make mcextract more userfriendly

python/loadleveller/mcextract.py

@@ -20,7 +20,7 @@ class MCArchive:
             doc = json.load(f)
 
         param_names = set(sum([list(task['parameters'].keys()) for task in doc], []))
-        observable_names = set(sum([list(task['results'].keys()) for task in doc], []))
+        observable_names = set(sum([list(task['results'].keys()) if task['results'] != None else [] for task in doc], []))
         self.num_tasks = len(doc)
         
         self.parameters = dict(zip(param_names, [[None for _ in range(self.num_tasks)] for _ in param_names]))
@@ -30,7 +30,8 @@ class MCArchive:
             for param, value in task['parameters'].items():
                 self.parameters[param][i] = value
 
-            for obs, value in task['results'].items():
+            results = task['results'] if task['results'] else {}
+            for obs, value in results.items():
                 o = self.observables[obs]
                 o.rebinning_bin_length[i] = int(value.get('rebin_len',0))
                 o.rebinning_bin_count[i] = int(value.get('rebin_count',0))
@@ -47,9 +48,18 @@ class MCArchive:
 
     def get_parameter(self, name, unique=False, filter={}):
         selection = list(itertools.compress(self.parameters[name], self.filter_mask(filter)))
-        
+        if len(selection) == 0:
+            raise KeyError('Parameter {} not found with filter {}'.format(name,filter))
+       
         if unique:
-            return list(sorted(set(selection)))
+            selection = list(sorted(set(selection)))
+            
+        dtypes = set(type(p) for p in selection)
+        if len(dtypes) == 1:
+            dtype = list(dtypes)[0]
+            if dtype == float or dtype == int:
+                selection = np.array(selection)
+        
         return selection
 
     def get_observable(self, name, filter={}):