Set a default weight

common/lib/xmodule/xmodule/combined_open_ended_module.py

@@ -82,7 +82,8 @@ class CombinedOpenEndedFields(object):
         display_name="Maximum Attempts",
         help="The number of times the student can try to answer this problem.",
         default=1,
-        scope=Scope.settings, values={"min" : 1 }
+        scope=Scope.settings,
+        values={"min" : 1 }
     )
     is_graded = Boolean(
         display_name="Graded",
@@ -99,7 +100,8 @@ class CombinedOpenEndedFields(object):
     skip_spelling_checks = Boolean(
         display_name="Disable Quality Filter",
         help="If False, the Quality Filter is enabled and submissions with poor spelling, short length, or poor grammar will not be peer reviewed.",
-        default=False, scope=Scope.settings
+        default=False,
+        scope=Scope.settings
     )
     due = Date(
         help="Date that this problem is due by",
@@ -123,7 +125,8 @@ class CombinedOpenEndedFields(object):
     weight = Float(
         display_name="Problem Weight",
         help="Defines the number of points each problem is worth. If the value is not set, each problem is worth one point.",
-        scope=Scope.settings, values={"min" : 0 , "step": ".1"},
+        scope=Scope.settings,
+        values={"min" : 0 , "step": ".1"},
         default=1
     )
     markdown = String(

common/lib/xmodule/xmodule/open_ended_grading_classes/combined_open_ended_modulev1.py

@@ -727,7 +727,12 @@ class CombinedOpenEndedV1Module():
         """
         max_score = None
         score = None
-        if self.is_scored and self.weight is not None:
+
+        #The old default was None, so set to 1 if it is the old default weight
+        weight = self.weight
+        if weight is None:
+            weight = 1
+        if self.is_scored:
             # Finds the maximum score of all student attempts and keeps it.
             score_mat = []
             for i in xrange(0, len(self.task_states)):
@@ -740,7 +745,7 @@ class CombinedOpenEndedV1Module():
                     for z in xrange(0, len(score)):
                         if score[z] is None:
                             score[z] = 0
-                        score[z] *= float(self.weight)
+                        score[z] *= float(weight)
                     score_mat.append(score)
 
             if len(score_mat) > 0:
@@ -754,7 +759,7 @@ class CombinedOpenEndedV1Module():
 
             if max_score is not None:
                 # Weight the max score if it is not None
-                max_score *= float(self.weight)
+                max_score *= float(weight)
             else:
                 # Without a max_score, we cannot have a score!
                 score = None

common/lib/xmodule/xmodule/peer_grading_module.py

@@ -57,7 +57,7 @@ class PeerGradingFields(object):
         scope=Scope.settings
     )
     max_grade = Integer(
-        help="The maximum grade that a student can receive for this problem.", 
+        help="The maximum grade that a student can receive for this problem.",
         default=MAX_SCORE,
         scope=Scope.settings,
         values={"min": 0}
@@ -214,6 +214,11 @@ class PeerGradingModule(PeerGradingFields, XModule):
     def get_score(self):
         max_score = None
         score = None
+        weight = self.weight
+
+        #The old default was None, so set to 1 if it is the old default weight
+        if weight is None:
+            weight = 1
         score_dict = {
             'score': score,
             'total': max_score,
@@ -238,11 +243,10 @@ class PeerGradingModule(PeerGradingFields, XModule):
                 # Ensures that once a student receives a final score for peer grading, that it does not change.
                 self.student_data_for_location = response
 
-        if self.weight is not None:
-            score = int(count_graded >= count_required and count_graded > 0) * float(self.weight)
-            total = self.max_grade * float(self.weight)
-            score_dict['score'] = score
-            score_dict['total'] = total
+        score = int(count_graded >= count_required and count_graded > 0) * float(weight)
+        total = self.max_grade * float(weight)
+        score_dict['score'] = score
+        score_dict['total'] = total
 
         return score_dict