mattdrayer/rebase-20140926-cherrypicks: Added recent commits to rebase branch

lms/djangoapps/api_manager/courseware_access.py

@@ -147,62 +147,3 @@ def get_course_child_content(request, user, course_key, child_descriptor):
         field_data_cache,
         course_key)
     return child_content
-
-
-def calculate_proforma_grade(grade_summary, grading_policy):
-    """
-    Calculates a projected (proforma) final grade based on the current state
-    of grades using the provided grading policy.  Categories equate to grading policy
-    'types' and have values such as 'Homework', 'Lab', 'MidtermExam', and 'FinalExam'
-
-    We invert the concepts here and use the category weights as the possible scores by
-    assuming that the weights total 100 percent.  So, if a Homework category is worth 15
-    percent of your overall grade, and you have currently scored 70 percent for that
-    category, the normalized score for the Homework category is 0.105.  Note that
-    we do not take into account dropped assignments/scores, such as lowest-two homeworks.
-
-    After all scored categories are processed we apply the average category score to any
-    unscored categories using the value as a projection of the user's performance in each category.
-
-    Example:
-        - Scored Category: Homework,    Weight: 15%, Totaled Score: 70%,  Normalized Score: 0.105
-        - Scored Category: MidtermExam, Weight: 30%, Totaled Score: 80%,  Normalized Score: 0.240
-        - Scored Category: Final Exam,  Weight: 40%, Totaled Score: 95%,  Normalized Score: 0.380
-        - Average Category Score: (70 + 80 + 95) / 3 = 81.7
-        - Unscored Category: Lab,       Weight: 15%, Totaled Score: 81.7%, Normalized Score: 0.123
-        - Proforma Grade = 0.105 + 0.240 + 0.380 + 0.123 = 0.8475  (84.8%)
-    """
-    grade_breakdown = grade_summary['grade_breakdown']
-    proforma_grade = 0.00
-    totaled_scores = grade_summary['totaled_scores']
-    category_averages = []
-    categories_to_estimate = []
-    for grade_category in grade_breakdown:
-        category = grade_category['category']
-        item_scores = totaled_scores.get(category)
-        if item_scores is not None and len(item_scores):
-            total_item_score = 0.00
-            items_considered = 0
-            for item_score in item_scores:
-                if item_score.earned or (item_score.due and item_score.due < timezone.now()):
-                    normalized_item_score = item_score.earned / item_score.possible
-                    total_item_score += normalized_item_score
-                    items_considered += 1
-            if total_item_score:
-                category_average_score = total_item_score / items_considered
-                category_averages.append(category_average_score)
-                category_policy = next((policy for policy in grading_policy['GRADER'] if policy['type'] == category), None)
-                category_weight = category_policy['weight']
-                category_grade = category_average_score * category_weight
-                proforma_grade += category_grade
-            else:
-                categories_to_estimate.append(category)
-        else:
-            categories_to_estimate.append(category)
-    assumed_category_average = sum(category_averages) / len(category_averages) if len(category_averages) > 0 else 0
-    for category in categories_to_estimate:
-        category_policy = next((policy for policy in grading_policy['GRADER'] if policy['type'] == category), None)
-        category_weight = category_policy['weight']
-        category_grade = assumed_category_average * category_weight
-        proforma_grade += category_grade
-    return proforma_grade

lms/djangoapps/api_manager/users/views.py

@@ -40,7 +40,7 @@ from xmodule.modulestore import InvalidLocationError
 from xmodule.modulestore.django import modulestore
 
 from api_manager.courses.serializers import CourseModuleCompletionSerializer
-from api_manager.courseware_access import get_course, get_course_child, get_course_child_content, get_course_key, course_exists, calculate_proforma_grade
+from api_manager.courseware_access import get_course, get_course_child, get_course_key, course_exists
 from api_manager.permissions import SecureAPIView, SecureListAPIView, IdsInFilterBackend, HasOrgsFilterBackend
 from api_manager.models import GroupProfile, APIUser as User
 from api_manager.organizations.serializers import OrganizationSerializer
@@ -932,7 +932,7 @@ class UsersCoursesGradesDetail(SecureAPIView):
         )
         if len(queryset):
             current_grade = queryset[0].grade
-            proforma_grade = calculate_proforma_grade(grade_summary, grading_policy)
+            proforma_grade = grades.calculate_proforma_grade(grade_summary, grading_policy)
 
         response_data = {
             'courseware_summary': progress_summary,

lms/djangoapps/courseware/grades.py

@@ -9,6 +9,7 @@ from contextlib import contextmanager
 from django.conf import settings
 from django.db import transaction
 from django.test.client import RequestFactory
+from django.utils import timezone
 
