try to improve the scores pages
This commit is contained in:
Ross
+95
-121
@@ -3796,6 +3796,9 @@ class ExamViews(View, LoginRequiredMixin):
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else:
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user_answers_qs = self.UserAnswer.objects.filter(user=user, exam__id=pk).select_related("question")
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if self.app_name in ("anatomy", "rapids"):
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user_answers_qs = user_answers_qs.prefetch_related("question__answers")
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# Map question_id -> UserAnswer for O(1) lookup
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user_answers_map = {ua.question_id: ua for ua in user_answers_qs}
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@@ -3927,19 +3930,7 @@ class ExamViews(View, LoginRequiredMixin):
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return max_score
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def exam_scores_all(self, request, pk):
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"""The exam scores pages. Displays all user scores in a tabular format.
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Args:
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request (_type_): _description_
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pk (_type_): _description_
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Raises:
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Http404: _description_
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PermissionDenied: _description_
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Returns:
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_type_: _description_
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"""
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"""The exam scores pages. Displays all user scores in a tabular format."""
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exam: ExamBase = get_object_or_404(self.Exam, pk=pk)
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if not exam.exam_mode:
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@@ -3949,21 +3940,17 @@ class ExamViews(View, LoginRequiredMixin):
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if request.user not in exam.author.all():
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raise PermissionDenied
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# user_answers_and_marks = defaultdict(list)
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user_answers_marks = defaultdict(list)
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# user_answers = defaultdict(list)
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# user_names = {}
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# cid_passcodes = {}
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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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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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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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if self.app_name in ("rapids"):
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if self.app_name in ("rapids",):
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user_answers_callstates = defaultdict(list)
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user_answers_callstates_counted = {}
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@@ -3977,34 +3964,31 @@ class ExamViews(View, LoginRequiredMixin):
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questions = list(questions_qs)
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question_index_map = {q: i for i, q in enumerate(questions)}
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# We could prefetch the UserAnswers.answers here (if we didn't cache them)
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# Also select_related the user to avoid per-answer user lookups in the loop
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cid_user_answers = (
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# Fetch and prefetch the UserAnswers
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cid_user_answers_qs = (
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self.UserAnswer.objects.select_related("question", "user")
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.filter(question__in=questions, exam__id=pk)
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)
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if self.app_name in ("anatomy", "rapids"):
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cid_user_answers_qs = cid_user_answers_qs.prefetch_related("question__answers")
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cid_user_answers = list(cid_user_answers_qs)
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question_number = len(questions)
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cids = set()
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plain_cids = set()
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user_ids = set()
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cids_user_id_map = {}
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# Loop through all candidates
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for cid_user_answer in cid_user_answers:
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# Convoluted (probably...)
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if cid_user_answer.user is None:
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cid = f"c/{cid_user_answer.cid}"
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cids_user_id_map[cid] = cid
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# cid_passcodes[cid] = cid_user_answer.passcode
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cids.add(cid)
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plain_cids.add(cid_user_answer.cid)
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else:
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cid = f"u/{cid_user_answer.user.pk}"
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# cids_user_id_map[cid] = cid_user_answer.user.username
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name = f"{cid_user_answer.user.first_name} {cid_user_answer.user.last_name}"
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if not name.strip():
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name = cid_user_answer.user.username
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@@ -4013,53 +3997,41 @@ class ExamViews(View, LoginRequiredMixin):
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user_ids.add(cid_user_answer.user.pk)
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s = cid_user_answer
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# user_names[cid] = cid
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q = cid_user_answer.question
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# if not s:
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# # skip if no answer
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# user_answers_marks[cid].append(0)
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# user_answers[cid].append("")
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# by_question[q].append(("", 0))
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# continue
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ans = s.get_answer_string()
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answer_score = s.get_answer_score()
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if answer_score == "unmarked":
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# Use precomputed map to avoid repeated scanning/indexing of questions
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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[cid].append(ans)
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user_answers_marks[cid].append(answer_score)
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if self.app_name == "rapids":
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callstate = s.get_answer_callstate()
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by_question[q][cid] = (ans, answer_score, callstate)
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user_answers_callstates[cid].append(callstate)
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elif self.app_name in ("anatomy", "sbas", "longs", "shorts"):
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by_question[q][cid] = (ans, answer_score)
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else:
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zipped_ans_scores = zip(ans, answer_score)
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by_question[q][cid] = zipped_ans_scores
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if table_only:
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ans = s.get_answer_string()
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if self.app_name == "rapids":
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by_question[q][cid] = (ans, answer_score, callstate)
