.
This commit is contained in:
Ross
-231
@@ -585,123 +585,6 @@ def mark_review(request, exam_pk, sk):
|
||||
return mark(request, exam_pk, sk, unmarked_exam_answers_only=False, review=True)
|
||||
|
||||
|
||||
@login_required
|
||||
def exam_scores_cid2(request, pk):
|
||||
exam = get_object_or_404(Exam, pk=pk)
|
||||
|
||||
if not exam.exam_mode:
|
||||
raise Http404("Packet not in exam mode")
|
||||
|
||||
user_answers_and_marks = defaultdict(list)
|
||||
user_answers_marks = defaultdict(list)
|
||||
user_answers = defaultdict(list)
|
||||
user_names = {}
|
||||
|
||||
score_by_question = defaultdict(dict)
|
||||
ans_by_question = defaultdict(dict)
|
||||
unmarked = set()
|
||||
|
||||
questions = exam.exam_questions.all()
|
||||
|
||||
cid_user_answers = CidUserAnswer.objects.filter(question__in=questions, exam__id=pk)
|
||||
|
||||
cids = set()
|
||||
|
||||
# Loop through all candidates
|
||||
for cid_user_answer in cid_user_answers:
|
||||
# Convoluted (probably...)
|
||||
cid = cid_user_answer.cid
|
||||
cids.add(cid)
|
||||
s = cid_user_answer
|
||||
user_names[cid] = cid
|
||||
|
||||
q = cid_user_answer.question
|
||||
|
||||
# if not s:
|
||||
# # skip if no answer
|
||||
# user_answers_marks[cid].append(0)
|
||||
# user_answers[cid].append("")
|
||||
# by_question[q].append(("", 0))
|
||||
# continue
|
||||
if s.normal:
|
||||
ans = "Normal"
|
||||
else:
|
||||
ans = s.answer
|
||||
answer_score = s.get_answer_score()
|
||||
if answer_score == "unmarked":
|
||||
index = exam.get_question_index(q)
|
||||
unmarked.add(index)
|
||||
user_answers[cid].append(ans)
|
||||
user_answers_marks[cid].append(answer_score)
|
||||
user_answers_and_marks[cid].append((ans, answer_score))
|
||||
|
||||
score_by_question[q][cid] = answer_score
|
||||
ans_by_question[q][cid] = ans
|
||||
|
||||
user_scores = {}
|
||||
user_scores_normalised = {}
|
||||
for user in user_answers_marks:
|
||||
user_scores[user] = sum(
|
||||
[i for i in user_answers_marks[user] if i != "unmarked"]
|
||||
)
|
||||
user_scores_normalised[user] = normaliseScore(
|
||||
sum([i for i in user_answers_marks[user] if i != "unmarked"])
|
||||
)
|
||||
|
||||
user_scores_list = list(user_scores.values())
|
||||
|
||||
if len(user_scores_list) < 1:
|
||||
mean = 0
|
||||
median = 0
|
||||
mode = 0
|
||||
fig_html = ""
|
||||
else:
|
||||
mean = statistics.mean(user_scores_list)
|
||||
median = statistics.median(user_scores_list)
|
||||
try:
|
||||
mode = statistics.mode(user_scores_list)
|
||||
except statistics.StatisticsError:
|
||||
mode = "No unique mode"
|
||||
|
||||
df = user_scores_list
|
||||
fig = px.histogram(
|
||||
df,
|
||||
x=0,
|
||||
title="{}: distribution of scores".format(exam),
|
||||
labels={"0": "Score"},
|
||||
height=400,
|
||||
width=600,
|
||||
)
|
||||
fig_html = fig.to_html()
|
||||
|
||||
max_score = len(questions) * 2
|
||||
|
||||
return render(
|
||||
request,
|
||||
"rapids/exam_scores_new.html",
|
||||
{
|
||||
"cids": sorted(cids),
|
||||
"exam": exam,
|
||||
"unmarked": unmarked,
|
||||
"questions": questions,
|
||||
"score_by_question": score_by_question,
|
||||
"ans_by_question": ans_by_question,
|
||||
"user_answers": dict(user_answers),
|
||||
"user_answers_marks": dict(user_answers_marks),
|
||||
"user_scores": user_scores,
|
||||
"user_scores_normalised": user_scores_normalised,
|
||||
"user_scores_list": user_scores_list,
|
||||
"user_names": user_names,
|
||||
"user_answers_and_marks": user_answers_and_marks,
|
||||
"max_score": max_score,
|
||||
"mean": mean,
|
||||
"median": median,
|
||||
"mode": mode,
|
||||
"plot": fig_html,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
# @user_passes_test(user_is_admin, login_url="/accounts/login")
|
||||
@login_required
|
||||
def mark(request, exam_pk, sk, unmarked_exam_answers_only=True, review=False):
|
||||
@@ -855,120 +738,6 @@ def mark(request, exam_pk, sk, unmarked_exam_answers_only=True, review=False):
|
||||
)
|
||||
|
||||
|
||||
@login_required
|
||||
def exam_scores_cid(request, pk):
|
||||
exam = get_object_or_404(Exam, pk=pk)
|
||||
|
||||
if not exam.exam_mode:
|
||||
raise Http404("Packet not in exam mode")
|
||||
|
||||
questions = exam.exam_questions.all().prefetch_related("answers")
|
||||
|
||||
cids = (
|
||||
CidUserAnswer.objects.filter(question__in=questions, exam__id=pk)
|
||||
.order_by("cid")
|
||||
.values_list("cid", flat=True)
|
||||
.distinct()
|
||||
)
|
||||
|
||||
user_answers_and_marks = defaultdict(list)
|
||||
user_answers_marks = defaultdict(list)
|
||||
user_answers = defaultdict(list)
|
||||
user_names = {}
|
||||
|
||||
by_question = defaultdict(list)
|
||||
unmarked = set()
|
||||
|
||||
# Loop through all candidates
|
||||
for cid in cids:
|
||||
# Convoluted (probably...)
|
||||
user_names[cid] = cid
|
||||
for q in questions:
|
||||
# Get user answer
|
||||
s = q.cid_user_answers.filter(cid=cid, exam__id=pk).first()
|
||||
|
||||
if not s:
|
||||
# skip if no answer
|
||||
user_answers_marks[cid].append(0)
|
||||
user_answers[cid].append("")
|
||||
by_question[q].append(("", 0))
|
||||
continue
|
||||
elif s.normal:
|
||||
ans = "Normal"
|
||||
else:
|
||||
ans = s.answer
|
||||
answer_score = s.get_answer_score()
|
||||
if answer_score == "unmarked":
|
||||
index = exam.get_question_index(q)
|
||||
unmarked.add(index)
|
||||
user_answers[cid].append(ans)
|
||||
user_answers_marks[cid].append(answer_score)
|
||||
user_answers_and_marks[cid].append((ans, answer_score))
|
||||
|
||||
by_question[q].append((ans, answer_score))
|
||||
|
||||
user_scores = {}
|
||||
user_scores_normalised = {}
|
||||
for user in user_answers_marks:
|
||||
user_scores[user] = sum(
|
||||
[i for i in user_answers_marks[user] if i != "unmarked"]
|
||||
)
|
||||
user_scores_normalised[user] = normaliseScore(
|
||||
sum([i for i in user_answers_marks[user] if i != "unmarked"])
|
||||
)
|
||||
|
||||
user_scores_list = list(user_scores.values())
|
||||
|
||||
if len(user_scores_list) < 1:
|
||||
mean = 0
|
||||
median = 0
|
||||
mode = 0
|
||||
fig_html = ""
|
||||
else:
|
||||
mean = statistics.mean(user_scores_list)
|
||||
median = statistics.median(user_scores_list)
|
||||
try:
|
||||
mode = statistics.mode(user_scores_list)
|
||||
except statistics.StatisticsError:
|
||||
mode = "No unique mode"
|
||||
|
||||
df = user_scores_list
|
||||
fig = px.histogram(
|
||||
df,
|
||||
x=0,
|
||||
title="{}: distribution of scores".format(exam),
|
||||
labels={"0": "Score"},
|
||||
height=400,
|
||||
width=600,
|
||||
)
|
||||
fig_html = fig.to_html()
|
||||
|
||||
max_score = len(questions) * 2
|
||||
|
||||
return render(
|
||||
request,
|
||||
"rapids/exam_scores.html",
|
||||
{
|
||||
"cids": cids,
|
||||
"exam": exam,
|
||||
"unmarked": unmarked,
|
||||
"questions": questions,
|
||||
"by_question": by_question,
|
||||
"user_answers": dict(user_answers),
|
||||
"user_answers_marks": dict(user_answers_marks),
|
||||
"user_scores": user_scores,
|
||||
"user_scores_normalised": user_scores_normalised,
|
||||
"user_scores_list": user_scores_list,
|
||||
"user_names": user_names,
|
||||
"user_answers_and_marks": user_answers_and_marks,
|
||||
"max_score": max_score,
|
||||
"mean": mean,
|
||||
"median": median,
|
||||
"mode": mode,
|
||||
"plot": fig_html,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
def exam_scores_cid_user(request, pk, cid, passcode):
|
||||
exam = get_object_or_404(Exam, pk=pk)
|
||||
|
||||
Reference in New Issue
Block a user