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This commit is contained in:
Ross
+85
-61
@@ -2370,33 +2370,7 @@ class ExamViews(View, LoginRequiredMixin):
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},
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)
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@method_decorator(login_required)
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def exam_scores_refresh(self, request, pk):
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exam = get_object_or_404(self.Exam, pk=pk)
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if not exam.exam_mode:
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raise Http404("Packet not in exam mode")
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# We don't worry about order here
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questions = exam.exam_questions.all()
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cids = self.UserAnswer.objects.filter(question__in=questions, exam__id=pk)
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# Force a score update
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for c in cids:
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c.get_answer_score(cached=False)
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return render(
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request,
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f"{self.app_name}/base.html",
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{
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"simple_content": format_html(
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"""Answer scores updated <br/>
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<a href='{}'>Return</a>""",
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reverse(f"{self.app_name}:exam_scores_all", kwargs={"pk": exam.pk}),
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)
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},
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)
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def exam_cids(self, request, exam_id):
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"""View that displays an overview of users that have been added to the exam.
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@@ -3941,11 +3915,12 @@ class ExamViews(View, LoginRequiredMixin):
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raise PermissionDenied
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table_only = request.GET.get("table_only") == "true" or request.headers.get("HX-Target") == "answers-table-container"
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stats_only = request.GET.get("stats_only") == "true" or request.headers.get("HX-Target") == "stats-container"
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user_answers_marks = defaultdict(list)
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by_question = defaultdict(dict)
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unmarked = set()
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cached_scores = True
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cached_scores = False
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valid_cid_users = set(exam.valid_cid_users.all().values_list("cid", flat=True))
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valid_user_users = set(exam.valid_user_users.all().values_list("pk", flat=True))
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@@ -3955,7 +3930,6 @@ class ExamViews(View, LoginRequiredMixin):
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user_answers_callstates_counted = {}
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if self.app_name in ("physics", "sbas", "longs", "shorts"):
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cached_scores = False
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questions_qs = exam.get_questions()
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else:
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questions_qs = exam.get_questions().prefetch_related("answers")
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@@ -4004,6 +3978,7 @@ class ExamViews(View, LoginRequiredMixin):
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index = question_index_map.get(q)
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if index is not None:
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unmarked.add(index)
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user_answers_marks[cid].append(answer_score)
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if self.app_name == "rapids":
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@@ -4051,34 +4026,63 @@ class ExamViews(View, LoginRequiredMixin):
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user_answer_count[user] = len(user_answers_marks[user])
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# ignore scores of 0 for stats
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user_scores_list = [i for i in user_scores.values() if i > 0]
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# If table_only and rapids, populate user_answers_callstates_counted
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if table_only and self.app_name == "rapids":
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for u in cids:
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user_answers_callstates_counted[u] = dict(Counter(user_answers_callstates[u]))
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missing_user_ids = valid_user_users - user_ids
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missing_users = []
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if missing_user_ids:
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missing_users = User.objects.filter(pk__in=missing_user_ids)
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max_score = self.get_max_score(questions)
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mean = 0
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median = 0
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mode = 0
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fig_html = ""
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if stats_only:
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user_scores_list = [i for i in user_scores.values() if i > 0]
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mean = 0
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median = 0
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mode = 0
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fig_html = ""
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std_dev = 0
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q1 = 0
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q3 = 0
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min_score = 0
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max_score_achieved = 0
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passed_candidates_count = 0
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pass_rate = 0.0
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if not table_only:
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if len(user_scores_list) < 1:
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mean = 0
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median = 0
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mode = 0
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fig_html = ""
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else:
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# Exclude very low scores from statistics
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if len(user_scores_list) >= 1:
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lower_score_bound = max_score / 5
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bounded_scores = [i for i in user_scores_list if i > lower_score_bound]
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if bounded_scores:
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user_scores_list = bounded_scores
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mean = statistics.mean(user_scores_list)
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median = statistics.median(user_scores_list)
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mean = round(statistics.mean(user_scores_list), 2)