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elif self.app_name in ("anatomy", "sbas", "longs", "shorts"):
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by_question[q][cid] = (ans, answer_score)
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else:
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zipped_ans_scores = zip(ans, answer_score)
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by_question[q][cid] = zipped_ans_scores
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user_scores = {}
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user_scores_normalised = {}
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user_answer_count = {}
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for user in user_answers_marks:
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# For longs we have a default score of 3 (not 0) if unanswered
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# so we need to check for those
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if self.app_name == "longs":
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for question in questions:
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# If either question or user do not exist we give a default
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# not answered == score of 3
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if user not in by_question[question]:
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# print("NOT in")
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by_question[question][user] = ("Not answered", 3.0)
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user_answers_marks[user].append(3.0)
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missing_count = question_number - len(user_answers_marks[user])
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for _ in range(missing_count):
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user_answers_marks[user].append(3.0)
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if table_only:
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for question in questions:
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if user not in by_question[question]:
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by_question[question][user] = ("Not answered", 3.0)
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if self.app_name in ("physics",):
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user_scores[user] = sum(
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@@ -4081,69 +4053,76 @@ class ExamViews(View, LoginRequiredMixin):
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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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max_score = self.get_max_score(questions)
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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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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 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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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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try:
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mode = statistics.mode(user_scores_list)
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except statistics.StatisticsError:
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mode = "No unique mode"
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df = user_scores_list
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fig = px.histogram(
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df,
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x=0,
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title="{}: distribution of scores".format(exam),
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labels={"0": "Score"},
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height=400,
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width=600,
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)
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fig_html = fig.to_html()
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exam.stats_mean = mean
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exam.stats_median = median
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exam.stats_mode = mode
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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_graph = fig_html
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user_data = {}
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for u in cids:
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user_data[u] = {
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"score": user_scores[u],
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"normalised_score": user_scores_normalised[u],
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}
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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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# Exclude very low scores from statistics
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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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try:
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mode = statistics.mode(user_scores_list)
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except statistics.StatisticsError:
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mode = "No unique mode"
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df = user_scores_list
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fig = px.histogram(
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df,
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x=0,
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title="{}: distribution of scores".format(exam),
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labels={"0": "Score"},
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height=400,
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width=600,
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)
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fig_html = fig.to_html()
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exam.stats_mean = mean
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exam.stats_median = median
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exam.stats_mode = mode
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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_graph = fig_html
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user_data = {}
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for u in cids:
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# uid = cids_user_id_map[u]
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user_data[u] = {
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"score": user_scores[u],
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"normalised_score": user_scores_normalised[u],
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}
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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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# 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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@@ -4152,19 +4131,13 @@ class ExamViews(View, LoginRequiredMixin):
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"cids": sorted(cids),
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"missing_cids": valid_cid_users - plain_cids,
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"missing_users": missing_users,
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# "cid_passcodes": cid_passcodes,
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"exam": exam,
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"unmarked": unmarked,
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"questions": questions,
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"question_number": question_number,
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"by_question": by_question,
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# "user_answers": dict(user_answers),
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# "user_answers_marks": dict(user_answers_marks),
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"user_scores": user_scores,
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"user_scores_normalised": user_scores_normalised,
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# "user_scores_list": user_scores_list,
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# "user_names": user_names,
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# "user_answers_and_marks": user_answers_and_marks,
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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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@@ -4174,6 +4147,7 @@ class ExamViews(View, LoginRequiredMixin):
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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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if self.app_name == "rapids":
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