use precalculated scores per question group for team result

knowledge/survey/README.txt

@@ -84,7 +84,11 @@ Team evaluation
   >>> resp03 = Response(quest, 'mary')
   >>> resp03.values = {qu01: 1, qu02: 2, qu03: 4}
 
-  >>> res, ranks, averages = resp01.getTeamResult([resp01, resp03])
-  >>> ranks, averages
-  ([2], [0.6666...])
+  >>> resp01.values[qugroup] = resp01.getGroupedResult()[0][2]
+  >>> resp03.values[qugroup] = resp03.getGroupedResult()[0][2]
+
+  >>> ranks, averages = resp01.getTeamResult(resp03.getGroupedResult(), 
+  ...                                        [resp01, resp03])
+  >>> ranks, averages
+  ([1], [0.6666...])
 

knowledge/survey/questionnaire.py

@@ -110,18 +110,16 @@ class Response(object):
                 result.append((qugroup, qugroup.feedbackItems[int(wScore)], relScore))
         return result
 
-    def getTeamResult(self, teamData):
-        mine = self.getGroupedResult()
-        all = [d.getGroupedResult() for d in teamData]
+    def getTeamResult(self, mine, teamData):
         averages = []
         ranks = []
         for idx, qgdata in enumerate(mine):
             total = 0.0
-            pos = len(teamData)
-            for j, data in enumerate(all):
-                total += data[idx][2]
-                if qgdata[2] >= data[idx][2]:
+            values = sorted([data.values[qgdata[0]] for data in teamData])
+            for j, value in enumerate(values):
+                total += value
+                if qgdata[2] >= value:
                     pos = len(teamData) - j
             ranks.append(pos)
             averages.append(total / len(teamData))
-        return mine, ranks, averages
+        return ranks, averages