object)
         outputDic['data'][var][hist] = outData[var]
 
     if 'ProbabilityWeight' in inputDic['data'].keys():

framework/PostProcessors/InterfacedPostProcessor.py

@@ -140,6 +140,7 @@ def run(self, inputIn):
                               '" : The input object "'+ inp.name +'" provided is of the wrong type. Got "'+
                               inp.type + '" but expected "'+self.returnFormat("input") + '"!')
     inputDic= self.inputToInternal(inputIn)
+    self.raiseADebug('InterfacedPostProcessor Post-Processor '+ self.name +' : start to run')
     outputDic = self.postProcessor.run(inputDic)
     return outputDic
 

tests/framework/PostProcessors/InterfacedPostProcessor/gold/historySampling/PrintPPHistorySet_dump1_0.csv

@@ -1,11 +1,11 @@
-y,x,z,time
-4.34359778869,3.24346738646,4.15626305329,0.0
-8.70873346803,4.54560146877,4.74821383001,0.0544444444444
-14.9350741187,7.5098172182,7.3944487416,0.108888888889
-22.9312220448,12.3226460228,15.3278350715,0.163333333333
-26.2689310028,18.0422627229,32.5071756938,0.217777777778
-11.6874705955,19.4888099493,49.5699281169,0.272222222222
--8.36348704689,11.6636017187,45.4112588876,0.326666666667
--13.3433117535,1.49496346427,35.2325304154,0.381111111111
--12.3516934344,-4.84420932516,31.3951750805,0.435555555556
--10.6857759075,-7.79953251639,30.8501670182,0.49
+time,x,y,z
+0.0,3.24346738646,4.34359778869,4.15626305329
+0.0544444444444,4.54560144726,8.70873348729,4.74821381305
+0.108888888889,7.50981721821,14.9350741187,7.3944487416
+0.163333333333,12.3226460228,22.9312220448,15.3278350715
+0.217777777778,18.0422627229,26.2689310028,32.5071756938
+0.272222222222,19.4888099493,11.6874705955,49.5699281169
+0.326666666667,11.6636017187,-8.36348704689,45.4112588876
+0.381111111111,1.49496346427,-13.3433117535,35.2325304154
+0.435555555556,-4.84420933392,-12.3516934332,31.3951750587
+0.49,-7.79953251639,-10.6857759075,30.8501670182