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median = round(statistics.median(user_scores_list), 2)
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try:
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mode = statistics.mode(user_scores_list)
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if isinstance(mode, (int, float)):
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mode = round(mode, 2)
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except statistics.StatisticsError:
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mode = "No unique mode"
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std_dev = round(statistics.pstdev(user_scores_list), 2)
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if len(user_scores_list) >= 2:
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quants = statistics.quantiles(user_scores_list, n=4)
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q1 = round(quants[0], 2)
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q3 = round(quants[2], 2)
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else:
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q1 = round(user_scores_list[0], 2)
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q3 = round(user_scores_list[0], 2)
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min_score = round(min(user_scores_list), 2)
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max_score_achieved = round(max(user_scores_list), 2)
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passed_candidates_count = sum(1 for score in user_scores.values() if score >= max_score / 2)
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pass_rate = round((passed_candidates_count / len(cids)) * 100, 1) if cids else 0.0
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df = user_scores_list
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fig = px.histogram(
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df,
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@@ -4097,8 +4101,8 @@ class ExamViews(View, LoginRequiredMixin):
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exam.stats_candidates = len(user_scores_list)
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exam.stats_max_possible = max_score
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exam.stats_min = min(user_scores_list)
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exam.stats_max = max(user_scores_list)
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exam.stats_min = min_score
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exam.stats_max = max_score_achieved
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exam.stats_graph = fig_html
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@@ -4112,20 +4116,45 @@ class ExamViews(View, LoginRequiredMixin):
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if self.app_name == "rapids":
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counted_callstates = dict(Counter(user_answers_callstates[u]))
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user_data[u]["callstates"] = str(counted_callstates)
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user_answers_callstates_counted[u] = counted_callstates
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exam.user_scores = user_data
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exam.save()
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else:
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# If table_only and rapids, populate user_answers_callstates_counted
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if self.app_name == "rapids":
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for u in cids:
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user_answers_callstates_counted[u] = dict(Counter(user_answers_callstates[u]))
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missing_user_ids = valid_user_users - user_ids
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missing_users = []
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if missing_user_ids:
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missing_users = User.objects.filter(pk__in=missing_user_ids)
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expected_answer_count = len(cids) * question_number
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user_answer_count_total = sum(user_answer_count.values())
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completion_rate = round((user_answer_count_total / expected_answer_count) * 100, 1) if expected_answer_count > 0 else 0.0
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if hasattr(self.Answer, "MarkOptions") and hasattr(self.UserAnswer, "score"):
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unmarked_count = sum(1 for c in cid_user_answers if c.score == self.Answer.MarkOptions.UNMARKED or c.score is None)
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elif hasattr(self.UserAnswer, "is_marked"):
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unmarked_count = sum(1 for c in cid_user_answers if not c.is_marked())
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elif hasattr(self.UserAnswer, "score"):
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unmarked_count = sum(1 for c in cid_user_answers if c.score == "" or c.score is None)
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else:
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unmarked_count = 0
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context = {
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"exam": exam,
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"cids": sorted(cids),
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"question_number": question_number,
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"max_score": max_score,
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"mean": mean,
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"median": median,
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"mode": mode,
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"std_dev": std_dev,
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"q1": q1,
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"q3": q3,
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"min_score": min_score,
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"max_score_achieved": max_score_achieved,
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"passed_candidates_count": passed_candidates_count,
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"pass_rate": pass_rate,
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"expected_answer_count": expected_answer_count,
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"user_answer_count_total": user_answer_count_total,
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"completion_rate": completion_rate,
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"unmarked_count": unmarked_count,
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"plot": fig_html,
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}
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return render(request, "generic/partials/_exam_scores_stats.html", context)
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template_variables = {
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"cids": sorted(cids),
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@@ -4141,11 +4170,6 @@ class ExamViews(View, LoginRequiredMixin):
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"user_answer_count": user_answer_count,
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"cids_user_id_map": cids_user_id_map,
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"max_score": max_score,
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"mean": mean,
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"median": median,
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"mode": mode,
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"plot": fig_html,
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"cached_scores": cached_scores,
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"can_edit": exam.check_user_can_edit(request.user),
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"base_template": "generic/exam_scores_partial_base.html" if table_only else "generic/exam_scores_base.html",
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}
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