 from dogapi import dog_stats_api
 
@@ -546,3 +547,62 @@ def iterate_grades_for(course_id, students):
                     exc.message
                 )
                 yield student, {}, exc.message
+
+
+def calculate_proforma_grade(grade_summary, grading_policy):
+    """
+    Calculates a projected (proforma) final grade based on the current state
+    of grades using the provided grading policy.  Categories equate to grading policy
+    'types' and have values such as 'Homework', 'Lab', 'MidtermExam', and 'FinalExam'
+
+    We invert the concepts here and use the category weights as the possible scores by
+    assuming that the weights total 100 percent.  So, if a Homework category is worth 15
+    percent of your overall grade, and you have currently scored 70 percent for that
+    category, the normalized score for the Homework category is 0.105.  Note that
+    we do not take into account dropped assignments/scores, such as lowest-two homeworks.
+
+    After all scored categories are processed we apply the average category score to any
+    unscored categories using the value as a projection of the user's performance in each category.
+
+    Example:
+        - Scored Category: Homework,    Weight: 15%, Totaled Score: 70%,  Normalized Score: 0.105
+        - Scored Category: MidtermExam, Weight: 30%, Totaled Score: 80%,  Normalized Score: 0.240
+        - Scored Category: Final Exam,  Weight: 40%, Totaled Score: 95%,  Normalized Score: 0.380
+        - Average Category Score: (70 + 80 + 95) / 3 = 81.7
+        - Unscored Category: Lab,       Weight: 15%, Totaled Score: 81.7%, Normalized Score: 0.123
+        - Proforma Grade = 0.105 + 0.240 + 0.380 + 0.123 = 0.8475  (84.8%)
+    """
+    grade_breakdown = grade_summary['grade_breakdown']
+    proforma_grade = 0.00
+    totaled_scores = grade_summary['totaled_scores']
+    category_averages = []
+    categories_to_estimate = []
+    for grade_category in grade_breakdown:
+        category = grade_category['category']
+        item_scores = totaled_scores.get(category)
+        if item_scores is not None and len(item_scores):
+            total_item_score = 0.00
+            items_considered = 0
+            for item_score in item_scores:
+                if item_score.earned or (item_score.due and item_score.due < timezone.now()):
+                    normalized_item_score = item_score.earned / item_score.possible
+                    total_item_score += normalized_item_score
+                    items_considered += 1
+            if total_item_score:
+                category_average_score = total_item_score / items_considered
+                category_averages.append(category_average_score)
+                category_policy = next((policy for policy in grading_policy['GRADER'] if policy['type'] == category), None)
+                category_weight = category_policy['weight']
+                category_grade = category_average_score * category_weight
+                proforma_grade += category_grade
+            else:
+                categories_to_estimate.append(category)
+        else:
+            categories_to_estimate.append(category)
+    assumed_category_average = sum(category_averages) / len(category_averages) if len(category_averages) > 0 else 0
+    for category in categories_to_estimate:
+        category_policy = next((policy for policy in grading_policy['GRADER'] if policy['type'] == category), None)
+        category_weight = category_policy['weight']
+        category_grade = assumed_category_average * category_weight
+        proforma_grade += category_grade
+    return proforma_grade

lms/djangoapps/gradebook/management/commands/generate_gradebook_entries.py

@@ -69,13 +69,15 @@ class Command(BaseCommand):
                 request.user = user
                 grade_data = grades.grade(user, request, course)
                 grade = grade_data['percent']
+                proforma_grade = grades.calculate_proforma_grade(grade_data, course.grading_policy)
                 try:
                     gradebook_entry = StudentGradebook.objects.get(user=user, course_id=course.id)
                     if gradebook_entry.grade != grade:
                         gradebook_entry.grade = grade
+                        proforma_grade = proforma_grade
                         gradebook_entry.save()
                 except StudentGradebook.DoesNotExist:
-                    StudentGradebook.objects.create(user=user, course_id=course.id, grade=grade)
+                    StudentGradebook.objects.create(user=user, course_id=course.id, grade=grade, proforma_grade=proforma_grade)
                 log_msg = 'Gradebook entry created -- Course: {}, User: {}  (grade: {})'.format(course.id, user.id, grade)
                 print log_msg
                 log.info(log_msg)

lms/djangoapps/gradebook/models.py

@@ -22,6 +22,7 @@ class StudentGradebook(TimeStampedModel):
     user = models.ForeignKey(User, db_index=True)
     course_id = CourseKeyField(db_index=True, max_length=255, blank=True)
     grade = models.FloatField()
+    proforma_grade = models.FloatField()
 
     class Meta:
         """
@@ -121,6 +122,7 @@ class StudentGradebookHistory(TimeStampedModel):
     user = models.ForeignKey(User, db_index=True)
     course_id = CourseKeyField(db_index=True, max_length=255, blank=True)
     grade = models.FloatField()
+    proforma_grade = models.FloatField()
 
     @receiver(post_save, sender=StudentGradebook)
     def save_history(sender, instance, **kwargs):  # pylint: disable=no-self-argument, unused-argument
@@ -130,6 +132,7 @@ class StudentGradebookHistory(TimeStampedModel):
         history_entry = StudentGradebookHistory(
             user=instance.user,
             course_id=instance.course_id,
-            grade=instance.grade
+            grade=instance.grade,
+            proforma_grade=instance.proforma_grade
         )
         history_entry.save()

lms/djangoapps/gradebook/receivers.py

@@ -24,10 +24,12 @@ def on_score_changed(sender, **kwargs):
     request.user = user
     grade_data = grades.grade(user, request, course_descriptor)
     grade = grade_data['percent']
+    proforma_grade = grades.calculate_proforma_grade(grade_data, course_descriptor.grading_policy)
     try:
         gradebook_entry = StudentGradebook.objects.get(user=user, course_id=course_key)
         if gradebook_entry.grade != grade:
             gradebook_entry.grade = grade
+            gradebook_entry.proforma_grade = proforma_grade
             gradebook_entry.save()
     except StudentGradebook.DoesNotExist:
-        StudentGradebook.objects.create(user=user, course_id=course_key, grade=grade)
+        StudentGradebook.objects.create(user=user, course_id=course_key, grade=grade, proforma_grade=proforma_grade)